Can. J. Fish. Aquat. Sci. M(Suppl. 2 ) : 471485.Methods for estimating fish production in aquatic ecosystems range from simple empirically derived estimators, such as morphoedaphic indices, to complex ecosystem simulation models. As first-order estimators, the former are attractive to managers because they are simple and relatively inexpensive to apply and interpret. Application of the latter group has been limited because many of the data inputs are difficuit and expensive to obtain. Between these extremes are several models, such as the biomasssize spectrum model, that provide useful information for moderate expenditures of time and effort. Existing and new methods are reviewed in the light of production theory and several are applied to Great Lakes and Lake Winnipeg data. Eight empirical models derived from limnological variables were selected from the literature and used to estimate potential fish yield for the Great Lakes and Lake Winnipeg. The models predicted a fairly narrow range of potential yields, but when compared with historic yields, none was consistent for all lakes. The best overall empirically derived estimator of potential yield in the Great Lakes was the morphoedaphic index. Potential fish production estimated from invertebrate production with Borgmann's biomasssize spectrum mode! was considerably greater than historic yields or the yield theorie de la productivite et on applique piusieurs de ces m6thodes B des donn6es recueillies dans \es Grands Lacs et E e lac Winnipeg. On a choisi dans les ouvrages publies huit modeles empiriques tires de variables limnologiques; ils sewent a determiner le rendement potentiel en poissons des Grands Lacs et du lac Winnipeg. Les modeles predisent une gamme assez petite de rendements potentiels; toutefois, une '~oncribution No. 86-03 sf the Ontario Ministry of Natural Resources, Research Section, Fisheries Branch. Box 50, Maple, Ont. LOJ fE0. Can. J. Fish. Aquat. Sci. Downloaded from www.nrcresearchpress.com by Duke University on 10/14/12 For personal use only.Since Ryder's (1965) landmark paper there has k e n extensive Base of ME1 in addition to other physical, chemical, and biological indices. In general, such indices are designed for simplicity of application. They treat yield of fish as a "shadow" statistic representing fish production. This embodies the implicit assumption that the yield for a given lake represents the same fraction of total production as the yields for the other lakes with which it is to be compared. Where reliable and comparable

The destructiveness of major (Category 3 to 5) hurricanes along the United States Atlantic Ocean seaboard has been recognized for centuries. While the effects of hurricanes on coastal ecosystems are well known, the influence of hurricanes on pelagic seabirds is difficult to assess. During the annual Atlantic hurricane season (~1 June to 30 November), the endangered black-capped petrel Pterodroma hasitata aggregates in Gulf Stream habitats from Florida to North Carolina. On at least 8 occasions over the past century, hurricanes have driven petrels far inland (sometimes as far as the Great Lakes), suggesting the demise of 10s to 100s of individuals. This paper models >100 yr of data to characterize and compare key aspects of hurricanes that did and did not drive petrels inland. Our model suggests that the predicted increase in the frequency of Category 3 to 5 hurricanes in the region due to climate change could nearly double the expected number of wrecked petrels over the next century and place an endangered species at greater risk of extinction.

/ Past methods of prioritizing sites for protection and restoration have focused on lists of criteria or algorithms. These methods lack a common underlying framework, such that the process is explicit and repeatable, assumptions are highlighted, and commonalities and differences among prioritizations can be readily assessed. Our objective in this paper is to provide such a framework for cases where the goal of setting priorities is to maximize the ecological benefit gained from limited resources. We provide simple and general models that can be used to prioritize sites based on the projected ecological benefit per unit restoration or protection effort and to estimate the total projected benefit of restoring or protecting a set of sites. These models, which are based on an expression of the functional relationship between an end point and effort, hold up under a variety of situations and provide a common language for prioritization. We then discuss procedures for estimating model terms-calculations from regression curves when data are available, and use of judgement indicators when data are relatively limited. Finally, we present two case studies that apply the models and examine selected past prioritizations in the context of our framework.

Understanding the best way to allocate limited resources is a constant challenge for water quality improvement efforts. The synoptic approach is a tool for geographic prioritization of these efforts. It uses a benefit-cost framework to calculate indices for functional criteria in subunits (watersheds, counties) of a region and then rank the subunits. The synoptic approach was specifically designed to incorporate best professional judgment in cases where information and resources are limited. To date, the synoptic approach has been applied primarily to local or regional wetland restoration prioritization projects. The goal of this work was to develop a synoptic model for prioritizing watersheds within which suites of agricultural best management practices (BMPs) can be implemented to reduce sediment load at the watershed outlets. The model ranks candidate watersheds within an ecoregion or river basin so that BMP implementation within the highest ranked watersheds will result in the most sediment load reduction per conservation dollar invested. The model can be applied anywhere and at many scales provided that the selected suite of BMPs is appropriate for the evaluation area’s biophysical and climatic conditions. The model was specifically developed as a tool for prioritizing BMP implementation efforts in ecoregions containing watersheds associated with the USDA-NRCS conservation effects assessment project (CEAP). This paper presents the testing of the model in the little river experimental watershed (LREW) which is located near Tifton, Georgia, USA and is the CEAP watershed representing the southeastern coastal plain. The application of the model to the LREW demonstrated that the model represents the physical drivers of erosion and sediment loading well. The application also showed that the model is quite responsive to social and economic drivers and is, therefore, best applied at a scale large enough to ensure differences in social and economic drivers across the candidate watersheds. The prioritization model will be used for planning purposes. Its results are visualized as maps which enable resource managers to identify watersheds within which BMP implementation would result in the most water quality improvement per conservation dollar invested.

He received masters' degrees in ecology from the University of Tennessee and applied statistics from Louisiana State University, and a Ph.D. degree in wildlife and fisheries sciences from Texas A&M University. He joined the Forest Service in 1 991 , and has been modeling the population dynamics of salmonids since 1983. His current research focuses The model is written in the SAS® programming language, which allows the model to operate on a variety of computing systems and provides enhanced flexibility in the analysis of model output. Users of the model need not be proficient in SAS. Simple input forms and ancillary programs to analyze model results allow users to run the model with a minimum of prior instruction.