Soil C and N minimum detectable changes and treatment differences in a multi-treatment forest experiment

被引:25
作者
Homann, P. S. [1 ]
Bormann, B. T. [2 ]
Boyle, J. R. [3 ]
Darbyshire, R. L.
Bigley, R. [4 ]
机构
[1] Western Washington Univ, Dept Environm Sci, Huxley Coll Environm, Bellingham, WA 98225 USA
[2] USDA, Forestry Sci Lab, Corvallis, OR 97331 USA
[3] Oregon State Univ, Dept Forest Resources, Corvallis, OR 97331 USA
[4] Washington State Dept Nat Resources, Land Management Div, Olympia, WA 98504 USA
关键词
soil nitrogen; soil carbon; minimum detectable change; minimum detectable difference; change detection;
D O I
10.1016/j.foreco.2007.11.037
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Detecting changes in forest soil C and N is vital to the study of global budgets and long-term ecosystem productivity. Identifying differences among land-use practices may guide future management. Our objective was to determine the relation of minimum detectable changes (MDCs) and minimum detectable differences between treatments (MDDs) to soil C and N variability at multiple spatial scales. The three study sites were 701 100-year-old coniferous forests in Washington and Oregon. Area- and volumetric-based soil measurements were made before implementation of 7 treatments on 2-ha experimental units, replicated in 3 or 4 blocks per site. In the absence of treatment effects, whole-site MDCs are similar to 10% for mineral soil C and N masses and concentrations and similar to 40% for O-horizon C and N masses. When treatment differences occur, MDDs are similar to 40% for mineral soil and similar to 150% for O-horizon. MDDs are reduced as much as two-thirds by evaluating change from pre- to post-treatment rather than only post-treatment values. and by pairing pre- and post-treatment measurements within small subplots. The magnitude of MDD reduction is quantitatively related to pre-treatment soil variability at multiple spatial scales, with the greatest reductions associated with the largest within-block: within-plot and within-plot: within-subplot variability ratios. These quantified benefits can be weighed against costs and challenges to make informed decisions when selecting the most appropriate sampling design. (C) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:1724 / 1734
页数:11
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