Prioritizing sites for conservation based on similarity to historical baselines and feasibility of protection

The concept of shifting baselines in conservation science implies advocacy for the use of historical knowledge to inform these baselines but does not address the feasibility of restoring sites to those baselines. In many regions, conservation feasibility varies among sites due to differences in resource availability, statutory power, and land‐owner participation. We used zooarchaeological records to identify a historical baseline of the freshwater mussel community's composition before Euro‐American influence at a river‐reach scale (i.e., a kilometer stretch of river that is abiotically similar) in the Leon River of central Texas (U.S.A.). We evaluated how the community reference position and the feasibility of conservation might enable identification of sites where conservation actions would preserve historically representative communities and be likely to succeed. We devised a conceptual model that incorporated community information and landscape factors to link the best conservation areas to potential cost and conservation benefits. Using fuzzy ordination, we identified modern mussel beds that were most like the historical baseline. We then quantified housing density and land use near each river reach identified to estimate feasibility of habitat restoration. Using our conceptual framework, we identified reaches of high conservation value (i.e., contain the best mussel beds) and where restoration actions would be most likely to succeed. Reaches above Lake Belton were most similar in species composition and relative abundance to zooarchaeological sites. A subset of these mussel beds occurred in locations where conservation actions appeared most feasible. Our results show how to use zooarchaeological data (biodiversity data often readily available) and estimates of conservation feasibility to inform conservation priorities at a local spatial scale.     

HYDROLOGIC AND HYDRAULIC RESEARCH IN MOUNTAIN RWERS1

ABSTRACT: Although our current (1990) knowledge of hydrologic and hydraulic processes is based on many years of study, there are river environments where these processes are complex and poorly understood. One of these environments is in mountainous areas, which cover about 25 percent of the United States. Use of conventional hydrologic and hydraulic techniques in mountain-river environments may produce erroneous results and interpretations in a wide spectrum of water-resources investigations. An ongoing U.S. Geological Survey research project is being conducted to improve the understanding of hydrologic and hydraulic processes of mountainous areas and to improve the results of subsequent hydrologic investigations. Future hydrologic and hydraulic research needs in mountainous areas are identified.     

Evaluation of a population mobility,mortality, and birth surveillance system in South Kivu,Democratic Republic of the Congo

Prospective, community-based surveillance systems for measuring birth, death, and population movement rates may have advantages over the ‘gold-standard’ retrospective household survey in humanitarian contexts. A community-based, monthly surveillance system was established in South Kivu, Democratic Republic of the Congo, in partnership with a local implementing partner and the national ministry of health. Data were collected on the occurrence of births, deaths, arrivals, and departures over the course of one year, and a retrospective survey was conducted at the end of the period to validate the information. Discrepancies between the two approaches were resolved by a third visit to the households with discordant records. The study found that the surveillance system was superior in terms of its specificity and sensitivity in measuring crude mortality and birth rates as compared to the survey, demonstrating the method's potential to measure accurately important population-level health metrics in an insecure setting in a timely, community-acceptable manner.     

Neighborhood Level Spatial Analysis of the Relationship Between Alcohol Outlet Density and Criminal Violence

Misuse of alcohol is a significant public health problem, potentially resulting in unintentional injuries, motor vehicle crashes, drownings, and, perhaps of greatest concern, serious acts of violence, including assaults, rapes, suicides, and homicides. Although previous research establishes a link between alcohol consumption increased levels of violence, studies relating the density of alcohol outlets (e.g., restaurants, bars, liquor stores) and the likelihood of violent crime have been less common. In this paper we test for such a relationship at the small area level, using data from 79 neighborhoods in the city of Minneapolis, Minnesota. We adopt a fully Bayesian point of view using Markov chain Monte Carlo (MCMC) computational methods as available in the popular and freely available WinBUGS language. Our models control for important covariates (e.g., neighborhood racial heterogeneity, age heterogeneity) and also account for spatial association in unexplained variability using conditionally autoregressive (CAR) random effects. Our results indicate a significant positive relationship between alcohol outlet density and violent crime, while also permitting easy mapping of neighborhood-level predicted and residual values, the former useful for intervention in the most at-risk neighborhoods and the latter potentially useful in identifying covariates still missing from the fixed effects portion of the model.     

Characterization of fine primary biogenic organic aerosol in an urban area in the northeastern United States

Scanning electron microscopy coupled to energy-dispersive x-ray spectroscopy (SEM/EDX) was used to quantify individual bioparticles in PM_2.5 samples collected during the Pittsburgh Air Quality Study. Microscopy-based estimates of primary biogenic organic aerosol (PBOA) mass were compared to carbohydrate mass associated with PM_2.5. Carbohydrates show substantial seasonal variations, with higher concentrations in the spring and the fall. During the summer, carbohydrates were about 30% of the estimated PBOA concentrations, but in the winter carbohydrate concentrations often greatly exceeded the PBOA mass estimate. Spores and insect detritus were the most abundant PBOA types in the summer samples, while winter samples were comprised predominantly of a mixture of microorganisms, insect and vegetative detritus. During the summer PBOA contributed on average 6.9 ± 5.4% by mass of the PM_2.5 versus 3.3 ± 1.4% of the PM_2.5 mass during the winter.     

Visual fields in Flamingos: chick-feeding versus filter-feeding

In birds, the position and extent of the region of binocular vision appears to be determined by feeding ecology. Of prime importance is the degree to which vision is used for the precise control of bill position when pecking or lunging at prey. In birds that do not require such precision (probe and filter-feeders), the bill falls outside the binocular field, which extends above and behind the head, thus providing comprehensive visual coverage. Flamingos Phoenicopteridae are highly specialised filter-feeders. They employ a unique technique that does not require accurate bill positioning in which the inverted head is placed between the feet. Feeding flamingos often walk forwards with the head pointing “backwards”. Here we show that in Lesser Flamingos Phoeniconaias minor visual fields are in fact the same as those of birds that feed by precision pecking and that feeding flamingos are blind in the direction of their walking. We suggest that this is due to the requirement for accurate bill placement when flamingos feed their chicks with “crop-milk”, and possibly when building their nest. We propose that chick-feeding may be the ultimate determinant of visual field topography in birds, not feeding ecology.     

Further validation of artificial neural network-based emissions simulation models for conventional and hybrid electric vehicles

With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO2] and oxides of nitrogen [NO(x)]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO2 and NO(x) in the case of a class-8 truck but were more accurate as the truck weight increased.     

Recommended Design for More Accurate Duplication of Natural Conditions in Salt Marsh Creation

Construction of 653 ha of salt marsh habitat from dredged material near the Aransas National Wildlife Refuge, Texas, has been proposed, with the goal of increasing the area of habitat available to endangered whooping cranes (Grus americana). We assessed prototype created wetlands, and their similarity to natural reference sites, in terms of topography, vegetation, and hydrology. The created sites were steeply sloped relative to natural sites and were dominated by monotypic stands of Spartina alterniflora. Natural sites were dominated by vegetation more tolerant of desiccation and hypersalinity and by unvegetated salt pans. Differences in vegetation communities and distributions of habitat types resulted from efforts to enhance habitat diversity in created marsh cells through manipulation of marsh topography. However, the scale at which this diversity occurred in natural marsh of the study area was not considered. When constructing wetlands in cellular configurations, we recommend creation of large complexes of adjoining, hydrologically linked, cells wherein the desired habitat diversity is created at the scale of the entire complex, rather than within a single cell. Suggested design modifications would increase the similarity of created marshes to natural reference sites, potentially improving habitat function.     

Hierarchical spatial modeling for estimation of population size

Estimation of population size has traditionally been viewed from a finite population sampling perspective. Typically, the objective is to obtain an estimate of the total population count of individuals within some region. Often, some stratification scheme is used to estimate counts on subregions, whereby the total count is obtained by aggregation with weights, say, proportional to the areas of the subregions. We offer an alternative to the finite population sampling approach for estimating population size. The method does not require that the subregions on which counts are available form a complete partition of the region of interest. In fact, we envision counts coming from areal units that are small relative to the entire study region and that the total area sampled is a very small proportion of the total study area. In extrapolating to the entire region, we might benefit from assuming that there is spatial structure to the counts. We implement this by modeling the intensity surface as a realization from a spatially correlated random process. In the case of multiple population or species counts, we use the linear model of coregionalization to specify a multivariate process which provides associated intensity surfaces hence association between counts within and across areal units. We illustrate the method of population size estimation with simulated data and with tree counts from a Southwestern pinyon-juniper woodland data set.