African Journal of - PSAU green energy, Food technology etc. The Journal welcomes the submission of...

Volume 6 Number 1 January 2012

African Journal of

Environmental Science

and Technology

ISSN 1996-0786

About AJEST

The African Journal of Environmental Science and Technology (ISSN 1996-0786) is published monthly (one volume per year) by Academic Journals. African Journal of Environmental Science and Technology (AJEST) is an open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as Biocidal activity of selected plant powders against Tribolium castaneum Herbst in stored groundnut, evaluation of biomass gasifier for industrial thermal applications, green energy, Food technology etc. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published shortly after acceptance. All articles are peer-reviewed

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Editors

Oladele A. Ogunseitan, Ph.D., M.P.H. Professor of Public Health & Professor of Social Ecology Director, Industrial Ecology Research Group University of California Irvine, CA 92697-7070, USA. Prof. Sulejman Redzic Faculty of Science of the University of Sarajevo 33-35 Zmaja od Bosne St., 71 000 Sarajevo, Bosnia and Herzegovina.

Dr. Guoxiang Liu Energy & Environmental Research Center (EERC), University of North Dakota (UND) 15 North 23rd Street, Stop 9018, Grand Forks, North Dakota 58202-9018 USA. Dr. Ramesh Chandra Trivedi Chief Environmental Scientist DHI (India) Wateer & Environment Pvt Ltd, B-220, CR Park, New Delhi – 110019, India.

Editorial Board

Dr. Anthony O. Esilaba Kenya Agricultural Research Institute, City Square 00200, Nairobi, Area of Expertise: Agronomy- Soil science Kenya. Dr Dina Abbott University of Derby, Area of Expertise: Gender, Food processing and agriculture, Urban poverty UK. Dr. Jonathan Li University of Waterloo, Area of Expertise: Environmental remote sensing, Spatial decision support systems for informal settlement Management in Southern Africa Canada. Prof. Omer Ozturk The Ohio State University Department of Statistics, 1958 Neil Avenue, Columbus OH, 43210 Area of Expertise: Non parametric statistics, Ranked set sampling, Environmental sampling USA Dr. John I. Anetor Department of Chemical Pathology, College of Medicine, University of Ibadan, Ibadan, Area of Expertise: Environmental toxicology & Micronutrient metabolism (embracing public health nutrition) Nigeria. Dr. Ernest Lytia Molua Department of Economics and Management University of Buea, Area of Expertise: Global warming and Climate change, General Economics of the environment Cameroon. Prof. Muhammad Iqbal Hamdard University, New Delhi, Area of Expertise: Structural & Developmental Botany, Stress Plant Physiology, and Tree Growth India.

Dr. Télesphore SIME-NGANDO CNRS, UMR 6023, Université Blaise Pascal Clermont-Ferrand II, 24 Avenue des Landais 63177 Aubière Cedex, Area of Expertise: Aquatic microbial ecology France. Dr. Moulay Belkhodja Laboratory of Plant Physiology Faculty of Science University of Oran, Area of Expertise: Plant physiology, Physiology of abiotic stress, Plant biochemistry, Environmental science, Algeria. Prof. XingKai XU Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029, Area of Expertise: Carbon and nitrogen in soil environment, and greenhouse gases China. Prof. Andrew S Hursthouse University of the West of Scotland, Area of Expertise: Environmental geochemistry; Organic pollutants; Environmental nanotechnology and biotechnology UK. Dr. Sierra Rayne Department of Biological Sciences Thompson Rivers University Box 3010, 900 McGill Road Kamloops, British Columbia, Area of Expertise: Environmental chemistry Canada. Dr. Edward Yeboah Soil Research Institute of the Council for Scientific and Industrial Research (CSIR), Area of expertise: Soil Biology and Biochemistry stabilization of soil organic matter in agro-ecosystems Ghana. Dr. Huaming Guo Department of Water Resources & Environment, China University of Geosciences, Beijing, Area of Expertise: Groundwater chemistry; Environmental Engineering China.

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International Journal of Medicine and Medical Sciences

African Journal of Environmental Science and Technology

Table of Contents: Volume 6 Number 1 January 2012

ARTICLES

Research Articles ENVIRONMENTAL POLLUTION, HEALTH IMPACTS AND REMEDIATION TECHNOLOGY Observed urban heat island characteristics in Akure, Nigeria 1 Ifeoluwa A. Balogun, Ahmed A. Balogun and Zachariah D. Adeyewa Tillage effects on physical qualities of a vertisol in the central highlands of Ethiopia 9 Jaswant Singh, Rudra P. Singh and Anand K. Dubey Valuing the cost of environmental degradation in the face of changing climate: Emphasis on flood and erosion in Benin City, Nigeria 17

Odjugo, Peter Akpodiogaga-a Ovuyovwiroye Palynostratigraphy and palaeoenvironmental characterization and evidence of Oligocene in the terrestrial sedimentary basin, Bingerville area, Southern Côte d'Ivoire, Northern Gulf of Guinea 28

Bruno Zeli Digbehi, Mamery Doukoure, Juliette Tea-Yassi, Raphael Konan Yao, Jean-Paul N’goran Yao, David Kouakou Kangah and Ignace TAHI Effect of the standard clearing limit of forest road right-of-way on stand stock growth: Case study of Vaston forests, Hyrcanian zone 43

Ali Sorkhi, Seyed Ataollah, Hoseini, Majid Lotfalian and Aidin Parsakhoo

ARTICLES

ENVIRONMENTAL RESOURCE MANAGEMENT Food security and health in the southern highlands of Tanzania: A multidisciplinary approach to evaluate the impact of climate change and other stress factors[ 50 Richard Y. M. Kangalawe Effect of time of application of spent oil on the growth and performance of maize (Zea mays) 67 Kelechi L. Njoku, Modupe O. Akinola and Temitope O. Busari Implications of ecological and social characteristics to community livelihoods in the coastal areas of Tanzania 72

Majule A. E.

Table of Contents: Volume 6 Number 1 January 2012

African Journal of Environmental Science and Technology Vol. 6(1), pp. 1-8, January 2012 Available online at http://www.academicjournals.org/AJEST DOI: 10.5897/AJEST11.084 ISSN 1996-0786 ©2012 Academic Journals

Full Length Research Paper

Observed urban heat island characteristics in Akure, Nigeria

Ifeoluwa A. Balogun*, Ahmed A. Balogun and Zachariah D. Adeyewa

Department of Meteorology, Federal University of Technology, P. M. B 704, Akure 34000 – Nigeria.

Accepted 1 December, 2011

A climatological analysis of the differences in air temperature between rural and urban areas (∆Tu-r) corroborates the existence of an urban heat island (UHI) in Akure (7º 25’ N, 5º 20’ E), a tropical city in the south western part of Nigeria. The investigations which have been conducted out of a year-long experiment from fixed point observations focuses on the description of the climatology of urban canopy heat island in the Akure and the analysis of the results were presented. The results show that the nocturnal heat island was more frequent than the daytime heat island as it exists from less intense to higher intensity categories throughout the study period. Nocturnal heat Island intensity was observed to be stronger during the dry season. Although of lower intensity, daytime heat Island exists throughout the day except for few hours in the months of November and December that exhibits a reverse thermal contrast. The daytime heat island is observed to be intense in the wet months than the dry months, which may be caused by the evaporative cooling of wet surfaces. On the average, the urban/ rural thermal differences are positive, varying from 4°C at nocturnal hours during dry months to an approximate of 2°C around noon during wet months. This paper explain the aspects of heat islands and their relation to other causative agents such as the sky view factor (SVF) and also discusses its potential impact on energy demand. Key words: Urban heat island, sky view factor, energy demand.

INTRODUCTION The city of Akure has witnessed remarkable growth in its urbanisation in recent years, and its population during the past few decades has more than tripled. Urbanisation has been reported to modifiy local city climates. The resulting UHI is the characteristic warmth of urban areas compared to their outskirts. It is also often referred to as the increase of air temperature in the near-surface layer of the atmosphere within cities relative to their surrounding countryside (Voogt, 2002).

Essence of studies of the UHI are not only predicated on the necessity to gain knowledge of its numerous secondary effects when excessive, but also its practical needs in town planning, prevention of high concentration of air pollution and creation of optimum bioclimatic conditions (Rosenfeld, 1995; Balogun et al., 2010). *Corresponding author: E-mail: [email protected]. Tel: +234-803-919-4212.

Built-up environment has been found to exacerbate heat stress, particularly at night, during heat waves and provides a preferential site for spread of vector borne diseases (Samuels, 2004; Svensson and Tarvainen, 2004). It has also been well documented that weather-related factors play an important role in affecting electricity consumption. For many years, utility companies and the electric power industry have been interested in the relation between energy consumption and climate, and have developed empirical weather normalization algorithms aimed at improving load forecasting subject to variations in regional climate (Sailor, 2001).

Modification of air temperature by urban areas at roof level has been reported extensively in mid-latitude cities (Chandler, 1962; Oke, 1982), but it has however been noted that transferability of results from knowledge regarding the mid latitude studies is still limited (Oke et al., 1990, 1991). Lately, the heat-island phenomenon begin to receive attention in tropical environments where

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Figure 1. Google map of Akure showing the city centre (1) and Airport (2) sites. Inset (left and right) are photos of the sites and measurement systems respectively.

cities have been witnessing rapid growth in a chaotic manner (Imamura, 1988; Adebayo, 1991; Balogun et al., 2009a, b). Most of the studies on mid-latitude were undertaken during the summer, when prevailing cloudless skies and calm or light winds allow full development of the phenomenon. Since the above conditions are not often present during winter, with some exceptions (Munn et al., 1969; Unwin, 1980), rather few studies were attempted to describe the seasonal behavior of the heat island during an annual cycle. Findings regarding relationships between the intensity of the urban heat island and various parameters such as population of a city and sky-view-factor have been investigated (Yamashita, 1988; Park, 1987; Tumanov et al., 1995).

Urban microclimate studies of tropical regions are still rare, the few workdone in Nigeria have used mean monthly climatological data or 2 to 3 hourly interval short term manual measurements (Adebayo, 1991; Balogun et al., 2009a) and these have limited the studies to daytime conditions. This paper intends to provide additional insights on the descriptive aspects of the heat island phenomenon characterizing a tropical urban environment and discusses its relative impact on energy demand of the city and its enviroment. The importance of weather related parameters in determining the amount of energy

required to achieve desired human comfort needs to be harnessed, particularly during periods that are associated with high frequency of heat island and warmer nights which are also expected to vary in severity by different landuse types. This can be translated into economic value and also serve as a basis for policy formulation in urban planning and climate mitigation measures.

EXPERIMENTAL MEASUREMENT AND METHODS

The experiment was conducted from the period of October 2008 to September 2009. Figure 1 shows the location of the urban and rural stations used. The site at Oja Oba (meaning King’s market), representing the urban is located at the city center in a densely midrise built-up area characterized with dense population, intense transportation and commercial activity. The rural reference site is situated at the meteorological service observatory of the seldom use local airport located about 15 km east on the outskirt of the city, and is characterized by massive grass-covered open plots, few bungalow office buildings and the control tower shown as inset picture in the Figure 1. The Oja urban site (1) and the rural reference site (2) are classified as Built climate zone (BCZ5) and Agricultural climate zone (ACZ3) respectively (Stewart and Oke, 2009). The sites were selected for fixed point observations and data were obtained from shielded portable Lascar EL-USB-2 temperature/humidity data loggers, sampled at 5-minute intervals that were mounted on a lamp post above head height (3 m) in the city urban centre and on a mast at the same height in the local

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Airport. Position of the sensor at the urban site was carefully selected to prevent elevated heat sources such as rooftops. Afternoon air temperatures at 3 m above roof level are about 2°C higher than at 2 m above street level (Sakaida and Suzuki, 1994).

The difference in temperatures between the city and the out-of-town stations, Tu-Tr, is the most commonly used index of the intensity of the UHI. In this paper the quantity of this difference is accepted as a measure of the city's influence on thermal conditions. Cooling degree days are values complied daily to assess how much energy may be needed to cool buildings. In determining the CDD, average temperature value is calculated for a given day. If it is greater than the standard base, the standard base value is subtracted from calculated average temperature to yield the CDD. This is compiled for daily and totaled for entire month. The CDD is calculated using the following formula; CDD = Σ (ti - T) where ti is the daily mean temperature and T is the required room air temperature (25°C). The rationale behind this technique is that whenever average temperature exceeds the comfort range, some cooling will be required, the requirement for cooling increases with increasing.

The Hemispherical images are taken using a digital camera (Nikon Coolpix 950 with a 183-degree field of view fisheye lens) and the sky view factor was calculated from the hemispherical images using a method outlined by Chapman et al. (2001).

RESULTS AND DISCUSSION

Diurnal and annual course of the UHI intensity

It is evident that the daily course of the temperature fluctuations between the urban and rural site are function of the season of the year. The most essential feature of the annual course of urban canopy heat island in the city is that the greatest differences occur in the dry season reaching 3.5°C and the smallest difference occurs during the wet season. The results regarding the urban rural air

temperature differences (∆Tu-r) at both sites are presented in Figure 2. It shows that the UHI exists in Akure throughout the day except in November and December where urban cool island (UCI) is observed for few hours in the afternoon in both months. Daytime heat islands may be positive or negative depending on the particular characteristics of the urban area and their surroundings. Highest UHI values observed in the dry season agrees with Balogun et al. (2009b) that reported UCI at 1500 in October and November and higher UHI values in January and February in Akure. However, results from this study slightly differ as the higher UHI values are observed in November through January but with January recording the highest value in overall. During the wet season, the UHI formed at night is preserved and almost unchanged throughout the day while during the dry season; the UHI formed at night is preserved until the morning hours and significantly drops in intensity or completely vanishes during midday. Annual course of the UHI at the time of the morning observation depends more on the time of sunrise relative to the time of observation, than on any factual dynamics of the weather conditions. The figure further shows that the maximum UHI occurs at night between 1800 to 2200 h local time having its peak around 2100 h. The peak period, on the average, might be linked to the release of sensible heat from "rush hour traffic" occurring in the city as a result of closing hours and evening market transactions from about 6 to 9 pm thereabout. Thereafter, the heat island continues to develop through the early morning hours due mainly to the rural site net radiative energy loss to an unobstructed sky and less polluted atmosphere prior to sunrise. After this time, the solar


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Figure 3. Seasonal variation of urban heat island using mean monthly differences between maximum and minimum temperatures during the period (October 2008 to September 2009).

heating generates a turbulent mixed layer over both the urban surfaces and its environs, so thermal contrasts decline until around the end of the afternoon. Our result is however different from earlier reports that indicate that the maximum UHI occurs during the day time. The difference observed in months of highest value of UHI and the disagreement with time of maximum UHI occurrences exists because the earlier studies were restricted to daytime periods using the convectional mercury in glass thermometer. This result therefore provides new information on the diurnal characteristics of the UHI in Akure. Seasonal variation of the maximum and minimum UHI The seasonal variations of the urban-rural thermal differences at two critical hours of the day are presented in Figure 3. It shows the mean monthly values of thermal contrasts at the time of maximum and minimum temperature for the study period (October 2008 to September 2009). The variations observed may be as a result of different main causes of the UHI phenomenon explained by Oke (1982). Critical properties governing thermal contrasts during the night are the radiation geometry and the surface thermal properties, thermal admittance in particular while the dominant processes responsible during the day are turbulent sensible heat flux obtained from increased absorption of shortwave radiation and anthropogenic heat sources which are mainly industrial and vehicular.

The distinct seasonal variation which is peculiar to both the nocturnal and daytime phenomena is associated with

the seasonality of weather controls. It ranges from clear, calm nights in the dry season to unstable weather conditions with clouds and rain during the wet seasons (April to October). Therefore, as seen in Figure 3, the largest mean nocturnal heat islands (4.5°C) occur in the dry season when differences in urban/rural thermal admittance are more distinct, declining to a minimum (as low as 0.5°C) during the wet months of July and October when soil in the rural site is near saturation. The mean daytime heat island intensity is less intense reaching a maximum in September (3.5°C) (as a result of rural evaporative cooling from rainstorm), declining to a minimum (0.6°C) in November. The figure gives a clear indication that the urban-rural thermal contrasts, on the average always remain positive throughout the year and at all hours of the day for the 1-year period under study

In order to establish period of pronounced heat island occurrences, our target involves only days that well marked urban temperature excedance of greater than or equals to 1°C are being maintained over several hours. Data were available for 315 days only. Result obtained justifies our observation in Figure 2 that the nocturnal (1900 to 0600 h) heat island is far dominant than the daytime heat island (0700 to 1800 h) particularly intense during the dry months. It overtakes in all the months except June and September. However, it is noticed to be weaker and having a narrow margin with the daytime heat island throughout the wet season (April to September) especially during the monsoon, but prevailing from the transitional month of October through the dry season. The daytime heat islands (0700 to 1800 h) were mostly observed during the wet season and almost out of existence in the dry season.

The average and extreme values of the heat island

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Figure 4. Average and extreme values of heat island intensity for the daytime and nocturnal hours during the period of observation (October 2008 to September 2009).

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Figure 5. Seasonal variation of the cooling degree days at the urban and rural sites.

along the 1 year period of observations are illustrated in Figure 4. While the mean heat island intensity for nocturnal events is about 1.5°C, reaching as much as 2.5°C during the dry season and lowest during wet season (1°C). The mean daytime events have somewhat lower intensities in both dry (0.8°C) and wet seasons (1±C) and less variability of extremes. It further shows that there is hardly existence of daytime heat island from October through December. The average and extreme values of both daytime and nocturnal period of the day are nearly constant throughout the wet months from June to September (period of the peak rainfall). When they

occur, the daytime heat islands have about the same intensities as the night-time. Cooling degree days at the urban and rural sites Figure 5 shows the monthly mean numbers of the urban (CDDu) and rural cooling degree days (CDDr). The cooling degree day is clear measure for the comparison of the cooling energy consumption. The cooling season which has two epochs is characterized by significant cooling demand, the first which exists for a very short


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Figure 6. Study sites, its eye level picture, sky view photo and the obtained sky view factor.

period in November and the other epoch in March. These periods have peculiarities as they are both transitional months, November is the transitional month into harmattan period and March to April is transitional period into the summer monsoon. The peak cooling demand is observed to occur in March at both sites. The most significant difference appears in January (about 64°C higher in the urban than the rural site). Consequently, the effect of the city on the cooling energy demand is stronger than in other period of the cooling season. The months of July, August and September are noticed to exhibit totally different peculiarities as the three months in the both cases were absolutely typical of space heating demand rather than cooling. In this period, the summer monsoon has fully developed, resulting in reduced cooling demand due to cooling effect of monsoon winds. These are the periods discussed in the section above that both daytime and nighttime heat island intensities exhibit almost the same intensities. Nocturnal heat island Heat islands in the atmosphere are best expressed at night under calm and clear conditions when differential rates of radiative cooling are maximized between urban areas and their surroundings, with cities cooling more slowly than their surroundings. Mean hourly development of the heat island for days with clear skies and calm winds during the dry season was investigated and it was observed that average nighttime heat island under such atmospheric condition reaches its peak maximum value of 4.4°C at about 2100 h. This is similar to the results by

Oke (1982) for mid-latitude cities where urban/rural diverging cooling rates leads to maximum heat island intensity before midnight but differs from what is observed in the tropical city of Mexico (Jauregui, 1997), where average nocturnal heat island reaches its maximum value at the end of the cooling period at about sunrise (0700 to 0800 h).

The sky view factor (SVF) obtained from the hemispherical images taken at both the urban city core and the rural reference site situated at the old seldom used airport is presented in Figure 6. Facts emanating from the SVF calculation expatiate on why the heat island is more of a nocturnal phenomenon. The SVF is used in urban climatology to characterize radiative properties. By its definition SVF varies from zero when the whole sky is obscured to one when there is no obstruction. It has been proven to be an important concept in studies on radiation and temperature in different research areas. At night time, the rural site that is free from obstructions allows for quick escape of the longwave radiation causing an enhanced radiative cooling while the city centre with reduced sky view due to its peculiar midrise buildings allows the street canyon to serve as heat storage, thereby causing a much slower radiative cooling from the urban surfaces.

Daytime heat island Our results in Figures 2 and 7 show the existence of daytime heat island in the city of Akure. The daytime heat island is less intense during the dry season but more pronounced in the wet season (between April and

Balogun et al. 7

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Figure 7. Frequency distribution of daytime and nighttime heat island intensity in Akure.

September) on the average of 1.5°C, and least in August (less than 1°C) during the august break usually referred to as ‘little dry season’. It further revealed that the difference in air temperature between the city centre and the rural reference site in Akure in some days and particularly during November and December suggests the existence of the urban cool Island (UCI). This is similar to some earlier reports in mid latitudes and less continental cities that have been found to be cooler at certain daytime hours in summer (Chandler, 1962; Unwin, 1980). The cool island observed may be as a result of the facts explained by Oke (1982).

On the average, the mean intensities are quite small, during the dry season; it revolves around 0.8°C in the daytime and 2.4°C overnight but during the wet season, it is less intense with 1.1°C in daytime and 1.2°C in at night. The mean night-time intensity is larger than the daytime intensity in each month except for June to September (intense rainfall period) which have almost equivalent of the daytime. The daytime intensities were generally lower (0-0.9 to 1-1.9°C) than the nighttime that

exists within the range (1-1.9 to 3-3.9°C) category. This is clearer in the frequency distribution shown in Figure 7, which covers the total period.

During the wet season, particularly when the summer monsoon has fully developed (June- September), the frequency of less intense heat island (1-1.9°C) is absolute during the daytime and also high at night. This suggests the observed reduced cooling demand in those periods as presented in Figure 5. The dry season is characterized with more intense heat island, ranging as much as 3- 3.9°C and this also reflects on the cooling demand as presented by the results of the cooling degree day. Conclusion The characteristics of urban heat island in Akure have been investigated and results reveal some interesting new findings on the diurnal and seasonal characteristics of the urban heat island in Akure. The UHI has been

8 Afr. J. Environ. Sci. Technol. found to occur throughout the day and night except for a few hours after noon in November and December that existence of UCI, a reversed thermal contrast which may be as a result of relative abundance of moisture in the city compared to the rural surroundings was noticed. Weak daytime heat island exists throughout the wet season and extremely weak during the dry season accounting for reduced energy demand for cooling, but higher frequency of intense heat island at night time during the dry season is an indication of warmer nights capable of increasing the energy required for cooling. Results ascertain that the UHI is more of nocturnal phenomena in the tropical city of Akure as the highest UHI intensity occurs at night from 1800 to 2200 h having its maxima at 2100 h and also higher in the dry than the wet seasons. The elevation of temperature in the central urban areas at both day and night increases the potential for cooling of buildings. This may therefore lead to increased use of air-conditioning and hence adding more pressure to the electricity grid during peak periods of demand. This result has filled the knowledge gap on the nocturnal status of UHI in Nigeria as earlier studies were restricted to the daytime period due to lack of equipments capable of obtaining nocturnal data and has however supplemented previous attempts to fill knowledge gap of urban effects in tropical urban areas which is still insufficient as compared to the mid latitudes. ACKNOWLEDGEMENTS Authors are grateful to Dr. Jimmy Adegoke of University of Missouri, Kansas City without whom starting this research project would not have been nearly as expeditious. Also appreciated are the local airport authorities and the meteorological agency for obliging in giving permission for measurement stations to be set up in their premises. REFERENCES Adebayo YR (1991). Heat island in a humid tropical city and its

relationship with potential evaporation. Theor. Appl. Climatol., 43(3): 17-30.

Balogun AA, Balogun IA, Adefisan AE, Abatan AA (2009a). Observed characteristics of the urban heat island during the harmattan and monsoon in Akure, Nigeria. Eight Conference on the Urban Environment. AMS 89th Annual Meeting, 11 – 15 January, 2009, Phoenix, AZ. Paper JP4.6, http://ams.confex.com/ams/pdf papers/152809.pdf.

Balogun IA, Balogun AA, Adeyewa ZD (2009b). A note on the effect of urbanization on air temperature and humidity of Akure, Nigeria. Proceedings of the seventh International Conference of Urban Climate, 29th June - 3rd July 2009, Yokohama, Japan.

Balogun AA, Balogun IA, Adeyewa ZD (2010). Comparisons of urban

and rural heat stress conditions in a hot-humid tropical city. Global Health Action, 3: 5614. DOI: 10.3402/gha.v3i0. 5614.

Chandler T (1962). London's urban climate. Geogr. J., 128: 279-298. Chapman L, Thornes JE, Bradley AV (2001). Rapid determination of

canyon geometry parameters for use in surface radiation budgets. Theor. Appl. Climatol., 69(1/2): 81–89.

Imamura I (1988). Comparisons between observations at a mid-latitude city and two semiarid tropical cities. Int. Conf. Trop. Meteorol. Air Pollut., Indian Inst. Tech., Delhi, India.

Munn RE, Hirt MS, Findlay B (1969). A climatological study of the urban temperature anomaly at Toronto. J. Appl. Meteorol., 8: 411-422.

Oke TR (1982).The energetic basis of the urban heat island. Quart. J. Royal Meteorol. Soc., 108(45): 1-24.

Oke TR, Taesler, R, Olsson L (1990/1991). The tropical urban climate experiment. Energy and Buildings 15-16: 67-74.

Park HS (1987). Variations in the urban heat island intensity affected by geographical environments. Environmental Research Center Papers, Environmental Research Center, University of Tsukuba, 11: 79.

Rosenfeld AH, Akbari H, Bretz S, Fishman BL, Kurn DM, Sailor D, Taha H (1995). Mitigation of urban heat islands-materials, utility programs, updates. Energy Buildings, 22: 255-265.

Sailor DJ (2001). Relating residential and commercial sector electricity loads to climate-evaluating state level sensitivities and vulnerabilities. Energy, 26(10): 645–657.

Sakaida K, Susuki M (1994). Microclimate of an urban canyon with thick street trees. Geographical Review of Japan, 67 Series, A8: 506-517.

Samuels R (2004). Urban Heat Islands. Australian House of Representative Standing Committee on Environment and Heritage Sustainable Cities 2025 Enquiry.

Stewart I, Oke TR (2009). Classifying urban climate field sites by “Local climate zones” The case of Nagano, Japan. Proceedings of the seventh International Conference of Urban Climate, 29th June - 3rd July 2009, Yokohama, Japan.

Svensson D, Tarvainen L (2004). The Past and Present Urban Heat Island of Beijing, B416 Projektarbete Goteborg, Earth Sciences. Goteborg University, Sweden.

Tumanov S, Stan-Sion A, Soci C, Lupu A, Oprea C (1995). Local and mesoscale influences of the metropolitan areas on some meteorological parameters and phenomena to the city of Bucharest. Romanian J. Meteorol., 2: 1-18.

Unwin DJ (1980). The synoptic climatology of Birmingharn's urban heat island 1965-1974. Weather, 35(2): 43-50.

Voogt JA (2002). Urban heat island. In: Munn, T. (Ed.), Encyclopedia of Global Change. Wiley, New York, pp. 660–666.

Yamashita S (1988). Some studies of heat island in Japan with special emphasis on the climatological aspects. Geogr. Rev. Japan Series, B61: 1-13.



Effects of ultraviolet-B (UV-B) radiation on two cryptogamic plants pigments growing at high altitude

of central Himalayan region, India

Jaswant Singh*, Rudra P. Singh and Anand K. Dubey

Department of Environmental Sciences, Dr. R. M. L. Avadh University, Faizabad-224001, U.P., India.


Chlorofluorocarbons are mainly responsible for the depletion of stratospheric ozone layer which results in increase of UV-B radiation on earth’s environment and causing adverse effects on flora. In the present study we have investigated the effect of ultraviolet-B (UV-B) radiation on two cryptogamic plants (Xanthoria elegans and Bryum argenteum) growing at high altitude of central Himalayan region of India. These plants were naturally receiving UV-B radiation and were analyzed for photosynthetic pigments, UV-B absorbing compounds and phenolics. In the field experiments, both of these plants contain higher amounts of UV-B absorbing compounds and phenolics and no major changes in total chlorophyll and carotenoid under UV-B exposed conditions were recorded. B. argenteum contains higher amounts of total chlorophyll, carotenoids, UV-B absorbing compounds and phenolics than the X. elegans at the duration of 120 h. The maximum average UV-B irradiance was 4.38 Minimal Erythemal Dose per hour (MED/ h) at the experimental site while minimum average UV-B irradiance was 1.72 MED/ h. The UV-B absorbing compounds and phenolics provide protection to these plants against UV-B radiation. Key words: Total chlorophyll, high altitude, pigments, UV-B absorbing compounds, UV-B radiation.

INTRODUCTION Depletion of the stratospheric ozone layer results in to increase in the ultraviolet-B (UV-B) radiation (280 to 320 nm) reaching the earth surface. Destruction of ozone layer is due to release of chlorofluorocarbons, resulting in stratospheric ozone thinning (Anderson et al., 1991; Schoeberl and Hartmann, 1991), consequently UV-B levels increases (McKenzie et al., 2003). The high intensity of UV-B radiation on earth’s surface causes adverse effects on flora. The potential effects of UV-B radiation on phototrophic organisms may be grouped into three categories: (a) changes in photosynthesis and growth (Xiong and Day, 2001), (b) increased investment in UV-B absorbing or screening compounds (Cockell and Knowland, 1999; Searles et al., 2001) and (c) DNA damage, repair and photoreactivation (Lud et al., 2001a). *Corresponding author. E-mail: [email protected]. Tel: +91-5278-246223. Fax: +91-5278-246330.

UV-B radiation varies naturally with the latitude, season and depends on vegetation canopy, clouds etc., (Aphalo, 2003). According to Madronich et al. (1995) at high latitudes the relative ozone depletion is higher. Many of the studies conducted with vascular plants and bryophytes reveals that the UV-B effects were often highly variable, and depends on the species tolerance and UV-B doses. The naturally induced UV-B affects plant growth, morphology, secondary metabolism and photosynthesis (Allen et al., 1998; Searles et al., 2001; Pancotto et al., 2003). Plants are able to deal with UV-B induced stress because of UV-B absorbing compounds which are widespread and are found in lower to higher plants, including aquatic to terrestrial life forms (Rozema et al., 2002). One of the many roles of UV-B absorbing compounds and phenolics appears to be the protection of organisms from harmful effects of UV-B radiation by means of their direct absorption of 280 nm to 320 nm wavelengths. The phenolics were also protecting the plants from exposure of UV-B radiation, it may contribute


Experimental Sites

Site 1- X. elegans

Site 2- B. argenteum

Figure 1. Map indicating selected sites for field experiments near Mana village, district Chamoli, Uttrakhand, India (www.mapsofindia.com).

to the decrease in active oxygen species by acting as antioxidants (Husain et al., 1987; Markham et al., 1998; Ryan et al., 2002).

In the present study, we have measured the UV-B radiation and their effects on the pigments of two cryptogamic plants (Xanthoria elegans and Bryum argenteum) growing at high altitude of central Himalayan region (near Mana village, district Chamoli of Uttrakhand), India. MATERIALS AND METHODS Site selection

For the UV-B measurements, the sites near Mana village (3219 m, altitude) of district Chamoli, Uttrakhand, central Himalayan region of India were selected. For the UV-B filter frame studies, with X. elegans, site 1 was selected at Bheempul (30°44’577N;

70°29’628E) of Mana village, and for the B. argenteum, site 2 (30°44’540N; 70°29’598E) was selected at the down side of the Bheempul (Figure 1). Selection of plant species

Two plant species, lichen (X. elegans) and moss (B. argenteum) were selected and both were growing naturally on the mountains

with other cryptogamic vegetation (Figure 2a and b). We have selected these plants for the field experiments because of their uniform growth, availability and UV-B filter frames can be placed

over these plants. UV-B filter frames

The UV-B filter frames were made up of iron stands which were covered by plexiglas acrylic sheet, so that plants will get PAR (photosyntheticaly active radiation) but not UV-B radiation. The acrylic sheet (3 mm thick and 30.5 cm squire) absorbs about 98% of total UV-B radiation. Iron frames having holes for gaseous exchange and the other environmental factors were same for both the conditions. At five sites, the UV filters frames (30.5 cm length × 30.5 cm width × 30.5 cm height) were placed over the selected

plant species to develop UV-B unexposed conditions. Analysis of pigments

All the analysis performed with two different experimental set up (i) UV-B exposed (plants without UV-B filter frame) and (ii) UV-B unexposed (plants covered with UV-B filter frame) conditions. Plant

samples were harvested after 24, 48, 72, 96 and 120 h and washed with doubled distilled water, blotted dry on Whatman filter paper No.1 and their weight recorded. For the estimation of both pigments following standard methodologies used. Analysis of photosynthetic pigments (total chlorophyll and carotenoids)

The plant samples were crushed with 80% acetone, maintained at 4°C and centrifuged at 10,000 rpm for 15 min under refrigerated centrifuge at 4°C temperature. The centrifuged samples were

http://www.mapsofindia.com/

Singh et al. 11

Figure 2. Naturally growing plants of (a) Bryum argenteum and (b) Xanthoria elegans under

UV-B exposed conditions.

filtered by Whatman filter paper No. 1 and the supernatant was collected. The absorbance of supernatants was recorded at 663, 645, 480 and 510 nm by using UV-VIS spectrophotometer 117. The chlorophyll content was calculated from absorbance values at 663 and 645 nm (Arnon, 1949) and the carotenoid content from absorbance values at 480 and 510 nm (Parsons et al., 1984).

Estimation of UV-B absorbing compounds

For the estimation of UV-B absorbing compounds, methodology of Ruhland and Day (2001) was used. The plant samples were placed in 25 ml Erlenmeyer flasks containing 5 ml of acidified methanol (MeOH:HCl:H2O, 90:1:1 v/v). The supernatants were heated (60°C) and stirred for 10 min, cooled at room temperature for 15 min and filtered through 90 μm screens. Concentrations of soluble UV-B

absorbing compounds were estimated by measuring absorbance at 300 nm with spectrophotometer (Systronics UV-VIS spectrophotometer 117).

Estimation of phenolics

For phenolics estimation methodology of Pirie and Mullins (1976) was used. A ten percent (w/v) homogenate prepared in methanolic HCl (50% methanol, 0.05% concentrated HCl, pH 3.5). The precipitate was allowed to settle for 15 h in the dark at 0-4°C and filtered through Whatman filter paper No.5. The absorbance of supernatant was recorded at 280 nm and gallic acid (Sigma chemicals, Germany) was used as standard.

Measurement of UV- B radiation

The UV-B radiation recorded by the UV- Biometer (Solar UV- Biometer, SOLAR LIGHT CO. 501, recorder S. No. 9343 and sensor S. No. 10402, U. K.), from 31st August 2008 to 5th September 2008 at the site of experiments during the clear sunny days. Statistical analysis

The mean values along with standard error were calculated. The relative standard derivations of means were less than 5%. The

student ‘t’ test described by Fisher (1950) was employed to calculate the statistical significant values.

RESULTS UV-B radiation UV-B radiation (280 to 320 nm) were measured for the continuous 120 h at the selected sites and the average UV-B irradiances was 3.426 MED/h. The maximum average UV-B irradiance (4.38 MED/ h) was recorded at 72 h where as minimum was 1.72 MED/ h at 120 h (Figure 3). It was observed that the UV-B irradiance values were increasing from morning to noon and then decreased till evening. Photosynthetic pigments There was decrease (p<0.02) in total chlorophyll of UV-B exposed plants of B. argenteum at 96 h as compared to UV-B unexposed plants (Table 1) and at that time the UV-B irradiance was 3.67 MED/h. In UV-B exposed plants of X. elegans, the decrease (p<0.05) in total chlorophyll was found at 120 h as compared to UV-B unexposed plants (Table 1) and at that time the UV-B irradiance was 1.72 MED/h. The increase (p<0.02) in carotenoids of UV-B exposed plants of B. argenteum and X. elegans was recorded at 120 h as compared to UV-B unexposed plants (Table 2) and at that time the UV-B irradiance was 1.72 MED/h.

The significant increase (p<0.02) in UV-B absorbing compounds and phenolics of X. elegans were recorded at 120 h under the UV-B exposed conditions (Figures 4 and 5) and the values of UV-B irradiance was 1.72 MED/h. In B. argenteum, significant increase (p<0.02) in UV-B absorbing compounds and phenolics (p<0.05) were found at 120 h under UV-B exposed condition (Figures 6 and 7)


Figure 3. UV-B irradiance (MED/ h) from 0 h to 120 h. Inset: (a) Daily irradiance curve for one

clear sunny day.

Table 1. Changes in total chlorophyll of B. argenteum and X. elegans (mg/ g fresh weight) in UV-B exposed and unexposed.

Plant species Time (h)

0 24 48 72 96 120

B. argenteum Unexposed 0.660±0.006 0.658±0.012 0.655±0.009 0.657±0.013 0.659±0.010 0.656±0.008

Exposed 0.660±0.007 0.657±0.019 0.659±0.024 0.658±0.015 0.651±0.013 0.649±0.014

X. elegans Unexposed 0.540±0.011 0.539±0.014 0.537±0.021 0.538±0.011 0.535±0.007 0.538±0.003

Exposed 0.540±0.009 0.537±0.018 0.535±0.033 0.539±0.019 0.538±0.012 0.532±0.013

Above values are the mean±SE of three replicates.

Table 2. Changes in total carotenoid of B. argenteum and X. elegans (mg/ g fresh weight) in UV-B exposed and unexposed.

Plant species Time (h)

0 24 48 72 96 120

B. argenteum Unexposed 0.360±0.005 0.358±0.009 0.355±0.011 0.358±0.013 0.359±0.006 0.355±0.008

Exposed 0.360±0.009 0.355±0.012 0.359±0.017 0.357±0.022 0.358±0.012 0.363±0.021

X. elegans Unexposed 0.220±0.003 0.219±0.014 0.216±0.011 0.218±0.009 0.219±0.011 0.217±0.009

Exposed 0.220±0.007 0.217±0.012 0.219±0.013 0.216±0.016 0.217±0.015 0.224±0.019

Above values are the mean±SE of three replicates.

and the UV-B irradiance was 1.72 MED/h. However, increase in the phenolics in B. argenteum is more or less same at 72, 96 and 120 h. The UV-B absorbing compounds and phenolics of both plants were positively associated with UV-B radiation exposure. In both the UV-B unexposed plants, there were no significant changes in UV-B absorbing compounds and phenolics during the course of the study.

DISCUSSION The experimental evidences suggests that the ultraviolet radiation reaching on earth surface varies with altitude, atmospheric condition and types of instrument used for UV-B radiation measurement. Zaratti et al. (2003) reported that the erythemally weighted UV radiation increases with altitudes at an approximate rate of 7% per

Singh et al. 13

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Figure 4. UV-B absorbing compounds in X. elegans under the UV-B exposed and unexposed conditions.

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Figure 5. Phenolics in X. elegans under the UV-B exposed and unexposed

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km. Mckenzie et al. (2003) also reported that the erythemally weighted UV irradiances increases by approximately 5 to 7% per km with the greatest increase occurring at solar zenith angle (SZA) ~ 60-70°.

In B. argenteum and X. elegans, total chlorophyll and carotenoids concentration showed no major changes at 24 h interval under UV-B exposed and unexposed conditions. Decrease in chlorophyll of B. argenteum and


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Figure 6. UV-B absorbing compounds in B. argenteum under the UV-B exposed

and unexposed conditions.

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Figure 7. Phenolics in B. argenteum under the UV-B exposed and unexposed

conditions.

X. elegans was found at 96 and 120 h respectively while increase in carotenoid of both the plants were found at 120 h. Newsham et al. (2002) conducted the similar UV related onsite study with two Antarctic plants (Cephaloziella varians and Sanionia uncinata) and found no change in photosynthetic pigments except increase in

carotenoid. It was observed by Newsham et al. (2005) that the chlorophyll concentrations were reduced in sun exposed C. varians tissues. Robinson et al. (2005) found that the concentration of chlorophyll in Grimmia antarctici under near ambient UV radiation was lower and correspondingly high relative concentration of

carotenoids was recorded under reduced UV radiation. A similar study with lichen was conducted by Larsson et al. (2009) and documented no significant reduction in chlorophyll a and b on Lobaria pulmonaria and Xanthoria aureola at different UV-B levels (0, 0.1, 0.3 and 1.0 W m

-

2) under the laboratory conditions. Lud et al. (2001b) did

not found any differences in chlorophyll, carotenoid, UV-B absorbing compounds and photosystem II efficiency in Turgidosculum complicatulum exposed to various combinations of UV radiation and temperature. Day et al. (1999), Searles et al. (2001), Lud et al. (2002), and Newsham (2003) have found no effects of UV-B radiation on chlorophyll concentration of the plants.

We have found that UV-B absorbing compounds and phenolics in the exposed plants were increasing under the influence of UV-B radiation. Dunn (2000) reported that out of the three dominant mosses (Bryum psudotriquetrum, Ceratodon purpureus and G. antarctici) only B. psudotriquetrum produced UV-B absorbing pigments in response to increased UV-B radiation. Newsham et al. (2002) reported that the UV-B screening pigment concentrations of C. varians and S. uncinata were positively associated with daily doses of UV-B radiation in an in situ study conducted at Rothera point under 4 to 6 week. de la Rosa et al. (2001) reported that the concentrations of total phenolics were significantly increases by UV-B radiation. Dunn and Robinson (2006) reported that the higher concentration of UV-B absorbing compounds in two cosmopolitan moss with B. psudotriquetrum and C. purpureus, while Schistidium antarctici showing the lower concentration of UV-B absorbing compounds in response to UV-B radiation over the season (November 1999 - March 2000). Cockell and Knowland (1999) reported that the plants are accumulating the UV screening compounds in response to UV-B radiation stress. Rozema et al. (2002) and Singh et al. (2011) reported that the atronin, usnic acid, perlatolic acid and fumarphotocetraric acid were appeared to be constitutive in lichen, these all are UV-B absorbing compounds, takes a major part in lichens and are particularly induced by UV-B radiation. The UV-B absorbing compounds and phenolics are produced by the plants under the influence of UV-B radiation and thereby provides protection against the UV-B radiation. Therefore, in B. argenteum and X. elegans UV-B absorbing and phenolic might be responsible for providing protection against UV-B radiation.

Conclusion Our study demonstrates the changes in pigments of two cryptogamic plants under UV-B exposed conditions at high altitude of central Himalayan region of India. B. argenteum and X. elegans were naturally exposed to UV-B radiation at study sites with a maximum average UV-B irradiance of 4.38 MED/ h and minimum average UV-B irradiance of 1.72 MED/ h during the study period. In both

Singh et al. 15 the UV-B exposed plants, UV-B absorbing compounds and phenolics were increasing during the study period. These findings suggest that the UV-B radiation induces synthesis of UV-B absorbing compounds and phenolics, therefore, these plants are able to deal with negative effects of UV-B radiation. REFERENCES

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Valuing the cost of environmental degradation in the face of changing climate: Emphasis on flood and

erosion in Benin City, Nigeria

Odjugo, Peter Akpodiogaga-a Ovuyovwiroye

Department of Geography and Regional Planning, University of Benin, P. M. B. 1154, Benin City, Edo State, Nigeria. E-mail: [email protected]. Tel: +2348023718654.

Accepted 3 January, 2012

There are numerous environmental problems that plague different parts of the world in the face of climate change. These range from pollution, deforestation, indiscriminate bush burning and natural wild fire, desertification, climate change, rain and windstorms, flood, earthquake, volcanicity, drought and erosion among others. Of these environmental problems, Nigeria is affected by all except natural wildfire, volcanicity and earthquake. In Benin City, flood and erosion are two major environmental problems seriously affecting the city in recent times causing damage to property and loss of lives. The seriousness of these problems necessitated this study, which investigated the cost of environmental degradation in Benin City. Climatic trend (air temperature and rainfall) in Benin City between 1940 and 2010 were analysed while the flood and erosion characteristics in Benin City were also measured between 2008 and 2010. 741 questionnaires were administered to analyse the impacts of flooding and erosion on the respondents. The service of experts in estate valuing was sort and with that, the cost of damage caused by flood and erosion was determined. The data were analysed using time series and percentages among others. The results show that the length of the gullies ranges between 168 m and 695 m while the depth was between 0.6m and 24 m. The cost of damage to buildings and property due to erosion and flooding was N3.9billion ($23.9million) while flood claimed 14 lives between 1999 and 2010. Key words: Climate change, eateries, rainfall, damage, property, commercial activities, gullies, urban forestry.

INTRODUCTION There are lots of environmental problems that plague different parts of the world. These range from pollution, deforestation, indiscriminate bush burning and natural wild fire, drought, desertification, climate change, rain and windstorms, flood, earthquake, volcanicity and erosion among others. These are conceptualized in Figure 1. These environmental problems are caused either by unsustainable human activities, nature, or both, leading to environmental hazards or disasters. Of all the environmental problems in Figure 1, Nigeria is affected by all except natural wildfire, volcanicity and earthquake.

Although these environmental problems affect all parts of Nigeria, some are more pronounced in specific geographical regions of the country. While drought and desertification are major environmental problems

associated with northern Nigeria, deforestation, flood and erosion are the main environmental issues affecting the southern and eastern parts of the country (Odjugo and Ikhuoria, 2003; Odjugo, 2009). This research focuses on erosion and flood. While the destructive impact of erosion is relatively gradual, that of flood is more sudden and devastating. The devastating effects of flood on buildings can be categorized into different structural groups as shown in Adedeji (2008), and they include; (1) Buildings washed away due to the impact of the water under high stream velocity. Such buildings are usually destroyed or dislocated beyond feasible reconstruction. (2) Floatation of buildings caused by rising water. This occurs when light–weight houses are not securely anchored or braced. (3) Damage caused by inundation of buildings: A building


Figure 1. Global environmental problems. Nigeria is not currently affected by the shaded environmental

issues. Source: Author.

may remain intact and stable on its foundation, while its material is gradually and severely damaged. (4) Undercutting of building: here the velocity of flood may scour and erode the building‟s foundation or the soils under the foundation. This may result in total collapse of the affected buildings. (5) Damage caused by debris: massive floating objects like trees and materials from other collapsed houses may have impact significant enough to cause severe damage to the standing buildings. Structural impact like serial numbers 3 and 4 above are most common in Benin City.

Erosion and flood have seriously affected man for millennia and despite prodigious efforts to stop them, the problems still remain till today causing damage to property and loss of lives. The first ever recorded flood in the Bible destroyed all global property and lives at that time except that of Noah and his immediate family (Genesis 7: 17 to 24). The Japanese Tsunami of 2011 killed over 18,000 people while the Asian Tsunami of 2004, claimed 150,000 lives in 12 countries across Southeast Asia and Eastern Africa (Mbamba, 2004). In the U.S.A. flood disasters from hurricanes like Rita, Katrina, Wema etc, have claimed many lives and destroyed properties worth millions of dollars since 2005. The Pakistan flood claimed over 1,500 lives, displaced over 3. 2 million people and destroyed property worth millions of dollars in August 2010 (Hung, 2010). In Nigeria, the collapse of Baguda dam near Kano in 1988 with its associated flood destroyed 18,000 houses and left 210,000 people homeless. The Ogumpa River‟s flood of 1983 claimed 30 lives, destroyed many houses and left 15,000 people homeless. The flood that hit Lagos the most populous city of Nigeria on the 10th of July, 2011 claimed 25 lives (Akoni et al, 2011), that of Ibadan, Nigeria that happened in August, 2011, killed 98. Both floods rendered over 35,000 people homeless (Anibokun, 2011).

Ahmad and Ahmed (2002) shows that erosion in eastern Nigeria is caused more by relief followed by

rainfall intensity and exposed earth surface materials. Such view was also held by Osahon (2007) who says that in Auchi, Edo State, relief is the major cause of soil erosion followed by lack of vegetal cover occasioned by deforestation, poor agricultural practices and urbanization effects. The major causes of flood in urban areas of Nigeria are blocked gutters and water channels, poor drainage systems, increasing rainfall intensity, building on natural water causes, nature of topography and reduced infiltration occasioned by concrete and cemented compound (Odjugo and Iweka, 2006).

Although environmental problems have been affecting mankind throughout the ages, researches have shown that climate change has started aggravating these problems and the situation will be worse as the climate change impacts intensify Intergovernmental Panel on Climate Change (IPCC, 2007). Climate change is found to be caused by both natural and anthropogenic factors (Figure 2), but the current climate change has been attributed mainly to the former, which upset the global climate system.

Earlier studies on flood and erosion concentrated more on analyzing the causes and the physical impacts of these environmental problems. The financial implications of these environmental problems have not been receiving adequate attention in Nigeria whereas it is the financial implications that can push home the point clearer to policy makers to take action. It is on this premise that this study is structured to analyze the cost of erosion and flooding in a tropical town of Benin City, Nigeria.

MATERIALS AND METHODS

The study was carried out in Benin City, Nigeria. Benin City is located on latitude 6.20°N and longitude 5.37°E. It is situated within the equatorial climatic belt (Af Koppen‟s climatic classification). It has an annual rainfall of above 2000 mm, and its mean monthly temperature and relative humidity are 28°C and 80% respectively. Benin City occupies the lower plain of the Esan Plateau. The

eastern edge of the city tilts towards the Ikpoba River, which drains

Odjugo 19

Figure 2. Causal factors of climate change. Source: Odjugo (2010).

the north eastern portion of the city, while the western edge slopes gently toward Ogba River (Figure 3). Benin City is about 85 m above the sea level at the highest point.

The Edo State Ministry of Environment identifies 60 flood sites

and 25 erosion sites within Benin metropolis. While some of these are still minor environmental problems, others are major and devastating. Of these sites, 5 erosion sites and 7 flood areas (Figure 3) were purposefully selected because they are the worst erosion and flood areas in Benin City as indicated by the Ministry of Environment. The erosion sites include the University of Benin (E1), Costain Street (E2), Ogiso quarters (E3), Oregbeni estate (E4) and Ogbesan quarters (E5). The flooded sites are Adolo College Road (F1), Uwasota road (F2), Tomline (F3), Five Junction (F4), Siloko/Uwelu Roads (F5), Ogiso (F6) and Dumez Road (F7) (Figure 3).

Data needed for this study include erosion characteristics like the length, width, depth and area coverage, while flood data collected are flood depth and area coverage. The Ministry of Environment did not have current data on erosion and flood of the affected areas.

The data available were measured depth and width of two gully sites and four flood areas in 2002. These data are dated since the current area coverage and magnitude of damage by flood and erosion is far more than that of 2002. As a result of this deficiency, direct field measurement was conducted between 2008 and 2010. The flood characteristics were measured at the end of September every year while the erosion characteristics were measured at the end of December. The month of September usually record the highest rainfall intensity and in most cases rainfall amount with associated flood problems in Benin City (Odjugo and Iweka, 2006), that is why September is selected for the flood measurements. The


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Figure 3. Benin City showing the study area.

rains decline drastically in the month of October and dry seasons sets in by November. So by the month of December soil erosion caused by rainfall must have ended for that year hence December was chosen for the measurement of erosion.

The length, depth and width of the eroded and flooded areas were measured using the ranging poles, ropes and tapes. For the

eroded sites, the length and width were measured with a tape. At the length of every 10 m, the width and the height of the gullies were measured. The ranging poles were used to align the gully width before they were measured with the tape. The depth was also measured with the aid of rope and tape. A heavy metal nut was tied to the rope and lowered into the gully. When it gets to the bottom, the person inside the gully will signal the person on the earth surface and the point is marked on the rope. This will be drawn up and the depth is measured. The area of the gully was computed at

every 10 m length and then all the computed areas were summed up.

The extent of the flooded areas was marked with pegs then the length and width of the flooded areas were measured between September 20th and 28th of every year. A traverse of the flooded area was taken and the depth of the flooded areas was measured with the aid of ranging roles and tapes. The area was computed by measuring the length and the breadth. The cost of landed property

destroyed by the gullies and flood were arrived at by the aid of an expert in estate valuing.

The impact of flooding on vehicular damage was also assessed in four of the flooded areas where road is covered with water for hours after the rains in the month of September. The areas were Adolo College Road, Tomline, Siluko Road and Five Junction. In these areas, the number of vehicles that water enters their engines and stopped in the flooded water was counted and the phone numbers of the vehicle owners were taken on each rainy day.

Between three and seven days after, these individuals were contacted to know what it cost them to repair their vehicles.

Odjugo 21

Te

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°C

Figure 4. Temperature and rainfall trend in Benin City between 1970 and 2010.

Questionnaires were administered to 15 to 25 traders (store

owners) in each flood site who accepted to respond to the questions. This gave a total of 147 questionnaires administered. Their daily sales in the month of February and March (dry season) and June and September (Rainy season) were recorded. Four months were chosen in order to reduce the pressure of daily stock taking on the traders since it was not their custom. Secondly, February and March are the driest months in the study area while June and September the wettest.

Flooding also has advantages since it encourages street trading in Nigeria and hike in prices of public transportation. In each flooded site, 10 street traders were randomly selected and given a questionnaire to record their sales on flooded and non-flood days in the month of September. This gave a total of 40 respondents. Moreover, 60 transporters (bus drivers and motor - cyclists) were selected randomly and given questionnaires to fill in the number of passengers and the total amount earned during flooded and non-flooded days in the month of September. In all, 741 questionnaires were used for the study and they were analysed using the time

series and percentages. RESULTS AND DISCUSSION The general climatic pattern in Benin City between 1970 and 2010 shows increasing trend in both rainfall and temperature (Figure 4). While the increasing trend in temperature tends to be sharp, that of rainfall is very

gentle. The observed increasing trend in both rainfall and temperature is a major feature of, or evidence of, climate change in Benin City. Although there is a gradual decrease in rainfall in Nigeria, annual and decadal fluctuations are noticed (Figure 4). There is a sharp drop in rainfall in the following years – 1973, 1982 to 1983, 1992 to 1993 and 2003. These decadal reduction in rainfall pattern coincided with the El Nino and drought years in Nigeria with the worst drought in 1983 (Odjugo, 2005). Like rainfall, the temperature pattern also shows annual variations with 2010 recording the highest temperature followed by 2002, 2005 and 1998. These are also the world‟s warmest years ever recorded World Meteorological Organization (WMO, 2011). In Nigeria, the decade 2000 to 2010 is the hottest decade on record. Ahmad and Ahmed (2000), IPCC (2001) and Nigerian Environmental Study/Action Team (NEST, 2003) provided indicators that one could use to assess the evidence of climate change in a region. These include increasing temperature and evapotranspiration, decreasing rainfall amount in the continental interiors, increasing rainfall in the coastal areas, increasing disruption in climate patterns among others. This study reveals at least two of these features namely, increasing temperature and rainfall.


Table 1. Physical characteristics of erosion sites.

Site Length (m) Width range (m) Depth range (m) Deposited area (m2) Rate of head-on erosion

University of Benin 560 5 to16 0.6-12 113.321 4.2

Costain Road 322 4 to 26 0.9-17 16.570 1.3

Ogiso Quarters 168 4 to13 0.4-9 121.871 2.1

Ogbesan Quarters 695 3 to 25 0.9-22 140.301 5.1

Oregbeni Estate 484 7 to 29 1.1-24 136.271 7.6

Total 528.334

Table 2. Financial cost of erosion and depositions.

Site Building Eroded and Deposited area

No Cost N ($)* Area (m2) No. of plots Cost N ($)

University of Benin 5 N45 m ($300,000) 119,481 132.8 N292.219 ($1.95 m)

Costain Road 8 N72.3 m ($513.372) 21,722 24.1 N192.8 m($1.39 m)

Ogiso Quarters 9 N91.100 m ($303.000) 123,383 137.1 N383.900 ($2.560 m)

Ogbesan Quarters 25 N283.500 m ($1.89 m) 143,531 159.5 N366.9 m ($2.45 m)

Orogbeni Estate 16 N137.6m ($917,333.3) 152,464 169.4 (N N355.7 m) ($2.37 m)

58 N650.5 m ($4.33 m) 560,582 622.9 N N1.524b ($10.17 m)

*Throughout the paper, the exchange rate used was N150 to $1.

The physical features of the erosion sites are shown in Table 1. The length of the gullies varies between 168 m in Ogiso quarters to 695 m in Oregbeni Estate. Ogbesan quarters recorded the deepest (24 m) and the widest (29 m). While Oregbeni Estate recorded the largest area coverage (140,301 m

2) of sand deposits of the gully

erosion, the smallest area coverage was Costain Road (16,570 m

2). The total area eroded by the gullies was

32,248 m2 while that of deposition was 528,334 m

2. The

five gullies together with their sand deposits covered an area of 560,582 m

2 (5.6 km

2). The lowest head-on

erosion was recorded in Constain Road and the highest in Ogbesan (Table 1). With the exception of Constain Road, the rate of head-on erosion increases with increasing gully depth. Okechukwu (2010) also notes that increasing depth and gradient were major factors that accelerated gullies development in eastern Nigeria. The exception noticed in Constain is due to human factor that used the head-on side of the gully as dumpsite. Most of the solid wastes from the nearby New Benin Market (the second largest market in Benin City) and the domestic wastes by people far and near are dumped in the Constain gully. This act of refuse dump drastically reduced the rate of head-on erosion in the Constain gully.

The number of buildings that caved into the gullies and those abandoned due to the threat of the gullies and sand deposits were 58 and they were estimated to cost N650.5 m ($4.33 m) (Table 2). Out of these 58 building, the Ogbesan Quarters gully erosion has engulfed two blocks of 16 classrooms of Queen Ede Primary School and the third classroom building has been abandoned

since part of it has caved into the gully (Plate 1). The Ogbesan quarters gully has cut two roads into two and the head-on erosion is just 30.4m away from the Benin-Agbor Express Road. If no urgent and serious action is taken now, judging from the rate of head-on erosion (Table 1), the gully will cut the road into two in the next six years. The most worrisome is the University of Benin gully that has claimed one-fourth of the western fence of the University, staff quarters and buildings of individuals of Ekosodin community sharing common boundary with the University. The largest Block of Flats of the University that house both staff and students and other staff quarters are under serious threat. Gully erosion in Benin City has caused a lot of hazard not only to individual property but also to government infrastructure. The total area eroded by the gullies together with the sand deposits measured 560,582 m

2. This area was converted

to building plots of 30 by 30 m (the standard building plot of land in the study area) to ease estimation. The total building plots were 623 and these amounted to N1.52 billion ($10.2 m) (Table 2). Magbemi (2008) and Okechukwu (2010) also mention that buildings worth millions of Naira have been destroyed by gullies in Nigeria, but these works did not carry out detailed study of the number of buildings affected and the cost of gully damage to property in their study areas.

The flooded areas covered 913,313 m2 and the number

of buildings abandoned as a result of the flood (Plate 2) was 67 and these cost N1.05 billion ($7.02 m) (Table 3). The flood in Dumez Road and Siloko/Uwelu Roads has totally covered the two primary school buildings and the

Odjugo 23

Plate 1. Ogbesan Gully, Benin City showing school building caving in and the failed community effort

of drain construction to solve the gully problem.

Plate 2. One of the flooded and abandoned buildings along Siloko Road by Teachers‟ House.


Table 3. Financial cost of flooding.

S/N Location Area coverage (m2) No. of buildings Cost No. of plots Cost

1 Adolo College Road 54.000 2 76.3 m ($108.666) 3 9.30m ($62,000)

2 Tomeline 143.261 6 47.8 m ($318,666) 16 124.4 ($826,666)

3 Five Junction 95.761 - - - -

4 Siluko/Uwelu Road 391.240 12 414.4($2,763 m) 32 153.6 m ($1.024 m)

5 Dumez Road 121.500 14 438.2 m ($2,921 m) 25 135.6 m ($904,000)

6 Ogiso Quarters 79.200 5 33.4 m ($222,666) 18 81.7 m ($544,666)

7 Uwasota Road 28.351 4 42.1 m ($280,660) 46.4 m (309,333)

Total 913.313 m 67 1.052b ($7,015 m) 102 551 m (3.671 m)

Table 4. Number of vehicles damaged and the cost of repairs.

S/N Location Vehicle damaged/cost Vehicles not damaged but pushed across flood /cost

1 Adolo College Road 108 N496,800 $3212 465 N608,400 ($6528)

2 Tomline 171 N 752,400 $5016 612 N979,200 ($6528)

3 Five Junction 28 N 748440 4989.6 471825 N919800 ($6132)

4 Siluko Road 72 N 320,400 $2136 254 N259,200 ($1728)

Total 495 N 2,181,200 $14,541 2064 N2,766,600 ($184,044)

Table 5.Volume of sales during rainy and dry season in flooded areas.

S/N Locations No. of respondents Dry season Rainy season Reduction of sales during

rainy season (%)

1 Adolo College Road 25 N632,655($4,218) N380,700($2,538) 39.8

2 Tomline 26 N529,050($3,527) N284,310($1,895) 46.3

3 Five Junction 28 N748,440($4,790) N471,825($2,146) 37

4 Siloko Rd. 20 N518,010($3,453) N280,462($1,870) 45.9

5 Ogiso 15 N192,675($1,285) N124,740($832) 35.4

6 Dumez Road 15 N202,879($1,353) N84,702 ($565) 41.8

7 Uwasota 16 N241,170($1,608) N128,993($860) 46.5

Total N3,194,199($21,295) N1,869,091($12,461) 41.8

two schools have been abandoned and their students and staff relocated. The flood creates poundage which usually last for hours, weeks or months. So the flooding pattern experienced in Benin City is both flash and seasonal. In the areas affected by prolonged poundage (months) most of the building plots were left undeveloped. These were measured and they totaled 102 plots of land, which cost N550.6 m ($3.4 m) (Table 3). The total financial cost of flooding (Number of building and building plots abandoned) therefore amounted to N1.6 billion ($10.6 m).

The flooded areas in Benin City also encompass roads with heavy traffic. This has caused a lot of damage to vehicles that ply the roads as shown in Table 4. The number of vehicles that were damaged by the flood was 495 and it cost the owners N2.2 m ($14,541.3) to repair them. There were 2,064 drivers who could not risk driving

through the flood. This group of drivers employed the services of boys who are always in the flooded portion of the roads to push their vehicles across the flood while the vehicles‟ engines were put off. It cost the drivers N2.8 m ($18,444) to pay the boys that helped them to push their vehicles across the water. This amounted to an average of N1, 340 ($8.09) per driver. The total amount spent by drivers in the flooded areas was N4.95 m ($32,985).

Commercial activities were also affected by the flood as indicted in Table 5. The respondents revealed that during the dry season their sales amounted to N3.2 m ($21,295) while it was N1.9 m ($12,461) during the rainy season. This implies that the flood reduced sales by 42%. It is difficult for the consumers to wade through the water to buy things that they wanted that is why the sales were reduced during the flood period. The total cost of what was lost to flood and erosion in Benin City within the

Odjugo 25

Plate 3. Flood problem: Local effort of bridge construction to get to homes, business centres and eateries.

study area and period (2008 to 2010) is N3.63 billion $24.2 m). The aspect of commercial activities that was enhanced by the flood in Benin City is street trading and public transportation. The flood leads to various sizes of pot-holes on the road. The flood water and the bad spots lead to traffic hold up that spans for hours in most cases. The drivers and passengers in the long queues of vehicles trapped as a result of the flood become good customers to the street traders who sell various kinds of items ranging from table water, gala, bread to bumper reflectors, fire extinguishers and handkerchiefs among others. The mean sales was N4, 600 ($30.7) and N1, 480 ($9.9) for flooded and non-flooded days respectively. So while traders with permanent stores who could not involve themselves in street trading either because of their age or the type of items they sell are crying of low patronage, the street traders are laughing home with much money and even praying for more floods and traffic jams. The public transporters (taxi drivers and motorcyclists) always hike their prices between 100 and 500% whenever it rains and the roads flooded. The increase in price is worst when the flood occurs during the rush hours of the day (7 to 9 am and 4 to 8 pm). The public transporters were able to make a mean of N5, 400 during flood days and N2, 900 in non-flood days. Although the flood reduced the number of trips the public transporters could make in a day, the astronomical

increase in fares charged favour their daily take-home. The aforementioned analysis only depicts the aspect of

erosion and flood that could be quantified. The psychological depression and emotional trauma suffered by displaced landlords and tenants due to these two environmental problems, time spent by drivers (non-commercial) and their passengers in the flood, lives lost and those who fell into side drains and sustain various degree of injuries, infections caused by those who wade through the water, possible food poisoning since there are lots of eateries in the flooded areas (Plate 3), malaria fever due to stagnant water that increases mosquito breeding amongst others are difficult to quantify. Available information from the Ministry of Environment shows that while there are no reported cases of death associated with gully erosion in Benin City, flood claimed 14 lives between 1999 and 2010. In Nigeria and other parts of the world, flood has claimed lot of lives and destroyed property. For example, as at April, 2011, the Japan tsunami claimed 18,000 lives and 14,000 people were still missing six weeks after the flood and World Bank estimates that it will cost $145 biliion to repair the damage (McCurry, 2011). The South African floods of January 2011 killed over 120 people and damaged over 13,000 homes and property worth more than $211 million, while that of Rio De Jeneiro caused at least 903 deaths, (Erin, 2011).


Table 6. Perceived major causes of flooding in Benin City.

S/N Perceived causes of flooding Percentage (%)

1 Lack of drainage 87

2 Blocked drainage 85

3 Habits of dumping refuse in the run-off 81

4 Habits of building on the natural water ways 75

5 Cemented compounds that prevent infiltration and encourage run-off 72

5 Increasing rainfall intensity (70% 70

PLANNING IMPLICATIONS The major causes of flooding in Benin City as shown by the respondents are many and they include lack of drainage in some areas (87%), blocked drainage (85%), habits of dumping refuse in the run-off (81%), habits of building on the natural water ways (75%), cemented compounds that prevent infiltration and encourage run-off (72%) and increasing rainfall intensity (70%). Obi (2009) also observes some of these factors as causes of urban flooding in Nigeria. The respondents have the correct perception by showing that the major cause of flood is lack of drainage systems, because most parts of Benin City have no drains that direct the water to the rivers or purposefully acquired drain sites (Table 6).

Moreover, where there are drains, they are always very narrow and shallow thus get easily blocked by sand and refuse dumped into the run-off by the residents. It is a common practice in Benin City that whenever it rains heavily, some of the residents usually dump their refuse into the run-off principally to avert payment of fees meant for refuse collection. The Edo State government needs to urgently embark on the construction of more deep and wide surface and underground drainage systems and restructure most of the existing ones that can accommodate the run-off. These should be channeled to either Ikpoba River or Ogba River. While the government should constantly de-silt the drains, the law enforcement agencies should arrest and prosecute those who form the habit of dumping refuse into the drains. This is going to be a tedious task because for the law enforcement agents to arrest the offenders, they must have to monitor the drains while it is raining since there are no existing automated cameras installed in Benin City that can do such monitoring.

The government should ensure that buildings and other structures on the natural waterways are pulled down to allow free natural flow. Pulled down structures with approved government plans should be adequately compensated. The Urban and Town Planning Department together with the Ministry of Environment should encourage urban forestry and discourage the practice of totally cementing the entire section of the compound not built. Trees, grasses and flowers will not

only enhance infiltration, add to the aesthetics of the compound and reduce run-off but also act as sources of vitamins and income if most of them are economic trees. If these appropriate measures are taken, for sure, the drains will accommodate the water despite the fact that the intensity of rains is increasing in Benin City.

The survey also shows that lack of drainage system (92%), poor maintenance of the existing drains (84%), negligence on the part of government (82%) and improper land use (76%) were identified as the major causes of erosion in Benin City. Since the drainages are inadequate to properly channel the water, the water then finds it way thereby creating its channels which may later develop to gullies. The neglect by government in solving the erosion problems when the gullies were small led to the present precarious state of gullies in Benin City. The communities where the gullies are found have been making frantic efforts in resolving the erosion problems in Benin City. For example, the Ogbesan Community raised money in 2007 to channel the water to the river. The drain constructed (Plate 2) could not survive the first rainy season before the lateral erosion led to its collapse. This clearly shows that the problem is beyond their financial and technical reach to solve. The solution to most gullies‟ problems in Benin City seems hopeless since the cost of resolving the problem is now beyond the financial capability of the inhabitants, institutions and even the State Government. The Edo State Government made it clear since 2003 that the solution to gullies that this study is investigating is beyond her financial reach. To make the situation more hopeless, the Minister of Environment having inspected the gullies in Benin City and other parts of Edo State in 2010 openly declared that the assistance of the Work Bank is needed to tackle the erosion menace in the State. This paper is therefore making a clarion call on the World Bank and other international ecological foundations to come and rescue the inhabitants of Benin City from the hazards of gullies. Conclusion The study reveals that different parts of Benin City are affected either by flood or gully erosion. While the length

of the major gullies ranges from 168 to 695 m, their width and depth were 3 to 29 m and 0.4 to 24 m, respectively. The gullies together with their sand deposits cover an area of 560,582 m

2, while flood occupies 913,313 m

2.

The number of buildings that caved into the gullies and those abandoned due to erosion threat and deposits are 58 while flood either destroy or forced people to abandon 67 buildings.

The cost of damage caused by erosion and its associated sand deposits amounted to N1.52 billion ($10.17 m). Flood damage to buildings and land rendered useless for any construction purpose cost N1.524 billion, while the cost of damage to vehicles is N4.95 million ($32,985). A drop in sales during the rainy season when compared to that of dry season is 42%. Overall, N3.9 billion ($23.9 million) has been lost to erosion and flood in selected sites in Benin City. The implication is that if damage caused by 7 flood and 5 gullies is as much as N3.9 billion one could imagine the damage the 60 flood sites and 25 gullies in Benin City must have caused. This is outside the unquantifiable cost of gully erosion and flood that caused deaths, psychological and emotional trauma.

The paper shows that while flooding problem in Benin City is still within the reach of the state government to solve, the gully problem has gone beyond the financial limits of the state government. The Federal Government in collaboration with international organizations should as a matter of urgency come to the rescue of those being threatened by gullies in Benin City. The Edo State Government should as a matter of urgency start solving the smaller gully erosion problems in Benin City now before they turn to major gullies that will demand billions of naira to solve. A stitch in time, they say saves nine. ACKNOWLEDGMENT The author wish to acknowledge the Centre for Population and Environmental Development (CPED), Benin City, Nigeria, that partly sponsored this research. REFERENCES

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http://www.scribd.com/doc/9268022/%20Environmental-Hazards-Flooding-and-Its-Effects-on-Residential-Buildings-in-Ilorin-Nigeria

http://www.scribd.com/doc/9268022/%20Environmental-Hazards-Flooding-and-Its-Effects-on-Residential-Buildings-in-Ilorin-Nigeria



Palynostratigraphy and palaeoenvironmental characterization and evidence of Oligocene in the

terrestrial sedimentary basin, Bingerville area, Southern Côte d'Ivoire, Northern Gulf of Guinea

Bruno Zeli Digbehi1*, Mamery Doukoure1, Juliette Tea-Yassi2, Raphael Konan Yao2, Jean-Paul N’goran Yao1, David Kouakou Kangah2 and Ignace TAHI2

1Université de Cocody, UFR-STRM, 22 BP 582 Abidjan 22, Côte d’Ivoire.

2Petroci, Centre d’Analyses et de Recherche (CAR), B.P. V 194, Abidjan, Côte d’Ivoire.

Accepted 24 October, 2011

A palynological investigation of two shallow boreholes in Anna, Bingerville area, at 13 km Northwest Abidjan, Southern Côte d’Ivoire, yielded rich and relatively well-preserved dinoflagellate cyst’s assemblages that allowed recognition of Oligocene age. This recognition was based on global dinoflagellate cyst events, including mainly Lejeunecysta species represented by cf. Lejeunecysta communis, L. lata, L. pulchra, Lejeunecysta sp. cf. L. granosa, cf. L. globosa, L. beninensis and other Pheolodinium magnificum, P. africanum, Selenopemphix nephroïdes and Cordosphaeridium inodes. They are associated to terrestrial spores and pollen grains such as Magnastriatites howardii, Spirosyncolpites spiralis, Perfotricolpites digitatus, Retitricoporites irregularis, Retimonocolpites irregularis, Pachydermites diederixii, Psilatricolporites operculatus and Punctodiporites harrisii. The palynostratigraphic interpretations are based on a comparison with calibrated dinoflagellate cyst ranges from several reference sections, mainly in the peri-atlantic and incidentally peri-pacific basins. This study showed changes in the relative abundances of different species or groups of morphologically related species. These changes are palaeoenvironmentally controlled, indicating a deposition occurred between the continental nearshore and marginal marine areas under continental influence. The prevalence of peridinioid dinocysts assemblage suggests deposition in a subtropical province whereas terrestrial pollen grains and spores provided by plants of coastal vegetation dominated by pteridophyts and angiosperms evoke mangrove and swamp forests. These new palynological data, notably the presence of Oligocene especially in the Ivorian terrestrial basin north of the so called “faille des lagunes”, specifies and modifies the previous local stratigraphic scale. Key words: Palynostratigraphy, palaeoenvironment, Oligocene, sedimentary basin, Côte d’Ivoire.

INTRODUCTION Many works based on Cretaceous-Tertiary sedimentation in Côte d'Ivoire basin (Figure 1) were summarized recently by Sombo (2002) and indicated Oligocene hiatus also recorded in some West African coastal basins. For these studies, this hiatus was probably due to a general *Corresponding author. E-mail: [email protected]. Tel: +225 20 370 977 / 09 356 739.

uplift of continental shelves, followed by the West African coastal erosion by the end of Eocene. In recent years, the Laboratory of geology at the University of Cocody, Côte d’Ivoire, undertook sedimentological and biostratigraphic studies especially in the terrestrial part of the coastal basin (Charpy and Nahon, 1978; Bachiana et al., 1982; Digbehi et al., 1993; 1994) where Oligocene stage was never recorded.

In Bingerville area (Figure 2), are exposed various facies of the "continental terminal" series, a package of

Digbehi et al. 29

Figure 1. Geological setting and Cretaceous-tertiary sedimentary basin of Côte d'Ivoire.

Mio-Plio-Quaternary age as described in the synthesis of Digbehi et al. (2001). Few works in this area provided controversial results concerning the age of deposits that underlie this ―continental terminal‖ series. Thus, Bacchiana et al. (1982) identified Miocene formations based on foraminifera assemblage and terrestrial spores and pollen species (Verrutricolporites rotundiporus, Racemonocolporites hians, Psilatricolporites crassus, Retibrevitricolporites protrudens, Arecipites exilimuratus).

In contrast, recent student’s unpublished works around Bingerville, located North of the so called ―faille des lagunes‖, and performed on gray clay underlying the ―continental terminal‖ series, described a palynological assemblage characterizing Oligocene age. The present

study was undertaken to establish a precise local palynostratigraphy in this area. It also aimed to propose a palaeogeagraphic reconstruction of the deposits crossed by the two shallow boreholes based on palyno-facies analysis. COTE D'IVOIRE STRATIGRAPHIC OVERVIEW Synthetic stratigraphic models proposed by many authors cited by Digbehi (1987), Chierici (1996) and Sombo (2002), summarized geological history of Côte d’Ivoire basin in four main steps: a) a rifting phase (Barremian-Albian) with margino-littoral sediments; b) a phase of


Figure 2. Surface geological settings and location of the shallow boreholes P1 and P2 in Bingerville area.

initial ocean expansion with first true marine transgressive deposits (Cenomanian-Lower Senonian) that allowed deposition of calcispherids limestones eroded during lower Senonian; c) a phase of active expansion and subsidence (Campanian-Maastrichtian) with transgressive marine clays overlying surfaces of erosion affecting in places cenomanian series; d) a phase of maximum expansion in tertiary during which occurred a major regressive phase ranging from late Eocene to Oligocene. During Cenozoic, marine sedimentation is mainly silico-clastic and occasionally carbonated. The Palaeocene series are generally clayey and occasionally glauconitic with limestone and sand observed in outcrops (Fresco) by Reyre and Tea (1981) based on dinoflagellate (Apectodinium) assemblage. In the eastern basin, palaeocene reaches 500 m thick (Digbehi et al., 1996; 1997). The Eocene (490 m) consists of sandy clays with small limestone beds (Ypresian-Lutetian) and shale’s more or less sandy and glauconitic (Aka, 1991). The Lower Miocene is described in a small depression around Abidjan where it consists of dark shales of 600 m thick, rich in foraminifera (Klasz and Klasz, 1992). These marine shales are overlain or pass laterally into red shales, gray and white, kaolinitic facies.

MATERIALS AND ANALYTICAL METHODS

Fifty-three cutting samples recovered from indistinct tertiary

succession in Bingerville area, (Figure 2) penetrated by two shallow boreholes P1 (20'21''N 03° 51'33''W, 29 samples) and P2 (05°20'18'' N and 03°51'34'' W, 24 samples), drilled in Southern Côte d’Ivoire terrestrial basin, are investigated for this study. These boreholes are separated by approximately 135 m, and are respectively 10.14 and 11.13 m of total depth.

Lithological analysis based on the field visual description of the 53 cuttings was complemented by observations of washing residue under a binocular microscope in. It resulted in synthetic lithological logs of two boreholes. Only 25 productive samples (the 28 others were barren and unproductive) were prepared according to standard palynological procedures (Oboh et al., 1996; Mahmoud and Shranck , 2007). Dilute hydrochloric (HCl 50%) and cold concentrated hydrofluoric (HF 70%) acids were used to remove

carbonates and silicates respectively. The digested residues were then treated again with HCl (50%) to dissolve fluorides if any. Residues were screened through a 10 μm nylon polyamide sieve. For qualitative and quantitative study, at least two permanent slides per sample were prepared using Canada Basalm as mounting medium. The slides were examined using a Motic light microscope equipped with an integrated Motic digital camera. For quantitative palynology, a count of about 100 to 150 grains was made for each

sample (when possible). Taxonomic determination of spores and pollen grains was based on morphographic classification of Potonie (1970) whereas identification of dinoflagellate cysts was done following Lentin and Williams (1985; 1987; 1989). The slides were stored at the Laboratory of Biostratigraphy, University of Cocody, Abidjan. The age determination of the drilled sediments was based solely on these palynological results. Palynostratigraphic interpretations were based on comparison with already identified dinoflagellate cysts ranging from several reference sections, mainly

in the peri-Atlantic basins. Their relative abundance was assessed in each well by adopting

an arbitrary classification using the concepts of rare (0-5 taxa),

Digbehi et al. 31

Figure 3. Lithostratigraphical correlation summary of the boreholes P1 and P2 in Bingerville area.

present (6 to 15), common (16 to 50) and abundant (>50). Depositional palaeoenvironment was approached by changes in the relative abundance of different species or groups of morphologically related species more specifically between terrestrial pollen and spores and marine dinoflagellate cysts, as adopted in many works (El-Beialy, 1990; Sluijs et al., 2005; Prebble et al., 2006). RESULTS Figure 3 shows lithostratigraphic correlation synthesis of the two boreholes. Four lithofacies are distinguished along each of them and they range upwards as follows: (i) gray clays which provided the whole microflora analyzed; they are overlain by (ii) variegated clays above a hard surface (or hard ground) consisting of ferruginized clay that seems to represent periods of stop in the cementation process, with the result this soft sediment units alternate one with the other layers; (iii) subjacent ochre’s sandy clays include gravel; these sandy clays are topped by (iv) gray clayey sands called "terre de barre" with levels of stone line. Because of their sharp deterioration, the twenty-eight samples of superficial levels (0 to 5, 64 m in P1 and 0 to 5, 63 m in P2), were

barren and provided no microfossil (foraminifera and palynomorphs). Palynostratigraphical approach The residual materials recovered after maceration of samples for palynological analysis are mainly composed of amorphous organic matter and fragments with colors ranging from brown to dark. The most abundant are wood remains (wood cuticles or stems). Microflora provided by these boreholes includes modest numbers of marine and terrestrial palynomorphs with an average abundance of 30 species (Index). These assemblages exceptionally limited in diversity but globally dominated by Lejeunecysta species (Lejeunecysta sp. cf. L. communis, L. lata, L. pulchra, cf. L. granosa, L. globosa, cf. L. beninensis) associated with other species Pheolodinium magnificum, P. africanum, Tuberculodinium vancampoae, Selenopemphix nephroïdes, Batiacasphaera spp dont Batiascaphaera sp. cf. B. micropapillata and Cordosphaeridium inodes. Terrestrial assemblage retrieved from this section was composed of


DEPTH (M)

Batiacasphaera spp

Exochoshaeridium bifidium

Cometodinium spp

Achosmophaera spp

Lejeunecysta spp

Inaperturopollenites spp

Monosulcites spp

Tricolpopollenites spp

Retitricolporites irregularis

Retitricolporites spp

Monocolpites spp

Retimonocolpites irregularis

Triorites spp

Tetrad spp

Verrucatosporites usmensus

Deltoidospora spp

Hystrischopharidium sp

cf. Spinidium spp

Cordosphaeridium inodes

Tuberculodinium vancampoae

Crototricolpites densus

Pachydermites diederixi

Spirosyncolpites spiralis

Psilatricolporites operculatus

Spore indet

Glaphyrocysta spp

Perfotricolpites digitatus

Phelodinium spp

Retibrevitricolpites triangularis

Magnastriatites howardii

Operculodinium spp

Bombacacidites spp

Tricolpites spp

Acritarchs

Foraminiferal test inner linings

STAGE

DEPTH (M)

Figure 4. Relative frequency of main palynomorphs populations (spores, pollen grains and dinoflagellate cysts) recorded in the borehole P1 in Bingerville area.

Magnastriatites howardii, Spirosyncolpites spiralis, Retimonocolpites irregularis, Retitricoporites irregularis, Pachydermites diederixii, Perfotricolpites digitatus and Psilatricolporites operculatus. The taxa most representative of this assemblage are recorded in Figures 4 and 5 according to depth in each of two boreholes. The relative frequency of occurrence of these taxa in both borehols a P1 and P2 shows a broadly similar distribution (Figures 4 and 5): 1) Batiacasphaera spp including the species

Batiacasphaera sp cf. micropapillata is the most abundant dinoflagellate cysts identified; 2) The whole species of Lejeunecysta spp. is present and relatively concentrated on the top wards; They are more frequent in P2. 3) Cordosphaeridium inodes is observable only in one sample at the base of P1 (sample 10.14 m); 4) Retitricolporites irregularis and Retimonocolpites irregularis broadly follow the same vertical pattern while Psilatricolporites operculatus is only visible in the upper two-thirds of the productive interval; They are very

Digbehi et al. 33

DEPTH (M)

Batiacasphaera spp

Exochoshaeridium bifidium

Cometodinium spp

Achosmophaera spp

Dino indet

Tuberculodinium vancampoae

Selenopemphix nephroides

Lejeunecysta spp

Inaperturopollenites spp

Monosulcites spp

Monocolpites spp

Tricolpopollenites spp

Retitricolporites irregularis

Retimonocolpites irregularis

Spirosyncolpites spiralis

Triporites spp

Psilatricolporites operculatus

Tetrad

Verrucatosporites usmensus

Deltoidospora spp

Polyadopollenites spp

Spore indet

Perfotricolpites digitatus

Retibretricolpites triangularis

Magnastriatites howardii

Pachydermites diederixi

Phelodinium spp

Stephanocolporites spp

Tricolpites spp

Acritarchs

Foraminiferal test inner linings

STAGE

Figure 5. Relative frequency of main palynomorphs populations (spores, pollen grains and dinoflagellate cysts)

identified in the borehole P2.

constant in both boreholes 5) The whole palynological assemblage is dominated by non-diagnostic taxa such as indeterminate forms Inaperturopollenites spp., Monosulcites spp., Tricolpopollenites and Deltoidospora spp. that are common to numerous throughout the interval.

The best preserved taxa of spores, pollen grains and dinoflagellate cysts are illustrated in Plates 1, 2 and 3. This assemblage of both boreholes, thought to be Oligocene age, contains also microforaminiferal inner test linings (planispiral and trochospiral shaped) and rare acritarchs.


Plate 1. Assemblage of main dinoflagellate cysts described in the two shallow boreholes in Bingerville area. All

dinocysts are ×1000. A. Lejeunecysta lata, M40/2; P2 (9.73 m). B. Lejeunecysta lata, D39/3; P1 (7.24 m). C. Lejeunecysta lata, S 34/4; P1 (7.24 m). D. Lejeunecysta sp.cf. L. beninensis. V 31/2, P2 (9.23 m). E. Lejeunecysta sp.cf. L beninensis, K 24/3, P2 (6.13 m). F. Lejeunecysta sp.cf. L granosa, R 44/4, P1 (7.24 m). G. Lejeunecysta sp.cf. L granosa, phase contraste, R 44/4, P1 (7.24 m). H. Lejeunecysta sp.cf. L granosa, O 37/1, P1 (10.14 m). I. Lejeunecysta sp.cf. L granosa, L 25/1, P1 (10.14 m). J. Lejeunecysta pulchra, V 44, P2 (6.13 m). K. Lejeunecysta sp.cf. L globosa, K 47/1, P1 (6.94 m). L. Lejeunecysta sp.cf. L communis × 1000, S 28/4, P2 (10.23 m).

Palynofacies and depositional environments Quantitatively, 6498 palynomorphs were counted in the two boreholes P1 (3035) and P2 (3463). In P1 (Figure 6A), 1760 spores and pollen grains represent 58% and 1275 dinocysts, acritarchs and microforaminiferal inner test linings, 42%. Marine microplanktons varied in proportion with inner walls (29.3%), dinocysts (61%) and acritarchs (9.7%). In contrast, P2 (Figure 6B) shows spores and pollen grains representing 36%, whereas marine microorganisms (64%) are mainly represented by microforaminifers (48.8%), dinocysts (46%) and acritarchs (around 5.2%). Among the dinoflagellate cysts in productive intervals (Figure 7) the vertical distribution shows populations of proximates relatively well represented in regards to chlorates types even if they appear ''sawtooth'' shaped in P1 than in P2.

In both boreholes, the relatively high values of Proximate populations (Batiacasphaera spp,

Lejeunecysta spp.) to the detriment of Chorate dinocyst (Achomosphaeridium sp., Cometodinium sp.) suggest shallow marine setting that could be attributed to estuarine-marginal marine environment. In the two boreholes two palynological sub-facies reflecting two distinct environments are distinguished (Figure 8).

In the sub-facies 1 (10.14 to 8.54 m) in P1, (10.23 to 8.73 m) in P2, fluctuation curves are ''sawtooth'' shaped reflecting more frequent neashore influence in marine marginal setting. - In sub-facies 2 (8.54 to 5.64 m) in P1 and (8.73 to 5.63 m) in P2, spores and pollen grains are dominant compared to marine microplankton in P1. This high percentage of terrestrial spores and pollen grains indicate a continental nearshore influence, also supported by the abundance of woody debris and epidermal tissues. In contrast, in P2, marine microplankton and terrerstrial populations are equivalent, suggesting marginal setting. Therefore, these two sub-facies suggest sedimentation operated in estuarine area

Digbehi et al. 35

Plate 2. Assemblage of main dinoflagellate cysts described in the two shallow boreholes in Bingerville area

(continued). All dinocysts are ×1000. M. Selenopemphix nephroides, E 44, P1 (8.14 m). N. Selenopemphix sp.cf. S. coronata, J 44/3, P2 (9.23 m). O. Achomosphaera sp. cf. A. gabonensis, J 32, P1 (10.14 m). P. Pheolodinium africanum, V 29/1, P2 (5.63 m). Q. Phelodinium magnificum, E 48/2, P1 (10.14 m). R. Tuberculodinium vancampoae, G 38/2, P2 (9.73 m). S. Cordosphaeridium inodes, V 46/1, P1 (10.14 m). T. Batiacasphaera sp. cf. B. micropapillata, E 33/4, P1 (8.54 m). U. Batiacasphaera sp. cf. B. micropapillata, K 38/4, P2 (6.78 m). V. Exochosphaeridium bifidum, J 26/1, P1 (10.14 m).W. Trochospiral microforaminiferal

inner test linings, Natural light × 400, G 23/1, P1 (8.54 m). ×. Planispiral microforaminiferal inner test linings, Phase contraste ×400, N 33/3, P1 (8.14 m).

under a marine influence. Attempt to botanical and paleoecological reconstruction Some taxa identified in this work led to grouping of them according to several botanical affinities (Figures 9 and 10): 1) Thallophytes fairly represented (1%) by Hytrichosphaeridaceae (Hystrichosphaeridium sp., Cordosphaeridium sp.) are common in tropical forests near the coast (Selkirk, 1974) and increased humidity associated with high temperature; 2) Pteridophyts are abundant (56% in P1 and 67.75% in P2) with various botanical affinities as Parkeriaceae (Magnastriatites howardii), Cyatheaceae (Deltoïdospora spp.) and Polypodiaceae (Verrucatosporites usmensis). According to Salard, (1977), this association suggests a

wet and marshy area whereas the palaeoclimate is considered to have been warm temperate and humid in accordance to works of Mai (1998). 3) Spermaphyts (43% in P1 and 32.25% in P2) associating monocotyledon Palms (Retimonocolpites irregularis), and dicotyledon Guttiferous (Pachydermites diederixii, Psilastephanocolporites sp.) as well as Leguminosae (Spirosyncolpites spiralis) indicate moist evergreen forests and swamp. In conclusion, many microorganisms of terrestrial origin in Bingerville area, are provided by coastal vegetation plants (mangrove and swamp forests) dominated by Cyathaaceae, Polypodiaceae and Palms; vegetation developed under tropical climates usually hot and humid. DISCUSSION Many works (Dybkjær, 2004; Hannah, 2006; Pross et al., 2009) use dinocyst data as an important tool for pointing


Plate 3. Main terrestrial spores and pollen grains recorded in the two shallow borehones in Bingerville area. All taxa

are ×1000. A. Magnastriatites howardii, E33/3, P2 (9.73 m) .B. Spirosyncolpites spiralis, D 39/1, P1 (9.66 m). C. Pachydermites diederixii, W 18/3, P2 (9.73 m) . D. Perfotricolpites digitatus x1000, L 29/3, P1 (9.84 m). E. Punctodiporites harrisii, N 19/3 P1 (5.64 m). F. Retitricolporites irregularis, F 20/4, P1 (6.94 m). G. Retitricolporites irregularis, F 20/4, P1(6.94 m) H. Crototricolpites densus, T 46, P1 (7.24 m). I. Psilatricolporites operculatus, Q 47/4, P1 (8.14 m). J. Retimonocolpites irregularis, T 41, P1 (7.24 m). K. Bombacacidites sp. ×1000, F 24/1, P2 (7.73 m). L. Verrucatosporites usmensis , U 46/1, P1 (7.24 m). M. Inaperturopollenites in tetrad, U 33/4, P2 (9.73 m). N. Polyadopollenites sp., F 19/1, P1 (6.94 m). O. Palynological facies (organic matters) ×100. V 42/3, P1(9.24 m).

out stratigraphic sequences in boreholes, showing distinct changes at the sequence boundaries and increased relative abundance and diversity of dinocysts at marine flooding surfaces. These dinocysts are herein used for correlating between the two studied boreholes, for dating deposits, for interpreting changes in the depositional environment because eustatic sea-level

changes are considered to be the main factor in sequence formation and changes in the depositional environment (Larson et al., 2010). Other works (Bruch

and Mosbrugger, 2002; Hably et al., 2007; Akkiraz et al., 2011) document that stratigraphic intervals were also analyzed to reconstruct climate and vegetation based on independent or combined quantitative approaches when

Digbehi et al. 37

Figure 6. Sectorial distribution of palynomorphs in P1(A) and P2 (B) in Bingerville area.

applied on detailed palynological data. In ancient depositional environments (Oboh et al., 1998; Beraldi et al., 2006; Vincens et al., 2006), the diversity and abundance of palynomorphs being transported into, and preserved in the basin of deposition, are dependent on number of fundamental factors (climate, vegetation and sediment supply) as well as burial conditions. In this way, successive shifts in the composition of the dinoflagellate cyst assemblages are often interpreted in terms of sea-level and sea-surface temperature (SST) fluctuations (Brinkhuis, 1994).

It is true that all these general considerations are not applicable to this study performed in Bingerville area. But based on available data from this work, it is conceivable to discuss two fundamental aspects: (i) the validity of the local palynostratigraphic scale proposed and (ii) the paleobotanical and paleoecologic context of sedimentation in this part of the Ivorian terrestrial basin during Oligocene. Validity of the local palynostratigraphical scale proposed In general, almost species of Lejeunecysta (Lentin and Williams, 1985) including Lejeunecysta. lata, L. pulchra, L. fallax, L. cf. granosa, characterize Oligocene age, and most of these species were encountered in the present palynological residues. In other works (Salard, 1977; Duenas, 1980; Biffi and Grignani, 1983; Prebble et al.,

2006) they are associated to terrestrial or other marine Oligocene indicator species (Cicatricosisporites dorogensis, Verrutricolporites rotundiporus, Selenopemphix nephroïdes, Magnastriatites howardii, Cicatricosisporites dorogensis Punctodiporites harrisii (although scarce in our study) , Perfotricolpites digitatus). In contrast, Salard-Cheboldaeff (1979) estimated that species Pachydermites diederixii, Retitricolporites irregularis and Bombacacidites sp. are Miocene age in Senegal, while Verrutricolporites rotundiporis marks this stage in kwa-kwa formations in Cameroon. This species is absent in residues studied, indicative therefore of a probable absence of Lower Miocene in Bingeville area. Moreover, according to works citez by Mao et al. (2004), Cordosphaeridium inodes, uncommon in Bingerville area (only five specimen are recorded in borehole P1, 10.14 m deep) is Oligocene age in Australia, Oligocene-middle Miocene or Eocene age in Germany. The absence of Fossil mimosoid pollen recorded in the Lower Oligocene of the Ebro Basin, northern Spain (Cavagnetto and Guinet, 1994) is indicative of the correlatively absence of Lower Oligocene in Bingerville area. Number of other works (Mao et al., 2004; Versteegh et al., 2007) mentions key species of Oligocene (Enneadocysta pectiniformis; Cordosphaeridium gracile, Homotryblium tenuispinosum Thalassiphora pelagic) that are unfortunately absent in the present works. According to Bujak (2009), Tuberculodinium vancampoae is mainly Miocene- top of Pleistocene age, Lejeunecysta golobosa of upper-middle Miocene age, Selenopemphix nephroides is base of


Figure 7. Vertical distribution of Proximate and Chorate Dinoflagellate cysts in

5.63

6.13

Figure 7. Vertical distribution of Proximate and Chorate Dinoflagellate cysts in

the two boreholes P1 (A) and P2 (B) compared to terrestrial populations in Bingerville area.

Oligocene top of Pliocene age, Lejeunecysta granosa is Rupelian age and Cordosphaeridium inodes is assigned to Paleocene to Priabonian age. Some species of Oligcène assembage age defined in this work have a vertical extent varying according to latitude and basins. Thus, according Slimani et al. (2010), Lejeunecysta globosa, Lejeunecysta communis and Cordosphaeridium inodes as well as many of indeterminate forms Glaphyrocysta spp. are known in the top of the Maastrichtian at Ouled Haddou, southeastern Rif, Morocco. Similarly, species Exocosphaeridium bifidum, and Phelodinium africanum and P. magnificum are known from the base of the Danian. Moreover, many forms of indeterminated Lejeunecysta are recorded in the Miocene deposits on the continental margin of New Jersey, USA (Verteuil, 1996). For other palynomorphs, the FAD and LAD were established in the Llanos and Llanos basins in footshills Colombia (Jaramillo et al., 2005). Thus, Selenopemphix nephroides is between the FAD (17.83 Ma) and LAD (6.89 Ma), Tuberculodinium

vancampoae (18.03 to 3.46 Ma), Verrucatosporites usmensis (36.57 to 0, 08 Ma), Perfotricopites digitatus (49.62 to 1.26 Ma), Spirosyncolpites spiralis (42.69 to 2.22 Ma) and Retibrevitricolpites triangulatus (51.28 to 32, 14 Ma). In shallow marine deposits of Kalmthout wells North of Belgium, Louwye and Laga (1998) showed a palynflora which most species were encountered in this study but dated of undifferentiated Neogene age. These species are Tubeculodinium vancampoae, Selenopemphix nephroides, Selenopemphix coronata, Cordosphaeridium inodes,, Cordosphaeridium gracile, Batiacasphaera micropapillata, Adnasphaeridium multispinosum and Apectodinium homomorphum.

In Deutschland, the compiled distribution of dinoflagellate cysts established by Kothe and Piesker (2007) indicates that Selenopemphix nephroides is comprised between Paleocene (D4na) and Eocene (DN2B), Batiacasphaera micropapillata and Tuberculodnium vancampoae were recorded in the interval late middle Eocene (D11), late middle Miocene

Digbehi et al. 39

Figure 8. Vertical distributions of palynomorphs and depositional interpretation in the boreholes P1(A) and P2 (B) in Bingerville

area.

(D19), Cordosphaeridium inodes observed in the indistinct Paleogene (D3na-D15) and Phelodinium magnificum (D3nb-D6). Pramparo and Papu (2006) have identified in Upper Maastrichtian age formations of Cerro Butalo, south of the province of Mendoza in Argentina, species such as Lejeunecysta granosa and Phelodinium magnificum. In addition, Costa and Downie (1979) described in the Rockall Plateau, the species Cordosphaeridium inodes and have dated Paleocene - top middle Eocene.

Despite some differences in palynological assemblages composition between west-central Africa coastal basins and the study area (Northern Gulf of Guinea), main stratigraphical species indicators of Oligocene occur in both regions. Therefore, the stratigraphic distribution of species identified in this work clearly confirms Oligocene age (Figures 4 and 5). The present palynological analysis substantially improves the understanding of the depositional history and processes within the Northern so-called ―faille des lagunes‖ in Bingerville area. Palaeocological and palaeobotanical contexts Detailed investigations of biological affinities of some

pollen grains revealed a number of plant fossils. Therefore, we conclude that the floral diversity and ecological characteristics of the pollen taxa identified indicated that Oligocene vegetation in Bingerville area was characterized by a complex mangrove swamp reflecting warm climatic conditions in accordance to works of Cavagnetto and Anadón (1996). Furthermore, in many regions, evidences of temperature increase were established at the end of the Oligocene or at the beginning of the Miocene, more precisely during the Aquitanian (Sittler, 1967). According to Germeraad et al. (1968), one of the most important aspects of nearly twenty years of intensive study of the pollen-and-spore content of tertiary sediments in some parts of tropical South America, Africa and Asia, is their statistically achieved uniformity. This is demonstrated by a larger number of marker species which occurred notably in both the South American and west African regions, tropical today (transatlantic distribution). More later, this uniformity continued to be observed. Indeed, works of Servant et al. (1993) showed that late Quaternary pollen assemblages from three lacustrine cores (West Cameroon, southeastern Amazonia and central Brazil) are correlated, by the radiocarbon chronology, with other palaeoenvironmental records in Africa and South


Figure 9. Sectorial distributions of various botanical affinities identified within the boreholes P1 and P2 in Bingerville

42.54

55.6

32.25

67.75

1.09

Figure 9. Sectorial distributions of various botanical affinities identified within the boreholes P1 and P2 in

Bingerville area.

Figure 10. Botanical affinities of palynomorphs deducted form the palynological studies of boreholes P1 and P2 in

Bingerville area.

America, with a well-developed dense forest observed in both continents at this time.

Conclusions

The following conclusions may be drawn from the results of the present study:

1) The palynological analysis of gray clays that underlies the barren Mio-Pliocene variegated clays in Bingerville area, reveals a palynoflora relatively rich, well preserved. Marine Dinoflagellate cysts assemblage recorded is dominated by species Lejeunecysta pulchra L. lata, L. fallax, L. cf. granosa associated to Selenopemphix nephroïdes, Tuberculodinium vancampoae, Batiacasphaera sp. cf. Batiacasphaera micropapillata and Cordosphaeridium inodes. Terrestrial spores and pollen are associated to this assemblage namely

Magnastriatites howardii, Spirosyncolpites spiralis Perfotricolpites digitatus, Pachydermites Diederixii, Bombacacidites sp., Punctodiporites harrisii, Retitricolporites irregularis, Retimonocolpites irregularis etc.. This assemblage is particularly very similar to that described in Nigeria, which characterizes Oligocene age; 2) Detailed facies within the sections show a sedimentation realized on marginal marine areas with frequent continental influence. 3) Terrestrial spores and pollen imply botanical affinities as plants of a coastal vegetation (mangrove and swamp forests). This vegetation with dominant Cyatheacea, Polypodiaceae and Palms, generally develops under hot and humid tropical climate conditions. 4) These new results complement the previous local palynostratigraphic scale and confirm the presence of Oligocene in north of the so-called ―Faille des lagunes‖ within the terrestrial sedimentary basin of Côte d'Ivoire.

List of the main recorded taxa Dinoflagellate cysts Achomosphaera sp.cf. A. ramulifera gabonensis. (Boltenhagen, 1977) Lentin and Williams, 1981 Batiacasphaera sp. cf. B. micropapillata (Stover, 1977) Cometodinium sp. Cordosphaeridium inodes (Klumpp, 1953) Eisenack, 1963, emend. Sarjeant, 1981. Dino indet. Exochosphaeridium bifidum (Clarke and Verdier, 1967) Clarke et al., 1968). Glaphyrocysta spp. Hystrichosphaeridium spp. Lejeunecysta sp. cf. L. beninensis (Biffi and Grignani, 1983) Lejeunecysta sp. cf. L.communis (Biffi and Grignani, 1983) Lejeunecysta globosa (Biffi and Grignani, 1983) Lejeunecysta sp. cf. L. granosa (Biffi and Grignani, 1983). Lejeunecysta lata (Biffi & Grignani, 1983). Lejeunecysta sp. cf. L. pulchra (Biffi and Grignani, 1983). Lejeunecysta spp. Operculodinium sp. Phelodinium sp. cf. L. africanum (Biffi and Grignani, 1983). Phelodinium magnificum (Stanley, 1965) Stover and Evitt 1978 Selenopemphix nephroides (Benedek, 1972) Bujak et al., 1980. Selenopemphix coronata (Bujak in Bujak et al. 1980) Spinidinium spp. Tuberculodinium vancampoae (Rossignol, 1962) Wall, 1967. Spores and pollen grains

Bombacacidites spp. Crototricolpites densus (Salard-Cheboldaeff, 1978). Deltoïdospora spp. Monocolpites spp Inaperturupollenites sp. Magnastriatites howardii (Germeraad et al., 1968). Monosulcites sp. Pachydermites diederixi (Germeraad et al., 1968). Perfotricolpites digitatus (Gonzalez, 1967) Polyadopollenites spp. Psilatricolporites operculatus, (Van der Hammen and Wijmstra, 1964). Psilatricolporites sp. Punctodiporites harrisii (C.P. Varma and Rawat, 1963). Retibrevitricolpites triangulatus (Van Hoeken-Klinkenberg, 1966) Retimonocolpites irregularis (Salard-Cheboldaeff, 1978). Retitricoporites irregularis (Van der Hammen and Wijmstra, 1964).

Digbehi et al. 41 Spirosyncolpites spiralis (Gonzalez, 1967) Spore indet Stephanocolpites spp. Tetrad indet Tricolpites spp. Tricolporopollenites spp. Triorites spp. Verrucatosporites usmensis (Van der Hammen) Germeraad et al., 1968. ACKNOWLEDGEMENT Authors wish to thank Centre of Analyses and Research (CAR) of Côte d’Ivoire National Society of Petroleum (PETROCI) for usefully helping them to conduct these palynological analyses.

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Effect of the standard clearing limit of forest road right-of-way on stand stock growth: Case study of Vaston

forests, Hyrcanian zone

Ali Sorkhi*, Seyed Ataollah, Hoseini, Majid Lotfalian and Aidin Parsakhoo

Department of Forestry, Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resources University, Mazandaran, Iran.


Forest roads must be constructed according to the technical standards and guidelines published by the scientific organizations. The main aims of this research was to compare the standard clearing limit with existence status and assess the effects of the application of improper clearing limit on forest stock growth. In this research the standard design of clearing limit was determined based on soil texture and hillside gradient. Slope steepness map were obtained from DEM. 17 clearing limit samples were taken for each of the slope classes. The soil samples number were determined according to the length of roads which have passed from each slope classes. Results showed that the difference between the standard and existing clearing limit in secondary forest road was significantly higher than that in main forest road. Difference between stand volume decrease in standard and existing clearing limit in silt soil was significantly more than that in silt clay and clay soils. The difference between standard and existing clearing limit as well as the difference between standard and existing trees stock growth in different slope classes and soil sub-units was significant. Difference between stand volume increased significantly as difference between standard and existing clearing limit. Key words: Forest road, clearing limit, right-of-way, stock growth, standard design.

INTRODUCTION Forest roads are necessary for emergency forest management (Potočnik et al., 2008) like timber harvesting, recreation, fire control and etc. During the construction project of a forest road, the standard design must be carried out on the ground to achieve the desired road with minimal impact on environment (Hosseini, 2010). Sometimes the standard design cannot be useful for determining clearing limit of forest roads (Tunay and Melemez, 2004).

These standards are often ignored by executives. In some cases when the standard design of roads is considered, the vegetative characteristics of edge stands determine the real clearing limit of roads (Parsakhoo et *Corresponding author. E-mail: [email protected]. Tel:+989111293747.

al., 2009). Moreover, tree markers avoid from cutting valuable trees on sensitive points such as cut slopes and fill slopes to preserve them as genetic sources. So when the planner and executors want to determine forest road right-of-way should attend to the natural condition.

One of the negative effects of roads is the loss of forest area due to their construction in the forest environment. The proliferation of human-made clearings may have important impacts on wildlife populations (Laurance et al., 2004). The clearance of a forest road cross-section affects both the forest and the road (Potočnik et al., 2008). One of the first steps in forest road construction is clearing trees. At this phase, trees and other large vegetation within the right-of-way boundaries should be felled and bucked. In addition hazardous snags and unsafe trees adjacent to the right-of way should also be felled (LeDoux, 2004).

Forest road right-of-way is the width of a strip in forest

Tel:+989111293747

44 Afr. J. Environ. Sci. Technol. which is clear-cut for road construction. The width of this strip is variable in different types of roads (Sarikhani and Majnonian, 1994). The clearing limit of road depends on hillside gradient, trees height, tree species, regional climate, direction of wind blowing, slope direction and bedrock type (Potočnik et al., 2008).

The use of reinforced soil enables steeper slopes to be utilized for road construction, with a consequent reduction in the width of right-of-way. In forest areas the initial approach to clearing the site involve removing from the right-of-way trees, hedges, underbrush, other vegetation and rubbish (O’Flaherty, 2007). Typically, right-of-way clearing and subsequent thinning of roadside vegetation during the operation phase exposes habitats near the road to the drying effect of winds and the sun, which may eliminate favorable germination and growing conditions for certain plant species surprisingly far from the road cut itself (Rajvanshi et al., 2001).

Road right-of-ways need to be as wide as possible to allow sun drying of the roadway after rainfall (Schiess and Whitaker, 1986). While there may be some merit in this viewpoint, particularly in heavy clay soil conditions, most of the problems in achieving a stabilized road surface can usually be attributed to poor water management, lack of adequate compaction, and inadequate surfacing of the road (Klassen, 2006). One of the important factors in forest road construction phases is cost analysis of clearing limit. The clearing and piling cost can be calculated by estimating the number of hectares of right of way to be cleared and piled per kilometer of road (Sessions, 2007). The clearing and piling. Most studies of large-scale linear clearings in roads and power lines have focused on determining their effects on the distribution and abundance of wildlife species in the adjacent habitat. Moreover many studies have been conducted about the technical parameters of clearing limit, whereas the influence of clearing limit on vegetative parameters has not been. So, this study attempts to compare the standard clearing limit with existence status and assess the effects of the application of improper clearing limit on forest stock growth including trees density and volume per hectare. MATERIALS AND METHODS

Study area

Vaston forest with an area of 1611 ha is located in watershed number 71 and in north of Iran. The latitude, longitude and elevation ranges of this forest are 36˚ 02′ 18′′ to 36˚ 18′ 13′′ N and 53˚ 06′ 52′′ to 53˚ 10′ 55′′ E and 300-1010 m at sea level, respectively. The main woody species in Vaston are Fagus orientalis Lipsky, Ulmus glabra Huds, Acer velutinum Boiss, Carpinus betulus, Parottia persica and Alnus subcordata L. The dominant species in our research area is Fagus orientalis Lipsky. Herbaceous vegetation in the forest encompasses Asperula (Asprula odorata), Ferfion (Ephorbia sp.), Metumeti (Hypericum

androseamum) and fern (Polystichum sp.). The study area includes 27 compartments and 17.2 km forest roads. These roads were

planned only based on hillside slope parameter and then constructed in year of 1993. The mean annual air temperature is 17.1°C. The region receives 724 mm of precipitation annually. The forest type in the study area is deciduous uneven aged irregular mixed forest dominated by beech and horn-beam. In these forests, cutting regime and silvicultural method were selection system and cuts were done as group-selection and single-tree selection. In our study area the general slope of the hillside is less than 30% (Anonymous, 2004) (Figure 1).

The bedrock is marl, calcareous sandstone and limestone. The forest has three types of soil consisting of non-developed randzin, forest washed brown soil and forest brown soil. The study area has three soil sub-unit consisting of 1.5.2 soil sub-unit 2.5.2 soil sub-unit

and 1.5.3 soil sub-unit. The bedrock origin in 1.5.2 sub-unit is marnlime and sandstone lime; Soil type in 2.5.2 sub-unit is brown waterworn with calcic lyer and the bedrock origin in it is lime, sand lime and siltymarn; The bedrock origin in 1.5.3 sub-unit is lime, marn, siltyand limestone (Figure 2). Data collection

Road routes were also collected with track mode by GPS MAP 76CSX. The standard design of clearing limit was determined based on soil texture and hillside gradient (Sarikhani and Majnonian, 1994). For produce slope steepness map digital elevation model (DEM) was generated from 1:25000 map 2d 3d in GIS software (Arc Map 9.3) and from surface analysis. The slope map divided in seven classes; from 10% slope to 60% divided in sex classes and from 60% to maximum slope divide in one class (Sarikhani and Majnonian, 1994) (Figure 3).

According to soil map and forestry plan booklet data the digital layer of soil sub-units were produced. The track status of road in different slope classes of soil sub-units was determined by overlaying road map and soil sub-unit map. To be able to investigate the effects of soil texture on determining standard clearing limit of road right of way, the soil samples number were determined according to the length of roads which have passed from each slope classes. According to this approach 39 samples

were taken to analyse soil texture. After determining soil texture, appropriate cut and fill slopes were appointed for each soil texture. Appropriate cut and fill slopes determination was based on soil stability. In this research roadbed width was spotted 7.5 m for main road and 5.5 m for secondary road ((Sarikhani and Majnonian, 1994). Then 17 clearing limit samples were taken for each of the slope classes. AutoCAD 2010 software was used to design the map of clearing limit in road right of way. Number of trees per hectare and stand volume per hectare was extracted from the forestry plan booklet. The study was established as a randomized complete block design with two type blocks (slope classes and soil type) and treatments (main road, secondary road and soil sub-units). All data were subjected to analysis of variance (ANOVA) using the GLM procedure in SAS software (SAS Institute Inc. 2000). Wherever treatment effects were significant the Duncan test at probability level of 5% was carried out to compare the means. The graphs drawing were done in excel software.

RESULTS AND DISCUSSION The fill and cut hillsides appropriate slope for each soil type of road route in our study area show at Table 1 (standard table).

Soil texture along forest road were divided into three groups, clay, silty-clay and silty soils. The standard clearing limit for clay soil was determined 8.5 m. For

Sorkhi et al. 45

Figure 1. The geographical position of the study area.

Figure 2. The map of soil sub-units in study area.


Figure 3. The map of slope classes in study area.

Table 1. Fill and cut hillsides appropriate slope for each soil type of road route.

Determined slope

Soil texture Cut slpe (%) Fill slope (%)

CL (clay) 66 70 to 80

SL (silty-loam) 60 to 70 80

SCL (silty-clay) 50 80

silty-clay and silty soils the standard clearing limit was determined 10.5 m. The present study clearly demonstrated that the difference between standard and existing clearing limit were influenced not only by the road type but also by the soil sub-units. Nevertheless, the effects of independent parameters on existing clearing limit were not statistically significant. There were

significant differences between the standard and existing trees stock growth (density and volume per hectare) in response to road type and soil sub-units (Table 2).

The difference between standard and existing clearing limit in secondary forest road was significantly higher than that in main forest road. Moreover the difference between standard and existing trees stock growth in

Sorkhi et al. 47

Table 2. Analysis of variance for the clearing limit and stock growth parameters.

Parameter Source DF SS MS F value Pr > F

Existing clearing limit (ECL)

Road 1 11.62 11.62 1.06 0.33ns

Soil sub-units 2 11.19 5.59 0.51 0.62ns

Slope 6 73.09 12.18 1.11 0.43ns

Soil texture 2 2.51 1.25 0.11 0.89ns

Difference between standard and existing clearing limit (DSEC)

Road 1 6.54 6.54 5.25 0.05٭

Soil sub-units 2 16.90 8.45 6.78 0.01٭٭

Slope 6 19.05 3.17 2.55 0.11ns

Soil texture 2 2.27 1.14 0.91 0.43ns

Difference between standard and existing trees density (DSED)

Road 1 164279.9 164279.9 5.62 0.04٭

Soil sub-units 2 448494.1 224247.0 7.67 0.01٭٭

Slope 6 539680.0 89946.7 3.08 0.07ns

Soil texture 2 212523.9 106261.9 3.64 0.07ns

Difference between standard and existing trees volume (DSEV)

Road 1 491595.1 491595.1 6.98 0.03٭

Soil sub-units 2 1127618.4 563809.2 8.00 0.01٭٭

Slope 6 1401543.9 233590.7 3.32 0.06ns

Soil texture 2 126060.1 63030.1 0.89 0.45ns

*: Significant at probability level of 5%, **: significant at probability level of 1%, ns: non-significant, DF: degree of freedom, SS: sum square, MS: mean square, F value: F quantity, Pr>F: significant level.

secondary forest road was significantly higher than that in main forest road. The difference between standard and existing trees density in silt soil was significantly more than that in silt clay and clay soils. The difference between standard and existing clearing limit as well as the difference between standard and existing trees stock growth in different slope classes and soil sub-units was significant (Table 3).

Kachenderfier (1970) suggested that the road width in steep slopes must be constructed less than that in gentle slopes to reduce earth working width and clearing area. This may cause decrease

in fill slope length and increase erosion rate (Artour et al., 1998). If the clearing limit is determined less than standard design, the road structure would damaged by the dangerous and troublous trees. Besides, if the clearing limit is determined more than standard design, the trees growth at the edge of forest road would decrease by weather warming and cold (Mirzaei, 2004). Results showed that there was no significant relationship between difference of standard and existing clearing limit and existing clearing limit (p>0.05; r = 0.005). There was no significant relationship between difference of standard and

existing trees density and existing clearing limit (p>0.05; r =-0.084). Difference between standard and existing trees volume increased significantly as difference between standard and existing trees density increased (P<0.01; r=0.839) (Table 4). Conclusions Increasing the clearing limit of forest road increases the amount of environmental damages and sediment yield from earth working area to ditch through soil creep, sheet wash and slumping.


Table 3. Comparison of the means of parameters in different classes based on Duncan's multiple range tests.

Source Classes Existing clearing

limit (ECL)

Difference between standard and existing clearing limit (DSEC)

Difference between standard and existing trees density (DSED)

Difference between standard and existing trees volume (DSEV)

Road Main road 23.54

A 0.35

B 89.50

B 107.10

B

Secondary road 19.88A 1.11

A 228.40

A 304.70

A

Slope (%)

0 to 10 18.15A 0.67A

B 117.4BA

C 181.3B

A

10 to 20 19.55A 2.75

A 482.4

A 723.2

A

20 to 30 24.46A 1.07A

B 173.5

BAC 321.2

BA

30 to 40 18.05A 0.30A

B 416.9

BA 88.7

B

40 to 50 19.14A 0.17

B 28.4

C 46.0

B

50 to60 20.11A 0.04

B 4.7

C 10.9

B

More than 60 22.65A 0.48A

B 79.5

BC 153.6

BA

Soil sub-units

1.5.2 19.00A 0.08

A 15.20

B 26.00

B

2.5.2 19.37A 1.75A

B 381.90

A 458.00

A

1.5.3 21.60A 0.75

B 143.30

AB 221.70

AB

1.34A 239.3

B 357.7

A

Soil type

CL (clay) 19.45A 0.75

A 121.1

B 218.5

A

SCL(silty clay) 21.57A 0.33

A 786.8

A 96.0

A

SL(silty loam) 17.76A

In a same column, values with same superscript are not significantly different at 5% level based on Duncan’s test.

Table 4. Pearson correlation coefficients among dependent variables.

No. Variables 1 2 3 4

1 Existing clearing limit 1

2 Difference between standard and existing clearing limit 0.005 1

3 Difference between standard and existing trees density -0.084 0.841*** 1

4 Difference between standard and existing trees volume 0.026 0.996*** 0.839*** 1

***: is significant at probability level of 0.1%.

This study proved that the difference between standard and existing clearing limit were affected not only by the road type but also by the soil sub-units. The difference between standard and existing clearing limit in secondary forest road was significantly more than that in main forest road. Difference between standard and existing trees volume increased as difference between standard and existing trees density increased.

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Food security and health in the southern highlands of Tanzania: A multidisciplinary approach to evaluate the

impact of climate change and other stress factors

Richard Y. M. Kangalawe

Institute of Resource Assessment, University of Dar es Salaam, P.O. Box 35097, Dar es Salaam, Tanzania. E-mail: [email protected]. Tel: +255-22-2410144. Fax: +255-22-2410393.

Accepted 9 January, 2012

Tanzania like many African countries is highly vulnerable to global environmental change, particularly climate change. The impacts of particular concern are related to food production, human health and water resources. Agricultural production, which is essential to ensure food security, is weather-dependent, which has occasionally subjected the country to food shortage and insecurity in years with low rainfall. Food security varies spatially and temporally depending on rainfall patterns and other multiple stress factors such as soil conditions, types of crops grown, socio-economic and cultural factors. The southern highlands of Tanzania which are the grain basket for the country are highly vulnerable to impacts of global change, especially decrease in the amounts of rainfall. In some parts, extreme events (for example, floods) have destroyed infrastructure hence affecting food distribution and access by the affected communities. Environmental change has also impacted on human health in various parts of Tanzania. The rise in mean temperatures is an important factor for increased incidences of malaria in the highlands that were traditionally free from malaria. Long-term climate records for the southern highlands of Tanzania confirm that the climate of the region is changing. Temperatures have steadily increased over the last forty to fifty years, and are closely associated with increasing prevalence of malaria and other health risks as confirmed by existing hospital records. Key words: Food security, human health, climate change, environmental change, multiple stress factors, southern highlands of Tanzania, multidisciplinary approaches.

INTRODUCTION Like many other parts of Tanzania, the southern highlands (Figure 1) are vulnerable to climate change. This paper highlights on the impacts of environmental change, particularly climate change, on food security and human health

1. Particular concerns are on agricultural

production (crop and livestock production), which is an essential component of food security. To a large extent, agricultural production in the southern highlands of Tanzania is weather-dependent, which subjects the area to occasional food shortage and insecurity especially in years with extreme climatic events. In some parts,

1 The original version of this paper was presented at the "The 5th Conference

on Global Health and Vaccination Research: Environmental Change and

Global Health”, held in Tromsø, Norway, 6-8 June 2010, and organised by The

Research Council of Norway through the Global Health and Vaccination

Research (GLOBVAC) programme..

extreme events (for example, floods) have destroyed infrastructure hence affecting food distribution and access by the affected communities. Increasing temperature associated with environmental change has been a cause of various health risks, such as increased incidences of malaria in the southern and other highlands of Tanzania (Kangalawe, 2009; Yanda et al., 2006).

This paper is based on studies undertaken in the southern highlands of Tanzania to assess the impacts of environmental change on people’s livelihoods, food security, health and associated community adaptations. Environmental change, particularly climate change, is a challenge to both sustainable livelihood and economic development. The adverse impacts of climate change are now evident in many parts of the world, particularly in the developing countries, including United Republic of

Kangalawe 51

Figure 1. Map of Tanzania showing the southern highlands (shaded) with district boundaries.

Tanzania (URT, 2009). This is especially true where changes in rainfall and temperature patterns threaten sustainable development goals related to poverty reduction, water, food security, health, education and biodiversity management (URT, 2009).

According to the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC, 2007), warming of the global system is unequivocal. The report predicts that progression of global warming will increase the frequency of extreme weather events such as heavy floods and droughts, and increase health hazards through infectious diseases. It may also lead to food crisis resulting from depletion of water resources. Many developing countries particularly in Africa are regarded as being vulnerable to the adverse impacts of climate change because of factors such as widespread poverty, recurrent droughts, inequitable land distribution, and overdependence on rainfed agriculture (IPCC, 2001, 2007). For Tanzania, the adverse impacts of climate

change are already vivid in almost all sectors of the economy (URT, 2009), including agriculture and health. Thus strategic actions are required to address climate change impacts on agriculture and other key economic sectors (URT, 2008a).

Both climatic and environmental changes have resulted in declining agricultural productivity, deterioration of water quality and quantity and loss of biodiversity. These have serious implications on the livelihoods of the people and the environment (Hulme, 1996). While climate change is a global phenomenon, its negative impacts are more severely felt by poor people and poor countries. They are more vulnerable because of their high dependence on natural resources, and their limited capacity to cope and adapt with climate variability and extremes (McCarthy et al., 2001; World Bank, 2005). In addition, poor communities are not only located in high-risk areas, but the lack of economic and social resources mean they are ill-equipped to adjust to the long-term impacts of


Table 1. List of selected districts, health facilities and village’s involved in the study.

District Ward Health facility Nearby village

Chunya

Chokaa District Hospital (Kibaoni) Kibaoni

Mbuyuni Mbuyuni Health Centre Chang’ombe

Mkwajuni Mwambani DDH Mkwajuni

Mbeya Rural

Ikumbi District Hospital (Ifisi) Ikumbi

Ilembo Ilembo Health Centre Ilembo

Inyala Inyala Health Centre Inyala

Mbozi

Vvwawa District Hospital (Vwawa) Vwawa

Nyimbili District Hospital (Vwawa) Nyimbili

Igamba Mbozi Mission DDH Mbozi

Ivuna Mbozi Mission DDH Ntungwa

Rungwe

Malinyo/Mpuguso District Hospital (Tukuyu) Mpuguso

Ikuti Ikuti Health Centre Ikuti

Kinyala Igogwe Hospital Isumba

changing climate. In Tanzania, the impact of climate change is

increasingly becoming evident in various sectors, such as health, agriculture, forestry and wildlife. Among the evidences in the health sector is the increased incidences of highland malaria, for example, in places like Mbeya (Kangalawe, 2009) and Kagera (Yanda et al., 2006). The similarity in the long-term temperature and malaria trends confirm the association between climate change and prevalence of highland malaria. Thus with increasing temperatures the risk of highland malaria also increases (URT, 2009). Other sectors such as livestock keeping are also impacted. For example, occurrence of droughts has been more frequent during the last few decades causing shortage of pastures and prompting long distance migrations among livestock keepers searching for pastures and water in the southern highlands (Mbonile et al., 1997; Kangalawe and Liwenga, 2004; Kangalawe et al., 2007). The impacts of climate changes are also evident in the islands of Zanzibar, where some historical ruins in Ras Mkumbuu peninsular have been submerged as a result of sea level rise (URT, 2009). Overall these experiences call for concerted efforts to increase community awareness of climate change and enhance their adaptive capacities.

METHODOLOGY

This paper is based on studies undertaken in Mbeya Region between 2007 and 2009. It involved four main methodological approaches, namely focus group discussions, interviews, field observations and secondary data collection. The interviews involved consultations with key informants, including agricultural and health officers at regional and district levels, selected health centres and interviews with households in villages surrounding the

health centres using a structured questionnaire. Consultations were first made with the Mbeya Regional

Administrative Secretary (RAS) and the Mbeya Regional Medical Officer (RMO) to introduce the study and obtain permission for carrying out the study in the selected districts and identifying representative health facilities that could be visited in the sampled districts. Two to three health facilities were selected from each of the selected districts. These included respective district hospitals and two other health centres. At all these health facilities a questionnaire was filled by the medical or nursing officer in charge of the facility. A random sample of 56 households was also selected for interviews from villages surrounding the health facilities (Table 1) to capture local perceptions, perspectives and experiences related to climate change and health in their respective areas. Apart from climatic change, household interviews also entailed collection of information on other stress factors with impact on local community livelihoods, food security and human health.

Human health data particularly for malaria outpatients, inpatients and deaths were collected from records available at health facilities. The data on malaria collected from the selected health facilities, included outpatient, inpatient and deaths for <5 and 5+ years of age. Data was collected for as long period as it was available, the major sources being the MTUHA (Mfumo wa Taarifa za Uendeshaji wa Huduma za Afya, literally meaning record system for health services) records for each health facility. Despite the challenge of record keeping in many parts of Africa, MTUHA has ensured that available records are well organized and were considered adequate for the study. Additional information was obtained from various reports available at district and regional level, and from literature. Field observation was undertaken in the study sites to capture possible evidence of changes that could have occurred as a result of changing climate, for example changes in stream flow.

Data from focus group discussion and key informant interviews were triangulated during the discussions. Data from household interviews was processed and analysed using the statistical package for social science (SPSS). The sustainable livelihood approach (DFID, 1999) was used as an analytical tool to understand the adaptive capacities. The sustainable livelihood approach provided a means of analysis of livelihood strategies and community vulnerability to external shocks and stresses. The approach was also used to assess adaptive capability of different

Kangalawe 53

Table 2. Percentage responses on local understanding of climate in four districts in the southern highlands of Tanzania.

Local understanding of climate Chunya Mbeya Rural Mbozi Rungwe Average

Climate as rainfall 100 89.5 50 95.2 83.7

Climate as temperature 100 89.5 50 95.2 83.7

Outbreak of human diseases 64.3 42.1 100 61.9 67.1

Climate as drought 78.6 52.6 50 61.9 60.8

Climate as floods 78.6 42.1 50 42.9 53.4

Climate as wind 92.9 36.8 0 61.9 47.9

Climate as humidity (dryness of the air) 64.3 26.3 0 66.7 39.3 socio-economic groups in the respective villages based on household livelihood assets. Malaria data from hospital records was processed and analysed using excel computer package to establish patterns on malaria incidences and prevalence.

RESULTS AND DISCUSSION

Local perceptions and indicators of climate change

Local perceptions of changing climate

Global change may be perceived differently by various communities. Thus while addressing the concepts of changing climate at the community level; it is important to establish the local understanding of the concept “climate”. Interviews with various stakeholders at the village level showed that there is a growing concern that climate change and variability is already occurring. Table 2 presents findings from interviews in selected districts in the southern highlands of Tanzania. It shows that people understand climate, among others as rainfall, temperature, drought, floods, wind and humidity (Kangalawe, 2009). The concept “climate change” was associated with variability in weather conditions such as rainfall inconsistency and unpredictability over years. The variability was related to increased seasonality of rainfall which affects the agricultural calendar and hence the local livelihoods.

Rainfall and temperature were ranked highest among the aspects mentioned to indicate the local understanding of climate, followed by drought, floods, wind and humidity. Concerns about drought were raised more in Chunya district, perhaps owing to the relatively low amounts of average annual rainfall usually received in the area compared to the other three districts. Other aspects were mentioned by smaller proportions of respondents, indicating that they are not commonly used to reflect local understanding of climate change.

Responses to the inquiry on rainfall situation during the last 30 to 40 years showed a general concern that in all the eleven villages studied rainfall has been decreasing, as expressed by 82% of respondents. The decrease in rainfall was also associated with the disappearance of

short rains that used to be received around September, delayed and fluctuations in the onset of heavy rains (Kangalawe, 2009). Very few reported an increase in rainfall. This was locally associated with extreme events such as El Niño that took place some ten years ago (1997/1998). Long term rainfall records for Mbeya seem to support this latter observation (Figure 2).

Documentary records indicate that the climate of the southern highlands is generally tropical with marked seasonal and altitudinal temperature variations and sharply defined dry and rainy seasons. The rains normally start in October and go through to May followed by a dry and cold spell between June and September (URT, 2003). However, the pattern has become more unpredictable in recent years. Similar observations have also been reported elsewhere in Tanzania and East Africa in general (Yanda et al., 2006; Wandiga et al., 2006).

Regarding temperature conditions, majority of the respondents claimed that temperature has increased over last 10 to 30 years, with their areas becoming much warmer (Kangalawe, 2009; Liwenga et al., 2009). The observations from the local communities seem to be supported by meteorological data for Mbeya (Figure 3), which shows that both the mean maximum and mean minimum temperatures for February increased steadily since 1955 (Mpeta, 2009). February falls within the rainy season that, according to local people, is a period with more incidences of malaria. The combined effect of warmer temperatures during the season and the availability of ample breeding sites for mosquitoes make the communities in the area vulnerable to malaria if appropriate adaptation measures are not undertaken. In places like Rungwe, the temperature increase was reported to have been associated with a decline in frost incidences that used to be experienced in the past (Liwenga et al., 2009).

Local indicators of the perceived changing climate

Table 3 presents the local indicators of climate change used by communities in villages involved in the assessment of the impacts of climate change on human


1940 1950 1960 1970 1980 1990 2000500

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Oct-MayTrendLineMean

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ll (m

m)

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Mbeya October to May rainfall total (1937 to 2006) R2 = 0.03

Figure 2. October-May rainfall in Mbeya - 1940-2008. Source : Mpeta (2009).

Te

mp

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ture

°C

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pe

ratu

re °

C

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pe

ratu

re °

C

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pe

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re °

C

Period in years Figure 3. Long-term temperature record for Mbeya meteorological station. Source: Mpeta (2009).

Kangalawe 55

Table 3. Percentage responses on local indicators of climate change in selected parts of Mbeya Region.

Indicator of climate change Chunya Mbeya Rural Mbozi Rungwe Total

Increasing temperatures 85.7 89.5 100 85.7 90.2

Shortened growing seasons 85.7 78.9 100 95.2 90.0

Rainfall coming late in the seasons 78.6 73.7 100 66.7 79.8

Recurrent food shortage 85.7 63.2 100 52.4 75.3

Rainfall coming too early in the seasons 71.4 47.4 100 66.7 71.4

Increased incidences of drought 100 63.2 50 66.7 70.0

Outbreak of other human diseases 64.3 42.1 100 61.9 67.1

Outbreak of malaria 50.0 26.3 100 38.1 53.6

Increased rainfall amounts 71.4 36.8 50.0 47.6 51.5

Decreasing crop productivity 71.4 26.3 50.0 33.3 45.3

Increasing crop productivity 78.6 52.6 0 38.1 42.3

Decrease in the number of livestock kept 50.0 31.6 0 33.3 28.7

Outbreak of livestock diseases 50.0 26.3 0 33.3 27.4

Outbreak of plant diseases 42.9 5.3 0 33.3 20.4

health in the southern highlands of Tanzania (Kangalawe, 2009; URT, 2009). The diversity of indicators shows that perhaps no single indicator may be sufficient to explain a climatic phenomenon among the rural communities. Increasing temperatures; shortened growing seasons; late coming of rains in the seasons, recurrent food shortage, rainfall coming too early in the seasons, and increased incidences of drought emerged as the major indicators of climate change, as indicated by the large proportions of respondents reporting them (Table 3). It may appear surprising that both late and early rains were reported as indicators of climate change. This may explain the fluctuations that are experienced over the years, where in some seasons rains start earlier than expected while in others rains start late in the season.

Outbreak of human diseases is among the top ten local indicators of climate change as expressed by 67.1% of the respondents. The diseases that were reported to be associated with seasonal variations of climate include diarrhoeal diseases, which were reported to be more prevalent during the rainy season; and respiratory infections that were claimed to be more common during the cool months. Outbreak and increased incidences of malaria was reported by 53.6% of respondents, indicating a growing awareness of the relationship between the climate change phenomena and prevalence of mosquitoes and malaria.

Some of the local indicators of climate change may however be difficult to ascertain because of the complementarities that exist between climate phenomena and other stress factors. For example decrease/increase in crop productivity may be a function of several factors, including climatic, edaphic factors and agronomic practices. It may therefore be difficult to isolate the single impact of climate change. However, it is worth noting that local communities recognise the relationship between climate change and agricultural production.

Environmental change impacts on livelihoods and food security Livelihoods of the majority of people living in rural areas of Tanzania depend on agriculture and other natural resources, particularly forest products (URT, 1998). In many sub-Saharan African countries, smallholder agriculture underpins most rural livelihoods and national economies, and worsening poverty and increasing food insecurity is closely linked to low and/or declining levels of agricultural productivity. Already there are reports that agricultural production and food security (including access to food) in many African countries are likely to be severely compromised by climate change and climate variability (Boko et al., 2007). However, as reported by Sen (1981) food insecurity may occur not because there is not enough food, but because people do not have access to enough food. The Tanzania’s National Food Security Policy (URT, 2008b) also recognizes food availability, accessibility and utilization as three major pillars of food security. Improved food security leads to improved human capital and higher wages in the labour market. Food security is therefore a development issue that must be streamlined in the development agenda to ensure a healthy and productive nation (URT, 2008b). The rest parts of this paper analyses how environmental change, particularly climate change, has impacted on various sectors and its consequences on food security. Decline in agricultural productivity (crops and livestock) Tanzania’s economy depends heavily on agriculture, which accounts for almost half of GDP, provides 85% of exports, and employs 80% of the work force (URT, 2008a). Agriculture is highly vulnerable to climate

56 Afr. J. Environ. Sci. Technol. Table 4. Impacts of climate change on agriculture (crops and livestock).

Agriculture Livestock

Unpredicted rainfall will lead to uncertainty in cropping patters Favourable condition for ticks, snail, blood-sucking insects and pests outbreaks

Areas with less rainfall will loose water through evapotranspiration and require irrigation

Increased east coast fever and rift valley fever

Region with increase rainfall will experience nutrient leaching, soil erosion and water logging

Eruption of new pest and diseases

The incidence of pests and diseases will rise on areas with increased rainfall

Reduced productivity (draught power, milk, and meat) as increased carbon dioxide reduced protein available from vegetation

Prolonged dry spells may extend beyond normal patterns Livestock deaths due to heat waves

Decline in maize yields by 33% overall Shrink the rangelands and shortage of pastures

Cotton yields expected to fall in some areas, rise in others Shortage of water

Shifts in agro-ecological zones

Increased weed competition with crops for moisture, nutrients and light

Source: Compiled from URT (2003, 2007) and Ehrhart and Twena (2006).

variability and long-term climate change, which could in many parts of the country result in food shortages, higher food prices and lower domestic revenues; and climate change will only aggravate falling harvests (Devereux and Edward, 2004). In Tanzania, for example, famine resulting from either floods or drought has become increasingly common since the mid-1990s, undermining food security (URT, 2003). In addition, increased rainfall could lead to nutrient leaching, loss of topsoil and water logging, all of which will seriously affect agricultural production. Increased incidence of crop pests and diseases is also expected due to higher temperatures and rainfall. This is likely to lead to farmers using more agrochemicals and disease resistant varieties, thus increasing production costs (Orindi and Murray, 2005).

According to URT (2007), climate change is expected to shrink the rangelands which are particularly important for livestock keeping communities. This shrinkage will be more aggravated by the fact that about 60% of the total rangeland areas in the country are infested by tsetse fly making it unsuitable for livestock pastures and human settlements (URT, 2007). Shrinkage of rangelands is likely to exacerbate conflicts between livestock keepers and crop farmers, thereby affecting the livelihoods of both groups. This has been among the reasons for livestock keepers in the northern parts of the country shifting their herds towards southern Tanzania in search for pastures (Mbonile et al., 1997; URT, 2003, 2007; Kangalawe et al.,

2007). The overall impacts of changing climate on the agricultural sector are summarised in Table 4. Increased risk of food shortage and famine Droughts and floods result in crop damages and failure (Kangalawe and Liwenga, 2005), and in combination with other stress factors lead to chronic food shortages. Although most rural farming communities are aware of climate variability and have risk reduction methods for example, multi-cropping, increasing crop diversity (Kangalawe, 2001, 2003; Kangalawe et al., 2005), the traditional rain-fed subsistence agriculture is extremely vulnerable to changing climatic patterns through shifts in growing season conditions. The rainfall pattern is no longer predictable. There have been recurrent droughts in recent years including those in 1994/1995 and 2005/2006, which triggered food shortage and a severe power crisis (Mwandosya, 2006). Since most rural communities rely on their agricultural produce for food and for income generation, poverty is directly coupled to agricultural production. However, neither at household nor at the community level can people adequately cope with climate change-induced extreme variability.

According to McCarthy et al. (2001) climate change will negatively affect agricultural production and therefore worsen food security, mainly through increased

extremes, its influence on land use and temporal and spatial shifts in water availability. Also as a result of increasing water stress and land degradation, other land use options, such as inland fisheries will be rendered more vulnerable to episodic drought and habitat destruction. Impact of climate change/variability on food security Experiences from selected sites in Rungwe district in the southern highlands of Tanzania, namely Idweli (in the highland zone), Mibula (in the middle zone) and Busisya (in the lowland zone) indicate that agriculture is the major livelihood activity that has been impacted by climate change. Although there are very few incidences of severe food insecurity in the area, climate change and variability have some negative impacts on the local economies (Liwenga et al., 2009). Such impacts are manifested in terms of increased costs of agrochemicals required to control crop pests, whose severity was associated with increasing seasonality of rainfall and increasing temperatures. Communities in the middle lands, where the staple foods are bananas and maize, reported for instance that food insecurity implies inadequate availability of bananas since the crop can be consumed directly or easily sold to generate income. The incomes obtained could further be used to purchase other food items such as maize. The productivity of bananas was reported to vary with prevailing climatic conditions.

Lesser important crops such as bambaranuts, cassava, cocoyam and sweet potatoes were reported to have helped in overcoming food shortage and insecurity. However, the acreage of these crops was reported to be declining as the land they used to be grown has increasingly been taken for commercial crops like tea and bananas production. According to Liwenga et al. (2009) crop diversity is high in the midlands zone and this has helped the respective communities to ensure food security. However, the increasing replacement of farmlands for crops such as cassava and yams by more commercial non-food crops like tea may negatively impact on food security in the long run. This is a basically non-climatic stress factor impacting on food security situation of the area. Similar experiences were also reported in other parts of the southern highlands where commercial crops like tea are grown (Kangalawe and Liwenga, 2007).

In 2008 the Ministry of Agriculture, Food Security and Cooperatives conducted a study to examine the strategies for addressing negative effects of climate change in food insecure areas of Tanzania (URT, 2008b). The objective of this study was to identify and enhance adaptive strategies for addressing negative effects of climate change in areas with recurrent food shortage consistent with the Ministry’s goal towards sustainable food security in the country. Among the sites included in

Kangalawe 57 the study were Mufindi and Mbarali districts (in Iringa and Mbeya region respectively) in the southern highlands of Tanzania. That assessment examined various aspects of food security, including what food shortage actually meant, experiences of food shortages and associated causes, and how households dealt with food shortages.

Findings from that study indicated that maize was the main staple in all districts in the southern highlands. These results indicated specialization of respondents in only few staple foods, which has implications in relation to food security, particularly in case of crop failures. Many respondents (65.6%) in that study associated “food shortage” with shortages of main food staples and particularly shortage of food from own farms, while others associated food shortage with unavailability of food in the market and reduction in number of meals per day (15 and 43.1%, respectively). Such variability in how the communities perceived food security may be an important consideration when addressing food security issues at local levels. The findings from household interviews indicated that there are several causes of food shortages and insecurity, ranging from natural to socio-economic factors. However, the main causes of food shortages were reported to be drought, floods, strong winds and excessive rainfall, all being influenced by climate change. Other significant causes included increased incidences of crop pests and diseases, low soil fertility, lack of labour, weeds, lack of agricultural inputs, small farm sizes, destructive birds and use of local varieties. The latter are among the non-climatic stressors impacting on local food security.

Responses on how households addressed food shortages indicated buying food, selling livestock to buy food, work for food, reducing amount of food eaten, eating unusual foods, borrowing food, getting relief food, reducing number of meals, migrating to other areas and assistance from relatives. Buying of food appeared to be the most prominent way of dealing with food shortages, which implies the need for alternative income generating activities to provide the required cash. While most of the southern highlands are food secure, with more than 70% of community members having sufficient food for the households throughout the year, there have been occasions of food shortage. Such occasions were reported to be addressed in various ways, including reducing the number of meals per day. About 70% reported to take between 2 to 4 meals a day, while only about 30% reported to usually have one meal per day (Maro et al., 2008). The number of meals could however, be influenced by several other factors. The ones mentioned during field survey included distances to crop fields and poverty. During the growing seasons when most of the household members are busy with farm work, the number of meals could be reduced because there is limited time for people to spend in the homesteads preparing meals. Thus farmers whose crop fields are located long distances from their homesteads were

58 Afr. J. Environ. Sci. Technol. reported to take fewer meals.

Destruction of infrastructures also hampers food access and availability. Floods have occasionally destroyed hectares of croplands as well as harvested produce and houses. Transportation infrastructure, such as roads and railways, and water systems may also be at risk from impacts of climate change. Already some parts remain impassable until the flood water subsides. For instance, the El Niño rains of 1997/1998 disrupted the transport system, washing away some roads and bridges and damaging parts of the railway network thereby hampering crop and livestock haulage from main production to consumption areas. Consequently, this caused sharp consumer price increases that limited food access to market dependent consumers. This had considerable impacts on the food security situation. Environmental change and human health risks Human health risks associated with environmental change Health is one of the key sectors that are affected by environmental change, particularly changing climate. This manifests itself through increase of average temperature leading to among others, widespread malaria in highland areas. It is very likely that climate change will alter the ecology of some diseases in Africa and consequently the spatial and temporal transmission of such diseases (cf. Tonnang et al., 2010). For instance, higher peak flows contribute to floods which adversely affect human settlements and health. More frequent floods destroy infrastructure, buildings and belongings in the floodplains. Moreover, warming, flooding and increased rainfall increase the spread and incidence of vector-borne diseases such as malaria. Droughts impact settlements, requiring more time for water collection and resulting in reduced water use. This impairs hygiene and contributes to the spreading of contagious diseases such as cholera.

Among the various vector-borne diseases malaria is a major public health concern in Tanzania, especially among pregnant women and children under five (COWI et al., 2007). It accounts for 16.7% of all reported deaths in the country and 12% of under-fives, and is one of the leading causes of morbidity (URT, 2003). About 95% of the Tanzania’s population is reported to be at risk for malaria (Mboera et al., 2007). Already the disease causes between 70,000 and 125,000 deaths annually, and accounts for about 19% of the health expenditure (De Savigny et al., 2004). Reported malaria cases for the year 2003 mounted to 10.7 million and the actual numbers of malaria cases are considered to be much higher since the majority of cases in Tanzania are not reported (WHO and UNICEF, 2005).

The link between climate and malaria distribution has long been established. Sustained transmission depends

on favourable conditions for both vector and parasite (Githeko et al., 2000; Tonnang et al., 2010). The effect of temperature on the malaria parasite and vector survival is particularly important. The study by Kangalawe (2009) conducted in Mbeya region in the southern highlands of Tanzania to assess the local impacts of climate change on highland malaria demonstrated clear association between temperature trends and malaria incidences. Other diseases also increasing with climate change include cholera, dysentery and respiratory diseases.

Malaria was mentioned by all respondents in the districts consulted (Table 5). Other important diseases were diarrhoeal diseases, respiratory diseases (mainly the acute respiratory infections), HIV/AIDS and tuberculosis. A follow up inquiry on whether malaria was among the most prevalent diseases in the area again confirmed that the diseases is prevalent, and was a concern of majority (85.9%) of respondents; and that majority of the respondents (88%) had once suffered from malaria (Table 5).

Malaria is locally perceived as a recent phenomenon in the southern highlands of Tanzania, with more incidences being reported over the past 10 to 30 years, suggesting that environmental conditions have changed over that period in favour of the malaria vector and parasites. Further, there is a general concern among communities in this area that malaria is a very severe disease, which points to the low immunity inherent in highland communities not historically exposed to malaria. Many respondents in the survey reported that historically malaria was not a common phenomenon in their areas, except in Chunya District which has since been relatively warmer compared to the other three districts. Findings presented in Table 6 confirm that in the 1960s there were very few incidences of malaria in most parts of the southern highlands, and the trends have been increasing with time.

The locally perceived trends regarding prevalence of malaria in the studied areas is also supported by diagnostic records from nearby health facilities (Figure 4). Although it was difficult to obtain long-term data from all the health facilities (data from other health facilities was from 1994), available malaria data indicates a generally increasing trend. Long-term data on malaria cases found at Igogwe Hospital in Rungwe district attests that malaria has steadily increased since the 1960s, especially for the inpatients (Figure 4). Even when taking into account the factor of increasing population, the same increasing pattern of malaria inpatients can be discerned (Figure 5). Although there had been fluctuations over the years (Figures 4 and 5), the numbers of patients hospitalised have generally increased. The peaks in number of malaria cases coincided with climatic events such as El Niño, and warmer temperatures associated with droughts, for example, between 2002 and 2005. The number of deaths between 1994 and 2007 also shows a generally increasing trend for almost all the health

Kangalawe 59 Table 5. Percentage responses on common diseases and frequency of having malaria.

Common diseases in the area Chunya Mbeya Rural Mbozi Rungwe Total

Malaria 100 100 100 100 100

Diarrhoeal diseases 92.9 84.2 100 71.4 87.1

Respiratory diseases 64.3 73.7 100 61.9 75.0

HIV/AIDS 50 26.3 50 47.6 43.5

Tuberculosis 46.2 15.8 50 23.8 34.0

Presence and frequency of having malaria

Presence of malaria/mosquitoes

Is malaria among the most prevalent diseases in the area? 100 57.9 100 85.7 85.9

Are there mosquitoes in the area? 100 89.5 100 90.5 95.0

Have you ever contracted malaria? 92.9 68.4 100 90.5 88.0

Frequency of having malaria

Occasionally 28.6 57.1 100 71.4 64.3

Regularly 35.7 14.2 0 19.1 17.3

Rarely 28.6 21.4 0 9.5 14.9

Do not know 7.1 7.2 0 0 3.6

Table 6. Percent response on the history of malaria incidence in selected districts in the southern highlands of Tanzania.

Malaria situation over different periods Chunya Mbeya Rural Mbozi Rungwe Total

Since 1960s

No malaria 7.1 31.6 0 19 14.4

Few incidences of malaria 50.0 31.6 100 57.1 59.7

Many incidences malaria 14.3 5.3 0 4.8 6.1

Do not know 28.6 31.6 0 19 19.8

Total 100 100 100 100 100

Since the 1970s

No malaria 7.1 21.1 0 4.8 8.3

Malaria increased 64.4 47.3 100 61.9 68.4

Malaria decreased 7.1 0 0 4.8 3.0

No change in malaria incidences 7.1 10.5 0 19 9.2

Do not know 14.3 21.1 0 9.5 11.2

Total 100 100 100 100 100.0

The last ten years 1990-2000s

No malaria 14.3 73.7 0 14.3 25.6

Malaria increased 78.6 15.8 100 71.4 66.5

Malaria decreased 7.1 10.5 0 9.5 6.8

No change in malaria incidences 0 0 0 4.8 1.2

Do not know 100 100 100 100 100

facilities consulted (Figure 6). The numbers of outpatients at Igogwe Hospital have

greatly fluctuated over the last forty years, with peaks between 1985 and 1989, 1996 and 1998, and between 2002 and 2005. These peaks of malaria cases coincided with periods with warmer temperatures (Figure 3). This

confirms the association between increasing temperatures and increased risk of malaria. The latter therefore indicates that with global warming, and thus climate change, such highland areas may face increased risk of highland malaria. And given the fact that highland communities have lower natural immunity to malaria


y = 19.891x + 498.59

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Figure 4. Long-term malaria trends from Igogwe Hospital records. Source: Compiled from Hospital Annual Reports (1969-1993) and MTUHA records (1994 to 2007).

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Figure 5. Long-term malaria trends from Igogwe Hospital records expressed as percent of total Rungwe District Population. Source: Computed from Hospital Annual Reports (1969-1993) and MTUHA records (1994 to 2007).

because of not having been exposed to malaria parasites, the impact of climate change will be greater compared to similar situations in the traditionally warmer lowlands (Yanda et al., 2006; Kangalawe, 2009). However, proper health and climate record keeping is

necessary to facilitate understanding and projection of future trends.

An inquiry on the link between human disease and the perceived climate change revealed that majority of the people recognised such linkage (Figure 7). Malaria,

Kangalawe 61

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Figure 6. Deaths due to malaria in selected health facilities in Mbeya Region. Source: Compiled from MTUHA records 1994 to 2007.

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Figure 7. Responses on the link between climate change and malaria in Mbeya region.

diarrhoeal and respiratory diseases were linked to climate change in that they are influenced by seasonal fluctuations of weather factors such as increasing/decreasing amounts of rainfall or temperature. Responses from household and key informant interviews indicated that in Mbeya malaria is most prevalent during the rainy season, as reported by about 77% of respondents (Table 7), locally attributed to presence of mosquito breeding sites in most areas. This period is also much warmer compared to the cold months like June to August

The responses by some respondents that malaria has become a common phenomenon during other times of the year indicates that generally mosquitoes and associated malaria have found a suitable habit in an area that would traditionally be devoid of malaria without climate change. Traditionally, malaria transmission has

been limited in the highlands because of their low temperatures, which deter mosquitoes and malaria parasites. However, with a rise in global temperatures this trend is changing (Githeko et al., 2000; Wandiga et al., 2006). It was noted in some villages, such as Ilembo in Mbeya Rural district that although there were still no mosquitoes in the area because of the very cold climate, there were many clinical malaria cases. The explanation given was that those who got malaria were bitten by mosquitoes when they travelled outside the village on short-term basis, and returned back to the village with the parasites. Given their low natural immunity they succumb easily to malaria. This shows that apart from climate change mobility could be a compounding stress factor for the prevalence of malaria in some areas (Kangalawe, 2009).

Diarrhoeal diseases were also reported to be most


Table 7. Percentage responses on time of the year when malaria is most prevalent in selected districts in the southern highlands.

Time of the year/season Chunya Mbeya Rural Mbozi Rungwe Total

Rainy season (November to May) 82.4 61.1 100.0 63.6 76.8

Dry season (June to October) 17.6 5.6 0.0 27.4 12.6

All times 0.0 33.3 0.0 9.0 10.6

Total 100 100 100 100 100.0

63.4

16.2

5.5 7.3 7.6

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

0-100,000 101,000-

200,000

201,000-

300,000

301,000-

400,000

>500,000

Household income per month

Perc

entage of re

spondents

Pe

rce

nta

ge

of

res

po

nd

en

ts

Figure 8. Average household monthly income (shillings) in selected villages in Mbeya region.

prevalent during the rainy season, mainly between October and May. This is a generally wet period for most parts of southern highlands of Tanzania. Respiratory diseases were reported to be most prevalent during the cooler months, especially from June to September. Community’s expressions of periods with more disease incidences were also supported by hospital records in all the eleven health facilities visited as part of the assessments of the impacts of climate change on human health in Mbeya region (Kangalawe, 2009). Impacts of malaria on household economy and local livelihoods Many of the respondents who reported to have had malaria or patients suffering from malaria indicated that they had to pay for treatments at the nearby health facility or to buy medication from pharmaceutical shops (Kangalawe, 2009). The low incomes (Figure 8) among most community members may indicate their limited capacity to pay for medical treatment

2 from the health

facilities available in the area. Such low incomes may as well indicate inability to meet various costs related to

2 There was a considerable variation between households regarding experiences

with costs for malaria treatment. The costs were reported to range between 500 and 30,000/= Tanzanian shillings, with a mean value of 10,225/=. The upper

and lowest extremes are values for patients hospitalized and for outpatient

respectively.

climate change adaptations, especially with increased prevalence of highland malaria.

There was a majority concern that the amount they have to pay for malaria treatment is very high and many of them could not afford. This was one of the reasons why in case of a household member getting malaria the household may have to sell livestock or food crops to get cash for malaria treatment. Selling food crops and livestock may have negative impacts on the household food security especially where overselling becomes a problem. As such some households did not afford modern medicine, opting for herbal medicines, as expressed by 17.9% of respondents. This may have some negative consequences on their livelihoods. A Multidisciplinary approach to evaluate the impact of climate change and other stress factors Assessment of non-climate stress factors affecting livelihoods A stress factor in this case is considered as any factor or combination of factors; be it environmental, socio-economical, health related or political that has negative impacts on the natural resource base and livelihoods of the local communities. Table 8 presents examples of non-climate stress factors related to agricultural production, natural resource base and local livelihoods in

Kangalawe 63

Table 8. Examples of non-climatic stress factors in Mbozi District.

Rank Ntugwa village Nyimbili village

1 Health related factors (HIV/AIDS infections; malaria) Health related factors (HIV/AIDS infections; malaria)

2 Crops and livestock diseases/pests Declining soil fertility

3 Shortage of agricultural inputs Shortage of agricultural inputs

4 Shortage of experts Poor road infrastructure

5 Water management problem in farmlands Low prices of agricultural produce

6 Declining soil fertility Inadequate livestock facilities

7 Crimes e.g. stealing food stuffs in fields Youth out migration

8 Water logging during the rainy seasons Lack of capital

9 Poor roads and other transport infrastructure Lack of clean and safe water

Source: Liwenga et al. (2007b).

some parts of the southern highlands of Tanzania. The factors have been ranked based on locally perceived importance.

Health related factors were ranked high, particularly malaria. According to respondents in the study areas even when climatic factors and soil fertility are good enough for agricultural production, good human health remains of paramount necessity for effective management of the farms. A healthy person can undertake various livelihood activities more successfully compared to a less healthy one, even when the climate is favourable. Further, human diseases reduce the labour force, making the undertaking of various livelihood activities by the household rather difficult (Liwenga et al., 2007b; Kangalawe, 2009).

Other common stress factors include declining soil fertility, which was attributed to continuous cultivation without adequate nutrient replacement, which has resulted in declining agricultural productivity. Declining soil fertility was further linked to shortage of agricultural inputs such as fertilizers, improved seeds, pesticides and herbicides. It was reported in Nyimbili that the problem is further compounded by land scarcity that limited agricultural expansion. Nyimbili village is surrounded by protected natural forests, which cannot be exploited for agriculture. With increasing population growth shifting cultivation practices have also declined and fallow periods shortened due to increasing land scarcity (Liwenga et al., 2007b). A combination of these situations compounds the negative impacts of climate change and subsequently threatens the food security situation of the area.

Lack of capital and poor road infrastructure were also reported to be a serious stress factors in many parts of the southern highlands. Out migration of youth from the villages was regarded as an important factor affecting agricultural production and, consequently, food security. Youths were reported to migrate to urban and peri-urban areas of Mbeya town looking for alternative livelihoods. This was reported to be a stress factor limiting the attainment of food security because it reduces labour force at household level thereby reducing sizes of

cultivated farms, and consequently low crop production. Lack of clean and safe water was considered to be

another stress factor due to the fact that in many parts existing water sources such as springs are shared between humans and livestock. In this case, water pollution was reported to be a problem, which could be a cause for various human health risks, such as diarrhoeal diseases. Villages located in lowlands and dominated by clay soils often suffer from water logging during the rainy seasons. This was reported to cause damage to rainfed crops, particularly maize and sorghum, thereby affecting the local people in terms of income as well as food security. This was a particular concern in Ntungwa village located within the Lake Rukwa basin. Another stress factor that impacts the food security situation in many parts of the southern highlands is crop trade. It was reported by communities in Mbozi District, for instance, that crop trade is responsible for food insecurity, the way it happened in 2006 when most of the humid highland areas of the district reported food shortage due to overselling of food crops. This shortage was due to higher prices offered for food crops especially by traders from neighbouring countries (Liwenga et al., 2007b). The areas that were most affected were those easily accessed by the major roads. Thus an area traditionally with favourable climate for agricultural production faced occasional food insecurity because of the influence of market forces. Thus, climatic and non-climatic stress factors may complement or compound the impacts of each other. An already stressed socio-economic environment becomes more vulnerable to environmental change like climate change and variability compared to a less stressed environment under the same level of exposure to risks of climate change and variability. Using multidisciplinary approaches in assessing impacts of climate change and other stress factors Thorough understanding of the impacts of climate change and other stress factors related to food security and


Figure 9. Using participatory approaches in assessing the impacts of climate change and other stress factors in Ntungwa village,

Mbozi – brainstorming (left) and matrix scoring (right).

human health need a multidisciplinary approach. This may be reflected in the assessment tools used, mainly considering the field experiences and ability of the people to comprehend the different tools. Some of the tools used are discussed here.

Field experiences in the southern highlands indicated that for establishing overviews on patterns and impacts of climate change and variability participatory approaches (Chambers, 1992; Mikkelsen, 1995), such as brainstorming could be used, as they facilitate participants to contribute in the discussions (Figure 9). Timelines and key informant interviews are among the other tools that could be effectively used in establishing global change patterns at the local level.

Identification of other stress factors and the magnitude of their impacts on the natural resource base and livelihoods can successfully be undertaken at community level using matrix scoring (Figure 9). Field experience has shown that such an exercise makes participants more excited and eager to participate. Wealth ranking has proven to be another very helpful tool in examining the levels of vulnerability to environmental change and other stress factors in the southern highlands of Tanzania (Kangalawe and Liwenga, 2007; Liwenga et al., 2007a,b). This approach, which determines the endowment of livelihood assets by respective households, is particularly useful in social stratification that influences adaptation and vulnerability to various stress factors such as climate change. Wealth ranking may also provide explanations to questions of why and how certain groups are more vulnerable or most adaptive than others in the same community, for example, as indicated by sizes of farms and number of livestock owned, ownership of food or cash crops, and level of food security of a particular household, among others.

Despite the effectiveness of these tools in assessing the impacts of climate change and other stress factors, these tools need to be integrated as they complement

each other. Nevertheless, field experience has shown that participatory assessments of climate change do contribute to the quick understanding of the patterns of climate variability, the impacts, and adaptive capacities, as well as other stress factors impacting on the livelihood of rural communities. However, for more quantitative analysis such tools need to be complemented by some traditional approaches like household surveys and modelling. Conclusions Like many other parts of the country the southern highlands of Tanzania are vulnerable to environmental change, particularly climate change. Such vulnerability is reflected in various impacts of environmental change on, among others, food security and human health. Agricultural production, which is an essential component of food security, is largely rainfed. This subjects the area to occasional food shortage especially in years with extreme climatic events such as floods and droughts. Droughts have become more recurrent, while floods have often destroyed infrastructure and affecting food distribution and access by many communities. While food security and/or insecurity varies spatially and temporarily depending on rainfall patterns, other stress factors such as soil conditions, socio-economic, cultural factors and access have often influenced food security in the southern highlands of Tanzania and globally.

Environmental change has also had significant impacts on human health in various parts of the country. The rise in global temperatures has been a factor for increased incidences of highland malaria in the southern highlands, areas that were traditionally free from mosquitoes and malaria. Other climate-related health risks have also increased, for example, diarrhoeal and respiratory diseases. Increased health risks due to environmental

change are of particular concern as they impact on the population, including reducing the labour force in agricultural production and other sectors of the economy. Thus sound adaptation mechanisms are needed to address the consequence of climate change on agricultural production, food insecurity and health. While addressing global change impacts on food security and human health it is also important to consider the multiple, and often interdependent, stress factors that affect the community livelihoods, especially in the rural areas. REFERENCES Boko M, Niang I, Nyong A, Vogel C, Githeko A, Medany M, Osman-

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Effect of time of application of spent oil on the growth and performance of maize (Zea mays)

Kelechi L. Njoku*, Modupe O. Akinola and Temitope O. Busari

Department of Cell Biology and Genetics, University of Lagos, Nigeria.


The effect of spent oil pollution on the growth and performance of Zea mays at different stages of growth was investigated in this study. It involved addition of different quantities of spent oil to soils where Zea mays plants at different stages of growth were growing on. The plants showed differential response to quantities of spent oil added to the soils and the times of application. Plants exposed to spent oil pollution one week after germination had the highest level of growth inhibition and the highest chlorophyll content. The leaf area development of the plant was inhibited by the exposure of the plant to spent oil pollution as observed seven weeks after germination. The application of spent oil to the soils three and five weeks, respectively after the germination of the seeds of Z. mays had similar effects on dry matter accumulation of the plant. Statistical differences occur on the growth and performance of the plants exposure to spent oil pollution at different stages of growth (p<0.05, p<0.01 and p<0.001). The results from this study showed that generally Z. mays may suffer greater inhibition of growth and performed poorly when it is exposed to spent oil pollution at tender stage of growth. Key words: Spent oil, time application, growth, performance, Zea mays.

INTRODUCTION Various studies have reported the adverse effect of petroleum products on plants ranging from reduced germination of seeds, reduced survival of plants to reduced yield of plants (Akinola et al., 2004; Andrade et al., 2004). Most of the reports on the effects of petroleum products on plants have focused on crude oil, diesel and gasoline (Siddiqui and Adams, 2002; Inoni et al., 2006) which get to the environment through accidental spillage. However, through the activities of automobile, generator, other machines, and servicing engineers (mechanics) spent oil is discharged to the environment indiscriminately.

Spent engine oil here refers to used motor oil collected from mechanical/automobile, workshops, garages, and industry sources like hydraulics oil, turbine oils, process oil and metal working fluids (Olugboji and Ogunwole, 2008). Spent oil is produced when new mineral-based crankcase is subjected to high temperature high *Corresponding author. E-mail: [email protected]. Tel: +2348033842956.

mechanical strain (ATSDR, 1997). Spent oil is a mixture of different chemicals (Wang et al., 2000) including petroleum hydrocarbons, chlorinated biphenyls, chlorodibenzofurans, lubricative additives, decomposition products and heavy metals that come from engine parts as they wear away (ATSDR, 1997). Spent oil contains polycyclic aromatic hydrocarbons (PAHs) and chemical additives like lead, zinc, sulphur, phosphorus, magnesium, iron, vanadium, aluminum, nickel, calcium, barium, phenols, amines and benzenes (Meinz, 1999). The concentration of PAHs in spent oil increases with time of usage (Vwioko and Fashemi, 2005).

Spent oil is usually obtained after servicing and subsequent draining from automobile and generator engines (Sharifi et al., 2007). Spent oil is a common and toxic environmental contaminant not naturally found in the environment (Dominguez-Rosado and Pichtel, 2004). It gets to the environment due to discharge by motor and generator mechanics (Odjegba and Sadiq, 2002) and from the exhaust system during engine use and due to engine leaks (Anoliefo and Edegai, 2000; Osubor and Anoliefo, 2003). Also the discharge of spent oil to the environment takes place when plants are at different


Table 1. The shoot length (cm) of maize seedlings treated with different amounts of spent oil at their different times of growth.

Treatment days Control 5 ml 10 ml 15 ml 20 ml

Week 1 98.00±4.19 75.57±1.23 69.80±1.85 44.67±22.34 42.37±21.18

Week 3 98.00±4.19 78.13±0.55 74.53±0.38 70.83±0.77 67.87±0.75

Week 5 98.00±4.19 80.50±1.31 76.70±0.60 73.467±0.52 69.23±1.27

Week 7 98.00±4.19 76.37±1.78 68.50±2.22 60.400±5.82 56.03±7.05

stages of growth. The disposal of spent oil into open vacant plots and

farms, gutters and water drains is an environmental risk (Odjegba and Sadiq, 2002). Since spent oil is liquid, it easily migrates into the environment and eventually pollutes either water or soil (Olugboji and Ogunwole, 2008). Contamination of soils with spent oil leads to significant reduction of soil moisture (Akoachere et al., 2008). Spent oil significantly inhibits the activities of soil catalase and dehydrogenase (Achuba and Peretiemo-Clarke, 2007). Spent oil delays germination of seeds and causes reduction in the growth of plants (Adenipekun et al., 2008). The PAHs in spent oil have been shown to have indirect secondary effects like disruption of plant-water-air relationship (Renault et al., 2000) and effects on microorganisms like mycorrhizal fungi (Nicolotti and Egli, 1998).

The disposal of spent oil on farm land can take place when the crops grown on such land are at their different stages of growth. Plants are known to respond differently to their environment at their different stages of growth. It therefore became necessary to study what the effect of disposal of spent oil into the environment will have on the growth and performance of crops with time. This was done in this study using Zea mays as the test plant. Findings obtained in this study will help to guide people in knowing the harmful effect of discharging spent oil on farmlands. As such, farmers will know the stage of the plant growth when it is absolutely necessary to avoid spent oil discharge on farmlands. Such will help to reduce poor yield of crops associated with spent oil spillage. METHODOLOGY

A total of fifty one buckets each filled with 4000 g of loam soil obtained from the Biological Garden of the University of Lagos were used for this study. Three of the buckets were used for control studies and were not polluted with spent oil while the others were

divided into four groups. Each group was subdivided into four subgroups with each subgroup containing three buckets. Each group represented a period of application of spent oil while each subgroup represented a volume of spent oil added to the soil. The spent oil was applied at week 1, 3, 5 and 7 after germination of the seeds of the test plant while the quantities of spent oil applied are 5, 10, 15 and 20 ml.

The plants samples from each bucket were obtained two weeks after the 7th week application of the spent oil by carefully uprooting

one plant from each bucket. The shoot length, dry matter content, leaf area and chlorophyll content of the uprooted plant samples were determined. The shoot length was determined by measuring

the plants from the base of each plant to the tip while the dry matter content was determined as was described by Merkl et al. (2004).

Plant samples were oven dried at 60°C to constant weight for 24 h after which the weights of the dry samples were determined using a sensitive weighing balance (Acculab-USA VIC 300 Model). The leaf area was determined as was described by Pearcy et al. (1989) after measuring the length of the longest part of the leaf and the width of the widest part of leaf by using the formula 0.5 x L x B (L = length and B = breadth). The chlorophyll content of the plant was determined using the method of Heidcamp (2003). It involved the extraction of the chlorophyll of 1 g of each leaf with 10 ml of 80%

acetone. The optical density (OD) of each extract was read off at 652 nm using spectrophotometer. The chlorophyll content (mg/l) of each leaf was determined by dividing the OD reading with 34.5 (Heidcamp, 2003).

The data obtained for the different parameters were statistically analyzed using Graphpad prism 4.0 software. This was done to determine the impact of the different quantities of spent oil applied to the plants and also the impact of the different times of application

of the spent oil on the plant. These were done at 5, 1 and 0.1% levels of significance.

RESULTS

The shoot lengths of maize seedlings exposed to different amount of spent oil at different points of growth are shown in Table 1. The shoot length of the plant treated with 10 mls of spent oil at the first and seventh weeks was significantly shorter than the shoot length of the plant from the control treatment (P<0.01) at same period. Treatment of the seedlings with 15 ml spent oil at first and seventh weeks of growth led significantly shorter shoot than the control treatment at the same period (P<0.001; P<0.01). At all weeks of application, 20 ml treatment led to significant reduction of the shoot length of maize (P<0.05; P<0.01; P<0.001). Plants treated with 15 and 20 ml spent oil were also significantly shorter than those with 5 ml spent oil at one week after germination (P<0.05). The dry matter content the plant was significantly affected by the quantity of spent oil added to the soil (P< 0.05, 0.01, 0.001) as shown in Table 2. Application of 15 and 20 ml of spent oil led to significant reduction of the dry matter content of maize (P<0.05, P<0.01; P<0.001) at all weeks of treatment. 10 ml treatment significantly reduced the dry matter content of maize (P<0.01) only when it was applied seven weeks after the germination of the seeds. Significant differences were also observed in the dry matter content of maize treated with different quantities of spent oil at the different weeks of application. For the dry matter of the maize

Njoku et al. 69

Table 2. The Dry weight of maize seedlings treated with different amounts of spent oil at their different times of growth.


Week 1 0.903±0.05 0.713±0.06 0.630±0.09 0.310±0.16 0.407±0.20

Week 3 0.903±0.05 0.850±0.03 0.770±0.10 0.550±0.09 0.463±0.03

Week 5 0.903±0.05 0.867±0.03 0.803±0.07 0.560±0.04 0.420±0.15

Week 7 0.903±0.05 0.653±0.07 0.440±0.07 0.390±0.05 0.283±0.06

Table 3. The Leaf area (cm2) of maize seedlings treated with various amounts of spent oil at their different times of growth.


Week 1 134.867±9.193 113.87±2.20 106.17±9.74 65.53±33.46 54.87±27.44

Week 3 134.867±9.193 107.40±3.72 101.20±8.10 82.93±9.69 77.00±4.08

Week 5 134.867±9.193 116.67±4.39 109.37±2.24 104.37±1.15 94.20±6.40

Week 7 134.867±9.193 103.93±6.53 105.20±12.19 70.10±5.49 69.07±10.61

Table 4. The chlorophyll content (µg/g) of the leaves of maize seedlings treated with various amounts of spent oil at their different times of growth.


Week 1 0.043±0.009 0.034±0.001 0.030±0.002 0.019±0.009 0.007±0.003

Week 3 0.043±0.009 0.032±0.004 0.027±0.002 0.025±0.001 0.017±0.001

Week 5 0.043±0.009 0.028±0.001 0.023±0.001 0.019±0.002 0.014±0.000

Week 7 0.043±0.009 0.019±0.002 0.017±0.001 0.012±0.001 0.008±0.002

Comment on Why same values were for the control at the different times of Application: The control results are same for all the weeks because nothing was added to the control and the samples were obtained the same time (that is, 9th week) after the germination of the seeds. The standard error values for the shoot lengths of the crops treated with 15 and 20 ml of spent oil are

correct. The high error values are because each treatment was replicated thrice and result for one of the replicates was very low compared with other two replicates. Same reason goes for the high error values in the leaf area results.

plants treated with 15 ml spent oil was significantly lower than that of the plant treated with 5 ml of spent oil week one after germination (P<0.01). The dry matter content of maize treated with 20 ml spent oil was also significantly lower than the dry matter of the plants treated with 5 ml of spent oil at the 3rd, 5th and 7th weeks of application (P<0.05; P<0.01).

The leaf areas of the plants treated with low levels of spent oil are higher than the leaf areas of the plants treated with higher levels of spent oil (Table 3). Statistical differences exist among the leaf areas of the plants treated at different times. The leaf areas of maize treated with 15 ml spent oil at the first, third and seventh weeks of growth were significantly smaller than the leaf area of the plant not treated with spent oil (P<0.001; P<0.05 and P<0.01) respectively. At the same times of application of spent oil, similar smaller leaves were noticed in plants treated with 20 ml spent oil than in plant not treated with spent oil (P<0.001; P<0.01)(Table 4). Treating the plants with 15 ml spent oil and 20 ml spent produced greater impacts on the leaf area of the plant than treating the plant with 5 ml spent oil (P<0.05 and P<0.01)

respectively. The chlorophyll of the maize plant generally decreased

with the increase in the amount of spent oil added to the soil. While the 5 ml treatment led to significant reduction of the chlorophyll content on at the first week of application (P<0.01), the chlorophyll content of the plant treated with 10 ml spent oil at the first and third weeks of growth was significantly lower than that of the plants from the control treatment (P<0.05; P<0.01). Treating the plant with 15 ml spent oil at the first, fifth and seventh weeks of growth significantly reduced the chlorophyll content of the plant (P<0.01; P<0.001). At the same level of significance, treatment of the plants with 20 ml spent oil at all the weeks of application led to significant reduction of the chlorophyll content of the plant. The chlorophyll content of the plant treated with 20 ml spent oil was also significantly lower than that of the plant treated with 5 ml spent oil at the third week (P<0.01) and the chlorophyll content of the plant treated with 10 ml oil at the first week of growth (P<0.01). The chlorophyll contents of the plants treated at the fifth and seventh weeks were more closely related than the chlorophyll of the plants treated on the

70 Afr. J. Environ. Sci. Technol. other weeks.

DISCUSSION

The reduction of the plant growth observed in this study could be due to reduction of mineral element with increasing oil concentration in the soil reported by Odjegba and Atebe (2007). This could have occurred as a result of reduced availability of mineral elements because according to Clarkson and Hanson (1980), plant nutrition is based not only on the presence of mineral elements in the soil but their availability. Another possible cause of the effects of spent oil on the maize plant observed in this study could be due to either the increased acidity in the soil or reduction in the catalase activity reported by Achuba and Peretiemo-Clark (2007). Such increase soil acidity can affect the microbial distribution in the soil reducing their activities in the rhizosphere. The reduction of the catalase activity can affect the optimal soil conditions required for plant growth hence the reduction of plant growth observed in this study.

According to Meinz (1999), spent oil contains heavy metals and polycyclic aromatic hydrocarbons and chemical additives including amines, phenols, benzenes, calcium, zinc, lead, barium, manganese, phosphorus and sulphur which are dangerous to living organisms. The high level of toxic heavy metals and polycyclic aromatic hydrocarbon which has been reported to be present in spent oil can also account for the growth inhibition observed in this study.

The reduction of the chlorophyll content of the plant could be due to the interference of the oil on the ability of the plant to absorb some of the mineral nutrients. Minerals like magnesium, iron, boron, and manganese are essential for chlorophyll synthesis (Campbell, 1996; Taylor et al., 1997; Kent, 2000). Such interference and the reduced rate of photosynthesis which accompanies reduction of chlorophyll can lead to plant death and stunted growth. Also the reduced leaf areas of the plants due to the addition of the spent oil can aggravate the photosynthesis level in the plant with resultant poor performance of the plant. All these can lead to low yield of the plant and low availability of food. The lower performance of the plants treated with spent oil at the first week of growth indicates that the plant has less resistant to pollution by spent at tender age than when it grows older. This is similar to the observation of Agbogidi et al. (2007) who observed more adverse effects on maize exposed to crude oil pollution at tender stage than at later stage. The greater impact of the spent oil on the tender plants indicates that the tender tissues are more susceptible to injurious effects possibly due to severe disintegration of the cell in soft basal stem segment of the plant. This is similar to the findings of Baker (1970) and Anoliefo (1998). This suggests that apart from the level of

pollution, the age of plant has much influence on the survival of plants to oil pollution. As suggested by Agbogidi et al. (2007) the higher resistance of the older plants to the spent oil pollution may be due to the presence of already cutinised tissues in such plants.

In conclusion, from the results obtained in this study, it is advised here that to reduce loss of plant due to oil pollution, plants should not be exposed to oil pollution when they are at the tender stages. Also there should be stricter measures on indiscriminate disposal of spent oil in the environment particularly farmlands as this will reduce the yield of crops affected by indiscriminate disposal of petroleum products pollution to the environment. REFERENCES

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Prestige Oil spill on salt marsh soils on the coast of Galicia (Northwestern Spain). J. Environ. Qual., 33: 2103 – 2110.

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Implications of ecological and social characteristics to community livelihoods in the coastal areas of Tanzania

Majule A. E.

Institute of Resource Assessment (IRA), University of Dar es Salaam, P.O. Box 35097, Dar es Salaam, Tanzania. E-mail: [email protected].


This study explored the implications of both ecological and social economic characteristics on community livelihoods and environment in distinct villages namely Mwanambaya and Kwala in Mkuranga and Kibaha districts respectively. Both districts located in coastal areas of Tanzania experienced pressure on natural resources appearing in different ecological settings. Data were collected using different tools and the analysis employed SPSS package. Results showed that agriculture production is the main source of livelihoods by 78 and 74% of respondents in Mwanambaya and Kwala respectively. Fertile soils, available water, more and suitable pasture, more vegetation with large trees attracted pastoralist in particular Wasukuma and Maasai tribes to Kwala area. Exploitation of different natural resources including cutting trees for charcoal and building, overgrazing contributed to land degradation mostly in Kwala by 40 and 20% of respondents in Mwanambaya. This study has established that community livelihoods in both urban and rural areas of Tanzania depend on natural resources organized in a form of an ecological gradient. This organization allows for different livelihood systems to interact and thus creating impacts on ecosystems and social economic undertakings. In order to sustain ecosystems productivity, establishment and implementation of village land use plans is a necessity. This will further address conflicts over resource uses that may arise due to livelihood systems interactions. Key words: Agriculture, coastal region, ecological gradient, livelihoods, Ruvu river, Tanzania.

INTRODUCTION In Sub-Sahara Africa, the majority of community obtains their livelihoods through exploitation of natural resources and their products (Liwenga, 2005; Majule et al., 2009). Different natural resources found in the region including Tanzania are widely distributed depending of ecological settings which are also diverse in nature (De Pauw, 1984). The United Republic of Tanzania (URT) is located in Eastern Africa between longitude 29° and 41° East, Latitude 1° and 12° south and it is boarded with Uganda, Burundi, Rwanda, Kenya, Malawi, Zambia and Mozambique. Tanzania has a spectacular landscape of mainly three physiographic regions namely the Islands and the coastal plains to the east; the inland saucer-shaped plateau; and the highlands. The Great Rift Valley that runs from north east of Africa through central Tanzania is another landmark that adds to the scenic view of the country (De Pauw, 1984). It also has pristine sandy beaches and Africa’s highest and snow-capped

mountain, Mountain Kilimanjaro. Tanzania is home to the world famous national parks and game reserves which attracts tourism activities. Physiographic feature and landforms allows for different social economic undertakings allowing for significant interactions to take place among different communities across well defined ecological gradients (Maitima et al., 2009; Majule et al., 2009). It is generally accepted that in Tanzania agriculture plays a very important role in providing food and income for the majority of the population (Shao, 1999). Over 70% of the population depends on subsistence agriculture which is entirely rain fed. Agriculture accounts for an average of 50% of gross national product (GNP) and about 66% of total export earnings.

Land suitability studies in Tanzania have indicated that there are seven major farming system zones suitable for different agricultural crops and livestock farming activities

http://www.tanzaniatouristboard.com/places_to_go/national_parks_and_reserves

(De Pauw, 1984). Of interest to this paper is the eastern and southern coast zone which is a cashew and cassava based farming system. This zone exhibit different forms of gradients where different livelihood activities interact across societies (Majule et al., 2009). The interactions across gradients may occur within land-use or livelihood systems being influenced by both ecological and social economical factors. For examples availability of livestock feeds and water in wetter parts of Tanzania in particular the Kilombero and Ruaha Sub catchments has attracted a number of livestock keepers from drier central parts of Tanzania (Majule and Mwalyosi, 2005; Majule and Kalonga, 2008). On the other hand presence of conducive social economic activities and social infrastructures are clearly known to bring about in migration of people from different areas within the country. Such kind of relationship is also very common in many other parts of Africa and has been documented by a number of scholars including Bernard et al. (1989) Campbel et al. (2003) and Majule et al. (2009). Finding from such studies have indicated that communities and ecosystems tends to interact in a number of ways depending on a particular service required. Recently, the impacts of climate change have been reported among others to accelerate the rate of human movements from low to high potential areas (Majule et al., 2008; Lema and Majule, 2009).

Studies conducted by Madulu (1996); Rosenzweig et al. (2002); Kangalawe and Liwenga (2005); Mongi et al. (2009) revealed that changes in rainfall patterns and amounts have led to loss of crops and reduced livestock production due lack of pasture and water availability. A common tendency has been for agro pastoralist to move with their livestock to potential areas that receives significant amount of rainfall exceeding 1,000 mm per season (Maitima et al., 2009). In this case climate change is likely to intensify drought and increase potential vulnerability of the communities to future climate change (Hillel and Rosenzweig, 1989), where crop production and livestock keeping are critically important to food security and rural livelihoods. On the other hand linkages between rural and urban centers in terms of livelihoods can not be avoided because this acts as a copping or adaptation measure in response a multifactor effects on community livelihoods and ecosystems productivity. The present research explored the implications of both ecological and social characteristics of two distinct areas on community livelihoods. The study also established driving forces for immigrants in study areas. METHODOLOGY

Description of the study area The study was carried out in two districts of the coast region namely

Mkuranga and Kibaha in Tanzania (Figure 1). In Mkuranga, the study was conducted in Mwanambaya village where by in Kibaha it was conducted in Kwala village. The two district were selected due

Majule 73 to their variations in terms of ecology, Mkuranga being located along the coastal shores of Indian Ocean dominated by dry sand soils namely Arenosals and also by having two distinct rain seasons namely short (vuli) and long ones (masika) where as Kibaha is located in the inner parts of the coastal region with variable soil types ranging from sand soils, mbugas and fluvisols (De Pauw, 1984) influenced by flooding of Ruvu river. On the other hand ariation in social economic and livelihood activities between the two districts was assumed to have impacts on natural resource use and human settlement patterns.

Two villages, namely Mwanambaya and Kwala located in Mkuranga and Kibaha districts respectively (Figure 1) were selected with an assistance of respective district natural resource officers

because the villages were found to be the most representative for addressing the objective of this study. They constitutes to the four administrative districts of the coast region in Tanzania. Mkuranga is located on the coastal land with undulating plains while Kibaha is located in the inland coastal plains that constitute the Ruvu sub basin of Rufiji Basin (Figure 1). The environmental of Mkuranga is characterized by a variation in both maximum and minimum coastal temperature with both short and long rain seasons. The climate of Mkuranga district is basically of an inland equatorial type modified

by the effects of altitude and distance from the Equator (De Pauw, 1984). Data and analysis Both secondary and primary data were collected from various source using different techniques. Secondary sources included published research papers and relevant social and ecological

reports about the area. Primary data were collected using multiple approaches including both quantitative and qualitative participatory rural assessment (PRA). The methods included focus group discussions (FGD) and household questionnaire. For FGD discussion at total of 15 people in each village were involved. For household interview a total of 52 and 38 head of houses were interviewed using a semi structured questionnaire and two figures represents 10% of the total number of households for

Mwanambaya and Kwala respectively. A stratified random sampling procedure based on the locally perceived wealth categories was used for household interviews (Kothari, 2004). The methodology used in data collection and analysis is quite similar to that reported by Kangalawe et al. (2005); Majule and Kalonga (2008) and Lema and Majule (2009). Key informant interviews and FGD generated general information about the villages on ecological gradients and linkages across and within gradients and also social economic information. On the other hand, household data validated critical information generated during FDG. Qualitative data from household survey were first edited, coded and entered in a computer and the statistical package for social science (SPSS) software version 11.5 spread sheet was used for the analysis. Tables and bar charts were used to present different evolution of variables.

RESULTS AND DISCUSSION Social economic characteristics Ethnicity in both villages studied is presented in Table 1. Results show that both villages have more than one tribe and this suggests that in migration has taken place due to different ecological and social economical factors. Common tribes in Mwanambaya village are Zaramo, Ngindo and Wandengereko forming 48, 24 and 16% respectively of the total number of households. Zaramo


Figure 1. Map of coastal region showing the location of the study villages (need to be improved-not clear).

Table 1. Ethnicity of communities by % in two villages studied.

Major tribes Study villages

Mwanambaya (n=52) Kwala (n=38)

Zaramo 48 56

Ngindo 24 0

Ndengereko 16 0

Sukuma 4 24

Chaga 4 0

Maasai 4 20

Total 100 100

and Ndengereko are native tribes while Ngindo originated from Lindi region and they migrated into the area for agricultural reasons in particular cashewnut and cassava farming.

On the other hand, Kwala village which is found within Ruvu sub basin is also dominated by Zaramo. However Maasai from the northern pastoral areas of Tanzania and Sukuma tribes from the central and western parts of

Majule 75

Table 2. Education profiles by % of community members in study villages.

Level of education Study villages


No formal education 44 32

Primary education 36 68

Secondary education 4 0

Post secondary education 16 0

Total 100 100

Figure 2. Main sources of livelihoods by % in study villages.

Tanzania have migrated into the village. The Maasai are pastoralist and have moved into the area for livestock keeping due to suitable characteristics of the village in terms of water and pasture. Sukuma are agro pastoralist. They have moved into the village due to similar reasons but additionally they are also engaged into farming activities due to high natural fertility of soils in area. During focus group discussions it was revealed that the number of immigrants for livestock keeping is increasing although it was not possible to establish the actual statistics.

Education level plays a significant role in managing natural resources and ecosystems. The numbers of household members who have no formal education (Table 2) are not comparable in both villages probable due to some cultural reasons. This is suggesting a need for promoting and encouraging communities to allow their children to attend schools. More have attended primary education in Kwala due a presence of a nearby primary school within a village while slightly lower members have attended primary school in Mwanambaya due to the fact that a primary school a little bit far from the village.

Provision of social services near the communities including schools (both primary and secondary) is under the government agenda and this is a being effected in order to improve education levels in the country. The numbers of households who have attended secondary and post secondary education is high in Mwanambaya due to accessibility to urban center (Dar es Salaam and Mkuranga) where secondary schools area found. Main sources of livelihoods in study area Figure 2 presents major sources of livelihoods in study villages. Agriculture is the main source of income in both villages and is followed by employment in formal sectors such as teaching and health sectors in on both villages. Such pattern is quite similar to that reported by Majule et al. (2009) for southern coastal areas of Tanzania.

According to focus discussions conducted in study villages and also household interview results (Table 3), different crops contributes to community livelihoods. For example cassava and pineapples contributes more in

% o

f re

sp

on

de

nts


Table 3. Major crops grown in study villages by % of respondents.

Livelihood source Study villages


Cassava 32 8

Maize 8 40

Rice 4 32

Pineapples 28 12

Coconut 16 0

Water melon 16 8

Total 100 100

Table 4. Formal land use prior occupation by % in study villages.

Formal land use Study villages


Forest land

64

56

Woodlands 4 32

Grazing land 0 8

Crop land 32 4

Total 100 100

Mwanambaya village as compared to maize and rice in Kwala village. Maize and rice are heavy feeder crops which needs fertile soils, reliable rainfall and enough water to grow (Rowell, 1994; Sakala, 1998; Majule and Mwalyosi, 2005). Such ecological conditions are found in Kwala village and this indicates a potential for promoting such crops in the long run due to land suitability.

Studied villages are not densely (with less than 100 people per square km) populated at the moment and this is indicated by the fact that 96 and 80% of the households surveyed does own land in Mwanambaya and Kwala villages respectively. An increase in the proportion of households renting land in Kwala (12%) compared with 4% in Mwanambaya is mainly for livestock and grazing and agricultural production reasons. The findings suggests that in both villages there are opportunities for absorbing immigrants unlike high potential areas in east African gradients reported by Maitima et al. (2009). Major landuse/cover and changes There has been a significant change in landuse over the last 50 years in study villages according to FDG discussions. Household survey statistics (Table 4) also revealed that; i) forest land has decreased on the expense of agriculture and human settlements in both villages; ii) in Kwala village there is still more land covered by woodlands and this allows for charcoal production and trade to continue; iii) crop land (32%) is

common in Mwanambaya village and this is managed by immigrants from urban areas; iv) grazing land is still available in Kwala village and this has been a driving force for agropastoralist (Wasukuma and Maasai tribes) who migrate to Kwala with their livestock as coping and adaptation strategies from their degraded environment.

In exploring reasons contributed to landuse changes in the coast region of Tanzania, this study has revealed that both social economical and ecological factors have played a significant role (Table 5). Accessibility to market centers accounts for 56 and 20% in Mwanambaya and Kwala villages respectively. The reason for such a difference is that Mwanambaya is very close to urban centers compared to Kwala village. Being close to market centers in urban areas whereby demand on natural resources and products is high has been reported to contribute towards landuse changes in many areas (Muganyizi, 2009; Majule et al., 2009). On the other hand, Mwanambaya is well connected to urban areas by a tarmac road to from Dar es Salaam city to the southern parts of Tanzania (Figure 1). This allows for easy and faster transport of different products from and to the village. This is not the case with Kwala village although it has railway connection which is not functional most of the time. Deforestation (Table 5) is more significant in Kwala and this has contributed significantly to landuse changes (40%). Invasion by livestock keepers coupled with expansion of farmland in Kwala also contributes to landuse changes. These observations are in broad agreement with findings by Majule et al. (2010) under similar environment in western parts of Tanzania.

Majule 77

Table 5. Major factors for land use changes in study area.

Major reasons Study villages


Accessibility to market centers 56 20

Deforestation 12 40

Arrival of livestock keepers 8 24

Expansion of farmland 24 16

Total 100 100

Figure 3. Major services offered by ecosystems in study villages.

On the other hand, both villages are equally important in terms of providing different services from the natural resources they have. Figure 3 presents contributions from different natural resources to community livelihoods. The ecology of Kwala provides conducive environment for livestock grazing as compared to Mwanambaya and this is due to availability of water from Ruvu river and associated wetlands as well as pasture for livestock. As indicated in Figure 3, the ecosystem in Kwala provides a wide opportunity for grazing livestock equally followed by agricultural, charcoal supply and seasonal hunting. Hunting activity was reported to be negatively affected by increasing number of livestock keepers looking for pasture land and this has pushed wildlife animal further into protected areas. On the other hand there is large opportunity for crop cultivation in Mkuranga but more people are now moving into the area to settle. The cost of land has increased over the last 10 years from an equivalent price of approximately US$ 200 in year 2000 to more than US$ 1000 to date based on local market prices.

More land in Mwanambaya is currently under agricultural crops in particularly cashewnut, cassava and orchards particularly citrus. However there is more expansion of human settlements in Mwanambaya due to in migration of people from urban areas in particularly Dar es Salaam. On the other hand, the woodlands and forests in Kwala are designated as open areas which also accommodate wild animals including elephants and buffaloes. They are therefore a source of animal proteins from wild animals. Through FDG it was revealed that invasion of livestock has pushed further towards to the boundaries of Selous Game Reserve which has a diversity of wildlife species and types thus threatening their security and survival. Negative impact due to pastoral and human activities on wildlife dynamics has also been reported by Kangalawe et al. (2005) and Majule and Kalonga (2008). In general the ecology of Kwala allows for different social economic activities to be undertaken. However sustainable management plan of natural resources needs to be developed and implemented in order to reduce land degradation (Majule,

% o

f re

sp

on

de

nts


Table 6. Commodity flows by % from study villages to peri and urban centers.

Sources of income Study villages


Sell of cattle 04 32

Sale of fruits 24 4

Sale of cash crops 20 8

Supply of charcoal 20 32

Supply of building poles 24 08

Supply of wild meat 08 16

Total 100 100

2008; Kangalawe and Lyimo, 2010). Rural-urban linkages in relation to ecological and social settings Commodities and products flowing from the two villages (Table 6) to peri and urban centers are not equally the same in terms of magnitudes and this reflects a strong variation in terms of ecological characteristics to offer a particular service. More meat and charcoal for example comes from Kwala village due to abundant livestock keeping (32%) of the total respondents and more charcoal dwellers (32%). More building poles come from Mwanambaya probably due to availability and accessibility to the market centre. On the other hand fruits particular oranges, pineapples and passion originates from Mwanambaya and this is due to favorable physical conditions particularly deep and well drained sand soils which favors the production of such crops (Rowell, 1994). Different products also flow from urban areas to study area. Those of relevance includes maize and wheat flours, clothes, roofing materials, cooking oils and other products like kerosene oil. Most of the products flowing to study areas are from manufacturing industries.

Community livelihoods of the majority of people living in both urban and rural areas depend on natural resources and their products for their livelihoods (Majule et al., 2009). Findings reported are also in broad agreement with those reported by other scientists under similar conditions.

Conclusions Crop production and livestock keeping are the major agricultural activities in the coastal areas of Tanzania. The study has been able to establish that different ecological and social economic settings have significant contribution to community livelihoods in a number of ways. They also determine a kind of service and products to be offered depending on a particular need in both rural and urban areas. Potential areas in terms of soil fertility, water availability and pastures for livestock attract agro-

pastoralists to migrate into. Such interaction brings about changes in landuse and degradation of natural resources in case of unsustainable extraction of different natural resources. Expansion of agricultural activities further contributes to landuse changes. In order to sustain the ecosystems productivity the study recommends establishment and implementation of village landuse plans and come up with sustainable strategies for use of natural resources in their villages. These must be supported by their local district councils for their effectiveness. ACKNOWLEDGMENTS Author appreciates a support from the University of Dar es Salaam, Tanzania through the Institute of Resource Assessment (IRA) for granting a permission to a researcher to conduct this study. Staff members of the District Agricultural and Livestock Office for Mkuranga and Kibaha districts are also thanked for their guidance on sites selection and provision of secondary data. Finally, author would like to send his sincere thanks to research assistants Mr Brown Gwambene and Obed Mambo for assisting in primary data collection and analysis. Village leader and communities who participated in providing data are also thanked.

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