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Background: Logged forests cover four million square kilometres of the tropics. Restoration of logged tropical forests is hailed as a nature-based solution to the interlinked climate and biodiversity crises, but there are concerns that recovery may be hampered by increasingly severe El Niño Southern Oscillation (ENSO) droughts.

Hypothesis: That early successional woodlands would be more heavily impacted by drought than later-successional woodlands, and would be slow to recover once the rains return. Also that riparian forests, with greater access to soil water, would be less affected by ENSO events.

Method: We use repeated airborne surveys (LiDAR and photogrammetry) to map canopy height growth and tree mortality over 100 hectares of secondary forest in Indonesia. The timing of the surveys (in 2014, 2017 and 2018) allowed us to assess the impact of a severe ENSO drought (2015-2016) on forest dynamics and subsequent recovery processes, providing insights into forest resilience to climate change.

Results: Early-successional forest experienced a ~50 % loss of canopy height and 90 % of established trees appear to have died in response to the drought, but taller canopies showed greater resistance. Riparian forests, with greater access to soil water, were less impacted by the drought than forests further away from the rivers. In the post-drought period, we observed strong recovery in height growth, particularly in the early-successional stands.

Conclusion: This study shows that the height growth of recovering tropical forests was surprisingly resilient to the severe ENSO event, suggesting the benefits of these nature-based solutions could endure as the climate warms.

Keywords:

Forest, resistance, resilience, ENSO, Lidar, RGB imagery, Indonesia

David Coomes, Jonathan Williams, Tom Swinfield, Elva Gemita

Presentation within symposium:

S-23 Emerging uses of large-scale remote sensing in tropical forest monitoring

Applications of airborne LiDAR and RGB imagery to track the impacts of climate change on forests

-Review-

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