Managing troubled data: coastal data partnerships smooth data integration

Understanding the ecology, condition, and changes of coastal areas requires data from many sources. Broad-scale and long-term ecological questions, such as global climate change, biodiversity, and cumulative impacts of human activities, must be addressed with databases that integrate data from several different research and monitoring programs. Various barriers, including widely differing data formats, codes, directories, systems, and metadata used by individual programs, make such integration troublesome. Coastal data partnerships, by helping overcome technical, social, and organizational barriers, can lead to a better understanding of environmental issues, and may enable better management decisions. Characteristics of successful data partnerships include a common need for shared data, strong collaborative leadership, committed partners willing to invest in the partnership, and clear agreements on data standards and data policy. Emerging data and metadata standards that become widely accepted are crucial. New information technology is making it easier to exchange and integrate data. Data partnerships allow us to create broader databases than would be possible for any one organization to create by itself.     

Effects of red light camera enforcement on fatal crashes in large U.S. cities

Objective

To estimate the effects of red light camera enforcement on per capita fatal crash rates at intersections with signal lights.

Methods

From the 99 large U.S. cities with more than 200,000 residents in 2008, 14 cities were identified with red light camera enforcement programs for all of 2004-2008 but not at any time during 1992-1996, and 48 cities were identified without camera programs during either period. Analyses compared the citywide per capita rate of fatal red light running crashes and the citywide per capita rate of all fatal crashes at signalized intersections during the two study periods, and rate changes then were compared for cities with and without cameras programs. Poisson regression was used to model crash rates as a function of red light camera enforcement, land area, and population density.

Results

The average annual rate of fatal red light running crashes declined for both study groups, but the decline was larger for cities with red light camera enforcement programs than for cities without camera programs (35% vs. 14%). The average annual rate of all fatal crashes at signalized intersections decreased by 14% for cities with camera programs and increased slightly (2%) for cities without cameras. After controlling for population density and land area, the rate of fatal red light running crashes during 2004-2008 for cities with camera programs was an estimated 24% lower than what would have been expected without cameras. The rate of all fatal crashes at signalized intersections during 2004-2008 for cities with camera programs was an estimated 17% lower than what would have been expected without cameras.

Conclusions

Red light camera enforcement programs were associated with a statistically significant reduction in the citywide rate of fatal red light running crashes and a smaller but still significant reduction in the rate of all fatal crashes at signalized intersections.

Impact on Industry

The study adds to the large body of evidence that red light camera enforcement can prevent the most serious crashes. Communities seeking to reduce crashes at intersections should consider this evidence.     

Nutrient Bioassays of Growth Parameters for Algae in the North Bosque River of Central Texas1

Abstract: Nutrient dose‐response bioassays were conducted using water from three sites along the North Bosque River. These bioassays provided support data for refinement of the Soil and Water Assessment Tool (SWAT) model used in the development of two phosphorus TMDLs for the North Bosque River. Test organisms were native phytoplanktonic algae and stock cultured Pseudokirchneriella subcapitata (Korshikov) Hindak. Growth was measured daily by in vivo fluorescence. Algal growth parameters for maximum growth (μ_max) and half‐saturation constants for nitrogen (K_N) or phosphorus (K_P) were determined by fitting maximum growth rates associated with each dose level to a Monod growth rate function. Growth parameters of native algae were compared between locations and to growth parameters of P. subcapitata and literature values. No significant differences in half‐saturation constants were indicated within nutrient treatment for site or algal type. Geometric mean K_N was 32 μg/l and for K_P 7 μg/l. A significant difference was detected in maximum growth rates between algae types but not between sites or nutrient treatments. Mean μ_max was 1.5/day for native algae and 1.2/day for stock algae. These results indicate that watershed‐specific maximum growth rates may need to be considered when modeling algal growth dynamics with regard to nutrients.     

Integrating environmental impact assessment with master planning: lessons from the US Army

The US National Environmental Policy Act (NEPA) requires agencies to consider environmental impacts in the early stages of planning and decision-making. Despite this mandate, agencies typically conduct EIA for projects, rather than for earlier and more strategic decisions, such as plans. This research investigated the extent to which a large federal agency, the US Army, has integrated NEPA analyses with master planning for their installations. Using in-depth case studies of 16 installations, we investigated how and why EIA was (or was not) integrated with planning, and identified the factors that promote or impede integration. Typically, integration has been regarded as concurrence, meaning that the EIA and planning processes are conducted together. Results of this research show, however, that integration can occur, even if the NEPA documents and master plans are not concurrently prepared. In this sense, integration can be viewed as the influence of the EIA process on agency planning and decision-making. Results also indicate that regulations are only one factor, and that several other factors influence the extent of integration, such as agency leadership and organizational incentives. Lessons from this study can help improve both the integration and the substantive implementation of EIA.     

Biological Integrity in Mid-Atlantic Coastal Plains Headwater Streams

The objective of this study was to assess the applicability of using landscape variables in conjunction with water quality and benthic data to efficiently estimate stream condition of select headwater streams in the Mid-Atlantic Coastal Plains. Eighty-two streams with riffle sites were selected from eight-two independent watersheds across the region for sampling and analyses. Clustering of the watersheds by landscape resulted in three distinct groups (forest, crop, and urban) which coincided with watersheds dominant land cover or use. We used non-parametric analyses to test differences in benthos and water chemistry between groups, and used regression analyses to evaluate responses of benthic communities to water chemistry within each of the landscape groups. We found that typical water chemistry measures associated with urban runoff such as specific conductance and dissolved chloride were significantly higher in the urban group. In the crop group, we found variables commonly associated with farming such as nutrients and pesticides significantly greater than in the other two groups. Regression analyses demonstrated that the numbers of tolerant and facultative macroinvertebrates increased significantly in forested watersheds with small shifts in pollutants, while in human use dominated watersheds the intolerant macroinvertebrates were more sensitive to shifts in chemicals present at lower concentrations. The results from this study suggest that landscape based clustering can be used to link upstream landscape characteristics, water chemistry and biotic integrity in order to assess stream condition and likely cause of degradation without the use of reference sites. Notice: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.     

Human Influences on Water Quality in Great Lakes Coastal Wetlands

A better understanding of relationships between human activities and water chemistry is needed to identify and manage sources of anthropogenic stress in Great Lakes coastal wetlands. The objective of the study described in this article was to characterize relationships between water chemistry and multiple classes of human activity (agriculture, population and development, point source pollution, and atmospheric deposition). We also evaluated the influence of geomorphology and biogeographic factors on stressor-water quality relationships. We collected water chemistry data from 98 coastal wetlands distributed along the United States shoreline of the Laurentian Great Lakes and GIS-based stressor data from the associated drainage basin to examine stressor-water quality relationships. The sampling captured broad ranges (1.5–2 orders of magnitude) in total phosphorus (TP), total nitrogen (TN), dissolved inorganic nitrogen (DIN), total suspended solids (TSS), chlorophyll a (Chl a), and chloride; concentrations were strongly correlated with stressor metrics. Hierarchical partitioning and all-subsets regression analyses were used to evaluate the independent influence of different stressor classes on water quality and to identify best predictive models. Results showed that all categories of stress influenced water quality and that the relative influence of different classes of disturbance varied among water quality parameters. Chloride exhibited the strongest relationships with stressors followed in order by TN, Chl a, TP, TSS, and DIN. In general, coarse scale classification of wetlands by morphology (three wetland classes: riverine, protected, open coastal) and biogeography (two ecoprovinces: Eastern Broadleaf Forest [EBF] and Laurentian Mixed Forest [LMF]) did not improve predictive models. This study provides strong evidence of the link between water chemistry and human stress in Great Lakes coastal wetlands and can be used to inform management efforts to improve water quality in Great Lakes coastal ecosystems.     

Perceptions of Wood in Rivers and Challenges for Stream Restoration in the United States

This article reports a study of the public perception of large wood in rivers and streams in the United States. Large wood is an element of freshwater aquatic ecosystems that has attracted much scientific interest in recent years because of its value in biological and geomorphological processes. At the heart of the issue is the nature of the relationship between scientific recognition of the ecological and geomorphological benefits of wood in rivers, management practices utilizing wood for river remediation progress, and public perceptions of in-channel wood. Surveys of students’ perceptions of riverscapes with and without large wood in the states of Colorado, Connecticut, Georgia, Illinois, Iowa, Missouri, Oregon, and Texas suggest that many individuals in the United States adhere to traditionally negative views of wood. Except for students in Oregon, most respondents considered photographs of riverscapes with wood to be less aesthetically pleasing and needing more improvement than rivers without wood. Analysis of reasons given for improvement needs suggest that Oregon students are concerned with improving channels without wood for fauna habitat, whereas respondents elsewhere focused on the need for cleaning wood-rich channels for flood risk management. These results underscore the importance of public education to increase awareness of the geomorphological and ecological significance of wood in stream systems. This awareness should foster more positive attitudes toward wood. An integrated program of research, education, and policy is advocated to bridge the gap between scientific knowledge and public perception for effective management and restoration of river systems with wood.