Spatial variation in soil properties among North American ecosystems and guidelines for sampling designs.
Spatial variation in soil properties among North American ecosystems and guidelines for sampling designs.
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DOI：
10.1371/journal.pone.0083216
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Brunke M
中科院分区：
文献类型：
--
作者：
Loescher H;Ayres E;Duffy P;Luo H;Brunke M
土壤在许多空间尺度上都是高度可变的，这使得设计研究以准确估计空间上土壤特性的平均值具有挑战性。空间相关性结构对于开发鲁棒的采样策略（例如，样本大小和样本间隔）。目前的研究设计指南建议进行初步调查，以表征这种结构，但很少遵循，抽样设计往往是由后勤，而不是定量考虑。在60个地点的10.1公顷范围内对土壤的空间变异性进行了评估。作为国家生态观测网络部署的扩展战略的一部分，选择了代表美国关键生态系统的地点。我们测量了土壤温度（Ts）和含水量（SWC），因为这些属性介导地下和地上的生物/地球化学过程，并使用半变异函数来估计空间相关性，以量化空间变异性。我们制定了定量指导方针，为未来的土壤研究提供样本大小和样本间隔，例如，20个样本足以测量Ts的平均值的10%以内，90%的置信度在每个温带和亚热带网站在生长季节，而一个数量级更多的样本，需要在一些高纬度网站，以满足这一精度。在大多数研究中心，SWC的变异性明显大于Ts，因此需要至少10倍以上的SWC样本才能满足相同的准确度要求。以前的研究调查了平均值和变异性之间的关系（即，Sill），并且经常（但不总是）观察到方差或标准差在SWC的中间值处达到峰值，并且在低SWC和高SWC处降低。最后，我们量化了样本必须间隔多远才能在统计上独立。半方差结构从10个12个占主导地位的土壤订单在美国各地进行了估计，推进我们的大陆尺度的土壤行为的理解。
Soils are highly variable at many spatial scales, which makes designing studies to accurately estimate the mean value of soil properties across space challenging. The spatial correlation structure is critical to develop robust sampling strategies (e.g., sample size and sample spacing). Current guidelines for designing studies recommend conducting preliminary investigation(s) to characterize this structure, but are rarely followed and sampling designs are often defined by logistics rather than quantitative considerations. The spatial variability of soils was assessed across ∼1 ha at 60 sites. Sites were chosen to represent key US ecosystems as part of a scaling strategy deployed by the National Ecological Observatory Network. We measured soil temperature (Ts) and water content (SWC) because these properties mediate biological/biogeochemical processes below- and above-ground, and quantified spatial variability using semivariograms to estimate spatial correlation. We developed quantitative guidelines to inform sample size and sample spacing for future soil studies, e.g., 20 samples were sufficient to measure Ts to within 10% of the mean with 90% confidence at every temperate and sub-tropical site during the growing season, whereas an order of magnitude more samples were needed to meet this accuracy at some high-latitude sites. SWC was significantly more variable than Ts at most sites, resulting in at least 10× more SWC samples needed to meet the same accuracy requirement. Previous studies investigated the relationship between the mean and variability (i.e., sill) of SWC across space at individual sites across time and have often (but not always) observed the variance or standard deviation peaking at intermediate values of SWC and decreasing at low and high SWC. Finally, we quantified how far apart samples must be spaced to be statistically independent. Semivariance structures from 10 of the 12-dominant soil orders across the US were estimated, advancing our continental-scale understanding of soil behavior.
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