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RESEARCH ARTICLE
Contents Vol 47(7)

Spatial heterogeneity of soil chemical properties in a lowland tropical moist forest, Panama

J. B. Yavitt A E , K. E. Harms B , M. N. Garcia C , S. J. Wright C , F. He D and M. J. Mirabello A
+ Author Affiliations
- Author Affiliations

A Department of Natural Resources, Cornell University, Ithaca, NY 14853-3001, USA.

B Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA.

C Smithsonian Tropical Research Institute, Apartado 0843-03092, Balboa, Ancon, Panama.

D Department of Renewable Resources, University of Alberta, Edmonton, Alberta, T6G 2H1, Canada.

E Corresponding author. Email: jby1@cornell.edu

Australian Journal of Soil Research 47(7) 674-687 https://doi.org/10.1071/SR08258
Submitted: 30 November 2008  Accepted: 25 June 2009   Published: 6 November 2009

Abstract

We evaluated spatial heterogeneity for pH and a comprehensive set of nutrient and trace elements in surface (0–0.1 m depth) and subsurface (0.3–0.4 m depth) soils across 26.6 ha of old-growth, lowland, tropical moist forest, established on a highly weathered soil in Panama. Little is known about spatial heterogeneity patterns of soil properties in tropical forest soils. Soil was moderately acidic (pH 5.28) with low concentrations of exchangeable base cations (13.4 cmolc/kg), Bray-extractable PO4 (2.2 mg/kg), KCl-extractable NO3 (5.0 mg/kg), and KCl-extractable NH4 (15.5 mg/kg). The coefficient of variation for soil properties ranged from 24% to >200%, with a median value of 84%. Geostatistical analysis revealed spatial dependence at a scale of 10–100 m for most of the soil properties; however, pH, NH4, Al, and B had spatial dependence at a scale up to 350 m. Best-fit models to individual variograms included random, exponential, spherical, Gaussian, linear, and power functions, indicating many different spatial patterns among the set of soil properties. Correlation among individual elements was poor, indicating independent patterns. Our results show complex spatial patterns in soil chemical properties and provide a basis for future investigations on soil–plant relationships and soil nutrient niche differentiation.

Additional keywords: base cations, geostatistical analysis, nutrients, spatial variability, trace elements, variogram.


Acknowledgments

Research support provided by grants from the Andrew W. Mellon Foundation and the Smithsonian Scholarly Studies program. The Smithsonian Tropical Research Institute provides much support for the ongoing Gigante Fertilization Project. We thank the many students in Panama and at Cornell for assistance in the field and in the laboratory.


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