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Volume 12, issue 19
Biogeosciences, 12, 5735–5751, 2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Biogeosciences, 12, 5735–5751, 2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 08 Oct 2015

Research article | 08 Oct 2015

Evaluation of stem rot in 339 Bornean tree species: implications of size, taxonomy, and soil-related variation for aboveground biomass estimates

K. D. Heineman1, S. E. Russo2, I. C. Baillie3,4, J. D. Mamit4,5, P. P.-K. Chai4, L. Chai4, E. W. Hindley6, B.-T. Lau4, S. Tan7, and P. S. Ashton8 K. D. Heineman et al.
  • 1Program for Ecology, Evolution, and Conservation Biology, University of Illinois-Urbana Champaign, USA
  • 2School of Biological Sciences, University of Nebraska–Lincoln, Nebraska, USA
  • 3National Soil Resources Institute, Cranfield University, UK
  • 4Forest Department, Kuching, Sarawak, Malaysia
  • 5Datuk Menteri Yang Berhormat, Federal Parliament of Malaysia, Kuala Lumpur, Malaysia
  • 602 591 57 W Avenue, Vancouver, British Columbia, Canada
  • 7Center for Tropical Forest Science, Smithsonian Institution, Washington DC, USA
  • 8Organismic and Evolutionary Biology, Harvard University, USA and Royal Botanic Gardens, Kew, UK

Abstract. Fungal decay of heart wood creates hollows and areas of reduced wood density within the stems of living trees known as stem rot. Although stem rot is acknowledged as a source of error in forest aboveground biomass (AGB) estimates, there are few data sets available to evaluate the controls over stem rot infection and severity in tropical forests. Using legacy and recent data from 3180 drilled, felled, and cored stems in mixed dipterocarp forests in Sarawak, Malaysian Borneo, we quantified the frequency and severity of stem rot in a total of 339 tree species, and related variation in stem rot with tree size, wood density, taxonomy, and species' soil association, as well as edaphic conditions. Predicted stem rot frequency for a 50 cm tree was 53 % of felled, 39 % of drilled, and 28 % of cored stems, demonstrating differences among methods in rot detection ability. The percent stem volume infected by rot, or stem rot severity, ranged widely among trees with stem rot infection (0.1–82.8 %) and averaged 9 % across all trees felled. Tree taxonomy explained the greatest proportion of variance in both stem rot frequency and severity among the predictors evaluated in our models. Stem rot frequency, but not severity, increased sharply with tree diameter, ranging from 13 % in trees 10–30 cm DBH to 54 % in stems ≥ 50 cm DBH across all data sets. The frequency of stem rot increased significantly in soils with low pH and cation concentrations in topsoil, and stem rot was more common in tree species associated with dystrophic sandy soils than with nutrient-rich clays. When scaled to forest stands, the maximum percent of stem biomass lost to stem rot varied significantly with soil properties, and we estimate that stem rot reduces total forest AGB estimates by up to 7 % relative to what would be predicted assuming all stems are composed strictly of intact wood. This study demonstrates not only that stem rot is likely to be a significant source of error in forest AGB estimation, but also that it strongly covaries with tree size, taxonomy, habitat association, and soil resources, underscoring the need to account for tree community composition and edaphic variation in estimating carbon storage in tropical forests.

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Short summary
Stem rot is a poorly constrained source of error in forest biomass estimates. We quantified frequency and severity of rot in stems felled, drilled, and cored in a Bornean rainforest and the association of stem rot with tree size, taxonomy, and edaphic conditions. Stem rot frequency increased with tree size and varied widely among taxa. Stem rot encompassed 9% of stem volume on average, and the reduction in forest biomass lost to rot was greater on low fertility compared to high fertility soils.
Stem rot is a poorly constrained source of error in forest biomass estimates. We quantified...
Final-revised paper