Decomposing the spatial and temporal effects of climate on bird populations in northern European mountains

The relationships between species abundance or occurrence versus spatial variation in climate are commonly used in species distribution models to forecast future distributions. Under “space‐for‐time substitution”, the effects of climate variation on species are assumed to be equivalent in both space...

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Bibliographic Details
Published in:	Global change biology Vol. 28; no. 21; pp. 6209 - 6227
Main Authors:	Bradter, Ute, Johnston, Alison, Hochachka, Wesley M., Soultan, Alaaeldin, Brommer, Jon E., Gaget, Elie, Kålås, John Atle, Lehikoinen, Aleksi, Lindström, Åke, Piirainen, Sirke, Pavón‐Jordán, Diego, Pärt, Tomas, Øien, Ingar Jostein, Sandercock, Brett K.
Format:	Journal Article
Language:	English
Published:	England Blackwell Publishing Ltd 01.11.2022 John Wiley and Sons Inc
Subjects:	Abundance Animal breeding Animals anticipatory forecasts Biologi Biological Sciences Bird populations Birds Birds - physiology Breeding Breeding seasons Climate Change climate decomposition Climate effects Climate models Climate Research Climate Science climatic factors Components Decomposition dynamic forecasts Earth and Related Environmental Sciences Ecology Ecology (including Biodiversity Conservation) Ecosystem Ekologi Environmental Sciences Equivalence forecast horizon Geographical distribution Geovetenskap och relaterad miljövetenskap Klimatforskning Klimatvetenskap Land cover Miljövetenskap Mountains Natural Sciences Naturvetenskap Population Dynamics Scandinavia Seasons space‐for‐time substitution Spatial variations spatiotemporal forecasts spatiotemporal pattern Species species abundance species distribution models static forecasts Substitutes Surveys Temperature temporal variation Temporal variations topography Fennoscandia Scandinavia anticipatory forecasts spatiotemporal pattern space-for-time substitution species distribution models forecast horizon static forecasts dynamic forecasts climate decomposition spatiotemporal forecasts
ISSN:	1354-1013, 1365-2486, 1365-2486
Online Access:	Get full text
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