Rocchini, D., Luque, S., Pettorelli, N., Bastin, L., Doktor, D., Faedi, N., Feilhauer, H., Feret, J.-B., Foody, G.M., Gavish, Y., Godinho, S., Kunin, W.E., Lausch, A., Leitao, P.J., Marcantonio, M., Neteler, M., Ricotta, C., Schmidtlein, S., Vihervaara, P., Wegmann, M., Nagendra, H. (2018). Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring. Methods in Ecology and Evolution, 9: 1787-1798. https://doi.org/10.1111/2041-210X.12941
Fact: One of the mostly used methods to infer biodiversity is based on taxonomic approaches and community ecology theories. However, gathering extensive data in the field is
difficult due to logistic problems, especially when aiming at modelling biodiversity changes in space and time, which assumes statistically sound sampling schemes.
Solution: Extending on previous work, in this manuscript, Rochcini et al.(2018) review and propose new approaches for estimating beta-diversity from airborne or satellite remote sensing, passing from multivariate statistical analysis to the spectral species concept, to self-organizing
feature maps, and multidimensional distance matrices coupled with the Rao’s Q diversity.
Outreach: Each of these measures addresses one or several issues related to turnover measurement. This manuscript is the first methodological example encompassing (and enhancing) most of the available methods for estimating beta-diversity from remotely sensed imagery and potentially relating them to species diversity in the field.