Using nearest-neighbor designs and analyses in ecological experiments
- Savannah River Ecology Laboratory, Aiken, SC (United States)
Most ecological experiments handle spatial variation either by ignoring it (e.g. completely randomized designs) or by identifying putatively homogeneous areas (e.g. a blocked design). Analysis of data from two experiments, estimating density effects on frog growth and variety differences in yield of triticale, show that there can be large correlations (r = 0.51 and r = 0.72) between residuals on adjacent plots. Nearest-neighbor ANOVA methods use the spatial correlation among residuals to improve the estimation of treatment effects. Incorporating the spatial correlation reduces the variance of treatment effects by 50-75%, depending on the size of the correlation and the arrangement of plots in the field. This decreased variance is equivalent to that from experiments that are 2[times] or 4[times] larger. Potential problems include estimating the spatial correlation, adjusting the error degrees of freedom, and confounding the treatment and spatial effects if there are few replicates. The consequences of these problems will be illustrated.
- OSTI ID:
- 7016915
- Report Number(s):
- CONF-940894-; CODEN: BECLAG
- Journal Information:
- Bulletin of the Ecological Society of America; (United States), Vol. 75:2; Conference: Annual Ecological Society of America (ESA) meeting: science and public policy, Knoxville, TN (United States), 7-11 Aug 1994; ISSN 0012-9623
- Country of Publication:
- United States
- Language:
- English
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