Detecting nutrient pool changes in rocky forest soils
- Andrew Kulmatiski *a,
- Daniel J. Vogtb,
- Thomas G. Siccamac and
- Karen H. Beardd
- a Dep. of Biology and Ecology Center, Utah State Univ., Logan, UT 84322
b College of Forest Resources, Univ. of Washington, Box 352100, Seattle, WA 98195
c Yale School of Forestry and Environmental Studies, Greeley Lab., 310 Prospect Street, New Haven, CT 06511
d Dep. of Forest, Range, and Wildlife Sciences and Ecology Center, Utah State Univ., Logan, UT 84322
Microsite heterogeneity often complicates the accurate measurement of soil properties. Many sampling techniques have been developed to overcome this difficulty, but use of these techniques requires the direct comparison of measurements from each technique. In this paper, we present estimates of C and N pool sizes determined from two commonly used, but previously not compared, techniques. Composite coring (core) and excavation mensuration (pit) techniques were performed in glacially stratified Inceptisols of southern New England. Estimates of total C pool size (forest floor [FF] −15 cm) from the pit and core techniques were significantly correlated (r 2 = 0.61, P < 0.0001) and very similar (5.64 ± 0.32 and 5.63 ± 0.29, respectively). However, the core technique reduced variance in the sample population, allowing fewer samples to detect a 10% change in nutrient storage (21 core vs. 29 pit samples). In addition, sampling each plot with the core technique required less than one-half the sampling time of the pit technique. The pit technique, however, allowed quantitative sampling below 15 cm and direct measurement of large coarse fragments. Data from the pit technique revealed a strong exponential decline in nutrient storage with depth. This exponential decline allowed the extrapolation of C and N pools to greater depths. Carbon storage (kg m−2) was described by depth (cm) as: exp (5.53–0.04 depth); P < 0.0001. N storage (kg m−2) was described by depth (cm) and tree basal area (ba, m2 ha−1) as: exp (3.280–0.025 depth– 0.003 ba); P < 0.0001. Our data suggest that composite core sampling is more efficient than, but well supplemented by, pit sampling.Please view the pdf by using the Full Text (PDF) link under 'View' to the left.
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