Status and Trends of Dissolved Oxygen in Corpus Christi Bay, Texas, U.S.A.

The purpose of this studywas to determine status and long-term trends of dissolved oxygen concentrations (DO) in Corpus Christi Bay, Texas, U.S.A. A 20-year record of randomized stations was used to determine the trend of surface water DO, salinity, and temperature over space and time. A 13-year record of two fixed stations was used to determine the temporal nutrient trends. A 10-year record of fixed stations in the southeastern region of Corpus Christi Bay was used to determine the status of disturbance caused by low DO in bottom waters. From 1982 to 2002, there was a significant decrease in surface water DO at a rate of 0.06 mg L⁻¹ yr⁻¹ and a significant increase in surface water temperature at a rate of 0.07°C yr⁻¹. The southeastern region of Corpus Christi Bay had the lowest average DO, and during July and August, DO are steadily declining at a rate of 0.09 mg L⁻¹ yr⁻¹. It is not likely that eutrophication is causing hypoxia, because freshwater inflow rates have significantly decreased since 1941 and nutrient levels have not changed from 1987 to 2000. Even though long-term trends indicate that average surface DO is decreasing, disturbance by hypoxia appears to be stable, but this may be due to just eight years of data. In fact, if the current trend continues, surface water DO will not meet exceptional aquatic life standards (≤5 mgL⁻¹) in 2032.     

Linking Land Cover and Water Quality in New York City’S Water Supply Watersheds

The Catskill/Delaware reservoirs supply 90% of New York City’s drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.The United States Environmental Protection Agency through its Office of Research and Development funded and managed the research described here. It has been subjected to Agency’s administrative review and approved for publication as an EPA document.     

A modular approach to Integrated Assessment modeling

In this paper, we present a new approach to model coupling that probably forms the methodological basis of a new generation of Integrated Assessment models. This approach respects the knowledge and expertise that is embodied in existing models and encourages their gradual evolution. Modularity is the guiding principle. Our approach is distinguished by the way modules are coupled which is based on an interplay of a job control module, a numerical coupling module, and a couple of stand-alone functional modules. The numerical coupling module - the core component - serves to treat the feedbacks between the functional modules. A first implemented example that couples an economic and a climate module by means of a two-phase meta-optimization is presented here. The algorithm and mathematical structure behind are discussed as well as important features such as convergence behavior and reliability.     

Climate impact on social systems: the risk assessment approach

A novel approach to the problem of estimating climate impact on social systems is suggested. This approach is based on a risk concept, where the notion of critical events is introduced and the probability of such events is estimated. The estimation considers both the inherent stochasticity of climatic processes and the artificial stochasticity of climate predictions due to scientific uncertainties. The method is worked out in some detail for the regional problem of crop production and the risks associated with global climate change, and illustrated by a case study (Kursk region of the FSU). In order to get local climatic characteristics (weather), a so-called statistical weather generator is used. One interesting finding is that the 3% risk level remains constant up to 1.0–1.1°C rise of mean seasonal temperature, if the variance does not change. On the other hand, the risk grows rapidly with increasing variance (even if the mean temperature rises very slowly). The risk approach is able to separate two problems: (i) assessment of global change impact, and (ii) decision making. The main task for the scientific community is to provide the politicians with different options; the choice of admissible (from the social point of view) critical events and the corresponding risk levels is the business of decision makers.     

evaluation of a measurement method for forest vegetation in a large-scale ecological survey

We evaluate a field method for determining species richness andcanopy cover of vascular plants for the Forest Health MonitoringProgram (FHM), an ecological survey of U.S. forests. Measurementsare taken within 12 1-m² quadrats on 1/15 ha plots in FHM.Species richness and cover are determined for four height classes(strata) within each quadrat and aggregated by stratum over the entireplot. We estimated (1) the agreement between experienced trainers andinexperienced technicians who collected the data on this survey(accuracy) and (2) the agreement among the technicians (precision) forresults on species richness and cover from 3 test plots at 3 timeintervals. The methods appear to be highly precise, although somediscrepancies with the values obtained by the trainers were found.Trainers found significantly more species in the ground stratum (0–0.6 m) and measured significantly more cover in the uppermost stratum(>4.9 m). The proportion of variation due to measurement error andtemporal variability was less than 13% for species richness (all strata)and cover (all but one stratum). This indicates that the method issuitable for monitoring changes in species richness and canopy coverfor a large-scale synoptic monitoring project such as FHM.     

linking various aspects of atmospheric change through a systems analysis of food

Although interdisciplinary collaboration to address a singleenvironmental problem is more common than in the past, all toooften the significant atmospheric problems of our day such asstratospheric ozone depletion, acidic deposition or climaticchange are addressed on a single issue basis. Systems analysis isa way of looking at a problem in a holistic, integrated fashionthrough including as many as practicable of the importantcomponents, and the linkages among them. Systems analysisoften begins with a conceptual model which, even if lackingquantification, is a useful means of changing ones thinking to amulti-issue approach. If possible, conceptual models areoperationalized by quantification (using the best availablescientific knowledge) of the stocks and flows of the relevantcomponents of the problem, and the processes that are involved.In this paper, a systems approach to food production is used tolink various atmospheric issues such as regional acidification andclimatic change. A spreadsheet model of food demand andproduction in various world regions examined the possible effectof atmospheric change on how much food we can grow, andwhether or not we may be able to meet the increased demand inthe year 2025. Using relatively modest changes in factors ofagricultural production, the spreadsheet model calculated globalshortfalls by the year 2025 of the order of 10 to 20% in someimportant agricultural crops, despite the improvements in cropproduction factors that are envisaged by the Food andAgricultural Organization from now until the year 2010, and thatwere extrapolated in this paper to 2025. The model alsocalculated that climatic change in combination with eithertropospheric ozone or increased UV-B radiation caused bydepletion of the stratospheric ozone layer may in general makethe situation worse than in the case of climatic change alone.Given the large uncertainties in the input data, the results in thispaper should not be viewed as predictions but rather as anexample of taking a relatively simple systems approach to foodproduction using a spreadsheet model, and calculating the effectsthat various aspects of atmospheric change might have upon it.Therefore, it is extremely important to know the effects uponcrop production factors of climatic change, tropospheric ozoneand increased UV-B radiation not only as individual issues, butalso of their combined effect since it is probable that in manyregions they will occur in combination.     

Modeling the spatial pattern of farmland using GIS and multiple logistic regression: a case study of Maotiao River Basin, Guizhou Province, China

Land use change is an important topic in the field of global environmental change and sustainable development. Land use change modeling has attracted substantial attention because it helps researchers understand the mechanisms of land use change and assists regulatory bodies in formulating relevant policies. Maotiao River Basin is located in the province of Guizhou, China, which has a developed agricultural industry in the karst mountain areas. This paper selected biophysical and social–economic factors as independent variables, and constructed a multiple logistic regression of farmland spatial distribution probability by random sampling. Then, by using GIS technology and integrating the 2000 data, this study predicted the farmland spatial pattern. When the predicted map was compared with the actual farmland map for 2000, we noted that 71% of the simulation is in accordance with the 2000 farmland pattern. The result satisfactorily proves the reasonability and applicability of our model.     

Assessing land use impacts on flood processes in complex terrain by using GIS and modeling approach

A distributed hydrologic modeling and GIS approach is applied for the assessment of land use impact in the Steinsel sub-basin, Alzette, Grand-Duchy of Luxembourg. The assessment focuses on the runoff contributions from different land use classes and the potential impact of land use changes on runoff generation. The results show that the direct runoff from urban areas is dominant for a flood event compared with runoff from other land use areas in this catchment, and tends to increase for small floods and for the dry season floods, whereas the interflow from forested, pasture and agricultural field areas contributes to the recession flow. Significant variations in flood volume, peak discharge, time to the peak, etc., are found from the model simulation based on the three hypothetical land use change scenarios.     

Mega-Development Trends in the Amazon: Implications for Global Change

This paper describes four global-change phenomena that are having major impacts on Amazonian forests. The first is accelerating deforestation and logging. Despite recent government initiatives to slow forest loss, deforestation rates in Brazilian Amazonia have increased from 1.1 million ha yr^–1 in the early 1990s, to nearly 1.5 million ha yr^–1 from 1992–1994, and to more than 1.9 million ha yr^–1 from 1995–1998. Deforestation is also occurring rapidly in some other parts of the Amazon Basin, such as in Bolivia and Ecuador, while industrialized logging is increasing dramatically in the Guianas and central Amazonia.The second phenomenon is that patterns of forest loss and fragmentation are rapidly changing. In recent decades, large-scale deforestation has mainly occurred in the southern and eastern portions of the Amazon — in the Brazilian states of Pará, Maranho, Rondônia, Acre, and Mato Grosso, and in northern Bolivia. While rates of forest loss remain very high in these areas, the development of major new highways is providing direct conduits into the heart of the Amazon. If future trends follow past patterns, land-hungry settlers and loggers may largely bisect the forests of the Amazon Basin.The third phenomenon is that climatic variability is interacting with human land uses, creating additional impacts on forest ecosystems. The 1997/98 El Niño drought, for example, led to a major increase in forest burning, with wildfires raging out of control in the northern Amazonian state of Roraima and other locations. Logging operations, which create labyrinths of roads and tracks in forsts, are increasing fuel loads, desiccation and ignition sources in forest interiors. Forest fragmentation also increases fire susceptibility by creating dry, fire-prone forest edges.Finally, recent evidence suggests that intact Amazonian forests are a globally significant carbon sink, quite possibly caused by higher forest growth rates in response to increasing atmospheric CO₂ fertilization. Evidence for a carbon sink comes from long-term forest mensuration plots, from whole-forest studies of carbon flux and from investigations of atmospheric CO₂ and oxygen isotopes. Unfortunately, intact Amazonian forests are rapidly diminishing. Hence, not only is the destruction of these forests a major source of greenhouse gases, but it is reducing their intrinsic capacity to help buffer the rapid anthropogenic rise in CO₂.     

Using environmental stressor information to predict the ecological status of Maryland non-tidal streams as measured by biological indicators

In Maryland, U.S., an interim framework has recentlybeen developed for using biologically based thresholds, or `biocriteria', to assess the health of nontidal streams statewide at watershed scales. The evaluation of impairment is based on indices of biological integrity from the Maryland Biological Stream Survey (MBSS). We applied logistic regression to quantify how the biotic integrity of streams at a local scale is affected by cumulative effects resulting from catchment land uses, point sources, and nearby transmission line rights-of-way. Indicators for land use were developed from the remote sensing National Land Cover Data and applied at different scales. We determined that the risk of local impairment in nontidal streams rapidly increases with increased urban land use in the catchment area. The average likelihood of failing biocriteria doubled with every 10% points increment in urban land, thus an increase in urban land use from 0 to 20% quadruples the risk of impairment. For the basins evaluated in this study, catchments with more than 40–50% urban land use had greater than 80% probability of failing biocriteria, on average. Inclusion of rights-of-way and point sources in the model did not significantly improve the fit for this data set, most likely because of their low numbers. The overall results indicate that our predictive modeling approach can help pinpoint stream ecosystems experiencing or vulnerable to degradation.