Allocating Sampling Effort to Equalize Precision of Electrofishing Catch per Unit Effort

We used a spatially explicit simulation model to examine the effects of lake shoreline length and lakewide fish density on electrofishing catch-per-unit-effort (CPUE) estimates of fish density. We also tested model predictions regarding the influence of shoreline length and fish density on precision of CPUE estimates by analyzing electrofishing data from Ohio reservoirs for juvenile gizzard shad Dorosoma cepedianum, which is a schooling fish, and largemouth bass Micropterus salmoides, a more solitary fish. Our goals were to estimate the impact of these factors on variability associated with population estimates derived from CPUE and to determine how these factors influence the minimum number of transects required to sample populations with a reliable degree of precision. Neither ‘‘minimum transect number’’ (number of transects sampled per lake in which all of 10 replicate simulations provided density estimates within 610% of the mean) nor ‘‘minimum variance’’ (variance among estimates given 20 transects/estimate) were affected by the size of lake being sampled. However, minimum transect number decreased with lakewide fish density, and minimum variance increased with fish density, particularly when fish were patchily distributed. Our results show that it is reasonable to choose one effort level (i.e., a constant number of transects per lake) for a variety of systems. This constant level of effort can achieve acceptable precision in systems differing in lake shoreline length, fish density, and fish patchiness, except in those systems having extremely low overall fish densities. In this case, more transects may be required.Support for this project was provided by Federal Aid in Sport Fish Restoration, project F-69-P, administered jointly by the U.S. Fish and Wildlife Service and the Ohio Division of Wildlife, and by the Department of Zoology, Ohio State University

Life After Death in Lake Erie: Nutrient Controls Drive Fish Species Richness, Rehabilitation

We explored the recent (1969–1996) dynamics of fish communities within Lake Erie, a system formerly degraded by eutrophication and now undergoing oligotrophication owing to phosphorus abatement programs. By merging bottom trawl data from two lake basins of contrasting productivity with life-history information (i.e., tolerances to environmental degradation, diet and temperature preferences), we examined (1) the relationship between system productivity and species richness, (2) whether fish communities are resilient to eutrophication, and (3) whether oligotrophication necessarily leads to reduced sport and commercial fish production. Reduced phosphorus loading has led to fish community rehabilitation. In the productive west basin, six species tolerant of eutrophy (i.e., anoxia, turbidity) declined in abundance, whereas the abundance of three intolerant species increased through time. In the less productive central basin, although only one tolerant species declined, four species intolerant of eutrophic conditions recovered with oligotrophication. These differential responses appear to derive from dissimilar mechanisms by which reduced productivity alters habitat and resource availability for fishes. Specifically, enhanced bottom oxygen, combined with reduced biogenic turbidity and sedimentation, likely drove the loss of tolerant species in the west basin by reducing detrital mass or the ability of these species to compete with intolerant species under conditions of improved water clarity. In contrast, reduced bottom anoxia, which enhanced availability of cool- and cold-water habitat and benthic macroinvertebrate communities, appears important to the recovery of intolerant species in the central basin. Ultimately, these productivity-induced shifts caused species richness to decline in Lake Erie’s west basin and to increase in its central basin. Beyond confirming that unimodal models of productivity and species diversity can describe fish community change in a recovering system, our results provide optimism in an otherwise dismal state of affairs in fisheries management (e.g., overexploitation), given that many recovering intolerant species are desired sport or commercial fishes.Support for this work was provided by (1) Federal Aid in Sport Fish Restoration F-69-P (to R. A. Stein), administered jointly by the U.S. Fish and Wildlife Service and ODNR-ODW, (2) the Department of Evolution, Ecology, and Organismal Biology at The Ohio State University, and (3) a Presidential Fellowship awarded to S. A. Ludsin by The Ohio State University

Modeling sources of variation for growth and predatory demand of Lake Erie walleye (Stizostedion vitreum), 1986-1995

Abstract in English and FrenchGiven the variable nature of the Lake Erie ecosystem, we investigated biotic and abiotic sources of variation for walleye (Stizostedion vitreum) growth, consumption, and population-wide predatory demand. We determined how temperature, population structure, and age-specific consumption influenced walleye growth and consumption during 1986-1995. For each year, we used individual-based bioenergetics modeling to compare growth and consumption by walleye in Lake Erie's western or central basin with those of walleye moving seasonally between basins. Population structure strongly affected walleye growth and consumption but had little influence on interbasin growth rate comparisons. Based on water temperature alone, growth and consumption by western basin walleye were generally lower than for central basin or migratory populations and were more limited by summer water temperatures. In simulations combining effects of population structure, temperature, and age-specific consumption, migratory walleye grew most rapidly, taking advantage of temperature-related growth peaks in both basins. Estimates of walleye predatory demand declined with population size from 1988 through 1995. With natural feedbacks, predatory demand interacts with prey production, limiting walleye reproductive potential when prey availability is low. However, immediate impact on predatory inertia is limited, complicating our ability to predict how predatory demand and prey availability interact in Lake Erie.Support for this project was provided by a University Fellowship from the Graduate School of the Ohio State University (to M.W.K.) and by Federal Aid in Sportfish Restoration F-69-P, administered jointly by the U.S. Fish and Wildlife Service and the Ohio Division of Wildlife, and by the Department of Zoology, Ohio State University

Patterns of Landscape Distribution, and Morphological and Genetic Variability in Cutthroat Trout of the Snake River Headwaters, Wyoming

We used a landscape scale approach to facilitate the synthesis of geomorphic, ecological, and genetic information regarding the distribution and organization of Yellowstone cutthroat trout, Oncorhynchus clarkii bouvieri, and finespotted Snake River cutthroat trout, Oncorhynchus clarkii subspecies, in the Snake River headwaters of northwest Wyoming. Selection criteria allowed us to hierarchically analyze for morphological or geographic structuring from the basin scale, to the stream reach scale. Multivariate morphometric analyses of spotting patterns can discriminate between the large and finespotted morphotypes when assessing fish that represent the extremes, although enough overlap in spotting patterns exist within the respective morphotypes to confound clear cut distinction. We were unable to genetically differentiate between the morphotypes using an 1,150 bp region of the ND2 mitochondrial genome. Genetic differences among drainages were apparent, and two distinct clades were present in the mtDNA dataset. Morphological and genetic differences were observed in rainbow-cutthroat hybrids that distinguished them from cutthroat trout, and hybridization was limited. Further genetic work is recommended using the existing sample set with nuclear markers, combined with additional collections from the main stem of the Snake River

Appendix B. Transition graphs showing shifts in soil characteristics across ecotones from the core of one ecosystem to the core of another ecosystem.

Transition graphs showing shifts in soil characteristics across ecotones from the core of one ecosystem to the core of another ecosystem

Appendix E. Tree species identified at Jennings Woods, with variance explained (adjusted R²) by ecosystem type and soil properties.

Tree species identified at Jennings Woods, with variance explained (adjusted R²) by ecosystem type and soil properties