A Guide to Understanding Social Science Research for Natural Scientists

Natural scientists are increasingly interested in social research because they recognize that conservation problems are commonly social problems. Interpreting social research, however, requires at least a basic understanding of the philosophical principles and theoretical assumptions of the discipline, which are embedded in the design of social research. Natural scientists who engage in social science but are unfamiliar with these principles and assumptions can misinterpret their results. We developed a guide to assist natural scientists in understanding the philosophical basis of social science to support the meaningful interpretation of social research outcomes. The 3 fundamental elements of research are ontology, what exists in the human world that researchers can acquire knowledge about; epistemology, how knowledge is created; and philosophical perspective, the philosophical orientation of the researcher that guides her or his action. Many elements of the guide also apply to the natural sciences. Natural scientists can use the guide to assist them in interpreting social science research to determine how the ontological position of the researcher can influence the nature of the research; how the epistemological position can be used to support the legitimacy of different types of knowledge; and how philosophical perspective can shape the researcher's choice of methods and affect interpretation, communication, and application of results. The use of this guide can also support and promote the effective integration of the natural and social sciences to generate more insightful and relevant conservation research outcomes. Una Guía para Entender la Investigación de Ciencias Sociales para las Ciencias Naturales Katie Moon     

Using environmental heterogeneity to plan for sea‐level rise

Environmental heterogeneity is increasingly being used to select conservation areas that will provide for future biodiversity under a variety of climate scenarios. This approach, termed conserving nature's stage (CNS), assumes environmental features respond to climate change more slowly than biological communities, but will CNS be effective if the stage were to change as rapidly as the climate? We tested the effectiveness of using CNS to select sites in salt marshes for conservation in coastal Georgia (U.S.A.), where environmental features will change rapidly as sea level rises. We calculated species diversity based on distributions of 7 bird species with a variety of niches in Georgia salt marshes. Environmental heterogeneity was assessed across six landscape gradients (e.g., elevation, salinity, and patch area). We used 2 approaches to select sites with high environmental heterogeneity: site complementarity (environmental diversity [ED]) and local environmental heterogeneity (environmental richness [ER]). Sites selected based on ER predicted present‐day species diversity better than randomly selected sites (up to an 8.1% improvement), were resilient to areal loss from SLR (1.0% average areal loss by 2050 compared with 0.9% loss of randomly selected sites), and provided habitat to a threatened species (0.63 average occupancy compared with 0.6 average occupancy of randomly selected sites). Sites selected based on ED predicted species diversity no better or worse than random and were not resilient to SLR (2.9% average areal loss by 2050). Despite the discrepancy between the 2 approaches, CNS is a viable strategy for conservation site selection in salt marshes because the ER approach was successful. It has potential for application in other coastal areas where SLR will affect environmental features, but its performance may depend on the magnitude of geological changes caused by SLR. Our results indicate that conservation planners that had heretofore excluded low‐lying coasts from CNS planning could include coastal ecosystems in regional conservation strategies.     

Highway toll and air pollution: Evidence from Chinese cities

Most highways in urban China are tolled to finance their construction. During the eight-day National Day holiday in 2012, highway tolls were waived nationwide for passenger vehicles. We use this to identify the effects of highway tolls on air pollution. Using daily pollution and weather data for 98 Chinese cities in 2011 and 2012 and employing both a regression discontinuity design and differences-in-differences method with the 2011 National Day holiday as a control, we find that eliminating tolls increases pollution by 20% and decreases visibility by one kilometer. We also estimate that the toll elasticity of air pollution is −0.15. These findings complement the scant literature on the environmental impact of road pricing.     

A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis

IntroductionWith the development of industries and increased diversity of their associated hazards, the importance of identifying these hazards and controlling the Occupational Health and Safety (OHS) risks has also dramatically augmented. Currently, there is a serious need for a risk management system to identify and prioritize risks with the aim of providing corrective/preventive measures to minimize the negative consequences of OHS risks. In fact, this system can help the protection of employees’ health and reduction of organizational costs. Method: The present study proposes a hybrid decision-making approach based on the Failure Mode and Effect Analysis (FMEA), Fuzzy Cognitive Map (FCM), and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) for assessing and prioritizing OHS risks. After identifying the risks and determining the values of the risk assessment criteria via the FMEA technique, the attempt is made to determine the weights of criteria based on their causal relationships through FCM and the hybrid learning algorithm. Then, the risk prioritization is carried out using the MOORA method based on the decision matrix (the output of the FMEA) and the weights of the criteria (the output of the FCM). Results: The results from the implementation of the proposed approach in a manufacturing company reveal that the score at issue can overcome some of the drawbacks of the traditional Risk Priority Number (RPN) in the conventional FMEA, including lack of assignment the different relative importance to the assessment criteria, inability to take into account other important management criteria, lack of consideration of causal relationships among criteria, and high dependence of the prioritization on the experts’ opinions, which finally provides a full and distinct risk prioritization.     

Fine‐resolution conservation planning with limited climate‐change information

Climate‐change induced uncertainties in future spatial patterns of conservation‐related outcomes make it difficult to implement standard conservation‐planning paradigms. A recent study translates Markowitz's risk‐diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However, this method is information intensive and requires a large number of forecasts of ecological outcomes associated with possible climate‐change scenarios for carrying out fine‐resolution conservation planning. We developed a technique for iterative, spatial portfolio analysis that can be used to allocate scarce conservation resources across a desired level of subregions in a planning landscape in the absence of a sufficient number of ecological forecasts. We applied our technique to the Prairie Pothole Region in central North America. A lack of sufficient future climate information prevented attainment of the most efficient risk‐return conservation outcomes in the Prairie Pothole Region. The difference in expected conservation returns between conservation planning with limited climate‐change information and full climate‐change information was as large as 30% for the Prairie Pothole Region even when the most efficient iterative approach was used. However, our iterative approach allowed finer resolution portfolio allocation with limited climate‐change forecasts such that the best possible risk‐return combinations were obtained. With our most efficient iterative approach, the expected loss in conservation outcomes owing to limited climate‐change information could be reduced by 17% relative to other iterative approaches.     

NABat: A top-down,bottom-up solution to collaborative continental-scale monitoring

Collaborative monitoring over broad scales and levels of ecological organization can inform conservation efforts necessary to address the contemporary biodiversity crisis. An important challenge to collaborative monitoring is motivating local engagement with enough buy-in from stakeholders while providing adequate top-down direction for scientific rigor, quality control, and coordination. Collaborative monitoring must reconcile this inherent tension between top-down control and bottom-up engagement. Highly mobile and cryptic taxa, such as bats, present a particularly acute challenge. Given their scale of movement, complex life histories, and rapidly expanding threats, understanding population trends of bats requires coordinated broad-scale collaborative monitoring. The North American Bat Monitoring Program (NABat) reconciles top-down, bottom-up tension with a hierarchical master sample survey design, integrated data analysis, dynamic data curation, regional monitoring hubs, and knowledge delivery through web-based infrastructure. NABat supports collaborative monitoring across spatial and organizational scales and the full annual lifecycle of bats.     

Ethanol mediated As(III) adsorption onto Zn-loaded pinecone biochar: Experimental investigation, modeling, and optimization using hybrid artificial neural network-genetic algorithm approach

Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box–Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand–metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model–genetic algorithm (RSM–GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47 μg/g) is facilitated at 30.22 mg C/L of EtOH with initial As(III) concentration of 196.77 μg/L at pH 5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM.     

Pseudomonas sp. ZXY-1, a newly isolated and highly efficient atrazine-degrading bacterium, and optimization of biodegradation using response surface methodology

Atrazine, a widely used herbicide, is increasing the agricultural production effectively, while also causing great environmental concern. Efficient atrazine-degrading bacterium is necessary to removal atrazine rapidly to keep a safe environment. In the present study, a new atrazine-degrading strain ZXY-1, identified as Pseudomonas, was isolated. This new isolated strain has a strong ability to biodegrade atrazine with a high efficiency of 9.09 mg/L/hr.Temperature, p H, inoculum size and initial atrazine concentration were examined to further optimize the degradation of atrazine, and the synthetic effect of these factors were investigated by the response surface methodology. With a high quadratic polynomial mathematical model(R~2= 0.9821) being obtained, the highest biodegradation efficiency of 19.03 mg/L/hr was reached compared to previous reports under the optimal conditions(30.71°C, pH 7.14, 4.23%(V/V) inoculum size and 157.1 mg/L initial atrazine concentration).Overall, this study provided an efficient bacterium and approach that could be potentially useful for the bioremediation of wastewater containing atrazine.     

生物滴滤塔装置脱硝效率优化改进实验

针对生物滴滤塔系统脱硝效率偏低的问题,在原实验室装置基础上,对滴滤塔系统进行改进,并模拟燃煤烟气的特性,考察了重金属离子、氧气含量以及强化剂对净化效果的影响,并探究了生物滴滤塔系统对锅炉非稳定运行工况的适应性。结果显示:烟气内的重金属离子对微生物具有较强的抑制作用,其中As离子和Pb离子对体系微生物组成的毒性影响最大,Zn离子的影响最小;氧气含量对脱硝效率影响的研究结果表明,系统含氧量越低,脱硝效率降低幅度越大;强化剂组合结果表明,亚硝酸钠+Fe(II)EDTA的组合,强化效果最为明显;生物滴滤塔脱硝系统对锅炉非稳定运行工况适应能力较差,系统停运再启动,停运1周之内,系统经过10 d可以恢复至原来的性能,如果停运12 d以上,系统恢复则长达30 d。根据研究结果,为中试研究提出优化及研究方向建议。     

流体剪切与超声空化破解剩余污泥的参数优化

为提高剩余污泥的破解效果并降低能耗,采用FS（fluid shear,流体剪切）、UC（ultrasonic cavitation,超声空化）、FS和UC联合工艺（FS-UC,UC-FS）破解剩余污泥,并应用单因素试验结合响应面法对联合工艺进行优化.结果表明:FS对剩余污泥破解效果一般,只在开始阶段具有较好效果,随作用时间延长,破解效果未有显著提高甚至下降.UC对剩余污泥破解效果明显,随作用时间延长,破解效果显著提升,但能耗也随之增大,EDR（energy disintegration ratio,效能比）明显下降.相同作用时间下,UC破解效果优于FS破解效果,UC破解剩余污泥的DD_COD（degree of disintegration,破解率）与EDR均明显高于FS方法.单因素试验得出的较优FS作用时间范围为2~8 min,较优UC作用时间范围为5~15 min.响应面法试验结果显示,联合工艺的剩余污泥破解效果和能量利用率均优于单一方法,联合工艺中FS-UC工艺的破解效果优于UC-FS工艺.FS-UC工艺的最佳参数:FS处理5.6 min再UC处理15.0 min,该条件下剩余污泥实际DD_COD为50.8%,EDR为26.8%.UC-FS工艺的最佳参数:先UC作用15.0 min再FS作用7.8 min,该条件下剩余污泥实际DD_COD为36.5%,EDR为17.1%.研究显示,以DD_COD和EDR为指标,4种工艺的高效性顺序为FS-UC > UC-FS > UC > FS,其中FS-UC工艺具有能耗低、破解效率高的特点,是4种工艺中剩余污泥破解效果最好的一种工艺.