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Predicting Population Trends Under Environmental Change: Comparing PREDICTING POPULATION TRENDS UNDER ENVIRONMENTAL CHANGE: COMPARING METHODS AGAINST OBSERVED DATA Fiona Elizabeth Bridget Spooner A thesis submitted in partial fulfilment of the requirements for the degree of: Doctor of Philosophy of University College London 2019 Primary supervisor: Prof. Richard G. Pearson Secondary supervisor: Dr Robin Freeman I, Fiona Elizabeth Bridget Spooner, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis ABSTRACT In this thesis I examine a range of approaches for predicting the impact of recent climate change and land use change on observed population trends. The thesis is split into three main parts. Firstly, I used linear mixed effects models to provide the first global assessment of the effects of environmental change on bird and mammal population trends. I find that populations have declined more rapidly in areas which have experienced rapid warming, this effect was more pronounced in bird populations. Secondly, I built habitat suitability models for 16 mammal species to explore the relationship between predicted habitat suitability and population abundance. I explored the correlations between time-series of rates of change in habitat suitability and corresponding time-series of observed population growth rates. There was little evidence to support the idea that population growth rates are directly linked to habitat suitability. However, when lagged responses are considered there is a stronger positive relationship between changes in habitat suitability and population growth rates, highlighting the importance of biodiversity time-series. Lastly, I built coupled niche-demographic (CND) models for three mammal species: Alpine ibex, brown bear and red deer. These are habitat suitability models linked with population models with dispersal mechanisms; they can be used to predict species abundance trends. CND models have been assumed have greater predictive accuracy than habitat suitability models, but there has been limited validation of CND model predictions against observed data. I found that CND models are an improvement on habitat suitability models. However, both sets of models perform relatively poorly. Simpler linear mixed effects models were able to provide more accurate estimates of average population growth. This suggests that i the high data requirements and computational resources needed to run CND models may be excessive, as currently, more parsimonious models provide better predictions of population growth rates. ii IMPACT STATEMENT In recent decades global biodiversity has faced multiple human-driven threats, leading to extinction rates being 1,000 times higher than expected. Two of the most significant threats to biodiversity are climate change and loss of habitat to anthropogenic land use. Both processes are anticipated to continue to threaten biodiversity for the foreseeable future. Understanding the patterns and processes of these threats on biodiversity is crucial to the effective conservation of populations and the consequent maintenance of ecosystem function. In this thesis I examined a range of approaches for predicting the impacts of recent climate change and land use change on observed animal population trends. I focussed on population trends of terrestrial birds and mammals, as these species tend to be well studied, and there is sufficient information available on them to build models across a spectrum of complexity. In Chapter Two I analysed the recent impacts of climate change and land use change on observed bird and mammal population trends (1950-2005), providing the first global study of the impacts of recent environmental change on vertebrate population trends. I found that both bird and mammal population trends have declined fastest in locations where mean temperature has increased most rapidly, this effect is more noticeable in birds. This work has been published in a leading international peer reviewed journal and has been presented to a range of audiences, most notably a major international conservation conference. This work was also included in the Living Planet Report (2018), a biennial report produced by WWF which receives high levels of publicity. Additionally, this work was cited in a Scientific American article – “Trump to Curb Protections as Warming Endangers Species”. iii This thesis also assesses the predictive accuracy of a novel modelling techniques by comparing predictions of population trends to observed population trends. There is potential for this technique to be used to estimate species extinction risk due to climate change, which would have major policy impact. However, this technique has not yet been validated against observed population trends and this is what I present in this thesis. The outputs of this work will be brought about through publication in high-impact journals. iv ACKNOWLEDGEMENTS First and foremost, I would like to thank my supervisors, Prof. Richard G. Pearson and Dr Robin Freeman for their support and guidance throughout the last four years. Their enthusiasm, ideas and knowledge have been invaluable, and without them this thesis this would not exist. I have been lucky to be part of two friendly and vibrant research groups, the Centre for Biodiversity and Environment Research at UCL and the Institute of Zoology. Both centres are filled with wonderful people who have ensured the last four years have passed by easily and enjoyably. This thesis is entirely dependent on several open source datasets of software packages, so I would like to extend my gratitude to everyone that contributed to each of these. In particular, this thesis would not have been possible without the Living Planet database, which has been meticulously built and curated by many excellent people at the Indicators and Assessments Unit at the Institute of Zoology, to whom I am very grateful. I’m thankful for my friends both inside and outside the office for providing advice and welcome escapes from PhD life. Special thanks to the Gigglegang, Sam Jones, Leejiah Dorward, Kate & Tom Harvey, Anthony Dancer, Paul Barnes, Dan Bayley, Sergio Henriques, Guillherme Fereira, Henry Ferguson-Gow, Heidi Ma, Harry Owen and Thalassa McMurdo Hamilton. Finally, I would like to thank my amazing girlfriend Michaela who has been an incredible support every step of the way, and my family without whom I would not have started this PhD, let alone finished it. v TABLE OF CONTENTS Predicting Population Trends Under Environmental Change: Comparing Methods Against Observed Data ....................................................................................................................... i Abstract ................................................................................................................................. i Impact Statement ................................................................................................................ iii Acknowledgements .............................................................................................................. v Chapter One: Introduction ................................................................................................... 1 Drivers of Biodiversity Loss............................................................................................. 2 Habitat Loss................................................................................................................... 2 Climate Change ............................................................................................................. 3 Interactions Between Climate Change and Habitat Loss .............................................. 4 Measuring The Impacts of Environmental Change....................................................... 5 Predicting Species Responses to Environmental Change................................................. 6 Habitat Suitability Models ............................................................................................ 6 Coupled Niche-Demographic Models ........................................................................... 7 Validating Predicted Species Responses ....................................................................... 8 Thesis Overview ............................................................................................................... 9 Chapter Two: Rapid Warming is Associated with Population Decline Among Terrestrial Birds and Mammals Globally ............................................................................................ 12 Abstract ........................................................................................................................... 13 Introduction .................................................................................................................... 13 Materials and Methods ................................................................................................... 16 Population Time Series Data ....................................................................................... 16 Climate Data ................................................................................................................ 19 Land Use Data ............................................................................................................. 19 Body Mass ................................................................................................................... 20 Protected Areas ..........................................................................................................
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