T3 AM Ecological Risk Assessment (Part 2)
Tuesday, 15 November 2005: 8:00 AM - 11:40 AM in Ballroom 3

(NAC-1117-819384) An approach to assess risks to wildlife populations from mercury and other stressors.

Nacci, D¹, Bennett, R², Copeland, J³, Grear, J¹, Kuhn, A¹, Nichols, J², Nicholson, M¹, Walters, S¹, Vogel, H⁴, Taylor, K⁴, ¹ US EPA ORD NHEERL Atlantic Ecology Division, Narragansett, RI, USA² US EPA ORD NHEERL Mid-Continental Ecology Division, Duluth, MN, USA³ CSC, Narragansett, RI, USA⁴ New Hampshire Loon Preservation Committee, Moultonborough, NH, USA

ABSTRACT- Traditionally, EPA has conducted ecological risk assessments and developed criteria for specific stressors (such as mercury) based on results of controlled studies assessing the effects of isolated stressors on the reproduction and survival of individual test organisms. But, are such test results relevant (or sufficient) to protect wildlife populations that are exposed more typically to multiple stressors concurrently and throughout their lifetimes? In this research project, we are developing methods to project the effects on wildlife populations of stressors as they occur more realistically, i.e., in the context of other stressors. To demonstrate and test these methods, we have focused on population effects to common loons of mercury (Hg) exposure and habitat alteration (loss and degradation). First, we have focused on New Hampshire (NH) because of the relative abundance of relevant monitoring information to relate these stressors to loon abundance, distribution and productivity, and ultimately loon population persistence. Specifically, loon and environmental monitoring data were available for recent decades for hundreds of NH lakes from the New Hampshire Loon Preservation Committee, the New Hampshire Department of Environmental Services, and the US EPA Regional Monitoring and Assessment Program (REMAP). Initial assessments are made at three scales: the lake, region, and state. In addition, we are partnering with other researchers concurrently investigating loons in Wisconsin to provide additional information and permit regional comparisons. To assess risks to loons , we use data and models to: (1) describe current status, and temporal and spatial trends in abundance and distribution of loons and stressors; (2) relate stressors to specific aspects of loon fitness, using information from controlled studies (Hg) and from field data (Hg and habitat); (3) project loon population effects from changes in stressors, and test these projections using field data; (4) identify those data most critical to improving projections of stressor effects.

Key words: Ecological Risk Assessment, Wildlife Population, Mercury, Avian