Abstract
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 “significant†is very difficult when survival averages 90% or less. We estimate that about half of regeneration trials (average survival of pines <90%) cannot declare a 12% difference as statistically significant (alpha = 0.05). When researchers realize their tree planting trials have low statistical power, they should consider using more replications. 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.
Highlights
Researchers often fail to reject the null hypothesis, they should never accept a null hypothesis
We examine the impact of replication on the power of establishment trials that report survival
The standard error decreased when doubling replications involved doubling the area planted (Fig. 2) but the standard error increased when doubling replications resulted in smaller experimental units (Fig. 3)
Summary
Researchers often fail to reject the null hypothesis, they should never accept a null hypothesis. In several studies, an examined factor was not significant (α= 0.05) but the treatment increased survival of pine seedlings by at least 20% (Table 1). Could this type of increase be both biologically significant and statistically insignificant? Because of a combination of limited resources and tradition, the design of most seedling survival trials has insufficient replication to detect a “true” 8% difference in survival. This is because most researchers in the southern United States use four replications or less. Installing additional replications will cost more, but it will improve the power of survival tests (i.e. 1 - beta value)
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