气候变化领域集成服务门户(CCPortal): Using time series of MODIS land surface phenology to model temperature and photoperiod controls on spring greenup in North American deciduous forests

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DOI	10.1016/j.rse.2021.112466
	Using time series of MODIS land surface phenology to model temperature and photoperiod controls on spring greenup in North American deciduous forests
	Moon M.; Seyednasrollah B.; Richardson A.D.; Friedl M.A.
发表日期	2021
ISSN	00344257
卷号	260
英文摘要	The timing of leaf emergence in temperate and boreal forests is changing, which has profound implications for a wide array of ecosystem processes and services. Spring phenology models, which have been widely used to predict the timing of leaf emergence, generally assume that a combination of photoperiod and thermal forcing control when leaves emerge. However, the exact nature and magnitude of how photoperiod and temperature individually and jointly control leaf emergence is the subject of ongoing debate. Here we use a continuous development model in combination with time series of land surface phenology measurements from MODIS to quantify the relative importance of photoperiod and thermal forcing in controlling the timing of canopy greenup in eastern temperate and boreal forests of North America. The model accurately predicts biogeographic and interannual variation in the timing of greenup across the study region (median RMSE = 4.6 days, median bias = 0.30 days). Results reveal strong biogeographic variation in the period prior to greenup when temperature and photoperiod influence greenup that covaries with the importance of photoperiod versus thermal controls. Photoperiod control on leaf emergence is dominant in warmer climates, but exerts only modest influence on the timing of leaf emergence in colder climates. Results from models estimated using ground-based observations of cloned lilac are consistent with those from remote sensing, which supports the realism of remote sensing-based models. Overall, results from this study suggest that apparent changes in the sensitivity of trees to temperature are modest and reflect a trade-off between decreased sensitivity to temperature and increased photoperiod control, and identify a transition in the relative importance of temperature versus photoperiod near the 10 °C isotherm in mean annual temperature. This suggests that the timing of leaf emergence will continue to move earlier as the climate warms, and that the magnitude of change will be more pronounced in colder regions with mean annual temperatures below 10 °C. © 2021 Elsevier Inc.
英文关键词	Bayesian; Climate change; Deciduous forests; Hierarchical modeling; Land surface phenology; MODIS; Photoperiod; Spring phenology; Temperature sensitivity
语种	英语
scopus关键词	Cloning; Economic and social effects; Ecosystems; Forestry; Plants (botany); Radiometers; Remote sensing; Surface measurement; Time series; Bayesian; Deciduous forest; Green-up; Hierarchical modeling; Land surface phenology; Photoperiod; Spring phenology; Temperate forests; Temperature sensitivity; Times series; Climate change
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/178838
作者单位	Department of Earth and Environment, Boston University, United States; School of Informatics, Computing, and Cyber Systems, Northern Arizona University, United States; Center for Ecosystem Science and Society, Northern Arizona University, United States
推荐引用方式 GB/T 7714	Moon M.,Seyednasrollah B.,Richardson A.D.,et al. Using time series of MODIS land surface phenology to model temperature and photoperiod controls on spring greenup in North American deciduous forests[J],2021,260.
APA	Moon M.,Seyednasrollah B.,Richardson A.D.,&Friedl M.A..(2021).Using time series of MODIS land surface phenology to model temperature and photoperiod controls on spring greenup in North American deciduous forests.Remote Sensing of Environment,260.
MLA	Moon M.,et al."Using time series of MODIS land surface phenology to model temperature and photoperiod controls on spring greenup in North American deciduous forests".Remote Sensing of Environment 260(2021).