Consider the mechanisms which reduce the number of live seeds.
Hypothesis 1. Soil quality determines what proportion will germinate. Crowding reduces
the share of the available nutrient resources per
seed.
Hypothesis 2. Predation by birds is more likely when the density is higher so that the
seeds are more visible.
Hypothesis 3. Competition with other plants (weeds) determines the survival of the
target seeds.
I see no problem with the descriptive measures proposed, but the experiment should be
tailored to the kinds of alternative hypotheses
entertained.
"Richard M. Barton" wrote:
> A biology student came to me with a data analysis situation that I wasn't sure how
>to deal with. Sound advice would be appreciated.
>
> Scenario:
>
> Ben has a number of 1 meter square plots where he placed one or more seeds:
> 50 plots with 1 seed
> 10 plots with 25 seeds
> 10 plots with 50 seeds
>
> He replicated that design with four species of seeds.
>
> He visited the plots every day for a week to count the number of seeds remaining.
>
> So the questions of interest are:
> a) Does density have an effect on seed survival?
> b) Does species have an effect on survival?
> c) What does the data look like over time?
>
> We considered modelling/analyzing the data in two ways (using SAS):
>
> 1) with seed as the unit of analysis, using Proc Lifetest to generate survival
>curves.
> The problem: for medium and high density plots, seeds would not seem to be
> independent.
>
> 2) with plot as the unit of analysis, using GLM to get a mixed model, where
> time is a repeated measure and density and species are between groups factors.
> Problem: low density (1 seed) plots have a dichotomous outcome, so much
> of the data is non-normal.
>
> Any suggestions? Thanks.
>
> rick barton
>
>
