search.noResults

search.searching

dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
Determining multi-species site use outside the protected areas of the Maasai Mara, Kenya, using false positive site-occupancy modelling E MIL Y K. MADSEN and FEMKE BRO E K H U I S


Abstract Although protected areas are the basis for many conservation efforts they are rarely of an adequate size for the long-term survival of populations of large, wide-roam- ing mammals. In the Maasai Mara, Kenya, communally owned wildlife conservancies have been developed to ex- pand the area available for wildlife. As these continue to de- velop it is important to ensure that the areas chosen are beneficial to wildlife. Using presence data for cheetahs Acinonyx jubatus,elephants Loxodonta africana, spotted hyaenas Crocuta crocuta,leopards Panthera pardus,lions Panthera leo andwilddogs Lycaon pictus, collected through interviews with 648 people living outside protected areas, we identify key wildlife areas using false positive site-occu- pancymodelling. The probabilities of site usewere first deter- mined per species based on habitat, distance to protected area, human presence and rivers, and these probabilities were then combined to create a map to highlight key wildlife areas. All species, except hyaenas, preferred sites closer to the protected areas but site use varied by species depending on habitat type. All six species avoided human presence. Leopards, elephants, lions and wild dogs preferred sites closer to rivers. The result- ing combined map highlights areas that could potentially benefit from conservation efforts, including the expansion of wildlife areas, and areas where human development, such as a newly tarmacked road, could have an impact on wildlife.


Keywords Carnivores, false positive, interview data, Maasai Mara, mapping, occupancy modelling, protected areas, wildlife distribution


Supplementary material for this article is available at https://doi.org/10.1017/S0030605318000297


Introduction P


rotected areas are the basis for many conservation efforts but in many cases are not sufficiently large to


EMILY K. MADSEN* (Corresponding author) Royal Veterinary College, 4 Royal College St, London, NW1 0TU, UK. E-mail: emadsen6@rvc.ac.uk


FEMKE BROEKHUIS† Kenya Wildlife Trust, Nairobi, Kenya


*Also at: The Zoological Society of London, Institute of Zoology, London, UK †Also at: Wildlife Conservation Research Unit, Department of Zoology, Tubney, UK


Received 6 September 2017. Revision requested 23 November 2017. Accepted 8 February 2018. First published online 25 September 2018.


maintain sustainable populations of many species (Stokes et al., 2010; Okello et al., 2016). Approximately 15.4%of the world’s terrestrial area is now formally protected and in Kenya 8% of the land is protected as either a national park or reserve (Western et al., 2009). Nonetheless, 65– 70% of the country’s wildlife resides in unprotected areas where they are under threat (Western et al., 2009; Stolton et al., 2014) and so there is a desire to protect more land for wildlife (Republic of Kenya, 2013). The Maasai Mara in south-west Kenya, for example, is renowned for its annual migration of wildebeest Connochaetes taurinus and high densities of predators (Broekhuis & Gopalaswamy, 2016; Elliot & Gopalaswamy, 2017) but it is under increasing an- thropogenic pressure. Since the 1980s there has been an in- crease in human population growth and fencing of private land outside protected areas (Lamprey & Reid, 2004; Løvschal et al., 2017), which has resulted in wildlife popula- tions decreasing by up to 75% in the 20th century (Ogutu et al., 2011). The Maasai Mara National Reserve (hereafter the Reserve) covers 1,503 km2 and in the last 25 years surrounding areas have been put aside for wildlife to address these declines (Jandreau&Berkes, 2016). These Community Wildlife Conservancies do not have the same status as the Reserve but are nonetheless recognized as being beneficial for wildlife (Stolton et al., 2014). In the conservancies land- owners limit their use of resources and receive an income from tourist operators who pay for exclusive access (Jandreau & Berkes, 2016). The development of conservan- cies has added c. 1,000 km2 of designated wildlife area to the Reserve, with a plan to increase this further (MMWCA, 2015). It is important to ensure that the areas chosen will benefit wildlife conservation, but land protection schemes can be costly and therefore planning needs to be based upon reliable information, from evidence-based research, to ensure cost-effectiveness (Zeller et al., 2011). Land protection schemes are often based on species’ oc-


currence because presence/absence data are easier and cheaper to collect than demographic data such as densities or whole population counts (Gu & Swihart, 2004). Information on wildlife presence can be collected with the help of local people, as they often have good knowledge of their local ecosystem and can provide insights into the dis- tribution of wildlife (Turvey et al., 2015). Interview surveys can be a useful method of collecting this information be- cause of cost-effectiveness and relatively simple logistics (Turvey et al., 2015; Petracca et al., 2018). However, the use


Oryx, 2020, 54(3), 395–404 © 2018 Fauna & Flora International doi:10.1017/S0030605318000297


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78  |  Page 79  |  Page 80  |  Page 81  |  Page 82  |  Page 83  |  Page 84  |  Page 85  |  Page 86  |  Page 87  |  Page 88  |  Page 89  |  Page 90  |  Page 91  |  Page 92  |  Page 93  |  Page 94  |  Page 95  |  Page 96  |  Page 97  |  Page 98  |  Page 99  |  Page 100  |  Page 101  |  Page 102  |  Page 103  |  Page 104  |  Page 105  |  Page 106  |  Page 107  |  Page 108  |  Page 109  |  Page 110  |  Page 111  |  Page 112  |  Page 113  |  Page 114  |  Page 115  |  Page 116  |  Page 117  |  Page 118  |  Page 119  |  Page 120  |  Page 121  |  Page 122  |  Page 123  |  Page 124  |  Page 125  |  Page 126  |  Page 127  |  Page 128  |  Page 129  |  Page 130  |  Page 131  |  Page 132  |  Page 133  |  Page 134  |  Page 135  |  Page 136  |  Page 137  |  Page 138  |  Page 139  |  Page 140  |  Page 141  |  Page 142  |  Page 143  |  Page 144  |  Page 145  |  Page 146  |  Page 147  |  Page 148