10.5061/DRYAD.X95X69PNF
Waite, Catherine
0000-0003-3092-5867
University of Nottingham
van der Heijden, Geertje
University of Nottingham
Field, Richard
University of Nottingham
Burslem, David
University of Aberdeen
Dalling, James
Smithsonian Tropical Research Institute; University of Illinois
Nilus, Reuben
Sabah Forestry Department
Rodriguez-Ronderos, M. Elizabeth
National University of Singapore; Yale-NUS College
Marshall, Andrew
University of the Sunshine Coast; University of York
Boyd, Doreen
University of Nottingham
Landscape-scale drivers of liana load across a Southeast Asian forest
canopy differ to the Neotropics
Dryad
dataset
2022
landscape ecology
liana ecology
unmanned aerial system
gap ecology
tropical canopy science
Remote sensing
Boosted Regression Trees
FOS: Earth and related environmental sciences
University of Nottingham
https://ror.org/01ee9ar58
2022-10-12T00:00:00Z
2022-10-12T00:00:00Z
en
453455 bytes
6
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Lianas (woody vines) are a key component of tropical forests, known to
reduce forest carbon storage and sequestration and to be increasing in
abundance. Analysing how and why lianas are distributed in forest canopies
at landscape scales will help us determine the mechanisms driving changes
in lianas over time. This will improve our understanding of liana ecology
and projections of tropical forest carbon storage now and into the future.
Despite competing hypotheses on the mechanisms driving spatial patterning
of lianas, few studies have integrated multiple tree-level biotic and
abiotic factors in an analytical framework. None have done so in the
Palaeotropics, which are biogeographically and evolutionarily distinct
from the Neotropics, where most research on lianas has been conducted. We
used an unoccupied aerial system (UAS; drone) to assess liana load in
50-ha of Palaeotropical forest canopy in Southeast Asia. We obtained data
on hypothesised drivers of liana spatial distribution in the forest
canopy, including disturbance, tree characteristics, soil chemistry, and
topography, from the UAS, from airborne LiDAR, and from ground surveys. We
integrated these in a comprehensive analytical framework to extract
variables at an individual-tree level and evaluated the relative strengths
of the hypothesised drivers and their ability to predict liana
distributions through boosted regression tree (BRT) modeling. Tree height
and distance to canopy gaps were the two most important predictors of
liana load, with relative contribution values in BRT models of 34.60%
45.39% and 7.93% - 10.19%, respectively. Our results suggest that taller
trees were less often and less heavily infested by lianas than shorter
trees, opposite to Neotropical findings. Lianas also occurred more often,
and to a greater extent, in tree crowns close to canopy gaps and to
neighbouring trees with lianas in their crown. Synthesis: Despite their
known importance and prevalence in tropical forests, lianas are not well
understood, particularly in the Palaeotropics. Examining 2,428 trees
across 50-ha of Palaeotropical forest canopy in Southeast Asia, we find
support for the hypothesis that canopy gaps promote liana infestation. Our
finding that liana presence and load declined with tree height, opposite
to well-established Neotropical findings, suggests a fundamental
difference between Neotropical and Southeast Asian forests. Considering
that most liana literature has focused on the Neotropics, this highlights
the need for additional studies in other biogeographic regions to clarify
potential differences and enable us to better understand liana impacts on
tropical forest ecology, carbon storage and sequestration.