Simulation and observational analysis demonstrates that lianas reduce tree height and carbon storage in tropical forests, highlighting their critical role in global biogeochemical cycles.
Lianas (woody vines) are an iconic feature of tropical forests as they represent on average 25% of all woody stems. Lianas are structural parasites that use the stems of self-supporting plants to reach the top of the canopy. From there, they strongly compete with trees for above- (light) and below-ground (water nutrients) resources. Despite their importance, lianas are completely neglected by terrestrial models. To fill this gap, we developed the first mechanistic representation of lianas in a state-of-the-art vegetation model, the Ecosystem Demography model version 2 (ED2.2). Model simulations revealed the critical role of liana for forest biogeochemical cycles (e.g., tree gross and net productivity decreases when lianas are present with the magnitude of the reduction varying with liana abundance) but also for the energy balance (e.g., lianas increase forest albedo and buffer the microclimate of forest understorey). In addition, we used a combination of terrestrial lidar scanning and a meta-analysis of field and drone observations of tree shape and structure to evaluate the impacts of lianas on tree allometries. In total, we gathered 45,000+ observations of individual tree height, 1.000+ observations of tree crown areas and 150+ tree quantitative structure models over more than 40 sites spread over the tropics, together with liana infestation levels. Those datasets converged to identify a key role of lianas on the shape and structure of tree in tropical forests, independently of the tree species. Liana heavy infestation was responsible for a strong reduction of tree height (-10.7%), crown area (-12.6%), branch length (-45.9%), and overall aboveground carbon stocks (-19.6%). We estimated the global potential liana impact on aboveground tree carbon stocks to be 13.5 Tg over the tropics, or about 7% of the total tropical forest biomass.
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Verbeeck et al. (2024) studied this question.
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