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Harvard Forest REU Symposium Abstract 2009
- Title: Forecasting potential habitat of Tsuga canadensis under climate change using bioclimatic envelope models.
- Author: Eliza Ledwell (University of Maryland - Baltimore County)
- Abstract:
Recent climate change has already caused changes in the geographic distributions of species and range shifts are expected to be a dominant response of species to projected changes in climate during the next century. A common approach to forecasting such changes in distribution is the application of bioclimatic models. These models are attractive because they require only two, relatively easy to obtain inputs: (1) information on the distribution of the species and (2) environmental predictor variables. Despite their relative ease of parameterization, bioclimatic models do not incorporate biotic factors also known to influence species distributions, such as dispersal ability, interactions with other species, and evolutionary change and therefore their forecasts are often considered unreliable. Further, studies rarely quantify uncertainty in model forecasts. Here we employed a variety of models to assess the potential influence of climate change on the distribution of Eastern Hemlock (Tsuga canadensis). We addressed two key questions: (1) How well do models developed under current climate predict mid-Holocene distributions and vice versa and (2) How do forecasts differ between different climate change projections? Our results showed that climate is a good predictor of Hemlock distribution both at present and in the past, suggesting the bioclimatic envelopes may serve as a reasonable first approximation to the response of hemlock to climatic change. Forecasts developed from both current and past distributions of hemlock agree that its climatic range will shift in north-eastern direction in the future given no dispersal limitations. By evaluating the reliability of the species distribution models and quantifying the uncertainty associated with future range shifts, we hope to assist policy makers in making decisions about conservation plans.
- Research Category: Ecological Informatics and Modelling
