The Role ofFarm Dams in Conserving ha.bitat thus structuring specificspecies assemblages on different wetland types. (Siegfried, 1976; Kantrud ... continents, whereas others travel

The Role of Farm Dams in ConservingWaterbird and Wetland Diversity in the

Western Cape, South Africa.

Albert Froneman

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

THE ROLE OF FARM DAMS IN CONSERVING

WATERBIRD AND WETLAND DIVERSITY IN THE

WESTERN C,APE, SOUTH AFRICA.

AlbertFroneman

Percy FitzPatrick Institute ofAfrican Ornithology, University ofCape Town, Rondebosch 7700, SA.

A Project submitted to the University of Cape Town in partial fulfilment of the requirements for the Degree of

M.Sc. in Conservation Biology.

February 1997

ABSTRACT

Freshwater wetlands are among the most threatened habitats on earth. Effective wetland

biodiversity conservation can, however, not be evaluated without understanding the role of

artificial waterbodies as substitute refuges. Waterbird assemblages were examined on 59 farm

dams in the Elgin and Caledon regions of the Western Cape, South Africa. This study

examines the relationship between waterbird use and habitat characteristics of farm dams.

Patterns of temporal and spatial variation ofwaterbird species richness and abundance were

quantified in relation to the habitat characteristics of each dam. These variables were

evaluated in terms of creating a mosaic of biotopes through varying degrees of vegetation

structure, which may be a useful tool to enhance waterbird habitats at farm dams.

Multivariate statistical analyses were used to explain the observed patterns. Both cluster

analysis and regression procedures identified surface area of the farm dams as an important

variable determining the presence ofmany waterbird species. Structural diversity in terms of

vegetation was especially important in determining waterbird usage of the dams. The study

concludes that the high number of artificial impoundments in the transformed habitat matrix

of the Western Cape play an important role in supporting waterbirds.

INTRODUCTION

An important problem in practising effective biodiversity conservation in southern Africa isa lack of

knowledge on the impact of anthropogenic-transformations on various ecosystem processes

(Macdonald, 1989). The maintenance of natural wetland ecosystem structure and functioning

should thus form an integral element of water allocation to ensure environmental integrity.

Equitable allocation of South Africa's dwindling water resources is therefore an essential question,

and innovative approaches are needed to find the best solutions to this problem. Reallocated water

such as farm dams should be managed to ensure a significant contribution to conserving wetland

biodiversity. The traditional approach to the problem of environmental water allocation has been

blinkered by a perception that water is allocated either to the environment or for use by humans,

after which it is 'lost' to the environment.

The maintenance of functional integrity of natural wetlands in South Africa has received some

research attention (Rogers & Higgins, 1993). Little effort has however been directed towards

assessing the biological importance of the large number of artificial waterbodies in South Africa. To

achieve effective biodiversity conservation, the true impacts of alterations to natural wetlands cannot

be evaluated without understanding the role that artificial waterbodies playas substitute refuges for

biodiversity.

Waterbird communities and wetlands

It is well known that waterbird species are ecologically specialised with respect to the use of food

and ha.bitat thus structuring specific species assemblages on different wetland types. (Siegfried, 1976;

Kantrud & Stewart, 1977; Kauppinen, 1995). Certain environmental factors of a wetland affecting

avian community structure may remain fairly stable, such as size, whereas others can be more

variable, such as depth and vegetation (Kauppinen, 199~).

1

Kauppinen (1995) reasoned that

gradients of waterfowl community structure in boreal lakes were explained by the quantity of

emergent vegetation, and the size and depth of the lake. .Avian community structure of single, small

lakes therefore fluctuates, with wider amplitude than communities on a regional scale. This

supports the idea of instability and higher disturbance levels often found in small artificial wetlands.

In South Dakota a large number (88 000) of stock watering ponds have been formed by construction

of earthen dams across natural waterways (Mack & Flake, 1980). Many of these ponds are of

considerable value to the local waterbird populations. The use of these stock ponds by waterfowl is

related to the habitat variation in adjacent wetlands and the upland habitat. Breeding ducks are thus

often dependent on a diverse array of wetland types (Flake, 1978). In the prairie pothole region,

stock ponds are of considerable value to waterfowl especially as breeding habitat. The relatively

short life span of these stock ponds is influenced by the prevailing land use practises and it is

therefore argued that they should not be viewed as replacement wetlands for mitigating the effect of

draining glacial marshes.

Wetland size and waterbird diversity

The role that wetland size plays in the assessment of artificial wetland importance is dictated by both

the theory of island biogeography and a concern for the efficient use and allocation of resources.

The theory of island biogeography addresses the relationship between island size and species richness

(MacArthur & Wilson, 1967). Specifically, isolated patches of habitat (i.e. habitat islands) will not

retain a high species complement over time. The extensive body of literature on this subject

indicates that species richness is associated most with tract size. The tract size-species richness

relationship is Jog linear, with larger tracts having more species, other factors being equal. Because

of this log linear relationship there is a size below which whole compliments of species are lost

(Brown & Dinsmore, 1986). A similar relationship can therefore be expected between wetland size

and bird species richness and bird biomass.

2

Waterbirds and artificial waterbodiesin southern Africa

The creation of artificial aquatic habitat may modify waterbird distribution and species richness

considerably, sometimes fostering large aggregations of birds (Siegfried et al., 1975). Various bird

species have expanded their ranges in southern Africa by.exploiting transformed biotopes, and an

estimated 85 species have benefited from habitat changes in the Western Cape, South Africa

(Hockey et al., 1989). The influence of biotope transformation on the diversity of natural biota in

southern Africa is however poorly understood and seldom quantified.

Jackson (1987) identifies the eastern Free State wetlands as some of the most important waterfowl

breeding areas of southern Africa, and stresses the severe impact that agricultural activities have had

on these wetlands. Intensive agricultural activities have drained pristine wetlands and only a fraction

of the previous wetl~nd diversity remains. Waterfowl have, however, adapted to the many dams that

have been excavated in the area, especially some of the major storage dams such as the Sterkfontein

Dam. Waterfowl numbers abound on these artificial waterbodies but the natural wetland system,

which still supports a vast number of the subcontinent's aquatic avifauna, is under serious threat

from agricultural development.

Although it is known that some African ducks (Anatidae) are highly migratory, moving between

continents, whereas others travel shorter distances or are sedentary, movements of many species are

still unclear (Newman, 1982). Little et al. (1995) point out that the relatively long incubation

periods in ducks combined with the precocial nature of the ducklings demands parental care for an

extended period. To be effective in supporting a diversity of waterbirds, farm dams should thus

provide the necessary habitat requirements and food resources throughout extended breeding cycles.

3

Waterbirds and artificial water bodies in the Western Cape

Guillet and Crowe (1986) investigated the patterns of distribution and species richness for southern

African .. waterbirds and suggested that the Western Cape was discrete in terms of resident and

migrant species. 'Guillet and Crowe (1984) emphasised that the superabundance of ephemeral

wetlands in the Western Cape explains the high diversity of waterbirds in relation to terrestrial birds.

Aquatic biotopes suitable for Anatidae (e.g. 'discrete' pond-like water bodies) tend to be of an order

of magnitude higher in the Western Cape than elsewhere in South Africa (Guillet & Crowe, 1986).

They illustrated a positive correlation between Anatidae species richness and impoundment density in

the Western Cape.

There are more than 4000 farm dams in the Western Cape with a combined storage capacity in

excess of 120 x 106 m3 (Berg et al., 1994). As part of the Western Cape System Analysis, Berg et

al. (1994) calculated the number of farm dams in more localised regions and used an area-height­

integration method to calculate dam size and depth. The Palmiet river basin which incorporates the

Elgin study area contains some 399 farm dams with a total area of 5 749 316 m2 which stores

approximately 24 198 113 m3 of water. Dams in the Palmiet river basin 'have an average size of 14

409 m2. The Overberg study area partly falls into the Riviersonderend basin which contains 435

farm dams with a total surface area of 3 544 272 m2 and a storage capacity of 11 506 908 m3. The

average dam size is 8 147 m2 which is considerably less than that indicated for the Palmiet river

basin.

This study addresses the influence of farm dams as relatively new biotopes in terms of waterbird

diversity and richness, .andevaluates their role in conserving the wetland avifauna of the Western

Cape. Little and Crowe (1994) suggested that the addition of new biotopes (e.g. farm dams) in the

deciduous fruit farming district of Elgin have helped to in~rease the pre-farming avian diversity as a

result of district-wide land use practises. They suggest that the increased species richness today,

4

compared to before the establishment of the deciduous fruit orchards is mostly due to the

introduction of novel waterbird habitats, resulting from the construction of storage dams for orchard

irrigation. This study quantifies the characteristics favoured by waterbirds on a farm dam and

describes the 'ideal' farm dam in terms of waterbird diversity and richness. Recommendations are

made on improving current farm dams to attract more waterbirds and thus contribute to the

potentially important role that farm dams play in supporting waterbirds in a highly transformed

fiabitat matrix.

STUDY AREA

Fifty-nine farm dams were selected in the Elgin/Grabouw (28 dams) and Overberg/Caledon (31

dams) districts of the Western Cape, South Africa (Figure 1). This ensured a representative sample

ofdifferent physical attributes and gradientsin vegetation cover. The Western Cape is a primarily

winter rainfall (May w August) region which is suitable for a wide diversity of farming practises. The

Elgin region is primarily a deciduous fruit farming area, while the Overberg region is primarily

cultivated for cereal crops. The co-ordinates and surface area of each of the 59 farm dams are listed

in Appendix 1.

METHODS

To study temporal variation in waterbird usage of the farm dams, the dams were visited during the

winter (June - August) of 1996 and the following summer (October w January) of 1996/97. After

preliminary investigations, the measurement techniques used for physical attributes and vegetation

during the winter samplingperiod were improved upon for the summer samplingperiod.

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6

Dam Characteristics and Habitat Measurements

Dams were selected to obtain a range from those with poor diversity to those almost mimicking

natural wetlands. All dams were located on private land and permission was obtained from the

relevant landowners to perform observations and measurements at each dam. Various physical

attributes and vegetation characteristics were measured at each dam.

Dam perimeter was measured using a 100m tape and verified by measurements from aerial

photographs (1:12500) and orthophotos (1:10 000). Dam surface area was then calculated for each

dam using a combination of area estimation techniques suggested by Millar (1973) and standard

trigonometrical .and geometric area estimation techniques. Dam surface area changed quite

significantly in some cases from winter to summer due to high rainfall experienced in the Western

Cape during September - November 1996. Dam depth was estimated based on the height of the

dam wall and classified into five depth classes ranging from shallow « 2m) to deep (> 6m). Each

dam was assigned a water level percentage index based on visual estimation of a percentage of the

available basin that was flooded. The slope of the terrain adjacent to the dam was recorded and the

number of inlets and outlets present and whether the water level of the dam was only dependent on

runoff from adjacent land. Adjacent land use practises were also recorded. The percentage

exposed shoreline and bare embankment was estimated as this was considered to be an important

variable in determining the avian diversity at the dams. Watercolour and turbidity was recorded

according to seven different classes ranging from clear to dull murky brown.

Vegetation cover around each dam was estimated as a percentage cover. Three major vegetation

life forms were recognised, i.e. aquatic vegetation, emergent edge vegetation and surrounding

embankment vegetation. A percentage estimate of aquatic vegetation present in the dam and the

percentage cover of a dense surface mat of aquatic vegetation if present was recorded. Emergent

edge vegetation is particularly important in terms of wetland avian diversity (Losito & Baldassarre,

7

1995). Emergent edge vegetation was initially estimated as a percentage of the total shoreline

length of each dam and. subsequently according. to different structural groupings. Structural

groupings included short sparse or dense grass, tall sparse or dense grass, bullrushes Thypa spp,

reeds Phragmites spp., sedges Cyperacea, indigenous shrub and exotic shrub. Vegetation on the

embankment or upland areas adjacent to each farm dam was classified using the same groupings as

for emergent vegetation. Other vegetation variables recorded included alien tree presence and

overhanging trees both dead and alive. The percentage cover of dead vegetation around each dam

was also recorded. Anthropogenic disturbance around the dams was recorded, such as roads,

houses, power-lines, and the presence of small-stock.

To investigate the possible effects of isolation on the diversity of waterbirds at each dam the number

of dams in a 1 km radius around each dam was recorded. Measurements between the relevant dams

were done using GPS locations and verified from measurements on detailed aerial and orthophotos.

Waterbird Surveys

For the purpose of this study waterbirds are defined as those species which are dependent on non­

marine aquatic biotopes for a major life function such as reproduction, cover or feeding. Appendix

2 lists the waterbird species recorded at the farm dams in the Elgin and Overberg regions.

The number of individuals per species present at each dam was recorded on a list consisting of 42

species. Three counts were done per dam: once in the morning before 10:00, once at midday

between 10:00 and 15:00 and once in the afternoon after 15:00. Birds were counted at each dam,

using 9 x 25mmbinoculars· and a 20x spotting .scope, from a location along the edge of the dam

where all or most ofthe surface area and edge was visible (Bibby et al., 1992). The playback of the

calls of secretive species such as Black Crake Amauromis flavirostris and African Sedge Warbler

Bradypterns baboecala were used to detect their presence in dense patches of. bullrushes or

8

reedbeds. On some occasions, surveys were done from distances further away from the dam

~

particularly ifbirds reacted to the presence of the observer.

The duration of each survey encompassed the time required to thoroughly scan a dam, identify and

count all the waterbirds present on the dam. Birds were counted at their point of first detection and

particular care was taken to make sure that birds were counted once only. After completion of the

point count, I walked along the accessible edges of the dam to detect any unseen birds and to do

more detailed counts of high density breeding colonies ·of species such as weavers and bishops.

Birds flying over the dams were not counted unless they landed on the dam. The number of young

in dependent broods was included in the analysis, after it was found that the influence of young on

the analysis was not significant.

Data analysis

Data collected in the field were entered into a computer database from which data sheets for further

analysis could be generated. To investigate the 'carrying capacity' of each dam the cumulative

biomass of the maximum number of birds was calculated, using the mean bird mass data (Maclean,

1993).

Similarities between dams

To compare dams in Elgin with those in the Overberg, a cluster analysis was performed on the

shared physical attributes of dams from both regions. Cluster analyses (Anderberg, 1973; Field &

McFarlane 1968, Clarke & Warwick, 1990) were performed using the Bray Curtis similarity measure

and a group average sorting method. To investigate the similarities further observed in the clusters

and similarity matrix, a non-metric multi-dimensional scaling (MDS) was performed from which

ordination plots were produced (Clarke & Warwick, 1990; Clarke, 1993). From the ordination

plots, the relationships between the dam groupings could be considered in a non-hierarchical manner.

9

The Primer statistical software package was used to performboth the cluster analysis and MDS

(Clarke & Warwick 1990).

Student-Newman-Keuls multiple range tests were used to explore differences between groupings of

dams observed in the cluster analysis and MDS ordinations (Dixon et al., 1990). The Student­

Newman-Keuls test performs a pairwise multiple comparison between the means of each variable in

each group, ranks the groups in order of magnitude, and indicates the significant differences between

the identified groups.

Similar cluster analyses and ordinations were used to analyse patterns of waterbird species richness

and abundance. The Bray Curtis similarity measure proved sufficiently robust for the bird data, is

not affected by joint absences (Field and Macfarlane, 1968), and gives more weight to abundant

species (when comparing samples) than to rare ones, which is what most ecologists do intuitively

(Field et al., 1982). Based on the expectation that birds would favour similar dams during both

winter and summer combined, winter and summer bird abundance data were compared with the

results for the separate seasons. Subsequent Student-Newman-Keuls multiple range statistics were

used to distinguish between species that significantly influenced the observed grouping pattern.

Waterbirds

To determine the associations between the patterns of farm dam utilisation by waterbirds in relation

to vegetation and physical attribute variables, a multiple stepwise regression analysis was performed

using the STATISTICA software program (Statsoft, Inc., 1996). Multiple regression addresses the

question ofwhich independent variable (e.g. vegetation) is the best predictor of a certain dependent

variable (e.g. bird species richness). The statistical procedure involves the fitting of a multiple linear

regression equation in a forward stepwise manner by entering one variable at a time from a list of

potential predictors starting with the variable which explains most of the variability. Investigations

10

into the dependence of species diversity on a farm dam in relation to its surface area were determined

using standard species area relationship techniques. Linear regression techniques within the

STATISTICA software program were used to assess this relationship between dam surface area and

the bird species richness and biomass.

RESULTS

Waterbirds

A combined total of 44 bird species wererecorded at the 59 farm dams in both the study regions

(Appendix 2). Figure 2 presents the number of species recorded in each region during winter and

summer and the mean number of birds recorded at each dam. In Elgin a total of 29 species were

recorded during winter and 33 during summer. The Overberg region hosted' 32 species during

winter and 36 during summer. In Elgin, six additional species were recorded during summer

whereas only two additional species were present during winter. Seven extra species were recorded

during summer and four additional species during winter in the Overberg. The highest number of

species present at a farm dam in Elgin was 13 during winter and 21 during summer, whereas in the

Overberg the highest numbers were 15 during winter and 21 species during summer (Figure 2).

Dam attributes

The 59 farm dams studied displayed a high degree of physical and habitat variation. The average

size of dams sampled in Elgin was 16 877m2 which was significantly larger than the average size of 5

584m2 in the Overberg. This finding corresponds with Berg et al. (1994) who indicated that dams

in Elgin (palmiet river catchment) were larger in surface area than those in the Overberg

(Riviersonderendcatchment) region.

Cluster Analysis used to group all 59 farm dams on shared habitat characteristics suggested that,

although some overlap was evident between the two study areas, two main groupings exist, which

11

separate the two geographical areas. After careful scrutinyof preliminary analysis, 78% of the dams

were used to discriminate between the two main groupings observed in the cluster. The remaining

22% of dams were unresolvedin terms of groupings within the cluster. Cluster branching patterns

which discriminate between Elgin and the Overberg were supported by an ordination plot.

Subsequent Student-Newman-Keuls multiple range tests indicated significant (95%; P < 0.05)

differences for many ofthe shared variables between the two main groupings (Table 1).

40

35

30

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0Elgin Overberg

Regions

o Winter

• Summer

<> Mean no.ofspp/dam

Figure 2: Total number of bird species recorded in both regions during

winter and summer. Also indicated is the maximum,

minimum and mean number of birds recorded at the farm

dams.

12

Table 1: Significant discriminating shared variables between the two geographical regions, showing

the mean for each variable and the significance level. * Indicates the higher mean value.

illll!II!!I!!!!I!I!I!illll!I!!IIII.IIIIIIIIIIIIII!!!II!11111!llllll!!11111111111111111.1111!11!llllll 1111111111111!111/lllllllllllll!Water level (%) *90.23 76.25 0.05

Inlet/outlet (count)j

*2.14 1.45 0.05

Bare bank (%) 3.64 *15.75 0.01

Beach (%) 3.18 *13.25 0.01

Stream (presence absence) 0.05 *0.41 0.01

Bullrush patches (count) *1.86 0.50 0.01

Edge short sparse grass (%) 2.27 *8.50 0.05

Edge short dense grass (%) 6.14 *25.00 0.01

Bank tall sparse grass (%) 2.27 *20.25 0.01

Edge 'tallsparse grass (%) 1.36 *7.75 0.05

Bank tall dense grass (%) 6.59 *32.50 0.01

Edge tall dense grass (%) 9.09 *22.00 0.05

Edge bullrushes (%) *26.59 3.25 0.01

Bank indigenous shrub (%) *12.27 0.00 0.01

Bank exotic shrub (%) *18.64 1.00 0.01

Eucalyptus.(presence absence) 0.00 *0.30 0.01

Exotic trees (%) *22.27 1.50 0.01

Overhanging trees (%) *8.18 2.25 0.01

Dead vegetation (%) *14.55 1.00 0.01

Dams tn 1km radius (count) *15.05 8.20 0.01

Power-lines (presence absence) *0.36 0.05 0.05

Field/grazing (presence absence) 0.00 *0.45 0.01

Subsequent seasonal comparison between the farm dams in Elgin with those in the Overberg

required detailed analysis of both the physical attribute and habitat data as well as the avian

abundance data for each farm dam. Dendrograms from the Cluster analyses and corresponding

ordination plots are presented in Appendix 3 for Elgin and'Appendix 4 for Overberg.

13

Table 1: Significant discriminating shared variables between the two geographical regions, showing

the mean for each variable and the significance-level. * Indicates the higher mean value.

1IIIIlll!!ll!II!IIII~llllllllllllt.lllil.1111111111111IIIIII!III!IIIIIII!IIII 11111111111111111111111111111llllilllll!1!111!1!!lllll!!!!!1Water level (%) *90.23 76.25 0.05

Inlet!outlet (count) *2.14 1.45 0.05

Bare bank: (%) 3.64 *15.75 0.01

Beach (%) 3.18 *13.25 0.01

Stream (presence absence) 0.05 *0.41 0.01

Bullrush patches (count) *1.86 0.50 0.01

Edge short sparse grass (%) 2.27 *8.50 0.05

Edge short dense grass (%) 6.14 *25.00 0.01

Bank tall sparse grass (%) 2.27 *20.25 0.01

Edge tall sparse grass (%) 1.36 *7.75 0.05

Bank tall dense grass (%) 6.59 *32.50 0.01

Edge tall dense grass (%) 9.09 *22.00 0.05

Edge bullrushes (%) *26.59 3.25 0.01

Bank indigenous shrub (%) *12.27 0.00 0.01

Bank exotic shrub (%) *18.64 1.00 0.01

Eucalyptus. (presence absence) 0.00 *0.30 0.01

Exotic trees·(%) *22.27 1.50 0.01

Overhanging trees (%) *8.18 2.25 0.01

Dead vegetation (%) *14.55 1.00 0.01

Dams tn 1km radius (count) *15.05 8.20 0.01

Power-lines (presence absence) *0.36. 0.05 0.05

Field/grazing (presence absence) 0.00 *0.45 0.01

Subsequent seasonal comparison between the farm dams in Elgin with those in the Overberg

required detailed analysis of both the physical attribute and habitat data as well as the avian

abundance data for each farm dam. Dendrograms from the Cluster analyses and corresponding

ordination plots are presented in Appendix 3 for Elgin andAppendix 4 for Overberg.

13

Elgin dams physical attributes and habitat variables .

Cluster analysis for the Elgin farm dam physical attributes and habitat variables, revealed clear

groupings of various dams for data fro~ both seasons. More vegetated groups of dams in winter

were quantified by, especially emergent edge vegetation and bul1rushes around the dam. In contrast,

more sparsely vegetated dams in winter, grouped separately to the right along the x-axis scale and

are characterised by sparse or no vegetation cover around the dam perimeter and on the

embankment. During summer, the more vegetated dams were characterised by bullrushes and to a

lesser extent by aquatic vegetation. The dams grouping at the base of the x-axis were significantly

characterised by exposed shoreline.

Overberg dams physical attributes and habitat variables

Thephysical attributes and habitat variables of the Overberg dams during both seasons separated

distinct groups through cluster analysis and in MDS ordinations. During winter more vegetated

dams emerged as clear groups at the lower end of the x-axis of the ordination. Acorresponding

increase in surface area and exposed shoreline was observed along the x-axis. Aquatic vegetation

results in some additional groupings in the central area of the ordination. Dams with high levels of

disturbance grouped at the upper end of the y-axis of the ordination. Habitat variables such as

bullrushes along the edges and bank of the dams in comparison to reeds divided the more densely

vegetated dams during winter into two distinct groups. During summer opposite trends were

however observed. Dams with more dense vegetation cover grouped at the upper end of the x-axis,

while dams with bare banks and.open shorelines grouped at the lower end of the x-axis. These

observations are supported by significant differences (P < 0.05) between the dams grouping along

the upper end of the x-axis in terms of bullrushes,emergent edge sedges, and short dense grass

around the dam.

14

Cluster analysis for bird observation data

The Cluster analysis on bird abundance data delineated groups of dams based on different species

and the number of individuals present at each dam. If no significantly distinct species could be

identified for the grouping pattern the groups with maximum mean number, indicated by the Student-

Newman-Keuls multiple range statistic, were used to give some estimate on the uniqueness of each

group.

Elgin Birds

Cluster analysis and subsequent :MDS ordinations on the number of individual birds of different

species observed at each dam revealed distinct groupings. Data were analysed separately for both

seasons as well as a combination for winter and summer. No groups of dams were significantly

different in terms of a specific species during winter. Differences, although not significant, do

however exist between groups for various species. The Moorhen Gallinula ehloropus showed an

increase in mean number of individuals observed along the x-axis of the ordination. Groups with

high incidence of individuals of a specific species are located in the centre of the ordination.

Waterfowl such as Egyptian Goose Alopoehen aegyptiaeus, Yellowbilled Duck Anas undulata and

African Black Duck Anas sparsa form part of the species found in these central groups. During the

analysis of summer data the Student-Newman-Keuls multiple range statistic revealed several species,

which showed significant differences interms of abundance between different groups of dams. High

mean occurrences of Sacred Ibis Threskiornis aethiopieus, Hadeda Ibis Bostryehia hagedash,

Spoonbill Platalea alba, Threebanded Plover Charadrius trieol/aris, and Blacksmith Plover

Vanellus armatus clearly described a group. Five dams formed a group which supported the largest

assemblageofpiscivorous birds. Combining both the winter and summer bird count data at the

dams in Elgin clearly separated dams characterised by low bird counts during both winter and

~.

summer from groups with higher bird diversity. Dams forming distinct out-groups are possibly

avoided due to their small size and close proximity to other dams with more preferred habitat.

15

Overberg Birds

Cluster analysis and subsequent MDS ordinations ofbird observation data during winter and summer

in the Overberg region illustrated distinct groupings. High mean occurrences of Malachite

Kingfisher A/cedo cristata and African Sedge Warbler characterised a significant grouping of several

dams during winter. A clearly delineated group is recognised by high mean occurrences ofEgyptian

Goose, Yellowbilled Duck, and Red Bishops Eup/ectes orix. During summer in the Overberg, the

presence of the common Cape Wagtail Motaci//a capensis significantly explained an especially

species rich grouping. Apart from delineating a specific group of dams the number of Redknobbed

Coot Fu/ica cristata increased in mean abundance along the x-axis of the ordination. The presence

of Threebanded Plovers, which require exposed shoreline for feeding, also significantly explained the

delineation of a group. When combining bird abundance data for both winter and summer, groups

of dams with high species diversity lie at the upper end ofthe x-axis ofthe ordination. These groups

are significantly defined by species such as Blacksmith Plover, Grey Heron Ardea cinerea, and

Brownthroated Martin Riparia paludicola. The presence of high numbers of Spurwinged Goose

Plectropterus gambensis clearly explains a group.

Stepwise regression

Stepwise regression on the physical attributes and habitat variables of the dams in the two

geographic areas' determined which variables have the greatest influence on specific dependent

variables. Dependent variables selected for investigation included species richness, total number of

all birds present on the dam, and bird biomass. These dependent variables were investigated for

both summer and winter in the two geographic regions.

16

Table 2: Stepwise multiple regression on waterbird data (Elgin n = 28; Caledon n = 31). Only variables which met the minimum tolerance ofO.OOl are represented up to a level after

which an added independent variable failed to increase the multiple R2 by at least 0.05. The sign (+ or -) indicates whether the specific independent variable is positively or

negatively correlated with the dependent variable

Surface (+) 0.318 1.1x10-7....

Bank herbs (+) 0.560 7.5x10·e....

Houses (-) 0.712 0.0001....

Dams in 1km radius (-) 0.807 0.0001....

Bare bank (-) 0.840 0.0001 ***.

Surface (+) 0.538 5.3x10-6 -*••

Roads (-) 0.641 1.0x10·5 .-*-Dead vegetation (+) 0.711 2.2x10.5 ----Water colour (+) 0.792 0.0001 ----Average distance of dams (-) 0.841 3.5x10·5 •• *-

Water colour (-) 0.362 0.0029...

Bank reeds (+) 0.522 0.0020...

Surface (+) 0.716 0.0052...

Number of bullrushes (-) 0.831 0.0103..

Wheat (+) 0.860 0.0031...

Surface (+) 0.698 0.0008....

Poplar (-) 0.762 0.0018...

Edge short sparse grass (+) 0.812 0.0012...

Roads (-) 0.860 0.0007 ..*.

Beach (+) 0.266 1.6x10-6-*_.In &outlets (+) 0.454 0.0053 ...Edge reeds (+) 0.611 0.0002 ----Depth (+) 0.694 0.0158··

Bank bullrushes (+) 0.742 0.0424 ..Surface (+) 0.407 1Ax1()"7 ....Bank Reeds (+) 0.542 0.0083

...Aquatic vegetation(+} 0.632 0.0190

..Bank trees (+) 0.675 10.0098

...

Species Richness

Biomass

Biomass

Species Richness

Number of Birds

'­~1-----------t-=-=~:"':'::'::"::'='~--------i--.;:..;.....-.,;;"..+----t--1

c:~I-- --+-=-=J..::::.::.::":"=:~:..:.:.:..l....!--__-I-_~~__-+--t

L. Number of BirdsQ)

EEI-----------t----..:.-L.-------I-----4----4---l::J(/)1-----------f-------1--...!.---------1I---.-,;.;..~_+_------+____l

Depth (+) 0.267 0.0368 ..Bare bank (-) 0.429 0.0002 ****

Bank bushes (-) 0.535 0.0040 ...Bank herbs (-) 0.627 0.0093 ...Dams in 1km radius (+) 0.687 0.0350 ..Bank reeds (+) 0.713 0.1871

Beach (+) 0.189 0.0929 ..Bare bank (-) 0.314 0.0024 ...Edge herbs (+) 0.388 0.2761

Bank herbs (-) 0.443 0.0189 ..Bank bushes (-) 0.509 0.0405 ..Dams in 1km radius (+) 0.598 0.0484 ..Depth (+) 0.364 0.0094 ...Edge sedges (+) 0.502 0.0118 ..Aquatic vegetation (+) 0.655 0.0092 ...Beach (+) 0.708 0.0096 ...Edge bushes (-) 0.743 0.4157

Surface (+) 0.294 0.0002 .._-Edge bullrushes (+) 0.487 0.0003 .*_.Natural Vegetation (-) 0.600 0.0003 •• *-

Orchard (+) 0.655 0.0005 ._*.Beach (-) 0.692 0.0003 ....Surface (+) 0.585 2.3x10·5 ** ••

Nat vegetation (-) 0.660 0.0001 •• *.

Oak (+) 0.728 0.0002 ****

Wattle (+) 0.762 0.0001 .*-.

Surface (+) 0.497 0.0002 •• *-

Natural vegetation (-) 0.599 0.0001 .-..Eucalyptus trees (+) 0.652 0.0001 ****

Stream (+) 0.700 0.0003 .***

Number of Birds

Species Richness

Biomass

Number of Birds

Species Richness

Biomass

L.(1)

EE::J

(/)

Significance levels: • P < 0.10 •• P < 0.05 .** P < 0.01 •••• P < 0.001

Stepwise regression selected farm dam depth as the independent variable with the greatest influence

during winter in Elgin. Waterbird species richness and biomass bothare positively correlated with

depth of farm dams. Various levels of ~egetationcover along the edge and bank of the dams had a

significant influence on bird abundance. Exposed shoreline was positively correlated with the total

number of birds present at each dam. Surface area had the greatest influence during summer in

Elgin. Surface area was positively correlated with the three dependent variables. Species richness

~t .the dams during summer also depended on bullrushes along the edge of the dam. Further

variables which entered the regression equations included natural vegetation (negative correlation)

and various alien tree species (positive correlation). Natural vegetation around the farm dams was

not an important factor in determining the presence of waterbirds thus indicating the ability of the

species to adapt to a transformed habitat.

When combining winter and summer data for the Overberg, surface area was again highlighted as the

independent variable with the greatest influence. Surface area was positively correlated with both

total numbers of birds and biomass. Exposed shoreline was associated with species richness of

waterbirds at the farm dams. Other variables which subsequently entered the regression equation

included various degrees of vegetation cover around the dams with positive correlations with bird

numbers, biomass and species richness. The number of inlets and outlets present at each dam also

significantly influenced the presence of species at the dams. In accordance with results for Elgin,

surface area was also highlighted as an important variable during summer in the Overberg region.

The number of birds present at each dam highlighted water turbidity (negative correlation) as the

most important determining variable while reedbeds around the dam and surface area also had a

significant influence.

18

Species area relationships and island biogeography effects

Stepwise multiple regression analysis clearly indicated that the surface area of farm. dams have a

significant influence on the occurrence of waterbirds in both regions. Further analysis investigating

the relationship between species diversity, bird biomass and dam surface area was subsequently

performed. Preliminary investigations were carried out to determine the possible effects of dam

isolation on bird species richness.

Species richness in relation to the surface area of the dams using log transformed data produced

scatter-plots to which a regression line was fitted thus estimating the variability of the values around

the regression line. For both regions, a positive correlation was observed for species richness in

relation to the surface area of the dam. In Elgin, correlations reflected a relatively high degree of

variability during the winter with only 39% (R2 = 0.385; P < 0.01) of the original variability

explained by the linear regression line (Figure 5a). Residual dams influencing this high degree of

variability were dams where no birds were observed. The above mentioned dams are far smaller

than the average dam size in Elgin. Other dams, which also influenced the high degree of variability,

were dams where only one species was observed. A lesser degree of variability (R2 = 0.36; P <

0.001) was however explained by the regression line during summer where only dam one contained

no birds (Figure 5b).

In the Overberg region a similar pattern was observed, where in winter a regression line explained

only 26% (R2= 0.257; P < 0.01) of the original variation (Figure 5c). This can once again be

ascribed to the fact that no birds were observed at residual dams which are characterised by a small

surface area and unfavourable habitat conditions for avifauna. Various dams are however also

represented by .only a single species and thus add to the variability of the data. The situation

changed dramatically for the summer data, where less variability was observed at 69% (R2 = 0.69; P

< 0.0001) by the regression line (Figure 5d). Birds were recorded at each dam during summer thus

explaining the lesser degree ofvariability observed in the data.

19

'.5 Logbildbiorna•• = 1.0' Log surracear.. • 0.4 6.. ; R' = 0.32 P < 0.01 .j............... ..·~OO'..

4 ~ , , :d.o........... i 0 ..

• 3.5 · · ..f 'O (j~.·..·O'··..··_···.~· ..~ ! ..I ':~ 3 ·.. · · .. ·..r · ·..· -;-.... ..·· ·..··1· • · ·, .i z.5 +........ .. ;.. ;

!.~:~::~+~::~~:t:~~-t:_\t::~::-2 U U U U

Log*Ulface ar•• (mz)

e) Log linear relationshipbetween bird biomes.sand the surt8ce area of the Elgindams duringwinter

4.8•••1.8o

1 2.8 3.4

Loa---Im;a) Log linear relationship between species richness and the surfilce area of tile Elgin

dams duringwinter.

....3.83.22.6

3-l-----~-----+ .;..,......-__-i- ....j

2

Log surface area (mz)

f) Loglinear relationohipbetween bird biomass and the surface areaof the Elgindams during summer.

3.2

3.'

4.43.83.2•. 6

0-l------....;..-_----i--__,,;.-. -;..- -1

2

Log ourfac. or.. I.... '

b) Loglinear relationshipbetween species richness and the surface area of the Elgindams during summer.

i 0

1.. .. LogSpeeles~cIlness=0.27 • Logswtace area· 0.21 j.o o + oo o .R'=0.36 P<0.001 10:

I0.: ::::::::::::::::::::::J::::::::::::::::::::f::::::::::::::·····:.~:::::::::::~::::.l.~:::::::::::::::::::.~ : o· o :~ 0.6 .. ·· ..~ <>..· ··1..·..·..·..·..· ·+ ··...J 0.4 l ~..L ~ L...~ l ~ .

0.. ..· ·..·~·..·..·..L. ·..·· L...· ·~·..· I ·..···· ~ .; :

'.5

, ,: :

·~·o··f······..........·+·,o..···....·--·. ,. ... ~ ..• OO ~.--~ .

-······r··················

3.5

o

o

z,5

log bird biomass =0.9 • Log surface area + 0.55 __ R'= 0.40 P < 0.001

2 ·.. -- •..T..· -- ; .1+-.---+---.....;....----i----...j -i-__---l

24.63.4

Log surface area em2)

2.8o2.2

1.6r-----,----;:::==============;-ii Log Species richness=0.38 • LogSlIfacearea. 0.691.4 .. • · · .. ·: ·R'=O.26 P<0.01

1.2 i··· ·..·I.,.. -·-q..;·-..-..-··- oo-..·-..-..o-·o-·j -..-..·-..-..- · -·..-··: -· · ..

I0.: :::::::::::.::::::::::::I::::::::::::~::::::::::J:::::::~::::::::::: j::::::~::::::::: ~ ..l 0.6 L O- ~o : : :go 0 0 : .. · ~ .. · 1 · · j ..

~:: ·_···_·············-,~T:F:··_:;··

c) Loglinear relationshipbetween species richness and the surface area of the Overbergdams duringwinter

g) Loglinearrelationship between bird biomass and the surface area of the Overbergdams duringwinter.

d) Loglinear relationship between species richness and the surface area of the Overbergdams duringsummer.

e e

o

..: ] --0 [ -- + ~ .

··..·..·:..··0·..·....··10······..···: 0 '0 a....i:i0 ~: : ,., 0,

,..

o

··_········ f - j.•......•...._._~ ······_·····~_···· ·._ t _._ -:-.

2J.----:------i-__........;'--__-i-.-__-!.--__-:.__-12

~ lao b"'Cbiomoss" 0.49 • log surraca 2.14 04,5 ·············-1··~······· .."'-·-0-1-P_<-OOOO-'-_--- ..1··0.. - ~ _" t.- .

2.5 •• __. _•••••••••• ~ •••••

3.2 3.6

L08.~• .,.. (m')

h) Loglinear relationohip between species richness and the surface area of the Overbergdams during summer.

j'0 3.5

i!

32 3.8

Loesurfac...... (m'l"

14 1'" LogSpeciesrichness =0.39' Log\\lilac. area -0.49 + .R' = 0.69 P < 0.0001 :

12 , , Q O.

: : 0 00, 0

I.: .......•••••.•.•.••:r.....••••.•~:·t-:·:1°:L:0' .. OO.. O..;. ~ 'J:::: :.: :::: ::::~' :: .. :.:::::::::::::o. .. ·.. ··: ~ r .0.' ,

Figure 5: Linear regression analysis between 1) the species richness and surface area of the farm

dams (a - d), and 2) the total bird biomass and surface area of the farm dams (e - h) for

winter and summer in both regions.

20

Similar analyses for total bird biomass present at each dam showed positive correlation with dam size

during both seasons in both regions. Linear regression analysis for Elgin during winter explained

32% (R2 = 0.32;P <0.01) of the observed variation (Figure 5e). The high variability can again be

ascribed to the dams where no birds were observed. During summer, the regression line explained a

higher 48% (R2 = 0.48; P < 0.0001) of the variability (Figure 5f). Dams still influencing the 52%

unexplained variation were those with a small sutface area and low total numbers of bird species

present. 40% of the variation (R2 =0.40; P < 0.001) in the Overberg during winter was explained

by the regression line (Figure 5g). Dams that influenced this high degree of variability were those

where no birds were observed. Regression analysis on biomass in relation to dam sutface area for

the summer data explained only 41% (R2 = O. 41; P < 0.0001) of the variability in spite of the fact

that birds were recorded on each dam (Figure 5h).

A regression analysis was used to determine a possible relationship between species richness and the

number of dams in a 1 km radius around a particular farm dam. Island biogeography theory

suggests that more isolated patches support less diverse species assemblages. These analyses,

however, revealed no significance (Elgin summerR2 = 0.004 P< 0.9; Overberg summer R2 = 0.03, P

< 0.4) in terms of isolated dams supporting fewer species. This indicates that dams function

autonomously as a functional unit or that the waterbird community does not suffer from the effects

of isolation due to the extremely high number of dams in the habitat matrix.

DISCUSSION

It is evident that farm dams contribute significantly to supporting. waterbird communities in both of

thestu4yregi()ns.. Guillet and Crowe (1984) and Winterbottom (1972) hypothesised the importance

of artificial impoundments acting as ecological substitutes for natural wetlands in the Western Cape.

Although a proportion of the waterbirds observed at the farm dams can be classified as generalists,

that would be able to exploit marginal habitat conditions, the farm dams do however support a

21

diverse assemblage of waterbirds. To make conclusions on why waterbirds prefer specific farm

dams the results obtained from investigating seasonal variation in waterbird abundance are evaluated.

These results are subsequently used to compile some recommendations on how to improve farm

dams to enhance their contribution to supporting diverse waterbird populations.

The Elgin Area

Dams in Elgin with a high percentage of vegetation cover were frequented by Redknobbed Coot,

Black Crake and Moorhen during both winter and summer. Wading species such as the

Threebanded Plover seem to prefer dams with a mixture of vegetation and exposed shoreline. Dams

with vast exposed areas such as bare embankment and exposed shoreline were negatively correlated

with avian abundance. During winter, an increase in edge vegetation around the dam outlined a

positive correlation with species richness, abundance and bird biomass. Shrub vegetation on the

embankment, however, displayed a negative correlation. Bullrushes at the edge of the dams had a

significant influence on waterbird diversity, creating habitat for species such as Black Crakes and

Cape Reed Warblers Acrocephalus gracilirostris. Research conducted by Losito and Baldassarre

(1995) illustrated a similar correlation between wetland basins dominated by emergent vegetation

and. their. importance. to. waterbirds. Natural vegetation around the dams showed a negative

correlation with bird diversity indicating the ability of waterbirds to exploit transformed biotopes.

Other variables such as specificvegetation types or invertebrates that serve as preferred food sources

would also have a significant influence on waterbird distribution.

22

Structural diversity in vegetation and the productivity of a wetland plays a fundamental role in

determining the abundance of waterbirds around a farm dam (Colwell & Lodd, 1994; Paquette &

Ankeney, 1996). The overall trend observed in Elgin corresponds with this finding to the extent

that the cluster analysis and stepwise regression showed a general increase in bird diversity in relation

to an increase in structural diversity around the dam. This influenceof structural diversity of a farm

dam becomes particularly clear when investigatingbird abundance for both seasons. Dams with low

structural diversity around the water's edge and on the surrounding embankment form a distinct

group which is clearly distinguishable from dams more preferred by avifauna.

The Redknobbed Coot prefers dams with an abundance of its main food supply aquatic vegetation.

Numbers of Redknobbed Coots in relation to the area of wetland may be a useful indicator of the

health of wetlands with open-water habitat - the more coot the healthier the wetland (Lamont,

1996). Healthy wetlands tend to have underwater plants and grass verges which are the coot's main

food sources (Maclean, 1993). Lamont (1996) observed a dramatic fall-off in coot numbers on the

Paardevlei dam in the Western Cape. The decline in numbersis ascribed to the eutrophication of the

dam, which resulted in an algal bloom that destroyed the food source of the coots.

The number of species and the biomass of birds present at dams in Elgin showed a positive

correlation with surface area throughout the year. In winter, waterbirds concentrated on deeper

dams while in summer, when overall water levels were higher, waterbirds preferred dams with larger

surface area which provided more suitable food resources in shallow submerged areas. Wetlands

with more shallow area are more productive than deeper wetlands due to the effect of available light

penetration. Patterns of habitat use and morphology dictate that each waterbird species has a

general limit to potential food resources (paquette & Ankeney, 1996). Species such as Yellowbilled

23

Duck feed primarilyby dabbling or tipping, and their use of shallow wetlands thus reflect a response

that facilitates feeding on benthic food resources.

A common conclusion for the Elgin area would be that waterbirds prefer farm dams exhibiting a high

degree of structural diversity and inhabit less suitable dams only when they are forced into them by

overcrowding.

The Overberg Area

A high diversity of waterbirds present at dams in the Overberg seems to be a direct effect of the

surface area of the dam as this is indicated by both the ordinations (Appendix 4) and regression

analyses (Figure 5). Patterson (1976) illustrated as in many other studies that the total number of

birds that agricultural ponds can accommodate is primarily a function of the pond surface area.

Dams with a larger surface area, a higher degree of exposed shoreline and bare embankment, are

characterised by higher waterbird species diversity. Regression analysis also supports the positive

correlation between species richness and some exposed shoreline. The number of inlets and outlets

present at each dam also significantly influenced the presence of species at the dams. This in part

corresponds to the findings of Murphy et ale (1984) who indicated that ponds of eastern Alaska

which were hydrologically connected to a stream system had greater use by waterbirds as well as

higher levels of most nutrients and ions than isolated ponds. The presence of aquatic vegetation

corresponds to the occurrence of Redknobbed Coots. Disturbance at or near the farm dam seems

to significantly influence the presence of waterbirds, both the species diversity and the total number

of birds. The presence of roads near the dams results in a significant negative correlation with bird

diversity, especially during summer. This is also supported by the cluster and ordination for

combined winter and summer data where roads and the level of livestock grazing is linked to a low

diversity of birds present at the dams.

24

During summer, the maximum species diversity grouping overlaps with a cluster in the dam

attributes ordination,'. which is significantly delineated by surface area. The same cluster is

characterised by short-dense grass along the edge of the dams and taller grass and sedges on the

embankment. This' illustrates the preference ofwaterbirds for more open and accessible dams in the

Overberg, in comparison with Elgin, where dams with a higher degree of structural diversity and

some tall emergent edge vegetation were preferred. In support of the observed preference for short

edge vegetation in the Overberg, Colwell and Lodd (1994) illustrated an inverse relationship between

vegetation height and waterbird diversity. They suggest that waterbird diversity could be increased

by directly manipulating grazing regimes to create a landscape mosaic of pastures with varying

vegetation heights and flooded conditions.

When combining data from both seasons a clear relationship exists between the bird specres

abundance and favourable dam characteristics. This relationship is explained by shallow dams with

dull murky brown water and little noteworthy vegetation, which does not support a high diversity of

waterbirds. This is further verified by the multiple regression results, which identifies surface area as

the most important driving variable for both seasons.

Reedbed specialists such as the Cape Reed Warbler and the African Sedge Warbler, which grouped

together in terms of abundance, showed overlap with dams ." characterised by a high number of

reedbeds present around the dams. In the combined summer and winter ordination birds with high

biomass such as the Spurwinged Goose, characterised the grouping of three dams. Biomass showed

a significant positive relationship to the size of dams during linear regression analysis, which again

indicated the significant correlation between surface area and presence of waterbirds. Partial

overlap in the ordinations for birds and dam attributes indicated that studied dams with a high

number of surrounding dams correspond to a diversity ofbird species.

25

~ In comparison to Elgin, the ideal Overberg dam is thus characterised by less structural diversity in

terms of vegetation and dam characteristics. The preference for larger surface area is, however,

evident in both regions.

MANAGEMENT IMPLICATIONS

Bethke and Nudds (1995) and Jackson (1987) described dramatic declines in the number of

waterbirds using wetlands. The driving cause behind these observed declines are suggested to be

an increase in agricultural activities, which often destroys both the wetland and the surrounding

natural vegetation. In contrast to the above finding, the Western Cape illustrates that the creation of

artificial waterbodies in agricultural areas can however, increase habitat available to waterbirds both

in terms of providing a food resource and breeding habitat.

The creation and restoration of new wetland habitat is a newly developing science/technology

(Mitsch & Wilson, 1996). Understanding enough about wetlands to be able to create and restore

them requires a substantial training in plants, soil, wildlife, hydrology, water quality and engineering.

Optimism, however, does exist that wetlands, which support a diverse array of wildlife, can be

restored or created.

Various farm dam characteristics have been indicated by the study to strongly correlate with the

presence and diversity of waterbirds. An important ingredient to the success of the farm dam is its

ability to support a diverse and productive botanical community. The initial establishment of

vegetation along the dam margin is an important feature in ensuring subsequent successional

processes (Giles, 1992).·· -Emergentedge vegetation speeds up the process of colonisation by other

species and reduces the problems of erosion. Restoration processes around the dams should aim at

"creating a diverse vegetation structure, which is extremely attractive to a variety of wildlife. Farm

dams in both the study regions are managed primarily for water storage, this often results in dramatic

26

In comparison to Elgin, the ideal Overberg dam is thus characterised by less structural diversity in

terms of vegetation and dam characteristics. The preference for larger surface area is, however,

evident in both regions.

MANAGEMENT IMPLICATIONS

Bethke and Nudds (1995) and Jackson· (1987) described dramatic declines in the number of

waterbirds using wetlands. The driving cause behind these observed declines are suggested to be

an increase in agricultural activities, which often destroys both the wetland and the surrounding

natural vegetation. In contrast to the above finding, the Western Cape illustrates that the creation of

artificial waterbodies in agricultural areas can however, increase habitat available to waterbirds both

in terms of providing a food resource and breeding habitat.

The creation and restoration of new wetland habitat is a newly developing science/technology

(Mitsch & Wilson, 1996). Understanding enough about wetlands to be able to create and restore

them requires a substantial training in plants, soil, wildlife, hydrology, water quality and engineering.

Optimism, however, does exist that wetlands, which support a diverse array of wildlife, can be

restored or created.

Various farm dam characteristics have been indicated by the study to strongly correlate with the

presence and diversity of waterbirds. An important ingredient to the success of the farm dam is its

ability to support a diverse and productive botanical community. The initial establishment of

vegetation along the dam margin is an important feature in ensuring subsequent successional

processes (Giles;·1992). Emergent edge vegetation speeds up the process of colonisation by other

species and reduces the problems of erosion. Restoration processes around the dams should aim at

"creating a diverse vegetation structure, which is extremely attractive to a variety of wildlife. Farm

dams in both the study regions are managed primarily for water storage, this often results in dramatic

26

water level fluctuations. By increasing the structural diversity around the dam the potential does,

however exist to attract more waterbirds. If structural diversity around the dams is thus increased,

it can be hypothesised, .that farm dams will be able to play an even greater role in supporting

waterbird.communities in the Western Cape.

CONCLUSION

Habitat destruction worldwide is resulting in the loss of species and a shrinking of the complex web

of nature. Wetlands are among the most threatened habitats on earth. Remaining wetland habitat

thus requires careful long-term management. It is not sufficient to protect only the remaining

natural fragments, but man made wetlands such as farm dams can, however, also increase wetland

resources for the future.

I thus conclude that waterbird diversityin the transformed habitat matrix of the Western Cape clearly

illustrates the potential importance of these relatively new wetlands. A wide diversity of waterbirds

aggregate on the .dams in the Elgin and Overberg study areas and reinforces the importance of

artificial impoundments to the region's waterbirds. The high number of dams present in the region

ensures variation in the physical attributes of the dams, which is essential in supporting the wide

diversity of waterbirds. Surface area of the dam significantly influences the species richness of

waterbirds encountered. Structural diversity in terms of vegetation is especially important in

determining the waterbird usage of the dam. The availability of a food resource, adequate shelter

and breeding habitat were in many cases important factors in determining the presence of specific

species at the dams. In addition to the few migrant wader species, seasonal variation also influenced

the foraging preferences of waterbirds, with dabbling ducks preferring the shallow submerged shore,

which corresponds to the higher rainfall season.

27

The potential of farm dams supporting a diverse waterbird community in the Western Cape can now

be recognised. Proper management procedures and co-operation with landowners will ensure that

farm dams play an even greater role in the future conservation ofwaterbirds.

ACKNOWLEDGEMENTS

This research was funded in part by grants from SASOL Limited, the BIOCORE program of the

""Foundation for Research Development and the African Gamebird Research, Education and

Development Trust (AGRED). I thank the apple and wheat farmers of the Elgin and Overberg\\

districts, especially D. Bridgeman and J. Fick, for graciously allowing me access to their lands. I

gratefully acknowledge the assistance of Assoc. Prof T.M. Crowe and Dr. R.M. Little for their

assistance with the statistical analyses, general support and constructive comments throughout this

study. I acknowledge the field assistance of M. Mangnall for collecting the winter data. MBB

Consulting Engineers in Stellenbosch generously provided aerial photographs of the Elgin study

region. The Percy FitzPatrick Institute of the University of Cape Town provided invaluable logistic

support.

28

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31

Appendix 1: Precise co-ordinates for the location of each farm dam and the surface area of each

farm dam..

Region Dam Code Latitude Longitude Surface Area (m")

Elgin E01 S 34(110.47' E 019(104.67' 44240E02 S 34(110.56' E 01"9(105.30' 144E03 S 34(110.43' E 019(106.28' 1378E04 S 34(110.36' E 019(106.56' 54743E05 S 34(111.76' E 019°04.49' 55056E06 S 34°11.74' E 019°03.39' 28118E07 S 34(112.12' E 019°03.71' 50907E08 S 34(112.00' E 019(102.95' 6732E09 S 34°11.52' E 019(103.25' 6035E10 S 34°11.50' E 019°03.20' 193E11 S 34°11.33' E 019(103.16' 18424E12 S 34°11.07' E 019°03.15' 28134E13 S 34(111.03' E 019°03.49' 7758E14 S 34°13.35' E019°03.72' 6775E15 S 34(111.19' E 019(102.45' 7578E16 S 34°11.55' E 019(102.62' 57983E17 S 34(112.19' E 019°02.67' 2792E18 S 34°12.18' E 019(102.72' 755E19 S 34°12.29' E 019°02.54' 35618E20 S 34°12.44' E 019°02.52' 1365E21 S 34°12.04' E 019°02.51' 16299E22 S 34°12.63' E 019°02.66' 3014E23 S 34°13.00' E 019°03.39' 6088E24 S 34(113.08' E 019°03.38' 6100E25 S 34(113.33' E 019(103.62' 1755E26 S 34°13.42' E 019(103.83' 10375E27 S 34(112.81' E 019°03.14' 2425E28 S 34°12.96' E 019°02.27' 7920

Overberg 001 S 34°14.11' E 019°15.56' 12426.5002 S 34°13.50' E 019(117.55' 170003 S 34(113.17' E 019(118.70' 937004 534°12.75' E 019°19.93' 1990.5005 S 34°12.85' E 019°19.78' 2341.5006 534(112.49' E 019(120.63' 7397.5007 534(112.71' E 019°20.74' 770.5008 534°13.07' E 019°20.97' 566.5009 S 34°12.72' E 019°21.72' 1325010 S 34°12.61' E 019°22.47' 1410011 S 34°12.68' E 019°22.44' 1167012 534°11.96' E 019°24.25' 4812.5013 S 34°11.95' E 019°24.30' 15845014 S 34°12.08' E 019°23.89' 473015 534°12.71' E 019°24.01' 8469.5016 534°13.40' E 019(123.77' 3573.5017 S 34(114.14' E 019°27.16' 39708018 534(114.73' E 019(127.73' 1521.5019 534°14.95' E 019(127.63' 38536.5020 534(115.65' E 019°27.54' 3471021 S 34°15.84' E 019°27.25' 1597.5022 534°16.26' E 019°27.55' 1755023 534°16.60' E 019°27.19' 954.5024 S 34(116.84' E 019(127.59' 9431025 S 34°16.95' E019°27.64' 894.5026 S 34°15.24' E 019°27.43' 1417.5027 534°14.70' E 019°27:04' 1047.5028 534°14.46' E 019°27.59' 4727029 534°14.88' E 019°28.15' 1682030 534°14.85' E 019°28.41' 1878031 S 34°15.07' E 019°28.57' 4695.5

32 Appendix 1

Appendix 2: Bird species recorded at the farm dams during winter and summer in both regions.

~~<-0 0

0<- ~~~O· ~'lt~ ~'b-~ ~ 0<- ~..;s. ~~

~ ~0q, ~(J ~~~ ~~ 0~ ~O;;

'!)0 fifJ ·~0~~f ~f 0~ 0~

~ ~~ ~e; ~~ ~ O~ O~

8 Dabchick TachybatJtus ruficollis * * * *55 White Breasted Cormorant Phalacrocorax carbo * *58 Reed Cormorant Phalacrocorax africanus * * * *60 Darter Anhinaaruta * * * *62 Grey Heron Ardea cinerea * * * *63 Blackheaded Heron Ardea melanocephala * * * *65 Purple Heron Ardea pUffJUrea *71 Cattfe Egret Bubulcusibis *78 Littfe Bittern Ixobrychusminutus *81 Hamerkop Scopusumbretta * * * *91 Sacred Ibis Threskiomis aethiopicus * * * *94 Hadeda Ibis Bostrychiahaaedash * * *95 African Spoonbill Plataleaalba * * *

102 Egyptian Goose Alopochenaegyptiacus * * * *104 Yellowbilled Duck Anas undulata * * * *105 African Black Duck Anas sparsa * * * *106 Cape Teal Anas capensis *108 Redbilled Teal Anas erythrorhyncha * *112 Cape Shoveller Anas smithii * * *116 Spurwinged Goose Plectropterus gambensis * *168 Black Harrier Circusmaurus *213 Black Crake Amauromisflavirostris * * *226 Moorhen Gallinulachloropus * * * *228 Redknobbed Coot Fulica cristata * * * *248 Kittfitz's Plover Charadrius oecuenu« *249 Threebanded Plover Charadrius tricollaris * * * *258 Blacksmith Plover Vanel/us armatus * * * *266 Wood Sandpiper Trinaa glareola *270 Greenshank Tringa nebularia *428 Pied Kinatisher Cerylerudis * *429 Giant Kingfisher Cerylemaxima * * *431 Malachite Kinatisher Alcedo eristata * * * *520 Whitethroated Swallow Hirundoalbigularis * *533 Brownthroated Martin Ripariapaludico/a * * * *631 African Marsh Warbler Acroeephalus baeticatus *635 Cape Reed Warbler Acrcephalusaracilirostris * * * *638 African Sedge Warbler Bradypterus baboecala * * * *677 Le Vaillant's Cisticola Cisticola tinniens * * * *713 Cape Wagtail Motacillaceoensis * * * *813 Cape Weaver P/oceus eapensis * * * *814 Masked Weaver Ploeeus velatus * *824 Red Bishop cup/eetasonx * * * *827 Yellowrumped Widow cup/aetesceoensis * *846 Common Waxbill cstrilda astri/d * * * *

33 Appendix2

Appendix 3: Dendrograms and corresponding ordination plots for the farm dam attributes and bird

data from Elgin.

Group: 2 3 4 5 6 7

60.

~~

o .Indicates Group• Number

OJ

E13

E21

• El

E6

E12Ell

X-axis

Figure i: Dendrogram produced by cluster analysis and the corresponding ordination plot for dam

attribute data and habitat variables during winter in the Elgin region.

34 Appendix 3·

Group: 7~-..l.:o-.'----.::,,)-Oo--qQJ- U - G ~ ~ U N NUJ LL LJ...J LL UJ LW LU LU UJ

100.

90.

60.

50.

~~

E2

E1C

X-axis

GEl 8

@]

E3[X] • Indicates GroupII Number

Figure ii: Dendrogram produced by cluster analysis and the corresponding ordination plot for dam

attribute data and habitat variables during summer intheElgin region.

35 Appendix 3

Group: 1 2 3 4 5 6 7

100.

90.

80.

70.i;

~60. ~

Vi(I)

~:::l

50. U~

~1XI

40.

30.

20.

10.

E17

E16

CD E2

X-axis

00 • indicatesGroupII Number

Figure iii: Dendrogram produced by cluster analysis and the corresponding ordination plot for bird

species abundance data during winter in Elgin:

36 Appendix 3

70. ~

~~en

60, U)i==

5o:>:

50, ~a:l

80,

30.

90.

40.

100.

-.00-" r-, co ~ '--J co~~:'J~~0J0J0J

LLiLU'-lJl...LJLULUu...JW

5321-o<:OLO'<:t000­WWLULU

Group:r---~-

20,

o -Indicates GroupII Number

26

E3 I]J

E18E25 E23

CIl';;:9 E24>- • E2'!

CE28B E4

E17 E7£19

E20 E2?

IIE~'~,

X-axis

Figure iv: Dendrogram produced by cluster analysis and.the corresponding ordination plot for bird

species abundance data during summer inElgin.

37 Appendix 3

Appendix 4: Dendrograms and corresponding ordination plots for the farm dam attributes and bird

data from the Overberg.

Group: 5CO·('f')O-Nr.....i.O

885588()100.

90.

70.

60,

o -Indicates Group• Number

027()3

014 .. 018J26 09 04

0:11 029 II020 031(J) 016 II'xo:vI

05>- \) 01

06

\J\

("" .

X-axis

Figure i: Dendrogram produced by cluster analysis and the corresponding ordination plot for dam

attribute data and habitat variables during winter in the Overberg region.

38 Appendix 4

Group:

90.

70.

60.

015

o -Indicates Group• Number

02

,.;:j!----~\d

all 026

013

X-axis

Figure ii: Dendrogram produced by cluster analysis and the corresponding ordination plot for dam

.attribute data and habitat variables during summer in the Overberg region.

39 Appendix 4

1 6

100.

90.

,BO.

70.

60.

50.

40.

30.

20.

10.

542 3Group:...---=---

026012

II

028 031013 \ m-Indicates Group I

07 029 II Numberen 018'x 024 010(\3I

Old>- ...OJ 011

014 II09

021 20 05

[ID03

04017 01

06

X-axis

Figure iii: Dendrogram produced by cluster analysis and the corresponding ordination plot for bird

species abundance data during winter in the Overberg.

40 Appendix 4

011

2

..014

3<ONU':tOO- .....~T""¥- ... NNC'.I0000000

<§'ol] 013

X-axis

4

07

5

90.

80.

70.

?=60. i

en

50. ~:::;)

0>"~

40. co

30.

20.

10.

O.

o -Indicates GroupII Number

Figure iv: Dendrogram produced by cluster analysis and the corresponding ordination plot for bird

species abundance data during summer in the Overberg.

41 Appendix 4