Calibrating Tropical Forest Coexistence in Ecosystem Demography Models Using Multi‐Objective Optimization Through Population‐Based Parallel Surrogate Search

• Published in: Journal of advances in modeling earth systems Vol. 16; no. 8
• Main Authors: Cheng, Yanyan, Wang, Wenyu, Detto, Matteo, Fisher, Rosie, Shoemaker, Christine
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 01.08.2024; American Geophysical Union (AGU)
• Subjects: Biomass; Calibration; Carbon; Climate change; Coexistence; Deforestation; Demography; Earth; ecosystem demography model; Ecosystems; Environmental changes; Flowers & plants; Forest biomass; Forest management; Forest practices; Forests; Hydrologic models; Hydrology; Logging; multi‐objective optimization; optimization; Optimization algorithms; Precipitation; Recovery; Terrestrial ecosystems; Trees; Tropical forests; Vegetation; Panama
• ISSN: 1942-2466; 1942-2466
• DOI: 10.1029/2023MS004195

Tropical forest diversity governs forest structures, compositions, and influences the ecosystem response to environmental changes. Better representation of forest diversity in ecosystem demography (ED) models within Earth system models is thus necessary to accurately capture and predict how tropical forests affect Earth system dynamics subject to climate changes. However, achieving forest coexistence in ED models is challenging due to their computational expense and limited understanding of the mechanisms governing forest functional diversity. This study applies the advanced Multi‐Objective Population‐based Parallel Local Surrogate‐assisted search (MOPLS) optimization algorithm to simultaneously calibrate ecosystem fluxes and coexistence of two physiologically distinct tropical forest species in a size‐ and age‐structured ED model with realistic representation of wood harvest. MOPLS exhibits satisfactory model performance, capturing hydrological and biogeochemical dynamics observed in Barro Colorado Island, Panama, and robustly achieving coexistence for the two representative forest species. This demonstrates its effectiveness in calibrating tropical forest coexistence. The optimal solution is applied to investigate the recovery trajectories of forest biomass after various intensities of clear‐cut deforestation. We find that a 20% selective logging can take approximately 40 years for aboveground biomass to return to the initial level. This is due to the slow recovery rate of late successional trees, which only increases by 4% over the 40‐year period. This study lays the foundation to calibrate coexistence in ED models. MOPLS can be an effective tool to help better represent tropical forest diversity in Earth system models and inform forest management practices. Plain Language Summary Tropical forests have extremely high levels of tree species diversity, which are estimated to harbor about 50% of the world's terrestrial plant species. Representing tropical forest diversity in Earth system models (ESMs) is important to accurately capture and predict the interactions between tropical forests and environmental changes. But simulating coexistence in ESMs is challenging, as only a limited number of models can simulate forest functional coexistence. In addition, only a few algorithms have been developed to calibrate ecosystem fluxes and tree coexistence concurrently. This study applies an advanced multi‐objective optimization algorithm to calibrate (a) carbon, water, and energy cycle‐related variables and (b) coexistence of two typical tropical forests (i.e., early and late successional forests). Our multi‐objective optimization algorithm can satisfactorily capture the dynamics in tropical forest ecosystems and effectively lead many more model runs to successful and stable coexistence than random sampling. The improved parameterization is further applied to investigate the recovery of forest biomass following various intensities of clear‐cut deforestation scenarios. Our results have important implications for capturing tropical forest diversity as well as their responses to environmental changes and human interventions such as wood harvest. Key Points We calibrate tropical forest coexistence in a state‐of‐the‐art ecosystem demography model using advanced multi‐objective (MO) optimization The MO algorithm is easy to identify objective functions to achieve forest coexistence and much more effective than random sampling We use the calibrated model to analyze the recovery trajectory of forest aboveground biomass under different intensities of deforestation