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Status and trends of the elephant population in the Tsavo-Mkomazi ecosystem



This paper updates the data on the population status of elephants in the Tsavo-Mkomazi ecosystem. Data were acquired through aerial census of elephants in the ecosystem, from 7 to 12 February 2011. The census covered an area approximately 48,319 km2, which was divided into 44 counting blocks. Each block was assigned to a specific aircraft; the crew consisted of a pilot, front-seat observer and two rear-seat observers for the four-seater light aircraft, and a pilot and an observer for a two-seater light aircraft. The census lasted five days and involved nine light aircraft and about 252 hours of actual counting time, representing a mean search rate of about 191 km2/hr. A total of 12,573 elephants were counted, indicating a modest increase of 2% after the 2008 census and a 96% increase after the 1988 census (n = 6,399). Most elephants (69%, n = 8,614 individuals) were counted inside the protected areas; about 31% (n = 3,859 individuals) were outside protected areas. About 50% of the elephants (n = 6,214) were in Tsavo East National Park, 22% (n = 2,751) in the Taita ranches and 17% (n = 2,142) in Tsavo West National Park. A programme of providing water to elephants in the northern parts of Tsavo is recommended as well as electric fencing and establishment of administration and security structures at South Kitui National Reserve. This will create more space for the increasing population of elephants as well as improve their security.
38 Pachyderm No. 53 January–June 2013
Ngene et al.
Status and trends of the elephant population in the
Tsavo–Mkomazi ecosystem
Shadrack Ngene,1* Steve Njumbi,2 Martha Nzisa,1 Kenneth Kimitei,1 Joseph Mukeka,3
Shadrack Muya,4 Festus Ihwagi 5 and Patrick Omondi 6
1 Kenya Wildlife Service, Biodiversity Research and Monitoring, Tsavo Conservation Area, PO Box 14, Voi, Kenya
2 International Fund for Animal Welfare, PO Box 25399 – 00603, Nairobi, Kenya
3 Kenya Wildlife Service, Biodiversity Research and Monitoring, GIS Unit, PO Box 40241 – 00100, Nairobi, Kenya
4 Jomo Kenyatta University of Agriculture and Technology, PO Box 62000 – 00200, Nairobi, Kenya
5 Save the Elephants, PO Box 54667 – 00200, Nairobi, Kenya
6 Kenya Wildlife Service, Biodiversity Research and Monitoring, Species Conservation and Management, PO
Box 40241 – 00100, Nairobi, Kenya
*Corresponding author email: or
This paper updates the data on the population status of elephants in the Tsavo–Mkomazi ecosystem. Data were
acquired through aerial census of elephants in the ecosystem, from 7 to 12 February 2011. The census covered
an area approximately 48,319 km2, which was divided into 44 counting blocks. Each block was assigned to a
specic aircraft; the crew consisted of a pilot, front-seat observer and two rear-seat observers for the four-seater
light aircraft, and a pilot and an observer for a two-seater light aircraft. The census lasted ve days and involved
nine light aircraft and about 252 hours of actual counting time, representing a mean search rate of about 191
km2/hr. A total of 12,573 elephants were counted, indicating a modest increase of 2% after the 2008 census and
a 96% increase after the 1988 census (n = 6,399). Most elephants (69%, n = 8,614 individuals) were counted
inside the protected areas; about 31% (n = 3,859 individuals) were outside protected areas. About 50% of the
elephants (n = 6,214) were in Tsavo East National Park, 22% (n = 2,751) in the Taita ranches and 17% (n =
2,142) in Tsavo West National Park. A programme of providing water to elephants in the northern parts of
Tsavo is recommended as well as electric fencing and establishment of administration and security structures
at South Kitui National Reserve. This will create more space for the increasing population of elephants as well
as improve their security.
Additional key words: aerial census, carcass, drought
Ce document met à jour les donnés sur la situation des populations d’éléphants dans l’écosystème de Tsavo-
Mkomazi. Les données ont été acquises grâce à un recensement aérien des éléphants dans l’écosystème, du 7
au 12 février 2011. Ce recensement a couvert une supercie d’environ 48.319 km2, qui était divisée en 44 blocs
de comptage. On avait assigné à chaque bloc un avion spécique, l’équipage étant composé, pour l’avion léger
à quatre places, d’un pilote, d’un observateur sur le siège avant et de deux observateurs sur le siège arrière, et
pour un avion léger biplace, d’un pilote et d’un observateur. Le recensement, auquel ont participé neuf avions
légers, a pris cinq jours et environ 252 heures de temps de comptage réel, ce qui représente un taux de recherche
moyen d’environ 191 km2/heure. Un total de 12.573 éléphants ont été dénombrés, ce qui indique une légère
augmentation de 2% après le recensement de 2008 et une augmentation de 96% après le recensement de1988 (n
= 6.399). La majorité des éléphants (69%, n = 8.614 éléphants) ont été comptés à l’intérieur des aires protégées;
environ 31% (n = 3.859 éléphants) étaient en dehors des aires protégées. Environ 50% des éléphants (n = 6,214)
étaient dans le Parc national de Tsavo-Est, 22% (n = 2,751) dans les ranchs de Taita et 17% (n = 2,142) dans
Pachyderm No. 53 January–June 2013 39
Status and trends of the elephant population in the Tsavo–Mkomazi ecosystem
le Parc national de Tsavo Ouest. Un programme d’approvisionnement en eau pour les éléphants au nord de
Tsavo est recommandé ainsi que les clôtures électriques et une mise en place des structures administratives
et sécuritaires dans la Réserve nationale du sud-Kitui. Cela va créer plus d’espace pour l’augmentation de la
population d’éléphants ainsi qu’améliorer leur sécurité.
Mots clés supplémentaires : recensement aérien, carcasse, sécheresse
parks. The proportion of ‘recent’ carcasses however
did not change signicantly, conrming illegal killing
was still taking place through 1988 when the ‘recent’
carcass ratio peaked at 6.69%. Despite this, the 1989
count was the rst authoritative conrmation that the
elephant population was on a recovery course, a trend
observed till 2008.
The 2002 wet season survey was undertaken as part
of Kenya Wildlife Service (KWS) and Monitoring of
Illegal Killing of Elephants (MIKE) joint initiatives
to establish the status of Tsavo’s elephant population
and provide baseline data on poaching. The count
revealed that the Tsavo population had increased by
5% since 1999, from 8,068 to 9,284 (Kahumbu et al.
1999). Fifty percent (n = 10) of the recent carcasses
were recorded in Galana, where poaching pressure
was high in the 1970s and 1980s. The gure could
have been an underestimate as the thick vegetation
may have obscured some carcasses. The census noted
a remarkable increase in livestock in the protected
areas from about 820 animals in 1999 to about 5,190
animals in 2002 (Omondi et al. 2002).
It is important to caution against direct comparisons
of results of past aerial counts due to different
methodologies, counting effort and climatic conditions
between the years (Douglas-Hamilton et al. 1994). For
instance, this possibly explains the large discrepancies
observed between sample and total counts in the
1970s. Over the years, elephant densities varied
considerably both by blocks and through time, from
as low as 0.002 elephants/km2 in Galana to as high as
0.921 elephants/km2 in Tsavo East south (Douglas-
Hamilton et al. 1994; Kahumbu et al. 1999; Omondi et
al. 2002; Omondi and Bitok 2005; Omondi et al. 2008).
Surface water availability and security are believed to
be the major factors inuencing elephant distribution.
In 2002, a dramatic shift in elephant distribution was
observed between Tsavo East north and Tsavo East
south, as the former had received more rainfall prior
to the count (Omondi et al. 2002). Understanding these
ecosystem-use dynamics by elephants and other large
mammals is important in their management.
The Tsavo ecosystem is home to Kenya’s largest
elephant population (Blanc et al. 2007). This popula-
tion was over 35,000 animals by the end of 1974 (Cobb
1976) and about 11,733 in 2008 (Omondi et al. 2008).
The February 2011 dry season census was conducted one
year after the severe drought of 2009 to early 2010 when
it was feared that many elephants (Loxodonta africana)
had succumbed, as had happened during the unusually
dry conditions of 1970 and 1971 that led to elephant
mortality of unanticipated magnitude. Between 6,000
and 9,000 elephants died in the eastern sector of Tsavo
National Park (Coreld 1973; Cobb 1976).
The ecosystem has been the subject of detailed
sample and total aerial counts since the early 1960s.
Recent total counts include Olindo et al. (1988),
Douglas-Hamilton et al. (1994), Kahumbu et al.
(1999), Omondi et al. (2002), Omondi and Bitok
(2005) and Omondi et al. (2008). Past sample counts
include those by Cobb (1976), Leuthold (1976),
WCMD (1976), IUCN (1978) and Inamdar (1996).
Both sample and total counts in the 1970s showed
remarkably high numbers of elephants, though sample
counts appear to have overestimated the numbers by
a wide margin—almost twice the total count gures.
The 1988 counts showed a 75% decline in elephant
numbers within the protected areas and a further 87%
decline in the adjacent non-protected areas since the
1972 total counts (Olindo et al. 1988). Two major
factors have contributed to the observed overall
continental decline of elephant numbers: reduced
carrying capacity of Africa for elephants due to habitat
change, and hunting for ivory (Milner-Gulland and
Beddington 1993a,b). Since 1988, there has been
a steady increase in elephant numbers. The 1988
distribution of ‘recent’ carcasses conrmed heavy
poaching was still rampant, especially on the periphery
of the parks, and the older carcasses conrmed that
poaching had taken place in the heart of the reserves
in the early 1980s. The distribution of elephants in
1989 conrmed that elephants previously counted
along the periphery had moved further inside the
40 Pachyderm No. 53 January–June 2013
Ngene et al.
The goal of the 2011 aerial
survey was to sustain the long-term
aerial monitoring of elephants in the
Tsavo–Mkomazi ecosystem. This
consistent monitoring programme
began in early 1999 and has been
closely and accurately monitoring
the status and trends of elephants
and other large mammals since
then. Therefore, it is important
to continue with the tri-annual
aerial census of elephants in the
Tsavo–Mkomazi ecosystem. The
information generated will show
the number, density and distribution
of elephants in the ecosystem.
The information will be used by
park managers and policymakers
to make management decisions
regarding the management of
emerging trends and distribution
of elephants in the ecosystem.
Materials and methods
Study site
The Tsavo–Mkomazi ecosystem
consists of an area of about 48,319
km2 (Cobb 1976). The ecosystem
lies between 2–4°S, and 37.5–
39.5ºE. Common rivers traversing
the ecosystem include Galana, Voi,
Tiva, Tsavo and Athi (Figure 1).
The ecosystem’s mean annual
rainfall varies locally between 250
and 500 mm (Leuthold 1978). Most
of the rain falls in two rainy seasons:
in March–May and November–
December (Tyrrell and Coe 1974);
June through October constitutes a
long dry season (Leuthold 1978).
The terrain of the Tsavo–
Mkomazi ecosystem is generally
at and undulating in the southeastern and northern
sections (Leuthold 1978). Mukeka (2010) provides
a detailed description of the ecosystem’s terrain.
Generally, the area lies about 300–500 m above sea
level. The soils of the Tsavo–Mkomazi ecosystem
show a wide range in depth, colour, drainage condition,
structure and chemical and physical properties. The
soils are rich in quartz and ferruginous gravel, with
ner sand cemented by a red lateritic crust. Sand and
gravel of the alluvial soils are cross-bedded together
along the river loops of the Galana (Leuthold 1978).
The vegetation consists of remnants of formerly
extensive CommiphoraAcacia woodlands that
9A 10A
major river
counting block
Taita ranch
national boundary
Tsavo East NP north
Tsavo East NP south
Tsavo West NP
Chyulu National Park (NP)
17 16
G3 G4
G5 G6
0 12.5 25 50 75 100 km
Mkomazi NP (north, central and south)
South Kitui
National Reserve
Figure 1. Counting blocks used during the aerial count of elephants and
other large mammals in the Tsavo–Mkomazi ecosystem (7–12 February
2011). Blocks 7B, 9A, 10A, 12B and RB cover the Taita ranches, blocks
G1–G6 represent Galana ranches, blocks 24 and 25 represent other
ranches east of the ecosystem, and blocks 13, 14 and 15 represent the
Ndii–Ndara plains. (Source: KWS, 2011.)
Pachyderm No. 53 January–June 2013 41
Status and trends of the elephant population in the Tsavo–Mkomazi ecosystem
ight paths. The GPS units were set to Universal
Transverse Mercator kilometre grids on both north
and south axes. The teams took off at dawn, ensuring
that counting started before the day got hot. Parallel
lines were own, whose interval was determined by
the front observer and the pilot based on terrain and
visibility. Fuel was strategically distributed in the
various airstrips in the ecosystem for convenience
of refuelling from blocks distant from the counting
centre. In a few blocks, the topography inuenced the
ight paths as rugged terrain was avoided.
Data recording and cleaning
The aerial census took place from 7 to 12 February
2011. Most of the crew members were highly
experienced. Test ights were conducted a day before
the actual counting commenced to familiarize and
refresh the crew. Speeds of approximately 130–180
have been destroyed or at least thinned out
by elephants (Cobb 1976). The vegetation
communities in the ecosystem are described
in detail by Napier-Bax and Sheldrick (1963),
Laws (1969, 1970), Tyrrell and Coe (1974) and
Mukeka (2010).
The major herbivores are elephant
(Loxodonta africana), African buffalo
(Syncerus caffer), eland (Taurotragus oryx
pattersonianus), fringe-eared oryx (Oryx
beisa callotis), Coke’s hartebeest (Alcelaphus
buselaphus cokii), Burchell’s zebra (Equus
burchelli), impala (Aepyceros melampus),
giraffe (Giraffe camelopardalis) and Grant’s
gazelle (Gazella granti) (Cobb 1976).
Census blocks design
The aerial count followed the method described
by Douglas-Hamilton (1996). The aircraft
consisted of two-seater crew Supercabs or
four seater crew Cessnas. Forty-four counting
blocks, as designed for previous censuses,
were adopted for ease of comparing ndings.
Flight lines of 1-km spacing were designed
to ensure that all elephant herds and large
mammals were sighted and counted (Figure 2).
The blocks are dened mostly by recognizable
features like roads, rivers, hills and protected
area boundaries, except for the Voi triangle
and blocks 13–17. The blocks were of suitable
sizes that could be own in a day by one or
two teams. The average block size was 1,098
km² (SE = ±445 km²; n = 44). The smallest block
(block 21) measured 248 km² and the largest (block
12C) 2,008 km². In the larger blocks, two planes were
deployed to count simultaneously to ensure counting
was completed within a day.
Aircraft and crew
Nine xed-wing aircraft (Cessna and Husky) with
high wings to give an unobstructed ground view were
used during the six-day event. The crew comprised
a pilot and one front-seat observer for a two-seater
aircraft, and a pilot, one front-seat observer and two
rear-seat observers for a four-seater aircraft. Each
team was given the ight maps of assigned blocks
the evening before to allow the team to plan for the
next day. A geographical positioning system (GPS)
was used for navigation and to record waypoints and
major river
block boundary
ight lines
4006080 100 km20
Figure 2. Flight lines used during the aerial count (7–12
February 2011) in the Tsavo–Mkomazi ecosystem.
42 Pachyderm No. 53 January–June 2013
Ngene et al.
km/hr and heights of about 200–400 ft (60–120 m)
above ground level were maintained. Blocks separated
by rivers were counted simultaneously to minimize
double count or omission due to elephants crossing the
river. Pilots ew overlaps of approximately 1–2 km
into the adjacent blocks to ensure that herds moving
into the block were not missed by either team. Both
dead and live elephants were counted. Where large
herds were encountered, the pilots circled to give
observers ample time to count. Elephant carcasses
were classied as ‘fresh’, ‘recent’, ‘old’ or ‘very
old’, as described by Douglas-Hamilton and Hillman
(1981). For analyses, the rst and second categories
were pooled as ‘recent’, and the third and fourth as
‘old’. Standard codes were used to denote elephants
and the different categories of carcasses. Front-seat
observers cleaned the data sheets when necessary
before handing them over to the data entry team.
Waypoints and tracks were downloaded onto ArcGIS
9.3. The tabulated species data were added onto
the ArcGIS software and a spatial join was created
based on the waypoint (Mitchell 2009). The le was
converted into a shape le for each block. Duplicates in
the zones of overlap of adjacent blocks were identied
and corrected before merging all datasets into one for
analysis and preparation of distribution maps.
Data analysis
For regression analysis, data were pooled for areas
that were consistently surveyed from 1988 to 2011.
These areas included Tsavo East (north), Tsavo East
(south), Tsavo West, Mkomazi NP, and Galana and
Taita ranches. The regression analysis followed the
procedures described by Zar (1996). Fourth-order
polynomial analysis was used to get the line of best
t during the regression analysis (Zar 1996).
The observed rate of population increase (¯r ) was
calculated from the natural logarithms of the total
number of elephants counted in 1988 and 2011 using
the formula (Caughley 1977):
¯r = logeNt – logeN0
where loge = natural logarithm; Nt = total number
of elephants counted in 2011; N0 = total number of
elephants counted in 1988.
The orientation of elephant distribution and the
centre of their concentration were analysed using the
standard deviational ellipse and mean centre (Esri
1997; Mitchell 2009). General distribution patterns
(random, dispersed or clustered) and distribution of
herd sizes were analysed for elephants. We tested
for the general distribution patterns of the elephants
using the Getis-Ord general G statistic as described
by Mitchell (2009). The distribution of different herd
sizes was mapped using the hot/cold-spot analysis;
Getis-Ord Gitrations of large (hot spots) and small
(cold sports) groups of elephants were sighed during
the aerial survey (Esri 2007; Mitchell 2009). Z scores
were used for interpretation of signicance levels
of statistical tests (Zar 1996). High positive Z score
indicates a higher clustering for locations with large
numbers of elephants while negative Z score indicates
clustering of areas with small groups of elephants.
The results were interpreted as described in detail by
Mitchell (2009).
To analyse the relationship between elephant
distribution and water pans (dry and wet) and rivers, a
kernel density of the elephant was created as described
by Mitchell (2009) using a search radius of 24 km
(Mukeka 2010). A simple density surface for water
pans (dry and wet) and distance surface for rivers was
created as described by Mitchell (2009). Using spatial
analyst tool in ArcGIS 9.3, the raster cell values of the
respective surfaces were extracted onto the elephant
count point shape-le (Esri 2007). Then the extracted
values were exported into an MS Excel spreadsheet to
obtain a set of elephant density data against distance
to water pans and rivers. A simple correlation analysis
was performed using this data as described by Zar
(1996). The strength of the correlations was interpreted
following guidelines described by Fowler et al. (1998).
The proportion of recent to old was calculated as
an index of the previous year’s mortality (Douglas-
Hamilton 1996), noting that 2009 to early 2010 was
marked by a severe drought.
Aerial census effort
A total of about 252 hours of actual counting time
was spent during the census. This represents a mean
search rate of about 191 km2/hr or 5.2 hours for every
1,000 km2 in a counting area of about 48,319 km2. The
search rate was more intense than the aerial counts in
1988, 1994 and other preceding counts (see Olindo
et al. 1988; Douglas-Hamilton et al. 1994; Omondi
et al. 2002; Omondi and Bitok 2005; Omondi et al.
Pachyderm No. 53 January–June 2013 43
Status and trends of the elephant population in the Tsavo–Mkomazi ecosystem
2008) although the difference in the number
of hours spent per 1,000 km2 during this
census and those of past aerial census (1988
to 2008) was not statistically signicant.
Status and trends of elephants
The estimate for the February 2011 aerial
census was 12,573 elephants in the Tsavo–
Mkomazi ecosystem, representing a modest
increase of about 2% in the last three years
(Table 1). Of these elephants 69% (n =
8,614) were counted inside the parks and
31% (n = 3,859) outside the parks. About
50% (n = 6,214) of the elephants were in
Tsavo East NP, 22% (n = 2,751) in the Taita
ranches and 17% (n = 2,142) in Tsavo West
NP (Table 1). The number of elephants
increased from about 6,399 in 1988 to
about 12,573 in 2011, which represents a
96% increase in 23 years. From 1999 (n =
9,447), the population increased by 33%. A
fourth-order polynomial regression analysis
on trend of elephant numbers from 1988
to 2011 showed an increase in elephant
population during the period (R2 = 0.99, n =
9, Figure 3). The estimated observed rate of
population growth over the 23-year period
was 0.68, representing an approximate
annual growth rate of 0.03.
Distribution and density of
Figure 4 shows the distribution of elephants
in the ecosystem. Most of the herds were
found in Tsavo East NP, within about 45
km north and south of the Galana River.
High densities of about 1 elephant/km2
were recorded in Tsavo East NP, south of
the Galana River (Figure 5).
The elephants exhibited a highly
clustered distribution (Z score = 5.36,
P = 0.01, critical value = 2.58). Taita
ranches have the largest herds of elephant
concentration while the smallest herds are
found in Tsavo East north of the Galana
River. The mean centre of the distribution
was within the Ndara plains in Tsavo East
NP, south of the Galana River (Figure 6).
Elephants occurred as individuals (n = 213
Table 1. Elephants counted in the Tsavo–Mkomazi ecosystem from 1962 to 2011 (no.)
Area 2011 2008 2005 2002 1999 1994 1991 1989 1988 1978* 1973 1972 1970* 1969* 1965* 1962
Tsavo East (N) 2,094 4,118 2,499 4,089 1337 399 450 134 770 220 9,011 6,435 0 6,619 8,056 4,073
Tsavo East (S) 4,120 3,731 3,896 2,087 3221 2,733 3,436 3,020 2,283 2,469 3,955 6,633 6,008 5,709 4,744 1,358
Tsavo West 2,142 2,161 2,626 2,168 2,119 3,132 1,233 2,106 1,274 1,938 9,208 4,328 6,592 8,134 2,238 1,394
Chyulu NP 135 131
South Kitui NR 0 0 0 0
Mkomazi NP 256 8 41 63 77 302 131 11 93 667 2,067
Galana 398 308 11 14 27 46 50 74 90 1,076 500 4,379 2,964 3,540
Taita 2,751 1,108 1,292 828 1,245 287 1,413 642 853 79 1,235 500
Rombo 0 0 31 2 12 446 – 193 – – – – – – – –
Other blocks 509 130 1 35 30 26 50 46 300 100
Outside 168 38 1,376 1,391 1,107 1,644 966 1,036
Total (parks) 8,614 10,149 9,062 8,344 6,754 6,566 5,250 5,271 4,420 5,294 22,174 19,463 12,600 20,462 15,038 6,825
Total (non-parks) 3,959 1,584 2,680 940 2,693 1,466 3,157 1,728 1,979 1,155 500 5,914 100 3,464 – 3,540
Total 12,573 11,733 11,742 9,284 9,447 8,032 8,407 6,999 6,399 6,449 22,674 25,377 12,700 23,926 15,038 10,365
Source: Leuthold 1973; Olindo et al. 1988; Douglas–Hamilton et al. 1994; Kahumbu et al. 1999; Omondi et al. 2008
* Data in that year were acquired using the sample counts method; in years without *, data were acquired using the total count method. From 1999 to 2011, data were collected in late
January or early February (dry season); from1962 to 1994 data were collected in June, immediately after the April–May wet season.
N = north, S = south, NP = national park, NR = national reserve.
– Periods when no aerial census took place in the location.
44 Pachyderm No. 53 January–June 2013
Ngene et al.
herds) or in groups (n = 1,195 herds). The herd sizes
ranged from 2 to 189 animals with ±95% condence
interval of herd sizes being 10–11 elephants. The
observed and expected size of elephant herds was
signicantly different (Χ 2 = 1,725, df = 9, P <
0.05). Larger herds of elephants were found in the
Taita ranches, southern parts of Tsavo West NP
(Njukini and Jipe areas) and north Mkomazi NP
(Figure 7). The smallest herds of elephants were
counted north to northeast and south of the Galana
River in Tsavo East NP (Figure 7). High densities
of elephants occurred close to wet water pans and
rivers; low densities were recorded near dry water
pans (wet water pans: r = 0.90, n = 1,408, P < 0.05;
dry water pans: r = 0.19, n = 1,408, P < 0.05). There
was a weak negative relationship between elephant
density and distance to water pans (r = 0.37; n =
1408; P < 0.05).
Number, density and
distribution of elephant
A total of 567 elephant carcasses were
recorded during this census. Table 2
provides a summary of the number
of carcasses counted during the aerial
census, including the carcass ratio. In
2008 there were only 8 recent carcasses;
in 2011, 48 recent carcasses were
seen, which represents an increase of
about 600%. The carcass ratio also
increased from 0.6% in 2008 to 4.3%
in 2011. High carcass density (about
0.031–0.037 km2) was recorded in
Tsavo East NP south of the Galana River
(Figure 8), and modest (about 0.02 km2)
and lowest (0.001–0.008 km2) carcass
densities were recorded in Tsavo East
NP north of the Galana River and Tsavo
West NP; and, the rest of the remaining
areas (Figure 8). Figure 9 provides a
summary of the general distribution of
the elephant carcasses according to age
class in the Tsavo–Mkomazi ecosystem.
9A 10A
major river
protected area
Taita ranches
national boundary
17 16
G3 G4
G5 G6
counting block
0510 20 30 40 km
Figure 4. Distribution of elephant herds
in the Tsavo–Mkomazi ecosystem. No
elephants were counted in South Kitui
National Reserve (SK).
= –0.141x4 + 1,135.x3 – 3E + 06x2 + 5E + 09x – 2E + 12
R2 = 0.999
Number of elephants (’000s)
1985 1990 1995 2000 2005 2010 2015
Figure 3. Total aerial count estimates of the Tsavo–
Mkomazi ecosystem elephant population, 1988–2011.
Pachyderm No. 53 January–June 2013 45
Status and trends of the elephant population in the Tsavo–Mkomazi ecosystem
Figure 5. Elephant densities in the Tsavo–Mkomazi
ecosystem (7–12 February 2011).
Tanzania Indian
Tsavo River Galana River
Tiva River
Athi River
200406080 100 km
Elephant densities (no./km2)
9A 10A
Chyulu NP
Tsavo East NP
South Kitui
low: 0
high: 1.58
major river
mean centre
protected area
Taita ranches
national boundary
standard deviation ellipse
17 16
G3 G4
G5 G6
counting block
0510 20 30 40km
West NP
Figure 6. Kernel density of elephants in the Tsavo–
Mkomazi ecosystem; mean centre and standard
deviational ellipses based on data collected 7–12
February 2011. (J Mukeka, KWS GIS section)
Table 2. Elephants and elephant carcasses counted in theTsavo–Mkomazi ecosystem (no.), 1988–2011
dead (no.)
Total dead
Carcass ratio
(dead/dead plus
live) (%)
Std natural
mortality @ 4%
Carcass ratio
recent (%)
1988 5,363 162 2,421 31.1 215 2.9
1989 6,033 115 1,752 22.5 241 1.9
1991 6,763 4 1,210 15.2 271 0.1
1994 7,371 1 1,362 15.6 295 0.0
1999 8,068 6 427 5.0 323 0.1
2002 9,284 14 302 3.2 371 0.2
2005 10,397 6 138 1.3 416 0.1
2008 11,696 4 68 0.6 468 0.0
2011 12,573 48 567 4.3 497 0.4
Old carcasses are calculated by subtracting recent dead from total dead. The old carcasses include ‘very old’ and ‘old’
carcasses; recent dead include ‘fresh’ and ‘recent’ carcasses.
46 Pachyderm No. 53 January–June 2013
Ngene et al.
The results revealed that the population of elephants
in the Tsavo–Mkomazi ecosystem increased from
11,733 in 2008 to 12,573 in 2011, representing a 2%
increase in three years. Compared with the rate of
increase between 2005 and 2008 (4%), this represents
a 2% decrease in population change between 2008
and 2011. The decreasing rate of increase could be
attributed mainly to natural mortality (Figure 10). The
data indicate that natural causes of elephant deaths
were high between 2008 and 2010 (84%, n = 674)
compared with deaths from 2005 to 2007 (16%; n =
131). Specically, the 2009 and early 2010 droughts
were responsible for these natural deaths, with more
deaths in 2009 (83%, n = 366) and 2010 (52%, n = 96)
than in previous years (Figure 10). Of the 674 elephant
carcasses reported in the study area between 2008 and
2010, 86% (n = 576) had the two tusks recovered, 1%
(n = 9) had one tusk recovered and 13% (n = 89) had
no tusks recovered (KWS-TCA 2011). Also, most
of the carcasses were classied as ‘old’ (91%, n =
517), a category for elephants that had been dead for
more than one year (Douglas-Hamilton 1996). This
period coincides with the period when the study site
experienced a drought. The drought led to scarcity of
forage and water culminating in the starvation of many
elephants. Most of the old carcasses were recorded
in Tsavo East and northern parts of Tsavo West NPs;
these were the areas that lacked water during the
2009 drought. Elephants are water-dependent animals
(Ngene et al. 2009), therefore many could have died
during the period due to lack of water.
Search effort during aerial counts determine the
020406080 100 km
> 2.0
1.0 to 2.0
–1.0 to 1.0
–2.0 to –1.0
< –2.0
Athi River
Tiva River
Galana River
Tsavo River
Carcass densities (no./km2)
Figure 8. Elephant carcass densities (no./km2) in the
Tsavo–Mkomazi ecosystem (early February 2011).
9A 10A
> 2.0
1.0 to 2.0
–1.0 to 1.0
–2.0 to –1.0
< –2.0
GiZ core
Taita ranches
Tsavo East NP north
Tsavo East NP south
Tsavo West NP
Chyulu West
Elephant hot/cold spots
Galana ranch
Mkomazi NP
other areas
17 16
G2 G3
G5 G6
Figure 7. A hot spot analysis of the locations with
different sizes of elephant herds in the Tsavo–Mkomazi
ecosystem. Large herds of elephants (Z score = > 1.0)
were recorded in the Taita ranches, northern parts of
Mkomazi NP and southern and western parts of Tsavo
West NP. High positive values of Z scores indicate
locations where large groups of elephants occurred
(hot spots) whereas low negative values of Z scores
indicate where smaller groups of elephants (cold
spots) were sighted during the aerial survey.
Pachyderm No. 53 January–June 2013 47
Status and trends of the elephant population in the Tsavo–Mkomazi ecosystem
0510 20 30 40 50 km
9A 10A
very old
Taita ranches
Tsavo East NP north
Tsavo East NP south
Tsavo West
Chyulu West NP
Galana ranch
Mkomazi NP
other areas
17 16
G2 G3
G5 G6
Carcass stage
Figure 9. Spatial distribution of elephant carcasses
according to different age classes in early February 2011.
Most of the carcasses were ‘old’ and ‘very old’.
number of large mammals counted during the
exercise (Douglas-Hamilton et al. 1994). This
report uses the term ‘search effort’ to refer to
the area (km2) covered by the aerial count crew
in one hour (km2/hour) (Douglas-Hamilton et
al. 1994). High and low search efforts result in
higher and lower numbers of the large mammals
being counted (Douglas-Hamilton et al. 1994).
The 2011 aerial census recorded a search effort
of 191 km2/hour, which was higher than for
previous aerial census—321 km2/hour in 1988,
276 km2/hour in 1989, 247 km2/hour in1991, 210
km2/hour in 1994, 242 km2/hour in 2002, 224
km2/hour in 2005, and 213 km2/hour in 2008
(Douglas-Hamilton et al. 1994; Omondi et al.
2008). It is therefore possible that the high number
of elephants counted in 2011 is not because of
actual population increase but due to increased
search effort (Figure 11).
High density of elephants was recorded in the
southern part of Tsavo East NP. The area was also
the mean centre where many groups of elephants
were counted. This area has two permanent rivers
(Galana and Voi) and many water pans, which
are lacking in other parts of the ecosystem.
High densities of elephants were recorded about
1–15 km from the rivers and water points. Since
elephants are water-dependent animals (Estes
1991), their density is expected to be high in
areas within 10–15 km from water points
Number of dead elephants
2006 2007 2008 2009 2010
Natural Illegal *PAC Unknown
Figure 10. Number of dead elephants against causes of elephant mortality in the Tsavo Conservation Area,
2008–2010. Other causes of death include train accidents, sickness and lion predation.
*PAC = problem animal control.
48 Pachyderm No. 53 January–June 2013
Ngene et al.
(Ngene et al. 2009). Analogous ndings were made
for elephants in Marsabit NP and Reserve (Ngene
et al. 2009), Samburu National Reserve in Kenya
(Thouless 1995), Masai Mara Game Reserve in Kenya
(Khaemba and Stein 2000), Maputo Elephant Reserve
in Mozambique (Boer et al. 2000), Serengeti NP in
Tanzania (McNaughton 1990), the Kunene region
in northwest Namibia (Leggett 2006), the northern
Namib Desert (Viljoen 1989), and northern Kenya
(Leeuw et al. 2001).
Despite an increase in the number of carcasses
since the 2008 census (Figure 12), the population is
on the increase. The carcass ratio calculated using
recent carcasses only is very low (0.4%). This further
compels us to believe that most of the carcasses are
attributed to the drought in 2009 and early 2010. Under
conditions of low rainfall, as experienced in preceding
years, the rate of carcass disintegration is minimal
(Douglas-Hamilton and Hillman 1981). As a result,
more carcasses would be sighted during an aerial
census. Similar to the 1970–1971 dry season census
(Coreld 1973), most of the carcasses were recorded
in Tsavo East along the Galana River, where elephant
densities are apparently highest in the ecosystem.
Visibility during the 2011 survey was good as it was at
the height of the dry season when vegetation is limited.
Large herds of elephants were recorded
outside protected areas (Taita and Galana
ranches). Possibly lack of security in these areas,
leading to incidence of elephant poaching, is
forcing the elephants to congregate in large
numbers outside protected areas whereas inside
our secure protected areas, the groups are small.
Similar results have been reported in Meru NP
(Njumbi 1995), Queen Elizabeth NP (Abe 1994)
and Mikumi NP (Moss and Poole 1983).
Conclusions and
From the results and discussion, we conclude:
Elephant numbers in the Tsavo–Mkomazi
ecosytem have continued to increase since
1988, though with a declining rate of 2% over
that of the last three years (2008 to 2011).
This declining rate is attributed mainly to the
drought of 2009 that saw a proportionately
high rate of natural mortality.
The highest elephant densities, of
approximately 1 elephant/km2, were observed
in Tsavo East south of the Galana River.
Elephant distribution in Tsavo–Mkomazi
remains clustered inside the protected areas
of Tsavo East NP along the Galana River and
its tributaries as well as in articial water
points south of the river.
In contrast, congregations of large herds were
recorded outside the protected areas: in the
Taita ranches between Tsavo East and West
NPs. However, isolated large herds were also
observed on the outskirts of Galana ranch,
Number of elephants
y = –0.000x4 + 0.171x3 – 46.15x2 + 5,442.x – 23,157
R2 = 0.988
120 140 160 180 200 220 240 260
Counting time (hours)
Figure 11. Number of elephants counted in the Tsavo–
Mkomazi ecosystem against the total counting hours. (Data
are for 1988, 1989, 1991, 1994, 2002, 2005, 2008 and 2011.)
y = 2E + 119e–0.139x
R2 = 0.76256
Elephant carcass ratio (%)
1986 1990 1994 1998 2002 2006 2010 2014
Figure 12. Trends of elephant carcass ratio in the Tsavo–
Mkomazi ecosystem, 1985–2011.
Pachyderm No. 53 January–June 2013 49
Status and trends of the elephant population in the Tsavo–Mkomazi ecosystem
the southwestern periphery of Tsavo West
NP, and northwestern Mkomazi.
We recommend:
While it is evident that drought, as a natural
regulator, can check the population increase of
the Tsavo–Mkomazi elephant population, there
is need to ensure that human-induced mortality
is minimal through effective anti-poaching and
human–elephant conflict resolution. This will
allow the population to regulate naturally based
on habitat condition and climatic characteristics.
The high density and clustering of elephants
along the Galana and Ndii–Ndara plains, relative
to the rest of the ecosystem, can be explained by
the availability of water. If left unattended, and
with increasing elephant numbers, this situation
could lead to habitat degradation in these high-
density areas. It is recommended, after extensive
environmental impact assessment, to desilt old
water pans and open new water points north of
Tiva River, in the eastern parts of Tsavo East, and
in the central to southern parts of Tsavo West NP. In
this regard, the South Kitui National Reserve at the
extreme northern section of the ecosystem serves
as an obvious focus for future water provision.
The clustering and high density along the Galana
River also has implications: patrols andmobile
unites should be deployed for anti-poaching efforts.
Congregation of large herds as observed in the Taita
ranches, in northern Galana and in southwestern
Tsavo West NP may indicate poaching pressure;
thus security should be directed to these areas. In
addition, ongoing efforts to establish conservancies
in these unprotected areas should be prioritized as a
means of ensuring these critical elephant corridors
and dispersal areas.
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... The TTC is part of the Tsavo ecosystem, where the vast conservation areas host diverse wildlife species and unique wildlife habitats. The ecosystem is a known elephant stronghold, hosting about a 33% of elephants in Kenya (Ngene et al., 2013) and about 3% of Africa's population. Land use practices vary across the TTC, with the major type being conservation, which covers 62% of the county's land area, about 22% is under agriculture and settlements, and the remaining is rangeland mainly used for cattle ranches and pastoralism (County Government of Taita Taveta, 2018). ...
... The HEC incident records over 15 years (2004e2018) were organized into five 3-year groupings arranged consecutively from the earliest to the most recent. The 3-year intervals were applied because total elephant counts are conducted every 3 years (Ngene et al., 2013), hence by using these intervals one census year was automatically included. Additionally, the 3-year interval was preferred to permit comparison of HEC incidents before and after building the new Standard Gauge Railway (SGR) 2014e2016, which is a major linear infrastructure in the area . ...
... Our findings indicate that while no statistically significant difference existed between the five 3-year periods, 2007e2009, 2013e2015, and 2016e2018 stood out with higher proportions of HEC. The 2007e2009 period contains a severe drought in 2009 which afflicted the county following the failed rains in 2008 (Amara et al., 2020), resulting in the death of 366 elephants in the Tsavo ecosystem (Ngene et al., 2013;Wato et al., 2018). Our findings show a negative relationship between rainfall and HEC (Fig. 6) which agrees with other studies that have shown an increase in HEC when received rainfall is below normal (Mariki et al., 2015). ...
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People and wildlife have co-occurred, sharing resources for thousands of years, however, over the last four decades records of human–wildlife conflict have increasingly emerged. Human–elephant conflict is a form of such conflict, resulting from negative interactions between people and elephants. Human–elephant conflict affects local community livelihood and the success of elephant conservation. Tsavo East and Tsavo West National Parks, which cover about 60% of the Taita Taveta County land area, host the single largest elephant population in Kenya. We analysed human–elephant conflict incident data over 15 years (2004–2018) in Taita Taveta County, which forms part of the Tsavo ecosystem in south-eastern Kenya. We identified eight forms of human–elephant conflict comprising elephant threat, crop raiding, property damage, injury to people, human death, elephant death, elephant injury, and livestock death. Three forms of conflict accounted for 97% of the reported incidents, namely elephant threat to humans, constituting the highest number of incidents (62.46%), followed by crop raiding (32.46%) and property damage (2.33%). Conflicts occurred throughout the year, with June to July having the highest number of incidents. Rainfall, distance from the Tsavo national parks, and human population density were used as covariates to explain HEC patterns. This study seeks to provide a detailed evaluation of the spatial–temporal patterns of human–elephant conflict in Taita Taveta County and to yield information useful for human–elephant conflict mitigation and elephant conservation.
... The wildlife census is conducted by the Kenya Wildlife Service (KWS) every three years to establish the status of key species in the Tsavo ecosystem. The census is carried out from fixed-wing aircrafts and the data collection procedure is described in detail in [73]. The animal spatial distribution and densities were further compared with AGB in the studied landscape ( Figure 3). ...
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... African elephant, circuitscape, conservation planning, fences, human-elephant conflict, landscape connectivity, step-selection function of HEC spanning 50 years (Kioko, Kiringe, & Omondi, 2006;Western & Waithaka, 2005) and the area has experienced rapid agricultural expansion-with the percentage of agricultural areas increasing from 925 km 2 (11.9% of the ecosystem) in the 1970s to 3,025 km 2 in the 2010s (38.9% of the ecosystem) (from Amboseli Conservation Programme long-term aerial monitoring). At the same time, the elephant population has grown steadily since the 1970s (Moss et al., 2011) leading to increasing conflict with farmers (Kioko et al., 2006;Ngene et al., 2013;Okello, 2005;Western & Waithaka, 2005). The severity of the conflict is intensified by the loss in biomass available to elephants in the area due to competing livestock grazing pressure (Western, Mose, Worden, & Maitumo, 2015). ...
1.Fencing is one of the most common methods of mitigating human‐wildlife conflicts. At the same time, fencing is considered one of the most pressing threats emerging in conservation globally. Although fences act as barriers and can cause population isolation and fragmentation over time, it is difficult to quantitatively predict the consequences fences have for wildlife. 2.Here, we model how fencing designed to mitigate human‐elephant conflict (HEC) on the Borderlands between Kenya and Tanzania will affect functional connectivity and movement corridors for African elephants. Specifically, we (1) model functional landscape connectivity integrating natural and anthropogenic factors; (2) predict seasonal movement corridors used by elephants in non‐protected areas; and (3) evaluate whether fencing in one area can potentially intensify human‐wildlife conflicts elsewhere. 3.We used GPS movement and remote sensing data to develop monthly step‐selection functions to model functional connectivity. For future scenarios, we used an ongoing fencing project designed for HEC mitigation within the study area. We modelled movement corridors using least‐cost path and circuit theory methods, evaluated their predictive power and quantified connectivity changes resulting from the planned fencing. 4.Our results suggest that fencing will not cause landscape fragmentation and will not change functional landscape connectivity dramatically. However, fencing will lead to a loss of connectivity locally and will increase the potential for HEC in new areas. We estimate that wetlands, important for movement corridors, will be more intensively used by the elephants, which may also cause problems of overgrazing. Seasonal analysis highlights an increasing usage of non‐protected lands in the dry season and equal importance of the pinch point wetlands for preserving overall function connectivity. 5.Synthesis and applications. Fencing is a solution to small‐scale human‐elephant conflict problems but will not solve the issue at a broader scale. Moreover, our results highlight that it may intensify the conflicts and overuse of habitat patches in other areas, thereby negating conservation benefits. If fencing is employed on a broader scale, then it is imperative that corridors are integrated within protected area networks to ensure local connectivity of affected species. This article is protected by copyright. All rights reserved.
Tsavo Trust is an action‐orientated, field‐based, not‐for‐profit conservation organization headquartered in Tsavo, Kenya. In association with Kenya Wildlife Service and other partners, Tsavo Trust utilizes a unique strategy to work on direct wildlife‐conservation projects. Tsavo Trust also engages with specific local communities in the stewardship of conservancies, in order to encourage participation in conservation activities that benefit the marginalized people who live on the border of the formal Protected Area. Tsavo Trust recognizes the importance of a holistic approach to biodiversity conservation, using a combination of professional wildlife conservation activities, grass‐roots community engagement, valued partnerships and committed supporters to create a virtuous circle for the protection of Tsavo. The mission is to conserve the vast wilderness of the Tsavo Conservation Area, which encompasses Kenya's biggest Protected Area, and is home to Kenya's largest elephant population, including several iconic ‘Tuskers’, and numerous high‐value species. Tsavo Conservation Area is one of the few truly wild places with significant wildlife left in Africa. This national heritage is under threat and faces multiple challenges, including wildlife crime, climate change and habitat loss. At the time of writing, the Tsavo elephant population contains eight bull ‘Tuskers’ and five iconic cow ‘Tuskers’, as well as c. 26 younger bulls that may emerge as ‘Tuskers’ in the next 5 years. Tsavo Trust's work focuses on four core programmes: ‘Wildlife Conservation Program: Big Tusker Project’, ‘Community Conservancy Program’, ‘Animal Welfare Program’ and ‘Conservation Partnerships’. Through the Big Tusker Project, Tsavo Trust, in partnership with Kenya Wildlife Service, provides extra protection for the last ‘Super Tuskers’ of Tsavo using aerial surveillance and mobile ground‐based units. Tsavo Trust is an action‐orientated, field‐based, not‐for‐profit conservation organization headquartered in Tsavo, Kenya. The Tsavo Trust works in association with Kenya Wildlife Service and other partners on direct wildlife conservation projects, and engages with specific local communities in the stewardship of conservancies. Tsavo Trust's mission is to conserve the vast wilderness of the Tsavo Conservation Area, which is home to Kenya's largest elephant population, including several iconic ‘Tuskers’ and ‘Super Tuskers’, and numerous threatened species. This national heritage is under threat and faces multiple challenges, including wildlife crime, climate change and habitat loss. ‘Tuskers’ are exceedingly rare elephants that carry extraordinary tusks that reach the ground. Through the Big Tusker Project, Tsavo Trust, in partnership with Kenya Wildlife Service, provides extra protection for the ‘Super Tuskers’ of Tsavo using aerial surveillance and mobile ground‐based units. (Photo: Richard Moller, Tsavo Trust)
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The illegal killing of elephants, i.e. poaching and human-elephant related mortality, is the greatest immediate threats to elephants. They have led to declining of many populations of elephants in Africa. The Monitoring of Illegal Killing of Elephants (MIKE) program of the Convention on International Trade in Endangered Species (CITES) was set up in the year 2002 as a framework of monitoring trends in illegal killing in 57 African sites. MIKE program seeks to establish the relationships between the levels of illegal killing of elephants and various possible explanatory variables within and beyond the monitoring sites. The effort in implementing MIKE program vary from site to site, and to make the results comparable; a metric referred to as the Proportion of Illegally Killed Elephants (PIKE) out of all recorded deaths in a site has been adopted as the standard measure of severity of illegal killing. Loss of habitat due to the expansion of agriculture and infrastructural developments are the largest long-term threats to elephants. The migratory corridors of elephants and other wildlife in many landscapes have been cut off. The majority of wildlife resides outside formally protected areas on private and community lands. In the landscapes shared by wildlife and humans, competition for resources influences the spatial-temporal distributions of wildlife. Efforts to win the goodwill of private and community landowners regarding hosting of wildlife on their lands are ongoing in many sites across the elephant range. Despite the numerous studies on the nature of risk faced by elephants, fewer studies have focused on the behavioural adaptations of elephants living in those risky landscapes. This thesis sought to understand the site level drivers of illegal killing and how elephants adapt to the threat in Africa’s most intensively monitored site, the Laikipia-Samburu MIKE in northern Kenya. Using field verified records of causes of elephant mortality, the distribution of live elephants, and, the cadastral attributes of land parcels in the ecosystem, the thesis established that land use type is the most important correlate of levels of illegal killing and not its ownership. The study analyses the movement of elephants at hourly, day and night, and overall 24 hr activity cycle in relation to the spatial and temporal variation of the levels of illegal killing. Past studies have given a lot of attention to movement behaviour along corridors. The research in this thesis focusses on movement within core areas. At the hourly time interval, the research showed that elephants walk with lower tortuosity when they are in core areas with higher levels of illegal killing, i.e., higher risk. The study found that elephants move more at night when they are in core areas with higher risk, than when they are in safer core areas. Based on this finding, the research presents a new metric for inferring the levels of risk, i.e., night-day sped ratio. When elephants move from a core area to another one with a different level of risk, they alter their daily activity pattern to include a longer resting phase during the mid-day hours, and this is even more pronounced in core areas closest to permanent human settlements. The study found that as a result of the alteration of activity cycle within 24-hour periods, elephants loose approximately one hour of activity time. The results have the potential use as a remote means of assessing the spatial and temporal variation of risk by analysing elephant movement behaviour remotely thus complimenting patrol based anti-poaching efforts. The study provides new insight into the ecology of elephants living in fear. The confirmed increase of night-time movement potentially predisposes calves to the savannah predators, who are more active at night.
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Full-text available at: ___________________________________________________________________________ Large-mammal populations are ecological linchpins1, and their worldwide decline2 and extinction3 disrupts many ecosystem functions and services4. Reversing this trend requires understanding the determinants of population decline, to predict when and where collapses will occur and to guide effective, cost-efficient conservation and restoration policies2,5. Many correlates of large-mammal declines are known, including slow life histories, overhunting, and habitat destruction2,6,7. However, persistent uncertainty about the effects of one widespread factor—armed conflict—complicates conservation-planning and priority-setting efforts5,8. Case studies reveal that conflict can have either positive or negative local impacts on wildlife8–10, but the direction and magnitude of its net effect over large spatiotemporal scales have not previously been quantified5. Here we show that conflict frequency predicts the occurrence and severity of population declines among wild large herbivores in African protected areas from 1946–2010. Conflict was extensive during this interval, occurring in 71% of protected areas, and conflict frequency was the single most important predictor of wildlife population trends among the variables analyzed. Population trajectories were stable (λ≈1.0) in peacetime, fell significantly below replacement with only slight increases in conflict frequency (≥1 conflict-year every 2–5 decades), and were almost-invariably negative in high-conflict sites, both in the full 65-year dataset and in an analysis restricted to recent decades (1989–2010). Yet total population collapse was infrequent, indicating that war-torn faunas can often recover. Human population density was also correlated (positively) with wildlife population trajectories in recent years; however, we found no significant effect in either interval of species’ body mass, protected-area size, conflict intensity (i.e., human fatalities), drought frequency, presence of extractable mineral resources, or various metrics of development and governance. Our results suggest that sustained conservation activity in conflict zones—and rapid interventions following ceasefires—may help to save many at-risk populations and species.
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Two major factors are likely to have caused recent elephant population declines: carrying capacity reductions and hunting for ivory. A model is developed to disentangle the effects of these two factors on elephant population dynamics since 1814. The model suggests that carrying capacity reductions were a major cause of elephant population declines in the 19th Century and first half of the 20th Century, but that, since 1950, hunting for ivory has been the cause of an increasingly rapid population decline. These results are extremely robust to changes in parameter values within a reasonable range.
The preferred habitats of the African bush elephant, Loxodonta africana, are forestedge, woodland, bushland and wooded or bushed grassland. Increasing amounts of grass in the elephants' diet are correlated with conversion of wood habitats towards grassland, and with increasing elephant mobility, poorer physical condition, and progressively increasing natural regulatory processes leading to decrease in numbers. Elephant occur in discrete unit populations. Each population shows a series of highly contagious instantaneous distributions which, when averaged over a period of time, probably tend, in a uniform habitat, to approach a random or regular distribution. High densities or disturbance by man lead to increase in mean group size and more uneven distribution. The effect on woody vegetation is greater and more lasting than on grass or herbs and usually radiates outwards from the initial centre of damage. The typical cycle begins with destruction of the understory, followed by ringbarking of adult trees, and is accelerated by fire. Several case studies involving forest, moist and dry woodlands, and dry bushland are described which fit this pattern. /// Предпочитаемые местообитания Африканских слонов Loxodonta africana - опушки леса, лесистые местности, кустарник и открытые участки с деревьями или кустами. Увеличение относительного количества травы в диете слонов коррелирует со сменой лесных местообитаний открытыми, увеличением подвижности слонов, ухудшением физических условий и усилением действия естественных регулирующих процессов, ведущих к снижению поголовья. Слоны встречаются отдельными разрозненными популяциями. Каждая популяция образует ряд временных, вступающих в контакт группировок, которые при анализе в среднем за определенный промежуток времени очевидно имеют тенденцию к однородным местообитаниям, и их распределение приближается к рандомическому распределению. Высокая плотность и влияние деятельности человека приводит к увеличению стад слонов и еще более неравномерному распределению. Повреждения древесной растительности более сильные и длительные, чем травянистой. Обычно эти повреждения распространяются вширь от одного исходного очага. Типичный цикл смены местообитаний начинается с уничтожения подстилки и обгрызания коры на деревьях. Эта деятельность усугубляется пожарами. Приведены некоторые случаи исследований во влажных и сухих лесах и сухих кустарниках, которые подтверждают эту схему.
(1) The age structure of elephants in several areas of Tsavo East and West National Parks, Kenya, was determined by means of vertical aerial photography and the age-length key of Croze (1972) in 1972 and 1974. (2) The proportion of young (0-5 years) elephants was found to be substantially reduced in some areas, compared to the situation in 1962-66 and in other populations, due to the 1970-71 drought (Corfield 1973) and continued high juvenile mortality since then. (3) The deficits in the youngest age classes are more pronounced in Tsavo East, where environmental conditions are generally harsher than in Tsavo West. (4) These results suggest that the present elephant population is in a phase of decline, at least in Tsavo East.
The bimodal rainfall regime of the greater part of Kenya has long been recognized (Miller, 1931). But due partly to the inadequacy of the rain gauge network and to the low density of population, few detailed studies of the seasonal characteristics of precipitation have been carried out, particularly for the semi-arid region of Kenya. The necessity for sound management strategies in all the low rainfall zones of Kenya is particularly apparent in many of the national parks and game reserves, and calls for a careful assessment of these environments. This study uses a variety of indices to outline spatial differences in the seasonal rainfall regimes of the Tsavo National Park and adjacent areas.