Christensen et al. criticized the application of Beals' index of sociological favourability to adjust for incomplete species lists when comparing repeated surveys. Their main argument was that using Beals' conditional occurrence probabilities would systematically underestimate biodiversity change compared to using observed frequencies. Although this might be the case for rare species, as we explicitly stated in our original publication, we here use a worked-out example to show that this criticism is unjustified for species that are sufficiently represented in the reference data set. In our opinion, the misconception derives from ignoring one of the key requirements for applying Beal's index, which is the use of a sufficiently large reference data set to derive a reliable co-occurrence matrix. We here show how the predicted probability for the occurrence of a species depends on the size of the reference data set and give recommendations on the premises for applying Beals' approach for monitoring purposes.
Bruelheide, H., Jansen, F., Jandt, U., Bernhardt-Romermann, M., Bonn, A., Bowler, D., et al. (2021). A checklist for using Beals' index with incomplete floristic monitoring data Reply to Christensen et al. (2021): Problems in using Beals' index to detect species trends in incomplete floristic monitoring data. DIVERSITY AND DISTRIBUTIONS, 27(7), 1328-1333 [10.1111/ddi.13277].
A checklist for using Beals' index with incomplete floristic monitoring data Reply to Christensen et al. (2021): Problems in using Beals' index to detect species trends in incomplete floristic monitoring data
Sabatini, FM;
2021
Abstract
Christensen et al. criticized the application of Beals' index of sociological favourability to adjust for incomplete species lists when comparing repeated surveys. Their main argument was that using Beals' conditional occurrence probabilities would systematically underestimate biodiversity change compared to using observed frequencies. Although this might be the case for rare species, as we explicitly stated in our original publication, we here use a worked-out example to show that this criticism is unjustified for species that are sufficiently represented in the reference data set. In our opinion, the misconception derives from ignoring one of the key requirements for applying Beal's index, which is the use of a sufficiently large reference data set to derive a reliable co-occurrence matrix. We here show how the predicted probability for the occurrence of a species depends on the size of the reference data set and give recommendations on the premises for applying Beals' approach for monitoring purposes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.