An Accurate and Efficient Method for Sorting Biomass Extracted from Soil Cores Using Point-Intercept Sampling Rebecca C. Wenk,* John J. Battles, Randall D. Jackson, James W. Bartolome, and Barbara Allen-Diaz ABSTRACT 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 ex- tracted organic material over a grid and record the category of ran- domly 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 21 ) allowed us to process 43% more cores during the same period. We applied the same technique to components of aboveground herba- ceous biomass, but with less success because these pools tended to be less uniformly distributed throughout the sample layer. We recom- mend the approach for sorting belowground biomass components from soil cores, but the method requires more development before being used to sort other ecosystem components. F INE ROOT PRODUCTION is a major component of net primary productivity (NPP) in most ecosystems. Fine roots account for 30 to 50% of the annual C contribution to NPP in forests (Grier et al., 1981; Jackson et al., 1997) and an even higher percentage in grasslands (Schles- inger, 1997; McNaughton et al., 1998; Tufekcioglu et al., 1998). Net primary productivity is an important metric of ecosystem response to climate change and distur- bance (Grier et al., 1981; Jackson et al., 1997; Millikin and Bledsoe, 1999; Johnson and Matchett, 2001). The amount of biomass fixed by primary producers and available to consumers drives trophic dynamics and biogeochemical cycling (Schlesinger, 1997). Measuring belowground biomass is difficult and time-consuming (Vogt et al., 1998). Despite the promise of indirect approaches such as N budgeting (Aber et al., 1985) and isotopic tracers (Bledsoe et al., 1999; Fahey et al., 1999), most estimates of root production still depend on con- ventional biomass assessment (e.g., sequential coring and ingrowth cores) (Bledsoe et al., 1999; Fahey et al., 1999; Lauenroth, 2000). The most daunting practical problem with biomass assessment of roots is the high labor cost associated with washing and sorting the sam- ples (Persson, 1990). Moreover, the tremendous vari- ability in the spatial distribution of fine root biomass compels the collection of many cores to accommodate this inherent heterogeneity. Typically the soil cores (usual volume ,300 cm 3 ) are washed over screens to remove soil, rocks, and debris leaving a mass of organic matter spanning the continuum of decomposition from large partially decayed leaves and twigs to fine par- ticulate matter whose original form is indeterminate. Separating fine roots (,2 mm diam.) from other cate- gories of organic matter is a tedious, time-consuming process most often performed by undergraduate assis- tants. Turnover of these assistants is usually very high, thereby raising the costs associated with training and quality control. Here we describe a point-intercept approach to mea- suring the fine root mass in washed soil cores. Using the complete census of fine roots as the standard, we cal- culate the accuracy and efficiency of the point-sampling technique. We also explore the general utility of this approach by applying it to other cryptic components of ecosystems biomass budgets. MATERIALS AND METHODS Study Site We conducted this work at the University of California Sierra Foothill Research and Extension Center, located approximately 32 km northeast of Marysville, CA (398159 N, 1218179 W) in the Sierra Nevada foothills. The climate is Medi- terranean; cool, wet winters and hot, dry summers predomi- nate. Mean annual temperature is 15.88C and mean annual precipitation is 71 cm. Soils in this area are generally shallow and classified as Auburn (loamy, mixed, superactive, thermic Lithic Haploxerepts) and Argonaut (fine, mixed, superactive, thermic Mollic Haploxeralfs) series (Jackson and Allen-Diaz, 2002). Soils are derived from metavolcanic greenstone bed- rock (Herbert and Begg, 1969). The study area was an oak savanna consisting primarily of deciduous blue oak (Quercus douglasii Hook. & Arn.) and annual grasses (Shlisky, 2001). Other trees and shrubs included R.C. Wenk, J.J. Battles, J.W. Bartolome, and B. Allen-Diaz, 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. R.D. Jackson, Agronomy Dep., Univ. of Wisconsin, 1575 Linden Dr., Madison, WI 53706 USA. Received 27 Sept. 2004. *Corresponding author (rcwenk@nature.berkeley.edu). Published in Soil Sci. Soc. Am. J. 70:851–855 (2006). Forest, Range & Wildland Soils, Soil Biology & Biochemistry doi:10.2136/sssaj2004.0316 ª Soil Science Society of America 677 S. Segoe Rd., Madison, WI 53711 USA 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. Reproduced from Soil Science Society of America Journal. Published by Soil Science Society of America. All copyrights reserved. 851 Published online March 29, 2006