TIP1AM Ecological Epidemiology in Action (Part 1)|
Tuesday, 15 November 2005: 8:00 AM - 11:40 AM in 349-350
IP023 (NOR-1117-755303) The Evolution of the Causal Analysis/Diagnosis Decision Information System (CADDIS).
Start time: 8:00 AM
Norton, S1, Suter, G2, Cormier, S2, 1 U.S. Environmental Protection Agency, Washington, DC, USA2 U.S. Environmental Protection Agency, Cincinnati, OH, USA
The Causal Analysis/Diagnosis Decision Information System (CADDIS) (http://www.epa.gov/caddis) is a web-based decision support system that helps investigators in the regions, states and tribes find, access, use and share information to determine the causes of biological impairments in aquatic systems. It is based on the USEPA's Stressor Identification process, which is a formal method for identifying causes. This presentation describes how CADDIS and stressor identification have evolved in response to feedback from case studies and peer reviews. The step-by-step guide to stressor identification that is featured in CADDIS reflects current thinking on how best to develop a defensible causal analysis. In addition to the guide, CADDIS includes downloadable worksheets and examples, a library of conceptual models, and links to helpful information. Future plans include modules on deriving empirical stressor-response relationships; stressor-specific tolerance values; and databases and syntheses of relevant literature on sediments and toxic metals. Future versions will be developed incrementally and iteratively, and frequent user input and feedback will be essential to the system's success.
IP024 (SCH-1117-748282) Using conceptual models to guide causal analysis and communication.
Start time: 8:00 AM
Schofield, K1, 1 AAAS Risk Policy Fellow, NCEA-EPA
The initial step in the U.S. Environmental Protection Agency′s stressor identification process is to list candidate causes of the biological impairment. A key component of this is the development of conceptual models, or graphic representations of the potential links between sources, stressors, and biological responses. Development of conceptual models at the beginning of the stressor identification process provides participants (scientists, managers, and the public) a framework for first brainstorming possible causal pathways, and then explicitly laying out hypothesized pathways of concern in a clear, easy-to-follow manner. Although conceptual model construction appears relatively straightforward, in practice there are many challenges (e.g., deciding how much mechanistic detail to incorporate into the model). Once developed, conceptual models can serve as valuable tools throughout causal analysis. Pathways lacking adequate data can be identified, enabling data-gathering efforts to be directed more effectively. As evidence accumulates for or against particular pathways, conceptual models can be annotated to track changes in the plausibility of candidate causes. Perhaps most important, conceptual models can be invaluable communication devices, allowing the public to see how their input is incorporated into causal analysis, and providing a window into the thought processes guiding stressor identification. Use of the models as communication tools can be aided by the development of web-based hierarchical, or layered, models. Such models allow viewers to ′query′ simple models for increasingly detailed information (e.g., specific mechanisms linking sources, stressors, and responses; supporting literature for specific causal pathways; specific taxa likely to be affected by a given stressor). This layered design can enable conceptual models to expand from relatively simple schematics into easily manipulated information management devices.
IP025 (COR-1117-814684) Primer for ecological epidemiological projects: USEPA stressor identification guidance in a nutshell.
Start time: 8:00 AM
Cormier, S1, Suter, G1, 1 U.S. Environmental Protection Agency, National Center for Environmental Assessment
Determining the causes of ecological effects is daunting. The many potential interactions among living things and their environment create webs of possible interactions. Yet, determining the probable causes of biological impairment is required by US law. The US EPA published the Stressor Identification Guidance Document in 2000 to ensure a credible process existed for determining causes of biological impairment in aquatic systems. Recently the USEPA has developed the CADDIS website to make this process easier to perform. One component of the website is a convenient handbook to reference to the stressor identification process. It provides brief descriptions and illustrations of the types of considerations used for elimination, diagnosis and strength of evidence. It also has illustrated scoring sheets for strength of evidence. The handbook makes the stressor identification process more accessible and transparent.
IP026 (PAU-1117-835968) Quantitative methods for stressor identification in biological impairment for freshwater streams.
Start time: 8:00 AM
Paul, J, Shaw-Allen, P2, Cormier, S3, Suter, G2, Norton, S4, Kurtz, J5, 2 NCEA/ORD, USEPA, Cincinnati, OH, USA3 NERL/ORD, USEPA, Cincinnati, OH4 NCEA/ORD, USEPA, Washington, DC, USA5 NHEERL/ORD, USEPA, Gulf Breeze, FL, USA
A common element across all of the case studies presented in this special poster session is the quantitative methods used to provide the weight of evidence for identification of possible stressors are the cause of biological impairment in the freshwater streams. All of the quantitative methods are limited by the data that were available for the case studies. Typical limitations include, but are not limited to, small number of samples, non-concurrent acquisition of measures at a sampling site, missing data for some indicators, and lack of a probability design for the sample site selection. All of the case studies were able to utilize stressor and response indicators in the analyses. The quantitative methods included basic exploratory data analysis techniques, such as means, medians, correlations, standard deviations, ranges, comparisons of groups of sites (e.g., with reference sites), scatter plots, correlations, regressions, and associations, and other methods such as quantile regression, conditional probability, and various multivariate techniques. Examples form the various case studies are used to illustrate how these various techniques were in the weight of evidence.
IP027 (SHA-1117-824687) Causal Analysis/Diagnosis Decision Information System for determining the causes of biological impairments in aquatic systems: Tools for evaluating metals as causal agents.
Start time: 8:00 AM
Shaw-Allen, P1, Norton, S1, Cormier, S1, Suter, G1, 1 U.S. Environmental Protection Agency, Office of Research and Development, National Center for Environmental Assessment
Over a thousand US waters are listed by states as biologically impaired. For many of these, the cause of the impairment is also reported as "unknown". Exceedence of metals criteria is the second most common reason for listing a water body as impaired, and therefore metals are likely to be a common cause of the biological impairments. Before an appropriate action can be taken to address a biological impairment, its primary cause must be determined. Defensible causal analyses require knowledge of the mechanisms, symptoms, and stressor-response relationships for various specific stressors as well as the ability to use that knowledge to draw appropriate conclusions. Components developed for the evaluation of metals as causes of biological impairments will be available through the Causal Analysis/Diagnosis Decision Information System (CADDIS). CADDIS is a web-based decision support system that will help investigators in the USEPA regions, states, and tribes find, access, organize, and share information useful for causal evaluations in aquatic systems. It is based on the USEPA's Stressor Identification process, which is a formal method for identifying causes of impairments in aquatic systems. Tools developed for the assessment of metals as causal agents include empirical stressor-response relationships such as species sensitivity distributions and exposure and tissue concentration response models. Species sensitivity distributions are interpreted in terms of consistency of taxa location among distributions as well as evenness of guild representation along these distributions. Syntheses of existing field data for metals effects under complex environmental conditions are also presented. Future versions will be developed incrementally and iteratively, and frequent user input and feedback will be essential to the system's success.
IP028 (KUR-1117-723967) Causal analysis at work: lessons learned from case studies.
Start time: 8:00 AM
Kurtz, J1, Cormier , S2, Suter, G3, 1 U.S. Environmental Protection Agency, ORD/NHEERL, Gulf Breeze, FL, USA2 U.S. Environmental Protection Agency, ORD/NERL, Cincinnati, Ohio, USA3 U.S. Environmental Protection Agency, ORD/NCEA, Cincinnati, Ohio, USA
During a recent USEPA workshop, state resource management agencies from Iowa, Washington, Mississippi, Maine, West Virginia and Connecticut were canvassed for recommendations that could improve application of the Stressor Identification (SI) guidance to identify the causes of biological impairments in streams. Four main themes emerged from the discussion: 1. the regulatory context, 2. improvements to the guidance, 3. efficiency, and 4. methodological issues. Regulatory context issues arise because scientific conclusions are subject to change when new data or evidence becomes available, but once conclusions are provided they may become the foundation for TMDLs, permits or remediation actions which are not as flexible. Improvements to the SI guidance were suggested for enhancement and elaboration of certain concepts including: identification and definition of candidate causes especially when multiple agents may be interacting, developing conceptual models, using scoring sheets, determining regional reference conditions as distinguished from controls, and using habitat suitability and other indices. Guidance is also needed to preclude the use of the same evidence in multiple causal considerations. Efficiency for determining causes of biological impairments may be enhanced by forming teams to process multiple cases, developing screening tools to streamline some aspects, considering similar systems simultaneously, and validating the impairment at the outset. Methodological issues were associated with sensitivity, robustness, validation and probability of recovery. The lessons learned from states using the USEPA Stressor Identification Guidance will be addressed in a report and be reflected in future guidance.