Spatial determinants of habitat use, mortality and connectivity for elephant populations across southern Africa

Southern Africa contains 58% of the world’s savannah elephant population, yet 72% of their range occurs outside of protected areas. It is, therefore, important to develop management guidelines that satisfy the needs of both elephants and people while maintaining environmental heterogeneity and ecosystem processes. Managing elephants as a metapopulation may provide the solution. The goal of this thesis was then to use a habitat-based approach to identify landscape characteristics which could contribute to the functionality of a metapopulation for elephants. Using resource selection function models, I identified habitat suitability for elephants across southern Africa and used these models to evaluate whether current habitat configurations allow for the assumptions of connectivity and asynchronous population dynamics required by a metapopulation. I found that water, tree cover, slope, and human presence were important predictors of elephant habitat selection. Furthermore, functional responses in habitat selection were present across space and time for water and tree cover, showing the adaptability of this generalist species to resource heterogeneity. Using habitat selection along with circuit theory current flow maps, I then found a high likelihood of connectivity in the central portion of our study area (i.e. between the Chobe, Kafue, Luangwa, and Zambezi cluster). Main factors limiting connectivity were the high human density in the east and a lack of surface water in the west. These factors effectively isolate elephants in the Etosha cluster in Namibia and Niassa clusters in Mozambique from the central region. Models further identified two clusters where elephants might benefit from being managed as part of a conservation network, 1) northern Zambia and Malawi and 2) northern Mozambique. Incorporating information on elephant mortalities in northern Botswana into habitat selection estimations, I found that source habitats for elephants occurred within the central Okavango Delta region and sink habitats were associated with periphery of the study area where human use was highest. Eighty percent of elephant mortalities occurred within 25 km of people. The protected designation of an area had less influence on elephant mortality than did the locations of the area in relation to human development. To exacerbate human-elephant conflicts, people tended to settle in areas of high-quality elephant habitats, creating resource competition between elephants and people. Consequently, elephant mortality near humans increased as a function of habitat suitability, and elephants responded by using less suitable habitats. While humans occupied only 0.7% of the study area, mortality and behavioural effects impacted 43%. Based on the habitat factors examined here, elephants in southern Africa could be managed as a metapopulation if (1) connectivity is maintained and encouraged and (2) spatial heterogeneity in resources and risks serves to stabilize elephant demography. This habitat-based system of management could serve to alleviate unstable elephant populations in southern Africa and create more natural, self-sustaining regulatory mechanisms.Thesis (PhD)--University of Pretoria, 2013.Zoology and Entomologyunrestricte

Functional connectivity within conservation networks : delineating corridors for African elephants

Managing multiple parks, reserves, and conservation areas collectively as conservation networks is a recent, yet growing trend. But in order for these networks to be ecologically viable, the functional connectivity of the landscape must be ensured. We assessed the connectivity between six African savanna elephant populations in southern Africa to test whether existing conservation networks were functioning and to identify other areas that could benefit from being managed as conservation networks. We used resource selection function models to create an index of habitat selection by males and female elephants. We employed this habitat use index as a resistance surface, and applied circuit theory to assess connectivity between adjacent elephant populations within six clusters of protected areas across southern Africa. Circuit theory current flow maps predicted a high likelihood of connectivity in the central portion of our study area (i.e. between the Chobe, Kafue, Luangwa, and Zambezi cluster). Main factors limiting connectivity across the study area were high human density in the east and a lack of surface water in the west. These factors effectively isolate elephants in the Etosha cluster in Namibia and Niassa clusters in Mozambique from the central region. Our models further identified two clusters where elephants might benefit from being managed as part of a conservation network, 1) northern Zambia and Malawi and 2) northern Mozambique. We conclude that using habitat selection and circuit theory models to identify conservation networks is a data-based method that can be applied to other focal species to identify and conserve functional connectivity.The Conservation Foundation Zambia, Conservation International’s southern Africa’s Wildlife Programme, Conservation Lower Zambezi, the International Fund for Animal Welfare, the Mozal Community Development Trust, the National Research Foundation, the National Postcode Lottery of the Netherlands, the Peace Parks Foundation, the US Fish and Wildlife Services, the University of Pretoria, the World Wildlife Fund (SARPO; Mozambique; SA), the Walt Disney Grant Foundation, and the Wildlifewins Lottery for several years of research funding to RJ van Aarde.www.elsevier.com/ locate/bioconhb2013ab201

Incorporating mortality into habitat selection to identify secure and risky habitats for savannah elephants

Empirical models of habitat selection are increasingly used to guide and inform habitat-based management plans for wildlife species. However, habitat selection does not necessarily equate to habitat quality particularly if selection is maladaptive, so incorporating measures of fitness into estimations of occurrence is necessary to increase model robustness. Here, we incorporated spatially explicit mortality events with the habitat selection of elephants to predict secure and risky habitats in northern Botswana. Following a two-step approach, we first predict the relative probability of use and the relative probability of mortality based on landscape features using logistic regression models. Combining these two indices, we then identified low mortality and high use (primary habitat) and areas of high mortality and high use (primary risk). We found that mortalities of adult elephants were closely associated with anthropogenic features, with 80% of mortalities occurring within 25 km of people. Conversely, elephant habitat selection was highest at distances of 30–50 km from people. Primary habitat for elephants occurred in the central portion of the study area and within the Okavango Delta; whereas risky areas occurred along the periphery near humans. The protected designation of an area had less influence on the proportion of prime habitat therein than did the locations of the area in relation to human development. Elephant management in southern Africa is moving towards a more self-sustaining, habitat-based approach, and information on selection and mortality could serve as a baseline to help identify demographic sources and sinks to stabilize elephant demography.Elephants Without Borders, the International Fund for Animal Welfare, and the University of Pretoria.The aerial survey was sanctioned and supported by the Botswana Department of Wildlife and National Parks, through a grant administered by the Conservation Trust Fund (CTF/2010/56). Additional funding was received from the Zoological Society of San Diego.http://www.elsevier.com/locate/bioconhb2013ab201

Functional responses in the habitat selection of a generalist mega-herbivore, the African savannah elephant

Resource selection function (RSF) models are commonly used to quantify species/ habitat associations and predict species occurrence on the landscape. However, these models are sensitive to changes in resource availability and can result in a functional response to resource abundance, where preferences change as a function of availability. For generalist species, which utilize a wide range of habitats and resources, quantifying habitat selection is particularly challenging. Spatial and temporal changes in resource abundance can result in changes in selection preference affecting the robustness of habitat selection models. We examined selection preference across a wide range of ecological conditions for a generalist mega-herbivore, the African savannah elephant (Loxodonta africana), to quantify general patterns in selection and to illustrate the importance of functional responses in elephant habitat selection. We found a functional response in habitat selection across both space and time for tree cover, with tree cover being unimportant to habitat selection in the mesic, eastern populations during the wet season. A temporal functional response for water was also evident, with greater variability in selection during the wet season. Selection for low slopes, high tree cover, and far distance from people was consistent across populations; however, variability in selection coefficients changed as a function of the abundance of a given resource within the home range. This variability of selection coefficients could be used to improve confidence estimations for inferences drawn from habitat selection models. Quantifying functional responses in habitat selection is one way to better predict how wildlife will respond to an ever-changing environment, and they provide promising insights into the habitat selection of generalist species.Support for this study was provide by Billiton, Conservation Foundation Zambia, Conservation International’s southern Africa’s Wildlife Programme, the Conservation Lower Zambezi, Duke University, the International Fund for Animal Welfare, the Mozal Community Development Trust, the National Research Foundation, the National Postcode Lottery of the Netherlands, Peace Parks Foundation, the US Fish and Wildlife Services, the University of Pretoria, the World Wildlife Fund (SARPO; Mozambique; SA), the Walt Disney Grant Foundation, and the Wildlifewins Lottery. Logistical support was provided by Bateleurs, South African National Parks, Tracks4Africa, and Wings for Wildlife. This research was sanctioned and supported by the Botswana Department of Wildlife & National Parks, Direcção Nacional de Areas de Conservação, the Namibian Ministry of Tourism & Environment, the Malawian Wildlife Department, Ezemvelo KZN Wildlife of South Africa, and the Zambian Wildlife Authority.http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1600-0587hb2017Zoology and Entomolog