Temporal Trends of Young-of-Year Fishes in Lake Erie and Comparison of Diel Sampling Periods

We explored temporal trends of young-of-year (YOY) fishes caught in bottom trawl hauls at an established offshore monitoring site in Lake Erie in fall during 1961–2001. Sampling was conducted during morning, afternoon, and night in each year. Catches per hour (CPH) of alewife (Alosa pseudoharengus) YOY were relatively low and exhibited no temporal trend. This result was consistent with the species’ intolerance to Lake Erie’s adverse winter water temperatures. Gizzard shad (Dorosoma cepedianum) YOY decreased sharply after 1991, which was consistent with recent oligotrophication of the lake. Following the establishment in 1979 and rapid increase of white perch (Morone americana) YOY, white bass (Morone chrysops) and freshwater drum (Aplodinotus grunniens) YOY decreased. Trout-perch (Percopsis omiscomaycus) YOY decreased during 1986–1991, but recovered to previous levels during 1991–2001. The recovery coincided with the resurgence of mayflies (Ephemoptera) in the lake. CPH of spottail shiner (Notropis hudsonius) and emerald shiner (N. atherinoides) YOY exhibited no temporal trend between 1961 and the late 1970s to early 1980s. CPH of yellow perch (Perca flavescens) YOY decreased during 1961–1988, and walleye (Sander vitreum) YOY increased overall during the time series. These observations were consistent with published studies of adults in the region. CPH of 4 of the 10 species of YOY considered were greatest during night. CPH for walleye YOY was higher in the morning than in the afternoon, but there was no significant difference between night and morning abundances. The results suggest that (1) CPH of YOY fishes may be a useful monitoring tool for Lake Erie, and (2) offshore monitoring programs that do not include night sampling periods may underestimate recruitment for several common species.     

Development of the gap model ZELIG-CFS to predict the dynamics of North American mixed forest types with complex structures

When the development of gap models began about three decades ago, they became a new category of forest productivity models. Compared with traditional growth and yield models, which aim at deriving empirical relationships that best fit data, gap models use semi-theoretical relationships to simulate biotic and abiotic processes in forest stands, including the effects of photosynthetic active radiation interception, site fertility, temperature and soil moisture on tree growth and seedling establishment. While growth and yield models are appropriate to predict short-term stemwood production, gap models may be used to predict the natural course of species replacement for several generations. Because of the poor availability of historical data and knowledge on species-specific allometric relationships, species replacement and death rate, it has seldom been possible to develop and evaluate the most representative algorithms to predict growth and mortality with a high degree of accuracy. For this reason, the developers of gap models focused more on developing simulation tools to improve the understanding of forest succession than predicting growth and yield accurately.In a previous study, the predictions of simulations in two southeastern Canadian mixed ecosystem types using the ZELIG gap model were compared with long-term historical data. This exercise highlighted model components that needed modifications to improve the predictive capacity of ZELIG. The updated version of the model, ZELIG-CFS, includes modifications in the modelling of crown interaction effects, survival rate and regeneration. Different algorithms representing crown interactive effects between crowns were evaluated and species-specific model components that compute individual-tree mortality probability rate were derived. The results of the simulations were compared using long-term remeasurement data obtained from sample plots located in La Mauricie National Park of Canada in Quebec. In the present study, three forest types were studied: (1) red spruce-balsam fir-yellow birch, (2) yellow birch-sugar maple-balsam fir, and (3) red spruce-balsam fir-white birch mixed ecosystems. Among the seven algorithms that represented individual crown interactions, two better predicted the changes in basal area and individual-tree growth: (1) the mean available light growing factor (ALGF), which is computed from the proportion of light intercepted at different levels of individual crowns adjusted by the species-specific shade tolerance index, and (2) the ratio of mean ALGF to crown width. The long-term predicted patterns of change in basal area were consistent with the life history of the different species.     

A framework for predicting personal exposures to environmental hazards

This paper presents a general framework for constructing a predictive distribution of the exposure to an environmental hazard sustained by a randomly selected member of a designated population. The individual’s exposure is assumed to arise from random movement through the environment, resulting in a distribution of exposure that can be used for environmental risk analysis. A specialization of the general framework is that of predicting human exposure to air pollution that can be used to develop models for such things as exposure to particulate matter; practical aspects of their construction are considered. These models can help answer questions such as what fraction of the population sustained ‘high’ levels of exposure for say 5 days in a row. The immediate implementation of the above framework takes the form of a computing platform referred to as pCNEM. This provides a facility for simulating exposures to airborne pollutants and is described in detail elsewhere. This paper considers some theoretical aspects underpinning probabilistic exposure models of this type, with the ideas illustrated in developing a model for predicting human exposure to PM ₁₀.     

Assessment of contamination and biomarker responses in two species of herons on the St. Lawrence river

This study was undertaken to validate potential biomarkers of exposure and effects due to chemical contaminants in breedingcolonies of the Great Blue Heron and the Black-crowned Night-Heron on the St. Lawrence River. Eggs and fledglings from both species were collected from many colonies along theRiver. The fledglings from colonies in freshwater and brackishwater were more contaminated by mercury and PCBs than those from estuarine and gulf colonies. With respect to fledglings ofthe two heron species, some morphometric and blood biochemicalmeasurements, including plasma thyroid hormones and retinol, were significantly different among colonies. Significant differences were also observed in liver retinoids, EROD and porphyrins among colonies. The results of this study suggestthat plasma retinoids and thyroid hormones are good biomarkersof exposure and effects, and are sufficiently sensitive to reflect local and regional variations in contamination. Along with the measure of contaminants in egg and plasma, they constitute non-invasive biomarkers which represent an importantcriteria for long term monitoring of wildlife species. It is concluded that the Great Blue Heron is an appropriate sentinelspecies in the surveillance network for the St. Lawrence River.     

Life cycle assessment of upflow anaerobic sludge blanket sludge management and activated sludge systems aiming energy use in the municipality of Itajubá, Minas Gerais,Brazil

Journal of Material Cycles and Waste Management - This study aimed to carry out the Life Cycle Analysis (LCA) targeting to decide the better management system for sludge from both Activated Sludge...     

Landscape-level influences of terrestrial snake occupancy within the southeastern United States

Habitat loss and degradation are thought to be the primary drivers of species extirpations, but for many species we have little information regarding specific habitats that influence occupancy. Snakes are of conservation concern throughout North America, but effective management and conservation are hindered by a lack of basic natural history information and the small number of large-scale studies designed to assess general population trends. To address this information gap, we compiled detection/nondetection data for 13 large terrestrial species from 449 traps located across the southeastern United States, and we characterized the land cover surrounding each trap at multiple spatial scales (250-, 500-, and 1000-m buffers). We used occupancy modeling, while accounting for heterogeneity in detection probability, to identify habitat variables that were influential in determining the presence of a particular species. We evaluated 12 competing models for each species, representing various hypotheses pertaining to important habitat features for terrestrial snakes. Overall, considerable interspecific variation existed in important habitat variables and relevant spatial scales. For example, kingsnakes (Lampropeltis getula) were negatively associated with evergreen forests, whereas Louisiana pinesnake (Pituophis ruthveni) occupancy increased with increasing coverage of this forest type. Some species were positively associated with grassland and scrub/shrub (e.g., Slowinski's cornsnake, Elaphe slowinskii) whereas others, (e.g., copperhead, Agkistrodon contortrix, and eastern diamond-backed rattlesnake, Crotalus adamanteus) were positively associated with forested habitats. Although the species that we studied may persist in varied landscapes other than those we identified as important, our data were collected in relatively undeveloped areas. Thus, our findings may be relevant when generating conservation plans or restoration goals. Maintaining or restoring landscapes that are most consistent with the ancestral habitat preferences of terrestrial snake assemblages will require a diverse habitat matrix over large spatial scales.     

PROBLEMS IN FORECASTING WATER REQUIREMENTS1

ABSTRACT. Methodological problems associated with forecasting water requirements by use of regression analysis are examined. Problems occurring when long-range forecasts are based on linear and nonlinear extrapolation of time series models include possible changes in socioeconomic conditions, water allocation system structure, and limits to growth. Problems arising in forecasting based on multiple regression models are likely to involve serially dependent errors, multicollinear explanatory variables, and difficulties inherent to the presence of explanatory variables that must themselves be predicted.     

Evaluation of an acid ammonium oxalate extraction to determine fluoride resident concentrations in soils

Fluoride depositions near aluminum smelters and other fluoride-emitting plants can lead to fluoride accumulation in soils, which constitutes a risk for ground water contamination. This study was conducted to investigate the capacity of a 0.2 M acid ammonium oxalate solution to selectively and quantitatively extract fluoride accumulated in soils. The recovery of fluoride added to three soils was evaluated following 7- to 28-d incubations. Oxalate extraction was also compared with a total fluoride extraction method, using oxalate-extractable fluoride (Fox) and total fluoride (Ftot) accumulation profiles derived from column percolation experiments. To determine low-level fluoride concentrations without interference from high Al and Fe concentrations, an adapted ion chromatography method was used. Following soil incubations, oxalate extracted 42 to 86% of added fluoride. Recovery varied between soils and, in one soil, increased with added fluoride concentration. Recovery was unaffected by incubation time. Maximum recovery was obtained in a soil high in amorphous Fe and Al, low in clay, and free of carbonate. Lower recoveries were obtained in soils with higher clay or carbonate contents. Only 4 to 8% of Ftot was extracted in untreated samples using Fox, which suggests a high selectivity of this method for added fluoride. In percolation experiments, the use of Fox reduced considerably the background noise associated with Ftot for the evaluation of fluoride accumulation profiles. Because of its high selectivity and despite incomplete fluoride recovery, the use of Fox to determine fluoride resident concentrations in soils may improve environmental monitoring of fluoride accumulation and movement in contaminated soils.