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.     

Understanding and addressing the environmental risk of microplastics

Over the past decades, the plastic production has been dramatically increased. Indeed, a category of small plastic particles mainly with the shapes of fragments, fibers, or spheres, called microplastics (particles smaller than 5 mm) and nanoplastics (particles smaller than 1 μm) have attracted particular attention. Because of its wide distribution in the environment and potential adverse effects to animal and human, microplastic pollution has been reported as a serious environment problem receiving increased attention in recent years. As one of the commonly detected emerging contaminants in the environment, recent evidence indicates that the concentration of microplastics show an increasing trend, for the reason that up to 12.7 million metric tons of plastic litter is released into aquatic environment from land-based sources each year. Furthermore, microplastic exposure levels of model organisms in laboratory studies are usually several orders of magnitude higher than those found in environment, and the microplastics exposure conditions are also different with those observed in the environment. Additionally, the detection of microplastics in feces indicates that they can be excreted out of the bodies of animal and human. Hence, great uncertainties might exist in microplastics exposure and health risk assessment based on current studies, which might be exaggerated. Policies reduce microplastic emission sources and hence minimize their environmental risks are determined. To promote the above policies, we must first overcome the technical obstacles of detecting microplastics in various samples.     

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。     

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。     

What happened to the Second World? Earthquakes and postsocialism in Kazakhstan

There is an assumption that with the disintegration of the Soviet Union, the Second World ceased to exist. Yet the demise of the Communist bloc as a geopolitical reality did not mean that it stopped exerting a defining influence over how people think and behave. This article examines how the postsocialist state in Kazakhstan deals with potential crises such as earthquakes and the extent to which the Soviet legacy still shapes intellectual debates, state structures, and civil society organisations in in that country. Drawing on fieldwork and interviews, this paper re-examines the Second World in its historical context and re-establishes it as a conceptual framework for considering disaster risk reduction in the former Soviet bloc. It argues that it is essential to pay attention to this legacy in Kazakhstan both in policy and practice if earthquake risk reduction is to be made more effective.     

西南山地区域森林火险综合预报模型研究——以重庆市为例

森林火灾严重破坏森林生态系统的结构和功能,针对其风险预报开展研究具有重要的理论意义和应用价值。通过融合气象、地表覆盖和人类活动等要素的方式构建森林火险综合预报模型,是西南山地区域森林火险综合预报业务化应用的重要发展方向。基于《森林火险气象等级》国家标准(GB/T 36743-2018),本文研究首先构建了重庆市森林火险气象风险预报模型。然后通过融合可燃物因素和人为因素的方式,进一步构建重庆市森林火险综合预报模型。最后利用历史火点数据针对上述两类模型的精度进行对比和分析。研究结果表明:重庆市森林火灾发生次数较多,且呈现出季节性规律;重庆市森林火灾的发生不仅受到气象条件的影响,而且受到地表覆盖和人类活动等多种要素条件的共同影响;与森林火险气象风险预报结果相比,森林火险综合预报结果在空间分布上具有更高的精细程度;森林火险综合预报模型能有效提高森林火险等级预报精度。