Impacts of climate change on water fluxes and soybean growth in southern Brazil

Virnei Silva Moreira, Luiz Antonio Candido, Marcelo Crestani Mota, Geovane Webler, Elisangela Do Prado Oliveira, Debora Regina Roberti

Resumo


This study aims to analyze the consequences of climatic change in the water dynamic and growth soybean in Southern Brazil. Scenarios were created for conditions of a 2 ºC temperature increase, a 20% reduction, and a 50% increase in precipitation rates, representing hot, dry and wet scenarios, respectively. The atmospheric forcing generated were used as input data for the agricultural version of the Integrated Biosphere Simulator model (Agro-IBIS) and simulations were carried out for a soybean growing season in the northwestern Rio Grande do Sul, Brazil. The following variables estimated by Agro-IBIS were analyzed: soil moisture, soybean leaf area index (LAI), evaporation, and transpiration. The results showed that the climatic changes projected by the simulations influence soybean growth in the study area. By increasing the temperature in 2 °C, the Agro-IBIS model indicated the occurrence of shorter crop growth cycles and even more impactful results on the leaf area index, with a 70% reduction in the highest values. Furthermore, a 50% increase in precipitation rate showed positive effects on agriculture, indicated by increased LAI in the reproductive period. On the other hand, a 20% reduction in precipitation has a negative effect, as it exposes the crop to water deficit conditions, impacting soil moisture and decreasing LAI. The soil evaporation is also intensified with increased temperatures due to the higher evaporative demand of the atmosphere and a significant decline in LAI. The transpiration for the hot scenario is more strongly impacted during the vegetative growth stage and leaf senescence.

Palavras-chave


Manejo e Conservação de Água no Solo.

Texto completo:

PDF (English)

Referências


ALLEN, R. G.; PEREIRA, L. S.; RAES, D.; SMITH, M. Crop evapotranspiration: Guidelines for computing crop water requirements. Rome: FAO, 1998. 300 p. (FAO – Irrigation and Drainage Paper, 56).

ALVARES, C. A.; STAPE, J. L.; SENTELHAS, P. C.; GONÇALVES, J. L. M.; SPAROVEK, G. Köppen's climate classification map for Brazil. Meteorologische Zeitschrift, v. 22, n. 6, p. 711-728, 2013.

ATLAS SOCIOECONÔMICO DO RIO GRANDE DO SUL. 6. ed. Porto Alegre: Secretaria de Planejamento, Governança e Gestão - Departamento de Planejamento Governamental, 2021. 203 p.

BALL, J. T.; WOODROW, I. E.; AND BERRY, J. A. A model predicting stomatal conductance and its contribution to the control of photosynthesis under different environmental conditions. In: Biggins J. (ed). Progress in Photosynthesis Research. Springer, Dordrecht: Martinus Nijhoff Publishers, 1987. p. 221-224.

BATTISTI, R. et al. Assessment of crop-management strategies to improve soybean resilience to climate change in Southern Brazil. Crop and Pasture Science, v. 69, n. 2, p. 154-162, 2018(a).

BATTISTI, R.; SENTELHAS, P. C.; BOOTE, K. J. Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil. International Journal of Biometeorology, v. 62, p. 823-832, 2018(b).

BASSU, S. et al. How do various maize crop models vary in their responses to climate change factors. Global change biology, v. 20, n. 7, p. 2301-2320, 2014.

BORTOLOTTO, R. P. et al. Soil carbon dioxide flux in a no-tillage winter system. African Journal of Agricultural Research, v.10, n. 6, p. 450-457, 2015.

CHAVEZ, L. F. et al. Carbon dioxide efflux in a rhodic hapludox as affected by tillage systems in southern Brazil. Revista Brasileira de Ciência do Solo, v. 33, n. 2, p. 325-334, 2009.

COLLATZ, J. G.; GRIVET, C. AND BERRY, J. A. Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: A model that includes a laminar boundary layer. Agricultural and Forest Meteorology, v. 54, n. 2-4, p. 107-136, 1991.

CRAUFURD , P. Q.; WHEELER, T. R. Climate change and the flowering time of annual crops. Journal of Experimental Botany, v.60, n.9, p. 2529-2539, 2009.

CUADRA, S. V. et al. A biophysical model of sugarcane growth. Global Change Biology Bioenergy, v. 4, n. 1, p. 36-48, 2012.

DIAS, H. B.; SENTELHAS, P. C. Evaluation of three sugarcane simulation models and their ensemble for yield estimation in commercially managed fields. Field Crops Research, v. 213, p. 174-185, 2017.

EGLI, D. B. et al. Air temperature during seed filling and soybean seed germination and vigor. Crop Science, v. 45, n. 4, p. 1329-1335, 2005.

EL MAAYAR, M.; SONNENTAG, O. Crop model validation and sensitivity to climate change scenarios. Climate Research, v. 39, n. 1, p. 47-59, 2009.

FARQUHAR, G. D.; VON CAEMMERER, S.; BERRY, J. A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta, v.149, n.1, p. 78-90, 1980.

FARQUHAR, G. D.; SHARKEY, T. D. Stomatal conductance and photosynthesis. Annual Review of Plant Physiology, v. 33, p. 317–345, 1982.

FEHR, W. R.; CAVINESS, C. E. Stages of Soybean Development. Iowa State University, Ames, IA, USA - Special Report 80, 1977. 12 p.

FOLEY, J. A. et al. An integrated biosphere model of land surface processes, terrestrial carbon balance and vegetation dynamics. Global Biogeochemical Cycles, v.10, n. 4, p. 603-628, 1996.

IGLESIAS, A.; ERDA, L.; ROSENZWEIG, C. Climate change in Asia: a review of the vulnerability and adaptation of crop production. Water, Air, and Soil Pollution, v. 92, p. 13-27, 1996.

IPCC – Intergovernmental Panel of Climate Change. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. PACHAURI, R. K. and MEYER, L. A. (eds.). IPCC, Geneva, Switzerland, 2014. 151 p.

KANG, Y.; KHAN, S.; MA, X. Climate change impacts on crop yield, crop water productivity and food security – A review. Progress in natural Science, v. 19, n. 12, p. 1665-1674, 2009.

KORRES, N. E. et al. Cultivars to face climate change effects on crops and weeds: a review. Agronomy for Sustainable Development, v. 36, n.1, p. 1-22. 2016.

KUCHARIK, C. J. et al. Testing the performance of a dynamic global ecosystem model: Water balance, carbon balance and vegetation structure. Global Biogeochemical Cycles, v. 14, n. 3, p. 795-825, 2000.

KUCHARIK, C. J.; BRYE, K. R. Integrated BIosphere Simulator (IBIS) Yield and Nitrate Loss Predictions for Wisconsin Maize Receiving Varied Amounts of Nitrogen Fertilizer. Journal of Environmental Quality, v. 32, n. 1, p. 247-268, 2003.

LIU, L.; BASSO, B. Impacts of climate variability and adaptation strategies on crop yields and soil organic carbon in the US Midwest. Plos One, v.15, n. 1, p. 1-20, 2020

LUDLOW, M. M.; MUCHOW, R. C. Crop improvement for changing climates. In: BUXTON, D. R.; SHIBLES, R.; FORSBERG, R. A.; BLAD, B. L.; ASAY, K. H.; PAULSEN, G. M.; WILSON, R. F. International Crop Science I. Crop Science Society of America, Madison, WI, USA. 1993, cap. 31, p. 247-250.

MARIN, F. R. et al. Climate change impacts on sugarcane attainable yield in southern Brazil. Climatic change, v. 117, n. 1-2, p. 227-239, 2013.

MOREIRA, V. S. et al. Seasonality of soil water exchange in the soybean growing season in southern Brazil. Scientia Agricola, v. 72, n. 2, p. 103-113, 2015.

MOREIRA, V. S. et al. Influence of Soil Properties in Different Management Systems: Estimating Soybean Water Changes in the Agro-IBIS Model. Earth Interactions, v. 22, n. 4, p. 1-19, 2018.

MOSS, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature, v. 463, n. 7282, p. 747-756, 2010.

NOAA - National Oceanic and Atmospheric Administration. Cold & Warm Episodes by Season. Retrieved from: https://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_v5.php. Accessed on February 28, 2022.

RODRÍGUEZ, D. et al. A coffee agroecosystem model: I. Growth and development of the coffee plant. Ecological Modelling, v. 222, n. 19, p. 3626-3639, 2011.

ROSA, S. L. K.; SOUZA, J. L. M. D.; TSUKAHARA, R. Y. Performance of the AquaCrop model for the wheat crop in the subtropical zone in Southern Brazil. Pesquisa Agropecuária Brasileira, v. 55, e01238, 2020.

ROSE, G. et al. Impact of progressive global warming on the global-scale yield of maize and soybean. Climatic Change, v.134, n. 3, p. 417-428, 2016.

ROSENZWEIG, C. et al. Climate change and agriculture: analysis of potential international impacts. American Society of Agronomy, vol. 59, Madison, WI, USA, 1995. 382 p.

SETIYONO, T. D. et al. Leaf area index simulation in soybean grown under near-optimal conditions. Field Crops Research, v. 108, n. 1, p. 82-92, 2008.

SLINGO, J. M. et al. Introduction: food crops in a changing climate. Philosophical Transactions of the Royal Society B, v. 360, n. 1463, p. 1983-1989, 2005.

SOLER, C. M. T.; SENTELHAS, P. C.; HOOGENBOOM, G. Application of the CSM-CERES-Maize model for planting date evaluation and yield forecasting for maize grown off-season in a subtropical environment. European Journal of Agronomy, v. 27, n. 2-4, p. 165-177, 2007.

SOUSA, J. M. et al. Evaluation of the WRF model's ability to represent Amazonian precipitation using different scales. Revista Brasileira de Meteorologia, v. 34, n. 2, p. 255-273, 2019.

STRECK, N. A.; ALBERTO, C. M. Simulation of the impact of climate change on available soil water in wheat, soybean and corn agroecosystems in Santa Maria, RS. Ciência Rural, v. 36, n. 2, p. 424-433, 2006.

TAIZ, L. et al. Plant physiology and development. 6th. ed. Sinauer Associates, Sunderland, CT. 2015. 761 p.

TARDIEU, F. Plant response to environmental conditions: assessing potential production, water demand, and negative effects of water deficit. Frontiers in Physiology, v. 4, n.17, p. 1-11, 2013.

TAYLOR, K. E.; STOUFFER, R. J.; MEEHL, G. A. An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, v. 93, n. 4, p. 485-498, 2012.

VANLOOCKE, A.; BERNACCHI, C. J.; TWINE, T. E. The impacts of Miscanthus×giganteus production on the Midwest US hydrologic cycle. Global Change Biology Bioenergy, v. 2, n. 4, p. 180-191, 2010.

WEBLER, G. et al. Evaluation of a dynamic agroecosystem model (Agro-IBIS) for soybean in Southern Brazil. Earth Interactions, v.16, n. 12, p. 1-15, 2012.

ZANON, A. J. et al. Branches contribution and leaf area index evolution in modern cultivars of soybean. Bragantia, v.74, n. 3, p. 279-290, 2015.




Revista Ciência Agronômica ISSN 1806-6690 (online) 0045-6888 (impresso), Site: www.ccarevista.ufc.br, e-mail: ccarev@ufc.br - Fone: (85) 3366.9702 - Expediente: 2ª a 6ª feira - de 7 às 17h.