Linking Nitrogen Export to Landscape Heterogeneity: The Role of Infrastructure and Storm Flows in a Mediterranean Urban System

Urban ecosystems are often sources of nonpoint source (NPS) nitrogen (N) pollution to aquatic ecosystems. However, N export from urban watersheds is highly variable. Examples of densely urbanized watersheds are not well studied, and these may have comparatively low export rates. Commonly used metrics of landscape heterogeneity may obscure our ability to discern relationships among landscape characteristics that can explain these lower export rates. We expected that differences not often captured by these metrics in the relative cover of vegetation, structures, and impervious surfaces would better explain observed variation in N export. We examined these relationships during storms in residential watersheds. Contrary to expectations, land cover did not directly predict variation in N or water export. Instead, N export was strongly linked to drainage infrastructure density. Our research highlights the role of fine‐scaled landscape attributes, mainly infrastructure, in explaining patterns of N export from densely urbanized watersheds. Changes to hydrologic flow paths by infrastructure explained more variation in N export than land cover. Our findings support further development of landscape ecological models of urban N export that focus on hydrologic modification by infrastructure rather than traditional landscape measures such as land use, as indicators for evaluating patterns of NPS nitrogen pollution in densely urbanized watersheds.     

Governing Change: Land-Use Change and the Prevention of Nonpoint Source Pollution in the North Coastal Basin of California

Many rural areas in the United States and throughout much of the postindustrial world are undergoing significant ecological, socioeconomic, and political transformations. The migration of urban and suburban dwellers into rural areas has led to the subdivision of large tracts of land into smaller parcels, which can complicate efforts to govern human–environmental problems. Non-point source (NPS) pollution from private rural lands is a particularly pressing human–environmental challenge that may be aggravated by changing land tenure. In this article, I report on a study of the governance and management of sediment (a common NPS pollutant) in the North Coastal basin of California, a region undergoing a transition from traditional extractive and agricultural land uses to rural residential and other alternative land uses. I focus on the differences in the governance and management across private timber, ranch, residential, vacation, and other lands in the region. I find that (1) the stringency and strength of sediment regulations differ by land use, (2) nonregulatory programs tend to target working landscapes, and (3) rural residential landowners have less knowledge of sediment control and report using fewer sediment-control techniques than landowners using their land for timber production or ranching. I conclude with an exploration of the consequences of these differences on an evolving rural landscape.     

WATER QUALITY IN AGRICULTURAL,URBAN, AND MIXED LAND USE WATERSHEDS1

ABSTRACT: Water quality and nonpoint source (NPS) pollution are important issues in many areas of the world, including the Inner Bluegrass Region of Kentucky where urban development is changing formerly rural watersheds into urban and mixed use watersheds. In watersheds where land use is mixed, the relative contributions of NPS pollution from rural and urban land uses can be difficult to separate. To better understand NPS pollution sources in mixed use watersheds, surface water samples were taken at three sites that varied in land use to examine the effect of land use on water quality. Within the group of three watersheds, one was predominately agriculture (Agricultural), one was predominately urban (Urban), and a third had relatively equal representation of both types of land uses (Mixed). Nitrogen (N), phosphorus (P), total suspended solids (TSS), turbidity, pH, temperature, and streamflow were measured for one year. Comparisons are made among watersheds for concentration and fluxes of water quality parameters. Nitrate and orthophosphate concentrations were found to be significantly higher in the Agricultural watershed. Total suspended solids, turbidity, temperature, and pH, were found to be generally higher in the Urban and Mixed watersheds. No differences were found for streamflow (per unit area), total phosphorus, and ammonium concentrations among watersheds. Fluxes of orthophosphate were greater in the Agricultural watershed that in the Urban watershed while fluxes of TSS were greater in the Mixed watershed when compared to the Agricultural watershed. Fluxes of nitrate, ammonium, and total phosphorus did not vary among watersheds. It is apparent from the data that Agricultural land uses are generally a greater source of nutrients than the Urban land uses while Urban land uses are generally a greater source of suspended sediment.     

Nonpoint Source Pollution Responses Simulation for Conversion Cropland to Forest in Mountains by SWAT in China

Several environmental protection policies have been implemented to prevent soil erosion and nonpoint source (NPS) pollutions in China. After severe Yangtze River floods, the “conversion cropland to forest policy” (CCFP) was carried out throughout China, especially in the middle and upper reaches of Yangtze River. The research area of the current study is located in Bazhong City, Sichuan Province in Yangtze River watershed, where soil erosion and NPS pollution are serious concerns. Major NPS pollutants include nitrogen (N) and phosphorus (P). The objective of this study is to evaluate the long-term impact of implementation of the CCFP on stream flow, sediment yields, and the main NPS pollutant loading at watershed level. The Soil and Water Assessment Tool (SWAT) is a watershed environmental model and is applied here to simulate and quantify the impacts. Four scenarios are constructed representing different patterns of conversion from cropland to forest under various conditions set by the CCFP. Scenario A represented the baseline, i.e., the cropland and forest area conditions before the implementation of CCFP. Scenario B represents the condition under which all hillside cropland with slope larger than 25° was converted into forest. In scenario C and D, hillside cropland with slope larger than 15° and 7.5° was substituted by forest, respectively. Under the various scenarios, the NPS pollution reduction due to CCFP implementation from 1996–2005 is estimated by SWAT. The results are presented as percentage change of water flow, sediment, organic N, and organic P at watershed level. Furthermore, a regression analysis is conducted between forest area ratio and ten years’ average NPS load estimations, which confirmed the benefits of implementing CCFP in reducing nonpoint source pollution by increasing forest area in mountainous areas. The reduction of organic N and organic P is significant (decrease 42.1% and 62.7%, respectively) at watershed level. In addition, this study also proves that SWAT modeling approach can be used to estimate NPS pollutants’ impacts of land use conversions in large watershed.     

WATERSHEDSS: A DECISION SUPPORT SYSTEM FOR WATERSHED-SCALE NONPOINT SOURCE WATER QUALITY PROBLEMS1

ABSTRACT: A significant portion of all pollutants entering surface waters (streams, lakes, estuaries, and wetlands) derives from non-point source (NPS) pollution and, in particular, agricultural activities. The first step in restoring a water resource is to focus on the primary water quality problem in the watershed. The most appropriate NPS control measures, which include best management practices (BMPs) and landscape features, such as wetlands and riparian areas, can then be selected and positioned to minimize or mitigate the identified pollutant(s). A computer-based decision sup. port and educational software system, WATERSHEDSS (WATER, Soil, and Hydro-Environmental Decision Support System), has been developed to aid managers in defining their water quality problems and selecting appropriate NPS control measures. The three primary objectives of WATERSHEDSS are (1) to transfer water quality and land treatment information to watershed managers in order to assist them with appropriate land management/land treatment decisions; (2) to assess NPS pollution in a watershed based on user-supplied information and decisions; and (3) to evaluate, through geographical information systems-assisted modeling, the water quality effects of alternative land treatment scenarios. WATERSHEDSS is available on the World Wide Web (Web) at http://h2osparc.wq.ncsu.edu .     

Modeling Agricultural Nonpoint Source Pollution Using a Geographic Information System Approach

Agricultural non-point source (NPS) pollution, primarily sediment and nutrients, is the leading source of water-quality impacts to surface waters in North America. The overall goal of this study was to develop geographic information system (GIS) protocols to facilitate the spatial and temporal modeling of changes in soils, hydrology, and land-cover change at the watershed scale. In the first part of this article, we describe the use of GIS to spatially integrate watershed scale data on soil erodibility, land use, and runoff for the assessment of potential source areas within an intensively agricultural watershed. The agricultural non-point source pollution (AGNPS) model was used in the Muddy Creek, Ontario, watershed to evaluate the effectiveness of management strategies in decreasing sediment and nutrient [phosphorus (P)] pollution. This analysis was accompanied by the measurement of water-quality parameters (dissolved oxygen, pH, hardness, alkalinity, and turbidity) as well as sediment and P loadings to the creek. Practices aimed at increasing year-round soil cover would be most effective in decreasing sediment and P losses in this watershed. In the second part of this article, we describe a method for characterizing land-cover change in a dynamic urban fringe watershed. The GIS method we developed for the Blackberry Creek, Illinois, watershed will allow us to better account for temporal changes in land use, specifically corn and soybean cover, on an annual basis and to improve on the modeling of watershed processes shown for the Muddy Creek watershed. Our model can be used at different levels of planning with minimal data preprocessing, easily accessible data, and adjustable output scales.     

EMPIRICAL MODELING OF HYDROLOGIC AND NFS POLLUTANT FLUX IN AN URBANIZING BASIN1

ABSTRACT: Long term effects of precipitation and land use/land cover on basin outflow and nonpoint source (NFS) pollutant flux are presented for up to 24 years for a rapidly developing headwater basin and three adjacent headwater basins on the urban fringe of Washington, D.C. Regression models are developed to describe the annual and seasonal responses of basin outflow and IMPS pollutant flux to precipitation, mean impervious surface (IS), and land use. To quantify annual change in mean IS, a variable called delta IS is created as a temporal indicator of urban soil disturbance. Hydrologic models indicate that total annual surface outflow is significantly associated with precipitation and mean IS (r²= 0.65). Seasonal hydrologic models reveal that basin outflow is positively associated with IS during the summer and fall growing season (June to November). NPS pollutant flux models indicate that total and storm total suspended solids (TSS) flux are significantly associated with precipitation and urban soil disturbance in all seasons. Annual NPS total nitrogen flux is significantly associated with both urban and agricultural soil disturbance (r²= 0.51). Seasonal models of phosphorus flux indicate a significant association of total phosphorus flux with urban soil disturbance during the growing season. Total soluble phosphorus (TSP) flux is significantly associated with IS (r²= 0.34) and urban and agricultural soil disturbance (r²= 0.58). In urbanizing Cub Run basin, annual TSP concentrations are significantly associated with IS and cultivated agriculture (r²= 0.51).     

Forecasting the Effects of Land-Use Change on Forest Rodents in Indiana

Forest cover in the upper Wabash River basin in Indiana was fragmented due to agricultural conversion beginning more than 175 years ago. Currently, urban expansion is an important driver of land-use change in the basin. A land transformation model was applied to the basin to forecast land use from 2000 to 2020. We assessed the effect of this projected land-use change scenario on five forest rodent species at three scales: using occupancy models at the patch level, proportional occupancy models at the landscape level, and ecologically scaled landscape indices to assess the change in connectivity at the watershed level. At the patch and landscape scales, occupancy models had low predictability but suggest that gray squirrels are most susceptible to land-use change. At the watershed scale, declines in connectivity did not correspond with the decline of forest. This study highlights the importance of map resolution and consideration of matrix elements in constructing forecast models. Unforeseen drivers of land use, such as changing economic incentives, may also have important ramifications.     

Agricultural BMP Effectiveness and Dominant Hydrological Flow Paths: Concepts and a Review

We present a conceptual framework that relates agricultural best management practice (BMP) effectiveness with dominant hydrological flow paths to improve nonpoint source (NPS) pollution management. We use the framework to analyze plot, field and watershed scale published studies on BMP effectiveness to develop transferable recommendations for BMP selection and placement at the watershed scale. The framework is based on the location of the restrictive layer in the soil profile and distinguishes three hydrologic land types. Hydrologic land type A has the restrictive layer at the surface and BMPs that increase infiltration are effective. In land type B1, the surface soil has an infiltration rate greater than the prevailing precipitation intensity, but there is a shallow restrictive layer causing lateral flow and saturation excess overland flow. Few structural practices are effective for these land types, but pollutant source management plans can significantly reduce pollutant loading. Hydrologic land type B2 has deep, well‐draining soils without restrictive layers that transport pollutants to groundwater via percolation. Practices that increased pollutant residence time in the mixing layer or increased plant water uptake were found as the most effective BMPs in B2 land types. Matching BMPs to the appropriate land type allows for better targeting of hydrologically sensitive areas within a watershed, and potentially more significant reductions of NPS pollutant loading.     

Assessing Impacts of Typhoons and the Chi-Chi Earthquake on Chenyulan Watershed Landscape Pattern in Central Taiwan Using Landscape Metrics

The Chi-Chi earthquake (M_L = 7.3) occurred in the central part of Taiwan on September 21, 1999. After the earthquake, typhoons Xangsane and Toraji produced heavy rainfall that fell across the eastern and central parts of Taiwan on November 2000 and July 2001. This study uses remote sensing data, landscape metrics, multivariate statistical analysis, and spatial autocorrelation to assess how earthquake and typhoons affect landscape patterns. It addresses variations of the Chenyulan watershed in Nantou County, near the earthquake’s epicenter and crossed by Typhoon Toraji. The subsequent disturbances have gradually changed landscape of the Chenyulan watershed. Disturbances of various types, sizes, and intensities, following various tracks, have various effects on the landscape patterns and variations of the Chenyulan watershed. The landscape metrics that are obtained by multivariate statistical analyses showed that the disturbances produced variously fragmented patches, interspersed with other patches and isolated from patches of the same type across the entire Chenyulan watershed. The disturbances also affected the isolation, size, and shape-complexity of patches at the landscape and class levels. The disturbances at the class level more strongly affected spatial variations in the landscape as well as patterns of grasslands and bare land, than variations in the watershed farmland and forest. Moreover, the earthquake with high magnitude was a starter to create these landscape variations in space in the Chenyulan watershed. The cumulative impacts of the disturbances on the watershed landscape pattern had existed, especially landslides and grassland in the study area, but were not always evident in space and time in landscape and other class levels.     

Effect of Land-Use Patterns on Total Nitrogen Concentration in the Upstream Regions of the Haihe River Basin, China

Nutrient loading into rivers is generally increased by human-induced land-use changes and can lead to increased surface water pollution. Understanding the extent to which land-use patterns influence nutrient loading is critical to the development of best-management practices aimed at water-quality improvement. In this study, we investigated total nitrogen (total N) concentration as a function of land-use patterns and compared the relative significance of the identified land-use variables for 26 upstream watersheds of the Haihe River basin. Seven land-use intensity and nine landscape complexity variables were selected to form the land-use pattern metrics on the landscape scale. After analyzing the significance of the land-use pattern metrics, we obtained five dominant principal components: human-induced land-use intensity, landscape patch-area complexity, area-weighted landscape patch-shape complexity, forest and grassland area, and landscape patch-shape complexity. A linear regression model with a stepwise selection protocol was used to identify an optimal set of land-use pattern predictors. The resulting contributions to the total N concentration were 50% (human-induced land-use intensity), 23.13% (landscape patch-shape complexity), 14.38% (forest and grassland area), and 12.50% (landscape patch-area complexity), respectively. The regression model using land-use measurements can explain 87% of total N variability in the upstream regions of Haihe River. The results indicated that human-related land-use factors, such as residential areas, population, and road density, had the most significant effect on N concentration. The agricultural area (30.1% of the study region) was not found to be significantly correlated with total N concentration due to little irrigative farmland and rainfall. Results of the study could help us understand the implications of potential land-use changes that often occur as a result of the rapid development in China.     

Land Use, Climate and Transport of Nutrients: Evidence Emerging from the Lake Vicocase Study

Soil erosion is a Europe-wide problem, causing both loss of soil fertility and pollution due to nutrient transport into water bodies. This process is particularly important in the Mediterranean area, where the climate, characterised by long periods of drought followed by intense precipitation, favours soil erosion. Research carried out in this field has amply described this process, showing that climate and land use/land cover (LU/LC) are the two main factors regulating this phenomenon. However, the interaction between these factors is complex and experimental research is needed to understand the nutrient loads deriving from different land uses. This paper shows the results of a long-term monitoring project carried out in the Lake Vico basin (central Italy), using high resolution data and runoff samples to determine the phosphorus (P) export from four different LU/LC classes resulting from the same climatic event. The results highlight the fundamental role that LU/LC plays in terms of phosphorus load. Furthermore, the results appear to indicate that the maximum rainfall registered for 30′ (I _{30, max}), rather than the total quantity of precipitation, has the greatest effect on levels of erosion, and consequently on the migration of nutrients rather than the total quantity of precipitation can affect on erosion and therefore the migration of nutrients. These data could contribute to scientific planning support for land management choices aimed at controlling water pollution from non-point pollution sources.     

COMPARATIVE EVALUATION OF LAND COVER DATA SOURCES FOR EROSION PREDICTION1

ABSTRACT: A fundamental problem in protecting surface drinking water supplies is the identification of sites highly susceptible to soil erosion and other forms of nonpoint source (NPS) pollution. The New York City Department of Environmental Protection is trying to identify erodible sites as part of a program aimed at avoiding costly filtration. New York City's 2,000 square mile watershed system is well suited for analysis with geographic information systems (GIS); an increasingly important tool to determine the spatial distribution of sensitive NPS pollution areas. This study used a GIS to compare three land cover sources for input into the Modified Universal Soil Loss Equation (MUSLE), a model estimating soil loss from rangeland and forests, for a tributary watershed within New York City's water supply system. Sources included both conventional data (aerial photography) and Landsat data (MSS and TM images). Although land cover classifications varied significantly across these sources, location-specific and aggregate watershed predictions of the MUSLE were very similar. We conclude that using Landsat TM imagery with a hybrid classification algorithm provides a rapid, objective means of developing large area land cover databases for use in the MUSLE, thus presenting an attractive alternative to photo interpretation.     

IDENTIFICATION OF CRITICAL NONPOINT POLLUTION SOURCE AREAS USING GEOGRAPHIC INFORMATION SYSTEMS AND WATER QUALITY MODELING1

n integrated approach coupling water quality computer simulation modeling with a geographic information system (GIS) was used to delineate critical areas of nonpoint source (NPS) pollution at the watershed level. Two simplified pollutant export models were integrated with the Virginia Geographic Information System (VirGIS) to estimate soil erosion, sediment yield, and phosphorus (P) loading from the Nomini Creek watershed located in Westmoreland County, Virginia. On the basis of selected criteria for soil erosion rate, sediment yield, and P loading, model outputs were used to identily watershed areas which exhibit three categories (low, medium, high) of non-point source pollution potentials. The percentage of the watershed area in each category, and the land area with critical pollution problems were also identified. For the 1505-ha Nomini Creek watershed, about 15, 16, and 21 percent of the watershed area were delineated as sources of critical soil erosion, sediment, and phosphorus pollution problems, respectively. In general, the study demonstrated the usefulness of integrating GIS with simulation modeling for nonpoint source pollution control and planning. Such techniques can facilitate making priorities and targeting nonpoint source pollution control programs.     

Landscape metrics and estuarine sediment contamination in the mid-Atlantic and southern New England regions

In a previously published study, quantitative relationships were developed between landscape metrics and sediment contamination for 25 small estuarine systems within Chesapeake Bay. These analyses have been extended to include 75 small estuarine systems across the mid-Atlantic and southern New England regions of the USA. Because of the different characteristics and dynamics of the estuaries across these regions, adjustment for differing hydrology, sediment characteristics, and sediment origins were included in the analysis. Multiple linear regression with stepwise selection was used to develop statistical models for sediment metals, organics, and total polycyclic aromatic hydrocarbons (PAHs). The landscape metrics important for explaining the variation in sediment metals levels (R2 = 0.72) were the percent area of nonforested wetlands (negative contribution), percent area of urban land, and point source effluent volume and metals input (positive contributions). The metrics important for sediment organics levels (R2 = 0.5) and total PAHs (R2 = 0.46) were percent area of urban land (positive contribution) and percent area of nonforested wetlands (negative contribution). These models included silt-clay content (metals) or total organic C (organics, total PAHs) of sediments and grouping by estuarine hydrology, suggesting the importance of sediment characteristics and hydrology in mitigating the influence of the landscape metrics on sediment contamination levels. The overall results from this study are indicative of how statistical models can be developed relating landscape metrics to estuarine sediment contamination for distributions of land cover and point source discharges.     

Regionalization of Landscape Pattern Indices Using Multivariate Cluster Analysis

Regionalization, or the grouping of objects in space, is a useful tool for organizing, visualizing, and synthesizing the information contained in multivariate spatial data. Landscape pattern indices can be used to quantify the spatial pattern (composition and configuration) of land cover features. Observable patterns can be linked to underlying processes affecting the generation of landscape patterns (e.g., forest harvesting). The objective of this research is to develop an approach for investigating the spatial distribution of forest pattern across a study area where forest harvesting, other anthropogenic activities, and topography, are all influencing forest pattern. We generate spatial pattern regions (SPR) that describe forest pattern with a regionalization approach. Analysis is performed using a 2006 land cover dataset covering the Prince George and Quesnel Forest Districts, 5.5 million ha of primarily forested land base situated within the interior plateau of British Columbia, Canada. Multivariate cluster analysis (with the CLARA algorithm) is used to group landscape objects containing forest pattern information into SPR. Of the six generated SPR, the second cluster (SPR2) is the most prevalent covering 22% of the study area. On average, landscapes in SPR2 are comprised of 55.5% forest cover, and contain the highest number of patches, and forest/non-forest joins, indicating highly fragmented landscapes. Regionalization of landscape pattern metrics provides a useful approach for examining the spatial distribution of forest pattern. Where forest patterns are associated with positive or negative environmental conditions, SPR can be used to identify similar regions for conservation or management activities.     

Assessing Watershed-Scale, Long-Term Hydrologic Impacts of Land-Use Change Using a GIS-NPS Model

Land-use change, dominated by an increase in urban/impervious areas, has a significant impact on water resources. This includes impacts on nonpoint source (NPS) pollution, which is the leading cause of degraded water quality in the United States. Traditional hydrologic models focus on estimating peak discharges and NPS pollution from high-magnitude, episodic storms and successfully address short-term, local-scale surface water management issues. However, runoff from small, low-frequency storms dominates long-term hydrologic impacts, and existing hydrologic models are usually of limited use in assessing the long-term impacts of land-use change. A long-term hydrologic impact assessment (L-THIA) model has been developed using the curve number (CN) method. Long-term climatic records are used in combination with soils and land-use information to calculate average annual runoff and NPS pollution at a watershed scale. The model is linked to a geographic information system (GIS) for convenient generation and management of model input and output data, and advanced visualization of model results. The L-THIA/NPS GIS model was applied to the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana, USA. Historical land-use scenarios for 1973, 1984, and 1991 were analyzed to track land-use change in the watershed and to assess impacts on annual average runoff and NPS pollution from the watershed and its five subbasins. For the entire watershed between 1973 and 1991, an 18% increase in urban or impervious areas resulted in an estimated 80% increase in annual average runoff volume and estimated increases of more than 50% in annual average loads for lead, copper, and zinc. Estimated nutrient (nitrogen and phosphorus) loads decreased by 15% mainly because of loss of agricultural areas. The L-THIA/NPS GIS model is a powerful tool for identifying environmentally sensitive areas in terms of NPS pollution potential and for evaluating alternative land use scenarios for NPS pollution management.     

An assessment of landscape characteristics affecting estuarine nitrogen loading in an urban watershed

Exploring the quantitative association between landscape characteristics and the ecological conditions of receiving waters has recently become an emerging area for eco-environmental research. While the landscape-water relationship research has largely targeted on inland aquatic systems, there has been an increasing need to develop methods and techniques that can better work with coastal and estuarine ecosystems. In this paper, we present a geospatial approach to examine the quantitative relationship between landscape characteristics and estuarine nitrogen loading in an urban watershed. The case study site is in the Pensacola estuarine drainage area, home of the city of Pensacola, Florida, USA, where vigorous urban sprawling has prompted growing concerns on the estuarine ecological health. Central to this research is a remote sensor image that has been used to extract land use/cover information and derive landscape metrics. Several significant landscape metrics are selected and spatially linked with the nitrogen loading data for the Pensacola bay area. Landscape metrics and nitrogen loading are summarized by equal overland flow-length rings, and their association is examined by using multivariate statistical analysis. And a stepwise model-building protocol is used for regression designs to help identify significant variables that can explain much of the variance in the nitrogen loading dataset. It is found that using landscape composition or spatial configuration alone can explain most of the nitrogen loading variability. Of all the regression models using metrics derived from a single land use/cover class as the independent variables, the one from the low density urban gives the highest adjusted R-square score, suggesting the impact of the watershed-wide urban sprawl upon this sensitive estuarine ecosystem. Measures towards the reduction of non-point source pollution from urban development are necessary in the area to protect the Pensacola bay ecosystem and its ecosystem services.     

Implications of Land Use/Land Cover Change in the Buffer Zone of a National Park in the Tropical Andes

The impacts of land use and land cover (LULC) change in buffer zones surrounding protected ecological reserves have important implications for the management and conservation of these protected areas. This study examines the spatial and temporal patterns of LULC change along the boundary of Rio Abiseo National Park in the Northern Peruvian Andes. Landscape change within four ecological zones was evaluated based on trends expected to occur between 1987 and 2001. Landsat TM and ETM imagery were used to produce LULC classification maps for both years using a hybrid supervised/unsupervised approach. LULC changes were measured using landscape metrics and from-to change maps created by post-classification change detection. Contrary to expectations, tropical upper wet montane forest increased despite being threatened by human-induced fires and cattle grazing of the highland grasslands inside the park. Within the park’s buffer zone, tropical moist forest remnants were fragmented into more numerous and smaller patches between 1987 and 2001; this was in part due to conversion into agricultural land. The methods used in this study provide an effective way to monitor LULC change detection and support the management of protected areas and their surrounding environments.     

A Water Quality Model for Regional Stream Assessment and Conservation Strategy Development

Non-point-source (NPS) pollution remains the primary source of stream impairment in the United States. Many problems such as eutrophication, sedimentation, and hypoxia are linked with NPS pollution which reduces the water quality for aquatic and terrestrial organisms. Increasingly, NPS pollution models have been used for landscape-scale pollution assessment and conservation strategy development. Our modeling approach functions at a scale between simple landscape-level assessments and complex, data-intensive modeling by providing a rapid, landscape-scale geographic information system (GIS) model with minimal data requirements and widespread applicability. Our model relies on curve numbers, literature-derived pollution concentrations, and land status to evaluate total phosphorus (TP), total nitrogen (TN), and suspended solids (SS) at the reach scale. Model testing in the Chesapeake Bay watershed indicated that predicted distributions of water quality classes were realistic at the reach scale, but precise estimates of pollution concentrations at the local scale can have errors. Application of our model in the tributary watersheds along Lake Ontario suggested that it is useful to managers in watershed planning by rapidly providing important information about NPS pollution conditions in areas where large data gaps exist, comparisons among stream reaches across numerous watersheds are required, or regional assessments are sought.