Ecological drivers and stand level equations in the estimation of Atlantic Forest carbon stocks - Pyles, Marcela Venelli (2022)
Understanding the mechanisms controlling forest carbon storage is crucial to support “nature- based” solutions for climate change mitigation. In the first article, we used a dataset of 892 Atlantic Forest inventories to assess the direct and indirect effects of environmental conditions, human impacts, tree community proprieties and sampling methods on tree above- ground carbon stocks. We showed that the widely accepted drivers of carbon stocks, such as climate, soil, topography, and forest fragmentation have a much smaller role than the forest disturbance history and functional proprieties of the Atlantic Forest. Specifically, within- forest disturbance level was the most important driver, with effect at least 30% higher than any of the environmental conditions individually. Thus, our findings suggest that the conservation of tropical carbon stocks may be dependable on, principally, avoiding forest degradation and that conservation policies focusing only on carbon may fail to protect tropical biodiversity. In the second article, using a large dataset of 697 Atlantic Forest inventories, we evaluated the application of regional and forest type-specific equations to estimate carbon stocks based on two stand structural variables: stand basal area and stand density. We compared the predictive ability of one- and two-variable equations and showed that estimating carbon stock from the stand basal area and stand density provides accurate results for moist and dry forests of the Atlantic Forest domain. The developed equations based only on the stand structural variables explained 85.2%-96.2% of the carbon stocks variations having less than 6.5% of estimation errors. Thus, carbon stocks from the stand forestry structural variables can be accurate, and thus may represent an alternative when individual tree measurements and identifications from where complete forest inventories are not available.