Keywords
Modeling
Semi-arid
How to Cite
Abstract
Studies on energy exchange in ecosystems are critical for understanding carbon flows amid different vegetation patterns. In semi-arid areas, comprehending the variability in carbon absorption is essential for quantifying and anticipating the impacts of changes in the caatinga ecosystem. This study aims to calibrate and evaluate models for Gross Primary Production (GPP), Net Ecosystem Exchange (NEE), and Ecosystem Respiration (Reco) in the caatinga biome. NEE measurements were obtained and calculated at 30-minute intervals using EddyPro 3.6 software, from raw data measured at 10 Hz. GPP was estimated by partitioning NEE and Reco, all measured in micromoles of CO2 per square meter per second (μmol CO2 m⁻² s⁻¹) using the eddy covariance (EC) tower, installed in a legal reserve at Embrapa Semiárido, in Petrolina, Pernambuco, within a section of the caatinga canopy. Following the measurement of carbon fluxes and ecosystem respiration, field measurements were conducted using a portable FieldSpec HandHeld spectroradiometer to obtain the reflectance of the canopy around the turbulent eddy covariance tower. These measurements were carried out in 2015 in a preserved caatinga area. Multiple linear regression models were developed to estimate carbon fluxes from orbital images, enabling accurate estimation of GPP, NEE, and Reco, using the MODIS/Terra Daily Surface Reflectance product (MOD09GA). The primary results demonstrate the effectiveness of the developed models, particularly the GPP model, which exhibited the best statistical indices (R = 0.97; R² = 0.95; Root Mean Square Error = 0.20). Observations from the EC tower indicated that the models developed to estimate NEE, GPP, and Reco, using visible and near-infrared reflectance data, accurately represented the dry period and effectively captured the phenological aspects of the caatinga ecosystem.
References
ALVARES, C. A.; STAPE, J. L.; SENTELHAS, P. C.; DE MORAES GONÇALVES, J. L.; SPAROVEK, G. Köppen's climate classification map for Brazil. Meteorologische Zeitschrift, Austrália, v. 22, n.6, p.711-728, 2013. https://doi.org/10.1127/0941-2948/2013/0507
BORGES, C. K.; C DOS SANTOS, C. A; CARNEIRO, R. G.; DA SILVA, L. L.; DE OLIVEIRA, G.; MARIANO, D.; SILVA, M. T.; DA SILVA, B. B.; BEZERRA, B. G.; PEREZ-MARIN, A. M.; DE MEDEIROS, S. S. Seasonal variation of surface radiation and energy balances over two contrasting areas of the seasonally dry tropical forest (Caatinga) in the Brazilian semi-arid region, Bethesda, v. 192, p. 524 -542, 2020.
https://doi.org/10.1007/s10661-020-08484-y
CERQUEIRA, D. B.; WASHINGTON FRANCA-ROCHA. Relationship between vegetation types and CO2 flow in the Caatinga Biome: Case study in Rio de Contas - Ba. Proceedings XIII Brazilian Symposium on Remote Sensing, Florianópolis, p. 2413–2419, 2007. Disponível em: http://marte.dpi.inpe.br/col/dpi.inpe.br/sbsr@80/2006/11.16.00.29/doc/2413-2419.pdf . Acesso em: 26 jul. 2024
CHU, X.; HAN, G.; XING, Q.; XIA, J.; SUN, B.; YU, J.; LI, D. Dual effect of precipitation redistribution on net ecosystem CO2 exchange of a coastal wetland in the Yellow River Delta. Agricultural and Forest Meteorology, Guelph, v. 249, p. 286–296, 2018. https://doi.org/10.1016/j.agrformet.2017.11.002
FLORES-RENTERÍA, D.; DELGADO-BALBUENA, J.; CAMPUZANO, E. F.; CURIEL YUSTE, J. Seasonal controlling factors of CO2 exchange in a semiarid shrubland in the Chihuahuan Desert, Mexico. Science of The Total Environment, Amsterdam v. 858, n. 3, p. 159918, 2013. https://doi.org/10.1016/J.SCITOTENV.2022.159918
GAO, Y.; YU, G.; LI, S.; YAN, H.; ZHU, X.; WANG, Q.; S.H.I, P.; ZHAO, L.; LI, Y.; ZHANG, F.; WANG, Y.; ZHANG, J. A remote sensing model to estimate ecosystem respiration in Northern China and the Tibetan Plateau. Ecological Modelling, Texas, v. 304, p. 34–43, 2015. https://doi.org/10.1016/j.ecolmodel.2015.03.001
HAO, Y.; WANG, Y.; MEI, X.; CUI, X. The response of ecosystem CO2 exchange to small precipitation pulses over a temperate steppe. Plant Ecology, v. 2, p. 335–347, 2010. https://doi.org/10.1007/S11258-010-9766-1
IBGE – INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA. Mapas cartográficos: IBGE, 2000. Disponível em: https://www.ibge.gov.br/geociencias/downloads-geociencias.html. Acesso em:10 maio, 2023.
JÄGERMEYR, J.; GERTEN, D.; LUCHT, W.; HOSTERT, P.; MIGLIAVACCA, M.; NEMANI, R. A high-resolution approach to estimating ecosystem respiration at continental scales using operational satellite data. Global Change Biology, v. 20, n. 4, p. 1191–1210, 2014. https://doi.org/10.1111/gcb.12443
JESUS, J. B DE.; KUPLICH, T. M.; BARRETO, Í. D. DE C.; GAMA, D. C. Dual polarimetric decomposition in Sentinel-1 images to estimate aboveground biomass of arboreal caatinga. Remote Sensing Applications: Society and Environment, v. 29, p. 1-10, 2023. https://doi.org/10.1016/J.RSASE.2022.100897
JIA, X.; MU, Y.; ZHA, T.; WANG, B.; QIN, S.; TIAN, Y. Seasonal and interannual variations in ecosystem respiration in relation to temperature, moisture, and productivity in a temperate semi-arid shrubland. Science of the Total Environment, v. 709, p. 136210, 2020. https://doi.org/10.1016/j.scitotenv.2019.136210
KIILL, L. H. P. Characterization of the vegetation of the Embrapa Semiarid legal reserve. 1. Ed. Petrolina: Embrapa Semiárido, 2017. Disponível em: https://ainfo.cnptia.embrapa.br/digital/bitstream/item/172951/1/SDC281.pdf. Acesso em: 26 nov. 2023
LANDIS J. R.; KOCH G. G. The measurement of observer agreement for categorical data. Biometrics. Washington, p. 159 – 174, v. 33, n. 1, 1977. https://doi.org/10.2307/2529310
LEES, K. J.; QUAIFE, T.; ARTZ, R. R. E.; KHOMIK, M.; CLARK, J. M. Potential for using remote sensing to estimate carbon fluxes across northern peatlands – A review. In Science of the Total Environment, Amsterdam, v. 615, p. 857–874, 2018. https://doi.org/10.1016/j.scitotenv.2017.09.103
LI, Q.; XIA, J.; SHI, Z.; HUANG, K.; DU, Z.; LIN, G.; LUO, Y. Variation of parameters in a Flux-Based Ecosystem Model across 12 sites of terrestrial ecosystems in the conterminous USA. Ecological Modelling, Texas, v. 336, p. 57–69, 2016. https://doi.org/10.1016/j.ecolmodel.2016.05.016
LIU, J. F.; CHEN, S. P.; HAN, X. G. Modeling gross primary production of two steps in Northern China using MODIS time series and climate data. Procedia Environmental Sciences, v. 13, p. 742–754, 2012. https://doi.org/10.1016/j.proenv.2012.01.068
LLOYD, J.; TAYLOR, J. A. On the Temperature Dependence of Soil Respiration. Functional Ecology, v. 8 n. 3, p. 315-323, 1994 https://doi.org/10.2307/2389824
MASELLI, F.; VACCARI, F. P.; CHIESI, M.; ROMANELLI, S.; D'ACQUI, L. P. Modeling and analyzing the water and carbon dynamics of Mediterranean macchia by the use of ground and remote sensing data. Ecological Modeling, v. 351, p. 1–13, 2017. https://doi.org/10.1016/j.ecolmodel.2017.02.012
MENDES, K. R.; CAMPOS, S.; MUTTI, P. R.; FERREIRA, R. R.; RAMOS, T. M.; MARQUES, T. V.; REIS, J. S.; VIEIRA, M. M DE L.; SILVA, A. C. N.; MARQUES, A. M. S.; SILVA, D. T. C., SILVA, D. F.; OLIVEIRA, C. P.; GONÇALVES, W. A.; COSTA, G. B.; POMPELLI, M. F.; MARENCO, R. A, ANTONINO, A. C. D.; MENEZES, R. S. C.; SILVA, C. M. S. E. Assessment of SITE for CO2 and Energy Fluxes Simulations in a Seasonally Dry Tropical Forest (Caatinga Ecosystem). Forests, v. 12, p. 86, 2021. https://doi.org/10.3390/F12010086
MIRANDA, R. Q.; NÓBREGA, R. L. B.; MOURA, M. S. B.; RAGHAVAN, S.; GALVÍNCIO, J. D. Realistic and simplified models of plant and leaf area indices for a seasonally dry tropical forest. International Journal of Applied Earth Observation and Geoinformation, v. 85, p. 101992, 2020. https://doi.org/10.1016/j.jag.2019.101992
MORAIS, Y. C. Spatial and temporal variation of gross primary production in the caatinga biome. Tese (Doutorado em Desenvolvimento e Meio Ambiente). UFPE, 2019. Disponível em: https://repositorio.ufpe.br/handle/123456789/33940. Acesso em: 01 nov, 2019.
MOURA, M. S. B.; GALVÍNCIO, J. D. G.; BRITO, L. T. L.; SOUZA, L. S. B.; SÁ, I. I. S.; SILVA, T. G. F. Climate and rainwater in the Semi-Arid. In: BRITO, L.T. L.; MOURA, M. S. B.; GAMA, G.F.B (org.). Potentialities of rainwater in the Brazilian Semi-Arid. Petrolina: Embrapa Semi-Árido, 2007. Disponível em: https://www.alice.cnptia.embrapa.br/bitstream/doc/159649/1/OPB1515.pdf. Acesso em: 15 dez. 2022.
PEREIRA, M. P. S.; MENDES, K. R.; JUSTINO, F.; COUTO, F.; SILVA, A. S.; SILVA, D. F.; MALHADO, A. C. M. Brazilian Dry Forest (Caatinga) Response To Multiple ENSO: the role of Atlantic and Pacific Ocean. Science of The Total Environment, v. 705, p. 135717, 2020. https://doi.org/10.1016/j.scitotenv.2019.135717
PRAKASH. S.; D., SHANKAR, B.; RANJAN PARIDA, B. Machine learning approach to predict terrestrial gross primary productivity using topographical and remote sensing data. Ecological Informatics, v. 70, p. 101697, 2022. https://doi.org/10.1016/j.ecoinf.2022.101697
REICHSTEIN, M.; FALGE, E.; BALDOCCHI, D.; PAPALE, D.; AUBINET, M.; BERBIGIER, P.; BERNHOFER, C.; BUCHMANN, N.; GILMANOV, T.; GRANIER, A.; GRÜNWALD, T.; HAVRÁNKOVÁ, K.; ILVESNIEMI, H.; JANOUS, D.; KNOHL, A.; LAURILA, T.; LOHILA, A.; LOUSTAU, D.; MATTEUCCI, G.; VALENTINI, R. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Global Change Biology, v. 9, n. 11, p. 1424–1439, 2005. https://doi.org/10.1111/J.1365-2486.2005.001002.X
SILVA, J. N. B.; GALVÍNCIO; J. D.; MIRANDA, R. D. Q.; MOURA, M. S. B. Temporal and spatial estimation of the performance of calibrated regression models for carbon fluxes in the Caatinga Seasonally Dry Tropical Forest area. Revista Da Casa Da Geografia de Sobral (RCGS), v. 26, n. 1, p. 183–206, 2024.
https://doi.org/10.35701/rcgs.v26.975
SILVA, J. N. B.; GALVÍNCIO; J. D.; MIRANDA, R. D. Q.; MOURA, M.S.B. Models of Gross Primary Productivity in seasonally dry tropical forest areas, using reflectance data from caatinga vegetation. Brazilian Journal of Physical Geography, v. 14, p. 3775–3784, 2021. https://doi.org/10.26848/rbgf.v14.6.p3775-3784
SILVA, J. N. B.; SILVA, J. L. B.; SANTOS, A. M.; SILVA, A. C.; GALVÍNCIO, J. D. Vegetation Index as a Subsidy in the Identification of Areas With Potential for Desertification. Journal of Environmental Analysis and Progress, v. 4 n. 2, p. 358–367, 2017. https://doi.org/10.24221/jeap.2.4.2017.1469.358-367
SILVA, J. N. B; GALVÍNCIO, J. D.; SILVA, J. L. B; SOARES, G. A. S; SILVA, J. F. B. Analysis of the spatial distribution of carbon fluxes in the caatinga ecosystem. Brazilian Journal of Remote Sensing, v. 123, p. 115–123, 2024. https://doi.org/10.5281/zenodo.11332937
SILVA, P. F; LIMA, J. R. S; ANTONINO, A. C. D, SOUZA, R.; DE SOUZA, E. S., SILVA, J. R. I; ALVES, E. M. Seasonal patterns of carbon dioxide, water and energy fluxes over the Caatinga and grassland in the semi-arid region of Brazil. Journal of Arid Environments, v. 147, p. 71–82, 2017. https://doi.org/10.1016/j.jaridenv.2017.09.003
SILVA, J. N. B.; GALVÍNCIO, J. D.; SILVA, J. L. B.; SOARES, G. A. S.; TIBURCIO, I. M.; BARROS, J. P. F. G. Estimates of carbon sequestration by different methods in forest ecosystems: an approach to the seasonally dry tropical forest (Caatinga). Brazilian Journal of the Environment, v. 93, p. 75–93, 2024. https://doi.org/10.5281/zenodo.11267197
SUN, J.; ZHOU, T. C.; LIU, M.; CHEN, Y. C.; LIU, G. H.; XU, M.; SHI, P. L.; PENG, F.; TSUNEKAWA, A.; LIU, Y.; WANG, X. D.; DONG, S. K.; ZHANG, Y. J.; LI, Y. N. Water and heat availability are drivers of the aboveground plant carbon accumulation rate in alpine grasslands on the Tibetan Plateau. Global Ecology and Biogeography, v. 29, p. 50–64, 2020. https://doi.org/10.1111/geb.13006
TABARELLI, M.; LEAL, I. R.; SCARANO, F. R.; SILVA, J. M. C. Caatinga: legacy, trajectory and challenges towards sustainability. Science and Culture, n. 70, v. 4, p. 25–29, 2018. https://doi.org/10.21800/2317-66602018000400009
THE R FOUNDATION. A: The R Project for Statistical Computing. 2018. Disponível em: https://www.r-project.org/. Acesso em: 10 maio, 2023.
VAIDYA, S.; SCHMIDT, M.; RAKOWSKI, P.; BONK, N.; VERCH, G.; AUGUSTIN, J.; SOMMER, M.; HOFFMANN, M. A novel robotic chamber system allowing to accurately and precisely determine spatio-temporal CO2 flux dynamics of heterogeneous croplands. Agricultural and Forest Meteorology, v. 296, p. 108206, 2021. https://doi.org/10.1016/j.agrformet.2020.108206
WANG, L.; ZHU, H., LIN, A.; ZOU, L.; QIN, W.; DU, Q. Evaluation of the Latest MODIS GPP Products across Multiple Biomes Using Global Eddy Covariance Flux Data. Remote Sensing, n. 9 v. 5, 2017. https://doi.org/10.3390/rs9050418
Este é um artigo de acesso aberto distribuído nos termos da Licença de Atribuição Creative Commons, que permite o uso irrestrito, distribuição e reprodução em qualquer meio, desde que o trabalho original seja devidamente citado.
WU, C.; GAUMONT-GUAY, D.; ANDREW BLACK, T.; JASSAL, R. S.; XU, S.; CHEN, J. M.; GONSAMO, A. Soil respiration mapped by exclusively use of MODIS data for forest landscapes of Saskatchewan, Canada. ISPRS Journal of Photogrammetry and Remote Sensing, v. 94, p. 80–90, 2014.
https://doi.org/10.1016/j.isprsjprs.2014.04.018
XUE, Y.; LIANG, H.; ZHANG, H.; YIN, L.; FENG, X. Quantifying the policy-driven large scale vegetation restoration effects on evapotranspiration over drylands in China. Journal of Environmental Management, n. 345, p. 118723, 2023. https://doi.org/10.1016/j.jenvman.2023.118723
ZHANG, X.; ZHANG, F.; QI, Y.; DENG, L.; WANG, X.; & YANG, S. New research methods for vegetation information extraction based on visible light remote sensing images from an unmanned aerial vehicle (UAV). International Journal of Applied Earth Observation and Geoinformation, v. 78, p. 215–226, 2019. https://doi.org/10.1016/J.JAG.2019.01.001
ZHOU, Y.; LI, X.; GAO, Y.; HE, M.; WANG, M.; WANG, Y.; ZHAO, L., LI, Y. Carbon fluxes response of an artificial sand-binding vegetation system to rainfall variation during the growing season in the Tengger Desert. Journal of Environmental Management, v. 266, p. 110556, 2020. https://doi.org/10.1016/j.jenvman.2020.110556
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright (c) 2023 Joélia Natália Bezerra Silva, Rodrigo de Queiroga Miranda, Gabriel Antonio Silva Soares, Magna Soelma Besera de Moura, Josiclêda Domiciano Galvíncio