# Why big square vegetation plots

## Found at: republic.circumlunar.space:70/~johngodlee/posts/2021-12-10-big_plots.txt

```TITLE: Why big square vegetation plots are best
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```DATE: 2021-12-10
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```AUTHOR: John L. Godlee
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```====================================================================
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```I had to write an email recently to persuade someone that using
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```bigger permanent vegetation survey plots in savannas was better
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```than small plots. In our field of research one of the basic field
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```measurements we do is to demarcate an area of savanna, tag all the
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```tree stems gt5 cm diameter, and then return every few years to
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```track growth and mortality of those trees.
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```The reasons for constructing small plots are mostly practical.
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```Small circular plots are very quick to set up, with a single metal
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```pole sunk into the ground at the centre of the plot. Then it's just
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```a case of running a tape measure out to the required radius and
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```moving round with the tape measure measuring all the trees that are
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```within the radius. It's also fairly easy this way to determine the
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```spatial distribution of tree stems by using a distance and compass
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```angle coordinate system. Big plots on the other hand are quite slow
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```to set up, because the trees get in the way of the tape measures,
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```and there's more chance of the tape measure drifting, which is
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```especially problematic for square/rectangular plots where the
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```corners have to be at 90 degrees. After a plot gets to be more than
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```about 25 m in radius, I would advocate for square plots instead, as
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```it actually becomes easier to set them up as squares at this size.
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```The problem is that small plots can leaf to un-representative
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```estimates of the biomass and species diversity of the landscape
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```they are sampling.
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```Measuring competition effects: There’s been some work in our
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```group on miombo woodland plots in Tanzania which suggests that
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```tree-tree competition is an important determinant of tree growth,
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```and that this competition effect peaks at about ~10-15 m radius
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```from the focal tree, on average. In the case of a small plot (e.g.
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```20 m radius circle), you will only really be able to understand
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```competition effects for a few individuals right at the centre of
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```the plot. I’m particularly interested in spatial distribution of
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```trees, and it’s something I would like SEOSAW to do more of. But
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```we can’t do that with small plots.
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```  [SEOSAW]: https://seosaw.github.io/
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```Edge effects and the representative-ness of biomass estimates: The
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```woody biomass per area estimates from small plots are much more
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```influenced by the presence or absence of large trees than larger
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```plots. To gather a representative estimate of the biomass per area
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```of a landscape, it can actually require greater effort per unit
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```area sampled to set up many small plots, than fewer big plots, as
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```you need to sample less area overall from big plots. Additionally,
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```edge effects are magnified when measuring smaller plots, as the
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```perimeter:area ratio doesn't scale geometrically, thus subjective
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```decisions about whether a tree/stem is inside or outside a plot are
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```more influential on plot level estimates of abundance, diversity,
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```and biomass. Finally, from personal experience there is more chance
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```that small plots will be opportunistically sited to include or
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```exclude certain features of the woodland, like a thicket area, or
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```large impressive trees, introducing bias when estimating landscape
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```processes. So, replication is not such an issue as compared to
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```sampling a few representative plots.
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```Matching with satellite data: In our lab group there are people
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```working on estimating biomass from L-band radar backscatter
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```relationships. Small plots are much worse for matching with these
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```remotely sensed data. A previous PhD student found that the R^2 of
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```the biomass estimation uncertainty peaked at about 1 ha (100x100
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```m), and was almost zero for plots lt0.2 ha (lt~25m radius circle).
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```You just can’t fit as many data points in a smaller plot. These
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```papers highlight similar issues. https://doi.org/10.3390/rs5031001,
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```https://doi.org/10.3390/rs10101586.
```