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Human Dimensions Discussion Area
Area for Members to add and join in Discussions
Document: Summary of CT Pilot Core Team Meeting & Call, 01-05-2015
Summary of meeting to discuss connectivity layer and relationship to connectors with the terrestrial design.
Summary (Feb 19th) call
Workshop Planning Team: notes from Feb 19th call (provide feedback to JanaS).
Summary (Feb 26th) call
Workshop planning team coordination call notes. JS
Forum Area
 
Link to Driftless Area Master planning document -- Paul Cunningham WDNR
Essentially - creating a report card to identify those areas to protect, etc.
Chazal, Anne
 
NFWPCAS - AppLCC alignment
This is a communication (i.e., not a required report - so each individual LCC communicated independently so no required reporting requirement at this (FY14) point.)
Climate and Nat'l Adaptation Reporting
 
Modeling spatially varying landscape change points in species occurrence thresholds
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.
Fall and Early Winter Movement and Habitat Use of Wild Brook Trout
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.
Detecting Temporal Trends in Freshwater Fisheries Surveys: Statistical Power and the Important Linkages between Management Questions and Monitoring Objectives
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.
Spatial and Temporal Dynamics in Brook Trout Density: Implications for Population Monitoring
T.Wagner et al., Abstract Many potential stressors to aquatic environments operate over large spatial scales, prompting the need to assess and monitor both site-specific and regional dynamics of fish populations. We used hierarchical Bayesian models to evaluate the spatial and temporal variability in density and capture probability of age-1 and older Brook Trout Salvelinus fontinalis from three-pass removal data collected at 291 sites over a 37-year time period (1975–2011) in Pennsylvania streams. There was high between-year variability in density, with annual posterior means ranging from 2.1 to 10.2 fish/100 m2 ; however, there was no significant long-term linear trend. Brook Trout density was positively correlated with elevation and negatively correlated with percent developed land use in the network catchment. Probability of capture did not vary substantially across sites or years but was negatively correlated with mean stream width. Because of the low spatiotemporal variation in capture probability and a strong correlation between first-pass CPUE (catch/min) and three-pass removal density estimates, the use of an abundance index based on first-pass CPUE could represent a cost-effective alternative to conducting multiple-pass removal sampling for some Brook Trout monitoring and assessment objectives. Single-pass indices may be particularly relevant for monitoring objectives that do not require precise site-specific estimates, such as regional monitoring programs that are designed to detect long-term linear trends in density.
State Stream Temperature Compilation
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NALCC Project Metadata spreadsheet w/ coding
Scott's email: As a starting point for discussion, Maritza and I have cross-walked our project pages with the fields in the National Project Catalog. We've color-coded them based on the degree to which they match (e.g., green = exact match, red = something in National system that we don't have). For the AppLCC, we also included Rose's cross-walk of your fields with the National Catalog.
Mallek, Maritza
 
Rose's Crosswalk - sent to Scott Jan 9th 2015
Rose's email: sending to you and Scott the crosswalk I worked on.
North Atlantic LCC Science Strategy
Original North Atlantic LCC Science Strategy primarily organized around Northeast Conservation Framework. Matrix at end updated annually. Recent updates will be provided separately.
AppLCC Site Map
AppLCC Site Map
Annual Planning Cycle v 2014-4-12 jb
Annual Planning Cycle v 2014-4-12 jb