Animal distributions and movement behaviors in relation to resource dynamics

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2008-11-17

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Abstract

Animal movements, whether spatially constrained or spread across broad spatial scales, are often motivated by a need for resources. This thesis seeks to explore the role spatial and temporal resource dynamics may play in animal movements and population distributions.

The first chapter synthesizes existing research of animal movements and builds a conceptual framework that integrates individual-level movement behaviors. It distinguishes among (1) non-oriented movements in response to proximate stimuli, (2) oriented movements utilizing perceptual cues of distant targets, and (3) memory mechanisms that assume prior knowledge of a target's location. I outline how species' use of these mechanisms should depend on resource dynamics and lead to population-level patterns, such as sedentary ranges, migration between disjunct and predictable seasonal resource areas, or nomadism when resource distributions are unpredictable in both space and time.

The second chapter examines resource dynamics in an empirical setting, which, especially in ecosystems where changes may happen rapidly across broad spatial scales, is challenging because field measurements may be logistically infeasible. I use satellite imagery of vegetation productivity to track habitat dynamics for Mongolian gazelles in the eastern steppes of Mongolia. I show that spatiotemporal variation of gazelle habitats is extremely high, which may force gazelles to range over vast areas in search of food. This has important conservation implications because single protected areas may not provide sufficient gazelle habitats at all times and landscape level management plans are needed.

In the third chapter I develop a theoretical simulation model, that implements and combines the three different classes of movement behaviors (non-oriented, oriented, memory) and explores their efficiency under different scenarios of resource dynamics. Adapting techniques from artificial evolution and intelligence, I show how individuals evolve to rely heavily on memory if their landscape dynamics are predictable. In contrast, non-oriented movement evolves predominately in situations where landscape dynamics are unpredictable. Oriented movement proves important at smaller scales, when movement targets are distributed within perceptual ranges.

Future studies may transfer this theoretical model into empirical settings and use actual dynamic habitat models like that developed in chapter two, to reveal the underlying movement behaviors of real animals.

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