Chilling injury is an important natural stress that can threaten cotton production, especially at the sowing and seedling stages in early spring. It is therefore important for cotton production to improve chilling tolerance at these stages. The current work examines the potential for glycine betaine (GB) treatment of seeds to increase the chilling tolerance of cotton at the seedling stage. Germination under cold stress was increased significantly by GB treatment. Under low temperature, the leaves of seedlings from treated seeds exhibited a higher net photosynthetic rate (PN), higher antioxidant enzyme activity including superoxide dismutase, ascorbate peroxidase and catalase, lower hydrogen peroxide (H2O2) content and less damage to the cell membrane. Enzyme activity was correlated negatively with H2O2 content and degree of damage to the cell membrane but correlated positively with GB content. The experimental results suggested that although GB was only used to treat cotton seed, the beneficial effect caused by the preliminary treatment of GB could play a significant role during germination that persisted to at least the four-leaf seedling stage. Therefore, it is crucial that this method is employed in agricultural production to improve chilling resistance in the seedling stage by soaking the seeds in GB.

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Understanding the vegetation greenness dynamics in the forest–steppe transition zone is essential for ecosystem management, and in order to study ecological changes in the region. This study provides a valuable record of the vegetation greenness dynamics in the western Greater Khingan Range over the past 193 years (1826–2018) based on tree-ring data represented by the normalized difference vegetation index (NDVI). The reconstructed vegetation greenness dynamics record contains a total of 32 years of high vegetation greenness and 37 years of low vegetation greenness, together occupying 35.8% of the entire reconstructed period (193 years). Climate (precipitation) is the main influence on the vegetation greenness dynamics at this site, but human activities have also had a significant impact over the last few decades. The magnitude, frequency, and duration of extreme changes in vegetation greenness dynamics have increased significantly, with progressively shorter intervals. Analyses targeting human behavior have shown that the density of livestock, agricultural land area, and total population have gradually increased, encroaching on forests and grasslands and reducing the inter-annual variability. After 2002, the government implemented projects to return farmland to its original ecosystems, and for the implementation of new land management practices (which are more ecologically related); as such, the vegetation conditions began to improve. These findings will help us to understand the relationship between climate change and inter- and intra- annual dynamics in northeastern China, and to better understand the impact of human activities on vegetation greenness dynamics.

IntroductionIt is of great significance to understand the characteristics and influencing factors of vegetation coverage variation in the warm temperate zone. As a typical region of the warm temperate zone in eastern China, the mountainous and hilly region in central-south Shandong Province has fragile ecological environment and soil erosion problem. Studying on vegetation dynamics and its influencing factors in this region will help to better understand the relationship between climate change and vegetation cover change in the warm temperate zone of eastern China, and the influence of human activities on vegetation cover dynamics.MethodsBased on dendrochronology, a standard tree-ring width chronology was established in the mountainous and hilly region of central-south Shandong Province, and the vegetation coverage from 1905 to 2020 was reconstructed to reveal the dynamic change characteristics of vegetation cover in this region. Secondly, the influence of climate factors and human activities on the dynamic change of vegetation cover was discussed through correlation analysis and residual analysis.Results and discussionIn the reconstructed sequence, 23 years had high vegetation coverage and 15 years had low vegetation coverage. After low-pass filtering, the vegetation coverage of 1911–1913, 1945–1951, 1958–1962, 1994–1996, and 2007–2011 was relatively high, while the vegetation coverage of 1925–1927, 1936–1942, 2001–2003, and 2019–2020 was relatively low. Although precipitation determined the variation of vegetation coverage in this study area, the impacts of human activities on the change of vegetation coverage in the past decades cannot be ignored. With the development of social economy and the acceleration of urbanization, the vegetation coverage declined. Since the beginning of the 21st century, ecological projects such as Grain-for-Green have increased the vegetation coverage.