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Directions: Venue - USFWS Regional Office
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by
Jean Brennan
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published
Feb 12, 2015
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April 2015 Workshop Materials & Logistical Information
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Directions to the USFWS Regional Office - Hadley MA
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by
Jean Brennan
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published
Feb 12, 2015
File
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Stream Temperature Questionnaire PDF
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by
Jean Brennan
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published
Feb 12, 2015
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last modified
Mar 20, 2015 12:44 AM
Modelers Questionnaire [Jana Stewart Coordinating]
Brook trout Research Questionnaire [Steve Faulkner Coordinating]
Research Profile (Template) [Rachel Muir Coordinating]
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April 2015 Workshop Materials & Logistical Information
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Summary (Feb 19th) call
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by
Jean Brennan
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published
Feb 26, 2015
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last modified
Feb 27, 2015 08:20 AM
Workshop Planning Team: notes from Feb 19th call (provide feedback to JanaS).
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April 2015 Workshop Materials & Logistical Information
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Summary (Feb 26th) call
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by
Jean Brennan
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published
Feb 27, 2015
Workshop planning team coordination call notes. JS
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2014 Lecture: Forecasting changes in stream flow, temperature, and salmonid populations in Eastern U.S. as a result of climate change
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by
Jean Brennan
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published
Feb 20, 2015
Ben Letcher
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Resource Materials: Presentations
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Forecasting environmental change: modeling thermal refugia and brook trout abundance
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by
Jean Brennan
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published
May 04, 2015
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last modified
May 04, 2015 11:45 AM
Forecasting environmental change:
modeling thermal refugia and brook trout
abundance by Dr. Than Hitt
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Link to Reprint: A Model for Evaluating Stream Temperature Response to Climate Change in Wisconsin
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by
Jean Brennan
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published
Feb 12, 2015
USGS report on stream temperature modeling and climate change in Wisconsin
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A regional neural network ensemble for predicting mean daily river water temperature
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by
Jean Brennan
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published
Feb 20, 2015
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last modified
Feb 20, 2015 08:17 AM
Abstract: 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 attributes, and used the median prediction from an ensemble of 100
ANNs as our final prediction for each model. The final model included air temperature, landform attributes
and forested land cover and predicted mean daily water temperatures with moderate accuracy
as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009
(RMSE = 1.91 C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010
(RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream
reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air
temperature, and network catchment area according to sensitivity analyses. Forest land cover at both
riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature
averaged for the month of July matched expected spatial trends with cooler temperatures in
headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures
throughout a large region, while other regional efforts have predicted at relatively coarse time
steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled
rivers under current conditions and future projections of climate and land use changes, thereby providing
information that is valuable to management of river ecosystems and biota such as brook trout.
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Predicting Brook Trout Occurrence in Stream Reaches throughout their Native Range in the Eastern United States
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by
Jean Brennan
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published
Feb 20, 2015
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last modified
Feb 20, 2015 08:06 AM
Abstract
The Brook Trout Salvelinus fontinalis is an important species of conservation concern in the eastern USA. We
developed a model to predict Brook Trout population status within individual stream reaches throughout the
species’ native range in the eastern USA. We utilized hierarchical logistic regression with Bayesian estimation to
predict Brook Trout occurrence probability, and we allowed slopes and intercepts to vary among ecological
drainage units (EDUs). Model performance was similar for 7,327 training samples and 1,832 validation samples
based on the area under the receiver operating curve (»0.78) and Cohen’s kappa statistic (0.44). Predicted water
temperature had a strong negative effect on Brook Trout occurrence probability at the stream reach scale and was
also negatively associated with the EDU average probability of Brook Trout occurrence (i.e., EDU-specific
intercepts). The effect of soil permeability was positive but decreased as EDU mean soil permeability increased.
Brook Trout were less likely to occur in stream reaches surrounded by agricultural or developed land cover, and an
interaction suggested that agricultural land cover also resulted in an increased sensitivity to water temperature.
Our model provides a further understanding of how Brook Trout are shaped by habitat characteristics in the
region and yields maps of stream-reach-scale predictions, which together can be used to support ongoing
conservation and management efforts. These decision support tools can be used to identify the extent of potentially
suitable habitat, estimate historic habitat losses, and prioritize conservation efforts by selecting suitable stream
reaches for a given action. Future work could extend the model to account for additional landscape or habitat
characteristics, include biotic interactions, or estimate potential Brook Trout responses to climate and land use
changes.
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