SoilTemp: A global database of near-surface temperature
Jazyk angličtina Země Velká Británie, Anglie Médium print-electronic
Typ dokumentu časopisecké články
Grantová podpora
12P1819N
Fonds Wetenschappelijk Onderzoek
WOG W001919N
Fonds Wetenschappelijk Onderzoek
EVK2-CT-2000-0006
European Union FP-5 project GLORIA-Europe
Swiss MAVA Foundation project
Swiss Federal Office for the Environment (FOEN); Foundation Dr. Joachim de Giacomi
Research Commission and Staff of the Swiss National Park
W47014118
Flexible Pool project
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
University of Alcalá
Fondation Mariétan, Société académique de Genève
Swiss Federal Office of Education and Science
17-13998S
Czech Science Foundation
17-07378S
Czech Science Foundation
20-05840Y
Czech Science Foundation
17-19376S
Czech Science Foundation
RVO 67985939
Czech Academy of Sciences
PRG609
Estonian Research Council
European Regional Development Fund
DFG GraKo 2010 Response
QUEX-CAS-QP-RD-18/19
Qatar Petroleum
Ministry of Education and Science of Ukraine
Toward INMS
VEGA 2/0132/18
Slovak Scientific Grant Agency
Lund University
University of Helsinki
LTAUSA19137
Ministry of Education, Youth and Sport of the Czech Republic, program Inter-Excellence, subprogram Inter-Action
LTAUSA18007
Ministry of Education, Youth and Sport of the Czech Republic, program Inter-Excellence, subprogram Inter-Action
CF16-0896
Carlsberg Foundation
17523
Villum Foundation
FZT 118
German Research Foundation
641918
EU Horizon 2020
NE/L002558/1
Natural Environmental Research Council
NE/M016323/1
Natural Environmental Research Council
NE/M016323/1
UK Natural Environmental Research Council ShrubTundra
INTER-TRANSFER LTT17017
Ministry of Education, Youth and Sports of the Czech Republic
MONB00363
National Institute of Food and Agriculture
2017-70006-27272
National Institute of Food and Agriculture
Slovak Research and Development Agency
9480-14
National Geographic Society
WW-240R-17
National Geographic Society
262064
Research Council of Norway
ABI-1759965
National Science Foundation
EF-1802605
National Science Foundation
Leverhulme Trust Research Fellowship
41971124
National Natural Science Foundation of China
Mendel University
Ministry of Youth and Sports of the Czech Republic
Ministry of Research and Innovation
19-04-01234-a
RFBR
ANR-19-CE32-0005-01
Agence Nationale de la Recherche (ANR)
172198
Swiss National Science Foundation - Switzerland
ERC-2562013-SyG-610028
European Research Council - International
PubMed
32311220
DOI
10.1111/gcb.15123
Knihovny.cz E-zdroje
- Klíčová slova
- climate change, database, ecosystem processes, microclimate, soil climate, species distributions, temperature, topoclimate,
- MeSH
- ekosystém * MeSH
- klimatické změny MeSH
- mikroklima * MeSH
- sníh MeSH
- teplota MeSH
- Publikační typ
- časopisecké články MeSH
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.
A Borza Botanical Garden Babes Bolyai University Cluj Napoca Romania
A N Severtsov Institute of Ecology and Evolution Russian Academy of Sciences Moscow Russia
Alfred Wegener Institute Helmholtz Center for Polar and Marine Research Potsdam Germany
ARAID Research and Development Zaragoza Spain
Asian School of Environment Nanyang Technological University Singapore Singapore
Australian Museum Sydney NSW Australia
Bioclimatology University of Goettingen Göttingen Germany
Biological and Environmental Sciences Faculty of Natural Sciences University of Stirling Stirling UK
CIRAD UMR Eco and Sols Dakar Senegal
Climate Change Unit Environmental Protection Agency of Aosta Valley Aosta Italy
CNR Institute for Mediterranean Agricultural and Forest Systems Ercolano Italy
County Administrative Board of Västra Götaland Gothenburg Sweden
Dartmouth College Hanover NH USA
Department of Biological and Environmental Sciences Qatar University Doha Qatar
Department of Biological Sciences University of Notre Dame Notre Dame IN USA
Department of Biology and Ecology Center Utah State University Logan UT USA
Department of Biology Norwegian University of Science and Technology Trondheim Norway
Department of Bioscience and Arctic Research Centre Rønde Denmark
Department of Botany University of Granada Granada Spain
Department of Earth and Environmental Sciences Leuven Belgium
Department of Earth Sciences University of Gothenburg Gothenburg Sweden
Department of Environmental Systems Science ETH Zurich Zurich Switzerland
Department of Forest Botany Dendrology and Geobiocoenology Mendel University Brno Czech Republic
Department of Forestry and NR H N B Garhwal University Srinagar Garhwal India
Department of Geography and Earth Sciences Aberystwyth University Wales UK
Department of Geography Masaryk University Brno Czech Republic
Department of Geography York St John University York UK
Department of Geology Geography and Environment University of Alcalá Madrid Spain
Department of Geosciences and Geography University of Helsinki Helsinki Finland
Department of Land Resources and Environmental Sciences Montana State University Bozeman MT USA
Department of Life Sciences Imperial College London Ascot UK
Department of Physical Geography and Ecosystem Science Lund University Lund Sweden
Department of Science and High Technology Insubria University Como Italy
Department of Theoretical and Applied Sciences Insubria University Varese Italy
Department of Wildlife Ecology and Conservation University of Florida Gainesville FL USA
Eco and Sols Univ Montpellier CIRAD INRAE IRD Institut Agro Montpellier France
Ecological Plant Geography Faculty of Geography University of Marburg Marburg Germany
Environment and Sustainability Institute University of Exeter Penryn UK
Environmental Science Center Qatar University Doha Qatar
EnvixLab Dipartimento di Bioscienze e Territorio Università degli Studi del Molise Termoli Italy
Facultad de Ciencias Exactas y Naturales Universidad Nacional de Cuyo Cuyo Argentina
Faculty of Biology University of Duisburg Essen Essen Germany
Faculty of Ecology and Environmental Sciences Technical University in Zvolen Zvolen Slovakia
Faculty of Forestry Technical University in Zvolen Zvolen Slovakia
Faculty of Science Department of Botany University of South Bohemia České Budějovice Czech Republic
Finnish Meteorological Institute Helsinki Finland
Forest and Nature Lab Department of Environment Ghent University Melle Gontrode Belgium
Geography Department Humboldt Universität zu Berlin Berlin Germany
Georgian Institute of Public Affairs Tbilisi Georgia
German Centre for Integrative Biodiversity Research Halle Jena Leipzig Leipzig Germany
Gothenburg Global Biodiversity Centre Gothenburg Sweden
Graduate School of Life and Environmental Sciences Osaka Prefecture University Osaka Japan
Grupo de Ecología de Poblaciones de Insectos IFAB Bariloche Argentina
Institute of Biology Leipzig University Leipzig Germany
Institute of Botany and Landscape Ecology University Greifswald Greifswald Germany
Institute of Botany of the Czech Academy of Sciences Průhonice Czech Republic
Institute of Ecology and Earth Sciences University of Tartu Tartu Estonia
Institute of Landscape Ecology Slovak Academy of Sciences Bratislava Slovakia
Instituto de Ecología y Biodiversidad Santiago Chile
Isotope Bioscience Laboratory ISOFYS Ghent University Gent Belgium
Jolube Consultor Botánico Jaca Spain
Majella Seed Bank Majella National Park Lama dei Peligni Italy
Mountains of the Moon University Fort Portal Uganda
National Forest Centre Forest Research Institute Zvolen Zvolen Slovakia
Plant Ecology Group Department of Evolution and Ecology University of Tübingen Tübingen Germany
Remote Sensing Laboratories Department of Geography University of Zurich Zurich Switzerland
Research Group PLECO University of Antwerp Wilrijk Belgium
Research Institute for Nature and Forest Brussels Belgium
School of Ecology and Environment Studies Nalanda University Rajgir India
School of Education and Social Sciences Adventist University of Chile Chile
School of GeoSciences University of Edinburgh Edinburgh UK
School of Life Sciences Arizona State University Tempe AZ USA
School of Natural Resources and Environment University of Florida Gainesville FL USA
Senckenberg Research Institute and Natural History Museum Frankfurt Gelnhausen Germany
Siberian Federal University Krasnoyarsk Russia
Swedish Species Information Centre Swedish University of Agricultural Sciences Uppsala Sweden
Swiss Federal Research Institute WSL Birmensdorf Switzerland
Swiss National Park Chastè Planta Wildenberg Zernez Switzerland
UK Centre for Ecology and Hydrology Midlothian UK
Unit of Land Change Science Swiss Federal Research Institute WSL Birmensdorf Switzerland
Universidad Nacional de San Antonio Abad del Cusco Cusco Peru
UR 'Ecologie et Dynamique des Systèmes Anthropisées' Univ de Picardie Jules Verne Amiens France
Woodrow Wilson School of Public and International Affairs Princeton University Princeton NJ USA
WSL Institute for Snow and Avalanche Research SLF Davos Switzerland
Zobrazit více v PubMed
Aalto, J., Riihimäki, H., Meineri, E., Hylander, K., & Luoto, M. (2017). Revealing topoclimatic heterogeneity using meteorological station data. International Journal of Climatology, 37, 544-556. https://doi.org/10.1002/joc.5020
Aalto, J., Scherrer, D., Lenoir, J., Guisan, A., & Luoto, M. (2018). Biogeophysical controls on soil-atmosphere thermal differences: Implications on warming Arctic ecosystems. Environmental Research Letters, 13, 074003. https://doi.org/10.1088/1748-9326/aac83e
Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A., & Hegewisch, K. C. (2018). TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015. Scientific Data, 5, 1958-2015. https://doi.org/10.1038/sdata.2017.191
Ashcroft, M. B., Cavanagh, M., Eldridge, M. D. B., & Gollan, J. R. (2014). Testing the ability of topoclimatic grids of extreme temperatures to explain the distribution of the endangered brush-tailed rock-wallaby (Petrogale penicillata). Journal of Biogeography, 41, 1402-1413.
Ashcroft, M. B., Chisholm, L. A., & French, K. O. (2008). The effect of exposure on landscape scale soil surface temperatures and species distribution models. Landscape Ecology, 23, 211-225. https://doi.org/10.1007/s10980-007-9181-8
Ashcroft, M. B., Chisholm, L. A., & French, K. O. (2009). Climate change at the landscape scale: Predicting fine-grained spatial heterogeneity in warming and potential refugia for vegetation. Global Change Biology, 15, 656-667. https://doi.org/10.1111/j.1365-2486.2008.01762.x
Ashcroft, M. B., & Gollan, J. R. (2012). Fine-resolution (25 m) topoclimatic grids of near-surface (5 cm) extreme temperatures and humidities across various habitats in a large (200 × 300 km) and diverse region. International Journal of Climatology, 32, 2134-2148.
Ashcroft, M. B., & Gollan, J. R. (2013). Moisture, thermal inertia, and the spatial distributions of near-surface soil and air temperatures: Understanding factors that promote microrefugia. Agricultural and Forest Meteorology, 176, 77-89. https://doi.org/10.1016/j.agrformet.2013.03.008
Bennie, J., Huntley, B., Wiltshire, A., Hill, M. O., & Baxter, R. (2008). Slope, aspect and climate: Spatially explicit and implicit models of topographic microclimate in chalk grassland. Ecological Modelling, 216, 47-59. https://doi.org/10.1016/j.ecolmodel.2008.04.010
Bennie, J., Wilson, R. J., Maclean, I. M. D., & Suggitt, A. J. (2014). Seeing the woods for the trees - When is microclimate important in species distribution models? Global Change Biology, 20, 2699-2700. https://doi.org/10.1111/gcb.12525
Bramer, I., Anderson, B., Bennie, J., Bladon, A., De Frenne, P., Hemming, D., … Gillingham, P. K. (2018). Advances in monitoring and modelling climate at ecologically relevant scales. Advances in Ecological Research, 58, 101-161.
Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez-Alfaro, B., Hennekens, S. M., … Jandt, U. (2018). Global trait-environment relationships of plant communities. Nature Ecology & Evolution, 2, 1906-1917. https://doi.org/10.1038/s41559-018-0699-8
Cameron, E. K., Martins, I. S., Lavelle, P., Mathieu, J., Tedersoo, L., Gottschall, F., … Eisenhauer, N. (2018). Global gaps in soil biodiversity data. Nature Ecology & Evolution, 2, 1042-1043. https://doi.org/10.1038/s41559-018-0573-8
Carter, A., Kearney, M., Mitchell, N., Hartley, S., Porter, W., & Nelson, N. (2015). Modelling the soil microclimate: Does the spatial or temporal resolution of input parameters matter? Frontiers of Biogeography, 7, 138-154. https://doi.org/10.21425/F5FBG27849
Copernicus Climate Change Service (C3s). (2019). C3S ERA5-Land reanalysis (Ed. Copernicus Climate Change Service).
Coûteaux, M.-M., Bottner, P., & Berg, B. (1995). Litter decomposition, climate and litter quality. Trends in Ecology & Evolution, 10, 63-66.
Daly, C. (2006). Guidelines for assessing the suitability of spatial climate data sets. International Journal of Climatology, 26, 707-721. https://doi.org/10.1002/joc.1322
De Boeck, H. J., Van De Velde, H., De Groote, T., & Nijs, I. (2016). Ideas and perspectives: Heat stress: More than hot air. Biogeosciences, 13, 5821-5825. https://doi.org/10.5194/bg-13-5821-2016
De Frenne, P., Rodriguez-Sanchez, F., Coomes, D. A., Baeten, L., Verstraeten, G., Vellend, M., … Verheyen, K. (2013). Microclimate moderates plant responses to macroclimate warming. Proceedings of the National Academy of Sciences of the United States of America, 110, 18561-18565. https://doi.org/10.1073/pnas.1311190110
Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37, 4302-4315. https://doi.org/10.1002/joc.5086
Geiger, R. (1950). The climate near the ground. Cambridge, MA: Harvard University Press.
Gottschall, F., Davids, S., Newiger-Dous, T. E., Auge, H., Cesarz, S., & Eisenhauer, N. (2019). Tree species identity determines wood decomposition via microclimatic effects. Ecology and Evolution, 9, 12113-12127. https://doi.org/10.1002/ece3.5665
Goulden, M. L., Wofsy, S. C., Harden, J. W., Trumbore, S. E., Crill, P. M., Gower, S. T., … Munger, J. W. (1998). Sensitivity of boreal forest carbon balance to soil thaw. Science, 279, 214-217. https://doi.org/10.1126/science.279.5348.214
Guerra, C. A., Heintz-Buschart, A., Sikorski, J., Chatzinotas, A., Guerrero-Ramírez, N., Cesarz, S., … Delgado-Baquerizo, M. (2019). Blind spots in global soil biodiversity and ecosystem function research. bioRxiv, 774356. https://doi.org/10.1101/774356
Hursh, A., Ballantyne, A., Cooper, L., Maneta, M., Kimball, J., & Watts, J. (2017). The sensitivity of soil respiration to soil temperature, moisture, and carbon supply at the global scale. Global Change Biology, 23, 2090-2103. https://doi.org/10.1111/gcb.13489
Jarraud, M. (2008). Guide to meteorological instruments and methods of observation (WMO-No. 8). Geneva, Switzerland: World Meteorological Organisation.
Jucker, T., Jackson, T., Zellweger, F., Swinfield, T., Gregory, N., Williamson, J., … Coomes, D. (2020). A research agenda for microclimate ecology in human-modified tropical forests. Frontiers in Forests and Global Change, 2. https://doi.org/10.3389/ffgc.2019.00092.
Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., … Kessler, M. (2017). Climatologies at high resolution for the earth's land surface areas. Scientific Data, 4, 170122. https://doi.org/10.1038/sdata.2017.122
Kattge, J., Bönisch, G., Díaz, S., Lavorel, S., Prentice, I. C., Leadley, P., … Wirth, C. (2019). TRY plant trait database-enhanced coverage and open access. Global Change Biology, 26, 119-188. https://doi.org/10.1111/gcb.14904
Kearney, M. R. (2019). MicroclimOz - A microclimate data set for Australia, with example applications. Austral Ecology, 44, 534-544. https://doi.org/10.1111/aec.12689
Kearney, M. R., Isaac, A. P., & Porter, W. P. (2014). microclim: Global estimates of hourly microclimate based on long-term monthly climate averages. Scientific Data, 1, 140006. https://doi.org/10.1038/sdata.2014.6
Kearney, M. R., Shamakhy, A., Tingley, R., Karoly, D. J., Hoffmann, A. A., Briggs, P. R., & Porter, W. P. (2014). Microclimate modelling at macro scales: A test of a general microclimate model integrated with gridded continental-scale soil and weather data. Methods in Ecology and Evolution, 5, 273-286. https://doi.org/10.1111/2041-210X.12148
Kearney, M., Shine, R., & Porter, W. P. (2009). The potential for behavioral thermoregulation to buffer “cold-blooded” animals against climate warming. Proceedings of the National Academy of Sciences of the United States of America, 106, 3835-3840. https://doi.org/10.1073/pnas.0808913106
Kissling, W. D., Walls, R., Bowser, A., Jones, M. O., Kattge, J., Agosti, D., … Guralnick, R. P. (2018). Towards global data products of essential biodiversity variables on species traits. Nature Ecology & Evolution, 2, 1531-1540. https://doi.org/10.1038/s41559-018-0667-3
Körner, C., & Hiltbrunner, E. (2018). The 90 ways to describe plant temperature. Perspectives in Plant Ecology, Evolution and Systematics, 30, 16-21. https://doi.org/10.1016/j.ppees.2017.04.004
Körner, C., & Paulsen, J. (2004). A world-wide study of high altitude treeline temperatures. Journal of Biogeography, 31, 713-732. https://doi.org/10.1111/j.1365-2699.2003.01043.x
Lembrechts, J. J., Lenoir, J., Roth, N., Hattab, T., Milbau, A., Haider, S., … Nijs, I. (2019). Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing. Global Ecology and Biogeography, 28, 1578-1596. https://doi.org/10.1111/geb.12974
Lembrechts, J., Nijs, I., & Lenoir, J. (2019). Incorporating microclimate into species distribution models. Ecography, 42, 1267-1279. https://doi.org/10.1111/ecog.03947
Lenoir, J., Hattab, T., & Pierre, G. (2017). Climatic microrefugia under anthropogenic climate change: Implications for species redistribution. Ecography, 40, 253-266. https://doi.org/10.1111/ecog.02788
Li, T.-T. (1926). Soil temperature as influenced by forest cover. New Haven, CT: Yale University - School of Forestry.
Macek, M., Kopecký, M., & Wild, J. (2019). Maximum air temperature controlled by landscape topography affects plant species composition in temperate forests. Landscape Ecology, 34, 2541-2556. https://doi.org/10.1007/s10980-019-00903-x
Maclean, I. M. (2019). Predicting future climate at high spatial and temporal resolution. Global Change Biology, 26, 1003-1011. https://doi.org/10.1111/gcb.14876
Maclean, I. M. D., Hopkins, J. J., Bennie, J., Lawson, C. R., & Wilson, R. J. (2015). Microclimates buffer the responses of plant communities to climate change. Global Ecology and Biogeography, 24, 1340-1350. https://doi.org/10.1111/geb.12359
Maclean, I. M. D., Suggitt, A. J., Wilson, R. J., Duffy, J. P., & Bennie, J. J. (2017). Fine-scale climate change: Modelling spatial variation in biologically meaningful rates of warming. Global Change Biology, 23, 256-268. https://doi.org/10.1111/gcb.13343
Maestre, F. T., & Eisenhauer, N. (2019). Recommendations for establishing global collaborative networks in soil ecology. Soil Organisms, 91, 73.
Medinets, S., Gasche, R., Kiese, R., Rennenberg, H., & Butterbach-Bahl, K. (2019). Seasonal dynamics and profiles of soil NO concentrations in a temperate forest. Plant and Soil, 445, 335-348. https://doi.org/10.1007/s11104-019-04305-5
Meineri, E., & Hylander, K. (2017). Fine-grain, large-domain climate models based on climate station and comprehensive topographic information improve microrefugia detection. Ecography, 40, 1003-1013. https://doi.org/10.1111/ecog.02494
Niittynen, P., & Luoto, M. (2017). The importance of snow in species distribution models of arctic vegetation. Ecography, 41, 1024-1037. https://doi.org/10.1111/ecog.03348
Opedal, O. H., Armbruster, W. S., & Graae, B. J. (2015). Linking small-scale topography with microclimate, plant species diversity and intra-specific trait variation in an alpine landscape. Plant Ecology & Diversity, 8, 305-315. https://doi.org/10.1080/17550874.2014.987330
Pincebourde, S., & Casas, J. (2019). Narrow safety margin in the phyllosphere during thermal extremes. Proceedings of the National Academy of Sciences of the United States of America, 116, 5588-5596. https://doi.org/10.1073/pnas.1815828116
Pincebourde, S., Murdock, C. C., Vickers, M., & Sears, M. W. (2016). Fine-scale microclimatic variation can shape the responses of organisms to global change in both natural and urban environments. Integrative and Comparative Biology, 56, 45-61. https://doi.org/10.1093/icb/icw016
Pleim, J. E., & Gilliam, R. (2009). An indirect data assimilation scheme for deep soil temperature in the Pleim-Xiu land surface model. Journal of Applied Meteorology and Climatology, 48, 1362-1376. https://doi.org/10.1175/2009JAMC2053.1
Portillo-Estrada, M., Pihlatie, M., Korhonen, J. F. J., Levula, J., Frumau, A. K. F., Ibrom, A., … Niinemets, U. (2016). Climatic controls on leaf litter decomposition across European forests and grasslands revealed by reciprocal litter transplantation experiments. Biogeosciences, 13, 1621-1633. https://doi.org/10.5194/bg-13-1621-2016
Pradervand, J.-N., Dubuis, A., Pellissier, L., Guisan, A., & Randin, C. (2014). Very high resolution environmental predictors in species distribution models: Moving beyond topography? Progress in Physical Geography, 38, 79-96. https://doi.org/10.1177/0309133313512667
Randin, C. F., Vuissoz, G., Liston, G. E., Vittoz, P., & Guisan, A. (2009). Introduction of snow and geomorphic disturbance variables into predictive models of alpine plant distribution in the Western Swiss Alps. Arctic, Antarctic, and Alpine Research, 41, 347-361. https://doi.org/10.1657/1938-4246-41.3.347
Rosenberg, N. J., Kimball, B., Martin, P., & Cooper, C. (1990). From climate and CO2 enrichment to evapotranspiration. In P. Wagoner (Ed.), Climate change and US water resources (pp. 151-175). New York, NY: John Wiley and Sons Inc.
Schimel, D. S., Braswell, B., Mckeown, R., Ojima, D. S., Parton, W., & Pulliam, W. (1996). Climate and nitrogen controls on the geography and timescales of terrestrial biogeochemical cycling. Global Biogeochemical Cycles, 10, 677-692. https://doi.org/10.1029/96GB01524
Slavich, E., Warton, D. I., Ashcroft, M. B., Gollan, J. R., & Ramp, D. (2014). Topoclimate versus macroclimate: How does climate mapping methodology affect species distribution models and climate change projections? Diversity and Distributions, 20, 952-963. https://doi.org/10.1111/ddi.12216
Suggitt, A. J., Gillingham, P. K., Hill, J. K., Huntley, B., Kunin, W. E., Roy, D. B., & Thomas, C. D. (2011). Habitat microclimates drive fine-scale variation in extreme temperatures. Oikos, 120, 1-8. https://doi.org/10.1111/j.1600-0706.2010.18270.x
Suggitt, A. J., Wilson, R. J., Isaac, N. J. B., Beale, C. M., Auffret, A. G., August, T., … Maclean, I. M. D. (2018). Extinction risk from climate change is reduced by microclimatic buffering. Nature Climate Change, 8, 713. https://doi.org/10.1038/s41558-018-0231-9
Vitasse, Y., Klein, G., Kirchner, J. W., & Rebetez, M. (2017). Intensity, frequency and spatial configuration of winter temperature inversions in the closed La Brevine valley, Switzerland. Theoretical and Applied Climatology, 130, 1073-1083. https://doi.org/10.1007/s00704-016-1944-1
Wason, J. W., Bevilacqua, E., & Dovciak, M. (2017). Climates on the move: Implications of climate warming for species distributions in mountains of the northeastern United States. Agricultural and Forest Meteorology, 246, 272-280. https://doi.org/10.1016/j.agrformet.2017.05.019
Western, A. W., Grayson, R. B., & Blöschl, G. (2002). Scaling of soil moisture: A hydrologic perspective. Annual Review of Earth and Planetary Sciences, 30, 149-180. https://doi.org/10.1146/annurev.earth.30.091201.140434
Whiteman, C. D. (1982). Breakup of temperature inversions in deep mountain valleys: Part I. Observations. Journal of Applied Meteorology, 21, 270-289. https://doi.org/10.1175/1520-0450(1982)021<0270:BOTIID>2.0.CO;2
Whittaker, R. H. (1975). Communities and ecosystems. Communities and ecosystems (2nd ed). New York, NY: Macmillan.
Zellweger, F., De Frenne, P., Lenoir, J., Rocchini, D., & Coomes, D. (2019). Advances in microclimate ecology arising from remote sensing. Trends in Ecology & Evolution, 34, 327-341. https://doi.org/10.1016/j.tree.2018.12.012
Zhang, Y., Wang, S., Barr, A. G., & Black, T. (2008). Impact of snow cover on soil temperature and its simulation in a boreal aspen forest. Cold Regions Science and Technology, 52, 355-370. https://doi.org/10.1016/j.coldregions.2007.07.001
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