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When it comes to testing for differences in seedling survival, researchers sometimes make a Type II statistical error (i.e. failure to reject a false null hypothesis) due to the inherent variability associated with survival in tree planting studies. For example, in one trial (with five replications) first-year survival of seedlings planted in October (42%) was not significantly different (alpha = 0.05) from those planted in December (69%). Did planting in a dry October truly have no effect on survival? Authors who make a Type II error might not be aware that as seedling survival decreases (down to an overall average of 50% survival), statistical power declines. As a result, the ability to declare an 8% difference as â€œsignificantâ€ is very difficult when survival averages 90% or less.Â  We estimate that about half of regeneration trials (average survival of pines <90%) cannot declare a 12% difference as statistically significant (alpha = 0.05).Â  When researchers realize their tree planting trials have low statistical power, they should consider using more replications.Â  Other ways to increase power include: (1) use a one-tailed test (2) use a potentially more powerful contrast test (instead of an overall treatment F-test) and (3) conduct survival trials under a roof.

Should forest regeneration studies have more replications?