Silva, Cláudio Moisés Santos eReis, Layara Campelo dos2020-09-222020-09-222020-06-30REIS, Layara Campelo dos. Produtividade da soja sob diferentes cenários de variabilidade climática na região do MATOPIBA, Brasil. 2020. 260f. Tese (Doutorado em Ciências Climáticas) - Centro de Ciências Exatas e da Terra, Universidade Federal do Rio Grande do Norte, Natal, 2020.https://repositorio.ufrn.br/jspui/handle/123456789/30172Soybean is an important economic product, since it is possible to produce raw materials for food, fuels and industry from it. The characterization of climatic variability provides valuable information for the management of this crop, inasmuch as yield is the result of the interaction of several meteorological factors and the genotype of the cultivar. Thus, the overall goal of this study was to analyze the influence of mechanisms in ocean-atmosphere interface (El NiñoSouth Oscillation and inter-hemispheric thermal gradient in the Tropical Atlantic) on the spatiotemporal variability of soybean productivity in MATOPIBA. Were used: i) daily meteorological data from 1980-2013 (Xavier et al., 2016); ii) (chemical, physical and hydric) properties of the predominant soil class in the area of interest, available on the World Inventory of Soil Emission Potentials (WISE) platform of the International Soil Reference and Information Center (ISRIC); and iii) genetic coefficients of soybean cultivar with Relative Maturity Group adapted to the conditions of the region, available in literature were used. For climate analysis, the following methods were used: i) cluster analysis; ii) Mann-Kendall test; iii) Climdex extreme indices analysis. Water Requirement Satisfaction Index (WRSI) to define agroclimatic risk and productivity was estimated using the DSSAT system (Decision Support System for Agrotechnology Transfer) CROPGRO-Soybean model. In the simulation, planting 9 dates between October and December during 33 agricultural years (1980-2013) were considered for three meteorological scenarios (climatology, favorable-wet and unfavorabledry). Cluster analysis indicated four sub-regions of homogeneous precipitation in MATOPIBA. Extreme indices analysis showed significant changes. Most changes were in temperature indicators. Nearby areas (CI and CII) showed significant opposite trends for precipitation indices. Different meteorological scenarios can alter precipitation spatio-temporal and agroclimatic risk. In the favorable-wet scenario, there was greater probability of an increase in yield and a greater favorable window for sowing soybean, while the opposite is true. However, considering the unfavorable-dry scenario, in some areas the reduction in yield losses will depend on the chosen planting date. This study will guide decision making by the productive sector considering climatic effects on soybean yield in MATOPIBA, thus allowing control in area expansion in benefit of climate regulating ecosystem services preservation.Acesso AbertoENOSAtlântico tropicalAgrometeorologiaTendênciasClimdexdoctoralThesis