Too few, too many, or just the right number of estimates? Goldilock’s problem on post-disturbance carbon emissions and removal factors in tropical forests.

Tropical forests are dynamic ecosystems shaped by deforestation, degradation, and recovery processes, with consequences for the carbon cycle. While emissions from deforestation have been well understood and quantified, information on emissions from degradation such as fire, logging, windrow and drought remain relatively poorly quantified, reflecting the complexity of these processes in space and time. Similarly, the carbon recovery potential of degraded forests is understudied compared to secondary forests regrowing after deforestation. Closing these knowledge gaps is crucial to reduce uncertainties in estimates of the tropical carbon budget and for addressing the priorities of international climate policies, which increasingly emphasize the value of protecting and restoring forests, without which we cannot constrain global warming to critical limits.

In recent years, research on carbon emissions and removals in tropical forests has surged, driven in part by advancements in Earth Observation. Here we synthesize these approaches with the aim to bring clarity and advance our understanding on aboveground carbon (AGC) emission and removal factors applicable for tropical moist forests. We contextualise the current studies, highlighting where there are sufficient data estimates to quantify emissions and removals post-disturbance, and where specific kinds of estimates are lacking.

Our synthesis of 66 studies of AGC loss due to disturbance shows emission estimates vary widely across disturbance types: average AGC losses are 3% (range 1–4%) for extreme drought, 27% (range 3–75%) for selective logging, and 52% (range 9–83%) for fire, relative to nearby und previously undisturbed forest. Our analysis underscores the need to account for disturbance severity, frequency and the cumulative effects of interacting disturbances to reduce variability between emissions estimates.

For AGC recovery, our synthesis of 68 studies indicates that degraded forests regained 41–117% of AGC within 20 years relative to undisturbed forests; significantly higher than forests regrowing from deforestation, which regained between 1% and 74% of undisturbed forest AGC. Younger recovering forests (<20 years) exhibit higher absolute regrowth rates, compared to older ones (> 20 years). In the Amazon region, where we have the greatest number of field site and region-specific remote sensing data, we see good agreement between field- and satellite- derived regrowth rate estimates. Remote sensing data therefore has the potential to fill the gaps in our spatial knowledge where field data is limited.

Our results also highlight some of the major gaps that still exist to provide long-lasting and relevant information into the policy and wider carbon budget science domain. Key research needs include: (i) reducing the variability of emission factors within disturbance types by further stratifying according to disturbance severity, frequency and co-occuring disturbances, (ii) addressing the research bias towards the Americas, particularly the Amazon, by expanding studies to areas where there are currently fewer estimates. Finally, we call for a more integrated approach between research focusing on deforestation, degradation and regrowth, recovery and consider these processes as interconnected, co-occurring and influencing each other in space and time.