An approach for determining the extent of contribution of construction project features to accident causation

In the pursuit of Health and Safety (H&S) improvement within the UK construction industry, several studies have been conducted to identify accident causal factors to enable the development of accident prevention measures. Adding to such studies, a critique of H&S literature demonstrates that construction project features (CPFs) such as the nature of project, method of construction, site restriction, project duration, procurement system, design complexity, level of construction, and subcontracting contribute to accident causation and that their contribution is through the introduction of proximal accident causal factors into the construction process. However, the extent of this contribution by these CPFs remains sparingly known and requires further investigation. The study provides this insight by indicating that the extent to which CPFs contribute to accident causation is influenced by two factors; the extent to which the proximal factors contribute to accident causation; and the extent to which the proximal factors are prevalent within the CPFs. In line with this fresh insight, an approach for determining the extent to which CPFs contribute to accident causation is put forth. The approach proposes to use a qualitative–quantitative rating scale to determine the two determinant factors and then combine them using a mathematical formula to obtain the extent to which CPFs contribute to accident causation. By this approach the grey areas in literature concerning the extent to which CPFs contribute to accident causation will be illuminated and by that contribute to improvement in construction accident prevention.     

Fine-scale habitat modeling of a top marine predator: do prey data improve predictive capacity?

Predators and prey assort themselves relative to each other, the availability of resources and refuges, and the temporal and spatial scale of their interaction. Predictive models of predator distributions often rely on these relationships by incorporating data on environmental variability and prey availability to determine predator habitat selection patterns. This approach to predictive modeling holds true in marine systems where observations of predators are logistically difficult, emphasizing the need for accurate models. In this paper, we ask whether including prey distribution data in fine-scale predictive models of bottlenose dolphin (Tursiops truncatus) habitat selection in Florida Bay, Florida, U.S.A., improves predictive capacity. Environmental characteristics are often used as predictor variables in habitat models of top marine predators with the assumption that they act as proxies of prey distribution. We examine the validity of this assumption by comparing the response of dolphin distribution and fish catch rates to the same environmental variables. Next, the predictive capacities of four models, with and without prey distribution data, are tested to determine whether dolphin habitat selection can be predicted without recourse to describing the distribution of their prey. The final analysis determines the accuracy of predictive maps of dolphin distribution produced by modeling areas of high fish catch based on significant environmental characteristics. We use spatial analysis and independent data sets to train and test the models. Our results indicate that, due to high habitat heterogeneity and the spatial variability of prey patches, fine-scale models of dolphin habitat selection in coastal habitats will be more successful if environmental variables are used as predictor variables of predator distributions rather than relying on prey data as explanatory variables. However, predictive modeling of prey distribution as the response variable based on environmental variability did produce high predictive performance of dolphin habitat selection, particularly foraging habitat.     

Flightlessness and the energetic cost of wing molt in a large sea duck

Although the replacement of feathers apparently represents the major event of somatic production in the annual cycle of wild birds, knowledge about the energetics of molt has always been hampered by logistical and technical difficulties, which are exacerbated by the fact that birds are able to compensate behaviorally to buffer any variation in energy demand. During wing molt, sea ducks (Mergini) and other diving birds lose all of their wing feathers at once, leading to a period of temporary flightlessness of variable duration, a condition that considerably restricts their movements and increases the probability of predation. In the present study, we present the first results aimed at quantifying the duration of flightlessness, energy expenditure, and foraging effort during molt of a wing-propelled diving bird, the Common Eider (Somateria mollissima). Data loggers were implanted in the body cavity of 13 females to record heart rate and hydrostatic pressure (depth) every two seconds for a period of 220 days. Flight frequency and duration were assessed from elevated and constant heart rate, and the absence of flight was used to quantify the duration of flightlessness, which lasted, on average, 36 +/- 8 days (mean +/- SD). Using a period of four weeks before and four weeks after the flightless period, we found that dive depth (ranging from 1 to 2 m, on average) and daily diving time did not vary during the course of the study. Daily metabolic rate increased by 9%, and resting metabolic rate by 12% from the pre-molt period to the flightless period and remained high during the post-molt period. This study indicates that the energetic costs of replacing flight remiges in female eiders are substantial, although this is not associated with any change in foraging effort, which suggests that female Common Eiders lose mass during wing molt. Finally, estimates of energy savings associated with the total absence of flights during wing molt represent 6% of daily metabolic rate or 14% of resting metabolic rate. This finding contrasts with the classical view that little or no benefit is associated with a flightless condition. We suggest that such energy savings may have favored the evolution of temporary flightlessness in diving birds.     

Mechanisms and impacts of an incentive-based conservation program with evidence from a randomized control trial

Conservation science needs more high-quality impact evaluations, especially ones that explore mechanisms of success or failure. Randomized control trials (RCTs) provide particularly robust evidence of the effectiveness of interventions (although they have been criticized as reductionist and unable to provide insights into mechanisms), but there have been few such experiments investigating conservation at the landscape scale. We explored the impact of Watershared, an incentive-based conservation program in the Bolivian Andes, with one of the few RCTs of landscape-scale conservation in existence. There is strong interest in such incentive-based conservation approaches as some argue they can avoid negative social impacts sometimes associated with protected areas. We focused on social and environmental outcomes based on responses from a household survey in 129 communities randomly allocated to control or treatment (conducted both at the baseline in 2010 and repeated in 2015–2016). We controlled for incomplete program uptake by combining standard RCT analysis with matching methods and investigated mechanisms by exploring intermediate and ultimate outcomes according to the underlying theory of change. Previous analyses, focused on single biophysical outcomes, showed that over its first 5 years Watershared did not slow deforestation or improve water quality at the landscape scale. We found that Watershared influenced some outcomes measured using the survey, but the effects were complex, and some were unexpected. We thus demonstrated how RCTs can provide insights into the pathways of impact, as well as whether an intervention has impact. This paper, one of the first registered reports in conservation science, demonstrates how preregistration can help make complex research designs more transparent, avoid cherry picking, and reduce publication bias.     

Quantitative analyses of selected polychlorinated biphenyl (PCB) congeners in water,soil, and sediment during winter and spring seasons from Msunduzi River,South Africa

The lack of information and the need for knowledge on the organic pollutants within the area of KwaZulu-Natal together with the global problem of water supply have prompted our investigation into the analyses of eight polychlorinated biphenyl (PCB) congeners in the Msunduzi River of KwaZulu-Natal, South Africa. Soil, sediment, and water samples were collected at ten different sites along the river during winter and spring seasons. Soil and sediment samples were extracted using ultra sonication with dichloromethane while water samples were liquid-liquid extracted using dichloromethane. All sample extracts were cleaned-up using a multi-layer silica gel column and analyzed with gas chromatography-mass spectrometry. Quality assurance measures were also determined. The percentage recoveries for water were 53–128 for all the PCBs analyzed, while sediment recoveries ranged between 69 and 105%. The highest total concentrations of the PCBs in sediment were 214.21–610.45 ng/g dw at the Du Toit sampling site and 30.86–444.43 ng/g dw basis at the wastewater treatment inlet for winter and spring, respectively. Soil PCB concentrations were 76.53–397.75 ng/g dw at the Msunduzi Town sampling site and 20.84–443.49 ng/g (dry weight) at the Du Toit sampling site for winter and spring, respectively. In addition, high PCB concentrations were found in effluent of the wastewater treatment inlet compared to other sampling sites, which ranged between 0.68–22.37 and 2.53–35.69 ng/mL for winter and spring seasons, respectively. In all the sampling sites selected for this study, Du Toit afforded the highest PCB concentration levels and the lowest was after chlorination at the Darvill wastewater treatment plant. The results presented are new and it is the first study of organic pollutants such as PCBs that has been carried out on this river.     

Assessing uncertainty in annual nitrogen,phosphorus, and suspended sediment load estimates in three agricultural streams using a 21-year dataset

Accurate estimation of constituent loads is important for studies of ecosystem mass balance or total maximum daily loads. In response, there has been an effort to develop methods to increase both accuracy and precision of constituent load estimates. The relationship between constituent concentration and stream discharge is often complicated, potentially leading to high uncertainty in load estimates for certain constituents, especially at longer-term (annual) scales. We used the loadflex R package to compare uncertainty in annual load estimates from concentration vs. discharge relationships in constituents of interest in agricultural systems, including ammonium as nitrogen (NH₄-N), nitrate as nitrogen (NO₃-N), soluble reactive phosphorus (SRP), and suspended sediments (SS). We predicted that uncertainty would be greatest in NO₃-N and SS due to complex relationships between constituent concentration and discharge. We also predicted lower uncertainty with a composite method compared to regression or interpolation methods. Contrary to predictions, we observed the lowest uncertainty in annual NO₃-N load estimates (relative error 1.5–23%); however, uncertainty was greatest in SS load estimates, consistent with predictions (relative error 19–96%). For all constituents, we also generally observed reductions in uncertainty by up to 34% using the composite method compared to regression and interpolation approaches, as predicted. These results highlight differences in uncertainty among different constituents and will aid in model selection for future studies requiring accurate and precise estimates of constituent load.     

Archetypical patterns and trajectories of land systems in Europe

Regional Environmental Change - Assessments of land-system change have dominantly focused on conversions among broad land-use categories, whereas intensity changes within these categories have...     

Impact of Length of Dataset on Streamflow Calibration Parameters and Performance of APEX Model

Due to resource constraints, long‐term monitoring data for calibration and validation of hydrologic and water quality models are rare. As a result, most models are calibrated and, if possible, validated using limited measured data. However, little research has been done to determine the impact of length of available calibration data on model parameterization and performance. The main objective of this study was to evaluate the impact of length of calibration data (LCD) on parameterization and performance of the Agricultural Policy Environmental eXtender model for predicting daily, monthly, and annual streamflow. Long‐term (1984‐2015) measured daily streamflow data from Rock Creek watershed, an agricultural watershed in northern Ohio, were used for this study. Data were divided into five Short (5‐year), two Medium (15‐year), and one Long (25‐year) streamflow calibration data scenarios. All LCD scenarios were calibrated and validated at three time steps: daily, monthly, and annual. Results showed LCD affected the ability of the model to accurately capture temporal variability in simulated streamflow. However, overall average streamflow, water budgets, and crop yields were simulated reasonably well for all LCD scenarios.