population dynamics and elephant movements within the...

Population dynamics and elephant movements within the Associated Private Nature Reserves

and adjoining Kruger National Park

Annual Report December 2006

Dr. Michelle & Steve Henley

STE Transboundary Elephant Research Programme

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1. Introduction The STE Transboundary Elephant Research Programme started in May 2003. Initially a substantial amount of effort was directd towrd getting the project established and recognised, securing funds for collars and other expenses, and securing the support of land-owners and managers within the Associated Private Nature Reserves (APNR). With time we have been able to get more collars deployed, build up a register of known individuals and accumulate resightings. Consequently, after 3½ years we have sufficient reliable data to provide meaningful insights into the ecology of elephants within the APNR and greater Kruger National Park (KNP) biosphere area. We are entering the first phase of data analyses and publication within the first cycle, and this will be a primary focus for the coming year. Objectives The research programme objectives, as originally stated in the project proposal, are: 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; 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 specific tree species. While the annual aerial census provides a count of the number of elephants within the APNR, this intentionally covers as short a period in time in the dry season each year as possible. As such these data may be compared from year to year. What is lacking is a more subtle measure of seasonal change in the population. This is of particular importance in reserves such as the APNR which are open to a larger population. The first two objectives of this study seek to address this question by applying relevant capture-recapture models to resightings data. The fifth objective places these data within their spatial context and seeks to identify potential drivers of population change. Identifying the elephants' spatial and temporal distribution patterns (Objective 6) require data of finer resolution and hence the fitting of telemetry collars to a subset of the population. The collars also enable us to address the fourth objective, determining movement patterns within the APNR and surrounds. The seventh objective is possibly the key research question behind the study: what determines the observed elephant distribution and movement patterns? The remaining two objectives (3 and 8) are of particular interest to managers within the APNR. The first of these, identifying large tusked bulls, stems from the unique opportunities inherent in studying a a population of known individuals, even if it is

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essentially an open population. The last objective, the interaction between elephants and specific trees, is essentially a stand alone exercise. Review period This report provides feedback on the project for the period December 2005 to November 2006. Environmental conditions Plant growth and phenology (life stage) is largely driven by day length, temperature and rainfall. This in turn exerts a strong influence on the availability and quality of habitat resources for animals such as elephants. Of these, rainfall is the most variable and visible, particularly through its effect on surface water availability and the herbaceous vegetation. While it is acknowledged that variability from year to year means that few years actually receive an average amount of rainfall, mean values are still of value to place any one month or season in context. Therefore, rainfall averages, both annual and monthly, have been calculated. These were derived as the mean from three localities that span the APNR and have reliable data for an extended period. The stations are: Ingwelala in the northern Umbabat PNR (1983 – 2004), Hoedspruit Air Force base west of the APNR (1977 – 1990) and Kingfisherspruit ranger station, KNP which is on the south-eastern bondary of the APNR (1957 – 2003). The total rainfall for the most recent austral cycle (July 2005 – June 2006), recorded at the elephant research station was 824.5 mm. This is more than 1.6 times the expected annual rainfall for this area (507mm). However, the past year was characterised by extreme fluctuation: a very wet wet-season and very dry dry-season. The five months making up the wet-season (November – March) on average received 207% of what may be expected based on the mean monthly value (range: 105 – 357%), i.e. twice as much. The dry season months (May - September) on average received less than a quarter of the monthly mean (range: 6 – 54%). The new season once again got off to a good start with the first month of the wet season (November) already having received more than 94mm, 1.3 times the mean.

Fig. 1.1. The monthly rainfall (mm) as recorded at the Elephant Research station between 1 October 2005 and 27 November 2006 and the monthly mean.

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Temperature and day-length are two other important environmental variables that influence both vegetation and wildlife growth and survival. Day-length does not vary in any meaningful way from year to year, however temperature does and as should be monitored.

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Fig. 1.2. The mean minimum and maximum daily temperatures (box) and the range (whisker plot) as recorded at the elephant research station between October 2005 and November 2006.

As part of the habitat monitoring effort we initiated a fixed point photograph programme close to where the rainfall and temperature data are gathered; the objective being to provide a visual record of the vegetation response to climatic data. Photographs were first taken in May 2006 and will continue to be taken each month. It must be noted that the camera used to take the photographs was changed between September and October. We will need to standardise the images, using the white page in the centre of the picture, before attempting any rigorous analyses. A subjective evaluation of the photograph sequence (Fig. 1.3) highlights the following points:

• in the absence of frost, the senescing of herbaceous vegetation took place between May and June, two to three months after the past substantial rains;

• there was a relatively high phytomass of dead grass material for much of the dry season, with a rapid drop off in cover over the months of September and October;

• grass regrowth was quite rapid following the rains in October and November; • leaf loss amongst the woody species appears to have been a more protracted

process, with a few evergreen species retaining some leaf material throughout the dry season;

• woody plant leaf emergence started for a few species in October with the increase in day length and daily temperature;

• the greatest change in the woody vegetation also appears to have taken place in November.

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Fig. 1.3. Fixed point photographs taken from May to November 2006. Photographs are taken on the 25th day of each month, or the next day with less than ¼ cloud cover.

These observations support our seasonal designation, with May to Sept being the dry season, October the transition between the dry and wet seasons and November the start of the wet season (cf Appendix 1 in the December 2005 Report).

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2. ID study 2.1. Identification of elephant bulls Individual identification records of sighted animals (bulls and cows) were recorded by collecting detailed photographs or drawings based on unique patterns of tears, nicks, holes and veins in the ears. The date, time and location of each sighting was noted in addition to the social context, the reaction index and reproductive status of the sighted individual. A total of 2 025 sightings of bulls have been made since May 2003 until November 2006. This figure includes multiple sightings of the same animal within a month as well as sightings of bulls of which only one ear pattern was collected (incomplete identification). The complete (both ears) identification kits of 564 individual bulls were collected during the study period. Bull sightings have been divided into size and age categories and all subsequent analyses have been conducted within each of these categories. These categories include: • Immature bulls – the identification of immature bulls have not been the primary focus

of the study and records were only collected if observation time within a breeding herd 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 will be continued as it will 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. • Prime bulls. Multiple sightings of an individual bull 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 (Fig. 2.1, r2= 0.99). By July 2004 the accumulative re-sighting rate of prime bulls had exceeded the accumulative sighting of new bulls so that re-sightings of prime bulls were more frequent than new sightings within this size category (Fig. 2.1 (c)). Results indicate that in the young- and immature bull categories, the new-sightings rates had not yet reached an asymptote. This could be expected for the immature bulls for the reasons outlined above. Although the number of identification records collected of young adult bulls exceeds those collected within any other size category of bulls, only 44% of these animals have been re-sighted since the start of this project (Table 2.1). These preliminary results therefore indicate that the majority of the bull population within the APNR is composed of young adult bulls while prime bulls represent the most stable component of the population.

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May July Sept Nov Jan Mar May Jul Sept Nov Jan Mar May Jul Sept Nov Jan Mar May Jul Sept Nov

Immature bull component of the population

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Fig. 2.1. The accumulative number of re-sightings and new sightings of immature (a), young (b) and prime bulls (c) from May 2003 until November 2006.

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Table 2.1. Immature, young adult and prime adult bull resightings and re-sightings 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 151 55 96 36 Young adult 242 106 136 44

Prime 171 126 45 74 Total 564 287 277 51

2.2. Musth in bulls The proportion of musth bulls increased and decreased in a similar way to the long term and short term mean monthly rainfall, but with a delay of approximately two months. The proportion of musth bulls reached a peak in March 2004, March 2005 and then in Aug 2006 (Fig. 2.2). In general, the largest proportion of bulls were in musth after the peak in the mean monthly rainfall (refer to the line drawings which depict trends). The early dry season would be the most suitable time for bulls to come into musth as it follows a two-month time lag in a peak in the mean monthly rainfall (long-term rainfall data). Cows that conceive from February through to June would give birth 22 months later from December through to April during the late rainy season. By implication, these cows would have access to the most nutritious food sources when their physiological needs would be the highest such as during late pregnancy and early lactation. Their offspring would consequently have the greatest chance of survival.

M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N0

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Monthly proportion of musth bulls

Mean monthly rainfall – calculated from three stations that span the area of the APNR andhave reliable data for a period of >14 years (Hoedspruit, Ingwelala and Kingfisherspruit)

Mean monthly rainfall - calculated from data collected throughout the reserve from May2003 until November 2006)

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Fig. 2.2. The proportion of musth bulls expressed as a percentage of the total number of bulls sighted within each month from May 2003 until November 2005. Please note that the musth trend line is continually being updated as long as additional data is received from landowners and other interested parties which submit photographs and sighting information on prime bulls.

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2.3. Identification of breeding herds A total of 489 sightings of breeding herds were made since May 2003 until November 2006. This figure includes multiple sightings of the same herd within a month as well as sightings of herds were no identification records could be collected either due to poor visibility or rapid movement amongst the members of the herd. The identification records of 236 individual cows have been collected from 19 independent breeding herds that have been identified and 29 identikits from cows that could not be ascribed to any particular herd at this point in time. Multiple sightings of the same herd were pooled within a month to obtain a monthly resighting 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 (Fig. 2.3, r2= 0.97 and r2= 0.99 respectively). By February 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.


Breeding herd component of the population


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Fig.2.3. The accumulative number of re-sightings and new sightings of breeding herds from May 2003 until November 2005. The re-sightings of breeding herds is at a 84% level since May 2003, this proportion more than likely over represents the actual re-sighting rate for the entire APNR but would accurately reflect the re-sighting rate of breeding herds utilising the central and

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northern regions of the Timbavati, the Umbabat and the area to the east of the Klaserie river within the Klaserie PNR (Table 2.2). Table 2.2. 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

Number of breeding herds sighted only once since

May 2003

Re-sighting percentage

19 16 3 84

Cows sighted in the north-west of Klaserie, within Balule and in the far south of the Timbavati have not been ascribed to any particular herd because of infrequent sightings and were excluded from the analyses. 3. Telemetry study Collars were fitted to eight new elephants in 2006, one female and seven males. Three collars were replaced, namely Classic, Diney and Joan. This brings the total number of collars currently deployed by this project to 18; 13 on males and five on females (Table 3.1). One other animal, a young adult male, was collared in 2004, but his collar was not replaced when it ceased functioning as he spent most of his time north of the APNR, within the PMC mining area and as such was not considered to be representative of the APNR-KNP population we are studying. Table 3.1. Summary information of telemetry collars currently deployed by the STE Transboundary Elephant Research Programme. The fitment date refers to the the date the collar was deployed, and not when the animal was first collared. Schedule refers to the current data recording interval in hours. The collar's life span is the estimated as the number of days it is expected to continue gathering data at the present schedule. Age & sex Fitted Type Schedule Lifespan Notes Alex ad ♂ Nov 2004 GPS-satellite 24 hr 131 collar due for replacement

Mac prime ♂ May 2005 GPS-satellite 24 hr 65

Barry ad ♂ May 2005 GPS-GSM 5 hr 2 345

Mandy ad ♀ May 2005 GPS-GSM 5 hr 2 312

Brazen prime ♂ Nov 2005 GPS-GSM 5 hr 2 494

Soshangane ad ♂ Nov 2005 GPS-GSM 5 hr 2 331

Monarch ad ♀ Nov 2005 GPS-GSM 5 hr 2 522

Classic prime ♂ June 2006 GPS-GSM 5 hr 1 320# replacement collar, schedule to change to 1hr

Striburus ad ♂ June 2006 GPS-GSM 1 hr 1 263

Diney ad ♀ June 2006 GPS-GSM 5 hr 1 308# replacement collar, schedule to change to 1hr

Everest prime ♂ Sept 2006 GPS-GSM 1 hr 1 288

Caughley ad ♂ Sept 2006 GPS-GSM 5 hr 1 324# schedule to change to 1hr

Tussle ad ♂ Sept 2006 GPS-GSM 1 hr 1 291

Gower ad ♂ Oct 2006 GPS-GSM 1 hr 1 309

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Lifespan Age & sex Fitted Type Schedule Notes Lapajuma ad ♀ Oct 2006 GPS-GSM 1 hr 1 308

Joan ad ♀ Oct 2006 GPS-GSM 1 hr 1 288 replacement collar

Wessa ad ♂ Nov 2006 GPS-GSM 1 hr no data downloaded

Proud ad ♂ Nov 2006 GPS-GSM 1 hr no data downloaded

# lifespan calculated using an hourly data gathering interval

Six collars have also been fitted to elephants as part of the Tembo research project, three males and three females. We have a reciprocal data sharing agreement with Tembo and these animals must also be considered when evaluating the demographic spread of monitored animals. In total 24 elephants are currently fitted with collars, 16 males and eight females. This means we have been able to deploy more collars by this time than was expected (cf Table 3.2), and the spread between males and females is as intended. Table 3.2. The expected number of elephants collared as presented in our February 2006 Quarterly Report. Dec 2005 Dec 2006 Dec 2007 prime-aged adult bulls 3 6 9 young adult bulls 3 6 10 adult cows 4 6 10 Total 10 18 29 To reach our objective of 30 collars concurrently deployed by the end of 2007, we will have to fit six new collars next year. Furthermore, one study animal, Alex, is due for a replacement collar (cf Table 3.1) and one of the collars fitted to a female, Mtsiri, as part of the Tembo project, may stopped functioning (no data has downloaded since August and yet the animal has been regularly resighted). If we are to continue monitoring these animals their collars will also have to be replaced next year. Therefore, we plan to fit eight collars in 2007. Given their current data gathering schedule (half-hourly interval), the five other collars deployed by Tembo will probably need to be replaced early in 2008. Seven collars were recently fitted to bull elephants along the eastern border of KNP with the support of SANParks. These will be used to monitor movements between KNP and Limpopo NP along the recently opened border between these protected areas. The elephants were collared in an area close to Mac's non-musth range, and so by providing insights into the movement patterns of other bulls from this area, will also be of relevance to the APNR study. When fitting collars we have tried to select animals that will provide a sample which is representative of the social diversity within an elephant population. Breeding herds are a relatively cohesive group and collared adult cows effectively tag the whole group. With

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bulls we tagged individuals representing different life stages or age classes. Growth in elephants is indeterminate and body size, particularly body length, increases continually with age (Haynes 1991). Hind foot length is strongly correlated with shoulder height and may also be used as surrogate measure of body size and age (Western et al. 1983; Lee & Moss 1986; Lee & Moss 1995). A plot of these morphometric parameters (Fig. 3.1) shows that the collared bulls span a range of body size as intended.

Fig. 3.1. Body length (following the curve) and mean hind foot length of the collared male elephants. Morphometric measurements were taken from immobilised animals during collaring operations.

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We currently have 10 study animals that have been monitored for more than a year. This represents a relatively robust data set in terms of range use and movement patterns which will change seasonally within the year. Five animals have been collared for two years or more, providing some insight into the persistence of these patterns over time. The telemetry component of this research programme is therefore entering a data analysis and publication phase, and this is expected to be the focus of much of our effort for the first half of next year. The aim is to adopt a deductive approach, with this period of analysis focusing on relatively broad-scale issues and providing the motivation for more specific research in future. This approach not only make sense from a reasoning point of view, it is also consistent with the available data. The first collars fitted were GPS-satellite collars which recorded data at 8 hour intervals at best. Since May last year we have been fitting primarily GPS-GSM collars, recording data at 5 hour intervals. The most recently fitted collars will be gathering location data hourly.

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The analyses presented in this report were based primarily on daily telemetry data of the 10 elephants monitored for a year or more, incorporating data up to the end of October 2006. 3.1. Elephant movement patterns Movements define location patterns, location in turn defines range use and habitat selection. It is logical therefore to look firstly at movement patterns, before discussing range use and habitat selection. We evaluate movement patterns primarily using two attributes: rate of movement, that is the distance travelled as a function of the interval between location points, and turning angle, the change in the direction travelled between consecutive location records. Rapid movements and small turning angles will maximise the distance between points. Low rates of movement and large turning angle will keep the animal within a confined area or particular range node (cf. the December 2005 annual report for more detail). Given the disparity in sample sizes between study animals (e.g. Mac: n = 4 932; Soshangane: n = 208) most analyses presented here were performed on the mean values for individual elephants. This will remove the bias toward individuals with a large number of location records and make the results reflect more closely the population. The mean rate of movement of the collared elephants was 0.14 km hr-1 and the mean turning angle = 94.80. In general the cows tended to have lower rates of movement ( = 0.13 km hr-1) and larger turning angles ( = 95.60) than bulls ( rate of movement = 0.15 km hr-1,; turning angle = 94.40), however these difference are not significant (2 – tailed unpaired t-test: rate of movement p = 0.23; turning angle p = 0.68). Seasonally, elephants appear to increase their rate of movement following the rains (Fig. 3.2). The seasonal difference in the movement rate is approaching statistical significance (two-tailed paired t-test on mean rates of movement t = 2.26, df = 9; p = 0.09).

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Fig 3.2. The mean seasonal movement parameters of collared elephants. Bulls are coloured blue and cows magenta.

Mac, a prime bull, undertakes exception movements each year, rapidly changing his nodal location from the north of KNP to the APNR and adjacent KNP during the wet-dry transition period, returning northward again toward the end of the dry season. The proximate driver behind these movement appears to be his musth status, and this may be influencing the seasonal movement patterns of the other elephants. If his data are removed, the seasonal difference in rate of movement becomes statistically significant (t = 2.31, df = 8 and p = 0.02). Classic, another large bull appears to have little or no discernible difference in seasonal movement patterns (Fig. 3.2). As with Mac, his musth cycle strongly influences his movement patterns (cf. the December 2005 report) and there is a significant difference in the rate of movement between his musth and non-musth phases (mean musth 0.26 km hr-1, mean non-musth = 0.09 km hr-1). It would seem, therefore, that the elephants within the APNR and adjacent KNP move further on a day to day basis in the wet season than in the dry. This is most probably in response to seasonal changes in resource availability. Following the rains, resources such as water, forage and shade are widely dispersed. In the dry season these tend to be localised, particularly in riverine areas and along drainage lines. However, amongst the large bulls, the musth cycle appears to exert a stronger influence then rainfall. This has potentially important implications in terms of dry season resource use and elephant impacts on vegetation, but needs to be confirmed once other collared bulls have repeated their musth cycles. We are also using the movement data to evaluate associations between individual elephants. The assumption being that an association is not only expressed by the proximity of one elephant to another, but also by their co-ordinated movement behaviour. Elephants are known to communicate over large distances, and if individuals show a strong correlation in the direction and rate of their movements it may be evidence of a degree of association between them.

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As a first evaluation of this approach we compared the daily telemetry data for two elephants over a 46 day period when Classic was known to have repeated associated with the Flowers herd, although not necessarily with Diney's family group. Location data were only used when the interval between the two elephants' plots was ≤ 15 minutes, that is both animal's data were recorded at approximately the same time of day. A plot of the distance between the two collared animals (Fig. 3.3) clearly shows periods when they were in relatively close proximity. However, these periods do not always correspond with the periods when the movement data suggest they may have been associating (i.e. difference in direction of movement ≤ 450 and difference in rate of movement ≤ 0.05 km hr-1). It is not surprising, therefore, that we found only weak correlation between the distance separating the two study animals and movement parameters (difference in rate of movement: r2 = 0.18; difference in direction of movement: r2 = 0.25). This implies that they are separate measures and the one is not a surrogate for the other.

Fig. 3.3. Distance (km) separating the daily location plots of Classic and Diney. Resighting events are marked by the red arrow. Green bars highlight periods when the two elephants were moving in a similar direction and speed.

There are four possible permutations of these two measures which may define different relationships between the study animals:

1. a lack of co-ordinated movement and substantial distance between the study animals reflecting an absence of association;

2. a lack of co-ordinate movement at a time of close proximity may reflect an episodic visitation, i.e. animals moving independently to briefly meet;

3. co-ordinated movements and close proximity may reflect a period of association;

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4. co-ordinated movements but a substantial distance separating may reflect either a diffuse association or similar movements in response to changes in the availability or quality of a shared resource.

The last scenario requires the most reflection and refinement. For example, it highlights the need for a critical distance, which has biological meaning (e.g. defined by ability to communicate), beyond which associations cannot be assumed to be sustainable. Secondly it requires the scale, both temporal and spatial, at which associations are being measured to be clear. In the light of the above we can identify different phases in the association between Classic and Diney as shown in Fig. 3.3. It must be borne in mind that at this time Classic was in musth, and this will influence his movement and association patterns. Firstly the period 1 to 3rd March, there was an absence of association. This was followed by a brief association centred on the 5th March and then an 18 day period showing an absence of association. The distance separating the two animals on the 13th and 14th March suggest that this was not a period of association despite their apparent co-ordinated movements. On the 25th March there was a visitation, followed by a period of association between the 4th and 9th April and again starting on the 14th April. Resightings records suggest that there may have been an oestrus female in the Flowers herd at this time. The above pattern of association may then reflect Classic's initial inspections, and him then returning for a period of association with this cow, interspersed with a brief respite between the 10th and 13th April. There would appear to be some merit in this method of analysis, and it may add value to typical measures of association based on proximity. We will be investigating it further in future, hopefully with the support of someone familiar with spatial statistics. 3.2. Elephant range use patterns A map of the daily distribution data for each of the 18 STE collared elephants is given in Appendix 1. One of the objectives of this project is “to establish the extent to which elephants frequent different parts of the APNR and KNP”; from these data it is clear that no collared elephant which we have been monitoring for a year or more uses less than four different management areas. Furthermore, all these animals make use of both the APNR and KNP to varying degrees. The distribution of location records across the Reserves is given below in Table 3.3. Balule PNR has been kept separate from the rest of the APNR as the fences between this reserve and the Klaserie PNR were only recently dropped. Table 3.3. Proportional distribution of elephant location data points within different protected areas of the Greater KNP biosphere area. APNR Balule PNR KNP other Diney 77 0 23 0

Joan 24 15 5 56

Mandy 89 10 1 0

Monarch 97 1 2 0

cow mean 72 7 8 14 Alex 63 0 24 14

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APNR Balule PNR KNP other Barry 45 0 40 15

Soshangane 82 3 7 9

adult bull mean 63 1 24 12 Brazen 98 0 1 1

Classic 97 0 3 0

Mac 10 0 88 2

prime bull mean 68 0 31 1

overall mean 68 3 19 10

Overall, the distribution of the collared elephants is centred on the APNR. However, contrary to expectations, breeding herds appear to be making as great if not greater use of the recently incorporated Balule PNR than the bulls. Two of the prime bulls (i.e. males >35 years old), Classic and Brazen, are essentially restricted to the APNR. This corroborates the developing idea that these individuals have an entrenched spatial and temporal distribution pattern, and seldom deviate from this. These bulls would have developed this pattern at a time when the APNR was isolated from both KNP and Balule PNR, and despite more recent opportunities, adhere to it. Mac, is an exception in many regards, nonetheless his range use pattern may also be best explained by the management legacy of these protected areas. At this stage there is no clear seasonal differentiation in the use of management areas. Key range attributes are summarised in Table 3.4. These serve to emphasise once again the fact that elephants collared within the APNR are moving over substantially larger areas then was expected based on earlier research (de Villiers & Kok 1997: bull MCP = 238 km2; cow MCP = 414 km2 Timbavati PNR and 183 km2 in the Klaserie PNR). Table 3.4. Collared elephant range summary statistics based on daily location data: minimum convex polygon (MCP) estimate of home range size (km2); the 90% kernel probability area (km2) and eccentricity - the ratio between the primary and secondary range axes as a measure of range shape (1 = circular, >1 = elliptical). Collared Data points MCP 90% Kernel Eccentricity Notes Mac May 02 1 150 5 105 2 988 2.72 Classic May 04 842 1 144 332 1.11 Diney May 04 792 1 255 377 1.63 Alex Nov 04 386 4 558 1 559 1.21 Joan Nov04 619 1 304 225 1.21 Barry May 05 416 2 740 729 1.32 Mandy May 05 462 1 144 541 1.83 Brazen Oct 05 289 1 341 512 1.49 Soshangane Oct 05 267 2 661 664 1.72 Monarch Oct 05 290 1 207 481 1.13 Striburus June 06 data covers <1 year Caughley Sept 06 data covers <1 year

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Eccentricity Collared Data points MCP 90% Kernel Notes Everest Sept 06 data covers <1 year Tussle Sept 06 data covers <1 year Gower Oct 06 data covers <1 year Lapajuma Oct 06 data covers <1 year Wessa Nov 06 data covers <1 year Proud Nov 06 data covers <1 year

Within these home ranges, the elephants are not evenly distributed but show a tendency toward a clumped distribution (Table 3.5). This is slightly less obvious amongst the younger adult bulls ( R = 0.72) compared with the cows ( R = 0.61) and prime bulls ( R = 0.62). In other words the young adult bulls appear to be slightly more inclined to use their entire home range evenly than the cows and prime bulls, which are more focused on specific areas within the greater home range. At this stage it is surmised that this is a response to localised resource distribution on the part of the females and the restricted non-musth range of prime bulls. Table 3.5. Nearest-neighbour index (R) of the degree of clustering or dispersion of points within the area defined by the extent of distribution (MCP). An R value = 1 indicates a random distribution, R < 1 indicates a tendency toward a clumped distribution and R > 1 a tendency toward a uniform dispersion of data points within the range area. Year Wet season Dry season Diney 0.56 0.55 0.37 Joan 0.55 0.70 0.24 Mandy 0.71 0.66 0.61 Monarch 0.62 0.49 0.39 Alex 0.74 0.64 0.40 Barry 0.71 0.71 0.36 Soshangane 0.71 0.74 0.50 Brazen 0.70 0.66 0.64 Classic 0.59 0.43 0.58 Mac 0.58 0.33 0.54

Habitat resources, such as forage and water, tend to become scarce in the dry season and so it is not surprising then that elephants are localised in their daily movements at this time. This holds true for the cows ( wet season R = 0.60; dry season R = 0.40) and younger adult bulls ( wet season R = 0.70; dry season R = 0.42). Prime bulls on the other hand show the inverse pattern ( wet season R = 0.47; dry season R = 0.59). A speculative explanation for this difference in pattern is that cows and younger adult bulls, being of smaller body-size and having relatively higher energy demands (mass-

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specific metabolism and reproduction), are more responsive to change in resource distribution and availability. The added burden of producing and raising a calf means that even in the wet season cows are more constrained when compared with the bulls and so the wet and dry season R values are lower and the difference between them smaller. Prime bulls on the other hand, typically spend the wet season within their non-musth range and a large part of the dry season in musth amongst the breeding herds. Their reproductive strategy, therefore, has a greater influence on range use patterns than resource distribution. Habitat modelling is a useful means of developing and evaluating hypotheses such as the above, as well as addressing many of the original objectives of this study. For this reason we have been developing broadscale habitat quality models and will be refining and validating these in future. We have adopted a deductive approach and as a first iteration are using daily data from the 10 elephants with at least a year's data (i.e. collared in Nov 2005 or earlier). We are working from the premise that habitat selection is determined by the need to meet life requisites (food and water), minimise risk (thermal stress and predation) and enable social interaction (avoid stress and reproduce). A habitat quality model should reflect changes in the distribution (spatial and temporal) of resources required to meet these needs and the elephants' response. Hence the model must be spatially explicit and have a clear seasonal context. At this stage, given the differences in data (GIS layers) available for the different management areas, we are focusing on the APNR (excluding Balule PNR) as the study area for developing a habitat quality model. In future, once we have identified key habitat variables and are able to standardise their definition and scale across the different management areas, we hope to extend the model to encompass the entire area available to the monitored elephants. Fig. 3.4 provides a conceptual outline of the elephant habitat quality model. Currently we are considering five habitat submodels: a vegetation submodel, a water submodel, a topography submodel, a social landscape submodel and a risk submodel. Each submodel comprises a number of habitat variables. Each variable will interact with an elephant response model (foraging, drinking, thermal comfort, risk avoidance and social interaction).

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Fig. 3.4. A conceptual outline of the proposed APNR elephant habitat quality model.

An APNR (Klaserie, Umbabt and Timbavati PNRs) vegetation map has been produced by N. van Rooyen and IRIS International, Potchefstroom. While it provides a very useful basis for habitat modelling, it must be borne in mind that the map was the product of an earlier phyotosociological study by Andy Purchase, and not an exercise in describing ungulate habitat units. Consequently we modified the vegetation types to form biotopes, where a biotope is defined as a homogeneously diverse spaces which contain recognisable communities on a scale consistent with the range of the organism under consideration (Carey 1981). Important considerations in defining biotopes were the temporal scale of the animal distribution data, i.e. daily movements used to define seasonal distribution patterns, and the change in vegetation physiognomy (structure) and phenology (life history) appropriate to this scale. Another consideration was the potential to extend them to other management areas such as the KNP and Balule PNR using either existing vegetation maps or satellite data. We opted for four primary biotopes within the APNR (Fig. 3.5), namely: microphyllous/acacia woodland, broad-leafed woodland, mopane woodland and riverine. These are a composite of the original vegetation types and their appropriateness still needs to be evaluated in the field. Current telemetry data suggest that elephants have a strong affinity for riverine areas. Classic is also making disproportionate use of the mopane woodland, particularly during his non-musth period.

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Fig. 3.5. Habitat biotopes within the APNR. Topography variables: slope and aspect, will be derived from GIS derived TIN (triangulated irregular network) layers using DEM data if we can access this or contour line coverages. Terrain complexity, heterogeneity or ruggedness is a potential third habitat variable that may provide a more useful measure of topographic influence on elephant movements and distribution. Water as a habitat parameter is being characterised by the dry season availability. This is based on observations in the field of persistence of surface water at the water points. Availability is also being characterised by the size of the water body (length and breadth) as measured in the field. The relationship between elephants and water points is expected to be non-linear and hence distance from water, as a measure of availability, was grouped into <1km, 1-2 km, 2-4 km, 4–8 km and >8km classes (Fig. 3.6).

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Fig. 3.6. Perennial water distribution within the APNR and distance from water points.

Risk is being largely defined by the human-elephant interaction. Hunting and mortality records, as received from the Reserve Managers, will be used to plot areas of known deaths. However, these are relatively scarce and only partially describe the interaction between people and elephants within the APNR. The frequency of land-owner visitations and their attitude towards elephants will be gauged from the returns on a questionnaire survey which was conducted when we first started this project. Indices of risk will be validated using our resightings data and recorded reaction indices. Terrain ruggedness and the distribution of bulls may also be potential determinants of risk. Finally, one of the interesting hypotheses proposed at the outset of this research programme is that elephants movements may be motivated by social benefits. We have therefore tried to define a social landscape. Annual aerial census data provides the most complete snap-shot image of the elephant population's distribution. We used census data from 1994 to 2004 to capture the dry season distribution of family groups within the APNR. A composite of the kernel probability distributions (90% isoline) of all 10 years was then used to generate a social landscape coverage (Fig. 3.7). Social landscape plots will be validated with independent telemetry and resightings records. It may be argued that the social landscape, as a measure of elephant distribution, is simply a product of habitat quality and not a variable in itself. This may be the case if a population has saturated all resource areas, occupied all the available range space and achieved a stable equilibrium state, which is not likely in an expanding population. Furthermore, we are

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testing whether the social landscape is a proximate driver in range selection and so consider it worthy of inclusion in the model.

Fig. 3.7. Social landscape as defined by the frequency of overlapping elephant breeding herd ranges (90% adaptive kernel isoline) based on aerial census data from 1994 to 2004.

The next step is to gather data on the spatial and temporal distribution of habitat variables (cf Fig. 3.7) and then to define their relationship with the elephants. Typically these interactions are non-linear and so response curves will be generated to define for example the interaction between vegetation structure (physiognomy) and thermal comfort – once the threshold of sufficient shade for an entire herd has been passed, an increase in tree canopy cover does not necessarily mean an equal improvement in quality habitat. Multiple regression models or discriminant functions will be used to define the relationship between habitat variables and habitat quality. The model will be made spatially explicit using a raster GIS format. 4. Vegetation impact study A number of landowners have started placing wire-netting around trees while the Vlakgezicht study site has been extended. To keep up with the growing number of trees that need to be monitored, it has become necessary to try to employ a local person to

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assist with data collection. A request has been made to the landowners by means of the Elephant Newsletter to financially assist with the employment of such a person.

Additional chilli repellent trials are still under way as we await more testing material. Preliminary trials have indicated that the development of an environmentally friendly elephant repellent would be in demand within the APNR. 5. Environmental awareness project With the inclusion of Andrea Webster in the research programme and financial support from the Gower Trust (through WESSA), we were able to initiate a small environmental awareness project this year. The project will be targeting children aged between ten and twelve attending schools from areas around the APNR and focused on an interactive and practical learning experience. In keeping with the STE philosophy, the Transboundary Elephant Research Programme hosted their first Environmental Education and awareness project in September on Birmingham property at the Timbavati Bush School. Together with other STE study sites, the Transboundary Elephant Research programme recognizes that the best potential ambassadors for elephants are the people with whom they share their land. By involving local communities at grassroots level in research and education we hope to develop a conservation ethic based on local knowledge and elephant needs. 5.1. Funding The initial funding was sponsored by the late Mrs. Phyll Gower and is administered by the Wildlife and Environmental Association of South Africa (WESSA) in conjunction with Board of Executors (BOE). An amount of R10 064 was allocated for the educational whilst the remainder of the funds were spent on the purchase of GMS/GPS collars. 5.2. Target Group After discussions with lodges in the Timbavati, it was found that the majority of educational programmes currently being run were directed at older children on the verge of leaving school and focused at an academic level, yet nothing existed for the younger age group (10-12 yrs old) leaving primary school and still to make their subject choices. What made our approach unique was that the course content focused on a tactile rather than academic awareness of their natural heritage. 5.3. Objectives Our objectives were fourfold.

1) To create awareness of the research being carried out by Transboundary Elephant Research within the APNR, as well as the objectives, methods and results of the project to date.

2) Educate in the native language of the students so nothing was lost in translation.

3) Utilise the traditional knowledge and skills of local individuals. 4) Contribute to a more community based ethic as well as supporting local

business and products.

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5.4. Activities The activities were designed to involve the children on a number of different levels. Everyone was given the opportunity to tell stories, in so doing re-kindling oral traditions and creating an environment where everybody’s opinion was to be valued. All parties involved participated in every activity, from making musical instruments out of seed pods and other bush litter, to spoor identification with Eckson Ndlovu. Ringetani Community Project provided the foundation to learn more about the cultural aspects of Shangaan tradition through traditional dance and drumming. Planting an indigenous tree emphasised the significance of putting something back and taking only what is needed. An entire morning and early afternoon were spent tracking elephant with high tech telemetry equipment in conjunction with the skills of Eckson to show the value of balancing both ancient practices and modern technology.

By utilizing the skills of local individuals like the Ringetani Community Project, the Inyanga (herbalist), food suppliers and staff from the reserve, as well as providing booklets containing information on general bush knowledge in Shangaan we feel we contributed to a more community based ethic that was understood by all as well as supporting local business and products. 5.5. Conclusion The Transboundary Elephant Research Programme aims to host at least two children’s educational projects next year depending on funds. We are also looking to contribute toward an adult education programme within the APNR through the procurement of equipment necessary for a resource centre. The expectation is that an adult education will provide addition skills which can be used to aid the cause of conservation as well as uplift the APNR community. 6. Misc. 6.1. Communication As conservationists and scientists, we accept that it is important to convey the knowledge and insights we are able to gain in the field to the broader public. In the 12 months from December 2005 to November 2006, we gave 57 presentations to 228 guests visiting the research centre, and one each to 8 quests at Ntsiri, 21 Dartmouth University students at Bateleur Wilderness Safaris and 17 guests from Kings Camp. In total we presented the research project to 274 guests to the APNR in the past year. A further 26 landowners and guests accompanied us into the field on 13 days. We were also invited to give presentations to members of the WESSA Lowveld Branch and the Endangered Wildlife Trust and at these meetings spoke to approximately 80 and 180 attendees respectively. At a Timbavati Lodges' promotional day, in Johannesburg, we gave a presentation to approximately 70 people. There were four collaring safaris this past year, and one green hunt. These were attended by 58 paying guest. The profits from these, approximately R75 000, was paid to the APNR reserves.

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In total, we have formally presented the research project to approximately 690 people on 81 occasions over the past year. Furthermore, two film crews were accommodated this year. In June an Italian crew from Missione Natura made a documentary on green hunting and in October, the UK-based Two Hand Productions made a brief insert on collaring and the ageing of elephants which will be aired on BBC television. Our project was also the subject of one BBC radio programme and the topic of seven popular articles in the past year. The STE website was also re-launched this year, with a substantial upgrade in the amount and quality of information presented. This is proving to be a useful communication tool. As research ecologists, it is important to communicate and work with other scientists. This year we participated in the annual Kruger Networking Meeting and the Tembo workshop, both held in Skukuza. We also attended the t4cd (technology for conservation and development) conference in Cambridge, UK and the EMOA (Elephant Owners and Managers Association) conference in Pretoria. Alone with another STE scientist from Kenya, we were invited to attend an EarthWatch capacity building expedition to Ghana in July to investigate the feasibility of elephant movement corridors in that country. From a research perspective we are not only collaborating with other STE scientists, but have a formal data sharing agreement with the TEMBO research project and are planning collaborative work with scientists from both the University of KwaZulu-Natal and Ondestepoort, Pretoria, in the near future. As a small research team, with limited time and resources, we will only able to address larger research questions and conservation issues through such collaborative ventures. Finally, over the past 12 months we were able to accommodate four volunteers and give them exposure to field research for short periods. These were Georgette Lagendijk, a Dutch student who went on do start a research project, Andrea Webster, who joined the project on a full-time basis, Rebecca Fitch, from the UK and Gloria Ngwenya, a partner of one of the Tanda Tula staff members. 7. Conclusion Substantial progress has been made towards meeting our objectives. The ID study is providing valuable information on how many elephants are potentially using the APNR (objective 1 & 2). Most of the large tusked bulls (with tusks in excess of 50lbs) are on record with new sightings of large tusked individuals proving to be both rare and infrequent (objective 3). The telemetry study has proved to be of prime importance when determining the movements of elephants within the APNR and adjacent areas (objective 4). Keeping track of mortalities within the APNR, with the help of the managers, has provided information on how deaths could possibly be influencing densities within the APNR. The re-sighting rate of the ID study for each of the age and sex groups provides information on how dispersal may be responsible for changes in elephant density. We plan to keep track of births more closely in future now that we are familiar

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with most of the herds frequenting the APNR (objective 5). All collared animals that have been monitored for more than a year make use of both the APNR and KNP to a greater or lesser degree. We have gained insight into the seasonal use and distribution patterns of elephants within the APNR (objective 6). The accumulated body of data will enable us to develop habitat suitability models which when developed, will establish which of the potential drivers of elephant movements (resource availability, social or safety benefits) are having the strongest influence on their patterns of aggregation or dispersion (objective 7). The impact of elephants on certain trees species is a long-term objective which needs to feed into the on-going monitoring programme over a number of years and rainfall cycles (objective 8). The telemetry component of this research programme is entering a period of data analysis and presentation. At the end of this phase we will be well placed to re-evaluate the objectives of the Transboundary Elephant Research Programme and refine our future research efforts to answer key questions and provide insights for wildlife managers. The project has, by means of the recent educational initiatives and increased levels of public participation also met with the broader objectives of Save the Elephants i.e. to secure a future for elephants and to sustain the beauty and ecological integrity of the places they live, to promote man’s delight in their intelligence and the diversity of their world, and to develop a tolerant relationship between the two species.

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References Carey, A. B. 1981. Multivariate analysis of niche, habitat and ecotope. In: Capen, D. E.

(ed.) The use of multivariate statistics in studies of wildlife habitat. USDA Forest Service, General Technical Report RM-87.

De Villiers, P. A. and Kok, O. B. 1997. Home range, association and related aspects of elephants in the eastern Transvaal Lowveld. African Journal of Ecology 35:224-236.

Haynes, G. 1991. Mammoths, mastodons, and elephants.Cambridge: Cambridge University Press.

Lee, P. C. and Moss, C. J. 1986. Early maternal investment in male and female African elephant calves. Behavioural Ecology and Sociobiology 18:353-361.

Lee, P. C. and Moss, C. J. 1995. Structural growth in known-age African elephants(Loxodonta africana). Journal of Zoology London 236:29-41.

Western, D., Moss, C. and Georgiadis, N. 1983. Age estimation and population age structure of elephants from foot dimensions. Journal of Wildlife Management 47:1192-1197.

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Appendix 1. Daily location plots of the collared elephants.

Barry Alex Brazen

Caughley Classic Diney

Gower

Joan Everest

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Lapajuma Mac Mandy

Monarch Proud Soshangane

Wessa

Striburus Tussle

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population dynamics and elephant movements within the...

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