Abstract
Meta-analysis synthesizes individual research results on the same subject and provides information that indicates bottlenecks in research. Due to the massive production of data, integrative analyzes are necessary, presenting more consistent views of biological phenomena. Broad themes such as plants’ response to climate change have been the subject of meta-analyses since 1996, as there is a global concern about the effect of elevated CO\(_{2}\) on plants and forests. We propose using meta-analysis to compile existing data, including studies related to the effects of high CO\(_{2}\) on Brazilian biomes’ vegetation. For that, we found 36 articles on the theme after a systematic review. Physiological parameters such as photosynthesis, leaf area, and non-structural carbohydrates are essential to understand the plant’s responses to elevated CO\(_{2}\) using meta-analysis. However, these parameters are not present in a considerable portion of the literature, decreasing the statistical power of meta-analytical strategies. The meta-analysis of plants’ biological responses is usually performed with several species, although there are also studies with single species. The use of many species increases the variance of the effects, highlighting the need for multilevel modeling to consider the dependence among data on the same species. We discuss how to carry out studies considering the variables needed in future meta-analyses to contribute to better data integration relevant to national reports. In this way, we expect that meta-analytical strategies could be essential for national decision-making and complement global analyses such as those made by the IPCC.
Supported by Capes. Fellowship: 88882.461730/2019-01.
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Fortirer, J.d.S., Grandis, A., de Toledo Castanho, C., Buckeridge, M.S. (2020). Importance of Meta-analysis in Studies Involving Plant Responses to Climate Change in Brazil. In: Setubal, J.C., Silva, W.M. (eds) Advances in Bioinformatics and Computational Biology. BSB 2020. Lecture Notes in Computer Science(), vol 12558. Springer, Cham. https://doi.org/10.1007/978-3-030-65775-8_21
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