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| accum | Split a dataframe column with binomial name into genus and species columns. Plots change in species richness over time, generates species accumulation curve, and compares SAC against simulated idealized curve assuming all unique taxa have equal probability of being sampled at any point in the time series. (author Dietmar Straile) |
| algae_search | Compare a genus and species name against the algaebase online database |
| bestmatch | fuzzy partial matching between a scientific name and a list of possible matches |
| date_mat | Transform a phytoplankton timeseries into a matrix of abundances for ordination |
| genus_species_extract | Split a dataframe column with binomial name into genus and species columns. |
| lakegeneva | example dataset from lake Geneva, Switzerland |
| mean_naomit | Compute mean value while ignoring NA's |
| phyto_ts_aggregate | Aggregate phytoplankton timeseries based on abundance. Up to 3 grouping variables can be given: e.g. genus, species, stationid, depth range. If no abundance var is given, will aggregate to presence/absence of grouping vars. |
| sampeff | Visually assess change in sampling effort over time (author: Dietmar Straile) |
| spp_list_algaebase | Wrapper for applying algae_search function to a data.frame that contains phytoplankton species |
| traitranges | surface/volume ratio and max linear dimension criteria for CSR From Reynolds 1988 and Reynolds 2006 |
| traits_to_csr | Assign phytoplankton species to CSR functional groups, based on surface to volume ratio and maximum linear dimension ranges proposed by Reynolds et al. 1988;2006 |
| traits_to_csr_df | Add CSR functional group classifications to a dataframe of phytoplankton species, based on surface to volume ratio and maximum linear dimension ranges proposed by Reynolds et al. 1988;2006 |
| traits_to_mfg | Assign MFG based on binary functional traits and taxonomy (Class and Order) |
| traits_to_mfg_df | Assign morphofunctional groups to a dataframe of functional traits and higher taxonomy |