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Compositional Acclimation Can Lessen Tropical Forest Change in Response to Increasing Lightning Frequency: Insights From Simulation Modeling #MMPMID41355757
Medvigy D; Gora EM; Yanoviak SP
Glob Chang Biol 2025[Dec]; 31 (12): e70635 PMID41355757show ga
Lightning frequency in tropical forests has been increasing for decades and lightning is a major agent of forest biomass mortality, but the implications of increased lightning frequency are unclear. Here, we provide a species- and spatially explicit implementation of lightning in a mechanistic forest dynamics model. We evaluated the model's ability to reproduce current-day observations in a Panamanian tropical forest, and the sensitivity of model outputs to plausible changes in lightning frequency. The lightning-enabled model simulated aboveground biomass (AGB), carbon flux, and stem densities that were consistent with observations. As expected, AGB declined with increasing lightning frequency. However, the magnitude of AGB decline was greatly reduced when trees were assigned empirically derived, species-specific lightning tolerances. Changes in species composition weakened the sensitivity of AGB to increasing lightning: the AGB of a small number of large-statured, lightning-tolerant species increased with increasing lightning frequency. In addition, the effect of lightning on AGB tended to saturate at high lightning frequencies because of the combined effect of changes in size structure and composition. Specifically, the number of large, lightning-susceptible trees was relatively small at high lightning frequencies. Overall, this study shows that an empirically informed representation of lightning captures the contemporary effects of lightning on forests, indicates that changes in lightning frequency will change forest AGB, species composition, and size structure, and shows that forests can partially acclimate to higher lightning frequency through changes in composition. Thus, more widespread inclusion of the lightning into global ecosystem models would be an important step toward improving simulations of forest responses to global change.
Glob+Chang+Biol 2025 ; 31 (12): e70635
