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We present a case-study evaluation of gillnet catches of Walleye Sander vitreus to assess potential effects of large-scale changes in Oneida Lake, New York, including disruption of trophic interactions by double-crested cormorants Phalacrocorax auritus and invasive dreissenid mussels. We used the empirical long-term gillnet time series and a negative binomial linear mixed model to partition variability into spatial and coherent temporal variance components, and we propose that variance partitioning can help quantify spatiotemporal variability and examine if variance structure differs before and after large-scale perturbation. Here, we found that average catch and total variability of catches decreased following...
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...
Poikilothermic animals comprise most species on Earth and are especially sensitive to changes in environmental temperatures. Species conservation in a changing climate relies upon predictions of species responses to future conditions, yet predicting species responses to climate change when temperatures exceed the bounds of observed data is fraught with challenges. We present a physiologically guided abundance (PGA) model that combines observations of species abundance and environmental conditions with laboratory-derived data on the physiological response of poikilotherms to temperature to predict species geographical distributions and abundance in response to climate change. The model incorporates uncertainty in...
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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/.
The number of fish collected in routine monitoring surveys often varies from year to year, from lake to lake, and from location to location within a lake. Although some variability in fish catches is expected across factors such as location and season, we know less about how large‐scale disturbances like climate change will influence population variability. The Laurentian Great Lakes in North America are the largest group of freshwater lakes in the world, and they have experienced major changes due to fluctuations in pollution and nutrient loadings, exploitation of natural resources, introductions of non‐native species, and shifting climatic patterns. In this project, we analyzed established long‐term data about...
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...
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Climate change affects the abundance and distribution of species worldwide. Poikilothermic animals comprise most species on Earth and are extremely sensitive to changes in environmental temperatures. Predicting species responses to climate change when temperatures exceed the bounds of observed data is fraught with challenges. Here, we combine empirical observations of species abundance and environmental conditions across the landscape with laboratory-derived data on the physiological response of poikilotherms to changes in temperature to predict species geographical distributions and abundance in response to climate change. We show that predicted changes in distributions, local extinction, and abundance of cold,...
    map background search result map search result map Code for Predicting climate change impacts on poikilotherms using physiologically guided species abundance models Code for Predicting climate change impacts on poikilotherms using physiologically guided species abundance models