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description Publicationkeyboard_double_arrow_right Other literature type 2010Publisher:OpenAlex Chuixiang Yi; D. M. Ricciuto; Runze Li; John Wolbeck; Xiyan Xu; Mats Nilsson; Luís Aires; J. D. Albertson; Christof Ammann; M. Altaf Arain; Alessandro Araújo; Marc Aubinet; Mika Aurela; Zoltán Barcza; Alan G. Barr; Paul Berbigier; Jason Beringer; Christian Bernhofer; Andrew Black; Paul V. Bolstad; Fred C. Bosveld; M. S. J. Broadmeadow; Nina Buchmann; Sean P. Burns; Pierre Cellier; Jingming Chen; Jiquan Chen; Philippe Ciais; Robert Clement; Bruce D. Cook; Peter S. Curtis; D. B. Dail; Ebba Dellwik; Nicolas Delpierre; Ankur R. Desai; Sabina Dore; D. Dragoni; Bert G. Drake; Éric Dufrêne; Allison L. Dunn; J.A. Elbers; Werner Eugster; Matthias Falk; Christian Feigenwinter; Lawrence B. Flanagan; Thomas Foken; J. M. Frank; J. Fuhrer; Damiano Gianelle; Allen H. Goldstein; Mike Goulden; André Granier; T. Gruenwald; Lianhong Gu; Haiqiang Guo; Albin Hammerle; Shijie Han; Niall P. Hanan; László Haszpra; Bernard Heinesch; Carole Helfter; Dimmie Hendriks; Lindsay B. Hutley; Andreas Ibrom; C. Jacobs; Torbjoern Johansson; Marjan Jongen; Gabriel G. Katul; Gerard Kiely; Katja Klumpp; Alexander Knohl; Thomas E. Kolb; Werner L. Kutsch; Peter M. Lafleur; Tuomas Laurila; R. Leuning; Anders Lindroth; Heping Li; Benjamin Loubet; Giovanni Manca; Michal V. Marek; Hank A. Margolis; Timothy A. Martin; W. J. Massman; Roser Matamala; Giorgio Matteucci; Harry McCaughey; Lutz Merbold; Tilden Meyers; Mirco Migliavacca; Franco Miglietta; Laurent Misson; Meelis Moelder; John Moncrieff; Russell K. Monson; Leonardo Montagnani; M. Montes-Helu; Eddy Moors; Christine Moureaux; M. M. Mukelabai;Comprendre les relations entre le climat et l'échange de carbone par les écosystèmes terrestres est essentiel pour prédire les niveaux futurs de dioxyde de carbone atmosphérique en raison des effets d'accélération potentiels des rétroactions positives du cycle climat-carbone. Cependant, les relations directement observées entre le climat et l'échange de CO2 terrestre avec l'atmosphère à travers les biomes et les continents font défaut. Nous présentons ici des données décrivant les relations entre l'échange net de carbone par les écosystèmes (NEE) et les facteurs climatiques tels que mesurés à l'aide de la méthode de covariance de Foucault sur 125 sites uniques dans divers écosystèmes sur six continents avec un total de 559 années de site. Nous trouvons que le NEE observé aux sites de covariance tourbillonnaire est (1) une fonction forte de la température annuelle moyenne aux latitudes moyennes et élevées, (2) une fonction forte de la sécheresse aux latitudes moyennes et basses, et (3) une fonction à la fois de la température et de la sécheresse autour de la ceinture moyenne-latitudinale (45°N). La sensibilité du NEE à la température annuelle moyenne se décompose à ~ 16 °C (une valeur seuil de la température annuelle moyenne), au-delà de laquelle aucune augmentation supplémentaire de l'absorption de CO2 avec la température n'a été observée et la sécheresse influence les règles de dépassement de l'influence de la température. Comprender las relaciones entre el clima y el intercambio de carbono por parte de los ecosistemas terrestres es fundamental para predecir los niveles futuros de dióxido de carbono en la atmósfera debido a los posibles efectos aceleradores de las retroalimentaciones positivas del ciclo clima-carbono. Sin embargo, faltan relaciones directamente observadas entre el clima y el intercambio terrestre de CO2 con la atmósfera a través de biomas y continentes. Aquí presentamos datos que describen las relaciones entre el intercambio neto de carbono (NEE) del ecosistema y los factores climáticos medidos utilizando el método de covarianza de remolinos en 125 sitios únicos en varios ecosistemas de seis continentes con un total de 559 años-sitio. Encontramos que la NEE observada en los sitios de covarianza de remolinos es (1) una fuerte función de la temperatura media anual en latitudes medias y altas, (2) una fuerte función de sequedad en latitudes medias y bajas, y (3) una función tanto de la temperatura como de la sequedad alrededor del cinturón latitudinal medio (45°N). La sensibilidad de NEE a la temperatura media anual se rompe a ~ 16 °C (un valor umbral de la temperatura media anual), por encima del cual no se observó ningún aumento adicional de la absorción de CO2 con la temperatura y la influencia de la sequedad anula la influencia de la temperatura. Understanding the relationships between climate and carbon exchange by terrestrial ecosystems is critical to predict future levels of atmospheric carbon dioxide because of the potential accelerating effects of positive climate–carbon cycle feedbacks. However, directly observed relationships between climate and terrestrial CO2 exchange with the atmosphere across biomes and continents are lacking. Here we present data describing the relationships between net ecosystem exchange of carbon (NEE) and climate factors as measured using the eddy covariance method at 125 unique sites in various ecosystems over six continents with a total of 559 site-years. We find that NEE observed at eddy covariance sites is (1) a strong function of mean annual temperature at mid- and high-latitudes, (2) a strong function of dryness at mid- and low-latitudes, and (3) a function of both temperature and dryness around the mid-latitudinal belt (45°N). The sensitivity of NEE to mean annual temperature breaks down at ~ 16 °C (a threshold value of mean annual temperature), above which no further increase of CO2 uptake with temperature was observed and dryness influence overrules temperature influence. يعد فهم العلاقات بين المناخ وتبادل الكربون بواسطة النظم الإيكولوجية الأرضية أمرًا بالغ الأهمية للتنبؤ بالمستويات المستقبلية لثاني أكسيد الكربون في الغلاف الجوي بسبب التأثيرات المتسارعة المحتملة للتغذية المرتدة الإيجابية لدورة المناخ والكربون. ومع ذلك، لا توجد علاقات ملحوظة مباشرة بين المناخ والتبادل الأرضي لثاني أكسيد الكربون مع الغلاف الجوي عبر المناطق الحيوية والقارات. نقدم هنا بيانات تصف العلاقات بين صافي تبادل النظام البيئي للكربون (NEE) والعوامل المناخية كما تم قياسها باستخدام طريقة التباين الدوامي في 125 موقعًا فريدًا في أنظمة بيئية مختلفة عبر ست قارات بإجمالي 559 سنة موقع. نجد أن NEE التي لوحظت في مواقع التباين الدوامي هي (1) وظيفة قوية لمتوسط درجة الحرارة السنوية عند خطوط العرض المتوسطة والعالية، (2) وظيفة قوية للجفاف عند خطوط العرض المتوسطة والمنخفضة، و (3) وظيفة لكل من درجة الحرارة والجفاف حول حزام العرض المتوسط (45درجةشمالاً). تنهار حساسية NEE لمتوسط درجة الحرارة السنوية عند حوالي 16 درجة مئوية (قيمة عتبة لمتوسط درجة الحرارة السنوية)، والتي لم يلاحظ فوقها أي زيادة أخرى في امتصاص ثاني أكسيد الكربون مع درجة الحرارة ويتجاوز تأثير الجفاف تأثير درجة الحرارة.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2019Publisher:American Geophysical Union (AGU) Authors: David M. Lawrence; Sean P. Burns; Sean P. Burns; Sean Swenson;doi: 10.1029/2018ms001476
AbstractAtmospheric models used for weather prediction and future climate projections rely on land models to calculate surface boundary conditions. Observations of near‐surface states and fluxes made at flux measurement sites provide valuable data with which to assess the quality of simulated lower boundary conditions. A previous assessment of the Community Land Model version 4.5 using data from the Niwot Ridge Subalpine Forest AmeriFlux tower showed that simulated latent heat fluxes could be improved by adjusting a parameter describing the maximum leaf wetted area, but biases in midday sensible heat flux and nighttime momentum flux were generally not reduced by model parameter perturbations. These biases are related to the model's lack of heat storage in vegetation biomass. A biomass heat capacity is parameterized in Community Land Model version 5 with measurable quantities such as canopy height, diameter at breast height, and tree number density. After implementing a parameterization describing the heat transfer between the forest biomass and the canopy air space, the biases in the mean midday sensible heat and mean nighttime momentum fluxes at Niwot Ridge are reduced from 47 to 13 W/m2 and from 0.12 to −0.03 m/s, respectively. The bias in the mean nighttime canopy air temperature was reduced from −5.9 to 0.4 °C. Additional simulations at other flux tower sites demonstrate a consistent reduction in midday sensible heat flux, a lower ratio of the sum of sensible and latent heat flux to net radiation, and an increase in nighttime canopy temperatures.
Journal of Advances ... arrow_drop_down Journal of Advances in Modeling Earth SystemsArticle . 2019 . Peer-reviewedLicense: CC BY NC NDData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess Routesgold 24 citations 24 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Journal of Advances ... arrow_drop_down Journal of Advances in Modeling Earth SystemsArticle . 2019 . Peer-reviewedLicense: CC BY NC NDData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal , Data Paper 2020Embargo end date: 09 Jul 2020 Germany, Italy, Denmark, Italy, Italy, Australia, Germany, Germany, Belgium, Australia, Italy, Netherlands, Belgium, Italy, Australia, Italy, Russian Federation, Germany, Czech Republic, Germany, Italy, Australia, Netherlands, Australia, Switzerland, Italy, Australia, Germany, Netherlands, Norway, Germany, Australia, Australia, Italy, Finland, Sweden, Czech Republic, France, Spain, Denmark, Netherlands, Finland, United StatesPublisher:Springer Science and Business Media LLC Publicly fundedFunded by:UKRI | RootDetect: Remote Detect...UKRI| RootDetect: Remote Detection and Precision Management of Root HealthAndreas Ibrom; Bruno De Cinti; Jean Marc Ourcival; Vincenzo Magliulo; Onil Bergeron; M. Altaf Arain; Andrew Feitz; Zulia Mayari Sanchez-Mejia; Christof Ammann; Yann Nouvellon; Siyan Ma; Brian D. Amiro; Kim Pilegaard; Eddy Moors; Michele Tomassucci; Asko Noormets; Shawn Urbanski; Damiano Gianelle; Anatoly A. Gitelson; E. Canfora; You Wei Cheah; Ko van Huissteden; Shicheng Jiang; Hans Peter Schmid; Albin Hammerle; Brent E. Ewers; Virginie Moreaux; Housen Chu; Anne Griebel; Timothy J. Arkebauer; Peter Cale; Barbara Marcolla; Alan G. Barr; Alan G. Barr; Scott D. Miller; Lutz Merbold; Ivan Schroder; Joseph Verfaillie; Stefan K. Arndt; Scott R. Saleska; Nicolas Delpierre; Catharine van Ingen; Christine Moureaux; Annalea Lohila; Annalea Lohila; Gabriela Posse; Bernard Heinesch; Pierpaolo Duce; Raimundo Cosme de Oliveira; Kenneth J. Davis; Markus Hehn; Torben R. Christensen; Tilden P. Meyers; Werner L. Kutsch; Lindsay B. Hutley; Üllar Rannik; W.W.P. Jans; Riccardo Valentini; Myroslava Khomik; Myroslava Khomik; Pierre Cellier; Ayumi Kotani; Xiaoqin Dai; Marta Galvagno; Frans-Jan W. Parmentier; Frans-Jan W. Parmentier; Eric Dufrêne; Marius Schmidt; Birger Ulf Hansen; Alessio Collalti; Alessio Collalti; Ivan Shironya; Christian Brümmer; Russell L. Scott; Serge Rambal; Jonas Ardö; Natalia Restrepo-Coupe; Donatella Zona; Elizabeth A. Walter-Shea; Russell K. Monson; Silvano Fares; Sean P. Burns; Sean P. Burns; Mauro Cavagna; Guoyi Zhou; Suzanne M. Prober; Juha Pekka Tuovinen; Georgia R. Koerber; Yuelin Li; Alexander Knohl; Mikhail Mastepanov; Mikhail Mastepanov; Yanhong Tang; Johan Neirynck; Matthew Northwood; Pauline Buysse; Thomas Grünwald; Sabina Dore; N. Pirk; N. Pirk; Hiroki Ikawa; Craig Macfarlane; Jean-Marc Limousin; Carlos Marcelo Di Bella; Leiming Zhang; Juha Hatakka; Margaret S. Torn; Mika Aurela; Bert Gielen; Jiquan Chen; Regine Maier; Karl Schneider; Christian Wille; Nina Buchmann; Daniel Berveiller; Peter D. Blanken; Wayne S. Meyer; Dennis D. Baldocchi; Benjamin Loubet; Giovanni Manca; Hatim Abdalla M. ElKhidir; James Cleverly; Harry McCaughey; Agnès de Grandcourt; Matthias Peichl; Adam J. Liska; Jonathan E. Thom; Christian Bernhofer; Jean Marc Bonnefond; Alexander Graf; Roser Matamala; M. Goeckede; Marian Pavelka; Hank A. Margolis; Eugénie Paul-Limoges; Andrew S. Kowalski; Taro Nakai; Taro Nakai; Marcelo D. Nosetto; Tomomichi Kato; Ray Leuning; Beniamino Gioli; Marc Aubinet; Tuomas Laurila; Andrej Varlagin; Ignacio Goded; David R. Bowling; Nigel J. Tapper; Ana López-Ballesteros; Denis Loustau; Iris Feigenwinter; Uta Moderow; Edoardo Cremonese; Gianluca Filippa; Domenico Vitale; Abdelrahman Elbashandy; Gilberto Pastorello; Ettore D'Andrea; Gil Bohrer; Thomas L. Powell; Serena Marras; Daniela Famulari; Christopher M. Gough; Enrique P. Sánchez-Cañete; Satoru Takanashi; Michael J. Liddell; Jason Brodeur; Marc Fischer; Zoran Nesic; William J. Massman; Janina Klatt; Samuli Launiainen; Anne De Ligne; Leonardo Montagnani; Sebastian Wolf; Rainer Steinbrecher; Yingnian Li; Donatella Spano; A. Ribeca; Rosvel Bracho; Walter C. Oechel; B.R. Reverter; Jiří Dušek; Sebastian Westermann; Rachhpal S. Jassal; Derek Eamus; Claudia Consalvo; Claudia Consalvo; Marty Humphrey; Timo Vesala; Cristina Poindexter; Jeffrey P. Walker; Humberto Ribeiro da Rocha; Paul V. Bolstad; Elise Pendall; Diego Polidori; Peter S. Curtis; Chad Hanson; Francisco Domingo; Jason Beringer;pmid: 32647314
pmc: PMC7347557
AbstractThe FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
CORE arrow_drop_down Archivio della ricerca- Università di Roma La SapienzaArticle . 2020License: CC BYData sources: Archivio della ricerca- Università di Roma La SapienzaGFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam)Article . 2020License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Full-Text: https://doi.org/10.6084/m9.figshare.12295910Data sources: Bielefeld Academic Search Engine (BASE)CGIAR CGSpace (Consultative Group on International Agricultural Research)Article . 2020License: CC BYFull-Text: https://hdl.handle.net/10568/108878Data sources: Bielefeld Academic Search Engine (BASE)CIRAD: HAL (Agricultural Research for Development)Article . 2020Full-Text: https://hal.science/hal-03778635Data sources: Bielefeld Academic Search Engine (BASE)Universitet i Oslo: Digitale utgivelser ved UiO (DUO)Article . 2020License: CC BYFull-Text: http://hdl.handle.net/10852/81470Data sources: Bielefeld Academic Search Engine (BASE)KITopen (Karlsruhe Institute of Technologie)Article . 2020License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Fondazione Edmund Mach: IRIS-OpenPubArticle . 2020Full-Text: http://hdl.handle.net/10449/64207Data sources: Bielefeld Academic Search Engine (BASE)The University of Melbourne: Digital RepositoryArticle . 2020License: CC BYFull-Text: http://hdl.handle.net/11343/244534Data sources: Bielefeld Academic Search Engine (BASE)Edith Cowan University (ECU, Australia): Research OnlineArticle . 2020Full-Text: https://ro.ecu.edu.au/ecuworkspost2013/9096Data sources: Bielefeld Academic Search Engine (BASE)Institut National de la Recherche Agronomique: ProdINRAArticle . 2020Full-Text: https://doi.org/10.6084/m9.figshare.12295910Data sources: Bielefeld Academic Search Engine (BASE)University of California: eScholarshipArticle . 2020Full-Text: https://escholarship.org/uc/item/2xf0f1djData sources: Bielefeld Academic Search Engine (BASE)The University of Adelaide: Digital LibraryArticle . 2020License: CC BYFull-Text: http://hdl.handle.net/2440/129213Data sources: Bielefeld Academic Search Engine (BASE)James Cook University, Australia: ResearchOnline@JCUArticle . 2020Full-Text: https://doi.org/10.1038/s41597-020-0534-3Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Full-Text: https://hal.science/hal-03778635Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2020Full-Text: https://hal.science/hal-03778635Data sources: Bielefeld Academic Search Engine (BASE)Recolector de Ciencia Abierta, RECOLECTAArticle . 2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTA2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTAScientific DataArticle . 2020Online Research Database In TechnologyArticle . 2020Data sources: Online Research Database In TechnologyHELDA - Digital Repository of the University of HelsinkiArticle . 2021 . Peer-reviewedData sources: HELDA - Digital Repository of the University of HelsinkiPublikationenserver der Georg-August-Universität GöttingenArticle . 2021Institutional Repository Universiteit AntwerpenArticle . 2020Data sources: Institutional Repository Universiteit AntwerpenUniversity of Oulu Repository - JultikaArticle . 2020Data sources: University of Oulu Repository - JultikaCopenhagen University Research Information SystemArticle . 2020Data sources: Copenhagen University Research Information SystemRepository of the Czech Academy of SciencesArticle . 2020Data sources: Repository of the Czech Academy of SciencesGöttingen Research Online PublicationsArticle . 2021Data sources: Göttingen Research Online PublicationsGFZ German Research Centre for GeosciencesArticle . 2020License: CC BYData sources: GFZ German Research Centre for GeosciencesWageningen Staff PublicationsArticle . 2020License: CC BYData sources: Wageningen Staff PublicationsWageningen Staff PublicationsArticle . 2021License: CC BYData sources: Wageningen Staff PublicationsUniversity of Western Sydney (UWS): Research DirectArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)University of Copenhagen: ResearchArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)Repositorio Institucional Universidad de GranadaArticle . 2020License: CC BYData sources: Repositorio Institucional Universidad de GranadaeScholarship - University of CaliforniaArticle . 2020Data sources: eScholarship - University of CaliforniaThe University of Queensland: UQ eSpaceArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)Università degli studi della Tuscia: Unitus DSpaceArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 896 citations 896 popularity Top 0.01% influence Top 1% impulse Top 0.01% Powered by BIP!
more_vert CORE arrow_drop_down Archivio della ricerca- Università di Roma La SapienzaArticle . 2020License: CC BYData sources: Archivio della ricerca- Università di Roma La SapienzaGFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam)Article . 2020License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Full-Text: https://doi.org/10.6084/m9.figshare.12295910Data sources: Bielefeld Academic Search Engine (BASE)CGIAR CGSpace (Consultative Group on International Agricultural Research)Article . 2020License: CC BYFull-Text: https://hdl.handle.net/10568/108878Data sources: Bielefeld Academic Search Engine (BASE)CIRAD: HAL (Agricultural Research for Development)Article . 2020Full-Text: https://hal.science/hal-03778635Data sources: Bielefeld Academic Search Engine (BASE)Universitet i Oslo: Digitale utgivelser ved UiO (DUO)Article . 2020License: CC BYFull-Text: http://hdl.handle.net/10852/81470Data sources: Bielefeld Academic Search Engine (BASE)KITopen (Karlsruhe Institute of Technologie)Article . 2020License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Fondazione Edmund Mach: IRIS-OpenPubArticle . 2020Full-Text: http://hdl.handle.net/10449/64207Data sources: Bielefeld Academic Search Engine (BASE)The University of Melbourne: Digital RepositoryArticle . 2020License: CC BYFull-Text: http://hdl.handle.net/11343/244534Data sources: Bielefeld Academic Search Engine (BASE)Edith Cowan University (ECU, Australia): Research OnlineArticle . 2020Full-Text: https://ro.ecu.edu.au/ecuworkspost2013/9096Data sources: Bielefeld Academic Search Engine (BASE)Institut National de la Recherche Agronomique: ProdINRAArticle . 2020Full-Text: https://doi.org/10.6084/m9.figshare.12295910Data sources: Bielefeld Academic Search Engine (BASE)University of California: eScholarshipArticle . 2020Full-Text: https://escholarship.org/uc/item/2xf0f1djData sources: Bielefeld Academic Search Engine (BASE)The University of Adelaide: Digital LibraryArticle . 2020License: CC BYFull-Text: http://hdl.handle.net/2440/129213Data sources: Bielefeld Academic Search Engine (BASE)James Cook University, Australia: ResearchOnline@JCUArticle . 2020Full-Text: https://doi.org/10.1038/s41597-020-0534-3Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Full-Text: https://hal.science/hal-03778635Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2020Full-Text: https://hal.science/hal-03778635Data sources: Bielefeld Academic Search Engine (BASE)Recolector de Ciencia Abierta, RECOLECTAArticle . 2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTA2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTAScientific DataArticle . 2020Online Research Database In TechnologyArticle . 2020Data sources: Online Research Database In TechnologyHELDA - Digital Repository of the University of HelsinkiArticle . 2021 . 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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2006Publisher:Springer Science and Business Media LLC Russell K. Monson; Steven K. Schmidt; Sean P. Burns; David L. Lipson; Andrew A. Turnipseed; Mark W. Williams; Anthony C. Delany;doi: 10.1038/nature04555
pmid: 16467835
Most terrestrial carbon sequestration at mid-latitudes in the Northern Hemisphere occurs in seasonal, montane forest ecosystems. Winter respiratory carbon dioxide losses from these ecosystems are high, and over half of the carbon assimilated by photosynthesis in the summer can be lost the following winter. The amount of winter carbon dioxide loss is potentially susceptible to changes in the depth of the snowpack; a shallower snowpack has less insulation potential, causing colder soil temperatures and potentially lower soil respiration rates. Recent climate analyses have shown widespread declines in the winter snowpack of mountain ecosystems in the western USA and Europe that are coupled to positive temperature anomalies. Here we study the effect of changes in snow cover on soil carbon cycling within the context of natural climate variation. We use a six-year record of net ecosystem carbon dioxide exchange in a subalpine forest to show that years with a reduced winter snowpack are accompanied by significantly lower rates of soil respiration. Furthermore, we show that the cause of the high sensitivity of soil respiration rate to changes in snow depth is a unique soil microbial community that exhibits exponential growth and high rates of substrate utilization at the cold temperatures that exist beneath the snow. Our observations suggest that a warmer climate may change soil carbon sequestration rates in forest ecosystems owing to changes in the depth of the insulating snow cover.
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For further information contact us at helpdesk@openaire.eu481 citations 481 popularity Top 1% influence Top 1% impulse Top 1% Powered by BIP!
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description Publicationkeyboard_double_arrow_right Other literature type 2010Publisher:OpenAlex Chuixiang Yi; D. M. Ricciuto; Runze Li; John Wolbeck; Xiyan Xu; Mats Nilsson; Luís Aires; J. D. Albertson; Christof Ammann; M. Altaf Arain; Alessandro Araújo; Marc Aubinet; Mika Aurela; Zoltán Barcza; Alan G. Barr; Paul Berbigier; Jason Beringer; Christian Bernhofer; Andrew Black; Paul V. Bolstad; Fred C. Bosveld; M. S. J. Broadmeadow; Nina Buchmann; Sean P. Burns; Pierre Cellier; Jingming Chen; Jiquan Chen; Philippe Ciais; Robert Clement; Bruce D. Cook; Peter S. Curtis; D. B. Dail; Ebba Dellwik; Nicolas Delpierre; Ankur R. Desai; Sabina Dore; D. Dragoni; Bert G. Drake; Éric Dufrêne; Allison L. Dunn; J.A. Elbers; Werner Eugster; Matthias Falk; Christian Feigenwinter; Lawrence B. Flanagan; Thomas Foken; J. M. Frank; J. Fuhrer; Damiano Gianelle; Allen H. Goldstein; Mike Goulden; André Granier; T. Gruenwald; Lianhong Gu; Haiqiang Guo; Albin Hammerle; Shijie Han; Niall P. Hanan; László Haszpra; Bernard Heinesch; Carole Helfter; Dimmie Hendriks; Lindsay B. Hutley; Andreas Ibrom; C. Jacobs; Torbjoern Johansson; Marjan Jongen; Gabriel G. Katul; Gerard Kiely; Katja Klumpp; Alexander Knohl; Thomas E. Kolb; Werner L. Kutsch; Peter M. Lafleur; Tuomas Laurila; R. Leuning; Anders Lindroth; Heping Li; Benjamin Loubet; Giovanni Manca; Michal V. Marek; Hank A. Margolis; Timothy A. Martin; W. J. Massman; Roser Matamala; Giorgio Matteucci; Harry McCaughey; Lutz Merbold; Tilden Meyers; Mirco Migliavacca; Franco Miglietta; Laurent Misson; Meelis Moelder; John Moncrieff; Russell K. Monson; Leonardo Montagnani; M. Montes-Helu; Eddy Moors; Christine Moureaux; M. M. Mukelabai;Comprendre les relations entre le climat et l'échange de carbone par les écosystèmes terrestres est essentiel pour prédire les niveaux futurs de dioxyde de carbone atmosphérique en raison des effets d'accélération potentiels des rétroactions positives du cycle climat-carbone. Cependant, les relations directement observées entre le climat et l'échange de CO2 terrestre avec l'atmosphère à travers les biomes et les continents font défaut. Nous présentons ici des données décrivant les relations entre l'échange net de carbone par les écosystèmes (NEE) et les facteurs climatiques tels que mesurés à l'aide de la méthode de covariance de Foucault sur 125 sites uniques dans divers écosystèmes sur six continents avec un total de 559 années de site. Nous trouvons que le NEE observé aux sites de covariance tourbillonnaire est (1) une fonction forte de la température annuelle moyenne aux latitudes moyennes et élevées, (2) une fonction forte de la sécheresse aux latitudes moyennes et basses, et (3) une fonction à la fois de la température et de la sécheresse autour de la ceinture moyenne-latitudinale (45°N). La sensibilité du NEE à la température annuelle moyenne se décompose à ~ 16 °C (une valeur seuil de la température annuelle moyenne), au-delà de laquelle aucune augmentation supplémentaire de l'absorption de CO2 avec la température n'a été observée et la sécheresse influence les règles de dépassement de l'influence de la température. Comprender las relaciones entre el clima y el intercambio de carbono por parte de los ecosistemas terrestres es fundamental para predecir los niveles futuros de dióxido de carbono en la atmósfera debido a los posibles efectos aceleradores de las retroalimentaciones positivas del ciclo clima-carbono. Sin embargo, faltan relaciones directamente observadas entre el clima y el intercambio terrestre de CO2 con la atmósfera a través de biomas y continentes. Aquí presentamos datos que describen las relaciones entre el intercambio neto de carbono (NEE) del ecosistema y los factores climáticos medidos utilizando el método de covarianza de remolinos en 125 sitios únicos en varios ecosistemas de seis continentes con un total de 559 años-sitio. Encontramos que la NEE observada en los sitios de covarianza de remolinos es (1) una fuerte función de la temperatura media anual en latitudes medias y altas, (2) una fuerte función de sequedad en latitudes medias y bajas, y (3) una función tanto de la temperatura como de la sequedad alrededor del cinturón latitudinal medio (45°N). La sensibilidad de NEE a la temperatura media anual se rompe a ~ 16 °C (un valor umbral de la temperatura media anual), por encima del cual no se observó ningún aumento adicional de la absorción de CO2 con la temperatura y la influencia de la sequedad anula la influencia de la temperatura. Understanding the relationships between climate and carbon exchange by terrestrial ecosystems is critical to predict future levels of atmospheric carbon dioxide because of the potential accelerating effects of positive climate–carbon cycle feedbacks. However, directly observed relationships between climate and terrestrial CO2 exchange with the atmosphere across biomes and continents are lacking. Here we present data describing the relationships between net ecosystem exchange of carbon (NEE) and climate factors as measured using the eddy covariance method at 125 unique sites in various ecosystems over six continents with a total of 559 site-years. We find that NEE observed at eddy covariance sites is (1) a strong function of mean annual temperature at mid- and high-latitudes, (2) a strong function of dryness at mid- and low-latitudes, and (3) a function of both temperature and dryness around the mid-latitudinal belt (45°N). The sensitivity of NEE to mean annual temperature breaks down at ~ 16 °C (a threshold value of mean annual temperature), above which no further increase of CO2 uptake with temperature was observed and dryness influence overrules temperature influence. يعد فهم العلاقات بين المناخ وتبادل الكربون بواسطة النظم الإيكولوجية الأرضية أمرًا بالغ الأهمية للتنبؤ بالمستويات المستقبلية لثاني أكسيد الكربون في الغلاف الجوي بسبب التأثيرات المتسارعة المحتملة للتغذية المرتدة الإيجابية لدورة المناخ والكربون. ومع ذلك، لا توجد علاقات ملحوظة مباشرة بين المناخ والتبادل الأرضي لثاني أكسيد الكربون مع الغلاف الجوي عبر المناطق الحيوية والقارات. نقدم هنا بيانات تصف العلاقات بين صافي تبادل النظام البيئي للكربون (NEE) والعوامل المناخية كما تم قياسها باستخدام طريقة التباين الدوامي في 125 موقعًا فريدًا في أنظمة بيئية مختلفة عبر ست قارات بإجمالي 559 سنة موقع. نجد أن NEE التي لوحظت في مواقع التباين الدوامي هي (1) وظيفة قوية لمتوسط درجة الحرارة السنوية عند خطوط العرض المتوسطة والعالية، (2) وظيفة قوية للجفاف عند خطوط العرض المتوسطة والمنخفضة، و (3) وظيفة لكل من درجة الحرارة والجفاف حول حزام العرض المتوسط (45درجةشمالاً). تنهار حساسية NEE لمتوسط درجة الحرارة السنوية عند حوالي 16 درجة مئوية (قيمة عتبة لمتوسط درجة الحرارة السنوية)، والتي لم يلاحظ فوقها أي زيادة أخرى في امتصاص ثاني أكسيد الكربون مع درجة الحرارة ويتجاوز تأثير الجفاف تأثير درجة الحرارة.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2019Publisher:American Geophysical Union (AGU) Authors: David M. Lawrence; Sean P. Burns; Sean P. Burns; Sean Swenson;doi: 10.1029/2018ms001476
AbstractAtmospheric models used for weather prediction and future climate projections rely on land models to calculate surface boundary conditions. Observations of near‐surface states and fluxes made at flux measurement sites provide valuable data with which to assess the quality of simulated lower boundary conditions. A previous assessment of the Community Land Model version 4.5 using data from the Niwot Ridge Subalpine Forest AmeriFlux tower showed that simulated latent heat fluxes could be improved by adjusting a parameter describing the maximum leaf wetted area, but biases in midday sensible heat flux and nighttime momentum flux were generally not reduced by model parameter perturbations. These biases are related to the model's lack of heat storage in vegetation biomass. A biomass heat capacity is parameterized in Community Land Model version 5 with measurable quantities such as canopy height, diameter at breast height, and tree number density. After implementing a parameterization describing the heat transfer between the forest biomass and the canopy air space, the biases in the mean midday sensible heat and mean nighttime momentum fluxes at Niwot Ridge are reduced from 47 to 13 W/m2 and from 0.12 to −0.03 m/s, respectively. The bias in the mean nighttime canopy air temperature was reduced from −5.9 to 0.4 °C. Additional simulations at other flux tower sites demonstrate a consistent reduction in midday sensible heat flux, a lower ratio of the sum of sensible and latent heat flux to net radiation, and an increase in nighttime canopy temperatures.
Journal of Advances ... arrow_drop_down Journal of Advances in Modeling Earth SystemsArticle . 2019 . Peer-reviewedLicense: CC BY NC NDData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess Routesgold 24 citations 24 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Journal of Advances ... arrow_drop_down Journal of Advances in Modeling Earth SystemsArticle . 2019 . Peer-reviewedLicense: CC BY NC NDData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1029/2018ms001476&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal , Data Paper 2020Embargo end date: 09 Jul 2020 Germany, Italy, Denmark, Italy, Italy, Australia, Germany, Germany, Belgium, Australia, Italy, Netherlands, Belgium, Italy, Australia, Italy, Russian Federation, Germany, Czech Republic, Germany, Italy, Australia, Netherlands, Australia, Switzerland, Italy, Australia, Germany, Netherlands, Norway, Germany, Australia, Australia, Italy, Finland, Sweden, Czech Republic, France, Spain, Denmark, Netherlands, Finland, United StatesPublisher:Springer Science and Business Media LLC Publicly fundedFunded by:UKRI | RootDetect: Remote Detect...UKRI| RootDetect: Remote Detection and Precision Management of Root HealthAndreas Ibrom; Bruno De Cinti; Jean Marc Ourcival; Vincenzo Magliulo; Onil Bergeron; M. Altaf Arain; Andrew Feitz; Zulia Mayari Sanchez-Mejia; Christof Ammann; Yann Nouvellon; Siyan Ma; Brian D. Amiro; Kim Pilegaard; Eddy Moors; Michele Tomassucci; Asko Noormets; Shawn Urbanski; Damiano Gianelle; Anatoly A. Gitelson; E. Canfora; You Wei Cheah; Ko van Huissteden; Shicheng Jiang; Hans Peter Schmid; Albin Hammerle; Brent E. Ewers; Virginie Moreaux; Housen Chu; Anne Griebel; Timothy J. Arkebauer; Peter Cale; Barbara Marcolla; Alan G. Barr; Alan G. Barr; Scott D. Miller; Lutz Merbold; Ivan Schroder; Joseph Verfaillie; Stefan K. Arndt; Scott R. Saleska; Nicolas Delpierre; Catharine van Ingen; Christine Moureaux; Annalea Lohila; Annalea Lohila; Gabriela Posse; Bernard Heinesch; Pierpaolo Duce; Raimundo Cosme de Oliveira; Kenneth J. Davis; Markus Hehn; Torben R. Christensen; Tilden P. Meyers; Werner L. Kutsch; Lindsay B. Hutley; Üllar Rannik; W.W.P. Jans; Riccardo Valentini; Myroslava Khomik; Myroslava Khomik; Pierre Cellier; Ayumi Kotani; Xiaoqin Dai; Marta Galvagno; Frans-Jan W. Parmentier; Frans-Jan W. Parmentier; Eric Dufrêne; Marius Schmidt; Birger Ulf Hansen; Alessio Collalti; Alessio Collalti; Ivan Shironya; Christian Brümmer; Russell L. Scott; Serge Rambal; Jonas Ardö; Natalia Restrepo-Coupe; Donatella Zona; Elizabeth A. Walter-Shea; Russell K. Monson; Silvano Fares; Sean P. Burns; Sean P. Burns; Mauro Cavagna; Guoyi Zhou; Suzanne M. Prober; Juha Pekka Tuovinen; Georgia R. Koerber; Yuelin Li; Alexander Knohl; Mikhail Mastepanov; Mikhail Mastepanov; Yanhong Tang; Johan Neirynck; Matthew Northwood; Pauline Buysse; Thomas Grünwald; Sabina Dore; N. Pirk; N. Pirk; Hiroki Ikawa; Craig Macfarlane; Jean-Marc Limousin; Carlos Marcelo Di Bella; Leiming Zhang; Juha Hatakka; Margaret S. Torn; Mika Aurela; Bert Gielen; Jiquan Chen; Regine Maier; Karl Schneider; Christian Wille; Nina Buchmann; Daniel Berveiller; Peter D. Blanken; Wayne S. Meyer; Dennis D. Baldocchi; Benjamin Loubet; Giovanni Manca; Hatim Abdalla M. ElKhidir; James Cleverly; Harry McCaughey; Agnès de Grandcourt; Matthias Peichl; Adam J. Liska; Jonathan E. Thom; Christian Bernhofer; Jean Marc Bonnefond; Alexander Graf; Roser Matamala; M. Goeckede; Marian Pavelka; Hank A. Margolis; Eugénie Paul-Limoges; Andrew S. Kowalski; Taro Nakai; Taro Nakai; Marcelo D. Nosetto; Tomomichi Kato; Ray Leuning; Beniamino Gioli; Marc Aubinet; Tuomas Laurila; Andrej Varlagin; Ignacio Goded; David R. Bowling; Nigel J. Tapper; Ana López-Ballesteros; Denis Loustau; Iris Feigenwinter; Uta Moderow; Edoardo Cremonese; Gianluca Filippa; Domenico Vitale; Abdelrahman Elbashandy; Gilberto Pastorello; Ettore D'Andrea; Gil Bohrer; Thomas L. Powell; Serena Marras; Daniela Famulari; Christopher M. Gough; Enrique P. Sánchez-Cañete; Satoru Takanashi; Michael J. Liddell; Jason Brodeur; Marc Fischer; Zoran Nesic; William J. Massman; Janina Klatt; Samuli Launiainen; Anne De Ligne; Leonardo Montagnani; Sebastian Wolf; Rainer Steinbrecher; Yingnian Li; Donatella Spano; A. Ribeca; Rosvel Bracho; Walter C. Oechel; B.R. Reverter; Jiří Dušek; Sebastian Westermann; Rachhpal S. Jassal; Derek Eamus; Claudia Consalvo; Claudia Consalvo; Marty Humphrey; Timo Vesala; Cristina Poindexter; Jeffrey P. Walker; Humberto Ribeiro da Rocha; Paul V. Bolstad; Elise Pendall; Diego Polidori; Peter S. Curtis; Chad Hanson; Francisco Domingo; Jason Beringer;pmid: 32647314
pmc: PMC7347557
AbstractThe FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
CORE arrow_drop_down Archivio della ricerca- Università di Roma La SapienzaArticle . 2020License: CC BYData sources: Archivio della ricerca- Università di Roma La SapienzaGFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam)Article . 2020License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Full-Text: https://doi.org/10.6084/m9.figshare.12295910Data sources: Bielefeld Academic Search Engine (BASE)CGIAR CGSpace (Consultative Group on International Agricultural Research)Article . 2020License: CC BYFull-Text: https://hdl.handle.net/10568/108878Data sources: Bielefeld Academic Search Engine (BASE)CIRAD: HAL (Agricultural Research for Development)Article . 2020Full-Text: https://hal.science/hal-03778635Data sources: Bielefeld Academic Search Engine (BASE)Universitet i Oslo: Digitale utgivelser ved UiO (DUO)Article . 2020License: CC BYFull-Text: http://hdl.handle.net/10852/81470Data sources: Bielefeld Academic Search Engine (BASE)KITopen (Karlsruhe Institute of Technologie)Article . 2020License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Fondazione Edmund Mach: IRIS-OpenPubArticle . 2020Full-Text: http://hdl.handle.net/10449/64207Data sources: Bielefeld Academic Search Engine (BASE)The University of Melbourne: Digital RepositoryArticle . 2020License: CC BYFull-Text: http://hdl.handle.net/11343/244534Data sources: Bielefeld Academic Search Engine (BASE)Edith Cowan University (ECU, Australia): Research OnlineArticle . 2020Full-Text: https://ro.ecu.edu.au/ecuworkspost2013/9096Data sources: Bielefeld Academic Search Engine (BASE)Institut National de la Recherche Agronomique: ProdINRAArticle . 2020Full-Text: https://doi.org/10.6084/m9.figshare.12295910Data sources: Bielefeld Academic Search Engine (BASE)University of California: eScholarshipArticle . 2020Full-Text: https://escholarship.org/uc/item/2xf0f1djData sources: Bielefeld Academic Search Engine (BASE)The University of Adelaide: Digital LibraryArticle . 2020License: CC BYFull-Text: http://hdl.handle.net/2440/129213Data sources: Bielefeld Academic Search Engine (BASE)James Cook University, Australia: ResearchOnline@JCUArticle . 2020Full-Text: https://doi.org/10.1038/s41597-020-0534-3Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Full-Text: https://hal.science/hal-03778635Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2020Full-Text: https://hal.science/hal-03778635Data sources: Bielefeld Academic Search Engine (BASE)Recolector de Ciencia Abierta, RECOLECTAArticle . 2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTA2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTAScientific DataArticle . 2020Online Research Database In TechnologyArticle . 2020Data sources: Online Research Database In TechnologyHELDA - Digital Repository of the University of HelsinkiArticle . 2021 . Peer-reviewedData sources: HELDA - Digital Repository of the University of HelsinkiPublikationenserver der Georg-August-Universität GöttingenArticle . 2021Institutional Repository Universiteit AntwerpenArticle . 2020Data sources: Institutional Repository Universiteit AntwerpenUniversity of Oulu Repository - JultikaArticle . 2020Data sources: University of Oulu Repository - JultikaCopenhagen University Research Information SystemArticle . 2020Data sources: Copenhagen University Research Information SystemRepository of the Czech Academy of SciencesArticle . 2020Data sources: Repository of the Czech Academy of SciencesGöttingen Research Online PublicationsArticle . 2021Data sources: Göttingen Research Online PublicationsGFZ German Research Centre for GeosciencesArticle . 2020License: CC BYData sources: GFZ German Research Centre for GeosciencesWageningen Staff PublicationsArticle . 2020License: CC BYData sources: Wageningen Staff PublicationsWageningen Staff PublicationsArticle . 2021License: CC BYData sources: Wageningen Staff PublicationsUniversity of Western Sydney (UWS): Research DirectArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)University of Copenhagen: ResearchArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)Repositorio Institucional Universidad de GranadaArticle . 2020License: CC BYData sources: Repositorio Institucional Universidad de GranadaeScholarship - University of CaliforniaArticle . 2020Data sources: eScholarship - University of CaliforniaThe University of Queensland: UQ eSpaceArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)Università degli studi della Tuscia: Unitus DSpaceArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert CORE arrow_drop_down Archivio della ricerca- Università di Roma La SapienzaArticle . 2020License: CC BYData sources: Archivio della ricerca- Università di Roma La SapienzaGFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam)Article . 2020License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Full-Text: https://doi.org/10.6084/m9.figshare.12295910Data sources: Bielefeld Academic Search Engine (BASE)CGIAR CGSpace (Consultative Group on International Agricultural Research)Article . 2020License: CC BYFull-Text: https://hdl.handle.net/10568/108878Data sources: Bielefeld Academic Search Engine (BASE)CIRAD: HAL (Agricultural Research for Development)Article . 2020Full-Text: https://hal.science/hal-03778635Data sources: Bielefeld Academic Search Engine (BASE)Universitet i Oslo: Digitale utgivelser ved UiO (DUO)Article . 2020License: CC BYFull-Text: http://hdl.handle.net/10852/81470Data sources: Bielefeld Academic Search Engine (BASE)KITopen (Karlsruhe Institute of Technologie)Article . 2020License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Fondazione Edmund Mach: IRIS-OpenPubArticle . 2020Full-Text: http://hdl.handle.net/10449/64207Data sources: Bielefeld Academic Search Engine (BASE)The University of Melbourne: Digital RepositoryArticle . 2020License: CC BYFull-Text: http://hdl.handle.net/11343/244534Data sources: Bielefeld Academic Search Engine (BASE)Edith Cowan University (ECU, Australia): Research OnlineArticle . 2020Full-Text: https://ro.ecu.edu.au/ecuworkspost2013/9096Data sources: Bielefeld Academic Search Engine (BASE)Institut National de la Recherche Agronomique: ProdINRAArticle . 2020Full-Text: https://doi.org/10.6084/m9.figshare.12295910Data sources: Bielefeld Academic Search Engine (BASE)University of California: eScholarshipArticle . 2020Full-Text: https://escholarship.org/uc/item/2xf0f1djData sources: Bielefeld Academic Search Engine (BASE)The University of Adelaide: Digital LibraryArticle . 2020License: CC BYFull-Text: http://hdl.handle.net/2440/129213Data sources: Bielefeld Academic Search Engine (BASE)James Cook University, Australia: ResearchOnline@JCUArticle . 2020Full-Text: https://doi.org/10.1038/s41597-020-0534-3Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Full-Text: https://hal.science/hal-03778635Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2020Full-Text: https://hal.science/hal-03778635Data sources: Bielefeld Academic Search Engine (BASE)Recolector de Ciencia Abierta, RECOLECTAArticle . 2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTA2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTAScientific DataArticle . 2020Online Research Database In TechnologyArticle . 2020Data sources: Online Research Database In TechnologyHELDA - Digital Repository of the University of HelsinkiArticle . 2021 . Peer-reviewedData sources: HELDA - Digital Repository of the University of HelsinkiPublikationenserver der Georg-August-Universität GöttingenArticle . 2021Institutional Repository Universiteit AntwerpenArticle . 2020Data sources: Institutional Repository Universiteit AntwerpenUniversity of Oulu Repository - JultikaArticle . 2020Data sources: University of Oulu Repository - JultikaCopenhagen University Research Information SystemArticle . 2020Data sources: Copenhagen University Research Information SystemRepository of the Czech Academy of SciencesArticle . 2020Data sources: Repository of the Czech Academy of SciencesGöttingen Research Online PublicationsArticle . 2021Data sources: Göttingen Research Online PublicationsGFZ German Research Centre for GeosciencesArticle . 2020License: CC BYData sources: GFZ German Research Centre for GeosciencesWageningen Staff PublicationsArticle . 2020License: CC BYData sources: Wageningen Staff PublicationsWageningen Staff PublicationsArticle . 2021License: CC BYData sources: Wageningen Staff PublicationsUniversity of Western Sydney (UWS): Research DirectArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)University of Copenhagen: ResearchArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)Repositorio Institucional Universidad de GranadaArticle . 2020License: CC BYData sources: Repositorio Institucional Universidad de GranadaeScholarship - University of CaliforniaArticle . 2020Data sources: eScholarship - University of CaliforniaThe University of Queensland: UQ eSpaceArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)Università degli studi della Tuscia: Unitus DSpaceArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2006Publisher:Springer Science and Business Media LLC Russell K. Monson; Steven K. Schmidt; Sean P. Burns; David L. Lipson; Andrew A. Turnipseed; Mark W. Williams; Anthony C. Delany;doi: 10.1038/nature04555
pmid: 16467835
Most terrestrial carbon sequestration at mid-latitudes in the Northern Hemisphere occurs in seasonal, montane forest ecosystems. Winter respiratory carbon dioxide losses from these ecosystems are high, and over half of the carbon assimilated by photosynthesis in the summer can be lost the following winter. The amount of winter carbon dioxide loss is potentially susceptible to changes in the depth of the snowpack; a shallower snowpack has less insulation potential, causing colder soil temperatures and potentially lower soil respiration rates. Recent climate analyses have shown widespread declines in the winter snowpack of mountain ecosystems in the western USA and Europe that are coupled to positive temperature anomalies. Here we study the effect of changes in snow cover on soil carbon cycling within the context of natural climate variation. We use a six-year record of net ecosystem carbon dioxide exchange in a subalpine forest to show that years with a reduced winter snowpack are accompanied by significantly lower rates of soil respiration. Furthermore, we show that the cause of the high sensitivity of soil respiration rate to changes in snow depth is a unique soil microbial community that exhibits exponential growth and high rates of substrate utilization at the cold temperatures that exist beneath the snow. Our observations suggest that a warmer climate may change soil carbon sequestration rates in forest ecosystems owing to changes in the depth of the insulating snow cover.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu481 citations 481 popularity Top 1% influence Top 1% impulse Top 1% Powered by BIP!
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