HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Figures Only Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Wenk, R. C. Articles by Allen-Diaz, B. Search for Related Content PubMed Articles by Wenk, R. C. Articles by Allen-Diaz, B. Agricola Articles by Wenk, R. C. Articles by Allen-Diaz, B. Related Collections Statistics Watershed-Scale Studies Root Growth

Forest, Range & Wildland Soils

An Accurate and Efficient Method for Sorting Biomass Extracted from Soil Cores Using Point-Intercept Sampling

^a Ecosystem Sciences Division, 151 Hilgard Hall, Univ. of California, Berkeley, CA 94720 USA. R.C. Wenk currently at Dep. of Botany, California Academy of Sciences, 875 Howard St., San Francisco, CA 94103 USA
^b Agronomy Dep., Univ. of Wisconsin, 1575 Linden Dr., Madison, WI 53706 USA

^* Corresponding author (rcwenk{at}nature.berkeley.edu)

We describe a point-intercept sampling technique that reduces the time and therefore the cost associated with hand sorting biomass extracted from soil cores. Typically, organic material that has been extracted from soil cores is painstakingly separated into categories such as roots, leaves, and unidentifiable organic matter so that each can be weighed. With the point-intercept method, we spread the extracted organic material over a grid and record the category of randomly located point intercepts within grid cells. The proportion of each category determined via point intercepts is then attributed to the total dry mass of the organic material. With a subset of our data, we determined ordinary least squares regression relationships between hand-sorted (census) and point-intercept (sample) estimates of the belowground biomass components roots, aboveground detritus, and soil organic matter. We then applied these regression models to the remainder of our data, which had been hand sorted to serve as a validation dataset. Using bootstrapped 95% confidence intervals of the ordinary least squares (OLS) bisector slope estimate, we found no significant differences between the point-intercept and hand-sorted values for all three belowground biomass components. The time saved sorting belowground biomass by the point-intercept method (15 min core^–1) allowed us to process 43% more cores during the same period. We applied the same technique to components of aboveground herbaceous biomass, but with less success because these pools tended to be less uniformly distributed throughout the sample layer. We recommend the approach for sorting belowground biomass components from soil cores, but the method requires more development before being used to sort other ecosystem components.

Abbreviations: aHS, actual hand-sorted biomass • AIC, Akaike's Information Criterion • HS, hand-sorted biomass • NPP, net primary productivity • OLS, ordinary least squares • pHS, predicted hand-sorted biomass • PI, point intercept estimate • SOM, soil organic matter • TOT, total core biomass