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Start Over Author "Bolstad, Paul V." Topic eddy covariance
11 results on '"Bolstad, Paul V."'

1. The FLUXNET 20165 dataset and the ONEFlux processing pipeline for eddy covariance data

Author

Pastorello, Gilberto, Trotta, Carlo, Canfora, Eleonora, Chu, Housen, Christianson, Danielle, Cheah, You - Wei, Poindexter, Cristina, Chen, Jiquan, Elbashandy, Abdelrahman, Humphrey, Marty, Isaac, Peter, Polidori, Diego, Riveca, Alessio, van Ingen, Catharine, Zhang, Leiming, Amiro, Brian, Ammann, Christof, Altaf Arain, M., Ardo, Jonas, Arkebauer, Timothy, Arndt, Stefan K., Arriga, Nicola, Aubinet, Marc, Aurela, Mika, Baldocchi, Dennis, Barr, Alan, Beamesderfer, Eric, Belelli Marchesini, Luca, Bergeron, Onil, Beringer, Jason, Bernhofer, Christian, Berveiller, Daniel, Billesbach, Dave, Black, Thomas Andrew, Blanken, Peter D., Bohrer, Gil, Boike, Julia, Bolstad, Paul V., Bonal, Damien, Bonnefond, Jean - Marc, Bowling, David R., Bracho, Rosuel, Brodeur, Jason, Brummer, Christian, Buchmann, Nina, Burban, Benoit, Burns, Sean P., Buysse, Pauline, Cale, Peter, Cavagna, Mauro, Cellier, Pierre, Chen, Shiping, Chini, Issac, Christensen, Storben, Cleverly, James, Collatti, Alessio, Consalvo, Claudia, Cook, Bruce, Cook, David, Coversolle, Carole, Cremonese, Edoardo, Curtis, Peter, D'Andrea, Ettore, da Rocha, Humberto, Dai, Xiaoqin, Davis, Kenneth, De Cinti, Bruno, de Grandcourt, agnes, De Ligne, Anne, De Oliveira, Raimundo C., Delpierre, Nicolas, Desai, Ankur R., Di Bella, Carlos Marcelo, di Tommasi, Paul, Dolman, Han, Domingo, Francisco, Dong, Gang, Dore, Sabina, Duce, Pierpaolo, Dufrêne, Eric, Dunn, Allison, Dušek, Jiří, Eamus, Derek, Eichelmann, Uwe, ElKhidir, Hatim abdalla M., Eugster, Werner, Ewenz, Cacilia M., Ewers, Brent, Famulari, Daniela, Fares, Silvano, Feigenwinter, Iris, Feitz, Andrew, Fensholt, Rasmus, Filippa, Gianluca, Fischer, Marc, Frank, John, Galvagno, Marta, Gharun, Mana, Gianelle, Damiano, Gielen, Bert, Gioli, Beniamino, Gitelson, Anatoly, Goded, Ignacio, Goeckede, Mathias, Goldstein, Allen H., Gough, Christopher M., Goulden, Michael L., Graf, Alexander, Griebel, Anne, Gruening, Carsten, Grünwald, Thomas, Hammerle, Albin, Han, Shijie, Han, Xingguo, Hansen, Birger Ulf, Hanson, Chad, Hatakka, Juha, He, Yongtao, Hehn, Markus, Heinesch, Bernard, Hinko-Najera, Nina, Hörtnagl, Lukas, Hutley, Lindsay, Ibrom, Andreas, Ikawa, Hiroki, Jackowicz-Korczynski, Marcin, Janouš, Dalibor, Jans, Wilma, Jassal, Rachhpal, Jiang, Shicheng, Kato, Tomomichi, Khomik, Myroslava, Klatt, Janina, Knohl, Alexander, Knox, Sara, Kobayashi, Hideki, Koerber, Georgia, Kolle, Olaf, Kosugi, Yoshiko, Kotani, Ayumi, Kowalski, Andrew, Kruijt, Bart, Kurbatova, Julia, Kutsch, Werner L., Kwon, Hyojung, Launiainen, Samuli, Laurila, Tuomas, Law, Bev, Leuning, Ray, Li, Yingnian, Liddell, Michael, Limousin, Jean-Marc, Lion, Marryanna, Liska, Adam J., Lohila, Annalea, López-Ballesteros, Ana, López-Blanco, Efrén, Loubet, Benjamin, Loustau, Denis, Lucas-Moffat, Antje, Lüers, Johannes, Ma, Siyan, Macfarlane, Craig, Magliulo, Vincenzo, Maier, Regine, Mammarella, Ivan, Manca, Giovanni, Marcolla, Barbara, Margolis, Hank A., Marras, Serena, Massman, William, Mastepanov, Mikhail, Matamala, Roser, Matthes, Jaclyn Hatala, Mazzenga, Francesco, McCaughey, Harry, McHugh, Ian, McMillan, Andrew M. S., Merbold, Lutz, Meyer, Wayne, Meyers, Tilden, Miller, Scott D., Minerbi, Stefano, Moderow, Uta, Monson, Russell K., Montagnani, Leonardo, Moore, Caitlin E., Moors, Eddy, Moreaux, Virginie, Moureaux, Christine, Munger, J. William, Nakai, Taro, Neirynck, Johan, Nesic, Zoran, Nicolini, Giacomo, Noormets, Asko, Northwood, Matthew, Nosetto, Marcelo, Nouvellon, Yann, Novick, Kimberly, Oechel, Walter, Olesen, Jørgen Eivind, Ourcival, Jean-Marc, Papuga, Shirley A., Parmentier, Frans-Jan, Paul-Limoges, Eugenie, Pavelka, Marian, Peichl, Matthias, Pendall, Elise, Phillips, Richard P., Pilegaard, Kim, Pirk, Norbert, Posse Beaulieu, Gabriela, Powell, Thomas, Prasse, Heiko, Prober, Suzanne M., Rambal, Serge, Rannik, Üllar, Raz-Yaseef, Naama, Reed, David, Resco de Dios, Victor, Restrepo-Coupe, Natalia, Reverter, Borja R., Roland, Marilyn, Sabbatini, Simone, Sachs, Torsten, Saleska, Scott R., Sánchez-Cañete, Enrique P., Sanchez-Mejia, Zulia M., Schmid, Hans Peter, Schmidt, Marius, Schneider, Karl, Schrader, Frederik, Schroder, Ivan, Scott, Russell L., Sedlák, Pavel, Serrano-Ortíz, Penélope, Shao, Changliang, Shi, Peili, Shironya, Ivan, Siebicke, Lukas, Šigut, Ladislav, Silberstein, Richard, Sirca, Costantino, Spano, Donatella, Steinbrecher, Rainer, Stevens, Robert M., Sturtevant, Cove, Suyker, Andy, Tagesson, Torbern, Takanashi, Satoru, Tang, Yanhong, Tapper, Nigel, Thom, Jonathan, Tiedemann, Frank, Tomassucci, Michele, Tuovinen, Juha-Pekka, Urbanski, Shawn, Valentini, Riccardo, van der Molen, Michiel, van Gorsel, Eva, van Huissteden, Ko, Varlagin, Andrej, Verfaillie, Joseph, Vesala, Timo, Vincke, Caroline, Vitale, Domenico, Vygodskaya, Natalia, Walker, Jeffrey P., Walter-Shea, Elizabeth, Wang, Huimin, Weber, Robin, Westermann, Sebastian, Wille, Christian, Wofsy, Steven, Wohlfahrt, Georg, Wolf, Sebastian, Woodgate, William, Li, Yuelin, Zampedri, Roberto, Zhang, Junhui, Zhou, Guoyi, Zona, Donatella, Agarwal, Deb, Biraud, Sebastien, Torn, Margaret, and Papale, Dario

Subjects
Remote Sensing, Red de Datos, Tratados, Treaties, Teledetección, Covarianza de Remolinos, Garantía de Calidad, Quality Assurance, Eddy Covariance, Data Network
Abstract

The 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. Fil: Pastorello, Gilberto. Lawrence Berkeley National Laboratory. Computational Research Division; Estados Unidos Fil: Trotta, Carlo. University of Tuscia. DiBAf; Italia Fil: Canfora, Eleonora. University of Tuscia. DiBAf; Italia. Euro-Mediterranean Centre on Climate Change Foundation (CMCC); Italia Fil: Chu, Housen. Lawrence Berkeley national Laboratory. Climate & Ecosystem Sciences Division; Estados Unidos Fil: Christianson, Danielle. Lawrence Berkeley National Laboratory. Computational Research Division; Estados Unidos Fil: Cheah, You - Wei. Lawrence Berkeley National Laboratory. Computational Research Division; Estados Unidos Fil: Poindexter, Cristina. California State University. Department of Civil Engineering; Estados Unidos Fil: Chen, Jiquan. Michigan State University. Department of Geography, Environment, and Spatial Sciences; Estados Unidos Fil: Elbashandy, Abdelrah man. Lawrence Berkeley National Laboratory. Computational Research Division; Estados Unidos Fil: Humphrey, Marty. University of Virginia. Department of Computer Science; Estados Unidos Fil: Isaac, Peter. TeRn Ecosystrem Processes; Australia Fil: Polidori, Diego. University of Tuscia. DiBAf; Italia. Euro-Mediterranean Centre on Climate Change Foundation (CMCC); Italia Fil: Riveca, Alessio. University of Tuscia. DiBAf; Italia. Euro-Mediterranean Centre on Climate Change Foundation (CMCC); Italia Fil: van Ingen, Catharine. Lawrence Berkeley National Laboratory. Computational Research Division; Estados Unidos Fil: Zhang, Leiming. Chinese Academy of Sciences. Institute of Geographic Sciences and Natural Resources Research. Key Laboratory of Ecosystem Network Observation and Modeling; China Fil: Amiro, Brian. University of Manitoba. Department of Soil Science; Canadá Fil: Ammann, Christof. Agroscope Research Institute. Department of Agroecology and Environment; Suiza Fil: Altaf Arain, M. McMaster University. School of Geography and Earth Sciences; Canadá. Fil: Ardo, Jonas. Lund University. Department of Physical Geography and Ecosystem Science; Suecia Fil: Arkebauer, Timothy. University of Nebraska-Lincoln. Department of Agronomy and Horticulture; Estados Unidos Fil: Arndt, Stefan K. The University of Melbourne. School of Ecosystem and Forest Sciences; Australia Fil: Arriga, Nicola. University of Antwerp. Department of Biology, Research Group PLECO; Bélgica. European Commission. Joint Research Centre; Italia Fil: Aubinet, Marc. University of Liege. TeRRA Teaching and Research Center; Bélgica Fil: Aurela, Mika. Finnish Meteorological Institute; Finlandia Fil: Baldocchi, Dennis. University of California Berkeley. ESPM; Estados Unidos Fil: Barr, Alan. University of Saskatchewan. Global Institute for Water Security; Canadá. Environment and Climate Change Canada. Climate Research Division; Canadá. Fil: Beamesderfer, Eric. McMaster University. School of Geography and Earth Sciences; Canadá. Fil: Belelli Marchesini, Luca. Fondazione Edmund Mach. Research and Innovation Centre. Department of Sustainable Agro-ecosystems and Bioresources; Italia. RUDN University. Agrarian-Technological Institute. Department of Landscape Design and Sustainable Ecosystems; Rusia Fil: Bergeron, Onil. Ministère du Développement durable de l’Environnement et de la Lutte contre les Changements Climatiques. Direction du Marché du Carbone; Canadá. Fil: Beringer, Jason. University of Western Australia. School of Agriculture and Environment; Australia. Fil: Bernhofer, Christia. Technische Universität Dresden. Institute of Hydrology and Meteorology; Alemania Fil: Berveiller, Daniel. Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique et Evolution; Francia Fil: Billesbach, Dave. University of Nebraska-Lincoln. Biological Systems Engineering; Estados Unidos Fil: Black, Tomas Andrew. University of British Columbia. Faculty of Land and Food Systems; Canadá. Fil: Blanken, Peter D. University of Colorado. Department of Geography; Estados Unidos Fil: Bohrer, Gil. Ohio State University. Department of Civil, Environmental & Geodetic Engineering; Estados Unidos Fil: Boike, Julia Alfred. Wegener Institute. Helmholtz Centre for Polar and Marine Research; Alemania. Humboldt-Universität zu Berlin. Geography Department; Alemania Fil: Bolstad, Paul V. University of Minnesota. Forest Resources; Estados Unidos Fil: Bonal, Damien. Université de Lorraine, AgroParisTech, INRAE, UMR Silva; Francia Fil: Bonnefond, Jean - Marc. ISPA, Bordeaux Sciences Agro, INRAE; Francia Fil: Bowling, David R. University of Utah. School of Biological Sciences; Estados Unidos Fil: Bracho, Rosuel. University of Florida.School of Forest Resources and Conservation; Estados Unidos Fil: Brodeur, Jason. McMaster University. McMaster University Library; Estados Unidos Fil: Brummer, Christian. Federal Research Institute of Rural Areas, Forestry and Fisheries. Thünen Institute of Climate-Smart Agriculture; Alemania Fil: Buchmann, Nina. ETH. Department of Environmental Systems Science; Suiza Fil: Burban, Benoit. INRAE UMR ECOFOG; Guyana Francesa Fil: Burns, Sean P. University of Colorado. Department of Geography; Estados Unidos. National Center for Atmospheric Research. Mesoscale and Microscale Meteorology Laboratory; Estados Unidos Fil: Buysse, Pauline. Université Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS; Francia Fil: Cale, Peter. Australian Landscape Trust; Australia Fil: Cavagna, Mauro. Fondazione Edmund Mach. Research and Innovation Centre. Department of Sustainable Agro-ecosystems and Bioresources; Italia Fil: Cellier, Pierre. Université Paris-Saclay. INRAE, AgroParisTech, UMR ECOSYS; Francia Fil: Che, Shiping. Chinese Academy of Sciences. Institute of Botany. State Key Laboratory of Vegetation and Environmental Change; China Fil: Chini, Issac. Fondazione Edmund Mach. Research and Innovation Centre. Department of Sustainable Agro-ecosystems and Bioresources; Italia Fil: Christensen, Storben. Aarhus University. Arctic Research Center. Department of Bioscience; Dinamarca Fil: Cleverly, James. University of Technology. School of Life Sciences; Australia. University of Technology. Terrestrial Ecosystem Research Network; Australia. Fil: Collalti, Alessio. University of Tuscia. DiBAf; Italia. National Research Council of Italy. Institute for Agricultural and Forestry Systems in the Mediterranean; Italia Fil: Consalvo, Claudia. University of Tuscia. DiBAf; Italia. National Research Council of Italy. Research Institute on Terrestrial Ecosystems; Italia Fil: Cook, Bruce. NASA Goddard Space Flight Center. Biospheric Sciences Laboratory; Estados Unidos Fil: Cook, David. Argonne National Laboratory. Environmental Science Division; Estados Unidos Fil: Coursolle, Carole. Natural Resources Canada. Canadian Forest Service; Canadá. Université Laval. Faculté de Foresterie, de Géographie et de Géomatique. Centre d’étude de la Forêt; Canadá Fil: Cremonose, Edoardo. Environmental Protection Agency of Aosta Valley. Climate Change Unit; Italia Fil: Curtis, Peter. Ohio State University. Department of Evolution, Ecology, and Organismal Biology; Estados Unidos Fil: D'Andrea, Ettore. National Research Council of Italy. Institute for Agricultural and Forestry Systems in the Mediterranean; Italia Fil: da Rocha, Humberto. Universidade de São Paulo. Instituto de Astronomia, Geofísica e Ciências Atmosféricas; Brasil Fil: Dai, Xiaoqin. Chinese Academy of Sciences. Institute of Geographic Sciences and Natural Resources Research. Key Laboratory of Ecosystem Network Observation and Modeling; China. Fil: Davis, Kenneth. The Pennsylvania State University. Department of Meteorology and Atmospheric Science; Estados Unidos Fil: De Cinti, Bruno. National Research Council of Italy. Institute of Research on Terrestrial Ecosystems; Italia Fil: de Grandcourt, Agnes. UMR Eco&Sols, CIRAD; Francia Fil: De Ligne, Anne. University of Liege. TeRRA Teaching and Research Center; Bélgica Fil: De Oliveira, Raimundo C. Pedology, Embrapa Amazonia Oriental; Brasil. Fil: Delpierre, Nicolas. Université Paris-Saclay. CNRS, AgroParisTech, Ecologie Systématique et Evolution; Francia Fil: Desai, Ankur R. University of Wisconsin-Madison. Atmospheric and Oceanic Sciences; Estados Unidos Fil: Di Bella, Carlos Marcelo. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina Fil: di Tommasi, Paul. National Research Council of Italy. Institute for Agricultural and Forestry Systems in the Mediterranean; Italia Fil: Dolman, Han. Vrije Universiteit Amsterdam. Department of Earth Sciences; Holanda Fil: Domingo, Francisco. CSIC. Experimental Station of Arid Zones. Desertification and Geoecology Department; España Fil: Dong, Gang. Shanxi University. School of Life Science; China. Fil: Dore, Sabina. HydroFocus; Estados Unidos Fil: Duce, Pierpaolo. National Research Council of Italy. Institute of Bioeconomy; Italia Fil: Dufrêne, Eric. Université Paris-Saclay, CNRS., AgroParisTech. Ecologie Systématique et Evolution; Francia Fil: Dunn, Allison. Worcester State University. Department of Earth, Environment, and Physics; Estados Unidos Fil: Dušek, Jiri. Global Change Research Institute of the Czech Academy of Sciences. Department of Matter and Energy Fluxes; República Checa Fil: Eamus Derek. University of Technology. School of Life Sciences; Australia. Fil: Eichelmann, Uwe.Technische Universität Dresden. Institute of Hydrology and Meteorology; Alemania Fil: ElKhidir, Hatim abdalla M. elObeid. Agricultural Research Corporation. Research Station; Sudán Fil: Eugster, Wener. ETH. Department of Environmental Systems Science; Suiza Fil: Ewenz, Cacilia M. Airborne Research Australia. TERN Ecosystem Processes Central Node; Australia Fil: Ewers, Brent. University of Wyoming. Department of Botany. Program in Ecology; Estados Unidos Fil: Famulari, Daniela. National Research Council of Italy. Institute for Agricultural and Forestry Systems in the Mediterranean; Italia Fil: Fares, Silvano. National Research Council of Italy. Institute of BioEconomy; Italia Fil: Feigenwinter, Iris. ETH. Department of Environmental Systems Science; Suiza Fil: Feitz, Andrew. Geoscience Australia; Australia Fil: Fensholt, Rasmus. University of Copenhagen. Department of Geosciences and Natural Resource Management; Dinamarca Fil: Filippa, Gianluca. Environmental Protection Agency of Aosta Valley. Climate Change Unit; Italia Fil: Fischer, Marc. Lawrence Berkeley National Laboratory. Energy Analysis & Environmental Impacts Division; Estados Unidos Fil: Frank, John. USDA Forest Service. Rocky Mountain Research Station; Estados Unidos Fil: Galvagno, Marta. Environmental Protection Agency of Aosta Valley. Climate Change Unit; Italia Fil: Gharun, Mana. ETH. Department of Environmental Systems Science; Suiza Fil: Gianelle, Damiano. Fondazione Edmund Mach. Research and Innovation Centre. Department of Sustainable Agro-ecosystems and Bioresources; Italia Fil: Gielen, Bert. University of Antwerp. Department of Biology. Research Group PLECO; Bélgica Fil: Gioli, Beniamino. National Research Council of Italy. Institute of BioEconomy; Italia Fil: Gitelson, Anatoly. University of Nebraska-Lincoln. School of natural Resources; Estados Unidos Fil: Goded, Ignacio. Joint Research Centre, European Commission; Italia Fil: Goeckede, Mathias. Max Planck Institute for Biogeochemistry; Alemania Fil: Goldstein. Allen H. University of California Berkeley. ESPM; Estados Unidos Fil: Gough, Christopher M. Virginia Commonwealth University. Department of Biology; Estados Unidos Fil: Goulden, Michael L. University of California Irvine. Department of Earth System Science; Estados Unidos Fil: Graf, Alexander. Agrosphere. (IBG3), Forschungszentrum Jülich; Alemania Fil: Griebel, Anne. The University of Melbourne. School of Ecosystem and Forest Sciences; Australia Fil: Gruening, Carsten. Joint Research Centre, European Commission; Italia Fil: Grünwald, Thomas. Technische Universität Dresden. Institute of Hydrology and Meteorology; Alemania Fil: Hammerle, Albin. University of Innsbruck. Department of Ecology; Austria. Fil: Han, Shijie. Henan University. School of Life Sciences. International Joint Research Laboratory for Global Change Ecology; China. Chinese Academy of Sciences. Institute of Applied Ecology; China. Fil: Han, Xingguo. Chinese Academy of Sciences.Institute of Botany. State Key Laboratory of Vegetation and Environmental Change; China Fil: Hansen, Birger Ulf. University of Copenhagen. Department of Geosciences and Natural Resource Management; Dinamarca Fil: Hanson, Chad. Oregon State University. Department of Forest Ecosystems and Society; Estados Unidos Fil: , Juha Hatakka, Juha. Finnish Meteorological Institute; Finlandia Fil: He, Yongtao. Chinese Academy of Sciences. Institute of Geographic Sciences and Natural Resources Research. Key Laboratory of Ecosystem Network Observation and Modeling; China. University of Chinese Academy of Sciences. College of Resources and Environment; China Fil: Hehn, Markus. Technische Universität Dresden. Institute of Hydrology and Meteorology; Alemania Fil: Heinesch, Bernard. University of Liege. TeRRA Teaching and Research Center; Bélgica Fil: Hinko-Najera, Nina. The University of Melbourne. School of Ecosystem and Forest Sciences; Australia. Fil: Hörtnagl, Lukas. ETH. Department of Environmental Systems Science; Suiza. Fil: Hutley, Lindsay. Charles Darwin University. Research Institute for the Environment and Livelihoods; Australia Fil: Ibrom, Andreas. Technical University of Denmark. Department of Environmental Engineering; Dinamarca Fil: Ikawa, Hiroki. National Agriculture and Food Research Organization. Institute for Agro-Environmental Sciences; Japón Fil: Jackowicz-Korczynski, Marcin. Lund University. Department of Physical Geography and Ecosystem Science; Suecia. Aarhus University. Arctic Research Center. Department of Bioscience; Dinamarca Fil: Janouš, Dalibor. Global Change Research Institute of the Czech Academy of Sciences. Department of Matter and Energy Fluxes; República Checa Fil: Jans, Wilma. Wageningen University and Research. Wageningen Environmental Research; Holanda Fil: Jassal, Rachhpal. University of British Columbia. Faculty of Land and Food Systems; Canadá. Fil: Jiang, Shicheng. Ministry of Education, Northeast Normal University. Key Laboratory of Vegetation Ecology; China Fil: Kato, Tomomichi. Hokkaido University. Research Faculty of Agriculture; Japón. Hokkaido University. GICore; Japón Fil: Khomik, Myroslava. Geography and Environmental Management; Canadá. Fil: Klatt, Janina. Karlsruhe Institute of Technology. Institute of Meteorology and Climate Research; Alemania Fil: Knohl, Alexander. University of Goettingen. Bioclimatology; Alelmania. University of Goettingen. Centre of Biodiversity and Sustainable Land Use; Alemania Fil: Knox, Sara. The University of British Columbia. Department of Geography; Canadá Fil: Kobayashi, Hideki. Japan Agency for Marine-Earth Science and Technology. Research Institute for Global change, Institute of Arctic Climate and Environment Research; Japón Fil: Koerber, Georgia. University of Adelaide. Biological Sciences; Australia. Fil: Kolle, Olaf. Max Planck Institute for Biogeochemistry; Alemania Fil: Kosugi, Yoshiko. Kyoto University. Graduate School of Agriculture; Japón Fil: Kotani, Ayumi. Nagoya University. Graduate School of Bioagricultural Sciences; Japón Fil: Kowalski, Andrew. University of Granada. Department of Applied Physics; España Fil: Kruijt, Bart. Wageningen University, Wageningen. Water systems and Global Change group; Holanda Fil: Kurbatova; Julia A. Russian Academy of Sciences. Severtsov institute of Ecology and Evolution; Rusia Fil: Kutsch, Werner L. Integrated Carbon Observation System (ICOS ERIC). Head Office; Finlandia Fil: Kwon, Hyojung. Oregon State University. Department of Forest Ecosystems and Society; Estados Unidos Fil: Launiainen, Samuli. Natural Resources Institute Finland; Finlandia Fil: Laurila, Tuomas. Finnish Meteorological Institute; Finlandia Fil: Law, Bev. Oregon State University. Department of Forest Ecosystems and Society; Estados Unidos Fil: Leuning. Ray. Lawrence Berkeley National Laboratory. Computational Research Division; Estados Unidos Fil: Li, Yingnian. Chinese Academy of Sciences. Northwest institute of Plateau Biology. Key Laboratory of Adaptation and Evolution of Plateau Biota; China Fil: Liddell, Michael. James Cook University. Centre for Tropical Environmental Sustainability Studies; Australia. Fil: Limousin, Jean-Marc. CEFE, CNRS, Univ Montpellier: Francia Fil: Lion, Marryanna. Forest Research Institute Malaysia. Forestry and Environment Division; Malasia Fil: Lohila, Annalea. University of Helsinki. Institute for Atmosphere and Earth System Research/Physics; Finlandia Fil: López-Ballesteros, Ana. Trinity College Dublin. School of Natural Sciences. Department of Botany; Irlanda Fil: López-Blanco, Efren. Aarhus University. Arctic Research Center. Department of Bioscience; Dinamarca Fil: Loubet, Benjamin. Université Paris-Saclay. INRAE, AgroParisTech, UMR ECOSYS; Francia Fil: Lucas-Moffat, Antje. Centre for Agrometeorological Research. German Meteorological Service; Alemania Fil: Lüers, Johannes. University of Bayreuth. Micrometeorology; Alemania. Bayreuth Center of Ecology and Environmental Research; Alemania Fil: Ma, Siyan. University of California Berkeley. ESPM; Estados Unidos Fil: Macfarlane, Craig. CSIRO Land and Water; Australia Fi: Magliulo, Vincenzo. Lawrence Berkeley National Laboratory. Computational Research Division; Estados Unidos Fil: Mammarella, Ivan. University of Helsinki . Institute for Atmosphere and Earth System Research/Physics; Finlandia Fil: Manca, Giovanni. Joint Research Centre, European Commission; Italia Fil: Marras, Serena. University of Sassari. Department of Agriculture; Italia Fil: Massman, William. USDA Forest Service. Rocky Mountain Research Station; Estados Unidos Fil: Mastepanov, Mikhail. University of Oulu. Oulanka Research Station; Finlandia Fil: Matamala, Roser. Argonne National Laboratory. Environmental Science Division; Estados Unidos Fil: Matthes, Jaclyn Hatala. Wellesley College. Department of Biological Sciences; Estados Unidos Fil: , Mazzenga, Francesco. National Research Council of Italy. Research Institute on Terrestrial Ecosystems; Italia Fil: McCaughey, Harry. Queen’s University. Department of Geography and Planning; Canadá. Fil: McHugh, Ian. The University of Melbourne. School of Ecosystem and Forest Sciences; Australia. Fil: McMillan, Andrew M.S. Environmental Analytics nZ, Ltd.; Nueva Zelanda Fil: Merbold, Lutz. International Livestock Research Institute. Mazingira Centre; Kenia. Fil: Meyer, Wayne. University of Adelaide. Biological Sciences; Australia. Fil: Meyers, Tilden. NOAA/OAR/Air Resources Laboratory; Estados Unidos Fil: Miller, Scott D. State University of New York at Albany. Atmospheric Sciences Research Center; Estados Unidos Fil: Minerbi, Stefano. Forest Department of South Tyrol; Italia Fil: Monson, Russell K. University of Arizona. Department of Ecology and Evolutionary Biology; Estados Unidos Fil: Montagnani, Leonardo. Forest Department of South Tyrol; Italia. Free University of Bolzano. Faculty of Science and Technology; Italia Fil: Moore, Caitlin E. University of Illinois at Urbana-Champaign. Department of Plant Biology; Estados Unidos Fil: Moors, Eddy. IHE Delft: Holanda. VU Amsterdam. Faculty of Science; Holanda Fil: Moreaux, Virginie. University Grenoble Alpes; Francia Fil: Moureaux, Christine. University of Liege. TeRRA Teaching and Research Center; Bélgica Fil: Munger, J. William. Harvard University. School of engineering and Applied Sciences; Estados Unidos. Harvard University. Department of Earth and Planetary Sciences; Estados Unidos Fil: Nakai, Taro. National Taiwan University. School of forestry and Resource conservation; Taiwan. University of Alaska Fairbanks. International Arctic Research Center; Estados Unidos Fil: Neirynck, Johan. Research Institute for Nature and Forest. Environment and Climate; Bélgica Fil: Nesic, Zoran. University of British Columbia. Faculty of Land and Food Systems; Canadá Fil: Nicolini, Giacomo. University of Tuscia. DiBAf; Italia. Euro-Mediterranean Centre on Climate Change Foundation (CMCC); Italia Fil: Noormets, Asko. Texas A&M University. College Station. Department of Ecosystem Science and Management; Estados Unidos Fil: Northwood, Matthew. Charles Darwin University. Research Institute for the Environment and Livelihoods; Australia Fil: Nosetto, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Matemática Aplicada San Luis. Grupo de Estudios Ambientales. Universidad Nacional de San Luis; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina Fil: Nouvellon, Yann. Université Montpellier-CIRAD-INRA-IRD-Montpellier SupAgro. Eco&Sols; Francia Fil: Novick, Kimberly O’Neill. Indiana University Bloomington. School of Public and Environmental Affairs; Estados Unidos Fil: Oechel, Walter. San Diego State University. Department of Biology. Global Change Research Group; Estados Unidos. University of Exeter. College of Life and Environmental Sciences. Department of Geography; Reino Unido Fil: Olesen, Jørgen Eivind. Aarhus University. Department of Agroecology; Dinamarca. Aarhus University. iCLIMATE; Dinamarca Fil: Ourcival, Jean-Marc. CEFE, CNRS, Université Montpellier; Francia Fil: Papuga, Shirley A. Wayne State University. Department of Geology; Estados Unidos Fil: Parmentier, Frans-Jan. University of Oslo. Department of Geosciences; Noruega Fil: Paul-Limoges, Eugenie. University of Zurich. Department of Geography; Suiza Fil: Pavelka, Marian. Global Change Research Institute of the Czech Academy of Sciences. Department of Matter and Energy Fluxes; República Checa Fil: Peichl, Matthias. Swedish University of Agricultural Sciences. Department of Forest Ecology and Management; Suecia Fil: Pendall, Elise. Western Sydney University. Hawkesbury Institute for the Environment; Australia Fil: Phillips, Richard P. Indiana University Bloomington. Department of Biology; Estados Unidos Fil: Pilegaard, Kim. Technical University of Denmark. Department of Environmental Engineering; Dinamarca Fil: Pirk, Norbert. CSiRO Land and Water; Australia. Fil: Posse Beaulieu, Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina Fil: Powell, Thomas. Lawrence Berkeley National Laboratory. Climate & Ecosystem Sciences Division; Estados Unidos Fil: Prasse, Heiko. Technische Universität Dresden. Institute of Hydrology and Meteorology; Alemania Fil: Reed, David. Michigan State University. Center for Global Change & Earth Observations: Estados Unidos. Michigan State University. Center for Global Change & Earth Observations; Estados Unidos Fil: Resco de Dios, Víctor. Western Sydney University. Hawkesbury Institute for the Environment; Australia. Southwest University of Science and Technology. School of Life Science and Engineering; China Fil: Restrepo-Coupe, Natalia. University of Arizona. Department of Ecology and Evolutionary Biology; Estados Unidos Fil: Reverter, Borja R. Universidade Federal da Paraiba. Departamento de Química e Física; Brasil Fil: Roland, Marilyn. University of Antwerp. Department of Biology. Research Group PLECO; Bélgica Fil: Sabbatini, Simone. University of Tuscia. DiBAf; Italia. Fil: Sachs, Torsten. GfZ German Research Centre for Geosciences. Remote Sensing and Geoinformatics; Alemania Fil: Saleska, Scott R. University of Arizona. Department of Ecology and Evolutionary Biology; Estados Unidos Fil: Sánchez-Cañete, Enrique P. University of Granada. Department of Applied Physics; España. Andalusian Institute for Earth System Research (CEAMA-IISTA); España Fil: Sanchez-Mejia, Zulia M. Instituto Tecnológico de Sonora. Ciencias del Agua y Medioambiente; México Fil: Schmid, Hans Peter. Karlsruhe Institute of Technology. Institute of Meteorology and Climate Research; Alemania Fil: Schmidt, Marius. Agrosphere (IBG3), Forschungszentrum Jülich; Alemania Fil: Schneider, Karl. University of Cologne. Geographical Institute; Alemania Fil: Schrader, Frederik Thünen. Federal Research Institute of Rural Areas, Forestry and Fisheries. Institute of Climate-Smart Agriculture; Alemania Fil: Schroder, Ivan. Geoscience Australia. Department of industry, Innovation and Science; Australia. Fil: Scott, Russell L. USDA-ARS. Southwest Watershed Research Center; Estados Unidos Fil: Sedlák, Pavel. Global Change Research Institute of the Czech Academy of Sciences. Department of Matter and Energy Fluxes; República Checa. Institute of Atmospheric Physics of the Czech Academy of Sciences; República Checa Fil: Serrano-Ortíz, Penélope. Andalusian Institute for Earth System Research (CEAMA-IISTA); España. University of Granada. Department of Ecology; España Fil: Shao, Changliang. Chinese Academy of Agricultural Sciences. National Hulunber Grassland Ecosystem Observation and Research Station & Institute of Agricultural Resources and Regional Planning; China. Fil: Shi, Peili. Chinese Academy of Sciences. Institute of Geographic Sciences and Natural Resources Research. Key Laboratory of Ecosystem Network Observation and Modeling; China. Fil: Shironya, Ivan A.n. Russian Academy of Sciences. Severtsov Institute of Ecology and Evolution; Rusia Fil: Siebicke, Lukas. University of Goettingen. Bioclimatology; Alemania Fil: Šigut, Ladislav. Global Change Research Institute of the Czech Academy of Sciences. Department of Matter and Energy Fluxes; República Checa Fil: Silberstein, Richard. University of Western Australia. School of Agriculture and Environment; Australia. Edith Cowan University. School of Science; Australia. Fil: Sirca, Costantino. Euro-Mediterranean Centre on Climate Change Foundation (CMCC); Italia. University of Sassari. Department of Agriculture; Italia Fil: Spano, Donatella. Euro-Mediterranean Centre on Climate Change Foundation (CMCC); Italia. University of Sassari. Department of Agriculture; Italia Fil: Steinbrecher, Rainer. Karlsruhe Institute of Technology. Institute of Meteorology and Climate Research; Alemania Fil: Stevens, Robert M. Sentek Pty Ltd.; Australia Fil: Sturtevant, Cove. National ecological Observatory Network Program; Estados Unidos Fil: Suyker, Andy. University of Nebraska-Lincoln. School of Natural Resources; Estados Unidos Fil: Tagesson, Torbem. Lund University. Department of Physical Geography and Ecosystem Science; Suecia. University of Copenhagen. Department of Geosciences and Natural Resource Management; Dinamarca Fil: Takanashi, Satoru. Forestry and Forest Products Research Institute. Kansai Research Center; Japón Fil: Tang, Yanhong. Peking University. College of Urban and Environmental Sciences; China. Fil: Tapper, Nigel. Monash University. School of Earth, Atmosphere and Environment; Australia Fil: Thom, Jonathan. University of Wisconsin-Madison. Space Science and Engineering Center; Estados Unidos Fil: Tiedemann, Frank. University of Goettingen. Bioclimatology; Alemania Fil: Tomassucci, Michele. University of Tuscia. DiBAf; Italia. Terrasystem srl; Italia Fil: Tuovinen, Juha-Pekka. Finnish Meteorological Institute; Finlandia Fil: Urbanski, Shawn. USDA Forest Service. Rocky Mountain Research Station; Estados Unidos Fil: Valentini, Riccardo. University of Tuscia. DiBAf; Italia. Euro-Mediterranean Centre on Climate Change Foundation (CMCC); Italia Fil: van der Molen, Michiel. Wageningen University. Meteorology and Air Quality Group; Holanda Fil: van Gorsel, Eva. Australian National University Canberra. Fenner School of Environment and Society; Australia. Fil: van Huissteden, Ko. Vrije Universiteit Amsterdam. Department of Earth Sciences; Holanda Fil: Varlagin, Andrej. Agroscope Research Institute. Department of Agroecology and Environment; Suiza Fil: Verfaillie, Joseph. University of California Berkeley. ESPM; Estados Unidos Fil: Vesala, Timo. University of Helsinki. Institute for Atmosphere and Earth System Research/Physics; Finlandia Fil: Vincke, Caroline. Chinese Academy of Sciences. South China Botanical Garden; China. Fil: Vitale, Domenico. University of Tuscia. DiBAf; Italia. Euro-Mediterranean Centre on Climate Change Foundation (CMCC); Italia Fil: Vygodskaya, Natalia. University of Bayreuth. Micrometeorology; Alemania Fil: Walker, Jeffrey P. Monash University. Department of Civil Engineering; Australia Fil: Walter-Shea, Elizabeth. University of Nebraska-Lincoln. School of natural Resources; Estados Unidos Fil: Wang, Huimin. Chinese Academy of Sciences. Institute of Geographic Sciences and Natural Resources Research. Key Laboratory of Ecosystem Network Observation and Modeling; China Fil: Weber, Robin. University of California Berkeley. ESPM; Estados Unidos Fil: Westermann, Sebastian. Instituto Nacional de Tecnologia Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Fil: Wille, Christian. GfZ German Research centre for Geosciences. Remote Sensing and Geoinformatics; Alemania Fil: Wofsy, Steven. Harvard University. School of engineering and Applied Sciences; Estados Unidos. Harvard University. Department of Earth and Planetary Sciences; Estados Unidos Fil: Wohlfahrt, Georg. University of Innsbruck. Department of Ecology; Austria. Fil: Woodgate, William. CSIRO Land and Water; Australia. Fil: Li, Yuelin. Chinese Academy of Sciences. South China Botanical Garden; China. Fil: Zampedri, Roberto. Fondazione Edmund Mach. Research and Innovation Centre. Department of Sustainable Agro-ecosystems and Bioresources; Italia Fil: Zhang, Junhui. Chinese Academy of Sciences. Institute of Applied Ecology; China. Fil: Zhou, Guoyi. Nanjing University of Information Science & Technology. College of Applied Meteorology; China. Fil: Zona, Donatella. San Diego State University. Department of Biology. Global Change Research Group; Estados Unidos. University of Sheffield. Department of Animal and Plant Sciences; Reino Unido Fil: Agarwal, Deb. Lawrence Berkeley National Laboratory. Computational Research Division; Estados Unidos Fil: Biraud, Sebastien. Lawrence Berkeley National Laboratory. Climate & Ecosystem Sciences Division; Estados Unidos Fil: Torn, Margaret. Lawrence Berkeley National Laboratory. Climate & Ecosystem Sciences Division; Estados Unidos Fil: Papale, Dario. University of Tuscia. DiBAf; Italia. Euro-Mediterranean Centre on Climate Change Foundation (CMCC); Italia

Published
2020

2. Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations

Author

Cook, Bruce D., Bolstad, Paul V., Næsset, Erik, Anderson, Ryan S., Garrigues, Sebastian, Morisette, Jeffrey T., Nickeson, Jaime, and Davis, Kenneth J.

Subjects
*OPTICAL radar, *SCANNING systems, *REMOTE sensing, *WETLANDS, *ECOLOGICAL models, *DATA analysis, *ARTIFICIAL satellites, *CLIMATE change, *SPECTRORADIOMETER, DESIGN & construction
Abstract

Abstract: Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine-resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire landscape. Failure to account for wetlands had little impact on landscape-scale estimates, because vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important. [Copyright &y& Elsevier]

Published
2009
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3. Comparing net ecosystem exchange of carbon dioxide between an old-growth and mature forest in the upper Midwest, USA

Author

Desai, Ankur R., Bolstad, Paul V., Cook, Bruce D., Davis, Kenneth J., and Carey, Eileen V.

Subjects
*FOREST reserves, *ECOLOGY, *CARBON dioxide, *TREES
Abstract

Abstract: Old-growth forests are often assumed to exhibit no net carbon assimilation over time periods of several years. This generalization has not been typically supported by the few whole-ecosystem, stand-scale eddy-covariance measurements of carbon dioxide exchange in old-growth forests. An eddy-flux tower installed in a >300-year-old hemlock–hardwood forest near the Sylvania Wilderness, Ottawa National Forest, MI, USA, observed a small annual carbon sink of CO2 of -72±36gCm-2year-1 in 2002 and -147±42gCm-2year-1 in 2003. This carbon sink was much smaller than carbon sinks of -438±49gCm-2year-1 in 2002 and -490±48gCm-2year-1 in 2003 observed by a nearby flux tower in a 70-year-old mature hardwood forest (Willow Creek, WI). The mature forest had vegetation similar to the old-growth site prior to European settlement. Both sites had slightly larger carbon sinks in 2003, which was a drier and cooler year than 2002. However, the difference in sink strength between the two years was smaller than the uncertainty in the results arising from missing and screened data. Both sites also had significant systematic errors due to non-representative fluxes during certain micrometeorological conditions, which required careful screening. The difference in sink strength between the two sites was driven mainly by greater ER at the old-growth site (965±35gCm-2year-1 in 2002 and 883±69gCm-2year-1 in 2003) compared to the mature site (668±21gCm-2year-1 in 2002 and 703±17gCm-2year-1 in 2003). GEP was lower at the old-growth site (1037±47gCm-2year-1 in 2002 and 1030±41gCm-2year-1 in 2003) compared to the mature site (1106±47gCm-2year-1 in 2002 and 1192±51gCm-2year-1 in 2003), especially in 2003. Observations also suggested that growing season ER had greater interannual variability at the old-growth site. These results imply that old-growth forests in the region may be carbon sinks, though these sinks are smaller than mature forests, mostly likely due to greater ER. [Copyright &y& Elsevier]

Published
2005
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4. A continuous measure of gross primary production for the conterminous United States derived from MODIS and AmeriFlux data

Author

Xiao, Jingfeng, Zhuang, Qianlai, Law, Beverly E., Chen, Jiquan, Baldocchi, Dennis D., Cook, David R., Oren, Ram, Richardson, Andrew, Wharton, Sonia, Ma, Siyan, Martini, Timothy A., Verma, Shashi B., Suyker, Andrew E., Scott, Russell L., Monson, Russell K., Litvak, Marcy, Hollinger, David Y., Sun, Ge, Davis, Kenneth J., Bolstad, Paul V., Burns, Sean P., Curtis, Peter S., Drake, Bert G., Falk, Matthias, Fischer, Marc L., Foster, David Russell, Gu, Lianhong, Hadley, Julian L., Katul, Gabriel G., Matamala, Roser, McNulty, Steve, Meyers, Tilden P., Munger, J. William, Noormets, Asko, Oechel, Walter C., Paw U, Kyaw Tha, Schmid, Hans Peter, Starr, Gregory, Torn, Margaret S., and Wofsy, Steven Charles

Subjects
Gross primary productivity, MODIS, AmeriFlux, Eddy covariance, Regression tree, US, Carbon fluxes, Interannual variability, Satellite data, Biomes
Abstract

The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide range of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000–2004, and was validated using observed GPP over the period 2005–2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km × 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr− 1 for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were dominated by these extreme climate events and disturbances., Engineering and Applied Sciences

Published
2010
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5. Estimation of Net Ecosystem Carbon Exchange for the Conterminous United States by Combining MODIS and AmeriFlux Data

Author

Drake, Bert G., Richardson, Andrew D., Cook, David R., Bolstad, Paul V., Curtis, Peter S., Zhuang, Qianlai, McNulty, Steve, Martin, Timothy A., Matamala, Roser, Hadley, Julian L., Suyker, Andrew E., Ma, Siyan, Wofsy, Steven, Wharton, Sonia, Sun, Ge, Torn, Margaret S., Xiao, Jingfeng, Starr, Gregory, Burns, Sean P., Foster, David R., Fischer, Marc L., Scott, Russell L., Gu, Lianhong, Verma, Shashi B., Katul, Gabriel G., Hollinger, David Y., Noormets, Asko, Law, Beverly E., Schmid, Hans Peter, Falk, Matthias, Monson, Russell K., Meyers, Tilden P., Litvak, Marcy, Munger, J. William, Oechel, Walter C., Paw U, Kyaw Tha, Baldocchi, Dennis D., Chen, Jiquan, and Oren, Ram

Subjects
eddy covariance, NEE, regression tree, Net ecosystem carbon exchange, MODIS, Ameriflux
Abstract

Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board the National Aeronautics and Space Administration's (NASA) Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a modified regression tree approach. The predictive model was trained and validated using eddy flux NEE data over the periods 2000–2004 and 2005–2006, respectively. We found that the model predicted NEE well (r = 0.73, p < 0.001). We then applied the model to the continental scale and estimated NEE for each 1 km × 1 km cell across the conterminous U.S. for each 8-day interval in 2005 using spatially explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE as determined from measurements and the literature. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets over large areas., Organismic and Evolutionary Biology, Earth and Planetary Sciences, Engineering and Applied Sciences

Published
2008
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6. Influence of vegetation and seasonal forcing on carbon dioxide fluxes across the Upper Midwest, USA: Implications for regional scaling

Author

Desai, Ankur R., Noormets, Asko, Bolstad, Paul V., Chen, Jiquan, Cook, Bruce D., Davis, Kenneth J., Euskirchen, Eugenie S., Gough, Christopher, Martin, Jonathan G., Ricciuto, Daniel M., Schmid, Hans Peter, Tang, Jianwu, and Wang, Weiguo

Subjects
*PINACEAE, *ECOLOGY, *CARBON compounds, *CARBON dioxide
Abstract

Abstract: Carbon dioxide fluxes were examined over the growing seasons of 2002 and 2003 from 14 different sites in Upper Midwest (USA) to assess spatial variability of ecosystem–atmosphere CO2 exchange. These sites were exposed to similar temperature/precipitation regimes and spanned a range of vegetation types typical of the region (northern hardwood, mixed forest, red pine, jack pine, pine barrens and shrub wetland). The hardwood and red pine sites also spanned a range of stand ages (young, intermediate, mature). While seasonal changes in net ecosystem exchange (NEE) and photosynthetic parameters were coherent across the 2 years at most sites, changes in ecosystem respiration (ER) and gross ecosystem production (GEP) were not. Canopy height and vegetation type were important variables for explaining spatial variability of CO2 fluxes across the region. Light-use efficiency (LUE) was not as strongly correlated to GEP as maximum assimilation capacity (Amax). A bottom-up multi-tower land cover aggregated scaling of CO2 flux to a 2000km2 regional flux estimate found June to August 2003 NEE, ER and GEP to be −290±89, 408±48, and 698±73gCm−2, respectively. Aggregated NEE, ER and GEP were 280% larger, 32% smaller and 3% larger, respectively, than that observed from a regionally integrating 447m tall flux tower. However, when the tall tower fluxes were decomposed using a footprint-weighted influence function and then re-aggregated to a regional estimate, the resulting NEE, ER and GEP were within 11% of the multi-tower aggregation. Excluding wetland and young stand age sites from the aggregation worsened the comparison to observed fluxes. These results provide insight on the range of spatial sampling, replication, measurement error and land cover accuracy needed for multi-tiered bottom-up scaling of CO2 fluxes in heterogeneous regions such as the Upper Midwest, USA. [Copyright &y& Elsevier]

Published
2008
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7. Evaporation from a temperate closed-basin lake and its impact on present, past, and future water level.

Author

Xiao, Ke, Griffis, Timothy J., Baker, John M., Bolstad, Paul V., Erickson, Matt D., Lee, Xuhui, Wood, Jeffrey D., Hu, Cheng, and Nieber, John L.

Subjects
*CLIMATE change, *WATER management, *LAKES, *EVAPORATION (Meteorology)
Abstract

Lakes provide enormous economic, recreational, and aesthetic benefits to citizens. These ecosystem services may be adversely impacted by climate change. In the Twin Cities Metropolitan Area of Minnesota, USA, many lakes have been at historic low levels and water augmentation strategies have been proposed to alleviate the problem. White Bear Lake (WBL) is a notable example. Its water level declined 1.5 m during 2003–2013 for reasons that are not fully understood. This study examined current, past, and future lake evaporation to better understand how climate will impact the water balance of lakes within this region. Evaporation from WBL was measured from July 2014 to February 2017 using two eddy covariance (EC) systems to provide better constraints on the water budget and to investigate the impact of evaporation on lake level. The estimated annual evaporation losses for years 2014 through 2016 were 559 ± 22 mm, 779 ± 81 mm, and 766 ± 11 mm, respectively. The higher evaporation in 2015 and 2016 was caused by the combined effects of larger average daily evaporation and a longer ice-free season. The EC measurements were used to tune the Community Land Model 4 – Lake, Ice, Snow and Sediment Simulator (CLM4-LISSS) to estimate lake evaporation over the period 1979–2016. Retrospective analyses indicate that WBL evaporation increased during this time by about 3.8 mm year −1 , which was driven by increased wind speed and lake-surface vapor pressure gradient. Using a business-as-usual greenhouse gas emission scenario (RCP8.5), lake evaporation was modeled forward in time from 2017 to 2100. Annual evaporation is expected to increase by 1.4 mm year −1 over this century, largely driven by lengthening ice-free periods. These changes in ice phenology and evaporation will have important implications for the regional water balance, and water management and water augmentation strategies that are being proposed for these Metropolitan lakes. [ABSTRACT FROM AUTHOR]

Published
2018
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8. Estimating the net ecosystem exchange for the major forests in the northern United States by integrating MODIS and AmeriFlux data

Author

Tang, Xuguang, Wang, Zongming, Liu, Dianwei, Song, Kaishan, Jia, Mingming, Dong, Zhangyu, Munger, J. William, Hollinger, David Y., Bolstad, Paul V., Goldstein, Allen H., Desai, Ankur R., Dragoni, Danilo, and Liu, Xiuping

Subjects
*FOREST ecology, *MODIS (Spectroradiometer), *EDDY flux, *VEGETATION & climate, *EARTH temperature, *GRISELINIA littoralis, *BIOTIC communities
Abstract

Abstract: The eddy covariance technique provides long-term continuous monitoring of site-specific net ecosystem exchange of CO2 (NEE) across a large range of forest types. However, these NEE estimates only represent fluxes at the scale of the tower footprint and need to be scaled up to quantify NEE over regions or continents. In the present study, we expanded a method developed previously and generated a new NEE model exclusively based on the Moderate Resolution Imaging Spectroradiometer (MODIS) products, including enhanced vegetation index (EVI), land surface water index (LSWI), land surface temperature (LST) and Terra nighttime LST′. This method, in our previous research, provided substantially good predictions of NEE and well reflected the seasonal dynamics of the deciduous broadleaf forest at the Harvard forest site. Studying NEE of forests in the middle-latitude regions of the Northern Hemisphere is significant because it may help to understand the ‘missing carbon sink’ from terrestrial ecosystems. In this study we selected eight eddy flux sites to represent the major forest ecosystems in the northern United States. Compared with the model based on a single site, we also established the general models that apply to evergreen needleleaf forest (ENF) and deciduous broadleaf forest (DBF), respectively. The results showed that our simpler model based entirely on MODIS products promised well to estimate NEE by the eddy covariance technique. The modeled annual mean NEE from DBF deviated from the measured NEE by 44.4%, whereas the modeled NEE from ENF was extremely close to the measured NEE within 5.5%. In the end, we also validated both general models for ENF and DBF using independent flux sites. It demonstrated this method performed well for estimating NEE. [Copyright &y& Elsevier]

Published
2012
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9. Assessing net ecosystem carbon exchange of U.S. terrestrial ecosystems by integrating eddy covariance flux measurements and satellite observations

Author

Xiao, Jingfeng, Zhuang, Qianlai, Law, Beverly E., Baldocchi, Dennis D., Chen, Jiquan, Richardson, Andrew D., Melillo, Jerry M., Davis, Kenneth J., Hollinger, David Y., Wharton, Sonia, Oren, Ram, Noormets, Asko, Fischer, Marc L., Verma, Shashi B., Cook, David R., Sun, Ge, McNulty, Steve, Wofsy, Steven C., Bolstad, Paul V., and Burns, Sean P.

Subjects
*BIOTIC communities, *ANALYSIS of covariance, *CARBON dioxide, *CLIMATE change, *CARBON cycle, *FORESTS & forestry, *SAVANNAS, *SPECTRORADIOMETER, *HURRICANES
Abstract

Abstract: More accurate projections of future carbon dioxide concentrations in the atmosphere and associated climate change depend on improved scientific understanding of the terrestrial carbon cycle. Despite the consensus that U.S. terrestrial ecosystems provide a carbon sink, the size, distribution, and interannual variability of this sink remain uncertain. Here we report a terrestrial carbon sink in the conterminous U.S. at 0.63pg C yr−1 with the majority of the sink in regions dominated by evergreen and deciduous forests and savannas. This estimate is based on our continuous estimates of net ecosystem carbon exchange (NEE) with high spatial (1km) and temporal (8-day) resolutions derived from NEE measurements from eddy covariance flux towers and wall-to-wall satellite observations from Moderate Resolution Imaging Spectroradiometer (MODIS). We find that the U.S. terrestrial ecosystems could offset a maximum of 40% of the fossil-fuel carbon emissions. Our results show that the U.S. terrestrial carbon sink varied between 0.51 and 0.70 pg C yr−1 over the period 2001–2006. The dominant sources of interannual variation of the carbon sink included extreme climate events and disturbances. Droughts in 2002 and 2006 reduced the U.S. carbon sink by ∼20% relative to a normal year. Disturbances including wildfires and hurricanes reduced carbon uptake or resulted in carbon release at regional scales. Our results provide an alternative, independent, and novel constraint to the U.S. terrestrial carbon sink. [ABSTRACT FROM AUTHOR]

Published
2011
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10. Estimation of net ecosystem carbon exchange for the conterminous United States by combining MODIS and AmeriFlux data

Author

Xiao, Jingfeng, Zhuang, Qianlai, Baldocchi, Dennis D., Law, Beverly E., Richardson, Andrew D., Chen, Jiquan, Oren, Ram, Starr, Gregory, Noormets, Asko, Ma, Siyan, Verma, Shashi B., Wharton, Sonia, Wofsy, Steven C., Bolstad, Paul V., Burns, Sean P., Cook, David R., Curtis, Peter S., Drake, Bert G., Falk, Matthias, and Fischer, Marc L.

Subjects
*EDDY flux, *GEOBIOLOGY, *EXTRAPOLATION
Abstract

Abstract: Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board the National Aeronautics and Space Administration''s (NASA) Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a modified regression tree approach. The predictive model was trained and validated using eddy flux NEE data over the periods 2000–2004 and 2005–2006, respectively. We found that the model predicted NEE well (r =0.73, p <0.001). We then applied the model to the continental scale and estimated NEE for each 1km×1km cell across the conterminous U.S. for each 8-day interval in 2005 using spatially explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE as determined from measurements and the literature. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets over large areas. [Copyright &y& Elsevier]

Published
2008
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11. A new model of gross primary productivity for North American ecosystems based solely on the enhanced vegetation index and land surface temperature from MODIS

Author

Sims, Daniel A., Rahman, Abdullah F., Cordova, Vicente D., El-Masri, Bassil Z., Baldocchi, Dennis D., Bolstad, Paul V., Flanagan, Lawrence B., Goldstein, Allen H., Hollinger, David Y., Misson, Laurent, Monson, Russell K., Oechel, Walter C., Schmid, Hans P., Wofsy, Steven C., and Xu, Liukang

Subjects
*PRIMARY productivity (Biology), *MODIS (Spectroradiometer), *REMOTE sensing, *TEMPERATURE, *VEGETATION greenness, *CARBON cycle, *VAPOR pressure, *PHOTOSYNTHETICALLY active radiation (PAR)
Abstract

Many current models of ecosystem carbon exchange based on remote sensing, such as the MODIS product termed MOD17, still require considerable input from ground based meteorological measurements and look up tables based on vegetation type. Since these data are often not available at the same spatial scale as the remote sensing imagery, they can introduce substantial errors into the carbon exchange estimates. Here we present further development of a gross primary production (GPP) model based entirely on remote sensing data. In contrast to an earlier model based only on the enhanced vegetation index (EVI), this model, termed the Temperature and Greenness (TG) model, also includes the land surface temperature (LST) product from MODIS. In addition to its obvious relationship to vegetation temperature, LST was correlated with vapor pressure deficit and photosynthetically active radiation. Combination of EVI and LST in the model substantially improved the correlation between predicted and measured GPP at 11 eddy correlation flux towers in a wide range of vegetation types across North America. In many cases, the TG model provided substantially better predictions of GPP than did the MODIS GPP product. However, both models resulted in poor predictions for sparse shrub habitats where solar angle effects on remote sensing indices were large. Although it may be possible to improve the MODIS GPP product through improved parameterization, our results suggest that simpler models based entirely on remote sensing can provide equally good predictions of GPP. [Copyright &y& Elsevier]

Published
2008
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