Lianas reduce tree height with negative consequences for carbon storage and growth estimates

Abstract Current evidence suggests that liana (woody vine) competition with trees could be threatening the carbon sink by reducing carbon uptake and storage in tropical forests. Previous studies investigating forest demography in liana removal experiments have, however, assumed similar allometries for trees, regardless of the amount of lianas they support. Yet, recent observations suggest that liana load may alter tree shape and structure, including height, which could result in an underestimation of the liana effects on forest carbon stocks and tree growth. In this study, we used terrestrial laser scanning (TLS) in a liana removal experiment in Gigante Peninsula, Panama, collected 11 years after removal to quantify the liana effect on tree height allometry. Furthermore, we assessed how the liana impact on tree allometry affects the estimates of carbon storage and sequestration. We fitted multiple tree height–diameter allometric relationships with a hierarchical Bayesian approach and combined the best resulting allometric model with inventories to estimate plot‐level biomass stocks and their changes over time. For the same diameter at breast height, we found the trees to be 1.8 m shorter on average in the control plots compared to those in the removal plots, indicating a substantial liana effect on tree height. Converting these height differences through the use of allometric models and inventory data led to a reduction in tree biomass stock estimates in the control plots of 1.8 Mg C ha, −1 while they increased by 2.5 Mg C ha −1 in removal plots 10 years after removal. TLS‐derived allometries led to estimates of tree biomass growth and tree biomass increment, respectively, 27.1% and 21.8% higher than when treatment‐specific height allometries were not accounted for. Synthesis . The use of TLS in a unique experiment site provides strong experimental evidence that lianas change tree allometry, which has repercussions for estimating the capacity of forests to store and accumulate carbon. Our findings highlight the importance of accounting for liana‐induced effects on tree shape and structure when using allometric equations to accurately estimate the impact of lianas on forest carbon dynamics.

Authors

Institutions

Publication Details

Journal
Journal of Ecology
Published
2025-04-18
DOI
https://doi.org/10.1111/1365-2745.70050
Citations
3
Primary Topic
Forest ecology and management
Type
article
Field-Weighted Citation Impact
6.94

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Lianas reduce tree height with negative consequences for carbon storage and growth estimates

Sruthi M. Krishna Moorthy, Barbara D’hont, Kasper Coppieters, Stefan A. Schnitzer et al.
3 citations
Journal of Ecology
Forest ecology and management
6.94
article

Lianas reduce tree height with negative consequences for carbon storage and growth estimates

Sruthi M. Krishna Moorthy, Barbara D’hont, Kasper Coppieters, Stefan A. Schnitzer, Geertje van der Heijden, Félicien Meunier, Hans Verbeeck, Frieke Van Coillie, Xingjian Cao
article en
3 citations

Abstract

Abstract Current evidence suggests that liana (woody vine) competition with trees could be threatening the carbon sink by reducing carbon uptake and storage in tropical forests. Previous studies investigating forest demography in liana removal experiments have, however, assumed similar allometries for trees, regardless of the amount of lianas they support. Yet, recent observations suggest that liana load may alter tree shape and structure, including height, which could result in an underestimation of the liana effects on forest carbon stocks and tree growth. In this study, we used terrestrial laser scanning (TLS) in a liana removal experiment in Gigante Peninsula, Panama, collected 11 years after removal to quantify the liana effect on tree height allometry. Furthermore, we assessed how the liana impact on tree allometry affects the estimates of carbon storage and sequestration. We fitted multiple tree height–diameter allometric relationships with a hierarchical Bayesian approach and combined the best resulting allometric model with inventories to estimate plot‐level biomass stocks and their changes over time. For the same diameter at breast height, we found the trees to be 1.8 m shorter on average in the control plots compared to those in the removal plots, indicating a substantial liana effect on tree height. Converting these height differences through the use of allometric models and inventory data led to a reduction in tree biomass stock estimates in the control plots of 1.8 Mg C ha, −1 while they increased by 2.5 Mg C ha −1 in removal plots 10 years after removal. TLS‐derived allometries led to estimates of tree biomass growth and tree biomass increment, respectively, 27.1% and 21.8% higher than when treatment‐specific height allometries were not accounted for. Synthesis . The use of TLS in a unique experiment site provides strong experimental evidence that lianas change tree allometry, which has repercussions for estimating the capacity of forests to store and accumulate carbon. Our findings highlight the importance of accounting for liana‐induced effects on tree shape and structure when using allometric equations to accurately estimate the impact of lianas on forest carbon dynamics.

Journal of EcologyVol. 113(7)
Marquette University (US), Smithsonian Tropical Research Institute (PA), University of Nottingham (GB), Ghent University (BE), University of Oxford (GB)
National Science Foundation, Smithsonian Institution, Fonds Wetenschappelijk Onderzoek, Smithsonian Tropical Research Institute, Division of Integrative Organismal Systems, Division of Environmental Biology, H2020 European Research Council
Openalex Percentile: Top 4%
Forest ecology and management
6.94
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.