Spatiotemporal Dynamics of Climate Potential Productivity of Agricultural Ecosystems in Liaoning Province, China, During 1950–2023

Global climate change has profoundly affected agricultural ecosystems by altering the spatiotemporal patterns of temperature and precipitation, disrupting ecological equilibrium, and increasing environmental variability for crop growth, thereby posing significant challenges to food security. Based on 1 km-resolution gridded datasets of mean precipitation and temperature for Liaoning Province from 1950 to 2023, this study integrated the Miami and Thornthwaite Memorial models with climate tendency rate analysis, Mann–Kendall trend tests, and inverse distance weighting interpolation to assess spatiotemporal changes in climate potential productivity (CPP) and its relationship with grain yield dynamics. The results show that, from 1950 to 2023, annual precipitation exhibited a fluctuating downward trend (−8.5 mm/10a), while mean annual temperature increased significantly (0.3 °C/10a). Consequently, precipitation-based climatic production potential declined at a rate of 10.4 g·m−2·(10a)−1, whereas temperature-based, evapotranspiration-based, and standard climate potential productivity (Yb) increased at rates of 23.3-, 6.6-, and 5.7 g·m−2·(10a)−1, respectively. Spatially, CPP displayed a distinct gradient characterized by higher values in the southeast and lower values in the northwest, with a stronger correlation to precipitation than to temperature. Climate classification analysis indicated that warm-humid conditions enhanced CPP, whereas cold-dry, cold-humid, and warm-dry conditions reduced productivity. Although grain yield per unit area and climate resource utilization efficiency increased by 89.4 g·m−2·(10a)−1 and 9.0% per decade, respectively, the yield-increasing potential declined by 84.1 g·m−2·(10a)−1, indicating that while advances in agricultural technology have improved resource conversion efficiency, the potential for further yield gains through climate-dependent strategies alone is increasingly limited.

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Publication Details

Journal
Agronomy
Published
2025-11-23
DOI
https://doi.org/10.3390/agronomy15122697
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Spatiotemporal Dynamics of Climate Potential Productivity of Agricultural Ecosystems in Liaoning Province, China, During 1950–2023

Zijiao Yang, Di Shi, Qianlai Zhuang, Xinxin Jin et al.
Agronomy
Remote Sensing in Agriculture
article

Spatiotemporal Dynamics of Climate Potential Productivity of Agricultural Ecosystems in Liaoning Province, China, During 1950–2023

Zijiao Yang, Di Shi, Qianlai Zhuang, Xinxin Jin, Yan Wang, Shuai Wang
article en

Abstract

Global climate change has profoundly affected agricultural ecosystems by altering the spatiotemporal patterns of temperature and precipitation, disrupting ecological equilibrium, and increasing environmental variability for crop growth, thereby posing significant challenges to food security. Based on 1 km-resolution gridded datasets of mean precipitation and temperature for Liaoning Province from 1950 to 2023, this study integrated the Miami and Thornthwaite Memorial models with climate tendency rate analysis, Mann–Kendall trend tests, and inverse distance weighting interpolation to assess spatiotemporal changes in climate potential productivity (CPP) and its relationship with grain yield dynamics. The results show that, from 1950 to 2023, annual precipitation exhibited a fluctuating downward trend (−8.5 mm/10a), while mean annual temperature increased significantly (0.3 °C/10a). Consequently, precipitation-based climatic production potential declined at a rate of 10.4 g·m−2·(10a)−1, whereas temperature-based, evapotranspiration-based, and standard climate potential productivity (Yb) increased at rates of 23.3-, 6.6-, and 5.7 g·m−2·(10a)−1, respectively. Spatially, CPP displayed a distinct gradient characterized by higher values in the southeast and lower values in the northwest, with a stronger correlation to precipitation than to temperature. Climate classification analysis indicated that warm-humid conditions enhanced CPP, whereas cold-dry, cold-humid, and warm-dry conditions reduced productivity. Although grain yield per unit area and climate resource utilization efficiency increased by 89.4 g·m−2·(10a)−1 and 9.0% per decade, respectively, the yield-increasing potential declined by 84.1 g·m−2·(10a)−1, indicating that while advances in agricultural technology have improved resource conversion efficiency, the potential for further yield gains through climate-dependent strategies alone is increasingly limited.

AgronomyVol. 15(12)
Jiujiang University (CN), Shenyang Agricultural University (CN), Purdue University West Lafayette (US)
Openalex Percentile: Top 65%
Remote Sensing in Agriculture
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