LARGE MAMMAL AERIAL TOTAL COUNT AMBOSELI – WEST ... West... · amboseli – west kilimanjaro and...

LARGE MAMMAL

AMBOSELI – WEST KILIMANJARO AND MAGADI

NATRON CROSS BORDER LANDSCAPE

DRY

KENYA WILDLIFE SERVICE AND TANZANIA WILDLIFE RESEARCH

AFRICAN WILDLIFE FOUNDATION,

NATIONAL PARKS AND WILDLIFE DIVISION

LARGE MAMMAL AERIAL TOTAL COUNT

WEST KILIMANJARO AND MAGADI

CROSS BORDER LANDSCAPE

DRY SEASON, OCTOBER 2013

Conducted by


INSTITUTE

With support from

AFRICAN WILDLIFE FOUNDATION, MARWELL WILDLIFE, TANZANIA

NATIONAL PARKS AND WILDLIFE DIVISION

WILDLIFE DIVISION

AERIAL TOTAL COUNT

WEST KILIMANJARO AND MAGADI-


TANZANIA

2013 Dry season cross borderaerial census report

ii

Recommended Citation Kenana, LM., Bakari, SK., Bitok, E. Machoke, NM., Hamzah,HK, Mukeka, J,., & Mwiu, SN, Kyale, DM,Cheptei, J (2013). Large mammalaerial total count for Amboseli – West Kilimanjaro and Magadi- Natron cross border landscape, October 2013. A technical Report for Kenya Wildlife Service (KWS), Kenya and Tanzania Wildlife Research Institute (TAWIRI), Tanzania

2013 Dry season cross borderaerial census report

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EXECUTIVE SUMMARY

The Amboseli-West Kilimanjaro/Magadi – Natron cross- border landscape comprises various ecologically important areas in Kenya and Tanzania and supports an abundant wildlife population. In order to understand the status of the wildlife populations in this landscape, a dry season total aerial count was conducted from 6th to 12th October 2013. The census covered an area of 25,623 km2 including 9,214 km2 of the Amboseli ecosystem, 6,348 km2 of the Namanga-Magadi areas in south-western Kenya, 3,013 km2 of the West Kilimanjaro and 7,047 km2 of the Natron areas in North Tanzania. The objectives of the census were to: (i) determine wildlife populations and distributions (ii) determine the extent and spread of human activities; and (iii) identify threats to wildlife conservation in the landscape. The count made use of 9- light aircraft fitted with observer calibrated streamers. Data were captured by observers using GPS and digital voice recorders. The census aircraft comprised of four 4-seater and five 2-seater planes, which were flown along transects spaced at 1000 m intervals within 31 predetermined counting blocks. The aircraft were flown at a mean altitude of 383.8 ±251 ft above ground and a mean speed of 156 Kph. Total counts of elephants, elephant carcasses, buffalo, giraffe, wildebeest, eland and several other wildlife species were made, as well as counts of livestock and other human activity A total of 24 wild mammalian and three avian species were recorded in the Amboseli-West Kilimanjaro and the Lake Natron landscape. Common Zebra (Equus burchelli) was the most abundant wildlife species (19,693) followed by Common Wildebeest (Connnochaetes taurinus) (8,862). Other species of interest include the African Elephant (Loxontoda africana) (1,200), Cape buffalo (Syncerus caffer) (184) and Maasai giraffe (Giraffa camelopardalis) (3,626).Compared to the dry season count of 2010, there was a general and varied increase of about 88 ± 99% in numbers of most herbivores with exception being observed among Cape buffalo, Coke’s hartebeest and Common waterbuck which decreased in their numbers by 39.8%, 57.8% and 21.8% respectively. The elephant population showed an increase of 12% between year 2010 and 2013. These population increases can be attributed largely to the recovery of the populations after drought induced mortalities experienced in the area between 2007 and 2009. However given the nature of this data, the components of population recovery attributable to immigration and reproduction are unclear. The survey However, demonstrates that this extended ecosystem provides viable habitat for a broad diversity, and is capable of hosting increasing densities, of wildlife. The resilience of these populations and their ability to recover, as they appear to be doing, is largely attributable to the trans-boundary nature of their distribution and the large-scale ecosystem they inhabit. We recommend that future wildlife studies/surveys should focus on assisting wildlife managers to better understand wildlife movement dynamics in this landscape.

2013 Dry season cross border aerial census report

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LIST OF ACRONYMS AND ABBREVIATIONS

AGL Above Ground Level ASL Above Sea Level ASTER Advanced Space borne Thermal Emission and Reflection ATE Amboseli Trust for Elephants AWKMN Amboseli-Kilimanjaro, Magadi –Natron AWF African Wildlife Foundation CIMU Conservation information and Monitoring Unit DEM Digital Elevation Model DNR Department of Natural Resources FSO Front Seat Observer GCA Game Controlled Area GIS Geographic Information Systems GPS Global Positioning System KINAPA Kilimanjaro National Park KWS Kenya Wildlife Service NP National Park RSO Rear Seat Observer SPSS Statistical Package for Social Sciences SRF Systematic Reconnaissance Flight TANAPA Tanzania National Parks TAWIRI Tanzania Wildlife Research Institute TC Total Count TWCM Tanzania Wildlife Conservation Monitoring UTM Universal Transverse Mercator WD Wildlife Division (Tanzania)


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Table of Contents

EXECUTIVE SUMMARY ...................................................................................................... iii

LIST OF TABLES ..................................................................................................................3

LIST OF FIGURES ................................................................................................................3

LIST OF APPENDICES ........................................................................................................3

INTRODUCTION ....................................................................................................................4

Purpose and Objectives of the Survey ................................................................................5

MATERIALS AND METHODS ..............................................................................................6

Study Area ............................................................................................................................6

Amboseli Area ..................................................................................................................7

Namanga-Magadi Area ...................................................................................................8

West Kilimanjaro Area .....................................................................................................8

Natron Area ......................................................................................................................9

Census Design .................................................................................................................... 10

Census Block Designand flight plan ............................................................................. 10

Data collection ................................................................................................................ 11

Estimation of Height Above Ground Level ................................................................. 13

Data handling andanalyses ........................................................................................... 13

Calculation of Search Effort ........................................................................................... 14

Determination of Population density and carcass ratio .............................................. 14

RESULTS ................................................................................................................................. 15

Survey parameters and Meta data ................................................................................ 15

Wildlife Abundance ........................................................................................................... 16

Species abundance, densities and Distribution ............................................................... 19

Common Zebra ............................................................................................................... 19

Common Wildebeest ...................................................................................................... 20

Grant’s gazelle ................................................................................................................ 21

Maasai Giraffe ................................................................................................................. 22

Thomson’s Gazelle ......................................................................................................... 23

African Elephant ............................................................................................................. 24

Impala .............................................................................................................................. 27

Maasai Ostrich ................................................................................................................ 28

Cape Eland ...................................................................................................................... 29

Fringe-Eared Oryx .......................................................................................................... 30

Cape Buffalo .................................................................................................................... 31

Gerenuk ........................................................................................................................... 32

Lesser kudu ..................................................................................................................... 33

Other wildlife species ..................................................................................................... 34

Human activities ............................................................................................................. 35

DISCUSSION .......................................................................................................................... 37

CONCLUSIONS AND RECOMMENDATIONS ................................................................ 40

ACKNOWLEDGEMENTS .................................................................................................... 41

REFERENCES: ........................................................................................................................ 42


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APPENDICES ......................................................................................................................... 45

LIST OF TABLES

Table 1: Aerial surveys done in Amboseli and West Kilimanjaro areas, 1997 – 2013 ........5

Table 2: Search effort per census region ............................................................................... 16

Table 3: Wildlife species numbers counted during the dry season survey of 2013. ......... 17

Table 4: Human activities recorded in the study area ......................................................... 35

LIST OF FIGURES

Figure 1:Map of the survey area showing the four census areas in Kenya and .................6

Figure 2: Map of the study area showing design of transects. ............................................ 11

Figure 3 Use of streamers showing the two band categories. ..................................................... 12

Figure 4: Survey flight paths showing coverage of the study area .............................................. 15

Figure 5: Population dynamics of selected wildlife speices during dry season counts: (A)

Changes in numbers between 2010 and 2013; (B) percentages changes over six year period

between 2007 and 2013 ............................................................................................................. 18

Figure 6: Distribution of common zebra in the study area in October 2013. ..................... 19

Figure 7: Map of the study area showing distribution of wildebeest, October 2013 ......... 20

Figure 8: Distribution of Grant’s gazelle in the study area in October 2013 ...................... 21

Figure 9: Distribution of Maasai Giraffe in the study area in October 2013 ...................... 22

Figure 10: Distribution of Thomson’s Gazelles in the study area, October 2013 ............... 23

Figure 11: Distribution of Elephants in the study area, October 2013 ................................ 24

Figure 12: Distribution of elephant carcasses, October 2013 ............................................... 26

Figure 13: Distribution of Impalas in study area, October 2013 .......................................... 27

Figure 14: Distribution of Ostrich in the study area in October 2013 ................................. 28

Figure 15: Distribution of Eland in the study area in October 2013 .................................... 29

Figure 16: Distribution of Fringe Eared Oryx in Study area, October 2013 ....................... 30

Figure 17: Distribution of Cape buffalo in the study area, October 2013 ........................... 31

Figure 18: Distribution of Gerenuks in the Study Area in October 2013 ............................ 32

Figure 19: Distribution of Lesser Kudu in the Study Area in October 2013. ...................... 33

Figure 20: Distribution of other wildlife species in the study area in October 2013 ......... 34

Figure 21: A) Shoats, B) Cattle, C) Camel and donkey and(D) Charcoal kilns in the study area in October 2013. .............................................................................................................. 36

LIST OF APPENDICES

Appendix 1: Wildlife densities per areas square kilometer .................................................. 45

Appendix 2: Wildlife population trends and change ..............................................................1

Appendix 3: Average rainfall pattern in over (Calendar year) Amboseli area since 1977. .1


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INTRODUCTION

Kenya Wildlife Service (KWS) and Tanzania Wildlife Research Institute (TAWIRI) conducted a dry season total aerial count of selected wildlife species in the Amboseli-West Kilimanjaro and Magadi –Natron cross-border landscape from 6thto12thOctober2013. The count was a follow up to a wet season count done in April 2013 and similar counts conducted in wet and dry seasons in the year 2010. As in previous counts this count was aimed at increasing the understanding of spatial and temporal variations in distribution and abundance of wildlife populations and selected human activities in the landscape in relation to prevailing climate change.

The Amboseli-Kilimanjaro, Magadi –Natron (AWKMN) as described in this report, is a cross-border landscape of great wildlife conservation importance. It comprises various Protected Areas (PAs) and nonprotected areas (NPAs) of various categories of land ownership and protection status, such as National Parks, Game Controlled Areas (GCAs), Wildlife Management Areas (WMAs), Conservancies and Ranches in Kenya and Tanzania. The area comprises two ecologically linked cross-border ecosystems as described in Kenana et al. (2013).Although this landscape is very significant for wildlife conservation, it has seldom been considered in its entirety as a conservation unit, either in terms of management or for scientific studies. There is paucity of landscape level studies in the area though there abound a number of localized studies (Western 1973; Western & Van Praet 1973; Lindsay 1994; Kikoti 2009) covering various segments of the landscape. Furthermore, most of these studies have been confined within each country’s national administrative boundaries. Similarly wildlife surveys prior to the year 2010 have been disconnected spatially, temporally and from a survey design perspective as well (TWCM 1998; CIMU 2002; KWS 2002; TAWIRI 2003; KWS 2009; TAWIRI 2009) Table 1. These inconsistencies were largely owing to differences in survey objectives and methodologies between Kenya and Tanzania. These fragmented studies and wildlife monitoring efforts have led to an incomplete understanding of wildlife dynamics in the landscape. Consequently, the wider picture of wildlife population dynamics has not been adequately captured. Beginningin2010, KWS and TAWIRI, in partnership with other institutions (KWS & TAWIRI 2010; Kenana et al. 2010; Kenana et al. 2013), initiated a program of integrated aerial censuses. Under this arrangement, regular wet season (March to May) and dry season (September to October) censuses are conducted with a frequency of every three years (KWS & TAWIRI 2010; Kenana et al. 2010; Kenana et al. 2013). To date, two wet season and two dry season censuses have been completed. A common survey methodology for both countries has been adapted to bridge previous differences between the countries. This common methodology integrates aspects of total and sample counts in a hybrid manner allowing data to be collected in such a way that it can be analyzed as a sample as well as a total count.


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Purpose and Objectives of the Survey

The purpose of this survey was to gather comprehensive dry season data on various wildlife species and human activities and compare them with the 2010 and 2013 surveys.

The specific objectives of the survey were to:

1. Determine wildlife population abundance and distribution in the landscape 2. Determine wildlife population trends in the landscape over time 3. Determine the extent and spread of human activities in the landscape 4. Identify threats to wildlife conservation in the landscape 5. Suggest strategies for effective wildlife management across the landscape 6. Develop and implement standardized aerial survey techniques for use in either sample or total counts

Table 1: Aerial surveys done in Amboseli and West Kilimanjaro areas, 1997 – 2013

Year Month Season Survey

Technique Name of area surveyed

*Area (km2)

Source

1997 June Wet SRF West Kilimanjaro

2,537 TWCM (1998)

2000 January Wet TC Amboseli 4,035 KWS (2000)

2001 May Wet SRF West Kilimanjaro

2,537 CIMU (2002)

2002 August Dry TC Amboseli 5,736 KWS (2002)

2002 August Dry TC West Kilimanjaro

6,909 TAWIRI (2003)

2007 May Wet TC Amboseli 5,542 KWS (2007)

2009 March Dry SRF West Kilimanjaro

2,558 TAWIRI (2009)

2010 March Wet TC Amboseli, West Kilimanjaro, Namanga- Magadi, Natron

24,108 KWS & TAWIRI, 2010

2010 October Dry TC Amboseli-West Kilimanjaro and Namanga-Magadi, Natron

24,788 KWS & TAWIRI, 2010

2013 April Wet TC Amboseli, West Kilimanjaro, Namanga- Magadi, Natron

25,623 KWS & TAWIRI, 2013

2013 October Dry TC Amboseli, West Kilimanjaro, Namanga- Magadi, Natron

25,623 This report

*Notice thedifferences in the areas covered and the harmonized area from 2010 when Kenya and Tanzania begun a collaborative effort to count wildlife as a team.


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MATERIALS AND METHODS

Study Area

The AWKMN area covers portions of Southern Kenya and Northern Tanzania between latitudes 10 37’ and 30 13’ South and longitude 350 49’ and 380 00’ East (Figure 1) (Kenana et al. 2013a). This ecosystem comprises Amboseli and Namanga-Magadi areas in Southern Kenya, and West Kilimanjaro and Natron in Northern Tanzania. The survey covered 25,623 km2 and extended from the foot of Chyulu hills to the east, Mt. Kilimanjaro to the south eastern boundary, Arusha National Park to the south, Lake Natron to the west and Lake Magadi to the North Westof the survey area. Similar to the 2010 wet season survey, this survey area was divided into four broad areas: Namanga-Magadi (labeled as Magadi on Maps and Tables), Amboseli, Natron and West Kilimanjaro.

Figure 1: Map of the survey area showing the four census areas in Kenya and

Tanzania.


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Amboseli Area

Amboseli area covers 9,214 km2 and consists of Amboseli National Park and the following surrounding group ranches and conservancies: Kimana/Tikondo conservancy, Elerai Conservancy, Olgulului/Olararashi group ranch, Selengei group ranch, Imbirikani group ranch , Osilalei group ranch, Mailuagroup ranch , Kaputei south group ranch and Kuku group ranch. The area is characterized by basement and saline plains, with fresh water springs flowing from the volcanic slopes of the Mt. Kilimanjaro to form several wetlands on the lowlands. The vegetation is mainly wooded bush lands, open woodlands, open grasslands and riverine vegetation . Quaternary volcanic soils on the northeastern Kilimanjaro slope dominate the southeastern area (Pratt and Gwynne, 1977) encouraging rain-fed agriculture while basement rock soils cover most of the rest of Olgulului, making only pastoralism possible. The Amboseli area has alow agricultural potential because it lies in the arid to semi-arid savanna environment in ecological zone VI of the agro-climatic zone map (Croze et al., 2006).The area is characterized by spatial and temporal variation in hydrology. Surface water is only found in the few permanent springs which flow through the wetlands to form streams which dry up before connecting to the main rivers (Kimana, Elselenkei-Kiboko and Lolterish rivers). These springs and the existing water resources are predominantly gravity fed from Mt. Kilimanjaro and emerge from underground in the lowlands. The springs and rains feed the rivers, streams and wetlands in the area (Engongu Narok and Loonginye in the Amboseli N. P., Namelok, Engum, Ol makau and Isnet at the intersection between Kimana, Olgulului and Mbirikani group ranches and Olngarua Lenker in Kuku).

There is scarcity of water in the area North and West of the Park, particularly in Olgulului/Olorarashi group ranch during the dry season. The group ranch depends mostly on a series of boreholes and dams, and the 65 km Amboseli National Park water pipeline to water livestock and for domestic use.

The dominant vegetation types are open grasslands towards the north and northeast to the Chyulu Hills; Acacia dominated bushland to the south up tothe forest belt of Mt. Kilimanjaro. Throughout these main vegetation types, there are patches of wetlands and Acacia woodlands following a roughly northwest-southeast line along the park's long axis, with wooded and bush grassland found wherever there is seasonal accumulation of water. There has been declinein Acacia xanthophloea and A. tortilis woodlandscover along the wetlands and to the southeast of the National Park (Croze et al., 2011).


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Namanga-Magadi Area

The Namanga-Magadi area (6348 km2) comprises of the following group ranches: Meto, Torosei, Elangata Wuas, Olkiramatian, Lorngosua, Shompole,Olkeri, Mbuko, Oldoinyoke and the southern part of Suswa ranch (Figure1). The topography of most parts of Meto and Torosei group ranches is a combination of gently undulating plains and outstanding hilly landscape of the Great Rift Valley. The soil is “black clayey” (grumosolic soils) and consist of a range of “black cotton” soils including the calcareous and non calcareous variants (Pratt and Gwynne, 1977).

The Uaso Ngiro river is the only permanent water source; however there are several seasonal rivers, for example, the Namanga and Esokota rivers which originate from Namanga and Meto hills. There are other seasonal rivers which hold water for short periods during the rainy season and remain dry for the better part of the year (Kenana et al, 2013). Namanga (Ol donyo Orok) hill is a crucial water catchment supplying water to most of the rivers in the area. There are other important water resources in the area (boreholes and artificial water dams) either publicly or privately owned (Kenana et al, 2013).

The area has distinct habitat types which are as a result of diverse physical features (lake, undulating hills and valleys). The area is dominatedby a number of tree speciesincluding Acaciaspp, Commiphora spp and Balanites spp. The major grasses include Chloris roxburgiana, Pennisetum stramenium, Pennisetum mezianum, Digitaria spp, Cynodon dactylon and Eragrostis spp.

The area receives low, bimodal and highly variable rainfallranging between 400 - 600 mm per year. Because the low rainfall allows only marginal agricultural potential the predominant land use is pastoralism by Maasai people (Kioko, 2008) though a few areas practice irrigation. Rain-fed agriculture is done mostly along Maili Tisa-Namanga road, along the main Uaso Ngiro river. Quarrying of building stones occurs mainly along the Kajiado-Namanga road while sand harvesting occasionally occurs in the dry river beds.

West Kilimanjaro Area

The West Kilimanjaro area (3013 km2) is within the Longido district of Arusha region in the United Republic of Tanzania. The northern extent of the area is the Tanzania-Kenya border from Namanga southeastward to Irkaswa. The eastern border is defined by the boundary of Kilimanjaro National Park extending southward to near the community of Sanya Juu. The southern extent of this study area extends west from Sanya Juu to the northeast corner of Arusha National Park, continuing along the northern park border to the Arusha-Nairobi Road that also defines the western extent of West Kilimanjaro area.

The area is a complex mosaic of diverse natural communities, extensive grazing lands, and large agricultural fields at lower elevations of Mt. Kilimanjaro. There are traditional, agro-pastoral Maasai communities that graze cattle and other livestock and


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also grow subsistence crops. In addition, there are five other medium-sized agricultural communities in the region. Protected areas in the region include Kilimanjaro NP (755 km2) on the eastern boundary and Arusha NP (137 km2) to the south. Additionally, there are two private conservation areas, West Kilimanjaro Ranch (303 km2), Endarakwai Ranch (44 km2); as well as, Longido Game Controlled Area (GCA, 1,700 km2), and Ngasurai Open Area (544 km2) that provide important habitats for wildlife.

Although the area varies in elevation (1,230 to 1,600 m ASL), the predominant ecological zone is semi-arid savannah (Pratt et al. 1966) interspersed with woodlands. There are extensive agricultural fields along the lower western flank of Mt. Kilimanjaro and lowland forests within the boundary of Kilimanjaro National Park (KINAPA) Distribution of rainfall is unpredictable, especially at lower elevations, and highly variable from year to year. Rainfall amounts average 341 mm/yr in semi-arid lower elevations (Moss, 2001) and 890 mm/yr in agricultural areas at lower elevations on Mt. Kilimanjaro and at Mt. Meru and Monduli areas in the southern portion of the survey area.

Natron Area

The Natron area (7,047 km2) is to the west of the West Kilimanjaro area with its northern extent defined by the Tanzania-Kenya border, extending from the border town of Namanga on the east and continuing northwest along the border to the northern terminus of Lake Natron. The western extent is along the east side of Lake Natron continuing south along the eastern border of Ngorongoro Conservation Area. The southern boundary extends from the southeast corner of Ngorongoro Conservation Area eastward to the northwest corner of Arusha National Park. The area is a mosaic of diverse natural communities and extensive grazing lands. There is a unique Maasai grazing area extending westward from the Kiserian-Mriata Ridge (on the eastern side of the study region) extending westward encompassing the grasslands adjacent to Gelai (2,942 m) and Kitumbeine (2,858 m) mountains. This area is characterized by well-drained savannah grasslands and woodlands where Maasai graze their cattle during the dry season and no permanent human settlements are allowed.

Within this study region, traditional Maasai communities graze their livestock and practice subsistence agriculture. The entire region is included within the Natron GCA and the northern portion of the Monduli GCA where wildlife is managed primarily for hunting. The predominant ecological zone is semi-arid savannah interspersed with open acacia woodlands (Acacia sp and Commiphora sp), especially on the western side of the Kiserian-Mriata Ridge. Distribution of rainfall is unpredictable and highly variable from year to year, but rainfall is typically less than 350 mm/yr.


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Census Design

As in previous counts compared here, this survey adopted a combination of principle methods of aerial censuses described byNorton–Griffiths, (1978) and Douglas-Hamilton (1996).Both 2013 counts made modifications to these, namely by adding extra survey parameters to a total count census which enhances the accuracy of data and allow for analyses of data as both a sample and a total count. These additional parameters involved integration and determination of strip widths by use of streamers on aircraft wing struts to standardize transect widths for observers, standardization of the aircraft altitude above ground (AGL) and airspeed. Other modifications came up in an effort to exploit efficiency brought about by availability of modern survey equipment. For example, the availability of Global Positioning Systems (GPS) has made navigation much easier reducing the reliance on physical features as delineators for counting blocks. This allowed for adjustments to be made in the philosophy for designing counting blocks as described in Douglas-Hamilton (1996).

The principle motivation for undertaking these modifications were: 1) to explore ways of estimating and reducing counting errors in total counts as currently practiced, 2) To increase the sampling effort, while reducing the complications in sample selection and 3) to explore ways of smoothly transitioning to sample counts for Kenyan based surveys. This hybrid of total and sample concept of data collection was chosen so that it would allow backward compatibility with the existing total count data while also enhancing comparability with existing and future sample counts (Kenana et al. 2013).

Census Block Design and flight plan

The 2010surveys used existing blocks that were delineated using principles described in Douglas Hamilton (1996). These counting blocks were irregular, defined by physical features on the ground such as road, rivers and ridges. These features were meant to make it easier for pilots to navigate the blocks. In this survey the counting blocks design was changed to conform to the following rules:

• Rivers were not used as boundaries of the blocks. Rivers are normally areas of concentration of animals hence not suitable as boundaries for counting blocks owing to the necessity to turn over this area and begin a new transect and the high possibility animals would move from one side of the river to the other, resulting in double counts.

• Blocks were made rectangular or square in shape. This eased navigation for pilots and FSOs using GPS and allowed more time for observations.

• Blocks were made small enough to be counted within a maximum of six hours a day. 900km2 was deemed to be a suitable average size of a block.

• Block boundaries did not cut across areas of high wildlife density as determined by kernel densities from previous surveys.


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The area was flown on north-south orientation while maintaining a separation between flight lines of one kilometer (Figure 2)

Figure 2: Map of the study area showing design of transects.

Data collection

To improve the quality of data collected on wildlife populations, the crew were trained on use of various counting and estimation techniques, use of equipment (GPS, voice recorders and cameras), species identification and estimation, carcass ageing, data


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handling and processing. Practical training sessions and test flights were included as rehearsal for the actual census. The test flights involved the different flight crews flying the same mock transects at different intervals while maintaining same orientation in order to assess inter observer variability in species detection, estimation and identification. Use of streamers on wing struts to define transect widths, a concept borrowed from Systematic Reconnaissance flight sample count method Norton–Griffiths (1978) was employed to aid in judgement of distance as well as calculation of observable strip widths. The streamers were calibrated for a flight height of 91.2m (300 ft) AGL. The outer streamer was set to limit the extent of observation to the maximum transect width (500m for 1 Km interval) and the inner streamer set at half that width. This provided a way of subdividing transects into two band strips (inner and outer) Figure 3. Observations were then apportioned to either of the bands (inner or outer) as they were sighted. This categorization provided for a way of analysing the data as total count or an experimental sample count. It also allows for the potential correction of the total count data by comparing densities of observations within the two bands. In determination of total counts, all observations irrespective of which band they were in, were included. In the sample count analysis however, only observations that were in the outer band were used.

Figure 3 Use of streamers showing the two band categories.


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Estimation of Height Above Ground Level

Due to lack of radar altimeters in most of the aircraft, handheld GPS units in combination with a Digital Elevation Model (DEM)(www.gdem.ersdac.jspacesystems.or.jp)were used to determine the height Above Ground Level (AGL). Prior to and after each flight the GPS were calibrated for elevation from a reference point with known elevation. A 30m ASTER Digital Elevation Model (DEM) for the entire survey area was downloaded from www.gdem.ersdac.jspacesystems.or.jp. Heights above ground were then calculated.

To obtain the height AGL for each observation, the following formula was used;

AGLp = Gp - Dp – (Dr – Gr)

Where: AGLp = Height Above Ground Level at a particular observation point Gp = GPS elevation value at a particular observation point Dp = DEM value at a particular observation point

Dr=DEM value at the reference location Gr=GPS elevation value at the reference location

Data handling andanalyses

On landing, the ground crew downloaded data recorded in GPS units and digital voice recorders. Voice records were processed digitally to remove background noises and improve the clarity. A team of data handlers transcribed the voice records onto datasheets and entered these into a digital database. At the end of each counting session, the GPS flight paths (as tracks) and waypoints were down loaded using DNR-Garmin software. Data were validated to identify and correct any errors made during collection and processing of data. This entailed cross checking each record for match between data captured during flights against the record in the database as well as eliminating double counts by consulting with FSO’s on flights in adjacent blocks.

Analyses presented in this report are for total count data. In the determination of trends in seasonal and temporal variation in wildlife abundance simple percentages were used. In comparison of wildlife census between the years, care was taken to compare data that had the same spatial extent. Jenks natural Breaks method was used to map the distribution of wildlife group sizes.


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Calculation of Search Effort

Search effort in this report refers to the area (km2) covered by the aerial crew in one hour (km2/hour) (Douglas-Hamilton et al. 1994).

Determination of Population density and carcass ratio

The population density of each wildlife species was computed as the number of individuals divided by area in square kilometer. In this report carcass ratio refers to the proportion of the carcasses in relation to the live elephants. This differs with carcass ratio as reported in Douglas-Hamilton & Hillman (1981), where the proportion of dead elephants to the summation of the live and the dead defined this ratio. For our purposes, Douglas Hamilton and Hillman’s ratio was defined as the mortality index.


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RESULTS

Survey parameters and Meta data

The census used a total of nine aircraft, 2 Cessna 182, 2 Cessna 185, 2 Piper Super Cubs and 3 Aviat Huskies. A total of 24,297.8 km of linear transects, each - 1 Km wide was flown during the survey excluding transit flights. The average height above ground for all aircraft on transect was 117.1 ± 76.7 M (383.8 ±251 ft) and the overall average ground speed of all aircraft was 156 Km/h (84.23 Kt). Transects in 25 of 31 census blocks were flown in a North South orientation as per the design while transects in the remaining blocks were partially or wholly either flown in an East-West orientation or irregularly due to terrain and or prevailing weather conditions (Figure 4). The overall average search effort for the entire area was 165.9km2/hour. Natron registered the lowest search effort (214.2km2/hour), while Magadi region registered the highest search effort (138.06km2/hour)(Table 2). There were a total of 13,488 records of observations in the census.

Figure 4: Survey flight paths showing coverage of the study area


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Table 2:Search effort per census region

Census Region Time (Hrs.) Size (Km2) Search effort (Km

2 /h)

Amboseli 59.62 9,214 154.5

Magadi 45.98 6348 138.1

Natron 32.9 7,047 214.2

West Kilimanjaro 16.38 3013 183.9

Total 154.88 165.4

Wildlife Abundance

A total of 24wild mammalian and three avian species were counted in the AWKMN survey (Table 3). Common Zebra (Equus burchelli) was the most abundant wildlife species (19,693) followed by Common Wildebeest (Connnochaetes taurinus) (8,862). Other species of interest include theAfrican Elephant (Loxontoda africana) (1,200), Cape buffalo (Syncerus caffer) (184) andMaasai giraffe (Giraffa camelopardalis) (3,626).Other abundant species included, Grant’s Gazelle (Gazella granti), Thomson’s Gazelle (Gazella thomsonii), Impala (Aepyceros melampus), Maasai ostrich (Struthio camelus),and Cape Eland (Taurotragus oryx).Other recorded species inncludedCheetah (Acinonyxjubatus ), Reedbuck (Redunca arundinum), Bushbuck (Tragelaphus scriptus) Spotted Hyena (Crocuta crocuta) and the Black Backed Jackal (Canis mesomelas).

In terms of population changes over time during the dry seasons, there was a general and varied increase of about 88 ± 99% in numbers of most herbivores between the year 2010 and 2013 (Figure 5A ). The exception to this trend was however observed among Cape buffalo, Coke’s hartebeest and Common waterbuck which decreased in their numbers by 39.8%, 57.8% and 21.8% respectively. All species however recorded positive change in numbers in the last six years (Figure 5B).


17

Table 3: Wildlife species numbers counted during the dry season survey of 2013.

SPECIES AMBOSELI

(9214.44 KM2)

WEST KILIMANJARO (3013.18 KM2)

MAGADI (6348.32 KM2)

NATRON (7047.26 KM2)

Grand Total

COMMON ZEBRA 10647 1632 3563 3851 19,693

COMMON WILDEBEEST 5726 189 1662 1285 8,862

GRANT'S GAZELLE 3161 544 2049 1297 7,051

MASAAI GIRAFFE 1444 348 815 1019 3,626

THOMSON'S GAZELLE 938 109 289 156 1,492

AFRICAN ELEPHANT 995 25 159 21 1,200

ELEPHANT CARCASS -

OLD 27 21 1 9 58

ELEPHANT CARCASS -

VERY OLD 13 1 1 3 18

IMPALA 404 109 343 257 1,113

MASAAI OSTRICH 488 74 231 297 1,090

CAPE ELAND 309 156 139 27 631

BABOON 13 40 164 55 272

FRINGE EARED ORYX 139 71 13 19 242

GERENUK 90 29 48 67 234

CAPE BUFFALO 184 184

LESSER KUDU 35 21 37 14 107

WARTHOG 62 19 16 10 107

HIPPOPOTAMUS 70 70

COKE’S HARTBEAST 27 3 30

DIKDIK 8 4 5 3 20

COMMON WATER BUCK 1 16 1 18

LION 5 5

SPOTTED HYENA 3 1 4

SILVER BACKED JACKAL 3 3

BUSHBUCK 1 1 2

KORI BUSTARD 1 1 2

CHEETAH 1 1

REED BUCK 1 1

SECRETARY BIRD 1 1

TOTAL 46,137

2013 Dry season cross border aerial

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19

Species abundance, densities and Distribution

Common Zebra

A total of19, 693 zebras were recorded (Table 3),and were distributed widely across the survey area. The highest concentrations were in Amboseli National Park and along the river Ewaso Nyiro in Magadi area. Lake Natron game control area and west Kilimanjaro had sparse distribution (Figure 6). The overall density was 0.0769/km2 with Amboseli having the highest density (1.155/km2)among the four survey regions followed by Magadi (0.561/km2), Natron (0.546/km2), and West Kilimanjaro (0.542/km2) respectively(appendix 1).The population increased by over 70% over the dry season count of 2010 resulting in an annual increase of 24%. (Appendix 2)

Figure 6: Distribution of common zebra in the study area in October 2013.


20

Common Wildebeest

A total of 8,862common wildebeest were counted making it the second most abundant species. The wildebeest distribution showed three clusters: Amboseli National Park, south of Lake Natron, and Shompole in Magadi area. They were noticeably absent in West Kilimanjaro with few individuals recorded on Amboseli group ranches (Figure 7). The overall density was 0.346/km2 with Amboseli recording the highest density (0.621/km2). This shows a discernible seasonal change in distribution in comparison tothe 2013 wet season when most of the wildebeest density was found in the Natron area. Magadi had the second highest density of 0.262/km2 followed by Lake Natron which had 0.182/km2 as compared to 1.06/km2 of wet season 2013. Finally West Kilimanjaro had the lowest density of 0.063/km2 (Table 3 and Appendix 1).The population has shown an increase of 14% as compared to the last dry season count in 2010 with an annual growth rate of 5%. This population shows a seasonal variation in abundance of about 40% compared to the wet season count in 2013 (Appendix 2).

Figure 7: Map of the study area showing distribution of wildebeest, October 2013


21

Grant’s gazelle

A total of 7,051Grant’s gazelles were counted making them the third most abundant species. They were widely distributed in the entire landscape and apparently occupying areas where wildebeest were at lower densities (Elangata Wuas, Suswa, Lorngosua, Natron and West Kilimanjaro (Figure 8).The overall density stood at 0.275/km2 with highest densities in the Amboseli and Magadi w of 0.343/km2 and 0.323/km2 respectively. Lowest densities were recorded in Natron and West Kilimanjaro with 0.184/km20.181/km2respectively(Appendix 1),thepopulation has increased 78% over the 2010 dry season count resulting in an annual increase of 26% (Appendix 2).

Figure 8: Distribution of Grant’s gazelle in the study area in October 2013


22

Maasai Giraffe

A total of 3,626 giraffes were recorded (Table 3). They were widely distributed in the entire ecosystem. They occurred in all the surveyed regions, however, few individuals were recorded in Elangata Wuas, Lolngosua, Meto, Osilalei and Mailua ranches. (Figure 8).The overall density was 0.142/km2in which the Amboseli region had the highest concentration of 0.157/km2 followed by Natron (0.145/km2). Magadi and West Kilimanjaro had densities of 0.128/km2 and 0.115/km2 respectively (Appendix 1).The population increased by 92% over the 2010 dry season with a notable seasonal fluctuation of about 52% in comparison to the wet season (Appendix 2).

Figure 9: Distribution of Maasai Giraffe in the study area in October 2013


23

Thomson’s Gazelle

Thomson’s gazelles were sparsely distributed in the study area, with 63% of all the recorded observations made from Amboseli region. Kimana sanctuary area, north of Ogulului and Kaptei south had high concentration (Figure 10).A total of 1492 individuals were counted in the entire survey area with an overall density of 0.058/km2. Amboseli region had the highest concentration of 0.102/km2 followed by Magadi which had 0.046/km2. West Kilimanjaro and Natron had 0.036/km2 and 0.022/km2 respectively (Appendix 1). Compared with the dry season count of 2010, the population showed a notable increase of over 100% .The Annual growth rate between 2010 and 2013 is 55% (Appendix 2).

Figure 10: Distribution of Thomson’s Gazelles in the study area, October 2013


24

African Elephant

A total of 1200 elephants were recorded during the survey with an overall density of 0.047/km2 (Table 3, Appendix 1). The number of elephants in the Amboseli region compared to the similar dry and wet season of 2010 remained almost the same at 995 and 1010 respectively (Appendix 2). Amboseli once again had the highest density of 0.108/km2. There was an increase of elephants in the Magadi and Natron areas; 7 to 159 and 5 to 21 respectively (0.025/km2 and 0.003/km2, Appendix 1). West Kilimanjaro had a density of 0.008/km2.The population has shown an increase of 13% since the 2010 dry season count, with an annual increase of 4% (Appendix 2). [Elephants were largely distributed in the Amboseli area (table 3) with a small concentration in the Suswa area of Magadi. Very few individuals were recorded in Natron and West Kilimanjaro (Table 3). Small groups were recorded in Mbirikani, Olgulului, Eselenkei and Osilalei in Amboseli region, Enduimet in West Kilimanjaro,Shompole and Erangata wuas (Figure 11).

Figure 11: Distribution of Elephants in the study area, October 2013


25

Elephant carcasses A total of 76 elephant carcasses were recorded, 18 of which were classified as very old (up to ten years old) and 58 carcasses classified as old (more than one year old). No recent or fresh carcasses were recorded (Table 4). As compared to 2010 there was an increase in the number of very old carcasses by about 50% while there was no major change in the number of old carcasses (Appendix 2) . Majority of the carcasses (53%) were found in the Amboseli region. West Kilimanjaro had 29% of all the carcasses recorded. Natron and Magadi had 12 and 2 carcasses respectively (Table 3, Figure 12). Proportionally the carcass ratio was highest in West Kilimanjaro (0.84) followed by Natron area (0.426), then by Amboseli area (0.027) and finally by Magadi area (0.007).

Table 4: Elephant carcass ratio and mortality index

Parameter AMBOSELI (9214.44 KM2)

WEST KILIMANJARO (3013.18 KM2)


NATRON (7047.26 KM2)

Total

Old elephant carcass

Carcass ratio 0.027 0.840 0.007 0.426 0.048

Mortality Index 0.026 0.457 0.006 0.300 0.046

% Carcass ratio 2.71 84 0.63 42.86 4.83

% Mortality index 2.64 45.65 0.63 30.00 4.61

Very old elephant carcass

Carcass ratio 0.013 0.040 0.006 0.143 0.015

Mortality Index 0.013 0.038 0.006 0.125 0.015

% Carcass ratio 1.31 4.00 0.63 14.29 1.50

% Mortality index 1.23 3.85 0.63 12.50 1.48

All carcases

Carcass ratio 0.040 0.880 0.013 0.571 0.063

Mortality Index 0.039 0.468 0.012 0.364 0.060

% Carcass ratio 4.02 88.00 1.26 57.14 6.33

% Mortality index 3.86 46.81 1.24 36.36 5.96


26

Figure 12: Distribution of elephant carcasses, October 2013


27

Impala

The population of Impala in the study area was 1,113 individuals (Table 3). The overall density was 0.043/km2. Magadi had the highest concentration of 0.054/km2followed by Amboseli with 0.044/km2. Natron and West Kilimanjaro areas had similar densities of 0.036/km2 (Appendix 1). Impala showed a notable increase of over 100% compared to the year 2010 with an annual increase of over 60% (Appendix 2). The species was sparsely distributed across the landscape with isolated groups occurring in all the four regions, however there appeared to be a pattern of increased occurrence of impala along the eastern rift escarpment from Magadi and Amboseli areas extending southwards into Natron. They were also found in the rift valley basin, lowland areas of West Kilimanjaro (Figure 13).

Figure 13: Distribution of Impalas in study area, October 2013


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Maasai Ostrich

A total 1,090 ostriches were counted in the entire landscape giving a density of 0.043/km2. The Amboseli region had the highest density of 0.053/km2 followed by Natron and Magadi region with 0.042/km2 and 0.036/km2 respectively (Figure 14). West Kilimanjaro had the lowest density of 0. 025/km2 (Appendix 1). As compared to similar dry period in 2010, there was a slight decline of 5 (Appendix 2).

Figure 14: Distribution of Ostrich in the study area in October 2013


29

Cape Eland

The population size of eland recorded in the study area was 631 individuals. The overall density was 0.025/km2. The highest density (0.052/km2) was found in West Kilimanjaro. Amboseli had the second highest concentration of 0.034/km2 while Magadi and Natron had densities of 0.022/km2 and 0.004/km2 respectively (Appendix 1). Since 2010, the population has increased by over 100% and the population annual growth rate of 52%. However there was a drastic decline of 87% when compared to the recent wet season count of 2013(Appendix 2).They were widely distributed in the survey area occurring in isolated groups with the exception of areas near Meto and Lorngosua where there were no Eland was recorded (Figure 15).

Figure 15: Distribution of Eland in the study area in October 2013


30

Fringe-Eared Oryx

A total of 242 Fringe-eared Oryx were recorded giving an overall density of 0.009/km2. West Kilimanjaro recorded the highest density of 0.024/km2 followed by Amboseli with 0.015/km2. Natron and Magadi had densities of 0.003/km2 and 0.002 respectively (Appendix 1). As compared to 2010 dry season survey the species showed an increase of over 200% giving an annual increase of 70% (Appendix 2). Distribution shows isolated pockets at the northern slopes of Chyulu hills in Amboseli region and Enduimet area in West Kilimanjaro region (Figure16).

Figure 16: Distribution of Fringe Eared Oryx in Study area, October 2013


31

Cape Buffalo

A total of 184 buffaloes were recorded in the landscape giving an overall density of 0.007/km2. Buffalo were found only in the Amboseli region at a density of 0.020/km2 (Figure 17, Appendix 1). As compared to 2010, there was a decline of 40%. The buffalo population in Amboseli has been declining since 2002 (KWS 2007).

Figure 17: Distribution of Cape buffalo in the study area, October 2013


32

Gerenuk

During the survey, 234 gerenuks were recorded and were sparsely and widely distributed in the landscape (Table 3, Figure 18). The overall density was 0.009/km2. Amboseli, Natron and West Kilimanjaro had similar densities of 0.010/km2 while Magadi had the least density of 0.08/km2 (Appendix 1).Compared to a similar dry season in 2010; the population has increased by over 100% with an annual increase of 36% (Appendix 2).

Figure 18: Distribution of Gerenuks in the Study Area in October 2013


33

Lesser kudu

A total number of 107 lesser kudu were recorded. They were sparsely and widely distributed in the entire landscape. They occurred in Elangata wuas, Lorngosua, Mailua ranches and west of Enduimet Wildlife Management Area (Figure 19). Magadi and Amboseli regions had the highest numbers recorded; 37 and 35 respectively. West Kilimanjaro and Magadi had the highest densities of 0.007/km2 and 0.006/km2 respectively. The overall density was 0.004/km2.

Figure 19: Distribution of Lesser Kudu in the Study Area in October 2013.


34

Other wildlife species

Other mammalian wild species recorded during the census with their abundances in brackets included the coke’s hartebeest (30), common waterbuck (18), hippopotamus (70), lesser kudu (107) and warthog (107). Most of these species were recorded in higher numbers during previous counts. The coke’s hartebeest and the waterbuck showed a general decline of 58% and 21% respectively compared to the 2010 dry season survey. The lesser Kudu, hippopotamus and the warthog increased by over 200%, 63% and over 150% respectively. The following wildlife species were also recorded: baboon (272), bushbuck (2), Dikdik (20), hyena (4), duiker (9), cheetah (1), and lions (5), silver-backed jackal (3), and bohor reedbuck (1). The distributions are summarized in Figure 20. The results from this survey are likely to be an under count for these species as some of them have poor detestability from the air while others are nocturnal (e.g. Lion) and some live in a confined environment (e.g. hippopotamus). Species under this category require other appropriate census techniques.

Figure 20: Distribution of other wildlife species in the study area in October 2013


35

Human activities

During the survey, a number of human activities were recorded, mainly the presence of livestock, including cattle, donkeys, camels, shoats (sheep and goats) and other environmental destructive activities such as charcoal production and tree cutting. The most abundant livestock was shoats 448,900) with the highest number being recorded in the Magadi region/area (151,603) followed by Amboseli (127,708) and the fewest were in Natron (106,885) and West Kilimanjaro (62, 704) (Table4 ). Shoats were widely distributed in the landscape (Table 4 and Figure 21) and their densities ranged from 14/km2 to 24/km2 in all the four regions.

Cattle were the second largest livestock category with a total count of 193,049 with the highest numbers in Amboseli (75,295) followed by Magadi (48,644), Natron (41,686) and West Kilimanjaro (27,424) (Table 4 and Figure 21).

Donkey keeping ranked third of the most abundant human activities recorded in the area (4,528). The area with highest donkey concentration was Magadi (1628) followed by Natron (1440), Amboseli (970) and West Kilimanjaro (440) (Table 4, Figure 21). On the other hand a total of 1232 camels were recorded in the area during the survey. The highest abundance of camels was in Magadi (1,041) followed by Amboseli (133) and Natron (58) (Table 4, Figure 21).

Another notable form human activity recorded in this survey area was charcoal burning with a total of 3,214 charcoal kilns and bags. Magadi had the highest concentration of 2,030 followed by Amboseli with 1,181. West Kilimanjaro and Natron had two and one charcoal burning incidences respectively (Table 4). There was high destruction of trees that might be associated with charcoal production in Mailua, Kaptei south, Osilalei, Meta and Lorngosua group ranches (Figure 21). Generally, all the human activities were widely distributed in the surveyed area.

Table 5: Human activities recorded in the study area

SPECIES

AMBOSELI (9214.44 KM2)


NATRON (7047 KM2.26)

WEST KILIMANJARO (3013.18 ) KM2 )

Grand Total

Camel 133 1041 58 0 1232

Cattle 75295 48644 41686 27424 193049

Charcoal 1181 2030 1 2 3214

Donkey 970 1628 1440 490 4528

Shoats 127708 151603 106885 62704 448900 Grand total 205287 204946 150070 90620 650923

2013 Dry season cross border aerial

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Figure 21: A) Shoats, B) Cattle, C) Camel

2013.

border aerial census report

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Camel and donkey and (D) Charcoal kilns in the study area in October

36

the study area in October


37

DISCUSSION The results of this study demonstrate that there has been an increase in wildlife and livestock numbers since the devastating drought of 2007-2009. Compared to 2010 census results (Kenana et al., 2010), the 2013 census showed a general rise in population numbers but with similar spatial distributions across the landscape. Overall, the abundance of all species in the ecosystem increased by over 56% with exceptions being seen in the Cape Buffalo, Maasai Ostrich, Kongoni (Coke’s hartebeest) and the Common Waterbuck. Most ungulates for example Zebra, Wildebeest, Grant’s gazelle and Thomson’s gazelle,whose populations were greatly affected by the 2009 – 2011 droughts, showed growth in numbers between the dry season count of 2010 and the current study (Appendix 2). This increase may be attributed to favorable climatic conditions that the region experienced for a while after a severe draught in the year 2009. As in previous studies (Kenana et al., 2013), this survey demonstrates that wildlife species are widely distributed in the landscape. The highest concentrations of all observations were recorded in the Amboseli region probably as a result of the availability of water in the wetlands found in the park (Obare, 2007, Ndambuki & Kioko 2009). During the wet season, wildlife is widely distributed outside the park (Kenana et al., 2013) as a result of the availability of alternative sources of water. This underscores the importance of the areas outside the park as wildlife dispersal ranges that should be protected from dangers of fragmentation or subdivision. Efforts therefore need to be made to secure areas that have not been converted to alternative uses such as agriculture. The Amboseli Elephant population has been extensively studied for over forty years (Western 1973; Western & Lindsay, 1984; Moss, 2001; Kioko et al., 2006). Trends from continuous monitoring show an increasing population since 1990s. Recent surveys show that the elephant population is relatively stable (1,087 in 2000, 1,090 in 2002 and 967 in 2007, 1420 in 2010 and 1930 in Wet season 2013), compared to the present population numbers of 1200 counted in the survey area during this dry season count. However, the results of this count compare well with similar count in 2010 when 1065 elephants were counted in the ecosystem. This shows a minor increase of 135 individuals. Elephants in Amboseli make seasonal movements in and out of the park (Western & Lindsay, 1984; Moss, 2001). Although there may be no direct evidence linking the Magadi- Nguruman population with the Amboseli population, recent studies of collared elephants indicate that the Amboseli elephants wander to most of the West Kilimanjaro area and further into Lake Natron area which is also utilized by elephants from Magadi-Nguruman area (Kikoti, 2009). These studies suggest that there are more interactive elephant movements within the greater Amboseli-West Kilimanjaro ecosystem and that elephant numbers in one area need to be evaluated in the context of numbers within other areas. It is also possible that the slight fluctuations


38

in elephant numbers recorded in previous counts could be accounted for by elephant movements since most of the previous counts focused on relatively smaller areas of the ecosystem. Despite threats facing elephants in the region, the elephant population showed an increase of 12% between 2010 and 2013. This translates to an annual increase of about 4% annually which is common for a normal elephant population (Appendix 2). The increase is attributed mainly to enhanced security by the relevant country’s wildlife protection agencies and other stakeholders. The seasonal variation between the wet and dry season elephant numbers of 2013 showed oscillation of 38%. This is explained by the fact that the elephants disperse during the wet season and congregate during the dry season around sources of permanent water. Some of the variation may also be attributed to low probability of detection during the dry season when there is reduced visual contrast between animals and ground features. More over in dry season there is tendency of herds clustering a lot which makes counting difficult and may result in under counts. The number of carcasses counted (76) during this count is similar to the one of the dry season count of 2010 (75). The overall carcass ratio for this season was 0.048 (4.83%) while that of 2010 was 0.059 (5.91%). There is a huge variation in carcass ratios observed between contiguous areas of Amboseli (0.027) and West Kilimanjaro (0.84) and similarly between Magadi (0.0063) and Natron (0.42). This variation is likely to be due to each of these contiguous areas sharing the same elephant population which freely move between them. The elephants at Amboseli are likely to be the same ones that move to West Kilimanjaro and similarly those at Magadi are likely to be the same ones that range in Natron as well. As compared to the wet season counts of 2010 and 2013 (Kenana et al., 2013), the carcass ratios in the dry seasons are higher than those in the wet seasons. This difference in ratio between the dry and wet season supports the recommendation by Hamilton & Burril (1991) that carcass numbers be evaluated preferably during dry seasons when carcasses are less likely to be hidden in vegetation. Amboseli region had the highest numbers of carcasses; however, all were either old or very old and could have been missed in the wet season because of poor visibility. There was however no recent or fresh carcasses detected in the ecosystem. This is in contrast to areas outside the ecosystem where elephants face severe threats from poaching, such as the Selous in Tanzania where a carcass ratio of 0.3 (30%) was recorded in 2013 (TAWIRI 2013). Again this underscores the importance of the landscape as a strategic cross border wildlife conservation unit that provides wildlife with the required resources throughout the year. It is therefore prudent that the area should be secured from any form of threat that will endanger its ability to sustain wildlife especially migratory species in the future Higher and lower numbers of large mammals are as a result of high and low search efforts respectively (Douglas-Hamilton et al. 1994). Comparison of search efforts and numbers of large mammals counted within these regions for previous counts was not


39

possible as previous reports did not record this important component. It is hoped that future counts will adopt this parameter. This large scale landscape is an important asset for local communities, who are mainly pastoralists, and whose main source economic livelihood depends largely on their livestock. Since 2007, livestock numbers have continued to increase due to favorable climatic conditions. Cattle numbers have risen by almost 80% since 2010 when a similar count was carried out (Appendix 2). This increase in livestock numbers is however a potential threat to wildlife conservation owing to direct competitions for limited grazing and water resources. Such competition may result in human wildlife conflicts. Increasing numbers may also lead to overstocking, and subsequent habitat degradation, which will minimize available resources for both livestock and wildlife. Another human activity representing a threat to wildlife conservation as well as livestock keeping is the environmental degradation caused commercialized charcoal production in Amboseli and Magadi regions of the landscape. If this activity is not controlled there is a potential that sooner or later wildlife dispersal areas will be lost. Increasing human population and demand for charcoal as a fuel may mean that most land cleared of woody vegetation for its production will become subdivided and converted into farmlands. This is particularly true in areas that receive reliable annual rainfall. This is a direct threat to wildlife dispersal areas and migratory routes which is a key focus for development in the Vision 2030 strategy. Interestingly camel population appears to be expanding in the landscape, from 200 in 2010 to the current figure of 1232, representing a 6 fold increase. Most of these camels are found in the Magadi block of Kajiado County. This phenomenon appears to be a diversification of the local communities’ economic base as result of influence from migrant Somali pastoralists. The population of baboons and other small mammals like Dikdik and Duikers are seriously under estimated owing to poor detection of small species from the air. However, this problem is common to all aerial surveys so the results are comparable to previous censuses. The 272 baboons recorded in this survey may be a small proportion of the baboon population that is part of a larger extended population of baboons in southern Kenya and northern Tanzania, which roam widely within the survey area (Loisel et al., 2006). The aerial survey also seriously underestimate the lion and hyena populations owing to their cryptic and nocturnal nature of their behavior and although numbers observed can be compared to previous efforts, they are so few that reliable trends for these species cannot be determined.(Kenana et al. 2013).


40

CONCLUSIONS AND RECOMMENDATIONS Once again the current survey demonstrates the importance of the Amboseli- West Kilimanjaro and Magadi –Natron cross-border landscape as a wildlife conservation and dispersal area. Migratory species such as elephants, wildebeest, zebra and eland move within and across the various constituent areas of the landscape. Data thus need to be evaluated in the context of the broader landscape. Recommendation 1. Conduct comparable aerial surveys to monitor wildlife populations in the region, with a dry and wet season count each in every third year.

2. Enhance efforts to minimize environmental degradation through charcoal burning by enforcing relevant laws and provision of alternative sources of fuel.

3. Increase efforts to encourage local community to keep livestock numbers that can be supported by the available habitats so as to ensureadherence to appropriate stocking levels.

4. Continue collaboration and information exchange among cross border conservation stakeholders.

5. Collaborate and improve law enforcement to prevent wildlife crimes including poaching and habitat destruction.

6. Coordinate ecosystem-wide research and data sharing among the stakeholders. 7. Coordinate wildlife management policies between Kenya and Tanzania.

8. Initiate land acquisition by regional governments outside the National Parks s to secure wildlife dispersal areas.


41

ACKNOWLEDGEMENTS

We would like to acknowledge all the contributions of the census teams from both Kenya and Tanzania and the various organizations for their financial, material and moral support. Funding, personnel and logistical support were provided by AWF, KWS, TAWIRI, WD and TANAPA and School of Field Studies in Kenya and Tanzania.

We are very grateful to the Director KWS, Director General of TAWIRI, Director ATE, Director of Wildlife Division (Tanzania), Director General of TANAPA, Senior Director-SFS, Kenya and Director SFS-Tanzania. We appreciate the support from Mwalunganje Elephant Trust, David Sheldrick Trust and Tsavo Elephant Trust for provision of aircraft and experienced pilots and observers. To the Pilots, survey observers, Ground crew and support personnel without whom the survey would not have been smooth, we applaud their effort and dedication. Finally, to all those who participated in anyway and have not been mentioned, we thank you for your contribution in making this exercise a success. Finally we would like to acknowledge and thank Dr. Zeke Davidson and Bill Eldrige for reviewing this report.


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45

APPENDICES

Appendix 1: Wildlife densities per areas square kilometer

Species Overall

25,623

Km2

Amboseli

9214.44

Km2

Magadi

6348.32

Km2

Natron

7047.26

Km2

West

Kilimanjaro

3013.18

Km2

COMMON ZEBRA 0.769 1.155 0.561 0.546 0.542

COMMON WILDEBEEST 0.346 0.621 0.262 0.182 0.063

GRANT'S GAZELLE 0.275 0.343 0.323 0.184 0.181

MASAAI GIRAFFE 0.142 0.157 0.128 0.145 0.115

THOMSON'S GAZELLE 0.058 0.102 0.046 0.022 0.036

AFRICAN ELEPHANT 0.047 0.108 0.025 0.003 0.008

IMPALA 0.043 0.044 0.054 0.036 0.036

MASAAI OSTRICH 0.043 0.053 0.036 0.042 0.025

CAPE ELAND 0.025 0.034 0.022 0.004 0.052

BABOON 0.011 0.001 0.026 0.008 0.013

FRINGE EARED ORXY 0.009 0.015 0.002 0.003 0.024

GERENUK 0.009 0.010 0.008 0.010 0.010

CAPE BUFFALO 0.007 0.020 0.000 0.000 0.000

LESSER KUDU 0.004 0.004 0.006 0.002 0.007

WARTHOG 0.004 0.007 0.003 0.001 0.006

HIPPOPOTAMUS 0.003 0.008 0.000 0.000 0.000

COKE"S HARTBEAST 0.001 0.003 0.000 0.000 0.000

DIKDIK 0.001 0.001 0.001 0.000 0.001

COMMON WATER BUCK 0.001 0.000 0.003 0.000 0.000


1

Appendix 2: Wildlife population trends and change

SPECIES

2010 DRY

Season

2013 DRY

Season

Dry

Season %

Change

2010-2013

Annual

growth

rate Dry

Season

2010 WET

SEASON

2013 WET

SEASON

Wet season

% Change

2010-2013

Annual

growth

rate Wet

seasons

population %

variation

2013 wet

season-2013

dry season

counts

AFRICAN ELEPHANT 1065 1200 12.68 4.23 1420 1,930 35.92 11.97 -37.82

CAPE BUFFALO 306 184 -39.87 -13.29 334 575 72.16 24.05 -68.00

CAPE ELAND 247 631 155.47 51.82 1992 5,035 152.76 50.92 -87.47

COKE"S HARTBEAST 71 30 -57.75 -19.25 441 550 24.72 8.24 -94.55

COMMON WATER BUCK 23 18 -21.74 -7.25 36 30 -16.67 -5.56 -40.00

COMMON WILDEBEEST 7780 8862 13.91 4.64 7240 14,728 103.43 34.48 -39.83

COMMON ZEBRA 11551 19693 70.49 23.50 13740 29,867 117.37 39.12 -34.06

FRINGE EARED ORXY 78 242 210.26 70.09 196 533 171.94 57.31 -54.60

GERENUK 112 234 108.93 36.31 117 262 123.93 41.31 -10.69

GRANT'S GAZELLE 3966 7051 77.79 25.93 8362 17,509 109.39 36.46 -59.73

HIPPOPOTAMUS 43 70 62.79 20.93 49 18 -63.27 -21.09 288.89

IMPALA 388 1113 186.86 62.29 1317 3,644 176.69 58.90 -69.46

LESSER KUDU 27 107 296.30 98.77 20 211 955.00 318.33 -49.29

MASAAI GIRAFFE 1884 3626 92.46 30.82 4164 7,627 83.17 27.72 -52.46

MASAAI OSTRICH 1142 1090 -4.55 -1.52 1461 2,010 37.58 12.53 -45.77

THOMSON'S GAZELLE 562 1492 165.48 55.16 933 2,699 189.28 63.09 -44.72

WARTHOG 39 107 174.36 58.12 46 131 184.78 61.59 -18.32

Total 29,284 45,750 41,868 87,359

Average 88.46 29.49 144.60 48.20 -30.46

ELEPHANT CARCASS -

RECENT 6 0 -100.00 -33.33

ELEPHANT CARCASS - VERY

OLD 12 18 50.00 16.67

ELEPHANT CARCASS -OLD 57 58 1.75 0.58

Population comparison between dry seasons and wet seasons 2010-2013


1

Appendix 3: Average rainfall pattern in over (Calendar year) Amboseli area since1977.

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