LARGE MAMMAL AERIAL TOTAL COUNT AMBOSELI WEST KILIMANJARO AND MAGADI- NATRON CROSS BORDER LANDSCAPE

Transcription

1 LARGE MAMMAL AERIAL TOTAL COUNT AMBOSELI WEST KILIMANJARO AND MAGADI- NATRON CROSS BORDER LANDSCAPE DRY SEASON, OCTOBER 2013 Conducted by KENYA WILDLIFE SERVICE AND TANZANIA WILDLIFE RESEARCH INSTITUTE With support from AFRICAN WILDLIFE FOUNDATION, MARWELL WILDLIFE, TANZANIA NATIONAL PARKS AND WILDLIFE DIVISION WILDLIFE DIVISION

2 2013 Dry season cross borderaerial census report 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 A technical Report for Kenya Wildlife Service (KWS), Kenya and Tanzania Wildlife Research Institute (TAWIRI), Tanzania ii

3 EXECUTIVE SUMMARY 2013 Dry season cross borderaerial census report 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 The census covered an area of 25,623 km 2 including 9,214 km 2 of the Amboseli ecosystem, 6,348 km 2 of the Namanga-Magadi areas in southwestern Kenya, 3,013 km 2 of the West Kilimanjaro and 7,047 km 2 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 ±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 These population increases can be attributed largely to the recovery of the populations after drought induced mortalities experienced in the area between 2007 and 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 largescale 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. iii

4 LIST OF ACRONYMS AND ABBREVIATIONS AGL ASL ASTER ATE AWKMN AWF CIMU DEM DNR FSO GCA GIS GPS KINAPA KWS NP RSO SPSS SRF TANAPA TAWIRI TC TWCM UTM WD Above Ground Level Above Sea Level Advanced Space borne Thermal Emission and Reflection Amboseli Trust for Elephants Amboseli-Kilimanjaro, Magadi Natron African Wildlife Foundation Conservation information and Monitoring Unit Digital Elevation Model Department of Natural Resources Front Seat Observer Game Controlled Area Geographic Information Systems Global Positioning System Kilimanjaro National Park Kenya Wildlife Service National Park Rear Seat Observer Statistical Package for Social Sciences Systematic Reconnaissance Flight Tanzania National Parks Tanzania Wildlife Research Institute Total Count Tanzania Wildlife Conservation Monitoring Universal Transverse Mercator Wildlife Division (Tanzania) 1

5 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 Census Block Designand flight plan Data collection Estimation of Height Above Ground Level Data handling andanalyses Calculation of Search Effort Determination of Population density and carcass ratio RESULTS Survey parameters and Meta data Wildlife Abundance Species abundance, densities and Distribution Common Zebra Common Wildebeest Grant s gazelle Maasai Giraffe Thomson s Gazelle African Elephant Impala Maasai Ostrich Cape Eland Fringe-Eared Oryx Cape Buffalo Gerenuk Lesser kudu Other wildlife species Human activities DISCUSSION CONCLUSIONS AND RECOMMENDATIONS ACKNOWLEDGEMENTS REFERENCES:

6 APPENDICES LIST OF TABLES Table 1: Aerial surveys done in Amboseli and West Kilimanjaro areas, Table 2: Search effort per census region Table 3: Wildlife species numbers counted during the dry season survey of Table 4: Human activities recorded in the study area 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 Figure 3 Use of streamers showing the two band categories Figure 4: Survey flight paths showing coverage of the study area 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 Figure 6: Distribution of common zebra in the study area in October Figure 7: Map of the study area showing distribution of wildebeest, October Figure 8: Distribution of Grant s gazelle in the study area in October Figure 9: Distribution of Maasai Giraffe in the study area in October Figure 10: Distribution of Thomson s Gazelles in the study area, October Figure 11: Distribution of Elephants in the study area, October Figure 12: Distribution of elephant carcasses, October Figure 13: Distribution of Impalas in study area, October Figure 14: Distribution of Ostrich in the study area in October Figure 15: Distribution of Eland in the study area in October Figure 16: Distribution of Fringe Eared Oryx in Study area, October Figure 17: Distribution of Cape buffalo in the study area, October Figure 18: Distribution of Gerenuks in the Study Area in October Figure 19: Distribution of Lesser Kudu in the Study Area in October Figure 20: Distribution of other wildlife species in the study area in October Figure 21: A) Shoats, B) Cattle, C) Camel and donkey and(d) Charcoal kilns in the study area in October LIST OF APPENDICES Appendix 1: Wildlife densities per areas square kilometer Appendix 2: Wildlife population trends and change...1 Appendix 3: Average rainfall pattern in over (Calendar year) Amboseli area since

7 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 6 th to12 th October2013. 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 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. 4

8 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, Year Month Season Survey Name of area * Area Source Technique surveyed (km 2 ) 1997 June Wet SRF West 2,537 TWCM (1998) Kilimanjaro 2000 January Wet TC Amboseli 4,035 KWS (2000) 2001 May Wet SRF West 2,537 CIMU (2002) Kilimanjaro 2002 August Dry TC Amboseli 5,736 KWS (2002) 2002 August Dry TC West 6,909 TAWIRI (2003) Kilimanjaro 2007 May Wet TC Amboseli 5,542 KWS (2007) 2009 March Dry SRF West 2,558 TAWIRI (2009) Kilimanjaro 2010 March Wet TC Amboseli, West 24,108 KWS & TAWIRI, 2010 Kilimanjaro, Namanga- Magadi, Natron 2010 October Dry TC Amboseli-West 24,788 KWS & TAWIRI, 2010 Kilimanjaro and Namanga- Magadi, Natron 2013 April Wet TC Amboseli, West 25,623 KWS & TAWIRI, 2013 Kilimanjaro, Namanga- Magadi, Natron 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. 5

9 MATERIALS AND METHODS Study Area The AWKMN area covers portions of Southern Kenya and Northern Tanzania between latitudes and South and longitude and 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 km 2 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. 6

10 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). 7

11 Namanga-Magadi Area The Namanga-Magadi area (6348 km 2 ) 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 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 km 2 ) 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 8

12 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 km 2 ) on the eastern boundary and Arusha NP (137 km 2 ) to the south. Additionally, there are two private conservation areas, West Kilimanjaro Ranch (303 km 2 ), Endarakwai Ranch (44 km 2 ); as well as, Longido Game Controlled Area (GCA, 1,700 km 2 ), and Ngasurai Open Area (544 km 2 ) 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 km 2 ) 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. 9

13 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. 900km 2 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. 10

14 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 11

15 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. 12

16 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)( 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 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. 13

17 Calculation of Search Effort Search effort in this report refers to the area (km2) covered by the aerial crew in one hour (km 2 /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. 14

18 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 ± 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 165.9km 2 /hour. Natron registered the lowest search effort (214.2km 2 /hour), while Magadi region registered the highest search effort (138.06km 2 /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 15

19 Table 2:Search effort per census region Census Region Time (Hrs.) Size (Km 2 ) Search effort (Km 2 /h) Amboseli , Magadi Natron , West Kilimanjaro Total 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). 16

20 Table 3: Wildlife species numbers counted during the dry season survey of SPECIES AMBOSELI ( KM 2 ) WEST KILIMA NJARO ( KM 2 ) MAGADI ( KM 2 ) NATRON ( KM 2 ) Grand Total COMMON ZEBRA ,693 COMMON WILDEBEEST ,862 GRANT'S GAZELLE ,051 MASAAI GIRAFFE ,626 THOMSON'S GAZELLE ,492 AFRICAN ELEPHANT ,200 ELEPHANT CARCASS - OLD ELEPHANT CARCASS - VERY OLD IMPALA ,113 MASAAI OSTRICH ,090 CAPE ELAND BABOON FRINGE EARED ORYX GERENUK CAPE BUFFALO LESSER KUDU WARTHOG HIPPOPOTAMUS COKE S HARTBEAST DIKDIK COMMON WATER BUCK LION 5 5 SPOTTED HYENA SILVER BACKED JACKAL 3 3 BUSHBUCK KORI BUSTARD CHEETAH 1 1 REED BUCK 1 1 SECRETARY BIRD 1 1 TOTAL 46,137 17

21 DRY Season 2013 DRY Season (A) Percentage change % change %change COMMON WILDEBEEST COMMON ZEBRA CAPE BUFFALO THOMSON'S GAZELLE GRANT'S GAZELLE MAASAI OSTRICH CAPE ELAND AFRICAN ELEPHANT MAASAI GIRAFFE (B) 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

22 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 /km 2 with Amboseli having the highest density (1.155/km 2 )among the four survey regions followed by Magadi (0.561/km 2 ), Natron (0.546/km 2 ), and West Kilimanjaro (0.542/km 2 ) 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

23 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/km 2 with Amboseli recording the highest density (0.621/km 2 ). 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/km 2 followed by Lake Natron which had 0.182/km 2 as compared to 1.06/km 2 of wet season Finally West Kilimanjaro had the lowest density of 0.063/km 2 (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

24 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/km 2 with highest densities in the Amboseli and Magadi w of 0.343/km 2 and 0.323/km 2 respectively. Lowest densities were recorded in Natron and West Kilimanjaro with 0.184/km /km 2 respectively(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

25 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/km 2 in which the Amboseli region had the highest concentration of 0.157/km 2 followed by Natron (0.145/km 2 ). Magadi and West Kilimanjaro had densities of 0.128/km 2 and 0.115/km 2 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

26 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/km 2. Amboseli region had the highest concentration of 0.102/km 2 followed by Magadi which had 0.046/km 2. West Kilimanjaro and Natron had 0.036/km 2 and 0.022/km 2 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

27 African Elephant A total of 1200 elephants were recorded during the survey with an overall density of 0.047/km 2 (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/km 2. There was an increase of elephants in the Magadi and Natron areas; 7 to 159 and 5 to 21 respectively (0.025/km 2 and 0.003/km 2, Appendix 1). West Kilimanjaro had a density of 0.008/km 2.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

28 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 ( KM 2 ) WEST KILIMANJARO ( KM 2 ) MAGADI ( KM 2 ) NATRON ( KM 2 ) Total Old elephant carcass Carcass ratio Mortality Index % Carcass ratio % Mortality index Very old elephant carcass Carcass ratio Mortality Index % Carcass ratio % Mortality index All carcases Carcass ratio Mortality Index % Carcass ratio % Mortality index

29 Figure 12: Distribution of elephant carcasses, October

30 Impala The population of Impala in the study area was 1,113 individuals (Table 3). The overall density was 0.043/km 2. Magadi had the highest concentration of 0.054/km 2 followed by Amboseli with 0.044/km 2. Natron and West Kilimanjaro areas had similar densities of 0.036/km 2 (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

31 Maasai Ostrich A total 1,090 ostriches were counted in the entire landscape giving a density of 0.043/km 2. The Amboseli region had the highest density of 0.053/km 2 followed by Natron and Magadi region with 0.042/km 2 and 0.036/km 2 respectively (Figure 14). West Kilimanjaro had the lowest density of /km 2 (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

32 Cape Eland The population size of eland recorded in the study area was 631 individuals. The overall density was 0.025/km 2. The highest density (0.052/km 2 ) was found in West Kilimanjaro. Amboseli had the second highest concentration of 0.034/km 2 while Magadi and Natron had densities of 0.022/km 2 and 0.004/km 2 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

33 Fringe-Eared Oryx A total of 242 Fringe-eared Oryx were recorded giving an overall density of 0.009/km 2. West Kilimanjaro recorded the highest density of 0.024/km 2 followed by Amboseli with 0.015/km 2. Natron and Magadi had densities of 0.003/km 2 and 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

34 Cape Buffalo A total of 184 buffaloes were recorded in the landscape giving an overall density of 0.007/km 2. Buffalo were found only in the Amboseli region at a density of 0.020/km 2 (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

35 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/km 2. Amboseli, Natron and West Kilimanjaro had similar densities of 0.010/km 2 while Magadi had the least density of 0.08/km 2 (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

36 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

37 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

38 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 ( KM 2 ) MAGADI ( KM 2 ) NATRON (7047 KM 2.26) WEST KILIMANJARO ( ) KM 2 ) Grand Total Camel Cattle Charcoal Donkey Shoats Grand total

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

40 DISCUSSION The results of this study demonstrate that there has been an increase in wildlife and livestock numbers since the devastating drought of 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 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 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 37