Incorporating Costs and Processes into Systematic Conservation Planning in a Biodiversity Hotspot Jonathan Michael Halsey Green Clare College A dissertation submitted for the degree of Doctor of Philosophy April 2012 2 Declaration This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except where specifically indicated in the text. It does not exceed 60,000 words in length and no part has been submitted for another degree or diploma. Signed: ………………………. Jonathan Green i ii Summary Given inadequate budgets with which to stem the rapid destruction of biodiversity, conservationists must set clear priorities for action. Systematic Conservation Planning (SCP) is an approach that uses spatially explicit data to identify areas that meet conservation targets efficiently, usually focusing on species’ representation. Only rarely is the long-term persistence of species taken into account and the costs of conservation are usually ignored. I use the Eastern Arc Mountains of Tanzania as a study area to develop novel methods for creating and integrating the necessary data to fill these gaps in a developing country context. These mountains exhibit exceptional biodiversity but are also highly imperilled. I describe the biological data that I assembled for use in a series of SCP analyses. Fine- scale distribution models for species were mapped for over 500 animal and plant species of conservation concern. I then mapped Ecological and Evolutionary Processes (EEPs), which are crucial to species’ persistence and contribute to healthy ecosystem functioning. My analyses show how the inclusion of biological processes can significantly alter priorities when compared to prioritisation using information on species’ presence alone. Despite their importance, EEPs are often excluded from SCP. This is largely due to the difficulties involved in expressing them quantitatively and in optimising reserve networks to represent them at a minimum cost. This reluctance should be challenged, otherwise reserve networks will, over time, lose those elements of biodiversity that they were established to conserve. I also investigate conservation costs. Despite chronic underfunding for conservation and the recognition that funds must be invested wisely, few data on the costs of conservation are available at the spatial scales needed to inform local site management. I present methods for estimating and mapping protected area management costs, wildlife damage cost and the opportunity costs of conservation. Costs are highest in densely populated and cultivated areas, particularly in the north, whereas large areas of the more remote mountain blocs in the south show lower costs. Integrating these data into SCP demonstrates that using real cost data (rather than assuming that cost per unit area is homogenous) alters priorities and increases the efficiency of conservation within the Eastern Arc. Importantly, the efficiency savings realised through using cost, rather than area, to prioritise conservation efforts were found to be most pronounced when budgets were limited so that not all conservation targets could be met. iii iv Acknowledgements First of all, I would like to thank my supervisors - Andrew Balmford for his energy and enthusiasm and Kerry Turner for his imperturbability and calm. They formed a conscientious and supportive ministering team and I am sure that they are as relieved as I am that this is all over. I have learnt a lot through observing them and through their teaching and I will always be grateful to their generosity of time and spirit which benefited me so much. I am also grateful to my PhD advisors David Aldridge and Rhys Green. I am thankful to the Miriam Rothschild foundation for funding my studentship, while the Department of Zoology, the Weis-Fogh fund, the Higgins fund and Clare College all gave generously, allowing me to conduct my fieldwork and to attend conferences. For logistical and financial support during data collection, I thank the Valuing the Arc project, funded by the Leverhulme Trust and WWF-Tanzania. I am also extremely grateful to the Cambridge Philosophical Society and the Zoology department for granting me extra funding during the critical phase of finishing up. Without this, the final months would have been a much greater struggle. During some of this time I was hosted at the Centre for Macroecology, Evolution and Climate Change in Copenhagen. I am grateful to Klaus Dons, Jonas Geldman and Carsten Rahbek for making me feel so welcome and for teaching me about coffee. Coming into the office was rarely a chore and for that I am indebted to the people that created the great sense of community. In particular to my office mates but also to all of the Conservation Science Group, Aquatic Ecology Group, Large Animal Research Group and the Tropical Biology Association for their conversations and company through many months. Special thanks to Clive Nuttman, who has just walked in with a bottle of champagne as I sit finishing my acknowledgements and also to Aaron Lobo and Vera Warmuth who have been great friends. There are many members of the Zoology Department that have helped me but I would particularly like to thank Linda Wheatley, Alice Nelson and Julian Jacobs for going the extra mile to make my life easier. I am extremely fortunate to have been a part of the Valuing the Arc Project and I would like to thank all of those involved with it. I am especially grateful to Brendan Fisher and Kerry Turner for stirring my interest in environmental economics. The following individuals gave specific help. In statistics, programming and GIS, I appreciate the help given by Sabri Al-Safi, Tatsuya Amano, Charlotte Chang, Rhys Green, Phil Platts, Mathieu Rouget and Ruth Swetnam. I also appreciate the following for their substantial help and guidance in using and creating species distribution maps, their generosity in giving their time freely and for the use of their data: Federica Chiozza, Francesco Ficetola, Jon Fjeldså, v Louis Hansen, Kim Howell, Moreno Di Marco, Philip Platts, Carlo Rondinini and Steve Spawls. I would also like to thank members of the African Elephant Database for making their data available. I am extremely grateful to Neil Burgess, Nike Doggart, Jon Fjeldså, Louis Hansen, Kim Howell, Seif Madoffe, Stephen Mmasi, Pantaleo Munishi, Evarist Nashanda, William Newmark, Niels Strange and Ruwa-Aichi Temu for various information and discussions regarding the biological processes in the Eastern Arc Mountains. During several months of fieldwork, I was fortunate in having reliable friends and colleagues. In particular, I am indebted to Alex Lowassary, whose driving was secondary only to his charisma in ensuring the project’s success. It was a pleasure to work alongside Joseph Makero and Neema Robert and I am deeply thankful to them and to the very many farmers, village committees and protected area staff who all contributed time and data with such great patience. I would also like to express gratitude to the Tanzania Commission for Science and Technology and the Forestry and Beekeeping Division for their assistance - particularly to Felician Kilahama and Luciana Mshana for encouragement and support. Thank you to Neil Burgess, Charlotte Chang, Ben Phalan, Phil Platts and Marije Schaafsma for reading through thesis chapters – often at short notice. Thank you also to three anonymous reviewers for constructive comments on earlier versions of chapter four, accepted as a manuscript to Biological Conservation. I have always had the unwavering support of my family and to them I am grateful for giving me the opportunity to take the paths that I have chosen. My interest in the environment and my years of education are a tribute to my parents in particular. Last of all, I thank Kate. She has done all of the above and more and even when I have been a miserable git, she has, mostly, responded with patience and kindness. She is a joy to be with and I cannot thank her enough. vi Acronyms and abbreviations AICc: Akaike’s Information Criterion with a correction for finite sample sizes AO: Area of Occurrence AUC: Area Under the Curve BLM: Boundary Length Modifier BBC: British Broadcasting Corporation CBNRM: Community-Based Natural Resource Management CFPF: Conservation Feature Penalty Factor CR: Critical (threat list status) DEM: Digital Elevation Model E: Endemic EAM: Eastern Arc Mountains EAMCEF: Eastern Arc Mountains Conservation Endowment Fund EEP: Ecological and Evolutionary Process EN: Endangered (threat list status) EO: Extent of Occurrence ESH: Extent of Suitable Habitat FAO: Food and Agriculture Organization FBD: Forestry and Beekeeping Division GAA: Global Amphibian Assessment GIS: Geographic Information System GMA: Global Mammal Assessment GR: Game Reserve ha: Hectare HSI: Habitat Suitability Index IQR: Inter-Quartile Range IUCN: International Union for the Conservation of Nature JFM: Joint Forestry Management kg: Kilogramme km: Kilometre LAFR: Local Authority Forest Reserve LC: Least Concern (threat list status) m: Metre MNRT: Ministry for Natural Resources and Tourism NE: Near-Endemic vii NFR: National Forest Reserve NP: National Park NPV: Net Present Value nr: Not recognised (threat list status) NR: Nature Reserve NT: Near-Threatened (threat list status) PU: Planning Unit ROC: Receiver Operating Characteristic RR: Restricted Range RVI: Relative Variable Importance SCP: Systematic Conservation Planning s.d.: Standard deviation SPF: Species’ Penalty Factor TANAPA: Tanzania National