A hierarchical, multivariate meta-analysis approach to synthesising global change experiments
© 2021 The Authors New Phytologist © 2021 New Phytologist Foundation.
| Veröffentlicht in: | The New phytologist. - 1979. - 231(2021), 6 vom: 16. Sept., Seite 2382-2394 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2021
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| Zugriff auf das übergeordnete Werk: | The New phytologist |
| Schlagworte: | Journal Article Meta-Analysis Bayesian meta-analysis climate warming elevated CO2 global change experiments hierarchical model incomplete reporting multivariate meta-analysis Soil mehr... |
| Zusammenfassung: | © 2021 The Authors New Phytologist © 2021 New Phytologist Foundation. 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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| Beschreibung: | Date Completed 26.08.2021 Date Revised 26.08.2021 published: Print-Electronic Citation Status MEDLINE |
| ISSN: | 1469-8137 |
| DOI: | 10.1111/nph.17562 |