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231225s2022 xx |||||o 00| ||eng c |
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|a 10.1111/gcb.15958
|2 doi
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|a pubmed24n1107.xml
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|a (NLM)34689389
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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 Rogers, Alistair
|e verfasserin
|4 aut
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| 245 |
1 |
0 |
|a Reducing model uncertainty of climate change impacts on high latitude carbon assimilation
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| 264 |
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1 |
|c 2022
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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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| 500 |
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|a Date Completed 24.02.2022
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|a Date Revised 24.02.2022
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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| 520 |
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|a © 2021 John Wiley & Sons Ltd. This article has been contributed to by US Government employees and their work is in the public domain in the USA.
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|a The Arctic-Boreal Region (ABR) has a large impact on global vegetation-atmosphere interactions and is experiencing markedly greater warming than the rest of the planet, a trend that is projected to continue with anticipated future emissions of CO2 . The ABR is a significant source of uncertainty in estimates of carbon uptake in terrestrial biosphere models such that reducing this uncertainty is critical for more accurately estimating global carbon cycling and understanding the response of the region to global change. Process representation and parameterization associated with gross primary productivity (GPP) drives a large amount of this model uncertainty, particularly within the next 50 years, where the response of existing vegetation to climate change will dominate estimates of GPP for the region. Here we review our current understanding and model representation of GPP in northern latitudes, focusing on vegetation composition, phenology, and physiology, and consider how climate change alters these three components. We highlight challenges in the ABR for predicting GPP, but also focus on the unique opportunities for advancing knowledge and model representation, particularly through the combination of remote sensing and traditional boots-on-the-ground science
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| 650 |
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4 |
|a Journal Article
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| 650 |
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4 |
|a Review
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| 650 |
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4 |
|a GPP
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| 650 |
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4 |
|a arctic
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| 650 |
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4 |
|a boreal
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| 650 |
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4 |
|a forest
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| 650 |
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4 |
|a photosynthesis
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| 650 |
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4 |
|a remote sensing
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| 650 |
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4 |
|a taiga
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| 650 |
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4 |
|a tundra
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| 650 |
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7 |
|a Carbon
|2 NLM
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| 650 |
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7 |
|a 7440-44-0
|2 NLM
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| 700 |
1 |
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|a Serbin, Shawn P
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Way, Danielle A
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t Global change biology
|d 1999
|g 28(2022), 4 vom: 15. Feb., Seite 1222-1247
|w (DE-627)NLM098239996
|x 1365-2486
|7 nnns
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| 773 |
1 |
8 |
|g volume:28
|g year:2022
|g number:4
|g day:15
|g month:02
|g pages:1222-1247
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1111/gcb.15958
|3 Volltext
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