Building robust conservation plans

Systematic conservation planning optimizes trade‐offs between biodiversity conservation and human activities by accounting for socioeconomic costs while aiming to achieve prescribed conservation objectives. However, the most cost‐efficient conservation plan can be very dissimilar to any other plan achieving the set of conservation objectives. This is problematic under conditions of implementation uncertainty (e.g., if all or part of the plan becomes unattainable). We determined through simulations of parallel implementation of conservation plans and habitat loss the conditions under which optimal plans have limited chances of implementation and where implementation attempts would fail to meet objectives. We then devised a new, flexible method for identifying conservation priorities and scheduling conservation actions. This method entails generating a number of alternative plans, calculating the similarity in site composition among all plans, and selecting the plan with the highest density of neighboring plans in similarity space. We compared our method with the classic method that maximizes cost efficiency with synthetic and real data sets. When implementation was uncertain—a common reality—our method provided higher likelihood of achieving conservation targets. We found that χ, a measure of the shortfall in objectives achieved by a conservation plan if the plan could not be implemented entirely, was the main factor determining the relative performance of a flexibility enhanced approach to conservation prioritization. Our findings should help planning authorities prioritize conservation efforts in the face of uncertainty about future condition and availability of sites.     

Optimizing conservation in species-specific agricultural landscapes

Recovery of grassland birds in agricultural landscapes is a global imperative. Agricultural landscapes are complex, and the value of resource patches may vary substantially among species. The spatial extent at which landscape features affect populations (i.e., scale of effect) may also differ among species. There is a need for regional-scale conservation planning that considers landscape-scale and species-specific responses of grassland birds to environmental change. We developed a spatially explicit approach to optimizing grassland conservation in the context of species-specific landscapes and prioritization of species recovery and applied it to a conservation program in Kentucky (USA). We used a hierarchical distance-sampling model with an embedded scale of effect predictor to estimate the relationship between landscape structure and abundance of eastern meadowlarks (Sturnella magna), field sparrows (Spizella pusilla), and northern bobwhites (Colinus virginianus). We used a novel spatially explicit optimization procedure rooted in multi-attribute utility theory to design alternative conservation strategies (e.g., prioritize only northern bobwhite recovery or assign equal weight to each species’ recovery). Eastern meadowlarks and field sparrows were more likely to respond to landscape-scale resource patch adjacencies than landscape-scale patch densities. Northern bobwhite responded to both landscape-scale resource patch adjacencies and densities and responded strongly to increased grassland density. Effects of landscape features on local abundance decreased as distance increased and had negligible influence at 0.8 km for eastern meadowlarks (0.7–1.2 km 95% Bayesian credibility intervals [BCI]), 2.5 km for field sparrows (1.5–5.8 km 95% BCI), and 8.4 km for bobwhite (6.4–26 km 95% BCI). Northern bobwhites were predicted to benefit greatly from future grassland conservation regardless of conservation priorities, but eastern meadowlark and field sparrow were not. Our results suggest similar species can respond differently to broad-scale conservation practices because of species-specific, distance-dependent relationships with landscape structure. Our framework is quantitative, conceptually simple, customizable, and predictive and can be used to optimize conservation in heterogeneous ecosystems while considering landscape-scale processes and explicit prioritization of species recovery.     

微生物除臭剂的筛选、复配及其除臭条件的优化

为了获取作为除臭微生物制剂的候选菌株,从垃圾渗滤液中分离筛选了4株具有对NH3和H2S高效降解菌株,分别标记为CC3、CC7、CC13和CC16.通过形态、生理生化和16S r DNA序列分析,分别鉴定为乳酸片球菌(Pediococcus acidilactici)、巨大芽孢杆菌(Bacillus megaterium)、嗜酸乳杆菌(Lactobacillus acidophilus)、粪产碱杆菌(Alcaligenes faecalis).菌株CC7、CC13和CC16组成的复配组合除臭效率最优,其复配比例为1∶1.5∶0.5,对NH3和H2S的去除率分别为83.56%和70.25%.通过单因素实验,确定微生物除臭剂最佳除臭条件:除臭时间为60 h,菌剂使用量为5%,除臭温度为30℃,初始培养基p H值为6.5.     

水资源规划优化技术研究进展及展望

文章针对水资源管理与规划的发展过程,详细论述了水资源系统管理与规划中常用优化技术的国内外研究成果及应用。根据是否考虑了模型参数或者模型结构的不确定性问题,将优化模型分为确定性优化模型和不确定性优化模型,同时对每种优化技术做了简要介绍,通过对不确定性优化模型的详细介绍指出了不确定性优化是当前水资源系统优化的热点;同时指出当前不确定性优化技术存在的问题,未来不确定性优化技术发展方向为多种不确定性以及多重效益的综合考虑等。     

针对PM2．5的武汉市大气监测点位的布局研究

武汉城市规模的扩大以及市内和周边的产业布局调整使得原有的大气监测网络不能准确反映城市大气污染现状,亟需进行布局优化。研究基于宏观视角,通过对武汉市自然条件、污染源分布和城市的发展规划进行综合分析,认为武汉市的大气污染以本地区的污染源影响为主;由于城市发展的“主城为核,多轴多心”空间结构,每个新城建成区应增设2-4个空气质量评价点,并按照人口比例作为权重纳入空气数据均值的计算;位于主城区的原有监测点基于PM2.5与原有监测项目有比较显著的相关性,可以继续使用。     

“三水优先”的海河流域“十二五”水污染防治战略研究

面对海河流域“十二五”期间突出的饮用水安全保障、城市水环境改善和跨界水协调的污染形势,提出了饮用水、城市水和跨界水为重点的“三水优先”的海河流域水污染防治战略：以“三水”为重点,依托骨干治污工程,创新水污染防治政策,规范重大经济活动,合理调配水资源,严格控制污染物排放,节水优先、增流为本、贴近民生、跨界协调,集中解决一批海河流域突出的水环境问题,努力为海河流域建设全面小康社会提供环境安全保障。     

基于RBF和PSO的双喉道气动矢量喷管优化设计

本文探索了一种能多变量综合优化的方法,即对喷管进行参数化设计后,用均匀试验设计(UED)将试验样本均匀散布在设计区间内,求出各性能参数后,利用径向基神经网络(RBF)对试验样本进行拟合,再用粒子群算法(PSO)对训练好的神经网络进行寻优,找出了更好的双喉道气动矢量喷管设计参数组合。数值模拟结果显示,优化后的双喉道气动矢量喷管的矢量角有了明显提高。试验表明这种优化方法具有很好的优化能力,可以用来对喷管几何外形进行参数优化。      

硫化氢降解菌包埋条件及降解特性研究

筛选获得2株硫化氢(H2S)高效降解菌株(T3和B3),分别鉴定为根瘤杆菌属和人苍白杆菌属。采用改进的海藻酸钠(SA)-聚乙烯醇(PVA)对2株菌的混合液进行包埋,并对最佳包埋条件及包埋后的降解效果进行研究,结果表明:SA-PVA包埋的最佳条件:复合载体的配比为2%SA和7%PVA混合溶液;在1%氯化钙和4%硼酸混合溶液中交联24 h;制得粒径为2 mm左右的固定化凝胶小球;包菌量为0.3 g/L;在pH 5.0¹0.0、温度为2510.0、温度为25⁴0℃时,固定化细胞对H2S具有较高的降解能力和抵抗性,当H2S浓度提高到700 mg/m3以上时,48 h后固定化细胞能达到93%以上的降解率,并且其重复脱硫能力明显优于游离态细胞,为工业应用提供了可能性。     

活性污泥工艺的多目标优化分析

研究了多目标优化方法在活性污泥工艺优化中应用的可行性,以国际水协(IWA)发布的基准仿真模型BSM1的工艺流程为对象,以出水水质、过程能耗和反应池体积的指标为优化目标,以反应池池容(5个)、混合液回流量、污泥回流量、污泥排放量、反应池氧气传质系数(3个)等11个变量为决策变量,构建了基于BSM1的多目标优化模型,并利用MatLab非支配排序遗传算法NSGA-II进行求解,获得了BSM1多目标优化模型的Pareto解.研究结果表明,在Dry进水条件下,通过将体积指标增大4.1%,可以明显改善出水水质指标(降低81.5%),能耗指标也能得到一定改善(降低13.3%);在3种进水条件(Dry,Rain,Storm)下,相对于BSM1工艺参数的缺省值,利用本研究的优化解作为工艺参数,均能不同程度改善出水水质、降低能耗.研究结果显示,在活性污泥过程不同目标之间进行权衡可以通过多目标优化方法来实现.     

均相Fenton法处理干法腈纶废水工艺优化与分析

采用均相Fenton法处理干法腈纶废水,并通过单因素试验和基于中心组合设计的响应面法考察了H2O2投加量、Fe2+投加量、初始pH值及反应时间的影响及其交互作用.同时,建立了以COD去除率为响应值的二次响应曲面模型,并采用方差分析对模型进行了验证.结果表明,影响COD去除效果的各因子显著性顺序依次为:Fe2+投加量>H2O2投加量>初始pH值>反应时间;Fe2+投加量与初始pH值的交互作用最为显著;反应最优组合条件为:H2O2投加量90.0mmol.L-1,Fe2+投加量30.0mmol.L-1、初始pH值3.1,反应时间113.6min,该条件下COD去除率为47.1%,与模型预测值48.5%基本一致.