4.5 Article

Dead Wood Necromass in a Moist Tropical Forest: Stocks, Fluxes, and Spatiotemporal Variability

期刊

ECOSYSTEMS
卷 22, 期 6, 页码 1189-1205

出版社

SPRINGER
DOI: 10.1007/s10021-019-00341-5

关键词

carbon cycling; decomposition; snag; coarse woody debris; suspended woody debris; branchfall; Panama; liana

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资金

  1. HSBC Climate Partnership
  2. Smithsonian Forest-GEO Program
  3. Smithsonian Tropical Research Institute Fellowship
  4. NSF [GRF-2015188266]

向作者/读者索取更多资源

Woody debris (WD) stocks and fluxes are important components of forest carbon budgets and yet remain understudied, particularly in tropical forests. Here we present the most comprehensive assessment of WD stocks and fluxes yet conducted in a tropical forest, including one of the first tropical estimates of suspended WD. We rely on data collected over 8 years in an old-growth moist tropical forest in Panama to quantify spatiotemporal variability and estimate minimum sample sizes for different components. Downed WD constituted the majority of total WD mass (78%), standing WD contributed a substantial minority (21%), and suspended WD was the smallest component (1%). However, when considering sections of downed WD that are elevated above the soil, the majority of WD inputs and approximately 50% of WD stocks were disconnected from the forest floor. Branchfall and liana wood accounted for 17 and 2% of downed WD, respectively. Residence times averaged 1.9 years for standing coarse WD (CWD; > 20 cm diameter) and 3.6 years for downed CWD. WD stocks and inputs were highly spatially variable, such that the sampling efforts necessary to estimate true values within 10% with 95% confidence were > 130 km of transects for downed CWD and > 550 ha area for standing CWD. The vast majority of studies involve much lower sampling efforts, suggesting that considerably more data are required to precisely quantify tropical forest WD pools and fluxes. The demonstrated importance of elevated WD in our study indicates a need to understand how elevation above the ground alters decomposition rates and incorporate this understanding into models of forest carbon cycling.

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