Using empirical models of species colonization under multiple threatening processes to identify complementary threat‐mitigation strategies

Approaches to prioritize conservation actions are gaining popularity. However, limited empirical evidence exists on which species might benefit most from threat mitigation and on what combination of threats, if mitigated simultaneously, would result in the best outcomes for biodiversity. We devised a way to prioritize threat mitigation at a regional scale with empirical evidence based on predicted changes to population dynamics—information that is lacking in most threat‐management prioritization frameworks that rely on expert elicitation. We used dynamic occupancy models to investigate the effects of multiple threats (tree cover, grazing, and presence of an hyperaggressive competitor, the Noisy Miner (Manorina melanocephala) on bird‐population dynamics in an endangered woodland community in southeastern Australia. The 3 threatening processes had different effects on different species. We used predicted patch‐colonization probabilities to estimate the benefit to each species of removing one or more threats. We then determined the complementary set of threat‐mitigation strategies that maximized colonization of all species while ensuring that redundant actions with little benefit were avoided. The single action that resulted in the highest colonization was increasing tree cover, which increased patch colonization by 5% and 11% on average across all species and for declining species, respectively. Combining Noisy Miner control with increasing tree cover increased species colonization by 10% and 19% on average for all species and for declining species respectively, and was a higher priority than changing grazing regimes. Guidance for prioritizing threat mitigation is critical in the face of cumulative threatening processes. By incorporating population dynamics in prioritization of threat management, our approach helps ensure funding is not wasted on ineffective management programs that target the wrong threats or species.     

Environmental cost of using poor decision metrics to prioritize environmental projects

Conservation decision makers commonly use project‐scoring metrics that are inconsistent with theory on optimal ranking of projects. As a result, there may often be a loss of environmental benefits. We estimated the magnitudes of these losses for various metrics that deviate from theory in ways that are common in practice. These metrics included cases where relevant variables were omitted from the benefits metric, project costs were omitted, and benefits were calculated using a faulty functional form. We estimated distributions of parameters from 129 environmental projects from Australia, New Zealand, and Italy for which detailed analyses had been completed previously. The cost of using poor prioritization metrics (in terms of lost environmental values) was often high—up to 80% in the scenarios we examined. The cost in percentage terms was greater when the budget was smaller. The most costly errors were omitting information about environmental values (up to 31% loss of environmental values), omitting project costs (up to 35% loss), omitting the effectiveness of management actions (up to 9% loss), and using a weighted‐additive decision metric for variables that should be multiplied (up to 23% loss). The latter 3 are errors that occur commonly in real‐world decision metrics, in combination often reducing potential benefits from conservation investments by 30–50%. Uncertainty about parameter values also reduced the benefits from investments in conservation projects but often not by as much as faulty prioritization metrics.     

Revisiting the national corporate social responsibility index

This paper relies on Gjølberg’s national corporate social responsibility (CSR) index while its purpose is twofold. First, it seeks to extend the methodological instrument for assessing national CSR and, second, it applies the new approach to a much larger pool of countries (n = 86) in an attempt to provide a global CSR outlook. The emergent picture from the study is one of deficient CSR penetration and wide variation among countries where most of the assessed countries are still lagging in the endorsement of international CSR initiatives and schemes. Findings offer fertile ground to theorists and researchers for a deeper investigation of the national specificity of CSR and to further identify institutional determinants that shape the social responsiveness and self-regulation of business entities. The study has also implications for managers and top executives to consider as it infers that the national background can be influential in the development of a CSR agenda and can condition the level of CSR penetration.     

Insight into selected emerging micropollutant interactions with wastewater colloidal organic carbon: implications for water treatment and analysis

Environmental Science and Pollution Research - This study reports how adding a membrane filter (0.45-μm cellulose nitrate filter) between a glass fibre filter and the solid phase extraction...     

Biogeochemical consequences of a changing Arctic shelf seafloor ecosystem

Unprecedented and dramatic transformations are occurring in the Arctic in response to climate change, but academic, public, and political discourse has disproportionately focussed on the most visible and direct aspects of change, including sea ice melt, permafrost thaw, the fate of charismatic megafauna, and the expansion of fisheries. Such narratives disregard the importance of less visible and indirect processes and, in particular, miss the substantive contribution of the shelf seafloor in regulating nutrients and sequestering carbon. Here, we summarise the biogeochemical functioning of the Arctic shelf seafloor before considering how climate change and regional adjustments to human activities may alter its biogeochemical and ecological dynamics, including ecosystem function, carbon burial, or nutrient recycling. We highlight the importance of the Arctic benthic system in mitigating climatic and anthropogenic change and, with a focus on the Barents Sea, offer some observations and our perspectives on future management and policy.     

A Regional Classification Scheme for Estimating Reference Water Quality in Streams Using Land-Use-Adjusted Spatial Regression-Tree Analysis

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States.     

Nitrate and sediment fluxes from a California rangeland watershed

Long-term water quality records for assessing natural variability, impact of management, and that guide regulatory processes to safeguard water resources are rare for California oak woodland rangelands. This study presents a 20-yr record (1981-2000) of nitrate-nitrogen (NO(3)-N) and suspended sediment export from a typical, grazed oak woodland watershed (103 ha) in the northern Sierra Nevada foothills of California. Mean annual precipitation over the 20-yr period was 734 mm yr(-1) (range 366-1205 mm yr(-1)). Mean annual stream flow was 353 mm y(-1) (range 87-848 mm yr(-1)). Average annual stream flow was 48.1 +/- 16% of precipitation. Mean annual NO(3)-N export was 1.6 kg ha(-1) yr(-1) (range 0.18-3.6 kg ha(-1) yr(-1)). Annual NO(3)-N export significantly (P < 0.05) increased with increasing annual stream flow and precipitation. Mean daily NO(3)-N export was 0.004 kg ha(-1) d(-1) (range 10(-5) to 0.55 kg ha(-1) d(-1)). Mean annual suspended sediment export was 198 kg ha(-1) yr(-1) (range 23-479 kg ha(-1) yr(-1)). There was a positive relationship (P < 0.05) between annual suspended sediment export, annual stream flow and precipitation. Mean daily suspended sediment export was 0.54 kg ha(-1) d(-1) (range 10(-4) to 155 kg ha(-1) d(-1)). Virtually no sediment was exported during the dry season. The large variation in daily and annual fluxes highlights the necessity of using long-term records to establish quantitative water quality targets for rangelands and demonstrates the difficulty of designing a water quality monitoring program for these ecosystems.     

Diuron in surface runoff and tile drainage from two grass-seed fields

The typical method of cool-season grass-seed production in Mediterranean climates briefly exposes surface waters to potentially high concentrations of the herbicide diuron [3-(3,4-dichlorophenyl)-1,1-dimethyl urea] during the initial season of growth. To better understand the process, and the degree, of diuron transport from agricultural fields, two grass-seed fields in the Willamette Valley of Oregon were monitored for diuron loss in surface runoff and tile drainage during the first wet season after planting. Initial diuron concentrations in surface runoff were high (>1000 microg L(-1) in one field and >100 microg L(-1) in the other), though they decreased by two orders of magnitude by the end of the season. Concentrations in the tile drains were as much as 1000 times lower than in the surface runoff during the first few weeks of runoff events, and they remained lower than surface water concentrations throughout the season. Total losses in surface runoff were between 1.3 and 3% of the amount applied-much higher than losses via the tile drains. It is also shown by means of a simple first-order decay model that, when little information is available, it may be best to describe diuron depletion in runoff water as a function of cumulative rainfall during the wet season.