Important role of forest disturbances in the global biomass turnover and carbon sinks

Forest disturbances that lead to the replacement of whole tree stands are a cornerstone of forest dynamics, with drivers that include fire, windthrow, biotic outbreaks and harvest. The frequency of disturbances may change over the next century with impacts on the age, composition and biomass of forests. However, the disturbance return time, that is, the mean interval between disturbance events, remains poorly characterized across the world’s forested biomes, which hinders the quantification of the role of disturbances in the global carbon cycle. Here we present the global distribution of stand-replacing disturbance return times inferred from satellite-based observations of forest loss. Prescribing this distribution within a vegetation model with a detailed representation of stand structure, we quantify the importance of stand-replacing disturbances for biomass carbon turnover globally over 2001–2014. The return time varied from less than 50 years in heavily managed temperate ecosystems to over 1,000 years in tropical evergreen forests. Stand-replacing disturbances accounted for 12.3% (95% confidence interval, 11.4–13.7%) of the annual biomass carbon turnover due to tree mortality globally, and in 44% of the forested area, biomass stocks are strongly sensitive to changes in the disturbance return time. Relatively small shifts in disturbance regimes in these areas would substantially influence the forest carbon sink that currently limits climate change by offsetting emissions.Forest stand-replacing disturbances significantly affect the biomass stocks in about a half of forested area globally, according to analyses of global forest loss from satellite data, together with a dynamic vegetation model.

• Publication year

  2019

• Venue

  Nature Geoscience

• Publication date

  2019-07-10

• Fields of study

  Medicine, Environmental Science

• Identifiers
  DOI 10.1038/s41561-019-0427-2PMID 31478009PMCID 6718285
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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