Descriptor: "Snow-cover" - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"Snow-cover"' showing total 32 results

Start Over Descriptor "Snow-cover"

32 results on '"Snow-cover"'

1. Investigating The Relationship Between Geomorphological Components (Elevation, Slope and Aspect) and The Maximum Snow-Cover Duration in Talesh Mountains.

Author: Shahzeidi, Somayeh Sadat
Subjects: GEOMORPHOLOGY, SNOW cover, SNOW, DURABILITY, SOIL erosion
Abstract: The shape of the surface is important for geomorphologists because the morphology influences other environmental components. One of the important environmental variables that strongly influence is the Snow-Cover Duration on elevations. SCDura in mountain reservoirs has a direct effect on temperature, hydrological, erosion, vegetation, and biological feedbacks, and as a result of studying the interaction of the topographic surface of the earth with the durability of snow cover, it becomes necessary and important. In this research, the relationship between the geomorphological components of the elevation, slope, and aspect with the max Snow-Cover Duration was calculated and investigated based on the data of Aqua and Terra satellites in the statistical period of 2003 to 2021. The Modis daily snow products named MOD10A1 and MYD10A1 were used for this purpose. The data was downloaded from NASA's official site and was prepared in the main database. In the first step, the data was binarized based on a threshold of 50%, then, the effect of the cloudiness was reduced using a spatial and temporal filter. Then, the data from Terra and Aqua satellites were combined and, the Max Snow-Cover Duration per cell in the raster network was calculated on an annual basis. The relationship between Max Snow-Cover Duration and elevational bands was investigated. The trend of changes in the Max Snow-Cover Duration shows that lower valleys and foothills of eastern Talash have a sharper decline. This situation can be attributed to human interventions, anthropogenic activities, as well as these areas locating in the transitional zone and to be more effective from environmental changes. [ABSTRACT FROM AUTHOR]
Published: 2023
Full Text: View/download PDF

2. Spatiotemporal distribution of Arctic herbivores in spring: Potential for competition?

Author: Anna Caroline Grimsby, Åshild Ønvik Pedersen, Dorothee Ehrich, Jesper Bruun Mosbacher, Ingrid Marie Garfelt Paulsen, Frida Kristine Brockmann, and Virve Ravolainen
Subjects: Behaviour, Barnacle goose, Camera-traps, Co-occurrence, Pink-footed goose, Snow-cover, Ecology, QH540-549.5
Abstract: Biotic interactions are important to the structure and dynamics of food webs and may affect the spatial and temporal distribution of species. In the Arctic, spring snow-cover limits food availability at a critical time for herbivores, potentially leading to resource competition. This study investigates the potential for competition over forage resources during spring in a high-Arctic herbivore community comprising the resident, endemic Svalbard reindeer (Rangifer tarandus platyrhynchus) and Svalbard rock ptarmigan (Lagopus muta hyperborea), and the migratory pink-footed goose (Anser brachyrhynchus) and barnacle goose (Branta leucopsis). First, we investigated herbivore behaviour that could indicate the potential for competition by conducting a field study, and second, we quantified the effects of snow-cover extent, vegetation type and presence of potential herbivore competitors on the spatiotemporal distributions of herbivores using camera-traps in one early and one late snow melt year. Only reindeer and geese appeared with sufficient sample sizes for analysis. The field study revealed that reindeer and geese foraged in the same areas, particularly moss tundra habitats. Although geese were regularly alerted by reindeer, no direct aggressive interactions were observed. The camera-trap study showed that neither of the herbivores significantly affected the spatiotemporal distribution of its potential competitor, but reindeer and goose distribution was instead driven by snow-cover extent and vegetation type. However, the shared space use by these species may lead to different types of interactions, such as facilitation or exploitative competition, which require further assessment, including dietary overlap studies, particularly in the context of climate change-induced shifts in snow melt timing and herbivore abundances.
Published: 2023
Full Text: View/download PDF

3. Predicted scarcity of suitable habitat for alpine plant communities in northern Japan under climate change.

Author: Yukihiro Amagai, Hiroyuki Oguma, and Fumiko Ishihama
Subjects: *PLANT habitats, *CLIMATE change, *PLANT communities, *MOUNTAIN plants, *TAIGAS, *HEATHLANDS, *HABITATS, *PHYSIOLOGICAL adaptation
Abstract: Question: Alpine vegetation is sensitive to climate change, with shifts in species ranges, changes in community composition, and an upward shift in the forest limit over decades. Under climate change, habitats suitable for alpine vegetation will progressively decrease in scale, making their protection and conservation particularly important. In the Taisetsu Mountains of Japan, alpine vegetation has changed remarkably during the last decade. The aim of this study was to estimate the distribution of habitats suitable for alpine and subalpine vegetation types (snowbeds, shrubs, and alpine heathland/fellfield) and competing vegetation types (Sasa spp. and subarctic forest), while considering uncertainties in future predictions and climate scenarios. Location: Taisetsu Mountains, Daisetsuzan National Park, Hokkaido (northern Japan). Methods: We estimated the habitat area suitable for each vegetation type from current vegetation maps on the basis of the predictions by three global climate models (GCMs) under two climate change scenarios (RCP2.6 and RCP8.5) using five habitat suitability models (HSMs) in two periods (2046-2050 and 2096-2100). We also compared the performances of the HSMs. Results: Mean summer temperature and snow-cover period had significant effects on the distribution of all vegetation types. The estimated distribution area for suitable habitat did not differ markedly among GCMs and HSMs. Under the RCP2.6 scenario, habitats suitable for snowbeds and alpine heathland/fellfield drastically decreased overall but were preserved in some regions. Under the RCP8.5 scenario, however, subarctic forest almost completely replaced alpine and subalpine vegetation types over time. Conclusions: Our projections indicate that the severity of future climate change will determine whether or not habitats suitable for alpine vegetation will remain. Monitoring the dynamics of endemic and rare species for the effects of global warming should be the priority for adaptation strategies to enable timely conservation measures. [ABSTRACT FROM AUTHOR]
Published: 2022
Full Text: View/download PDF

4. Substrate influences foraging selection by Eurasian Green Woodpeckers Picus viridis in autumn and winter: observations in Hungary over a 20-year period.

Author: Gorman, Gerard and Alder, Daniel
Subjects: *WOODPECKERS, *SNOW cover, *BRICK building, *PREY availability, *WINTER, *CLIFFS, *GRASSLANDS
Abstract: The foraging behaviour and habitat use of the Eurasian Green Woodpecker Picus viridis at various sites in Hungary over a 20-year period was documented. Detailed observations were recorded on foraging behaviour at hard substrates; in quarries, cliffs and human made structures of brick and stone construction. Using Chi-square tests on the frequency of observations of birds at hard substrates foraging sites, we compared usage during periods of snow cover and those without. Birds were found to be more frequently observed at hard substrates during periods of snow cover because these remained largely free of snow. We supposed that this response was due to invertebrate prey becoming increasingly scarce generally across typical foraging sites, i.e. grasslands and meadows during harsh winter conditions. Accessibility to the alternative sites became important as a source of food because availability of prey was more reliable. Vertical surfaces of hard substrates such as those associated with quarries, cliffs and buildings may be important to sustain Eurasian Green Woodpeckers in periods of snow cover where these provide a valuable foraging resource. [ABSTRACT FROM AUTHOR]
Published: 2022
Full Text: View/download PDF

5. Variability of Northern Hemisphere Spring Snowmelt Dates Using the AVHRR Polar Pathfinder Snow Cover During 1982–2004

Author: Zhao, Hongxu, Fernandes, Richard, Chuvieco, Emilio, editor, Li, Jonathan, editor, and Yang, Xiaojun, editor
Published: 2010
Full Text: View/download PDF

6. Investigating meteorological and snowpack drivers for glide-snow avalanching

Author: Altenbach, Moritz and Altenbach, Moritz
Abstract: Gleitschneelawinen können Infrastrukturen und Wälder beschädigen und zu Todesfällen führen. Die Vorhersage von Gleitschneelawinen ist nach wie vor eine Herausforderung. Dies ist vor allem auf begrenztes Wissen über die treibenden physikalischen Prozesse zurückzuführen, da Gleitschnee-lawinen bisher nur wenig wissenschaftliche Aufmerksamkeit erhalten haben. Das Ziel dieser Arbeit ist es, mithilfe eines einzigartigen Datensatzes von Gleitschneelawinen Beziehungen zwischen meteorologischen und Schneedeckenparametern und der Gleitschneelawinenaktivität herzustellen, um letztendlich deren Vorhersage zu verbessern. Wir verwendeten das mehrschichtige Schneedeckenmodell SNOWPACK, um Daten über die Schneedeckeneigenschaften in einem Testgebiet zu erhalten, welches durch eine hohe Gleitschneelawinenaktivität gekennzeichnet ist. Mehr als 800 Gleitschneelawinen wurden zwischen 2008 und 2022 mit Zeitrafferaufnahmen dokumentiert und mit den Schneedeckensimulationen verknüpft. Die Ergebnisse von SNOWPACK stimmten gut mit den meteorologischen Bedingungen und der Schneedecke überein, welche während der Wintersaison 2021/2022 am Untersuchungsort beobachtet wurden. Anschließend haben wir die Gleitschneelawinen in zwei Gruppen unterteilt, in «warm-temperature events» und «cold-temperature events», da wir davon ausgehen, dass diese durch unterschiedliche Prozesse gekennzeichnet sind. Dazu entwickelten wir einen neuen Schwellenwert, basierend auf dem Flüssigwassergehalt in der Schneedecke, und untersuchten, ob unterschiedliche meteorologische und Schneedeckenfaktoren für jeden Ereignistyp identifiziert werden können. Vier verschiedene Vergleichsansätze zwischen «cold-temperature» Tagen, «warm-temperature» Tagen, Ereignistagen und ereignislosen Tagen ermöglichten es uns, ein besseres Verständnis der potenziellen Treiber für jeden Prozess zu gewinnen. Für jeden Ansatz bestimmten wir die zehn wichtigsten Parameter, indem wir eine univariate Merkmalsauswahl basierend auf ANOVA f-Tests durchf, Glide-snow avalanches can damage infrastructure and forests and result in fatalities. Forecasting glide-snow avalanches remains a very challenging task. This is largely due to our limited knowledge of the driving physical processes, as glide-snow avalanches have received limited scientific attention. The goal of this work is to use a unique dataset of glide-snow avalanches to establish relationships between meteorological and snowpack parameters and glide-snow avalanche activity to ultimately improve forecasting. We applied the multi-layer snow-cover model SNOWPACK to obtain data on snow properties at a field site characterized by a high frequency of glide-snow avalanches. More than 800 glide-snow avalanches were documented using time-lapse photography between 2008 and 2022 and linked to the snow cover simulations. SNOWPACK output was in good agreement with meteorological and snowpack conditions recorded at the study site during the 2021/2022 winter season. We then separated the glide-snow avalanches into two groups, warm- and cold-temperature events, because we expect these are driven by different processes. To do so, we developed a new threshold based on liquid water content in the snowpack, and investigated whether different meteorological and snowpack drivers could be identified for each type of event. Four different comparison approaches between cold-temperature days, warm-temperature days, event days, and non-event days allowed us to gain a better understanding of potential drivers for each process. For each approach, we determined the top ten most important features performing a univariate feature selection using ANOVA f-tests. For warm-temperature events, we found liquid water induced by surface melting at the base of the snowpack. A modeled ground heat flux at the snow-soil interface close to zero as well as a higher total amount of water in the snowpack were indicative for event days. Cold-temperature events were characterized by very little water in the s, Masterarbeit Universität Innsbruck 2022
Published: 2022

7. Spatiotemporal distribution and co-occurrence of Arctic herbivores in spring

Author: Grimsby, Anna Caroline, Pedersen, Åshild Ønvik, Ravolainen, Virve, Ehrich, Dorothee, and Forchhammer, Mads
Subjects: VDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480::Økologi: 488, VDP::Mathematics and natural science: 400::Zoology and botany: 480::Ecology: 488, Svalbard, camera-traps, Arctic herbivores, spatiotemporal distribution, co-occurrence, snow-cover, competition, behaviour
Abstract: Biotic interactions play an important role in the structure and dynamics of food-webs and may drive the spatial distribution of species. In the Arctic, spring snow-cover limits the availability of resources at a critical time for resident and migratory herbivores, which could lead to resource competition. This study takes a first step towards understanding the potential for competition between the major Svalbard herbivores; Svalbard reindeer (Rangifer tarandus platyrhynchus), Svalbard rock ptarmigan (Lagopus muta hyperborea), pink-footed goose (Anser brachyrhynchus) and barnacle goose (Branta leucopsis) during spring when resources are limited. The behaviour of co-occurring herbivores was observed with the aim of describing behaviours that could indicate interference competition. Further, camera-trap data was used to quantify the effects of snow-cover extent, vegetation type and presence of potential competitors on the spatiotemporal distributions of reindeer and geese. Reindeer and geese in Svalbard were found to generally forage in the same areas, especially in moss tundra. Observations suggested that reindeer was the behaviourally dominant competitor, but even though geese were regularly disturbed by close encounters with reindeer, no direct interference interactions were observed. Quantitative analyses confirmed that their spatiotemporal distributions were mainly driven by snow-cover extent and vegetation type. While it was clear that reindeer did not avoid geese, the avoidance of reindeer by geese could not be rejected. Chasing of ptarmigans was observed from both reindeer and geese, however the potential for competition between these species is not further assessed in this study due to a low number of ptarmigan observations. Extensive snow-cover seemed to slightly increase the co-occurrence of reindeer and geese, and the effect is expected to be stronger in years of late snowmelt. The shared space use by these species could potentially lead to exploitative competition, however this should be further studied by assessing dietary overlap, especially in relation to timing of snowmelt which is predicted to change with climate warming. This study adds to the current knowledge of spatial ecology of reindeer and geese in Svalbard and gives insight to the potential for competition between these Arctic herbivores during spring.
Published: 2022

8. 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, Pieter [0000-0002-8613-0943], Kemppinen, Julia [0000-0001-7521-7229], Kopecký, Martin [0000-0002-1018-9316], Luoto, Miska [0000-0001-6203-5143], Maclean, Ilya MD [0000-0001-8030-9136], Crowther, Thomas W [0000-0001-5674-8913], Bailey, Joseph J [0000-0002-9526-7095], Haesen, Stef [0000-0002-4491-4213], Klinges, David H [0000-0002-7900-9379], Niittynen, Pekka [0000-0002-7290-029X], Scheffers, Brett R [0000-0003-2423-3821], Van Meerbeek, Koenraad [0000-0002-9260-3815], Aartsma, Peter [0000-0001-5086-856X], Abdalaze, Otar [0000-0001-8140-0900], Abedi, Mehdi [0000-0002-1499-0119], Aerts, Rien [0000-0001-6694-0669], Ahmadian, Negar [0000-0002-7427-7198], Ahrends, Antje [0000-0002-5083-7760], Alatalo, Juha M [0000-0001-5084-850X], Alexander, Jake M [0000-0003-2226-7913], Allonsius, Camille Nina [0000-0003-2599-9941], Altman, Jan [0000-0003-4879-5773], Ammann, Christof [0000-0002-0783-5444], Andres, Christian [0000-0003-0576-6446], Andrews, Christopher [0000-0003-2428-272X], Ardö, Jonas [0000-0002-9318-0973], Arriga, Nicola [0000-0001-5321-3497], Arzac, Alberto [0000-0002-3361-5349], Aschero, Valeria [0000-0003-3865-4133], Assis, Rafael L [0000-0001-8468-6414], Assmann, Jakob Johann [0000-0002-3492-8419], Bader, Maaike Y [0000-0003-4300-7598], Bahalkeh, Khadijeh [0000-0003-1485-0316], Barančok, Peter [0000-0003-1171-2524], Barrio, Isabel C [0000-0002-8120-5248], Barros, Agustina [0000-0002-6810-2391], Basham, Edmund W [0000-0002-0167-7908], Bauters, Marijn [0000-0003-0978-6639], Bazzichetto, Manuele [0000-0002-9874-5064], Marchesini, Luca Belelli [0000-0001-8408-4675], Bell, Michael C [0000-0002-3401-7746], Benavides, Juan C [0000-0002-9694-2195], Benito Alonso, José Luis [0000-0003-1086-8834], Berauer, Bernd J [0000-0002-9472-1532], Bjerke, Jarle W [0000-0003-2721-1492], Björk, Robert G [0000-0001-7346-666X], Björkman, Mats P [0000-0001-5768-1976], Björnsdóttir, Katrin [0000-0001-7421-9441], Blonder, Benjamin [0000-0002-5061-2385], Boeckx, Pascal [0000-0003-3998-0010], Boike, Julia [0000-0002-5875-2112], Bokhorst, Stef [0000-0003-0184-1162], Brum, Bárbara NS [0000-0002-8421-3200], Brůna, Josef [0000-0002-4839-4593], Buchmann, Nina [0000-0003-0826-2980], Camargo, José Luís [0000-0003-0370-9878], Campoe, Otávio C [0000-0001-9810-8834], Candan, Onur [0000-0002-9254-4122], Canessa, Rafaella [0000-0002-6979-9880], Cannone, Nicoletta [0000-0002-3390-3965], Carbognani, Michele [0000-0001-7701-9859], Carnicer, Jofre [0000-0001-7454-8296], Casanova-Katny, Angélica [0000-0003-3860-1445], Cesarz, Simone [0000-0003-2334-5119], Chojnicki, Bogdan [0000-0002-9012-4060], Choler, Philippe [0000-0002-9062-2721], Chown, Steven L [0000-0001-6069-5105], Cifuentes, Edgar F [0000-0001-5918-5861], Čiliak, Marek [0000-0002-6720-9365], Contador, Tamara [0000-0002-0250-9877], Convey, Peter [0000-0001-8497-9903], Cooper, Elisabeth J [0000-0002-0634-1282], Cremonese, Edoardo [0000-0002-6708-8532], Curasi, Salvatore R [0000-0002-4534-3344], Cutini, Maurizio [0000-0002-8597-8221], Dahlberg, C Johan [0000-0003-0271-3306], Daskalova, Gergana N [0000-0002-5674-5322], de Pablo, Miguel Angel [0000-0002-4496-2741], Della Chiesa, Stefano [0000-0002-6693-2199], Dengler, Jürgen [0000-0003-3221-660X], Descombes, Patrice [0000-0002-3760-9907], Di Cecco, Valter [0000-0001-9862-1267], Di Musciano, Michele [0000-0002-3130-7270], Dick, Jan [0000-0002-4180-9338], Dolezal, Jiri [0000-0002-5829-4051], Dorrepaal, Ellen [0000-0002-0523-2471], Dušek, Jiří [0000-0001-6119-0838], Eisenhauer, Nico [0000-0002-0371-6720], Eklundh, Lars [0000-0001-7644-6517], Erickson, Todd E [0000-0003-4537-0251], Erschbamer, Brigitta [0000-0002-6792-1395], Eugster, Werner [0000-0001-6067-0741], Exton, Dan A [0000-0001-8885-5828], Fanin, Nicolas [0000-0003-4195-855X], Fazlioglu, Fatih [0000-0002-4723-3640], Feigenwinter, Iris [0000-0001-7493-6790], Fenu, Giuseppe [0000-0003-4762-5043], Ferlian, Olga [0000-0002-2536-7592], Fernández-Pascual, Eduardo [0000-0002-4743-9577], Finckh, Manfred [0000-0003-2186-0854], Higgens, Rebecca Finger [0000-0002-7645-504X], Forte, T'ai GW [0000-0002-8685-5872], Freeman, Erika C [0000-0001-7161-6038], Frei, Esther R [0000-0003-1910-7900], Fuentes-Lillo, Eduardo [0000-0001-5657-954X], García, Rafael A [0000-0002-0591-0391], García, María B [0000-0003-4231-6006], Géron, Charly [0000-0001-7912-4708], Gharun, Mana [0000-0003-0337-7367], Ghosn, Dany [0000-0003-1898-9681], Gigauri, Khatuna [0000-0002-6707-0818], Gobin, Anne [0000-0002-3742-7062], Goded, Ignacio [0000-0002-1912-325X], Goeckede, Mathias [0000-0003-2833-8401], Gottschall, Felix [0000-0002-1247-8728], Goulding, Keith [0000-0002-6465-1465], Govaert, Sanne [0000-0002-8939-1305], Graae, Bente Jessen [0000-0002-5568-4759], Greenwood, Sarah [0000-0001-9104-7936], Greiser, Caroline [0000-0003-4023-4402], Grelle, Achim [0000-0003-3468-9419], Guénard, Benoit [0000-0002-7144-1175], Guillemot, Joannès [0000-0003-4385-7656], Haase, Peter [0000-0002-9340-0438], Haider, Sylvia [0000-0002-2966-0534], Halbritter, Aud H [0000-0003-2597-6328], Hamid, Maroof [0000-0003-3406-5008], Hammerle, Albin [0000-0003-1963-5906], Hampe, Arndt [0000-0003-2551-9784], Haugum, Siri V [0000-0003-4958-7132], Hederová, Lucia [0000-0003-1283-0952], Heinesch, Bernard [0000-0001-7594-6341], Helfter, Carole [0000-0001-5773-4652], Hepenstrick, Daniel [0000-0003-1090-6888], Herberich, Maximiliane [0000-0003-0716-1520], Hermanutz, Luise [0000-0003-0706-7067], Hik, David S [0000-0002-8994-9305], Hoffrén, Raúl [0000-0002-9123-304X], Homeier, Jürgen [0000-0001-5676-3267], Hörtnagl, Lukas [0000-0002-5569-0761], Høye, Toke T [0000-0001-5387-3284], Hrbacek, Filip [0000-0001-5032-9216], Hylander, Kristoffer [0000-0002-1215-2648], Iwata, Hiroki [0000-0002-8962-8982], Jackowicz-Korczynski, Marcin Antoni [0000-0002-6574-5703], Jactel, Hervé [0000-0002-8106-5310], Järveoja, Järvi [0000-0001-6317-660X], Jastrzębowski, Szymon [0000-0003-1239-4847], Jentsch, Anke [0000-0002-2345-8300], Jiménez, Juan J [0000-0003-2398-0796], Jónsdóttir, Ingibjörg S [0000-0003-3804-7077], Jucker, Tommaso [0000-0002-0751-6312], Jump, Alistair S [0000-0002-2167-6451], Juszczak, Radoslaw [0000-0002-5212-7383], Kanka, Róbert [0000-0002-7071-7280], Kašpar, Vít [0000-0002-0879-0137], Kelly, Julia [0000-0002-7370-1401], Khuroo, Anzar A [0000-0002-0251-2793], Klemedtsson, Leif [0000-0002-1122-0717], Klisz, Marcin [0000-0001-9486-6988], Kljun, Natascha [0000-0001-9650-2184], Knohl, Alexander [0000-0002-7615-8870], Kobler, Johannes [0000-0003-0052-4245], Kollár, Jozef [0000-0002-0069-4220], Kotowska, Martyna M [0000-0002-2283-5979], Kovács, Bence [0000-0002-8045-8489], Kreyling, Juergen [0000-0001-8489-7289], Lamprecht, Andrea [0000-0002-8719-026X], Lang, Simone I [0000-0002-6812-2528], Larson, Christian [0000-0002-7567-4953], Larson, Keith [0000-0001-7089-524X], Laska, Kamil [0000-0002-5199-9737], le Maire, Guerric [0000-0002-5227-958X], Leihy, Rachel I [0000-0001-9672-625X], Lens, Luc [0000-0002-0241-2215], Liljebladh, Bengt [0000-0002-2998-5865], Lohila, Annalea [0000-0003-3541-672X], Lorite, Juan [0000-0003-4617-8069], Loubet, Benjamin [0000-0001-8825-8775], Lynn, Joshua [0000-0002-7190-7991], Macek, Martin [0000-0002-5609-5921], Mackenzie, Roy [0000-0001-6620-1532], Magliulo, Enzo [0000-0001-5505-6552], Maier, Regine [0000-0003-3158-4136], Malfasi, Francesco [0000-0002-2660-8327], Máliš, František [0000-0003-2760-6988], Man, Matěj [0000-0002-4557-8768], Manca, Giovanni [0000-0002-9376-0310], Manco, Antonio [0000-0002-3677-4134], Manolaki, Paraskevi [0000-0003-3958-0199], Matula, Radim [0000-0002-7460-0100], Medinets, Sergiy [0000-0001-5980-1054], Medinets, Volodymyr [0000-0001-7543-7504], Meeussen, Camille [0000-0002-5869-4936], Merinero, Sonia [0000-0002-1405-6254], Mesquita, Rita de Cássia Guimarães [0000-0003-1746-3215], Meusburger, Katrin [0000-0003-4623-6249], Meysman, Filip JR [0000-0001-5334-7655], Michaletz, Sean T [0000-0003-2158-6525], Milbau, Ann [0000-0003-3555-8883], Moiseev, Pavel [0000-0003-4808-295X], Mondoni, Andrea [0000-0002-4605-6304], Montagnani, Leonardo [0000-0003-2957-9071], Moriana-Armendariz, Mikel [0000-0001-8251-1338], Morra di Cella, Umberto [0000-0003-4250-9705], Mörsdorf, Martin [0000-0002-3903-2021], Mosedale, Jonathan R [0000-0001-9008-5439], Muffler, Lena [0000-0001-8227-7297], Muñoz-Rojas, Miriam [0000-0002-9746-5191], Myers, Jonathan A [0000-0002-2058-8468], Myers-Smith, Isla H [0000-0002-8417-6112], Nardino, Marianna [0000-0001-9466-8340], Naujokaitis-Lewis, Ilona [0000-0001-9504-4484], Nicklas, Lena [0000-0002-9337-4153], Niedrist, Georg [0000-0002-7511-6273], Nilsson, Mats B [0000-0003-3765-6399], Normand, Signe [0000-0002-8782-4154], Nosetto, Marcelo D [0000-0002-9428-490X], Nouvellon, Yann [0000-0003-1920-3847], Nuñez, Martin A [0000-0003-0324-5479], Ogaya, Romà [0000-0003-4927-8479], Ogée, Jérôme [0000-0002-3365-8584], Okello, Joseph [0000-0003-4462-3923], Olejnik, Janusz [0000-0001-5305-1045], Olesen, Jørgen Eivind [0000-0002-6639-1273], Opedal, Øystein H [0000-0002-7841-6933], Orsenigo, Simone [0000-0003-0348-9115], Palaj, Andrej [0000-0001-7054-4183], Pampuch, Timo [0000-0002-6290-9661], Pärtel, Meelis [0000-0002-5874-0138], Pastor, Ada [0000-0002-7114-770X], Pauchard, Aníbal [0000-0003-1284-3163], Pauli, Harald [0000-0002-9842-9934], Pavelka, Marian [0000-0002-7339-3410], Pearse, William D [0000-0002-6241-3164], Peichl, Matthias [0000-0002-9940-5846], Penczykowski, Rachel M [0000-0003-4559-0609], Penuelas, Josep [0000-0002-7215-0150], Petit Bon, Matteo [0000-0001-9829-8324], Petraglia, Alessandro [0000-0003-4632-2251], Phartyal, Shyam S [0000-0003-3266-6619], Phoenix, Gareth K [0000-0002-0911-8107], Pio, Casimiro [0000-0002-3531-8620], Pitacco, Andrea [0000-0002-7260-6242], Pitteloud, Camille [0000-0002-4731-0079], Plichta, Roman [0000-0003-2442-8522], Porro, Francesco [0000-0001-9855-2468], Portillo-Estrada, Miguel [0000-0002-0348-7446], Poulenard, Jérôme [0000-0003-0810-0308], Poyatos, Rafael [0000-0003-0521-2523], Prokushkin, Anatoly S [0000-0001-8721-2142], Puchalka, Radoslaw [0000-0002-4764-0705], Pușcaș, Mihai [0000-0002-2632-640X], Radujković, Dajana [0000-0003-4981-5879], Randall, Krystal [0000-0003-2507-1000], Ratier Backes, Amanda [0000-0002-7229-578X], Renault, David [0000-0003-3644-1759], Risch, Anita C [0000-0003-0531-8336], Rixen, Christian [0000-0002-2486-9988], Robinson, Sharon A [0000-0002-7130-9617], Robroek, Bjorn JM [0000-0002-6714-0652], Rocha, Adrian V [0000-0002-4618-2407], Rossi, Graziano [0000-0002-5102-5019], Roupsard, Olivier [0000-0002-1319-142X], Rubtsov, Alexey V [0000-0002-9663-4344], Saccone, Patrick [0000-0001-8820-593X], Sallo Bravo, Jhonatan [0000-0001-9007-4959], Santos, Cinthya C [0000-0001-7042-5993], Sarneel, Judith M [0000-0001-6187-499X], Scharnweber, Tobias [0000-0002-4933-5296], Schmidt, Marius [0000-0001-5292-7092], Scholten, Thomas [0000-0002-4875-2602], Schuchardt, Max [0000-0003-3103-8063], Scott, Tony [0000-0002-6631-0672], Seeber, Julia [0000-0003-0189-7377], Seipel, Tim [0000-0001-6472-2975], Semenchuk, Philipp [0000-0002-1949-6427], Senior, Rebecca A [0000-0002-8208-736X], Serra-Diaz, Josep M [0000-0003-1988-1154], Sewerniak, Piotr [0000-0002-3071-3963], Shekhar, Ankit [0000-0003-0802-2821], Siegwart Collier, Laura [0000-0003-0985-9615], Simpson, Elizabeth [0000-0002-6107-0286], Siqueira, David P [0000-0002-0756-0153], Sitková, Zuzana [0000-0001-6354-6105], Six, Johan [0000-0001-9336-4185], Smiljanic, Marko [0000-0002-2324-0723], Smith, Stuart W [0000-0001-9396-6610], Somers, Ben [0000-0002-7875-107X], Souza, José João LL [0000-0003-4670-6626], Souza, Bartolomeu Israel [0000-0003-2173-8314], Souza Dias, Arildo [0000-0002-5495-3435], Spasojevic, Marko J [0000-0003-1808-0048], Speed, James DM [0000-0002-0633-5595], Spicher, Fabien [0000-0002-9999-955X], Stanisci, Angela [0000-0002-5302-0932], Steinbauer, Klaus [0000-0002-3730-9920], Steinbrecher, Rainer [0000-0002-5931-4210], Steinwandter, Michael [0000-0001-8545-6047], Stemkovski, Michael [0000-0002-9854-887X], Stephan, Jörg G [0000-0001-6195-7867], Stiegler, Christian [0000-0002-0130-2401], Stoll, Stefan [0000-0002-3656-417X], Svátek, Martin [0000-0003-2328-4627], Svoboda, Miroslav [0000-0003-4050-3422], Tagesson, Torbern [0000-0003-3011-1775], Tanentzap, Andrew J [0000-0002-2883-1901], Tanneberger, Franziska [0000-0002-4184-9671], Theurillat, Jean-Paul [0000-0002-1843-5809], Thomas, Haydn JD [0000-0001-9099-6304], Thomas, Andrew D [0000-0002-1360-1687], Tomaselli, Marcello [0000-0003-4208-3433], Treier, Urs Albert [0000-0003-4027-739X], Trouillier, Mario [0000-0001-9151-7686], Turtureanu, Pavel Dan [0000-0002-7422-3106], Tyystjärvi, Vilna A [0000-0002-1175-5463], Ueyama, Masahito [0000-0002-4000-4888], Ujházy, Karol [0000-0002-0228-1737], Ujházyová, Mariana [0000-0002-5546-1547], Uogintas, Domas [0000-0002-3937-1218], Urban, Josef [0000-0003-1730-947X], Urbaniak, Marek [0000-0002-1225-9170], Ursu, Tudor-Mihai [0000-0002-4898-6345], Vaccari, Francesco Primo [0000-0002-5253-2135], Van de Vondel, Stijn [0000-0002-0223-7330], van den Brink, Liesbeth [0000-0003-0313-8147], Van Geel, Maarten [0000-0001-8688-6225], Vandvik, Vigdis [0000-0003-4651-4798], Vangansbeke, Pieter [0000-0002-6356-2858], Varlagin, Andrej [0000-0002-2549-5236], Veen, GF [0000-0001-7736-9998], Veenendaal, Elmar [0000-0001-8230-2501], Venn, Susanna E [0000-0002-7433-0120], Verbeeck, Hans [0000-0003-1490-0168], Verbrugggen, Erik [0000-0001-7015-1515], Verheijen, Frank GA [0000-0001-6741-4249], Vitale, Luca [0000-0002-7637-264X], Vittoz, Pascal [0000-0003-4218-4517], Vives-Ingla, Maria [0000-0003-4887-8392], von Oppen, Jonathan [0000-0001-6346-2964], Walz, Josefine [0000-0002-0715-8738], Wang, Runxi [0000-0003-4902-169X], Wang, Yifeng [0000-0003-2660-7874], Way, Robert G [0000-0003-4763-7685], Wedegärtner, Ronja EM [0000-0003-4633-755X], Weigel, Robert [0000-0001-9685-6783], Wild, Jan [0000-0003-3007-4070], Wilkinson, Matthew [0000-0002-3858-553X], Wilmking, Martin [0000-0003-4964-2402], Wingate, Lisa [0000-0003-1921-1556], Winkler, Manuela [0000-0002-8655-9555], Wipf, Sonja [0000-0002-3492-1399], Wohlfahrt, Georg [0000-0003-3080-6702], Xenakis, Georgios [0000-0002-2950-4101], Yang, Yan [0000-0003-0858-7603], Yu, Zicheng [0000-0003-2358-2712], Yu, Kailiang [0000-0003-4223-5169], Zellweger, Florian [0000-0003-1265-9147], Zhang, Jian [0000-0003-0589-6267], Zhao, Peng [0000-0003-3289-5067], Ziemblińska, Klaudia [0000-0003-4070-6553], Zimmermann, Reiner [0000-0002-8724-941X], Zong, Shengwei [0000-0002-3583-6110], Zyryanov, Viacheslav I [0000-0002-1748-4801], Nijs, Ivan [0000-0003-3111-680X], Lenoir, Jonathan [0000-0003-0638-9582], Apollo - University of Cambridge Repository, Department of Biology (University of Antwerp), and University of Antwerp (UA)
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
Full Text: View/download PDF

9. The influence of snow cover on ground freeze-thaw frequency, intensity, and duration: An experimental study conducted in coastal northern Sweden.

Author: Sarady, Maria and Sahlin, Eva A.U.
Subjects: *SNOW cover, *SOIL temperature measurement, *SNOW, *ATMOSPHERIC temperature measurements, *SNOW accumulation, *THERMAL properties
Abstract: The impact of snow cover on seasonal ground frost and freeze-thaw processes is not yet fully understood. The authors therefore examined how snow cover affects seasonal ground frost in a coastal setting in northern Sweden. Air and soil temperatures were recorded in a paired-plot experiment, both with and without snow cover, during the frost season 2012–2013. The frequency, duration, and intensity of the freeze-thaw cycles during the frost season were calculated. The results showed that the freeze-thaw frequency was 57% higher at the soil surface and the intensity 10 °C colder in the spring of 2013, when the ground lacked snow cover. Furthermore, the duration of the seasonal freeze-thaw cycle was 30 days longer on average in cases where there was natural snow accumulation. The correlation between air and ground surface temperatures weakened with increased snow-cover depth. The authors conclude that continued increases in air temperature and decreases in snow in coastal northern Sweden might alter freeze-thaw cycles and thus affect natural and human systems such as geomorphology, ecology, spatial planning, transport, and forestry. [ABSTRACT FROM AUTHOR]
Published: 2016
Full Text: View/download PDF

10. Winter climates and coldhardiness in terrestrial insects

Author: William J. TURNOCK and Paul G. FIELDS
Subjects: winter climates, snow-cover, overwintering, terrestrial insects, winter climatic zones, freeze-tolerance, freeze-susceptibility, non-freezing mortality, supercooling point, coldhardiness, Zoology, QL1-991
Abstract: Overwintering insects must avoid injury and death from the freezing of tissues and from metabolic disruptions associated with exposure to low, non-freezing temperatures. The winter climates of the world are classified in relation to insect overwintering on the basis of their minimum temperatures and the duration of the winter (when temperatures are below the thermal range for activity and development). Outside the Tropical Wet zone, the severity of exposure to cold (temperature, snowfall, duration of exposure, predictability, variability) can vary from a few days at 0°C to months below -20°C with extremes as low as -60°C. The severity of the temperature exposure may be ameliorated by the selection by insects of overwintering sites (exposed, partly-exposed, protected). The relationships among overwintering habitats, the minimum winter temperature in climatic zones, and the supercooling points (SCP) of over 350 terrestrial insects from published reports were examined. Variability in the SCP among insects within each climatic zone and habitat was wide. Among the freeze-susceptible species that overwintered in exposed or partly-protected habitats the SCP and the cold severity of climate were correlated. This was not the case for insects that overwintered in protected habitats. The SCP's of freeze-tolerant insects were generally higher than the freeze-susceptible insects, and the SCP's were not tightly linked with the cold severity of climatic zone. Insects, both freeze-susceptible and freeze-tolerant, overwintering in exposed habitats had lower SCP's than insects from habitats that offered some protection from ambient temperatures. Thirty-eight species had reports of SCP's for different geographical locations. Although there were occasionally differences in the SCP's, there was no consistent pattern of insects having lower SCP's when overwintering in colder habitats. The incidence of freeze-tolerance was higher in boreal and polar climatic zones than in climatic zones with warmer winters. Holometabola insects had a higher incidence of freeze-tolerance than hemimetabola insects. Suggestions for future research directions are outlined.
Published: 2005
Full Text: View/download PDF

11. Global maps of soil temperature

Author: Lembrechts, JJ, van den Hoogen, J, Aalto, J, Ashcroft, MB, De Frenne, P, Kemppinen, J, Kopecký, M, Luoto, M, Maclean, IMD, Crowther, TW, Bailey, JJ, Haesen, S, Klinges, DH, Niittynen, P, Scheffers, BR, Van Meerbeek, K, Aartsma, P, Abdalaze, O, Abedi, M, Aerts, R, Ahmadian, N, Ahrends, A, Alatalo, JM, Alexander, JM, Nina Allonsius, C, Altman, J, Ammann, C, Andres, C, Andrews, C, Ardö, J, Arriga, N, Arzac, A, Aschero, V, Assis, RL, Johann Assmann, J, Bader, MY, Bahalkeh, K, Barančok, P, Barrio, IC, Barros, A, Barthel, M, Basham, EW, Bauters, M, Bazzichetto, M, Belelli Marchesini, L, Bell, MC, Benavides, JC, Luis Benito Alonso, J, Berauer, BJ, Bjerke, JW, Björk, RG, Björkman, MP, Björnsdóttir, K, Blonder, B, Boeckx, P, Boike, J, Bokhorst, S, Brum, BNS, Brůna, J, Buchmann, N, Buysse, P, Luís Camargo, J, Campoe, OC, Candan, O, Canessa, R, Cannone, N, Carbognani, M, Carnicer, J, Casanova‐Katny, A, Cesarz, S, Chojnicki, B, Choler, P, Chown, SL, Cifuentes, EF, Čiliak, M, Contador, T, Convey, P, Cooper, EJ, Cremonese, E, Curasi, SR, Curtis, R, Cutini, M, Johan Dahlberg, C, Daskalova, GN, Angel de Pablo, M, Della Chiesa, S, Dengler, J, Deronde, B, Descombes, P, Di Cecco, V, Di Musciano, M, Dick, J, Dimarco, RD, Dolezal, J, Dorrepaal, E, Dušek, J, Eisenhauer, N, Eklundh, L, Erickson, TE, Erschbamer, B, Eugster, W, Ewers, RM, Exton, DA, Fanin, N, Fazlioglu, F, Feigenwinter, I, Fenu, G, Ferlian, O, Rosa Fernández Calzado, M, Fernández‐Pascual, E, Finckh, M, Finger Higgens, R, Forte, TGW, Freeman, EC, Frei, ER, Fuentes‐Lillo, E, García, RA, García, MB, Géron, C, Gharun, M, Ghosn, D, Gigauri, K, Gobin, A, Goded, I, Goeckede, M, Gottschall, F, Goulding, K, Govaert, S, Jessen Graae, B, Greenwood, S, Greiser, C, Grelle, A, Guénard, B, Guglielmin, M, Guillemot, J, Haase, P, Haider, S, Halbritter, AH, Hamid, M, Hammerle, A, Hampe, A, Haugum, SV, Hederová, L, Heinesch, B, Helfter, C, Hepenstrick, D, Herberich, M, Herbst, M, Hermanutz, L, Hik, DS, Hoffrén, R, Homeier, J, Hörtnagl, L, Høye, TT, Hrbacek, F, Hylander, K, Iwata, H, Antoni Jackowicz‐Korczynski, M, Jactel, H, Järveoja, J, Jastrzębowski, S, Jentsch, A, Jiménez, JJ, Jónsdóttir, IS, Jucker, T, Jump, AS, Juszczak, R, Kanka, R, Kašpar, V, Kazakis, G, Kelly, J, Khuroo, AA, Klemedtsson, L, Klisz, M, Kljun, N, Knohl, A, Kobler, J, Kollár, J, Kotowska, MM, Kovács, B, Kreyling, J, Lamprecht, A, Lang, SI, Larson, C, Larson, K, Laska, K, le Maire, G, Leihy, RI, Lens, L, Liljebladh, B, Lohila, A, Lorite, J, Loubet, B, Lynn, J, Macek, M, Mackenzie, R, Magliulo, E, Maier, R, Malfasi, F, Máliš, F, Man, M, Manca, G, Manco, A, Manise, T, Manolaki, P, Marciniak, F, Matula, R, Clara Mazzolari, A, Medinets, S, Medinets, V, Meeussen, C, Merinero, S, de Cássia Guimarães Mesquita, R, Meusburger, K, Meysman, FJR, Michaletz, ST, Milbau, A, Moiseev, D, Moiseev, P, Mondoni, A, Monfries, R, Montagnani, L, Moriana‐Armendariz, M, Morra di Cella, U, Mörsdorf, M, Mosedale, JR, Muffler, L, Muñoz‐Rojas, M, Myers, JA, Myers‐Smith, IH, Nagy, L, Nardino, M, Naujokaitis‐Lewis, I, Newling, Emily, Nicklas, L, Niedrist, G, Niessner, A, Nilsson, MB, Normand, S, Nosetto, MD, Nouvellon, Y, Nuñez, MA, Ogaya, R, Ogée, J, Okello, J, Olejnik, J, Eivind Olesen, J, Opedal, Ø, Orsenigo, S, Palaj, A, Pampuch, T, Panov, AV, Pärtel, M, Pastor, A, Pauchard, A, Pauli, H, Pavelka, M, Pearse, WD, Peichl, M, Pellissier, L, Penczykowski, RM, Penuelas, J, Petit Bon, M, Petraglia, A, Phartyal, SS, Phoenix, GK, Pio, C, Pitacco, A, Pitteloud, C, Plichta, R, Porro, F, Portillo‐Estrada, M, Poulenard, J, Poyatos, R, Prokushkin, AS, Puchalka, R, Pușcaș, M, Radujković, D, Randall, K, Ratier Backes, A, Remmele, S, Remmers, W, Renault, D, Risch, AC, Rixen, C, Robinson, SA, Robroek, BJM, Rocha, AV, Rossi, C, Rossi, G, Roupsard, O, Rubtsov, AV, Saccone, P, Sagot, C, Sallo Bravo, J, Santos, CC, Sarneel, JM, Scharnweber, T, Schmeddes, J, Schmidt, M, Scholten, T, Schuchardt, M, Schwartz, N, Scott, T, Seeber, J, Cristina Segalin de Andrade, A, Seipel, T, Semenchuk, P, Senior, RA, Serra‐Diaz, JM, Sewerniak, P, Shekhar, A, Sidenko, NV, Siebicke, L, Siegwart Collier, L, Simpson, E, Siqueira, DP, Sitková, Z, Six, J, Smiljanic, M, Smith, SW, Smith‐Tripp, S, Somers, B, Vedel Sørensen, M, João L. L. Souza, J, Israel Souza, B, Souza Dias, A, Spasojevic, MJ, Speed, JDM, Spicher, F, Stanisci, A, Steinbauer, K, Steinbrecher, R, Steinwandter, M, Stemkovski, M, Stephan, JG, Stiegler, C, Stoll, S, Svátek, M, Svoboda, M, Tagesson, T, Tanentzap, AJ, Tanneberger, F, Theurillat, J, Thomas, HJD, Thomas, AD, Tielbörger, K, Tomaselli, M, Albert Treier, U, Trouillier, M, Dan Turtureanu, P, Tutton, R, Tyystjärvi, VA, Ueyama, M, Ujházy, K, Ujházyová, M, Uogintas, D, Urban, AV, Urban, J, Urbaniak, M, Ursu, T, Primo Vaccari, F, Van de Vondel, S, van den Brink, L, Van Geel, M, Vandvik, V, Vangansbeke, P, Varlagin, A, Veen, GF, Veenendaal, E, Venn, Susanna, Verbeeck, H, Verbrugggen, E, Verheijen, FGA, Villar, L, Vitale, L, Vittoz, P, Vives‐Ingla, M, von Oppen, J, Walz, J, Wang, R, Wang, Y, Way, RG, Wedegärtner, REM, Weigel, R, Wild, J, Wilkinson, M, Wilmking, M, Wingate, L, Winkler, M, Wipf, S, Wohlfahrt, G, Xenakis, G, Yang, Y, Yu, Z, Yu, K, Zellweger, F, Zhang, J, Zhang, Z, Zhao, P, Ziemblińska, K, Zimmermann, R, Zong, S, Zyryanov, VI, Nijs, I, Lenoir, J, Lembrechts, JJ, van den Hoogen, J, Aalto, J, Ashcroft, MB, De Frenne, P, Kemppinen, J, Kopecký, M, Luoto, M, Maclean, IMD, Crowther, TW, Bailey, JJ, Haesen, S, Klinges, DH, Niittynen, P, Scheffers, BR, Van Meerbeek, K, Aartsma, P, Abdalaze, O, Abedi, M, Aerts, R, Ahmadian, N, Ahrends, A, Alatalo, JM, Alexander, JM, Nina Allonsius, C, Altman, J, Ammann, C, Andres, C, Andrews, C, Ardö, J, Arriga, N, Arzac, A, Aschero, V, Assis, RL, Johann Assmann, J, Bader, MY, Bahalkeh, K, Barančok, P, Barrio, IC, Barros, A, Barthel, M, Basham, EW, Bauters, M, Bazzichetto, M, Belelli Marchesini, L, Bell, MC, Benavides, JC, Luis Benito Alonso, J, Berauer, BJ, Bjerke, JW, Björk, RG, Björkman, MP, Björnsdóttir, K, Blonder, B, Boeckx, P, Boike, J, Bokhorst, S, Brum, BNS, Brůna, J, Buchmann, N, Buysse, P, Luís Camargo, J, Campoe, OC, Candan, O, Canessa, R, Cannone, N, Carbognani, M, Carnicer, J, Casanova‐Katny, A, Cesarz, S, Chojnicki, B, Choler, P, Chown, SL, Cifuentes, EF, Čiliak, M, Contador, T, Convey, P, Cooper, EJ, Cremonese, E, Curasi, SR, Curtis, R, Cutini, M, Johan Dahlberg, C, Daskalova, GN, Angel de Pablo, M, Della Chiesa, S, Dengler, J, Deronde, B, Descombes, P, Di Cecco, V, Di Musciano, M, Dick, J, Dimarco, RD, Dolezal, J, Dorrepaal, E, Dušek, J, Eisenhauer, N, Eklundh, L, Erickson, TE, Erschbamer, B, Eugster, W, Ewers, RM, Exton, DA, Fanin, N, Fazlioglu, F, Feigenwinter, I, Fenu, G, Ferlian, O, Rosa Fernández Calzado, M, Fernández‐Pascual, E, Finckh, M, Finger Higgens, R, Forte, TGW, Freeman, EC, Frei, ER, Fuentes‐Lillo, E, García, RA, García, MB, Géron, C, Gharun, M, Ghosn, D, Gigauri, K, Gobin, A, Goded, I, Goeckede, M, Gottschall, F, Goulding, K, Govaert, S, Jessen Graae, B, Greenwood, S, Greiser, C, Grelle, A, Guénard, B, Guglielmin, M, Guillemot, J, Haase, P, Haider, S, Halbritter, AH, Hamid, M, Hammerle, A, Hampe, A, Haugum, SV, Hederová, L, Heinesch, B, Helfter, C, Hepenstrick, D, Herberich, M, Herbst, M, Hermanutz, L, Hik, DS, Hoffrén, R, Homeier, J, Hörtnagl, L, Høye, TT, Hrbacek, F, Hylander, K, Iwata, H, Antoni Jackowicz‐Korczynski, M, Jactel, H, Järveoja, J, Jastrzębowski, S, Jentsch, A, Jiménez, JJ, Jónsdóttir, IS, Jucker, T, Jump, AS, Juszczak, R, Kanka, R, Kašpar, V, Kazakis, G, Kelly, J, Khuroo, AA, Klemedtsson, L, Klisz, M, Kljun, N, Knohl, A, Kobler, J, Kollár, J, Kotowska, MM, Kovács, B, Kreyling, J, Lamprecht, A, Lang, SI, Larson, C, Larson, K, Laska, K, le Maire, G, Leihy, RI, Lens, L, Liljebladh, B, Lohila, A, Lorite, J, Loubet, B, Lynn, J, Macek, M, Mackenzie, R, Magliulo, E, Maier, R, Malfasi, F, Máliš, F, Man, M, Manca, G, Manco, A, Manise, T, Manolaki, P, Marciniak, F, Matula, R, Clara Mazzolari, A, Medinets, S, Medinets, V, Meeussen, C, Merinero, S, de Cássia Guimarães Mesquita, R, Meusburger, K, Meysman, FJR, Michaletz, ST, Milbau, A, Moiseev, D, Moiseev, P, Mondoni, A, Monfries, R, Montagnani, L, Moriana‐Armendariz, M, Morra di Cella, U, Mörsdorf, M, Mosedale, JR, Muffler, L, Muñoz‐Rojas, M, Myers, JA, Myers‐Smith, IH, Nagy, L, Nardino, M, Naujokaitis‐Lewis, I, Newling, Emily, Nicklas, L, Niedrist, G, Niessner, A, Nilsson, MB, Normand, S, Nosetto, MD, Nouvellon, Y, Nuñez, MA, Ogaya, R, Ogée, J, Okello, J, Olejnik, J, Eivind Olesen, J, Opedal, Ø, Orsenigo, S, Palaj, A, Pampuch, T, Panov, AV, Pärtel, M, Pastor, A, Pauchard, A, Pauli, H, Pavelka, M, Pearse, WD, Peichl, M, Pellissier, L, Penczykowski, RM, Penuelas, J, Petit Bon, M, Petraglia, A, Phartyal, SS, Phoenix, GK, Pio, C, Pitacco, A, Pitteloud, C, Plichta, R, Porro, F, Portillo‐Estrada, M, Poulenard, J, Poyatos, R, Prokushkin, AS, Puchalka, R, Pușcaș, M, Radujković, D, Randall, K, Ratier Backes, A, Remmele, S, Remmers, W, Renault, D, Risch, AC, Rixen, C, Robinson, SA, Robroek, BJM, Rocha, AV, Rossi, C, Rossi, G, Roupsard, O, Rubtsov, AV, Saccone, P, Sagot, C, Sallo Bravo, J, Santos, CC, Sarneel, JM, Scharnweber, T, Schmeddes, J, Schmidt, M, Scholten, T, Schuchardt, M, Schwartz, N, Scott, T, Seeber, J, Cristina Segalin de Andrade, A, Seipel, T, Semenchuk, P, Senior, RA, Serra‐Diaz, JM, Sewerniak, P, Shekhar, A, Sidenko, NV, Siebicke, L, Siegwart Collier, L, Simpson, E, Siqueira, DP, Sitková, Z, Six, J, Smiljanic, M, Smith, SW, Smith‐Tripp, S, Somers, B, Vedel Sørensen, M, João L. L. Souza, J, Israel Souza, B, Souza Dias, A, Spasojevic, MJ, Speed, JDM, Spicher, F, Stanisci, A, Steinbauer, K, Steinbrecher, R, Steinwandter, M, Stemkovski, M, Stephan, JG, Stiegler, C, Stoll, S, Svátek, M, Svoboda, M, Tagesson, T, Tanentzap, AJ, Tanneberger, F, Theurillat, J, Thomas, HJD, Thomas, AD, Tielbörger, K, Tomaselli, M, Albert Treier, U, Trouillier, M, Dan Turtureanu, P, Tutton, R, Tyystjärvi, VA, Ueyama, M, Ujházy, K, Ujházyová, M, Uogintas, D, Urban, AV, Urban, J, Urbaniak, M, Ursu, T, Primo Vaccari, F, Van de Vondel, S, van den Brink, L, Van Geel, M, Vandvik, V, Vangansbeke, P, Varlagin, A, Veen, GF, Veenendaal, E, Venn, Susanna, Verbeeck, H, Verbrugggen, E, Verheijen, FGA, Villar, L, Vitale, L, Vittoz, P, Vives‐Ingla, M, von Oppen, J, Walz, J, Wang, R, Wang, Y, Way, RG, Wedegärtner, REM, Weigel, R, Wild, J, Wilkinson, M, Wilmking, M, Wingate, L, Winkler, M, Wipf, S, Wohlfahrt, G, Xenakis, G, Yang, Y, Yu, Z, Yu, K, Zellweger, F, Zhang, J, Zhang, Z, Zhao, P, Ziemblińska, K, Zimmermann, R, Zong, S, Zyryanov, VI, Nijs, I, and Lenoir, J
Published: 2021

12. Roles of surface wind, NDVI and snow cover in the recent changes in Asian dust storm occurrence frequency

Author: Lee, Jong-Jae and Kim, Cheol-Hee
Subjects: *WIND speed, *NORMALIZED difference vegetation index, *SNOW cover, *DUST storms, *DUST & the environment, *SPATIOTEMPORAL processes, *SCIENTIFIC observation
Abstract: Abstract: This paper describes the recent variations in dust outbreak during the period from 1996 to 2007 over the Asian dust source regions. The Asian dust source regions were divided into four sub-regions; S1, Taklamakan; S2, Gobi; S3, Inner Mongolia-Manchuria; and S4, Loess, and the WMO SYNOP observation and satellite data were employed to analyze the features of recently changed dust outbreak frequencies (DOFs). There was no particular variation in region S1, but the recent spatiotemporal variations in DOFs over S2–S4 were well characterized by a severe and widespread increase in 2001–2002, and significant decreasing in 2003–2004 over the most source regions, with a steadily increasing trend again during 2005–2007. Seasonal features showed that the highest DOFs occurred in March–April before 2002, but was delayed by a month toward April–May during the next five years because of the shift in the month of highest strong wind-speed frequencies (SWFs). A secondary peak of DOF was also found, occurring in October–November since the year 2000. Over all the source regions, the primary controlling factor for explaining the spatiotemporal DOF patterns was the SWF, with a pattern correlation coefficient (PCC) of 0.66–0.76. Other secondary controlling factors varied from region to region. For example, the DOFs observed in region S2–S3 showed relatively greater sensitivity to the snow-cover fraction, and region S4 showed a better correlation with the normalized difference vegetation index (NDVI) than the other regions. Other recent significant changes in DOFs over the Asian dust source regions and their causes are also discussed in this study. [Copyright &y& Elsevier]
Published: 2012
Full Text: View/download PDF

13. Monitoring recent changes in snow cover in Central Asia using improved MODIS snow-cover products

Author: Liu, Jinping, Zhang, Wanchang, and Liu, Tie
Published: 2017
Full Text: View/download PDF

14. Extending the Utility of Modis Daily Snow-Cover Products through Snow-Cover Prediction of Cloud-Obscured Areas in Idaho's Big Lost River Basin (USA).

Author: Hruska, RyanC. and Lee, Randy
Subjects: *WATER supply, *STREAMFLOW, *HYDROLOGY, *ENVIRONMENTAL mapping, *MODIS (Spectroradiometer), *INFORMATION resources, *ENVIRONMENTALISM
Abstract: Increasing demand for water resources in the Western United States has given rise to many conflicts and has increased the need for more accurate and timely water management decisions. Snow-Covered Area (SCA) is an important hydrologic variable for both volumetric and daily stream flow forecasting. Satellite data provide the ideal way to map snow cover in mountain regions; however, the utility of these datasets have been limited due to the large number of scenes that are contaminated with cloud cover. To improve the utility of these datasets for the snowmelt season, in particular the Moderate Resolution Imaging Spectroradiometer (MODIS) Daily Snow-Cover Product dataset, a new procedure was developed to predict snow-cover in cloud-obscured areas using a snow-occurrence map technique. Results show that this method effectively increases the usefulness of the MODIS Snow-Cover product in mapping the daily evolution of snow cover extent in the Big Lost River Basin located in southeastern Idaho. [ABSTRACT FROM AUTHOR]
Published: 2008
Full Text: View/download PDF

15. Sowing date influence on winter oilseed rape overwintering in Estonia.

Author: Lääniste, Peeter, Jõudu, Juhan, Eremeev, viacheslav, and mäeorg, Erkki
Subjects: *OILSEEDS, *RAPESEED, *RAPE (Plant), *WINTER, *AUTUMN
Abstract: In 2001-2005 an overwintering investigation of winter oilseed rape (Brassica napus L.) was carried out at the Institute of Agricultural and Environmental Sciences of the Estonian University of Life Sciences. In our trial we used two winter oilseed rape varieties: 'Wotan' and 'Express'. The sowing was performed at four different times, with weekly intervals: 8, 15, 22 and 29 August. The soil type was Stagnic Luvisol by WRB classification; the texture was sandy loam with a humus layer of 20-30 cm. Our research indicated that successful wintering of winter oilseed rape depends directly on sowing date. From the data obtained it may be seen that differences between sowing dates and overwintering were statistically significant. Overwintering depends on numbers of growing-degree-days (GDD) in the autumn vegetative period. Three years' data showed that in the autumn period plants need 416 GDD for developing a strong root system and to prepare for wintering. [ABSTRACT FROM AUTHOR]
Published: 2007
Full Text: View/download PDF

16. Topography and climate in the upper Indus Basin: Mapping elevation-snow cover relationships.

Author: Smith, T., Rheinwalt, A., and Bookhagen, B.
Published: 2021
Full Text: View/download PDF

17. Observed climatic trends in the Pyrenees (1950-2015)

Author: Serrano-Notivoli, Roberto, Brustenga, Alba Llabrés, Prohom, Marc, Cuadrat, José M., Cunillera, Jordi, L. Trapero, Pons, Marc, Tejedor, Ernesto, Saz, Miguel Ángel, López-Moreno, Juan Ignacio, Llorens, Ramon Copons, S. Gascoin, M. Y. Luna, Rodriguez-Camino, Ernesto, Ramos-Calzado, Petra, Amblar-Francés, Pilar, and Jean-Michel Soubeyroux
Subjects: Climatic trends, Database, Temperature, Precipitation, Snow-cover
Abstract: Póster presentado en: EGU General Assembly 2019 celebrada del 7 al 12 de abril en Viena, Austria.
Published: 2019

18. Limitations and Challenges of MODIS-Derived Phenological Metrics Across Different Landscapes in Pan-Arctic Regions

Author: Xiao Cheng, Ivan Mammarella, Siyu Wang, Xinchen Lu, Xianglan Li, Matthias Peichl, INAR Physics, Micrometeorology and biogeochemical cycles, and Institute for Atmospheric and Earth System Research (INAR)
Subjects: 0106 biological sciences, DECIDUOUS BROADLEAF FOREST, 010504 meteorology & atmospheric sciences, Science, Eddy covariance, Climate change, Context (language use), Land cover, SPRING PHENOLOGY, 010603 evolutionary biology, 01 natural sciences, Normalized Difference Vegetation Index, remote sensing, CANOPY PHOTOSYNTHESIS, land surface phenology, pan-Arctic, vegetation index, solar-induced fluorescence, 1172 Environmental sciences, 0105 earth and related environmental sciences, LAND-SURFACE PHENOLOGY, Phenology, SUN-INDUCED FLUORESCENCE, SNOW-COVER, Vegetation, Enhanced vegetation index, 15. Life on land, 13. Climate action, Climatology, GROWING-SEASON, INDUCED CHLOROPHYLL FLUORESCENCE, General Earth and Planetary Sciences, Environmental science, NDVI TIME-SERIES
Abstract: Recent efforts have been made to monitor the seasonal metrics of plant canopy variations globally from space, using optical remote sensing. However, phenological estimations based on vegetation indices (VIs) in high-latitude regions such as the pan-Arctic remain challenging and are rarely validated. Nevertheless, pan-Arctic ecosystems are vulnerable and also crucial in the context of climate change. We reported the limitations and challenges of using MODerate-resolution Imaging Spectroradiometer (MODIS) measurements, a widely exploited set of satellite measurements, to estimate phenological transition dates in pan-Arctic regions. Four indices including normalized vegetation difference index (NDVI), enhanced vegetation index (EVI), phenology index (PI), plant phenological index (PPI) and a MODIS Land Cover Dynamics Product MCD12Q2, were evaluated and compared against eddy covariance (EC) estimates at 11 flux sites of 102 site-years during the period from 2000 to 2014. All the indices were influenced by snow cover and soil moisture during the transition dates. While relationships existed between VI-based and EC-estimated phenological transition dates, the R2 values were generally low (0.01–0.68). Among the VIs, PPI-estimated metrics showed an inter-annual pattern that was mostly closely related to the EC-based estimations. Thus, further studies are needed to develop region-specific indices to provide more reliable estimates of phenological transition dates.
Published: 2018
Full Text: View/download PDF

19. Effects of food abundance and early clutch predation on reproductive timing in a high Arctic shorebird exposed to advancements in arthropod abundance

Author: Jérôme Moreau, Jannik Hansen, Theunis Piersma, Lars H. Hansen, Olivier Gilg, Niels Martin Schmidt, Jeroen Reneerkens, Conservation Ecology Group, University of Groningen [Groningen]-Groningen Institute for Evolutionary Life Sciences, Department of Bioscience, Aarhus University [Aarhus]-Arctic Research Centre, Biogéosciences [Dijon] ( BGS ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Royal Netherlands Institute for Sea Research ( NIOZ ), Worksupported by an International Polar Year grant from the Netherlands Organisation for Scientific research (NWO), by the Metawad project awarded by Waddenfonds (WF209925, www.metawad.nl), by two INTERACT grants for Transnational Access from the European Community’s Seventh Framework Programme under grant agreement No262693 and a grant from World Wildlife Fund Netherlands, by the French Polar Institute (IPEV, 'Interactions' program 1036) and the Groupe de Recherche en Ecologie Arctique (GREA)., Biogéosciences [UMR 6282] [Dijon] (BGS), Centre National de la Recherche Scientifique (CNRS)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Royal Netherlands Institute for Sea Research (NIOZ), and Piersma group
Subjects: 0106 biological sciences, food.ingredient, Bird migration, chick growth, POPULATION-SIZE, NEST PREDATION, BREEDING PHENOLOGY, Biology, 010603 evolutionary biology, 01 natural sciences, phenology, 010605 ornithology, Predation, [ SDV.EE ] Life Sciences [q-bio]/Ecology, environment, nest survival, food, Calidris alba (Pallas, trophic mismatch, Abundance (ecology), INTERANNUAL VARIATION, CHANGING CLIMATE, timing, NORTHEAST GREENLAND, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation, Trophic level, Original Research, Calidris alba, trophic interactions, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Calidris alba (Pallas, 1764) [sanderling], [ SDE.BE ] Environmental Sciences/Biodiversity and Ecology, CLIMATE-CHANGE, Ecology, Phenology, Hatching, SNOW-COVER, 1764) [sanderling], PHENOLOGICAL MISMATCHES, Calidris, climate change, MIGRATORY BIRDS, Calidris alba [sanderling], [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Arctic ecology
Abstract: 12 pages; International audience; Climate change may influence the phenology of organisms unequally across trophic levels and thus lead to phenological mismatches between predators and prey. In cases where prey availability peaks before reproducing predators reach maximal prey demand, any negative fitness consequences would selectively favor resynchronization by earlier starts of the reproductive activities of the predators. At a study site in northeast Greenland, over a period of 17 years, the median emergence of the invertebrate prey of Sanderling Calidris alba advanced with 1.27 days per year. Yet, over the same period Sanderling did not advance hatching date. Thus, Sanderlings increasingly hatched after their prey was maximally abundant. Surprisingly, the phenological mismatches did not affect chick growth, but the interaction of the annual width and height of the peak in food abundance did. Chicks grew especially better in years when the food peak was broad. Sanderling clutches were most likely to be depredated early in the season, which should delay reproduction. We propose that high early clutch predation may favor a later reproductive timing. Additionally, our data suggest that in most years food was still abundant after the median date of emergence, which may explain why Sanderlings did not advance breeding along with the advances in arthropod phenology.
Published: 2016
Full Text: View/download PDF

20. A STUDY CHANGE OF DYNAMICS OF DESCRIPTIONS OF SNOW-COVER IN DISTRICT OF CHERNOGIRSKY MOUNTAIN-RANGE OF CARPATHIANS, AS FACTOR WHICH PROVIDES LEVEL DRINKABLE WATER IN THE R. PRUT

Author: Negadaylov, A. A.; Чернівецький факультет Національного технічного університету «ХПІ», Masikevich, Yu. G.; Чернівецький факультет Національного технічного університету «ХПІ», Myslytsky, V. F.; Вищий державний навчальний заклад України «Буковинський державний медичний університет», Чернівці, Burdenyuk, I. P.; Вищий державний навчальний заклад України «Буковинський державний медичний університет», Чернівці, Knistchuk, T. I.; Сніголавинна станція « Пожежевська», Negadaylov, A. A.; Чернівецький факультет Національного технічного університету «ХПІ», Masikevich, Yu. G.; Чернівецький факультет Національного технічного університету «ХПІ», Myslytsky, V. F.; Вищий державний навчальний заклад України «Буковинський державний медичний університет», Чернівці, Burdenyuk, I. P.; Вищий державний навчальний заклад України «Буковинський державний медичний університет», Чернівці, and Knistchuk, T. I.; Сніголавинна станція « Пожежевська»
Abstract: A snow-cover influences on forming of spring supplies of moisture in soil, and also thermal mode of soil and ground layer of air.Headwaters of the r.Prut which are the source of drinking-water of city Chernivci, are on carpatians Chernogirsky mountain-range. On Chernogirsky mountain-range snow lies from October for May, that is why a water level in the river substantially depends on the height of snow-cover. It in same queue influences on the water-supply of city Chernivci and health of habitants of city.Basic|main| descriptions of snow-cover is|appear| his|its| height|heigt| and closeness, stocked|reserve| water in snow and degree of covering by snow of circumferential localities|local|.The purpose of work was a study of dynamics of change of height of snow on the Pozhizhevskiy mountain valley.A task was put to expect the average annual and average monthly values of height of snow.There used the tables|table| of measurement of snow on a ground before the snowavalanche| station on the mountain|mining| valley|strath| of Pozhezhevskiy in the period of october-| may duering 2003-2015 calendar years.Researches|work-up| were conducted the method of the statistical|collation| processing of experimental|brassboard| data|information|. The average annual and average monthly heights|heigt| of snow settled accounts. Also the maxheights of snow of average| settled accounts for to the months|moon| and years.The got|receive| results show that the height|heigt| of snow is changeable on years, but on the average remains stable|high-stability|. The maxheight of snow at the snowavalanche| | station of “Pozhezhevskiy” was observed|exist| in 2006 year – 121 sm|q.v.|.A stable|high-stability| snow-cover on the mountain|mining|valley|strath| ofPozhezhevskiyis set|establish| in the middle|mean| of October snow mounts|ascend| in May months|moon|.The average monthly maxheights of snow-cover for probed|explore| period were observed|exist| in March – approximately 67 sm|q.v.|.Researches, Изложены результаты исследования динамики изменения снежного покрова в районе Черногорского хребта Карпат где находятся истоки реки Прут, который обеспечивает питьевой водой город Черновцы и другие города Запада Украины. Проводился забор проб воды с целью определения коли-индекса и коли-титра., У роботі розглянуто дослідження динаміки зміни снігового покриву в районі Чорногірського хребта Карпат, де знаходяться витоки річки Прут, що забезпечує питною водою місто Чернівці та інші міста України. У забраних пробах води визначали колі-індекс і колі-титр. Використовувалися дані спостережень сніголавинної станції «Пожежевська» на протязі 2003-2015 років. За результатами досліджень зроблені висновки про стан снігового живлення р. Прут та якість води в верхів’ях р. Прут.
Published: 2017

21. Possible processes of N2O production and emission on seasonally frozen soil

Author: Yanai, Yosuke, Nemoto, Manabu, Iwata, Yukiyoshi, and Hirota, Tomoyoshi
Subjects: 融雪, 積雪, 野外観測, 亜酸化窒素（一酸化二窒素, N2O）, nitrous oxide, snowmelt, Soil freezing, snow-cover, field observation, 土壌凍結
Abstract: 季節凍土では融雪期に短期集中的な亜酸化窒素（N2O）の排出が見られる. 著者らはその現象を積雪操作実験で再現することに成功した. 本稿では2008年11月から2010年10月にわたる野外観測の結果に基づいて, 積雪深・土壌凍結深とN2Oの土壌中での蓄積・土壌から大気へのN2Oの排出の関係を考察するとともに, 未解決の課題を提示する., Seasonally frozen soil has substantially high N2O emission under thawing conditions. We succeeded in insitu observation of the N2O emissions in a snow-cover manipulation experiment. Here, we discuss relationships among snow-cover height, soil frost depth, N2O concentration in soil and process of N2O release from soil to the atmosphere. In addition, unsolved issues are presented.
Published: 2012

22. Has prey availability for Arctic birds advanced with climate change? Hindcasting the abundance of tundra Arthropods using weather and seasonal variation

Subjects: alaska, migratory birds, growth, sandpiper calidris alpina, snow-cover, Wageningen Marine Research, Centrum Ecosystemen, Centre for Ecosystem Studies, avian reproduction, long-distance migrant, Wageningen Environmental Research, insects, arrival, life-cycles
Abstract: Of all climatic zones on earth, Arctic areas have experienced the greatest climate change in recent decades. Predicted changes, including a continuing rise in temperature and precipitation and a reduction in snow cover, are expected to have a large impact on Arctic life. Large numbers of birds breed on the Arctic tundra, and many of these, such as shorebirds and passerines, feed on arthropods. Their chicks depend on a short insect population outburst characteristic of Arctic areas. To predict the consequences of climate change for reproduction in these birds, insight into arthropod phenology is essential. We investigated weather-related and seasonal patterns in abundance of surface-active arthropods during four years in the tundra of NW Taimyr, Siberia. The resulting statistical models were used to hindcast arthropod abundance on the basis of a 33-year weather dataset collected in the same area. Daily insect abundance was correlated closely with date, temperature, and, in some years, with wind and precipitation. An additional correlation with the number of degree-days accumulated after 1 June suggests that the pool of potential arthropod recruits is depleted in the course of the summer. The amplitude of short-term, weather-induced variation was as large as that of the seasonal variation. The hindcasted dates of peak arthropod abundance advanced during the study period, occurring seven days earlier in 2003 than in 1973. The timing of the period during which birds have a reasonable probability of finding enough food to grow has changed as well, with the highest probabilities now occurring at earlier dates. At the same time, the overall length of the period with probabilities of finding enough food has remained unchanged. The result is an advancement of the optimal breeding date for breeding birds. To take advantage of the new optimal breeding time, Arctic shorebirds and passerines must advance the start of breeding, and this change could affect the entire migratory schedule. Because our analyses are based on a single site, we cannot conclude that this is a general pattern for the entire Arctic. To investigate the generality of this pattern, our approach should be applied at other sites too.
Published: 2008

23. Winter climates and coldhardiness in terrestrial insects

Author: Paul G. Fields and W. J. Turnock
Subjects: non-freezing mortality, Range (biology), media_common.quotation_subject, supercooling point, coldhardiness, Insect, snow-cover, freeze-tolerance, Overwintering, media_common, biology, Ecology, Insect winter ecology, fungi, biology.organism_classification, overwintering, terrestrial insects, freeze-susceptibility, winter climatic zones, Habitat, Boreal, QL1-991, Insect Science, Tern, Zoology, Holometabola, winter climates
Abstract: Overwintering insects must avoid injury and death from the freezing of tissues and from metabolic disruptions associated with exposure to low, non-freezing temperatures. The winter climates of the world are classified in relation to insect overwintering on the basis of their minimum temperatures and the duration of the winter (when temperatures are below the thermal range for activity and development). Outside the Tropical Wet zone, the severity of exposure to cold (temperature, snowfall, duration of expo- sure, predictability, variability) can vary from a few days at 0°C to months below -20°C with extremes as low as -60°C. The severity of the temperature exposure may be ameliorated by the selection by insects of overwintering sites (exposed, partly-exposed, protected). The relationships among overwintering habitats, the minimum winter temperature in climatic zones, and the supercooling points (SCP) of over 350 terrestrial insects from published reports were examined. Variability in the SCP among insects within each climatic zone and habitat was wide. Among the freeze-susceptible species that overwintered in exposed or partly-protected habitats the SCP and the cold severity of climate were correlated. This was not the case for insects that overwintered in protected habitats. The SCP's of freeze-tolerant insects were generally higher than the freeze-susceptible insects, and the SCP's were not tightly linked with the cold severity of climatic zone. Insects, both freeze-susceptible and freeze-tolerant, overwintering in exposed habitats had lower SCP's than insects from habitats that offered some protection from ambient temperatures. Thirty-eight species had reports of SCP's for different geographical locations. Although there were occasionally differences in the SCP's, there was no consistent pat- tern of insects having lower SCP's when overwintering in colder habitats. The incidence of freeze-tolerance was higher in boreal and polar climatic zones than in climatic zones with warmer winters. Holometabola insects had a higher incidence of freeze-tolerance than hemimetabola insects. Suggestions for future research directions are outlined.
Published: 2005

24. Spatial heterogeneity of albedo over a snow-covered agricultural landscape

Author: Mark J. Belding, Steven E. Hollinger, Kenneth E. Kunkel, Byron E. Gleason, and Scott A. Isard
Subjects: Albedo, measurement, Water Res Management, Atmospheric Science, albedo, woodlands, Woodland, Forests, snow-cover, Oceanography, Atmospheric sciences, Descriptors Snow Cover, grasslands, Agricultural land, Land Use, Earth and Planetary Sciences (miscellaneous), Meltwater, prairies, tillage, Water Science and Technology, Ecology, Forestry, Spatial heterogeneity, Geophysics, Deciduous, Soil Science, forests, Aquatic Science, reflectance, Geochemistry and Petrology, land-use, Forest Sciences, Cultivated Lands, Earth-Surface Processes, Hydrology, analysis, meteorological-factors, deciduous-forests, Paleontology, Snow, Water Resources Management, meltwater, melting, Space and Planetary Science, Snowmelt, Environmental science, agricultural-land, Snow Cover, Heterogeneity, Snow-Water Equivalent
Abstract: Measurements of albedo were obtained along a 100 km transect in east central Illinois using a combination of airborne and ground-based radiometers. Analysis of the measurements focused on three different land use categories: agricultural cropland, prairie grass, and woodland. The value of albedo over the woodland after a fresh snowfall was 0.30, which is somewhat higher than what has been measured in a previous experiment over an aspen forest but similar to previous measurements over a deciduous forest in the eastern United States. The albedo values over the grassland were similar to past experiments and similar to the values over cropland. The drifting that accompanied one of the snow events caused large differences in albedo during snowmelt compared to another event with minimal drifting but similar average snow depth. The albedo was lower over the melting wind-blown snow cover than for a snow cover of similar average depth that fell under light wind conditions. These large differences suggest that inclusion of meteorological conditions during snowfall in snow parameterizations may appreciably increase their accuracy. Different tillage practices used in the agricultural fields also caused measurable differences in albedo during the snowmelt phase.
Published: 1999
Full Text: View/download PDF

25. A remote sensing exploration of land surface phenology in the Australian Alps

Author: Thompson, Jeffery
Subjects: remote sensing, MODIS, snow-cover, phenology
Abstract: Seasonal snow-cover is a significant environmental factor influencing the vegetative phenology of alpine areas. As such, climate induced changes in snow country and trends towards fewer days with persistent snow-cover are likely to significantly alter alpine landscapes both globally and in Australia. In comparison with other mountainous environments, Australia’s alpine bioregion is somewhat diminutive in area and elevation range. Because of this constraint, there is little room for highland vegetation to expand as the climate warms. As a consequence, it has been predicted that Australia’s alpine bioregion will be significantly impacted by climatic change. In recent years, a number of studies have begun using remotely sensed time-series imagery to examine the land surface phenology of alpine areas. Early studies tended to employ time-series derived from AVHRR data, but increasing studies of alpine land surface phenology have utilized MODIS derived time-series. Broadly, most of the studies of alpine land surface phenology have noted the influence of elevation gradients, whereby higher elevations tend to have later starts to the growing period and have earlier ends to the growing period. Aspect has been noted as having a minor, but detectable influence on the phenology of alpine land surfaces. In terms of temporal considerations, there is little agreement within the literature on the direction of trends between regions, and virtually none of the studies have examined the influence of landscape disturbances on phenological changes. To date, there have been no studies that have explored the links between snow-cover and land surface phenology in Australia. In order to help fill the gap, this study used remotely sensed time-series imagery to explore links between changes in snow seasonality and the phenological responses of the land surface. This was accomplished using a number of 12-year time-series images (2000 – 2012) generated using the MODIS Daily Surface Reflectance Product (MOD09). The generation of seasonality descriptor time-series required the development of an improved cloud-mask as well as new methods for deriving descriptors of snow seasonality and vegetative phenology. The improved cloud-mask built upon previous methods and utilizing the existing MODIS cloud-mask results in conjunction with new thresholds to improved the discrimination of snow-cover from clouds. The cloud-masking algorithm and the new methods for deriving descriptors of snow seasonality and vegetative phenology represent important methodological contributions of this thesis. From the remotely sensed observations, three descriptor time-series of snow seasonality were generated and analyzed. These descriptors corresponded with the start, end and duration of the snow-covered period. Over the course of the time-series a slight trend towards a later start of the snow-covered period and a stronger trend towards an earlier end to the snow-covered period was detected across the alpine bioregion. Overall, there was a downward trend in the duration of the snow-covered period for the study area. For all three snow-seasonality descriptors, there was substantial spatial variability in these trends. Patterns from the remotely sensed image time-series for the start, end and duration of the vegetative growing period were also derived. A trend towards an earlier start of the growing period was observed across the alpine bioregion. This was more pronounced at lower elevations. A slight trend in the end of the growing period indicated that it was ending later over the course of the time-series. Corresponding with the changes in both the start and end of the growing period, a trend towards a longer growing period was detected in the time-series. Significant spatial variability was observed in the trends for the phenological descriptors. The relationships between the descriptors of snow seasonality and the land surface phenological descriptors were analyzed. To date, there have been no studies reported in the literature that have explicitly examined the relationships between snow seasonality and alpine land surface phenology using remotely sensed image time-series. Whist it was found that the end of the snow-covered period was often a reasonable predictor for the start of the growing period for some areas, it was not observed in all parts of the study area across the time-series. In contrast, the links between the start of the persistent snow-covered period and the end of the growing period were (almost) universally poor across the time-series for most of the study area. It is thought that these results are entirely new. Regarding disturbance, the 2003 alpine fires had a significant impact on the vegetation within the bioregion. An analysis of the fire severity in the northern section of the bioregion was undertaken. The analysis indicated that there were greater proportions of fire-affected pixels with negative trends in the duration of the snow-covered period. This suggests that some of the negative trends in the snow-covered period and associated trends in the vegetative growing period may be associated with the impacts of the alpine fires. This thesis makes several contributions that are both methodological and empirical in nature. Methodologically, an improved liberal cloud-masking algorithm was developed, which allowed for the enhanced detection of snow-cover in an alpine environment. The method for deriving seasonally persistent snow-cover descriptors is another methodological contribution of the work. Similarly, the development of a new phenology algorithm that was relatively free of the influence of snowmelt is another contribution. These new methods are not region specific, and can thus be readily applied to other snow-covered environments. Empirically, this thesis also demonstrates the utility of remotely sensed time-series imagery for detecting patterns in Australia’s alpine bioregion. It suggests that MODIS time-series imagery can be used to monitor this region, as well as others, for climate related impacts. The research also highlighted a link between observed trends in snow-cover duration and fire disturbance, which does not appear to have been discussed previously. This link has potential implications for alpine regions in a changing climate.
Published: 2013
Full Text: View/download PDF

26. Temporal trends in avalanche activity in the French Alps and subregions: from occurrences and runout altitudes to unsteady return periods

Author: Hélène Castebrunet, Mohamed Naaim, Nicolas Eckert, Christopher J. Keylock, Aurore Lavigne, Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Mathématiques et Informatique Appliquées (MIA-Paris), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Eros Torrentielle Neige & Avalanches, Department of Civil and Structural Engineering [Sheffield], University of Sheffield [Sheffield], French National Research Agency [ANR-09-RISK-007-01], French Ministry of the Environment (Risk Division (DGPR), British Council, French Ministere des Affaires Etrangeres et Europeennes, The British Council in India, ANR-09-RISK-0007,MOPERA,MOdélisation Probabiliste pour l'Evaluation du Risque Avalanche(2009), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), and Institut National de la Recherche Agronomique (INRA)-AgroParisTech
Subjects: Return period, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, 010506 paleontology, 010504 meteorology & atmospheric sciences, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, 01 natural sciences, Altitude, CHANGE-POINT ANALYSIS, SWISS ALPS, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Earth-Surface Processes, CLIMATE-CHANGE, LAST 50 YEARS, SNOW-COVER, FLUCTUATIONS, Snow, MODEL, VARIABILITY, 13. Climate action, HYDROMETEOROLOGICAL TIME-SERIES, Climatology, DEPTH, Period (geology), [STAT.ME]Statistics [stat]/Methodology [stat.ME], Geology
Abstract: We present an analysis of temporal trends in ∼55 000 avalanches recorded between 1946 and 2010 in the French Alps and two north/south subregions. First, Bayesian hierarchical modelling is used to isolate low-, intermediate- and high-frequency trends in the mean avalanche occurrence and runout altitude per year/winter. Variables are then combined to investigate their correlation and the recent evolution of large avalanches. Comparisons are also made to climatic and flow regime covariates. The results are important for risk assessment, and the development of new high-altitude climate proxies. At the entire French Alps scale, a major change-point exists in ∼1978 at the heart of a 10 year period of high occurrences and low runout altitudes corresponding to colder and snowier winters. The differences between this change-point and the beginning/end of the study period are 0.1 avalanche occurrences per winter and per path and 55 m in runout altitude. Trends before/after are well correlated, leading to enhanced minimal altitudes for large avalanches at this time. A marked upslope retreat (80 m for the 10 year return period runout altitude) accompanied by a 12% decrease in the proportion of powder snow avalanches has occurred since then, interrupted from about 2000. The snow-depth and temperature control on these patterns seems significant (R = 0.4–0.6), but is stronger at high frequencies for occurrences, and at lower frequencies for runout altitudes. Occurrences between the northern and southern French Alps are partially coupled (R∼0.4, higher at low frequencies). In the north, the main change-point was an earlier shift in ∼1977, and winter snow depth seems to be the main control parameter. In the south, the main change-point occurred later, ∼1979–84, was more gradual, and trends are more strongly correlated with winter temperature.
Published: 2013
Full Text: View/download PDF

27. Relationships between plant communities and late snow melting on Mount Prado (Northern Apennines, Italy)

Author: Ferrari, C. and Rossi, G.
Published: 1995
Full Text: View/download PDF

28. A remote sensing exploration of land surface phenology in the Australian Alps

Author: Paull, David, Physical, Environmental & Mathematical Sciences, UNSW Canberra, UNSW, Lees, Brian, Physical, Environmental & Mathematical Sciences, UNSW Canberra, UNSW, Thompson, Jeffery, Physical, Environmental & Mathematical Sciences, UNSW Canberra, UNSW, Paull, David, Physical, Environmental & Mathematical Sciences, UNSW Canberra, UNSW, Lees, Brian, Physical, Environmental & Mathematical Sciences, UNSW Canberra, UNSW, and Thompson, Jeffery, Physical, Environmental & Mathematical Sciences, UNSW Canberra, UNSW
Abstract: Seasonal snow-cover is a significant environmental factor influencing the vegetative phenology of alpine areas. As such, climate induced changes in snow country and trends towards fewer days with persistent snow-cover are likely to significantly alter alpine landscapes both globally and in Australia. In comparison with other mountainous environments, Australia’s alpine bioregion is somewhat diminutive in area and elevation range. Because of this constraint, there is little room for highland vegetation to expand as the climate warms. As a consequence, it has been predicted that Australia’s alpine bioregion will be significantly impacted by climatic change. In recent years, a number of studies have begun using remotely sensed time-series imagery to examine the land surface phenology of alpine areas. Early studies tended to employ time-series derived from AVHRR data, but increasing studies of alpine land surface phenology have utilized MODIS derived time-series. Broadly, most of the studies of alpine land surface phenology have noted the influence of elevation gradients, whereby higher elevations tend to have later starts to the growing period and have earlier ends to the growing period. Aspect has been noted as having a minor, but detectable influence on the phenology of alpine land surfaces. In terms of temporal considerations, there is little agreement within the literature on the direction of trends between regions, and virtually none of the studies have examined the influence of landscape disturbances on phenological changes. To date, there have been no studies that have explored the links between snow-cover and land surface phenology in Australia.In order to help fill the gap, this study used remotely sensed time-series imagery to explore links between changes in snow seasonality and the phenological responses of the land surface. This was accomplished using a number of 12-year time-series images (2000 – 2012) generated using the MODIS Daily Surface Reflectance P
Published: 2013

29. Has prey availability for Arctic birds advanced with climate change? Hindcasting the abundance of tundra arthropods using weather and seasonal variations

Author: Ingrid Tulp, Hans Schekkerman, and Dutch Centre for Avian Migration & Demography
Subjects: alaska, migratory birds, growth, Population, Climate change, Biology, snow-cover, long-distance migrant, Abundance (ecology), medicine, Hindcast, Wageningen Environmental Research, insects, education, Ecology, Evolution, Behavior and Systematics, arrival, education.field_of_study, Ecology, Phenology, sandpiper calidris alpina, Seasonality, medicine.disease, Tundra, Wageningen Marine Research, Centrum Ecosystemen, Centre for Ecosystem Studies, avian reproduction, Arctic, life-cycles
Abstract: Of all climatic zones on earth, Arctic areas have experienced the greatest climate change in recent decades. Predicted changes, including a continuing rise in temperature and precipitation and a reduction in snow cover, are expected to have a large impact on Arctic life. Large numbers of birds breed on the Arctic tundra, and many of these, such as shorebirds and passerines, feed on arthropods. Their chicks depend on a short insect population outburst characteristic of Arctic areas. To predict the consequences of climate change for reproduction in these birds, insight into arthropod phenology is essential. We investigated weather-related and seasonal patterns in abundance of surface-active arthropods during four years in the tundra of NW Taimyr, Siberia. The resulting statistical models were used to hindcast arthropod abundance on the basis of a 33-year weather dataset collected in the same area. Daily insect abundance was correlated closely with date, temperature, and, in some years, with wind and precipitation. An additional correlation with the number of degree-days accumulated after 1 June suggests that the pool of potential arthropod recruits is depleted in the course of the summer. The amplitude of short-term, weather-induced variation was as large as that of the seasonal variation. The hindcasted dates of peak arthropod abundance advanced during the study period, occurring seven days earlier in 2003 than in 1973. The timing of the period during which birds have a reasonable probability of finding enough food to grow has changed as well, with the highest probabilities now occurring at earlier dates. At the same time, the overall length of the period with probabilities of finding enough food has remained unchanged. The result is an advancement of the optimal breeding date for breeding birds. To take advantage of the new optimal breeding time, Arctic shorebirds and passerines must advance the start of breeding, and this change could affect the entire migratory schedule. Because our analyses are based on a single site, we cannot conclude that this is a general pattern for the entire Arctic. To investigate the generality of this pattern, our approach should be applied at other sites too.
Published: 2008

30. Has prey availability for Arctic birds advanced with climate change? Hindcasting the abundance of tundra Arthropods using weather and seasonal variation

Author: Tulp, I., Schekkerman, H., Tulp, I., and Schekkerman, H.
Abstract: Of all climatic zones on earth, Arctic areas have experienced the greatest climate change in recent decades. Predicted changes, including a continuing rise in temperature and precipitation and a reduction in snow cover, are expected to have a large impact on Arctic life. Large numbers of birds breed on the Arctic tundra, and many of these, such as shorebirds and passerines, feed on arthropods. Their chicks depend on a short insect population outburst characteristic of Arctic areas. To predict the consequences of climate change for reproduction in these birds, insight into arthropod phenology is essential. We investigated weather-related and seasonal patterns in abundance of surface-active arthropods during four years in the tundra of NW Taimyr, Siberia. The resulting statistical models were used to hindcast arthropod abundance on the basis of a 33-year weather dataset collected in the same area. Daily insect abundance was correlated closely with date, temperature, and, in some years, with wind and precipitation. An additional correlation with the number of degree-days accumulated after 1 June suggests that the pool of potential arthropod recruits is depleted in the course of the summer. The amplitude of short-term, weather-induced variation was as large as that of the seasonal variation. The hindcasted dates of peak arthropod abundance advanced during the study period, occurring seven days earlier in 2003 than in 1973. The timing of the period during which birds have a reasonable probability of finding enough food to grow has changed as well, with the highest probabilities now occurring at earlier dates. At the same time, the overall length of the period with probabilities of finding enough food has remained unchanged. The result is an advancement of the optimal breeding date for breeding birds. To take advantage of the new optimal breeding time, Arctic shorebirds and passerines must advance the start of breeding, and this change could affect the entire migratory sc
Published: 2008

31. Snow and snow-cover in central northeast Greenland

Author: Meltofte, Hans, Christensen, Torben R., Elberling, Bo, Forchhammer, Mads C., Rasch, Morten, Hinkler, Jørgen, Hansen, Birger, Tamstorf, Mikkel Peter, Sigsgaard, Charlotte, Petersen, Dorthe, Meltofte, Hans, Christensen, Torben R., Elberling, Bo, Forchhammer, Mads C., Rasch, Morten, Hinkler, Jørgen, Hansen, Birger, Tamstorf, Mikkel Peter, Sigsgaard, Charlotte, and Petersen, Dorthe
Published: 2008

32. Energy balance above a boreal coniferous forest: a difference in turbulent fluxes between snow-covered and snow-free canopies

Author: Kitamura, K., Sakamoto, T., Nakai, Y., Shirai, T., and Terajima, T.
Subjects: CLIMATOLOGY, EDDY flux, FORESTS & forestry
Published: 1999

Catalog

Books, media, physical & digital resources

See catalog results

Searchworks

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources

Refine your results

32 results on '"Snow-cover"'

1. Investigating The Relationship Between Geomorphological Components (Elevation, Slope and Aspect) and The Maximum Snow-Cover Duration in Talesh Mountains.

2. Spatiotemporal distribution of Arctic herbivores in spring: Potential for competition?

3. Predicted scarcity of suitable habitat for alpine plant communities in northern Japan under climate change.

4. Substrate influences foraging selection by Eurasian Green Woodpeckers Picus viridis in autumn and winter: observations in Hungary over a 20-year period.

5. Variability of Northern Hemisphere Spring Snowmelt Dates Using the AVHRR Polar Pathfinder Snow Cover During 1982–2004

6. Investigating meteorological and snowpack drivers for glide-snow avalanching

7. Spatiotemporal distribution and co-occurrence of Arctic herbivores in spring

8. Global maps of soil temperature

9. The influence of snow cover on ground freeze-thaw frequency, intensity, and duration: An experimental study conducted in coastal northern Sweden.

10. Winter climates and coldhardiness in terrestrial insects

11. Global maps of soil temperature

12. Roles of surface wind, NDVI and snow cover in the recent changes in Asian dust storm occurrence frequency

13. Monitoring recent changes in snow cover in Central Asia using improved MODIS snow-cover products

14. Extending the Utility of Modis Daily Snow-Cover Products through Snow-Cover Prediction of Cloud-Obscured Areas in Idaho's Big Lost River Basin (USA).

15. Sowing date influence on winter oilseed rape overwintering in Estonia.

16. Topography and climate in the upper Indus Basin: Mapping elevation-snow cover relationships.

17. Observed climatic trends in the Pyrenees (1950-2015)

18. Limitations and Challenges of MODIS-Derived Phenological Metrics Across Different Landscapes in Pan-Arctic Regions

19. Effects of food abundance and early clutch predation on reproductive timing in a high Arctic shorebird exposed to advancements in arthropod abundance

20. A STUDY CHANGE OF DYNAMICS OF DESCRIPTIONS OF SNOW-COVER IN DISTRICT OF CHERNOGIRSKY MOUNTAIN-RANGE OF CARPATHIANS, AS FACTOR WHICH PROVIDES LEVEL DRINKABLE WATER IN THE R. PRUT

21. Possible processes of N2O production and emission on seasonally frozen soil

22. Has prey availability for Arctic birds advanced with climate change? Hindcasting the abundance of tundra Arthropods using weather and seasonal variation

23. Winter climates and coldhardiness in terrestrial insects

24. Spatial heterogeneity of albedo over a snow-covered agricultural landscape

25. A remote sensing exploration of land surface phenology in the Australian Alps

26. Temporal trends in avalanche activity in the French Alps and subregions: from occurrences and runout altitudes to unsteady return periods

27. Relationships between plant communities and late snow melting on Mount Prado (Northern Apennines, Italy)

28. A remote sensing exploration of land surface phenology in the Australian Alps

29. Has prey availability for Arctic birds advanced with climate change? Hindcasting the abundance of tundra arthropods using weather and seasonal variations

30. Has prey availability for Arctic birds advanced with climate change? Hindcasting the abundance of tundra Arthropods using weather and seasonal variation

31. Snow and snow-cover in central northeast Greenland

32. Energy balance above a boreal coniferous forest: a difference in turbulent fluxes between snow-covered and snow-free canopies

Catalog

Searchworks

Select search scope, currently: Articles Catalog books, media & more in Jio Institute collections Articles journal articles & other e-resources

Search

Search Constraints

Refine your results

Search Limiters

Topic

Publication Year Range

Language

Publication Type

Journal

Region

Database

Publisher

32 results on '"Snow-cover"'

Search Results

Catalog

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources