Over the last decade, the ecosystem services (ESs) framework has been increasingly used to support mapping and assessment studies for sustainable land management purposes. Previous analysis of practical applications has revealed the significance of the spatial scale at which input data are obtained. This issue is particularly problematic with soil data that are often unavailable or available only at coarse scales or resolutions in various part of the world. In this context, four soil-based ecosystem services, namely biomass provision, water provision, global climate regulation, and water quality regulation, are assessed using three conventional soil maps at the 1:1,000,000, 1:250,000 and 1:50,000 scales. The resulting individual and joint ES maps are then compared to examine the effects of changing the spatial scale of soil data on the ES levels and spatial patterns. ES levels are finally aggregated to landforms, land use, or administrative levels in order to try to identify the determinants of the sensitivity of ES levels to change in the scale of input soil data. Whereas the three soil maps turn out to be equally useful whenever ESs levels averaged over the whole 100 km² territory are needed, the maps at the 1:1,000,000 and 1:250,000 induced biases in the assessment of ESs levels over spatial units smaller than 100 and 10 km², respectively. The simplification of the diversity and spatial distribution of soils at the two coarsest scales indeed resulted in local differences in ES levels ranging from several 10 to several 100%. Identification of the optimal representation of soil diversity and distribution to obtain a reliable representation of ESs spatial distribution is not straightforward. The ESs sensitivity to scale effect is indeed context-specific, variable among individual ESs, and not directly or simply linked with the soil typological diversity represented in soil maps. Forested and natural lands in the study area appear particularly sensitive to soil data scales as they occupy marginal soils showing very specific ESs signatures.

中文翻译：

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土壤数据空间尺度对土壤生态系统服务估计的影响：以法国 100 平方公里区域为例

在过去十年中，生态系统服务 (ESs) 框架越来越多地用于支持可持续土地管理目的的测绘和评估研究。先前对实际应用的分析揭示了获取输入数据的空间尺度的重要性。这个问题对于土壤数据来说尤其成问题，这些数据在世界各地通常无法获得或只能以粗略的比例或分辨率获得。在此背景下，使用三种比例为 1:1,000,000、1:250,000 和 1:50,000 的常规土壤图评估四种基于土壤的生态系统服务，即生物量供应、水供应、全球气候调节和水质调节。然后将生成的单个和联合 ES 地图进行比较，以检查改变土壤数据空间尺度对 ES 水平和空间格局的影响。ES 水平最终汇总到地貌、土地利用或行政级别，以尝试确定 ES 水平对输入土壤数据规模变化的敏感性的决定因素。而当 ESs 水平在整个 100 公里内平均时，三张土壤地图证明同样有用^{需要2 个}领土，1:1,000,000 和 1:250,000 的地图在评估小于 100 和 10 km ^{2的空间单位的 ESs 水平时会产生偏差}， 分别。在两个最粗糙的尺度上，土壤多样性和空间分布的简化确实导致了 ES 水平的局部差异，范围从几十％到几百％不等。确定土壤多样性和分布的最佳表示以获得 ES 空间分布的可靠表示并不简单。ES 对规模效应的敏感性确实是特定于上下文的，在各个 ES 之间是可变的，并且与土壤地图中表示的土壤类型多样性没有直接或简单的联系。研究区域的森林和自然土地似乎对土壤数据尺度特别敏感，因为它们占据显示非常具体的 ES 特征的边缘土壤。