东海赤潮发生时的营养盐分布研究

2010年春季对东海海域进行了赤潮专项调查,在3个海区发现有赤潮发生。对这些海区的水质和浮游植物进行了监测和分析。结果表明,调查中发现的赤潮原因种有东海原甲藻和中肋骨条藻2种;活性磷酸盐和铵盐是发生中肋骨条藻赤潮的重要营养条件,东海原甲藻可以耐受低营养环境,调查海区在较低的温度(17℃)下也能发生东海原甲藻赤潮。     

连云港环境问题及管理建议分析

利用生态红线解决环境问题是落实空间管控要求、实现精细化环境管理的有效手段。本文详细阐述了连云港市生态红线管理工作开展情况,并对生态红线信息化管理成效进行了分析,对其他地区实施生态红线管控有一定的参考意义。     

Habitat as a mediator of mesopredator‐driven mammal extinction

A prevailing view in dryland systems is that mammals are constrained by the scarcity of fertile soils and primary productivity. An alternative view is that predation is a primary driver of mammal assemblages, especially in Australia, where 2 introduced mesopredators—feral cat (Felis catus) and red fox (Vulpes vulpes)—are responsible for severe declines of dryland mammals. We evaluated productivity and predation as drivers of native mammal assemblage structure in dryland Australia. We used new data from 90 sites to examine the divers of extant mammal species richness and reconstructed historic mammal assemblages to determine proportional loss of mammal species across broad habitat types (landform and vegetation communities). Predation was supported as a major driver of extant mammal richness, but its effect was strongly mediated by habitat. Areas that were rugged or had dense grass cover supported more mammal species than the more productive and topographically simple areas. Twelve species in the critical weight range (CWR) (35–5500 g) that is most vulnerable to mesopredator predation were extirpated from the continent's central region, and the severity of loss of species correlated negatively with ruggedness and positively with productivity. Based on previous studies, we expect that habitat mediates predation from red foxes and feral cats because it affects these species’ densities and foraging efficiency. Large areas of rugged terrain provided vital refuge for Australian dryland mammals, and we predict such areas will support the persistence of CWR species in the face of ongoing mammal declines elsewhere in Australia.     

Predicting the conservation status of data‐deficient species

There is little appreciation of the level of extinction risk faced by one‐sixth of the over 65,000 species assessed by the International Union for Conservation of Nature. Determining the status of these data‐deficient (DD) species is essential to developing an accurate picture of global biodiversity and identifying potentially threatened DD species. To address this knowledge gap, we used predictive models incorporating species’ life history, geography, and threat information to predict the conservation status of DD terrestrial mammals. We constructed the models with 7 machine learning (ML) tools trained on species of known status. The resultant models showed very high species classification accuracy (up to 92%) and ability to correctly identify centers of threatened species richness. Applying the best model to DD species, we predicted 313 of 493 DD species (64%) to be at risk of extinction, which increases the estimated proportion of threatened terrestrial mammals from 22% to 27%. Regions predicted to contain large numbers of threatened DD species are already conservation priorities, but species in these areas show considerably higher levels of risk than previously recognized. We conclude that unless directly targeted for monitoring, species classified as DD are likely to go extinct without notice. Taking into account information on DD species may therefore help alleviate data gaps in biodiversity indicators and conserve poorly known biodiversity. Predección del Estado de Conservación de Especies con Deficiencia de Datos     

Framing the relationship between people and nature in the context of European conservation

A key controversy in conservation is the framing of the relationship between people and nature. The extent to which the realms of nature and human culture are viewed as separate (dualistic view) or integrated is often discussed in the social sciences. To explore how this relationship is represented in the practice of conservation in Europe, we considered examples of cultural landscapes, wildlife (red deer, reindeer, horses), and protected area management. We found little support, for a dualistic worldview, where people and nature are regarded as separate in the traditional practice of conservation in Europe. The borders between nature and culture, wild and domestic, public land and private land, and between protected areas and the wider landscape were blurred and dynamic. The institutionalized (in practice and legislation) view is of an interactive mutualistic system in which humans and nature share the whole landscape. However, more dualistic ideals, such as wilderness and rewilding that are challenging established practices are expanding. In the context of modern day Europe, wilderness conservation and rewilding are not valid for the whole landscape, although it is possible to integrate some areas of low‐intervention management into a wider matrix. A precondition for success is to recognize and plan for a plurality of values concerning the most valid approaches to conservation and to plan for this plurality at the landscape scale.     

Effects of roost specialization on extinction risk in bats

Understanding causes and consequences of ecological specialization is of major concern in conservation. Specialist species are particularly vulnerable to human activities. If their food or habitats are depleted or lost, they may not be able to exploit alternative resources, and population losses may result. We examined International Union for Conservation of Nature (IUCN) Red List bat data and the number of roosts used per species (accounting for phylogenetic independence) to determine whether roost specialization is correlated with extinction risk. We found a significant correlation between the IUCN Red List category and the number of roost types used. Species that use fewer roost types had a higher risk of extinction. We found that caves and similar structures were the most widely used roost types, particularly by species under some level of risk of extinction. Many critically endangered, endangered, or vulnerable species used natural roosts exclusively, whereas less threatened species used natural and human‐made roosts. Our results suggest that roost loss, particularly in species that rely on a single roost type, may be linked to extinction risk. Our focus on a single life history trait prevented us from determining how important this variable is for extinction risk relative to other variables, but we have taken a first step toward prioritizing conservation actions. Our results also suggest that roost specialization may exacerbate population declines due to other risk factors, such as hunting pressure or habitat loss, and thus that management actions to preserve species under risk of extinction should prioritize protection of roosting sites.     

2016年京津冀地区红色预警时段PM2.5污染特征与浓度控制效果

2016年12月京津冀地区发生一次重污染过程,北京和天津于12月16日20：00至12月21日24：00,河北省（除张家口、承德和秦皇岛）于12月16日00：00至12月22日18：00发布了重污染红色预警.为研究重污染过程与应急措施的控制效果,基于环境监测数据与模型模拟结果对本次重污染过程的污染物浓度、天气形势与气团输送、区域传输和减排效果进行了研究.本次重污染过程中各地市PM_2.5平均浓度均超过200 μg·m^-3,小时均值峰值为834.5 μg·m^-3.重污染期间气象条件非常不利于污染物扩散,低压控制与气团传输加剧了污染过程.各地市平均本地贡献为47.1%,受天气形势影响传输效果存在一定差异.本次红色预警期间京津冀地区PM_2.5浓度平均下降比例为27.6%,减排效果明显.如果提前实施重污染应急措施,可以使PM_2.5下降浓度有一定提升.提前2 d实施可以使PM_2.5浓度平均下降比例增加4.4%,提前3 d以上效果提升不明显.     

2015～2016年北京市3次空气重污染红色预警PM2.5成因分析及效果评估

北京市空气重污染应急指挥部分别于2015年12月7日18：00、12月18日07：00和2016年12月15日13：00发布了3次空气重污染红色预警.为了厘清3次红色预警的成因差异,评估应急措施在应对空气重污染的有效性,本文基于北京市环境和气象监测数据,分析了红色预警期间PM_2.5浓度、气象条件、天气形势及气团传输.3次预警期间均受污染物二次转化影响,但造成高浓度PM_2.5的原因主要为气象条件影响.第1、第2次预警期间,地面受均压场控制,区域传输分别受西南和南部气团影响,第3次预警地面受大范围低压场控制,受西南传输及局地气团叠加影响.第3次红色预警期间北京市PM_2.5污染最为严重,PM_2.5平均小时浓度最高为273.6 μg·m^-3,是前两次预警的1.2倍和1.3倍.此外,结合各污染源减排量,采用WRF-CMAQ模式对第3次红色预警应急措施效果进行评估,结果表明：应急措施实施后,污染物日平均减排量为678.4 t,PM_2.5质量浓度平均下降了79.1 μg·m^-3,平均下降比例为26.9%.应急措施中增加燃煤源及加大交通源和其他源控制、预警启动时间提前及区域间联防联控有效缓解了PM_2.5浓度加重趋势.     

臭氧微气泡处理酸性大红3R废水特性研究

微气泡技术与臭氧废水处理相结合,有助于促进臭氧气液传质、改善臭氧氧化效果并提高臭氧利用率.本研究采用臭氧微气泡氧化处理酸性大红3R废水,考察了臭氧微气泡的气液传质特性以及对酸性大红3R氧化降解特性,并与臭氧传统气泡进行比较.结果表明,微气泡能够强化臭氧气液传质,相同条件下其臭氧传质系数为传统气泡的3.6倍;同时微气泡系统的臭氧分解系数为传统气泡系统的6.2倍,有利于·OH产生.臭氧微气泡可显著提高酸性大红3R氧化降解速率和矿化效率,其TOC去除率可达78.0%,约为传统气泡的2倍.臭氧微气泡处理酸性大红3R过程中的臭氧利用率显著高于传统气泡:微气泡系统平均臭氧利用率为97.8%;传统气泡系统平均臭氧利用率为69.3%.臭氧微气泡通过促进·OH产生提高臭氧氧化能力,其对降解中间产物的氧化速率更快,其中对小分子有机酸的矿化能力约为传统气泡的1.6倍.     

红色预警期间北京市PM2.5浓度特征及应急措施效果评估

综合利用监测数据并结合数值模型,分析了2015年北京市第2次空气重污染红色预警期间PM_(2.5)浓度变化特征并初步评估了减排措施对PM_(2.5)浓度的影响.结果表明:污染初期北京市南部地区PM_(2.5)浓度明显偏高,且PM_(2.5)极端高值往往出现在北京南部站点.污染输送阶段,北京市PM_(2.5)小时浓度在短时内呈爆发式增长,浓度积累速率可达5~10μg·m~(-3)·h~(-1).污染缓解阶段,偏北风作用,空气质量转好.预警期间北京市空气质量南北差异较大.应急措施实施后,北京市PM_(2.5)环境浓度下降约20%~25%.PM_(2.5)累积速率呈现出交通站城区站背景站的特征,与重污染日平均值相比交通站下降幅度最大,表明减排措施在交通站更加显著.气象条件对重污染的形成和结束起着决定性作用,为了更好的做好空气质量预警预报工作,应加强对小尺度天气系统的研究,同时关注不同方位PM_(2.5)浓度峰值及重污染持续时间的变化,形成北京市分区预报预警的经验.