Temperature is important to fish in determining their geographic distribution. For cooland cold-water fish, thermal regimes are especially critical at the southern end of a species' range. Although temperature is an easy variable to measure, biological interpretation is difficult. Thus, how to determine what temperatures are meaningful to fish in the field is a challenge. Herein, we used the Connecticut River as a model system and Atlantic salmon (Salmo salar) as a model species with which to assess the effects of summer temperatures on the density of age 0 parr. Specifically, we asked: (1) What are the spatial and temporal temperature patterns in the Connecticut River during summer? (2) What metrics might detect effects of high temperatures? and (3) How is temperature variability related to density of Atlantic salmon during their first summer? Although the most southern site was the warmest, some northern sites were also warm, and some southern sites were moderately cool. This suggests localized, within basin variation in temperature. Daily and hourly means showed extreme values not apparent in the seasonal means. We observed significant relationships between age 0 parr density and days at potentially stressful, warm temperatures (C23°C). Based on these results, we propose that useful field reference points need to incorporate the synergistic effect of other stressors that fish encounter in the field as well as the complexity associated with cycling temperatures and thermal refuges. Understanding the effects of temperature may aid conservation efforts for Atlantic salmon in the Connecticut River and other North Atlantic systems.
1. Species distribution modelling can be useful for the conservation of rare and endangered species. Freshwater mussel declines have thinned species ranges producing spatially fragmented distributions across large areas. Spatial fragmentation in combination with a complex life history and heterogeneous environment makes predictive modelling difficult.2. A machine learning approach (maximum entropy) was used to model occurrences and suitable habitat for the federally endangered dwarf wedgemussel, Alasmidonta heterodon, in Maryland's Coastal Plain catchments. Landscape-scale predictors (e.g. land cover, land use, soil characteristics, geology, flow characteristics, and climate) were used to predict the suitability of individual stream segments for A. heterodon.3. The best model contained variables at three scales: minimum elevation (segment scale), percentage Tertiary deposits, low intensity development, and woody wetlands (sub-catchment), and percentage low intensity development, pasture/hay agriculture, and average depth to the water table (catchment). Despite a very small sample size owing to the rarity of A. heterodon, cross-validated prediction accuracy was 91%.4. Most predicted suitable segments occur in catchments not known to contain A. heterodon, which provides opportunities for new discoveries or population restoration. These model predictions can guide surveys toward the streams with the best chance of containing the species or, alternatively, away from those streams with little chance of containing A. heterodon. 5. Developed reaches had low predicted suitability for A. heterodon in the Coastal Plain. Urban and exurban sprawl continues to modify stream ecosystems in the region, underscoring the need to preserve existing populations and to discover and protect new populations.
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