Hawks, habitats and humans:

Aspects of land transformation and raptor conservation in

South Africa.

Letitia Maria Greyling

Percy FitzPatrick Institute of African Ornithology

University of Cape Town

Rondebosch, 7701

Cape Town, South Africa.

Supervisors: Dr Andrew Jenkins

Thesis submitted in partial fulfilment of the requirements for the degree of Master of

Science in Conservation Biology, University of Cape Town.

June 2000

The copyright of this thesis rests with the University of Cape Town. No

quotation from it or information derived from it is to be published

without full acknowledgement of the source. The thesis is to be used

for private study or non-commercial research purposes only.

Univers

ity of

Cap

e Tow

n

Hawks, habitats and humans:

Aspects ofland transformation and raptor conservation in South Africa

Letitia Maria Greyling

Percy FitzPatrick Institute of African Omithology, Department of Zoology, University of Cape Town,

Rondebosch, 7701 South Africa

"On a world scale, then, habitat destruction has already accounted for bigger reductions in raptor and

other wildlife populations than any other factor. " Jan Newton (1990)

Abstract

The effects of anthropogenic habitat change on the distributions of 15 selected raptor

species in South Africa were examined using a Geographical Information System, bird

atlas data and various habitat coverages. Affinities with natural and transformed habitat

characteristics were quantified, and predicted or historical distributions, for each species

under pristine conditions were generated using generalised linear modelling. Natural

habitat preferences were generally in accord with accounts given in the South African

Bird Atlas Project. In comparing present with predicted distributions, ranges were

considered to have expanded in five species (Secretarybird Sagittarius serpentarius.

Jackal Buzzard Buteo rufofuscus, Redbreasted Sparrowhawk Accipiter rufiventris, Black

Harrier Circus tnaurus and Lanner Falcon Falco biarmicuss, to have contracted in four

species (Cape Vulture Gyps coprotheres, Tawny Eagle A. rapax, Martial Eagle

Polemaetus bellicosus and Bateleur Terathopius ecaudatus), and to have remained

essentially unchanged in six species Blackshouldered Kite Elanus caeruleus, Black Eagle

Aquila verreauxii, Black Sparrowhawk A. melanoleucus, Pale Chanting Goshawk

Melierax canorus, African Marsh Harrier Circus ranivorus and the Greater Kestrel F.

rupicoloidesy. The overall effect of land transformation practices was considerable for

the majority of species. Grazing pressure, agriculture and afforestation represented key

land-use practices in affecting raptor distributions. Generally, the smaller species in the

studyrsample responded positively to habitat transformation, while large (and

particularly? scavenging) species seemed to be more sensitive to ecosystem integrity and

showed subsequent contractions of ranges. The importance of conservation-orientated

approach to all forms of land management is stressed.

Introduction

Southern Africa supports about 230/0 of the world's diurnal raptor species (Steyn 1982,

Watson 1991). This impressive diversity is largely a function of the remarkable range of

habitats available, which, in turn, is a product of the variety of prevailing climatic and

topographic conditions (Rogerson and McCarthy 1992, Harrison et a1. 1997). Sadly,

many of these habitats and environments are threatened by a burgeoning human

population, the spread of development and indiscriminate land management practices.

Loss of pristine habitat and continuous land transformation are widespread and rapid

(Macdonald 1989). Subjectively, raptors persist in this fast-changing environment with

varying degrees of success. However, we are still unsure about the actual effects of land

transformation and different land-uses on raptor populations. What seems certain is that

many raptors are strongly and negatively affected by anthropogenic changes to the

environment (Dean, 1975; Brandl et a1., 1985), with the result that almost 17% of the

threatened bird species in South Africa are raptors (Barnes 1998), although they comprise

only nine percent of the total avifauna.

Raptors are particularly hard hit by human activity because they are susceptible on a

number of fronts. Direct sources of mortality, including persecution, poisoning, collision

and electrocution have been the main focus of local conservation efforts to date (Jenkins,

1997). Attempts to minimise and control these factors have undoubtedly contributed to

the preservation of sustainable raptor populations in many parts of the region. However,

the influence of human activities on the nature of raptor habitats, and particularly on the

availability of essential resources for these birds, have not been adequately quantified.

These more subtle effects of habitat modification remain little studied and poorly

understood. They are potentially more damaging (Anderson et al., 1990) than inflated

rates of mortality, and could ultimately lead to the loss of indigenous raptor fauna unless

a more conservation-orientated approach is applied to all forms of land management.

2

their changing environment, and to identify crucial parameters that affect their

conservation status.

Methods

Study area

It was decided to confine this study to raptor distributions within the borders of South

Africa, primarily because of a lack of adequate information for other southern African

countries. Environmental data coverages for Namibia, Botswana, Zimbabwe and

Mozambique are either non-existent or of questionable quality, whereas South Africa has

coverages that are relatively available for research, and the fairly well documented

COnCe111S or advantages relating to these databases help to account for accuracy and

related problems (Smith et al., 1989; Harrison et al., 1997; ENPAT, 1996).

South Africa extends from about 34° south to just above the Tropic of Capricorn (22°S)

in the north, with longitude ranging from ca. 17° to '33° east. The country covers about

1.3 million km", including the kingdoms of Lesotho and Swaziland. Although the major

urban centres feature fairly high human population densities, South Africa is generally

sparsely populated. The average population density for the entire region is ca. 433

people per km- (or 4 people per hectare), and low densities occur over vast areas of the

central Karoo (ENPAT, 1996). Prevailing mean maximum and minimum temperatures

range from ca. 6°C to 23°C respectively. South Africa is a semi-arid country and annual

rainfall figures are generally low. Over a third of the country receives an annual average

rainfall of between 250 and 500nlnl, with averages below 250nln1 per annum recorded

over much of the western region, and averages over 750mlll per annum for the southern

and south eastern regions. Altitude ranges from sea-level to just over 3 400 m (USGS,

1996).

Data

Eight spatial data coverages' were used in this study (the source and details of all original

data sets are shown in Appendix 1). All analyses were performed using ..Arcview

4

Version 3.1 (Environmental Systems Research Institute, Redlands, California) and

Arc View Spatial Analyst 1.1 (Environmental Systems Research Institute, Redlands,

California), as well as the X-Too 1.£ extension. The Albe~s Equal Area Projection (based

on Clarke 1880 Spheroid, with 24° east longitude as the central meridian and the Equator

as the latitudinal reference point of the projection's origin) was used, to allow for area

calculations and values that were important for generating appropriate and meaningful

results.

The South African Bird Atlas Project (SABAP) distribution data (in the form of reporting

rates - Harrison et aI., 1997) was the theme used to show the ranges and distributions of

the raptor species included in this study. It was considered impractical to work with the

data for all South African raptor species. Therefore, a sample of 15 species was selected

to represent a cross-section of species perceived to be either negatively, positively or

neutrally influenced by habitat modification. Particularly rare or peripheral species were

not considered suitable because the atlas data available for these birds were generally

insufficient for rigorous analysis. The following 15 raptor species were used in this

study: Secretarybird Sagittarius serpentarius, Cape Vulture Gyps coprotheres,

Blackshouldered Kite Elanus caeruleus, Black Eagle Aquila verreauxii, Tawny Eagle A.

rapax, Martial Eagle Polemaetus bellicosus, Bateleur Terathopius ecaudatus, Jackal

Buzzard Buteo rufofuscus, Redbreasted Sparrowhawk Accipiter rufiventris, Black

Sparrowhawk A. melanoleucus, Pale Chanting Goshawk Melierax canorus, African

Marsh Harrier Circus ranivorus, Black Harrier Circus niaurus, Larmer Falcon Falco

biarmicus and the Greater Kestrel F. rupicoloides.

The environmental variables used in the analyses were selected according to natural

environmental, land managerial and even socio-political parameters considered likely to

impact on raptor distributions. These were limited by the quality of data available. Data

sets used in this study included coverages of biological features of South Africa, and

human-related factors contributing to South Africa's present geographical make-up, The

former comprised vegetation cover for South Africa, according to the broad Acocks

(1988) veld types classification, mean rainfall (mm per annum), and elevation (at l km

5

grid cell resolution, i.e. altitude given in 1 km intervals) Data sets used to describe

anthropogenic changes to the environment were human population density (people per

square kilometre); old «1994, .mcluding the former homeland areas) and present

provincial boundaries; and land-use. Land-use was broken into nine, broad categories,

namely areas designated as conservation and/or protected areas; natural areas; exotic

plantations; extensive cattle and/or game fanning; mixed fanning; sheep fanning;

subsistence farming; agricultural areas for wheat and maize production and urban areas.

The final theme is a combination of human-related and natural features of South Africa,

the National Land Cover (NLC) data set (Thompson, 1997). This coverage is categorised

into 31 classes (Thompson, 1997), but for the purposes of this study, these original

classes (although separately analysed) were grouped together into the following 12

classes: All cultivated lands; Barren rock, mines and quarries, dongas and sheet erosion

scars; Forest, forest and woodlands, forest plantations; Degraded forest and woodlands;

Herbland, shrubland and low fynbos; Degraded herbland, degraded shrubland and low

fynbos; Thicket and bushland (etc); Degraded thicket and bushland (etc);

Unimproved/natural grassland; Degraded unimproved grassland, improved grassland; All

urban and built-up land; Waterbodies and wetlands.

It is important to distinguish between land-use and land-cover. Land-cover refers to all

the natural and man-made features that cover the earth's immediate material surface,

whereas land-use is used to define the human activity associated with a specific land unit,

i.e. the utilisation, impacts or management practices (Thompson, 1996).

Analyses and Modelling

Coverages were used as is, with the appropriate projection as discussed above, except for

the data set showing the former homelands and provinces. This coverage was made from

an existing map showing the boundaries of the old provinces and former homelands as

various polygons (E.NPAT, 1996). By using a paper map (ref?) of the country (prior to

the name changing), area polygons, which fell within a specific region (or homeland),

were identified and named accordingly. These areas were merged based on the similar

6

names and a map for the Fonner Homelands and Provinces (see Figure 6) was produced.

This map was used in order to assess the possible effects of different political,

agricultural, economic and environmental agendas between the former homelands and

old provinces on raptor distributions. One should, however, keep in mind that correlation

between this coverage and bird distributions is mostly a function of biological

distribution.

Each of the environmental coverages was separately overlaid on the SABAP data and the

Identity command (from the X-Tools Extension) was used to produce a new theme that

showed the combined features in one theme. This enabled us to analyse the distribution

of each raptor species according to each type of variable, using reporting rate as an

indicator of abundance. Separate overlay-analyses were also done using a coverage of

the quarter degree squares (QDS) in combination with the variables, to give an idea of

type of coverage in each QDS (Harrison et al., 1997).

The analyses for the land cover data were performed using Arc/INFO Version 7.2.1

(Environmental Systems Research Institute, Redlands, California), as the data set was

considered too big to be properly analysed by ArcView. The Identity function was used,

which is similar to the Identity command in Arc View, to intersect the data and the

subsequent results were used in Arc View to create a frequency Table, exactly the same as

all the other coverages, using the Table Frequency command,

A frequency analysis was performed on all the attribute tables of the new Identity­

produced themes to calculate a proportional profile of the areas that a specific raptor

species (and each QDS) was found in. This allowed for a quantitative summary of the

number of times that an attribute occurs. The area field was used to reference each

particular attribute, i.e. the occurrence of each attribute was expressed as a value of

summarised area.

All the frequency analyses results are given in Tables 1 to 7. These tables are a summary

for each species in a particular type of coverage. These tables can be considered as

7

abundance tables, with each species' particular abundance grouped into four classes:

absent/rare; uncommon; common; or abundant. These groups are specific for each

species and the ranges for these classes were chosen according to the reporting rate

grouping given in the Bird Atlas of Southern Africa (Harrison et aI., 1997). The values

are expressed as percentages across each row, thereby showing high or low percentages

(which will be referred to as abundance value from now on) in a specific reporting rate

group. For instance, a percentage or abundance value in the abundance group will

indicate the percentage area that a bird occupied in that particular type of coverage. For

the purposes of this study, only the last three categories (uncommon; common; and

abundant) are of significant importance, as the first absent/rare-category included not

only the absent and/or rare QDSs, but also QDSs for which information was not available

(i.e. Lesotho and Swaziland). These additional zero values made the absent/rare category

seem disproportionately high.

Note that information on rainfall, human population density and land-use practices for

Swaziland was not available and could therefore not be incorporated into the analyses.

Swaziland is also 110t represented in the map of the former provinces and homelands.

Lesotho can also be regarded as an unanalysed area, due to missing data for rainfall and

land-use in this region. Any information obtained from the analyses for these two

kingdoms should be treated with caution and modelled distributions in these areas are

purely a by-product of the model and not biologically meaningful.

The Genstat statistical package was used to carry out the logistic regression analysis

(Payne et al., 1987). A set of environmental variables (see previous section Data) were

used as explanatory variables in the logistic model, with reporting rates of the bird

species, expressed as a binomial random variable, as the response variable. This use of

fully binomial logistic regression was used by Underhill et al. (1992) to describe

seasonality, but is applied here to model bird distribution. The same caveats as described

by Underhill et al. (1992) are relevant to this application. Only grid cells with complete

data for the existing explanatory variables were used in the regression analysis, thereby

8

excluding most of the cells lying on the South African political border (including coast

line ).

All variables (excluding land cover) were used to fit the model and the environmental

variables (vegetation, rainfall and elevation) were then used to model pristine or

historical distributions. The total deviance of the residual for each species was

calculated, as well as deviance values using only the three environmental variables

(elevation, rainfall, vegetation) and using all six variables (elevation, rainfall, vegetation,

former provinces, land-use, human population density). These values give an indication

of how much each raptor's distribution is explained by natural and by anthropogenically

related variables. This is very apparent when the percentages are compared and although

this is by no means a conclusive value, it does help to give an idea of the degree to which

certain species are influenced by anthropogenic change with reference to their

distributions.

Results

The results from the frequency analyses are given in Tables 1 to 7. The modelled maps

for the predicted, pristine distributions for each species are shown in figures 7 to 21, with

the contemporary Bird Atlas Data distributions as comparisons. Note that the modelled

distributions are presented in a smooth resolution, whereas the Bird Atlas Data's f01111at

is particular for each QDS. It is also important to realise that the reporting rate categories

of the modelled distributions differ from those of the Bird Atlas because of the way that

the modelling of the land-use variables was done. The first category was used by Genstat

as the baseline setting, and everything was scaled relative to this. This will produce

modelled reporting rates, which ought to have the right ordering, from smallest to largest.

Abundance values, quantitative deviance values (Table 8) and predicted pristine

distributions (Figures 7 to 21) for each raptor species are provided below. Results are

presentedasa brief summary for each bird, giving a profile of the bird's obvious natural

habitat affinities and the species' subsequent response to anthropogenic chariges.

9

Secretarybird

Natural affinities: The Secretarybird is most abundant in temperate and transition forests,

with similar high abundance values for tropical bush and savanna, and grassland

vegetation types (Table 1). No clear patterns could be detected for affinities for rainfall

averages (Table 3) or altitudes (Table 2).

Anthropogenic effects: Highest abundance values for this species were reported in areas

of moderate human population densities (Table 4) and unimproved grasslands (Table 5),

with conservation or protected areas showing highest abundance as a land-use type

(Table 6)

Modelled distributions: There seems to be some range expansion towards the coastal

areas of the country, especially along the south coast, with relatively little loss in range

size in the Namaqualand and Bushmanland areas (Northern Cape) when modelled

predicted and contemporary Bird Atlas Data distributions are compared (Figure 7).

Goodness of fit statistics strongly suggests that anthropogenic changes to habitats have

had a great influence on the distribution of this bird if one compares deviance percentages

for the combined model with that of the environmental model (Table 8).

Cape Vulture

Natural affinities: The Cape Vulture shows a definite preference for temperate and

transition forests (Table 1), very high rainfall (Table 3) and high altitude areas (Table 2).

Anthropogenic effects: Analyses from the land cover data suggested that it is associated

with improved and degraded, unimproved grasslands (Table 5) and was clearly most

abundant in subsistence farming areas (Table 6). It seems to avoid. areas with higher

human population densities (Table 4). It is found in highest abundance in Transkei and

Lesotho (Table 7).

10

Modelled distributions: The predicted, modelled distribution shows definite range

contraction for the Cape Vulture when compared to current Bird Atlas Data (Figure 8).

For example, this raptor is absent from Cape Peninsula, and southern Westem Cape

Province, as well as regions in the North West Province and Gauteng where they are

predicted to occur according to our analyses. The great difference between deviance

values (Table 8) for the combined and environmental model strongly suggests a serious

impact caused by anthropogenic changes on this vulture's distributional pattern.

Blackshouldered Kite

Natural affinities: Areas with grasslands (Table 1), high rainfall (Table 3) and medium

altitude (Table 2) showed the highest abundance values.

Anthropogenic effects: This bird's presumed association with certain agricultural areas

was confirmed: the highest abundance values were for wheat and maize fanning areas

(Table 6) and land cover denoting all cultivated areas (Table 5). Areas where forests and

woodlands is the main land cover scored equally high, with the second highest abundance

value in urban areas. High human population densities does not seem to affect this

species negatively, as higher hU111an density figures (Table 4) showed equally high

abundance values.

Modelled distributions: Apart from S0111e range contraction In the lower pari of the

Western Cape, the modelled and Bird Atlas Data distributions were fairly similar (Figure

9). According to the difference in deviance percentage for combined and environmental

models (Table 8), a moderate amount of this species' distribution could be explained by

anthropogenic environmental changes.

Black Eagle

Natural affinities: The Black Eagle showed clear preference for areas with high elevation

values (Table 2). Sclerophyllous bush was the type of vegetation with the highest

abundance percentage (Table 1).

11

Anthropogenic effects: Variables associated with human induced features, showed no

outstanding results, although Black Eagles were found to be absent from very densely

human populated areas (Table 4)~ Conservation or protected and natural areas had the

highest abundance values for types of land-use (Table 6).

Modelled distributions: A comparison between the modelled and current distributions for

Black Eagles (Figure 10) suggests a decrease in range size, with these birds being more

absent from the drier, western and north-western part of the country than predicted.

Goodness of fit statistics (Table 8) suggested that anthropogenic changes to habitats have

resulted in a biologically significant modification of Black Eagles' distribution, when

deviance percentages are compared for the combined and environmental model,

Tawny Eagle

Natural affinities: The Tawny Eagle showed highest abundance in low to medium rainfall

ranges (Table 3), lowest altitudes (Table 2) and in tropical bush and savanna (Table 1).

Anthropogenic effects: This species exhibited very strong associations with conserved

and protected areas (Table 6) and had highest abundance values in thicket and bushland

land covers (Table 5). The Tawny completely absent from populated areas (Table 4).

The former Transvaal and Venda made up most of the abundance percentages for this

species' distribution (Table 7).

Modelled distributions: A substantial reduction in distribution is evident when the

pristine, predicted model and the Bird Atlas Data distributions are compared (Figure 11).

The Tawny is totally absent from most parts of the Northern Cape, Western Cape and

Eastern Cape, with similar range contractions in the Northern Transvaal. A slight range

expansion seelns to occur in the KwaZulu-Natal region. This eagle showed the greatest

difference in deviance values between the combined model and the environmental model

(Table 8). This gives a very strong indication that anthropogenic influences are

responsible for the distribution pattern of the Tawny Eagle.

12

Martial Eagle

Natural affinities: The Martial Eagle is IUOSt abundant in tropical bush and savanna

(Table 1). It clearly favours areas with low altitudes (Table 2) and lower ranges of

rainfall averages (Table 3).

Anthropogenic effects: The Martial showed by far the highest abundance in conservation

and protected areas as a land-use type (Table 6) and areas where human population

densities are fairly low. Highest abundance values for the land cover data (Table 5) were

reported in thicket and bushlands (pristine and degraded), and herb lands, shrublands and

low fynbos (both pristine and degraded).

Modelled distributions: Modelled distribution for this species shows an overall range

contraction, especially along the northern borders of the country (Figure 12). The

predicted, pristine distribution also suggests the occurrence of Martial Eagles in the

western part of the Volestern Cape. The substantially higher deviance percentage for the

combined model, compared to the environmental model's deviance percentage (Table 8)

seems to indicate a very strong influence in the distribution of this raptor due to human

related changes in habitats.

Bateleur

Natural affinities: The Bateleur showed very clear affinities for specific types of the three

environmental variables. Areas with very low altitudes (Table 2) and medium rainfall

averages (Table 3) scored by far the highest values, with tropical bush and savanna

clearly being the most predominant vegetation type in this bird' s distribution (Table 1).

Anthropogenic effects: Forests and woodlands (Table 5), and conserved or protected

areas (Table 6) were the respective land cover and land-use types which predominated

most of this species' distribution. Higher human populated areas very negatively

influenced the Bateleur's abundance (Table 4).

13

Modelled distributions: The modelled distribution map (Figure 13) for this raptor

suggested that it's natural range has contracted, when compared to the contemporary

distribution data and this raptor- is absent in areas of the Western Cape where it's

predicted to be found. No deviance values for this bird could be calculated, as it was

modelled slightly differently. Range contraction for his species posed various problems

for the model and adjustments had to be made in order to produce a predicted distribution

map (i.e. some types of variables where the Bateleur does not occur in were left out of the

model). For this reason, one must interpret results for this species with caution.

Jackal Buzzard

Natural affinities: The Jackal Blizzard had the highest abundance values in areas with the

highest altitudes (Table 2), rainfall averages (Table 3) and was by far the most abundant

in temperate and transition forests (Table 1).

Anthropogenic effects: Analyses suggested a definite association with improved and

degraded, unimproved grasslands (Table 5). Areas with subsistence fanning as the

predominant land-use type had the highest abundance values, with exotic plantations also

showing high values and an overall association with fanned areas seems to exist (Table

6). The regions Ciskei, Lesotho and Transkei contributed most to this species

distribution in area (Table 7).

Modelled distributions: Comparisons between the modelled distribution and Bird Atlas

maps show various areas where range expansion has occurred (Figure 14). This shows a

huge range expansion into Northern Cape, and also the drier, north-eastern part of the

country (Northern Transvaal), although less so than the prior expansion. Deviance

percentages (Table 8) also strongly suggest a major role played by man in the

distributional pattern of this raptor.

Redbreasted Sparrowluiwk

Natural affinities: The Redbreasted Sparrowhawk showed an affinity for temperate and

transition forests, as well as sclerophyllous bush vegetation (Table 1). This Sparrowhawk

14

clearly prefers areas of very high altitude (Table 2) and annual rainfall averages (Table

3).

Anthropogenic effects: It was found to be 1110st abundant in exotic plantations, although

similar high abundance values for subsistence farming and conservation or protected

areas were also calculated (Table 6). A high percentage abundance in improved and

degraded, unimproved grasslands was shown (Table 5), with no varying abundance in

different human population densities, although total absence in heavily populated areas is

clear (Table 4).

Modelled distributions: Comparisons between modelled distributions and Bird Atlas Data

indicated a range expansion into the central Karoo and along the South Coast (Figure 15).

The Redbreasted Sparrowhawk is also currently found in the Soutpansberg region

(western Northern Transvaal), where predicted distributions show it to be absent. There

is a great discrepancy between the deviance value for the combined 1110del and that of the

environmental model (Table 8), which would suggest a strong hU111an related influence in

the distribution pattern of this raptor.

Black Sparrowh.awk

Natural affinities: The Black Sparrowhawk shows highest abundance values in areas of

high rainfall averages (Table 3) and it's affinity for forests and trees can clearly be seen

when looking at the obvious high abundance values for coastal tropical forests, as well as

temperate and transition forest vegetation types (Table 1).

Anthropogenic effects: This raptor is more prominent in the formerprovince of Natal and

Transkei homeland (Table 7) and heavily hU111an populated areas (Table 4). This species

was most abundant in areas where degraded forests and woodlands, and plantations are

found (Table 5). Although exotic plantations were shown to be the land-use type where

these Sparrowhawks are lTIOSt abundant, subsistence and mixed farming and urban areas

also had high values (Table 6).

15

Modelled distributions: The differences in modelled and contemporary Black

Sparrowhawk distribution (Figure 16) suggest an overall range contraction. Predicted

pristine or historical distribution 'shows the range of this bird extending into the North

West Province and upper Northern Cape regions. Differences in deviance percentages

(Table 8), however, indicate little contribution by man to this species' distributional

patterns.

Pale Chanting Goshawk

Natural affinities: The Pale Chanting Goshawk prefers the lower range of altitudes (Table

2), lowest rainfall averages (Table 3) and karoo type vegetation (Table 1) according to

the frequency analyses.

Anthropogenic effects: High human populated areas (Table 4) very negatively affect this

raptor's abundance and it is found to be most abundant in areas where degraded

herblands, shrublands and low fynbos constitute the land cover (Table 5). The PCG is

closely associated with sheep farming as a land-use practise (Table 6).

Modelled distributions: Virtually no change in distribution is apparent when the modelled

and contemporary distributions are compared (Figure 17). Some loss of range size in the

lower part of the Northern Transvaal and upper North West Province is detected,

although this could be due to the differences in showing distributions as "smooth" maps

(modelled distributions) or specific QDS abundance (Bird Atlas Data). Differences in

deviance values for the combined and environmental models suggest no major change in

distributions due to anthropogenic changes (Table 8).

African Marsh Harrier

Natural affinities: The African Marsh Harrier was found to be clearly associated with

high rainfall areas (Table 3). High abundance percentages were also calculated for

temperate, transition and coastal tropical forests (Table 1), although it must be noted that

these vegetation types are very broadly classified. When one compares the results to the

vegetation map (Figure 18) it becomes clear that these areas are where most of the

16

wetlands, swamps and marshes are found in South Africa, even though they fall into the

categories for forested areas in the vegetation classification.

Anthropogenic changes: This bird showed highest abundance values for wetlands and

waterbodies as land cover types (Table 5) and fairly densely human populated areas

(Table 4). Subsistence farming was the type of land-use most commonly associated with

this raptor (Table 6).

Modelled distributions: From the predicted, pristine distribution map (Figure 18)

modelled for this species, it is clear that range expansion has occurred into the Northern

Cape, North West Province and the Orange Free State. The difference in deviance

percentages (Table 8) for the combined and the environmental model for the African

Marsh Harrier are not great and thereby suggests no major distribution changes due to

anthropogenic changes.

Black Harrier

Natural affinities: The Black Harrier was most abundant in areas where vegetation is

mostly sclerophyllous bush and even karoo type cover (Table 1), and where higher

altitudes (Table 2) prevail.

Anthropogenic effects: For the human related variables, high abundance values were

calculated in lower human populated areas (Table 4) and areas with herblands,

shrublands and low fynbos (both pristine and degraded) as land cover types (Table 5).

This bird showed the highest abundance values for areas where sheep farming is the

predominant land-use type, but natural areas also scored similar high values (Table 6).

Modelled distributions: The predicted distribution model (Figure 19) for this species

indicated the presence of Black Harriers on the Cape Peninsula, where the Bird Atlas

Data (Harrison et aI., 1997) describes them as being absent. Further differences between

the predicted, historical or pristine distribution and current ranges are noted for the

Namaqualand, Northern Cape expansion of this bird's range and range contraction in the

17

Eastern Transvaal area. The difference in deviance percentages for the combined and

environmental models (Table 8) suggests a strong anthropogenic influence on this

Harrier's distribution.

Lanner Falcol1

Natural affinities: The Lanner Falcon showed highest abundance values in areas with the

highest altitudes (Table 2) and high rainfall averages (Table 3), as well as forested areas,

both coastal and temperate, transitional (Table 1).

Anthropogenic effects: This falcon is found mostly in the Transkei, and Lesotho and

former Natal area (Table 7). The Lanner had highest abundance values for areas

classified as improved and degraded, unimproved grasslands (Table 5) land cover types.

The land-use data suggested that these falcons are closely associated with subsistence

farming (Table 6).

Modelled distributions: There seems to be a reduction in Lanner numbers in the Northern

Cape region and Gauteng area, but also an expansion of their range into the southern part

of the Western Cape (Figure 20). Goodness of fit statistics suggests no great contribution

by anthropogenic changes on its distribution (Table 8).

Greater Kestrel

Natural affinities: Areas with fairly low altitudes (Table 2) and rainfall averages (Table 3)

showed highest abundance. Vegetation type preferences showed conflicting results, with

the same abundance values for karoo, and tropical bush and savanna regions (Table 1).

Anthropogenic effects: The most abundant land cover type where this species is found, is

clearly degraded thicket and bushland areas (Table 5). Extensive cattle and game

farming (as well as sheep farming) was the land-use type that showed the highest

abundance values (Table 6). This species showed high abundance values for areas with

fairly low human population densities (Table 4) and was by far most predominant in the

former homeland of Bophuthutswana (Table 7).

18

Modelled distributions: There is virtually no change in distributional patterns when the

predicted, pristine model and contemporary Bird Atlas Data maps are compared (Figure

21) for the Greater Kestrel. Goodness of fit statistics (Table 8) also suggests no major

contribution by man for this bird's distribution.

Discussion

The modelled distributions showing predicted distributions in a pristine environment (or

historical distributions) yielded generally satisfactory results. Although no ground­

truthing was done, the predicted distribution maps were sent to various raptor specialists

to get their input and comments. Overall, the response was positive and, for the most

part, these modelled distributions seem to reflect believable ranges for the 15 species

used in the study. Note that these distributions represents year-round range distributions

for each species, and are not broken down into breeding and non-breeding ranges.

The movement of Secretarybirds into the coastal areas (especially the Western Cape) of

the country could be explained by the development of agriculture along this region

(Figure 7). This has been found true for Blue Cranes, a comparable large, terrestrial bird,

where these cranes inhabited cultivated pastures and agricultural fields (Allan, 1993).

Historical data, however, suggest that Secretarybirds have been found in this region since

the 1700's (Boshoff et al., 1983), although this historical distribution probably largely

comprises sightings made after the advent of agriculture in this region.

An unexpectedly low relative abundance of this species in the Kruger National Park, on

the north-eastern border of South Africa, could be attributed to subsequent habitat loss in

the surrounding areas. This suggests that Secretarybirds favour conserved or protected

areas (Table 6), an association that has been suggested before (Boshoff and Allan, 1997).

It therefore seems probable that these birds are moving into the Kruger Park and are

currently more abundant than expected for this area, because they cannot adequately

maintain healthy populations outside a formally protected area. Also, the habitat within

19

the reserve may have changed sufficiently to make.it more attractive for Secretarybirds.

High elephant densities may have impacted heavily on the vegetation of Kruger Park,

opening up habitats and making them more suitable for Secretarybirds than they were

before.

Although the Secretarybird was apparently abundant in "temperate and transitional forest

and shrub types", this vegetation type includes the following: Highland Sourveld and

Dohne Sourveld; Natal Mist Belt 'Ngongoni Veld; Coastal Renosterveld and Coastal

Fynbos (Acocks, 1988). Therefore, this result can be interpreted as a close association

with the shrub-like vegetation types in this classification, which would support our theory

that Secretarybirds have been positively influenced by agricultural expansion near the

coast of South Africa. The vegetation data reflects pristine, untransformed, natural

vegetation, but these specific types (e.g. renosterveld, fynbos, etc.) have been largely

destroyed and replaced by vast areas of cereal crops, creating suitable habitat in naturally

unsuitable areas.

The predicted distribution map for the Cape Vulture (Figure 8) indicates the presence of

these birds on the Cape Peninsula and western part of the Western Cape. Historical

records corroborate this; these vultures were know to occur even on Table Mountain

above Cape Town (Steyn, 1982). The modelled distribution shows a larger range along

the south coast than contemporary data suggest. This extended, historical range is

probably realistic, given that Cape Vultures seem to be returning to this "original"

distribution, as it has been reported that the isolated population at Potberg is starting to

expand along the south coast (Boshoff and Robertson, 1985).

The absence of these vultures in the central Karoo is somewhat unexpected, but historical

distributions do agree with this, with the exception of a few isolated sightings in this area

bordering the grassland ecotone (Boshoff et aI., 1983). Boshoff and Vernon (1980)

showed that although several places in the then Cape Province contained the word

"vulture", "aasvoel" or other references to vultures in their names, this did not exactly

correspond published or unpublished records for the Cape Vulture. The loss of the

20

predicted distribution in the Mpumalanga (Eastern Transvaal) region could be attributed

to the heavily urbanised Gauteng area, which resulted in the discontinuity of the Cape

Vulture's range here. The frequency analysis results for human population densities

(Table 4) supports this. The expansion into the North West - Northern Cape area is

probably "over" predicted by the model and a thorough sensitivity analysis should be

performed in order to understand this better.

The predicted distribution of the Blackshouldered Kite was very similar to

contemporary distribution (Figure 9). The predicted occurrence of this species along the

west and south coast, in the fynbos biome, could be an artefact of this bird's long­

standing association with agricultural areas, confirmed by the high abundance percentage

for this species in wheat and maize land-use types (Table 6). Pristine vegetation analysis

(Table 1) indicated that the Blackshouldered Kite shows highest abundance in grasslands,

which is probably it's naturally preferred habitat (Mendelsohn, 1997). The interspersion

of cultivated lands throughout most vegetation types, probably allows for such a wide

distribution, as a direct correlation between Blackshouldered Kite populations and rodent

(which are abundantly found in cultivated areas) numbers is fairly well known

(Liversidge, 1984).

Human population density does not seem to impact negatively on this species (Table 4).

Skead (1974) suggested that the density of this species is enhanced by a more intensive

impact of man on the landscape. This, and the fact that this raptor seems flexible enough

to use highly managed area (Brandl et al., 1985), has allowed this species to persist and

remain in it's natural distribution.

The predicted absence of Black Eagles from the Waterberg and Soutpansberg areas

(Northern Province) seems spurious. This species is known to occur at high densities in

both these mountain ranges (Tarboton and Allan, 1984), and similar apparently erroneous

contrasts in other species between predicted and present distributions, indicate that there

maybe some problem with the model for this area.

21

Boshoff et aI. (1983) showed range contraction for Tawny Eagles deeper into the Eastern

Cape, away from the Northern and Western Cape, even in the early 1970's. The

predicted distribution map for this eagle therefore comes as no surprise, although the

extent of the' contraction is quite alarming. The species' very close association with

conserved or protected areas (Table 6) confirms the negative influence that human

populations have had on this birds habitats and subsequent distribution and abundance in

South Africa. All analyses performed with human-related variables and the Tawny's

current distribution showed the definitenegative impacts that man has had on this species

(Tables 4, 5, 6).

With such a great difference in deviance values (Table 8) for the respected models, it is

clear that anthropogenic changes in the environment are seriously detrimental to this

raptor's survival. A clear decline in abundance occurs when this raptor is associated with

almost any kind of farming practice (Table 6), which corresponds well with documented

declines of both Tawny and Martial Eagles populations on farmlands (Brandl et aI., 1985;

Brown, 1991). This negative effect of farming practices could explain the massive

decline and obvious absence of this species in the Western and Northern Cape regions.

Apart from the detrimental effects that the poisoning regime has had on these raptors

(Brown, 1988; Brown, 1991), primary productivity also seems to strongly influence

them. Dean and Macdonald (1994) have shown a loss of primary productivity in this

area, which is cause for concern. It has been shown that, especially eagle and vulture

population densities in southern Africa are depressed in areas with low productivity

(Hustler and Howells, 1990). Hustler and Howells (1989) showed that the breeding

densities of Tawny Eagles are influenced by the primary production of the biomes within

which they live.

The presence of Martial Eagles on the Cape Peninsula and surrounding areas has been

documented before (Boshoff et al., 1983), which provides some confirmation of the

accuracy of the predicted distribution model (Figure 12). The overall range contraction

of this species (especially in the Western and Northern Cape) may be attributed the loss

of primary production in the region (Dean and Macdonald, 1994). There seems to be a

22

" .

decrease in the productivity of rangelands in the semi-arid and arid areas of the Cape

Province, which would influence the abundance, and availability of prey species for

Martial Eagles and other large raptors. The goodness of fit statistics suggest a very

strong influence by man on the distribution of the Martial Eagle (Tables 8) and supports

calls for more active efforts to conserve this species (Barnes, 1998).

The Bateleur's predicted distribution is probably greatly under-represented (Figure 13).

This raptor's pristine distribution was modelled in a different way, as the technique used

to predict historical distributions for the other species included in this study was unable to

produce any result for the Bateleur. Apparently, the Bateleur's current distribution has

contracted to such an extent that the data available are simply insufficient to model

historical distribution. This species occurs almost exclusively in protected areas (Table

6), where the variety of vegetation types, rainfall patterns and altitudinal variation is so

limited and cannot accurately reflect possible habitats likely to be occupied by Bateleurs.

It is therefore almost impossible to deduce any kind of natural associations with these

environmental variables. The Tables produced by the frequency analyses for

anthropogenically related coverages (Tables 4, 5, 6), however, show the clear negative

impacts that people and their land management practises have had on this species'

abundance and distribution. Nonetheless, it is very interesting to note that the modelled

distribution map accounted for Bateleurs found in the Western Cape, which corresponds

to known historical records in this area (Boshoff et aI., 1983). The extended historical

distribution for this raptor is therefore believable, but probably much too modest.

The huge range expansion of the Jackal Buzzard into the Northern Cape SeelTIS puzzling

(Figure 14). Although the historical distribution (Boshoff et aI., 1983) shows the

presence of these buzzards in this region, the oldest records (1700 - 1899) correspond

exactly with our predicted distribution model. Bird observations made after 1899 show

the Jackal Buzzards present in this area, but this can probably be attributed to

anthropogenic changes in these habitats since the beginning of this century. A possible

explanation for the movement of Jackal Buzzards (a "strictly" montane species) into open

country areas, is the abundance of prey species caused by over-grazing and farming

23

practises in the region. This raptor's close association with farmed areas is evident from

the land-use-abundance table (Table 6) produced by the frequency analysis. It's been

suggested that resultant reduction in plant cover and structure by grazing, although is

decreases rodent abundance, it may increase plant and rodent diversity (Hanley and Page,

1982), thereby increase prey availability to raptors (Malan and Crowe, 1996). The Jackal

Buzzard could therefore be responding to increased numbers of rodents in these areas

where farming practises allow for grazing and overgrazing of the natural veld types. The

reductions that have occurred in the numbers of other raptors in the area have very likely

also benefited this species.

The strong influence of anthropogenic changes to natural habitats (Table 8) has greatly

altered the distributional patterns of the Redbreasted Sparrowhawk's range (Figure 15).

Although the acceptance of these birds' current presence in the Karoo has been debated

(Macdonald, 1986; Simmons, 1986), the historical absence of this species from the Karoo

seems to be quite believable (Boshoff et al., 1983; Macdonald, 1986; Simmons, 1986).

This range expansion is commonly attributed to the increased amount of alien plantations

in the region (Forsyth et aI., 1997). Confirmation for this statement is found in the high

abundance values in exotic plantations as land-use types (Table 6).

Differences in deviance values for the combined and environmental models were found

to be fairly small for the Black Sparrowhawk (Table 8). This suggests very little

interference from man on this species distribution in South Africa and seems clear when

the predicted and contemporary distributions are compared (Figure 16). This range

contraction is fairly unexpected, as it has been assumed that this species has prolifirated

in South Africa due to its assumed close association with man-altered environments

(Malan and Robinson, 1999). Our frequency analyses showed similar associations

between anthropogenically produced habitats (e.g exotic plantations, several farming

practices and urban areas) and this Sparrowhawk's abundance, but this does not seem to

have affected its range to a large degree (table 8).

24

Although the indicated range contraction is unexpected, the occurrence of this raptor in

the North West and Northern Cape (produced by the model) is unexplained. This area

has shown results contradictory 'to expected ranges for the Cape Vulture (Figure 8)

distribution and it would be safe to assume that some problem has occurred here in the

model, or that the area is sensitive to a specific variable. Further sensitivity analyses and

tweaking of the model is recommended to understand this phenomenon better.

Predicted historical distribution for the Pale Chanting Goshawk show virtually no

change to current distributions (Figure 17) and there is no indication that man has had a

prominent influence on this species' distribution (Table 8). The modelled distribution

seems to be in accordance with expected historical distribution. It should however be

mentioned again that the predicted presence of this bird in Lesotho should be ignored, as

discussed before. Interestingly enough, Pale Chanting Goshawks have been spotted in

this region (Jenkins, pers. corn.').

The African Marsh Harrier's predicted distribution is similar to that of the

contemporary Bird Atlas Data, with range expansion into the Free State (Figure 18). This

bird's close association with waterbodies and wetlands (Table 5) could suggest that it is

moving into cultivated or agricultural areas where artificial water sources have been

supplying farms and avi-fauna with additional habitats and resources, and, hence, created

favourable habitats for this bird.

The differences in predicted and contemporary distributions for the Black Harrier could

be interpreted with some confusion, due the combining of breeding and non-breeding

ranges on one map (Figure 19). One must keep in mind that these distributions depicted

here represent year round movements. Nonetheless, there does seem to be movement

I Dr.A.R. Ienkins.Percy FitzPatrick Institute, Department Zoology, University of Cape

Town, Rondebosch, Cape Town.

25

into the Namaqualand region (Northern Cape), which could be attributed to a possible

increase in rodent availability in the Northern Cape region due to grazing pressures from

the intense livestock farming industry in this area (Hanley and Page, 1982; Dean and

Macdonald, 1994).

According to the predicted distribution for Lanner Falcons, a range contraction has

occurred, especially in the Northern and Western Cape regions (Figure 20). The

historical distribution map suggests two centres of distribution, one in the Northern Cape

and the other along the east coast. The latter seems to have been very retained, but the

former Bushmanland and central Karoo area seem to have undergone a loss. There also

seems to be a decrease in range in the south-western part of Mpumalanga, but this is

probably as a result of the Gauteng and surrounding populated areas (Kemp, 1993) and

their subsequent effects on the environment and habitat modifications. It is interesting to

note that there is a range extension into the southern part of the Western Cape, which is

almost expected considering the amount of wheat fields in which these species have been

reported (Van Zyl, 1994). Even though no land-use data for Lesotho was available and

could therefore not be incorporated into the model, one can assume that it is mostly

subsistence farming. Even without the incorporation of this area into the analysis, the

results show this raptor in close association with subsistence farming (Table 6). The

abundant presence of Lanners in Lesotho and surrounding area (Table 7) suggests that

this type of farming (or the land practises implemented in the former homeland areas) is

beneficial to the Lanner Falcon.

The predicted distribution for the Greater Kestrel is very similar to that of the current

data represented by the Bird Atlas Data (Figure 21). The difference in deviance values

between the combined and environmental models is so small that it can be safely

assumed that anthropogenic changes to habitats have had little effect on this raptor.

Steyn (1982) suggested that this Kestrel's range might have expanded, especially in areas

where woodland has been cleared. The "lack" of range expansion showed from our

predicted distribution, corresponds well with similar findings by Brandl et al. (1985).

26

Conclusions

Most of the raptor species in this study showed distinct differences between modelled

historical and contemporary distributions. The present analyses provide evidence to

attribute the perceived changes in distribution to habitat modification and changes in

land-use practices. The alarming range contraction of, for example the Tawny Eagle, and

the surprising expansion of the Jackal Buzzard's distribution, on the other hand, is cause

for changes in land-use management. The thought that ranges like the Bateleur's have

been so severely reduced that it is difficult to predict without altering the model, is cause

for concern.

Ideally, measures of prey availability and abundance, as well as the availability of

artificial nesting habitats (i.e. artificial perches, telephone poles) should be factored into

further studies of this kind to improve the accuracy of the predicted distributions. It is

acknowledged that isolated examples were sometimes used to confirm suggested

explanations, but this study was not intended to give a full review of historical

information on range or abundance changes; the examples supply extra insight into

changes. A closer look into land-uses and management in the Western and Northern Cape

seems appropriate, as changes in distribution for several. species appear to have occurred

in this region. The documented loss (Dean and Macdonald, 1994) of especially primary

productivity here seems to be affecting biological diversity more than was previously

realised. This productivity directly relates into prey availability and abundance (Nel,

1983), which has been shown to be a major factor in determining raptor densities

(Newton, 1979). This area has never been the major focus of conservation concerns,

probably due to its low human population density and expected minimal impact on the

natural environment, which might not quite ring true for, at least, raptors.

Although this study is by no means the last word on the influence of land transformation

on our raptor community, it does take the first step in quantifying these effects, thereby,

hopefully, help in acknowledging the importance of land management practices.

27

Acknowledgements

I would like to extend my thanks to my supervisors Morne du Plessis, Les Underhill and

Andrew Jenkins. Les Underhill provided help with the interpretation and modelling of

data. This project would not have made it to its present stage, had it not been for the

knowledgeable advice, unselfish support and invaluable suggestions from Andrew

Jenkins. Sincere thanks are extended to Nicholas Lindenberg for his technical (and other)

support. I thank also Grant Benn and Mark Thompson for their suggestions and advice

concerning analyses and data "collection" respectively and Rene Navarro for all his help

with the Bird Atlas and National Land Cover data sets. Alan Kemp, Warwick Tarboton,

Rob Simmons, Rob Davies and Anthony van Zyl supplied valuable contributions and

interesting discussions regarding the biology and behaviour of these birds. A special note

of thanks is reserved for David Allan who helped review the rough draft and provided

helpful comments and suggestions. Financial support for this study was provided by the

Sustainable Environmental Programme of the National Research Foundation (NRF).

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Table 1: Frequency analyses results for Vegetation and raptor species (given in percentages)

Secretarybird

Cape

Vulture

Blackshouldered

Kite

Black

Eagle

Tawny

Eagle

Martial

Eagle

Bateleur

Jackal

Buzzard

Redbreasted

Sparrowhawk

Black

Sparrowhawk

Pale

Chanting

Goshawk

African

MarshHarrier

Black

Harrier

Lanner

Falcon

Greater

Kestrel

uncommoncommonabundant

uncommoncommonabundant

uncommoncommonabundant

uncommoncommonabundant

uncommoncommonabundant

uncommoncom1110nabundant

uncommoncommonabundant

uncommoncommonabundant

uncommoncommonabundant

uncommoncommonabundant

uncommoncommonabundant

uncommoncommonabundant

uncommoncommonabundant

uncommon

commonabundant

uncommoncommonabundant

207

4151226

31176

144

o1211o

22

1017181022

111222

8

163

293843

6

o222538

116

o15

1732

ooo

2323

.>: 23

221112

311

25

121211

94

2

9

97

2

o21813

191521101211

1253

19146

151217

1815

5

322119

12

2

136

3

121717

251011

22

14o1818o

59

oo9

227

87o

30oo62o21o5

ooo1385

515o

815196

3o17105

8

1612

139

7

81820

ooo131415

4

49

o

o22

45

48

2

3

9

1627

8

1612

233739

137

2

4

2

11

1717

133138

ooo19104

ooo

212411

44233111116

30

219

171811373831

1983

1032

142527

213442

101419201720

122117

1616164

139

131532173337

153334

7

4

3

15

3537

262622

182329

92o

102123193216

171411

8109

3242

73

81936

167669

123

o56

6

162338

352

23

3

91413

212339

Table 2: Frequency analyses results for Elevation and raptor species (given in percentages)

Description 0-493m 493-986m 986-1578m 1578-2071m 2071-2564m 2564-3057m 2564-3057m

Secretarybird uncommon 19 11 17 21 10 23 23common 14 12 22 24 17 12 12abundant 10 12 21 23 25 9 9

Cape uncommon 19 9 17 24 20 11 11Vulture common 22 10 12 16 27 14 14

abundant 4 5 4 11 33 43 43

Blackshouldered uncommon 22 17 11 4 17 27 27Kite common 17 15 15 11 21 22 22

abundant 17 10 23 36 10 4 4

Black uncommon 17 14 14 18 18 19 19Eagle common 15 17 18 18 22 10 10

abundant 7 13 10 16 20 33 33

Tawny uncommon 23 28 41 8 0 0 0Eagle common 44 32 21 3 0 0 0

abundant 70 22 8 1 0 0 0

Martial uncommon 26 21 17 14 11 10 10Eagle common 20 22 19 10 6 24 24

abundant 45 28 20 7 1 0 0

Bateleur uncommon 50 40 10 0 0 0 0common 57 35 7 0 0 0 0abundant 89 10 1 0 0 0 0

Jackal uncommon 23 21 19 32 5 0 0Buzzard common 25 19 18 16 12 11 11

abundant 8 7 7 14 31 33 33Redbreasted uncommon 9 6 5 25 20 36 36

Sparrowhawk common 6 5 5 13 26 44 44abundant 3 4 6 21 32 34 34

Black uncommon 25 5 7 12 5 46 46Sparrowhawk common 34 12 8 18 27 0 0

abundant 21 18 14 22 9 16 16Pale uncommon 18 23 31 11 6 11 11

Chanting common 19 43 32 4 1 0 0Goshawk abundant 12 49 36 3 0 0 0African uncommon 28 6 11 28 22 5 5l\1arsh common 33 11 17 - 34 5 0 0Harrier abundant 37 12 12 32 7 0 0

Black uncommon 25 11 12 27 7 18 18Harrier common 12 10 8 11 24 35 35

abundant 11 5 7 16 39 22 22

Lanner uncommon 28 12 17 27 10 5 5Falcon common 9 12 9 15 31 24 24

abundant 8 16 8 9 21 38 38

Greater uncommon 7 16 26 28 16 7 7Kestrel common 10 31 42 16 1 0 0

abundant 12 36 43 7 1 0 0

Table 3: Frequency analyses results for Rainfall andraptor species (given in percentages)

c:: S S S S.~ 8 8 8 8 8...... S 0 0 0 0 S 8e, 0 l() l() 0·C ~ l() \0 r- o. 8 0c::

I I I l()I:.J 0

, I 0 0c.n 0 0 0 0 0 0 l()Cl.l M 0 0 l() l() 0 0 -Q v M l() \0 t"- O\. - 1\

Secretarybird uncommon 5 12 19 21 12 13 19common 10 16 18 15 18 14 10abundant 8 19 13 12 19 17 12

Cape uncommon 1 14 26 16 18 17 7Vulture common 0 11 26 20 24 17 2

abundant 0 5 11 17 23 20 24

Blackshouldered uncommon 18 16 7 7 10 21 22Kite common 8 18 10 11 18 15 20

abundant 2 12 22 22 16 13 11

Black uncommon 8 10 13 20 22 20 8Eagle common 15 13 10 14 14 16 18

abundant 14 16 9 12 15 16 18

Tawny uncommon 7 29 23 15 11 12 3Eagle common 8 24 19 15 23 11 1

abundant 16 24 30 12 14 1 3

Martial uncommon 7 10 13 11 19 20 20Eagle common 17 17 14 9 14 11 18

abundant 22 23 19 8 11 13 4

Bateleur uncommon 5 14 10 14 18 23 15common 9 29 23 10 22 5 2abundant 8 16 43 13 10 10 0

Jackal uncommon 14 13 18 26 13 8 8Buzzard common 16 14 10 14 19 17 10

abundant 8 6 4 11 22 22 27

Redbreasted uncommon 3 8 5 13 22 19 30Sparrowhawk common 2 8 5 8 24 22 30

abundant 3 7 4 7 15 26 38

Black uncommon 0 2 6 13 18 19 41Sparrowhawk common I, 1 3 4 9 26 32 25

abundant 0 2 3 7 24 34 30

Pale uncommon 25 41 27 6 1 0 1Chanting common 55 41 4 0 0 0 0Goshawk abundant 65 33 3 0 0 0 0

African uncommon 1 7 13 21 17 21 19l\1arsh common 1 6 8 20 26 22 16Harrier abundant 1 2 3 11 28 31 24

Black uncommon / 8 15 12 15 16 17 16Harrier conllnon 14 16 14 ,. 9 9 12 25

abundant 17 17 7 16 14 13 16

Lanner Ul1COl1llnOn 7 14 18 15 14 13 20Falcon common 15 13 14 15 22 18 2

abundant 12 6 4 10 23 21 25

Greater uncommon 17 22 27 27 4 "l 0.)

Kestrel common 35 30 23 10 2 0 0abundant 41 35 22 2 0 0 0

Table 4: Frequency analyses results for Human Population Density (people/km) and raptor species

(given in percentages)

tf")M ~

~ \0 ~oS: 0\ 0\ ~M

0 M 0\""1" \0 I.... ""1" \0 ..... I I- c, l/'l ~ 'O:j" M ""1" ~ 0\

0 -.i-tf") 00 M I I tf") 0 ..... vi 001: M ..... ..... I I I M 00 -.i- M ..-.: tf")

(,J 0 I I I I· 0 ..... tf")en r- tf") ""1" 0 ...0 tf") \0 'O:j" ""1" 0\ tf")Q) I tf") r-: ~ \0 M ~ 0 l/'l r- M ..... M 0 M 00

Q 0 0 0 ..... -.i- ..... tf") 0\ M \0 M ""1" l/'l ..... M M

Secretarybird uncommon 10 2 4 5 10 13 12 12 11 8 3 10 0

common 5 10 9 12 14 15 10 8 8 9 0 0 0

abundant 6 5 7 20 22 13 9 10 3 0 5 0 0

Cape uncommon 7 1 0 6 12 13 7 8 14 3 0 0 29

Vulture common 20 4 0 7 14 10 13 19 13 0 0 0 0

abundant 23 1 0 5 I 12 8 19 20 8 5 0 0 0

Blackshouldered uncommon 14 8 14 13 7 3 7 7 7 6 4 0 9

Kite common 16 4 6 11 10 8 9 10 9 9 0 9 0

abundant 2 1 1 4 10 13 10 10 11 11 11 12 5

Black uncommon 6 3 4 4 8 8 6 7 9 9 6 22 8

Eagle common 3 6 11 6 11 7 8 7 6 6 1 9 18

abundant 9 10 10 15 15 7 7 7 6 4 10 0 0

Tawny uncommon 11 0 6 15 19 11 10 15 12 0 0 0 0

Eagle common 5 2 8 22 15 10 4 15 18 0 0 0 0

abundant 21 15 2 31 9 2 2 17 2 0 0 0 0

Martial uncommon 6 3 6 6 13 12 11 10 12 9 0 3 9

Eagle common 7 14 16 14 14 9 6 11 10 0 0 0 0abundant 9 21 12 21 12 6 5 9 6 0 0 0 0

Bateleur uncommon 19 0 3 14 7 5 6 20 27 0 0 0 0

common 7 0 7 23 12 7 12 16 16 0 0 0 0abundant 28 19 1 24 5 5 1 13 5 0 0 0 0

Jackal uncommon 7 6 6 6 10 10 9 8 12 8 6 3 7

Buzzard common 10 13 10 7 11 9 9 8 4 11 9 0 0abundant 18 7 13 5 12 9 13 13 4 5 0 0 0

Redbreasted uncommon 19 2 6 4 18 28 17 4 0 0 0 0 0

Sparrowhawk common 25 1 2 4 9 10 9 7 5 16 13 0 0abundant 19 0 2 5 14 8 7 8 7 0 30 0 0

Black uncommon 14 0 0 2 3 10 5 7 12 22 8 17 0

Sparrowhawk common 18 0 1 1 7 11 6 16 15 25 0 1 0abundant 1 0 0 0 2 4 5 5 7 4 22 2 47

Pale uncommon 3 15 11 13 16 10 11 4 9 2 7 0 0Chanting common 0 29 28 22 12 4 4 1 0 0 0 0 0Goshawk abundant 1 23 35 29 7 3 2 0 0 0 0 0 0

African uncommon 6 0 0 2 7 13 10 8 15 23 10 6 0Marsh common 5 0 2 3 9 13 12 10 10 11 7 0 19

Harrier abundant 7 0 O' 1 7 11 12 8 8 3 42 0 0

Black uncommon 6 0 7 11 18 17 18 6 3 14 0 0 0

Harrier common 13 9 10 8 18 11 10 6 0 7 8 0 0

abundant 15 12 21 10 24 6 9 2 0 0 3 0 0

Lanner uncommon 10 2 4 5 11 11 9 7 8 11 20 3 0

Falcon common 10 5 6 5 6 7 6 6 2 6 19 1 21

abundant 11 9 8 9 4 5 12 15 8 5 0~,

9.)

Greater uncommon 2 6 7 7 10 7 8 5 9 7 2 18 11

Kestrel common 0 16 22 15 10 12 8 5 5 0 7 0 0

abundant 1 14 19 26 7 12 8 tq 3 0 1 0 0

Table 5: Frequency analyses results for Land Cover and raptor species (given in percentages)

9 86 9

7711

9411

796

1164

910

911

911

89uncommon

commonSecretarybird

abundant 6 7 7 9 8 12 9 8 14 6 4 10

Cape Vulture uncommoncommon

86

128

128

139

2 5 811

48

128

822

9 711 6

abundant 6 7 7 9 7 10 12 26 10 4

BlackshoulderedKite

uncommoncommon

106

4

747

812

107

198

1010

711

48

911

5 108 6

abundant 7 13 13 9 3 5 7 6 11 6 12 7

Black Eagle uncommoncommon

98

96

96

1310

712

617

97

55

98

108

11 59 6

abundant 9 6 6 6 15 13 9 4 10 10 5 8

Tawny eagle uncommoncommon

76

86

86

1212

56

3 1522

1118

68

25

7 155 6

abundant 11 5 5 8 6 4 22 11 14 5 3 8

Martial eagle uncommoncommon

611

96

96

158

712

1112

912

78

87

6

57 85 8

abundant 9 4 4 5 12 12 14 14 8 5 4 10

Bateleur uncommoncommonabundant

365

722

223967

1594

ooo

ooo

16168

13113

4

44

33

5 125 53 3

J ackal Buzzard uncommon 9 11 11 10 8 14 7 4 8 3 8 7common 11 7 7 8 12 11 6 4 8 11 6 9abundant 6 6 6 12 9 6 4 3 12 23 6 7

Redbreastedsparrowhawk

uncommoncommonabundant

74

8

796

796

171614

867

1744

452

22o

121216

71923

4 87 66 7

Blacksparrowhawk

uncommoncommonabundant

542

797

797

212926

2 22

685

377

888

71116

19 127 513 6

Pale chantinggoshawk

uncommoncommonabundant

61412

93

93

5

o

132219

8 ..1326

121411

111014

856

4

2

7 82 121 9

African MarshHarrier

uncommoncommon

96

1312

1312

1310

23

48

65

53

11

11

512

11 78 11

abundant 4 8 8 18 2 4 4 5 9 11 7 21

BlacJ{ Harrier uncommon 9 11 11 6 8 18 5 11 6 5 9

common 9 10 10 2 11 19 5 10 12 4 8abundant 14 6 6 2 15 18 3 12 10 2 10

Larmer falcon uncommon 6 11 11 12 6 12 7 5 8 5 9 7common 7 7 7 9 7 10 8 9 9 12 8 5abundant 7 6 6 7 7 4 7 11 10 21 6 6

Greater kestreI uncommon 11 10 10 5 9 7 9 4 10 3 13 8common 10 8 8 3 13 13 9 7 9 2 4 12abundant 8 6 6 4 10 13 8 24 9 2 4 6

Table 6: Frequency analyses results for Land-use and raptor species (given in percentages)

~

CI)~

::"'0 :: 's:: CI)

:~ ~ Q)~ ~ ~

~l-c

~...... ...... ee :: CI) c.::: N

:: l-c ~ ...... :: 's ~:: CI) 'c:a:: ,~

...... ~ 'S 'S~ :: CJ ~ ~ ~ a CI)

,~ ...... "'0 ~ l-c l-c CJ ~ ,§...... ~ c.. ~ l-c c.:::~ l-c :: l-c

~c, > ~ > ~ c.::: ~ ~...... ~ ~';: l-c CJ 'c;) ......~ ~ ,~ :: ~

"'0 l-c c, CI) ; ~ ~CJ CI) ...... ...... ~ a ~ = ~'c;)

~CI) c: 0 0 ...... ~ ...... ~ .0 .0 .c ~~ 0 l-c ~ ~ ~ 's ~ .c = l-c

Q CJ e, ~ ~ ~ c: CI) CI) = ~c..

Secretarybird uncommon 9 14 8 13 9 6 9 13 18common 12 22 15 11 7 10 9 0 14abundant 25 14 13 6 8 15 8 0 11

Cape uncommon 20 8 10 11 9 5 11 11 15Vulture common 28 0 19 9 6 3 24 3 8

abundant 14 1 14 18 7 3 32 6 5

Blackshouldered uncommon 22 6 12 8 11 14 15 10 2Kite common 17 16 10 10 9 8 16 9 5

abundant 7 13 10 15 8 5 7 14 21

Black uncommon 7 21 5 17 9 7 9 18 6Eagle common 6 18 7 16 16 14 8 9 6

abundant 23 1 10 7 20 16 13 5 5

Tawny uncommon 17 1 32 7 8 14 9 1 11Eagle common 35 1 31 0 5 9 16 0 4

abundant 74 0 11 0 2 3 10 0 0

Martial uncommon 9 18 9 19 9 8 12 8 8Eagle common 16 7 16 12 13 16 11 1 7

abundant 44 0 17 6 9 12 11 0 1

Bateleur uncommon 18 10 31 3 5 0 34 0 0common 37 0 40 0 1 0 21 0 0abundant 86 1 7 0 1 0 5 0 0

Jackal uncommon 8 14 7 16 11 11 6 11 16Buzzard common 7 18 4 16 13 15 13 8 7

abundant 9 21 3 11 12 12 26 2 4

Redbreasted uncommon 10 49 1 10 11 5 5 0 9Sparrowhawk common 18 16 3 17 11 8 15 3 8

abundant 17 22 1 6 10 12 18 9 5

Black uncommon 14 33 4 6 3 0 9 26 4Sparrowhawk common 6 28 4 17 3 1 17 19 4

abundant 5 27 6 16 3 0 21 18 5

Pale uncommon 9 0 18 14 18 18 3 4 16Chanting common 4 0 22 4 26 42 0 0 2Goshawk abundant 16 0 23 1 22 37 0 0 0

African uncommon 5 28 4 18 6 2 8 16 13Marsh common 10 0 5 23 7 4 21 15 14Harrier abundant 10 6 7 21 5 2 31 7 10

Black uncommon 16 0 3 22 15 10 9 8 18Harrier common 12 0 3 19 19 16 14 0 16

abundant 9 0 3 15 23 29 10 0 11

Larmer uncommon 11 17 8 13 10 8 7 11 15Falcon common 6 11 11 14 12 12 13 12 10

abundant 14 0 11 9 12 8 35 8 3

Greater uncommon 5 1 12 8 15 15 1 20 23

Kestrel commonabundant

oo

22

Table 7: Frequency analyses results for Fonner Provinces & Homelands andraptor species (given in

percentages)

,..; ~

~~

C ~

C til 'S: ~

,S ] l. ";0 ~ 'Q)..... l.i' 0 ~C.

~ ~~ ..:t: ;,

';:: 'Q) .c:: bI.l til til ~

Qj ..... '; c: ~ C c ~~ C. ..:t: 0

. til C. til ..... ~ ..... ~ ~ c:~ 0 ~

til~ ~ l. ~ l. l. ~

~ ~ ~ U U ~ z; 000 Eo-< Eo-< >-Secretarybird uncommon 4 7 25 11 8 14 10 15 5

common 16 10 10 4 18 17 8 14 4abundant 10 11 7 4 20 22 9 14 2

Cape uncommon 9 3 16 8 10 12 8 14 18Vulture common 11 1 8 16 17 7 20 16 4

abundant 5 2 6 27 13 3 35 9 0

Blackshouldered uncommon 6 13 10 17 14 3 16 9 12Kite common 10 9 9 12 12 12 17 8 12

abundant 11 6 17 5 12 18 6 16 10

Black uncommon 3 8 23 9 13 7 10 11 16Eagle common 8 15 14 7 13 8 12 9 14

abundant 3 14 13 14 18 8 7 8 16

Tawny uncommon 20 7 0 0 20 17 0 25 11Eagle common 19 5 0 0 23 4 0 17 31

abundant 0 8 0 0 20 7 0 35 30

Martial uncommon 8 10 23 2 19 8 7 9 15Eagle common 9 12 13 4 17 9 3 10 23

abundant 10 16 16 0 13 4 12 19 11

Bateleur uncommon 3 2 0 0 14 0 0 8 73common 15 4 0 0 20 0 0 16 45abundant 0 5 0 0 25 0 0 60 9

Jackal uncommon 8 14 1 6 15 22 3 19 13

Buzzard common 1 13 15 12 13 10 13 6 18abundant 0 8 26 21 14 5 25 2 0

Redbreasted uncommon 0 11 15 19 16 13 15 11 0Sparrowhawk common 0 6 17 38 11 9 16 3 0

abundant 0 8 12 32 17 7 22 2 0

Black uncommon 0 3 18 8 21 1 7 13 29Sparrowhawk common 0 3 27 1 38 1 7 9 14

abundant 1 2 0 1 45 1 38 12 0

Pale uncommon 22 14 19 4 0 20 1 10 8Chanting common 31 43 0 0 0 19 0 7 0Goshawk abundant 38 50 0 0 0 6 1 5 0

African uncommon 2 7 15 2 22 14 9 17 11Marsh common 4 6 6 1 45 9 22 8 0

Harrier abundant 0 5 0 0 59 1 30 5 0

Black uncommon 0 11 41 8 14 18 6 3 0Harrier common 0 13 30 21 8 17 11 1 0

abundant 2 21 0 30 6 23 18 0 0

Larmer uncommon 4 8 33 8 11 13 6 13 6Falcon common 12 8 14 20 11 7 10 7 11

abundant 7 8 7 19 21 2 31 4 1

Greater uncommon 12 16 3 7 1 34.., 21

..,.) .)

Kestrel common 27 21 0 0 1 30 1 16 5

abundant 49 20 0 0 0 15 2 13 0

Table 8: Goodness of fit statistics

SPECIES TOT DEV DEV COMB 0/0 ENVIRO 0/6DEV (ALL) (ENVIRO)

Secretarybird 24048 9930 5876 34 22Cape Vulture 21520 11214 8623 52 40

Blackshouldered 33484 18327 15367 55 46Kite

Black Eagle 24064 7938 6205 33 26Tawny Eagle 18160 13968 10199 77 56

Martial Eagle 16957 9073 5755 54 34Bateleur - - - - -

Jackal Buzzard 36864 20652 13163 56 36Redbreasted 7504 3756 2636 50 35

SparrowhawkBlack 6695 3101 2822 46 42

SparrowhawkPale Chanting 40361 31775 29749 79 74

GoshawkAfrican Marsh 13302 6402 5462 48 41

HarrierBlack Harrier 9820 5064 3652 52 37Lanner Falcon 11826 3985 3375 34 29Greater Kestrel 22072 13560 12739 61 58

Key:TOT DEY = Total devianceDEY (ALL) = Deviance accounted for by the all the variablesDEY (ENVIRO) = Deviance accounted for by only the environmental variables

(elevation, vegetation, rainfall)COMB % = Percentage of total deviance accounted for by the combined model, i.e.

all the variables (:.DEV(ALL) / TOT DEY)ENVIRO°-lc> = Percentage of total deviance accounted for by the natural or environmental

model, i.e. 3 environmental variables ( .'.DEV(ENVIRO) I TOT DEV)