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Importance of Meta-analysis in Studies Involving Plant Responses to Climate Change in Brazil

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Advances in Bioinformatics and Computational Biology (BSB 2020)

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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References

  1. Aguiar, S., Santos, I.D.S., Arêdes, N., Silva, S.: Redes-bioma: Informação e comunicação para ação sociopolítica em ecorregiões. Ambiente Soc. 19(3), 233–252 (2016)

    Google Scholar 

  2. Ainsworth, E.A., Long, S.P.: What have we learned from 15 years of free-air co2 enrichment (face)? a meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising co2. New Phytol. 165(2), 351–372 (2005). https://doi.org/10.1111/j.1469-8137.2004.01224.x

    Article  PubMed  Google Scholar 

  3. Arenque, B.C., Grandis, A., Pocius, O., de Souza, A.P., Buckeridge, M.S.: Responses of Senna reticulata, a legume tree from the amazonian floodplains, to elevated atmospheric CO\({}_2\) concentration and waterlogging. Trees 28(4), 1021–1034 (2014). https://doi.org/10.1007/s00468-014-1015-0

    Article  CAS  Google Scholar 

  4. Cleveland, C.C., et al.: Relationships among net primary productivity, nutrients and climate in tropical rain forest: a pan-tropical analysis. Ecol. Lett. 14(9), 939–947 (2011). https://doi.org/10.1111/j.1461-0248.2011.01658.x

    Article  PubMed  Google Scholar 

  5. Cook, T.D.: The potential and limitations of secondary evaluations. In: Analysis and Responsibility, Educational Evaluation (1974)

    Google Scholar 

  6. Curtis, P.S., Wang, X.: A meta-analysis of elevated CO\(_2\) effects on woody plant mass, form, and physiology. Oecologia 113(3), 299–313 (1998). https://doi.org/10.1007/s004420050381

    Article  PubMed  Google Scholar 

  7. Curtis, P.: A meta-analysis of leaf gas exchange and nitrogen in trees grown under elevated carbon dioxide. Plant, Cell Environ. 19(2), 127–137 (1996). https://doi.org/10.1111/j.1365-3040.1996.tb00234.x

    Article  Google Scholar 

  8. De Souza, A.P., et al.: Elevated CO\({}_2\) increases photosynthesis, biomass and productivity, and modifies gene expression in sugarcane. Plant, Cell Environ. 31(8), 1116–1127 (2008). https://doi.org/10.1111/j.1365-3040.2008.01822.x

    Article  CAS  Google Scholar 

  9. Egger, M., Smith, G.D., Schneider, M., Minder, C.: Bias in meta-analysis detected by a simple, graphical test. Bmj 315(7109), 629–634 (1997). https://doi.org/10.1136/bmj.315.7109.629

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Glass, G.V.: Primary, secondary, and meta-analysis of research. Educ. Res. 5(10), 3–8 (1976). https://doi.org/10.3102/0013189X005010003

    Article  Google Scholar 

  11. Gurevitch, J., Koricheva, J., Nakagawa, S., Stewart, G.: Meta-analysis and the science of research synthesis. Nature 555(7695), 175–182 (2018). https://doi.org/10.1038/nature25753

    Article  CAS  PubMed  Google Scholar 

  12. Harrison, F.: Getting started with meta-analysis. Methods Ecol. Evol. 2(1), 1–10 (2011). https://doi.org/10.1111/j.2041-210X.2010.00056.x

    Article  Google Scholar 

  13. Haworth, M., Hoshika, Y., Killi, D.: Has the impact of rising CO\({}_2\) on plants been exaggerated by meta-analysis of free air CO\({}_2\) enrichment studies? Front. Plant Sci. 7, 1153 (2016). https://doi.org/10.3389/fpls.2016.01153

    Article  PubMed  PubMed Central  Google Scholar 

  14. Hedges, L.V., Gurevitch, J., Curtis, P.S.: The meta-analysis of response ratios in experimental ecology. Ecology 80(4), 1150–1156 (1999). https://doi.org/10.1890/0012-9658(1999)080[1150:TMAORR]2.0.CO;2

    Article  Google Scholar 

  15. Hedges, L.V., Pigott, T.D.: The power of statistical tests for moderators in meta-analysis. Psychol. Methods 9(4), 426 (2004). https://doi.org/10.1037/1082-989X.9.4.426

    Article  PubMed  Google Scholar 

  16. IPCC: Climate change: The ipcc 1990 and 1992 assessments (1990). https://www.ipcc.ch/report/climate-change-the-ipcc-1990-and-1992-assessments/. Accessed 25 Aug 2020

  17. IPCC: Sar climate change 1995: Synthesis report (1995). https://www.ipcc.ch/site/assets/uploads/2018/05/2nd-assessment-en-1.pdf. Accessed 25 Aug 2020

  18. IPCC: Tar climate change 2001: Synthesis report (2001). https://www.ipcc.ch/report/ar3/syr/. Accessed 25 Aug 2020

  19. IPCC: Ar4 climate change 2007: Synthesis report (2007). https://www.ipcc.ch/report/ar4/syr/. Accessed 25 Aug 2020

  20. IPCC: Global warming of 1.5 \(^\circ \)c: Special report (2018). https://www.ipcc.ch/sr15/. Accessed 25 Aug 2020

  21. Jones, A.G., Scullion, J., Ostle, N., Levy, P.E., Gwynn-Jones, D.: Completing the face of elevated CO\({}_2\) research. Environ. Int. 73, 252–258 (2014). https://doi.org/10.1016/j.envint.2014.07.021

    Article  CAS  PubMed  Google Scholar 

  22. Koricheva, J., Gurevitch, J., Mengersen, K.: Handbook of meta-analysis in ecology and evolution. Princeton University Press, New Jersey (2013)

    Book  Google Scholar 

  23. Körner, C.: Plant CO\({}_2\) responses: an issue of definition, time and resource supply. New Phytol. 172(3), 393–411 (2006). https://doi.org/10.1111/j.1469-8137.2006.01886.x

    Article  CAS  PubMed  Google Scholar 

  24. Körner, C.: Responses of humid tropical trees to rising CO\({}_2\). Annu. Rev. Ecol. Evol. Syst. 40, 61–79 (2009). https://doi.org/10.1146/annurev.ecolsys.110308.120217

    Article  Google Scholar 

  25. Lambers, H., Chapin III, F.S., Pons, T.L.: Plant Physiological Ecology. Springer, New York (2008)

    Book  Google Scholar 

  26. Leakey, A.D., et al.: Photosynthesis, productivity, and yield of maize are not affected by open-air elevation of CO\({}_2\) concentration in the absence of drought. Plant Physiol. 140(2), 779–790 (2006). https://doi.org/10.1104/pp.105.073957

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lei, X., Peng, C., Tian, D., Sun, J.: Meta-analysis and its application in global change research. Chin. Sci. Bull. 52(3), 289–302 (2007). https://doi.org/10.1007/s11434-007-0046-y

    Article  CAS  Google Scholar 

  28. Liberati, A., et al.: The Prisma statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J. Clin. Epidemiol. 62(10), e1–e34 (2009). https://doi.org/10.1016/j.jclinepi.2009.06.006

    Article  PubMed  Google Scholar 

  29. Lovejoy, T.E., Nobre, C.: Amazon tipping point: last chance for action (2019). https://doi.org/10.1126/sciadv.aba2949

  30. Luo, Y., Hui, D., Zhang, D.: Elevated CO\({}_2\) stimulates net accumulations of carbon and nitrogen in land ecosystems: a meta-analysis. Ecology 87(1), 53–63 (2006). https://doi.org/10.1890/04-1724

    Article  PubMed  Google Scholar 

  31. Moles, A.T., et al.: Which is a better predictor of plant traits: temperature or precipitation? J. Veg. Sci. 25(5), 1167–1180 (2014). https://doi.org/10.1111/jvs.12190

    Article  Google Scholar 

  32. MRE: Ministério das relações exteriores do brasil (2019). http://www.itamaraty.gov.br/pt-BR. Accessed 25 Aug 2020

  33. Nakagawa, S., Noble, D.W., Senior, A.M., Lagisz, M.: Meta-evaluation of meta-analysis: ten appraisal questions for biologists. BMC biology 15(1), 1–14 (2017). https://doi.org/10.1186/s12915-017-0357-7

    Article  Google Scholar 

  34. Nakagawa, S., et al.: Research weaving: visualizing the future of research synthesis. Trends Ecol. Evol. 34(3), 224–238 (2019). https://doi.org/10.1016/j.tree.2018.11.007

    Article  PubMed  Google Scholar 

  35. Palacios, C., Grandis, A., Carvalho, V., Salatino, A., Buckeridge, M.: Isolated and combined effects of elevated CO\({}_2\) and high temperature on the whole-plant biomass and the chemical composition of soybean seeds. Food Chem. 275, 610–617 (2019). https://doi.org/10.1016/j.foodchem.2018.09.052

    Article  CAS  PubMed  Google Scholar 

  36. Quintana, D.S.: From pre-registration to publication: a non-technical primer for conducting a meta-analysis to synthesize correlational data. Front. Psychol. 6, 1549 (2015). https://doi.org/10.3389/fpsyg.2015.01549

    Article  PubMed  PubMed Central  Google Scholar 

  37. Ribeiro, W.C.: A ordem ambiental internacional. Editora Contexto (2001)

    Google Scholar 

  38. Ruddiman, W.F.: The anthropogenic greenhouse era began thousands of years ago. Climatic Change 61(3), 261–293 (2003). https://doi.org/10.1023/B:CLIM.0000004577.17928.fa

    Article  CAS  Google Scholar 

  39. Sterne, J.A., Egger, M.: Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J. Clin. Epidemiol. 54(10), 1046–1055 (2001). https://doi.org/10.1016/S0895-4356(01)00377-8

    Article  CAS  PubMed  Google Scholar 

  40. Stevens, N., Lehmann, C.E., Murphy, B.P., Durigan, G.: Savanna woody encroachment is widespread across three continents. Glob. Change Biol. 23(1), 235–244 (2017). https://doi.org/10.1111/gcb.13409

    Article  Google Scholar 

  41. Sutton, A.J., Higgins, J.P.: Recent developments in meta-analysis. Stat. Med. 27(5), 625–650 (2008). https://doi.org/10.1002/sim.2934

    Article  PubMed  Google Scholar 

  42. Team, R.C., et al.: R: A language and environment for statistical computing (2013)

    Google Scholar 

  43. UNFCCC: Kyoto protocol to the united nations framework convention on climatechange (1997). http://unfccc.int/resource/docs/convkp/kpeng.pdf. Accessed 25 Aug 2020

  44. UNFCCC: Statements on behalf of the group of g77 and china (2009). https://unfccc.int/resource/docs/2009/cop15/eng/11a01.pdf. Accessed 25 Aug 2020

  45. UNFCCC: Adoption of the paris agreement. united nations framework convention on climate change (2015). http://unfccc.int/paris_agreement/items/9485.php. Accessed 25 Aug 2020

  46. Viechtbauer, W.: Conducting meta-analyses in r with the metafor package. J. Stat. Softw. 36(3), 1–48 (2010). https://doi.org/10.18637/jss.v036.i03

  47. Wand, S.J., Midgley, G.F., Jones, M.H., Curtis, P.S.: Responses of wild c4 and c3 grass (poaceae) species to elevated atmospheric CO\({}_2\) concentration: a meta-analytic test of current theories and perceptions. Glob. Change Biol. 5(6), 723–741 (1999). https://doi.org/10.1046/j.1365-2486.1999.00265.x

    Article  Google Scholar 

  48. Wickham, H.: Elegant Graphics for Data Analysis (ggplot2). Springer, New York (2009)

    Google Scholar 

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Correspondence to Marcos Silveira Buckeridge .

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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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  • DOI: https://doi.org/10.1007/978-3-030-65775-8_21

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