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Novel methods improve prediction of species' distributions from occurrence data. Á/ Ecography 29: 129 Á/151. Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on(More)
Given the rate of projected environmental change for the 21st century, urgent adaptation and mitigation measures are required to slow down the ongoing erosion of biodiversity. Even though increasing evidence shows that recent human-induced environmental changes have already triggered species' range shifts, changes in phenology and species' extinctions,(More)
Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution(More)
1. Compared to bioclimatic variables, remote sensing predictors are rarely used for pre-dictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial(More)
The knowledge about potential climate change impacts on forests is continuously expanding and some changes in growth, drought induced mortality and species distribution have been observed. However despite a significant body of research, a knowledge and communication gap exists between scientists and non-scientists as to how climate change impact scenarios(More)
The usefulness of species distribution models (SDMs) in predicting impacts of climate change on biodiversity is difficult to assess because changes in species ranges may take decades or centuries to occur. One alternative way to evaluate the predictive ability of SDMs across time is to compare their predictions with data on past species distributions. We(More)
Pine mistletoe (Viscum album ssp. austriacum) is common in natural Scots pine (Pinus sylvestris L.) forests in the alpine Rhone Valley, Switzerland. This semi-parasite, which is regarded as an indicator species for temperature, increases the drought stress on trees and may contribute to the observed pine decline in the region. We recorded mistletoes on(More)
Recruitment algorithms in forest gap models are examined with particular regard to their suitability for simulating forest ecosystem responses to a changing climate. The traditional formulation of recruitment is found limiting in three areas. First, the aggregation of different regeneration stages (seed production, dispersal, storage, germination and(More)