Proximal microclimate: Moving beyond spatiotemporal resolution improves ecological predictions

Aim The scale of environmental data is often defined by their extent (spatial area, temporal duration) and resolution (grain size, temporal interval). Although describing climate data scale via these terms is appropriate for most meteorological applications, for ecology and biogeography, climate dat...

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Veröffentlicht in:	Global ecology and biogeography 2024-09, Vol.33 (9), p.e13884-n/a
Hauptverfasser:	Klinges, David H., Baecher, J. Alex, Lembrechts, Jonas J., Maclean, Ilya M. D., Lenoir, Jonathan, Greiser, Caroline, Ashcroft, Michael, Evans, Luke J., Kearney, Michael R., Aalto, Juha, Barrio, Isabel C., De Frenne, Pieter, Guillemot, Joannès, Hylander, Kristoffer, Jucker, Tommaso, Kopecký, Martin, Luoto, Miska, Macek, Martin, Nijs, Ivan, Urban, Josef, Brink, Liesbeth, Vangansbeke, Pieter, Von Oppen, Jonathan, Wild, Jan, Boike, Julia, Canessa, Rafaella, Nosetto, Marcelo, Rubtsov, Alexey, Sallo‐Bravo, Jhonatan, Scheffers, Brett R.
Format:	Artikel
Sprache:	eng
Schlagworte:	Alberta Aquatic insects Biogeography biophysical ecology Borneo Case studies Climate climate change Climate prediction Climatic data Culicidae Ecological models Ecology ecophysiology Ekologi Environmental Sciences Fysisk geografi Grain size macroclimate Malaysia meteorological data Microclimate Mosquitoes nonlinearity North Carolina Organisms phenology Physical Geography Proximity resolution salamanders and newts soil Soil temperature Spatial discrimination Spatial resolution Spatiotemporal data species distribution model temperature Temporal resolution Tennessee
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