Seed dormancy models suggest that evaluation of environmental conditions should influence the decision to germinate and that waiting for more favourable conditions may increase potential fitness. However, because rapid emergence is often positively correlated with performance and survival, an alternative strategy to accelerate the rate of emergence may increase the potential for site pre-emption. This response is more likely to be found in seasonal environments with greater potential for rapid resource depletion in which early emergence may confer a competitive advantage. The experiments reported here found more rapid emergence in a perennial grass species when it was planted in potentially highly competitive interspecific neighbourhoods. This response suggests an inherent ability in seeds of this species to sense and respond to the competitive nature of the immediate neighbourhood.
A procedure is presented for constructing an exact confidence interval for the ratio of the two variance components in a possibly unbalanced mixed linear model that contains a single set of m random effects. This procedure can be used in animal and plant breeding problems to obtain an exact confidence interval for a heritability. The confidence interval can be defined in terms of the output of a least squares analysis. It can be computed by a graphical or iterative technique requiring the diagonalization of an m X m matrix or, alternatively, the inversion of a number of m X m matrices. Confidence intervals that are approximate can be obtained with much less computational burden, using either of two approaches. The various confidence interval procedures can be extended to some problems in which the mixed linear model contains more than one set of random effects. Corresponding to each interval procedure is a significance test and one or more estimators.
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