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Dryad

Meta-analysis shows forest soil CO2 effluxes are dependent on the disturbance regime and biome type

Cite this dataset

Akande, Oluwabunmi et al. (2023). Meta-analysis shows forest soil CO2 effluxes are dependent on the disturbance regime and biome type [Dataset]. Dryad. https://doi.org/10.5061/dryad.51c59zwcr

Abstract

Forest soil CO2 efflux (FCO2) is a crucial process in global carbon cycling; however, how FCO2 responds to disturbance regimes in different forest biomes is poorly understood. We quantified the effects of disturbance regimes on FCO2 across boreal, temperate, tropical, and Mediterranean forests based on 1240 observations from 380 studies. Globally, climatic perturbations such as elevated CO2 concentration, warming, and increased precipitation increase FCO2 by 13 to 25%. FCO2 is increased by forest conversion to grassland and elevated carbon input by forest management practices but reduced by decreased carbon input, fire, and acid rain. Disturbance also changes soil temperature and water content, which in turn affect the direction and magnitude of disturbance influences on FCO2. FCO2 is disturbance- and biome-type dependent, and such effects should be incorporated into earth system models to improve the projection of the feedback between the terrestrial C cycle and climate change.

Methods

Peer-reviewed journal articles from 1970 to 2021 were searched using the ISI Web of Science database.  This study narrowed the search to disturbance effects on FCO2 in boreal, temperate, tropical, and Mediterranean forests, and excluded non-forest ecosystems. Searches were limited to disturbance effects on FCO2 under field conditions. Studies that lasted less than one growing season were also excluded. Each observation had at least one pair of total (FCO2), autotrophic (AFCO2) or heterotrophic (HFCO2) components measured simultaneously in both the control and treatment groups. If studies reported more than one disturbance level, each level was recorded and listed as a separate observation.

Usage notes

Microsoft Excel

Funding

National Natural Science Foundation of China, Award: 32101272

Natural Sciences and Engineering Research Council