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Emerging remote sensing technologies and population genetic analyses for chimpanzee conservation in Tanzania

Bonnin, N (2021) Emerging remote sensing technologies and population genetic analyses for chimpanzee conservation in Tanzania. Doctoral thesis, Liverpool John Moores University.

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Abstract

Chimpanzees are declining at a rate of up to 6.5% per year in some parts of Africa due to human impacts. Effective conservation relies on accurate and reliable information on population density, distribution and connectivity. Yet, traditional line transect surveys are costly to conduct over large areas and particularly at sufficiently regular intervals to determine trends in abundance. Moreover, they often fail to identify critical areas for animal movement. Given the vast landscape across which chimpanzees are found, we need new methods that are time and cost efficient while providing precise and accurate data across broad spatial scales. This thesis explores the potential of multiple remote sensing technologies along with molecular methods to provide critical information on population distribution, density and connectivity across broad spatial and temporal scales. My research first investigated the potential of drones for chimpanzee population surveys in Tanzania. More specifically, I evaluated drone performance in detecting chimpanzee nests by comparing ground and aerial surveys in the Issa valley, western Tanzania. I found ground and aerial nest numbers to be correlated, with an average of 10% of nests observed from the ground detectable from the air. Although I highlight challenges in using drones for chimpanzee surveys, the study provides guidance for future investigations and emphasises the importance of contrasting background and high-resolution images. Next, using satellite imagery from 1973 and 2018 and a landcover projection for 2027, I model landscape connectivity change for chimpanzees within the Greater Mahale Ecosystem (GME), an area containing nearly all of Tanzanian’s chimpanzees. The model reveals a series of corridors allowing chimpanzee movement throughout the ecosystem, as well as a reduction of connectivity over time likely to continue through 2027. By identifying critical areas for chimpanzee movement, the model provides valuable guidance on where to focus conservation efforts. Finally, using two molecular markers (mitochondrial control region sequences and 10 microsatellite loci), I describe population structure and genetic diversity of Tanzania’s chimpanzees. My analyses confirm historical gene flow between Gombe National Park (GNP) and the GME but also suggest complete interruption of chimpanzee movements between the two areas in recent years. Both genetic markers suggest high genetic diversity with no evidence of inbreeding and a greater mitochondrial DNA diversity within GNP. This surprising result might be explained by potential gene flow with extra-park chimpanzees and evidence of Gombe females preference for genetically dissimilar mates. Results of this study resolve previous contrasting findings on connectivity between GNP and the GME and support the establishment of two conservation units. Together, these chapters demonstrate the diversity of non-invasive technologies that can be applied, not only to help chimpanzee conservation, but also any large-bodied species facing accelerated rates of anthropogenic disturbance.

Item Type: Thesis (Doctoral)
Uncontrolled Keywords: Drone; Great apes; Connectivity; Population genetic
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Q Science > QH Natural history
Q Science > QH Natural history > QH301 Biology
Q Science > QH Natural history > QH426 Genetics
T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Divisions: Biological & Environmental Sciences (new Sep 19)
Date Deposited: 07 Jun 2021 09:18
Last Modified: 03 Sep 2021 23:17
DOI or Identification number: 10.24377/LJMU.t.00015075
Supervisors: Wich, S, Piel, A and Pintea, L
URI: https://researchonline.ljmu.ac.uk/id/eprint/15075

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