population dynamics and elephant movements within the...
TRANSCRIPT
Final Report
(March 2009)
1. Project title Population dynamics and elephant movements within the Associated Private Nature Reserves adjoining(APNR) the Kruger National Park (KNP) 2. Senior Researcher and co-workers Henley, M.D. Transboundary Elephant Research Programme (Save the Elephants) Henley, S.R. Transboundary Elephant Research Programme (Save the Elephants) Douglas-Hamilton, I. (Founder Save the Elephants) Whyte, I.J. South African National Parks (Retired from Scientific Services) 3. Duration Project registered with SANParks from May 2003 until December 2008. Project registered with the APNR from April 2003 until April 2008. 4. Area of study The project study area extends from the Associated Private Nature Reserves (APNR: Balule PNR, Klaserie PNR, Umbabat PNR and Timbavati PNR) eastward into the Kruger Nation Park (KNP). However, elephants collared within the APNR have moved through all the protected areas contiguous with the western boundary of the KNP as well most of the KNP itself. Two additional projects have been initiated by STE-SA that contribute toward meeting some of the objectives of this study: the deployment of collars on bulls along the eastern border of KNP and a telemetry and ID study in the far north of KNP. These projects focus primarily on exploring movements of elephants from KNP into neighbouring National Parks (Limpopo NP and Gonarezhou NP) and extend the study area to include the entire Great Limpopo Transfrontier Park. The bounding co-ordinates of this study area are: 21.10 – 25.530S and 30.80 – 32.000E. 5. Objectives The following objectives were set in consultation with SANParks and the Wardens of the APNR in 2003:
1) To determine how many elephant bulls use the APNR. 2) To determine how many breeding herds frequent the APNR. 3) To identify the big tuskers that frequent the APNR. 4) To determine the movement of elephants within the APNR and adjacent areas. As
these reserves are linked with the KNP and other Trans-frontier Reserves in Mozambique and Zimbabwe, the study can potentially provide information on the movements of elephants at the meta-population level.
5) To determine the changes in the density of elephants within the APNR and how this changes over time and whether these changes are through births, deaths or elephant movements to and from the KNP.
6) To establish the extent to which elephants frequent different parts of the APNR and KNP.
7) To determine whether food resources and/or social and safety benefits motivate elephant movements.
8) To quantify the impact of elephants on certain tree species.
Results Objective 1: To determine how many elephant bulls use the APNR. The position, size and shape of all distinguishing features (nicks, tears, notches, folds and veins) of each of the ears of sighted animals were used for identification according to the techniques described by Douglas-Hamilton (1972). Bull sightings were divided into size and age categories and all subsequent analyses have been conducted within each of these categories: • Immature bulls: Immature bulls are dependent on their respective family units and
refer to the juveniles and sub-adult animals found within herds. These individuals form an integral part within their respective family and are rarely found away from the herd. The identification of immature bulls have not been the focus of the study and records have only been collected if observation time within a breeding herd has permitted this after photos of the young adult bulls and cows within the breeding herd have been collected. The lack of significant markings to the ears of immature animals has also proved problematic when it comes to re-sighting data. Sampling immature animals have therefore been biased towards those individuals with characteristic features. Nevertheless, identikits of ‘recognisable‘ immature bulls could provide valuable information on how far and when bulls disperse from their natal herds as these bulls enter older age categories in the years to come.
• Young adults: Young bulls are behaviourally gradually breaking away from their family units and may start to experience their first musth cycle at around 25 years of age. When young bulls are found within breeding herds they should be taller than the oldest cow at around 17 years of age. Young adults thus include sub-adult bulls (bulls between 12 and 25 that are breaking away from their family unit but haven’t experienced musth) and adult bulls (bulls between 25 and 35 years old that experience short, erratic musth cyles and which haven’t fully established discreet musth and non-musth ranges)
• Senior adult bulls: Senior bulls are older than 35 years of age and experience regular annual musth cycles and mostly associate in bachelor herds or are solitary. When in musth they actively seek out females within breeding herds.
A total of 3 245 sightings of bulls have been made over the five year period. This figure includes multiple sightings of the same animal within a month. Identification kits of 769 individual bulls were collected during the study period (Table 1). The re-sighting rate of senior bulls has been approximately 70% for a number of months while young and immature bulls’ re-sighting rates have gradually increased over time (quarterly reports to Wardens of the APNR). Table 1 The re-sighting percentage of immature, adult and senior adult bulls. Re-sightings were calculated as a percentage of the total number of bulls identified within each size category within the APNR.
Size category IDs collected since May 2003
Bulls re-sighted since May 2003
Bulls sighted only once since May 2003
Re-sighting percentage
Immature 232 102 130 44 Young adult 332 182 150 55
Senior 205 150 55 73 Total 769 434 335 56
Multiple sightings of an individual animal were pooled within a month to obtain a monthly re-sighting rate. Third order polynomial models were used to describe the relationship between the accumulative number of new sightings over time and the rate at which elephant bulls were re-sighted. For all categories of bulls, the regression model adequately explained the variation in new sightings and re-sightings over time (Figure 1, r2= 0.99). By July 2004 the accumulative new sightings of senior bulls had exceeded the re-sightings. For young bulls the accumulative re-sighting rate exceeded the new sightings rate by December 2006 while for the immature bull component of the study, it has taken even longer to reach this cross over point (April 2007). These results could partly be explained by prioritising the collection of identikits from young and senior bulls and not immature bulls whilst conducting field work. Nevertheless, both the young and immature component of the bull population are slowly approaching the asymptote where very few new sightings are recorded over time as is evident within the senior bull component of the population (Figure 1). Young bulls not only have a lower re-sighting rate when compared to senior bulls but local declines in young bulls within the APNR appear to be buffered by immigrations from the KNP. These findings corroborate that younger bulls represent a less stable component of the population when compared to senior bulls, not only because they move more freely between the APNR and the KNP but also because they are doing so in greater numbers. As the accumulative re-sighting rate has exceeded the new sighting rate in all three components of the bull population, important estimates of the bull population size could be determined. Using our bull re-sightings data we applied the Jolly stochastic method to estimate the number of young adult (17-35 years old) and senior adult (>35 years) bulls in the APNR each year. The Jolly stochastic model was applied as the basic model allows birth, death, immigration, and permanent emigration to occur and is therefore appropriate for an open system like the APNR (Jolly 1965). The dataset was prepared in the following way:
Data obtained from collared animals were removed from the dataset as ‘recapture’ events of these animals were not random.
The sampling period was taken to start on May 2003 when the project was started on a full-time basis until December 2008. All animals prior to this date were considered ‘unmarked’.
All sightings of breeding units and immature animals associating with them were removed from the dataset as the numbers and identikits of animals involved in these social units could not be accurately and consistently assessed across seasons. Immature bulls were removed from the dataset for reasons outlined above. Furthermore, as aerial census figures can’t distinguish immature bulls from immature females within breeding herds, immature bull estimates can not be compared with aerial counts.
All bulls from which incomplete IDs were collected (one ear pattern only) were removed from the dataset as identification of these animals in future sampling events was uncertain.
The total number of individual animals recorded within each year, was considered as one mark-recapture event to provide annual estimates of young and prime adult bulls respectively.
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Figure 1. The accumulative number of new sightings and re-sightings of bulls.
To calculate a population estimate for the first year of the study, the total number of individuals identified before 2003 but not resighted during 2003 is required. Hence estimates of population size can not be obtained for the first year of the study. Furthermore, the Jolly stochastic model requires data from the capture period (year 1) and the recapture period (year 2) to estimate the population in year 1, hence we don’t have an estimate for 2008. The survival rate calculations of 2007 would depend on the number of animals at ‘risk’ of being identified in 2008, divided by the number of animals at risk
before 2007, minus those identified in 2007, plus the new identikits added at the end of 2007. As the number of animals at risk of being identified in 2008 can not be calculated for reasons outlined above, survival rates for 2007 and 2008 will depend on gathering data in subsequent years (Table 2). Table 2. The annual estimated population size (estimate ± SE) of young adult (17-35 years) and senior adult (>35 years) elephant bulls as estimated by the Jolly stochastic capture-recapture model (Jolly 1965) and the bull count recorded during the annual aerial census.
Year Model population estimate Aerial census
Young adult bulls
Young adult Survival %
Senior adult bulls
Senior bulls Survival %
Total bulls
Total Bulls
2003 - 86 - 94 - 176 2004 235 (± 53) 64 128 (± 11) 84 362 174 2005 199 (± 24) 85 136 (± 11) 75 335 147 2006 281 (± 36) 66 132 (± 10) 57 413 191 2007 201 (± 19) - 80 (± 4) - 281 188 2008 - - - - - 109
The aerial census is conducted in an accepted, standardized manner at a similar time every year (Dr. Ian Whyte's annual census reports), creating the best opportunity for a precise count of the population. To test this assumption, the Jolly Stochastic model provided an independent measure of the elephant population. The Jolly stochastic model calculated a bull population which was twice that of the census for most years with the exception of 2007 (range = 1.50 to 2.28 times) (Table 2). The total number of bulls calculated by means of the model, showed similar trends in terms of increases and decreases when compared to the census results (Figure 2 (c)). This is encouraging as it suggests that both methods are tracking the same pattern in the elephant population despite being based on different data collected over different periods of time and serves to corroborate the aerial census data. These findings substantiate that movements in and out of the APNR, and especially those of young adult bulls, critically determine the fluctuations in the number of bulls from year to year. Although census results have indicated that there has been a sharp decline in the number of bulls counted in 2008 when compared to previous years (Figure 2.(c)), both the young and senior bull segment of the population had declined in 2007 according to the model predictions (Figure 2 (a) and (b)). The consistent decline in the senior bull segment of the population over the past four years has however been masked by the annual aerial survey results because of the inability of this survey technique to distinguish between young and prime bulls from the air. The importance of the Jolly Stochastic model’s ability to distinguish changes in the number of different segments of the bull population is apparent in the survival rate estimates of both young and senior bulls. The survival rate of senior bulls has decreased over time (r2= 0.98, F=91.3, P=0.01) while the survival rate of young bulls has fluctuated more widely (Table 2).
2003 2004 2005 2006 2007 20080
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Figure 2. Annual estimates of the number of young (a), senior (b) and total (c) number of bulls within the APNR.
Objective 2: To determine how many breeding herds use the APNR. Twenty four different breeding herds have been identified within the APNR. In total 385 different cows have been identified while 61 cow identikits could not be grouped into any particular herd and have been classified as ‘uncategorised’. Identikits which could not be classified were collected during sightings were visibility was poor due to the density of the vegetation or in areas where breeding herds where skittish which only permitted one or two unknown individuals to be sighted. The re-sighting rate of cows is 88% (Table 3) Table 3. The proportion of breeding herds that have been re-sighted of the total number of herds identified within the APNR.
Total number of breeding herds
identified since May 2003
Number of breeding herds re-
sighted since May 2003
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sighted only once since May 2003
Re-sighting percentage
24 21 3 88 Multiple sightings of the same herd were pooled within a month to obtain a monthly re-sighting rate. A third order polynomial model was used to describe the relationship between the accumulative number of new sightings over time and the rate at which breeding herds were re-sighted. The regression model adequately explained the variation in new sightings and re-sightings over time (Figure 3, r2= 0.99 and r2= 0.99 respectively). By May 2004 the accumulative re-sighting rate of breeding herds had exceeded the accumulative sighting of new herds so that re-sightings of identified herds were more frequent than new sightings of herds. Similarly to senior bulls, breeding herds form the stable components of the population as very few new sightings of herds have been made over time.
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Figure 3. The accumulative number of re-sightings and new sightings of individual breeding herds
Objective 3: To identify the big tuskers that frequent the APNR. Elephant tusks grow at a constant rate in length throughout life with the tusks of bulls increasing on average, at 11cm per year while female tusks increase at 8.5 cm per year. In elephants the rate at which the tusks increase in weight accelerates as the pulp cavity fills and this does not occur until old age in bulls. Although tusks increase in weight at a rate of 2g a day (Spinage 1994), the almost exponential increase in male tusks weight with age is not reflected in this daily rate of tusk growth. Laws (1966) found that in bulls the rate of tusk growth increases progressively throughout life to at least 240 lbs (109 kg) at 60±5 years. Growth in tusks does however depend on genetics, the geology of the place that the elephant occupies as well as the frequency at which the tusks are used. If there was no wear and tear on a bull elephant’s tusks he could acquire tusks as long as 550cm in his lifetime however, bull’s tusks generally reach 250cm in length upon old age (Spinage 1994). Large tusked bulls are under-represented in most African elephant populations (Douglas-Hamilton 1997). This is the legacy of a history of uncontrolled hunting and poaching on this continent. Although, trophy hunting is now regulated in a few countries it still continues to focus on the few large tusked individuals remaining in the population. There is concern that long-term selective off takes will ultimately depress the quality of trophies (Stalmans et al. 2002). Bulls with tusks estimated to be in excess of 50lbs were specifically recorded as large tusked individuals to determine how many large tusked bulls frequent the APNR. Since May 2003 we have recorded 26 large tusked individuals. For large tusked bulls, the regression model adequately explained the variation in new sightings and re-sightings over time (Figure 4, r2= 0.99). In July 2004 the accumulative re-sighting rate exceeded the new sightings over time. Furthermore, the accumulative new sighting rate had reached an asymptote by January 2005 which means that very few new large tusked individuals are entering the APNR. Hence we recommend that bulls with tusks in excess of 50lbs should be afforded protection throughout the APNR in terms of their aesthetic, social and genetic importance.
Large tusked bulls
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Figure 4. The accumulative number of re-sightings and new sightings of prime bulls with tusks in excess of 50lbs.
Objective 4: To determine the movement of elephants between the APNR and adjacent areas. Objective 6: To establish the extent to which elephants frequent different parts of the APNR and KNP. These two objectives focus on the distribution of elephants, differing primarily in their spatial and temporal scale. The first (Objective 4) considers distribution between Protected Areas and the second patterns (Objective 6) within these. Between May 2004 and December STE-SA fitted GPS-telemetry collars to 28 elephants within the APNR, 21 bulls and seven cows. The distribution data derived from these are used to determine movement patterns (see section 5 for information on the deployment of collars, study animals and the quality of the data). Elephants collared within the central APNR move freely between these private reserves, the KNP and to a lesser degree the other protected areas contiguous with the western border of KNP. On average, just over 72% of the location records lay within the APNR, 20% occurred within KNP, less than 2.5% in other conservation areas and almost 5% outside protected areas. Movements outside protected areas are primarily north of the Olifants River between the APNR and Phalaborwa. There are differences in distribution according to sex, on average 84.7% of the cows location records are located within the APNR, compared with 68.8% of the senior adult bull's; 67% of the adult bull's and 68.7% of the sub-adult bulls' data points (Figure 5), however these are not statistically significant (Friedman's ANOVA). It is possible that individual variability within these groups is masking the biological significance of the differences between them.
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s Figure 5. The proportional abundance of elephant distribution data points within different conservation areas. The veterinary fence that defines the western boundary of the study represents an artificial and abrupt barrier to elephant movements, for this reason the recently developed Local Convex Hull (LoCoH) method of home range determination (Getz & Wilmers 2004) is appropriate. Getz et al. (2007) found the adaptive LoCoH (a-LoCoH) to be superior to others. They recommend, as a rule of thumb, using greatest distance between any two points as the estimate for the a value. Given the eccentric shape of many of the home ranges within the study we refined this rule of thumb to be the average of the
primary axis (greatest distance between any two data points) and the secondary axis (greatest distance between two points perpendicular to the 10 axis). This is intended to reduce the difference in the a value between ranges of a similar area but differing eccentricity. The annual a-LoCoH plots for each study animal are presented in Figure 6. Table 4 includes the mean annual home range size for each of the study animals for which there are sufficient data (≥ 1 year October – September). The average breeding herd home range, as derived from the a-LoCoH plot is 490 km2. Bull’s annual home ranges are substantially larger with the sub-adult bulls being on average 1 599 km2, the adult bulls 809 km2 for and the senior adult bulls 805 km2. Table 4. Telemetry summary and range statistics for elephant collared by STE-SA since 2002. Age classes of bulls cover the following periods: sub-adult <25 years old; adult 25-35 years old; senior adult >35 years old. All cows are adults. Collared refers to the month and year the animal was first tagged and so indicates the period for which telemetry data are available. Sample size (n) includes data points up the end of September 2008. MCP (minimum convex polygon) is the home range estimate in km2. Adaptive local convex hull (a-LoCoH) is the area of the 100% isopleth in km2. Age class Collared n MCP a-LoCoH Notes TKM06 Classic senior adult May 04 16718 1437 750 TKM07 Alex adult Nov 04 3904 3341 1327 TKM08 Benjamin adult Nov 04 667 data stops July 2005 TKM09 Barry adult May 05 5041 2382 1297 TKM10 Soshangane sub-adult Oct 05 9556 2105 1298 TKM11 Brazen senior adult Oct 05 1815 1441 711 data stops March 2007 TKM15 Striburus sub-adult June 06 12581 1301 750 TKM16 Tussle sub-adult Sept 06 15675 5627 2353 TKM17 Caughley adult Sept 06 14215 827 563 TKM18 Everest adult Sept 06 15430 804 396 data stops July 2008 TKM19 Gower senior adult Oct 06 16225 1200 863 TKM20 Proud adult Nov 06 15446 931 450 TKM21 Wessa adult Nov 06 13667 3698 1200 TKM22 Mellow senior adult April 07 12410 2222 897 TKM23 Capt Hook adult April 07 12350 871 431 TKM24 Snap adult June 07 5192 data stops January 2008 TKM25 Iain senior adult June 07 8340 data stops June 2008 TKM26 Namaste sub-adult June 07 10986 8629 1997 TKM27 Vee senior adult Nov 07 4718 data stops July 2008 TKM12 Intwandamela senior adult April 08 3777 Nov 2005 – collared by TEMBO TKM13 Matambu adult July 08 1540 Nov 2005 – collared by TEMBO TKF01 Diney May 04 2806 914 435 TKF02 Joan Nov 04 15305 945 451 TKF03 Mandy May 05 10821 1267 640 TKF04 Umbabat Oct 05 4056 935 457 TKF08 Lapajuma Oct 06 14819 379 260 TKF09 Keoleria July 07 12629 1526 696 TKF07 Summer July 08 1656 Nov 2005 – collared by TEMBO
Figure 6. Annual adaptive local convex hull home-range plots (100% isopleth) of elephants collared within the APNR. Annual data starts from the beginning of October (typically the dry-wet transition month when the first substantial rains fall) and end in September (typically the end of the dry season).
Figure 6 cont. Annual adaptive local convex hull home-range plots (100% isopleth) of elephants collared within the APNR. Annual data starts from the beginning of October (typically the dry-wet transition month when the first substantial rains fall) and end in September (typically the end of the dry season).
Figure 7. Adaptive local convex hull home-range plots (100% isopleth) of elephants collared in the eastern Kruger NP. Data from December 2006 to September 2008 are included in the range calculation.
Two other STE-SA projects are also relevant to Objective 4: the deployment of eight collars on bulls in the east of KNP in December 2006, and the fitting of collars to elephants in the far north of the KNP. The first project aims to explore movements between KNP and Limpopo NP in Mozambique and the second movements between KNP and Gonarezhou NP in Zimbabwe. Of the seven new elephants collared south of Shingwedzi (the last collar was fitted to Mac TKM05) two (28.6%) moved into LNP within seven weeks and have not returned in two years following (Figure 7). The results of this study are currently being written up for publication. The first of 12 collars to d be deployed in the northern KNP was fitted to a young bull elephant in October 2008. We plan to deploy another 8 or more this winter. STE-SA is also exploring the possibility of collaboration with wildlife biologists in Zimbabwe to have collars fitted in Gonarezhou NP. Objective 5: To determine the changes in the density of elephants within the APNR and how this changes over time and whether these changes are through births, deaths or elephant movements to and from the KNP.
Census results In 1992 the fence between the Timbavati-Umbabat and Klaserie PNRs was taken down, creating the consolidated Associated Private Nature Reserves (APNR). A year later the fence separating the APNR and Kruger NP was completely removed. These actions radically altered the landscape and dynamics of the elephants within the Private Reserves and created a situation where management decisions have to take into consideration the circumstances and actions of the other properties as well. Fortunately a repeated annual aerial census across the three reserves was initiated in 1992 and so we have comparable data reflecting dry season population estimates over the past 16 years. However, animal movements and environmental conditions such as rainfall and woody canopy cover, as well as observer bias change from year to year giving aerial counts an inherent variability over and above real changes in the animal's demographics. For this reason it is preferable to track trends in the population rather than focus on the absolute value in any one year. To reduce the erroneous variability in census results, a weighted average (two-point weighted interpolation - Owen-Smith, Mason & Ogutu 2005) was calculated and the smoothed plot is also presented in Figure 8. This smoothing function relies on the data of the year in question as well as the next year's data hence there is no estimate for 2008. Balule PNR recently joined the APNR (in 2005) which meant that including these data in the evaluation would render comparisons over longer time periods invalid. Furthermore, no data is currently available on the break down of the number of bulls, breeding herds and calves within Balule PNR. Consequently the subsequent evaluation focused on elephant demographics within the Timbavati, Klaserie and Umbabat PNRs. In general, the 16 years since 1992 has seen an increase in elephant numbers within the APNR from ca. 500 to ca. 1 300, reflecting a mean annual population growth of just less than 6.1%. This is less than the inferred 6.7% growth in Kruger NP during the culling period (1973-1994, Whyte et al. 1998) when the population was at a lower density and below the 7% physiological limit suggested by Hanks & McIntosh (1973), Calef (1988) and Owen-Smith (1988). A growth rate of 6.1% is nevertheless larger than growth rates
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typically reported elsewhere (2-4%) for elephant populations under favourable environmental conditions, in the absence of external influences such as poaching, demographic distortion or range compression (Armbruster & Landel 1993; Moss 2001). Growth rates greater than 10% have recently been reported from other areas in southern Africa (van Jaarsveld et al. 1999; Mackey et al. 2006), however these are derived from small populations subject to very artificial conditions. ‘Natural’ populations (i.e. large with relatively undistorted demographics) have experienced growth rates of 9.6 - 11.2% (Chobe NP 1973 to 1993, Junker et al 2008) and 17.7% (Hwange 1986 to 1990, Chamaillé-Jammes et al 2008) but these have been largely ascribed to immigration from surrounding areas and in both cases the population appears to have subsequently stabilized.
Figure 8. Consolidated elephant census data from the Klaserie, Timbavati and Umbabat PNRs
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Figure 9. The annual elephant population (observed census data) and the hypothetical population based on a 6.1% annual growth rate (hypothetical). Black bars show years when the census counts were larger than the hypothetical population and light grey bars indicate when it was less. The annual growth rate is the percentage change in the observed population from year to year (thick red line). The above may suggest that the increase in APNR elephant numbers is due to the inherent growth expected of a population under favourable habitat conditions. However, when one looks at change in the APNR population from year to year substantial fluctuations are obvious, even in the smoothed data (Figure 8). Annual growth rates between 1992 and 2008 vary between -34% and 120% and in most years the observed population was below that predicted by a 6.1% growth rate (Figure 9). Two explanations may account for this: 1) erratic counting from year to year and 2) movement of elephants between the APNR and other protected areas within the
Great Limpopo Transfrontier Park. When considering how each of the various segments of the population (breeding herds, bulls and calves) contribute towards the overall trends in density, the total elephant population density in the APNR appears to be largely determined by the density of breeding units. The trends in the total population density follow those of breeding units more closely than any other component of the population (Figure 10 (a) and (b)). Breeding units also make up the largest proportion of the total population when compared to either bulls or calves (81% as opposed to 15% and 4% on average since 1992). Since 2003, breeding unit numbers within the APNR have fluctuated above and below the general trend in numbers found within the KNP (Figure 10(b)). The density of bulls
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Figure 10. Trends in population densities over time for the total elephant population in the Kruger NP and the APNR (a). The trends in the densities of different segments of the population are shown for the breeding herds (b), the adult bulls (c) and the calves (d) according to the Kruger NP annual census figures.
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within the APNR has consistently been higher than those of the KNP since 2001, although there has been a sharp decrease in bulls counted in 2008 (Figure 10 (c)). The number of calves counted annually within the APNR has followed similar trends to those counted within the KNP (Figure 10 (d)). Mortalities Population trends and the health of a population in terms of poaching pressure or other forms of mortality are often assessed by looking at the carcass ratio (Dublin & Douglas-Hamilton 1987). The carcass ratio simply looks at the proportion of dead elephants to live ones. The carcass ration was calculated according to the following formula: Carcass ratio = (No. carcasses) X 100 (No. carcasses + No. live elephants) 1 where all natural elephant mortalities and mortalities due to trophy hunting were recorded within the ANR. As numerical records on trophy hunts reported conflicting figures, trends were examined within minimum and maximum numbers given within a particular year.
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Figure11. The carcass ratios for natural mortalities recorded within the KNP (during aerial censuses) and the APNR (based on reports by wardens, guides and researchers traversing the APNR). The carcass ratios of elephants that have died due to natural causes, both within the KNP and the APNR, fluctuate quite widely and typifies a population that has not been susceptible to poaching (Figure 11). The carcass ration on average, is three times the baseline ratio (delineated by natural mortalities) when mortalities due to trophy hunting of bulls are included in the analysis (Figure 12). Difference in mortality between the sexes over the past 16 years has meant that for every dead elephant cow recorded, nine bulls have been found dead.
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1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 20080.0
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Figure 12. The carcass ratios for natural mortalities recorded within the APNR (based on reports by wardens, guides and researchers traversing the APNR) as well as annual carcass ratios when trophy hunted bulls are included in the analyses. . Objective 7: To determine whether food resources and/or social and safety benefits motivate elephant movements. Elephant movements and range use patterns are being determined using either GPS-satellite or GPS-GSM collars. Given the political diversity and physical extent of the study area, environmental variables are derived primarily through remote sensing and existing GIS coverages. For example, landsat images and phytosociological GIS layers (e.g. landscapes – Gertenbach 1983) are being used to generate a biotope map that has relevance across the entire study area; NDVI values are derived from MODIS satellite images and digital elevation models (DEM) are being used to map terrain ruggedness. Mapping of environmental variables such as the size and persistence of surface water is being done primarily within the APNR. This has led to a difference in the scale and quality of habitat parameters. Consequently elephant habitat modelling within the APNR will be done at a finer resolution than that possible for the greater study area. Similarly, social and safety benefits rely extensively on elephant re-sightings data and a known population; as such consideration of these as determinants of elephant movements is restricted to those within the APNR. Elephant risk perception has been determined using reaction index data collected in the field. The assumption being that humans are the primary predator of elephants within the study area and changes in their reaction to encounters with observes reflects changes in their spatial perception of risk. Reaction index data have been collected from the more than 4 000 observations of elephants within the APNR using the following four point scale: 1 - Elephant totally relaxed and show no overt response to the arrival of the observer. 2 - Elephant shows a mild response, either interrupting its behavioural activity (e.g.
stops feeding; listens while swivelling trunk which hangs limply; opens its eyes; lifts its trunk to smell; foot-swings; touches temporal glands etc) or alters its movement path.
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3 - Elephant shows moderate signs of agitation and aggression (flaps ears; dips head and stands tall; kicks up dust; trumpets; musth bulls will gush or dribble urine more profusely, exudates secreted from the temporal glands of bulls and cows).
4 - A strong positive (charges) or negative (runs away as quickly as possible) response to the presence of an observer.
Using observation data gathered prior to December 2007 we plotted the mean reaction index per property of seven herds with more than 20 reliable observations and then averaged across the herds for each property (Figure 13). Assumptions being: 1) cows, with dependent younger individuals, are particularly aware of potential threats and so serve as a more sensitive indicator than adult bulls and 2) herds reflect the collective response of the group, ameliorating individual variation. The majority of study animals were collared by December 2007 and so we now have data from 17 elephants that spans more than two years (see Section 5). We are therefore in a position to start analysing these data and this will be the focus of our efforts for the next year.
Figure 13. The mean elephant breeding herd reaction index per property. Index values were derived from seven herds for which there were more than 20 reliable observation records. Mean reaction index values are scaled according to colour from low (green) to high (red). Labels reflect the number of observations used to calculate the mean (n).
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Objective 8: To quantify the impact of elephants on certain tree species. In total 2971 large trees (>5m in height) within the Associated Private Nature Reserves have been labelled and the impact of elephants on these individual trees are being followed over time. The vegetation surveys within the APNR have focused on the tall tree component of Sclerocarya birrea (Marula) and Acacia nigrescens (Knob thorn) trees. Six study sites have been established throughout the APNR that have and will be monitored on an annual basis. These include the Ntsiri and De Luca study sites in the Umbabat PNR, Vlakgezicht, Sumatra and Zebenine sites in the Timbavati PNR and the Charlesoscar study site in the Klaserie PNR. At all of these study sites, with the exception of Zebenine, have both wired protected and unprotected trees that are being monitored. A total of 1446 large trees have been protected on request of various landowners to maintain the aesthetic features of certain landscape types. The methodology includes the direct application of 13mm mesh wire netting around the trunk of mature tree stems to prevent these trees from being extensively bark stripped by elephants. The wire netting techniques did not protect trees from being uprooted or broken. Results from these studies indicate that the absolute use or avoidance of protected trees may not be as important as the degree to which the wire-netting prevents extensive bark-stripping and consequently increases the survival rate of trees that are susceptible to bark-stripping by elephants. Survival curves were calculated using the product limit (Kaplan-Meier) method (Kaplan & Meier 1958). For each period in time the fraction still alive is shown while the standard error bars depict the uncertainty of the fractional survival. The calculations take into account those trees that were ‘censored’ because they could not be found again. When considering the effect of elephant impact on survival rate, wire and unwired trees were separated and all other deaths caused by means other than elephants that impacted on the trees whether they were wire protected or not (unknown causes, fire, wind toppling or insect attack), were considered censored. The survival curves of the treated (wire-protected) trees were compared with those of the unwired trees using the Mantel-Cox test to test the hypothesis that treatment does not change a tree’s survival for two of the study sites that have been monitored for three or more years (Mantel 1966). The overall survival of the monitored tall trees at the Ntsiri study site is 91.8 % (± 2.8 SE). Eight trees died from 2005 until 2008, three of which died due to fire and five due to elephant impact. When considering the trees that died primarily due to elephant impact, the wired trees had a higher survival rate when compared to the unwired trees although the difference did not test statistically significant (χ2= 2.33, df=1, P=0.127). The overall survival of the monitored tall trees at the Vlakgezicht study site is 81.8 % (± 3.5 SE). Seventy six trees died between from 2004 until 2008, 37 of which died due to the combined effect of elephant impact and fire while 39 died due to elephant impact, wind-toppling, insect attack and other unknown causes. When considering the trees that died primarily due to elephant impact, the wired trees had a higher survival rate when compared to the unwired trees although the difference did not test statistically significant (χ2=3.59, df=1, P=0.06, Figure 14).
8
0 200 400 600 800 1000 120070
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85
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0 200 400 600 800 1000 1200 140070
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Figure 14. Survival rate of unwired and wired trees in response to elephant impact at the Ntsiri (a) and Vlakgezicht (b) study site. 1. Conclusion The identification study has proved invaluable as the re-sighting rate of known individuals has highlighted which components of the elephant population are the more stable (breeding herds and senior bulls). Young adult bulls seem to move more freely and in larger numbers from core conservation areas, such as the KNP, into adjacent reserves and vice versa. These results are of importance to both the KNP and the APNR as the rate and extent of movement of this component of the population will not only influence population dynamics but also local elephant impact. Furthermore, the results from the Jolly Stochastic model have indicated that due to the limitations of the aerial surveys, if both senior and young bulls were being utilised through trophy hunting at an order of magnitude of 1-2% per year, any slow attrition in numbers may not be detected on an annual basis by a technique that returns data at a coarser demographic resolution (Stalmans 2003). Failure to detect downward trends in senior bulls in particular would not only be masked by the errors associated with aerial surveys but also by the inability to distinguish between age groups from the air. These results have important implications for the managers of the APNR that depend on trophy hunting of elephants to help cover conservation costs. The identification of large tusked bulls has shown that continued strict protocols to protect large tuskers from being hunted in areas adjacent to the KNP are necessary as replacements of these individuals occurs from within the KNP population and at a rate that may not prove to be sustainable in the long run. Socially these older, more experienced bulls are important to breeding females (Poole & Moss 1981, Poole 1982, Poole 1987).and younger bulls (.Slotow et al. 2000, Slotow et al. 2001, Slotow & van Dyk 2001). These results are of importance to the photo-tourism industry of both the APNR and the KNP in addition to the social importance of these large older bulls The telemetry study has revealed that most of the elephants collared within the APNR spend the majority of their time in these reserves. A proportion of the elephants that were collared within the APNR are using the KNP but to a lesser extent. The former western boundary fence of the KNP and the present western boundary fence of the APNR have been restricting east-west movements. These restrictions may have greater significance than any restrictions to the south as a greater proportion of distribution points have been found outside of the protected areas even if these areas are potentially more risky, as opposed to other private reserves to the south. The findings of the telemetry study corroborate the predictions that have come out of the elephant identity study. The sub-adult bulls within the young bull category are moving over larger areas than either the senior bulls or the breeding herds. The
9
breeding herds that were collared within the APNR are spending most of their time in the reserves compared to any other segment of the population. By consistently collecting data from any recorded elephant mortalities within the APNR we have been able to classify the different causes of death throughout the reserves. The number and age category of dead elephants could provide important information on the carcass recovery rate within a highly patrolled and effectively protected reserve when compared to the number of elephant carcasses that are sighted during the aerial surveys. This data could be of importance to establishing mortality rates within the population as well as providing baseline data needed by the MIKE (Monitoring of the Illegal Killing of Elephants) programme. Elephants are known to live in complex societies, communicate over long distances, to mourn their dead, and to exhibit post traumatic stress disorders after traumatic events (Payne 1998, Payne 2003, Bradshaw et al. 2005, Burke 2005, McComb et al 2005). The combination of these factors compounds any culling or hunting practices within small, confined reserves. Furthermore as attacks by elephants on tourists are on the increase, special caution should be taken when considering any such activities in areas that are used by tourists (Bradshaw 2004). The preliminary analysis of the safety benefits of elephant movements has revealed that elephants have a spatial and temporal awareness of safety. The implications of these results are two fold. Firstly conservation areas that contain elephants should be large enough to ensure that refuge areas are available in both time and space to ensure that traumatised elephants can avoid conflict with humans until their stress levels have declined and so that they can choose to move back into areas occupied by tourists when they are ready to do so. Secondly, to avoid an increase in tourist-elephant conflict and to ensure a high level of photo-tourism amenity in conservation areas with elephants, we suggest exclusive zones of disturbance in reserves that either practise hunting or culling and refuge areas where no such practices will occur. These refuge areas should at least approximate the average size of a breeding unit’s home range specific to that conservation area. More complete analyses of the safety and social benefits of elephants are underway (Objective 7). These results will provide valuable information to both the APNR and the KNP in terms of not only considering the ecological implications of elephant management practises but also the social landscape of the areas that elephants occupy. A recent study has revealed that protecting pre-existing social mechanisms in elephants can mitigate the ecological impacts of higher densities of elephants (Wittemyer 2007). In this study the sociality and hierarchy of various breeding herds of elephants were found to not only determine their fitness but also the distribution of the population density across the ecosystem. The results from the vegetation impact study have indicated that elephant impact mitigation methods can increase the survival rate of large trees but the data would need to be collected over the longer-term before any conclusions can be drawn. Elephant impact within high-impact types (bark-stripping, uprooting and main stem breaking) on individually, unprotected identified trees has been low with 3 % being uprooted, 2% pollard and 4% bark-stripped (average ± SE) on an annual basis across 5 sites. The accumulated impact of elephants over a number of years, does however appear to make a larger proportion of trees either susceptible to insect attack or fire. Specific studies aimed at determining recruitment rates and resilience to elephant impact, for each of the favoured woody species, should be conducted before predictions on the persistence of particular tree populations can be made. Bulls are
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known to have a higher overall impact on the vegetation when compared to cows (Greyling 2004, Shannon 2005). However, the potential impact by this component of the population on an area cannot be assessed without knowing how, when and why they distribute themselves in time and space. Furthermore, the importance of studies on elephant movements and distribution in both space and time are highlighted by the inability to extract such information from annual aerial surveys. To conclude, the study has achieved most of its objectives and further analyses of the data will answer some of the questions relating to Objective 7. As the elephant identification study, the telemetry study and the vegetation study will provide additional valuable information in the long term which could help to manage elephants in accordance with the Draft National Norms and Standards for the Management of Elephants in South Africa (DEAT 2007), we will be applying to renew the study with a new suite of objectives for another five years. 2. Publications Scientific GREYLING, M.D, McCAY, M & DOUGLAS-HAMILTON, I. 2004. Green Hunting as an
alternative to lethal hunting. In (ed.) Jayewardene, Jayantha. Endangered elephants, past present & future. Proceedings of the Symposium on Human Elephant Relationships and Conflicts, Sri Lanka, September 2003. Biodiversity & Elephant Conservation Trust, Colombo. Pages 228.
HENLEY, M.D. 2005. A neighbour’s perspective on the new management policy of the
Kruger National Park. In (ed.) Grant, C.C. A compilation of contributions by the scientific community for SANParks. Elephant effects on Biodiversity: an assessment of current knowledge and understanding as a basis for elephant management in SANParks, South African National Parks, Skukuza: Scientific Services. Scientific Report 3/2005.
HENLEY, M.D. & HENLEY, S.R. 2005. The potential influence of elephants on Southern
Ground Hornbill nesting sites. In (eds) Daly, B, Morrison, K., Kemp, A., Kemp, M., Turner, A., Engelbrecht, D., Gunn, D., Ngwenya, R., Jordan, M., Potgieter, C. & Friedmann, Y. Southern Ground Hornbill (Bucorvus leadbeateri). A Population an Habitat Viability Assessment Workshop. Conservation Breeding Specialist Group (SSC/IUCN), Apple Valley, MN
GRANT, C.C., BENGIS, R., BALFOUR, D., PEEL, M., MOSTERT, W., KILLIAN, K.,
LITTLE, R. SMIT, I., GARAI, M., HENLEY, M.D. & ANTHONY, B. In Press. Controlling the distribution of elephant. In (eds.) Scholes, R.J. & Mendell, K.G. Elephant Management: A Scientific Assessment for South Africa. Witwatersrand University Press, Johannesburg.
LőTTER, H.P.P., HENLEY, M.D., FAKIR, S. & PICKOVER, M. In Press. Ethical
considerations in elephant management. In (eds.) Scholes, R.J. & Mendell, K.G. Elephant Management: A Scientific Assessment for South Africa. Witwatersrand University Press, Johannesburg.
• 29 professional ecological and conservation related reports (Scientific reports to the
Associated Private Nature Reserves, Scientific reports to the Kruger National Park, International Conservation Services on Human-Elephant Conflict, and the IUCN Elephant Library Database)
• List of publications in prep. with dates of submission in brackets:
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Movements of elephants into Limpopo National Park and how geological divisions influence elephant movements (June 2009)
Using Capture-Recapture models to estimate population size and seasonal trends (June 2009)
The characteristics of bull areas and their implications (September 2009) When must musth be? (September 2009) Review and motivation of functional social groups (December 2009) Aging elephants using various techniques (December 2009)
In draft form by the end of 2009: Differential food selection by bulls and breeding units of elephants (December
2009) How does the feeding habits of elephants influence ground hornbills? (March
2010) Perceptions, protection and postcard pictures of large trees (March 2010)
Popular
HENLEY, M.D. & HENLEY, S.R. 2006. Green Hunting. In: Marais, J & Hadaway, D. 2006. Great tuskers of Africa. Penguin Books, Johannesburg.
HENLEY, S.R. & HENLEY, M.D. 2007. Tracking elephants: the path to the satellite era.
Quest: Science for South Africa 3: 3-8. HENLEY, S.R. & HENLEY, M.D. In Press. Elephants on the move. African Wildlife. • Compilation and distribution of 10 popular newsletters on the Transboundary Elephant
Research Programme to over 500 landowners/shareblock holders within the Reserves as well as to a near equal amount of interested parties.
3. Presentations Posters: HENLEY, S.R., HENLEY, M.D. & McCAY, M. 2007. The influence of musth on the
movement and range use patterns of elephant bulls. 5th Annual Science Network Meeting, Kruger National Park, Skukuza, South Africa (poster).
HENLEY, M.D., OWEN-SMITH, N. & DU TOIT, J.T. 2007. Size- and sex-related feeding
distinctions among African elephants: differences in diet quality use of plant species, parts and height classes. 5th Annual Science Network Meeting, Kruger National Park, Skukuza, South Africa (poster).
HENLEY, M.D., HENLEY, S.R., HAGENS, Q., RODE, S.C., BROWN, L.R & DOUGLAS-
HAMILTON, I. 2008. How does the feeding habits of elephants influence ground hornbills? 6th Annual Science Network Meeting, Kruger National Park, Skukuza, South Africa.
Oral: GREYLING, M.D., McCAY, M. & DOUGLAS-HAMILTON, I. 2004. Green Hunting as an
alternative to lethal hunting. Symposium on Human Elephant Relationships and Conflicts, Colombo, Sri Lanka.
HENLEY, S.R. & HENLEY, M.D. 2005. Tracking elephants across boundaries: new tools
for biotelemetry. Technology for Conservation and Development in South Africa ICT symposium and training workshop in conservation, Johannesburg, South Africa.
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HENLEY, M D. 2005. Considering More than Elephants. Elephants Alive Conference, University of the Witwatersrand, Johannesburg, South Africa.
HENLEY, S.R. & HENLEY, M.D. 2005. Save the Elephants’ Transboundary Elephant
Research Programme. Save the Elephants Annual General Meeting, Samburu, Kenya. HENLEY, M.D. 2006. Save the Elephants’ Transboundary Elephant Research Programme.
Lowveld Co-ordinated Research Forum. Hans Hoheisen, Orpen, South Africa. HENLEY, M.D., CATTON, G., HENLEY, S.R. & NAUDE, T.W. 2006. Alleviating human-
elephant conflict as naturally as possible: a newly developed Chile spray as deterrent. Elephant Management and Owners Association Annual General Meeting , SANBI, Pretoria, South Africa.
CATTON, D.G., HENLEY, M.D., HENLEY, S.R. & NAUDE, T.W. 2006. Repelling
elephants the natural way. Wildlife Session of the South African Veterinary Association Congress, Durban, South Africa (presentation).
HENLEY, S.R. & HENLEY, M.D. 2007. Save the Elephants’ Transboundary Elephant
Research Programme. Kruger National Park Workshop on Modeling the Exceedence of Thresholds of Potential Concern due to Elephant Impact, Skukuza, South Africa (presentation).
HENLEY M.D. 2007. Save the Elephants’ Transboundary Elephant Research Programme.
Lowveld Co-ordinated Research Forum, Olifants River Game Reserve Head Quarters, South Africa (presentation).
• Additional presentations on the project were delivered to students from the South
African Wildlife College (Michigan and Ferrum Universities), Dartmouth College, the Honorary Rangers of the KNP (Phalaborwa) and the Head Rangers of the APNR.
• Over 363 informal presentations informal presentations have been given to over 1300 guests visiting the Research Office since 2003 when the Transboundary Elephant Research Programme started on a full-time basis.
• More than 10 popular presentations at lodge manager’s meetings or at meetings organised to promote the lodges within the reserves.
4. Data The meta data files were sent to Judith Kruger in 2008. After the STE Trustees have received the data contract with Kruger, the data will be handed over to the KNP promptly. The original goal was to have a sample of 30 tagged elephants within the APNR and by the end of 2008 we had managed to fit collars to 29 animals. Of these, 17 have now been monitored for more than two years. To maintain this sample population over time we have had to replace the collars of seven elephants once, one twice and one three times. Since May 2002 STE-SA has deployed 38 collars on. The deployment of collars and the growth of the sample population over time is shown graphically in Figure 15
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20092008200720062005200420032002 2013201220112010
KEM07 - Nhungu
KEM06 - Nkombo
KEM05 - Tsevo
KEM04 - Quinto
KEM03 - Mune
KEM02 - Tercievo
KEM01 - Mbiri
TEMBO collar
TKF09 - Koeleria
TKM26 - Namaste
TKM25 - Iain
TKM24 - Snap
TKM23 – Capt. Hook
TKM22 - Mellow
TKM21 - Wessa
TKM20 - Proud
TKF08 - Lapajuma
TKM19 - Gower
TKM18 - Everest
TKM17 - Caughley
TKM16 - Tussle
TKM15 - Striburus
TKF04 - Umbabat
TKM11 - Brazen
TKM10 - Soshangane
collar to be replaced
TKM09 - Barry
TKM08 - Benjamin
TKF02 - Joan
TKM05 - Mac
TKM06 - Classic
TKF01 - Diney
TKM07 - Alex
KNM01 - Mapimbi
TKF03 - Mandy
collar to be replaced
TKM27 - Vee
TEMBO collar
TKM12 - Intwandamela
TEMBO collar
TKF07 - Summer
TM13 - Matambo
Figure 15. Timeline of collar deployment and animal tracking at the end of 2008. The lifespan of currently active collars, based on their battery capacity, data recording schedule and erroneous plots, is projected beyond 2009. 5. Acknowledgements We would like to thank SANParks for their continued support. The following KNP personnel are thanked for never failing to be supportive: Dr. Danie Pienaar, Dr. Freek Venter, Dr. Stefanie Freitag-Ronaldson, Dr. Sam Ferreira, Dr. Markus Hofmeyr and Dr. Peter Buss. We would like to thank Jacques Brits, Colin Rowles and Craig Ferguson, as the Wardens of the APNR, for their interest and assistance during collaring operations. We are very grateful to all the landowners of the APNR who have kindly allowed us to traverse their properties. The following organisations have offered invaluable financial and logistical support: Intel, Save the Elephants, Tanda Tula Safari Lodge, Toyota, WESSA and Wildlife Pharmaceuticals. Numerous smaller private sponsors have made the purchasing of collars possible. Last but not least, we would like to express our heartfelt gratitude to Marlene McCay, South African representative of Save the Elephants for her unfailing support and interest at all levels of the project.
8. Other information (references) Armbruster, P. & Lande, R. 1993. A population viability analysis for African
elephant (Loxondonta africana): how big should reserves be? Conservation Biology 7:602-610.
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Bradshaw, G.A. 2004. Not by bread alone: symbolic loss, trauma, and recovery in elephant communities. Society and Animals v. 12( 2) p. 143-158.
Bradshaw, G.A., A.N. Schore, L.B. Brown, J.H. Poole & C.J. Moss. 2005. Elephant breakdown. Nature 433, 807.
Burke, T. 2005. The effect of human disturbance on elephant behaviour, movement
dynamics and stress in a small reserve: Pilansberg National Park. MSc thesis, University of KwaZulu Natal, Durban.
Calef, G.W. 1988. Maximum rate of increase in the African elephant. African Journal
of Ecology 26:323–327. Chamaille-Jammes, S., Fritz, H., Valeix, M., Murindagomo, F. & Clobert, J. 2008.
Resource variability, aggregation and direct density dependence in an open context: the local regulation of an African elephant population. Journal of Animal Ecology 77:13-144.
DEAT 2007. Draft National Norms and Standards for the management of elephants in
South Africa. Department of Environment and Tourism. Government Gazette, 2 March 2007.
Douglas-Hamilton I. 1972. On the ecology and behaviour of the African elephant.
PhD thesis, Oxford University, Oxford. Douglas-Hamilton, I. 1997. Proposal for “green hunting” of elephants as an
alternative to lethal sport hunting. Pachyderm 24: 30-32. Dublin, H.T & Douglas-Hamilton, I. 1988. Status and trends of elephant of the Serengeti-Mara ecosystem. African Journal of Ecology 25: 1933. Gertenbach, W.P.D. 1983. Landscapes of the Kruger National Park. Koedoe 26: 9-121. Getz, W.M. & Wilmers, C. C. 2004. A local nearest-neighbor convex-hull
construction of home ranges and utilization distributions. Ecography 27:489-505. Getz, W.M., Fortmann-Roe, S., Cross, P.C., Lyons, A.J., Ryan, S.J. & Wilmers, C.C.
2007. LoCoH: nonparameteric kernel methods for constructing home ranges and utilization distributions. PLoS ONE 2:e207.
Greyling, M. D. 2004. Sex and age related distinctions in the feeding ecology of the
African elephant, Loxodonta africana. PhD. Thesis, University of the Witwatersrand, Johannesburg.
Hanks, J. & McIntosh, J.E.A. 1973. Population dynamics of the African elephant
(Loxodonta africana). Journal of Zoology, 169:29–38. Jolly, G. M 1965. Explicit estimates from capture-recapture data with both death and
immigration – stochastic model. Biometrika 52:225-247.
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Junker, J., van Aarde, R.J. & Ferreira, S.M. 2008. Temporal trends in elephant Loxodonta africana numbers and densities in northern Botswana: is the population really increasing? Oryx 42:58-65.
Kaplan, E.L. & Meier, P. 1958. Nonparametric estimation from incomplete
observations. Journal of the American Statistical Association 53: 457-481. Laws, R.M. 1966. Age criteria for the African elephant, Loxodonta africana. East
African Wildlife Journal 4: 1-37.
Mackey, R.L., Page, B.R., Duffy, K.J. & Slotow, R. 2006. Modelling elephant population growth in small, fenced, South African reserves. South African Journal of Wildlife Research 36:33–43.
Mantel, N. 1966. Evaluation of survival data and two new rank order statistics arising
in its consideration. Cancer Chemotherapy Reports 50(3): 163-170. McComb, K., Baker, L. & Moss, C. 2005. African elephants show high levels of
interest in the skulls and ivory of their own. Biology Letters, Royal Society of London. pp. 1-3. (doi:10.1098/rsbl.2015.0400).
Moss, C.J. 2001. The demography of an African elephant (Loxodonta africana)
population in Amboseli, Kenya. Journal of Zoology, London 255:145-156. Owen-Smith, N., Mason, D.R. & Ogutu, J.O. 2005. Correlates of survival rates for 10
African ungulate populations: density, rainfall and predation. Journal of Animal Ecology 74:774-788.
Owen-Smith, R.N. 1988. Megaherbivores: the influence of large body size on
ecology. Cambridge Univ. Press. Payne, Katy. 1998. Silent thunder: In the presence of elephants. New York: Penguin
Books. Payne, Katy. 2003. “Sources of social complexity in three elephant species” in Frans
de Waal, and B.M. & Peter L. Tyack, Animal Social Complexity: Intelligence, Culture, and Individualized Societies. Cambridge, Massachusetts: Harvard University Press, pp.58 – 85.
Poole, J.H. & Moss, C.J. 1981. Musth in the African elephant (Loxodonta africana).
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thesis, Cambridge University Press, Cambridge. Poole, J.H. 1987. Rutting behaviour in African elephants: the phenomenon of musth.
Behaviour 102: 283-316. Shannon, G. 2005. The effects of sexual dimorphism on the movements and foraging
ecology of the African elephant. PhD. Thesis, University of KwaZulu-Natal, Durban.
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Slotow, R & van Dyk, G. 2000. Role of delinquent young "orphan" male elephants in high mortality of white rhinoceros in Pilansberg National Park, South Africa. Koedoe 44: 85-94.
Slotow, R. & van Dyk, G. 2001. Role of delinquent young "orphan" male elephants in
high mortality of white rhinoceros in Pilanesberg National Park, South Africa. Koedoe 44:85-94.
Slotow, R., Balfour, D & Howison, O. 2001. Killing of black and white rhinoceros by
African elephant in Hluhluwe-Umfolozi Park, South Africa. Pachyderm 31:14-20. Slotow, R., van Dyk, G., Poole, J., Page, B. & Klocke, A. 2000. Older bull elephants
control young males. Nature 408: 425-426. Spinage, C.A. 1994. Elephants. T & A D Poyser, London. Stalmans, M, Attwell, B & Estes, L. 2002. Hunting in the Associated Private Nature
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Stalmans, M, Attwell, B & Estes, L. 2003. Hunting in the Associated Private Nature
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van Jaarsveld, A.S., Nicholls, A.O. & Knight, M. H. 1999. Modelling and assessment
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seasonal movements, and spatial segregation in African elephants: a contribution to conservation behavior. Behavioral Ecology and Sociobiology 61: 1919-1931.
Senior researchers contact details
Title Drs. Initials & Surname M. D. & S.R. Henley
Position Research ecologists Institution Save the Elephants (STE)
Department Transboundary Elephant Research Programme (STE-SA) Postal address PO. Box 960, Hoedspruit 1380
Telephone number 015-7930369 Fax number 015-7930496
Cell phone number e-mail address [email protected]
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