Linking Drone and Ground-Based Liana Measurements in a Congolese Forest

canopy; Central Africa; competition; remote sensing; strategy; UAV systems; woody vines; Forestry; Ecology; Global and Planetary Change; Nature and Landscape Conservation; Environmental Science (miscellaneous)

Abstract :

[en] 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.

Disciplines :

Environmental sciences & ecology
Phytobiology (plant sciences, forestry, mycology...)

Author, co-author :

Kaçamak, Begüm; AMAP, Univ. Montpellier, IRD, CNRS, CIRAD, INRAE, Montpellier, France ; UPR Forêts et Sociétés, Cirad, France

Barbier, Nicolas; AMAP, Univ. Montpellier, IRD, CNRS, CIRAD, INRAE, Montpellier, France

Aubry-Kientz, Mélaine; AMAP, Univ. Montpellier, IRD, CNRS, CIRAD, INRAE, Montpellier, France

Forni, Eric; UPR Forêts et Sociétés, Cirad, France

Gourlet-Fleury, Sylvie; UPR Forêts et Sociétés, Cirad, France

Guibal, Daniel; Cirad-PERSYST-UPR BioWooEB, Montpellier, France

Loumeto, Jean-Joël; Faculté des Sciences et Techniques, Université Marien Ngouabi, Brazzaville, Democratic Republic Congo

Pollet, Sasha ; Université de Liège - ULiège

Rossi, Vivien; UPR Forêts et Sociétés, Cirad, France ; Plant Systematic and Ecology Laboratory, Department of Biology, Higher Teachers’ Training College, University of Yaoundé I, Yaoundé, Cameroon

Rowe, Nick; AMAP, Univ. Montpellier, IRD, CNRS, CIRAD, INRAE, Montpellier, France

van Hoef, Yorick; UPR Forêts et Sociétés, Cirad, France

Réjou-Méchain, Maxime; AMAP, Univ. Montpellier, IRD, CNRS, CIRAD, INRAE, Montpellier, France

Language :

English

Title :

Linking Drone and Ground-Based Liana Measurements in a Congolese Forest

Publication date :

11 March 2022

Journal title :

Frontiers in Forests and Global Change

eISSN :

2624-893X

Publisher :

Frontiers Media S.A.

Volume :

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://www.frontiersin.org/articles/10.3389/ffgc.2022.803194/full

Funding text :

This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 824074 in form of a prize awarded to BK. It also benefited from financial support from the French National Research Institute for Sustainable Development. The studied experimental site has been settled within the DynAfFor project (French Fund for the Global Environment; grant nos. CZZ1636.01D and CZZ1636.02D), the International Foundation for Science (grant no. D/5822-1), F.R.S-FNRS (grant no. 2017/v3/5/332 – IB/JN – 9500), Nature+ (asbl, Belgium) and the Republic of Congo (OGES-Congo). MR-M was supported by the DESSFOR ANR project (grant no. ANR-20-CE32-0010).

Available on ORBi :

since 17 December 2022

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