Search

Ice-free areas occupy 5 m in bedrock sites in the Antarctic Peninsula. The deepest and most variable ALTs (ca. 40 to >500 cm) were found in the Antarctic Peninsula, whereas the maximum ALT generally did not exceed 90 cm in Victoria Land and East Antarctica. Notably, found that the mean annual near-surface temperature follows the latitudinal gradient of −0.9 °C/deg. (R2 = 0.9) and the active layer thickness 3.7 cm/deg. (R2 = 0.64). The continuous permafrost occurs in the vast majority of the ice-free areas in Antarctica. The modelling of temperature on the top of the permafrost indicates also the permafrost presence in South Orkneys and South Georgia. The only areas where deep boreholes and geophysical surveys indicates discontinuous or sporadic permafrost are South Shetlands and Western Antarctic Peninsula.

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

Research in environmental science relies heavily on global climatic grids derived from estimates of air temperature at around 2 meter above ground1-3. These climatic grids however fail to reflect conditions near and below the soil surface, where critical ecosystem functions such as soil carbon storage are controlled and most biodiversity resides4-8. By using soil temperature time series from over 8500 locations across all of the world’s terrestrial biomes4, we derived global maps of soil temperature-related variables at 1 km resolution for the 0–5 and 5–15 cm depth horizons. Based on these maps, we show that mean annual soil temperature differs markedly from the corresponding 2 m gridded air temperature, by up to 10°C, with substantial variation across biomes and seasons. Soils in cold and/or dry biomes are annually substantially warmer (3.6°C ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are slightly cooler (0.7 ± 2.3°C). As a result, annual soil temperature varies less (by 17%) across the globe than air temperature. The effect of macroclimatic conditions on the difference between soil and air temperature highlights the importance of considering that macroclimate warming may not result in the same level of soil temperature warming. Similarly, changes in precipitation could alter the relationship between soil and air temperature, with implications for soil-atmosphere feedbacks9. Our results underpin that the impacts of climate and climate change on biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments.

© 2020 John Wiley & Sons Ltd Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.

Este Proyecto tiene por objeto la ordenación cinegetica del coto privado de caza “Campoespacio”, con matrícula SO-10.096, situado al sur del término municipal de Abejar, en la provincia de Soria. El coto comprende una superficie de 1.029,736 hectáreas. El coto tiene aprovechamiento principal de caza menor y aprovechamiento secundario de caza mayor. Las principales especies cinegéticas del coto sobre las que se actuará serán ciervo, corzo y jabalí en caza mayor y zorro, liebre, conejo y perdiz en la caza menor. De todas ellas se ha estudiado la biología, el hábitat y la situación de sus poblaciones. Comparando las densidades observadas sobre el terreno con las densidades ideales, mediante el cálculo de la posibilidad cinegética del coto, se pretende alcanzar, con un adecuado plan de mejoras, las máximas densidades que el hábitat sea capaz de producir, obteniendo los mejores rendimientos cinegéticos posibles sin comprometer dichas densidades. Como mejoras del hábitat se plantearán las siembras para la caza, comederos para las perdices, bebederos, colocación de bolas de sal y colocación de un majano para realizar una repoblación de conejos. También se llevará a cabo un control de predadores, además de mejorar la señalización. Por último, se plantea la posibilidad de contratar un servicio de vigilancia para el coto a media jornada. El presupuesto de todas estas actuaciones asciende a 8.320,25 €, Grado en Ingeniería Forestal: Industrias Forestales

Este estudio surge en el ámbito de la investigación del movimiento de ciertos sujetos voluntarios al andar. Para profundizar en ello, en este estudio se ha realizado el análisis del movimiento de los marcadores colocados en la columna de los pacientes con el fin de observar la posición de los marcadores, el movimiento que describen al moverse y posteriormente, según una serie de parámetros definidos, clasificar a los sujetos en diferentes categorías. El análisis ha sido llevado a cabo gracias a los datos obtenidos en el laboratorio SATI de la universidad de Valencia partiendo de la idea de doble paso medio o DPM a partir del cual se calcularon las muestras que han sido analizadas. El análisis se ha llevado a cabo utilizando la herramienta de cálculo matemático “Matlab” tanto para la obtención de gráficas como para el análisis matemático y la clasificación de los resultados., Grado en Ingeniería de Tecnologías de Telecomunicación

En climas semi-áridos, la gestión del estado hídrico en verano es un factor esencial que condiciona los principales parámetros de calidad. Por este motivo muchas bodegas se plantean la definición de unidades de manejo hídrico diferenciado para la obtención de uva de una calidad homogénea. El objetivo de este trabajo es la evaluación del interés del empleo del Índice Vegetativo Diferencial Normalizado (NDVI), Número de Racimos (NR) y Conductividad Eléctrica aparente del suelo (ECa), tanto de forma individual como combinada, para la definición de unidades de manejo diferenciadas desde el punto de vista hídrico en viñedo. Se emplean estos índices porque pueden proporcionar información de manera temprana del estado hídrico del viñedo. El trabajo posee dos partes. En ambas el objetivo es evaluar el interés de tres variables (NDVI, NR y ECa) para delimitar unidades diferenciadas de manejo que se correspondan con niveles hídricos distintos. En la primera parte se han comparado con los resultados del ratio isotópico del carbono (δ13C), el cual está estrechamente relacionado con el estrés hídrico acumulado durante el verano, más concretamente al final del verano. Los resultados obtenidos en esta parte han mostrado que únicamente el NDVI de forma individual ha permitido la zonificación de tres áreas con un comportamiento hídrico diferente. Sin embargo, la combinación de NDVI+NR+ECa permite una zonificación con menor grado de significación que empleando exclusivamente el NDVI. En los contrastes a posteriori con Test de Tukey se obtienen dos grupos que no coinciden con los grupos formados con el NDVI+NR+ECa. Mientras que la segunda parte consiste en compararlos con los resultados obtenidos de mediciones directas de potencial xilemático en puntos característicos de la parcela durante el verano, concretamente los potenciales de las 11:00 y 14:00 hora solar entre los meses de julio y septiembre. Tras obtener los resultados se ha podido comprobar que dichos índices no permiten desde el punto de vista estadístico la zonificación para estas condiciones de estudio. Sin embargo se han podido observar de manera visual tendencias en dichos comportamientos hídricos. Destacando la variable NDVI-ECa, que mostraba una estrecha relación con el potencial xilemático. In semi-arid climates, the management of water status is an essential factor which conditions the main parameters of quality. This is the reason why many wineries are considering the definition of unities of differentiated water management to obtain grapes of homogeneous quality. The aim of this study is to evaluate the interest of the employment of Normalized Difference Vegetation Index (NDVI), bunch number (BN) and soil apparent electrical conductivity (ECa), both in an individual and in a combined basis in order to define the differentiated unities of management in terms of water resources in the vineyard. These indexes are used because they are able to provide early information about the water status of the vineyard. This study is made of two parts. In both parts, the aim is to validate the interest of the three variables (NDVI, BN and ECa) to delimit differentiated unities of management which correspond with different water levels. On that account, they have been compared with different measurements of water stress. In the first part, they have been compared with the results of carbon isotope ratio (δ13C), which is strongly associated with the water stress accumulated during the summer, more precisely at the end of the summer. The results obtained in this section have shown that only the NDVI in an individual basis has permitted the zonation of three areas with different water behaviour. However, the combination of NDVI+BN+ECa allows a zonation of a lower grade of significance than in case of using the NDVI exclusively. In the a posteriori contrasts with Tuky’s test two groups are obtained which do not coincide with the groups formed with the NDVI+BN+ECa. Concerning the second part, these variables are compared with the results obtained of direct measurements of the water potential in characteristic spots of the smallholding during the summer, exactly the potential between 11.00 and 14.00 solar times in July, August and September. After obtaining these results, it has been proved that from statistical point of view these indexes do not allow the zonation for these conditions of study. Nonetheless, tendencies in these water behaviours have been visually observed. The variable NDVI-ECa is highlighted as it showed a close connection with the xylematic potential. Graduado o Graduada en Ingeniería Agroalimentaria y del Medio Rural por la Universidad Pública de Navarra Nekazaritzako Elikagaien eta Landa Ingurunearen Ingeniaritzan graduatua Nafarroako Unibertsitate Publikoan

Durante el verano austral de 2008 se realizaron dos perforaciones en la cima del monte Reina Sofía (275 m snm) (628390S, 608210W) en las proximidades de la Base Antártica Española Juan Carlos I en la isla Livingston. Uno de ellos alcanzó una profundidad de 25m (PG-1, Permamodel-Gulbelkian-1) y el otro 15 m de profundidad (PG-2) ambas perforaciones se realizaron en roca cuarcita. En todos los casos se extrajo el testigo de la perforación para su posterior análisis físico, químico y biológico. Una vez realizados los sondeos fueron entubados en forma hermética para alojar en su interior las cadenas termométricas que registran en forma permanente la evolución temporal del gradiente térmico del suelo con periodo horario de registro de temperaturas. Presentamos en este trabajo los datos de temperaturas registrados durante 2008 en las perforaciones PG-1 y PG-2 a diferentes profundidades, tras su primer año de funcionamiento. De estos datos podemos evaluar la profundidad de amplitud térmica anual cero y su temperatura, así como el gradiente térmico y una primera estimación de la profundidad del permafrost continuo en esta zona de estudio. El presente trabajo se encuadra en proyecto internacional del Año Polar Internacional (API) y promovido por la Asociación Internacional del Permafrost (IPA) que lleva como título “Thermal State of Permafrost”(TSP).

El programa de monitoreo de capa activa (CALM) fue desarrollado en las últimas décadas con la finalidad de comprender el impacto del cambio climático sobre los ambientes con permafrost. Este trabajo analiza los resultados obtenidos, en los últimos seis años, de los sitios CALM-S Irizar, Cráter Lake y Refugio Chileno, ubicados en Isla Decepción. En ellos se ha medido el espesor, el estado térmico y la distribución espacial de la capa activa. En los sitios Irizar y Refugio Chileno la evolución del espesor de capa activa varió interanualmente sin una clara tendencia dentro del corto período analizado; por el contrario, el sitio Cráter Lake evidenció una tendencia a la disminución de espesor. La distribución espacial como el espesor de dicha capa en los tres sitios de monitoreo, mostraron estar condicionados principalmente por la potencia de la cubierta de nieve, la litología y la exposición a los vientos. El relieve, la topografía de detalle, la orientación de las laderas frente a la radiación solar incidente, ejercieron un control menor sobre esta distribución. El estado térmico de la capa activa evidenció el control ejercido sobre ella de la temperatura del aire y de la cubierta nival. Así bajo reducidos espesores de nieve, el modelo de penetración en profundidad de la isoterma de 0 ºC, ha permitido aproximar satisfactoriamente el espesor de capa activa. The Circumpolar Active Layer Monitoring (CALM) program developed over the last two decades has a leading edge in comprehensive efforts to study the impacts of climate change in permafrost environments. This paper describes results obtained during the last six years, on the active layer thickness, thermal regime and spatial patterns of thaw, at the CALM-S Irizar, Crater Lake and Refugio Chileno sites in Deception Island. In Irizar and Refugio Chileno CALM-S sites the active layer depth varied interannually without any clear trend over the short record available. By contrast, Crater Lake CALM-S showed a slight thinning trend. In all sites, the spatial patterns of thaw and active layer thickness were mainly controlled by snow cover conditions, lithology and the effect of aspect on wind. The relief, the detailed topography and the effect of aspect on solar radiation also exert a local control over its patterns. Air temperature and snow cover controlled the thermal state of active layer. In absence of snow, the use of depth penetration model of the 0 ºC isotherm allowed approximated satisfactorily active layer thickness. Fil: Goyanes, Gabriel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Estudios Andinos "Don Pablo Groeber". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Estudios Andinos "Don Pablo Groeber"; Argentina Fil: Vieira, Gonçalo. Universidad de Lisboa; Portugal Fil: Caselli, Alberto Tomás. Universidad Nacional de Río Negro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Mora, Carla. Universidad de Lisboa; Portugal Fil: Ramos, Miguel Esteban. Universidad de Alcalá; España. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: de Pablo, Miguel Angel. Universidad de Alcalá; España Fil: Neves, Mario. Universidad de Lisboa; Portugal Fil: Santos, Fernando. Universidad de Lisboa; Portugal Fil: Bernardo, Ivo. Universidad de Lisboa; Portugal Fil: Gilichinsky, David. Academia Rusa de Ciencias; Rusia Fil: Abramov, Andrey. Academia Rusa de Ciencias; Rusia Fil: Batista, Vanessa. Universidad de Lisboa; Portugal Fil: Melo, Raquel. Universidad de Lisboa; Portugal Fil: Nieuwendam, Alexandre. Universidad de Lisboa; Portugal Fil: Ferreira, Alice. Universidad de Lisboa; Portugal Fil: Oliva, Marc. Universidad de Lisboa; Portugal

Close to the Spanish Antarctic Station our research team drilled, at the 1999-2000 Antarctic campaign, a 2,30 m shallow borehole in quartzite bedrock. This borehole was instrumented with temperature data loggers (Tinytag model) that have allowed us to register the gradient thermal in a continuous regime evolution during the 2000-2011 period. The analysis of the temperature data allows to describe the temporal evolution of the freezing and thawing cycles in the active layer, as well as the N-Factor variability, related with the soil surface thermal behavior and its energy balance. In this work we discuss the different freezing and thawing mechanisms in monthly and annual periods. The study shows a important freezing and thawing inter annual variability,, the annual cumulative index showed values in the following intervals: freezing index (-700, -300 ºC day) and thawing index (400, 700 ºC day).

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

A condutividade térmica e a difusividade térmica são dois parâmetros físicos importantes para a interpretação dos fenómenos de transferência de calor em rocha. Neste trabalho são apresentados os valores da condutividade térmica e a difusividade térmica medidos em testemunhos obtidos em duas sondagens realizadas na Ilha de Livingston, perto da Base Antárctica Búlgara (BAB). Uma das sondagens foi realizada no sítio CALM perto da BAB e a outra no sítio chamado de Papagal, perto do sítio CALM. As duas sondagens atingiram uma profundidade máxima de 5 e 6 metros. A determinação laboratorial da condutividade térmica e da difusividade térmica foi realizada em testemunhos secos. Para o furo no sítio CALM a condutividade térmica apresenta um valor médio de 3,14 W/mK, enquanto que para o furo no sítio Papagal a condutividade térmica média é de 3,17 W/mK. Para a difusividade térmica o furo do sítio CALM apresenta um valor médio de 1,58 x 10-6 m2/s enquanto que o furo do sítio Papagal apresenta um valor de 1,52 x 10-6 m2/s. Para cada um dos furos foi ainda estimada a produção de calor tendo-se obtido os valores de 1,30 μW/m3 para o furo no sítio CALM e 0,70 μW/m3 para o sítio Papagal.

No âmbito do projecto Permantar (Permafrost and Climate Change in the Maritime Antarctic), durante os meses de Janeiro e Fevereiro de 2009 foram realizados seis tomografias de resistividade eléctrica (TER) em duas áreas da Ilha de Livingston; três deles foram realizados numa vertente virada a norte a cerca de 300 metros da Base Antárctica Búlgara (BAB) de St. Kliment Ohridski, e outros três no sítio CALM também localizado perto da mesma base. O projecto Permantar integra-se na contribuição Portuguesa para os core projects do Ano Polar Internacional, ANTPAS (Antarctic and Sub-Antarctic Permafrost, Soils and Periglacial Environments) and TSP (Permafrost Observatory Project – Thermal State of Permafrost). O principal objectivo da campanha geoeléctrica recorrendo a tomografias eléctricas foi o de tentar identificar zonas com permafrost e avaliar a sua extensão espacial. Os métodos eléctricos e, em particular, as tomografias eléctricas são muito úteis em estudos de permafrost devido ao facto de se verificar um aumento substancial da resistividade eléctrica do subsolo com o aumento da quantidade de material gelado e com a diminuição da temperatura. Nos dois locais junto à Base Antárctica Búlgara, para cada um dos perfis tomográficos foram utilizados 40 eléctrodos de aço com um espaçamento de 2 metros entre cada um deles. Modelos geoeléctricos preliminares, a duas dimensões, para as zonas onde os perfis tomográficos foram realizados, foram obtidos por inversão dos valores da resistividade eléctrica aparente medidos ao longo de cada um dos perfis. Todos os modelos geoeléctricos apresentam secções com elevada resistividade eléctrica (da ordem de 104 ohm.m). Por limitações de espaço, apenas os perfis tomográficos realizados no sítio CALM são apresentados; aí as zonas de maior resistividade eléctrica parecem indicar a existência de solo gelado, que podem corresponder a bolsas pouco espessas de permafrost ou a resíduos de gelo sazonal.