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PREDICTING NUTRIENT AND SEDIMENT LOADINGS TO STREAMS FROM LANDSCAPE METRICS: A MULTIPLE WATERSHED STUDY FROM THE UNITED STATES MID-ATLANTIC REGION
Citation:
Jones, K B., A C. Neale, M S. Nash, R. D. van Remortel, J D. Wickham, K. H. Riitters, AND R. V. O'Neill. PREDICTING NUTRIENT AND SEDIMENT LOADINGS TO STREAMS FROM LANDSCAPE METRICS: A MULTIPLE WATERSHED STUDY FROM THE UNITED STATES MID-ATLANTIC REGION. LANDSCAPE ECOLOGY 16(4):301-312, (2001).
Impact/Purpose:
The primary objectives of this research are to:
Develop methodologies so that landscape indicator values generated from different sensors on different dates (but in the same areas) are comparable; differences in metric values result from landscape changes and not differences in the sensors;
Quantify relationships between landscape metrics generated from wall-to-wall spatial data and (1) specific parameters related to water resource conditions in different environmental settings across the US, including but not limited to nutrients, sediment, and benthic communities, and (2) multi-species habitat suitability;
Develop and validate multivariate models based on quantification studies;
Develop GIS/model assessment protocols and tools to characterize risk of nutrient and sediment TMDL exceedence;
Complete an initial draft (potentially web based) of a national landscape condition assessment.
This research directly supports long-term goals established in ORDs multiyear plans related to GPRA Goal 2 (Water) and GPRA Goal 4 (Healthy Communities and Ecosystems), although funding for this task comes from Goal 4. Relative to the GRPA Goal 2 multiyear plan, this research is intended to "provide tools to assess and diagnose impairment in aquatic systems and the sources of associated stressors." Relative to the Goal 4 Multiyear Plan this research is intended to (1) provide states and tribes with an ability to assess the condition of waterbodies in a scientifically defensible and representative way, while allowing for aggregation and assessment of trends at multiple scales, (2) assist Federal, State and Local managers in diagnosing the probable cause and forecasting future conditions in a scientifically defensible manner to protect and restore ecosystems, and (3) provide Federal, State and Local managers with a scientifically defensible way to assess current and future ecological conditions, and probable causes of impairments, and a way to evaluate alternative future management scenarios.
Description:
There has been an increasing interest in evaluating the relative condition or health of water resources at regional and national scales. Of particular interest is an ability to identify those areas where surface and ground waters have the greatest potential for high levels of nutrient and sediment loadings. High levels of nutrient and sediment loadings can have adverse effects on both humans and aquatic ecosystems. We analyzed the ability of landscape metrics generated from readily available, spatial data to predict nutrient and sediment yield to streams in the Mid-Atlantic Region in the United States. We used landscape metric coverages generated from a previous assessment of the entire Mid-Atlantic Region, and a set of stream sample data from the U.S. Geological Survey. Landscape metrics consistently explained high amounts of variation in nitrogen yields to streams (65 to 86% of the total variation). They also explained 73 and 79% of the variability in dissolved phosphorus and suspended sediment.
Although there were differences in the nitrogen, phosphorus, and sediment models, the amount of agriculture, riparian forests, and atmospheric nitrate deposition (nitrogen only) consistently explained a high proportion of the variation in these models. Differences in the models also suggest potential differences in landscape-stream relationships between ecoregions or biophysical settings. The results of the study suggest that readily available, spatial data can be used to assess potential nutrient and sediment loadings to streams, but that it will be important to develop and test landscape models in different biophysical settings.
URLs/Downloads:
JOURNAL ARTICLE..PDF (PDF, NA pp, 30 KB, about PDF)http://link.springer.com/article/10.1023/A%3A1011175013278
