Social-ecological outcomes of agricultural intensification

Land-use intensification in agrarian landscapes is seen as a key strategy to simultaneously feed humanity and use ecosystems sustainably, but the conditions that support positive social-ecological outcomes remain poorly documented. We address this knowledge gap by synthesizing research that analyses how agricultural intensification affects both ecosystem services and human well-being in low- and middle-income countries. Overall, we find that agricultural intensification is rarely found to lead to simultaneous positive ecosystem service and well-being outcomes. This is particularly the case when ecosystem services other than food provisioning are taken into consideration

Assessing the Microbial Community and Functional Genes in a Vertical Soil Profile with Long-Term Arsenic Contamination

Conceived and designed the experiments: GW. Performed the experiments: JX GL. Analyzed the data: JX JZ GW. Contributed reagents/materials/analysis tools: ST JZ GW. Wrote the paper: JX ZH JDVN JZ GW.Arsenic (As) contamination in soil and groundwater has become a serious problem to public health. To examine how microbial communities and functional genes respond to long-term arsenic contamination in vertical soil profile, soil samples were collected from the surface to the depth of 4 m (with an interval of 1 m) after 16-year arsenic downward infiltration. Integrating BioLog and functional gene microarray (GeoChip 3.0) technologies, we showed that microbial metabolic potential and diversity substantially decreased, and community structure was markedly distinct along the depth. Variations in microbial community functional genes, including genes responsible for As resistance, carbon and nitrogen cycling, phosphorus utilization and cytochrome c oxidases were detected. In particular, changes in community structures and activities were correlated with the biogeochemical features along the vertical soil profile when using the rbcL and nifH genes as biomarkers, evident for a gradual transition from aerobic to anaerobic lifestyles. The C/N showed marginally significant correlations with arsenic resistance (p = 0.069) and carbon cycling genes (p = 0.073), and significant correlation with nitrogen fixation genes (p = 0.024). The combination of C/N, NO3− and P showed the highest correlation (r = 0.779, p = 0.062) with the microbial community structure. Contradict to our hypotheses, a long-term arsenic downward infiltration was not the primary factor, while the spatial isolation and nutrient availability were the key forces in shaping the community structure. This study provides new insights about the heterogeneity of microbial community metabolic potential and future biodiversity preservation for arsenic bioremediation management.Yeshttp://www.plosone.org/static/editorial#pee

Eye-Tracking Metrics as an Indicator of Workload in Commercial Single-Pilot Operations

There is a current trend in commercial aviation that points toward a possible transition from two-crew to single-pilot operations (SPO). The workload on the single pilot is expected to be a major issue for SPO. In order to find the best support solutions for the pilot in SPO, a thorough understanding of pilot workload is required. The present study aims at evaluating pilot workload by means of eye-tracking metrics. A flight simulator study was conducted with commercial pilots. Their task was to fly short approach and landing scenarios with or without the support of a second pilot. The results showed that fixation frequencies were higher during SPO, average dwell durations decreased, and participants transitioned more frequently between different areas of interest. These results suggest that particularly the temporal demand might be an issue for a possible transition to SPO. The eye-tracking metrics support results obtained from subjective workload ratings

The benefits of tree-based models for stock selection

The identification of the primary drivers of stock returns has been of great interest to both financial practitioners and academics alike for many decades. Influenced by classical financial theories such as the CAPM (Sharp, 1964; Lintner, 1965) and APT (Ross, 1976), a linear relationship is conventionally assumed between company characteristics as derived from their financial accounts and forward returns. Whilst this assumption may be a fair approximation to the underlying structural relationship, it is often adopted for the purpose of convenience. It is actually quite rare that the assumptions of distributional normality and a linear relationship are explicitly assessed in advance even though this information would help to inform the appropriate choice of modelling technique. Non-linear models have nevertheless been applied successfully to the task of stock selection in the past (Sorensen et al, 2000). However, their take-up by the investment community has been limited despite the fact that researchers in other fields have found them to be a useful way to express knowledge and aid decision-making..