Fishing‐gear restrictions and biomass gains for coral reef fishes in marine protected areas

Considerable empirical evidence supports recovery of reef fish populations with fishery closures. In countries where full exclusion of people from fishing may be perceived as inequitable, fishing‐gear restrictions on nonselective and destructive gears may offer socially relevant management alternatives to build recovery of fish biomass. Even so, few researchers have statistically compared the responses of tropical reef fisheries to alternative management strategies. We tested for the effects of fishery closures and fishing gear restrictions on tropical reef fish biomass at the community and family level. We conducted 1,396 underwater surveys at 617 unique sites across a spatial hierarchy within 22 global marine ecoregions that represented 5 realms. We compared total biomass across local fish assemblages and among 20 families of reef fishes inside marine protected areas (MPAs) with different fishing restrictions: no‐take, hook‐and‐line fishing only, several fishing gears allowed, and sites open to all fishing gears. We included a further category representing remote sites, where fishing pressure is low. As expected, full fishery closures, (i.e., no‐take zones) most benefited community‐ and family‐level fish biomass in comparison with restrictions on fishing gears and openly fished sites. Although biomass responses to fishery closures were highly variable across families, some fishery targets (e.g., Carcharhinidae and Lutjanidae) responded positively to multiple restrictions on fishing gears (i.e., where gears other than hook and line were not permitted). Remoteness also positively affected the response of community‐level fish biomass and many fish families. Our findings provide strong support for the role of fishing restrictions in building recovery of fish biomass and indicate important interactions among fishing‐gear types that affect biomass of a diverse set of reef fish families.     

Understanding implications of consumer behavior for wildlife farming and sustainable wildlife trade

Unsustainable wildlife trade affects biodiversity and the livelihoods of communities dependent upon those resources. Wildlife farming has been proposed to promote sustainable trade, but characterizing markets and understanding consumer behavior remain neglected but essential steps in the design and evaluation of such operations. We used sea turtle trade in the Cayman Islands, where turtles have been farm raised for human consumption for almost 50 years, as a case study to explore consumer preferences toward wild‐sourced (illegal) and farmed (legal) products and potential conservation implications. Combining methods innovatively (including indirect questioning and choice experiments), we conducted a nationwide trade assessment through in‐person interviews from September to December 2014. Households were randomly selected using disproportionate stratified sampling, and responses were weighted based on district population size. We approached 597 individuals, of which 37 (6.2%) refused to participate. Although 30% of households had consumed turtle in the previous 12 months, the purchase and consumption of wild products was rare (e.g., 64–742 resident households consumed wild turtle meat [i.e., 0.3–3.5% of households] but represented a large threat to wild turtles in the area due to their reduced populations). Differences among groups of consumers were marked, as identified through choice experiments, and price and source of product played important roles in their decisions. Despite the long‐term practice of farming turtles, 13.5% of consumers showed a strong preference for wild products, which demonstrates the limitations of wildlife farming as a single tool for sustainable wildlife trade. By using a combination of indirect questioning, choice experiments, and sales data to investigate demand for wildlife products, we obtained insights about consumer behavior that can be used to develop conservation‐demand‐focused initiatives. Lack of data from long‐term social–ecological assessments hinders the evaluation of and learning from wildlife farming. This information is key to understanding under which conditions different interventions (e.g., bans, wildlife farming, social marketing) are likely to succeed.     

水中总氮测定方法存在问题的研究及改进

碱性过硫酸钾消解紫外分光光度法测定水中总氮采用的消解器皿是玻璃比色管,易造成空白偏高、结果偏低等问题。采用双圆柱状的消解杯对水样进行消解。结果表明,消解杯消解水中总氮,线性相关系数均大于0.999,检出限为0.05 mg/L,相对标准偏差小于5%,相对误差为0.88%~1.00%;改进后的消解器皿具有较好的精密度和准确度,能够更加准确测定水中总氮的含量。     

Fire risk reduction through a community‐based risk assessment: reflections from Makola Market,Accra, Ghana

This paper explores the level of vulnerability to the hazard of fire that exists in Makola Market in Accra, Ghana, and assesses how this threat can be reduced through a community‐based risk assessment. It examines the perceptions of both market‐stall occupants and primary stakeholders regarding the hazard of fire, and analyses the availability of local assets (coping strategies) with which to address the challenge. Through an evaluation of past instances of fire, as well as in‐depth key stakeholder interviews, field visits, and observations, the study produces a detailed hazard map of the market. It goes on to recommend that policymakers consider short‐to‐long‐term interventions to reduce the degree of risk. By foregrounding the essence of holistic and integrated planning, the paper calls for the incorporation of disaster mitigation measures in the overall urban planning process and for the strict enforcement of relevant building and fire safety codes by responsible public agencies.     

水环境指示生物筛选及水质评价方法研究

以齐齐哈尔市近30年地表水生物监测数据、理化监测数据为研究依据,提出一套基于指示生物的地表水体评价方法。该方法将地表水体划分为5个级别,并从中筛选出每个级别对应的指示生物,最终建立一套基于指示生物描述水体污染程度的评价体系。该方法以理化指标为基础,筛选多种优势种作为指示生物,对水体进行综合评价。相比单一生物监测评价指标,该评价方法更能反映整个生态系统状况,从而更客观地反映水体真实情况,有望为地表水体污染评价新方法的建立提供参考。     

Developing Effective Decision Support for the Application of “Gentle” Remediation Options: The GREENLAND Project

Gentle remediation options (GRO) are risk management strategies/technologies that result in a net gain (or at least no gross reduction) in soil function as well as risk management. They encompass a number of technologies, including the use of plant (phyto‐), fungi (myco‐), and/or bacteria‐based methods, with or without chemical soil additives or amendments, for reducing contaminant transfer to local receptors by in situ stabilization, or extraction, transformation, or degradation of contaminants. Despite offering strong benefits in terms of risk management, deployment costs, and sustainability for a range of site problems, the application of GRO as practical on‐site remedial solutions is still in its relative infancy, particularly for metal(loid)‐contaminated sites. A key barrier to wider adoption of GRO relates to general uncertainties and lack of stakeholder confidence in (and indeed knowledge of) the feasibility or reliability of GRO as practical risk management solutions. The GREENLAND project has therefore developed a simple and transparent decision support framework for promoting the appropriate use of gentle remediation options and encouraging participation of stakeholders, supplemented by a set of specific design aids for use when GRO appear to be a viable option. The framework is presented as a three phased model or Decision Support Tool (DST), in the form of a Microsoft Excel‐based workbook, designed to inform decision‐making and options appraisal during the selection of remedial approaches for contaminated sites. The DST acts as a simple decision support and stakeholder engagement tool for the application of GRO, providing a context for GRO application (particularly where soft end‐use of remediated land is envisaged), quick reference tables (including an economic cost calculator), and supporting information and technical guidance drawing on practical examples of effective GRO application at trace metal(loid) contaminated sites across Europe. This article introduces the decision support framework. ©2015 Wiley Periodicals, Inc.     

基于Landsat多光谱与PALSAR/PALSAR-2数据的汉江流域森林覆盖变化研究

汉江流域是南水北调中线工程的水源地,森林覆盖对于保障水源地生态安全具有重要作用.为监测汉江流域2007～2017年森林变化情况,以Landsat多光谱数据与ALOS(Advanced Land Observation Satellite)雷达遥感数据为基础,在GooSe Earth Engine平台上对数据进行处理分析,根据区域特点,选取9个特征指数,利用随机森林分类算法,提取2007和2017年森林分布,监测汉江流域森林覆盖变化.结果 表明:结合Landsat多光谱数据与ALOS雷达遥感数据的分类精度最高,2007年森林分类整体精度为98.0％,2017年森林分类整体精度为98.6％,精度明显高于单独使用Landsat多光谱数据或ALOS雷达数据的森林分类结果;2007 ～ 2017年十年间汉江流域森林面积增加了5 653.21 km2;森林呈现增多的区域主要分布在河南省的西峡县、南召县和丹江口水库附近,而森林呈现减少的区域在荆门市、十堰市和汉中市附近区域.     

Monitoring land cover change detection with NOAA-AVHRR and MODIS remotely sensed data in the North and West of Africa from 1982 to 2015

Environmental Science and Pollution Research - Mapping land cover changes (LCC) cover three decades over North and West Africa regions provides critical insights for the climate research that...