Determining multi-species site use outside the protected areas of the Maasai Mara, Kenya, using false positive site-occupancy modelling

Emily K. Madsen*, Femke Broekhuis

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)

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-roaming mammals. In the Maasai Mara, Kenya, communally owned wildlife conservancies have been developed to expand the area available for wildlife. As these continue to develop 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 and wild dogs Lycaon pictus, collected through interviews with 648 people living outside protected areas, we identify key wildlife areas using false positive site-occupancy modelling. The probabilities of site use were first determined 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 resulting 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.

Original languageEnglish
Pages (from-to)395-404
Number of pages10
JournalOryx
Volume54
Issue number3
DOIs
Publication statusPublished - 1 May 2020
Externally publishedYes

Keywords

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

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