Many plants have high ornamental value during specific phenophases, and plant phenology correlates highly with seasonal vegetation landscape. Determination of the span and spatiotemporal patterns of the tourism season...Many plants have high ornamental value during specific phenophases, and plant phenology correlates highly with seasonal vegetation landscape. Determination of the span and spatiotemporal patterns of the tourism season for ornamental plants could provide tourism administrators and the tourists themselves with a theoretical basis for making travel arrangements. Based on data derived from on-the-ground observations of three phenophases, specifically first leafing date, full flowering date, and end of leaf coloring date, and corre- sponding meteorological data at 12 sites in China, we divided the tourism season into its starting date, peak （best date） and end date for ornamental plants by computing frequency distributions of these phenophases. We also determined how the peak of this tourism season changed during the course of the past 50 years. We found that： （1） The peak of the tourism season ranged from March 16 （in Guilin） to May 5 （in Harbin） for first leafing, from April 3 （in Kunming） to May 24 （in Mudanjiang） for full flowering, and from October 1 （in Mudanjiang） to November 30 （in Shanghai） for leaf coloring. As might be expected, the peaks of both the first leafing and full flowering tourism seasons were positively associated with latitude, while for leaf coloring it was negatively correlated with latitude. （2） The ideal tourism season for first leafing and full flowering advanced by more than 0.16 days/year over the past 50 years in Beijing and Xi＇an, while the peak of the tourism season for leaf coloring became significantly delayed （by 0.16 days/year in Beijing and 0.21 days/year in Xi＇an）. （3） The tourism season was significantly associated with temperature across related phenological observation sites. The ideal time for first leafing and full flowering was determined to have advanced, respectively, by 4.02 days and 4.04 days per 1℃ increase in the spring （March-May） temperature. From September to November, the best time for leaf coloring correlated significantly and positively with average temperature, and the spatial sensitivity was 2.98 days/℃.展开更多
Based on historical records of extreme climate events and population densities in Gansu and Shaanxi, and information on climate change, populations, new cultivated cropland, and administrative system reform in Xinjian...Based on historical records of extreme climate events and population densities in Gansu and Shaanxi, and information on climate change, populations, new cultivated cropland, and administrative system reform in Xinjiang, this study explores the interaction between climate change, migration, and regional administrative reform in the middle Qing Dynasty. The results showed that the surge in population migration from Gansu and Shaanxi to Xinjiang during 1760–1820 was caused by extreme climate events(droughts and floods) and population pressure in Gansu and Shaanxi. During 1760–1880, the climate in Xinjiang was unusually cold and humid, which was highly conducive to abundant regional water resources. This provided favorable conditions for farmland irrigation and further promoted agricultural cultivation, population growth, and town development within this region. Additionally,the interactions between climate change and the above-mentioned social factors, which acted as driving forces, spurred the reform in the administrative system of Xinjiang whereby the military administration system was transformed to a province administration system. Through this reform, the Qing government managed to restore peace and stability in Xinjiang. This study contributes to a better understanding of climate-related population migration and enhances our knowledge of the impact-response chain between climate change, ancient social developments, and political coping strategies, especially in regional administrative reform.展开更多
Phenological modeling is not only important for the projection of future changes of certain phenophases but also crucial for systematically studying the spatiotemporal patterns of plant phenology.Based on ground pheno...Phenological modeling is not only important for the projection of future changes of certain phenophases but also crucial for systematically studying the spatiotemporal patterns of plant phenology.Based on ground phenological observations,we used two existing temperature-based models and 12 modified models with consideration of precipitation or soil moisture to simulate the bud-burst date(BBD)of four common herbaceous plants-Xanthium sibiricum,Plantago asiatica,Iris lactea and Taraxacum mongolicum-in temperate grasslands in Inner Mongolia.The results showed that(1)increase in temperature promoted the BBD of all species.However,effects of precipitation and soil moisture on BBD varied among species.(2)The modified models predicted the BBD of herbaceous plants with R^2 ranging from 0.17 to 0.41 and RMSE ranging from 9.03 to 11.97 days,better than classical thermal models.(3)The spatiotemporal pattern of BBD during 1980–2015 showed that species with later BBD,e.g.X.sibiricum(mean:day of year 135.30)exhibited an evidently larger spatial difference in BBD(standard deviation:13.88 days)than the other species.Our findings suggest that influences of temperature and water conditions need to be considered simultaneously in predicting the phenological response of herbaceous plants to climate change.展开更多
基金National Natural Science Foundation of China, No.41171043 National Basic Research Program of China, No.2012CB955304+1 种基金 Major National Research Program of Scientific Instruments, No.41427805 National Natural Science Foundation of China, No.41030101
文摘Many plants have high ornamental value during specific phenophases, and plant phenology correlates highly with seasonal vegetation landscape. Determination of the span and spatiotemporal patterns of the tourism season for ornamental plants could provide tourism administrators and the tourists themselves with a theoretical basis for making travel arrangements. Based on data derived from on-the-ground observations of three phenophases, specifically first leafing date, full flowering date, and end of leaf coloring date, and corre- sponding meteorological data at 12 sites in China, we divided the tourism season into its starting date, peak （best date） and end date for ornamental plants by computing frequency distributions of these phenophases. We also determined how the peak of this tourism season changed during the course of the past 50 years. We found that： （1） The peak of the tourism season ranged from March 16 （in Guilin） to May 5 （in Harbin） for first leafing, from April 3 （in Kunming） to May 24 （in Mudanjiang） for full flowering, and from October 1 （in Mudanjiang） to November 30 （in Shanghai） for leaf coloring. As might be expected, the peaks of both the first leafing and full flowering tourism seasons were positively associated with latitude, while for leaf coloring it was negatively correlated with latitude. （2） The ideal tourism season for first leafing and full flowering advanced by more than 0.16 days/year over the past 50 years in Beijing and Xi＇an, while the peak of the tourism season for leaf coloring became significantly delayed （by 0.16 days/year in Beijing and 0.21 days/year in Xi＇an）. （3） The tourism season was significantly associated with temperature across related phenological observation sites. The ideal time for first leafing and full flowering was determined to have advanced, respectively, by 4.02 days and 4.04 days per 1℃ increase in the spring （March-May） temperature. From September to November, the best time for leaf coloring correlated significantly and positively with average temperature, and the spatial sensitivity was 2.98 days/℃.
基金supported by Key Research Program of the Chinese Academy of Sciences (Grant No. ZDRW-ZS-2016-6)the National Key Research and Development Program of China (Grant No. 2016YFA0602704)
文摘Based on historical records of extreme climate events and population densities in Gansu and Shaanxi, and information on climate change, populations, new cultivated cropland, and administrative system reform in Xinjiang, this study explores the interaction between climate change, migration, and regional administrative reform in the middle Qing Dynasty. The results showed that the surge in population migration from Gansu and Shaanxi to Xinjiang during 1760–1820 was caused by extreme climate events(droughts and floods) and population pressure in Gansu and Shaanxi. During 1760–1880, the climate in Xinjiang was unusually cold and humid, which was highly conducive to abundant regional water resources. This provided favorable conditions for farmland irrigation and further promoted agricultural cultivation, population growth, and town development within this region. Additionally,the interactions between climate change and the above-mentioned social factors, which acted as driving forces, spurred the reform in the administrative system of Xinjiang whereby the military administration system was transformed to a province administration system. Through this reform, the Qing government managed to restore peace and stability in Xinjiang. This study contributes to a better understanding of climate-related population migration and enhances our knowledge of the impact-response chain between climate change, ancient social developments, and political coping strategies, especially in regional administrative reform.
基金National Key R&D Program of China,No.2018YFA0606102National Natural Science Foundation of China,No.41771056,No.41901014
文摘Phenological modeling is not only important for the projection of future changes of certain phenophases but also crucial for systematically studying the spatiotemporal patterns of plant phenology.Based on ground phenological observations,we used two existing temperature-based models and 12 modified models with consideration of precipitation or soil moisture to simulate the bud-burst date(BBD)of four common herbaceous plants-Xanthium sibiricum,Plantago asiatica,Iris lactea and Taraxacum mongolicum-in temperate grasslands in Inner Mongolia.The results showed that(1)increase in temperature promoted the BBD of all species.However,effects of precipitation and soil moisture on BBD varied among species.(2)The modified models predicted the BBD of herbaceous plants with R^2 ranging from 0.17 to 0.41 and RMSE ranging from 9.03 to 11.97 days,better than classical thermal models.(3)The spatiotemporal pattern of BBD during 1980–2015 showed that species with later BBD,e.g.X.sibiricum(mean:day of year 135.30)exhibited an evidently larger spatial difference in BBD(standard deviation:13.88 days)than the other species.Our findings suggest that influences of temperature and water conditions need to be considered simultaneously in predicting the phenological response of herbaceous plants to climate change.
