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Title: From inventories to interactions : inferring mammal community patterns and processes from camera trap data
Author: Cusack, Jeremy
ISNI:       0000 0004 6499 3435
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2016
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The deployment of camera traps, which automatically take pictures of wild animals moving in front of them, is now routinely used to survey terrestrial mammal communities worldwide. The resulting photographic data are used to answer questions relating to the richness and structure of mammal communities, the density of their component species, and how the latter might interact. This thesis fills key methodological gaps in how these questions are addressed. My first data chapter assesses how the exact placement of camera traps on natural game trails influences the characterisation of community richness, composition and structure in an east African savannah landscape. I find that a trail-based placement strategy leads to more species being detected more rapidly relative to a random one, and increases capture rates for carnivore species in particular. In contrast, I reveal in Chapter 3 how a non-random camera trap placement strategy can bias estimates of absolute density for an unmarked large carnivore, the lion Panthera leo, obtained using an ideal gas model approach. Chapter 4 considers spatiotemporal patterns in camera trap data, and to what extent they can be used to infer on the kleptoparasitic and predatory tendencies of spotted hyenas and lions, respectively, in Tanzania's Ruaha landscape. I find patterns to be generally uninformative, and so, in Chapter 5, turn to another method of collecting spatiotemporal data, Global Positioning Satellite telemetry, to make inferences on the spatial response of elk to wolves in Yellowstone National park. I find no evidence for a significant spatial avoidance of wolves by elk, suggesting that species interactions may not always lead to measurable spatial patterns. Nevertheless, in my final chapter, I use an individual-based modelling framework to simulate different types of prey responses to predator movement in the absence of confounding factors, and find that a huge amount of camera trapping effort would be required to distinguish between them. This thesis highlights how camera trap placement can affect the description of mammal communities and the estimation of species density. It also shows that we cannot rely solely on spatiotemporal patterns derived from camera traps to make inferences on complex interactive processes.
Supervisor: Dickman, Amelia ; Coulson, Timothy ; Carbone, Chris Sponsor: Natural Environment Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available