Effects of climate change and crop management on changes in rice phenology in China from 1981 to 2010

Abstract

BACKGROUND: Crop phenology change is co-determined by climate change and adaptation strategies, such as crop management, but their combined and isolated impacts on rice phenology are still unclear. Quantifying the impacts and identifying the main contributors are critical to food security under climate change. Thus we distinguished and quantified the relative contribution of climate change and crop management to rice (Oryza sativa L.) phenological changes in China from 1981 to 2010, using a first-difference multivariate regression method. RESULTS: Rice phenology has changed over the past 30 years in China. The mean length of the phenological stage from emergence to transplanting was shortened, whereas the mean length of the stage from transplanting to heading, from heading to maturity, was prolonged. The relative contribution of crop management was greater than that of climate change for single and late rice, which took up over 90% of the total change in certain phenology stages. Among the climatic factors, temperature was the dominant contributor, which accounted for more than 50% of the change in rice phenology. The stage from transplanting to heading of early rice and late rice had strongly negative sensitivities to increasing temperature. CONCLUSIONS: Crop management has offset the adverse effects of climate change on single and early rice phenology in China over the past 30 years to some extent, while further adaptation measures such as adjusting sowing date, shifting rice varieties, applying nitrogen fertilizer and irrigation should be applied to late rice in southern China, especially in a warmer future.

Precipitation and Anthropogenic Activities Jointly Green the China–Mongolia–Russia Economic Corridor

“…The response of vegetation change to climatic factors can be estimated using a multiple regression model [48], as shown in Equation ( 7):…”

Concurrent Precipitation Extremes Modulate the Response of Rice Transplanting Date to Preseason Temperature Extremes in China

“…Observed rice phenology data recorded by agrometeorological stations from 1981 to 2018 were obtained from the CMA. The data set has been widely used and recognized as a high‐quality observation data set in China (Chen et al., 2021; L. Zhang, Zhang, Tao, et al., 2022; Tao et al., 2013). Observations were recorded by professional staff at two‐day intervals following the specifications for agrometeorological observation—Rice (QX/T 468–2018).…”

“…A similar focus on concurrent precipitation extremes was also mentioned concerning crop yield, as concurrent extremes could cause larger impacts than individual extremes (Feng et al, 2019;. Such high-impact modulation effects of concurrent precipitation extremes are currently ignored by agriculture risk management using empirical statistical models, which mostly rely on future temperature sensitivity (Liu, Zhang, et al, 2021), and process-based models, whose structure excluded the potential influence of such modulation effects (Zhang & Tao, 2019). Additionally, current widely accepted adaptation measures only based on the response to temperature, such as adjusting sowing date and breeding long growth period cultivar, need to reappraise their robustness for this underappreciated risk on agriculture production and for better adapting to climate change (Ding et al, 2020;.…”

“…Moreover, adjusting the transplanting date is an important adaptation strategy (H. Zhao et al., 2016). On average, the transplanting dates are advanced with a warmer pre‐season temperature but also are determined by other climate factors like precipitation and sunshine hours (J. Chen et al., 2021; Yujie Liu et al., 2019). In this study, we investigate the response of rice transplanting dates to pre‐season temperature extremes and evaluate how concurrent precipitation extremes modulate such temperature responses for early, single, and late rice varieties in mainland China from observed and remotely sensed transplanting dates.…”

Asian Rice Calendar Dynamics Detected by Remote Sensing and Their Climate Drivers

“…For example, rising temperatures shortened the GP for early rice, prolonged the GP for late rice, and had less impact on the GP for single rice in China [35][36][37]. Chen et al [38] incorporated temperature, precipitation, and sunshine hours into a linear regression model to estimate the phenology response in China. He found that the maximum positive sensitivity came from the sunshine hour and the maximum negative sensitivity was from temperature.…”