Leaf onset in the northern hemisphere triggered by daytime temperature
TL;DR: This work shows that the interannual anomalies of LUD during 1982–2011 are triggered by daytime (Tmax) more than by nighttime temperature (Tmin), and suggests a new conceptual framework of leaf onset using daytime temperature to improve the performance of phenology modules in current Earth system models.
Abstract: Recent warming significantly advanced leaf onset in the northern hemisphere. This signal cannot be accurately reproduced by current models parameterized by daily mean temperature (Tmean). Here using in situ observations of leaf unfolding dates (LUDs) in Europe and the United States, we show that the interannual anomalies of LUD during 1982–2011 are triggered by daytime (Tmax) more than by nighttime temperature (Tmin). Furthermore, an increase of 1 Ci nTmax would advance LUD by 4.7 days in Europe and 4.3 days in the United States, more than the conventional temperature sensitivity estimated from Tmean. The triggering role of Tmax, rather than the Tmin or Tmean variable, is also supported by analysis of the large-scale patterns of satellite-derived vegetation green-up in spring in the northern hemisphere (430N). Our results suggest a new conceptual framework of leaf onset using daytime temperature to improve the performance of phenology modules in current Earth system
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TL;DR: In this paper, a new method to improve phenology estimates of bamboo forests by coupling the particle filter (PF) assimilation algorithm and a logistic model was proposed, and the results reveal that the R2 values between the start of the growing season (SOS) and end of the Growing Season (EOS) estimated by the assimilated LAI and ground-observed values are the highest (>0.50) and the root mean square errors (RMSEs) are the smallest (
Abstract: Phenology plays an important role in revealing the spatiotemporal evolution of forest ecosystem carbon cycles. The accuracy of vegetation phenology estimates based on remote sensing has improved in temperate zones. However, subtropical vegetation is complex, and the corresponding phenology estimates using remote sensing face great challenges. Bamboo forests are subtropical unique forest types and exhibit on– and off-years, fast growth, high productivity and carbon sequestration capability. In this study, we propose a new method to improve phenology estimates of bamboo forests by coupling the particle filter (PF) assimilation algorithm and a logistic model. The phenological metrics are estimated using high-precision leaf area index (LAI) assimilation products and a logistic model from 2001 to 2018, and the results are compared to those extracted from Moderate-Resolution Imaging Spectroradiometer (MODIS) LAI and the enhanced vegetation index (EVI) calculated based on the MODIS reflectance data. The results reveal that the R2 values between the start of the growing season (SOS) and end of the growing season (EOS) estimated by the assimilated LAI and ground-observed values are the highest (>0.50) and the root mean square errors (RMSEs) are the smallest (
18 citations
TL;DR: In this article, the authors used time series of satellite-derived Normalized Difference Vegetation Index (NDVI) (1985-2015) to track recent changes in maximum vegetation growth (the maximum of NDVI (NDVImax) and the peak of growing season (POS)) in the continental US.
17 citations
TL;DR: The results demonstrate the potential of satellite remote sensing for providing reliable timings of bud phenological events using calibrated NDVI time series on wide regions that are remote or with limited access.
Abstract: Satellite remote sensing is a widely accessible tool to investigate the spatiotemporal variations in the bud phenology of evergreen species, which show limited seasonal changes in canopy greenness. However, there is a need for precise and compatible data to compare remote sensing time series with field observations. In this study, fortnightly MODIS-NDVI was fitted using double-logistic functions and calibrated using ordinal logit models with the sequential phases of bud phenology collected during 2015, 2017 and 2018 in a black spruce stand. Bud break and bud set were spatialized for the period 2009–2018 across 5000 stands in Quebec, Canada. The first phase of bud break and the last phase of bud set were observed in the field in mid-May and at the beginning of September, when NDVI was 80.5% and 92.2% of its maximum amplitude, respectively. The NDVI rate of change was estimated at 0.07 in spring and 0.04 in autumn. When spatialized on the black spruce stands, bud break was detected earlier in the southwestern regions (April–May), and later in the northeastern regions (mid to end of June). No clear trend was observed for bud set, with different patterns being detected among the years. Overall, the process bud break and bud set lasted 51 and 87 days, respectively. Our results demonstrate the potential of satellite remote sensing for providing reliable timings of bud phenological events using calibrated NDVI time series on wide regions that are remote or with limited access.
17 citations
Cites background from "Leaf onset in the northern hemisphe..."
...NDVI is considered as a potential remote sensing proxy to investigate the effect of climate on vegetation phenology at regional to continental scales due to its close relationship with plant activity [18,19]....
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...Given that MODIS vegetation indices (NDVI, EVI) are primarily sensitive to changes in leaf chlorophyll content and structure [18,19,64], NDVI may be more representative of phenological changes in evergreen species during the first part of the growing season (from mid-spring to summer) than in the autumn [4,22]....
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17 citations
TL;DR: The results suggested that there was a very significant increasing trend in both daytime and nighttime temperatures in Northwest China from 1982 to 2015; night temperatures increased about 1.2 times faster than daytime temperatures, showing diurnal asymmetric warming; and various types of vegetation responded differently to asymmetric afternoon and nighttime warming.
Abstract: Though temperature over the past three decades has shown an asynchronous warming trend between daytime and nighttime, the response of vegetation activity to such non-uniform warming is still not very clear. In this study, the least squares linear trend analysis and geographic information system spatial analysis were conducted to analyze the spatiotemporal patterns of the daytime and nighttime warming based on the daily temperature data from 1982 to 2015 in Northwest China. The normalized difference vegetation index (NDVI) from Global Inventory Monitoring and Modeling System and vegetation type data were used to investigate the responses of vegetation activity to the daytime and nighttime warming using the partial correlation analysis. Our results suggested that (1) there was a very significant increasing trend in both daytime and nighttime temperatures in Northwest China from 1982 to 2015; night temperatures increased about 1.2 times faster than daytime temperatures, showing diurnal asymmetric warming; (2) the responses of vegetation activity to daytime and nighttime warming in Northwest China showed a distinct spatial pattern; the change in night temperatures had a more significant (positive in most regions) effect on vegetation; (3) various types of vegetation responded differently to asymmetric daytime and nighttime warming. Grassland NDVI, broad-leaved, and coniferous forest NDVI significantly responded to daytime warming. Shrub NDVI and desert NDVI significantly responded to night warming. These findings can deepen the understanding of the effects of the daytime and nighttime warming on vegetation activities in arid regions in the context of the current asymmetric warming.
17 citations
Cites background from "Leaf onset in the northern hemisphe..."
...For example, Piao et al. (2015) found that plant leaf onset was determined mainly by preseason Tmax in most middle- and high-latitude area in the Northern Hemisphere....
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...When the effect of precipitation in the growing seasons is removed in the partial correlation, the day and night warming tended to influence vegetation activity differently (Peng et al. 2013; Piao et al. 2015; Shen et al. 2016; Xia et al. 2018; Yang et al. 2016)....
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References
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01 Jan 2007
TL;DR: The first volume of the IPCC's Fourth Assessment Report as mentioned in this paper was published in 2007 and covers several topics including the extensive range of observations now available for the atmosphere and surface, changes in sea level, assesses the paleoclimatic perspective, climate change causes both natural and anthropogenic, and climate models for projections of global climate.
Abstract: This report is the first volume of the IPCC's Fourth Assessment Report. It covers several topics including the extensive range of observations now available for the atmosphere and surface, changes in sea level, assesses the paleoclimatic perspective, climate change causes both natural and anthropogenic, and climate models for projections of global climate.
32,826 citations
01 Jan 2013
TL;DR: In this paper, a summary of issues to assist policymakers, a technical summary, and a list of frequently-asked questions are presented, with an emphasis on physical science issues.
Abstract: Report summarizing climate change issues in 2013, with an emphasis on physical science. It includes a summary of issues to assist policymakers, a technical summary, and a list of frequently-asked questions.
7,858 citations
01 Jan 2007
TL;DR: Drafting Authors: Neil Adger, Pramod Aggarwal, Shardul Agrawala, Joseph Alcamo, Abdelkader Allali, Oleg Anisimov, Nigel Arnell, Michel Boko, Osvaldo Canziani, Timothy Carter, Gino Casassa, Ulisses Confalonieri, Rex Victor Cruz, Edmundo de Alba Alcaraz, William Easterling, Christopher Field, Andreas Fischlin, Blair Fitzharris.
Abstract: Drafting Authors: Neil Adger, Pramod Aggarwal, Shardul Agrawala, Joseph Alcamo, Abdelkader Allali, Oleg Anisimov, Nigel Arnell, Michel Boko, Osvaldo Canziani, Timothy Carter, Gino Casassa, Ulisses Confalonieri, Rex Victor Cruz, Edmundo de Alba Alcaraz, William Easterling, Christopher Field, Andreas Fischlin, Blair Fitzharris, Carlos Gay García, Clair Hanson, Hideo Harasawa, Kevin Hennessy, Saleemul Huq, Roger Jones, Lucka Kajfež Bogataj, David Karoly, Richard Klein, Zbigniew Kundzewicz, Murari Lal, Rodel Lasco, Geoff Love, Xianfu Lu, Graciela Magrín, Luis José Mata, Roger McLean, Bettina Menne, Guy Midgley, Nobuo Mimura, Monirul Qader Mirza, José Moreno, Linda Mortsch, Isabelle Niang-Diop, Robert Nicholls, Béla Nováky, Leonard Nurse, Anthony Nyong, Michael Oppenheimer, Jean Palutikof, Martin Parry, Anand Patwardhan, Patricia Romero Lankao, Cynthia Rosenzweig, Stephen Schneider, Serguei Semenov, Joel Smith, John Stone, Jean-Pascal van Ypersele, David Vaughan, Coleen Vogel, Thomas Wilbanks, Poh Poh Wong, Shaohong Wu, Gary Yohe
7,720 citations
Technische Universität München1, Central Institution for Meteorology and Geodynamics2, University of Tartu3, Swedish Museum of Natural History4, University of Latvia5, Humboldt University of Berlin6, University of Ljubljana7, MeteoSwiss8, Trinity College, Dublin9, Autonomous University of Barcelona10, Norwegian University of Life Sciences11, Norwegian Meteorological Institute12, Finnish Meteorological Institute13, Czech Hydrometeorological Institute14, Environment Agency15, Wageningen University and Research Centre16, University of Oslo17
TL;DR: In this article, the authors used an enormous systematic phenological network data set of more than 125 000 observational series of 542 plant and 19 animal species in 21 European countries (1971-2000) and concluded that previously published results of phenological changes were not biased by reporting or publication predisposition.
Abstract: Global climate change impacts can already be tracked in many physical and biological systems; in particular, terrestrial ecosystems provide a consistent picture of observed changes. One of the preferred indicators is phenology, the science of natural recurring events, as their recorded dates provide a high-temporal resolution of ongoing changes. Thus, numerous analyses have demonstrated an earlier onset of spring events for mid and higher latitudes and a lengthening of the growing season. However, published single-site or single-species studies are particularly open to suspicion of being biased towards predominantly reporting climate change-induced impacts. No comprehensive study or meta-analysis has so far examined the possible lack of evidence for changes or shifts at sites where no temperature change is observed. We used an enormous systematic phenological network data set of more than 125 000 observational series of 542 plant and 19 animal species in 21 European countries (1971–2000). Our results showed that 78% of all leafing, flowering and fruiting records advanced (30% significantly) and only 3% were significantly delayed, whereas the signal of leaf colouring/fall is ambiguous. We conclude that previously published results of phenological changes were not biased by reporting or publication predisposition: the average advance of spring/summer was 2.5 days decade � 1 in Europe. Our analysis of 254 mean national time series undoubtedly demonstrates that species’ phenology is responsive to temperature of the preceding
2,457 citations