Tools for the Occurrence of Free-Living and Symbiotic Organisms in Space and Time

151 Pages·2017·12.61 MB·English

University of Colorado, Boulder
CU Scholar
Ecology & Evolutionary Biology Graduate Teses &
Ecology & Evolutionary Biology
Dissertations
Spring 1-1-2016
Tools for the Occurrence of Free-Living and
Symbiotic Organisms in Space and Time
Maxwell B. Joseph
University of Colorado at Boulder,
Tools for the occurrence of free-living and symbiotic
organisms in space and time
by
Maxwell B. Joseph
B.S., University of California Davis, 2008
A thesis submitted to the
Faculty of the Graduate School of the
University of Colorado in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
Department of Ecology and Evolutionary Biology
2016
This thesis entitled:
Tools for the occurrence of free-living and symbiotic organisms in space and time
written by Maxwell B. Joseph
has been approved for the Department of Ecology and Evolutionary Biology
Prof. Pieter T. J. Johnson
Prof. Vanja Dukic
Prof. Samuel Flaxman
Prof. Andrew Martin
Prof. Valerie McKenzie
Date
The final copy of this thesis has been examined by the signatories, and we find that both the
content and the form meet acceptable presentation standards of scholarly work in the above
mentioned discipline.
iii
Joseph, Maxwell B. (Ph.D., Ecology and Evolutionary Biology)
Tools for the occurrence of free-living and symbiotic organisms in space and time
Thesis directed by Prof. Pieter T. J. Johnson
This doctoral dissertation broadly aims to improve methods for understanding the occurrence
of organisms in space and time, including organisms that cause disease. The processes that drive
occurrence are often represented mathematically as ecological theories, which can be applied to
uncover actionable insights into disease management. This was a focus of my first chapter which
characterized the gap between disease ecology theory and infectious disease management. My
second chapter focused on filling in a gap theoretically at the intersection of multi-host pathogens
and host community disassembly. Specifically, I construct a theoretical model to evaluate disease
consequences when hosts are extirpated according to a variety of rules predicted from community
ecology. The third chapter develops a method to link representations of latent processes that
drive species occurrence to observable (with error) data, with the goal of understanding multiple
causal pathways in an occupancy model. The fourth also extends occupancy models, but to allow
for multi-host multi-symbiont (parasites included) systems. Chapter five is somewhat different
topically, focusing on missing species trait interpolation, but methodologically is not much of a
departure, drawing on Bayesian hierarchical modeling as in the previous two chapters. The final
chapter develops a theoretical model to generate predictions about the effect of host diversity on
the diversity and transmission of symbiotic organisms.
Dedication
To my family and friends, bipedal and otherwise.
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Acknowledgements
None of this would have been possible without my loving family and friends. I would like
to thank my labmates Joseph Mihaljevic, Sarah Orlofske, Sara Paull, Katherine Richgels, Travis
McDevitt-Galles, Dan Preston, Miranda Redmond, Jazzmin Jenkins, Dain Calhoun, Will Stutz,
Sarah Haas, Bethany Hoye, Jason Hoverman, Kim Medley, and Yuri Springer. Many faculty
have been gracious with their time including Nichole Barger, John Basey, Dean Bowers, Kendi
Davies, Michael Grant, Brett Melbourne, Rebecca Safran, Stacey Smith, and Carol Wessman.
Many fellow students have helped me along the way as well, including Aidan Beers, Amanda
Hund, Amy Churchill, Angela Boag, Caroline Tucker, Chris Steenbock, Christine Avena, Collin
Schwan Quixote Schwantes, David Zonana, Evelyn Cheng, Gaurav Vaidya, Helen McCreery, Jeff
McClenahan, Joey Hubbard, Jon Leff, Jordan Keueneman, Julian Resasco, Kevin Bracy Knight,
Kika Tarsus, Lauren Shoemaker, Lisette Arellano, Matt Marty Milkins Wilkins, Megan Blanchard,
Nathan Kleist, Nora Connor, Se Jin Song, Teal Potter, Tim Szewczyk, Toby Hammer, Topher
Weiss-Lehman, Tim Farkas, and Ty Tuff.
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Contents
Chapter
1 Taming wildlife disease: bridging the gap between science and management 1
1.1 Why manage wildlife diseases? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Assessing theory application in WDM literature . . . . . . . . . . . . . . . . . . . . . 4
1.2.1 Systematic search protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.4 Overcoming challenges to theory-based management . . . . . . . . . . . . . . . . . . 7
1.4.1 Bringing Together Academics and Managers: Obstacles and Opportunities . 7
1.4.2 Meeting the Needs of Managers and Academics . . . . . . . . . . . . . . . . . 9
1.4.3 Making Theory Explicit Through Mathematical Modelling . . . . . . . . . . . 10
1.4.4 Cautionary Notes and Limitations . . . . . . . . . . . . . . . . . . . . . . . . 11
1.4.5 New Approaches to Reducing Host Susceptibility: Co-infection Dynamics
and Probiotics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.4.6 Improving Transmission Interventions in Populations . . . . . . . . . . . . . . 13
1.4.7 Community Matters: Predators, Competitors and Multi-host Parasites . . . . 15
1.4.8 Evolutionary Responses to Management: A Black Box? . . . . . . . . . . . . 16
1.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2 Does life history mediate changing disease risk when communities disassemble? 22
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
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2.2 Determinants of Extirpation Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.3 Determinants of Host Competence . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.4 Covariance Between Extirpation Risk and Host Competence . . . . . . . . . . . . . . 26
2.5 Exploring the Consequences of Host Competence-Extirpation Risk Relationships . . 27
2.5.1 Model structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.6 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.7 Discussion and future directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.8 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.9 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3 Integrating occupancy models and structural equation models to understand species occur-
rence 44
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.2 Study system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.3 Data collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.4 Conceptual model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.5 Model formalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.6 Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
3.7 Model assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
3.8 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.8.1 Parameter recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.8.2 Empirical results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.9 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
3.10 Management implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.10.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
4 Multilevel models for the distribution of hosts and symbionts 69
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
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4.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
4.3 Case study: amphibian communities and their parasites . . . . . . . . . . . . . . . . 75
4.4 Parameter estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
4.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
4.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
5 Species trait prediction via phylogenetic latent factors 86
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
5.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
5.2.1 Data description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
5.2.2 Model structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
5.2.3 Parameter estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
5.2.4 Evaluating predictive performance . . . . . . . . . . . . . . . . . . . . . . . . 91
5.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
5.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
6 Host diversity begets symbiont diversity but reduces symbiont transmission 102
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
6.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
6.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
6.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
Bibliography 121
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Tables
Table
1.1 Selected theoretical concepts in disease ecology . . . . . . . . . . . . . . . . . . . . . 21
2.1 Parameter definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35