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

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...

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Bibliographic Details
Published in:Forest ecology and management 2008-04, Vol.255 (5), p.1724-1734
Main Authors: Homann, P.S., Bormann, B.T., Boyle, J.R., Darbyshire, R.L., Bigley, R.
Format: Article
Language:English
Subjects:
Animal and plant ecology
Animal, plant and microbial ecology
Biological and medical sciences
Change detection
Fundamental and applied biological sciences. Psychology
Minimum detectable change
Minimum detectable difference
Soil carbon
Soil nitrogen
Synecology
Terrestrial ecosystems
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Summary: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 70–100-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 ∼10% for mineral soil C and N masses and concentrations and ∼40% for O-horizon C and N masses. When treatment differences occur, MDDs are ∼40% for mineral soil and ∼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.
ISSN:0378-1127
1872-7042
DOI:10.1016/j.foreco.2007.11.037