Data from: Informative plot sizes in presence-absence sampling of forest floor vegetation

1. Plant communities are attracting increased interest in connection with
forest and landscape inventories due to society’s interest in ecosystem
services. However, the acquisition of accurate information about plant
communities poses several methodological challenges. Here we investigate
the use of presence-absence sampling with the aim to monitor state and
change of plant density. We study what plot sizes are informative, i.e.
the estimators should have as high precision as possible. 2. Plant
occurrences were modeled through different Poisson processes and tests
were developed for assessing the plausibility of the model assumptions.
Optimum plot sizes were determined by minimizing the variance of the
estimators. While state estimators of similar kind as ours have been
proposed in previous studies, our tests and change estimation procedures
are new. 3. We found that the most informative plot size for state
estimation is 1.6 divided by the plant density, i.e. if the true density
is 1 plant per square meter the optimum plot size is 1.6 square meters.
This is in accordance with previous findings. More importantly, the most
informative plot size for change estimation was smaller and depended on
the change patterns. We provide theoretical results as well as some
empirical results based on data from the Swedish National Forest
Inventory. 4. Use of too small or too large plots resulted in poor
precision of the density (and density change) estimators. As a
consequence, a range of different plot sizes would be required for jointly
monitoring both common and rare plants using presence-absence sampling in
monitoring programmes.