On the effects of scale for ecosystem services mapping.
On the effects of scale for ecosystem services mapping.
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DOI：
10.1371/journal.pone.0112601
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Tappeiner U
中科院分区：
文献类型：
--
作者：
Grêt-Regamey A;Weibel B;Bagstad KJ;Ferrari M;Geneletti D;Klug H;Schirpke U;Tappeiner U
生态系统提供人类文明所依赖的维持生命的服务，但其退化基本上有增无减。为了更好地指导决策，特别是山区系统的决策，需要关于生态系统服务提供的空间明确信息，山区系统的特点是垂直梯度和孤立，地形复杂，对全球变化特别敏感。但是，虽然空间上明确的环境服务量化和估值允许确定丰富或有限的供应和需求的环境服务的领域，信息的准确性和有用性取决于所使用的规模和方法有很大的不同。使用来自欧洲和美国山区的四个案例研究，在绘制五个ES --碳封存、洪水调节、农业生产、木材采伐和风景--时，我们以粗分辨率和细分辨率（欧洲为250米对25米，美国为300米对30米）量化了信息增益和损失。我们分析了尺度对ES估计及其空间格局的影响，并展示了这些影响如何与不同的ES，地形结构和模型属性有关。在所有案例研究和所有服务中，ES估计值在精细和粗分辨率分析之间存在很大差异。这种规模效应并不是对所有专家系统都一样强。我们发现，空间上明确的信息，非集群，孤立的ES往往会丢失在粗糙的分辨率和预期，主要是在不那么崎岖的地形，这需要更精细的分辨率评估在这种情况下。地形崎岖的影响也与模型特性有关，例如对土地利用-土地覆盖数据的依赖性。我们关闭与建议映射ES，使所得到的地图更具可比性，并建议一个四步的方法来解决规模的问题时，映射ES，可以提供信息，以支持ES为基础的决策具有更高的准确性和可靠性。
Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.
影响因子：
3.4
作者：
Anton, Christian;Young, Juliette;Settele, Josef
通讯作者：
Settele, Josef
影响因子：
7.6
作者：
Bagstad, Kenneth J.;Semmens, Darius J.;Winthrop, Robert
通讯作者：
Winthrop, Robert
影响因子：
4.1
作者：
Bagstad, Kenneth J.;Villa, Ferdinando;Johnson, Gary W.
通讯作者：
Johnson, Gary W.