Lifetime reproductive success and composition of the home range in a large herbivore

The relationship between individual performance and nonrandom use of habitat is fundamental to ecology; however, empirical tests of this relationship remain limited, especially for higher orders of selection like that of the home range. We quantified the association between lifetime reproductive success (LRS) and variables describing lifetime home ranges during the period of maternal care (spring to autumn) for 77 female roe deer (Capreolus capreolus) at Trois-Fontaines, Champagne-Ardenne, France (1976-2000). We maintained population growth rate (adjusted to account for removals of non-focal animals) near rmax, which enabled us to define the fitness-habitat relationship in the absence of density effects. Using a negative binomial model, we showed that a roe deer's incorporation into its home range of habitat components important to food, cover, and edge (meadows, thickets, and increased density of road allowances) was significantly related to LRS. Further, LRS decreased with increasing age of naturally reclaimed meadows at the time of a deer's birth, which may have reflected a cohort effect related to, but not entirely explained by, a decline in quality of meadows through time. Predictive capacity of the selected model, estimated as the median correlation (rs) between predicted and observed LRS among deer of cross-validation samples, was 0.55. The strength of this relationship suggests that processes like selection of the site of a home range during dispersal may play a more important role in determining fitness of individuals than previously thought. Individual fitness of highly sedentary income breeders with high reproductive output such as roe deer should be more dependent on home range quality during the period of maternal care compared to capital breeders with low reproductive output. Identification of the most important habitat attributes to survival and reproduction at low density (low levels of intraspecific competition) may prove useful for defining habitat value ("intrinsic habitat value").     

Privileged Knowledge and Social Change: Effects on Different Participants of Using Geographic Information Systems Technology in Natural Resource Management

The use of geographic information systems (GIS) technology in natural resource management has expanded rapidly: It is the preferred tool of spatial data analysis addressing large landscapes and is typically the presentation medium for conveying landscape-scale scientific findings to all kinds of audiences. In a case study using the Coastal Landscape Analysis and Modeling Study in western Oregon, it was found that the use of GIS to analyze and display natural resource data in that project produced a variety of responses among different participants and participant groups. The findings offer insights into the workings of groups attempting public involvement in natural resource management.     

Temperature Measurement and Stratification in Facultative Waste Stabilisation Ponds in the UK Climate

Temperature measurements were taken at three pilot-scale facultative ponds located at Esholt wastewater treatment works in West Yorkshire, UK over two one-year periods. The measurements were taken at different depths using a technology called Thermochron iButton. The iButton readings were compared with temperature measurements taken by a YSI sonde probe and maximum/minimum thermometers: they were found to be within 1 .C. In the temperature range 3.18 .C the mean weekly and monthly air temperatures were found to be good predictors for the mean weekly and monthly pond water-column temperatures. The level of stratification in the ponds under UK climatic conditions was assessed; the data revealed that the ponds remained thermally stratified for significant periods during the year despite their shallow depth.     

Climate adaptation in fragmented governance settings: the consequences of reform in public administration

The impact of dominant trends in public administration, such as decentralisation and privatisation on complex collective challenges is insufficiently understood. This is relevant in settings where climate change impacts become manifest at local level, and where financing power resides at national level but decisions are made more locally in a fragmented institutional setting. This study assists in overcoming this gap by analysing how the institutional context (i.e. a decentralised, privatised, fragmented setting) influences the capacity to address climate change challenges in a vulnerable area (the South Devon coast in the UK). There has been little action to address expected climate change impacts in this vulnerable stretch of coast. A lack of clarity around responsibility for addressing climate impacts and a lack of a deliberative structure between various actors involved, within a context of austerity, hamper climate change adaptation. The findings question whether decentralised decision making is sufficient for addressing climate adaptation challenges.     

A New Open‐Access HUC‐8 Based Downscaled CMIP‐5 Climate Model Forecast Dataset for the Conterminous United States

Watershed‐scale hydrologic simulation models generally require climate data inputs including precipitation and temperature. These climate inputs can be derived from downscaled global climate simulations which have the potential to drive runoff forecasts at the scale of local watersheds. While a simulation designed to drive a local watershed model would ideally be constructed at an appropriate scale, global climate simulations are, by definition, arbitrarily determined large rectangular spatial grids. This paper addresses the technical challenge of making climate simulation model results readily available in the form of downscaled datasets that can be used for watershed scale models. Specifically, we present the development and deployment of a new Coupled Model Intercomparison Project phase 5 (CMIP5) based database which has been prepared through a scaling and weighted averaging process for use at the level of U.S. Geological Survey (USGS) Hydrologic Unit Code (HUC)‐8 watersheds. The resulting dataset includes 2,106 virtual observation sites (watershed centroids) each with 698 associated time series datasets representing average monthly temperature and precipitation between 1950 and 2099 based on 234 unique climate model simulations. The new dataset is deployed on a HydroServer and distributed using WaterOneFlow web services in the WaterML format. These methods can be adapted for downscaled General Circulation Model (GCM) results for specific drainage areas smaller than HUC‐8. Two example use cases for the dataset also are presented.     

Reduction of U(VI) by the deep subsurface bacterium, Thermus scotoductus SA-01, and the involvement of the ABC transporter protein

In this study we investigated the effect of uranium on the growth of the bacterium Thermus scotoductus strain SA-01 as well as the whole cell U(VI) reduction capabilities of the organism. Also, site-directed mutagenesis confirmed the identity of a protein capable of a possible alternative mechanism of U(VI) reduction. SA-01 can grow aerobically in up to 1.25 mM uranium and has the capability to reduce low levels of U(VI) in under 20 h. TEM analysis performed on cells exposed to uranium showed extracellular and membrane-bound accumulation of uranium. The reductase-like protein was surprisingly identified as a peptide ABC transporter, peptide-binding protein. This study showcases the concept of protein promiscuity, where this protein with a distinct function in situ can also have the unintended function of a reactant for the reduction of U(VI).     

Lagrangian sampling of 3-D air quality model results for regional transport contributions to sulfate aerosol concentrations at Baltimore,MD, in summer 2004

We use ensemble-mean Lagrangian sampling of a 3-D Eulerian air quality model, CMAQ, together with ground-based ambient monitors data from several air monitoring networks and satellite (MODIS) observations to provide source apportionment and regional transport vs. local contributions to sulfate aerosol and PM_2.5 concentrations at Baltimore, MD, for summer 2004. The Lagrangian method provides estimates of the chemical and physical evolution of air arriving in the daytime boundary layer at Baltimore. Study results indicate a dominant role for regional transport contributions on those days when sulfate air pollution is highest in Baltimore, with a principal transport pathway from the Ohio River Valley (ORV) through southern Pennsylvania and Maryland, consistent with earlier studies. Thus, reductions in sulfur emissions from the ORV under the EPA's Clean Air Interstate Rule may be expected to improve particulate air quality in Baltimore during summer. The Lagrangian sampling of CMAQ offers an inexpensive and complimentary approach to traditional methods of source apportionment based on multivariate observational data analysis, and air quality model emissions separation. This study serves as a prototype for the method applied to Baltimore. EPA is establishing a system to allow air quality planners to readily produce and access equivalent results for locations of their choice.     

Modeling Nitrate-Nitrogen Load Reduction Strategies for the Des Moines River,Iowa Using SWAT

The Des Moines River that drains a watershed of 16,175 km² in portions of Iowa and Minnesota is impaired for nitrate-nitrogen (nitrate) due to concentrations that exceed regulatory limits for public water supplies. The Soil Water Assessment Tool (SWAT) model was used to model streamflow and nitrate loads and evaluate a suite of basin-wide changes and targeting configurations to potentially reduce nitrate loads in the river. The SWAT model comprised 173 subbasins and 2,516 hydrologic response units and included point and nonpoint nitrogen sources. The model was calibrated for an 11-year period and three basin-wide and four targeting strategies were evaluated. Results indicated that nonpoint sources accounted for 95% of the total nitrate export. Reduction in fertilizer applications from 170 to 50 kg/ha achieved the 38% reduction in nitrate loads, exceeding the 34% reduction required. In terms of targeting, the most efficient load reductions occurred when fertilizer applications were reduced in subbasins nearest the watershed outlet. The greatest load reduction for the area of land treated was associated with reducing loads from 55 subbasins with the highest nitrate loads, achieving a 14% reduction in nitrate loads achieved by reducing applications on 30% of the land area. SWAT model results provide much needed guidance on how to begin implementing load reduction strategies most efficiently in the Des Moines River watershed.     

An investigation into the origins of a series of PM10 anomalies at a remote location in NW England

Throughout 2004, PM(10) concentrations were measured at 10 min intervals at Hazelrigg, a remote location in NW England. The annual mean concentration was 6.1 microg m(-3) and likely origins were determined using directional and particle size characteristics. The fine temporal resolution of the monitoring also allowed several short periods (< 20 h) of persistently high PM(10) concentration to be identified and then 'typed' by event start time, duration, wind direction and particle size characteristics. A series of night time PM(10) anomalies (concentration < 465 microg m(-3)) of no obvious source were identified, and by elimination assumed to have originated from a ground-based fire of particle-rich fodder. A novel methodology combining Stokes' Law with systematic and rigorous modelling of source strength (using ADMS3.2) was developed to locate a possible burn site. The process was limited by the lack of previous modelling studies related to ground-based fires, and also by the capacity of ADMS3.2 to model sub-hourly time-varying emissions and fluctuations in wind speed and direction in the near field. However, modelling did suggest the source was located <400 m SSE of Hazelrigg, and investigation of this area revealed a burn site where tyres and plastic bags were piled nearby. Few studies have combined directional analysis and modelling to locate a source based on sampled data. This innovative methodology could be used by regulatory bodies to investigate the origins of unidentified PM(10) observed within the particle record.     

Is shrimp farming a successful adaptation to salinity intrusion? A geospatial associative analysis of poverty in the populous Ganges–Brahmaputra–Meghna Delta of Bangladesh

The Ganges–Brahmaputra–Meghna delta of Bangladesh is one of the most populous deltas in the world, supporting as many as 140 million people. The delta is threatened by diverse environmental stressors including salinity intrusion, with adverse consequences for livelihood and health. Shrimp farming is recognised as one of the few economic adaptations to the impacts of the rapidly salinizing delta. Although salinity intrusion and shrimp farming are geographically co-located in the delta, there has been no systematic study to examine their geospatial associations with poverty. In this study, we use multiple data sources including Census, Landsat Satellite Imagery and soil salinity survey data to examine the extent of geospatial clustering of poverty within the delta and their associative relationships with salinity intensity and shrimp farming. The analysis was conducted at the union level, which is the lowest local government administrative unit in Bangladesh. The findings show a strong clustering of poverty in the delta, and whilst different intensities of salinization are significantly associated with increasing poverty, neither saline nor freshwater shrimp farming has a significant association with poverty. These findings suggest that whilst shrimp farming may produce economic growth, in its present form it has not been an effective adaptation for the poor and marginalised areas of the delta. The study demonstrates that there are a series of drivers of poverty in the delta, including salinization, water logging, wetland/mudflats, employment, education and access to roads, amongst others that are discernible spatially, indicating that poverty alleviation programmes in the delta require strengthening with area-specific targeted interventions.