全球智库信息集成服务系统

The composition and health of forests across western North America have shown signs of change over the last half-century associated with altered climate conditions. Most models developed to predict responses to variation in climate assume that the ecological distribution of adult trees provides a sound basis for projecting potential shifts in a species’ range. Under a dynamic climate, however, recently established seedlings may more closely reflect changes in climate conditions. This study combined the simple, widely tested physiological model 3-PG with an empirical regeneration dataset, composed of 21,097 plots, to assess regional scale changes in tree species distributions across British Columbia, Canada. We geographically registered all plot locations to correspond with topographically-adjusted 1 km monthly climatic data for the period 2000-2009. By comparing the distribution of seedlings to that of mature trees present in an earlier period (1950-1975), we could assess where alterations in the environment have occurred, and the extent to which changes may make a species vulnerable to replacement in some places or likely to regenerate and migrate elsewhere. Decision tree models were developed to assess the relative importance of suboptimal temperatures, frost, soil water deficits and evaporative demand on the growth and distribution of four widely distributed species: Douglas-fir (Pseudotsuga menziesii), lodgepole pine (Pinus contorta), western larch (Larix occidentalis), and subalpine fir (Abies lasiocarpa). Tree responses varied by species, with areas suitable for lodgepole pine experiencing the largest relative increase in summer drought and areas dominated by western larch experiencing the least. Those areas modelled as suitable for species range expansions occurred 79% (SD = 16%) of the time in places where seedlings of a designated species were predicted in 2000–2009 using the regeneration dataset. We conclude that employing seedling surveys in concert with tree surveys provide valuable ecological insights when predicting species responses to climate shifts.