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DOs AND DON'Ts OF SPATIALLY EXPLICIT ECOLOGICAL RISK ASSESSMENTS

机译:空间显性生态风险评估的可做与不可

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Location affects exposure and response to stressors at scales ranging from small sites to large regions. Tools such as geographic information systems (GIS) make it feasible to conduct spatially explicit ecological risk assessments (ERAs). However, no tools provide a panacea, and complex models based on sparse data can be inappropriate and misleading. Operations such as an interpolation within a GIS are models, and so they contain assumptions and uncertainties. Errors can propagate easily as numerous operations are performed, and the resulting uncertainties should be made explicit. Analysts should assure that space actually matters by using explanatory data prior to investigating spatial correlation. Exposure and risk estimates from experimental plots or monitoring stations may require scaling factors if they are to be used for larger watersheds or regional analyses. Maps are useful because they present complex spatial information in a manner that is easily interpreted. However, they must be prepared and interpreted with caution because they can suggest that there is a great deal more information than actually exists. In addition to presenting maps of predicted risks, maps of the spatial patterns in the uncertainties in these risk estimates should be included in risk assessments.
机译:位置会影响从应激源到小型场所到大型区域的暴露和对应激源的反应。诸如地理信息系统(GIS)之类的工具使进行空间明确的生态风险评估(ERA)变得可行。但是,没有工具提供灵丹妙药,并且基于稀疏数据的复杂模型可能是不合适的并且具有误导性。 GIS中的插值等操作是模型,因此它们包含假设和不确定性。由于执行大量操作,错误很容易传播,因此应明确表明不确定性。在调查空间相关性之前,分析人员应通过使用解释性数据来确保空间确实重要。如果要用于较大的集水区或进行区域分析,则从试验区或监测站进行的暴露和风险估算可能需要比例因子。地图之所以有用,是因为它们以易于解释的方式呈现了复杂的空间信息。但是,必须谨慎准备和解释它们,因为它们可能暗示比实际存在更多的信息。除了提供预测风险图之外,这些风险估计中不确定性的空间格局图也应包括在风险评估中。

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