The need for spatially explicit quantification of benefits in invasive‐species management

Worldwide, invasive species are a leading driver of environmental change across terrestrial, marine, and freshwater environments and cost billions of dollars annually in ecological damages and economic losses. Resources limit invasive‐species control, and planning processes are needed to identify cost‐effective solutions. Thus, studies are increasingly considering spatially variable natural and socioeconomic assets (e.g., species persistence, recreational fishing) when planning the allocation of actions for invasive‐species management. There is a need to improve understanding of how such assets are considered in invasive‐species management. We reviewed over 1600 studies focused on management of invasive species, including flora and fauna. Eighty‐four of these studies were included in our final analysis because they focused on the prioritization of actions for invasive species management. Forty‐five percent (n = 38) of these studies were based on spatial optimization methods, and 35% (n = 13) accounted for spatially variable assets. Across all 84 optimization studies considered, 27% (n = 23) explicitly accounted for spatially variable assets. Based on our findings, we further explored the potential costs and benefits to invasive species management when spatially variable assets are explicitly considered or not. To include spatially variable assets in decision‐making processes that guide invasive‐species management there is a need to quantify environmental responses to invasive species and to enhance understanding of potential impacts of invasive species on different natural or socioeconomic assets. We suggest these gaps could be filled by systematic reviews, quantifying invasive species impacts on native species at different periods, and broadening sources and enhancing sharing of knowledge.     

Minimizing opportunity costs to aquatic connectivity restoration while controlling an invasive species

Controlling invasive species is critical for conservation but can have unintended consequences for native species and divert resources away from other efforts. This dilemma occurs on a grand scale in the North American Great Lakes, where dams and culverts block tributary access to habitat of desirable fish species and are a lynchpin of long‐standing efforts to limit ecological damage inflicted by the invasive, parasitic sea lamprey (Petromyzon marinus). Habitat restoration and sea‐lamprey control create conflicting goals for managing aging infrastructure. We used optimization to minimize opportunity costs of habitat gains for 37 desirable migratory fishes that arose from restricting sea lamprey access (0–25% increase) when selecting barriers for removal under a limited budget (US$1–105 million). Imposing limits on sea lamprey habitat reduced gains in tributary access for desirable species by 15–50% relative to an unconstrained scenario. Additional investment to offset the effect of limiting sea‐lamprey access resulted in high opportunity costs for 30 of 37 species (e.g., an additional US$20–80 million for lake sturgeon [Acipenser fulvescens]) and often required ≥5% increase in sea‐lamprey access to identify barrier‐removal solutions adhering to the budget and limiting access. Narrowly distributed species exhibited the highest opportunity costs but benefited more at less cost when small increases in sea‐lamprey access were allowed. Our results illustrate the value of optimization in limiting opportunity costs when balancing invasion control against restoration benefits for diverse desirable species. Such trade‐off analyses are essential to the restoration of connectivity within fragmented rivers without unleashing invaders.     

Fine‐resolution conservation planning with limited climate‐change information

Climate‐change induced uncertainties in future spatial patterns of conservation‐related outcomes make it difficult to implement standard conservation‐planning paradigms. A recent study translates Markowitz's risk‐diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However, this method is information intensive and requires a large number of forecasts of ecological outcomes associated with possible climate‐change scenarios for carrying out fine‐resolution conservation planning. We developed a technique for iterative, spatial portfolio analysis that can be used to allocate scarce conservation resources across a desired level of subregions in a planning landscape in the absence of a sufficient number of ecological forecasts. We applied our technique to the Prairie Pothole Region in central North America. A lack of sufficient future climate information prevented attainment of the most efficient risk‐return conservation outcomes in the Prairie Pothole Region. The difference in expected conservation returns between conservation planning with limited climate‐change information and full climate‐change information was as large as 30% for the Prairie Pothole Region even when the most efficient iterative approach was used. However, our iterative approach allowed finer resolution portfolio allocation with limited climate‐change forecasts such that the best possible risk‐return combinations were obtained. With our most efficient iterative approach, the expected loss in conservation outcomes owing to limited climate‐change information could be reduced by 17% relative to other iterative approaches.     

Microwave digestion method in environmental analysis

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洱海地面水环境监测优化布点研究

根据１９８７年以后五年洱海水质监测数据的数理统计分析，选择污染指数大的ｐＨ、ＣＯＤ＿（Ｍｎ）、ＢＯＤ＿５、Ｔ－Ｎ、Ｔ－Ｐ进行单项方差分析，进而再进行灰色关联聚类分析和年际相关分析，确知洱海三个水质监测断面可归于一类。考虑水下地形、湖流、环湖工农业布局，水质监测点优化为两个即可保证其准确性、可控性和代表性。     

层次分析法在功能区噪声监测点位优选中的应用

运用层次分析法对功能区噪声进行优选,各功能区噪声监测点位个数分配根据功能区面积和复杂性、各功能区噪声监测点位确定根据专家比例标度赋值进行评定。     

咸淡水地区种植结构优化模型

本文将地下水系统控制与作物种植系统相结合,建立以浅层地下水投入效益为目标,在水土资源等多种约束条件下咸淡水地区种植结构优化模型。该模型被用于确定河北省南皮县几个典型年份(1985,1990,1995,2000)种植结构优化方案。     

优化模型在污泥处理厂选址中的应用

在我国大中城市,污水处理厂的不断兴建使污泥处理问题应运而生。采用混合整数优化模型可以解决污泥处理厂的科学选址问题,达到科学布点、合理运输、节省投资费用的目的。在传统厂群规划模型的基础上将目标规划、周密的约束条件等融于其中,并采用对于线形规划和非线性规划问题适用的LINGO软件进行求解。根据东莞市拟建的36个污水处理厂污泥产生预测情况,对污泥处理厂的设置进行了分析预测,详细对比了建一个、两个、三个污泥处理厂的运输费用、投资费用、运行费用等,最终确定兴建两个规模均为800t/d的处理厂,其位置分别位于东莞市厚街镇和常平镇,为厂址选择和规模提供了科学依据和保障。     

泸州市降水监测布点优化研究

在泸州市2016—2020年大气降水监测数据的基础上,借助聚类分析、多元方差分析等统计分析手段,对原有降水监测点位进行优化研究,并验证优化结果。在遵循《酸沉降监测技术规范》(HJ/T 165—2004)点位布设要求的前提下,建立了降水监测点位评价体系,从原有7个降水监测点位中优化筛选出3个。优化后的点位对监测结果的影响显著性均>0.05,表明优化前后全市降水数据无显著性差异,该优化方案不会影响区域整体代表性。     

危险品泄漏事故后动态路网应急疏散研究

在建立以最短车辆总疏散时间为目标的应急车辆疏散模型过程中,考虑路网上的车流是时变的,以动态交通流分配理论对应急车辆流进行优化分配。基于计算的复杂性和粒子群算法(PSO)的优点,采用PSO对模型进行求解。算例试验结果表明,优化后的方案能够减轻整个疏散车辆的拥堵程度,为应急管理部门决策提供理论支持。