河流水污染定量研究进展

水质模型可定量地反映出水质状况与污染物排放之间的关系,从而为进行水质评价与预测、选择污染控制方案以及制定水质标准和排放污染规定提供可靠的依据.文章从建立模型所采用的数学方法角度出发,较为详细的概述了近年来水质模拟的研究进展,并对确定性模型所存在的问题和河流水质模型的发展趋势做出评价.     

陆地生态系统净第一性生产力过程模型研究综述

陆地生态系统净第一性生产力的模拟已从统计模型发展到过程模型时代。过程模型从机理上对植物的生物物理过程以及影响因子进行分析和模拟,理论框架完整,结构严谨。论文从植物器官、个体、冠层、景观以及区域等不同尺度对过程模型进行分析。近年来,由于遥感和GIS技术的支持,使得遥感过程模型融合了遥感及时、准确、宏观、多尺度的优势而成为当前生产力模型的主攻方向。遥感过程模型可实现生态系统NPP的及时模拟和动态监测,便捷、准确地反映NPP的时空变化格局。而在NPP建模过程中,尺度转换是所面临的一个重要问题。不同尺度模型间扩展时,需要采取相应的数学手段进行尺度转换,同时遥感和GIS技术提供了尺度转换的有力工具。综观我国NPP研究的发展,起步晚、发展快是其特点。虽然取得了大量的研究成果,但过程模型的建模方面还很不足,这是一个亟待解决的问题。     

我国海洋灾害经济损失评估模型研究

针对目前我国海洋灾害给海洋环境及造成损害的实际情况，运用环境经济学及系统动力学的理论和方法，并在溢油模型及ＧＩＳ的支持下，首次建立了用一系列密切相关的子模块来评估经济损失的数学模型。它对于促进我国海洋灾害经济损失评估的定量化进程将起到一定的作用。     

基于损伤检测的腐蚀疲劳寿命预测概率模型

建立了飞机结构腐蚀疲劳寿命预测的4阶段概率模型,结合腐蚀疲劳损伤检测结果,通过检测的灵敏度和准确度2个随机变量来描述检测技术的可靠性;建立了检测后的修正腐蚀疲劳寿命预测概率模型,通过对比分析修正前后的腐蚀疲劳寿命分布,得出腐蚀损伤尺寸的检测结果。对腐蚀疲劳寿命的评估影响很大,并且检测技术越可靠,寿命评估越准确。     

基于改进遗传算法的河流水污染源反演方法

针对河流水污染应急响应过程中污染源排放历史迟知、未知的问题,结合多种群遗传算法和自适应遗传算法,利用一维河流水质模型和水质监测数据,研究建立了基于改进遗传算法的河流水污染定量源反演方法,实现了对河流污染源排放历史的识别与重构.将该方法应用于美国特拉基河流的3个不同流量下的示踪剂实验中,对示踪剂排放历史进行定量源反演分析.结果表明：IGA算法对高、中、低不同流量下的3次示踪剂实验均可以很好的重构和识别示踪剂排放历史,对于实际河流水污染源反演分析的误差均在可接受范围内.IGA算法在河流水污染源反演分析中具有一定的可靠性和稳定性,可为河流水污染精准溯源与治理提供科学的技术支撑.     

基于模糊物元模型的西苕溪流域生态系统健康评价

本文借助RS/GIS技术,结合遥感影像数据、环境监测数据和社会经济数据,运用模糊物元模型,从水域、水陆交错带和陆域子系统选取21项评价指标,建立了流域生态系统健康综合评价指标体系,对西苕溪流域生态系统健康状况的空间分布规律和限制性因子进行了探讨.研究结果表明,西苕溪流域生态系统健康整体呈现出优良状态,其中,生态系统健康优秀地区面积占68.2%,良好地区面积占31.8%,能够正常发挥流域服务功能,维持生态系统可持续发展.西苕溪流域生态系统健康在空间分布上呈现出上游好、下游差的局面.在各子系统健康评价中,水域生态系统优于陆域生态系统,水陆交错带生态系统最差.底栖动物完整性遭受破坏、湿地退化、人为干扰活动、水源涵养功能减弱、点源和面源污染负荷较重是限制西苕溪流域部分评价单元生态系统健康的重要因素.     

基于非参数核密度估计模型的尾矿库事故后沉积物中Pb和Hg的水生生物风险评估

汞(Hg)和铅(Pb)是2种典型的重金属污染物,对水生生态系统具有较强的毒害作用,是环境管理的重要指标。2015年11月的陇星锑业尾矿库泄露事件,造成嘉陵江流域约346 km长河段受到重金属污染,尾矿砂中高含量Hg和Pb主要归宿在污染团经过的河道沉积物中,引起的嘉陵江流域生态风险尚未被全面评估。为解决沉积物中污染物对水生生物的毒性效应数据较少的问题,采用相平衡分配法,利用大量的水生生物毒理试验数据,将其转化为相应的沉积物毒性效应数据;采用基于非参数核密度估计的物种敏感度分布(SSD)法,对嘉陵江沉积物中2种重金属(Hg和Pb)进行生态风险评价,并与其他分布模型(Normal、Logistic和Weibull)进行对比。结果表明:Hg的非参数核密度估计模型的K-S检验统计量、均方根误差(RMSE)和误差平方和(SSE)分别为0.111 1、0.025 04和0.000 627,相较其他分布模型为最小;Pb的非参数核密度估计模型的K-S检验统计量为0.125 0,相较其他分布模型为最小,RMSE和SSE分别为0.028 42和0.000 807,为较优。非参数核密度估计模型对2种重金属毒性数据有很好的适应性,可获得较优的模拟效果。嘉陵江流域15个采样点沉积物中Pb浓度显著高于Hg,但沉积物中Hg的生态风险水平远高于Pb。     

Using empirical models of species colonization under multiple threatening processes to identify complementary threat‐mitigation strategies

Approaches to prioritize conservation actions are gaining popularity. However, limited empirical evidence exists on which species might benefit most from threat mitigation and on what combination of threats, if mitigated simultaneously, would result in the best outcomes for biodiversity. We devised a way to prioritize threat mitigation at a regional scale with empirical evidence based on predicted changes to population dynamics—information that is lacking in most threat‐management prioritization frameworks that rely on expert elicitation. We used dynamic occupancy models to investigate the effects of multiple threats (tree cover, grazing, and presence of an hyperaggressive competitor, the Noisy Miner (Manorina melanocephala) on bird‐population dynamics in an endangered woodland community in southeastern Australia. The 3 threatening processes had different effects on different species. We used predicted patch‐colonization probabilities to estimate the benefit to each species of removing one or more threats. We then determined the complementary set of threat‐mitigation strategies that maximized colonization of all species while ensuring that redundant actions with little benefit were avoided. The single action that resulted in the highest colonization was increasing tree cover, which increased patch colonization by 5% and 11% on average across all species and for declining species, respectively. Combining Noisy Miner control with increasing tree cover increased species colonization by 10% and 19% on average for all species and for declining species respectively, and was a higher priority than changing grazing regimes. Guidance for prioritizing threat mitigation is critical in the face of cumulative threatening processes. By incorporating population dynamics in prioritization of threat management, our approach helps ensure funding is not wasted on ineffective management programs that target the wrong threats or species.     

The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.     

我国城镇化进程中碳排放影响因素的实证研究

利用1980—2013年间的城镇人口与碳排放数据,选取城镇化进程中影响碳排放的城镇化水平、城镇建设用地面积、第三产业增加值、人均可支配收入、城镇人均绿化面积等因素,实证分析了城镇化对我国碳排放的影响程度,并利用格兰杰夫因果关系与误差修正模型分析了二者的因果关系与时间效应。最后,从降低工业碳排放、加快低碳城镇化试点建设、推进低碳社区发展,促进新能源发展等方面提出了相关建议。