A systematic review of animal personality in conservation science

Although animal personality research may have applied uses, this suggestion has yet to be evaluated by assessing empirical studies examining animal personality and conservation. To address this knowledge gap, we performed a systematic review of the peer-reviewed literature relating to conservation science and animal personality. Criteria for inclusion in our review included access to full text, primary research articles, and relevant animal conservation or personality focus (i.e., not human personality studies). Ninety-two articles met these criteria. We summarized the conservation contexts, testing procedures (including species and sample size), analytical approach, claimed personality traits (activity, aggression, boldness, exploration, and sociability), and each report's key findings and conservation-focused suggestions. Although providing evidence for repeatability in behavior is crucial for personality studies, repeatability quantification was implemented in only half of the reports. Nonetheless, each of the 5 personality traits were investigated to some extent in a range of conservations contexts. The most robust studies in the field showed variance in how personality relates to other ecologically important variables across species and contexts. Moreover, many studies were first attempts at using personality for conservation purposes in a given study system. Overall, it appears personality is not yet a fully realized tool for conservation. To apply personality research to conservation problems, we suggest researchers think about where individual differences in behavior may affect conservation outcomes in their system, assess where there are opportunities for repeated measures, and follow the most current methodological guides on quantifying personality.     

Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.     

Mowers versus growers: Riparian buffer management in the Southern Blue Ridge Mountains,USA

Despite long-standing knowledge of the benefits of riparian buffers for mitigating nonpoint source pollution, many streams are unprotected by buffers. Even landowners who understand ecological values of buffers mow riparian vegetation to the streambank. Do trends in rural riparian conditions reflect the development of riparian forest science? What motivates residential riparian management actions? Using high-resolution orthoimagery, we quantified riparian conditions and trends between 1998 and 2015 in the rural upper Little Tennessee River basin in Macon County, North Carolina and explored how landowners view riparian zone management and riparian restoration programs. Buffer composition in 2015 was as follows: no buffer (32.5%), narrow (19.3%), forested (26.7%), shrub (7.2%), and intermediate (7.0%). Relative to 1998, the greatest decrease occurred in the no buffer class (−17.7%, 46 km) and the largest increases occurred in the shrub (+72.5%, 20 km) and narrow (12.6%, 14 km) classes. Forested buffer marginally increased. Semi-structured interview data suggest that landowners prioritize recreational and scenic aspects of riparian buffers over ecological functions such as filtration and bank stabilization. Riparian restoration programs might be made more enticing to non-adopters if outreach language appealed to landowner priorities, design elements demonstrated intentional management, and program managers highlighted areas where ecological goals and landowner values align.     

Five-wheel framework for system-based monitoring of heavy metal pollution in rivers

Sectorial approach for monitoring heavy metal pollution in rivers has failed to report realistic pollution status and associated ecological and human health risks. The increasing spread of heavy metals from different sources and emerging risks to human and environmental health call for reexamining heavy metal pollution monitoring frameworks. Also, the sources, spread, and load of heavy metals in the environment have changed significantly over time, requiring consequent modification in the monitoring frameworks. Therefore, studies on heavy metal monitoring in rivers conducted in the last decade were evaluated for experimental designs, research frameworks, and data presentations. Most studies (∼99%) (i) lacked inclusiveness of all environmental compartments; (ii) focused on “one pollutant – one/two compartment” or sometimes “one pollutant – one compartment – one effect” approach; and (iii) remained “data-rich but information poor.” An ecological approach with integrative system thinking is proposed to develop a holistic approach for monitoring river pollution. It is visualized that heavy metal monitoring, risk analyses, and water management must incorporate tracking pollutants in different environmental compartments of a river (water, sediment, and floodplain/bank soil) and consider correlating it with riverbank land use. The systems-based pollution monitoring and assessment studies will reveal the critical factors that drive heavy metals pollutant movement in ecosystems and associated potential risks to the environment, wildlife, and humans. Also, water quality and pollution indexing tools would help better communicate complex pollution data and associated risks among all stakeholders. Therefore, integrating systems approaches in scientific- and policy-based tools would help sustainably manage the health of rivers, wildlife, and humans.     

Experimental investigation on the effect of liquid phase and vapor phase separation over performance of falling film evaporator

Energy, cost, and environmental concerns play a vital role in understanding governing parameters of distributor design in falling film evaporators. Distributor design is a hidden parameter in many experimental papers. The uniform distribution of liquid refrigerant over the tube bundle mostly depends on two-phase liquid refrigerant and vapor refrigerant. This work conducted experiments with two distribution systems with and without separation of liquid-vapor refrigerant after expansion valve for the same evaporator capacity with R134a as a refrigerant. Results reveal that; separating vapor refrigerant has a positive impact on the approach of the evaporator with an open system distributor arrangement. The highest delta T and lowest practice are found at a heat flux of 13.97 kW/m² with an available system distributor compared to a closed system with a heat flux of 14.25 kW/m². The open system arrangement in the distributor is the novel parameter for distributor design, ensuring uniform distribution with minimum pressure drop and dry suction. An open system distributor has an average 16.1% capacity increase over a closed system. The experimental analysis helps to understand different parameters for the design of distributors in falling film evaporators for uniform distribution.     

基于火探管式的锂离子电池灭火技术研究

为研究锂离子电池灭火方案,基于火探管灭火技术同时利用新型清洁灭火剂Novec 1230,组装成火探管灭火系统。在灭火测试平台上以功率为200 W的电热管作为外热源引发单电池或电池模组热失控,通过改变火探管的布置位置,记录相应的灭火行为以及灭火效率,并对实验结果进行了分析。研究结果表明,当火探管灭火系统直接布置在电池正上方时,在起火后的5.6s内控制火情;随着灭火剂用量增加可以显著降低体系温度,防止电池复燃以及连锁热失控现象发生;火探管有效覆盖区域外的失控电池作为热源将继续加热临近电池,引发连锁热失控,造成灭火系统失效;根据电池热失控后的燃烧行为以及传热行为,提出相应的火探管灭火系统复合方案。     

基于微型无人机遥感数据的城市水环境信息提取初探

近年来,黑臭水体整治已经成为各级政府的重要工作内容。为更好地开展黑臭水体筛查和监管工作,提出基于多旋翼无人机搭载多光谱相机的遥感监测方案,尝试采用影像特征变换结合面向对象分类方法提取黑臭水体的遥感信息。结果表明:(1)无人机影像上地物具有更加丰富的色彩和纹理;(2)与主成分变换和纹理分析方法相比,光谱指数对典型地物具有较好的判别能力;(3)采用标准最邻近分类法提取城市水环境信息,能够获得较高分类精度。     

基于变权灰色云模型的江苏省水环境系统脆弱性评价

水环境系统脆弱性是水资源利用与生态环境研究的热点问题，通过研究水环境系统的内在机理，综合考虑影响水环境系统脆弱性的资源、环境、经济、社会等因素，借助驱动力-压力-状态-影响-响应-管理（DPSIRM）框架构建水环境系统脆弱性评价指标体系。在此基础上，构建基于变权灰色云模型的评价方法，对2004~2014年江苏省水环境系统脆弱性进行评价。结果表明：2004~2014年水环境系统脆弱性指数由47.056提高到63.210，脆弱性等级由“重度脆弱”演化为“中度脆弱”，并长期维持在“中度脆弱的”等级，2014年出现了向“轻度脆弱”状态转变的趋势。分析各个子系统对水环境系统脆弱性影响程度可知，影响子系统和响应子系统对江苏省水环境脆弱性系统的影响程度逐年增加；而压力子系统和管理子系统对水环境系统脆弱性的影响程度逐年下降；其它子系统对水环境系统脆弱性的影响维持在一定水平小幅度波动。     

生活垃圾强制分类形势下的多源废荧光灯管回收管理机制建议

废荧光灯管的来源广泛，包括工业来源和社会来源，社会来源又包括居民来源，企业事业单位、公共场所等机构来源，具有多来源的特性。废荧光灯管中含有汞，若不经过妥善处理，会造成环境污染，对人的身体健康造成危害。随着国内生活垃圾分类的开展，废荧光灯管作为生活垃圾中有害垃圾的典型类别被强制分类，但仍存在很多问题。本文梳理了我国废荧光灯管的产生情况、LED灯替代情况，并对美国、欧盟、日本和我国国内典型城市的废荧光管理情况进行了总结。针对我国废荧光灯管的回收现状，从责任主体、责任划分、收集渠道、资金机制等角度提出了相关的管理建议，为推动我国废荧光灯管的管理提供借鉴。     

“竞争申请制”:可持续发展政策试点与央地关系重构

可持续发展目标(SDGs)的提出,开启了人类可持续发展领域最宏大的政策实验,也为开展国际视野的比较公共政策研究提供了难得机遇。执行SDGs及国家可持续发展政策需要处理好中央政府与地方政府间关系,而政策试点是协调这一关系的重要政策工具。已有文献对经济政策试点做了较充分的研究,然而对旨在实现经济、社会与环境协调的可持续发展政策试点,现有研究尚缺乏成型理论。在复杂央地关系格局下,对于需持续投入成本且成果难以界定的可持续发展政策试点,其具有怎样的不同于经济政策试点的机制?此外,众多西方学者将美国作为政策试点研究的制度基础并视其为“民主实验室”。然而,政策试点在以中国为代表的不同体制国家中同样存在,并以多样的机制发挥作用。那么,不同国家体制内的可持续发展政策试点又有哪些异同?政策试点影响下中国既有的央地关系发生了怎样的重构?对此,本文基于最典型案例原则,选取中国与美国响应SDGs分别开展的政策试点进行比较研究。笔者识别了不同体制下试点机制的异同,指出中国基于“竞争申请制”开展的可持续发展政策试点强化了中央部委与地方政府间关系,形成了地方官员的可持续发展激励,保障了政策试点的实施。