Impact/Purpose:

The overarching objective is to develop and test landscape indicator statistical models for condition of streams and aquatic biota in relation to pesticides, nutrients, sediments and toxic substances, nationwide. The indicator models will serve as tools for managers who want consistent methods to compare potential impacts on streams within a biophysical region for differing landscape patterns. To accomplish this objective, several sub objectives will be important:

Develop landscape indicator statistical models of stream vulnerability for selected regions of the U.S., beginning with the Mid-Atlantic Coastal Streams; studies in the Midwest, California, and the Southeast will follow.

Demonstrate the application of the landscape indicator models for the ranking of watersheds, the identification of "hot spots," and the evaluation of management options using projected future scenarios of land use for the study areas selected above.

Develop statistical distributions for physical characteristics of small water bodies for use in OPP modeling.

Leverage resources for this research by incorporating existing data into the model development process, and by sharing field study costs with other projects in the same geographic areas.

This task represents a topic area within the Landscape Sciences research program which is described in A National Assessment of Landscape Change and Impacts to Aquatic Resources. A 10-Year Research Strategy for the Landscape Sciences Program, EPA/600/R-00/001. It also supports the Regional Vulnerability Assessment (ReVA) Program.

Besides being responsive to the Office of Pesticide Programs, this research directly supports long-term goals established in ORD's multi-year research plans related to GPRA Goal 2 (Water Quality) and GPRA Goal 8.1.1 (Sound Science/Ecological Research). Relative to the GPRA Goal 2 multi-year plan, this research will "provide tools to assess and diagnose impairment in aquatic systems and the sources of associated stressors" and "provide the tools to restore and protect aquatic ecosystems and to forecast the ecological, economic, and human health outcomes of alternative solutions" (Long Term Research Goals 2 and 3). Relative to the Goal 8 multi-year plan, this research will develop and demonstrate methods to provide states, tribes, and federal, state and local managers with abilities to: (1) assess the condition of waterbodies in a scientifically-defensible and representative way, while allowing for aggregation and assessment of trends at multiple scales; (2) diagnose cause and forecast future condition in a scientifically defensible fashion to more effectively protect and restore valued ecosystems; and (3) assess current and future ecological conditions, probable causes of impairments, and management alternatives.

Description:

Evaluating environmental conditions at community, watershed, regional, and national scales is a growing interest among Federal agencies, states, and the public. At the same time, the relatively high cost of collecting environmental data has limited the implementation of regional- and national-scale monitoring programs. Alternatives to, and adaptations of, traditional monitoring approaches are possible using high-resolution, remotely-sensed data and derivative products now available. One alternative applies a combination of concepts from landscape ecology, hydrology, and geography in conjunction with spatial data and geographic information system (GIS) technology to the environmental assessment process. Landscape metrics are central to this approach. These metrics describing biophysical properties within an area, such as percent forest or agriculture in a watershed or county, can be computed at relatively low cost over large areas using satellite-derived land use data. The landscape metrics are combined with stream data and used to develop landscape indicator statistical models with the stream data as the dependent variables and the landscape metrics as the explanatory variables. Other biophysical spatial data (e.g., soil characteristics, roads, or U.S. Census data) can also be used as explanatory data. The landscape indicator models enable each stream from a population of streams in the study area to be ranked relative to the other streams, according to level of concern for water quality or stream condition. Resources for monitoring or mitigation then can be spent accordingly.

The focus for these studies is pesticides and nutrients in small freshwater streams and water bodies. Pesticides were selected because understanding their occurrence and distribution in water bodies that may be used for drinking water is important for development of the Food Quality Protection Act regulatory processes. Nutrients were selected because they are principal pollutants causing water quality problems according to the Clean Water Act 305b listings for states nationwide. Pond and small water body (SWB) physical characteristics were selected because these water body features are used in the Office of Pesticide Program (OPP) models for pesticide registration decision making.

Landscape metrics are typically derived from remote sensing imagery and other mapped information and include land use and land cover; soils information, locations of streams, lakes, and other water bodies; topography; underlying geology; and locations of industrial facilities, transportation corridors, and other man-made features. The interpretation of this information is augmented by our understanding of the physical processes affecting chemicals in the environment and the capability of Geographic Information Systems to manipulate the spatial information. The detailed relationships between landscape settings and the associated conditions in streams, and how these relationships vary for different climates, ecoregions, and biophysical settings nationwide, are an active area for research. Thus, the fundamental goal of this task is to empirically investigate relationships between proposed landscape indicators and pesticides, nutrients, sediments, toxic substance concentrations and biotic condition in streams. Over the time frame from 1998 to 2011, studies are planned in selected areas nationwide, beginning with the Mid-Atlantic Coastal Streams in 2000, followed by studies in the Midwest, Indiana, California, and the Southeast. These Landscape Investigations for Pesticides Studies (LIPS) will combine evaluation of existing data with collection of additional data to develop landscape indicator models that characterize status and vulnerability of streams and to measure the physical characteristics of ponds and small water bodies. These landscape indicator models will then be applied to rank watersheds, identify "hot spots," and evaluate management options. Data for SWBs will be used in the modeling performed by OPP. Specific geographic test areas for these application activities will be selected in consultation with our stakeholders (Office of Pesticide Programs, Office of Water, EPA Regional Offices, and the states). Results will be delivered as journal articles followed by summaries, fact sheets, and databases designed to reach the general public, environmental managers, and other research scientists, respectively.

Record Details:

Record Type:PROJECT

Start Date:10/01/1991

Projected Completion Date:09/01/2011

Record ID: 29224

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Project Information:

Progress :In FY98, for Landscape Indicators for Pesticides Study Mid-Atlantic Coastal Streams (LIPS-MACS), the USGS interagency agreement for the Mid-Atlantic collaboration was initiated (EPA); the analysis of existing pesticides data was completed (EPA, USGS); and an extensive literature review was completed (EPA).

In FY99, the LIPS-MACS research plan was developed, reviewed and revised. (Note: This plan addresses both tasks 5451 and 5448.) In addition, sensitivity studies were conducted at three sites to determine timing of high/low flow conditions and identify optimum sampling times (USGS); the hydrogeologic framework which underlies the statistical sampling design was proposed and reviewed (USGS); existing GIS coverages were augmented to include the New Jersey and southern North Carolina portions of the Coastal Plain (EPA); OPP headquarters staff were briefed on the project; meetings were held with NERL-ERD (Athens) and NERL-EERD (Cincinnati) staff about modeling and macroinvertebrate sampling, respectively (EPA); and the analysis of watersheds to select sampling sites was completed (EPA and USGS). A poster (Landscape Indicators for Pesticides in Mid-Atlantic Coastal Streams - 8/99) was also completed/presented.

In FY00, the LIPS-MACS field study was conducted (EPA and USGS), OPP and OWOW staff were briefed on the study twice. Briefings on study were also presented at the Maryland Department of Natural Resources and the U.S. Department of Agriculture National Agricultural Statistics Service Maryland State Office, and to some staff of EPA Region 3. A website and website announcement were created for the project. The peer-reviewed research plan is: Testing Landscape Indicators for Stream Vulnerability to Pesticides and Nutrients; Landscape Indicators for Pesticides Study for Mid-Atlantic Coastal Streams.

In FY01, once the laboratory analyses of the field study samples were complete, most of the data compilation and the statistical analyses focused on evaluating the performance of several new approaches to the landscape indicator development process, summarized in Landscape Approach for Assessing Stream Condition: Landscape Indicators for Pesticide Study Mid-Atlantic Coastal Streams (TIP # 01-126, APM 130, Journal Article). This paper describes the successful implementation of the unequal probability, stratified random study design; integration of the hydrogeologic framework into the design process; sampling during baseflow conditions; incorporation of soil metrics into the landscape indicator statistical models; and use of data from a one-time sampling effort to develop landscape indicator models for pesticides and nutrients. Key results are listed below:

The LIPS-MACS unequal probability, stratified random sampling design effectively provided a gradient of landscape conditions (undeveloped to developed land use) for the landscape indicator model analyses, and also provided statistically representative samples to estimate the condition of the Mid-Atlantic Streams with respect to pesticides and nutrients at the subregional scale.

The landscape indicator models were developed using stepwise regression analyses with stream concentrations of nutrients, herbicides, and chloride as the dependent variables, and landscape and soil metrics as the independent variables. The resulting statistical models explained 44% to 86% of the variability. Both landscape and soil metrics were included in the models.

In FY02, the landscape indicator models were improved using an alternative set of variables developed using factor analysis. The procedure for selecting the sites for the LIPS-MACS study was evaluated in terms of the sites actually sampled. Data sets and references were assembled for the Midwest for the Ohio and Missouri River Basins. The principal point of contact for the Midwest within the USGS was identified (Minnesota State Office), and the next interagencyagreement for the Midwesagre

Relevance :The results of this research will be landscape indicator statistical models and monitoring design tools which are relevant to performing drinking water quality risk assessments for pesticides under the Food Quality Protection Act; performing ecological assessments; and determining Total Maximum Daily Load allocations for nutrients and pesticides under the Clean Water Act. The landscape indicator models will be applied to perform regional prioritization of stream conditions, prepare area-wide assessments, identify "hot spots", and evaluate "what if" scenarios. These applications will be demonstrated with examples developed through collaboration with stakeholders for each of the study areas. The data from the Pond Study will be used by the OPP in the modeling used to support pesticide registration decisions.

Clients :Ingrid Sunzenauer, Elizabeth Leovey, Jim Hetrick, James Felkel, Mark Corbin, Office of Pesticide Programs; Chuck Sutfin, Laura Gabanski, Doug Norton, Office of Water; Ron Landy, EPA Region 3

Project IDs:

ID Code :5448

Project type :OMIS