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Downloaded on 22 May 2018 CONSERVATION PRIORITIZATION AND ECOLOGY OF DATA- POOR MARINE SPECIES UNDER HUMAN PRESSURES by Xiong Zhang B.S., Chongqing University, 2010 M.Sc., The University of Chinese Academy of Sciences, 2013 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Zoology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2019 © Xiong Zhang, 2019 The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Conservation Prioritization and Ecology of Data-poor Marine Species under Human Pressures submitted by Xiong Zhang in partial fulfillment of the requirements for the degree of Doctor of Philosophy In The Faculty of Graduate and Postdoctoral Studies (Zoology) Examining Committee: Dr. Amanda Vincent Supervisor Dr. William Cheung Supervisory Committee Member Dr. Tara Martin University Examiner Dr. Mary O’Connor University Examiner Additional Supervisory Committee Members: Dr. Christopher Harley Supervisory Committee Member Dr. Sarah Gergel Supervisory Committee Member ii Abstract Securing a healthy and biodiverse ocean is vital to our human wellbeing. However, marine conservation is challenging, especially for data-poor species, whose habitats and threats are understudied. My dissertation explored how to address such challenges at two large spatial scales (in China and globally), with a focus on the little studied seahorses (Hippocampus spp.). In the first two data chapters, I explored the utility of various sources of information about species and habitat covariates in species distribution models (SDMs). My results from the first chapter showed that local ecological knowledge provided useful biogeographic data of five Chinese seahorse species to predict their distributions, which were mainly associated with ocean temperature. My second chapter at the global scale indicated that integrating citizen sciences, museum collections, and research-grade data with continuous predictors derived the best SDM models; these models predicted reliable habitat maps for 33 out of 42 species that were primarily associated with depths, proximity to macrohabitats (e.g., sponges), pH, and ocean temperature. In the third analytical chapter, I explored global threat patterns and conservation status for 42 seahorse species with two cumulative-human-impact (CHI) models (spatial and non-spatial) and random forest (RF) models. I found that human-impact indices (from the CHI models) can be used to predict conservation status at high accuracies (87% and 96%) in RF models. Applying a non-spatial CHI model derived indices better predicted conservation status, while using a spatial CHI model identified distribution patterns of threats. In the fourth data chapter, I integrated the derived biogeographic and threat maps in a novel framework to set conservation priorities for seahorse habitats in China and globally, using Marxan software. I found that the two major outputs of Marxan (i.e., selection frequency and best solution) were useful to determine feasible priority solutions at large spatial scales. iii My results identified valuable datasets and approaches to advancing ecological and conservation knowledge for data-poor marine species, an essential precursor to action for the ocean. iv Lay Summary Managing and protecting marine life requires an understanding of where species live, what threatens them and their habitats, and what we might do to help them. Seahorses are particularly charming examples of the many marine species that are little understood. I set off to study seahorses in China, where they are heavily fished, and around the world. I found we could learn most by integrating information from diverse sources, including local fishers’ knowledge, citizen science (e.g., divers’ observations), museum collections, and scientists’ knowledge and data. We then applied novel computer techniques (e.g. machine learning models and decision-making software) and considered our results from both natural and social science perspectives. This helped us find out what seahorses are threatened and allowed us to plan possible conservation action, particularly for deciding where to urge creation of protected areas. Our new methods are of value to many species and spaces. v Preface This dissertation contains four scientific papers of which I am or will be the first author. I designed the framework, scope, and question of each research chapter with my supervisor, Dr. Amanda Vincent. I was primarily responsible for conducting the research, including project planning, field work and data gathering, development of methodology, data analysis, interpretation of results, and manuscript writing. My supervisor, Dr. Amanda Vincent, guided me through all these processes, especially helping me with grant applications, project management, field work, and drafting and refining the manuscripts. My committee members, Dr. William Cheung, Dr. Sarah Gergel, and Dr. Christopher Harley also provided intellectual feedback that helped me refine my research methods and manuscript writing. For Chapter 2, Dr. William Cheung introduced me to local colleagues in China who facilitated my field work. This field work was assisted by many Chinese colleagues (see Acknowledgements). For Chapter 3, some undergraduate and graduate students at UBC worked with me to gather seahorse data from peer-reviewed literature (see Acknowledgements). My Chapters 2 and 3 have resulted in two publications: • Chapter 2: Zhang, X. and Vincent, A.C. (2017) Integrating multiple datasets with species distribution models to inform conservation of the poorly-recorded Chinese seahorses. Biological Conservation, 211, 161-171. I conceived the preliminary idea, conducted the field work, analyzed the data, and wrote the manuscript. Dr. Amanda Vincent helped me refine the idea and the manuscript. • Chapter 3: Zhang, X. and Vincent, A.C. (2018) Predicting distributions, habitat preferences and associated conservation implications for a genus of rare fishes, seahorses (Hippocampus spp.). Diversity and Distributions. https://doi.org/10.1111/ddi.12741. I conceived the preliminary idea, conducted the research and wrote the manuscript. Dr. Amanda Vincent helped me refine the idea and the manuscript. Chapters 4 and 5 will be submitted to leading journals as two co-authored papers with Dr. Amanda Vincent. vi The field work in my dissertation was approved by UBC’s Animal Care Committee Office of Research Service (A12-0288-A011) and UBC’s Human Behavioural Research Ethics Board (H12-02731). vii Table of Contents Abstract ............................................................................................................................. iii Lay Summary .................................................................................................................... v Preface ............................................................................................................................... vi Table of Contents ........................................................................................................... viii List of Tables ................................................................................................................... xii List of Figures ................................................................................................................. xiv List of Symbols ............................................................................................................. xviii List of Abbreviations ..................................................................................................... xix Acknowledgements ......................................................................................................... xx Dedication ...................................................................................................................... xxii Chapter 1: Introduction ................................................................................................... 1 1.1 Rationale ................................................................................................................................ 1 1.2 Background ........................................................................................................................... 2 1.3 Case Study ............................................................................................................................. 6 1.4 Context and Collaborators ..................................................................................................... 9 1.5 Research Questions ............................................................................................................... 9 1.6 Thesis Outline ...................................................................................................................... 10 1.6.1 Chapter 2: Integrating multiple datasets with species distribution models to inform conservation of the poorly-recorded Chinese seahorses ........................................................ 12 1.6.2 Chapter 3: Predicting distributions, habitat preferences, and associated conservation implications for a genus of data-poor species, seahorses (Hippocampus spp.) 12 1.6.3 Chapter 4: Cumulative human impact models reveal threat patterns of seahorses (Hippocampus spp.) ..............................................................................................................
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