An integrated approach for predicting fates of reintroductions with demographic data from multiple populations

We devised a novel approach to model reintroduced populations whereby demographic data collected from multiple sites are integrated into a Bayesian hierarchical model. Integrating data from multiple reintroductions allows more precise population-growth projections to be made, especially for populations for which data are sparse, and allows projections that account for random site-to-site variation to be made before new reintroductions are attempted. We used data from reintroductions of the North Island Robin (Petroica longipes), an endemic New Zealand passerine, to 10 sites where non-native mammalian predators are controlled. A comparison of candidate models that we based on deviance information criterion showed that rat-tracking rate (an index of rat density) was a useful predictor of robin fecundity and adult female survival, that landscape connectivity and a binary measure of whether sites were on a peninsula were useful predictors of apparent juvenile survival (probably due to differential dispersal away from reintroduction sites), and that there was unexplained random variation among sites in all demographic rates. We used the two best supported models to estimate the finite rate of increase (λ) for populations at each of the 10 sites, and for a proposed reintroduction site, under different levels of rat control. Only three of the reintroduction sites had λ distributions completely >1 for either model. At two sites, λ was expected to be >1 if rat-tracking rates were <5%. At the other five reintroduction sites, λ was predicted to be close to 1, and it was unclear whether growth was expected. Predictions of λ for the proposed reintroduction site were less precise than for other sites because distributions incorporated the full range of site-to-site random variation in vital rates. Our methods can be applied to any species for which postrelease data on demographic rates are available and potentially can be extended to model multiple species simultaneously.     

The influence of host diversity and composition on epidemiological patterns at multiple spatial scales

Spatial patterns of pathogen prevalence are determined by ecological processes acting across multiple spatial scales. Host-pathogen interactions are influenced by community composition, landscape structure, and environmental factors. Explaining prevalence patterns requires an understanding of how local determinants of infection, such as community composition, are mediated by landscape characteristics and regional-scale environmental drivers. Here we investigate the role of local community interactions and the effects of landscape structure on the dynamics of barley and cereal yellow dwarf viruses (B/CYDV) in the open meadows of the Cascade Mountains of Oregon. B/CYDV is an aphid-transmitted, generalist pathogen of over 100 wild and cultivated grass species. We used variance components analysis and model selection techniques to partition the sources of variation in B/CYDV prevalence and to determine which abiotic and biotic factors influence host-pathogen interactions in a Cascades meadowsystem. B/CYDV prevalence in Cascades meadows varied by host species identity, with a significantly higher proportion of infected Festuca idahoensis individuals than Elymus glaucus or Bromus carinatus. Although there was significant variation in prevalence among host species and among meadows in the same meadow complex, there was no evidence of any significant variation in prevalence among different meadow complexes at a larger spatial scale. Variation in prevalence among meadows was primarily associated with the local community context (host identity, the relative abundance of different host species, and host species richness) and the physical landscape attributes of the meadow. These results highlight the importance of local host community composition, mediated by landscape characteristics such as meadow aspect, as a determinant of the spatial pattern of infection of a multi-host pathogen.     

Midwest U.S. landscape change to 2020 driven by biofuel mandates

Meeting future biofuel targets set by the 2007 Energy Independence and Security Act (EISA) will require a substantial increase in production of corn. The Midwest, which has the highest overall crop production capacity, is likely to bear the brunt of the biofuel-driven changes. In this paper, we set forth a method for developing a possible future landscape and evaluate changes in practices and production between base year (BY) 2001 and biofuel target (BT) 2020. In our BT 2020 Midwest landscape, a total of 25 million acres (1 acre = 0.40 ha) of farmland was converted from rotational cropping to continuous corn. Several states across the Midwest had watersheds where continuous corn planting increased by more than 50%. The output from the Center for Agriculture and Rural Development (CARD) econometric model predicted that corn grain production would double. In our study we were able to get within 2% of this expected corn production. The greatest increases in corn production were in the Corn Belt as a result of conversion to continuous corn planting. In addition to changes to cropping practices as a result of biofuel initiatives we also found that urban growth would result in a loss of over 7 million acres of productive farmland by 2020. We demonstrate a method which successfully combines economic model output with gridded land cover data to create a spatially explicit detailed classification of the landscape across the Midwest. Understanding where changes are likely to take place on the landscape will enable the evaluation of trade-offs between economic benefits and ecosystem services allowing proactive conservation and sustainable production for human well-being into the future.     

Integrated approach to winery waste: waste generation and data consolidation

The winemaking process involves the generation of a significant amount of waste and wastewater. These residues should be addressed for recycling or treatment before being returned to environment. As each winery is unique in waste generation and disposal, plans for environmentally friendly waste management are not universal and should be tested for their effectiveness. In this study, a diagnostic was made during three years, in different wineries, throughout Portugal, in order to quantify and characterize the waste and the wastewater produced. The results showed that solid waste and wastewater are mainly produced during the harvest period, corresponding to 74% and 87%, respectively. One ton of processed grape approximately produce 0.13 t marc, 0.06 t lees, 0.03 t of stalks and 1.65 m³ of wastewater. No significant differences (P≤0.05) were observed for grape marc, lees and wastewater ratios, between years or wineries. With respect to the stalk ratio, there was no effect of year but the winery significantly affected this ratio (P≤0.05). During the study period the treated wastewater, since diluted, revealed suitable characteristics for irrigation representing an additional source of water. In this regard, the data acquisition and consolidation ensure the transfer of information and experience which constitute an essential step in a support decision tool design.     

Modeling scale up of anthropogenic impacts from individual pollinator behavior to pollination systems

Understanding how anthropogenic disturbances affect plant–pollinator systems has important implications for the conservation of biodiversity and ecosystem functioning. Previous laboratory studies show that pesticides and pathogens, which have been implicated in the rapid global decline of pollinators over recent years, can impair behavioral processes needed for pollinators to adaptively exploit floral resources and effectively transfer pollen among plants. However, the potential for these sublethal stressor effects on pollinator–plant interactions at the individual level to scale up into changes to the dynamics of wild plant and pollinator populations at the system level remains unclear. We developed an empirically parameterized agent-based model of a bumblebee pollination system called SimBee to test for effects of stressor-induced decreases in the memory capacity and information processing speed of individual foragers on bee abundance (scenario 1), plant diversity (scenario 2), and bee–plant system stability (scenario 3) over 20 virtual seasons. Modeling of a simple pollination network of a bumblebee and four co-flowering bee-pollinated plant species indicated that bee decline and plant species extinction events could occur when only 25% of the forager population showed cognitive impairment. Higher percentages of impairment caused 50% bee loss in just five virtual seasons and system-wide extinction events in less than 20 virtual seasons under some conditions. Plant species extinctions occurred regardless of bee population size, indicating that stressor-induced changes to pollinator behavior alone could drive species loss from plant communities. These findings indicate that sublethal stressor effects on pollinator behavioral mechanisms, although seemingly insignificant at the level of individuals, have the cumulative potential in principle to degrade plant–pollinator species interactions at the system level. Our work highlights the importance of an agent-based modeling approach for the identification and mitigation of anthropogenic impacts on plant–pollinator systems.     

Coupling PCSWMM and WASP to Evaluate Green Stormwater Infrastructure Impacts to Storm Sediment Loads in an Urban Watershed

We coupled rainfall–runoff and instream water quality models to evaluate total suspended solids (TSS) in Wissahickon Creek, a mid‐sized urban stream near Philadelphia, Pennsylvania. Using stormwater runoff and instream field data, we calibrated the model at a subdaily scale and focused on storm responses. We demonstrate that treating event mean concentrations as a calibration parameter rather than a fixed input can substantially improve model performance. Urban stormwater TSS concentrations vary widely in time and space and are difficult to represent simply. Suspended and deposited sediment pose independent stressors to stream biota and model results suggest that both currently impair stream health in Wissahickon Creek. Retrofitting existing detention basins to prioritize infiltration reduced instream TSS loads by 20%, suggesting that infiltration mitigates sediment more effectively than detention. Infiltrating stormwater from 30% of the watershed reduced instream TSS loads by 47% and cut the frequency of TSS exceeding 100 mg/L by half. Settled loads and the frequency of high TSS values were reduced by a smaller fraction than suspended loads and duration at high TSS values. A widely distributed network of infiltration‐focused projects is an effective stormwater management strategy to mitigate sediment stress. Coupling rainfall–runoff and water quality models is an important way to integrate watershed‐wide impacts and evaluate how management directly affects urban stream health.     

There's nowhere to go: counting the costs of extreme weather to the homeless community

People experiencing homelessness are vulnerable to extreme weather in unique ways. The entrenched inequalities that underpin disaster vulnerability are compounded by extreme isolation and the stress of transient living on mental and physical health. However, the impacts of extreme weather on the homeless in Australia are largely undocumented and rarely incorporated in emergency planning. Interviews with and surveys of emergency and homeless services and service users revealed that the primary ramifications of losing shelter and worsening mental health deepen the cycle of homelessness and trauma. Consequently, homeless shelter losses, such as tents, should be included in pre‐ and post‐event impact statistics and subsequent recovery support. Extreme weather response plans should include early triggers and strategies for ‘non‐severe’ weather events, as the homeless community is affected earlier and by a wider range of meteorological conditions. Moreover, this study also explores the benefits of a trauma‐informed response to extreme weather when working with the homeless.     

Solar‐powered in situ soil washing with surfactant to collect LNAPL

This article presents the findings of a sustainable, surfactant‐enhanced, product recovery pilot‐scale study (PSS) completed between January 2010 and May 2010 at the Hydrocarbon Burn Facility located at the John F. Kennedy Space Center in Florida. The goal of this study was to implement a unique, simple, and sustainable light nonaqueous‐phase liquid (LNAPL) recovery process and evaluate site‐specific volumes and rates of LNAPL that could be collected and the degree of soil and groundwater cleanup that could be achieved. The recovery process was a combination of groundwater recirculation at a rate of approximately 2.9 gallons per minute (11.0 liters per minute), soil washing via LNAPL mobilization, and collection of LNAPL via a hydrophobic LNAPL skimmer. A biodegradable surfactant, ECOSURF^TM SA‐15, was added to the recirculation line to lower the interfacial tension and facilitate LNAPL recovery via mobilization. All equipment (submersible pump, LNAPL skimmer, surfactant feed pump, controls, and various other equipment) used was powered by a solar panel array. Approximately 60 gallons (227 liters) or 429 pounds (195 kilograms) of LNAPL were collected at the recirculation site over approximately three months during the PSS. The data suggest that surfactant amendments greatly enhanced free product collection. The maximum rate of free product collection was approximately 1 gallon (3.8 liters) per day. © 2012 Wiley Periodicals, Inc.