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Providing students with a solid understanding of core ecological concepts while explaining how ecologists raise and answer real-world questions, this second edition weaves together classic and cutting-edge case studies to bring the subject to life. It is fully updated throughout, including two chapters devoted to climate change ecology, along with extensive coverage of disease ecology, and has been designed specifically to equip students with the tools to analyze and interpret real data. Each chapter emphasizes the linkage between observations, ideas, questions, hypotheses, predictions, results, and conclusions. Additional summary sections describe the development and evolution of research programs in each of ecology's core areas, providing students with essential context. Integrated discussion questions, along with end-of-chapter questions, encourage active learning. These are supported by online resources including tutorials that teach students to use the R programming language for statistical analyses of data presented in the text.
There is a long history of describing communities in ecology. It is now time to develop a general predictive framework for this discipline. The goal is to simultaneously provide a consistent theoretical framework to guide research and a practical framework to guide conservation of wild landscapes. We propose that this framework has four key elements: the species pool vector P, the local community vector C, a vector of environmental filters E, and a vector of functional traits T. The central challenge of community ecology is to predict the species composition of any community C, using prior knowledge of P, E and T. Common filters include flooding, fire and herbivory. Each community C is a subset of the regional species pool P and is the result of filtering that matches species’ traits to the local environmental conditions. Dispersal, competition and time are also important in community assembly.
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