@Article{StarkESLSLACO:2015:LiCaLe,
author = "Stark, Scott C. and Enquist, Brian J. and Saleska, Scott R. and
Leitold, Veronika and Schietti, Juliana and Longo, Marcos and
Alves, Luciana F. and Camargo, Plinio B. and Oliveira, Raimundo
C.",
affiliation = "{University of Arizona} and {University of Arizona} and
{University of Arizona} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Instituto Nacional de Pesquisas ~ da
Amazonia (INPA)} and {Harvard University} and {Instituto
Agronomico de Campinas (IAC)} and {Universidade de S{\~a}o Paulo
(USP)} and {Embrapa Amaz{\^o}nia Oriental}",
title = "Linking canopy leaf area and light environments with tree size
distributions to explain Amazon forest demography",
journal = "Ecology Letters",
year = "2015",
volume = "18",
number = "7",
pages = "636--645",
month = "July",
keywords = "Amazon forest,canopy plasticity,canopy structure,forest
dynamics,leaf area profiles,LiDAR,light competition,metabolic
scaling theory,remote sensing,tree demography.",
abstract = "Forest biophysical structure the arrangement and frequency of
leaves and stems emerges from growth, mortality and space filling
dynamics, and may also influence those dynamics by structuring
light environments. To investigate this interaction, we developed
models that could use LiDAR remote sensing to link leaf area
profiles with tree size distributions, comparing models which did
not (metabolic scaling theory) and did allow light to influence
this link. We found that a light environment-to-structure link was
necessary to accurately simulate tree size distributions and
canopy structure in two contrasting Amazon forests. Partitioning
leaf area profiles into size-class components, we found that
demographic rates were related to variation in light absorption,
with mortality increasing relative to growth in higher light,
consistent with a light environment feedback to size
distributions. Combining LiDAR with models linking forest
structure and demography offers a high-throughput approach to
advance theory and investigate climate-relevant tropical forest
change.",
doi = "10.1111/ele.12440",
url = "http://dx.doi.org/10.1111/ele.12440",
issn = "1461-023X",
language = "en",
urlaccessdate = "27 abr. 2024"
}