Patterns of Spatial Dynamics and Distribution of African Elephants (Loxodonta africana) in the Central Kalahari Game Reserve, Botswana

Full text

Original research article
Patterns of spatial dynamics and distribution of african elephants
(Loxodonta africana) in the Central Kalahari Game
Reserve, Botswana
Keoikantse Sianga
a,*
, Shimane. W. Makhabu
b
, Victor. K. Muposhi
a
,
Mpho Setlalekgomo
b
, Tebogo Selebatso
b
, Albertinah Matsika
a
, Kelebogile Selala
c
,
Amo. O. Barungwi
d
, Emang Molojwane
b
, Boipuso Legwatagwata
b
,
Maitumelo Losologolo
b
, Oreemetse Dingake
d
, Comfort Nkgowe
c
a
Department of Wildlife and Aquatic Resources, Botswana University of Agriculture and Natural Resources, Gaborone Private Bag 0027, Botswana
b
Department of Biological Sciences, Botswana University of Agriculture and Natural Resources, Gaborone Private Bag 0027, Botswana
c
Department of Wildlife and National Parks, Ministry of Environment and Tourism, Gaborone P O Box 131, Botswana
d
Department of Wildlife and National Parks, Ministry of Environment and Tourism, Ghanzi P O Box 48, Botswana
ARTICLE INFO
Keywords:
Articial water points
Home range
Diel displacement
Movement patterns
Satellite collars
Kalahari
ABSTRACT
The African elephant (Loxodonta africana), once thought to be absent from the Kalahari Desert in
Southern Africa, has recently reestablished or expanded its range into the Central Kalahari Game
Reserve (CKGR), Botswana, with documented occurrences over the past decade. This study ex-
plores the temporal and spatial dynamics of elephants in and around the CKGR, focusing on their
largely understudied movement patterns. Movement and home range data was obtained from two
adult female and eight adult male elephants using GPS/UHF collars. The analysis revealed distinct
seasonal ranging behaviours. Collared females migrated between CKGR and the Okavango Delta
periphery, while collared male showed both migratory and sedentary patterns around articial
water points and Gope mine in CKGR. Some collared male elephants migrated to the Kavango
Zambezi Transfrontier Conservation Area (KAZA) during the wet season, returning to the CKGR in
the dry season. This pattern conrms established migration routes and the emergence of pseudo-
resident male elephants within CKGR. These ndings highlight the importance of management
strategies that integrate water distribution, elephant movement, and human-elephant conicts.
Ensuring ecological connectivity beyond the KAZA region is vital for the long-term survival of
elephants and other key species.
1. Introduction
The movement patterns of large herbivores between discrete seasonal habitats is a global phenomenon (Berger, 2004; Harris et al.,
* Corresponding author.
E-mail addresses: ksianga@buan.ac.bw (K. Sianga), smakhabu@buan.ac.bw (Shimane.W. Makhabu), vmuposhi@buan.ac.bw
(Victor.K. Muposhi), msetlale@buan.ac.bw (M. Setlalekgomo), tselebatso@buan.ac.bw (T. Selebatso), amogotsi@buan.ac.bw (A. Matsika),
lalahditshego@gmail.com (K. Selala), amokeitsile@gmail.com (Amo.O. Barungwi), emolojwane@buan.ac.bw (E. Molojwane), blegwata@buan.
ac.bw (B. Legwatagwata), mlosologolo@buan.ac.bw (M. Losologolo), oddingake@gmail.com (O. Dingake), comnkgowe@gmail.com (C. Nkgowe).
Contents lists available at ScienceDirect
Global Ecology and Conservation
journal homepage: www.elsevier.com/locate/gecco
https://doi.org/10.1016/j.gecco.2024.e03284
Received 17 May 2024; Received in revised form 3 November 2024; Accepted 4 November 2024
Global Ecology and Conservation 56 (2024) e03284
Available online 5 November 2024
2351-9894/© 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license
( http://creativecommons.org/licenses/by/4.0/ ).

2009). Literature suggest that these movements involve seasonal migrations (Leggett, 2006; Lindeque and Lindeque, 1991; Thouless,
1995; Viljoen, 1988) or localized sedentary behaviours (De Villiers and Kok, 1997; Douglas-Hamilton, 1971). Research to date suggests
that the movement patterns of large herbivores are driven by surface water and forage quality and quantity (Boone et al., 2006; Fryxell
and Sinclair, 1988; McNaughton, 1985; Murray, 1995; Williamson et al., 1988) and human activities (Adams et al., 2022; Boettiger
et al., 2011; Gaynor et al., 2018). The African elephant (Loxodonta africana Blumenbach) follows a mixed-feeding strategy, incorpo-
rating both browse and grass into its diet. In African ecosystems, elephants act as ecosystem engineers, playing a crucial role in shaping
and maintaining ecological processes. (Kerley et al., 2008; Laws, 1970; Lewis, 1986; Loarie et al., 2009), and their impacts are
noticeable when in higher densities (Laws, 1970; Lewis, 1986; Loarie et al., 2009; Shannon et al., 2008). This has been noted
particularly around wetlands and articial waterpoints (AWPs) (Leggett, 2006; Sianga et al., 2017a).
Northern Botswana’s permanent wetlands, including the Okavango Delta, Kwando, and Chobe Rivers, provide crucial foraging
resources for the region’s large elephant population (Chase, 2017; Chase et al., 2018; Spinage, 1990). High-quality resources and
permanent water sources attract a high density of elephants during the dry season, while in the wet season, elephants prefer woodlands
located farther from permanent water (Stokke and Du Toit, 2002). The timing of seasonal shifts between these ranges over time has
been linked to rainfall and forage availability (Babaasa, 2000; Thouless, 1995; Western and Lindsay, 1984; White, 1994). However, the
establishment of articial water points in woodlands distant from wetlands has altered the seasonal migration patterns of elephants
between habitats (Othile, 2012). These AWPs exert a signicant inuence on the seasonal movement behaviours of elephants, ul-
timately impacting the surrounding woody vegetation and ecosystem (Teren, 2016).
In the Central Kalahari Game Reserve (CKGR), there are currently sixteen Articial Water Points (AWPs). Nine of these (Matswere,
Sunday Pan, Passarge, Motopi, Letiahau, Piper Pan, Quee Pan, Xaka, and Moriso) were established between 1986 and 1990 (Bonica,
1992), while the remaining AWPs (i.e., Xade, Tsau, Tsetseng, and Sex) were established after 2000. This was a strategy to mitigate high
mortalities of wildlife particularly during drought periods, as evidenced through the massive die offs of blue wildebeest Connochaetes
taurinus and red hartebeest Alcelaphus buselaphus populations between 1982 – 1986 (Williamson and Mbano, 1988; Williamson and
Williamson, 1984). AWPs were established to serve as drinking points for a diversity of wildlife populations during the dry seasons
when surface water in the ephemeral pans gets depleted. However, with water being available annually in CKGR, a new phenomenon
unfolded, where the rst signs of elephant were seen in 2009, and with the rst elephant sighted in 2010 (Personal Comm, DWNP).
Aerial survey conducted in 2015 estimated about 786 elephants in the Ghanzi Region. There have been frequent sightings of elephants,
often in higher densities around AWPs in CKGR (Chase, 2011). This has resulted in the need to investigate and understand their
movement patterns for management and policy formulation purposes.
In this study, we investigated the movement patterns and spatial distribution of elephants in CKGR using GPS telemetry data from
collared individuals. The objectives for this study were to, (i) investigate the movement patterns of African elephants within the CKGR
Fig. 1. : Map showing the study area, Central Kalahari Game Reserve, Botswana.
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through the analysis of GPS telemetry data, and (ii) establish the spatial distribution and home range of GPS-collared male and female
elephants in the CKGR and surrounding areas.
2. Materials and methods
2.1. Study area
The CKGR, located between latitude 21◦and 24◦south and between longitude 22◦and 26◦east and covers an area of 52,000 km
2
in
the Kalahari Desert covers about 40 % of the Ghanzi District, Botswana (Fig. 1). Climate is semi-arid, with mean annual rainfall ranging
between 350 and 400 mm, in the north and western sides of the reserve, respectively, most of which occurs between December and
March (Bhatora, 1985; Botswana Meteorological Services, 2023). Annual temperatures ranges between −1–37 ◦C, with lowest and
maximum records in June and October, respectively (Botswana Meteorological Services, 2023).
Soils in the CKGR are dominated by calcrete and clays around the pans, whereas outside the pans, the deep Kalahari sandy soils
dominate (Departmentof Surveys and Mapping, 2022). Vegetation in the CKGR can be categorized into; (i) fossil river valley and pan
habitats – dominated by grasslands interspersed by trees, (ii) dune habitats, (iii) interdunal habitats and (iv) plain habitat – charac-
terised by mixed shrub and grasslands. The dune and dunal habitats are characterized by a mosaic of woodlands, shrub, and grassland.
Woody species such as Philenoptera nelsii, Vachellia/Senegalensis spp and Terminalia sericea dominate, while edges of pans are associated
with pockets of Rhigozium brevispinosum and Catophractes alexandrii. Herbaceous layer is dominated by Stipagrostis spp., Aristida spp.,
Eragrostis and Schmidtia spp. (DHV, 1980; Makhabu et al., 2002).
2.2. Elephant collaring
The study primarily targeted female elephants for collaring because they typically maintain stronger social bonds within family
units, and their movements are often constrained closer to these units. In contrast, adult males tend to exhibit looser social bonds,
frequently moving independently and often traveling farther from family groups (Duffy et al., 2011). Mature bulls are generally
associated with female herds primarily during musth periods (Poole, 1987). However, initial surveillance of elephant herds in the
Central Kalahari Game Reserve (CKGR) conducted a week prior to and during the collaring operation revealed a higher proportion of
male herds than female dominated herds. From May 16–19, 2023, we immobilized and tted GPS-enabled collars (Africa Wildlife
Tracking, Pretoria, South Africa) on ten individuals for this year-long study. The group included two females and eight males, with ve
adult males and three sub-adult males from various herds (Table 1). The elephants were immobilised using 13 mg of M99 (Etorphine
hydrochloride) and 20 mg of Azaperone, and the sedation was reversed with 130 mg of Naltrexone following collar installation.
Observations continued until the elephants stabilized and rejoined their herds. The GPS collars were programmed to record four
location xes per day at six-hour intervals, enabling consistent data collection. Although the study period spanned 365 days, the exact
number of days varied slightly among individual elephants, depending on their collar deployment dates (Table 1). Notably, no collar
malfunctions occurred throughout the study period, ensuring uninterrupted data collection.
This study, conducted in collaboration with the Department of Wildlife and National Parks (DWNP) of Botswana, adhered to strict
ethical standards and guidelines on handling wildlife species during research. All procedures were carried out by a government-
registered wildlife veterinarian and authorized under research permit ENT 8/36/4 LV (23) and supplementary permit ENT 8/36/4
LV (55) from the Ministry of Environment, and Tourism of Botswana. Darting was performed from vehicles or helicopters, following
best practices to minimize animal distress. During these operations, efforts to mitigate heat stress included actively cooling the ele-
phants by pouring water over them. We consistently monitored the vital signs of the elephant, including its breathing and heart rate,
during sedation to maintain stable health conditions. Top of Form Post-collaring, continuous monitoring was conducted to assess any
adverse effects of the collars on the health and well-being of the elephants. The collars, equipped to record GPS data for a full year,
were planned for removal after two years.
Table 1
Summary of collared African elephant, sex, group size and place of collaring in CKGR, Botswana.
Collar ID Sex Group Size Collaring Place Collaring date No. of data points
7104 Male 7 Gope 5/18/2023 1359
7105 Female 8 Tsao Hill 2 5/19/2023 1349
7106 Male 12 Xaka Waterhole 5/17/2023 1360
7107 Male 8 Tsao2 5/19/2023 1352
7108 Male 7 Qwee Pan 5/17/2023 1361
7109 Male 11 Xade Waterhole 5/17/2023 1363
7110 Male 10 Gope 5/18/2023 1361
7111 Male 14 Xade Waterhole 5/16/2023 1721
7112 Female 15 Tsao Hill 1 5/19/2023 1356
7113 Male 8 Tsao 5/19/2023 1420
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2.3. Data analysis
2.3.1. Movement patterns and home ranges estimation
We analysed all xes or locations (n =13,101) from collared elephants over a period of 12 months to delineate their movement
pathways using ArcGIS Pro 3.0 (ESRI, 2022). To facilitate for accurate displacement distance and home range area calculations, we
cleaned the data and further transformed the latitude and longitude coordinates into a planar coordinate system (e.g., UTM) using the
sp package (Bivand et al., 2013) in R version 4.4.0 (R Core, 2023). The diel displacement between consecutive GPS xes was calculated
using the ‘distVincentySphere’ function from the ‘geosphere’ package (Hijmans, 2010). This function computes the shortest distance
between two points on the Earth’s surface, assuming an ellipsoidal Earth model. The displacement between consecutive GPS points
Fig. 2. Movement patterns and spatial extent of African elephants in Central Kalahari Game Reserve, Botswana. Notes: (a) Movement paths of in-
dividual elephants (IDs 7104–7113) overlaid on a map of Botswana including protected areas and surrounding landscapes. (b) Spatial extent and movement
trajectory of elephants (IDs 7104–7113) based on gyration radii (0.5 and 1.0). The size of the circles represents the gyration radius, with larger circles
indicating a greater spatial extent of movement. Colour coding corresponds to individual elephant IDs as shown in the legend.
K. Sianga et al.
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was calculated using the methods outlined by Yang et al., (2019). In this study, we dened dial displacement as the movement or
distance traveled by elephants within a 24-hour cycle (Spooner, 2013). We further explored seasonal diel displacement to understand
how the daily movement patterns of elephants would vary across different seasons.
To establish movement patterns and clustering, spatial extent and gyration radii for each elephant were analysed using the ‘sp’ and
‘sf’ packages (Pebesma, 2018). The xes were used to calculate the home range area of the 95 % kernel density estimate (KDE) using
the ‘adeHabitatHR’ package, with the reference bandwidth used as a smoothing parameter to estimate the UDs (Calenge, 2007). We
used this method because it is robust and effectively accounts for the spatial distribution of data points and provides a smooth estimate
of the utilization distribution, which is critical for identifying core areas within the seasonal home ranges. Segmentation of data on
displacement and home range sizes was based on three seasons (cool dry, hot dry, hot wet) based on the date and GPS coordinates. In
this study, we dened the seasons as follows: (i) hot wet season (December, January, February, March and April) (ii) cool dry season
(May, June and July); and (iii) hot dry season (August, September and October, and November) based personal observations and
previous studies (Sianga et al., 2024).
2.4. Statistical analyses
Descriptive statistics, including mean, median, standard deviation, skewness, and kurtosis, were calculated for both displacement
rates and home range sizes to characterize the central tendency and distribution prole of the data. We assessed for normality and
homogeneity of variances using the Shapiro-Wilk test, Levene’s test respectively. The Shapiro-Wilk test indicated a non-normal dis-
tribution of daily displacement data across sex and season groups (p <0.05). Levene’s test also revealed unequal variances between
these groups (p <0.045). Given the non-normal distribution and heterogeneous variances, the Mann-Whitney U test was used for
pairwise comparisons of between sexes.
Displacement distances (km) for each individual elephant were computed for three distinct seasons and stratied by sex (females
and males) for comparative analysis. A Kruskal-Wallis test was used to assess statistically signicant differences in median
displacement across seasons, with effect sizes calculated using epsilon-squared (ϵ
2
) to quantify the variance in displacement due to
seasonal differences. Signicant results were followed by Dunn’s post-hoc tests with Holm-Bonferroni correction for pairwise com-
parisons. The analysis and visualization were conducted in R using the ‘ggstatsplot’ package (Patil, 2021), with violin plots generated
to display the distribution of displacement distances, highlighting medians and annotating signicant pairwise comparisons between
sexes with adjusted p-values.
3. Results
3.1. Movement patterns, spatial extent and displacement rates
The collared elephants moved within the CKGR, as well as the Okavango Delta (OD), Chobe region, and Hwange National Park
(HNP) in Zimbabwe. Movement patterns varied, with females 7105 and 7112 primarily ranging between the Tsau DWNP gate in CKGR
and the southern OD near Khoemacau Mine, while bull 7107 stayed near the Tsau DWNP gate and the western OD (Fig. 2a). In contrast,
males 7104, 7108, 7110, 7111, and 7112 remained within the CKGR year-round. Three male elephants exhibited extensive migratory
behaviour: 7109 migrated seasonally between Old Xade (CKGR) and the eastern OD, 7113 moved between the Tsau entrance (CKGR),
OD, Chobe, and HNP, and 7106 travelled from Old Xade (CKGR) to HNP via Makgadikgadi National Park (MNP), returning along the
same route during the dry season (Fig. 2a).
The spatial extent of elephant trajectories across study areas, segmented by individual elephant IDs and their respective gyration
radii. Elephants exhibited diverse movement patterns with notable spatial differentiation and distinct movement clusters. Each
elephant showed unique trajectories, with some elephants, such as IDs 7106 (black) and 7113 (red), demonstrating extensive
movement across the landscape, while others, like ID 7104 (green), exhibited more localized movement (Fig. 2b). The gyration radii,
represented by the circle sizes, indicate variations in the spatial extent of movement among the elephants. Larger circles denote a
Table 2
Diel displacement rates of African elephants in the study area across three seasons. Notes: values displayed show the median and inter quartile range (km).
Elephant ID Sex Season
Cool Dry Hot Dry Hot Wet
Median (IQR) Median (IQR) Median (IQR)
7104 Male 6.69 (4.68) 8.79 (4.84) 8.70 (5.23)
7105 Female 7.98 (6.80) 10.02 (8.27) 7.82 (5.33)
7106 Male 5.21 (4.21) 8.62 (6.86) 13.69 (11.08)
7107 Male 12.20 (6.13) 10.92 (7.49) 11.89 (7.94)
7108 Male 8.94 (4.08) 9.33 (4.90) 8.00 (5.72)
7109 Male 11.45 (6.54) 9.65 (7.05) 11.16 (12.63)
7110 Male 6.06 (4.21) 7.28 (4.78) 8.60 (5.38)
7111 Male 9.27 (5.64) 9.92 (7.86) 13.30 (8.58)
7112 Female 8.34 (6.37) 9.88 (5.99) 8.75 (6.26)
7113 Male 8.09 (4.34) 8.71 (5.73) 11.48 (11.49)
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broader range of movement, suggesting elephants with extensive roaming areas (e.g., Elephant IDs 7106, 7107, 7109, and 7113).
Conversely, smaller radii (e.g., Elephant ID 7104) suggest more sedentary movement patterns. Noticeable spatial clustering and
overlap in the movement paths of different elephants suggest common areas of activity or habitats used by multiple individuals
(Fig. 2b).
The median diel displacement and their respective interquartile ranges (IQRs) for each elephant across the three seasons are shown
in Table 2. Variability, based on IQR values, was notably higher in the hot wet season, suggesting greater dispersion and pronounced
seasonal effects on movement patterns. Overall, Mann-Whitney U test showed a statistically signicant difference in displacement
rates between female and male elephants (U =873,343, p =0.026).
Both male and female elephants displayed distinct seasonal variability in diel displacement (Fig. 3). Movements were highest
during the hot wet season (December–April), with females regularly covering over 30 km/day and occasionally reaching 50 km/day.
In contrast, during the cool dry season (May–July), female movements were lower, typically below 15 km/day, with a similar
reduction observed during the hot dry season (August–November), though occasional spikes exceeded 20 km/day. Male elephants also
showed increased displacement during the hot wet season, reaching up to 35 km/day, with rare outliers exceeding 100 km/day.
During the cool dry and hot dry seasons, male movements were more moderate, generally staying below 15 km/day, and were more
consistent than those of females, with fewer extreme spikes.
The Kruskal-Wallis test showed a signicant difference in diel displacement across seasons among females (
χ
2
=22.06, p =1.62e-
05). Dunn’s post-hoc test revealed signicant pairwise differences between the cool dry and hot dry season (p =1.07e-04), as well as
between the cool dry and hot wet season (p =2.32e-04). Median diel displacement values were highest in the hot dry season (9.91 km),
followed by the Hot Wet (8.48 km) and cool dry (8.08 km) seasons (Fig. 4). Similarly, there was a signicant difference in diel
displacement (
χ
2
=98.50, p =4.08e-22) for males across seasons. Dunn’s post-hoc test conrmed signicant pairwise differences
between all season pairs; cool dry and hot dry (p =1.98e-03), cool dry and hot wet (p =4.48e-12), and hot dry and hot wet (p =7.70e-
20). The median diel displacement values were highest in the hot wet season (10.54 km), followed by the hot dry (9.02 km) and cool
Fig. 3. Seasonal variation in African elephant diel displacement by sex with a 30-day rolling average. Notes: Black line represents the 30-day rolling
average for diel displacement. The plot for males employs a broken y-axis, with the lower section showing displacements ≤35 km and the upper
section showing displacements >35 km.
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dry (8.22 km) season (Fig. 4).
3.2. Seasonal and annual home ranges
The Kernel Density Estimation (KDE) results revealed signicant variation in elephant home range sizes, inuenced by both sex and
season (Table 3 and Fig. 5). Males generally had larger home ranges than females, with individuals like Elephant IDs 7106 and 7113
Fig. 4. Seasonal differences in diel displacement of female and male African elephants for the study period.
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showing particularly extensive ranges during the hot wet season. Females, on the other hand, exhibited smaller and more stable ranges,
except for Elephant ID 7105, which displayed an unusually large annual range. Seasonal effects were evident, with home ranges
expanding signicantly during the hot wet season compared to the cooler dry seasons. This suggests that seasonal shifts in environ-
mental conditions, such as resource availability, strongly inuence elephant movement patterns within the Central Kalahari Game
Reserve.
4. Discussion
This study marks a signicant advancement in understanding the seasonal movement patterns of elephants across the CKGR, OD,
Chobe, and HNP regions within the KAZA landscape. GPS-collar data offered the rst quantitative insights into how these large
herbivores utilise the landscape in response to seasonal uctuations in water availability, forage, and environmental conditions. These
Table 3
Seasonal and annual home range areas (km
2
) estimated using kernel density estimation (KDE) for African elephants in the Central Kalahari Game
Reserve.
Elephant ID Sex Season Annual
Cool Dry Hot Dry Hot Wet
KDE (km
2
) KDE (km
2
) KDE (km
2
) KDE (km
2
)
7104 Male 21.29 16.90 209.91 1890.10
7105 Female 436.65 276.64 184.39 4224.65
7106 Male 53.56 140.45 7422.32 38367.94
7107 Male 544.37 1820.99 1867.70 14639.83
7108 Male 56.27 5.78 359.70 3468.04
7109 Male 20.92 45.15 3248.51 33882.97
7110 Male 8.24 5.14 198.74 1432.54
7111 Male 40.08 18.70 2201.31 23733.00
7112 Female 49.49 10.80 244.39 1824.13
7113 Male 46.30 18.96 6850.29 58931.75
Fig. 5. : Seasonal home ranges of GPS-collared African elephants in the Central Kalahari Game Reserve and surrounding areas, Botswana. Notes: (A)
Hot wet season, (B) – Cool dry season and (C) Hot dry season.
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movement patterns highlight the critical importance of maintaining ecological connectivity between the KAZA and the Central
Kalahari Game Reserve. This connectivity is essential for the effective management and conservation of large herbivores across these
interconnected landscapes, with signicant implications for biodiversity and ecosystem resilience (Dures et al., 2020, 2021; McCarthy
and Ellery, 1998).
The study showed signicant differences in movement patterns between male and female elephants, with males exhibiting wider
ranges and more pronounced movement behaviour. The introduction of articial water points has likely increased male elephants’
residency within the CKGR; previously, they migrated north during the wet season in search of natural water sources. (Spinage, 1990).
The strategic placement of AWPs at locations such as Tsau Gate, Xaka, and Matswere has provided consistent water availability,
enabling male elephants to occupy areas that were historically part of their migratory routes year-round (Naha et al., 2019; Perkins,
2020). This shift aligns with similar observations in other semi-arid ecosystems, where articial water sources alter traditional
migration and ranging patterns (Chamaill´
e-Jammes et al., 2007; De Beer et al., 2006; Evans and Harris, 2008; Illius, 2006; Wato et al.,
2018). This shift in behaviour suggests that while AWPs provide essential resources, they may also alter traditional migratory patterns,
potentially leading to increased human-wildlife conict (Buchholtz et al., 2023, 2021; Graham et al., 2009; Kikoti et al., 2010) and
localized habitat changes (Dzinotizei et al., 2019; Hilbers et al., 2015; Shannon et al., 2009).
The male elephants in the CKGR maintain a regular presence near articial water points and moved north to Okavango Delta (OD),
Chobe, and Hwange National Park (HNP) during the wet season, returning in the dry season. In contrast, female elephants primarily
migrate between northern CKGR and southern OD. Historically, large herds in the OD and Chobe regions migrate to dryland woodlands
during the wet season, inuenced by water availability in ephemeral pans (Spinage, 1990; Stokke and Du Toit, 2002). The estab-
lishment of articial water points (AWPs) at Tsao Gate, Xaka, Matswere, Motopi, Sunday Pan, Piper Pan, Qwee, and Old Xade likely
contributed to the permanent residency of male elephants during the dry season by improving water access. Similarly, areas near
articial water sources at the Gope and Ghagho mines have become important habitats for elephants in the CKGR. This pattern is
consistent with research in semi-arid ecosystems, where water availability and forage are key drivers of elephant distribution
(Bucciarelli et al., 2024; Dzinotizei et al., 2019; Perkins, 2020; Shannon et al., 2009). Reports from the Department of Wildlife and
National Parks (DWNP) indicate that elephants were rst observed in the CKGR in 2010 near the Tsau AWP, with subsequent data
showing a steady rise in elephant density around AWPs in both wet and dry seasons.
The results showed ecologically signicant seasonal movement patterns around articial water points (AWPs) during both wet and
dry periods. Female elephants with calves strategically position themselves near the Okavango Delta (OD), particularly between Tsau
Gate and OD, highlighting their dependence on OD’s permanent water sources. This behaviour likely reduces the risks posed by water
scarcity at Tsau AWP, where solar pump failures have caused prolonged shortages, threatening juvenile survival. These ndings align
with broader research indicating that water shortages signicantly increase dehydration risks for vulnerable young elephants (Foley
et al., 2008; Leggett, 2006; Loveridge et al., 2006; Young and Van Aarde, 2011).
The displacement rates observed in this study generally show consistent movement patterns across seasons, with some variability
among collared elephants. Arguably, the observed differences in displacement rates between females and males can be attributed to
their distinct social structures (Archie et al., 2011; Moss et al., 2011), and divergent foraging strategies (Lee et al., 2011). Males, with
their broader foraging ranges, often explore unfamiliar habitats in search of forage and mates, venturing further from water sources to
access high-quality habitats, especially during dry seasons. (Lee et al., 2011; Skarpe et al., 2014). In contrast, female herds are con-
strained by the mobility of calves at varying developmental stages, limiting the distance they can travel from water sources (Ngene
et al., 2010). The movement patterns observed in this study show key regions with high overlap and frequent elephant activity,
suggesting areas where intensied conservation efforts could be most effective (Beger et al., 2022; Huang et al., 2022).
By analysing spatial trajectories and gyration radii, this study highlights the complexity and variability in elephant movement,
emphasising the necessity for conservation strategies that are both site-specic and adaptable to individual and collective behaviours
(Cushman et al., 2005; Polansky et al., 2015). Insights from elephant movement trajectories and spatial extent are crucial for
developing effective management plans to protect critical habitats patches and movement corridors (Adams et al., 2022;
Douglas-Hamilton et al., 2005), mitigate human-elephant conicts (Gerhardt et al., 2014; Jiren et al., 2021; K¨
onig et al., 2021;
Ostermann-Miyashita et al., 2021), and ensure the long-term sustainability of elephant populations in the region.
Research on elephant home ranges across Africa consistently shows that annual home ranges are signicantly larger than seasonal
or monthly estimates. Studies in northern Botswana (Chase, 2007; Othile, 2012) and South Africa (Loarie et al., 2009c) report similar
patterns. In this study, annual home ranges for the collared male elephants exceeded the combined seasonal ranges, with notable
differences between sexes and seasons. This aligns with ndings from other studies on African elephants (Bastille-Rousseau et al.,
2020; Wittemyer et al., 2007), where seasonal movements, driven by the need to access scarce resources during dry periods, result in
overlapping space use and range expansion (Mlambo et al., 2021).
We argue that the expansive home ranges of male elephants in this study some exceeding 30,000 km
2
, result from extensive
movements in search of mates and widely dispersed resources, particularly in resource-scarce regions like the Kalahari. These ranges
are comparable only to those recorded in Gourma, Mali, where collared female elephants exhibited a home range of 32,062 km
2
, and
males had ranges of up to 24,196 km
2
(Wall et al., 2013). Some males exhibited exceptionally large ranges, consistent with exploratory
or migratory behaviors observed in other studies (Bohrer et al., 2014; Othile, 2012; Wato et al., 2018). Males typically travel farther
than females, venturing beyond core areas to maximize mating opportunities and access seasonal resources (Stokke and Du Toit,
2002). Environmental factors, such as seasonal water availability and social behaviors like musth, further contribute to this increased
mobility by male African elephants (De Beer and Van Aarde, 2008; Loarie et al., 2009). In contrast, females maintained smaller, more
stable ranges, especially when accompanied by calves, staying closer to reliable water sources (Bastille-Rousseau et al., 2020; Benitez
et al., 2022; Cushman et al., 2005; Polansky et al., 2013). These patterns highlight elephants’ adaptive strategies to uctuating
K. Sianga et al.
Global Ecology and Conservation 56 (2024) e03284
9

resources and emphasize the critical need to conserve connected habitats across the Central Kalahari ecosystem and surrounding areas
to sustain their wide-ranging movements.
During the wet season, core home ranges for three male elephants extended into woodlands between the CKGR, OD, MNP, and
HNP, with these individuals venturing beyond their dry season ranges in CKGR. This behaviour mirrors patterns observed in Namibia’s
Hoanib River, where male elephants travel vast distances to access wet season habitats (Leggett, 2006; Viljoen, 1988). Such extensive
movements are typical of large herbivores, driven by the need to exploit diverse resources across wet and dry periods (Gordon et al.,
2004). In CKGR, elephant ranging patterns seem inuenced by the spatial distribution of water, indicating an ecological awareness of
articial water points (Wato et al., 2018), similar to behaviours observed in Tsavo National Park, Kenya (Polansky et al., 2015). The
wet season dispersal into woodlands across CKGR, OD, MNP, and HNP reects the seasonal abundance of resources, consistent with
patterns documented among large herbivores in northern Botswana (Bennitt et al., 2014; Naidoo et al., 2014, 2016; Sianga, 2014;
Sianga et al., 2017b).
5. Implications for conservation and management
This study provides insights into the complex spatial dynamics of elephants within the CKGR and highlights its critical connectivity
with the KAZA, one of the world’s largest and most signicant transboundary conservation landscapes (Kaszta et al., 2021; Osipova
et al., 2018; Purdon et al., 2018; Zacarias and Loyola, 2018). The establishment of articial water points within the CKGR has
signicantly altered traditional elephant movement patterns, prompting a shift toward more sedentary behaviour among male ele-
phants in areas that were historically occupied only seasonally. While these water provisioning is important in the arid CKGR envi-
ronment, there are concerns about habitat degradation, increased competition with other herbivores, disrupted ecosystem dynamics,
and the potential for escalating human-elephant conicts (Buchholtz et al., 2023, 2021; Gerhardt et al., 2014; Graham et al., 2009;
Kaszta et al., 2021; Naha et al., 2019; Pozo et al., 2018). The ndings highlight the critical need to maintain ecological connectivity
between protected areas beyond the KAZA region to secure the long-term viability of elephant populations and other key species
(Chibeya et al., 2021; Gara et al., 2021; Giliba et al., 2023; Keeley et al., 2017; Zacarias and Loyola, 2018).
Given the increasing threat of climate change exacerbating water scarcity and altering resource distribution, it is imperative to
adopt holistic, ecosystem-based adaptive management strategies that prioritize ecological integrity (Birg´
e et al., 2016; Nasr and Orwin,
2024), while balancing social and economic needs (van de Water et al., 2022). These approaches are particularly crucial in regions
where human activities, such as mining and agriculture, intersect with essential wildlife habitats and potential dispersal routes or
corridors (Schüßler et al., 2018). Further research is needed to monitor these shifting dynamics, particularly the long-term effects of
articial water points and environmental change on elephant movement, population health, human-elephant coexistence, and
ecosystem resilience. This research will be essential for informing conservation policies and management practices that enhance the
resilience of wildlife and human communities amid environmental change.
Ethics Statement
A research permit was applied and availed before the study was conducted.
Author contributions
Keoikantse Sianga, Shimane Makhabu, Victor Muposhi: Conceptualization; Keoikantse Sianga, Shimane Makhabu, Victor
Muposhi: Methodology; Keoikantse Sianga, Shimane Makhabu, Victor Muposhi, Tebogo Selebatso, Mpho Setlalekgomo,
Albertinah Matsika, Boipuso Legwatagwata, Amo Barungwi, Kelebogile Selala, Maitumelo Losologolo, Emang Molojwane,
Comfort Nkgowe, Oreemetse Dingake: Data curation; Keoikantse Sianga, Victor Muposhi: Formal analysis; Keoikantse Sianga:
Writing- Original draft preparation; Keoikantse Sianga, Victor Muposhi, Shimane Makhabu, Tebogo Selebatso, Amo Barungwi,
Albertinah Matsika: Writing - review and editing; Shimane Makhabu, Keoikantse Sianga, Victor Muposhi: Funding acquisition;
Keoikantse Sianga, Victor Muposhi: Software; Keoikantse Sianga, Victor Muposhi: Visualization; Keoikantse Sianga, Shimane
Makhabu, Victor Muposhi: Resources; Keoikantse Sianga, Victor Muposhi, Shimane Makhabu: Validation; Victor Muposhi:
Supervision; Shimane Makhabu, Keoikantse Sianga: Project administration.
Funding sources
This work was supported by the Wildlife Conservation Trust Fund (CTF) through the DWNP.
Declaration of Competing Interest
The authors declare the following nancial interests/personal relationships which may be considered as potential competing in-
terests. Keoikantse Sianga reports nancial support was provided by Conservation Trust Fund. None reports a relationship with None
that includes: non-nancial support. None has patent None pending to None. None If there are other authors, they declare that they
have no known competing nancial interests or personal relationships that could have appeared to inuence the work reported in this
paper.
K. Sianga et al.
Global Ecology and Conservation 56 (2024) e03284
10

Acknowledgements
The authors express their gratitude to the Ministry of Environment and Tourism and the Department of Wildlife and National Parks
for granting permission to conduct this research in CKGR and for providing their Cessna aircraft and ofcers for scouting and collaring
elephants. We also acknowledge Helicopter Horizons (Maun) for their invaluable assistance in supplying a helicopter and experienced
pilot during the collaring operations. Special thanks go to Dr. Donald Kgope for his expertise in darting the elephants during collar
tting. Lastly, we appreciate the efforts of all the DWNP ofcers in CKGR who facilitated this research throughout its duration.
Data availability
Data will be made available on request.
References
Adams, T.S., Leggett, K.E., Chase, M.J., Tucker, M.A., 2022. Who is adjusting to whom?: Differences in elephant diel activity in wildlife corridors across different
human-modied landscapes. Front. Conserv. Sci. 3, 872472.
Archie, E.A., Moss, C.J., Alberts, S.C., 2011. Friends and relations: kinship and the nature of female elephant social relationships. Amboseli Elephants Long. -Term.
Perspect. Long. -Lived Mammal. 238–245.
Babaasa, D., 2000. Habitat selection by elephants in Bwindi Impenetrable National Park, south-western Uganda.
Bastille-Rousseau, G., Wall, J., Douglas-Hamilton, I., Lesowapir, B., Loloju, B., Mwangi, N., Wittemyer, G., 2020. Landscape-scale habitat response of African
elephants shows strong selection for foraging opportunities in a human dominated ecosystem. Ecography 43, 149–160. https://doi.org/10.1111/ecog.04240.
Beger, M., Metaxas, A., Balbar, A.C., McGowan, J.A., Daigle, R., Kuempel, C.D., Treml, E.A., Possingham, H.P., 2022. Demystifying ecological connectivity for
actionable spatial conservation planning. Trends Ecol. Evol. 37, 1079–1091. https://doi.org/10.1016/j.tree.2022.09.002.
Benitez, L., Kilian, J.W., Wittemyer, G., Hughey, L.F., Fleming, C.H., Leimgruber, P., du Preez, P., Stabach, J.A., 2022. Precipitation, vegetation productivity, and
human impacts control home range size of elephants in dryland systems in northern Namibia. Ecol. Evol. 12. https://doi.org/10.1002/ece3.9288.
Bennitt, E., Bonyongo, M.C., Harris, S., 2014. Habitat selection by African buffalo (Syncerus caffer) in response to landscape-level uctuations in water availability on
two temporal scales. PloS One 9, 1–14. https://doi.org/10.1371/journal.pone.0101346.
Berger, J., 2004. The last mile: how to sustain long-distance migration in mammals. Conserv. Biol. 18, 320–331.
Bhatora, Y.P.R., 1985. Rainfall Maps Botsw.
Birg´
e, H.E., Allen, C.R., Garmestani, A.S., Pope, K.L., 2016. Adaptive management for ecosystem services. J. Environ. Manag., Adapt. Manag. Ecosyst. Serv. 183,
343–352. https://doi.org/10.1016/j.jenvman.2016.07.054.
Bivand, R.S., Pebesma, E., G´
omez-Rubio, V., 2013. Spatial Point Pattern Analysis. In: Bivand, R.S., Pebesma, E., G´
omez-Rubio, V. (Eds.), Applied Spatial Data Analysis
with R. Springer, New York, NY, pp. 173–211. https://doi.org/10.1007/978-1-4614-7618-4_7.
Boettiger, A.N., Wittemyer, G., Stareld, R., Volrath, F., Douglas-Hamilton, I., Getz, W.M., 2011. Inferring ecological and behavioral drivers of African elephant
movement using a linear ltering approach. Ecology 92, 1648–1657.
Bohrer, G., Beck, P.S., Ngene, S.M., Skidmore, A.K., Douglas-Hamilton, I., 2014. Elephant movement closely tracks precipitation-driven vegetation dynamics in a
Kenyan forest-savanna landscape. Mov. Ecol. 2, 2. https://doi.org/10.1186/2051-3933-2-2.
Bonica. (1992). Technical Assistance to the Department ofWildlife and National Parks; Initial Measures for the Conservation of the Kalahari Ecosystem. (Project
.6100.026.14.001.). Department of Wildlife and National Parks.
Boone, R.B., Thirgood, S.J., Hopcraft, J.G.C., 2006. Serengeti wildebeest migratory patterns modeled from rainfall and new vegetation growth. Ecology 87,
1987–1994.
Botswana Meteorological Services, 2023. Botswana Climate. Gaborone, Botswana.
Bucciarelli, J.R., Pimm, S.L., Huang, R.M., Chase, M.J., Leggett, K., Bastos, A.D., van Aarde, R.J., 2024. Local elephant movements, turning angles, and water access
across a rainfall gradient in Southern Africa. Biol. Conserv. 296, 110669. https://doi.org/10.1016/j.biocon.2024.110669.
Buchholtz, E.K., McDaniels, M., McCulloch, G., Songhurst, A., Stronza, A., 2023. A mixed-methods assessment of human-elephant conict in the Western Okavango
Panhandle, Botswana. People Nat. 5, 557–571. https://doi.org/10.1002/pan3.10443.
Buchholtz, E.K., Spragg, S., Songhurst, A., Stronza, A., McCulloch, G., Fitzgerald, L.A., 2021. Anthropogenic impact on wildlife resource use: Spatial and temporal
shifts in elephants’ access to water. Afr. J. Ecol. 59, 614–623. https://doi.org/10.1111/aje.12860.
Calenge, C., 2007. Exploring habitat selection by wildlife with adehabitat. J. Stat. Softw. 22, 2–19. https://doi.org/10.18637/jss.v022.i06.
Chamaill´
e-Jammes, S., Valeix, M., Fritz, H., 2007. Managing heterogeneity in elephant distribution: Interactions between elephant population density and surface-
water availability. J. Appl. Ecol. https://doi.org/10.1111/j.1365-2664.2007.01300.x.
Chase, M.J., 2007. Home ranges, transboundary movements and harvest of elephants in northern Botswana and factors affecting elephant distribution and abundance
in the Lower Kwando River Basin.
Chase, M., 2011. Dry season xed-wing aerial survey of elephants and wildlife in Northern Botswana. September-November 2010. (No. Report 2011). Kasane,
Botswana.
Chase, M., 2017. Dry season xed-wing aerial survey of elephants and wildlife in northern Botswana, September-November 2010. Botsw. Doc.
Chase, M., Schlossberg, S., Sutcliffe, R., Seonyatseng, E., 2018. Dry season aerial survey of elephants and wildlife in northern Botswana. Elephants Bord.
Chibeya, D., Wood, H., Cousins, S., Carter, K., Nyirenda, M.A., Maseka, H., 2021. How do African elephants utilize the landscape during wet season? A habitat
connectivity analysis for Sioma Ngwezi landscape in Zambia. Ecol. Evol. 11, 14916–14931. https://doi.org/10.1002/ece3.8177.
Core, R., 2023. R: A language and environment for statistical computing. R Foundation for Statistical Computing. Httpwww R-Proj. Org, Vienna, Austria.
Cushman, S.A., Chase, M., Grifn, C., 2005. Elephants in space and time. Oikos 109, 331–341. https://doi.org/10.1111/j.0030-1299.2005.13538.x.
De Beer, Y., Kilian, W., Versfeld, W., Van Aarde, R.J., 2006. Elephants and low rainfall alter woody vegetation in Etosha National Park, Namibia. J. Arid Environ. 64,
412–421.
De Beer, Y., Van Aarde, R.J., 2008. Do landscape heterogeneity and water distribution explain aspects of elephant home range in southern Africa’s arid savannas?
J. Arid Environ. 72, 2017–2025.
De Villiers, P.A., Kok, O.B., 1997. Home range, association and related aspects of elephants in the eastern Transvaal Lowveld. Afr. J. Ecol. 35, 224–236.
Departmentof Surveys and Mapping, Botswana, 2022. Soils Maps of Botswana.
DHV, 1980. Country Wide Animal and Range Assessment Project. Final report to the Department of Wildlife, National Parks and Tourism (No. 7), Volume 7. DHV
Consulting Engineers, Amersfoort., Government of Botswana.
Douglas-Hamilton, I., 1971. Radio-tracking of elephants. Symposium of Biotelemetry. CSIR, Pretoria.
Douglas-Hamilton, I., Krink, T., Vollrath, F., 2005. Movements and corridors of African elephants in relation to protected areas. Naturwissenschaften 92, 158–163.
https://doi.org/10.1007/s00114-004-0606-9.
Duffy, K.J., Dai, X., Shannon, G., Slotow, R., Page, B., 2011. Movement patterns of African elephants (Loxodonta africana) in different habitat types. South Afr. J.
Wildl. Res. -24-Mon. Delayed Open Access 41, 21–28.
K. Sianga et al.
Global Ecology and Conservation 56 (2024) e03284
11

Dures, S.G., Carbone, C., Loveridge, A.J., Maude, G., Midland, N., Gottelli, D., 2021. Population connectivity across a transboundary conservation network: potential
for restoration?
Dures, S.G., Carbone, C., Savolainen, V., Maude, G., Gottelli, D., 2020. Ecology rather than people restrict gene ow in Okavango-Kalahari lions. Anim. Conserv. 23,
502–515.
Dzinotizei, Z., Murwira, A., Masocha, M., 2019. Elephant-induced landscape heterogeneity change around articial waterholes in a protected savanna woodland
ecosystem. Remote Sens. Appl. Soc. Environ. 13, 97–105. https://doi.org/10.1016/j.rsase.2018.10.009.
ESRI, 2022. ArcGIS Pro Desktop.
Evans, K.E., Harris, S., 2008. Adolescence in male African elephants, Loxodonta africana, and the importance of sociality. Anim. Behav. 76, 779–787.
Foley, C., Pettorelli, N., Foley, L., 2008. Severe drought and calf survival in elephants. Biol. Lett. 4, 541–544.
Fryxell, J.M., Sinclair, A.R.E., 1988. Causes and consequences of migration by large herbivores. Trends Ecol. Evol. 3, 237–241. https://doi.org/10.1016/0169-5347
(88)90166-8.
Gara, T.W., Wang, T., Dube, T., Ngene, S.M., Mpakairi, K.S., 2021. African elephant (Loxodonta africana) select less fragmented landscapes to connect core habitats in
human-dominated landscapes. Afr. J. Ecol. 59, 370–377. https://doi.org/10.1111/aje.12839.
Gaynor, K.M., Branco, P.S., Long, R.A., Gonçalves, D.D., Granli, P.K., Poole, J.H., 2018. Effects of human settlement and roads on diel activity patterns of elephants
(Loxodonta africana). Afr. J. Ecol. 56, 872–881.
Gerhardt, K.V., Niekerk, A.V., Kidd, M., Samways, M., Hanks, J., 2014. The role of elephant Loxodonta africana pathways as a spatial variable in crop-raiding location.
Oryx 48, 436–444. https://doi.org/10.1017/S003060531200138X.
Giliba, R.A., Kiffner, C., Fust, P., Loos, J., 2023. Modelling elephant corridors over two decades reveals opportunities for conserving connectivity across a large
protected area network. PLOS ONE 18, e0292918. https://doi.org/10.1371/journal.pone.0292918.
Gordon, I.J., Hester, A.J., Festa-Bianchet, M., 2004. The management of wild large herbivores to meet economic, conservation and environmental objectives. J. Appl.
Ecol. 41, 1021–1031.
Graham, M.D., Douglas-Hamilton, I., Adams, W.M., Lee, P.C., 2009. The movement of African elephants in a human-dominated land-use mosaic. Anim. Conserv. 12,
445–455. https://doi.org/10.1111/j.1469-1795.2009.00272.x.
Harris, G., Thirgood, S., Hopcraft, J.G.C., Cromsigt, J.P.G.M., Berger, J., Cromsight, J., Berger, J., 2009. Global decline in aggregated migrations of large terrestrial
mammals. Endanger. Species Res. 7, 55–76. https://doi.org/10.3354/esr00173.
Hijmans, R.J., 2010. geosphere: Spherical Trigonometry. https://doi.org/10.32614/CRAN.package.geosphere.
Hilbers, J.P., van Langevelde, F., Prins, H.H.T., Grant, C.C., Peel, M.J.S., Coughenour, M.B., de Knegt, H.J., Slotow, R., Smit, I.P.J., Kiker, G.A., Boer, W.F., de, 2015.
Modeling elephant-mediated cascading effects of water point closure. Ecol. Appl. 25, 402–415. https://doi.org/10.1890/14-0322.1.
Huang, R.M., Aarde, R.J., van, Pimm, S.L., Chase, M.J., Leggett, K., 2022. Mapping potential connections between Southern Africa’s elephant populations. PLOS ONE
17, e0275791. https://doi.org/10.1371/journal.pone.0275791.
Illius, A.W., 2006. Linking functional responses and foraging behaviour to population dynamics. Conserv. Biol. Ser. -Camb. - 11, 71.
Jiren, T.S., Riechers, M., Kansky, R., Fischer, J., 2021. Participatory scenario planning to facilitate human–wildlife coexistence. Conserv. Biol. 35, 1957–1965. https://
doi.org/10.1111/cobi.13725.
Kaszta, ˙
Z., Cushman, S.A., Slotow, R., 2021. Temporal Non-stationarity of Path-Selection Movement Models and Connectivity: An Example of African Elephants in
Kruger National Park. Front. Ecol. Evol. 9. https://doi.org/10.3389/fevo.2021.553263.
Keeley, A.T.H., Beier, P., Keeley, B.W., Fagan, M.E., 2017. Habitat suitability is a poor proxy for landscape connectivity during dispersal and mating movements.
Landsc. Urban Plan. 161, 90–102. https://doi.org/10.1016/j.landurbplan.2017.01.007.
Kerley, G.I., Landman, M., Kruger, L., Owen-Smith, N., Balfour, D., de Boer, W.F., Gaylard, A., Lindsay, K., Slotow, R., 2008. Effects of elephants on ecosystems and
biodiversity, in: The 2007 Scientic Assessment of. Elephant Manag. South Afr. CSIR 101–147.
Kikoti, A.P., Grifn, C.R., Pamphil, L., 2010. Elephant use and conict leads to Tanzania’s rst wildlife conservation corridor. Pachyderm 48, 57–66.
K¨
onig, H.J., Ceaușu, S., Reed, M., Kendall, H., Hemminger, K., Reinke, H., Ostermann-Miyashita, E.-F., Wenz, E., Eufemia, L., Hermanns, T., Klose, M., Spyra, M.,
Kuemmerle, T., Ford, A.T., 2021. Integrated framework for stakeholder participation: Methods and tools for identifying and addressing human–wildlife conicts.
Conserv. Sci. Pract. 3, e399. https://doi.org/10.1111/csp2.399.
Laws, R.M., 1970. Elephants as agents of habitat and landscape change in East Africa. Oikos 1–15.
Lee, P., Lindsay, W., Moss, C., 2011. Ecological patterns of variability in demographic rates. In: Moss, C.J., Croze, H., Phyllis, C.L. (Eds.), The Amboseli Elephants.
University of Chicago Press, Chicago, IL.
Leggett, K., 2006. Effect of articial water points on the movement and behaviour of desert-dwelling elephants of north-western Namibia. Pachyderm 40, 24–34.
Lewis, D.M., 1986. Disturbance effects on elephant feeding: evidence for compression in Luangwa Valley, Zambia. Afr. J. Ecol. 24, 227–241.
Lindeque, M., Lindeque, P.M., 1991. Satellite tracking of elephants in northwestern Namibia. Afr. J. Ecol. 29, 196–206.
Loarie, S.R., van Aarde, R.J., Pimm, S.L., 2009c. Elephant seasonal vegetation preferences across dry and wet savannas. Biol. Conserv. 142, 3099–3107.
Loarie, S.R., Van Aarde, R.J., Pimm, S.L., 2009. Fences and articial water affect African savannah elephant movement patterns. Biol. Conserv. 142, 3086–3098.
Loveridge, A.J., Hunt, J.E., Murindagomo, F., Macdonald, D.W., 2006. Inuence of drought on predation of elephant (Loxodonta africana) calves by lions (Panthera
leo) in an African wooded savannah. J. Zool. 270, 523–530.
Makhabu, S.W., Marotsi, B., Perkins, J., 2002. Vegetation gradients around articial water points in the Central Kalahari Game Reserve of Botswana.
McCarthy, T.S., Ellery, W.N., 1998. The okavango delta. Trans. R. Soc. South Afr. 53, 157–182.
McNaughton, S.J., 1985. Ecology of a grazing ecosystem: the Serengeti. Ecol. Monogr. 55, 259–294.
Mlambo, L., Shekede, M.D., Adam, E., Odindi, J., Murwira, A., 2021. Home range and space use by African elephants (Loxodonta africana) in Hwange National Park,
Zimbabwe. Afr. J. Ecol. 59, 842–853. https://doi.org/10.1111/aje.12890.
Moss, C.J., Croze, H., Lee, P.C., 2011. The Amboseli Elephants: A Long-Term Perspective on a Long-Lived Mammal. Oxford. University Press, Chicago, IL.
Murray, M.G., 1995. Specic nutrient requirements and migration of wildebeest, in: Serengeti II: Dynamics, Management and Conservation of an Ecosystem.
Naha, D., Sathyakumar, S., Dash, S., Chettri, A., Rawat, G.S., 2019. Assessment and prediction of spatial patterns of human-elephant conicts in changing land cover
scenarios of a human-dominated landscape in North Bengal. PLOS ONE 14, e0210580. https://doi.org/10.1371/journal.pone.0210580.
Naidoo, R., Chase, M.J., Beytell, P., Du Preez, P., Landen, K., Stuart-Hill, G., Taylor, R., 2016. A newly discovered wildlife migration in Namibia and Botswana is the
longest in Africa. ORYX. https://doi.org/10.1017/S0030605314000222.
Naidoo, R., Du Preez, P., Stuart-Hill, G., Beytell, P., Taylor, R., 2014. Long-range migrations and dispersals of African buffalo (Syncerus caffer) in the Kavango–Zambezi
Transfrontier Conservation area. Afr. J. Ecol. 52, 581–584.
Nasr, M., Orwin, J.F., 2024. A geospatial approach to identifying and mapping areas of relative environmental pressure on ecosystem integrity. J. Environ. Manag.
370, 122445. https://doi.org/10.1016/j.jenvman.2024.122445.
Ngene, S.M., Van Gils, H.A.M., Van Wieren, S.E., Rasmussen, H., Skidmore, A.K., Prins, H.H.T., Toxopeus, A.G., Omondi, P., Hamilton, I.D., 2010. The ranging
patterns of elephants in Marsabit protected area, Kenya: the use of satellite-linked GPS collars. Afr. J. Ecol. 48, 386–400. https://doi.org/10.1111/j.1365-
2028.2009.01125.x.
Othile, M.B., 2012. Seasonal effects on the ecology and sociality of male African elephants (Loxodonta africana) in the Okavango Delta, Botswana (PhD Thesis).
University of Bristol.
Osipova, L., Okello, M.M., Njumbi, S.J., Ngene, S., Western, D., Hayward, M.W., Balkenhol, N., 2018. Fencing solves human-wildlife conict locally but shifts
problems elsewhere: A case study using functional connectivity modelling of the African elephant. J. Appl. Ecol. 55, 2673–2684. https://doi.org/10.1111/1365-
2664.13246.
Ostermann-Miyashita, E.-F., Pernat, N., K¨
onig, H.J., 2021. Citizen science as a bottom-up approach to address human–wildlife conicts: From theories and methods to
practical implications. Conserv. Sci. Pract. 3, e385. https://doi.org/10.1111/csp2.385.
Patil, I., 2021. Visualizations with statistical details: The “ggstatsplot” approach. J. Open Source Softw. 6, 3167. https://doi.org/10.21105/joss.03167.
K. Sianga et al.
Global Ecology and Conservation 56 (2024) e03284
12

Pebesma, E., 2018. Simple Features for R: Standardized Support for Spatial Vector Data. R. J. 10, 439. https://doi.org/10.32614/RJ-2018-009.
Perkins, J.S., 2020. Changing the Scale and Nature of Articial Water Points (AWP) Use and Adapting to Climate Change in the Kalahari of Southern Africa. In:
Keitumetse, S.O., Hens, L., Norris, D. (Eds.), Sustainability in Developing Countries: Case Studies from Botswana’s Journey towards 2030 Agenda. Springer
International Publishing, Cham, pp. 51–89. https://doi.org/10.1007/978-3-030-48351-7_4.
Polansky, L., Douglas-Hamilton, I., Wittemyer, G., 2013. Using diel movement behavior to infer foraging strategies related to ecological and social factors in
elephants. Mov. Ecol. 1, 13. https://doi.org/10.1186/2051-3933-1-13.
Polansky, L., Kilian, W., Wittemyer, G., 2015. Elucidating the signicance of spatial memory on movement decisions by African savannah elephants using state–space
models. Proc. R. Soc. B Biol. Sci. 282, 20143042.
Poole, J.H., 1987. Rutting behavior in African elephants: the phenomenon of musth. Behaviour 102, 283–316.
Pozo, R.A., Cusack, J.J., McCulloch, G., Stronza, A., Songhurst, A., Coulson, T., 2018. Elephant space-use is not a good predictor of crop-damage. Biol. Conserv. 228,
241–251. https://doi.org/10.1016/j.biocon.2018.10.031.
Purdon, A., Mole, M.A., Chase, M.J., van Aarde, R.J., 2018. Partial migration in savanna elephant populations distributed across southern Africa. Sci. Rep. 8, 11331.
https://doi.org/10.1038/s41598-018-29724-9.
Schüßler, D., Lee, P.C., Stadtmann, R., 2018. Analyzing land use change to identify migration corridors of African elephants (Loxodonta africana) in the Kenyan-
Tanzanian borderlands. Landsc. Ecol. 33, 2121–2136. https://doi.org/10.1007/s10980-018-0728-7.
Shannon, G., Druce, D.J., Page, B.R., Eckhardt, H.C., Grant, R., Slotow, R., 2008. The utilization of large savanna trees by elephant in southern Kruger National Park.
J. Trop. Ecol. 24, 281–289.
Shannon, G., Matthews, W.S., Page, B.R., Parker, G.E., Smith, R.J., 2009. The affects of articial water availability on large herbivore ranging patterns in savanna
habitats: a new approach based on modelling elephant path distributions. Divers. Distrib. 15, 776–783. https://doi.org/10.1111/j.1472-4642.2009.00581.x.
Sianga, K., 2014. Habitat use by buffalo and zebra in relation to spatial and temporal variability of resources in the Savuti-Mababe-Linyanti ecosystem of northern
Botswana. Unpublished Mphil Thesis. University of Botswana, Botswana.
Sianga, K., Fynn, R.W.S., Bonyongo, M.C., 2017a. Seasonal habitat selection by African buffalo Syncerus caffer in the Savuti-Mababe-Linyanti ecosystem of Northern
Botswana. Koedoe 59. https://doi.org/10.4102/koedoe.v59i2.1382.
Sianga, K., van Telgen, M., Vrooman, J., Fynn, R.W.S., van Langevelde, F., 2017b. Spatial refuges buffer landscapes against homogenisation and degradation by large
herbivore populations and facilitate vegetation heterogeneity. Koedoe 59. https://doi.org/10.4102/koedoe.v59i2.1434.
Sianga, K., Bonyongo, M.C., Fynn, R.W.S., 2024. Mechanisms underlying ungulate migration in African savannas: insights from Plains zebra Equus quagga migrations
in Botswana and the implications for conservation under climate change., in: Environmental Change and Biodiversity Conservation in Sub-Saharan Africa,
Chapter 4. Springer.
Skarpe, C., Du Toit, J.T., Moe, S.R., 2014. Elephants and SavannaWoodland Ecosystems: A Study From Chobe National Park, Botswana. JohnWiley & Sons, West
Sussex, Uk.
Spinage, C.A., 1990. Botswana’s problem elephants. Pachyderm 13, 14–19.
Spooner, F., 2013. When the Going Gets Tough, the Tough Restrict Their Movement: The Effect of Fluctuating Resources on the Daily Movements of African Elephants
(PhD Thesis). Citeseer.
Stokke, S., Du Toit, J.T., 2002. Sexual segregation in habitat use by elephants in Chobe National Park, Botswana. Afr. J. Ecol. 40, 360–371. https://doi.org/10.1046/
j.1365-2028.2002.00395.x.
Teren, G., 2016. Elephants and woody plant diversity: spatio-temporal dynamics of the Linyanti woodland, northern Botswana (PhD Thesis). University of the
Witwatersrand, Faculty of Science, School of Animal, Plant ….
Thouless, C.R., 1995. Long distance movements of elephants in northern Kenya. Afr. J. Ecol. 33, 321–334.
van de Water, A., Di Minin, E., Slotow, R., 2022. Human-elephant coexistence through aligning conservation with societal aspirations. Glob. Ecol. Conserv. 37,
e02165. https://doi.org/10.1016/j.gecco.2022.e02165.
Viljoen, P.J., 1988. The Ecology of the Desert-Dwelling Elephants Loxodonta africana (Blumenbach, 1797) of the Western Damaraland and Kaokoland. University of
Pretoria, South Africa.
Wall, J., Wittemyer, G., Klinkenberg, B., LeMay, V., Douglas-Hamilton, I., 2013. Characterizing properties and drivers of long distance movements by elephants
(Loxodonta africana) in the Gourma, Mali. Biol. Conserv. 157, 60–68. https://doi.org/10.1016/j.biocon.2012.07.019.
Wato, Y.A., Prins, H.H., Heitk¨
onig, I.M., Wahungu, G.M., Ngene, S.M., Njumbi, S., Van Langevelde, F., 2018. Movement patterns of African elephants (Loxodonta
africana) in a semi-arid savanna suggest that they have information on the location of dispersed water sources. Front. Ecol. Evol. 6, 167.
Western, D., Lindsay, W.K., 1984. Seasonal herd dynamics of a savanna elephant population. Afr. J. Ecol. 22, 229–244.
White, L.J., 1994. Sacoglottis gabonensis fruiting and the seasonal movements of elephants in the Lop´
e Reserve, Gabon. J. Trop. Ecol. 10, 121–125.
Williamson, D.T., Mbano, B., 1988. Wildebeest mortality during 1983 at lake Xau, Botswana. Afr. J. Ecol. 26, 341–344.
Williamson, D., Williamson, J., Ngwamotsoko, K.T., 1988. Wildebeest migration in the Kalahari. Afr. J. Ecol. 26, 269–280.
Williamson, D., Williamson, J., 1984. Botswana’s fences and the depletion of Kalahari wildlife. Oryx 18, 218–222.
Wittemyer, G., Getz, W.M., Vollrath, F., Douglas-Hamilton, I., 2007. Social dominance, seasonal movements, and spatial segregation in African elephants: a
contribution to conservation behavior. Behav. Ecol. Sociobiol. 61, 1919–1931. https://doi.org/10.1007/s00265-007-0432-0.
Yang, I., Jeon, W.H., Moon, J., 2019. A study on a distance based coordinate calculation method using Inverse Haversine Method. J. Digit. Contents Soc. 20,
2097–2102. https://doi.org/10.9728/dcs.2019.20.10.2097.
Young, K.D., Van Aarde, R.J., 2011. Science and elephant management decisions in South Africa. Biol. Conserv. 144, 876–885. https://doi.org/10.1016/j.
biocon.2010.11.023.
Zacarias, D., Loyola, R., 2018. Distribution modelling and multi-scale landscape connectivity highlight important areas for the conservation of savannah elephants.
Biol. Conserv. 224, 1–8. https://doi.org/10.1016/j.biocon.2018.05.014.
Further reading
Child, G., 1972. Observations on a wildebeest die-off in Botswana. National Museums of Rhodesia.
K. Sianga et al.
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