Search Results (1)

The vulnerability of regional agricultural systems continues to intensify under the influence of global climate change. Understanding the spatiotemporal variation in meteorological elements and their agricultural response mechanisms has become a critical scientific challenge for ensuring food security. This study focuses on the 852 Farm in the typical area of the albic soil region on the Sanjiang Plain in China. This research integrates multi-source meteorological observations and crop yield data from 2001 to 2024. Using methods such as wavelet analysis, grey relational analysis, and cross-wavelet analysis, this study systematically investigates the dynamic changes and cyclical evolution patterns of key meteorological factors and their impact on the yields of different staple crops. The results indicate that, in terms of trend evolution, air temperature, relative humidity, and surface temperature show no significant upward trend (Z > 0; p > 0.05), while precipitation significantly increases (Z > 0; p < 0.05). Evaporation and sunlight show a nonsignificant downward trend (Z < 0; p > 0.05). The yields of rice, soybean, and corn generally exhibit fluctuating upward trends (Z > 0; p > 0.05). In terms of periodic coupling characteristics, meteorological factors exhibit multi-time-scale oscillations at 22a, 12a, and 8a. The yields of the three staple crops form significant time–frequency couplings with meteorological factors in the 22a and 8a periods. Regarding the correlation, air temperature demonstrates the highest grey correlation degree (γ ≥ 0.8) and strong coherence with crop yields, followed by precipitation and sunlight. These findings provide a theoretical and quantitative basis for understanding the multi-scale interactive mechanisms of climate adaptation in agricultural systems of the albic soil region, as well as for managing and optimizing climate-resilient farming practices. Full article