Rethinking assessment of success of mitigation strategies for elephant-induced crop damage

Crop damage is the most common impact of negative interactions between people and elephants and poses a significant threat to rural livelihoods and conservation efforts. Numerous approaches to mitigate and prevent crop damage have been implemented throughout Africa and Asia. Despite the documented high efficacy of many approaches, losses remain common, and in many areas, damage is intensifying. We examined the literature on effectiveness of crop-damage-mitigation strategies and identified key gaps in evaluations. We determined there is a need to better understand existing solutions within affected communities and to extend evaluations of effectiveness beyond measurement of efficacy to include rates of and barriers to adoption. We devised a conceptual framework for evaluating effectiveness that incorporates the need for increased emphasis on adoption and can be used to inform the design of future crop-damage mitigation assessments for elephants and conflict species more widely. The ability to prevent crop loss in practice is affected by both the efficacy of a given approach and rates of uptake among target users. We identified the primary factors that influence uptake as local attitudes, sustainability, and scalability and examined each of these factors in detail. We argue that even moderately efficacious interventions may make significant progress in preventing damage if widely employed and recommend that wherever possible scientists and practitioners engage with communities to build on and strengthen existing solutions and expertise. When new approaches are required, they should align with local attitudes and fit within limitations on labor, financial requirements, and technical capacity.     

Using fuzzy set theory to address the uncertainty of susceptibility to drought

This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4) defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility, in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through the procedures of ‘fuzzification’ and ‘defuzzification’.     

EFFECTS OF ADJACENT AGRICULTURAL ACTIVITIES AND WATERSHED CHARACTERISTICS ON STREAM MACROINVERTEBRATE COMMUNITIES1

Benthic macroinvertebrate communities in streams adjacent to cornfields, streams where cows had unrestricted access, and reference locations without agriculture were compared to examine the effects of local land use and land use/land cover in the watershed. At each local site, macroinvertebrates and a variety of habitat parameters were measured upstream, adjacent, downstream, and farther downstream of the local land use. A geographic information system (GIS) was used to calculate drainage basin area, land use/land cover percentages in each basin, and the distance from sample sites to the stream source. Three‐way analysis of covariance (ANCOVA) tests with date, site type, and sampling location as main effects were used to explore differences in macroinvertebrate metrics using median substrate size, percent hay/pasture area, and stream depth as covariates. The covariates significantly improved model fit and showed that multiple contributing factors influence community composition. Local impacts were greatest at sites where cows had access, probably because of sedimentation and embeddedness in the substrate. Differences between the upstream and the adjacent and downstream locations were not as great as expected, perhaps because upstream recolonization was reduced by agricultural impacts or because of differences in the intensity or proximity of agriculture to riparian areas in the watershed. The results underscore the importance of both local and watershed factors in controlling stream community composition.     

Study on Assessing Economic Vulnerability of Small Island Regions

The main purpose of this study is to assess economic vulnerability of small island development regions as part of their sustainability constraints. By combining economic and environmental time series data, we assessed a composite index of economic vulnerability which is constructed from three exogenous variables, namely economic exposure, economic remoteness, and economic impact of environmental and natural disasters. We used the Amami Islands, Kagoshima Prefecture, Japan as the case studies for this paper.The results indicated that using a gross island products based valuation index, Kikaijima is the most vulnerable island in the Amami Islands with a composite economic vulnerability index (CEVI) value of 0.678, while by using a per capita based index, Okinoerabujima is considered the most vulnerable island with a CEVI value of 0.680. From the results we also revealed that smaller islands have relative higher vulnerability than the bigger one, which also confirms some previous country-level vulnerability studies.However, it is matter of fact that some islands that have relatively high vulnerability also have good economic performance as shown by their per capita income. In this regard, it can be argued that the success of these small islands could have been achieved in spite of and not because of their inherent vulnerability conditions as an indicator of sustainability constraint. Regarding these findings, we also examined a comparison between vulnerability results and the preliminary concept of an island's resilience in order to capture another perspective on sustainability assessment in a small island region.     

基于边介数的省域生态廊道构建方法优化

我国城市建设和生态保护工作均对土地资源有大量需求,二者之间的矛盾在经济优先发展区表现尤为明显.为了有效地改善生态环境,管控土地利用并引导其变化发展,需要建设具备不可替代特征的省域生态廊道.最小累积阻力模型（minimum cumulative resistance,MCR）是识别生态廊道最常用、有效的模型,但在应用于省域尺度时,MCR模型识别的潜在廊道路由存在冗余的问题.因此,通过引入网络科学中的边介数指数（edge-betweenness）对MCR模型进行优化,计算潜在廊道路由的边介数指数值,选取出其中最为重要和简明的结构来连通生态源地,即提取潜在路由中的骨干路由（backbone route）和关键战略点（key strategic point）作为不可替代的结构来指导省域生态廊道建设.将优化后的MCR模型应用于广东省,构建了全长5 493 km的省域生态廊道,其中包含生态源地20处,关键战略点11个,骨干生态廊道29条.骨干路由与关键战略点构成的不可替代省域生态廊道（irreplaceable provincial corridor）能够实现"廊道数量和占地面积最少、连通性基本不变"的目标.研究显示,边介数能够对潜在路由进行优化筛选,识别出维护省域生态安全的关键结构;不可替代生态廊道能够指导省域生态规划和土地空间的发展利用,并为更高水平的生态安全环境提供了演进的基础;同时也为土地资源紧张的地区提供了建设生态廊道的参考与依据.      

不同区域城市空气O3和PM2.5累积速率时序模型

利用2017—2018年全国7个区域10个典型城市环境空气O₃和PM_2.5浓度数据，统计污染物累积速率，进而采用回归方法拟合污染物浓度及其累积速率的时间序列模型，分析不同区域污染物时序变化特征差异。结果表明：不同区域O₃浓度时序曲线拟合程度总体高于PM_2.5，石家庄O₃拟合程度最高，西安PM_2.5拟合程度最高。以07：00、14：00分别作为O₃、PM_2.5模拟起点是24 h中的最优模型。不同城市夏季O₃小时浓度时序变化曲线均为单峰形态，O₃浓度及累积速率峰值出现时间可能由城市所处经度决定，太原O₃累积最快，西安O₃消解最快。各城市间冬季PM_2.5小时浓度及其累积速率时序变化曲线形态差异较大，沈阳PM_2.5累积和消解均最快。与浓度相比，城市环境空气O₃和PM_2.5累积速率与光照、扩散条件等有更好的时间相关性。     

Sharing the geo-Referenced Results of Climate Change Impact Research

The Prairie Adaptation Research Collaborative (PARC) has implemented an Internet Map Server (IMS) at the PARC web site (www.parc.ca) to 1) disseminate the geo-referenced results of PARC sponsored research on climate change impacts and adaptation, and 2) address data, information and knowledge management within the PARC network of researchers and partners. PARC facilitates interdisciplinary research on adaptation to the impacts of climate change in the Canadian Prairie Provinces. The web site is intended as a platform for sharing information and encouraging discussion of climate change impacts and adaptation. The IMS enables scientists and stakeholders to apply simple climate change scenarios to geo-referenced biophysical and social data, and dynamically create maps that display the geographic distribution of potential impacts of climate change. With a limited capacity for spatial analysis, most geo-processing and the climate impact modeling is done offline within a GIS environment. The IMS will serve the output from climate impact models, such that the model results can be customized by the web site user and be most readily applied to the planning and analysis of adaptation strategies.     

Using environmental stressor information to predict the ecological status of Maryland non-tidal streams as measured by biological indicators

In Maryland, U.S., an interim framework has recentlybeen developed for using biologically based thresholds, or `biocriteria', to assess the health of nontidal streams statewide at watershed scales. The evaluation of impairment is based on indices of biological integrity from the Maryland Biological Stream Survey (MBSS). We applied logistic regression to quantify how the biotic integrity of streams at a local scale is affected by cumulative effects resulting from catchment land uses, point sources, and nearby transmission line rights-of-way. Indicators for land use were developed from the remote sensing National Land Cover Data and applied at different scales. We determined that the risk of local impairment in nontidal streams rapidly increases with increased urban land use in the catchment area. The average likelihood of failing biocriteria doubled with every 10% points increment in urban land, thus an increase in urban land use from 0 to 20% quadruples the risk of impairment. For the basins evaluated in this study, catchments with more than 40–50% urban land use had greater than 80% probability of failing biocriteria, on average. Inclusion of rights-of-way and point sources in the model did not significantly improve the fit for this data set, most likely because of their low numbers. The overall results indicate that our predictive modeling approach can help pinpoint stream ecosystems experiencing or vulnerable to degradation.     

Biological complexity confounds the separation of point- and non-point sources of human impact on the natural world

Identifying process from pattern is one of the most vexing tasks inenvironmental monitoring. Given information on the distribution of speciesin a pre-defined area, together with comprehensive data on how environmentalconditions in that area have altered through time, is it possible toidentify the factors controlling the species‘ layout? Here, the practicalsignificance of this quandary is demonstrated using a series ofenvironmentally-degraded coastal lagoons in New South Wales. The TuggerahLakes (33°17′S,151°30′E) have over the last 50 yearsexperienced significant changes in species‘ distributions. Seagrasses,macroalgae, phytoplankton, molluscs, prawns and the jellyfish Catostylus mosaicus have altered in spatial pattern. Two human activitieshave been blamed for these perturbations: (1) agricultural clearance ofnative vegetation from the catchment, with associated input of top-soil andnutrients; (2) the commissioning of a coal-fired power station in 1967, withmassive uptake and recirculation of lake water for cooling purposes. In thispaper, spatial changes in macrophyte distributions over the last 50 yearsare reviewed in an attempt to identify the true source(s) of perturbation.The model adopted assumes that the power station is a point source of impactwhile nutrient inputs from the catchment are a diffuse source of impact;changes in species distributions can hypothetically be related back to thesesources according to whether they are localised or widespread. However,after a comprehensive analysis of available macrophyte data derived frominterviews, aerial photography and line transect methodologyies theconclusion is reached that changes in biogeographical pattern around theTuggerah Lakes cannot be attributed to specific anthropogenic pressures atanything beyond the coarsest of levels. This is considered to be the normfor most coastal management situations where natural background variation(’noise‘) and the complexity of linkages between physical, chemical andbiological components confounds the identification of causal relationships.The practical implications of this conclusion are discussed in the contextof litigation and remedial management design. Emphasis is placed on theneed to adopt an adaptive approach to estuarine management, incorporatingexplicit recognition of the limitations of available data, and to developnew techniques for identifying cause-effect relationships.     

煤中有害元素对环境和人体健康影响的评价参数

煤中有害元素对环境和人体健康影响的较为全面的评价体系一直未建立，环保部门也缺乏系统性评价参数对电厂等在煤煤过程中有害元素排向大气的释放量进行监测估算。本文在查阅大量资料（主要为外文）的基础上，认为评价煤中有害元素对环境和人体健康影响的参数应该包括以下方面的数据C、H、O、N、无机硫，有机硫，有害微量元素的含量，分布规律，赋存状态，迁移转化行为（在燃煤过程中），洁净能力，淋滤力，矿物质，有机化学特征，煤炭学特征，并对煤中有害元素的污染方法进行探讨，如果上述各参数的数据被全面提供，并据此数据作针对性的抑制措施，煤中有害元素对环境和人体健康危害影响必将降低到最小。