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Mixed temperate forests are the dominant ecosystem in eastern North America, Europe, and East Asia (Defries & Townshend, 1999; Friedl et al., 2002; Hansen et al., 2003) and they represent one of the most altered biomes on the planet (Wade et al., 2003). Temperate forests are expected to face significant further changes in composition related to global environmental change, including climate warming (Barbler et al., 2006; Iverson & Prassad, 1998), human-induced land change (Sala et al., 1986), and altered disturbance regimes (Dale et al., 2001). While these disturbance dynamics occur at landscape to global scales (Turner et al., 2001), the biophysical response to change is primarily a function of the physiological characteristics of individual tree species (Aber et al., 2001; Hansen et al., 2001). Monitoring and analysis of vegetative dynamics, therefore, requires characterization of mixed temperate forest composition at fine categorical detail over landscape and regional scales.
Species distributions in temperate forest ecosystems are notoriously complex and difficult to map due to both ecological and instrumental reasons. Gradients in dominant tree species are often not significant at the scale of stands (Masaki et al., 1992) or even ecoregions (McDonald et al., 2005), as ubiquitous generalist species fill numerous niches (Brokaw & Busing, 2000). Meanwhile, the ability to distinguish individual forest species using medium or coarse resolution satellite data is severely constrained by the spectral similarity of species and the mixed species composition within individual grid cells (Metzler & Sader, 2005; Woodcock & Franklin, 1989; Woodcock et al., 1994). High-spatial and high-spectral resolution sensors allow for individual tree crown identification (Lamar et al., 2005; Leckie et al., 2005) and leaf chemical differentiation (Martin et al., 1997; Pontius et al., 2005), respectively, but the spatial extent of these efforts is severely limited by resource and time costs (Fuller, 2006; Wulder & Nelson, 2003).
Species distribution modeling (SDM) is an alternative approach for estimating species distributions which relies on quantifying relationships between observed species distributions and environmental variables based on landscape ecological theory (Franklin, 1995). Advances in modeling techniques over the last decade, particularly through the integration of GIS platforms with semi-parametric and non-parametric modeling techniques, have expanded the range of applications using SDM from those involving individual charismatic species to more complex, landscape mapping exercises (Elith & Leathwick, 2009). Increasingly, the approach has been used for mapping species composition in complex temperate forest landscapes characterized by more shallow environmental gradients and greater human impacts (Pearson et al., 2004; Tasser et al., 2007; Taverna et al., 2005).
Species distribution models generally assume species are in equilibrium with their environments, or at least at a quasi-equilibrium where change is slow relative to the lifespan of the biota (Austin, 2007). However, land use conversion and other human alternations of ecosystems significantly alter species-environment relationships (Bellemere & Foster, 2002; Foster, 2002). The role of human activities in shaping the distribution of forest species in the northeastern US is well-established (Hall et al., 2002), though studies have generally been limited to plot level analyses and have not been used to generate landscape scale distribution estimates. European deforestation goes back much further in time with several phases of abandonment and reforestation (Hermy & Verheyen, 2007), and numerous studies have demonstrated the effects of human land use in shaping the complex ecological landscape in this region (Koerner et al., 1997; Thuiller et al., 2004). Other studies have demonstrated similar patterns in temperate forest regions around the world (Ito et al., 2004; Vila & Pujadas, 2001). Recruitment and dispersal lead to a new forest composition, and species establish a new quasi-equilibrium with the human-altered landscape (Benjamin et al., 2005; Hermy & Verheyen, 2007). Including past land use as a predictor variable in species distribution models in temperate regions therefore is critical.