Science Policy to Advance a Climate Change and Health Research Agenda in the United States.

Climate change is thought to be one of the greatest public health threats of the 21st century and there has been a tremendous growth in the published literature describing the health implications of climate change over the last decade. Yet, there remain several critical knowledge gaps in this field. Closing these gaps is crucial to developing effective interventions to minimize the health risks from climate change. In this commentary, we discuss policy trends that have influenced the advancement of climate change and health research in the United States context. We then enumerate specific knowledge gaps that could be addressed by policies to advance scientific research. Finally, we describe tools and methods that have not yet been fully integrated into the field, but hold promise for advancing the science. Prioritizing this advancement offers the potential to improve public health-related policies on climate change.

Achievements and needs for the climate change scenario framework.

Long-term global scenarios have underpinned research and assessment of global environmental change for four decades. Over the past ten years, the climate change research community has developed a scenario framework combining alternative futures of climate and society to facilitate integrated research and consistent assessment to inform policy. Here we assess how well this framework is working and what challenges it faces. We synthesize insights from scenario-based literature, community discussions and recent experience in assessments, concluding that the framework has been widely adopted across research communities and is largely meeting immediate needs. However, some mixed successes and a changing policy and research landscape present key challenges, and we recommend several new directions for the development and use of this framework.

Observed winter warming of the Chesapeake Bay estuary (1949-2002): implications for ecosystem management.

A large number of studies have documented 20th century climate variability and change at the global, hemispheric, and regional levels. However, understanding the implications of climate change for environmental management necessitates information at the level of the ecosystem. Historical monitoring data from the Chesapeake Bay estuary were used to identify temporal patterns of estuarine temperature anomalies in the surface (/=15 m) between 1949 and 2002. Data indicated a trend in surface and subsurface warming of +0.16 degrees C and +0.21 degrees C per decade, respectively, driven by warming during winter and spring. These trends suggest warming of the estuary since the mid-20th century of approximately 0.8-1.1 degrees C. Estuarine temperatures correlated well with other independent data records for sea surface and surface air temperatures in the region and to a lesser extent, the northern hemisphere. Gross long-term temperature variability in the estuary was consistent with North Atlantic climate variability associated with the prolonged positive North Atlantic Oscillation/Arctic Oscillation and increased anthropogenic radiative forcing, although localized environmental drivers likely are important as well. A simple spatial analysis revealed strong seasonal latitudinal and longitudinal gradients in estuarine temperature as well as a north-south gradient in long-term temperature trends. Continued warming of the estuary will have important implications for ecosystem structure and function as well as attempts to manage existing challenges such as eutrophication and benthic hypoxia. However, such management efforts must be cognizant of the effects of various climate and nonclimate drivers of environmental variability and change operating over different spatial and temporal scales.

Risk-based analysis of environmental monitoring data: application to heavy metals in North Carolina surface waters.

The state of North Carolina's Department of Environment and Natural Resources (NCDENR) conducts routine water quality monitoring throughout the state to assess the health of aquatic systems. The current study reports the results of a retrospective (1990-2000) ecological risk assessment of six heavy metals (arsenic, cadmium, copper, lead, mercury, and zinc) in 17 North Carolina basins that was conducted to estimate the risk of heavy metal toxicity to freshwater organisms and assess the sufficiency of NCDENR's monitoring data to identify water-quality-related ecological threats. Acute and chronic ecotoxicological thresholds (ETs) were calculated for each metal based upon the 10th percentile of species sensitivity distributions and were normalized for water hardness. Statewide probabilities (expressed as percentages) of a random sample exceeding acute or chronic ETs among the six metals ranged from 0.01% to 12.19% and 0.76% to 21.21%, respectively, with copper having the highest and arsenic and mercury the lowest risk. Basin-specific probabilities varied significantly depending upon water hardness and presumably watershed development. Although the majority of specific sites where data were collected were at low risk for metal toxicity, some specific sites had a high probability of toxic events associated with one or more metals. Analytical detection limits for metals were frequently higher than estimated chronic ET, limiting the ability to assess the risk of chronic toxicity in soft-water basins. Results suggest risk-based criteria may be useful for assessing and validating the sufficiency of monitoring programs and prioritizing management goals.

Multiple stressor effects on benthic biodiversity of Chesapeake Bay: implications for ecological risk assessment.

In natural aquatic systems, there is frequently overlap in the spatial distribution of both natural and anthropogenic stressors, particularly at regional geographic scales. Yet the proportional risk associated with individual stressors, their cumulative effects and the manner in which they interact to affect aquatic ecology is frequently unknown, limiting the robustness of multiple-stressor ecological risk assessments (ERA). The current study used historical environmental monitoring data (1984-1999) to identify a combination of natural and anthropogenic stressors that best accounted for observed patterns of benthic biodiversity in Chesapeake Bay. Geographic information systems (GIS) were used to geographically link spatially heterogeneous databases for benthic biodiversity, water quality and sediment toxicant concentrations. Single and multiple variable regression techniques were subsequently used to develop a statistical model to explain observed patterns of benthic biodiversity. Combinations of natural stressors alone accounted for as much as 34% of the variation in benthic biodiversity, and combinations of anthropogenic toxicants accounted for as much as 48% of the variation. The consideration of both natural and anthropogenic stressors resulted in a statistical model that accounted for approximately 73% of the observed variation in benthic biodiversity of Chesapeake Bay. These results suggest that benthic biodiversity in Chesapeake Bay is a function of complex interactions among water quality characteristics and anthropogenic toxicants. Therefore, new risk assessment methodologies are required to assess the risk of multiple stressors at regional scales.

Hazard prioritization in ecological risk assessment through spatial analysis of toxicant gradients.

The analysis of spatial relationships among the distribution of environmental stressors and observed or predicted adverse effects may be a useful method of prioritizing hazards in regional ecological risk assessment (ERA). Geographic information systems were used to compare the spatial distribution of toxicant concentrations in sediments of Chesapeake Bay with the distribution of areas in the basin where ecological impacts have historically been observed. Toxicants were then prioritized based upon the strength of their spatial association with the high impact areas. This method of hazard identification/prioritization was validated against the Chesapeake Bay Program's lists of toxics of concern and toxics of potential concern (TOC and TOPC, respectively). Of the 18 toxicants on the TOC/TOPC lists that were considered in the current study, 15 (83%) were identified as priority contaminants in the current study, 11 (73%) of which were either of primary or secondary concern. The use of spatial analysis tools in ERA may lead to more rapid and rigorous methods for prioritizing environmental risks.

Indirect effects in aquatic ecotoxicology: implications for ecological risk assessment.

Understanding toxicant effects at higher levels of biological organization continues to be a challenge in ecotoxicology and ecological risk assessment. This is due in part to a tradition in ecotoxicology of considering the direct effects of toxicants on a limited number of model test species. However, the indirect effects of toxicity may be a significant factor influencing the manner in which ecosystem structure and function respond to anthropogenic stressors. Subsequently, failure to incorporate indirect effects into risk assessment paradigms may be a significant source of uncertainty in risk estimates. The current paper addresses the importance of indirect effects in an ecotoxicological context. Laboratory, mesocosm, and whole ecosystem research into indirect effects is reviewed. The implications of indirect effects for ecological risk assessment and potential areas of profitable future research are also discussed.

Spatial patterns in benthic biodiversity of Chesapeake Bay, USA (1984-1999): association with water quality and sediment toxicity.

Non-point-source pollution is an increasing source of stress to aquatic, estuarine, and marine ecosystems. Such pollution may be of unknown etiology, distributed over extensive spatial scales, and comprised of multiple stressors. Current stressor-based paradigms for ecological risk assessment (ERA) may be insufficient to characterize risk from multiple stressors at regional spatial scales, necessitating the use of effects-based approaches. Historical data (1984-1999) for benthic macroinvertebrate biodiversity in Chesapeake Bay, USA, were incorporated into a geographic information system (GIS) and spatial analysis tools were used to model zones within the bay predicted to be of low or high anthropogenic impact. Data for benthic water quality and sediment toxicant concentrations from each of these zones were subsequently analyzed and compared to identify associations between benthic biodiversity and potential stressors. A number of stressors were significantly associated with high-impact zones, including increased nitrogen and phosphorus concentrations, low dissolved oxygen, heavy metals, pesticides, polycyclic aromatic hydrocarbons, and polychlorinated biphenyls. The spatial autocorrelation among multiple stressors suggests that traditional stressor-based approaches to ERA may result in the a priori exclusion of ecologically relevant stressors. Considering the effects of individual stressors rather than net effects of multiple stressors may result in underestimation of risk. The GISs are a useful tool for integrating multiple data sets in support of comprehensive regional ERA.