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Disentangling effects of key coarse woody debris fuel properties on its combustion, consumption and carbon gas emissions during experimental laboratory fire
- Zhao, Weiwei, van Logtestijn, Richard S.P., van der Werf, Guido R., van Hal, Jurgen R., Cornelissen, Johannes H.C.
- Forest ecology and management 2018 v.427 pp. 275-288
- carbon, carbon cycle, carbon dioxide, carbon monoxide, carbon sinks, climate, climate models, coarse woody debris, combustion, conifers, decayed wood, environmental factors, flammability, fuels, gas emissions, trees, vegetation, water content, wood density, wood moisture
- Coarse woody debris is a key terrestrial carbon pool, and its turnover through fire plays a fundamental role in global carbon cycling. Coarse dead wood fuel properties, which vary between tree species and wood decay stages, might affect its combustion, consumption and carbon gas emissions during fire, either directly or indirectly through interacting with moisture or ground-wood contact.Using controlled laboratory burns, we tried to disentangle the effects of multiple biotic and abiotic factors: tree species (one conifer and three hard wood species), wood decay stages, moisture content, and ground-wood contact on coarse wood combustion, consumption, and CO2 and CO emissions during fire. Wood density was measured for all samples.We found that, compared to the other tested factors, wood decay stages acted as a predominant positive driver increasing coarse wood flammability and associated CO2 and CO emissions during fire. Wood moisture content (30 versus 7%) moderately inhibited wood flammability with slight interaction with wood decay effects. Wood decay effects can be mainly attributed to the decreasing wood density as wood becomes more decomposed.Our experimental data provides useful information for how several wood properties, especially moisture content and wood decay stages, with wood density as the key underlying trait, together drive coarse wood carbon turnover through fire to the atmosphere. Our results will help to improve the predictive power of global vegetation climate models on dead wood turnover and its feedback to climate.