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J.W. Terrell

Publications and source records attributed to J.W. Terrell.

5 recordsLinked to original sources
USGS2008

Estimating fish body condition with quantile regression

We used quantile regression to compare the body condition of walleye Sander vitreus and white bass Morone chrysops before (1980-1988) and after (1989-2004) the establishment of alewives Alosa pseudoharengus in Lake McConaughy, Nebraska. Higher quantiles (percentiles = 100% x quantiles [0, 1]) of weight (W) at the same total length (TL) were indicative of better body condition in an allometric growth model that included separate slopes and intercepts for the before and after groups. All quantiles of walleye weights by TL increased in the years after alewife introduction, ranging from 1.01 to 1.12 times weights in the years before alewife introduction, with greatest increases for the lower (<0.50) quantiles and greater TLs. Quantiles up to 0.25 (the lowest 25th percentiles) of white bass weights were reduced in years after alewife introduction for TLs less than 300 mm, ranging from 0.78 to 0.98 times weights in the years before alewife introduction. However, quantiles greater than or equal to 0.50 (the upper 50th percentiles) of white bass weights increased for all TLs, ranging from 1.01 to 1.06 times the pre-1988 weights. A three-group analysis, which improved the model fit for longer white bass, indicated a reduction (0.80-1.0) in white bass body condition across all TLs in the first 2 years (1989-1990) after alewife introduction, whereas body condition actually improved (1.02-1.12) across all TLs in later years (1991-2004). Thus, after the establishment of alewives in 1988, walleye body condition improved for all fish at all lengths (the greatest improvement occurring among fish in poorer condition), whereas white bass body condition was initially reduced for all fish at all lengths for 2 years and improved in subsequent years. The approach that we developed for comparing fish body condition before and after a management action in Lake McConaughy could be applied to other weight-length data sets typically evaluated with relative weight indices. ?? Copyright by the American Fisheries Society 2008.

North American Journal of Fisheries Management↗
USGS2002

Influences of spatial and temporal variation on fish-habitat relationships defined by regression quantiles

We used regression quantiles to model potentially limiting relationships between the standing crop of cutthroat trout Oncorhynchus clarki and measures of stream channel morphology. Regression quantile models indicated that variation in fish density was inversely related to the width:depth ratio of streams but not to stream width or depth alone. The spatial and temporal stability of model predictions were examined across years and streams, respectively. Variation in fish density with width:depth ratio (10th-90th regression quantiles) modeled for streams sampled in 1993-1997 predicted the variation observed in 1998-1999, indicating similar habitat relationships across years. Both linear and nonlinear models described the limiting relationships well, the latter performing slightly better. Although estimated relationships were transferable in time, results were strongly dependent on the influence of spatial variation in fish density among streams. Density changes with width:depth ratio in a single stream were responsible for the significant ( P < 0.10) negative slopes estimated for the higher quantiles (>80th). This suggests that stream-scale factors other than width:depth ratio play a more direct role in determining population density. Much of the variation in densities of cutthroat trout among streams was attributed to the occurrence of nonnative brook trout Salvelinus fontinalis (a possible competitor) or connectivity to migratory habitats. Regression quantiles can be useful for estimating the effects of limiting factors when ecological responses are highly variable, but our results indicate that spatiotemporal variability in the data should be explicitly considered. In this study, data from individual streams and stream-specific characteristics (e.g., the occurrence of nonnative species and habitat connectivity) strongly affected our interpretation of the relationship between width:depth ratio and fish density.

Transactions of the American Fisheries Society↗
USGS1991

Application and partial validation of a habitat model for moose in the Lake Superior region

A modified version of the dormant-season portion of a Habitat Suitability Index (HSI) model developed for assessing moose ( Alces alces ) habitat in the Lake Superior Region was incorporated in a Geographic Information System (GIS) for 490 km 2 of Minnesota's Superior National Forest. Moose locations (n=235) were plotted during aerial surveys conducted in December 1988 and January 1990-1991. Dormant-season forage and cover quality for 1,000-m, 500-m, and 200-m radii plots around random points and moose locations were compared using U.S. Forest Service stand examination data. Cover quality indices were lower than forage quality indices within all plots. The median value for the average cover quality index was greater (P=0.003) within 200-m plots around cow moose locations than for plots around random points for the most severe winter of the study. The proportion of highest-quality winter cover, such as mixed stands dominated by mid-age class white spruce ( Picea glauca ) and balsam fir ( Abies balsanea ), was greater within 500-m and 200-m plots around cow moose than within similar plots around random points during the two most severe winters. These results indicate that suboptimum ratings of winter habitat quality used in the GIS for dormant-season forage >100 m from cover, as suggested in the original HSI model, are reasonable. Integrating the habitat model with forest stand data using a GIS permitted analysis of moose habitat within a relatively large geographic area. Simulation of habitat quality indicated a potential shortage of late-winter cover in the study area. The effects of forest management actions on moose habitat quality can be simulated without collecting additional data.

Lake Superior region↗
USGS1988

An overview of a habitat suitability index model for moose: Lake Superior region

A three-day workshop was held to develop a model for evaluation of moose habitat in the Lake Superior region. The ultimate goal of the workshop was to provide planning tools to enhance habitat management for moose and maximize the integration of those management objectives with silvicultural goals. An abstract of the models resulting from the workshop is presented and model validation concepts are discussed.

Lake Superior region↗