Abstract

The Atlantic Forest fragments have suffered from the impacts of climate change, resulting in the increased production of coarse woody debris (CWD), which needs to be evaluated in space and time to generate accurate estimates of carbon accumulation. Thus, the goals of this study were (i) to quantify the CWD volume, necromass, carbon stock, and annual increment of carbon (AIcarb) over a period of 4 years; and (ii) to select the optimal combination of climatic, topographic, edaphic, and intrinsic forest variables to accurately predict AIcarb using machine learning and multivariate analysis. The CWD volume, necromass, and carbon stock increased between 2017 and 2020. The AIcarb was 1.09 MgC ha−1 year−1 (2017–2018), 1.24 MgC ha−1 year−1 (2018–2019), and 2.31 MgC ha−1 year−1 (2019–2020). Statistical analysis indicated that climate variables had greater weight in the CWD carbon increment in the 2018–2019 and 2019–2020 periods, while edaphic, topographical, and intrinsic forest variables were more important for the 2017–2018 period. Our findings showed that the carbon increase in CWD was linked to temporal and spatial variables within forests. These results demonstrate the importance of this parameter in the carbon cycle of forest ecosystems and highlight that there should be greater international research efforts to quantify this carbon pool.

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