Reduced-impact logging shortens carbon recovery time in eastern Amazonian forests

Selective logging alters the ecological processes that govern aboveground carbon (AGC) dynamics in tropical forests. We evaluated AGC recovery over a 30-year period (1994-2023) using 73.5 ha of permanent sample plots in Paragominas, Pará, Brazil. Our study compared three management regimes: an unlogged control, Reduced Impact Logging (RIL), and Conventional Logging (CL). We fitted time-series growth models (GMs) to three key components: surviving trees (AGC_S, Mg C ha^-1), recruitment (AGC_R, Mg C ha^-1 yr^-1), and mortality (AGC_M, Mg C ha^-1 yr^-1). These components were integrated to estimate net carbon growth (AGC_netgrowth) and the treatment effect on carbon change (eChange). Post-logging AGC recovery was substantially faster under RIL (∼9 years) than under CL (∼32 years). Average net carbon growth was higher in RIL plots, reaching ∼1.67 Mg C ha^-1 yr^-1, highlighting efficiency of low-impact practices in carbon recovery. RIL net growth was driven by surviving-tree growth (∼32% higher stocks after 30 years), recruitment (∼26% higher, up to ∼1.48 Mg C ha^-1 yr^-1), and lower mortality (∼14% lower early post-logging). Relative to the control, RIL showed greater eChange (∼0.46 Mg C ha^-1 yr^-1 at 30 years), whereas CL showed lower recruitment. Our findings demonstrate that AGC recovery trajectories are governed by the interplay between tree survival, recruitment, and mortality, with logging intensity and technique strongly modulating these processes. From a management perspective, adopting RIL accelerates carbon recovery and enhances net post-harvest accumulation, providing a viable strategy to reconcile timber production with climate change mitigation in Amazonian forests.