Abstract
Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential for non-climate aspects of the environment to pose a constraint to range expansion under climate change.
Highlights
Climate is a strong predictor of plant species distribution at regional and continental scales, and climate change is expected to lead to range shifts [1]
When abiotic predictors other than climate are included in species distribution models, they are often those that can be interpreted across large expanses/grain sizes, such as the ones derived from digital elevation models, generalized geological characteristics, or satellite imagery [2]–[4]
Because there was no great difference between statistical models, the rest of the results are presented for the average of the four models
Summary
Climate is a strong predictor of plant species distribution at regional and continental scales, and climate change is expected to lead to range shifts [1]. Recent studies have shown that including edaphic variables, along with climate variables, can greatly influence predicted species distribution even at large regional extents, with important consequences for predictions of range expansion or contraction under climate change [7]–[11]. As these studies have focused on a few woody species and grasses, it is recognized that this work needs to be extended to a larger suite of species, growth-forms, and regions since it cannot be assumed that all species would respond to climatic or edaphic gradients uniformly [10], [12], [13]
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