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WUE and CO2 Estimations by Eddy Covariance and Remote Sensing in Different Tropical Biomes
- Source :
- Remote Sensing, Vol 14, Iss 14, p 3241 (2022)
- Publication Year :
- 2022
- Publisher :
- MDPI AG, 2022.
-
Abstract
- The analysis of gross primary production (GPP) is crucial to better understand CO2 exchanges between terrestrial ecosystems and the atmosphere, while the quantification of water-use efficiency (WUE) allows for the estimation of the compensation between carbon gained and water lost by the ecosystem. Understanding these dynamics is essential to better comprehend the responses of environments to ongoing climatic changes. The objective of the present study was to analyze, through AMERIFLUX and LBA network measurements, the variability of GPP and WUE in four distinct tropical biomes in Brazil: Pantanal, Amazonia, Caatinga and Cerrado (savanna). Furthermore, data measured by eddy covariance systems were used to assess remotely sensed GPP products (MOD17). We found a distinct seasonality of meteorological variables and energy fluxes with different latent heat controls regarding available energy in each site. Remotely sensed GPP was satisfactorily related with observed data, despite weak correlations in interannual estimates and consistent overestimations and underestimations during certain months. WUE was strongly dependent on water availability, with values of 0.95 gC kg−1 H2O (5.79 gC kg−1 H2O) in the wetter (drier) sites. These values reveal new thresholds that had not been previously reported in the literature. Our findings have crucial implications for ecosystem management and the design of climate policies regarding the conservation of tropical biomes, since WUE is expected to change in the ongoing climate change scenario that indicates an increase in frequency and severity of dry periods.
- Subjects :
- gross primary production
evapotranspiration
water use efficiency
Science
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 14
- Issue :
- 14
- Database :
- Directory of Open Access Journals
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.51a28c791b904ed99225df5ada79f145
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/rs14143241