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Soil Sampling Strategies for the Characterization of Spatial Variability Under Two Distinct Land Uses
Communications in Soil Science and Plant Analysis ( IF 1.8 ) Pub Date : 2021-06-10 , DOI: 10.1080/00103624.2021.1921190
Sunshine A. De Caires 1 , Mark N. Wuddivira 1 , De Shorn E. Bramble 1 , Melissa Atwell 2 , Ronald Roopnarine 1 , Kegan K. Farrick 2
Affiliation  

ABSTRACT

Spatial heterogeneity is a universal phenomenon existing in ecological systems at all scales. In the humid tropics, soil sampling and characterization are complex due to high spatial variability. The inability of researchers to capture this spatial variability inhibits the effective management of resources in terrestrial ecosystems. Hence, simple sampling approaches that are labor and cost-efficient but generate representative samples are required to optimize soil sampling and characterization. In this paper, we used a combination of descriptive statistics and geostatistics to characterize the spatial variability of soil under two land uses. One-way ANOVA and a Student t-test were also used to assess the effectiveness of three distinct sampling designs at capturing the variation in the soil’s physicochemical properties. The wetland soils generally exhibited low spatial variability, whereas the variability of the agroforest ranged from low (coefficient of variance (CV) < 25%) to highly variable (CV > 75%). Results show that in the wetland, CVs of samples obtained using the random sampling design (RSD) and response surface directed design (RSDD) were highly correlated (pearson correlation coefficient (r) = 0.98). Similarly, in the agroforest, the CVs of the stratified random sampling design (SRSD) and RSDD gave almost the same accuracy (r = 0.97). Thus, it is recommended that in this and similar humid-tropical wetland and agroforest ecosystems, the RSD and the RSDD, which require the least samples, can be used, respectively. However, more comprehensive testing is required on a broader range of soils before its more widespread application in other climatic conditions.



中文翻译:

两种不同土地利用下空间变异特征的土壤采样策略

摘要

空间异质性是存在于各个尺度生态系统中的普遍现象。在潮湿的热带地区,由于高度的空间变异性,土壤采样和表征很复杂。研究人员无法捕捉到这种空间变异性,阻碍了对陆地生态系统资源的有效管理。因此,需要采用劳动力和成本效益高但能生成代表性样本的简单采样方法来优化土壤采样和表征。在本文中,我们结合使用描述性统计和地质统计学来表征两种土地利用下土壤的空间变异性。单向方差分析和学生 t 检验也用于评估三种不同采样设计在捕捉土壤物理化学特性变化方面的有效性。湿地土壤通常表现出较低的空间变异性,而农林的变异性范围从低(变异系数(CV)< 25%)到高度可变(CV > 75%)。结果表明,在湿地中,使用随机抽样设计 (RSD) 和响应面定向设计 (RSDD) 获得的样本的 CV 高度相关(皮尔逊相关系数 (r) = 0.98)。同样,在农林中,分层随机抽样设计 (SRSD) 和 RSDD 的 CV 给出了几乎相同的准确度 (r = 0.97)。因此,建议在这个和类似的湿热带湿地和农林生态系统中,可以分别使用需要最少样本的 RSD 和 RSDD。然而,

更新日期:2021-06-10
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