US-IALE 2018

AUTHORS: Kathryn C. Baer *, Andrew N. Gray – US Forest Service Pacific Northwest Research Station

ABSTRACT: A central question in landscape ecology concerns the environmental determinants of species distributions and the scale at which these determinants act. This question is of particular importance when attempting to predict the distribution of invasive species. Biogeographical theory upon which distribution modeling techniques are built predicts that abiotic constraints are of primary importance at the landscape scale, while biotic resistance or facilitation are likely to primarily impact a species’ local distribution. However, tests of this theory have yielded equivocal results. In this study, we utilized observational data collected on over 9,000 plots from 2004-2011 in Washington, Oregon, and California to identify and evaluate the relative importance of correlates of the presence of Bromus tectorum, Cirsium vulgare, and Rubus armeniacus across spatial scales. Contrary to predictions that biotic constraints should not affect distribution at this level, the landscape-scale presence of all three invasive species was strongly correlated with aspects of both the biotic and abiotic environment. Proximity to the nearest road was more strongly predictive of C. vulgare and R. armenicus presence at the landscape than the local scale, indicating dispersal limitation of these species’ geographic distributions. Several abiotic conditions such as annual precipitation showed a stronger relationship with local- than landscape-scale patterns of invasive species presence. Aspects of the local biotic environment including forest vegetation cover and grazing history were also more important at the local level, providing a measure of support for the prediction of biogeographical theory that interactions such as biotic resistance and herbivory are likely to be more important in determining local than landscape-level distributions. Our results suggest that the incorporation of biotic variables and dispersal limitation into the construction of distribution models, particularly for invasive species, is likely substantially improve the accuracy of their predictions.