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    Statistical meta-analysis is a powerful and useful tool to quantitatively synthesize the information conveyed in published studies on a particular topic. It allows identifying and quantifying overall patterns and exploring causes of variation. The inclusion of published works in meta-analyses requires, however, a minimum quality standard of the reported data and information on the methodology used. Our experience with conducting a meta-analysis on the relationship between seedling quality and field performance is that nearly one third of the apparently relevant publications had to be discarded because essential data, usually statistical dispersion parameters, were not properly reported. In addition, we encountered substantial difficulty to explore the effect of covariates due to the poor description of nursery cultivation methods, plantation location, and management in a significant proportion of the selected primary studies. Thus, we present guidelines for improving methodology detail and data presentation so that future forest restoration-oriented research can be more readily incorporated into meta-analyses. In general, research studies should report data on means, sample size, and any measure of variation even if they are not statistically significant. The online availability of raw data is the best practice to facilitate the inclusion of primary research on meta-analyses. Providing full information about the production of nursery seedlings, such as plant material and experimental conditions, is essential to test whether these procedures might have an effect on seedling quality. In addition, detailed information about field trials such as site climate, soil preparation techniques, previous land use, or post-plantation management, is needed to elucidate whether seedling quality is context-dependent. Thus, we provide a detailed checklist of important information that should be included when reporting forest restoration research involving the use of nursery-produced seedlings. All this will help to quantitatively synthetize current state-of-knowledge and thus contribute to the advancement of the forest restoration discipline.

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    Andivia, Enrique; Villar‑Salvador, Pedro; Oliet, Juan A.; Puertolas, Jaime; Dumroese, R. Kasten. 2019. How can my research paper be useful for future meta-analyses on forest restoration practices? New Forests 50: 255-266.


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    data quality, data reporting, meta-analysis, methodology guideline, seedling quality, research synthesis

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