Published online by Cambridge University Press: 05 June 2014
Introduction
One of ecology’s fundamental pursuits centres on explaining controls over the distribution of species. Interest in species distributions is also increasing in the context of global change. There is a growing emphasis on providing information to decision-makers on where to protect and restore ecosystems and the species they harbour. Nowhere does this seem more obvious, or more pressing, than in tropical forests. Land-use change continues to strike deep into tropical forest regions, and climate change has come to the forefront in tropical forest conservation and planning. Temperature, precipitation and other climatic factors are shifting in some regions, or they are becoming highly variable (Cox et al. 2004; Williams, Jackson & Kutzbach 2007), and these changes are placing species in novel conditions that will force them to adapt, move or die (Asner, Loarie & Heyder 2010; Loarie et al. 2009).
We currently have few tools for mapping species distributions in tropical forests under these changing conditions, and our ability to monitor distributional changes remains limited despite their critical importance to ecology and conservation. Today, our understanding of species distributions comes from contrasting, and geographically limited, information sources. On the one hand, we have incredibly dense information at small scales of up to 50 hectares or so (Condit et al. 2005; Hubbell & Foster 1986). This information is key to understanding local-scale community patterns (Harms et al. 2001), but sparsely distributed plots cannot resolve ecological and biogeographic processes operating at the scales of long-range dispersal, migration or landscape evolution. On the other hand, we have longer-range, transect-based information on species occurrence, which does not provide the comprehensive inventories required for ecological modelling, although it is critical to basic conservation planning (http://fieldmuseum.org/explore/department/ecco). Emerging satellite-based methods, especially when combined with field observations, are beginning to fill in the geographic void with predictions of community patch-matrix patterns (Higgins et al. 2011; Turner et al. 2003), but current approaches do not constitute direct measurements of species distributions or diversity levels. With mainstream technologies, it is not possible to monitor spatially explicit change in species distributions and biological diversity, which is likely to be non-random over landscape, regional and global scales.
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