All R functions here listed are described in detail and available at https://github.com/lgcarvalheiro/
Richness change calculations based on historical datasets
Estimates of species richness change based on historical records require a methodology that corrects for the effects of sampling effort (e.g. number of records per grid cell and time period), as well as bias associated with collectors (e.g. preference for rare species, under-representation of singletons due to efforts to capture differences due to sexual dimorphism).
Functions:
Multilevel.RAR_EXTR.r - allows to obtain estimates of richness based on species accumulation curves (providing estimates of expected richness with increasing number of records) using 3 approaches: (1) only interpolation, (2) only extrapolation, and (3) combination of extrapolation and interpolation.
Trend.extractorV3 - For datasets where richness change estimates are done for multiple geographical regions,‘Trend.extractor’ allows to check if accumulation curve estimations did completely remove the bias due to sampling effort.
Beta-diversity calculations based on historical datasets
C19