Influence of Water Allocation and Freshwater Inflow on Oyster Production: A Hydrodynamic–Oyster Population Model for Galveston Bay,Texas, USA

A hydrodynamic–oyster population model was developed to assess the effect of changes in freshwater inflow on oyster populations in Galveston Bay, Texas, USA. The population model includes the effects of environmental conditions, predators, and the oyster parasite, Perkinsus marinus, on oyster populations. The hydrodynamic model includes the effects of wind stress, river runoff, tides, and oceanic exchange on the circulation of the bay. Simulations were run for low, mean, and high freshwater inflow conditions under the present (1993) hydrology and predicted hydrologies for 2024 and 2049 that include both changes in total freshwater inflow and diversions of freshwater from one primary drainage basin to another. Freshwater diversion to supply the Houston metropolitan area is predicted to negatively impact oyster production in Galveston Bay. Fecundity and larval survivorship both decline. Mortality from Perkinsus marinus increases, but to a lesser extent. A larger negative impact in 2049 relative to 2024 originates from the larger drop in fecundity under that hydrology. Changes in recruitment and mortality, resulting in lowered oyster abundance, occur because the bay volume available for mixing freshwater input from the San Jacinto and Buffalo Bayou drainage basins that drain metropolitan Houston is small in comparison to the volume of Trinity Bay that presently receives the bulk of the bay's freshwater inflow. A smaller volume for mixing results in salinities that decline more rapidly and to a greater extent under conditions of high freshwater discharge. Thus, the decline in oyster abundance results from a disequilibrium between geography and salinity brought about by freshwater diversion. Although the bay hydrology shifts, available hard substrate does not. The simulations stress the fact that it is not just the well-appreciated reduction in freshwater inflow that can result in decreased oyster production. Changing the location of freshwater inflow can also significantly impact the bay environment, even if the total amount of freshwater inflow does not change.     

Factor structure of the transformational leadership model in human service teams

The purpose of this study was to examine the factor structure of the transformational leadership model in human service teams. As the nature of this work environment mandates certain management‐by‐exception practices, patterns of correlations between perceptions of active and passive management‐by‐exception behaviors and transformational, transactional, and laissez‐faire leadership were of interest. 236 leaders and 620 subordinates from 54 mental health teams completed the Multifactor Leadership Questionnaire, form 8Y. Results suggest that active and passive management‐by‐exception factors are independent constructs. Copyright © 2003 John Wiley & Sons, Ltd.     

Regional Variations in the Implementation of the Local Air Quality Management Process within Great Britain

The UK National Air Quality Strategy has required local authorities to review and assess air quality in their area of jurisdiction and determine locations in their areas where concentrations of specific air quality pollutants are predicted to exceed national air quality objectives in the future. Statutory air quality management areas (AQMAs) are designated where air quality is predicted to be above specified objective concentrations by specific target dates, and statutory air quality action plans will be necessary to improve the local air quality within these areas. Over 124 local authorities in England (including London), Wales and Scotland anticipate declaring AQMAs following the conclusion of the statutory air quality review and assessment process. However, other influences are being exerted on the local air quality management process and AQMA decision-making processes. Such influences include regional and sub- regional collaborative working between local authorities and government agencies and wider political decision-making processes. Some regions of Great Britain (encompassing England (including London), Scotland and Wales) anticipate many AQMA designations, whilst other regions are not anticipating any such designations despite apparently similar air quality circumstances. Evidence for regional or sub-regional variations in the locations of anticipated AQMAs are examined through an evaluation of the outcomes of the scientific review and assessment process undertaken by local authorities declaring AQMAs, and through a local authority survey to identify influences on decision-making processes at a level above that of the local authority. Regional variation is reported in the type of pollutant causing AQMAs to be declared, in the numbers of AQMAs in regions and in the spatial distribution of AQMAs across Great Britain.     

A Conceptual Framework for Selecting and Analyzing Stressor Data to Study Species Richness at Large Spatial Scales

/ In this paper we develop a conceptual framework for selectingstressor data and analyzing their relationship to geographic patterns ofspecies richness at large spatial scales. Aspects of climate and topography,which are not stressors per se, have been most strongly linked withgeographic patterns of species richness at large spatial scales (e.g.,continental to global scales). The adverse impact of stressors (e.g., habitatloss, pollution) on species has been demonstrated primarily on much smallerspatial scales. To date, there has been a lack of conceptual developmenton how to use stressor data to study geographic patterns of speciesrichness at large spatial scales.The framework we developed includes four components: (1) clarification of theterms stress and stressor and categorization of factors affecting speciesrichness into three groups-anthropogenic stressors, natural stressors, andnatural covariates; (2) synthesis of the existing hypotheses for explaininggeographic patterns of species richness to identify the scales over whichstressors and natural covariates influence species richness and to providesupporting evidence for these relationships through review of previousstudies; (3) identification of three criteria for selection of stressor andcovariate data sets: (a) inclusion of data sets from each of the threecategories identified in item 1, (b) inclusion of data sets representingdifferent aspects of each category, and (c) to the extent possible, analysisof data quality; and (4) identification of two approaches for examiningscale-dependent relationships among stressors, covariates, and patterns ofspecies richness-scaling-up and regression-tree analyses.Based on this framework, we propose 10 data sets as a minimum data base forexamining the effects of stressors and covariates on species richness atlarge spatial scales. These data sets include land cover, roads, wetlands(numbers and loss), exotic species, livestock grazing, surface water pH,pesticide application, climate (and weather), topography, and streams.KEY WORDS: Anthropogenic impacts; Biodiversity; Environmental gradients;Geographic information systems; Hierarchy     

ENVIRONMENTAL AUDITING: An Approach for Characterizing Tropospheric Ozone Risk to Forests

/ The risk tropospheric ozone poses to forests in the United States is dependent on the variation in ozone exposure across the distribution of the forests in question and the various environmental and climate factors predominant in the region. All these factors have a spatial nature, and consequently an approach to characterization of ozone risk is presented that places ozone exposure-response functions for species as seedlings and model-simulated tree and stand responses in a spatial context using a geographical information systems (GIS). The GIS is used to aggregate factors considered important in a risk characterization, including: (1) estimated ozone exposures over forested regions, (2) measures of ozone effects on species' and stand growth, and (3) spatially distributed environmental, genetic, and exposure influences on species' response to ozone. The GIS-based risk characterization provides an estimation of the extent and magnitude of the potential ozone impact on forests. A preliminary risk characterization demonstrating this approach considered only the eastern United States and only the limited empirical data quantifying the effect of ozone exposures on forest tree species as seedlings. The area-weighted response of the annual seedling biomass loss formed the basis for a sensitivity ranking: sensitive-aspen and black cherry (14%-33% biomass loss over 50% of their distribution); moderately sensitive-tulip popular, loblolly pine, eastern white pine, and sugar maple (5%-13% biomass loss); insensitive-Virginia pine and red maple (0%-1% loss). In the future, the GIS-based risk characterization will include process-based model simulations of the three- to 5-year growth response of individual species as large trees with relevant environmental interactions and model simulated response of mixed stands. The interactive nature of GIS provides a tool to explore consequences of the range of climate conditions across a species' distribution, forest management practices, changing ozone precursors, regulatory control strategies, and other factors influencing the spatial distribution of ozone over time as more information becomes available.KEY WORDS: Ecological risk assessment; GIS; Ozone; Risk characterization; Forests; Trees     

Strategic environmental product planning within Philips sound & vision

Until now no structured methodology existed for attuning environmental considerations to the business strategy of companies. The Environmental Competence Centre of Philips Sound & Vision in The Netherlands has developed and tested a methodology for this purpose. This methodology, called Selection of STRrategic Environmen Tal CHallenges (STRETCH), has proven to lead to promising results and should therefore be actively promoted. In this article, the authors show how the application of STRETCH provides the possibility of meeting three main objectives: First, focusing on the incorporation of environmental aspects into the company's business strategy can elicit innovations that may enhance the competitive position of the company by cost reduction and/or higher market shares. Second, the environmental opportunities and threats to be expected in the future can be anticipated in an earlier phase. Through this proactive approach a company can avoid external criticism and take the lead in environmental priority setting. Third, by applying the STRETCH methodology even higher eco-efficiencies are expected to be reached than through incremental, step-by-step environmental improvements.     

Using digital image projections to visualize forest landscape changes due to management activities and forest growth

A pedagogic problem in forestry and landscape management is to visualize future landscape effects of forest growth and current management activities in the forest. This paper presents a method for forecasting digital image projections of forest landscape dynamics. Static nonlinear regression functions estimate the digital numbers in a Landsat Thematic Mapper image. Regressors used are forest stand variables. By estimating the future forest stand data, based on intermediate treatment and growth, future satellite digital images are created. In a case study example, the future landscape of a forest block in the province of Västernorrland, Sweden, is projected to demonstrate the application of this visualization technique.