Modeling the spatial dynamics of regional land use: the CLUE-S model

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.     

Definition of Homogeneous Environmental Management Units for the Catalan Coast

Geographical areas constitute the basic implementation locus for integrated coastal zone management strategies and activities. Because the definition of territorial planning objectives may be affected by socioeconomic and environmental characteristics, one of the main steps in the process involves dividing the coast into homogeneous environmental management units (HEMUs). This article presents a general and simple method for regionalizing the landside of a coastal zone into HEMUs and illustrates it through application to the Catalan coast. Socioeconomic and natural (biophysical) subsystems were selected as the most appropriate dimensions of the regionalization process. Dimensions were described using 11 spatial themes, which were managed in a geographic information system environment that proved to be an adequate tool for the purpose. A final coastal zone map of four classes of HEMUs connected to local administrative units was obtained, and because it reflects the current natural and socioeconomic dynamics, it can be considered as an initial step in the planning process for the Catalan coast. Although the proposed method was developed based on the characteristics of the Catalan coast, it is general enough to be adapted and applied to most developed or developing coastal areas.     

MULTISCALE RIVER ENVIRONMENT CLASSIFICATION FOR WATER RESOURCES MANAGEMENT1

ABSTRACT: River Environment Classification (REC) is a new system for classifying river environments that is based on climate, topography, geology, and land cover factors that control spatial patterns in river ecosystems. REC builds on existing principles for environmental regionalization and introduces three specific additions to the “ecoregion” approach. First, the REC assumes that ecological patterns are dependent on a range of factors and associated landscape scale processes, some of which may show significant variation within an ecoregion. REC arranges the controlling factors in a hierarchy with each level defining the cause of ecological variation at a given characteristic scale. Second, REC assumes that ecological characteristics of rivers are responses to fluvial (i.e., hydrological and hydraulic) processes. Thus, REC uses a network of channels and associated watersheds to classify specific sections of river. When mapped, REC has the form of a linear mosaic in which classes change in the downstream direction as the integrated characteristics of the watershed change, producing longitudinal spatial patterns that are typical of river ecosystems. Third, REC assigns individual river sections to a class independently and objectively according to criteria that result in a geographically independent framework in which classes may show wide geographic dispersion rather than the geographically dependent schemes that result from the ecoregion approach. REC has been developed to provide a multiscale spatial framework for river management and has been used to map the rivers of New Zealand at a 1:50,000 mapping scale.     

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     

ESTIMATING MARYLAND CRITICAL AREA ACVS IMPACT ON FUTURE NONPOINT POLLUTION ALONG THE RHODE RWER ESTUARY1

ABSTRACT: This paper presents the results of an investigation of the effects of the Maryland Critical Area Act on generation of non-point source loads of phosphorus, nitrogen, and sediment to the Rhode River estuary. The Simple Method model, the Marcus and Kearney regression model, and the CREAMS model were used to estimate annual loads under: (1) present conditions, (2) maximum land use development allowable under the Act, and (3) two sets of future land use conditions that might occur if the Act were not in place. Results indicate that the Critical Area Act can reduce the present generation of nonpoint nutrient and sediment loadings 20–30 percent from the regulated area. These reductions can occur while preserving agricultural lands and allowing limited residential and urban development. The decrease in nutrient loadings is primarily dependent upon implementation and enforcement of agricultural best management practices (BMPs). The BMPs could reduce present agricultural nutrient loadings by 90 percent to a level comparable to loadings from residential areas. The estimated effectiveness of the Critical Area Act is even greater when compared to potential future nutrient loadings if development in the area remains unregulated. Unrestricted residential and urban development could increase nutrient loadings by 200 percent to 1000 percent as compared to controlled development under Critical Area Act guidelines. The Critical Area Act primarily prevents these future increases by severely limiting woodland cutting, with lesser results obtained by requiring urban BMPs.     

A conceptual model for response to Arctic oil spills

The potential for oil spills in Arctic regions has increased significantly because of the development of petroleum resources. Response to an oil spill in the Arctic is likely to be much slower than that in the temperate region because of the remoteness of the area and its severe climate. In the face of these unique problems, accurate prediction of the extent and subsequent movement of an oil spill is vital to any cleanup effort. Presented is the framework of a program to study the movement of oil spills in the Arctic. Existing models of oil spreading and polar ice dynamics are reviewed and areas where new model development is required are defined. A system design is developed that may be used for developing a plan to act in the event of a major spill.     

Environmental democracy in action: The Toxics Release Inventory

The Toxics Release Inventory (TRI) created by the 1986 Emergency Planning and Community Right-to-Know Act initially received limited attention. During the early years of its implementation, the TRI has become the basis for a national experiment in voluntaristic problem solving among citizens and industry, but that process of environmental democracy hinges on citizens' ability to actually acquire, understand, and apply the new data on industrial toxic emissions. A national study of TRI-using organizations in the public and private sectors reveals that effective citizen access depends in part on the efforts of intermediary public interest groups to bridge individual needs and right-to-know data. Although the TRI has had early success as a supplement to conventional command and control regulation, questions exist about the extent to which state and federal government should or must provide special efforts to make environmental information access work for citizens.     

Improving lake riparian source area management using surface and subsurface runoff indices

Sensitivity indices, which rank factors pertinent to surface and subsurface runoff pathways, were used to identify phosphorus source areas in riparian zones of 15 northern Minnesota lakes. Watershed models were first developed using a geographic information system (GIS). Empirical models were then developed correlating water quality with land use, lake morphometry, and riparian sensitivity. Base models of forested, cultivated, pasture/open, wetland and residential land use within 100, 200, 400, and 2000 m of the study lakes were regressed on total phosphorus and chlorophyll-a. Area-weighted groundwater and surface runoff sensitivity indices were then incorporated into each model and tested for significance. Within the 200-m buffer, the total phosphorus base model was improved by including the groundwater index alone. The chlorophyll-a base model at 200 m was improved by including: (1) the groundwater index alone, and (2) both the groundwater and surface runoff sensitivity indices. Results suggest that surface and subsurface runoff analysis of potential source areas can improve decision making for lake riparian management.     

Application of a GIS-based stream buffer generation model to environmental policy evaluation

In this article a GIS method is presented for riparian environmental buffer generation. It integrates a scientifically tested buffer width delineation model into a GIS framework. Using the generally available data sets, it determines buffer widths in terms of local physical conditions and expected effectiveness. Technical burdens of data management, computation, and result presentation are handled by the GIS. The case study in which the method was used to evaluate the stream buffer regulations in a North Carolina county demonstrates its capability as a decision support tool to facilitate environmental policy formulation and evaluation, and environmental dispute resolution.     

Adaptive management: Promises and pitfalls

Proponents of the scientific adaptive management approach argue that it increases knowledge acquisition rates, enhances information flow among policy actors, and provides opportunities for creating shared understandings. However, evidence from efforts to implement the approach in New Brunswick, British Columbia, Canada, and the Columbia River Basin indicates that these promises have not been met. The data show that scientific adaptive management relies excessively on the use of linear systems models, discounts nonscientific forms of knowledge, and pays inadequate attention to policy processes that promote the development of shared understandings among diverse stakeholders. To be effective, new adaptive management efforts will need to incorporate knowledge from multiple sources, make use of multiple systems models, and support new forms of cooperation among stakeholders.