Leaf phenology as one important driver of seasonal changes in isoprene emissions in central Amazonia

• Main Authors: E. G. Alves, J. Tóta, A. Turnipseed, A. B. Guenther, J. O. W. Vega Bustillos, R. A. Santana, G. G. Cirino, J. V. Tavares, A. P. Lopes, B. W. Nelson, R. A. de Souza, D. Gu, T. Stavrakou, D. K. Adams, J. Wu, S. Saleska, A. O. Manzi
• Format: Article
• Language: English
• Published: Copernicus Publications 2018-07-01
• Series: Biogeosciences
• Online Access: https://www.biogeosciences.net/15/4019/2018/bg-15-4019-2018.pdf

<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>² = 0.59, <i>p</i> &lt; 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>² = 0.52, <i>p</i> &lt; 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>