1. Introduction
Soybean (
Glycine max (L.) Merrill) is the main rainfed crop that can be cultivated in a wide range of latitudes [
1]. In recent decades, the soybean has gained great importance in the global market and has become an important agricultural commodity due to the increase in its consumption as a staple food. This increase has been greatly induced by the growing global demand for food [
2]. In traditional Asian cuisine, soy has been used for thousands of years. In Western countries, it was introduced about a hundred years ago and has recently been used mainly for the production of substitute foods in vegetarian diets (meat analogues and milk replacers), due to its high protein content [
3]. To meet the growing worldwide demand for staple foods, including soybeans, crops depend on vast areas and enormous amounts of water resources [
2,
4].
In this context, the soybean became an extremely important product for Brazil’s economy by the end of the 1960s. In the mid-1970s, its increasing production boosted investments in technology by producers and the government in order to adapt it to Brazilian conditions. Until the mid-1970s, the three states of Southern Brazil—a humid subtropical zone [
5]—accounted for approximately 80% of the national production. Throughout the 1980s and 1990s, production expanded towards central-west Brazil, and also towards the states of Minas Gerais, Bahia, Maranhão, Piauí, Tocantins, and Amazônia, in the tropical zone [
5,
6].
This expansion was crucial for Brazil to reach the second global position in production and exportation of this commodity, accounting for 32.4% of total global production, with almost 115 million tons, occupying an area of 35.8 million hectares, in the 2018/19 crop year, according to the Brazilian National Supply Company [
7]. In light of this expansion scenario, the region that covers part of the states of MAranhão, TOcantins, PIauí, and BAhia (MATOPIBA) stands out. This region has a warm climate all year round, a well-defined wet season, and highly homogeneous spatial and temporal rainfall patterns. These characteristics led to the intensification of agricultural activities, making the region currently the main frontier for new agribusiness investments in Brazil [
8,
9,
10]. In crop year 2018/19, MATOPIBA was responsible for approximately 11% of the national production of soybeans, which corresponds to 13.3 million tons [
7].
However, the increase in soybean yield is subject to risks associated with climate variability and several studies indicate impacts on yield as well as a new geography of production due to climate change [
11,
12,
13,
14]. Regarding the influence of climate variability on soybean production, studies show that the El Niño–Southern Oscillation (ENSO) is the most investigated large-scale phenomenon. The alternation of its warm (El Niño) and cold (La Niña) phases displaces the ascending and descending branches of the Walker’s circulation and has a direct influence on the hydrological and thermal regimes in several regions of South America and Northeast Brazil [
15,
16,
17,
18], being responsible for severe agriculture losses in many regions of the globe [
19,
20,
21]. In Brazil, the areas most affected by the ENSO are the eastern Amazon (tropical zone), northern portion of Northeast Brazil (tropical climate with dry winter—Aw, according to Köppen’s classification [
5]), and the extratropical zone of South Brazil. In the Northeast and North Brazil, ENSO warm phases are usually associated with the occurrence of droughts while during its cold phases there is an increase in precipitation [
22,
23,
24,
25].
In addition, variations in sea surface temperature (SST) in the Tropical Atlantic modulate the north–south displacement of the Intertropical Convergence Zone, which also plays an important role in the occurrence of rainfall over the North and Northeast regions of Brazil [
26,
27,
28]. Studies show that the ENSO and the variability of Tropical Atlantic SST directly affect agricultural activities [
29,
30,
31,
32] due to their impact on weather conditions, especially rainfall intensity and air temperature. Crop models can be a useful tool to assess the influence of climatic and other environmental factors on the development and yield of a crop [
33,
34], as shown by several studies in Brazil for soybeans [
35,
36,
37,
38].
The interactions between rainfall, solar radiation, air temperature, and genotype–environment parameters are of great importance in determining the best development condition for soybean crops regarding yield [
39,
40]. These interactions can be impacted when large-scale atmospheric–oceanic phenomena are taken into consideration, limiting yields [
41,
42,
43,
44] due to the increase in air temperature and alternating rainfall patterns which affect the development of the crop. According to references [
45,
46], under moderate or intense water shortage, soybean crops usually accelerate maturation and shorten the pod-filling period, which may hamper productivity as reported by reference [
47]. Furthermore, severe water deficit (mainly during the critical period of flowering and pod-filling) reduces leaf expansion and leaf area, and accelerates senescence, altering the interception of solar radiation, and reducing carbon dioxide uptake and photosynthesis rate [
48,
49,
50]. These issues may be further amplified if air temperature increases at the same time [
51]. Thus, considering the vulnerability of soybeans to water deficit conditions and extreme temperatures [
37,
47,
52,
53], there is a clear need to determine its best sowing period, taking into account the assessment of risks to yield [
37,
54,
55,
56,
57], especially when the region is under the influence of large-scale atmospheric phenomena. Studies on the influence of climate variability on soybean yield in producing regions of Brazil are scarce, as reported by reference [
44]. However, there are no studies aimed at identifying these characteristics under the influence of different large-scale atmospheric circulation mechanisms, notably the combination of Atlantic and Pacific climate variability drivers, which allows a better understanding of the modulation of climate parameters.
Therefore, the objective of this study was to analyze the influence of large-scale atmospheric–oceanic mechanisms on the spatial and temporal variability of soybean yield in MATOPIBA, from the perspective of favorable and unfavorable climatic conditions to the occurrence of rainfall, in order to determine the best sowing period regarding climate variability. To this end, we used objective criteria for the definition of these scenarios, based on the occurrence of warm and cold phases of the ENSO and the interhemispheric gradient of SST in the Tropical Atlantic (also known as the Atlantic Meridional Mode). In addition, we analyzed the temporal variability of different meteorological factors and delimited areas at agroclimatic risk given the probability of occurrence of water deficits during the most critical period for soybean cultivation (flowering/pod-filling), considering different meteorological scenarios.
Thus, we expect to provide valuable information for the elaboration of public policies, agricultural planning, guidelines for exportation, research, changes in production models, definitions for the access to agricultural credit and insurance, and adaptation measures for soybean cultivars in the MATOPIBA region.
4. Discussion
The results obtained in this study show that large-scale atmospheric–oceanic mechanisms in the Pacific and Atlantic oceans play a fundamental role in the alternation between dry and wet years over the MATOPIBA region, as well as in the spatial coverage of drought, which is in agreement with recent analyses [
105]. The higher rainfall rates observed in the favorable (wet) years are mainly related to a better distribution of rains in the course of the wet season and not to the occurrence of excess rainfall in a few months (January and February). The maximum values observed in these months during dry years are possibly associated with extreme rainfall events in Northeast Brazil and in the Cerrado areas, which have been documented in recent studies [
106,
107].
The results of the trend analysis point out that the soybean sowing seasons in the MATOPIBA region, from the 1980s on, are increasingly exposed to higher temperatures, with a sharp increase in exposure to climate risk, consistent with the analyses performed in references [
23,
59,
107,
108,
109] in areas with agricultural potential in Brazil. The increase in air temperature causes physiological damage to soybean plants, which is further accentuated by the occurrence of water deficits [
23,
54]. In addition, this increase shortens the crop cycle due to the faster accumulation of energy (growing degree-day—GDD) [
110]. Regarding precipitation, the results corroborate the studies in references [
107,
111] which show no trends in precipitation rates in several regions of the North and Northeast of Brazil.
For much of the region, the exposure of soybeans to the risk caused by water deficit is minimized with the establishment of the wet season (late October to mid-November). These results are consistent with several studies [
39,
40,
55,
112,
113,
114,
115] that demonstrated that the amount of rainfall is positively correlated with the WRSI, contributing to the reduction of yield loss due to the water deficit.
In the wet years, low-risk areas were more frequent in the central portion of the region, regardless of the sowing date. In addition, there was a decrease in high-risk areas in the northern portion of the region for sowings taking place in the month of November. This situation is associated with the increase in the total volume of rainfall in the region as identified in previous studies [
26,
69,
70,
71], which show that rainfall in most of Northeast Brazil is modulated by the combination of the effects of ocean–atmosphere interaction mechanisms in the Pacific and Atlantic oceans. In contrast, in dry years, there was an increase in areas with high-risk patterns, mainly in the northern portion of the region, corroborating the references [
116,
117] which verified significant correlation patterns between the hot phase of the ENSO and the seasonal rainfall regime in South America, particularly in the northern portion of Northeast Brazil.
Considering the achievable yield of soybean crops, the simulated results showed a certain homogeneity in the region, basically due to climatic conditions, with a regular distribution of rainfall during the sowing season (October to April), typical of the “Aw” climate type according to the Köppen classification [
5]. Based on the two contrasting climatic scenarios (wet and dry), it could be noted that the region faces yield losses in dry years and yield increases in wet years, which is more clearly observed in the locations in the northern portion of the region, which in turn is consistent with the results of the agroclimatic risk delimitation. In addition, it was found that yield varied according to water deficit conditions during the flowering/pod-filling phase in the 10 analyzed locations, corroborating the studies in references [
47,
62,
118].
In the central-eastern region of MATOPIBA, more precisely in the Balsas (MA) and Uruçuí (PI) locations, there is an increase in soybean yield during favorable (wet) conditions, with a larger best sowing window. Alternatively, in the dry years, there is a shortening of this window, agreeing with the study in reference [
44]. It should be noted that the reduction in soybean yield during unfavorable weather conditions may be aggravated by the reduction in rainfall rates and by the increase in air temperature [
16,
119,
120]. The severity of droughts is more pronounced when the hot phase of the ENSO is associated with the occurrence of negative SST anomalies in the South Atlantic—dry scenario [
26,
28,
120,
121]. Meteorological droughts can be devastating for soybean cultivation, being amplified by the combination of low rainfall and warmer temperatures, damaging the physiology of the plants [
23,
99,
122,
123], and impacting soil moisture due to the increase in crop evapotranspiration [
124].
Although results are more positive for the wet years, some exceptions were clearly observed in the southeastern part of the region (São Desidério/BA and Serra do Ramalho/BA), when positive effects on yield were identified during unfavorable (dry) years. This result highlights the importance of adjusting the sowing date in order to optimize the success of yield by choosing the period with the highest water availability for the development of the crop [
12,
114,
118,
125].
Results are less conclusive for the central-western portion of the region (Pedro Afonso/TO and Figueirópolis/TO), where all analyzed sowing dates provide positive results for soybean yield in all three weather conditions. This indicates that large-scale climate variability does not necessarily lead to negative anomalies in the meteorological conditions over this region and, consequently, does not compromise final soybean yield. It was possible to observe that the ideal condition for the success of yield in this region is related to the availability of rainfall, demonstrated by its regular distribution during the period of soybean cultivation, from October to April [
5], and confirmed by the results of water availability in these locations. Favorable climatic conditions minimize the effects of limiting factors for soybean cultivation, optimizing the development of the crop by improving its vegetative and productive capacity [
126,
127].
Regarding the performance of the model, results were similar or better than those obtained in other studies, such as references [
67,
68,
128], in which RMSE values of 226 to 650 kg ha
−1, 201 to 413 kg ha
−1, and 548 kg ha
−1, respectively, were found.
5. Conclusions
The DSSAT/CROPGRO-Soybean model showed a good predictive capacity, confirmed by the statistical parameters, indicating high applicability for the environmental conditions of MATOPIBA. The approach used in this study showed that the effects of climate variability and the interactions between different sowing dates and genotype–environment characteristics of the analyzed region can result in different levels of yield, as well as regional patterns of agroclimatic risk, depending on the probability of occurrence of water deficit in the flowering/pod-filling phase.
The trends of yield associated with large-scale atmospheric–oceanic mechanisms varied according to the sowing dates and locations, since the choice of the best sowing period may minimize the effects of climate variability. In addition, strong evidence was found regarding the reduction of yield as a function of the intensity of the water deficit. In relation to the sowing dates, it was verified that in most of the region, yield gains are more substantial for the sowings carried out from the month of November to the beginning of December.
In general, during the wet years, there was a clear tendency for an increase in the average values of achievable yield. In the dry scenario, these values were lower. Among the analyzed areas, the northern region of MATOPIBA was the most affected, registering positive and negative impacts (wet and dry scenarios, respectively) in all the analyzed dates. In the central-eastern and southeastern portions of the MATOPIBA region, the effects of climate variability were clear and directly related to the choice of the sowing window, with a shortening and a delay of the best window considering the dry scenario. Furthermore, it was found that the delay of the best sowing window in the southeast region increases the yield values in relation to other meteorological conditions, i.e., when choosing the best sowing period, the potentially negative anomalies produced by the dry scenario conditions may generate positive effects in soybean yield in this area. In the central-eastern portion of the MATOPIBA region, the effects of the analyzed weather conditions were barely noticeable, since variations in the yield behavior were small in all the sowing windows.
These results are unprecedented as they are the first to address the influence of large-scale mechanisms in the Pacific and the Atlantic oceans on the achievable yield of soybeans in an area of great agricultural potential, currently considered the main frontier for new investments in large-scale agriculture in Brazil. In general, most farmers in the MATOPIBA region sow at the onset of the wet period (mid-October to November) in order to try to minimize the effects of climate variability on productivity. However, our results show that these effects, particularly in the unfavorable-dry scenario, may be minimized by selecting the best sowing window (mid-December). Furthermore, no negative impacts on productivity were observed in some locations, regardless of the climate variability scenario. Thus, the study provides relevant information that can support and guide agribusiness agents (producers, researchers, credit institutions, policy makers) in making decisions for the better planning of their activities; in adopting strategic actions that take into account climate conditions, especially the occurrence of rainfall; and finding the best sowing window and location as a way to improve crop management for successful yield.
In
Figure 9, we present the best sowing windows for soybean considering the three analyzed meteorological conditions in the different MATOPIBA locations.