Journal ArticleDOI
Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006
Michael A. White,Kirsten M. de Beurs,Kamel Didan,David W. Inouye,Andrew D. Richardson,Olaf P. Jensen,John O'Keefe,G. Zhang,Ramakrishna R. Nemani,Willem J. D. van Leeuwen,Jesslyn F. Brown,Allard de Wit,Michael E. Schaepman,Xioamao Lin,Michael D. Dettinger,Amey S. Bailey,John S. Kimball,Mark D. Schwartz,Dennis D. Baldocchi,J. T. Lee,William K. Lauenroth +20 more
TLDR
In this paper, the authors assess 10 start-of-spring (SOS) methods for North America between 1982 and 2006 and find that SOS estimates were more related to the first leaf and first flowers expanding phenological stages.Abstract:
Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by � 60 days and in standard deviation by � 20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOSread more
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Journal ArticleDOI
Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008
TL;DR: Admitting regional heterogeneity, changes in hemispheric features suggest that the longer-lasting vegetation growth in recent decades can be attributed to extended leaf senescence in autumn rather than earlier spring leaf-out.
Journal ArticleDOI
Plant phenology and global climate change: Current progresses and challenges
Shilong Piao,Shilong Piao,Qiang Liu,Anping Chen,Ivan A. Janssens,Yongshuo H. Fu,Yongshuo H. Fu,Junhu Dai,Lingli Liu,Xu Lian,Miaogen Shen,Xiaolin Zhu +11 more
TL;DR: It is suggested that future studies should primarily focus on using new observation tools to improve the understanding of tropical plant phenology, on improving process-based phenology modeling, and on the scaling of phenology from species to landscape-level.
Journal ArticleDOI
Influence of spring and autumn phenological transitions on forest ecosystem productivity
Andrew D. Richardson,T. Andy Black,Philippe Ciais,Nicolas Delbart,Mark A. Friedl,Nadine Gobron,David Y. Hollinger,Werner L. Kutsch,Bernard Longdoz,Sebastiaan Luyssaert,Sebastiaan Luyssaert,Mirco Migliavacca,Leonardo Montagnani,Leonardo Montagnani,J. William Munger,Eddy Moors,Shilong Piao,Corinna Rebmann,Markus Reichstein,Nobuko Saigusa,Enrico Tomelleri,Rodrigo Vargas,Andrej Varlagin +22 more
TL;DR: Investigation of relationships between phenology and productivity in temperate and boreal forests finds the productivity of evergreen needleleaf forests is less sensitive to phenology than is productivity of deciduous broadleaf forests, which has implications for how climate change may drive shifts in competition within mixed-species stands.
Journal ArticleDOI
Characteristics, drivers and feedbacks of global greening
Shilong Piao,Shilong Piao,Xuhui Wang,Taejin Park,Taejin Park,Chi Chen,Xu Lian,Yue He,Jarle W. Bjerke,Anping Chen,Philippe Ciais,Philippe Ciais,Hans Tømmervik,Ramakrishna R. Nemani,Ranga B. Myneni +14 more
TL;DR: In this article, the authors examined the detection of the greening signal, its causes and its consequences, and showed that greening is pronounced over intensively farmed or afforested areas, such as in China and India, reflecting human activities.
Journal ArticleDOI
Phenological change detection while accounting for abrupt and gradual trends in satellite image time series
TL;DR: BFAST as mentioned in this paper integrates the decomposition of time series into trend, seasonal, and remainder components with methods for detecting change within time series, showing that the phenological change detection is influenced by the signal-to-noise ratio of the time series.
References
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Journal ArticleDOI
Canopy duration has little influence on annual carbon storage in the deciduous broad leaf forest
TL;DR: In this paper, the authors investigated the relationship between phenological metrics and annual net ecosystem exchange (NEE) of carbon and found that NEE was extremely weakly related to canopy duration (days from leaf appearance to complete leaf fall).
Journal ArticleDOI
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Journal ArticleDOI
Trend analysis of time-series phenology of North America derived from satellite data
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Journal ArticleDOI
Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data
TL;DR: In this article, the authors examined how satellite based time-series vegetation greenness data and phenological measurements can be used to monitor and quantify vegetation recovery after wildfire disturbances and examined how pre-fire fuel reduction restoration treatments impact fire severity and impact vegetation recovery trajectories.
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