Intra-annual distribution of precipitation in central Amazonia leads to a short mild dry season, which is associated with an increase in irradiance and temperature and a decline in relative humidity; however, the independent effect of each individual climatic variable on tree growth is still under investigation. The objective of this study was to determine how tree growth (inferred from radial stem increment) responds to monthly variations of micrometeorological variables in the central Amazon. During five years (2013-2017) we measured tree growth in 51 trees from nine species and, above the forest canopy, collected environmental data, such as photosynthetically active radiation (PAR), air temperature (T), precipitation, air relative humidity (RH), air vapor pressure deficit (VPD), reference evapotranspiration (ETo), and soil water content (SWC). We used principal component regression to evaluate the effect of micrometeorological variability on tree growth. Mean tree growth across species was responsive to variations in almost all the micrometeorological variables examined, with the exception of mean and minimum temperature, maximum RH, and minimum VPD. Mean tree growth across species increased with increasing precipitation, RHmean, RHmin and SWC, while it decreased with increasing PAR, Tmax, and ETo. It was also shown that an increase in VPDmean and VPDmax has a negative effect on tree growth. These results contribute to improve our understanding of effect of climate variability on tree growth, and shed light on the potential effect of severe droughts in the central Amazon.
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Citation
Antezana-Vera SA, Marenco RA (2021). Intra-annual tree growth responds to micrometeorological variability in the central Amazon. iForest 14: 242-249. - doi: 10.3832/ifor3532-014
Academic Editor
Rossella Guerrieri
Paper history
Received: May 21, 2020
Accepted: Apr 08, 2021
First online: May 21, 2021
Publication Date: Jun 30, 2021
Publication Time: 1.43 months
© SISEF - The Italian Society of Silviculture and Forest Ecology 2021
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This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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