Download Meso and Mega-herbivores of Balule

Ecological Report Struwig EcoReserve
by
Wildlife & Ecological
Investments:
Mega-herbivores and impact
on woody vegetation
2012 - 2016
Contents
Introduction ................................................................................................................................ 3
Study Area ................................................................................................................................... 4
Methods ...................................................................................................................................... 5
Habitat assessments ................................................................................................................. 5
Mega-herbivores ...................................................................................................................... 8
Results......................................................................................................................................... 8
Habitat assessments ................................................................................................................. 9
Mega-herbivores .................................................................................................................... 14
Discussion.................................................................................................................................. 17
Recommendations ..................................................................................................................... 17
References................................................................................................................................. 17
Wildlife & Ecological Investments
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Introduction
Wildlife and Ecological Investments (WEI) along with Operation Wallacea has conducted ecological
surveys and biodiversity monitoring in the Struwig Eco-Reserve since 2012. Consistent collection of
data over an extended time period allows for an opportunity to detect trends and patterns. To best
understand the health of an ecosystem we need to 1) monitor the response of organisms to their
environment, 2) examine the response of populations of a specific species to the environment and
considering processes such as abundance and fluctuations and 3) investigate the composition and
structure of communities within a defined area. With this information we are better able to further
examine the processes occurring within an ecosystem.
Ecosystems have a wide range of components each responding to their environment. Complete and
holistic biodiversity monitoring is impossible due to the large taxa representation. It is for this reason
that WEI surveys macro fauna and flora. By surveying key organisms within an ecosystem, we obtain
clues into ecosystem functioning and processes. To date the data that has been collected covers a
wide ecological range and consists of herbaceous, woody vegetation, bird, insects and mammal
surveys. The data has been collected systematically and consistently using the same methods within
the same sampling sites.
Vegetation communities are a critical foundation for determining numerous factors about an
ecosystem. The health of an ecosystem can be determined by the quality of the vegetation particularly
in terms of its function to provide food, shelter and soil stabilising amongst others. Detecting changes
in vegetation quantity and quality influences the available browse and graze for ungulates. When
considering large mammals such as elephants then monitoring of vegetation becomes of high
importance for management. For this reason, WEI conducts habitat assessments and includes
monitoring the impacts on woody vegetation by elephants specifically however other ungulates are
taken into account. Although Struwig Eco-Reserve is an open system with the Kruger National Park,
understanding the impacts of elephants on vegetation may provide insight into the role of elephants
as drivers in an ecosystem.
Elephants are recognised as having distinct seasonal dietary preferences between the wet and dry
seasons (Viljoen et al., 2013). (Owen-Smith & Chafota, 2012). Although we did not directly measure
the dietary components of elephants, we did however monitor the movement, location and the
number of days that they are seen on the reserve. In closed systems elephants have a measurable
constant impact on the habitat, however in an open system where elephants disperse, the localized
effect would be anticipated to be less (Loarie, van Aarde & Pimm, 2009). It is for this reason the WEI
team measures the temporal and spatial scales of elephant interaction with the habitat in Struwig
through habitat assessments and game transects.
The reserve can make use of the data collected and analysed by WEI to review changes over time
particularly pre and during the drought. A drought was defined as occurring when rainfall is below
75% of mean annual rainfall (Vogel 1994). In Limpopo province years of below average rainfall that
were classified as drought were documented as recently as 2002 (Maponya & Mpandeli 2012). The
baseline data can contribute towards understanding the movement patterns and resource use of
mega-herbivores in an open system.
This report supplies information on the trends and data collected between 2012 and 2016. For the
purpose of this report we have analysed vegetation and specific meso-herbivore data (impala and
kudu) and mega-herbivore data, particularly elephants.
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Study Area
Struwig Eco- Reserve is approximately 2,700ha and falls within Balule Game Reserve. The Olifants
River forms the northern border. Ecological surveying began in 2012 in 17 sample sites evenly
distributed across the reserve. The 16 sample sites are each 1ha plots and are GPS geotagged for ease
of relocating (Figure 1). In 2015 we used a different method where nine plots were set up according
to distance from water. The collection of data from 2012 to 2016 has allowed us to obtain benchmark
information to detect trends and patterns. This is particularly relevant in the face of drought and
climatic changes that may impact the reserve. The survey sites are intended to be representative of
the Struwig Eco-Reserve and thus we can use this data and methodology to infer the trends and
patterns on neighbouring properties. When classifying the habitat sites, we used features which are
outlined in the methodology and not floristic classification due to lack of statistical support when
running the data through Primer 7®.
Figure 1: Location of the 1 ha habitat assessment sites surveyed from 2012 to 2016 (except 2015).
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Methods
Habitat assessments
The original 17 sites were randomly selected however due to accessibility reasons one of the sites was
removed. In 2015 the habitat assessments where set up differently from the fixed 16 sites. The sites
were identified using Google Earth at predefined distances from water. Data on the terrain and
landscape (aspect, slope gradient, soil texture and stoniness) of the sites were recorded. After we
identified each site, we classified them into habitat types (Table 1):










Riparian
Dry Riverbed
Flowing River
Dam
Plateau
Crest
Valley bottom
Hill slope
Sodic Site
Koppie
Table 1: Terrain and landscape of the ecological sites where habitat assessments were conducted
between 2012 and 2016 including 2015.
Site
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
S4P1
S4P2
S4P3
S4P4
S5P1
S5P2
S5P3
S5P4
S5P5
Habitat type
Dry riverbed / Riparian
Dry riverbed
Hill slope
Hill slope
Plateau
Hill slope
Dry riverbed / Riparian
Crest
Hill slope
Plateau
Hill slope
Plateau
Hill slope
Plateau
Plateau
Hill slope
-
Wildlife & Ecological Investments
Distance from Olifants River (m)
30 - 100
30 - 100
200 - 300
500 - 1,000
>1,000
>1,000
300 - 400
400 - 500
>1,000
>1,000
>2,000
>2,000
>2,000
>3,000
>3,000
30 - 100
100 - 200
200 - 300
500 - 1000
30 - 100
100 - 200
200 - 300
500 – 1,000
>1,000
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At each of the habitat assessment sites we recorded all woody vegetation over 1 metre tall. Other
data recorded included species name, height class, basal stem diameter, average stem diameter (for
multi-stemmed bushes), the width of the widest point of the canopy, and the extent of elephant and
fire impact (fire data is not featured in this report because of the lack of burning activity in the area).
We recorded impact on vegetation by both meso and mega-herbivores. A qualitative and quantitative
evaluation of elephant and other browser impact was graded according to the Walker Scale (Walker
1976) as detailed below:
TYPE:
CODE:
Pulled or kicked out
A
Pushed over and dead or apparently dead
B
Main trunk broken, is or appears to be dead
C
Main trunk broken but re-sprouting or likely to re-sprout
D
Pushed over but still alive
E
Main trunk tusk-slashed
F
Main trunk debarked (% of the circumference)
*G
Roots exposed and eaten (% of the circumference)
*H
Primary branches broken
*J
Secondary and/or smaller branches broken
*K
None:
Z
*Impact types G, H, J, K must be quantified according to the percentage classes given below. The percentage classes
refer to the percentage of the total canopy volume (J & K) and are estimated. In the case of exposed roots and
debarking of the main trunk (types G & H), the percentage of the root base or trunk's perimeter (i.e. a circle) affected
must be estimated and coded accordingly.
1-10%
11-25%
26-50%
51-75%
76-90%
91-100%
For the purpose of this report we focused on the height categories and species of the woody
vegetation at each site and habitat type. The One-way ANOVA was used to determine if at each site
and habitat type there was an overall change between the years the woody vegetation was measured
in terms of the species and height categories. If a significant difference was found, we used the Tukey
Test to identify where the difference was. Although we measured all woody species, for this report
seven woody plants of interest were focused on because they have been classified in literature as
forming a critical component of elephant diet (Viljoen et al., 2013; Owen-Smith & Chafota, 2012).
These species were:





Vachellia erubesense
Vachellia nigresense
Combretum apiculatum
Combretum herense
Dichrostachys cinera





Grewia bicolor
Grewia flavesens
Grewia monticola
Sclerocarya birrea
Terminalia pruniodes
We used the Chao1 estimator to identify the species abundance at each site and a Chao 2 estimator
to estimate species richness at each site.
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Chao1 with bias-corrected:
SChao1 = Sobs +
𝑓1 (𝑓1 −1)
2 (𝑓2 −1)
Where Sobs is the total number of species observed in a sample, f1 is the number of singleton species
and f2 the number of doubleton species. The variance estimator calculates the degree of uncertainty.
Variance estimator:
𝑓1 /𝑓2
)⁴
4
𝑓
𝑓1 /𝑓2
)² ]
2
+ (𝑓1 )³ + (
var(S1) = f2 [(
2
To estimate the species richness, we used Chao2 which uses the occurrence data from multiple
samples (sites) to estimate the species diversity of the area.
Chao2:
𝑚 −1
𝑞 (𝑞 −1)
) ( 21(𝑞 1+1) )
𝑚
2
SChao2 = Sobs + (
Where m represents the total number of samples, q1 is species only occurring in one sample and q2
the species occurring in two samples. Similar to Chao1, the variance estimator calculates the degree
of uncertainty.
Variance estimator:
𝐴 𝑞
2 𝑞2
𝑞
𝑞2
var(SChao2) = q2 [ ( 1 ) ² + 𝐴2 ( 1 ) ³ +
1
4
𝑞
𝑞2
𝐴2 ( 1 ) ⁴]
The impact of elephants on woody vegetation was analysed by generating an impact score (IS):
% impacted = (
𝑠𝑖
𝑁𝑡𝑖
)𝑥100
Where si is the number of trees of the species or height category impacted and Nti is the total number
of trees impacted.
% availability = (
𝑠
𝑁𝑡
) 𝑥 100
Where s is the number of tree species or height category measured and Nt is the total number of trees.
%𝑖𝑚𝑝𝑎𝑐𝑡𝑒𝑑
IS = %𝑎𝑣𝑎𝑖𝑙𝑎𝑏𝑖𝑙𝑖𝑡𝑦
If the resulting IS value is < 1.00 then there was no selection, if the value is >1.00 this demonstrates
selection. If the species was impacted but not selected for then it was likely because of availability
and not for preference. To verify this, we used the Jacobs’s Index.
We also used the Jacob’s Index to identify if there was a preference for either a species or a height
category:
D=
𝑟−𝑝
𝑟+𝑝−2𝑟𝑝
Where r is the proportion of the impacted trees by elephants in a year and p is the proportional
availability of each species given the total trees sampled. The resulting values range from +1 which is
maximum preference and -1 which is maximum avoidance.
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Mega-herbivores
The mega-herbivores that were monitored included elephant, buffalo and both black and white rhino.
During game transects and drives through the reserve details regarding the observation of these
mega-herbivores was recorded. This included the local, group size, age and sex ratios. The habitat that
the animals were in was also recorded. This was divided into wet (between October and April) and dry
season (between May and September) determined using rainfall data for the area from literature
(Figure 2). The wet season rainfall is critical because it controls the vegetation growth and the annual
food production for herbivores. Rainfall during the dry season helps to extend food availability for
herbivores during the critical time when resources are scarce. For this reason, we used both the
seasonal and annual rainfall patterns for the analysis.
We identified the total number of days that drives were taken and the number of days each of the
mega-herbivores were seen. This allowed us to estimate the number of days the animals were likely
utilising the habitat. We used the proportion of days seen and not the total numbers to compensate
for days when no drives were conducted.
120.0
Mean Rainfall (mm)
100.0
80.0
60.0
40.0
20.0
0.0
Figure 2: Mean monthly rainfall (mm) from data collected in 2012 to 2016.
Results
Annual mean rainfall in the area is 492 mm therefore a drought at 75% below the mean was defined
at 123 mm (Vogel 1994). Below average rainfall that was classified as drought was reported in 1997,
2002 and more recently in 2016 (Figure 3). From the start date of data collection in Struwig, the annual
rainfall has been steadily declining (Figure 4). Although rainfall data collection for 2016 is not yet
complete, at the time of writing this report the mean rainfall was already within the drought category.
Struwig is an open system most herbivores have the ability to relocate to other areas where resources
may be greater. When we analysed the rainfall data, animal movement and frequency of observation
during game drives we could better identify trends and patterns.
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300.0
Mean rainfall (mm)
250.0
200.0
150.0
100.0
50.0
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012/2013
2013/2014
2014/2015
2015/2016
0.0
Figure 3: Mean rainfall in with drought being defined as 75% mean annual rainfall as indicated with
the orange line.
250.0
Mean rainfall (mm)
200.0
150.0
100.0
50.0
0.0
2012/13
2013/2014
2014/2015
2015/2016
Figure 4: Mean rainfall (mm) during WEI study periods, between 2012 and 2016.
Habitat assessments
When we compared the methodology of habitat assessments between the I ha plots and the 15 x 15m
plots of 2015. When the methods were compared they both indicated similar patterns of woody
vegetation abundance. However, overall the 15 x 15m plot did not sufficiently reflect the richness and
diversity. In regards to impact on the vegetation, the methods were comparable.
The total number of sites measured each year differed slightly due to accessibility, the number of
people available and other unforeseen circumstances (Table 2). A total of 87 tree species was recorded
between 2012 and 2016.
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Table 2: Number of sites measured each year between 2012 and 2015 and the number of trees
measured at each site.
Year
2012
2013
2014
2015
2016
# of sites surveyed
10
16
12
9
8
# of trees measured
425
747
685
160
268
# of species
41
38
48
20
34
Of the trees measured there was greatest representation in the 1-2 m and the 2-4 m height category
for all years (Figure 5). Trees below the 4m height category had the greatest impact detected (Figure
6 and 7). We did not detect a significant difference between sites in terms of the number of trees
measured in 2012 (F9,8 = 2.34. p<0.05), 2013 (F9,14 = 1.14, p>0.05), and in 2014 (F9,11 = 0.89 p>0.05) using
the One-Way ANOVA.
500
1-2
450
2-4
400
4-6
350
6-10
300
>10
250
200
150
100
50
0
2012
2013
2014
Available
2015
2016
2012
2013
2014
2015
2016
Impacted
Figure 5: The total number of trees measured that were available and impacted in the different
height categories over the study period 2012 to 2016.
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2.50
Impact Score
2.00
1.50
1.00
0.50
0.00
1-2
2-4
2012
4-6
2013
2014
6-10
2015
>10
2016
Figure 6: The Impact Score of trees measured in the different height categories over the study
period 2012 to 2016.
Number of trees measured
30
25
20
15
10
5
0
S4P1
S4P2
S4P3
1-2
S4P4
2-4
4-6
S5P1
6-10
S5P2
S5P3
S5P4
S5P5
>10
Figure 7: Height of trees measured in 2015 with increasing distance from water (P1 = 30-100m to P4
≥ 1km).
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When comparing the woody species abundance, richness and diversity with distance from water, we
found that according to Chao1 woody abundance increased with distance from water with 3km being
the distinct difference. Similarly, we found that according to Chao2 woody species richness increased
slightly with distance from water again with a distinct difference from 3km. Site 8 and 13 had the
greatest species richness.
Of the 87 tree species measured (Figure 8A) we found that there were seven species that were
preferred, Vachellia erubescens, V. nigrescens, Combretum apiculatum, C. hereoense, Dichrostachys
cinerea, Grewia bicolor, G. flavescense, G. monitocla, Sclerocarya birrea and Terminalia pruniodes. Of
these species using the impact score (IS), in 2012 Combretum apiculatum, Terminalia pruniodes and
Grewia bicolor had the greatest impact. In 2013 Combretum apiculatum, C. hereoense and Sclerocarya
birrea had the greatest impact. In 2014 Sclerocarya birrea and Combretum apiculatum had the
greatest impact scores. In 2016, the data suggests that Combretum heroense and Grewia flavenscens
had the greatest impact (Figure 8B).
To verify if species were selected because of availability or if they were preferred we used the Jacob’s
Index. According to the Jacob’s Index, in 2012 Vachellia nigrescense, Combretum hereoense and
Dichrostachys cinerea were preferred. In 2013 Dichrostachys cinerea and Combretum hereoense were
preferred. In 2014, according to the Jacob’s Index, Combretum apiculatum was preferred and in 2015,
according to the Jacob’s Index, Vachellia erubescens and V. nigrescense were preferred.
From the data collected we began to compare the use of woody vegetation of meso-herbivores and
elephants. We compared the proportion of impact on woody vegetation caused by browsers and
elephants across the years (Figure 9). The extent of impact caused by browsers was generally between
11% and 25 % and classified as secondary branch damage. For this report the elephant damage
categories we focused on were K (secondary branches or smaller branches). We used this category
because it best represents both mega and meso-herbivore feeding behaviour.
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250
2012
200
2013
2014
150
2015
100
2016
50
0
A
2
2012
2013
2014
1
2015
2016
0
B
Figure 8: The total number of each tree species measured in the study period from 2012 to 2016 (A) and the Impact Score of the recorded woody species
cross the study period from 2012 to 2016 (B).
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180
160
140
120
100
80
60
40
20
0
A
B
C
2012
D
2013
E
F
2014
G
2015
J
K
JK
2016
Figure 9: Primary (A-G) damage and secondary (J-K, JK) damage on the woody vegetation by elephants
and browsers during the study period 2012 to 2016.
For ease of assessing and determining the movement of the browsers and the elephants, the sites
were categorised according to landscape features and general habitat characteristics. We were able
to classify the sites into five main categories; Hill slope (slope greater than 30°), Dry Riverbed (Olifants
River), Plateau (similar to plains) and Crest (inaccessible to elephants). We did not conduct a floristic
classification because of the lack of statistical support. Only site number 13 and 8 had statistical
support. According to the habitat types we did manage to categorise, site 8 was classified as Crest.
The lack of statistical support is likely due to the ecological and environmental conditions in the area.
We compared only the secondary elephant impact with the meso-herbivores to determine the
proportion of woody impact per habitat type. In 2012 and 2013, the meso-herbivores had greater
impact than elephants however in 2014 and 2016, the elephants had greater impact (Figure 10). In
2014 and 2016 we were unable to measure the vegetation impact on the crest due to inaccessibility.
Mega-herbivores
The sightings of the mega-herbivores were categorised into the same habitat types as the habitat
assessments and were classified into dominant and secondary vegetation selected. This was then
divided into seasons. The buffalo were predominantly seen in the Hill Slope habitat (55%) and
secondary was in the Olifants River (29%). When divided into seasons, the Hill slope remained the
dominant habitat where the buffalo were seen. The white rhino was predominantly seen in the Hill
slope habitat (80%) and secondarily in the river (14%). There was insufficient data to determine
seasonal preference. The elephant were predominantly seen in the Hill Slope habitat (59%) and
secondarily in the Plateau (27%) and the Olifants River (21%).
Generally, the primary preferred habitat was the Hill Slope and the Plateau. As the secondary habitat
type, the mega-herbivores were generally seen either in the Olifants River and on the Plateau
proportionately.
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100
100
90
90
80
80
70
70
60
60
50
50
40
40
30
30
20
20
10
10
0
0
Dry riverbed
Hill slope
Plateau
Browsers
Crest
Dry riverbed
Elephants
Hill slope
Browsers
2012
Plateau
Crest
Elephants
2013
100
100
90
90
80
80
70
70
60
60
50
50
40
40
30
30
20
20
10
10
0
0
Dry riverbed
Hill slope
Plateau
Browsers
Elephants
Crest
Dry riverbed
Hill slope
Browsers
2014
Plateau
Crest
Elephants
2016
Figure 10: Proportion of woody vegetation impacted by elephants and browsers in 2012, 2013, 2014 and 2016 in the different habitats.
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We counted the number of days the elephants, buffalo and rhino were seen on game transects and
compared this to the mean annual rainfall each year (Figure 11). There was a positive correlation
between the number of days the mega-herbivores were seen on the reserve and the mean rainfall (R
= 0.79) We specifically focused on the elephants so we could compare the impact score against the
amount of time the elephants were seen in the area (Figure 12). There was a positive correlation (R =
0.20) between the amount of impact caused by elephants and the number of days the elephants were
seen on the reserve.
70.00
250
60.00
200
50.00
150
40.00
30.00
100
20.00
50
10.00
0.00
0
2012
2013
Elephant
Buffalo
2014
2016
Rhino
rainfall avg
Figure 11: Proportion of days’ elephant, buffalo and rhino were seen on the reserve between 2012
and 2016 (excluding 2015) and the average rainfall (mm) each year.
100
90
80
70
60
50
40
30
20
10
0
2012
2013
Elephant Days
2014
2016
Elephant Impact
Figure 12: The proportion of elephant impact given the proportion of days’ elephants were seen on
Struwig Eco-Reserve between 2012 and 2016 (excluding 2015).
Discussion
The 1ha plots provided the best data regarding tree abundance, richness and diversity. The 15 x 15m
plots did address the question of impact on vegetation however it did not adequately account the
species richness and diversity.
The data suggests that there was a positive relationship between the amount of time the megaherbivores were seen on the reserve and the mean rainfall each year. This is likely due to water
availability in the Olifants River. The data further suggests that the elephant impact increased as the
number of elephant days increased. As the mean rainfall decreased, the mega herbivores spent more
time on the reserve or near the river. This explains why the damage increased with decreasing rainfall.
Recommendations
From the data collected, measuring the facilitation or competition by elephants and browsers could
be further analysed. We suggest monitoring elephant feeding behaviour through direct observation.
This will allow us to quantify how the elephants are using the habitat as mean annual rainfall
fluctuates. Over the long term we will then better detect and anticipate the elephant impact. Although
we did not analyse the amount of insect damage to the woody vegetation, it may be appropriate to
assess if there is a relationship or pattern of insect impact on vegetation as a consequence of
vulnerability from damage caused by elephants.
We could adapt the methodology of distributing plots with distance from roads rather than distance
from water. At the moment the plot distance from roads is within 200m, this will have to change by
increasing the increments of distance. We will continue to use the 1ha plots as these provide the most
relevant empirical data.
The data collected to date provides an opportunity for future analysis as we continue surveying over
the long term. We currently gather very detailed information from few sites in a small area. The lack
of significance with some of the results is likely due to the lack of data from a larger survey area. From
the data collected and the information provided thus far, we could significantly increase the number
of survey sites throughout Balule Game Reserve so that we can start to develop species distribution
maps and impact scores on vegetation for the wider area. We could then better map species richness
and diversity facilitating the development of a floristic map of the reserve. Furthermore, we could
detect trends and patterns and monitor the health of a greater ecosystem.
The bird life recorded from Struwig was entered and sent to Birds in Reserves Project (BIRP) which is
one of the largest ‘Citizen Science’ projects based at University of Cape Town. The data is used to
identify and collect the occurance of birds in South African protected areas. This data helps to identify
if there are threatened or endangered birds that are nesting or using the area as part of their migration
route. We suggest that in a larger area we can better supply BIRP with data regarding the occurrence
and nesting/breeding activity of birds of interest.
Acknowledgements
Thank you to the WEI team who supervised the collection of the data and the students from Operation
Wallacea who spent time in the field collecting the data.
References
Owen-Smith, N. & Chafota, J. 2012. Selective feeding by a megaherbivore, the African elephant
(Loxodonta Africana). Journal of Mammalogy. 93(3): 698 – 705.
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Loarie, S.R., van Aarde, R.J & Pimm, S.L. 2009. Elephant seasonal vegetation preferences across dry
and wet savanna. Biological Conservation. 142: 3099 – 3107.
Maponya, P. & Mpandeli, S. 2012. Impact of drought on food security in Limpopo province, South
Africa. African Journal of Agricultural Research. 7(37): 5270 – 5277.
Viljoen, J.J., Reynecke, H.C., Panagos, M.D., Langbauer, W.R. & Ganswindt. A. 2013. Seasonal
selection preferences for woody plants by breeding herds of African elephants (Loxodonta africana)
in a woody savanna. International Journal of Ecology.
Vogel, C. 1994. (Mis)management of droughts in South Africa: past, present and future. South
African Journal of Science. 90: 4 – 6.
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