Begüm Kaçamak’s research while affiliated with Institute of Research for Development and other places

Lianas are important components of tropical forest diversity and dynamics, yet little is known about the drivers of their community structure and composition. Combining extensive field and LiDAR data, we investigated the influence of local topography, forest structure, and tree composition on liana community structure, and their floristic and functional composition, in a moist forest in northern Republic of Congo. We inventoried all lianas ≥ 1 cm in diameter in 144 20 × 20‐m quadrats located in four 9‐ha permanent plots, where trees and giant herbs were inventoried. We characterized the functional strategies of selected representatives of the main liana taxa using a set of resource‐use leaf and wood traits. Finally, we used complementary statistical analyses, including multivariate and randomization approaches, to test whether forest structure, topography, and tree composition influence the structure, floristic composition, and functional composition of liana communities. The structure of liana communities was strongly shaped by local forest structure, with higher abundances and total basal areas in relatively open‐canopy forests, where lianas competed with giant herbs. Liana floristic composition exhibited a weak spatial structure over the study site but was marginally influenced by the local forest structure and topography. Only forest structure had a weak but significant effect on liana functional composition, with more conservative strategies—higher stem tissue density and lower PO4 leaf concentration and SLA values—in tall and dense forests. Finally, we found evidence of host specificity with significant attraction/repulsion for 19% of the tested liana and tree species associations, suggesting that the unexplained floristic variation may be partly attributed to these host‐species‐specific associations, although the underlying mechanisms behind remain elusive. Overall, our findings demonstrate that liana communities' structure can be much better predicted than their composition, calling for a better understanding of the implications of the large functional diversity observed in liana communities.

Lianas are important components of tropical forest diversity and dynamics, yet little is known about the drivers of their community structure and composition. Combining extensive field and LiDAR data, we investigated the influence of local topography, forest structure and tree composition on liana community structure and composition in a moist forest in northern Republic of Congo. We inventoried all lianas ≥ 1 cm in diameter in 144 20×20 m quadrats located in four 9-ha permanent plots, where trees and giant herbs were inventoried. We characterized the functional strategies of selected representatives of the main liana taxa using a set of resource-use leaf and wood traits. Finally, we used complementary statistical tests, including multivariate and randomization schemes, to test whether forest structure, topography and tree composition influence the structure, floristic, and functional composition of liana communities. The structure of liana communities was strongly shaped by local forest structure, with higher abundances and total basal areas in relatively open-canopy forests, where lianas competed with giant herbs. Liana floristic composition exhibited a weak spatial structure over the study site, but was marginally influenced by local forest structure and topography. Only forest structure had a weak but significant effect on liana functional composition with more conservative strategies—higher stem tissue density and lower PO4 leaf concentration and SLA values—in tall and dense forests. Finally, we found evidence of host specificity with significant attraction/repulsion for 19% of the tested liana and tree species associations, suggesting that the unexplained floristic variation may be partly attributed to these host species-specific associations, although the underlying mechanisms behind remain elusive. Overall, our findings demonstrate that the structure of liana communities can be much better predicted than their composition, calling for a better understanding of the implication of the large functional diversity observed in liana communities.

Lianas are abundant and diverse in tropical forests and impact forest dynamics. They occupy part of the canopy, forming a layer of leaves overtopping tree crowns. Yet, their interaction with trees has been mainly studied from the ground. With the emergence of drone-based sensing, very high-resolution data may be obtained on liana distribution above canopies. Here, we assessed the relationship between common liana ground measurements and drone-determined liana leaf coverage over tree crowns, tested if this relationship is mediated by liana functional composition, and compared the signature of liana patches and tree crowns in our drone images. Using drone platforms, we acquired very high resolution RGB and multispectral images and LiDAR data over two 9-ha permanent plots located in northern Republic of Congo and delineated liana leaf coverage and individual tree crowns from these data. During a concomitant ground survey, we focused on 275 trees infested or not by lianas, for which we measured all lianas ≥ 1 cm in diameter climbing on them (n = 615) and estimated their crown occupancy index (COI). We additionally measured or recorded the wood density and climbing mechanisms of most liana taxa. Contrary to recent findings, we found significant relationships between most ground-derived metrics and the top-of-view liana leaf coverage over tree crowns. Tree crown infestation by lianas was primarily explained by the load of liana climbing on them, and negatively impacted by tree height. Liana leaf coverage over individual tree crowns was best predicted by liana basal area and negatively mediated by liana wood density, with a higher leaf area to diameter ratio for light-wooded lianas. COI scores were concordant with drone assessments, but two thirds differed from those obtained from drone measurements. Finally, liana patches had a higher light reflectance and variance of spectral responses than tree crowns in all studied spectra. However, the large overlap between them challenges the autodetection of liana patches in canopies. Overall, we illustrate that the joint use of ground and drone-based data deepen our understanding of liana-infestation pathways and of their functional and spectral diversity. We expect drone data to soon transform the field of liana ecology.