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Detecting Temporal Trends in Freshwater Fisheries Surveys: Statistical Power and the Important Linkages between Management Questions and Monitoring Objectives
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by T.Wagner et al., ABSTRACT: Monitoring to detect temporal trends in biological
and habitat indices is a critical component of fisheries
management. Thus, it is important that management objectives
are linked to monitoring objectives. This linkage requires a
definition of what constitutes a management-relevant “temporal
trend.” It is also important to develop expectations for the
amount of time required to detect a trend (i.e., statistical power)
and for choosing an appropriate statistical model for analysis.
We provide an overview of temporal trends commonly encountered
in fisheries management, review published studies that
evaluated statistical power of long-term trend detection, and
illustrate dynamic linear models in a Bayesian context, as an
additional analytical approach focused on shorter term change.
We show that monitoring programs generally have low statistical
power for detecting linear temporal trends and argue that
often management should be focused on different definitions of
trends, some of which can be better addressed by alternative
analytical approaches.
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Fall and Early Winter Movement and Habitat Use of Wild Brook Trout
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Abstract
Brook Trout Salvelinus fontinalis populations face a myriad of threats throughout the species’ native range in
the eastern United States. Understanding wild Brook Trout movement patterns and habitat requirements is essential
for conserving existing populations and for restoring habitats that no longer support self-sustaining populations.
To address uncertainties related to wild Brook Trout movements and habitat use, we radio-tracked 36 fish in a
headwater stream system in central Pennsylvania during the fall and early winter of 2010–2011. We used generalized
additive mixed models and discrete choice models with random effects to evaluate seasonal movement and habitat
use, respectively. There was variability among fish in movement patterns; however, most of the movement was
associated with the onset of the spawning season and was positively correlated with fish size and stream flow. There
was heterogeneity among fish in selection of intermediate (0.26–0.44 m deep) and deep (0.44–1.06 m deep) residual
pools, while all Brook Trout showed similar selection for shallow (0.10–0.26 m) residual pools. There was selection for
shallow residual pools during the spawning season, followed by selection for deep residual pools as winter approached.
Brook Trout demonstrated a threshold effect for habitat selection with respect to pool length, and selection for pools
increased as average pool length increased up to approximately 30 m, and then use declined rapidly for pool habitats
greater than 30 m in length. The heterogeneity and nonlinear dynamics of movement and habitat use of wild Brook
Trout observed in this study underscores two important points: (1) linear models may not always provide an accurate
description of movement and habitat use, which can have implications for management, and (2) maintaining stream
connectivity and habitat heterogeneity is important when managing self-sustaining Brook Trout populations.
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Modeling spatially varying landscape change points in species occurrence thresholds
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by T. Wagner and S. Miday, Abstract. Predicting species distributions at scales of regions to continents is often necessary, as largescale
phenomena influence the distributions of spatially structured populations. Land use and land cover
are important large-scale drivers of species distributions, and landscapes are known to create species
occurrence thresholds, where small changes in a landscape characteristic results in abrupt changes in
occurrence. The value of the landscape characteristic at which this change occurs is referred to as a change
point. We present a hierarchical Bayesian threshold model (HBTM) that allows for estimating spatially
varying parameters, including change points. Our model also allows for modeling estimated parameters in
an effort to understand large-scale drivers of variability in land use and land cover on species occurrence
thresholds. We use range-wide detection/nondetection data for the eastern brook trout (Salvelinus
fontinalis), a stream-dwelling salmonid, to illustrate our HBTM for estimating and modeling spatially
varying threshold parameters in species occurrence. We parameterized the model for investigating
thresholds in landscape predictor variables that are measured as proportions, and which are therefore
restricted to values between 0 and 1. Our HBTM estimated spatially varying thresholds in brook trout
occurrence for both the proportion agricultural and urban land uses. There was relatively little spatial
variation in change point estimates, although there was spatial variability in the overall shape of the
threshold response and associated uncertainty. In addition, regional mean stream water temperature was
correlated to the change point parameters for the proportion of urban land use, with the change point value
increasing with increasing mean stream water temperature. We present a framework for quantify
macrosystem variability in spatially varying threshold model parameters in relation to important largescale
drivers such as land use and land cover. Although the model presented is a logistic HBTM, it can
easily be extended to accommodate other statistical distributions for modeling species richness or
abundance.
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NorEaST Workshop - December 2014
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Co-hosted by the US Geological Survey, Michigan State University and University of Wisconsin – Platteville. This meeting was organized as part of the “NorEaST – Stream Temperature Web Portal Demonstration and Application” project funded by the USGS Northeast Climate Science Center. Presentations are available for download.
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NorEaST - invitation
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NorEaST – Stream Temperature Web Portal Demonstration and User Testing. USGS Wisconsin Water Science Center, Middleton, WI, December 9th-10th, 2014.
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NorEaST Workshop - December 2014
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NorEaST - agenda
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Meeting Objectives:
• Provide overview of stream temperature monitoring protocols and data management
• Introduce and demonstrate the NorEaST Stream Temperature Web Portal
• Conduct User testing of the NorEaST Web Portal and gain feedback
• Demonstrate ways to automate data analysis and quality assurance of data
• Demonstrate and discuss applications of continuous stream temperature data
• Discuss leveraging NorEaST web portal with other efforts
• Discuss moving NorEaST into the future (development needs, funding mechanisms/models, other site types, expanded geography, etc.)
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NorEaST Workshop - December 2014
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NorEast - Presentations
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Go to link to download all presentations as a zip file
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NorEaST Workshop - December 2014
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2014 Stream Temperature Modeling (Meeting II)
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2014 Workshop - May 1st Stream Temperature Data and Modeling Meeting II
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Co-hosted by EPA Region 1, U.S. Fish and Wildlife Service, North Atlantic Landscape Conservation Cooperative, USGS Northeast Climate Science Center, and USGS Conte Anadromous Fish Research Center. Presentations are available - see agenda below for a link to the files.
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2014 Stream Temperature Modeling (Meeting II)
