Improving invasive species management by integrating priorities and contributions of scientists and decision makers

Managing invasive species is a major challenge for society. In the case of newly established invaders, rapid action is key for a successful management. Here, we develop, describe and recommend a three-step transdisciplinary process (the “butterfly model”) to rapidly initiate action for invasion management. In the framing of a case study, we present results from the first of these steps: assessing priorities and contributions of both scientists and decision makers. Both scientists and decision makers prioritise research on prevention. The available scientific knowledge contributions, however, are publications on impacts rather than prevention of the invasive species. The contribution of scientific knowledge does thus not reflect scientists’ perception of what is essentially needed. We argue that a more objective assessment and transparent communication of not only decision makers’ but also scientists’ priorities is an essential basis for a successful cooperation. Our three-step model can help achieve objectivity via transdisciplinary communication.     

Decision making under uncertainty in case of soil remediation

Decisions on soil remediation are one of the most difficult management issues of municipal and state agencies. The assessment of contamination is uncertain, the costs of remediation are high, and the impacts on the environment are multiple. This paper presents a general, transparent, and consistent method for decision making among the remediation alternatives. Soil washing, phytoremediation, and no remediation are exemplarily considered. Multi-criteria utility functions including (a) the cost of remediation (b) the impact on human health and agricultural productivity, and (c) the economic gain after remediation are constructed using probability density functions representing contamination for all site coordinates. Herewith, the probability of different types of (i) correct decisions such as a hit or a true rejection and (ii) erroneous decisions such as a false alarm or miss are examined. The decision theoretic model is applied to a case study on heavy metal contaminated soil. This case study reveals the non-linear structure of multi-criteria-decision making. The case study shows that the geostatistical uncertainties of the log-normal distributed soil contamination must be taken into account: When uncertainties are not considered and the utilities are assessed according to the estimated value for a spatial unit, only few (N=26) spatial units result where the utility score of the alternative soil washing are higher than the utility score to the no remediation alternative. However, when taking into account geostatistical uncertainties of the log-normal soil distribution this number is about ten times greater (N=237). Furthermore, the use of 'maximizing expected utility' as decision rule is critical in that it may lead to a high probability of misses.     

Definition of Homogeneous Environmental Management Units for the Catalan Coast

Geographical areas constitute the basic implementation locus for integrated coastal zone management strategies and activities. Because the definition of territorial planning objectives may be affected by socioeconomic and environmental characteristics, one of the main steps in the process involves dividing the coast into homogeneous environmental management units (HEMUs). This article presents a general and simple method for regionalizing the landside of a coastal zone into HEMUs and illustrates it through application to the Catalan coast. Socioeconomic and natural (biophysical) subsystems were selected as the most appropriate dimensions of the regionalization process. Dimensions were described using 11 spatial themes, which were managed in a geographic information system environment that proved to be an adequate tool for the purpose. A final coastal zone map of four classes of HEMUs connected to local administrative units was obtained, and because it reflects the current natural and socioeconomic dynamics, it can be considered as an initial step in the planning process for the Catalan coast. Although the proposed method was developed based on the characteristics of the Catalan coast, it is general enough to be adapted and applied to most developed or developing coastal areas.     

TUGAI: An Integrated Simulation Tool for Ecological Assessment of Alternative Water Management Strategies in a Degraded River Delta

The development of ecologically sound water allocation strategies that account for the needs of riverine ecosystems is a pressing issue, especially in semiarid river basins. In the Aral Sea Basin, a search for strategies to mitigate ecological and socioeconomic deterioration has been in process since the early 1990s. The Geographic Information System–based simulation tool TUGAI has been developed to support the policy determination process by providing a simple, problem-oriented method to assess ecological effects of alternative water management strategies for the Amudarya River. It combines a multiobjective water allocation model with simple, spatially explicit statistical and rule-based models of landscape dynamics. Changes in environmental conditions are evaluated by a fuzzy habitat suitability index for Populus euphratica, which is the dominant species of the characteristic riverine Tugai forests. Water management scenarios can be developed by altering spatiotemporal water distribution in the delta area or the amount of water inflow into the delta. Outcomes of scenario analysis are qualitative comparisons of the ecological effects of different options for a time period of up to 28 years. The given approach utilizes different types of knowledge, from quantitative hydrological data to qualitative local expert knowledge. The main purpose of the tool is to integrate the knowledge in a comprehensive way to make it available for discussions on alternative policies in moderated workshops with stakeholders. In this article, the modules of the tool, their integration, and three hypothetical scenarios are presented. Based on the experience gained when developing the TUGAI tool, we propose that the general framework can be transferred to other areas where tradeoffs in water allocation between the environment and other water users are of major concern. The potential for a simulation tool to structure and inform a complex resource management situation by involving local experts and stakeholders in the development of possible future scenarios will become increasingly valuable for transparent and participatory resource management.     

半导体企业的EHSMS评价体系研究

为了给员工提供安全、环保、健康的工作环境,半导体制造企业必须建立环境管理和职业健康安全管理体系(EHSMS).为此,评价EHSMS运行的有效性、完整性以及合法性就显得十分重要.本文在分析半导体企业污染物影响环境和健康基础上,建立了EHSMS评估体系.为了实施EHSM评估系统,方便半导体企业用户使用,提出了一套EHSM评价系统的计算机软件解决方案.     

地表水环境遥感监测关键技术与系统

本文主要是围绕地表水环境遥感检测展开讨论,全面介绍了水环境检测的关键技术和系统,建立改进双峰法的水体分布遥感提取方法,并以具体地区为例进行分析,采用不同方法建立解析方法,从根本上提升反演方法的区域和积极适用性,希望能够对相关人员起到参考性价值。     

矿区生态环境遥感监测数据库系统设计与实现

以肥城矿区为背景,基于Personal Geodatabase模型构建了空间数据库,采用C#作为开发语言,借助ArcGIS Engine的控件开发了矿区生态环境遥感监测数据库系统.根据数据获取方式不同,将空间数据库分为基础地理数据库、专题数据库、实地监测数据库和表格数据库4部分,系统实现了矿区空间数据和属性数据的统一存储和管理,多时相遥感数据的对比分析,水质、土壤湿度的动态监测,矿区各类地物面积的统计分析等功能.     

Projecting Climate Change Effects on Forest Net Primary Productivity in Subtropical Louisiana,USA

This study projected responses of forest net primary productivity (NPP) to three climate change scenarios at a resolution of 5 km × 5 km across the state of Louisiana, USA. In addition, we assessed uncertainties associated with the NPP projection at the grid and state levels. Climate data of the scenarios were derived from Community Climate System Model outputs. Changes in annual NPP between 2000 and 2050 were projected with the forest ecosystem model PnET-II. Results showed that forest productivity would increase under climate change scenarios A1B and A2, but with scenario B1, it would peak during 2011–2020 and then decline. The projected average NPP under B1 over the years from 2000 to 2050 was significantly different from those under A1B and A2. Forest NPP appeared to be primarily a function of temperature, not precipitation. Uncertainties of the NPP projection were due to large spatial resolution of the climate variables. Overall, this study suggested that in order to project effects of climate change on forest ecosystem at regional level, modeling uncertainties could be reduced by increasing the spatial resolution of the climate projections.     

Contaminants in the coastal karst aquifer system along the Caribbean coast of the Yucatan Peninsula, Mexico

Intensive land development as a result of the rapidly growing tourism industry in the “Riviera Maya” region of the Yucatan Peninsula, Mexico may result in contamination of groundwater resources that eventually discharge into Caribbean coastal ecosystems. We deployed two types of passive sampling devices into groundwater flowing through cave systems below two communities to evaluate concentrations of contaminants and to indicate the possible sources. Pharmaceuticals and personal care products accumulated in the samplers could only have originated from domestic sewage. PAHs indicated contamination by runoff from highways and other impermeable surfaces and chlorophenoxy herbicides accumulated in samplers deployed near a golf course indicated that pesticide applications to turf are a source of contamination. Prevention and mitigation measures are needed to ensure that expanding development does not impact the marine environment and human health, thus damaging the tourism-based economy of the region.     

A Two-Stage Particle Swarm Optimization Algorithm for MPPT of Partially Shaded PV Arrays

The power-voltage (P-V) characteristic curves of a PV array are nonlinear and have multiple peaks under partially shaded conditions (PSCs). This paper proposes a novel maximum power point tracking (MPPT) method for a PV system with reduced steady-state oscillation based on a two-stage particle swarm optimization (PSO) algorithm. The grouping method of the shuffled frog leaping algorithm (SFLA) is incorporated in the basic PSO algorithm (PSO-SFLA), ensuring fast and accurate searching of the global extremum. An adaptive speed factor is also introduced into the improved PSO to further enhance its convergence speed. Test results show that the proposed method converges in less than half the time taken by the conventional PSO method, and the power is improved by 33% under the worst PSCs, which confirms the superiority of the proposed method over the standard PSO algorithm in terms of tracking speed and steady-state oscillations under different PSCs.