Reducing Nonpoint Source Pollution Through Collaboration: Policies and Programs Across the U.S. States

Nonpoint source (NPS) pollution has emerged as the largest threat to water quality in the United States, influencing policy makers and resource managers to direct more attention toward NPS prevention and remediation. In response, the United States Environmental Protection Agency (USEPA) spent more than $204 million in fiscal year (FY) 2006 on the Clean Water Act’s Section 319 program to combat NPS pollution, much of it on the development and implementation of watershed-based plans. State governments have also increasingly allocated financial and technical resources to collaborative watershed efforts within their own borders to fight NPS pollution. With increased collaboration among the federal government, states, and citizens to combat NPS pollution, more information is needed to understand how public resources are being used, by whom, and for what, and what policy changes might improve effectiveness. Analysis from a 50-state study suggests that, in addition to the average 35% of all Section 319 funds per state that are passed on to collaborative watershed groups, 35 states have provided financial assistance beyond Section 319 funding to support collaborative watershed initiatives. State programs frequently provide technical assistance and training, in addition to financial resources, to encourage collaborative partnerships. Such assistance is typically granted in exchange for requirements to generate a watershed action plan and/or follow a mutually agreed upon work plan to address NPS pollution. Program managers indicated a need for greater fiscal resources and flexibility to achieve water quality goals.     

Behavioral responses of bison and elk in Yellowstone to snowmobiles and snow coaches.

Managers of public lands are charged with protecting some of our most important natural resources and ecosystems, while providing for their use and enjoyment by visitors. Almost one million visitors entered Yellowstone National Park by motorized means on snowmobiles (87%) or snow coaches (13%) during 1992-2003. Most vehicles toured the central portion of the park where bison (Bison bison) and elk (Cervus elaphus) concentrate in geothermal areas. We sampled >6500 interactions between groups of these species and groups of snowmobiles and snow coaches (collectively, OSV, over-snow vehicles) during five winters (1999-2000, 2002-2004). Multinomial logits models were used to identify conditions leading to behavioral responses. Elk responded three times as often (52%) as bison (19%) during interactions with groups of snowmobiles and snow coaches due to increased vigilance responses (elk, 44%; bison, 10%). However, the frequency of higher-intensity movement responses by bison and elk were similar (6-7% travel, 1-2% flight, <1% defense) and relatively low compared to other studies of ungulates and snowmobile disturbance. The likelihood of active responses by bison and elk increased significantly if animals were on or near roads, groups were smaller, or humans approached. The likelihood of an active response by bison decreased within winters having the largest visitation, suggesting some habituation to snowmobiles and snow coaches. There was no evidence that snowmobile use during the past 35 years affected the population dynamics or demography of bison or elk. Thus, we suggest that regulations restricting levels and travel routes of over-snow vehicles (OSVs) were effective at reducing disturbances to bison and elk below a level that would cause measurable fitness effects. We recommend park managers consider maintaining OSV traffic levels at or below those observed during our study. Regardless, differing interpretations of the behavioral and physiological response data will continue to exist because of the diverse values and beliefs of the many constituencies of Yellowstone.     

A Comparison of Data Sets Varying in Spatial Accuracy Used to Predict the Occurrence of Wildlife-Vehicle Collisions

Wildlife-vehicle collisions (WVCs) pose a significant safety and conservation concern in areas where high-traffic roads are situated adjacent to wildlife habitat. Improving transportation safety, accurately planning highway mitigation, and identifying key habitat linkage areas may all depend on the quality of WVC data collection. Two common approaches to describe the location of WVCs are spatially accurate data derived from global positioning systems (GPS) or vehicle odometer measurements and less accurate road-marker data derived from reference points (e.g., mile-markers or landmarks) along the roadside. In addition, there are two common variable types used to predict WVC locations: (1) field-derived, site-specific measurements and (2) geographic information system (GIS)-derived information. It is unclear whether these different approaches produce similar results when attempting to identify and explain the location of WVCs. Our first objective was to determine and compare the spatial error found in road-marker data (in our case the closest mile-marker) and landmark-referenced data. Our second objective was to evaluate the performance of models explaining high- and low-probability WVC locations, using congruent, spatially accurate (<3-m) and road-marker (<800-m) response variables in combination with field- and GIS-derived explanatory variables. Our WVC data sets were comprised of ungulate collisions and were located along five major roads in the central Canadian Rocky Mountains. We found that spatial error (mean ± SD) was higher for WVC data referenced to nearby landmarks (516 ± 808 m) than for data referenced to the closest mile-marker data (401 ± 219 m). The top-performing model using the spatially accurate WVC locations contained all explanatory variable types, whereas GIS-derived variables were only influential in the best road-marker model and the spatially accurate reduced model. Our study showed that spatial error and sample size, using road-marker data for ungulate species, are important to consider for model output interpretation, which will impact the appropriate scale on which to apply modeling results. Using road-marker references <1.6 km or GPS-derived data locations may represent an optimal compromise between data acquisition costs and analytical performance. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Distribution of Selected Soil and Water Conservation Practices in the U.S. as Identified with Google Earth

The proper representation of conservation practices on agricultural lands is an important factor in large‐scale assessments of water quality in the United States. Unfortunately, there are few publicly available data sources at the local level and even fewer at the national scale. In this research, randomly selected points within agricultural lands were examined for selected conservation practices using Google Earth aerial imagery by a team of interpreters. In total, 13,530 points had field boundaries digitized, and were subsequently examined and classified. The presence of terraces, grassed waterways, contour farming, center pivot irrigation, strip cropping, ponds, riparian vegetation, filter strips, and land cover were noted. Subjectivity among interpreters was evaluated using duplicate samples and was found to be similar to image misclassification rates in other research. Conservation practice adoption rates for selected major river basins compared favorably with data collected by the Conservation Effects Assessment Project. The frequency of occurrence of each conservation practice was summarized and presented by ecoregion. To facilitate future research, point level data and software source code developed in this research are available via the web at http://nlet.brc.tamus.edu/Conservation . Aerial imagery was found to be a powerful, inexpensive, and easily accessible tool to assess large‐scale conservation practice implementation for certain conservation practices.     

Exploring Patterns of Seafood Provision Revealed in the Global Ocean Health Index

Sustainable provision of seafood from wild-capture fisheries and mariculture is a fundamental component of healthy marine ecosystems and a major component of the Ocean Health Index. Here we critically review the food provision model of the Ocean Health Index, and explore the implications of knowledge gaps, scale of analysis, choice of reference points, measures of sustainability, and quality of input data. Global patterns for fisheries are positively related to human development and latitude, whereas patterns for mariculture are most closely associated with economic importance of seafood. Sensitivity analyses show that scores are robust to several model assumptions, but highly sensitive to choice of reference points and, for fisheries, extent of time series available to estimate landings. We show how results for sustainable seafood may be interpreted and used, and we evaluate which modifications show the greatest potential for improvements.     

Sensitivity of atmospheric dispersion simulations by HYSPLIT to the meteorological predictions from a meso-scale model

Mesoscale transport and dispersion of air pollutants from a few major point sources in the Mississippi Gulf coastal region is calculated using a coupled modeling system consisting of the atmospheric dynamical model WRF and the lagrangian particle model HYSPLIT. The sensitivity of the dispersion model results to the meteorological fields is studied by conducting an ensemble of simulations using the WRF model for the same dispersion case. Several parameterization schemes for the physical processes of boundary layer turbulence and land surface temperature/moisture prediction in WRF are used in various combinations to produce different meteorological members which are then used for dispersion simulation. The uncertainty in the simulated concentration probabilities to the meteorological model configurations and the ensemble mean are presented. The parameters used for determining the uncertainties include the wind fields, temperature, area of concentration and the levels of concentration. The results indicate that dispersion model results are influenced by the choices made in respect of the planetary boundary layer and land surface schemes in the mesoscale model to produce the meteorological forecast thereby leading to certain amount of uncertainty in the resultant concentrations. Results show that the specific choices made about the atmospheric model configuration can significantly after the simulated concentrations.     

The role of prenatal diagnosis following preimplantation genetic testing for single-gene conditions: A historical overview of evolving technologies and clinical practice

Preimplantation genetic testing for monogenic conditions (PGT-M) has become a valued reproductive option for couples at risk of having a child with a single gene condition. In line with developments in molecular genetics, there has been an overall trend toward laboratory techniques with higher accuracy in comparison to earlier PGT-M techniques. The recommendation for confirmatory prenatal diagnostic testing has remained a standard component of PGT-M counseling, reflecting the inherent difficulties of testing the limited number of cells obtained from embryo biopsy, as well as recognition of the biological and human factors that may lead to misdiagnosis in a PGT-M cycle. Reported misdiagnosis rates are less than 1 in 200 pregnancies following PGT-M, although updated data regarding newer methods of PGT-M are required. There is limited evidence available regarding clinician and patient behavior in pregnancies resulting from PGT-M cycles. It remains essential that clinicians involved in the care of patients undergoing PGT-M provide appropriate counseling regarding the risks of misdiagnosis and the importance of confirmatory prenatal diagnosis. The nature of PGT-M test design lends itself to cell-free DNA-based noninvasive prenatal testing for monogenic conditions (NIPT-M), which is likely to become a popular method in the near future.     

Consequences of resource competition for sex allocation and discriminative behaviors in a hyperparasitoid wasp

Population-wide mating patterns can select for equal parental investment in both sexes, but limiting resources, such as mates or developmental substrates, can increase competition leading to biased sex ratios in favor of either sex. Such competition for resources typically occurs in spatially structured populations, where dispersal is limited. In this laboratory study, we investigate if and how resource competition affects sex allocation, discriminative behaviors and competitive interactions of the wingless hyperparasitoid Gelis acororum, which exploits patchily distributed hosts. We show that G. acororum sex ratios are male-biased and that this is not a consequence of constrained reproduction by virgin females. Our results suggest that this pattern of reproductive investment, which is only rarely observed in parasitoids, is a consequence of resource limitation, in terms of hosts rather than mates. Further, G. acororum appears not to respond to intrinsic host quality or to prior oviposition in its host. When competing inter-specifically for host resources, G. acororum outcompetes its congener Gelis agilis, but does so mainly when ovipositing on the host first. Overall, our results suggest that host resource limitation could be an important environmental factor shaping sex allocation in G. acororum, with competition taking place both intra- and inter-specifically.