Plant phenology becoming a focus of current research worldwide is a sensitive indicator of global climate change. To understand observed soybean phenology and explore its climatic determinants in frigid region (Northeast China and northeast in Inner Mongolia), we studied the phenological changes of soybean [Glycine max (L.) Merr.] for the frigid region during 1981–2017, then analyzed the contribution of major causal climate factors to phenology based on multiple stepwise regression. Altogether, the average temperature from sowing to maturity (WGP) was significant increasing, accumulated precipitation and sunshine hours were decreasing. More than 50% of observations showed delays in sowing, emergence and maturity stage and short durations of sowing to flowering (VGP), flowering to maturity (RGP) and sowing to maturity (WGP). The late sowing was getting the following phenological timing backward, but the flowering and maturity delaying trends were much less than that of sowing timing due to the warming accelerated growth of soybean. Detailed analysis indicated mean temperature and accumulated precipitation of the 1–3 months immediately preceding the mean emergence, flowering and maturity dates influenced the phenological timing in higher latitude areas (HLJ and FL), while in JL and LN, accumulated precipitation and sunshine hours(replacing mean temperature) were the climatic determinants. These results brought light the importance of research and policy to support strategies for adaptation to local condition under the climate change.

Situated at middle-to-high latitudes with limited thermal resources, Northeast China is the primary maize-producing region in China. It is also one of the regions most significantly impacted by climate change. Given the persistent impact of climate change, it is crucial to elucidate the effects of the varying thermal conditions and low temperatures for different sowing dates on the growth, development, and grain maturity of spring maize. To ensure secure maize production and disaster prevention, choosing the optimal sowing time for spring maize holds significant implications for the judicious utilization of climatic resources, risk mitigation, and the provision of meteorological guidance. Moreover, it can serve as a technical reference for relevant departments to conduct climate evaluation, disaster monitoring, prediction, and assessment, as well as impact analysis of corn production safety. Additionally, it can provide meteorological evidence to ensure food security and promote the sustainable development of modern agriculture. An interval sowing experiment of spring maize was conducted in Harbin in the north of Northeast China. Two varieties were used in the experiment. Four sowing dates were set, and the interval between adjacent sowing dates was 10 days. The local perennial sowing time, 5 May, was set as the second sowing date, with one date set later and two dates set earlier. During the experiment, the growth process, grain dry matter, seed moisture content, yield components, and temperature of spring maize were observed. The impact of temperature conditions on maize growth and yield formation was analyzed in this paper through mathematical statistics, which further led to the establishment of a monitoring and evaluation model for assessing the effect of thermal conditions and temperature on maize. The results showed that the growth rate of spring maize was closely related to temperature. When the average temperature, minimum temperature, and maximum temperature increased by 1 °C, the average emergence rate increased by 1.05%, 0.99%, and 1.07%, respectively, and the average vegetative growth rate increased by 0.16%, 0.16%, and 0.09%, respectively. The change rate of ≥10 °C active accumulated temperature was significantly correlated with the change rate of the dry weight of the grain kernel, which conformed to the quadratic equation of one variable. The temperature influence coefficients of different sowing dates varied from 1.0% to 1.7%. The relationship between the accumulated values of 10 ℃ active accumulated temperature and the grain moisture content of spring maize was a logarithmic function. From 10 to 50 days after anthesis, the effect of temperature can explain about 95% of the change in grain moisture content. After physiological maturity, the effect of thermal conditions can only explain 56–83%. The temperature influence coefficient ranges from 1.3% to 13.8%. Comparatively speaking, the second sowing date is the most suitable sowing date. Early sowing is prone to encounter low temperatures, resulting in underutilization of the early heat, while late sowing is prone to less heat. Both conditions are not conducive to better improve the yield of spring maize.

Objective: This study aims to evaluate the soil rill erosion intensity in the Northeast Black Soil Region of China and explore the relationship between extreme precipitation events and soil erosion over the period from 1980 to 2020. Methods: The Revised Universal Soil Loss Equation (RUSLE) model was applied to estimate soil rill erosion values using a combination of meteorological observations, remote sensing, soil physicochemical properties, and Geographic Information Systems. A correlation analysis framework was developed to link soil rill erosion values with extreme precipitation indices, and the spatial-temporal dynamics were analyzed. Results: The annual soil rill erosion value in the region averaged 0.84 ± 0.22 t·ha ⁻¹ ·yr ⁻¹ , with no significant trend over four decades. The Eastern Mongolian subregion exhibited the highest erosion rates, exceeding 2.0 t·ha ⁻¹ ·yr ⁻¹ . Strong correlations were identified between soil rill erosion and factors such as consecutive rainy days, cumulative precipitation, and extreme rainfall events. Conclusions: Extreme precipitation events play a significant role in driving soil rill erosion, emphasizing the need for refined models that integrate hydrological processes. The study provides critical insights for regional soil conservation and climate adaptation strategies.

Agroclimatic regionalization is an effective way to utilize agricultural climate resources in a reasonable manner. Accurate and objective agroclimatic regionalization plays a great directive role in ecological layout and decision support for agriculture farming. The purpose of this article was to investigate the influence of climate change on agroclimatic regions in China. Following the same regionalization principle concept as the theory and techniques of agroclimatic regionalization, three agroclimatic regions, the Tibetan High Cold Region (THCR), Northwest Arid Region (NAR), and Eastern Monsoon Region (EMR) were identified in China. The changes in the three agroclimatic regions were analyzed from 1961 to 2020 in the past and from 2006 to 2060 in the future. Future changes in agroclimatic regions were estimated from 2006 to 2030 and from 2031 to 2060 under scenarios RCP2.6, RCP4.5, and RCP8.5 for greenhouse gas emissions. The borders of agoclimatic regions had changed as a result of global climate warming and precipitation variability. There was a surplus in the geographical displacement and range of agroclimatic region borders in 1991 to 2020, especially when compared to those in 1961–1990. The TCHR exhibited significant spatial variation, with its northeast corner shifting nearly 170 km to the southwest. In the future, the area ratio of the THCR will be 26% by 2031–2060 under the RCP8.5 scenario, with the highest decline (1% compared to that in the reference period of 1981–2005), while under the RCP4.5 and RCP2.6 scenarios it will stabilize the area ratio at 27%. The eastern boundary of the NAR will migrate south or east, while the center boundary will rise northward. Under all three climatic scenarios, the area ratio will be 25% (down 1%). The range of the EMR will expand. The area ratio of the EMR will increase by 1% under the RCP2.6 and RCP4.5 scenarios and by 2% under the RCP8.5 scenario. Overall, our study may facilitate an in-depth understanding of agroclimatic regions changes and thus provide a scientific reference for the distribution of agricultural production and sustainable development under climate change in China.