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Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Daily Overview

Session

Biomass and Ecosystem Modelling
Location: Purple Hall
Session Chair: Jerome Chave, Cnrs
Session Chair: Roman Guliaev, DLR e.V.

Presentation 3

5:00pm - 5:20pm

Long-term impacts of forest degradation on biomass: Insights from P-band SAR

Stéphane Mermoz¹, Juan Doblas Prieto¹, Claudio Almeida², Thierry Koleck^3,4, Mariane Souza Reis², Laurent Ferro-Famil^3,5, Cassiano Gustavo Messias², Alexandre Bouvet³, Marta Bottani^3,4,5,6, Thuy Le Toan^1,3

1: GlobEO, Toulouse, France; 2: INPE, São José Dos Campos, Brazil; 3: CESBIO, Toulouse, France; 4: CNES, Toulouse, France; 5: ISAE-Supaéro, Toulouse, France; 6: TéSA, Toulouse, France

Recent studies show that forest degradation partly explain the decline in the forest carbon sink observed by top-down approaches. Tropical forest degradation is estimated to be responsible for 25% of forest carbon emissions, with approximately 20% of tropical forests disturbed by logging activities. In the Brazilian Amazon, CO2 emissions from fires and forest fragmentation reached 88% of gross deforestation emissions (Silva et al., 2021).

Improving knowledge of greenhouse gas emissions from these processes is essential to better understand and seize opportunities to mitigate climate change. However, many aspects of carbon loss associated with forest degradation remain insufficiently understood. Post-perturbation recovery, the impact of recurrent perturbations (especially understory fires and wildfires), and net biomass loss are still subject to active research.

In this paper, we assess the potential of the BIOMASS P-band radar sensor to evaluate the impact of forest degradation on tropical dense forests. In particular, We analyze the long-term impacts of degradation on forest biomass and structure as reflected in P-band backscatter, measuring post-perturbation resilience as a function of perturbation type, recurrence, and edge effects.

We use the extensive Deter system archive over the Brazilian Amazon as reference perturbation data. This dataset, produced by the National Institute for Space Research (INPE), comprises over 300,000 deforestation warnings and 180,000 degradation warnings spanning 2015-2025. This temporal coverage enables a chronosequence approach to build post-perturbation recovery curves for each perturbation type. By leveraging the Deter archive and chronosequence analysis, we aim to characterize recovery trajectories following various perturbations and assess the compounding effects of recurrent disturbances and edge effects on forest biomass. These results are expected to improve carbon emission estimates from forest degradation and enhance understanding of forest resilience in the Brazilian Amazon, with implications for REDD+ monitoring and tropical forest management.