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Estimating the regional mean status and change of soil properties: two distinct objectives for soil survey
Author(s) -
Lark R. M.
Publication year - 2009
Publication title -
european journal of soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.244
H-Index - 111
eISSN - 1365-2389
pISSN - 1351-0754
DOI - 10.1111/j.1365-2389.2009.01156.x
Subject(s) - sampling (signal processing) , resampling , environmental science , soil water , simple random sample , sampling design , statistics , sample (material) , soil science , computer science , mathematics , chemistry , chromatography , population , demography , filter (signal processing) , sociology , computer vision
Summary There is a general requirement for inventories to establish the status of soils with respect to key indicator properties, and for monitoring to detect changes in these indicators. The design of sampling protocols for soil survey must meet these dual requirements. This paper emphasizes that the status and change of an indicator are different variables and so their variability may differ. We therefore may not assume that a sampling scheme that is suitable for inventory is also suitable for monitoring; this poses a practical problem since information on the variability of the change in soil is not in general available at present. In this paper some plausible statistical models of change in the soil are examined, and their implications for sampling to estimate mean change in large regions are considered. Paired sampling, with baseline and resampling at common sites, is generally preferable to sampling at independent sites on the two dates, unless the error from relocation of the sample sites is large by comparison to other sources of variation. A simple process model of soil organic carbon in soils of lowland tropical forest is used to examine the problem of resampling to estimate change. This shows the expected advantages of paired sampling for change, and the very different sampling requirements that may pertain for inventory and monitoring. One implication of these results is that, while sampling schemes for inventory may be designed on the basis of available information (from samples taken at a single time), the precise requirements for monitoring might not be apparent until a reconnaissance resampling is undertaken subsequently.