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Environmental attributes were extracted for each plot from global datasets.
Precipitation, mean annual temperature, winter minimum temperature and vapour pressure deficit were estimated for each plot from thin-plate splines fitted to meteorological data collected at local climate stations (Leathwick et al. [2002]).
We then subtracted the observed proportions for each plot from the mean proportion expected by chance, calculated by averaging the proportions in 1000 replications.
In Figure 4B F, the number of loci is doubled for each plot from panel B to panel F. Our estimate of FST is equal to 0.54 in C. rubella.
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This framework allowed the gorge plots to be assigned to pre-existing vegetation alliances or associations based on their compositional distance (calculated using the importance values for each species on each plot) from the cluster centroids (in the space of the Chord distance) of these alliances or associations.
The FIA class assignment for each plot came directly from the FIA database.
Stand age for each plot was obtained from the stand GIS data.
Then, AGB of average tree (kg) for each plot was calculated from stand AGB (Mg ha−1) and stand density.
The silvicultural history and stand age for each plot was extracted from the stand records maintained by the forest manager.
For each plot, signal was sorted from highest to lowest intensity, and plotted as a solid line.
Submodels 5 and 6 were used to predict BA and ρ from TCH for each plot (i.e. (widehat {BA}, widehat {rho })), and these predictions entered into Eq. 4 to predict ACD.
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