Optimal bioeconomic management of changing marine resources Emily Alison Moberg

161 Pages·2016·6.15 MB·English

Optimal bioeconomic management of changing marine
resources
by
Emily Alison Moberg
B.S., Massachusetts Institute of Technology (2011)
Submitted to the MIT-WHOI Joint Program in Oceanography and Applied Ocean
Science and Engineering
in partial fulfillment of the requirements for the degree of
Doctor of Philosophy
at the
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
and the
WOODS HOLE OCEANOGRAPHIC INSTITUTION
September 2016
○c 2016 Emily A. Moberg
All rights reserved.
The author hereby grants to MIT and WHOI permission to reproduce and to
distribute publicly paper and electronic copies of this thesis document in whole or in
part in any medium now known or hereafter created.
Signature of author................................................................
MIT-WHOI Joint Program in Oceanography and Applied Ocean Science and
Engineering
Massachusetts Institute of Technology
& Woods Hole Oceanographic Institution
July 21, 2016
Certified by........................................................................
Dr. Michael G. Neubert
Senior Scientist
Woods Hole Oceanographic Institution
Thesis Supervisor
Accepted by.......................................................................
Dr. Ann Tarrant
Chairman, Joint Committee for Biological Oceanography
Massachusetts Institute of Technology
Woods Hole Oceanographic Institution
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Optimal bioeconomic management of changing marine resources
by
Emily Alison Moberg
Submitted to the MIT-WHOI Joint Program in Oceanography and Applied Ocean Science
and Engineering
Massachusetts Institute of Technology
& Woods Hole Oceanographic Institution
on July 21, 2016, in partial fulfillment of the
requirements for the degree of
Doctor of Philosophy
Abstract
Marine populations are increasingly subjected to changing conditions whether through har-
vest or through broad-scale habitat change. Historically, few models have accounted for
such trends over time, and even fewer have been used to study how trends affect optimal
harvests.
I developed and analyzed several models that explore, first, endogenous change caused
by harvest and, second, exogenous change from factors (such as rising ocean temperatures)
outside harvesters’ control. In these models, I characterized the profit–or yield–maximizing
strategy when harvesting damages habitat in a multispecies fishery, when harvest creates a
selective pressure on dispersal, and when rising temperatures cause changes in vital rates.
I explore this last case in both deterministic and stochastic environments, and also allow
the harvester to learn about unknown parameters of the stock recruitment model while
harvesting. I also develop an unambiguous definition of and describe a statistical test for a
shift in a species’ spatial distribution.
My results demonstrate that optimal harvesting strategies in a changing environment
differ in important ways from optimal strategies in a constant environment.
Thesis Supervisor: Dr. Michael G. Neubert
Title: Senior Scientist
Woods Hole Oceanographic Institution
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Acknowledgments
This work was supported by NSF GRFP grant number 1122374, MIT’s Ida Green Fellow-
ship, WHOI’sOceanVentureFund, andWHOIAcademicProgramsOffice. Iamalsograte-
ful for travel support I received to attend the AARMS-Sustainability of Aquatic Ecosystem
Networks and to the BIRS Impact of climate change on biological invasions and popula-
tion distributions workshop. For Chapter 2, additional funding came from the The Seaver
Institute and the National Science Foundation (OCE-1031256) through grants awarded to
Julie Kellner and Michael Neubert. The co-authors of Chapter 3 received funding from
The Woods Hole Oceanographic Institution’s Investment in Science Fund to MGN; The
Recruitment Program of Global Experts to YL; The University of Tennessee Center for
Business and Economics Research to SL; and the U.S. National Science Foundation (NSF)
through grants OCE-1031256, DEB-1257545, and DEB-1145017 to MGN, CNH-0707961 to
GEH, DMS-1411476 to YL.
I also received incredible support during graduate school from friends and family in the
form of advice and a sympathetic ear. This work would not have been possible without the
loving support from my family–mom, dad, Maddy, and Amelia Rose. Thank you so much
for your encouragement over the years, and for the many times you have read over drafts
and listened to practice presentations.
My family away from home on Cape Cod have been the New England Ballet Theatre
and John Wesley United Methodist church. Being a part of these wonderful communities
has been an integral part of keeping me grounded and sane while working on this thesis.
Iwouldalsoliketothankmycommitteeandlab-mates, whohaveprovidedanincredible
amount of support, advice, and feedback on this thesis from the nascent versions. They
have also provided travel funding for conferences and collaboration; this work and my grad-
uate experience would have been poorer without any of them. My lab-mates in particular
answered my many questions and were great inspirations for me.
Finally, I would like to thank Mr. Samilenko for inspiring my interest in environmental
science and pushing me to become the best scholar I can be and to the late Mr. Malkovsky
who shared his infectious love of science and encouraged me always to achieve my dreams.
MIT’s Terrascope program, Dr. Jerolmack, Dr. Adams, Dr. Hemond, Dr. Linkov, and Dr.
Sosik gave me invaluable introductions to research.
None of this would have been possible without all of the people mentioned here, and I
am eternally grateful to all of them.
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Contents
1 Introduction 11
2 Bioeconomics and biodiversity in harvested metacommunities: a patch-
occupancy approach 23
2.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.3 Patch Occupancy Framework . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4 Null Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.4.1 Null Model: Equilibria . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.4.2 Null Model: Diversity and Profit . . . . . . . . . . . . . . . . . . . . 35
2.4.3 Null Model: Spatial Management . . . . . . . . . . . . . . . . . . . . 40
2.5 Facilitation Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
2.5.1 Facilitation Model: Equilibria . . . . . . . . . . . . . . . . . . . . . . 46
2.5.2 Facilitation Model: Diversity and Profit . . . . . . . . . . . . . . . . 47
2.5.3 Facilitation Model: Spatial Management . . . . . . . . . . . . . . . . 50
2.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3 On the Bioeconomics of Marine Reserves when Dispersal Evolves 65
3.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
3.3 Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.4 Evolution of dispersal and the ESS . . . . . . . . . . . . . . . . . . . . . . . 71
3.4.1 Calculating the ESS . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
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3.4.2 Convergence stability of the ESS . . . . . . . . . . . . . . . . . . . . 74
3.5 The ESOHS and effects of evolution on optimal management . . . . . . . . 75
3.5.1 Management with reserves . . . . . . . . . . . . . . . . . . . . . . . . 78
3.5.2 Is the ESOHS economically stable? . . . . . . . . . . . . . . . . . . . 78
3.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
4 Testing for an Unambiguous Shift in a Species Distribution 89
4.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
4.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
4.3 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
4.3.1 Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
4.3.2 Statistical Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
4.4 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
4.5 Illustration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
4.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
4.7 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
5 Optimal Harvest in a Deteriorating Environment 103
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
5.2 Optimal Harvest in a Constant Environment . . . . . . . . . . . . . . . . . 106
5.3 Optimal Harvest in a Deteriorating Environment . . . . . . . . . . . . . . . 108
5.3.1 Interior Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
5.3.2 Exiting the Fishery . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
5.3.3 Qualitative Behavior of Optimal Escapement Policy . . . . . . . . . 112
5.4 Example: Beverton-Holt Stock Recruitment Model . . . . . . . . . . . . . . 113
5.4.1 Increasing density-dependent mortality rate (𝜇 ) . . . . . . . . . . . 115
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5.4.2 Decreasing fecundity (𝛼) . . . . . . . . . . . . . . . . . . . . . . . . . 115
5.5 Yield Maximizing Harvest . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
5.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
5.7 Appendix: Stochastic Case . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
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6 Adaptive managment in stationary and changing environments 127
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
6.2 Stationary Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
6.2.1 Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
6.3 Yield Maximizing Beverton-Holt Growth with Uniform, Multiplicative Shocks136
6.4 Sustainable or not? Yield Maximizing Piecewise Linear Growth Function
with Multiplicative, Uniform Shocks . . . . . . . . . . . . . . . . . . . . . . 141
6.5 Non-stationary case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
6.6 Non-stationary Yield Maximizing Beverton-Holt Model . . . . . . . . . . . 146
6.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
7 Discussion 157
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