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.     

Geography and Recovery under the U.S. Endangered Species Act

Abstract: The U.S. Endangered Species Act (ESA) defines an endangered species as one “at risk of extinction throughout all or a significant portion of its range.” The prevailing interpretation of this phrase, which focuses exclusively on the overall viability of listed species without regard to their geographic distribution, has led to development of listing and recovery criteria with fundamental conceptual, legal, and practical shortcomings. The ESA's concept of endangerment is broader than the biological concept of extinction risk in that the “esthetic, ecological, educational, historical, recreational, and scientific” values provided by species are not necessarily furthered by a species mere existence, but rather by a species presence across much of its former range. The concept of “significant portion of range” thus implies an additional geographic component to recovery that may enhance viability, but also offers independent benefits that Congress intended the act to achieve. Although the ESA differs from other major endangered‐species protection laws because it acknowledges the distinct contribution of geography to recovery, it resembles the “representation, resiliency, and redundancy” conservation‐planning framework commonly referenced in recovery plans. To address representation, listing and recovery standards should consider not only what proportion of its former range a species inhabits, but the types of habitats a species occupies and the ecological role it plays there. Recovery planning for formerly widely distributed species (e.g., the gray wolf [Canis lupus]) exemplifies how the geographic component implicit in the ESA's definition of endangerment should be considered in determining recovery goals through identification of ecologically significant types or niche variation within the extent of listed species, subspecies, or “distinct population segments.” By linking listing and recovery standards to niche and ecosystem concepts, the concept of ecologically significant type offers a scientific framework that promotes more coherent dialogue concerning the societal decisions surrounding recovery of endangered species.     

不同扰动下外源磷在形态磷间的分布规律

研究了3种扰动方式对外源磷在上覆水、间隙水、底泥中的数量分布的影响,并分析了内源磷形态间的转化过程.结果表明,与对照实验相比,物理扰动能促进上覆水中磷向底泥迁移,并高于生物扰动和组合扰动的促进作用,并且,三者均高于对照实验.这可归因于溶解氧的渗入.物理扰动能降低间隙水中DIP的平均含量,相比对照实验降低了12.13%(第6 d和第10 d平均值),但降低程度不如生物扰动(38.63%)和组合扰动(50.79%).3种扰动均能促进Fe/Al-P和Ca-P的形成,其中,物理扰动下Fe/Al-P和Ca-P平均形成量最大,物理扰动下AAP含量一直在减小,暗示物理扰动明显促进了AAP向闭蓄态的Fe/Al-P或者Ca-P转化.     

天津冬季一次重污染过程颗粒物中水溶性离子粒径分布特征

为研究天津冬季重污染天气过程中颗粒物水溶性离子的粒径谱分布及二次离子生成机制,于2014年1月利用Anderson撞击式分级采样器在中国气象局天津大气边界层观测站内采集颗粒物样品,并使用离子色谱仪分析Na~+、NH_4~+、K~+、Mg~(2+)、Ca~(2+)、Cl~-、NO_3~-、SO_4~(2-)等8种水溶性无机离子(TWSII).结果表明,采样期间PM_(2.5)和PM_(10)质量浓度均值分别为(138±100)μg·m~(-3)和(227±142)μg·m~(-3),粗、细粒子中TWSII的平均浓度分别为(34.07±6.16)μg·m~(-3)和(104.16±51.76)μg·m~(-3).细粒子中SO_4~(2-)、NO_3~-和NH_4~+这3种离子的浓度远高于其他离子,且相关性较好,粗粒子中NO_3~-、SO_4~(2-)、Cl~-浓度较高.随着污染程度加剧,细粒子中TWSII浓度增加明显,粗粒子中则变化不大.水溶性离子的粒径谱分布显示,SO_4~(2-)以单模态分布,优良天峰值出现在0.43~0.65μm,NO_3~-在优良日呈现三模态分布,峰值分别出现在0.43~0.65、2.1~3.3和5.8~9.0μm,NH_4~+呈双模态分布,优良日峰值出现在0.43~0.65μm和4.7~5.8μm,污染日3种二次离子峰值均以0.65~1.1μm的单模态分布为主,与三者之间的热动力平衡过程有关.细粒子中NH_4~+除与SO_4~(2-)和NO_3~-结合外,还与部分Cl~-结合,粗粒子中NH_4~+全部与NO_3~-和SO_4~(2-)结合后,剩余的NO_3~-和SO_4~(2-)与其他阳离子结合.     

供水管网铁释放的影响因素相对重要性分析

供水管网的铁释放问题近年来日益受到关注.影响供水管网铁释放的因素众多,本研究选取了pH、溶解氧(DO)、碱度(Alk)、硬度、氯离子(Cl~-)、硫酸根(SO_4~(2-))、温度(T)和水力停留时间(HRT)这8个影响因素,利用逐步回归和偏相关分析,建立了铁释放的非线性幂指数模型,并用标准化回归系数和偏相关系数比较了这些因素的相对重要性.结果表明,铁释放模型拟合效果良好;用标准化回归系数衡量影响因素相对重要性时,SO_4~(2-)、HRT、Cl~-和T是相对重要的因素,相对重要性排序为SO_4~(2-)≈HRTCl~-T;用偏相关系数衡量时,HRT、SO_4~(2-)、Alk、Cl~-和T是相对重要的因素,排序为HRTSO_4~(2-)AlkCl~-T.综合两种系数的分析结果,HRT、SO_4~(2-)和Cl~-是本研究条件下相对重要的因素,T和Alk的相对重要性视实际情况变动.     

北京市地下水中典型抗生素分布特征与潜在风险

应用气相色谱与质谱联用仪分析了北京市地下水内磺胺类(SAs)、氟喹诺酮类(FQs)、四环素类(TCs)、β-内酰胺类和大环内酯类等5大类抗生素.结果表明,北京地下水抗生素以SAs、FQs和TCs等3类为主,检出率分别为78.9%、100%和47.3%,其中甲氧苄氨嘧啶(TMP)、环丙沙星(CIP)和诺氟沙星(NOR)检出率均在70%以上.污灌区地下水样点抗生素浓度显著高于水源地和南水回灌区样点,磺胺二甲嘧啶(SDD)和磺胺嘧啶(SDZ)在污灌区检出峰值达到236 ng·L-1和96.8ng·L-1.生态风险评价结果表明,研究区地下水抗生素污染风险较小,但在污灌区显示中等或高等风险等级.CIP应作为研究区地下水抗生素监测中的重点监测对象.     

长江口-浙闽沿岸沉积色素的分布特征及其指示意义

利用高效液相色谱法分析了长江口-浙闽沿岸表层沉积物中的色素组成和含量,探讨了海洋初级生产力、浮游植物功能类群和浮游植物色素保存效率的空间分布特征及其影响因素.结果表明,沉积物中的色素类型主要为沉积绿素(chloropigments,Chlorins)[包括叶绿素a(chlorophyll-a,Chl-a)及其降解产物(pheopigments,Pheo-a),如脱镁叶绿素a(pheophytin-a,PHtin-a)、脱镁叶绿酸a(pheophorbide-a,PHide-a)、焦脱镁叶绿素a(p Pheophytin-a,p PHtin-a)、甾醇绿素酯(sterol chlorin esters,SCEs)和胡萝卜醇绿素酯(carotenol chlorin esters,CCEs)].Chlorins高值区呈南北两大斑块状分布,可能主要是受到长江冲淡水及浙闽沿岸泥质区上升流输运的营养盐的影响.研究区域内类胡萝卜素整体上无明显趋势性变化,在长江口以及浙闽沿岸各呈现一个高值区.基于沉积物中特征类胡萝卜素比例估算得到的浮游植物功能类群中硅藻、甲藻、定鞭藻、青绿藻、隐藻和蓝藻的相对贡献分别为48.8%±17.4%、10.7%±11.5%、8.1%±7.2%、18.6%±8.2%、9.4%±6.4%和4.3%±3.2%.对营养盐水平、水体盐度等外界环境的偏好导致硅藻和甲藻比例离岸降低,青绿藻、隐藻和蓝藻比例离岸增加.Chl-a/Pheo-a比值的分布表明,较高的沉积速率以及季节性的底层水体缺氧事件导致了近岸海域(长江口最大浑浊带外缘、杭州湾湾口以及浙闽沿岸上升流区)具有较高的沉积色素保存效率,这些沉积色素保存效率较高的区域可能是进行海洋生态环境历史重建的理想区域,而杭州湾水体通过舟山群岛与外部海水进行水体交换时造成的较差沉积环境可能是导致杭州湾外海具有较低沉积色素含量和较低保存效率的主要原因.     

山东省临沂市土壤有机氯农药滴滴涕残留量与空间分布特征

通过对临沂市全区表层土壤每36 km2进行样品收集,测试分析了DDTs、Org C、N等指标,主要研究了区域表层土壤DDTs的残留现状、组成和来源、影响因素、空间分布和环境质量特征.结果表明,调查区表层土壤中DDTs检出率为71.75%,平均含量为0.035μg·g-1;检出样品中p,p'-DDT和p,p'-DDE为主要残留物,平均残留分别为0.033μg·g-1和0.010μg·g-1,分别占检出样的60.99%和34.62%.DDTs降解率指示区域58%表层土壤为新近输入区,新近输入区在调查区中南部分布尤为明显;而p,p'-DDD/p,p'-DDE指示区域DDTs降解以氧化环境为主,o,p'-DDT/p,p'-DDT指示71.37%区域土壤DDTs输入可能与工业级DDTs有关.相关分析表明,影响土壤DDTs分布的外在因素包括土壤Org C、N、C和p H等指标,且DDTs中p,p'-DDT组分占比越高,影响越明显.DDTs的空间分布具明显点源特征,市县周围均出现明显浓集中心,中南部部分区域浓度明显较高.全区DDTs土壤环境质量污染程度较低,主要以一二类土壤为主,分别占78.95%和21.05%.     

福建省地级市人为源活性氮排放及其特征分析

在人口增长和快速城市化的背景下,活性氮排放对生态环境的影响日益加剧.为研究省级尺度活性氮排放规律,采用排放因子法建立2000、2005及2010年福建省人为源活性氮排放清单,分析各地市3个年份活性氮排放量及排放强度特征.结果表明,3个年份福建省活性氮排放总量分别为538.4、587.0和619.97 Gg,呈整体增加趋势.在9个地级市中,增速最快的为莆田市,而漳州市排放量有所下降.排放量最大的为漳州和泉州,排放量最小的为宁德与厦门.从排放来源看,90%以上的排放来自农田生态系统和畜禽养殖系统.能源活动贡献较小,但其排放增长最为显著.2010年,各地市单位面积活性氮排放强度呈"东南沿海高西北内陆低"的格局,最高为厦门市,最低为三明市;GDP和人口排放强度则呈"东南沿海低西北内陆高"的格局,最高为南平市,最低为厦门市.在分析各地市活性氮排放源特征的基础上,探讨了不同地区活性氮减排重点,研究结果可为福建省及下辖各地市活性氮减排提供科学依据.     

Metal distribution characteristic of MSWI bottom ash in view of metal recovery

Bottom ash is the major by-product of municipal solid waste incineration(MSWI), and is often reused as an engineering material, such as road-base aggregate. However, some metals(especially aluminum) in bottom ash can react with water and generate gas that could cause expansion and failure of products containing the ash; these metals must be removed before the ash is utilized. The size distribution and the chemical speciation of metals in the bottom ash from two Chinese MSWI plants were examined in this study, and the recovery potential of metals from the ash was evaluated. The metal concentrations in these bottom ashes were lower than that generated in other developed countries. Specifically, the contents of Al,Fe, Cu and Zn were 18.9–29.2, 25.5–32.3, 0.7–1.0 and 1.6–2.5 g/kg, respectively. Moreover,44.9–57.0 wt.% of Al and 55.6–75.4 wt.% of Fe were distributed in bottom ash particles smaller than 5 mm. Similarly, 46.6–79.7 wt.% of Cu and 42.9–74.2 wt.% of Zn were concentrated in particles smaller than 3 mm. The Fe in the bottom ash mainly existed as hematite, and its chemical speciation was considered to limit the recovery efficiency of magnetic separation.