Face mask and medical waste generation in the City of Baguio,Philippines: its current management and GHG footprint

Journal of Material Cycles and Waste Management - The daily use of facemask to prevent virus transmission increases the negative effect on the environment because of improper waste disposal. Due to...     

Long-term Dynamics of Pike Infection by Parasites Triaenophorus crassus and T. nodulosus (Plathelminthes,Cestoda) in the Rybinsk Reservoir: Effect of Hydraulic Construction and Climate Warming

Russian Journal of Ecology - The long-term dynamics (over more than 70 years) of pike infection by cestodes Triaenophorus crassus and T. nodulosus in the Rybinsk Reservoir (the Volga River) has...     

Effect of Anthropogenic Factors on the Ability of Narrow-skulled Voles (Lasiopodomys gregalis) to Adapt to Captive Conditions

Russian Journal of Ecology - To test the hypothesis that animals from habitats exposed to high anthropogenic pressure are more successful in adapting to captivity, immature narrow-skulled voles...     

Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida).     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

Time perspective balance and team adaptation in dynamic task contexts

The concept of time perspective balance has attracted increased attention from scholars in the past decade, reflected in published evidence suggesting positive outcomes ranging from enhanced mood to life satisfaction for those individuals possessing balance among their past, present, and future time perspectives, and assumedly able to shift their time perspective to match situational demands. In this paper, we consider the notion of time perspective balance in an organizational setting within which much consequential adaptation often occurs—the team environment—and explore different configurations of time perspective balance in teams facing dynamic task contexts. Drawing from work on situational awareness, we first consider the mechanism by which time perspective balance likely influences individual adaptation in dynamic task-focused situations. Next, we postulate what types of team configurations—ones with more balanced time perspective uniformity or ones with more time perspective variety—might be more appropriate in dynamic contexts given key team conditions. We illustrate our analysis with examples from healthcare team settings and offer ideas for future research.     

Empirical analysis of shared leadership promotion and team creativity: An adaptive leadership perspective

Promoting shared leadership in teams and enhancing team creativity is aided by complementarity between leader and team member characteristics. We integrate insights from social learning theory and dominance complementarity perspective with the team leadership and creativity literature to explore the facilitating role of formal participative leadership for enhancing team creativity indirectly by promoting shared leadership. The relationships among formal participative leadership, shared leadership, and team creativity are bounded by team voice behavior and team creative efficacy. To test our theoretical model, we collected multisource and multiwave survey data from 382 members of 73 teams. Results revealed a significant positive relationship of participative leadership with shared leadership in teams, which in turn was positively associated with team creativity. Team voice behavior and team creative efficacy moderated these relationships, respectively, by strengthening the positive relationships. We discuss the theoretical contributions, practical implications, and future directions of our findings.     

Environmental pollution,hydropower and nuclear energy generation before and after catastrophe: Bathtub-Weibull curve and MS-VECM methods

In this paper, the life span of hydro and nuclear energy generations and the relationship between hydro and nuclear energy generations, environmental pollution, and economic growth were investigated for Japan covering the period of 1960–2018 by employing the Bathtub-Weibull curve and Markov switching-vector error correcting (MSVEC) method, respectively. According to the Bathtub-Weibull curve analysis, a rising failure rate for nuclear energy was found, indicating that the life of nuclear energy has expired, but a decreasing failure rate for hydroelectric energy has been detected. Then two different MSVEC models were used. The MSVEC method, unlike traditional approaches, determines the relationship between variables under different regimes. The results of MSVEC methods indicate three important points. First, regime-dependent asymmetry and regime changes are crucial for policy recommendations. Second, the shocks to hydropower and nuclear energy generations cause temporary deviations from the long-run growth path in both regimes. Lastly, the increase in hydropower generation leads to a decrease in environmental pollution and an increase in GDP, and an increase in nuclear power generation increases pollution and growth in both regimes.