A new method for broad-scale modeling and projection of plant assemblages under climatic,biotic, and environmental cofiltering

There is increasing interestin broad-scale analysis, modeling, and prediction of the distribution and composition of plant species assemblages under climatic, environmental, and biotic change, particularly for conservation purposes. We devised a method to reliably predict the impact of climate change on large assemblages of plant communities, while also considering competing biotic and environmental factors. To this purpose, we first used multilabel algorithms in order to convert the task of explaining a large assemblage of plant communities into a classification framework able to capture with high cross-validated accuracy the pattern of species distributions under a composite set of biotic and abiotic factors. We applied our model to a large set of plant communities in the Swiss Alps. Our model explained presences and absences of 175 plant species in 608 plots with >87% cross-validated accuracy, predicted decreases in α, β, and γ diversity by 2040 under both moderate and extreme climate scenarios, and identified likely advantaged and disadvantaged plant species under climate change. Multilabel variable selection revealed the overriding importance of topography, soils, and temperature extremes (rather than averages) in determining the distribution of plant species in the study area and their response to climate change. Our method addressed a number of challenging research problems, such as scaling to large numbers of species, considering species relationships and rarity, and addressing an overwhelming proportion of absences in presence–absence matrices. By handling hundreds to thousands of plants and plots simultaneously over large areas, our method can inform broad-scale conservation of plant species under climate change because it allows species that require urgent conservation action (assisted migration, seed conservation, and ex situ conservation) to be detected and prioritized. Our method also increases the practicality of assisted colonization of plant species by helping to prevent ill-advised introduction of plant species with limited future survival probability.     

乌东德库区消落带土壤水分分布特征

消落带土壤水分是制约植物生长发育的关键因素,对库区消落带生态修复意义重大.本文系统分析了乌东德库区消落带修复试验区土壤含水量分布,探索了土壤水分空间变化和影响因素.结果表明:研究区5月水分含量低于5％,不同试验分区和高程区域土壤水分分布受到微地形、土壤特征、植被类型和植被覆盖度等影响.土壤水分随深度变化的主控因素包括地...     

2,4,6-三氯酚在模型水生生态系统中的归宿

测定了模型水生生态系统水、底泥中2.4,6-三氯酚(TCP)浓度随时间的变化值,以及TCP从水中挥发、光解、底泥吸附、解吸、微生物降解的速率常数.假设水中TCP的迁移和转化遵循—级速率过程,水中物质平衡能通过数学等式来描述,显示出室系统教学模型能粗略预测模型水生生态系统中TCP浓度随时间的变化.最后,应用该模型预测了排放到天津室外兼性塘中TCP的迁移、归宿,发现15d后出口水中TCP浓度已降低到入口水中浓度的10%     

同位素示踪法研究有机污染物在模拟水生生态系统中的行为

应用同位素示踪技术，研究了模拟水生生态系统中三氯苯、邻苯二甲酸正丁酯，２，４，６－三氯酚－＾１４Ｃ的分布、迁移、转化行为。实验周期后，水中污染物浓度分别降低了８９％，８０％，９５％以上，三氯苯在底泥和浮游生物中有积累。测定了标记物在水、悬浮物、＾１４ＣＯ２吸收溶液，ＸＡＤ－２树脂上的放射性强度。假设水中标记物的降解遵循一级速率过程，２４ｄ后，水中２，４，６－三氯酚－＾１４Ｃ浓度已降为原来浓度的５％     

Occurrence and distribution of antibiotic resistance genes in the sediments of the East China Sea bays

The coastal area of the East China Sea has experienced rapid urbanization and industrialization in China since 1980 s, resulting in severe pollution of its environments.Antibiotic resistance genes(ARGs) are regarded as a kind of emerging pollutant with potential high risk. The sediment samples were collected from Hangzhou Bay(HB),Xiangshan Bay(XB), and Taizhou Bay(TB) to investigate the spatial occurrence and distribution of 27 ARGs and class I integron–integrase gene(intI1) in the coastal area of the East China Sea. The PCR results showed the frequent presence of 11 ARGs and intI1 in the sediments of the three bays. The qPCR results further showed that sulfonamide resistance was the most prevalent ARG type and antibiotic target replacement and protection were the most important resistance mechanisms in the sediments. Regarding the subtype of ARGs, sulI, tetW, and dfrA13 were the most abundant ARGs, in which sulI was higher in TB(based on both the absolute and relative abundances) and dfrA13 was higher in HB(based on the relative abundances). The network analysis revealed that intI1 had significant correlations with tetC, sulI, sulII, and blaPSE-1. Oil was the key connected factor, which had positive connections with sulI, sulII, and blaPSE-1. In addition, the joint effect of heavy metals and nutrients organic pollutants might be crucial for the fate of ARGs in the coastal sediments.     

垃圾填埋场PBFC防渗浆材吸附性能试验研究∗

以水泥-膨润土为主要材料,以粉煤灰替代部分水泥,辅以碳酸钠,聚乙烯醇(PVA)等外掺剂制备一种低渗透性,对垃圾渗滤液具有较好吸附阻滞效果的防渗浆材(即PBFC防渗浆材)。通过该浆材的吸附阻滞试验及SEM微观分析探讨了其吸附阻滞作用机理。SEM图显示,掺入PVA可使水泥水化反应更充分,从而提高浆材吸附性能。PBFC防渗浆材的PVA掺量为1.5 g/L时,其渗透系数最低可达到0.7×10-8cm/s。通过PBFC防渗浆材吸附阻滞作用的有效发挥,垃圾场渗滤液中部分有害成分的浓度达到了《城市生活垃圾填埋场污染控制标准》的要求,且PVA掺量为1.5 g/L时,渗滤液有害成分的浓度值降到最低,这与PVA对防渗浆材渗透系数的影响是一致的。PBFC防渗浆材对铅、汞等重金属离子的吸附阻滞率接近100%,满足生活垃圾填埋场的使用要求。     

两室堆肥生物反应装置研究

以堆肥过程中物料平衡、热量平衡以及垃圾生物发酵特性为依据,设计了二室堆肥生物反应装置,并通过堆肥试验实际检验反应装置设计的合理性.装置主要结构包括:二室堆肥发酵仓、保温层、通风供氧系统、空气加热系统以及二次污染控制系统.装置的主要特点为:两发酵仓能够独立完成堆肥发酵,也可以实现堆肥一次、二次发酵串联工艺组合;通过二次污染控制系统,可以很好地减少堆肥过程中产生的废水臭气排放;采用空气加热系统,可以快速均匀地加热堆体,以满足不同堆肥工艺的需要.装置在试验研究以及小规模垃圾堆肥处理领域有一定的应用价值.     

基于混合生命周期方法的私人电动汽车温室气体排放研究

近年来,电动汽车因其在行驶过程中无任何尾气排放,被各国政府视为推动交通部门清洁、低碳发展的重要途径,主要发达国家纷纷推出了各自的电动汽车发展战略。但是,由于电力属于二次能源,其上游电力生产阶段的能源消费是否清洁将对电动汽车的减排效果产生重要影响。考虑到目前中国绝大部分电力源于煤炭,电动汽车是否真正有益于减排还有待进一步验证。目前一些专家和学者基于传统的过程生命周期评价方法对电动汽车的能源消费、温室气体排放做了一些研究,但研究结果差异较大。为了对电动汽车的减排效果进行更精确的研究,本文采用混合生命周期方法对电动汽车的能源消费、温室气体排放进行了计算。同时,在考虑电动汽车的燃料生命周期、车辆制造生命周期的基础上,将相关配套充电设施建设生命周期纳入到电动汽车的全生命周期系统边界内,以使对电动汽车全生命周期的研究结果更加完整、精确。研究结果显示,纯电动汽车并非是"零排放"的,在燃料周期,虽然纯电动汽车的单位里程能源消费强度较小,约为传统汽油车的94.6%,但以煤为主的高碳电力结构导致目前纯电动汽车燃料周期的单位里程温室气体排放强度约为传统汽油车的1.12倍;车辆周期内,纯电动汽车的能源消费和温室气体排放量也略高于传统汽油车;此外,配套充电设施的建设也将增加纯电动汽车全生命周期的能源消费和温室气体排放量。综合燃料、车辆及充电设备的全生命周期,在当前的电源结构及技术条件下,电动汽车虽然具有较高的能源效率和较好的石油替代效果,但其全生命周期内的煤炭消费较高,导致其温室气体排放量高于传统汽油车,在当前的情况下大规模发展电动汽车并不利于温室气体减排。     

区域差异下农业用水效率对农业用水量的影响

基于全国30个省份1998~2015年面板数据,采用Super-SBM模型测算农业用水效率,并在观察农业用水量、农业用水效率动静态演进特征的基础上,利用门槛面板回归模型探究农业用水效率对农业用水量的影响。结果表明,全国农业用水量和农业用水效率均呈阶段性下降。农业用水效率对降低农业用水量具有显著的门槛效应,提高农业用水效率是降低农业用水量的有效途径;东部农业用水效率促进农业用水量下降,但须警惕回弹效应;中部农业用水效率抑制农业用水量增长,且作用逐渐增强;西部农业用水效率提高能够快速降低农业用水量,但作用逐渐减弱。另外,提升农民受教育水平、增加绿水足迹、扩大农业劳动人口能够降低农业用水量,而丰富的水资源禀赋促进农业用水量增加。     

安徽省农产品主产区生态承载力与产业协同发展分析及优化路径

以农产品主产区安徽省为例,基于耦合协调度模型和剪刀差模型,利用熵权法确定综合权重,测算出2007~2018年安徽省农产品主产区生态承载力与产业协同发展的耦合协调度和两系统变化速率差异。结果表明：研究期间两系统处于低水平基本协同发展状态,耦合协调度在\[0.570 3,0.797\]波动,总体呈现上升趋势,2007~2010年度,处于经济滞后型基本协同发展,2011~2018年,属于生态滞后型基本协同发展;两系统变化速率差异稳定在\[0.021 9,0.037 3\],呈现倒U型趋势。讨论分析后提出优化农产品主产区空间总体布局、产业发展、融合发展、绿色转型等发展路径,推动农产品主产区生态承载力与产业协同发展。