Leaf phenology as one important driver of seasonal changes in isoprene emissions in central Amazonia
<p>Isoprene fluxes vary seasonally with changes in environmental factors (e.g., solar radiation and temperature) and biological factors (e.g., leaf phenology). However, our understanding of the seasonal patterns of isoprene fluxes and the associated mechanistic controls is still limited, es...
Main Authors: | , , , , , , , , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2018-07-01
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Series: | Biogeosciences |
Online Access: | https://www.biogeosciences.net/15/4019/2018/bg-15-4019-2018.pdf |
Summary: | <p>Isoprene fluxes vary seasonally with changes in environmental factors (e.g.,
solar radiation and temperature) and biological factors (e.g., leaf
phenology). However, our understanding of the seasonal patterns of isoprene
fluxes and the associated mechanistic controls is still limited, especially in
Amazonian evergreen forests. In this paper, we aim to connect intensive,
field-based measurements of canopy isoprene flux over a central Amazonian
evergreen forest site with meteorological observations and with tower-mounted camera leaf phenology to improve our understanding of patterns and causes
of isoprene flux seasonality. Our results demonstrate that the highest
isoprene emissions are observed during the dry and dry-to-wet transition
seasons, whereas the lowest emissions were found during the wet-to-dry
transition season. Our results also indicate that light and temperature cannot totally explain isoprene flux seasonality. Instead, the camera-derived
leaf area index (LAI) of recently mature leaf age class (e.g., leaf ages of
3–5 months) exhibits the highest correlation with observed isoprene flux
seasonality (<i>R</i><sup>2</sup> = 0.59, <i>p</i> < 0.05). Attempting to better represent
leaf phenology in the Model of Emissions of Gases and Aerosols from Nature
(MEGAN 2.1), we improved the leaf age algorithm by utilizing results from the
camera-derived leaf phenology that provided LAI categorized into three
different leaf ages. The model results show that the observations of
age-dependent isoprene emission capacity, in conjunction with camera-derived
leaf age demography, significantly improved simulations in terms of seasonal
variations in isoprene fluxes (<i>R</i><sup>2</sup> = 0.52, <i>p</i> < 0.05). This study
highlights the importance of accounting for differences in isoprene emission
capacity across canopy leaf age classes and identifying forest adaptive
mechanisms that underlie seasonal variation in isoprene emissions in
Amazonia.</p> |
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ISSN: | 1726-4170 1726-4189 |