Stream Crossing Barrier Prioritization Methods for Increasing Eastern Brook Trout Habitat in the Little Androscoggin River Watershed

Eastern Brook Trout (Salvelinas fontanalis) are an important cold water fishery in the state of Maine. While populations in Maine are relatively abundant there has been decline in some parts of its range due in part to loss of habitat connectivity. Brook trout require access to specific types of stream habitat for spawning, feeding, and seasonal thermal refuges. Stream crossing structures such as undersized, poorly installed, or blocked culverts, as well as small remnant dams, can create barriers to accessing important stream habitat for brook trout. A recent Fish Barrier/Culvert Survey in the Little Androscoggin River Watershed provided data about crossing structures and stream conditions that was used to identify barriers that were limiting connectivity of stream habitat. The data was used to prioritize identified barriers in terms of creating better access to higher quality and quantity of stream habitat. To accomplish this the survey data was processed using the Barrier Assessment Tool, a GIS tool that is used to calculate quantities of stream habitat that could be gained both up and downstream of identified barriers. Then raster data for several key parameters of high quality brook trout habitat was created, re-classified and given weighted values. Overlays of the weighted rasters were used to identify the stream reaches with best habitat value. Using the combination of these two methods, identified barriers can be prioritized for future remediation, assisting with efforts to strategically reconnect fragmented Eastern Brook Trout habitat

Exploration of Stream Habitat Spatial Modeling; Using Geographically Weighted Regression, Ordinary Least Squares Regression, and Natural Neighbor Interpolation to Model Depth, Flow, and Benthic Substrate in Streams

Assessment and modeling of stream habitat are integral to understanding streams and the biota within them. In the past several decades, assessment sophistication of ecologic systems increased due to analysis power afforded by gains in computing capability. Spatial data analysis methodology grew alongside computing power and incorporated spatial qualities of ecological data, thereby providing new insights. New methods like geographically weighted regression (GWR) and more established methods like interpolation are now being used in ecological studies to guide assessments and management decisions. However, their accuracy and utility for analysis of stream habitat data have not been fully explored. To clarify their impacts on stream habitat data, the five chapters of this dissertation examined spatial qualities (e.g. heterogeneity, scale, sample pattern) and the use of interpolation and GWR on depth, flow velocity, and benthic substrate.;Benthic substrate, depth, and flow velocity data were collected from four streams between July 2005 and August 2010. Data were collected from Aarons Creek, Monongalia County, WV, Elk River, Kanawha County, WV, Little Wapiti and Grayling creeks in Gallatin County, MT. Using GIS, the datasets were mapped, modeled, and analyzed between fall 2009 and summer 2011.;Results from our studies demonstrated GWR outperformed non-spatial ordinary least squares regression (OLS) when modeling benthic substrate. Our study showed stream data collected at a single scale may be used to generate meaningful results at scales other than that at which it was collected. This finding is important for stream habitat studies where data are often collected at varying spatial scales. As spatial heterogeneity of benthic substrate increased, accuracy levels of models decreased showing heterogeneity must be quantified in analysis of stream habitat variables. Large (\u3e20m width) and small (\u3c10m width) wadeable streams may be analyzed using the same type of spatial analysis though substrate deposition pattern may vary in different size streams. Benthic substrate depositional pattern was most effectively captured by non-random point selection which created more accurate maps than grid and random point sample methods.;Combined results demonstrated the need to address spatial qualities of stream habitat data in analysis, assessment, and how spatial attributes may guide data collection. Further, failure to quantify spatial attributes in stream habitat data can cause erroneous results and thus minimize effectiveness for useful ecologic conclusions and management decisions

Ex. 281-US-423

An Oregon Department of Fish and Wildlife stream habitat report of Crooked Creek to Wood River, reach 1

Ex. 281-US-423

An Oregon Department of Fish and Wildlife stream habitat report of Crooked Creek to Wood River, reach 1

Ex. 281-US-428

An Oregon Department of Fish and Wildlife stream habitat report of Fort Creek to Wood River, reach 1

Ex. 280-US-440

A Stream Habitat survey of the Sprague River conducted by the Oregon Department of Fish and Wildlife from reach 9B Anderso

Ex. 280-US-435

A Stream Habitat survey of the Sprague River conducted by the Oregon Department of Fish and Wildlife from reach 8A Kirk

Central Coast Region South District Basin Planning & Habitat Mapping Project

This is a report to the California Department of Fish and Game. Between 2003 and 2008, the Foundation of CSUMB produced fish habitat maps and GIS layers for CDFG based on CDFG field data. This report describes the data entry, mapping, and website construction procedures associated with the project. Included are the maps that have been constructed. This report marks the completion of the Central Coast region South District Basin Planning and Habitat Mapping Project. (Document contains 40 pages

Ex. 280-US-435

A Stream Habitat survey of the Sprague River conducted by the Oregon Department of Fish and Wildlife from reach 8A Kirk