Liana optical traits increase tropical forest albedo and reduce ecosystem productivity

Creators: Meunier, Félicien; Visser, Marco D.; Shiklomanov, Alexey; Dietze, Michael C.; Guzmán Q., J. Antonio; Sanchez‐Azofeifa, G. Arturo; De Deurwaerder, Hannes P. T.; Krishna Moorthy, Sruthi M.; Schnitzer, Stefan A.; Marvin, David C.; Longo, Marcos; Liu, Chang; Broadbent, Eben N.; Almeyda Zambrano, Angelica M.; Muller‐Landau, Helene C.; Detto, Matteo; Verbeeck, Hans

Abstract

Lianas are a key growth form in tropical forests. Their lack of self-supporting tissues and their vertical position on top of the canopy make them strong competitors of resources. A few pioneer studies have shown that liana optical traits differ on average from those of colocated trees. Those trait discrepancies were hypothesized to be responsible for the competitive advantage of lianas over trees. Yet, in the absence of reliable modelling tools, it is impossible to unravel their impact on the forest energy balance, light competition, and on the liana success in Neotropical forests. To bridge this gap, we performed a meta-analysis of the literature to gather all published liana leaf optical spectra, as well as all canopy spectra measured over different levels of liana infestation. We then used a Bayesian data assimilation framework applied to two radiative transfer models (RTMs) covering the leaf and canopy scales to derive tropical tree and liana trait distributions, which finally informed a full dynamic vegetation model. According to the RTMs inversion, lianas grew thinner, more horizontal leaves with lower pigment concentrations. Those traits made the lianas very efficient at light interception and significantly modified the forest energy balance and its carbon cycle. While forest albedo increased by 14% in the shortwave, light availability was reduced in the understorey (−30% of the PAR radiation) and soil temperature decreased by 0.5°C. Those liana-specific traits were also responsible for a significant reduction of tree (−19%) and ecosystem (−7%) gross primary productivity (GPP) while lianas benefited from them (their GPP increased by +27%). This study provides a novel mechanistic explanation to the increase in liana abundance, new evidence of the impact of lianas on forest functioning, and paves the way for the evaluation of the large-scale impacts of lianas on forest biogeochemical cycles.

Additional Information

© 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. Issue Online: 02 December 2021; Version of Record online: 30 October 2021; Accepted manuscript online: 15 October 2021; Manuscript accepted: 07 October 2021; Manuscript revised: 30 September 2021; Manuscript received: 08 June 2021. This research was funded by the European Research Council Starting Grant 637643 (TREECLIMBERS) and the Research Foundation – Flanders (FWO), senior research project G002321N. The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation – Flanders (FWO) and the Flemish Government – department EWI. During the preparation of this manuscript, FM was first funded by the BAEF and the WBI as a research fellow and then by the FWO as a junior postdoc (fellowship 1214720N) and is thankful to these organizations for their financial support. HPTDD was also a BAEF research fellow during the preparation of this manuscript and is as grateful to this organization for its support. MCD was supported by NSF ABI grant 1458021. We are grateful to the whole PEcAn group and the ED2 team for helpful discussions and support related to the functioning of BETY, PEcAn, and ED-RTM. The research carried out at the Jet Propulsion Laboratory, California Institute of Technology, was under a contract with the National Aeronautics and Space Administration. ML was supported by the NASA Postdoctoral Program, administered by Universities Space Research Association under contract with NASA. GatorEye data collection and processing by AMAZ and ENB was supported by the McIntire-Stennis program of the USDA and the University of Florida. Conflict of Interest: None declared. Authors' Contributions: FM, MV, MD, and HV designed the study. FM implemented the workflow, ran the simulations, and processed the results with inputs and support from MD and AS for PEcAn and ED-RTM technical aspects. Some of the co-authors contributed critical data to calibrate or validate the model outputs, including MV and HML (WorldView-3), JAG and ASA (raw spectral data), and ENB and AMAZ (GatorEye LiDAR). All authors contributed to the manuscript and critically revised it. Data Availability Statement: The data that support the findings of this study are openly available in Zenodo at https://doi.org/10.5281/zenodo.5560918, reference number 5560918.

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