Temperature sensitivity of spring vegetation phenology correlates to within-spring warming speed over the Northern Hemisphere |
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| Institution: | 1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China;2. Center for Environmental Biology and Ecosystem Studies, National Institute for Environmental Studies, Onogawa, Tsukuba 305-8506, Japan;1. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;2. Institute of Agriculture Sustainable Development, Shandong Academy of Agriculture Sciences, Jinan 250100, China;3. Department of Geography and Program in Planning, University of Toronto, 100 St. George St., Toronto, ON M5S 3G3, Canada;1. Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China;2. Department of Ecology, College of Urban and Environmental Sciences, Peking University, Beijing 100871 China;1. Environmental Research Institute, Shandong University, Qingdao 266237, China;2. Department of Environmental Sciences, University of Basel, 4056 Basel, Switzerland;3. Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, 90183 Umeå, Sweden;1. College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing, China;2. Ecologie Systématique Evolution, Université Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, 91400, Orsay, France;3. College of Water Sciences, Beijing Normal University, Beijing, China;4. Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing, 210044, China;1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;2. University of Chinese Academy of Sciences, Beijing 100049, China;3. Department of Biological and Environmental Sciences, College of Arts and Sciences, Qatar University, P.O. Box 2713, Doha, Qatar;1. Department of Earth and Environmental Sciences, Xi’an Jiaotong University, Xi’an 710049, China;2. Institute of Global Environmental Change, Xi’an Jiaotong University, Xi’an 710049, China;3. Research Center for Eco-Environmental Sciences, Northwestern Polytechnical University, Xi’an 710049, China;4. Aarhus University Centre for Circular Bioeconomy, Department of Agroecology, Aarhus University, Blichers Allé, 20, 8830 Tjele, Denmark |
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| Abstract: | The inter-annual shift of spring vegetation phenology relative to per unit change of preseason temperature, referred to as temperature sensitivity (days °C−1), quantifies the response of spring phenology to temperature change. Temperature sensitivity was found to differ greatly among vegetation from different environmental conditions. Understanding the large-scale spatial pattern of temperature sensitivity and its underlying determinant will greatly improve our ability to predict spring phenology. In this study, we investigated the temperature sensitivity for natural ecosystems over the North Hemisphere (north of 30°N), based on the vegetation phenological date estimated from NDVI time-series data provided by the Advanced Very High Resolution Radiometer (AVHRR) and the corresponding climate dataset. We found a notable longitudinal change pattern with considerable increases of temperature sensitivity from inlands to most coastal areas and a less obvious latitudinal pattern with larger sensitivity in low latitude area. This general spatial variation in temperature sensitivity is most strongly associated with the within-spring warming speed (WWS; r = 0.35, p < 0.01), a variable describing the increase speed of daily mean temperature during spring within a year, compared with other factors including the mean spring temperature, spring precipitation and mean winter temperature. These findings suggest that the same magnitude of warming will less affect spring vegetation phenology in regions with higher WWS, which might partially reflect plants’ adaption to local climate that prevents plants from frost risk caused by the advance of spring phenology. WWS accounts for the spatial variation in temperature sensitivity and should be taken into account in forecasting spring phenology and in assessing carbon cycle under the projected climate warming. |
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| Keywords: | Climate change NDVI time series Spring vegetation phenology Spring temperature Temperature sensitivity |
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