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231225s2018 xx |||||o 00| ||eng c |
| 024 |
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|a 10.1111/gcb.14450
|2 doi
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|a pubmed24n0962.xml
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|a (DE-627)NLM288750748
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|a (NLM)30238551
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Haest, Birgen
|e verfasserin
|4 aut
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| 245 |
1 |
4 |
|a The influence of weather on avian spring migration phenology
|b What, where and when?
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| 264 |
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|c 2018
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| 336 |
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Completed 04.03.2019
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|a Date Revised 30.03.2022
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2018 John Wiley & Sons Ltd.
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|a Over the past decades, spring arrival and passage of most short- and medium-distance migrating birds in the Northern Hemisphere have advanced. Changes in spring temperature at the passage or arrival area have been most frequently shown to be related to these changes in spring migration phenology. In most studies, preliminary assumptions are made on both the spatial location and the specific time frame of the weather influencing spring migration phenology. We performed a spatially explicit time-window analysis of the effect of weather on mean spring passage dates of nine short- and medium-distance passerines. We analysed data from standardized daily captures at the Helgoland (Germany) constant-effort site, in combination with gridded daily temperature, precipitation and wind data from the NCEP data set over a 55-year period (1960-2014), across the whole of West Europe and North Africa. Although we allowed for a time window of any length at any location, nevertheless incorporating various measures to avoid spurious correlations, time windows at the likely wintering or spring stopover grounds were almost exclusively selected as the best predicting variables (96%-100% of identified variables). The weather variables at the wintering and stopover grounds explain up to 77% of the interannual variability in spring passage. Yet, the response of spring migration phenology to weather at the winter or stopover areas does not fully explain the observed trends. Spring migration phenology is, hence, strongly driven by weather at the wintering and stopover grounds, but additional mechanisms are needed to fully explain the advancement of spring migration. Our results also clearly show that previously illustrated correlations, or the lack thereof, between spring migration phenology and weather at the passage or arrival location are due to spatio-temporal correlations in the weather data. This spatial mismatch might have led to false conclusions, especially the further away the wintering or stopover sites are
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| 650 |
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|a Journal Article
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| 650 |
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|a bird migration
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| 650 |
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4 |
|a climate change
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| 650 |
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4 |
|a environmental plasticity
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| 650 |
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4 |
|a precipitation
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| 650 |
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4 |
|a spatio-temporal analysis
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| 650 |
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4 |
|a temperature
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| 650 |
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4 |
|a time-window analysis
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| 650 |
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4 |
|a wind
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| 700 |
1 |
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|a Hüppop, Ommo
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Bairlein, Franz
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t Global change biology
|d 1999
|g 24(2018), 12 vom: 27. Dez., Seite 5769-5788
|w (DE-627)NLM098239996
|x 1365-2486
|7 nnns
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| 773 |
1 |
8 |
|g volume:24
|g year:2018
|g number:12
|g day:27
|g month:12
|g pages:5769-5788
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1111/gcb.14450
|3 Volltext
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