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A multi-scale sampling design, based on a restricted random selection of plots, was used to get information about vascular plants, bryophytes, lichens, fungi, oligochaetes, butterflies and birds.
Figure 1 shows a selection of plots produced by viRome.
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Moreover, we evaluated the effect of plot orientation along the main environmental gradient, to examine how the selection of plot orientation (when elongated plots are used) influences the number of species collected.
Selection of sampling plots targeted areas that were currently used for grazing.
In addition, selection of the plots had subjective elements and measurement of the stand characteristics was not accurate enough for growth modeling purposes.
The performance of the Bertalanffy-Richards models were next tested in various ways against the validation dataset which consisted of a random selection of 702 plots (19%) out of the original dataset.
Furthermore, the accuracy of the estimation can be improved by adopting appropriate techniques in both the design and estimation phases, beginning with the selection of sample plots and sample trees through model development.
Additionally, Figures 2 and 3 shows a selection of the plots resulting from the fitting of the data to the different kinetic models, so that the quality of the fit is clearly illustrated.
Our approach involved: (i) the random selection of x plots from the full field dataset; (ii) fitting a linear regression between wood volume and LiDAR metric; (iii) repeating steps i and ii y times and quantifying the distribution of the regression outputs.
A selection of the plots with the trendlines is shown in Fig. 6 and 7 corresponding to the sequences shown in the previous two figures.
The basic idea of this approach is to use the ALS metric to guide the selection of field plot locations (Pesonen et al. 2010a, b).
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CEO of Professional Science Editing for Scientists @ prosciediting.com