Seasonal changes in isoprene emission and deposition in central Amazonia

• Autor(a) principal: ALVES, ELIANE G.
• Data de Publicação: 2018
• Outros Autores: TOTA, JULIO, TURNIPSEED, ANDREW, VEGA BUSTILLOS, JOSE O.W., SANTANA, RAONI A., LOPES, PAULA R.C., CIRINO, GLAUBER G., TAVARES, JULIA V., LOPES, ALINE, NELSON, BRUCE, ROSA, DIOGO, VALE, DALTON, SOUZA, RODRIGO de, GU, DASA, STAVRAKOU, TRISSEVGENI, ADAMS, DAVID, WU, JIN, SALESKA, SCOTT, DIAS-JUNIOR, CLEO, YANEZ-SERRANO, ANA M., KESSELMEIER, JURGEN, KARL, THOMAS, MANZI, ANTONIO, GUENTHER, ALEX, ILEAPS SCIENCE CONFERENCE, 5th
• Tipo de documento: Artigo de conferência
• Título da fonte: Repositório Institucional do IPEN
• Texto Completo: http://repositorio.ipen.br/handle/123456789/29201

Isoprene fluxes vary seasonally with changes in environmental factors as light and temperature, and biological factors as leaf phenology. But, our understanding of isoprene seasonal dependency to these factors is still limited in Amazonia. It has been indicated that the dry season shows higher emissions than the wet season, because there is more light available and higher temperature. Also, leaf phenology was recently suggested to drive ecosystem isoprene emissions, but local seasonal observations were scarce or not available. Here, we present canopy isoprene flux measured in two sites of primary rainforest in central Amazonia and compare to changes in light, temperature, and leaf phenology. The highest emissions were during the dry and dry-to-wet transition seasons, and the wet and the wet-to dry transition seasons revealed net deposition for one site. Leaf phenology, referred as changes in observed mature Leaf Area Index, was the most correlated factor and explained up to 59% of seasonal isoprene emissions. Attempting to represent this with modeling, the MEGAN 2.1 leaf age algorithm was driven by inputs resulted from a leaf demography64 ontogeny model that uses leaf flushing observed in the fields. However, model emissions were overestimated and did not capture the seasonal behavior observed. Using the leaf phenology from the field as inputs for the leaf age algorithm of MEGAN 2.1, improved estimates of the proportion of leaves in different leaf age categories for each site, but did not change the relative isoprene emission capacity used for each age class. This study hightlights the importance of accounting for differential isoprene emission capacity across canopy leaf age classes and of identifying the forest adaptive mechanisms that underly seasonal variation of emission, and potentially deposition, of isoprene in Amazonia.