Why is Anthropogenic Disturbance Important?
Anthropogenic, or direct human disturbance of tropical forests includes deforestation, as well as forest degradation through activities such as selective logging and understory fires. Deforestation and degradation fragment forests and alter their functioning. These activities are estimated to release about 2.9 petagrams C per year, increasing atmospheric CO2 concentrations. About 30% of tropical forests are recovering from deforestation, representing a major global carbon sink of about 1.6 petagrams C per year, or roughly half of the total C released from deforestation and fire in the tropics.
Anthropogenic disturbances, especially degradation, and subsequent recovery are minimally represented in current models. Key missing processes include demographic, plant trait, and soil biogeochemical changes that alter the trajectory of forest recovery. Also, models lack architecture to implement realistic scenarios of anthropogenic disturbance. We lack long-term benchmark studies of forest degradation and recovery in the tropics because research has been biased towards relatively intact forest ecosystems. NGEE-Tropics is advancing understanding and model representation of anthropogenic disturbance and subsequent recovery of tropical forest structure.
NGEE-Tropics is advancing our understanding and model representation of anthropogenic disturbance and subsequent recovery of tropical forest structure.
In Phase 1 of NGEE-Tropics, we address ANTHROPOGENIC DISTURBANCE by:
- Developing software architecture for the NGEE-Tropics ACME-FATES model to simulate forest degradation.
- Developing data products to evaluate and diagnose model representation of forest degradation and secondary forest dynamics
- Synthesizing knowledge of the distribution and intensity of pantropical forest degradation and secondary forest recovery
- Identifying the priority knowledge gaps regarding biogeochemical, hydrological, demographic, and physiological effects of anthropogenic disturbance on tropical forests
- Testing a novel approach for quantifying forest biomass, leaf traits, and plant water stress using a multi-sensor, airborne, remote-sensing platform enabling analysis of limitations to secondary forest regrowth in Puerto Rico