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231225s2021 xx |||||o 00| ||eng c |
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|a 10.1111/nph.17562
|2 doi
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|a pubmed24n1089.xml
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|a eng
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| 100 |
1 |
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|a Ogle, Kiona
|e verfasserin
|4 aut
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| 245 |
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|a A hierarchical, multivariate meta-analysis approach to synthesising global change experiments
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|c 2021
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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 26.08.2021
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|a Date Revised 26.08.2021
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2021 The Authors New Phytologist © 2021 New Phytologist Foundation.
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|a Meta-analyses enable synthesis of results from globally distributed experiments to draw general conclusions about the impacts of global change factors on ecosystem function. Traditional meta-analyses, however, are challenged by the complexity and diversity of experimental results. We illustrate how several key issues can be addressed by a multivariate, hierarchical Bayesian meta-analysis (MHBM) approach applied to information extracted from published studies. We applied an MHBM to log-response ratios for aboveground biomass (AB, n = 300), belowground biomass (BB, n = 205) and soil CO2 exchange (SCE, n = 544), representing 100 studies. The MHBM accounted for study duration, climate effects and covariation among the AB, BB and SCE responses to elevated CO2 (eCO2 ) and/or warming. The MHBM revealed significant among-study covariation in the AB and BB responses to experimental treatments. The MHBM imputed missing duration (4.2%) and climate (6%) data, and revealed that climate context governs how eCO2 and warming impact ecosystem function. Predictions identified biomes that may be particularly sensitive to eCO2 or warming, but that are under-represented in global change experiments. The MHBM approach offers a flexible and powerful tool for synthesising disparate experimental results reported across multiple studies, sites and response variables
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|a Journal Article
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|a Meta-Analysis
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|a Bayesian meta-analysis
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| 650 |
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|a climate warming
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| 650 |
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4 |
|a elevated CO2
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| 650 |
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4 |
|a global change experiments
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| 650 |
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|a hierarchical model
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| 650 |
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4 |
|a incomplete reporting
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| 650 |
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4 |
|a multivariate meta-analysis
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| 650 |
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7 |
|a Soil
|2 NLM
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| 650 |
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7 |
|a Carbon Dioxide
|2 NLM
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| 650 |
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7 |
|a 142M471B3J
|2 NLM
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| 700 |
1 |
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|a Liu, Yao
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Vicca, Sara
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Bahn, Michael
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t The New phytologist
|d 1979
|g 231(2021), 6 vom: 16. Sept., Seite 2382-2394
|w (DE-627)NLM09818248X
|x 1469-8137
|7 nnns
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| 773 |
1 |
8 |
|g volume:231
|g year:2021
|g number:6
|g day:16
|g month:09
|g pages:2382-2394
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| 856 |
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|u http://dx.doi.org/10.1111/nph.17562
|3 Volltext
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