北京市地热资源开发的时空变化

简要介绍了北京地热资源特点,分析了北京地热资源开发的时空演变规律.在搜集资料和实地调查的基础上,绘制出了北京城区地热井分布示意图,并针对其开发利用中可能出现的问题提出了对策.     

Trait‐based prediction of extinction risk of small‐bodied freshwater fishes

Small body size is generally correlated with r‐selected life‐history traits, including early maturation, short‐generation times, and rapid growth rates, that result in high population turnover and a reduced risk of extinction. Unlike other classes of vertebrates, however, small freshwater fishes appear to have an equal or greater risk of extinction than large fishes. We explored whether particular traits explain the International Union for Conservation of Nature (IUCN) Red List conservation status of small‐bodied freshwater fishes from 4 temperate river basins: Murray‐Darling, Australia; Danube, Europe; Mississippi‐Missouri, North America; and the Rio Grande, North America. Twenty‐three ecological and life‐history traits were collated for all 171 freshwater fishes of ≤120 mm total length. We used generalized linear mixed‐effects models to assess which combination of the 23 traits best explained whether a species was threatened or not threatened. We used the best models to predict the probability of 29 unclassified species being listed as threatened. With and without controlling for phylogeny at the family level, small body size—among small‐bodied species—was the most influential trait correlated with threatened species listings. The k‐folds cross‐validation demonstrated that body size and a random effect structure that included family predicted the threat status with an accuracy of 78% (SE 0.5). We identified 10 species likely to be threatened that are not listed as such on the IUCN Red List. Small body size is not a trait that provides universal resistance to extinction, particularly for vertebrates inhabiting environments affected by extreme habitat loss and fragmentation. We hypothesize that this is because small‐bodied species have smaller home ranges, lower dispersal capabilities, and heightened ecological specialization relative to larger vertebrates. Trait data and further model development are needed to predict the IUCN conservation status of the over 11,000 unclassified freshwater fishes, especially those under threat from proposed dam construction in the world's most biodiverse river basins.     

Spatial Patterns of Breeding Success of Grizzly Bears Derived from Hierarchical Multistate Models

Conservation programs often manage populations indirectly through the landscapes in which they live. Empirically, linking reproductive success with landscape structure and anthropogenic change is a first step in understanding and managing the spatial mechanisms that affect reproduction, but this link is not sufficiently informed by data. Hierarchical multistate occupancy models can forge these links by estimating spatial patterns of reproductive success across landscapes. To illustrate, we surveyed the occurrence of grizzly bears (Ursus arctos) in the Canadian Rocky Mountains Alberta, Canada. We deployed camera traps for 6 weeks at 54 surveys sites in different types of land cover. We used hierarchical multistate occupancy models to estimate probability of detection, grizzly bear occupancy, and probability of reproductive success at each site. Grizzly bear occupancy varied among cover types and was greater in herbaceous alpine ecotones than in low‐elevation wetlands or mid‐elevation conifer forests. The conditional probability of reproductive success given grizzly bear occupancy was 30% (SE = 0.14). Grizzly bears with cubs had a higher probability of detection than grizzly bears without cubs, but sites were correctly classified as being occupied by breeding females 49% of the time based on raw data and thus would have been underestimated by half. Repeated surveys and multistate modeling reduced the probability of misclassifying sites occupied by breeders as unoccupied to <2%. The probability of breeding grizzly bear occupancy varied across the landscape. Those patches with highest probabilities of breeding occupancy—herbaceous alpine ecotones—were small and highly dispersed and are projected to shrink as treelines advance due to climate warming. Understanding spatial correlates in breeding distribution is a key requirement for species conservation in the face of climate change and can help identify priorities for landscape management and protection. Patrones Espaciales del Éxito Reproductivo de Osos Pardos, Derivados de Modelos Jerárquicos Multi‐Estado     

Estimating abundance without recaptures of marked pallid sturgeon in the Mississippi River

Abundance estimates are essential for assessing the viability of populations and the risks posed by alternative management actions. An effort to estimate abundance via a repeated mark‐recapture experiment may fail to recapture marked individuals. We devised a method for obtaining lower bounds on abundance in the absence of recaptures for both panmictic and spatially structured populations. The method assumes few enough recaptures were expected to be missed by random chance. The upper Bayesian credible limit on expected recaptures allows probabilistic statements about the minimum number of individuals present in the population. We applied this method to data from a 12‐year survey of pallid sturgeon (Scaphirhynchus albus) in the lower and middle Mississippi River (U.S.A.). None of the 241 individuals marked was recaptured in the survey. After accounting for survival and movement, our model‐averaged estimate of the total abundance of pallid sturgeon ≥3 years old in the study area had a 1%, 5%, or 25% chance of being <4,600, 7,000, or 15,000, respectively. When we assumed fish were distributed in proportion to survey catch per unit effort, the farthest downstream reach in the survey hosted at least 4.5–15 fish per river kilometer (rkm), whereas the remainder of the reaches in the lower and middle Mississippi River hosted at least 2.6–8.5 fish/rkm for all model variations examined. The lower Mississippi River had an average density of pallid sturgeon ≥3 years old of at least 3.0–9.8 fish/rkm. The choice of Bayesian prior was the largest source of uncertainty we considered but did not alter the order of magnitude of lower bounds. Nil‐recapture estimates of abundance are highly uncertain and require careful communication but can deliver insights from experiments that might otherwise be considered a failure.     

Applying network theory to prioritize multispecies habitat networks that are robust to climate and land‐use change

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land‐use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land‐use change projections with the latest developments in network‐connectivity research and spatial, multipurpose conservation prioritization. We used land‐use change simulations to explore robustness of species’ habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land‐use change. The application of connectivity criteria alongside habitat‐quality criteria for protected‐area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade‐offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low.     

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.     

长期施肥下浙江稻田不同颗粒组分有机碳的稳定特征

依托浙江水网地区稻田长期定位施肥试验(1996~2013年),利用固态13C核磁共振波谱技术,研究长期不同施肥措施下土壤各颗粒组分有机碳含量及其化学结构特征.结果表明,与不施肥对照(CK)相比,秸秆与化肥配施(NPKRS)、栏肥与化肥配施(NPKOM)、单施化肥(NPK)和单施栏肥(OM)处理均显著(P0.05)增加了砂粒(2~0.02 mm)、粉粒(0.02~0.002mm)和黏粒(0.002 mm)组分中有机碳含量;而单施秸秆(RS)处理仅显著增加砂粒组分有机碳含量.此外,与单施化肥处理相比,有机肥和化肥配施促进了新增有机碳在粉粒和黏粒组分的分配,更有利于新增有机碳的稳定.应用13C-NMR波谱技术进行结构表征,结果表明粉粒和黏粒组分有机碳的化学结构存在明显差异,粉粒组分烷氧碳、芳香碳的相对含量高于黏粒,而烷基碳、羰基碳的相对含量低于黏粒.长期有机肥与化肥配施下粉粒和黏粒烷基碳相对含量较单施有机肥处理分别降低9.1%~11.9%和13.7%~19.9%,烷氧碳的相对含量则分别增加2.9%~6.3%和13.4%~22.1%,表明有机肥与化肥配施处理降低了粉粒和黏粒组分有机碳的分解程度.长期单施化肥处理下粉粒和黏粒组分有机质的芳化度和疏水性低于单施有机肥处理和不施肥处理,有机质的矿化稳定性较低.长期有机肥与化肥配施,尤其是NPKOM处理,通过增加化学抗性化合物和碳水化合物的积累,并且减缓活性组分的分解提高粉粒和黏粒组分有机碳含量,是促进稻田土壤有机碳可持续积累的有效措施.     

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.     

SBR加载不同粒径磁性活性炭对其污泥颗粒化进程的影响机制

在相同序批式活性污泥反应器(SBR)中分别加载1.5 g·L~(-1)的80、140、200、和300目不同粒径的磁性活性炭(反应器编号依次为2、3、4、5号),同时以不投加磁性活性炭的SBR反应器(1号)作为对照组,研究各反应器污泥体积指数(SVI)、粒径分布特征、胞外聚合物(EPS)中胞外蛋白(PN)、胞外多糖(PS)的含量变化规律以及除污性能.结果表明,不同粒径磁性活性炭对污泥颗粒化进程有一定的影响,粒径过大、过小对促进污泥颗粒化进程的强化作用不明显,当磁性活性炭的粒径为140目和200目时,活性污泥很容易以其作为"成核"载体快速形成好氧颗粒污泥,并且形成的颗粒污泥结构紧密,沉降速率快.采用高斯函数分析污泥粒径分布和标准偏差发现,反应器运行的第50 d,3号和4号反应器内污泥平均粒径均达到了780μm以上,明显高于其他反应器,标准偏差分别为318.9μm和362.3μm,两反应器内形成的颗粒污泥粒径较均匀,处理系统较稳定.与此同时,投加不同粒径的磁性活性炭均有利于促进污泥胞外蛋白质PN含量的增加,对胞外多糖PS的含量影响不大;但合适的磁性活性炭粒径(140目和200目)越有利于污泥PN的分泌,颗粒化程度明显的3号和4号反应器的PN/PS比值均高于其他3个反应器.磁性炭基好氧颗粒污泥的形成符合"惰性内核模型".此外,3号、4号反应器对废水TN和TP的去除率分别达到50%和60%以上,均高于其他反应器.