Ngute, Alain, Schoeman, David, Pfeifer, Marion, van der Heijden, Geertje, Phillips, Oliver, van Breugel, Michiel, Campbell, Mason, Chandler, Chris, Enquist, Brian, Gallagher, Rachael, Gehring, Christoph, Hall, Jefferson, Laurance, Susan, Laurance, William, Letcher, Susan, Liu, Wenyao, Sullivan, Martin ORCID: https://orcid.org/0000-0002-5955-0483, Wright, Joseph, Yuan, Chunming and Marshall, Andrew (2024) Global dominance of lianas over trees is driven by forest disturbance, climate and topography. Global Change Biology, 30 (1). e17140. ISSN 1354-1013
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Abstract
Growing evidence suggests that liana competition with trees is threatening the global carbon sink by slowing forest recovery from disturbance. Emerging theory based on local and regional evidence further proposes that the competitive success of lianas over trees is driven by interactions between forest disturbance and climate. We present a first global assessment of liana–tree relative performance in response to forest disturbance and climate drivers, using an unprecedented dataset. We analysed 651 samples, worth 26,538 lianas and 82,802 trees, from 556 unique locations worldwide, extracted from 83 publications. Results show that lianas outperform trees (increasing liana-to-tree ratio) when forests are disturbed, under warmer temperatures and lower precipitations, and towards tropical lowlands. We also found that disturbed forests experiencing climate favourable to lianas can be a critical factor hindering forest recovery, as chronosequence data indicate that the liana dominance over trees can persist for decades following disturbances, especially when mean annual temperature is ≥ 23.4°C, precipitation is ≤ 1614 mm and climatic water deficit is ≥ -829 mm. These findings critically emphasise that degraded tropical forests with environmental conditions favouring lianas are the most vulnerable to stalled succession and hence also the highest priority for management attention, with important implications for the global carbon sink.
Impact and Reach
Statistics
Additional statistics for this dataset are available via IRStats2.