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Filters: Extensions: Citation (X) > partyWithName: Tyler Wagner (X)

Folders: ROOT > ScienceBase Catalog > National and Regional Climate Adaptation Science Centers > National CASC > FY 2009 Projects ( Show direct descendants )

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Abstract (from http://www.tandfonline.com/doi/abs/10.1080/00028487.2012.734892#.VDw7ExYXNyg): Predicting the distribution of native stream fishes is fundamental to the management and conservation of many species. Modeling species distributions often consists of quantifying relationships between species occurrence and abundance data at known locations with environmental data at those locations. However, it is well documented that native stream fish distributions can be altered as a result of asymmetric interactions between dominant exotic and subordinate native species. For example, the naturalized exotic Brown Trout Salmo trutta has been identified as a threat to native Brook Trout Salvelinus fontinalis in the eastern...
Climate change is expected to result in widespread changes in species distributions (e.g., shifting, shrinking, expanding species ranges; e.g., Parmesan and Yohe 2003), especially for freshwater fish species (Heino et al. 2009). Although anglers and other resource users could be greatly affected by changes in species distributions, predicted changes are rarely reported in ways that can be easily understood by the general public. In contrast, climate science that more directly affects human welfare or livelihoods is often more readily communicated to the general public because it is of greater concern or closely related to everyday life. Read More at http://news.fisheries.org/translating-climate-change-effects-into-everyday-language-an-example-of-more-driving-and-less-angling/.
Abstract (from http://www.sciencedirect.com/science/article/pii/S0022169414003990#): Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May-October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover...