Climate trends and soybean production since 1970 in Mississippi: Empirical evidence from ARDL model.

Studying historical response of crops to weather conditions at a finer scale is essential for devising agricultural strategies tailored to expected climate changes. However, determining the relationship between crop and climate in Mississippi (MS) remains elusive. Therefore, this research attempted to i) estimate climate trends between 1970 and 2020 in MS during the soybean growing season (SGS) using the Mann-Kendall and Sen slope method, ii) calculate the impact of climate change on soybean yield using an auto-regressive distributive lag (ARDL) econometric model, and iii) identify the most critical months from a crop-climate perspective by generating a correlation between the detrended yield and the monthly average for each climatic variable. Specific variables considered were maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), precipitation (PT), carbon dioxide emissions (CO2), and relative humidity (RH). All required diagnostic-tests i.e., pre-analysis, post-analysis, model-sensitivity, and assessing the models' goodness-of-fit were performed and statistical standards were met. A positive trend in Tmin (+0.25 °C/decade), and a negative trend in DTR (-0.18 °C/decade) was found. Although Tmax, PT, and RH showed non-significant trends, numerical changes were noted as +0.11 °C/decade, +3.03 mm/decade, and -0.06 %/decade, respectively. Furthermore, soybean yield was positively correlated with Tmin (in June and September), PT (in July and August), and RH (in July), but negatively correlated with Tmax (in July and August) and DTR (in June, July, and August). Soybean yield was observed to be significantly reduced by 18.11 % over the long-term and by 5.51 % over the short-term for every 1 °C increase in Tmax. With every unit increase in Tmin and CO2 emissions, the yield of soybeans increased significantly by 7.76 % and 3.04 %, respectively. Altogether, soybeans in MS exhibited variable sensitivity to short- and long-terms climatic changes. The results highlight the importance of testing climate-resilient agronomic practices and cultivars that encompass asymmetric sensitivities in response to climatic conditions of MS.

U.S. Agro-Climate in 20th Century: Growing Degree Days, First and Last Frost, Growing Season Length, and Impacts on Crop Yields.

Significant air temperature changes have occurred globally during the 20th century, which are spatially variable to a considerable degree and these changes can have substantial implications in agroecosystem productivity. The agroclimate indicators that are responsible in these contexts are first fall frost (FFF), last spring frost (LSF), climatological growing season (CGS) length, and heat accumulation (growing degree days, GDD). We explore spatial and temporal trends associated with these indices across the continental U.S. (CONUS) during 1900-2014 using datasets collected at 1218 sites. On average, FFF has been occurring later (by 5.4 days century-1), and LSF has been occurring earlier (by 6.9 days century-1), resulting in the average lengthening of the CGS (by 12.7 days century-1). Annual GDD has been increasing by 50 °C century-1. We also report trends for agricultural belts and climate regions. We developed relationships between county-level crop yields vs. agroclimate changes and found that all crops (maize, soybean, sorghum, spring wheat, winter wheat, and cotton) responded positively to a lengthened CGS, while responding negatively to increase in GDD, except cotton. Overall, we find that the observed changes in agroclimate, were beneficial for crop yields in the CONUS, albeit some crop and region specific exceptions.

Climate-Driven Crop Yield and Yield Variability and Climate Change Impacts on the U.S. Great Plains Agricultural Production.

Climate variability and trends affect global crop yields and are characterized as highly dependent on location, crop type, and irrigation. U.S. Great Plains, due to its significance in national food production, evident climate variability, and extensive irrigation is an ideal region of investigation for climate impacts on food production. This paper evaluates climate impacts on maize, sorghum, and soybean yields and effect of irrigation for individual counties in this region by employing extensive crop yield and climate datasets from 1968-2013. Variability in crop yields was a quarter of the regional average yields, with a quarter of this variability explained by climate variability, and temperature and precipitation explained these in singularity or combination at different locations. Observed temperature trend was beneficial for maize yields, but detrimental for sorghum and soybean yields, whereas observed precipitation trend was beneficial for all three crops. Irrigated yields demonstrated increased robustness and an effective mitigation strategy against climate impacts than their non-irrigated counterparts by a considerable fraction. The information, data, and maps provided can serve as an assessment guide for planners, managers, and policy- and decision makers to prioritize agricultural resilience efforts and resource allocation or re-allocation in the regions that exhibit risk from climate variability.