LINKING PATTERN AND PROCESS: APPLYING AGENT-BASED MODELS AND SPATIAL BAYESIAN STATISTICS TO THE STUDY OF ANIMAL MIGRATION Pubblico

Kendzel, Mitchell (Fall 2024)

Permanent URL: https://etd.library.emory.edu/concern/etds/02870x36w?locale=it
Published

Abstract

Animal migrations are the subject of widespread and interdisciplinary research. These movement events can vary significantly based on spatial and temporal scale (e.g., the cyclical migration of the sandhopper, Talitrus saltator, is measured in meters and hours as they follow transient tidal changes while the migratory movements of the Arctic tern, Sterna paradisaea, is measured in thousands of kilometers and months). Furthermore, the mechanisms and drivers activating and maintaining these behaviors can equally vary. To reach specific goals, whether that be habitats, mating opportunities, or influxes of resources that are utilized after a migration, animals have been found to use a variety of sensory and cognitive mechanisms to successfully migrate. The combination of these mechanisms determines an animal’s navigation strategy, such as piloting, inertial, compass, vector, and true navigation. However, research inferring specific strategies from observed movement data is lacking in many systems and historically limited to model cases. This has hampered comparisons of navigation strategies across systems and behaviors and created confusing terminology in the literature. Terminology often depends on the scale of movement, rather than the actual biology of the system, resulting in unclear distinctions between different navigation strategies. In this dissertation, I provide two frameworks to effectively categorize animals’ navigation strategies based on biology rather than geography. The first conceptual framework (1) unifies navigation terminology to be used regardless of movement scale; (2) summarizes unique characteristics of common navigation strategies to highlight differences in cognitive mechanisms between strategies; and (3) provides experimental and modeling approaches to define a strategy in an animal with special consideration on study design. The second, a statistical framework, utilizes simulations to predict geographic spread of migrants using varying navigation strategies to be comparable to observed patterns for the species. Applying this framework to the monarch butterfly as a case study, I found evidence that the butterfly’s long-distance, thousands of kilometers, migration is consistent with vector navigation and thus true navigation is not necessary in the system (a long-standing research question in the system). Thus, these frameworks aids in classifying animal navigation strategies and unifying navigation research across movement scales and model organisms.

Table of Contents

TITLE

ABSTRACT

ACKNOWLEDGEMENTS

TABLE OF CONTENTS

CHAPTER I: Introduction - 1

CHAPTER II -27

CHAPTER III- 42

CHAPTER IV - 75

CHAPTER V - CONCLUSIONS - 97

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