Author: "Ardö, Jonas" / Topic: ecology - Searchworks@Jio Institute Digital Library Search Results

7 results on '"Ardö, Jonas"'

1. Ecosystem properties of semiarid savanna grassland in West Africa and its relationship with environmental variability.

Author: Tagesson T, Fensholt R, Guiro I, Rasmussen MO, Huber S, Mbow C, Garcia M, Horion S, Sandholt I, Holm-Rasmussen B, Göttsche FM, Ridler ME, Olén N, Lundegard Olsen J, Ehammer A, Madsen M, Olesen FS, and Ardö J
Subjects: Senegal, Climate, Ecology methods, Environment, Grassland, Models, Biological, Poaceae growth & development
Abstract: The Dahra field site in Senegal, West Africa, was established in 2002 to monitor ecosystem properties of semiarid savanna grassland and their responses to climatic and environmental change. This article describes the environment and the ecosystem properties of the site using a unique set of in situ data. The studied variables include hydroclimatic variables, species composition, albedo, normalized difference vegetation index (NDVI), hyperspectral characteristics (350-1800 nm), surface reflectance anisotropy, brightness temperature, fraction of absorbed photosynthetic active radiation (FAPAR), biomass, vegetation water content, and land-atmosphere exchanges of carbon (NEE) and energy. The Dahra field site experiences a typical Sahelian climate and is covered by coexisting trees (~3% canopy cover) and grass species, characterizing large parts of the Sahel. This makes the site suitable for investigating relationships between ecosystem properties and hydroclimatic variables for semiarid savanna ecosystems of the region. There were strong interannual, seasonal and diurnal dynamics in NEE, with high values of ~-7.5 g C m(-2) day(-1) during the peak of the growing season. We found neither browning nor greening NDVI trends from 2002 to 2012. Interannual variation in species composition was strongly related to rainfall distribution. NDVI and FAPAR were strongly related to species composition, especially for years dominated by the species Zornia glochidiata. This influence was not observed in interannual variation in biomass and vegetation productivity, thus challenging dryland productivity models based on remote sensing. Surface reflectance anisotropy (350-1800 nm) at the peak of the growing season varied strongly depending on wavelength and viewing angle thereby having implications for the design of remotely sensed spectral vegetation indices covering different wavelength regions. The presented time series of in situ data have great potential for dryland dynamics studies, global climate change related research and evaluation and parameterization of remote sensing products and dynamic vegetation models., (© 2014 John Wiley & Sons Ltd.)
Published: 2015
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2. Global maps of soil temperature

Author: Lembrechts, Jonas J, Hoogen, Johan, Aalto, Juha, Ashcroft, Michael B, De Frenne, Pieter, Kemppinen, Julia, Kopecký, Martin, Luoto, Miska, Maclean, Ilya MD, Crowther, Thomas W, Bailey, Joseph J, Haesen, Stef, Klinges, David H, Niittynen, Pekka, Scheffers, Brett R, Van Meerbeek, Koenraad, Aartsma, Peter, Abdalaze, Otar, Abedi, Mehdi, Aerts, Rien, Ahmadian, Negar, Ahrends, Antje, Alatalo, Juha M, Alexander, Jake M, Allonsius, Camille Nina, Altman, Jan, Ammann, Christof, Andres, Christian, Andrews, Christopher, Ardö, Jonas, Arriga, Nicola, Arzac, Alberto, Aschero, Valeria, Assis, Rafael L, Assmann, Jakob Johann, Bader, Maaike Y, Bahalkeh, Khadijeh, Barančok, Peter, Barrio, Isabel C, Barros, Agustina, Barthel, Matti, Basham, Edmund W, Bauters, Marijn, Bazzichetto, Manuele, Marchesini, Luca Belelli, Bell, Michael C, Benavides, Juan C, Alonso, José Luis Benito, Berauer, Bernd J, Bjerke, Jarle W, Björk, Robert G, Björkman, Mats P, Björnsdóttir, Katrin, Blonder, Benjamin, Boeckx, Pascal, Boike, Julia, Bokhorst, Stef, Brum, Bárbara NS, Brůna, Josef, Buchmann, Nina, Buysse, Pauline, Camargo, José Luís, Campoe, Otávio C, Candan, Onur, Canessa, Rafaella, Cannone, Nicoletta, Carbognani, Michele, Carnicer, Jofre, Casanova‐Katny, Angélica, Cesarz, Simone, Chojnicki, Bogdan, Choler, Philippe, Chown, Steven L, Cifuentes, Edgar F, Čiliak, Marek, Contador, Tamara, Convey, Peter, Cooper, Elisabeth J, Cremonese, Edoardo, Curasi, Salvatore R, Curtis, Robin, Cutini, Maurizio, Dahlberg, C Johan, Daskalova, Gergana N, de Pablo, Miguel Angel, Della Chiesa, Stefano, Dengler, Jürgen, Deronde, Bart, Descombes, Patrice, Di Cecco, Valter, Di Musciano, Michele, Dick, Jan, Dimarco, Romina D, Dolezal, Jiri, Dorrepaal, Ellen, Dušek, Jiří, Eisenhauer, Nico, Eklundh, Lars, Erickson, Todd E, and Erschbamer, Brigitta
Subjects: Climate Action, Climate Change, Ecosystem, Microclimate, Soil, Temperature, bioclimatic variables, global maps, microclimate, near-surface temperatures, soil-dwelling organisms, soil temperature, temperature offset, weather stations, Environmental Sciences, Biological Sciences, Ecology
Abstract: Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.
Published: 2022

3. SoilTemp: A global database of near‐surface temperature

Author: Lembrechts, Jonas J, Aalto, Juha, Ashcroft, Michael B, De Frenne, Pieter, Kopecký, Martin, Lenoir, Jonathan, Luoto, Miska, Maclean, Ilya MD, Roupsard, Olivier, Fuentes‐Lillo, Eduardo, García, Rafael A, Pellissier, Loïc, Pitteloud, Camille, Alatalo, Juha M, Smith, Stuart W, Björk, Robert G, Muffler, Lena, Backes, Amanda Ratier, Cesarz, Simone, Gottschall, Felix, Okello, Joseph, Urban, Josef, Plichta, Roman, Svátek, Martin, Phartyal, Shyam S, Wipf, Sonja, Eisenhauer, Nico, Pușcaș, Mihai, Turtureanu, Pavel D, Varlagin, Andrej, Dimarco, Romina D, Jump, Alistair S, Randall, Krystal, Dorrepaal, Ellen, Larson, Keith, Walz, Josefine, Vitale, Luca, Svoboda, Miroslav, Higgens, Rebecca Finger, Halbritter, Aud H, Curasi, Salvatore R, Klupar, Ian, Koontz, Austin, Pearse, William D, Simpson, Elizabeth, Stemkovski, Michael, Graae, Bente Jessen, Sørensen, Mia Vedel, Høye, Toke T, Calzado, M Rosa Fernández, Lorite, Juan, Carbognani, Michele, Tomaselli, Marcello, Forte, T'ai GW, Petraglia, Alessandro, Haesen, Stef, Somers, Ben, Van Meerbeek, Koenraad, Björkman, Mats P, Hylander, Kristoffer, Merinero, Sonia, Gharun, Mana, Buchmann, Nina, Dolezal, Jiri, Matula, Radim, Thomas, Andrew D, Bailey, Joseph J, Ghosn, Dany, Kazakis, George, Pablo, Miguel A, Kemppinen, Julia, Niittynen, Pekka, Rew, Lisa, Seipel, Tim, Larson, Christian, Speed, James DM, Ardö, Jonas, Cannone, Nicoletta, Guglielmin, Mauro, Malfasi, Francesco, Bader, Maaike Y, Canessa, Rafaella, Stanisci, Angela, Kreyling, Juergen, Schmeddes, Jonas, Teuber, Laurenz, Aschero, Valeria, Čiliak, Marek, Máliš, František, De Smedt, Pallieter, Govaert, Sanne, Meeussen, Camille, Vangansbeke, Pieter, Gigauri, Khatuna, Lamprecht, Andrea, Pauli, Harald, Steinbauer, Klaus, Winkler, Manuela, Ueyama, Masahito, and Nuñez, Martin A
Subjects: Climate Action, Climate Change, Ecosystem, Microclimate, Snow, Temperature, climate change, database, ecosystem processes, microclimate, soil climate, species distributions, temperature, topoclimate, Environmental Sciences, Biological Sciences, Ecology
Abstract: Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.
Published: 2020

4. Patterns and controls of the variability of radiation use efficiency and primary productivity across terrestrial ecosystems

Author: Garbulsky, Martín F, Peñuelas, Josep, Papale, Dario, Ardö, Jonas, Goulden, Michael L, Kiely, Gerard, Richardson, Andrew D, Rotenberg, Eyal, Veenendaal, Elmar M, and Filella, Iolanda
Subjects: Carbon cycle, climatic controls, eddy covariance, gross primary productivity, radiation use efficiency, remote sensing, terrestrial vegetation, Physical Geography and Environmental Geoscience, Ecological Applications, Ecology
Abstract: Aim: The controls of gross radiation use efficiency (RUE), the ratio between gross primary productivity (GPP) and the radiation intercepted by terrestrial vegetation, and its spatial and temporal variation are not yet fully understood. Our objectives were to analyse and synthesize the spatial variability of GPP and the spatial and temporal variability of RUE and its climatic controls for a wide range of vegetation types. Location: A global range of sites from tundra to rain forest. Methods: We analysed a global dataset on photosynthetic uptake and climatic variables from 35 eddy covariance (EC) flux sites spanning between 100 and 2200 mm mean annual rainfall and between -13 and 26°C mean annual temperature. RUE was calculated from the data provided by EC flux sites and remote sensing (MODIS). Results: Rainfall and actual evapotranspiration (AET) positively influenced the spatial variation of annual GPP, whereas temperature only influenced the GPP of forests. Annual and maximum RUE were also positively controlled primarily by annual rainfall. The main control parameters of the growth season variation of gross RUE varied for each ecosystem type. Overall, the ratio between actual and potential evapotranspiration and a surrogate for the energy balance explained a greater proportion of the seasonal variation of RUE than the vapour pressure deficit (VPD), AET and precipitation. Temperature was important for determining the intra-annual variability of the RUE at the coldest energy-limited sites. Main conclusions: Our analysis supports the idea that the annual functioning of vegetation that is adapted to its local environment is more constrained by water availability than by temperature. The spatial variability of annual and maximum RUE can be largely explained by annual precipitation, more than by vegetation type. The intra-annual variation of RUE was mainly linked to the energy balance and water availability along the climatic gradient. Furthermore, we showed that intra-annual variation of gross RUE is only weakly influenced by VPD and temperature, contrary to what is frequently assumed. Our results provide a better understanding of the spatial and temporal controls of the RUE and thus could lead to a better estimation of ecosystem carbon fixation and better modelling. © 2009 Blackwell Publishing Ltd.
Published: 2010

5. Global maps of soil temperature

Author: Winkler, Manuela, Plichta, Roman, Buysse, Pauline, Lohila, Annalea, Spicher, Fabien, Boeckx, Pascal, Wild, Jan, Feigenwinter, Iris, Olejnik, Janusz, Risch, Anita, Khuroo, Anzar, Lynn, Joshua, di Cella, Umberto, Schmidt, Marius, Urbaniak, Marek, Marchesini, Luca, Govaert, Sanne, Uogintas, Domas, Assis, Rafael, Medinets, Volodymyr, Abdalaze, Otar, Varlagin, Andrej, Dolezal, Jiri, Myers, Jonathan, Randall, Krystal, Bauters, Marijn, Jimenez, Juan, Stoll, Stefan, Petraglia, Alessandro, Mazzolari, Ana, Ogaya, Romà, Tyystjärvi, Vilna, Hammerle, Albin, Wipf, Sonja, Lorite, Juan, Fanin, Nicolas, Benavides, Juan, Scholten, Thomas, Yu, Zicheng, Veen, G., Treier, Urs, Candan, Onur, Bell, Michael, Hörtnagl, Lukas, Siebicke, Lukas, Vives-Ingla, Maria, Eugster, Werner, Grelle, Achim, Stemkovski, Michael, Theurillat, Jean-Paul, Matula, Radim, Dorrepaal, Ellen, Steinbrecher, Rainer, Alatalo, Juha, Fenu, Giuseppe, Arzac, Alberto, Homeier, Jürgen, Porro, Francesco, Robinson, Sharon, Ghosn, Dany, Haugum, Siri, Ziemblińska, Klaudia, Camargo, José, Zhao, Peng, Niittynen, Pekka, Liljebladh, Bengt, Normand, Signe, Dias, Arildo, Larson, Christian, Peichl, Matthias, Collier, Laura, Myers-Smith, Isla, Zong, Shengwei, Kašpar, Vít, Cooper, Elisabeth, Haider, Sylvia, von Oppen, Jonathan, Cutini, Maurizio, Benito-Alonso, José-Luis, Luoto, Miska, Klemedtsson, Leif, Higgens, Rebecca, Zhang, Jian, Speed, James, Nijs, Ivan, Macek, Martin, Steinwandter, Michael, Poyatos, Rafael, Niedrist, Georg, Curasi, Salvatore, Yang, Yan, Dengler, Jürgen, Géron, Charly, de Pablo, Miguel, Xenakis, Georgios, Kreyling, Juergen, Forte, Tai, Bailey, Joseph, Knohl, Alexander, Goulding, Keith, Wilkinson, Matthew, Kljun, Natascha, Roupsard, Olivier, Stiegler, Christian, Verbruggen, Erik, Wingate, Lisa, Lamprecht, Andrea, Hamid, Maroof, Rossi, Graziano, Descombes, Patrice, Hrbacek, Filip, Bjornsdottir, Katrin, Poulenard, Jérôme, Meeussen, Camille, Guénard, Benoit, Venn, Susanna, Dimarco, Romina, Man, Matěj, Scharnweber, Tobias, Chown, Steven, Pio, Casimiro, Way, Robert, Erickson, Todd, Fernández-Pascual, Eduardo, Pușcaș, Mihai, Orsenigo, Simone, Di Musciano, Michele, Enquist, Brian, Newling, Emily, Tagesson, Torbern, Kemppinen, Julia, Serra-Diaz, Josep, Gottschall, Felix, Schuchardt, Max, Pitacco, Andrea, Jump, Alistair, Exton, Dan, Carnicer, Jofre, Aschero, Valeria, Urban, Anastasiya, Daskalova, Gergana, Santos, Cinthya, Goeckede, Mathias, Bruna, Josef, Andrews, Christopher, Jónsdóttir, Ingibjörg, Casanova-Katny, Angélica, Moriana-Armendariz, Mikel, Ewers, Robert, Pärtel, Meelis, Sagot, Clotilde, Herbst, Mathias, De Frenne, Pieter, Milbau, Ann, Gobin, Anne, Alexander, Jake, Kopecký, Martin, Buchmann, Nina, Kotowska, Martyna, Puchalka, Radoslaw, Penuelas, Josep, Gigauri, Khatuna, Prokushkin, Anatoly, Moiseev, Pavel, Jentsch, Anke, Klisz, Marcin, Barrio, Isabel, Ammann, Christof, Panov, Alexey, Van Geel, Maarten, Finckh, Manfred, Vaccari, Francesco, Erschbamer, Brigitta, Backes, Amanda, Robroek, Bjorn, Campoe, Otávio, Ahmadian, Negar, Boike, Julia, Thomas, Haydn, Pastor, Ada, Smith, Stuart, Pauli, Harald, Kollár, Jozef, de Cássia Guimarães Mesquita, Rita, Michaletz, Sean, Fuentes-Lillo, Eduardo, Urban, Josef, Greenwood, Sarah, Lens, Luc, Van de Vondel, Stijn, Vitale, Luca, Remmele, Sabine, Naujokaitis-Lewis, Ilona, Meusburger, Katrin, Cremonese, Edoardo, Barros, Agustina, Bokhorst, Stef, Svátek, Martin, Allonsius, Camille, Høye, Toke, Smiljanic, Marko, Hik, David, Canessa, Rafaella, van den Hoogen, Johan, Altman, Jan, Björkman, Mats, Cesarz, Simone, Blonder, Benjamin, Kazakis, George, Opedal, Øystein, Assmann, Jakob, Tanentzap, Andrew, Sidenko, Nikita, le Maire, Guerric, Ursu, Tudor-Mihai, Montagnani, Leonardo, Muffler, Lena, Hederová, Lucia, Rubtsov, Alexey, Pauchard, Aníbal, Tielbörger, Katja, Sørensen, Mia, Crowther, Thomas, Remmers, Wolfram, Pitteloud, Camille, Zyryanov, Viacheslav, Nilsson, Matts, Bazzichetto, Manuele, Sallo-Bravo, Jhonatan, Moiseev, Dmitry, Spasojevic, Marko, Haase, Peter, Pearse, William, Tutton, Rosamond, Fazlioglu, Fatih, Siqueira, David, Ardö, Jonas, Nardino, Marianna, Tomaselli, Marcello, Pavelka, Marian, García, Rafael, Nosetto, Marcelo, Bon, Matteo, Semenchuk, Philipp, Choler, Philippe, Scott, Tony, Halbritter, Aud, Dušek, Jiří, Mackenzie, Roy, Stanisci, Angela, Nouvellon, Yann, Kovács, Bence, Haesen, Stef, Veenendaal, Elmar, Juszczak, Radoslaw, Verheijen, Frank, de Andrade, Ana, Verbeeck, Hans, Bader, Maaike, RENAULT, David, Zimmermann, Reiner, Ferlian, Olga, Medinets, Sergiy, Walz, Josefine, Rossi, Christian, Rocha, Adrian, Lembrechts, Jonas, Jactel, Hervé, Brum, Barbara, Aartsma, Peter, Kobler, Johannes, Eisenhauer, Nico, Bjerke, Jarle, Pellissier, Loïc, Ueyama, Masahito, Manca, Giovanni, Bahalkeh, Khadijeh, Meysman, Filip, Niessner, Armin, Curtis, Robin, Six, Johan, Saccone, Patrick, Wang, Runxi, Ahrends, Antje, Okello, Joseph, Kolle, Olaf, Portillo-Estrada, Miguel, Laska, Kamil, Freeman, Erika, Di Cecco, Valter, Ashcroft, Michael, Steinbauer, Klaus, Della Chiesa, Stefano, van den Brink, Liesbeth, Herberich, Maximiliane, Loubet, Benjamin, Barančok, Peter, Hermanutz, Luise, Souza, Bartolomeu, Contador, Tamara, Zhang, Zhaochen, Aerts, Rien, Stephan, Jörg, Chojnicki, Bogdan, Manco, Antonio, Larson, Keith, Mondoni, Andrea, Palaj, Andrej, Schmeddes, Jonas, Hepenstrick, Daniel, Järveoja, Järvi, Manise, Tanguy, Barthel, Matti, Marciniak, Felipe, Weigel, Robert, Rixen, Christian, Turtureanu, Pavel, Hoffrén, Raúl, Iwata, Hiroki, Vittoz, Pascal, Wedegärtner, Ronja, Penczykowski, Rachel, Phartyal, Shyam, Sitková, Zuzana, Nagy, Laszlo, Ujházy, Karol, Heinesch, Bernard, Berauer, Bernd, Ogée, Jérôme, Malfasi, Francesco, Greise, Caroline, Helfter, Carole, Mosedale, Jonathan, Senior, Rebecca, Magliulo, Enzo, Nuñez, Martin, García, María, Wohlfahrt, Georg, Carbognani, Michele, Thomas, Andrew, Eklundh, Lars, Erfanian, Mohammad, Villar, Luis, Maier, Regine, Dahlberg, C., Guglielmin, Mauro, Jucker, Tommaso, Kelly, Julia, Olesen, Jørgen, Lang, Simone, Tanneberger, Franziska, Gharun, Mana, Jackowicz-Korczynski, Marcin, Convey, Peter, Aalto, Juha, Scheffers, Brett, Ujházyová, Mariana, Andres, Christian, Arriga, Nicola, Smith-Tripp, Sarah, Kanka, Róbert, Dick, Jan, Leihy, Rachel, Van Meerbeek, Koenraad, Maclean, Ilya, Vangansbeke, Pieter, Pampuch, Timo, Čiliak, Marek, Guillemot, Joannès, Sarneel, Judith, Souza, José, Svoboda, Miroslav, Björk, Robert, Merinero, Sonia, Zellweger, Florian, Simpson, Elizabeth, Cannone, Nicoletta, Abedi, Mehdi, Seipel, Tim, Klinges, David, Máliš, František, Basham, Edmund, Sewerniak, Piotr, Schwartz, Naomi, Trouillier, Mario, Vandvik, Vigdis, Shekhar, Ankit, Munoz-Rojas, Miriam, Nicklas, Lena, Goded, Ignacio, Manolaki, Paraskevi, Radujković, Dajana, Yu, Kailiang, Phoenix, Gareth, Cifuentes, Edgar, Seeber, Julia, Deronde, Bart, Lenoir, Jonathan, Frei, Esther, Wilmking, Martin, Hylander, Kristoffer, Graae, Bente, Calzado, M., Wang, Yifeng, Hampe, Arndt, Somers, Ben, Mörsdorf, Martin, Jastrzebowski, Szymon, Ejtehadi, Hamid, Terrestrial Ecology (TE), Universidad de Alcalá. Departamento de Geología, Geografía y Medio Ambiente, BioGeoClimate Modelling Lab, Department of Geosciences and Geography, Helsinki Institute of Sustainability Science (HELSUS), Institute for Atmospheric and Earth System Research (INAR), Universiteit Antwerpen = University of Antwerpen [Antwerpen], Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire d'Ecologie Alpine (LECA ), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), LTSER Zone Atelier Alpes, Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes (UMR Eco&Sols), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Senckenberg Research Institute and Natural History Museum [Frankfurt], Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung, Leibniz Association-Leibniz Association, Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Environnements, Dynamiques et Territoires de Montagne (EDYTEM), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Institut Universitaire de France (IUF), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ecologie et Dynamique des Systèmes Anthropisés - UMR CNRS 7058 (EDYSAN), Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), 12P1819N, Fonds Wetenschappelijk Onderzoek, ANR-10-LABX-0045,COTE,COntinental To coastal Ecosystems: evolution, adaptability and governance(2010), ANR-13-ISV7-0004,ODYSSEE,De nouvelles voies pour la modélisation des dynamiques d'assemblages d'espèces intégrant l'écologie et l'évolution: le cas des écosystèmes de montagne des Alpes et des Carpates(2013), ANR-20-EBI5-0004,ASICS,ASsessing and mitigating the effects of climate change and biological Invasions on the spatial redistribution of biodiversity in Cold environmentS(2020), ANR-19-CE32-0005,IMPRINT,IMpacts des PRocessus mIcroclimatiques sur la redistributioN de la biodiversiTé forestière en contexte de réchauffement du macroclimat(2019), European Project: 774124 , H2020,H2020-SFS-2017-2,SUPER-G (2018), European Project: 282910,EC:FP7:ENV,FP7-ENV-2011,ECLAIRE(2011), European Project: 641918,H2020,H2020-SC5-2014-two-stage,AfricanBioServices(2015), European Project: 678841,H2020,ERC-2015-STG,NICH(2016), European Project: 871128,eLTER PLUS (2020), European Project: 861974, H2020,SOCIETAL CHALLENGES - Food security, sustainable agriculture and forestry, marine, maritime and inland water research, and the bioeconomy,SustainSahel(2020), Lembrechts, Jonas J [0000-0002-1933-0750], van den Hoogen, Johan [0000-0001-6624-8461], Aalto, Juha [0000-0001-6819-4911], De Frenne, 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Subjects: 0106 biological sciences, Zoology and botany: 480 [VDP], Q1, 01 natural sciences, Global map, SDG 13 - Climate Action, Soil temperature, Zone climatique, bepress|Physical Sciences and Mathematics|Environmental Sciences, bioclimatic variables, global maps, microclimate, near-surface temperatures, soil temperature, soil-dwelling organisms, temperature offset, weather stations, ComputingMilieux_MISCELLANEOUS, General Environmental Science, Global and Planetary Change, GB, Geology, PE&RC, 6. Clean water, Near-surface soil temperature, international, [SDE]Environmental Sciences, 551: Geologie und Hydrologie, Plantenecologie en Natuurbeheer, Température du sol, Near-surface temperature, Near-surface temperatures, Biologie, P40 - Météorologie et climatologie, bepress|Physical Sciences and Mathematics|Earth Sciences, MITIGATION, bepress|Life Sciences|Ecology and Evolutionary Biology, bepress|Physical Sciences and Mathematics|Oceanography and Atmospheric Sciences and Meteorology|Climate, Bioclimatic variables, Settore BIO/07 - ECOLOGIA, 577: Ökologie, Biology, Ecosystem, Ekologi, Changement climatique, Cartographie, Biology and Life Sciences, Microclimate, 15. Life on land, bepress|Physical Sciences and Mathematics|Environmental Sciences|Environmental Monitoring, Agriculture and Soil Science, 0401 agriculture, forestry, and fisheries, Temperature offset, Weather stations, Plan_S-Compliant-OA, Soil, bepress|Life Sciences, ddc:550, Geología, Ecology, Temperature, 04 agricultural and veterinary sciences, Biological Sciences, FOREST, Weather station, Variation saisonnière, Chemistry, Bioclimatologie, bepress|Physical Sciences and Mathematics, 1171 Geosciences, Technology and Engineering, Climate Change, Plant Ecology and Nature Conservation, MOISTURE, LITTER DECOMPOSITION, PERMAFROST, ddc:570, SUITABILITY, G1, bepress|Physical Sciences and Mathematics|Oceanography and Atmospheric Sciences and Meteorology, Global maps, VDP::Mathematics and natural scienses: 400::Zoology and botany: 480, Environmental Chemistry, Zoologiske og botaniske fag: 480 [VDP], Soil-dwelling organisms, Aquatic Ecology, P30 - Sciences et aménagement du sol, Bioclimatic variable, SNOW-COVER, bepress|Physical Sciences and Mathematics|Earth Sciences|Soil Science, Earth sciences, PLANT-RESPONSES, CLIMATIC CONTROLS, Soil-dwelling organism, 13. Climate action, Earth and Environmental Sciences, VDP::Matematikk og naturvitenskap: 400::Zoologiske og botaniske fag: 480, 040103 agronomy & agriculture, Réchauffement global, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Environmental Sciences, 010606 plant biology & botany
Abstract: JJL received funding from the Research Foundation Flanders (grant nr. 12P1819N). The project received funding from the Research Foundation Flanders (grants nrs, G018919N, W001919N). JVDH and TWC received funding from DOB Ecology. JA received funding from the University of Helsinki, Faculty of Science (MICROCLIM, grant nr. 7510145) and Academy of Finland Flagship (grant no. 337552). PDF, CM and PV received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (ERC Starting Grant FORMICA 757833). JK received funding from the Arctic Interactions at the University of Oulu and Academy of Finland (318930, Profi 4), Maaja vesitekniikan tuki ry., Tiina and Antti Herlin Foundation, Nordenskiold Samfundet and Societas pro Fauna et Flora Fennica. MK received funding from the Czech Science Foundation (grant nr. 20-28119S) and the Czech Academy of Sciences (grant nr. RVO 67985939). TWC received funding from National Geographic Society grant no. 9480-14 and WW-240R-17. MA received funding from CISSC (program ICRP (grant nr:2397) and INSF (grant nr: 96005914). The Royal Botanic Garden Edinburgh is supported by the Scottish Government's Rural and Environment Science and Analytical Services Division. JMA received funding from the Funding Org. Qatar Petroleum (grant nr. QUEX-CAS-QP-RD-18/19). JMA received funding from the European Union's Horizon 2020 research and innovation program (grant no. 678841) and from the Swiss National Science Foundation (grant no. 31003A_176044). JA was supported by research grants LTAUSA19137 (program INTER-EXCELLENCE, subprogram INTER-ACTION) provided by Czech Ministry of Education, Youth and Sports and 20-05840Y of the Czech Science Foundation. AA was supported by the Ministry of Science and Higher Education of the Russian Federation (grant FSRZ-2020-0014). SN, UAT, JJA, and JvO received funding from the Independent Research Fund Denmark (7027-00133B). LvdB, KT, MYB and RC acknowledge funding from the German Research Foundation within the Priority Program SPP-1803 'EarthShape: Earth Surface Shaping by Biota' (grant TI 338/14-1&2 and BA 3843/6-1). PB was supported by grant project VEGA of the Ministry of Education of the Slovak Republic and the Slovak Academy of Sciences No. 2/0132/18. Forest Research received funding from the Forestry Commission (climate change research programme). JCB acknowledges the support of Universidad Javeriana. JLBA received funding from the Direccion General de Cambio Climatico del Gobierno de Aragon; JLBA acknowledges fieldwork assistance by Ana Acin, the Ordesa y Monte Perdido National Park, and the Servicio de Medio Ambiente de Soria de la Junta de Castilla y Leon. RGB and MPB received funding from BECC - Biodiversity and Ecosystem services in a Changing Climate. MPB received funding from The European Union's Horizon 2020 research and innovation program under the Marie Skodowska-Curie Grant Agreement No. 657627 and The Swedish Research Council FORMAS - future research leaders No. 2016-01187. JB received funding from the Czech Academy of Sciences (grant nr. RVO 67985939). NB received funding from the SNF (grant numbers 40FA40_154245, 20FI21_148992, 20FI20_173691, 407340_172433) and from the EU (contract no. 774124). ICOS EU research infrastructure. EU FP7 NitroEurope. EU FP7 ECLAIRE. The authors from Biological Dynamics of Forest Fragments Project, PDBFF, Instituto Nacional de Pesquisas da Amazonia, Brazil were supported by the MCTI/CNPq/FNDCT - AcAo Transversal no68/2013 - Programa de Grande Escala da Biosfera-Atmosfera na Amazonia - LBA; Project 'Como as florestas da Amazonia Central respondem as variacoes climaticas? Efeitos sobre dinamica florestal e sinergia com a fragmentacAo florestal'. This is the study 829 of the BDFFP Technical Series. to The EUCFLUX Cooperative Research Program and Forest Science and Research Institute-IPEF. NC acknowledges funding by Stelvio National Park. JC was funded by the Spanish government grant CGL2016-78093-R. ANID-FONDECYT 1181745 AND INSTITUTO ANTARTICO CHILENO (INACH FR-0418). SC received funding from the German Research Foundation (grant no. DFG- FZT 118, 202548816). The National Science Foundation, Poland (grant no. UMO-2017/27/B/ST10/02228), within the framework of the 'Carbon dioxide uptake potential of sphagnum peatlands in the context of atmospheric optical parameters and climate changes' (KUSCO2) project. SLC received funding from the South African National Research Foundation and the Australian Research Council. FM, M, KU and MU received funding from Slovak Research and Development Agency (no. APVV-19-0319). Instituto Antartico Chileno (INACH_RT-48_16), Iniciativa Cientifica Milenio Nucleo Milenio de Salmonidos Invasores INVASAL, Institute of Ecology and Biodiversity (IEB), CONICYT PIA APOYO CCTE AFB170008. PC is supported by NERC core funding to the BAS 'Biodiversity, Evolution and Adaptation Team. EJC received funding from the Norwegian Research Council (grant number 230970). GND was supported by NERC E3 doctoral training partnership grant (NE/L002558/1) at the University of Edinburgh and the Carnegie Trust for the Universities of Scotland. Monitoring stations on Livingston Island, Antarctica, were funded by different research projects of the Gobern of Spain (PERMAPLANET CTM2009-10165-E; ANTARPERMA CTM2011-15565-E; PERMASNOW CTM2014-52021-R), and the PERMATHERMAL arrangement between the University of Alcala and the Spanish Polar Committee. GN received funding from the Autonomous Province of Bolzano (ITA). The infrastructure, part of the UK Environmental Change Network, was funded historically in part by ScotNature and NERC National Capability LTS-S: UK-SCAPE; NE/R016429/1). JD was supported by the Czech Science Foundation (GA17-19376S) and MSMT (LTAUSA18007). ED received funding from the Kempe Foundation (JCK-1112 and JCK-1822). The infrastructure was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme I (NPU I), grant number LO1415 and by the project for national infrastructure support CzeCOS/ICOS Reg. No. LM2015061. NE received funding from the German Research Foundation (DFG- FZT 118, 202548816). BE received funding from the GLORIA-EU project no EVK2-CT2000-00056, the Autonomous Province of Bolzano (ITA), from the Tiroler Wissenschaftsfonds and from the University of Innsbruck. RME was supported by funding to the SAFE Project from the Sime Darby Foundation. OF received funding from the German Research Foundation (DFG- FZT 118, 202548816). EFP was supported by the Jardin Botanico Atlantico (SV-20-GIJON-JBA). MF was funded by the German Federal Ministry of Education and Research (BMBF) in the context of The Future Okavango (Grant No. 01LL0912) and SASSCAL (01LG1201M; 01LG1201N) projects. EFL received funding from ANID PIA / BASAL FB210006. RAG received funding from Fondecyt 11170516, CONICYT PIA AFB170008 and ANID PIA / BASAL FB210006. MBG received funding from National Parks (DYNBIO, #1656/2015) and The Spanish Research Agency (VULBIMON, #CGL2017-90040-R). MG received funding from the Swiss National Science Foundation (ICOS-CH Phase 2 20FI20_173691). FG received funding from the German Research Foundation (DFG- FZT 118, 202548816). KG and TS received funding from the UK Biotechnology and Biological Research Council (grant = 206/D16053). SG was supported by the Research Foundation Flanders (FWO) (project G0H1517N). KJ and PH received funding from the EU Horizon2020 INFRAIA project eLTER-PLUS (871128), the project LTER-CWN (FFG, F&E Infrastrukturforderung, project number 858024) and the Austrian Climate Research Program (ACRP7 - CentForCSink - KR14AC7K11960). SH and ARB received funding through iDiv funded by the German Research Foundation (DFG- FZT 118, 202548816). LH received funding from the Czech Science Foundation (grant nr. 20-28119S) and the Czech Academy of Sciences (grant nr. RVO 67985939). MH received funding from the Baden-Wurttemberg Ministry of Science, Research and Arts via the project DRIeR (Drought impacts, processes and resilience: making the in-visible visible). LH received funding from International Polar Year, Weston Foundation, and ArcticNet. DH received funding from Natural Sciences and Engineering Council (Canada) (RGPIN-06691). TTH received funding from Independent Research Fund Denmark (grant no. 8021-00423B) and Villum Foundation (grant no. 17523). Ministry of Education, Youth and Sports of the Czech Republic (projects LM2015078, VAN2020/01 and CZ.02.1.01/0.0/0.0/16_013/0001708). KH, CG and CJD received funding from Bolin Centre for Climate Research, Stockholm University and from the Swedish research council Formas [grant n:o 2014-00530 to KH]. JJ received funding from the Funding Org. Swedish Forest Society Foundation (grant nr. 2018-485-Steg 2 2017) and Swedish Research Council FORMAS (grant nr. 2018-00792). AJ received funding from the German Federal Ministry of Education and Research BMBF (Grant Nr. FKZ 031B0516C SUSALPS) and the Oberfrankenstiftung (Grant Nr. OFS FP00237). ISJ received funding from the Energy Research Fund (NYR-11 - 2019, NYR-18 - 2020). TJ was supported by a UK NERC Independent Research Fellowship (grant number: NE/S01537X/1). RJ received funding from National Science Centre of Poland (grant number: 2016/21/B/ST10/02271) and Polish National Centre for Research and Development (grant number: Pol-Nor/203258/31/2013). VK received funding from the Czech Academy of Sciences (grant nr. RVO 67985939). AAK received funding from MoEFCC, Govt of India (AICOPTAX project F. No. 22018/12/2015/RE/Tax). NK received funding from FORMAS (grants nr. 2018-01781, 2018-02700, 2019-00836), VR, support from the research infrastructure ICOS-SE. BK received funding from the National Research, Development and Innovation Fund of Hungary (grant nr. K128441). Ministry of Education, Youth and Sports of the Czech Republic (projects LM2015078 and CZ.02.1.01/0.0/0.0/16_013/0001708). Project B1-RNM-163-UGR-18-Programa Operativo FEDER 2018, partially funded data collection. Norwegian Research Council (NORKLIMA grants #184912 and #244525) awarded to Vigdis Vandvik. MM received funding from the Czech Science Foundation (grant nr. 20-28119S) and the Czech Academy of Sciences (grant nr. RVO 67985939). Project CONICYT-PAI 79170119 and ANID-MPG 190029 awarded to Roy Mackenzie. This work was partly funded by project MIUR PON Cluster OT4CLIMA. RM received funding from the SNF project number 407340_172433. FM received funding from the Stelvio National Park. PM received funding from AIAS-COFUND fellowship programme supported by the Marie Skodowska- Curie actions under the European Union's Seventh Framework Pro-gramme for Research, Technological development and Demonstration (grant agreement no 609033) and the Aarhus University Research Foundation, Denmark. RM received funding from the Ministry of Education, Youth and Sports of the Czech Republic (project LTT17033). SM and VM received funding from EU FP6 NitroEurope (grant nr. 17841), EU FP7 ECLAIRE (grant nr. 282910), the Ministry of Education and Science of Ukraine (projects nr. 505, 550, 574, 602), GEF-UNEP funded "Toward INMS" project (grant nr. NEC05348) and ENI CBC BSB PONTOS (grant nr. BSB 889). The authors from Biological Dynamics of Forest Fragments Project, PDBFF, Instituto Nacional de Pesquisas da Amazonia, Brazil were supported by the MCTI/CNPq/FNDCT - AcAo Transversal no68/2013 - Programa de Grande Escala da Biosfera-Atmosfera na Amazonia - LBA; Project 'Como as florestas da Amazonia Central respondem as variacoes climaticas? Efeitos sobre dinamica florestal e sinergia com a fragmentacAo florestal'. FJRM was financially supported by the Netherlands Organization for Scientific Research (VICI grant 016.VICI.170.072) and Research Foundation Flanders (FWO-SBO grant S000619N). STM received funding from New Frontiers in Research Fund-Exploration (grant nr. NFRF-2018-02043) and NSERC Discovery. MMR received funding from the Australian Research Council Discovery Early Career Research Award (grant nr. DE180100570). JAM received funding from the National Science Foundation (DEB 1557094), International Center for Advanced Renewable Energy and Sustainability (I-CARES) at Washington University in St. Louis, ForestGEO, and Tyson Research Center. IM-S was funded by the UK Natural Environment Research Council through the ShrubTundra Project (NE/M016323/1). MBN received funding from FORMAS, VR, Kempe Foundations support from the research infrastructures ICOS and SITES. MDN received funding from CONICET (grant nr. PIP 112-201501-00609). Spanish Ministry of Science grant PID2019-110521GB-I00 and Catalan government grant 2017-1005. French National Research Agency (ANR) in the frame of the Cluster of Excellence COTE (project HydroBeech, ANR-10-LABX-45). VLIR-OUS, under the Institutional University Coorperation programme (IUC) with Mountains of the Moon University. Project LAS III 77/2017/B entitled: \"Estimation of net carbon dioxide fluxes exchanged between the forest ecosystem on post-agricultural land and between the tornado-damaged forest area and the atmosphere using spectroscopic and numerical methods\", source of funding: General Directorate of State Forests, Warsaw, Poland. Max Planck Society (Germany), RFBR, Krasnoyarsk Territory and Krasnoyarsk Regional Fund of Science, project number 20-45-242908. Estonian Research Council (PRG609), and the European Regional Development Fund (Centre of Excellence EcolChange). Canada-Denmark Arctic Research Station Early Career Scientist Exchange Program, from Polar knowledge Canada (POLAR) and the Danish Agency for Science and Higher Education. AP received funding from Fondecyt 1180205, CONICYT PIA AFB170008 and ANID PIA / BASAL FB210006. MP received funding from the Funding Org. Knut and Alice Wallenberg Foundation (grant nr. 2015.0047), and acknowledges funding from the Swedish Research Council (VR) with contributing research institutes to both the SITES and ICOS Sweden infrastructures. JP and RO were funded by the Spanish Ministry of Science grant PID2019-110521GB-I00, the fundacion Ramon Areces grant ELEMENTAL-CLIMATE, and the Catalan government grant 2017-1005. MPB received funding from the Svalbard Environmental Protection Fund (grant project number 15/128) and the Research Council of Norway (Arctic Field Grant, project number 269957). RP received funding from the Ministry of Education, Youth and Sports of the Czech Republic (grant INTER-TRANSFER nr. LTT20017). LTSER Zone Atelier Alpes; Federation FREE-Alpes. RP received funding from a Humboldt Fellowship for Experienced Researchers. Prokushkin AS and Zyryanov VI contribution has been supported by the RFBR grant #18-05-60203-Arktika. RPu received founding from the Polish National Science Centre (grant project number 2017/27/B/NZ8/00316). ODYSSEE project (ANR-13-ISV7-0004, PN-II-ID-JRP-RO-FR-2012). KR was supported through an Australian Government Research Training Program Scholarship. Fieldwork was supported by the Global Challenges program at the University of Wollongong, the ARC the Australian Antarctic Division and INACH. DR was funded by the project SUBANTECO IPEV 136 (French Polar Institute Paul-Emile Victor), Zone Atelier CNRS Antarctique et Terres Australes, SAD Region Bretagne (Project INFLICT), BiodivERsa 2019-2020 BioDivClim call 'ASICS' (ANR-20-EBI5-0004). SAR received funding from the Australian Research Council. NSF grant #1556772 to the University of Notre Dame. Pavia University (Italy). OR received funding from EU-LEAP-Agri (RAMSES II), EU-DESIRA (CASSECS), EU-H2020 (SustainSahel), AGROPOLIS and TOTAL Foundations (DSCATT), CGIAR (GLDC). AR was supported by the Russian Science Foundation (Grant 18-74-10048). Parc national des Ecrins. JS received funding from Vetenskapsradet grant nr (No: 2014-04270), ALTER-net multi-site grant, River LIFE project (LIFE08 NAT/S/000266), Flexpeil. Helmholtz Association long-term research program TERENO (Terrestrial Environmental Observatories). PS received funding from the Polish Ministry of Science and Higher Education (grant nr. N N305 304840). AS acknowledges funding by ETH Zurich project FEVER ETH-27 19-1. LSC received funding from NSERC Canada Graduate Scholarship (Doctoral) Program; LSC was also supported by ArcticNet-NCE (insert grant #). Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (141513/2017-9); FundacAo Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro (E26/200.84/2019). ZS received funding from the SRDA (grants nos. APVV-16-0325 and APVV-20-0365) and from the ERDF (grant no. ITMS 313011S735, CE LignoSilva). JS, MB and CA received funding from core budget of ETH Zurich. State excellence Program M-V \"WETSCAPES\". AfricanBioServices project funded by the EU Horizon 2020 grant number 641918. The authors from KIT/IMK-IFU acknowledge the funding received within the German Terrestrial Environmental Observatories (TERENO) research program of the Helmholtz Association and from the Bavarian Ministry of the Environment and Public Health (UGV06080204000). Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project number 192626868, in the framework of the collaborative German-Indonesian research project CRC 990 (SFB): 'EFForTS, Ecological and Socioeconomic Functions of Tropical Lowland Rainforest Transformation Systems (Sumatra, Indonesia)'. MS received funding from the Ministry of Education, Youth and Sports of the Czech Republic (grant nr. INTER-TRANSFER LTT19018). TT received funding from the Swedish National Space Board (SNSB Dnr 95/16) and the CASSECS project supported by the European Union. HJDT received funding from the UK Natural Environment Research Council (NERC doctoral training partnership grant NE/L002558/1). German Science Foundation (DFG) GraKo 2010 \"Response\". PDT received funding from the MEMOIRE project (PN-III-P1-1.1-PD2016-0925). Arctic Challenge for Sustainability II (ArCS II; JPMXD1420318865). JU received funding from Czech Science Foundation (grant nr. 21-11487S). TU received funding from the Romanian Ministry of Education and Research (CCCDI - UEFISCDI -project PN-III-P2-2.1-PED-2019-4924 and PN2019-2022/19270201-Ctr. 25N BIODIVERS 3-BIOSERV). AV acknowledge funding from RSF, project 21-14-00209. GFV received funding from the Dutch Research Council NWO (Veni grant, no. 863.14.013). Australian Research Council Discovery Early Career Research Award DE140101611. FGAV received funding from the Portuguese Science Foundation (FCT) under CEECIND/02509/2018, CESAM (UIDP/50017/2020+UIDB/50017/2020), FCT/MCTES through national funds, and the co-funding by the FEDER, within the PT2020 Partnership Agreement and Compete 2020. Ordesa y Monte Perdido National Park. MVI received funding from the Spanish Ministry of Science and Innovation through a doctoral grant (FPU17/05869). JW received funding from the Czech Science Foundation (grant nr. 20-28119S) and the Czech Academy of Sciences (grant nr. RVO 67985939). CR and SW received funding from the Swiss Federal Office for the Environment (FOEN) and the de Giacomi foundation. YY received funding from the National Natural Science Foundation of China (Grant no. 41861134039 and 41941015). ZY received funding from the National Natural Science Foundation of China (grant nr. 41877458). FZ received funding from the Swiss National Science Foundation (grant nr. 172198 and 193645). PZ received funding from the Funding Org. Knut and Alice Wallenberg Foundation (grant no. 2015.0047). JL received funding from (i) the Agence Nationale de la Recherche (ANR), under the framework of the young investigators (JCJC) funding instrument (ANR JCJC Grant project NoANR-19-CE32-0005-01: IMPRINT) (ii) the Centre National de la Recherche Scientifique (CNRS) (Defi INFINITI 2018: MORFO); and the Structure Federative de Recherche (SFR) Condorcet (FR CNRS 3417: CREUSE). Fieldwork in the Arctic got facilitated by funding from the EU INTERACT program. SN, UAT, JJA and JvO would like to thank the field team of the Vegetation Dynamics group for their efforts and hard work. We acknowledge Dominique Tristan for letting access to the field. For the logistic support the crew of INACH and Gabriel de Castilla Station team on Deception Island. We thank the Inuvialuit and Kluane First Nations for the opportunity to work on their land. MAdP acknowledges fieldwork assistance and logistics support to Unidad de Tecnologia Marina CSIC, and the crew of Juan Carlos I and Gabriel de Castilla Spanish Antarctic Stations, as well as to the different colleagues from UAH that helped on the instrument maintenance. ERF acknowledges fieldwork assistance by Martin Heggli. MBG acknowledges fieldwork and technical assistance by P Abadia, C Benede, P Bravo, J Gomez, M Grasa, R Jimenez, H Miranda, B Ponz, J Revilla and P Tejero and the Ordesa and Monte Perdido National Park staff. LH acknowledges field assistance by John Jacobs, Andrew Trant, Robert Way, Darroch Whitaker; we acknowledge the Inuit of Nunatsiavut, and the Co-management Board of Torngat Mountains National Park for their support of this project and acknowledge that the field research was conducted on their traditional lands. We thank our many bear guides, especially Boonie, Eli, Herman, John and Maria Merkuratsuk. AAK acknowledges field support of Akhtar Malik, Rameez Ahmad. Part of microclimatic records from Saxony was funded by the Saxon Switzerland National Park Administration. Tyson Research Center. JP acknowledges field support of Emmanuel Malet (Edytem) and Rangers of Reserves Naturelles de Haute-Savoie (ASTERS). Practical help: Roel H. Janssen, N. Huig, E. Bakker, Schools in the tepaseforsoket, Forskar fredag, Erik Herberg. The support by the Bavarian Forest National Park administration is highly appreciated. LvdB acknowledges CONAF and onsite support from the park rangers from PN Pan de Azucar, PN La Campana, PN Nahuelbuta and from communidad agricola Quebrada de Talca. JL and FS acknowledge Manuel Nicolas and all forest officers from the Office National des Forets (ONF) who are in charge of the RENECOFOR network and who provided help and local support for the installation and maintenance of temperature loggers in the field., Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 p ixels ( summarized f rom 8 519 u nique t emperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications., FWO G018919N W001919N 12P1819N, DOB Ecology, University of Helsinki, Faculty of Science (MICROCLIM) 7510145, European Research Council (ERC) FORMICA 757833, Arctic Interactions at the University of Oulu, Academy of Finland 318930 337552, Maaja vesitekniikan tuki ry., Tiina and Antti Herlin Foundation, Nordenskiold Samfundet, Societas pro Fauna et Flora Fennica, Grant Agency of the Czech Republic 20-28119S 20-05840Y GA17-19376S 21-11487S, Czech Academy of Sciences RVO 67985939, National Geographic Society 9480-14 WW-240R-17, CISSC (program ICRP) 2397, Iran National Science Foundation (INSF) 96005914, Scottish Government's Rural and Environment Science and Analytical Services Division, Qatar Petroleum QUEX-CAS-QP-RD-18/19, European Union's Horizon 2020 research and innovation program 678841, Swiss National Science Foundation (SNSF), European Commission 172198 193645 31003A_176044, Ministry of Education, Youth & Sports - Czech Republic LTAUSA19137, Ministry of Science and Higher Education of the Russian Federation FSRZ-2020-0014, Independent Research Fund Denmark 8021-00423B 7027-00133B, German Research Foundation (DFG) DFG- FZT 118 202548816 TI 338/14-1 TI 338/14-2 BA 3843/6-1, grant project VEGA of the Ministry of Education of the Slovak Republic Slovak Academy of Sciences 2/0132/18, Forestry Commission, Universidad Javeriana, Direccion General de Cambio Climatico del Gobierno de Aragon, European Union's Horizon 2020 research and innovation program under the Marie Skodowska-Curie Grant 657627 SNF 407340_172433 40FA40_154245 20FI21_148992 20FI20_173691, European Commission 17841 774124, MCTI/CNPq/FNDCT 68/2013, Project 'Como as florestas da Amazonia Central respondem as variacoes climaticas? Efeitos sobre dinamica florestal e sinergia com a fragmentacAo florestal', Spanish Government, European Commission CGL2016-78093-R, ANID-FONDECYT 1181745, National Science Foundation, Poland UMO-2017/27/B/ST10/02228, National Research Foundation - South Africa, Australian Research Council, Slovak Research and Development Agency APVV-19-0319, Instituto Antartico Chileno INACH_RT-48_16 INACH FR-0418, Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) PIA APOYO CCTE AFB170008 PIA AFB170008, UK Research & Innovation (UKRI), Natural Environment Research Council (NERC), Research Council of Norway, European Commission 230970, NERC E3 doctoral training partnership grant at the University of Edinburgh NE/L002558/1, Carnegie Trust for the Universities of Scotland, Gobern of Spain PERMAPLANET CTM2009-10165-E ANTARPERMA CTM2011-15565-E PERMASNOW CTM2014-52021-R, University of Alcala, Spanish Polar Committee, Autonomous Province of Bolzano (ITA), ScotNature, NERC National Capability LTS-S: UK-SCAPE NE/R016429/1, Ministry of Education, Youth & Sports - Czech Republic LTAUSA18007, Kempe Foundation JCK-1112 JCK-1822, Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme I (NPU I) LO1415, project for national infrastructure support CzeCOS/ICOS LM2015061 GLORIA-EU EVK2-CT2000-00056, Tiroler Wissenschaftsfonds, University of Innsbruck, Sime Darby Foundation, Jardin Botanico Atlantico SV-20-GIJON-JBA, Federal Ministry of Education & Research (BMBF) 01LL0912 01LG1201M 01LG1201N, Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) CONICYT FONDECYT 11170516 1180205, ANID PIA / BASAL FB210006, National Parks (DYNBIO) 1656/2015, Spanish Research Agency (VULBIMON) CGL2017-90040-R, Swiss National Science Foundation (SNSF) 20FI20_173691, Biotechnology and Biological Sciences Research Council (BBSRC) 206/D16053 FWO G0H1517N, EU Horizon2020 INFRAIA project eLTER-PLUS 871128, project LTER-CWN (FFG, F&E Infrastrukturforderung) 858024, Austrian Climate Research Program ACRP7 - CentForCSink - KR14AC7K11960, iDiv by the German Research Foundation DFG- FZT 118 202548816, Baden-Wurttemberg Ministry of Science, Research and Arts, Weston Foundation, ArcticNet, Natural Sciences and Engineering Research Council of Canada (NSERC) RGPIN-06691, Villum Foundation 17523, Ministry of Education, Youth & Sports - Czech Republic LM2015078 VAN2020/01 CZ.02.1.01/0.0/0.0/16_013/0001708 LTT17033 LTT20017 INTER-TRANSFER LTT19018, Bolin Centre for Climate Research, Stockholm University, Swedish Research Council Swedish Research Council Formas 2014-00530 2018-00792 2016-01187, Swedish Forest Society Foundation 2018-485-Steg 2 2017, Federal Ministry of Education & Research (BMBF) FKZ 031B0516C SUSALPS, Oberfrankenstiftung OFS FP00237, Energy Research Fund NYR-11 - 2019 NYR-18 - 2020, UK NERC Independent Research Fellowship NE/S01537X/1, National Science Centre, Poland 2016/21/B/ST10/02271, Polish National Centre for Research and Development Pol-Nor/203258/31/2013, MoEFCC, Govt of India (AICOPTAX project) 22018/12/2015/RE/Tax, Swedish Research Council Formas 2018-01781 2018-02700 2019-00836, research infrastructure ICOS-SE, National Research, Development and Innovation Fund of Hungary K128441, Programa Operativo FEDER 2018 B1-RNM-163-UGR-18, Norwegian Research Council (NORKLIMA grants) 184912 244525, CONICYT-PAI 79170119, ANID-MPG 190029, project MIUR PON Cluster OT4CLIMA, Stelvio National Park, AIAS-COFUND fellowship programme - Marie Skodowska- Curie actions under the European Union's Seventh Framework Pro-gramme for Research, Technological development and Demonstration 609033, Aarhus University Research Foundation, Denmark, EU FP6 NitroEurope 17841, EU FP7 ECLAIRE 282910, Ministry of Education and Science of Ukraine 505 550 574 602, GEF-UNEP NEC05348, ENI CBC BSB PONTOS BSB 889, Netherlands Organization for Scientific Research (NWO) 016.VICI.170.072, New Frontiers in Research Fund-Exploration NFRF-2018-02043, Natural Sciences and Engineering Research Council of Canada (NSERC), Australian Research Council DE180100570, National Science Foundation (NSF) DEB 1557094, International Center for Advanced Renewable Energy and Sustainability (I-CARES) at Washington University in St. Louis, Smithsonian Institution Smithsonian Tropical Research Institute, Tyson Research Center, UK Natural Environment Research Council through the ShrubTundra Project NE/M016323/1, Swedish Research Council Formas Swedish Research Council, Kempe Foundations - research infrastructure ICOS Kempe Foundations - research infrastructure SITES, Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET) PIP 112-201501-00609, Spanish Government PID2019-110521GB-I00, Catalan government 2017-1005, French National Research Agency (ANR) ANR-10-LABX-45, General Directorate of State Forests, Warsaw, Poland, Max Planck Society, Russian Foundation for Basic Research (RFBR), Krasnoyarsk Territory Krasnoyarsk Regional Fund of Science 20-45-242908, Estonian Research Council PRG609, Knut & Alice Wallenberg Foundation 2015.0047, Swedish Research Council, fundacion Ramon Areces grant ELEMENTAL-CLIMATE, Svalbard Environmental Protection Fund 15/128, Research Council of Norway 269957, Humboldt Fellowship for Experienced Researchers, Russian Foundation for Basic Research (RFBR) 18-05-60203-Arktika, Polish National Science Centre 2017/27/B/NZ8/00316, ODYSSEE project (PN-II-ID-JRP-RO-FR-2012) ANR-13-ISV7-0004, Australian Government, Department of Industry, Innovation and Science, Global Challenges program at the University of Wollongong, ARC the Australian Antarctic Division, INACH, project SUBANTECO IPEV 136 (French Polar Institute Paul-Emile Victor), Zone Atelier CNRS Antarctique et Terres Australes, SAD Region Bretagne (Project INFLICT), BiodivERsa 2019-2020 BioDivClim call 'ASICS' ANR-20-EBI5-0004, National Science Foundation (NSF) 1556772, EU-LEAP-Agri (RAMSES II) EU-DESIRA (CASSECS) EU-H2020 (SustainSahel), AGROPOLIS, Total SA, CGIAR, Russian Science Foundation (RSF) 18-74-10048, Swedish Research Council 2014-04270, ALTER-net multi-site grant, River LIFE project LIFE08 NAT/S/000266, Flexpeil, Ministry of Science and Higher Education, Poland N N305 304840, ETH Zurich FEVER ETH-27 19-1, NSERC Canada Graduate Scholarship (Doctoral) Program, ArcticNet-NCE, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ) 141513/2017-9, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio De Janeiro (FAPERJ) E26/200.84/2019, SRDA APVV-16-0325 APVV-20-0365, ERDF (CE LignoSilva) ITMS 313011S735, ETH Zurich, EU Horizon 2020 641918, German Terrestrial Environmental Observatories (TERENO) research program of the Helmholtz Association, Bavarian Ministry of the Environment and Public Health UGV06080204000 German Research Foundation (DFG) 192626868, Swedish National Space Board (SNSB) 95/16, CASSECS project by the European Union, Natural Environment Research Council (NERC) NE/L002558/1, MEMOIRE project PN-III-P1-1.1-PD2016-0925, Arctic Challenge for Sustainability II (ArCS II) JPMXD1420318865, Consiliul National al Cercetarii Stiintifice (CNCS), Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii (UEFISCDI) PN-III-P2-2.1-PED-2019-4924 PN2019-2022/19270201, 25N BIODIVERS 3-BIOSERV, Russian Science Foundation (RSF) 21-14-00209., Netherlands Organization for Scientific Research (NWO) 863.14.013, Australian Research Council DE140101611, Portuguese Foundation for Science and Technology CEECIND/02509/2018 CESAM UIDP/50017/2020+UIDB/50017/2020, Portuguese Foundation for Science and Technology European Commission, FEDER, within the PT2020 Partnership Agreement, Compete 2020, Spanish Government FPU17/05869, Swiss Federal Office for the Environment (FOEN), Giacomi foundation, National Natural Science Foundation of China (NSFC) 41861134039 41941015 41877458, French National Research Agency (ANR) ANR-19-CE32-0005-01 Centre National de la Recherche Scientifique (CNRS), Structure Federative de Recherche (SFR) Condorcet (FR CNRS 3417: CREUSE), EU INTERACT program, Inuit of Nunatsiavut, Co-management Board of Torngat Mountains National Park, Saxon Switzerland National Park Administration, Bavarian Forest National Park administration, BECC - Biodiversity and Ecosystem services in a Changing Climate, Research Foundation Flanders (FWO-SBO) S000619N
Published: 2021

6. Effect of climate dataset selection on simulations of terrestrial GPP: Highest uncertainty for tropical regions.

Author: Wu, Zhendong, Boke-Olén, Niklas, Fensholt, Rasmus, Ardö, Jonas, Eklundh, Lars, and Lehsten, Veiko
Subjects: BIOGEOCHEMISTRY, ECOSYSTEMS, PRIMARY productivity (Biology), CARBON cycle, SIMULATION methods & models
Abstract: Biogeochemical models use meteorological forcing data derived with different approaches (e.g. based on interpolation or reanalysis of observation data or a hybrid hereof) to simulate ecosystem processes such as gross primary productivity (GPP). This study assesses the impact of different widely used climate datasets on simulated gross primary productivity and evaluates the suitability of them for reproducing the global and regional carbon cycle as mapped from independent GPP data. We simulate GPP with the biogeochemical model LPJ-GUESS using six historical climate datasets (CRU, CRUNCEP, ECMWF, NCEP, PRINCETON, and WFDEI). The simulated GPP is evaluated using an observation-based GPP product derived from eddy covariance measurements in combination with remotely sensed data. Our results show that all datasets tested produce relatively similar GPP simulations at a global scale, corresponding fairly well to the observation-based data with a difference between simulations and observations ranging from -50 to 60 g m-2 yr-1. However, all simulations also show a strong underestimation of GPP (ranging from -533 to -870 g m-2 yr-1) and low temporal agreement (r < 0.4) with observations over tropical areas. As the shortwave radiation for tropical areas was found to have the highest uncertainty in the analyzed historical climate datasets, we test whether simulation results could be improved by a correction of the tested shortwave radiation for tropical areas using a new radiation product from the International Satellite Cloud Climatology Project (ISCCP). A large improvement (up to 48%) in simulated GPP magnitude was observed with bias corrected shortwave radiation, as well as an increase in spatio-temporal agreement between the simulated GPP and observation-based GPP. This study conducts a spatial inter-comparison and quantification of the performances of climate datasets and can thereby facilitate the selection of climate forcing data over any given study area for modelling purposes. [ABSTRACT FROM AUTHOR]
Published: 2018
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7. Estimating and Analyzing Savannah Phenology with a Lagged Time Series Model.

Author: Boke-Olén, Niklas, Lehsten, Veiko, Ardö, Jonas, Beringer, Jason, Eklundh, Lars, Holst, Thomas, Veenendaal, Elmar, and Tagesson, Torbern
Subjects: PLANT phenology, SAVANNAS, PLANT productivity, METEOROLOGICAL precipitation, CARBON cycle, CLIMATE change
Abstract: Savannah regions are predicted to undergo changes in precipitation patterns according to current climate change projections. This change will affect leaf phenology, which controls net primary productivity. It is of importance to study this since savannahs play an important role in the global carbon cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical phenological model. We show that all three variables can be used to estimate savannah phenology on a global scale. However, it was not possible to create a simplified savannah model that works equally well for all sites on the global scale without inclusion of more site specific parameters. The simplified model showed no bias towards tree cover or between continents and resulted in a cross-validated r2 of 0.6 and root mean squared error of 0.1. We therefore expect similar average results when applying the model to other savannah areas and further expect that it could be used to estimate the productivity of savannah regions. [ABSTRACT FROM AUTHOR]
Published: 2016
Full Text: View/download PDF

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7 results on '"Ardö, Jonas"'

1. Ecosystem properties of semiarid savanna grassland in West Africa and its relationship with environmental variability.

2. Global maps of soil temperature

3. SoilTemp: A global database of near‐surface temperature

4. Patterns and controls of the variability of radiation use efficiency and primary productivity across terrestrial ecosystems

5. Global maps of soil temperature

6. Effect of climate dataset selection on simulations of terrestrial GPP: Highest uncertainty for tropical regions.

7. Estimating and Analyzing Savannah Phenology with a Lagged Time Series Model.

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