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Journal Article: Combining a Bayesian nonparametric method with a hierarchical framework to estimate individual and temporal variation in growth, Sigourney et al. 2012
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Sigourney, D. B., S. B. Munch, and B. H. Letcher. 2012. Combining a Bayesian nonparametric method with a hierarchical framework to estimate individual and temporal variation in growth. Ecological Modelling 247:125–134.
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Forecasting Changes in Aquatic Systems and Resilience of Brook Trout
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Journal Article: Quantifying the uncertainties of hydrology response under climate change, Steinschneider et al. 2012
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Steinschneider, S., A. Polebitski, C. Brown, and B. H. Letcher. 2012. Toward a statistical framework to quantify the uncertainties of hydrologic response under climate change. Water Resources Research 48:W11525.
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Forecasting Changes in Aquatic Systems and Resilience of Brook Trout
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Journal Article: Sampling strategies for estimating brook trout effective population size, Whiteley et al. 2012
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Whiteley, A. R., J. A. Coombs, M. Hudy, Z. Robinson, K. H. Nislow, and B. H. Letcher. 2012. Sampling strategies for estimating brook trout effective population size. Conservation Genetics.
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Forecasting Changes in Aquatic Systems and Resilience of Brook Trout
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Journal Article: Spatial variability in survival of adult brook trout within two intensively surveyed headwater stream networks
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Article
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Forecasting Changes in Aquatic Systems and Resilience of Brook Trout
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Journal Article: Modeling structured population dynamics using data from unmarked individuals
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Article
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Forecasting Changes in Aquatic Systems and Resilience of Brook Trout
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Journal Article: Fragmentation and patch size shape genetic structure of brook trout populations
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Article
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Forecasting Changes in Aquatic Systems and Resilience of Brook Trout
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Journal Article: Environmental Factors Affecting Brook Trout Occurrence in Headwater Stream Segments
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We analyzed the associations of catchment-scale and riparian-scale environmental factors with occurrence of Brook Trout Salvelinus fontinalis in Connecticut headwater stream segments with catchment areas of <15 km2 hierarchical Bayesian approach was applied to a statewide stream survey data set, in which Brook Trout detection probability was incorporated and statistical significance of environmental covariates was based on 95% credible intervals of estimated coefficients that did not overlap a value of zero. Forested land at the catchment scale was the most important covariate affecting Brook Trout occurrence; i.e., heavily forested catchments with corresponding low levels of developed and impervious land area were more likely to be occupied by Brook Trout. Coarse surficial geology (an indicator of groundwater potential) and stream slope had significantly positive effects on occurrence, whereas herbaceous plant cover and wetland and open water area had significantly negative effects. Catchment-scale and riparian-scale covariates were highly correlated in many instances, and no riparian-scale covariate was retained in the final model. Detection probability of Brook Trout at the stream-segment scale was high (mean, 0.85). Our model had a high predictive ability, and the mean value of receiver operating characteristic area under the curve was 0.80 across 100 leave-some-out iterations. The fine spatial grain of this study identified patches of suitable stream habitat for Brook Trout in Connecticut, particularly in the northwestern part. Our analysis revealed a more optimistic status of Brook Trout in Connecticut than did a coarser-grained analysis across the USA.
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Forecasting Changes in Aquatic Systems and Resilience of Brook Trout
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Document: 2012 April-June Quarterly Report - Coastal & Marine Classification
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2013 April-June Quarterly Report (2nd Quarter) - Coastal & Marine Classification
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Application of the Coastal and Marine Ecological Classification Standards (CMECS) to the Northeast
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Image: Seabed Forms & Depth
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NAMERA Seabed Forms & Depth Crosswalked to CMECS Geoform
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Application of the Coastal and Marine Ecological Classification Standards (CMECS) to the Northeast
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2013 April-June Quarterly Report - Northeast Vulnerability Assessment
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2013 April-June Quarterly Report (2ndQuarter) - Northeast Regional Vulnerability Assessment for Species Incorporating the NatureServe Climate Change Vulnerability Index
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Climate Change Vulnerability Index for Northeast species