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The effect of stand age on the statistical power for detecting a 1-year advance in stand development. A statistical power of 0.3 indicates there is a 70 percent chance of making a Type II error (α = 0.05).
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The initial effects of a silvicultural treatment on height or volume growth sometimes decline over time, and the early gains eventually disappear with very long rotations. However, in some reports initial gains are maintained until harvest
but due to statistical analyses, a researcher might conclude the treatment effect has “washed-out” by ages 10...
Context in source publication
Context 1
... our example, statistical power remained high for at least 8 years. The power (i.e., ability to detect a 1-year difference in stand development) dropped below 0.5 around ages 13 to 16 for basal area and volume, respectively ( fig. 6). Therefore, the ranking of growth variables in terms of relative power will vary with species, genotype ( Burr and Tinus 1996), study (VanderSchaaf and others 2003), and response variable (South and others ...
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Citations
... While treatment effect differences diminished over the 11-year duration of this study and analysis did not detect significant differences among treatments for Nuttall oak and swamp chestnut oak, it does not necessarily mean that those effects disappeared, but that they were not detected. Variation increases in biological studies over time, thus lessening the power of an analysis while potentially masking continued treatment effects [31,32]. It is likely that separation may occur in a test with more statistical power, but mechanical treatment averages for swamp chestnut oak DBH were not significantly different. ...
Mechanical site preparation is often prescribed as a tool for correcting soil condition problems encountered when planting former agricultural fields. While the impact of mechanical site preparation on early growth and survival of young oak seedlings is well-known, there is a shortage of information regarding the longer-term effects of these treatments. Four hundred and eighty, 1-0 bare-root seedlings each of Nuttall oak (Quercus texana Buckley), Shumard oak (Quercus shumardii Buckley), and swamp chestnut oak (Quercus michauxii Nutt.) seedlings were planted in February 2008 on a retired agricultural site in northwest Mississippi. Four site preparation treatments were utilized, with 160 seedlings of each species per species/mechanical treatment combination, totaling 1440 seedlings for the study. Mechanical site preparation included control, subsoiling, bedding, and combination plowing treatments applied on 3.1 m row centers. Eleven-year diameter (DBH), total height growth (HT), height-to-live crown (HTLC), and survival data were recorded in early 2019. Treatment effects were analyzed, and significant differences were not detected for tree survival. However, differences were observed in the DBH, HT, and HTLC averages of swamp chestnut oak and the DBH of Shumard oak.
... We and others have pointed out the importance of replications in both nursery (VanderSchaaf et al. 2003) and field trials (Zedeker et al. 1993;Foster 2001). In a previous paper, we examined the decline in power as plantations get older and increase in biomass (South and VanderSchaaf 2006). In this paper, we examine the impact of replication on the (a priori) power of establishment trials that report survival. ...
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.
