WUE and CO2 Estimations by Eddy Covariance and Remote Sensing in Different Tropical Biomes
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Policy and Use License
2.2. Description of Study Area
2.2.1. Cerrado Site
2.2.2. Caatinga Site
2.2.3. Pantanal Site
2.2.4. Amazon Site
2.3. Instrumentation and Data Processing
2.4. Flux Partitioning
2.5. MODIS Data
3. Results
3.1. Meteorological Conditions
3.2. Water and Energy Fluxes
3.3. Carbon Fluxes and WUE
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Forest Type | Slope | R2 | Reference |
---|---|---|---|
Alpine grassland | 1.30 | 0.50 | Zhu et al. [55] |
Alpine grassland | 0.58 | 0.17 | Zhu et al. |
Dry tropical forest | 0.24 | 0.27 | This study |
Floodplain forest | 5.39 | 0.01 | This study |
Primary forest | 5.34 | 0.02 | This study |
Semi-deciduous forest | 0.49 | 0.32 | Danelichen et al. [56] |
Temperate grassland | 1.59 | 0.70 | Zhu et al., 2018 |
Temperate grassland | 0.50 | 0.40 | Zhu et al., 2018 |
Tropical grassland | 0.89 | 0.53 | Zhu et al., 2018 |
Tropical peatland | 0.23 | 0.16 | Wang et al. [57] |
Tropical grassland | 0.91 | 0.63 | Zhu et al., 2018 |
Tropical grassland | 0.89 | 0.53 | Zhu et al., 2018 |
Wetland | 2.40 | 0.31 | This study |
Forest Types | WUE (g C kg−1H2O) | References |
---|---|---|
Wetland | 0.95 | This study |
Boreal treeless wetland | 1.2 | Kuglitsch et al. [58] |
Floodplain forest | 1.61 | This study |
Maritime pine | 1.69 | Berbigier et al. [59] |
Primary forest | 1.82 | This study |
Deciduous broadleaf forest | 1.87 | Wang et al. |
Old-growth forest | 1.83 | Liu et al. [60] |
Evergreen broadleaf forest | 2.35 | Tang et al. [61] |
Conifer plantation forest | 2.53 | Yu et al. [62] |
Deciduous broadleaf forest | 2.57 | Yu et al. |
Eucalypt plantation | 2.87 | Rodrigues et al. [63] |
Ponderosa pine | 2.97 | Law et al. [64] |
Evergreen broadleaf forest | 3.13 | Tang et al. |
Boreal aspen | 3.70 | Krishnan et al. [65] |
Temperate broad-leaved deciduous | 5.0 | Kuglitsch et al. |
Douglas-fir | 5.40 | Ponton et al. [66] |
Dry tropical forest | 5.79 | This study |
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Costa, G.B.; Santos e Silva, C.M.; Mendes, K.R.; dos Santos, J.G.M.; Neves, T.T.A.T.; Silva, A.S.; Rodrigues, T.R.; Silva, J.B.; Dalmagro, H.J.; Mutti, P.R.; et al. WUE and CO2 Estimations by Eddy Covariance and Remote Sensing in Different Tropical Biomes. Remote Sens. 2022, 14, 3241. https://doi.org/10.3390/rs14143241
Costa GB, Santos e Silva CM, Mendes KR, dos Santos JGM, Neves TTAT, Silva AS, Rodrigues TR, Silva JB, Dalmagro HJ, Mutti PR, et al. WUE and CO2 Estimations by Eddy Covariance and Remote Sensing in Different Tropical Biomes. Remote Sensing. 2022; 14(14):3241. https://doi.org/10.3390/rs14143241
Chicago/Turabian StyleCosta, Gabriel B., Cláudio M. Santos e Silva, Keila R. Mendes, José G. M. dos Santos, Theomar T. A. T. Neves, Alex S. Silva, Thiago R. Rodrigues, Jonh B. Silva, Higo J. Dalmagro, Pedro R. Mutti, and et al. 2022. "WUE and CO2 Estimations by Eddy Covariance and Remote Sensing in Different Tropical Biomes" Remote Sensing 14, no. 14: 3241. https://doi.org/10.3390/rs14143241
APA StyleCosta, G. B., Santos e Silva, C. M., Mendes, K. R., dos Santos, J. G. M., Neves, T. T. A. T., Silva, A. S., Rodrigues, T. R., Silva, J. B., Dalmagro, H. J., Mutti, P. R., Nunes, H. G. G. C., Peres, L. V., Santana, R. A. S., Viana, L. B., Almeida, G. V., Bezerra, B. G., Marques, T. V., Ferreira, R. R., Oliveira, C. P., ... Andrade, M. U. G. (2022). WUE and CO2 Estimations by Eddy Covariance and Remote Sensing in Different Tropical Biomes. Remote Sensing, 14(14), 3241. https://doi.org/10.3390/rs14143241