Trees for Development...Ingrid Haeckel - Trees for Development: Reforestation in Veracruz - CRP 386...
Transcript of Trees for Development...Ingrid Haeckel - Trees for Development: Reforestation in Veracruz - CRP 386...
Trees for Development:
Merging Environmental Restoration and Poverty Alleviation
Objectives via Reforestation in Veracruz, Mexico
Ingrid Haeckel
Department of Geography and the Environment
University of Texas at Austin
December 10, 2009
CRP 386: Intro to Geographic Information Systems
Ingrid Haeckel - Trees for Development: Reforestation in Veracruz - CRP 386 Fall 2009
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EXECUTIVE SUMMARY
Reforestation is gaining attention throughout the world, and particularly the tropics, as a
climate change mitigation strategy, as well as an opportunity to restore degraded areas
and ecosystem services that have been lost or diminished. The economic incentives
provided by emerging carbon markets have led many to speculate that reforestation could
provide synergistic environmental and development benefits in developing countries.
In Mexico, reforestation has emerged as a major environmental policy goal, highlighted
by the launch in 2007 of a new forestry program, Pro-Árbol. Pro-Árbol merges goals of
environmental restoration with poverty alleviation and aspires to create economic
development by fostering a sustainable forestry sector. Within Mexico, Veracruz has
been identified as one of the states with most success in meeting this goal. This project
examines whether the objectives to reduce poverty and marginalization in critical
environmental areas were targeted through reforestation funding during 2007-2009.
Suitable areas based on marginalization, indigenous population, soil degradation, and
hydrological service and biodiversity conservation areas are then ranked to prioritize
municipalities for future reforestation funding.
The 2007-2009 Pro-Árbol reforestation results indicate subsidies are being applied in
marginalized areas; however, environmental objectives need more attention. Women
were underrepresented among accepted project applicants and it is unclear to what extent
indigenous communities have participated. This analysis indicates that high priority areas
for reforestation, including Perote, Misantla, Orizaba, and Huayacocotla UMAFORs have
been well served by Pro-Arbol, but future outreach and funding for reforestation should
target the Totonacapan, Veracruz, Los Tuxtlas, and Uxpanapa UMAFORs. Altogether,
more monitoring and reporting is needed to assess the success of reforestation projects to
date and to more clearly address how they are contributing to rural development.
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INTRODUCTION
Reforestation and forest restoration are major environmental goals throughout the
tropics following decades of widespread deforestation. Recently, however, international
negotiations and policies to mitigate climate change have begun to generate powerful
political and financial incentives to reverse the trend of forest loss. Growing trees store
and sequester large volumes of carbon and contribute to rainfall patterns through high
evapotranspiration, serving an important role in global climate (Bonan 2008). In addition
to carbon sequestration, however, reforestation can restore environmentally degraded
areas by reducing soil erosion, meanwhile improving water quality and infiltration, as
well as potentially increasing water capture. The use of native tree species in reforestation
projects will furthermore enhance the value of restored areas for biodiversity (Chazdon
2008). The potential to restore a variety of ecosystem services where they have been lost
has led to many recent efforts at making reforestation attractive to the rural communities
where restoration is most needed and can have the greatest potential benefit to society
(Lamb, Erskine, and Parrotta 2005).
Carbon forestry projects of the Kyoto Protocol’s Clean Development Mechanism
(CDM) have emphasized the synergistic benefits between reforestation and livelihoods;
however the reality of benefits to the rural poor has been questioned critically by many
scholars (Smith and Scherr 2003). Unless reforestation projects can overcome the
significant implementation challenges facing rural poor households and communities that
they are intended to benefit, such policies will likely result in the continued expansion of
large-scale commercial plantations with little environmental or social benefit. The high
start-up costs of reforestation or plantation establishment, as well as distant benefits and
high risk of the investment are major hurdles to the adoption of forest restoration by
smallholder farmers in the tropics (Coomes et al. 2008). However, with government
subsidies and appropriate information and technical support, reforestation could be
successful as an element of a diversified rural development strategy (Lamb, Erskine, and
Parrotta 2005).
Mexico is one country that has embraced the issue of reforestation together with other
forest conservation and management strategies, establishing a national forestry
commission (CONAFOR) in 2001 and developing a comprehensive new forestry
program, Pro-Árbol, in 2007. Since then, Mexico has invested approximately US $1.5
billion in Pro-Árbol, funding forestry projects on 6.8 million hectares of land and
lowering the national deforestation rate. Policymakers in Mexico have embraced the
potential of forest restoration projects to alleviate poverty and lead to development based
on sustainable forest resource management. However, promoting trees for development is
a very new approach to Mexican forestry policy, which until the early 1990s was largely
based on the promotion of commercial tree plantations, often with exotic species
(Carabias, Arriaga, and Cervantes Gutiérrez 2007). Today, approximately 98% of trees
planted in Pro-Árbol reforestation projects are native species, and there is great demand
to increase the diversity of native species utilized (Valtierra Pacheco et al. 2008).
Although the use of native species is likely to increase the benefit of reforested areas to
biodiversity and possibly hydrological services based on studies elsewhere
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Figure 1.1
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(e.g., Kanowski, Catterall, and Wardell-Johnson 2005; Farwig, Sajita, and Böhning-
Gaese 2008; Bruijnzeel 2004), the actual economic incentives and benefits to reforesting
agricultural land for the rural poor in comparison with alternative land uses have not been
clearly articulated or examined in Mexico.
Within Mexico, Veracruz has been identified as one of the states with most success in
reforestation under Pro-Árbol and with high potential for establishing commercial tree
plantations, estimated at approximately a million and a half hectares (CONAFOR 2009;
Velázquez Álvarez 2007). Veracruz is located on the Gulf Coast of Mexico, flanked to
the west by the Sierra Madre Oriental (Figure 1.1) and neighbored by the states of
Tamaulipas, Hidalgo, Puebla, Oaxaca, and Tabasco. While the majority of the state’s
territory lies in the coastal plain, elevations climb sharply up to 5,200 m above sea level,
the height of the Pico de Orizaba, the highest mountain in Mexico (Figure 1.2). The
diverse topography results in high diversity of ecosystems and biodiversity and
endemism. Only 8.8% of Veracruz’ natural vegetation remains, with 72.1% of the state’s
territory in agricultural and urban land use (Figures 1.3) (Velázquez Álvarez 2007). The
state remains fifth in Mexico in terms of deforestation, losing approximately 30,000
hectares annually despite recent restoration efforts (Figure 1.4) (Velázquez Álvarez
2007). Approximately a third of Mexico’s surface freshwater flows through the major
watersheds of Veracruz, which underscores the significance of maintaining the
hydrological functions provided by forest cover.
Although Veracruz is known for its strong agricultural and industrial sectors, many
municipalities continue to have high indices of socio-economic marginalization, with 37
of the state’s 212 municipalities ranked as highly marginalized in 2005 (CONAPO 2005).
Depressed markets for agricultural products and high unemployment have led to a
significant increase in transnational migration from Veracruz in the last decade (R.
Torres, pers. comm.). It is not known what role the agricultural economy or migration has
played in the recent decisions of land owners to reforest former agricultural lands.
Pro-Árbol
Pro-Árbol was founded in 2007 to unite and expand upon several previous forestry
programs, including the Programa de Desarrollo de Plantaciones Forestales
(PRODEPLAN) and the Programa de Desarrollo Forestal (PRODEFOR) under a single
framework. The program provides subsidies for the conservation, restoration, and
management of forest resources, as well as for planning to increase the competitiveness
and productivity in the commercial forestry sector. Pro-Árbol is an umbrella for the
support of diverse forest-related activities in Mexico, but reforestation under the category
of conservation and restoration is the flagship activity and one of the largest destinations
for subsidy funding. Land owners who apply for funding to reforest land must
demonstrate legal ownership, meet certain rules regarding the application of subsidies,
and own a minimum of five hectares of land or join other land owners in a group to reach
the minimum required area. Importantly, subsidies are only given for properties in areas
that would naturally be forested or that can develop forests (SEMARNAT, 2009). In
addition to providing a subsidy to cover most of the expense for labor to plant the trees,
CONAFOR provides the saplings free of cost. Nearly all trees planted are native;
however, Pro-Árbol has been strongly attacked for counting Agave and Opuntia species
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Figure 1.2
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Figure 1.3
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Figure 1.4
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towards total reforestation estimates, accounting for more than 50% of the plants
reforested in 2007 (Valtierra Pacheco et al. 2008).
Applications for reforestation funding are prioritized according to several social and
technical parameters. Applicants from highly marginalized municipalities or
municipalities with over 50% indigenous population are given preference, as well as
women or members of community forestry organizations. Applicants who are in the
process of obtaining or have already completed certification in a forest management
program or related certification are also given preference, as well as those with land
under technical silvicultural supervision.
In addition to social and technical considerations, Pro-Árbol specifies areas eligible
for Mexico’s Payment for Ecosystem Services (PES) program, established in 2003 and
also administered by CONAFOR. In particular, areas eligible for payments are based on
the provisioning of hydrological services and biodiversity conservation. Multiple criteria
were utilized to determine these specific areas. Hydrological eligible areas are determined
based on forest cover, critical zones for aquifer recharge or in zones with problems of
surface water scarcity, water quality, and hydrological hazards. In particular, areas within
priority mountain regions or natural protected areas are given preference. Biodiversity
eligible areas are determined based on species distribution assessments, wetland
protected areas, priority mountain regions, and conservation priority areas determined by
the Comisión Nacional para el Uso y Conocimiento de la Biodiversidad (SEMARNAT,
2009).
Given the significant social and financial investment in reforestation under Pro-Árbol
since its inception in 2007, it is important to evaluate the program’s advances. Veracruz
will serve as a case study for examining the distribution of reforestation efforts during
2007-2009 to evaluate how the objectives of restoration and development were targeted
in funded projects. Geographic Information Systems (GIS) is employed as a tool to
weight Pro-Árbol’s unusually far-ranging objectives and rank the priority of certain
regions for future funding.
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PROBLEM STATEMENT & RESEARCH QUESTIONS
Given Pro-Árbol’s dual goals of environmental restoration and development,
reforestation subsidies should be targeted at municipalities with high levels of socio-
economic marginalization and high indigenous population, favor the participation of
women, as well as prioritize areas with known soil degradation or with high value to
hydrological services and biodiversity conservation. The distribution and density of
funded projects should reflect these diverse applicant selection criteria.
If reforestation funding thus far has not noticeably targeted these objectives, how
might future funding be more strategically allocated? Geographic Information Systems
(GIS) is a tool to store, manipulate, and analyze spatial data with applications for
planning. Suitability analysis is a method to identify and prioritize suitable areas based on
a set of criteria for a specific objective. Suitability analysis may be applied to identify and
rank areas in Veracruz based on socio-economic, cultural, and environmental criteria to
assist with the selection of future funded reforestation projects.
This study tests for the relationship between social and environmental variables and
total area reforested per municipality in Veracruz during the first three years of Pro-
Árbol. GIS is utilized to visualize initial reforestation results for Veracruz in terms of
area reforested and the gender composition of project participants. A methodology is then
created and tested for ranking eligible areas for reforestation in the state.
This particular study is limited by the coarse scale of municipal level data that is
available; however, the methodology could be adapted given more precise data on
individual applicants, such as socio-economic background and specific geographic
location. CONAFOR collects this information, but it is not publically available for
privacy reasons.
In summary, the main research questions are:
1) What if any relationship is there at the municipal level between the distribution
and density of reforestation projects and socioeconomic marginalization,
indigenous population, soil degradation, and hydrological and biodiversity
priority areas in Veracruz?
2) What areas are most suitable for future reforestation funding to further the goal of
environmental restoration and development?
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METHODOLOGY
The project was carried out in the following five steps:
1. Data acquisition
2. Data organization
3. Suitability Analysis to rank municipalities for future Pro-Árbol funding
4. Linear regressions to test the realization of funding objectives by allocation to
projects during 2007-2009
5. Create maps
1. Data Acquisition
Two main types of data were utilized in this study: tabular data from the Mexican
census and CONAFOR in Microsoft Excel files, and spatial data in ESRI shapefile
format. My ability to test the research questions was limited by the level of detail in
public records regarding Pro-Árbol participants and the characteristics and location of
areas reforested, as well as by the availability of online spatial datasets for Mexico.
Approved reforestation projects funded by Pro-Árbol are published annually on
CONAFOR’s website; however, the information provided in reports differs from year to
year. At present time, reports are available for category C1.1 Reforestation projects for
the years 2007-2009. I copied all information on these projects into Excel spreadsheets,
including columns for applicant name, municipality, area to be reforested, and funding
approved for project. In addition to funded projects, additional reports are published on
applicants that were approved without funding due to budget shortfalls, as well as
applicants who were rejected for various reasons. These reports include the same
information as described above (without approved funding); however, for 2009 no data
was given for area in reports on applicants approved without funding or rejected.
In addition to reforestation data from CONAFOR, the municipal-level index of
marginalization was downloaded in an Excel file from the Comisión Nacional de
Población (CONAPO), which calculated the index using the Conteo de Población y
Vivienda 2005 by the Instituto de Información Geográfica e Informatica (INEGI), as well
as the Encuesta Nacional de Ocupación y Empleo del IV trimestre de 2005 and the
Conciliación Demográfica 2000-2005. Additional municipal-level census data on
population speaking an indigenous language was acquired from the Censo General de
Población y Vivienda 2000 from the INEGI website. I used this data as a proxy for
indigenous population.
Spatial data were obtained from several Mexican government websites. Nearly all
spatial data for Mexico are produced by INEGI, a selection of which is available for free
download online. However, INEGI’s shapefiles are projected using the ITRF 1992
geographic coordinate system, which is poorly supported by ArcGIS 9.3. As a result, I
only downloaded shapefiles from INEGI that were not available elsewhere. Instead, the
majority of the shapefiles utilized were downloaded from The Comisión Nacional para el
Conocimiento y Uso de la Biodiversidad (CONABIO) website. Finally, some shapefiles
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were downloaded from CONAFOR’s E-Bosque website by request from the site
administrator.
The following data were utilized in analyses:
Pro-Árbol C1.1 Reforestation results for 2007, 2008, and 2009
CONAPO Index of Marginalization (2005)
INEGI Population Speaking Indigenous Languages (2000)
INEGI municipality shapefile
CONABIO state, localities, topography and 1993 land use and vegetation
shapefiles
CONAFOR hydrological and biodiversity eligible areas, 1993-2002 land use
change, 2002 Soil Degradation, and Veracruz UMAFORs
2. Data Organization
Reforestation data was copied into Excel into separate spreadsheets by year. The
gender of applicants was coded into male, female, or other, and uncertainties of gender
were clarified by a Mexican citizen. Other was used to represent ejidos, associations, and
governmental bodies that received funding from the program. Next, annual data on total
applicants, proportion by gender, and total area to be reforested was summarized by
municipality using the pivot table function in Excel. Finally, a new spreadsheet was
created to combine totals from the three years of data. The totals spreadsheet was copied
into a new Excel book to create a master spreadsheet for statistical and spatial analyses
organized with municipalities as rows.
The raw index of marginalization and the classification column (from very low to
very high) for Veracruz municipalities were copied from the CONAPO file into a new
Excel table with rows labeled by municipality. The marginalization index produced by
CONAPO weights the following variables:
Percent population over age 15 that is illiterate
Percent population over age 15 that did not complete primary school
Percent inhabitants in homes without plumbing or sewer
Percent inhabitants in homes without electricity
Percent inhabitants in homes without running water
Percent homes with dirt floor
Percent population in localities with less than 5000 inhabitants
Percent population earning less than two minimum wages
I opted not to use the index of human development from CONAPO in the study, which is
calculated using some of the variables above as well as GDP, because it is not used by
CONAFOR and because GDP is an inadequate measure of development in rural Mexico.
Following the same method, data on indigenous language for Veracruz municipalities
was copied from the census file into a new Excel table. The percent of inhabitants
speaking an indigenous language was calculated in a new column by dividing the number
of indigenous language speakers by total population for each municipality. The two
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marginalization columns and percent indigenous language column were copied into the
master spreadsheet.
Spatial analysis was conducted in ArcMap 9.3 (ESRI). In ArcCatalog, all shapefiles
were defined and projected into the custom WGS84 Lambert Conformal Conic projection
commonly used in Mexico. Except for Mexican states, all shapefiles were clipped to the
shape of Veracruz and renamed with the prefix Ver- or Veracruz. In the attribute table for
the municipality shapfile (“Veracruz_municipios”) I created a new column (“Aream2”)
and used the Calculate Geometry function to measure the area of each municipal polygon
in square meters. A second new column was created (“Areaha”) and the Field Calculator
was used to divide Aream2 by 10,000 to calculate area in hectares for each municipality.
The edited table was downloaded as a .dbf file and opened in Excel to copy the Areaha
column into the master spreadsheet.
In ArcGIS, I selected by attribute in the Soil Degradation shapefile
(“Ver_Soildegradation2001_02”) attribute table for strong or extreme degradation
(degree 3 or 4) among the five potential types of soil degradation per polygon. In other
words, any polygon with the presence of one or more types of strong or extreme
degradation was selected. A layer was created from the selection and exported as a new
file (“Degradedsoils”) and the file was clipped to the municipality shapefile to create
“Degradedsoils_Clip.” I calculated the geometry of new shapes in a new column and
exported the file as a .dbf. In Excel, I used the pivot table function to sum the area of
degraded land per municipality and calculated this area as a percent of municipal land.
The column of percent degraded land was added to the master spreadsheet. This method
was repeated with the 1993 land use map to select areas classified as forest or jungle
(bosque or selva) and calculate a column for percent forested area per municipality.
The hydrological and biodiversity eligible area shapefiles were already clipped to
municipalities and included columns for the percent of municipal area in the respective
eligible areas. Therefore, the attribute tables for both files were simply exported as .dbf
files and the percent area column for each was copied into the master spreadsheet.
The completed master Excel spreadsheet included all columns mentioned above and
was added to a new map with the Veracruz_municipios shapefile. The spreadsheet was
joined to the shapefile using the municipality field and exported as a new shapefile called
“ProArbolSuitabilityRanking.”
3. Suitability Analysis to rank municipalities for future Pro-Árbol funding
With the exception of certain coastal and wetland ecosystems and a small region of
matorral (shrubland), most of the state of Veracruz was historically forested and is
suitable for reforestation. No municipality is entirely unsuitable for reforestation; thus, all
were included in the suitability analysis. The five variables I included in the ranked
suitability analysis for future Pro-Árbol reforestation funding were: Marginalization
Index, Percent Indigenous Population, Percent Area with Soil Degradation, and Percent
Area in Hydrological or Biodiversity Eligible Areas, respectively.
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For all variables except marginalization, a higher numeric value corresponded to
higher suitability for reforestation according to Pro-Arból guidelines. Marginalization
was the opposite, with low (negative) index values corresponding to high
marginalization. In ArcMap, I created five data frames and added
ProArbolSuitabilityRanking to each. I displayed each variable using natural breaks with
five classes. I noted the value range for the natural break classes in each of my five maps
and then labeled the classes from 1 to 5, with 5 being most suitable for reforestation.
Next, I added six new columns to the attribute table of ProArbolSuitabilityRanking to
code the suitability class for each variable and sum the total. I then coded the class values
variable by variable into the new columns and used the Field Calculator to add the five
values in the sixth column, the total suitability ranking. Finally, I classified the suitability
ranking into three quantiles representing low, medium, and high priority for future
reforestation funding.
4. Linear Regressions to test the realization of funding objectives by allocation to
projects during 2007-2009
Linear regressions with single and multiple independent variables were utilized for
annual reforestation data to test for statistical relationships between the area reforested
per municipality in Veracruz and the five variables chosen for the suitability analysis. All
analyses were conducted in SPSS 16.0. Respective columns were copied from the master
spreadsheet into SPSS and formatted. Linear regressions with multiple independent
variables were run using all five variables for 2007, 2008, and 2009 reforested area data
and VIF measured to detect any effects of multicollinearity among variables, of which
there were none. In addition, linear regressions were run for single independent variables
for each of the three years. Beta values for variables were compared among years to
qualitatively evaluate the presence of shifts in funding allocation over time.
5. Create Maps, Charts, and Tables
In addition to the Series I reference and contextual maps for Veracruz presented in the
introduction, Series II includes maps presenting the results of Pro-Árbol C1.1
Reforestation during 2007-2009 in Veracruz according to total hectares reforested,
percent area reforested, total accepted applicants, percent female accepted applicants, and
rejected applicants. Data for Series II maps were classified manually; however, were
based on natural breaks. Series III includes five maps for the suitability analysis variables
with two frames each: one displaying original data or customary classification, and one
displaying the suitability ranking. A sixth map presents the final suitability ranking
classified into low, medium, and high priority for future reforestation funding.
Limitations
There are a number of limitations to my analysis, most importantly being the coarse scale
of publically available data on reforestation activities. There is a lack of detail on
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individual participants, as well as a lack of spatial data for actual sites reforested in the
published reports. This precludes a more meaningful environmental analysis of the
suitability of reforested sites, as well as a more informational demographic analysis of
project participants. This analysis does not attempt to answer whether reforestation is a
viable approach to economic development or poverty alleviation in Veracruz, nor does it
present any preliminary estimates of impact in this area. It’s still too early to tell how
reforestation projects will impact individuals and communities and whether there will in
fact be synergies between reforestation and development. However, this is an important
area for future qualitative research.
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RESULTS
List of Tables
Series II Pro-Árbol C1.1 Reforestation Results, 2007-2009
Table 2.1: Summary of Pro-Árbol C1.1 Reforestation Applicants and Funded
Projects 2007-2009
Table 2.2: Linear regression results for models with a single independent variable
Table 2.3: Linear regression results for models with all five independent variables
List of Figures
Series I Context Maps – Included in Introduction
Series II Pro-Árbol C1.1 Reforestation Results, 2007-2009
Figure 2.1: National Forestry Commission Forestry Management Units (UMAFORs) in
Veracruz
Figure 2.2: Total Hectares Reforested, Veracruz Municipalities 2007-2009
Figure 2.3: Percent Area Reforested, Veracruz Municipalities 2007-2009
Figure 2.4: Funded Pro-Árbol Applicants, Veracruz Municipalities 2007-2009
Figure 2.5: Rejected Pro-Árbol Applicants, Veracruz Municipalities 2007-2009
Figure 2.6: Percent Female Participation, Pro-Árbol Reforestation, Veracruz 2007-2009
Series III Suitability Ranking of Municipalities for Future Reforestation Funding
Figure 3.1: Marginalization in Veracruz
Figure 3.2: Indigenous Language in Veracruz
Figure 3.3: Hydrologic Service Prioritization in Veracruz
Figure 3.4: Biodiversity Service Prioritization in Veracruz
Figure 3.5: Soil Degradation in Veracruz
Figure 3.6: Suitability Ranking of Veracruz Municipalities for Pro-Árbol Funding
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Table 2.1: Summary of Pro-Árbol C1.1 Reforestation Applicants and Funded Projects
2007-2009
Result 2007 2008 2009 Total
Hectares reforested 33,043 24,978 15,614 73,635
Total accepted applicants 1944 2514 1343 5,801
Total accepted applicants
without funding 175 732 457 1364
Total rejected applicants 8 0 33 41
Percent individual female
accepted applicants* 16.3 17.5 14.9
Mean property size of
individual applicants*(ha) 15.4 9.6 11.4
Total subsidy (pesos) 31,707,239 27,611,221 18,060,491 77,357,711
*Excluding applications representing ejidos, associations, or government bodies
Table 2.2: Linear regression results for models with a single independent variable
Area Reforested 2007-2009
2007 2008 2009
Variable beta p-value beta p-value beta p-value
Marginalization 0.121 ns 0.144 ns 0.184 0.019
Percent Indigenous Pop -0.038 ns -0.082 ns -0.012 ns
Hydrological Priority 0.119 ns -0.006 ns -0.005 ns
Biodiversity Priority 0.113 ns 0.127 ns 0.154 0.033
Soil Degradation Priority -0.008 ns 0.057 ns 0.071 ns
R square 0.044
0.036
0.046
F 1.9
1.525
1.969
Model p-value 0.096
0.183
0.085
Sample size 212 212 212
ns = not significant.
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Table 2.3: Linear regression results for models with all five independent variables
Area Reforested 2007-2009
Marginalization 2007 2008 2009
beta value 0.153 0.102 0.136
R square 0.023 0.010 0.018
F 5.041 2.194 3.966
Model p-value 0.026 0.140 0.048
Percent Indigenous Pop 2007 2008 2009
beta value -0.044 -0.079 -0.008
R square 0.002 0.006 0
F 0.415 1.327 0.014
Model p-value 0.52 0.251 0.906
Hydrological Priority 2007 2008 2009
beta value 0.135 0.003 0.004
R square 0.018 0 0
F 3.879 0.002 0.003
Model p-value 0.05 0.963 0.956
Biodiversity Priority 2007 2008 2009
beta value 0.064 0.113 0.132
R square 0.004 0.013 0.018
F 0.864 2.729 3.752
Model p-value 0.354 0.1 0.054
Soil Degradation Priority 2007 2008 2009
beta value -0.081 0.002 0.001
R square 0.007 0 0
F 1.378 0.001 0
Model p-value 0.242 0.976 0.985
ns = not significant.
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Figure 2.1
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Figure 2.2
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Figure 2.3
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Figure 2.4
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Figure 2.5
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Figure 2.6
Figure 3.1
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Figure 3.2
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Figure 3.3
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Figure 3.4
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Figure 3.5
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Figure 3.6
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ANALYSIS OF FINDINGS
Analysis is divided according to the two series of maps corresponding to respective
research questions.
Series II Pro-Árbol C1.1 Reforestation Results, 2007-2009
Question: What if any relationship is there at the municipal level between the distribution
and density of reforestation projects and socioeconomic marginalization, indigenous
population, soil degradation, and hydrological and biodiversity priority areas in
Veracruz?
CONAFOR organizes forestry activities under forestry management units, or
Unidades de Manejo Forestal (UMAFORs), which are administrative regions sharing
similar environmental or cultural characteristics. Figure 2.1 displays the UMAFOR
regions for Veracruz and is useful for referring to the geographic distribution results. Table 1.1 summarizes descriptive results for C1.1 reforestation subsidized by Pro-
Árbol during 2007-2009. A total of 73,635 hectares were reforested during this period,
presented in Figure 2.2. Reforestation efforts were distributed throughout the state, with
only fourteen of the 212 municipalities lacking participants during the 2007-2009 period.
Figure 2.3 displays the reforestation in terms of percent area reforested by municipality.
This map normalizes the results and indicates a concentration of reforestation in the
central regions of Misantla, Perote, and Orizaba, as well as in Huayacocotla in the north.
A total of 5,801 applicants were approved for Pro-Árbol reforestation subsidies
(Table 1.1, Figure 2.4). The number of individuals that received support was actually
higher, since a portion of the applicants represented ejidos, or communal landholding
groups, as well as silvicultural associations and government bodies (i.e., municipal
governments, state parks, public universities). Applications on behalf of such
organizations were excluded from descriptive statistics on female participation and
property size to minimize biased results.
During the period reviewed, 1,364 applicants were accepted without funding for C1.1
reforestation projects because of budgetary limitations. Many applicants were or will be
granted priority for funding in subsequent years. Even if funding was not available,
applicants were still eligible for free saplings to plant.
Only 41 applicants were rejected for funding based on errors related to application
rules and program regulations. Of these, 10 were women. The distribution of rejected
applicants is presented in Figure 2.5. The low number of rejected applicants calls into
question the process of prioritization or selection of applicants based on program
objectives. If nearly all applicants are accepted, can subsidies be said to be targeted?
Greater clarity is needed in CONAFOR’s publicity materials regarding the prioritization
of applicants for reforestation subsidies. On the other hand, it may simply signal that
individuals who reach the final stage of application submission have already been
selected out from a larger initial pool of interested but less qualified citizens.
Ingrid Haeckel - Trees for Development: Reforestation in Veracruz - CRP 386 Fall 2009
31
The average percent of female applicants by program year was between 14.9 and 16.3
percent (Table 1.1). Actual female participation may have been higher because they may
have participated in the organization applications mentioned above. Figure 2.6 displays
the distribution of female applicants granted funding. Although female participation was
high in some municipalities, 65 municipalities with participation had no accepted female
applicants Female participation appears to have been particularly lower in the
mountainous zones of the state. Female participation is limited by gendered divisions in
property rights, since the applicant to Pro-Árbol must demonstrate legal ownership in his
or her name.
Mean property size for individual applicants ranged between 9.6 to 15.4 hectares,
which corresponds to the size of many small to medium-scale landholders in Veracruz.
Typical property size varies from region to region in Veracruz, however, complicating
the analysis of property size n relation to marginalization. The smallest properties granted
subsidies were 3 ha.
A total of $77,357,711 pesos were awarded in subsidies to reforestation participants
in Veracruz during 2007-2009. Subsidies were equivalent to approximately US$850 per
hectare reforested. This is a large investment and reinforces the need for monitoring of
reforestation projects to assess the efficiency of the investment.
No significant relationships were found in the linear regressions testing independent
funding objective variables and area reforested (Table 1.3). However, for regressions
testing single independent variables there was a significant relationship between the
marginalization index and reforestation in 2007 and 2009 (Table 1.2). There was also a
significant relationship between hydrological priority areas and reforestation in 2007. For
all other years of data and variables relationships were not significant. There was no
multicollinearity among the variables tested and for the few variables that did have
significant results, R2
values were very low, indicating low explanation of the variance in
area reforested. There were no distinguishable trends over time in the beta values for
individual variables that would indicate conscious shifts in funding targets to meet
objectives over the years of the study.
The descriptive results and linear regression results cast some doubt on whether Pro-
Árbol program objectives are consciously being addressed through selective awarding of
reforestation subsidies. However, there are some indications that funding is reaching
marginalized municipalities regardless of a specific prioritization process, fulfilling at
least one of Pro-Árbol’s major goals. Nevertheless, the lack of significant relationship
between reforestation and environmental variables of concern to CONAFOR indicates
that the environmental objectives of Pro-Árbol should be more explicitly targeted in the
future.
Ingrid Haeckel - Trees for Development: Reforestation in Veracruz - CRP 386 Fall 2009
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Series III Suitability Ranking of Municipalities for Future Reforestation Funding
Question: What areas are most suitable for future reforestation funding to further the goal
of environmental restoration and development?
Figure 3.1 shows that with the exception of urban areas such as Coatzacoalcos,
Veracruz, Orizaba, Xalapa, and Poza Rica, much of the state of Veracruz is categorized
by indices of marginalization considered medium to high for Mexico by CONAPO. The
highest concentrations of marginalization are found in the montane regions of
Huayacocotla, Totonacapan, Orizaba, and Los Tuxtlas. The distribution pattern of
populations retaining indigenous languages is more evenly distributed throughout the
state, as seen in Figure 3.2. Identifiable concentrations of indigenous language are found
in the Otontepec and Totonacapan regions.
Figures 3.3 and 3.4 depict hydrological service and biodiversity conservation eligible
areas for payment for ecosystem services. Hydrological services are not surprisingly
concentrated in montane zones, as well as coastal zones prone to flood damage from
hurricanes and other extreme weather. Additionally, the Uxpanapa region, including the
Coatzacoalcos River watershed is highlighted as important areas to protect. In contrast to
the hydrologic eligible areas, biodiversity eligible areas are concentrated in the lower
elevations of the central montane zone and near large coastal wetland and inland marsh
ecosystems, such as the Laguna de Alvarado and lakes of Los Tuxtlas. These areas are
important for migratory bird species. Finally, soil degradation, presented in Figure 3.5, is
more sparsely and evenly distributed across ecoregions and elevation zones in Veracruz.
A slightly higher trend of degraded areas is noticeable along the coast.
The final ranked suitability map combining individual rankings for the five social and
environmental variables is presented in Figure 3.6. When compared with Figure 2.2, it
appears that the high priority areas of Perote, Misantla, Orizaba, and Huayacocotla have
been well served by Pro-Arbol, but that other priority areas in the northern and southern
areas of the state have not. In particular, Totonacapan, Veracruz, Los Tuxtlas, and
Uxpanapa UMAFOR regions should increase outreach to potential participants and
perhaps identify potential barriers to participation among residents in these areas.
Ingrid Haeckel - Trees for Development: Reforestation in Veracruz - CRP 386 Fall 2009
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CONCLUSIONS
To conclude, the 2007-2009 Pro-Árbol reforestation results indicate subsidies are
being applied in marginalized areas; however, environmental objectives need more
attention. It is additionally unclear to what extent indigenous communities have
participated. Women’s participation should be further encouraged and explored in greater
depth – are women involved in planting and maintaining trees, even if not named in Pro-
Árbol applications? Understanding how women participate or are affected by
reforestation activities is critical to the overall objectives of equitable development.
Based on this analysis, future outreach and funding for reforestation should target the
Totonacapan, Veracruz, Los Tuxtlas, and Uxpanapa UMAFOR regions. An analysis
conducted at the locality or property-level would provide greater detail regarding the
success of Pro-Árbol funding thus far, as well as help to orient future funding to those in
most need and in locations of greatest ecological restoration importance. This could
certainly be done within CONAFOR.
More importantly, CONAFOR should publish the results of monitoring for areas
already reforested over the long term to evaluate the success rate of projects and the long-
term benefits to participants. This data is of utmost importance to assessing the real value
of reforestation to both environmental restoration and economic development. More
information is needed to understand what land uses are being abandoned to reforestation,
why, and with what perceived benefits among property owners. Finally, physical
monitoring of the impacts of reforestation on the production and flow of ecosystem
services will provide empirical evidence for the environmental benefit of reforestation
with native species, of which little research exists.
Ingrid Haeckel - Trees for Development: Reforestation in Veracruz - CRP 386 Fall 2009
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DATA SOURCES
Censo General de Población y Vivienda. (2000). D.F., México: Instituto Nacional de
Estadística e Geografía (INEGI).
Degredación de Suelos COLPOS [computer files]. 2002. D.F., México: Comisión
Nacional Forestal (CONAFOR). Available by request:
http://www.cnf.gob.mx:81/emapas/Admin/Maps.aspx
Índices de Marginación 2005 [Excel file]. (2005). D.F., México: Consejo Nacional de
Población (CONAPO). Available: http://www.conapo.gob.mx/index.php?option=com_content&;view=article&id=78&Item
id=194
Marco Geoestadístico Nacional: Áreas Geoestadísticas Municipales [computer file].
(2005). D.F., México: Instituto Nacional de Estadística e Geografía (INEGI). Available:
http://mapserver.inegi.org.mx/data/mgm/?s=geo&;c=1298
Mapoteca digital: Entidades federativas, Curvas nivel, Uso de Suelo y Vegetación,
Localidades, and Carreteras [computer files]. (1996-2005). D.F., México: Comisión
Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO). Available:
www.conabio.gob.mx
Pro-Árbol Resultados [Excel and PDF files]. (2007-2009). D.F., México: Comisión
Nacional Forestal (CONAFOR). Available:
http://www.conafor.gob.mx/index.php?option=com_content&;task=view&id=26&Itemid
=455
Pro-Árbol Áreas Elegibles (Veracruz): Biodiversidad, Hydrológicos [computer files].
2008. D.F., México: Comisión Nacional Forestal (CONAFOR). Available:
http://www.conafor.gob.mx/index.php?option=com_content&;task=view&id=166&Itemi
d=401
Projection
Data were projected to the custom Lambert Conformal Conic (LCC) projection
commonly used in Mexico. Shapefiles originating in ITRF 1992 were discovered to
already be projected in LCC, although this was not found in the Metadata. Problems with
ArcMap’s lack of ITRF 1992 geographic coordinate system transformations were
avoided by projecting these files into WGS84 and then back into LCC.
The custom projection parameters are:
North_America_Lambert_Conformal_Conic
False_Easting: 2500000; False_Northing: 0
Central_Meridian: -102
Standard_Parallel_1: 17.5; Standard_Parallel_2: 29.5
Latitude_Of_Origin: 12.0
Linear unit: meter