tol_metrics | R Documentation |
Indicate sensitivity of the assemblage and component species to various types of disturbance.
tol_metrics(dataset, store = FALSE, dec_c = ".", verbose = FALSE)
dataset |
A data.frame obtained from |
store |
A logical value indicating if the user want to store the results in a file. |
dec_c |
A character used for decimal separator on results file. |
verbose |
A logical value indicating if progress messages should be given. |
Most of the metrics applied in the study of macroinvertebrates use as a key factor the tolerance or intolerance of the different taxa to a certain disturbance, normally organic contamination. The relationship between the number of organisms that are tolerant and intolerant to contamination is a common resource in the metrics used. Further metrics (multimetric indexes) can be derived from a combination of these primary metrics (Prat et al., 2009). The Limnodrilus hoffmeisteri/total density ratio, which was developed by Marchese & Ezcurra de Drago (1999), increases in environments with organic contamination.
This function returns a data.frame with all the calculated tolerance measures.:
r_oligochir |
Oligochaeta/Chironomidae. |
r_oligoset |
Oligochaeta with setaform chaetae/Oligochaeta without setaform chaetae. |
r_tanychir |
Tanytarsini/Chironomidae. |
den_t_lhoff |
Limnodrilus hoffmeisteri/Total density. |
den_t_bothr |
Bothrioneurum/Total density. |
den_t_tubi |
Tubifex/Total density. |
den_t_dero |
Dero/Total density. |
den_t_prist |
Pristina/Total density. |
den_t_chiro |
Chironomus/Total density. |
Juan Manuel Cabrera and Julieta Capeletti.
Marchese M & Ezcurra de Drago I (1999). Use of benthic macroinvertebrates as organic pollution indicators in lotic environments of the Parana River drainage basin. https://agro.icm.edu.pl/agro/element/bwmeta1.element.agro-article-e981d07b-e469-4460-a7fe-3239650cd089
Prat N, RĂos B, Acosta R & Rieradevall M (2009). Los macroinvertebrados como indicadores de calidad de las aguas. http://www.ub.edu/riosandes/docs/MacroIndLatinAmcompag0908.pdf
read_data
#Load example data example_data #Run tol_metrics with that example_data tolmetrics<-tol_metrics(example_data) #Check results tolmetrics
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