THE VALUE OF SPECIES DISTRIBUTION MODELS AS A TOOL FOR CONSERVATION AND ECOLOGY IN EGYPT AND BRITAIN Tim Newbold, Bsc. (Hons.) Thesis submitted to the University of Nottingham for the degree of Doctor of Philosophy November 2009 Abstract Knowledge about the distribution of species is limited, with extensive gaps in our knowledge, particularly in tropical areas and in arid environments. Species distribution models offer a potentially very powerful tool for filling these gaps in our knowledge. They relate a set of recorded occurrences of a species to environmental variables thought to be important in determining the distributions of species, in order to predict where species will be found throughout an area of interest. In this thesis, I explore the development, potential applications and possible limitations of distribution models using species from various taxonomic groups in two regions of the world: butterflies, mammals, reptiles and amphibians in Egypt, and butterflies, hoverflies and birds in Great Britain. Specifically I test: 1) which modelling methods produce the best models; 2) which variables correlate best with the distributions of species, and in particular whether interactions among species can explain observed distributions; 3) whether the distributions of some species correlate better with environmental variables than others and whether this variation can be explained by ecological characteristics of the species; 4) whether the same environmental variables that explain species‘ occurrence can also explain species richness, and whether distribution models can be combined to produce an accurate model of species richness; 5) whether the apparent accuracy of distribution models is supported by ground-truthing; and 6) whether the models can predict the impact of climate change on the distribution of species. Overall the use of distribution models is supported; my models for species in both Egypt and Britain explained observed occurrence very well. My results shed some light on factors that may be important in 2 determining the distributions of species, particularly on the importance of interactions among species. As they currently stand, distribution models appear unable to predict accurately the impacts of climate change. 3 Acknowledgements Foremost, I wish to thank my fiancée, Laura, for her support and understanding throughout my PhD project. I also thank: Tom Reader, Francis Gilbert and Andrew MacColl for supervision and advice; all staff at Egypt‘s BioMAP project (Ahmed Yakoub, Alaa Awad, Muhammed Sherif, Shama Omran, Shaimaa Esa, Yasmin Safwat, Nahla Ahmed, Esraa Saber), and especially Samy Zalat, Ahmed El-Gabbas and Sherif Baha-El-Din whose efforts made the field expeditions possible; Wiebke Berg, Wael M. Shohdi, Rashed Rafaey, Ahmed Rafaey and other Egyptian field guides for help during the field expeditions; Richard Field for valuable comments on my work; Mustafa Fouda (Director of the Nature Conservation Sector, Egyptian Environmental Affairs Agency); Italian Cooperation (Debt for Development Swap) for funding the BioMAP project; Dr. Stuart Ball, Chris du Feu and Dr. Jennifer Owen for their help with the work described in Chapter 8; Malcolm Edmunds for giving me the idea for the study presented in Chapter 6; Dr. Abd El Aal Hassan and Keith Mortensen for help with GIS; all of the volunteers and scientists who contributed data to the databases used, especially the bird ringers at Treswell Wood in Nottinghamshire; and finally the reviewers who have made valuable comments on my manuscripts. My PhD was supported by the Natural Environment Research Council (grant number NER/S/A/2006/14170). 4 Publications A list of peer-reviewed publications based on the work presented in this thesis: Newbold T. (2010). Applications and limitations of museum data for conservation and ecology, with particular attention to species distribution models. Progress in Physical Geography, 34, 3-22. Newbold T., Reader T., Zalat S., El-Gabbas A. & Gilbert F. (2009). Effect of characteristics of butterfly species on the accuracy of distribution models in an arid environment. Biodiversity & Conservation, 18, 3629-3641. Newbold T., Gilbert F., Zalat S., El-Gabbas A. & Reader T. (2009). Climate-based models of spatial patterns of species richness in Egypt‘s butterfly and mammal fauna. Journal of Biogeography, 36, 2085-2095. Newbold T., Reader T., El-Gabbas A., Berg W., Shohdi, W.M., Zalat S., Baha El Din S. & Gilbert F. (in press). Testing the accuracy of species distribution models using species records from a new field survey. Oikos. 5 Contents 1. Introduction: ecological niches, distributions and species distribution modelling 7 2. General methods 45 3. Testing factors influencing distribution-model accuracy using data from real and simulated species 83 4. The effect of characteristics of species on the accuracy of distribution models for Egyptian butterfly species 112 5. Modelling patterns of species richness using species distribution models 132 6. The effect of interspecific interactions on the distribution of species 159 7. Testing the accuracy of species distribution models using new species occurrence data collected during a field survey 182 8. Testing the ability of species distribution models to predict changes in the distribution of species as a result of climate change 206 9. Final discussion 228 10. Appendices 239 11. References 262 6 Chapter 1. Introduction: ecological niches, distributions and species distribution modelling1 1.1 Abstract Statistical models which combine data on species occurrence with environmental variables to predict the distributions of species have gained prominence in ecology in recent years. Species distribution models have their grounding in niche theory. In the first part of this chapter, I provide a very brief review of niche theory with some discussion of recent developments. In the second part, I introduce species distribution models, their relationship to niche theory and some of the challenges associated with them. I review some of the applications for which distribution models have been used in the past, and the relative merits and limitations of these applications. Finally, I introduce records of species occurrence from museums, natural history collections and literature as a valuable source of data on species‘ distributions, discussing some of the problems with data from these sources and the implications of these problems for developing distribution models. 1 Parts of this chapter were used in a paper published in Progress in Physical Geography 7 1.2 Niche theory 1.2.1 Formulation of the niche concept Joseph Grinnell (1917, 1924) is credited with first using the term ―niche‖ to describe the environmental conditions within which a species can survive and reproduce; these could include abiotic factors, such as temperature or rainfall, or interactions with other species (Grinnell 1924; Vandermeer 1972). Charles Elton (1927), on the other hand, saw a species‘ niche as its place or role within the ecological community, placing less emphasis on the abiotic conditions and more on relationships with other species (Vandermeer 1972) and the impact that species have on the environment (Leibold 1995; Chase & Leibold 2003). Niche theory was first properly formalized by G Evelyn Hutchinson (1957). He described a species‘ fundamental niche as a space in an ‗n-dimensional hypervolume‘ defined by numerous (abiotic) environmental axes. Hutchinson‘s (1957) fundamental niche describes the environmental conditions within which a species could survive and reproduce in the absence of interactions with other species (Figure 1.1a). The realized niche describes the environmental conditions within which a species actually lives, taking into account interactions with other species (Figure 1.1b). Species distribution models deal with Grinnellian or Hutchinsonian fundamental niches, rather than Eltonian niches (Peterson 2006), and so I focus on these here. 8 o o o o o o o o o o a) o o o b) o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o + o + + + o o + + + + o o o + + + o o + o o o o + + + o o + + o o o + o o + o + + + + o o v + + o o o v + + o o o 2 o + + 2 o + + o + + o + o + + o o + + o o o o o + o o o o + o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o v1 v1 o o o o o o o o o o c) o o o d) o o o o o o o + o + o o o o o o o o o + o o o o o o o o o o o + o + o o o o + + + o o o + + + o o o + + + + o + o + o o + o o o o + + + o o + o + + o + o + + + + v o + o o o v + + o + o 2 o + o 2 o + + o + + o + + + o o o + + o o o o o + o o o + + o o o + o o o o o o o o o o o o o o o o + o + o o o o o o o o o o o o o o o o o o o o o o o o o o o + o o v1 v1 Figure 1.1 – Various plausible relationships between the fundamental niche, shown here by dark grey shading, and the actual distribution of species, shown here as hypothetical instances of species presence (+) or absence (o), modified from Pulliam (2000). For simplicity, the niche is assumed to be a simple function of two environmental variables, v1 and v2: (a) the species occupies its entire fundamental niche; (b) the presence of a superior competitor (light grey shading) excludes the species from part of its fundamental niche, leaving it to occupy the realized niche; (c) dispersal limitation means that the species is unable to reach all environmentally-suitable areas; (d) continued migration from areas of suitable habitat (sources) allows the species to persist in areas of unsuitable habitat (sinks).