CREAF, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain; Agroscope, Reckenholzstr. 191, CH-8046 Zurich, Switzerland.
CREAF, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain.
Sci Total Environ. 2018 Jun 1;626:1270-1283. doi: 10.1016/j.scitotenv.2018.01.150. Epub 2018 Feb 19.
The implementation of the Ecosystem Services (ES) framework (including supply and demand) should be based on accurate spatial assessments to make it useful for land planning or environmental management. Despite the inherent dependence of ES assessments on the spatial resolution at which they are conducted, the studies analyzing these effects on ES supply and their relationships are still scarce. To study the influence of the spatial level of analysis on ES patterns and on the relationships among different ES, we selected seven indicators representing ES supply and three variables that describe forest cover and biodiversity for Catalonia (NE Iberian Peninsula). These indicators were estimated at three different scales: local, municipality and county. Our results showed differences in the ES patterns among the levels of analysis. The higher levels (municipality/county) removed part of the local heterogeneity of the patterns observed at the local scale, particularly for ES indicators characterized by a finely grained, scattered distribution. The relationships between ES indicators were generally similar at the three levels. However, some negative relationships (potential trade-offs) that were detected at the local level changed to positive (and significant) relationships at municipality and county. Spatial autocorrelation showed similarities between patterns at local and municipality levels, but differences with county level. We conclude that the use of high-resolution spatial data is preferable whenever available, in particular when identifying hotspots or trade-offs/synergies is of primary interest. When the main objective is describing broad patterns of ES, intermediate levels (e.g., municipality) are also adequate, as they conserve many of the properties of assessments conducted at finer scales, allowing the integration of data sources and, usually, being more directly relevant for policy-making. In conclusion, our results warn against the uncritical use of coarse (aggregated) spatial ES data and indicators in strategies for land use planning and forest conservation.
生态系统服务（ES）框架（包括供应和需求）的实施应基于准确的空间评估，使其可用于土地规划或环境管理。尽管 ES 评估固有地依赖于其进行的空间分辨率，但分析这些对 ES 供应的影响及其关系的研究仍然很少。为了研究分析水平对 ES 格局和不同 ES 之间关系的影响，我们选择了七个代表 ES 供应的指标和三个描述加泰罗尼亚（伊比利亚半岛东北部）森林覆盖和生物多样性的变量。这些指标在三个不同的尺度上进行估计：局部、市镇和县。我们的研究结果表明，在不同的分析层次上，ES 格局存在差异。较高的层次（市镇/县）消除了局部尺度上观察到的模式的部分局部异质性，特别是对于具有精细、分散分布特征的 ES 指标。ES 指标之间的关系在三个层次上通常相似。然而，在局部层次上检测到的一些负相关关系（潜在的权衡）在市镇和县级层次上变为正相关（且显著）关系。空间自相关显示出局部和市镇层次上的模式之间存在相似性，但与县级层次存在差异。我们得出的结论是，只要有可能，使用高分辨率空间数据是可取的，特别是在确定热点或权衡/协同作用是首要关注点时。当主要目标是描述 ES 的广泛格局时，中间层次（例如市镇）也是足够的，因为它们保留了在更细尺度上进行评估的许多特性，允许数据来源的集成，并且通常更直接与决策相关。总之，我们的研究结果警告不要在土地利用规划和森林保护策略中不加批判地使用粗糙（聚合）的空间 ES 数据和指标。
