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Why do most vegetation monitoring programs rely on permanent plots?

Take the context of a single ecological restoration site, for example. Let's say the variable of interest is cover by plant species, and monitoring is conducted throughout several seasons to track the relative/total cover of multiple species.

If plots are randomly sampled within homogeneous vegetation assemblages, why not just establish new plots each sampling period, rather than locating and re-sampling the same plots over and over again?

If the goal of sampling the is to represent characteristics of the population (i.e. the homogeneous area of vegetation), then why do researchers always sample permanent monitoring plots again and again rather than using a new set of randomly selected plots each time?

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  • $\begingroup$ Are you asking in the context of a single longitudinal study using particular plots, or in the context of multiple separate studies over time? $\endgroup$ – Bryan Krause Jun 10 at 20:46
  • $\begingroup$ A single study area. I will edit my question to be more clear. $\endgroup$ – eyerah Jun 10 at 21:49
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The answer boils down to statistics rather than anything particular about this type of experiment.

If you have a sample of plots, and then take repeated measurements in that same sample over time, the variance in the values you record is a function of the variance of the time-dependent process causing changes.

If you take future measurements from a new sample of plots, you have additional variance to account for due to choosing a new sample. That is, even if you would have measured no change at all in the same plots, you expect the second sample will be different from the first just because of sampling. Because of this additional variance, you have less ability to detect smaller changes over time: less statistical power.

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