Package: algaeClassify 2.0.2

algaeClassify: Tools to Standardize Phytoplankton Taxonomic Data and Perform Functional Group Classifications

Functions that facilitate the use of accepted taxonomic nomenclature, collection of functional trait data, and assignment of functional group classifications to phytoplankton species. Possible classifications include Morpho-functional group (MFG; Salmaso et al. 2015 <doi:10.1111/fwb.12520>) and CSR (Reynolds 1988; Functional morphology and the adaptive strategies of phytoplankton. In C.D. Sandgren (ed). Growth and reproductive strategies of freshwater phytoplankton, 388-433. Cambridge University Press, New York). Versions 2.0.0 and later includes new functions for querying the algaebase online taxonomic database (www.algaebase.org), however these functions require a valid API key that must be acquired from the algaebase admin. Note that none of the algaeClassify authors are affiliated with algaebase in any way. Taxonomic names can also be checked against a variety of taxonomic databases using the geographic name resolution service (GNRS) via wrapper functions for the taxize package, with convenient output format and unlikely names for phytoplankton taxa removed. In addition, currently accepted and outdated synonyms, and higher taxonomy, can be extracted for lists of species from the ITIS database using wrapper functions for the ritis package. The algaeClassify package is a product of the GEISHA (Global Evaluation of the Impacts of Storms on freshwater Habitat and Structure of phytoplankton Assemblages), funded by CESAB (Centre for Synthesis and Analysis of Biodiversity) and the USGS John Wesley Powell Center for Synthesis and Analysis, with data and other support provided by members of GLEON (Global Lake Ecology Observation Network). DISCLAIMER: This software has been approved for release by the U.S. Geological Survey (USGS). Although the software has been subjected to rigorous review, the USGS reserves the right to update the software as needed pursuant to further analysis and review. No warranty, expressed or implied, is made by the USGS or the U.S. Government as to the functionality of the software and related material nor shall the fact of release constitute any such warranty. Furthermore, the software is released on condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from its authorized or unauthorized use.

Authors:Vijay Patil [aut, cre], Torsten Seltmann [aut], Nico Salmaso [aut], Orlane Anneville [aut], Marc Lajeunesse [aut], Dietmar Straile [aut]

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algaeClassify.pdf |algaeClassify.html✨
algaeClassify/json (API)
NEWS

# Install 'algaeClassify' in R:
install.packages('algaeClassify', repos = c('https://vppatil.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • csrTraits - Database of functional traits for MFG classification, derived from Rimet et al. 2019
  • lakegeneva - Example dataset from lake Geneva, Switzerland
  • mfgTraits - Functional Trait Database derived from Rimet et al.
  • mfg_csr_library - MFG-CSR correspondence based on CSR-trait relationships in Reynolds et al. 1988 and MFG-trait relationships in Salmaso et al. 2015
  • species_mfg_library - Trait-based MFG classifications for common Eurasion/North American phytoplankton species. See accompanying manuscript for sources
  • traitranges - Surface/volume ratio and max linear dimension criteria for CSR From Reynolds 1988 and Reynolds 2006

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

27 exports 5 stars 1.08 score 127 dependencies 1 mentions 7 scripts 3.8k downloads

Last updated 8 months agofrom:27394c77d0. Checks:OK: 7. Indexed: yes.

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Doc / VignettesOKAug 25 2024
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R-4.5-linuxOKAug 25 2024
R-4.4-winOKAug 25 2024
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R-4.3-winOKAug 25 2024
R-4.3-macOKAug 25 2024

Exports:accumalgaebase_genus_searchalgaebase_output_parsealgaebase_search_dfalgaebase_species_searchbestmatchdate_matgenus_search_itisgenus_species_extractget_apikeyget_apikey_fromfilegnr_simplegnr_simple_dfitis_search_dfmean_naomitmfg_csr_convertmfg_csr_convert_dfphyto_ts_aggregatesampeffset_algaebase_apikey_headerspecies_search_itisspecies_to_mfgspecies_to_mfg_dftraits_to_csrtraits_to_csr_dftraits_to_mfgtraits_to_mfg_df

Dependencies:apeaskpassassertthatbackportsbase64encbitbit64bitopsboldbslibcachemcheckmateclicliprclustercodetoolscolorspaceconditionzcpp11crayoncrulcurldata.tabledigestdplyrevaluatefansifarverfastmapfastmatchfontawesomeforeachforeignFormulafsgenericsggplot2gluegridExtragtablehighrHmischmshtmlTablehtmltoolshtmlwidgetshttpcodehttrigraphisobanditeratorsjquerylibjsonliteknitrlabelinglatticelazyevallifecyclelubridatemagrittrMASSMatrixmemoisemgcvmimemunsellnatservnlmennetopensslpbapplyphangornpillarpkgconfigplyrprettyunitsprogresspurrrquadprogR6rappdirsratelimitrRColorBrewerRcppRCurlreadrrentrezrexritisrlangrmarkdownrnclrotlrpartrredlistrstudioapisassscalessolriumstringistringrsystaxizetibbletidyselecttimechangetinytextriebeardtzdburltoolsutf8uuidvctrsviridisviridisLitevroomWikidataQueryServiceRWikidataRWikipediRwikitaxawithrworrmsxfunXMLxml2yamlzoo

Readme and manuals

Help Manual

Help pageTopics
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)accum
Search algaebase for information about a genus of phytoplanktonalgaebase_genus_search
Helper function for parsing output from algaebasealgaebase_output_parse
Search algaebase for information about a list of phytoplankton namesalgaebase_search_df
Retrieve taxonomic information from the algaebase online database (www.algaebase.org) based on a user-specified genus and species name . This function requires a valid API key for algaebase.algaebase_species_search
fuzzy partial matching between a scientific name and a list of possible matchesbestmatch
Database of functional traits for MFG classification, derived from Rimet et al. 2019csrTraits
Transform a phytoplankton timeseries into a matrix of abundances for ordinationdate_mat
Wrapper function for several functions in ritis:: Searches ITIS database for matches to a genus namegenus_search_itis
Split a dataframe column with binomial name into genus and species columns.genus_species_extract
Get value of algaebase API key from Environment variable Return an error if variable not set.get_apikey
Get value of algaebase API key from a fileget_apikey_fromfile
Wrapper function for taxize::gnr_resolve() checks species names against a variety of online databases supports fuzzy partial matchinggnr_simple
Wrapper function to apply gnr_simple across a data.frame or list of species namesgnr_simple_df
Wrapper function for applying genus_search_itis and species_search_itis to a whole data.frame containing scientific namesitis_search_df
example dataset from lake Geneva, Switzerlandlakegeneva
Compute mean value while ignoring NA'smean_naomit
Returns a CSR classification based on Morphofunctional group (MFG). Correspondence based on Salmaso et al. 2015 and Reynolds et al. 1988mfg_csr_convert
Returns a CSR classification based on Morphofunctional group (MFG). Correspondence based on Salmaso et al. 2015 and Reynolds et al. 1988mfg_csr_convert_df
MFG-CSR correspondence based on CSR-trait relationships in Reynolds et al. 1988 and MFG-trait relationships in Salmaso et al. 2015mfg_csr_library
Functional Trait Database derived from Rimet et al.mfgTraits
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.phyto_ts_aggregate
Visually assess change in sampling effort over time (author: Dietmar Straile)sampeff
Add algaebase API key to curl handleset_algaebase_apikey_header
Trait-based MFG classifications for common Eurasion/North American phytoplankton species. See accompanying manuscript for sourcesspecies_mfg_library
Wrapper function for several functions in ritis:: Searches ITIS database for matches to a binomial scientific name outputs matches, current accepted names, synonyms, and higher taxonomyspecies_search_itis
Conversion of a single genus and species name to a single MFG. Uses species.mfg.libraryspecies_to_mfg
Wrapper function to apply species_phyto_convert() across a data.framespecies_to_mfg_df
surface/volume ratio and max linear dimension criteria for CSR From Reynolds 1988 and Reynolds 2006traitranges
Assign phytoplankton species to CSR functional groups, based on surface to volume ratio and maximum linear dimension ranges proposed by Reynolds et al. 1988;2006traits_to_csr
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;2006traits_to_csr_df
Assign MFG based on binary functional traits and taxonomy (Class and Order)traits_to_mfg
Assign morphofunctional groups to a dataframe of functional traits and higher taxonomytraits_to_mfg_df