Package 'benthos'

Marine Benthic Ecosystem Analysis

Description

benthos provides functions for facilitating the analysis of marine benthos data. Examples are indicators like species abundance, species richness, Margalef's index of diversity, Shannon's Entropy, AZTI's Marine Biotic Index, and the Infaunal Trophic Index (ITI). In addition functions for data pooling, genus-to-species conversion and validation and conversion of species names to those recommended by the World Register of Marine Species are provided.

Details

All functions are designed to work seamlessly with the dplyr-package which implements a grammar for structured data manipulation.

The benthos-package contains functions for estimating various species abundance, species richness, species heterogeneity and species sensitivity measures:

• total abundance (total_abundance)

• abundance (abundance)

• species richness (species_richness)

• Margalef's index of diversity (margalef)

• Rygg's index of diversity (rygg)

• Hurlbert's Expected Number of Species (hurlbert)

• Simpson's measure of concentration (simpson)

• Hurlbert's probability of interspecific encounter (PIE) (hpie)

• Shannon's index or entropy (shannon)

• Hill's diversity number (hill)

• AZTI Marine Biotic Index (AMBI) (ambi)

• Infaunal Trophic Index (ITI) (iti)

• Bray-Curtis dissimilarity (bray_curtis)

In addition, functions are available for data preparation, e.g.:

• data pooling (pool)

• genus to species conversion (genus_to_species)

For an overview of all the functions in the package click on the index link at the bottom of this page.

Author(s)

Dennis Walvoort [email protected]

See Also

The BEQI2-package on CRAN, and the package vignettes.

---

Abundance

Description

The number of individuals in each taxon.

Usage

abundance(taxon = NULL, count)

Arguments

taxon	character vector containing taxa
count	numeric vector containing counts

Value

numeric vector with abundance per taxon.

Note

due to pooling, the abundance is not necessarily an integer

Examples

abundance(
     taxon = c("Euspira pulchella", "Nephtys cirrosa"),
     count = c(4, 6)
 )

---

AZTI Marine Biotic Index (AMBI)

Description

AZTI Marine Biotic Index (AMBI) according to Borja et al. (2000).

Usage

ambi(taxon, count, group = NULL)

has_ambi(taxon, group = NULL)

Arguments

taxon	species names
count	counts of individuals (numeric)
group	sensitivity groups I, II, III, IV, or V

Details

The index is given by:

$c_\mathrm{b} = \frac{3}{2} \sum_{i=2}^5 (i-1) p_i$

where $p_i$ is the proportion of species in sensitivity group $i$.

Value

numeric vector of length 1 containing the AMBI

Functions

• has_ambi(): tests if an AMBI sensitivity group is available for taxon (returns TRUE (available) or FALSE (unavailable))

References

Borja, A., J. Franco and V. Perez, 2000. A Marine Biotic Index to Establish the Ecological Quality of Soft-Bottom Benthos Within European Estuarine and Coastal Environments. Marine Pollution Bulletin 40:1100-1114

Examples

ambi(
     taxon = c("Euspira pulchella", "Nephtys cirrosa"),
     count = c(4, 6)
 )

     data(oosterschelde)
     has_ambi(oosterschelde$TAXON)

---

Convert Taxon Names to Comply with WoRMS/TWN

Description

Taxon names are standardized according to the World Register of Marine Species (WoRMS) database. The conversion is case-insensitive. For this conversion, the TWN-list (Taxa Water management the Netherlands) is used, extended with species of the Southern North Sea. See references below for download locations.

Usage

as_accepted(taxon, taxa = NULL)

Arguments

taxon	character vector, containing taxon names
taxa	an optional table usually created with read_taxa.

Value

character vector with WoRMS/TWN compliant species names

References

https://www.marinespecies.org/

https://taxainfo.nl/

---

Bray-Curtis Dissimilarity

Description

Bray-Curtis Dissimilarity

Usage

bray_curtis(n1, n2)

Arguments

n1	abundances of species at site 1
n2	abundances of species at site 2

Value

Bray-Curtis dissimilarity (0..1, 0 = equal, 1 = different)

Note

species in n1 and n2 need to be aligned

Examples

n1 <- c(11,  0, 7,  8, 0)
     n2 <- c(24, 37, 5, 18, 1)
     bray_curtis(n1, n2)

---

Ecological Quality Ratio (EQR)

Description

The ecological quality ratio is the ratio beween a parameter value and its reference value:

$EQR = \frac{x-bad}{ref-bad}$

Depending on bad and ref, the EQR usually (but not necessarily!) varies between 0 (bad ecological quality) and 1 ( ecological quality equals the reference status).

Usage

eqr(x, bad, ref)

Arguments

x	numeric vector containing benthic indices
bad	the value for a bad status
ref	the value for a reference status

Value

numeric vector with EQR-values: low values indicate bad ecological quality and high values indicate good ecological quality.

---

Genus to Species Conversion

Description

This algorithm reallocates the counts of taxa, that are only identified at the genus level to taxa in the same sampling unit and of the same genus but that are identified on the species level. The redistribution of counts is proportional to the number of counts at the species level.

Usage

genus_to_species(is_genus, count)

Arguments

is_genus	logical vector with elements TRUE if the corresponding taxon is on the genus level, and FALSE if it is on the species level.
count	numeric vector with elements giving the counts of each corresponding taxon.

Value

numeric vector with updated counts. The counts for the taxon on the genus level have been set to zero.

Note

Parameters is_genus and count are of the same length and correspond to the same taxon.

The resulting counts are not necessarily integers.

Examples

genus_to_species(is_genus = c(TRUE, FALSE, FALSE), count = c(3, 10, 20))
     genus_to_species(is_genus = c(TRUE, FALSE, FALSE), count = c(1, 10, 20))

---

Get Supplementary AMBI Sensitivity Groups

Description

This function gets sensitivity groups that are supplementary to the AMBI of Borja et al., (2000)

Usage

get_ambi(which = "NL")

Arguments

which

which AMBI supplement? Currently only the Dutch supplement is available (which = "NL")

Value

a data frame with columns TAXON containing taxa and GROUP containing Dutch AMBI-groups

References

Borja, A., J. Franco and V. Perez, 2000. A Marine Biotic Index to Establish the Ecological Quality of Soft-Bottom Benthos Within European Estuarine and Coastal Environments. Marine Pollution Bulletin 40:1100-1114

---

Get Infaunal Trophic Index

Description

This function gets the sensitivity groups to estimate the infaunal trophic index of Gittenberger et al., (2011)

Usage

get_iti()

Value

a data frame with columns TAXON containing taxa and GROUP containing the ITI-groups of Gittenberger & Van Loon (2013).

References

Gittenberger A. and W. van Loon, 2013. Sensitivities of marine macrozoobenthos to environmental pressures in the Netherlands. Nederlandse Faunistische Mededelingen 41: 79-112.

---

Harmonize Case

Description

Convert text to the most occuring case. In case of ties, the first occurence in sorted order will be taken.

Usage

harmonize(x)

Arguments

x	character vector

Value

character vector with harmonized names (i.e., same case)

Examples

x <- c("FOO", "Foo", "bar", "FOO", "bar", "FOO", "Bar")
 y <- harmonize(x)
 stopifnot(all.equal(y, c("FOO", "FOO", "bar", "FOO", "bar", "FOO", "bar")))

---

Hill's Diversity Numbers

Description

According to Hill (1973): "a diversity number is figuratively a measure of how many species are present if we examine the sample down to a certain depth among its rarities. If we examine superficially (e.g., by using $N_2$) we shall see only the more abundant species. If we look deeply (e.g., by using $N_0$) we shall see all the species present."

Usage

hill(taxon, count, a = 0)

hill0(taxon, count)

hill1(taxon, count)

hill2(taxon, count)

Arguments

taxon	character vector containing taxa
count	numeric vector containing counts
a	exponent in Hill's diversity number (R, with special cases for a in {0, 1, 2} (see details))

Details

Hill's diversity numbers are given by:

$N_a=\sum{i=1}^S (p_i^a)^{1/(1-a)}$

Special cases are:

$N_{-\infty}$

reciprocal of the proportional abundance of the rarest species;

$N_0$

total number of species present;

$N_1$

exp(H), where H: Shannon's index (see also shannon);

$N_2$

reciprocal of Simpson's index (see also simpson);

$N_{\infty}$

reciprocal of the proportional abundance of the commonest species.

Value

numeric vector of Hill's numbers

Functions

• hill0(): $N_0$

• hill1(): $N_1$

• hill2(): $N_2$

References

Hill, M.O., 1973. Diversity and Evenness: A Unifying Notation and Its Consequences. Ecology 54:427-432

See Also

species_richness, shannon, simpson

Examples

hill(
         taxon = c("Euspira pulchella", "Nephtys cirrosa"),
         count = c(6, 12),
         a = 0
     )
     hill0(
         taxon = c("Euspira pulchella", "Nephtys cirrosa"),
         count = c(6, 12)
     )

---

Hurlbert's Probability of Interspecific Encounter (PIE)

Description

The probability that two individuals selected at random (without replacement) from a sample will belong to different species is given by (Hurlbert, 1971, p.579, Eq. 3):

$\Delta_1 = \sum_{i=1}^S (\frac{N_i}{N})(\frac{N-N_i}{N-1}) = (\frac{N}{N-1})\Delta_2$

where $\Delta_2$ (Hurlbert, 1971, p.579, Eq. 4) is the probability that two individuals selected at random (with replacement) from a sample will belong to different species:

$\Delta_2 = 1-\sum_{i=1}^S \pi_i^2$

where $N_i$ is the number of individuals of the ith species in the community, $N$ is the total number of individuals in the community, $\pi_i = N_i/N$, and $S$ is the number of species in the community. Note that Hurlbert's PIE hpie is the complement of simpson.

Usage

hpie(taxon, count)

Arguments

taxon	character vector containing taxa
count	numeric vector containing counts

Value

A numeric vector with the probability of interspecific encounter (PIE).

References

Hurlbert, S.H., 1971. The Nonconcept of Species Diversity: A Critique and Alternative Parameters. Ecology 52:577-586.

See Also

simpson, hurlbert

Examples

hpie(
         taxon = c("Euspira pulchella", "Nephtys cirrosa"),
         count = c(6, 12)
     )

---

Hurlbert's Expected Number of Species

Description

The expected number of species in a sample of n individuals:

Usage

hurlbert(taxon, count, n = 100L)

Arguments

taxon	character vector containing taxa
count	numeric vector containing counts
n	number of individuals in a standard sample

Value

expected number of species in a sample of n individuals

References

Hurlbert, S.H., 1971. The Nonconcept of Species Diversity: A Critique and Alternative Parameters. Ecology 52:577-586.

Examples

hurlbert(
         taxon = c("Euspira pulchella", "Nephtys cirrosa"),
         count = c(4, 6),
         n = 8
     )

---

Test for Azoic Samples

Description

Case-insensitive test for taxa starting with 'azoi'

Usage

is_azoic(x)

Arguments

x	character vector containing taxa

Details

Azoic samples need special attention during data analysis. They should be marked as 'azoic', and taken care of during analysis. Note that an azoic sample is not the same as a record where a taxon has zero counts. The latter should be removed from further analysis, whereas the former provides important information.

Value

logical vector, with elements TRUE for azoic samples, and FALSE otherwise.

---

Binomial Names

Description

is_binomial tests for valid binomial names, generic_name extracts the genus to which the species belongs, specific_name extracts the species within the genus.

Usage

is_binomen(x)

generic_name(x)

specific_name(x)

strip_sp(x)

Arguments

x	character vector, containing the binomial name(s) of species (a.k.a. binomen or scientific name)

Value

character vector with either the generic name or the specific name of the species.

Functions

• generic_name(): extracts the genus to which the species belongs

• specific_name(): extracts the species within the genus

• strip_sp(): strips postfix sp. or spp. from a binomen

Examples

is_binomen("Venerupis corrugata") # TRUE
 generic_name("Venerupis corrugata") # Venerupis
 specific_name("Venerupis corrugata") # corrugata
 generic_name("venerupis corrugata") # NA (genus part should be capitalized)

---

Infaunal Trophic Index (ITI)

Description

Computes the Infaunal Trophic Index (ITI) according to Gittenberger & van Loon (2013).

Usage

iti(taxon, count, group = NULL)

has_iti(taxon, group = NULL)

Arguments

taxon	species names
count	counts of individuals (numeric)
group	sensitivity groups I, II, III, or IV

Details

The Infaunal Trophic Index (ITI) is given by

$\mathrm{ITI} = 100 \sum_{i=1}^3 \frac{(4-i)}{3} p_i$

where $p_i$ is the proportion of species in class $i$, where

• group I are suspension feeders (highest quality);

• group II are interface feeders

• group III are surface deposit feeders and

• group IV are subsurface deposit feeders (lowest quality).

Value

numeric vector of length 1 containing the ITI

Functions

• has_iti(): tests if an ITI sensitivity group is available for taxon (returns TRUE (available) or FALSE (unavailable))

References

Gittenberger A. and W. van Loon, 2013. Sensitivities of marine macrozoobenthos to environmental pressures in the Netherlands. Nederlandse Faunistische Mededelingen 41: 79-112.

Examples

iti(taxon = c("Euspira pulchella", "Nephtys cirrosa"), count = c(4, 6))

---

Margalef Index of Diversity

Description

Margalef Index of Diversity is given by

$D = \frac{S-1}{\ln(N)}$

Usage

margalef(taxon, count)

Arguments

taxon	taxa names (character)
count	counts (numeric)

Details

For $N=1$, the index is set to 0.

Value

Margalef diversity index (numeric vector of length 1)

Examples

margalef(
    taxon = c("Euspira pulchella", "Nephtys cirrosa"),
    count = c(4, 6)
)

---

MWTL North Sea Bentos Data

Description

MWTL North Sea Bentos Data

Usage

northsea

Format

An object of class tbl_df (inherits from tbl, data.frame) with 24983 rows and 9 columns.

---

Oosterschelde Marine Benthos Data

Description

Oosterschelde data set. The Oosterschelde is located in the southwest of the Netherlands.

Usage

oosterschelde

Format

An object of class tbl_df (inherits from tbl, data.frame) with 4269 rows and 8 columns.

Details

The Oosterschelde data contains the following columns:

• ID sample identifier

• HABITAT specification of the habitat

• AREA sampled area

• DATE sampling date (YYYY-MM-DD, ISO 8601)

• TAXON standardized taxon code (see WoRMS-website https://www.marinespecies.org/)

• COUNT number of individuals of 'TAXON'

Note

This is not the original data set, but a simplified version of it meant for didactic purposes only! For instance it only contains taxa identified at the species level. Other taxa have been removed.

Source

Rijkswaterstaat Water, Transport and Living Environment, Department of Information Management, Lelystad, The Netherlands (contact: [email protected])

---

Pooling

Description

This function randomly assigns samples to pools of approximately equal area

Usage

pool(sample_id = seq_along(area), area, target_area, max_try = 100L)

.pool(sample_id = seq_along(area), area, target_area, max_try = 100L)

Arguments

sample_id	sample identifier
area	sampling area of sample_id (in the same units as target_area)
target_area	vector of length 2 containing the lower and upper bound of the pooled area (same units as area)
max_try	maximum number of unsuccessful pooling tries before the algorithm gives up.

Value

vector with idenitifiers (integers) indicating the pool to which each sample belongs (NA for samples that could not be pooled)

Functions

• .pool(): internal function not supposed to be called directly.

---

Read and Validate AMBI Sensitivity Data

Description

This function reads and checks files with AMBI sensitivity data. The data should be stored in 'comma separated values' format (csv) consisting of two columns:

TAXON

species name;

GROUP

Roman numeral (I, II, III, IV, V) giving the sensitivity group

Usage

read_ambi(filename)

validate_ambi(x)

Arguments

filename	name of the AMBI sensitivity file (character)
x	table in AMBI-format

Details

The function performs the following tasks:

• checks the existence of filename;

• checks availability of required columns (case insensitive);

• removes redundant spaces;

• removes duplicated records.

Functions

• validate_ambi(): validator for AMBI-format

References

Borja, A., J. Franco and V. Perez, 2000. A Marine Biotic Index to Establish the Ecological Quality of Soft-Bottom Benthos Within European Estuarine and Coastal Environments. Marine Pollution Bulletin 40:1100-1114

---

Read and Validate BEQI2 Input Files

Description

This function reads and checks BEQI2 input files. The format has been specified in Van Loon (2013) and is described in the vignette of the BENMMI-package.

Usage

read_beqi2(filename)

validate_beqi2(x)

Arguments

filename	name of BEQI2 input file (character)
x	table in BEQI2-format

Details

The function performs the following tasks:

• checks the existence of filename;

• checks availablitity of required columns (case insensitive);

• make column names with aggregation data case-insensitive;

• removes redundant spaces;

• checks if DATE-field adheres to ISO 8601 (YYYY-mm-dd);

• constructs a unique identifier ID by concatenating columns OBJECTID and DATE;

• checks that each ID has a unique AREA;

• checks azoic samples for VALUE=0;

• removes records with VALUE=0, not belonging to azoic samples;

• checks VALUE-field on missing values;

• checks if VALUE-field is an integer;

Functions

• validate_beqi2(): validator for BEQI2-format

References

Willem van Loon, 2013. BEQI2 INPUT FORMAT. See the package-vignette of the BENMMI-package.

---

Read and Validate Infaunal Trophic Index Files

Description

This function reads and checks files containing Infaunal Trophic Index (ITI) data (Gittenberger & Van Loon, 2013)

Usage

read_iti(filename)

validate_iti(x)

Arguments

filename	name of the ITI file (character).
x	table in ITI-format

Details

The function performs the following tasks:

• checks the existence of filename;

• checks availability of required columns (case insensitive), i.e., TAXON and GROUP;

• removes redundant spaces;

• removes duplicated records;

• checks if all ITI classes are I, II, III, or IV

The column 'GROUP' contains the Roman numerals I, II, III, and IV, with the following meaning:

I:

suspension feeders;

II:

interface feeders;

III:

surface deposit feeders;

IV:

subsurface deposit feeders.

Value

A data frame with columns TAXON containing taxa and GROUP containing user-defined ITI-groups (see Gittenberger & Van Loon, 2013).

Functions

• validate_iti(): validator for ITI-format

References

Gittenberger A. and W. van Loon, 2013. Sensitivities of marine macrozoobenthos to environmental pressures in the Netherlands. Nederlandse Faunistische Mededelingen 41: 79-112.

---

Read and Validate Habitat References Files

Description

This function reads and checks files with reference values

Usage

read_ref(filename, indicators = c("S", "H", "AMBI"))

validate_ref(x, indicators = c("S", "H", "AMBI"))

Arguments

filename	name of the habitat reference file (character)
indicators	indicators to be processed (character, see details)
x	table in REF-format

Details

The function performs the following tasks:

• checks the existence of filename;

• checks availablitity of required columns (case insensitive);

• removes redundant spaces

• removes duplicated records

Argument indicators is a character vector of additional benthic indicators to be checked for. For example, if indicators = "ITI", then the habitat reference file should also contain columns ITIREF and ITIBAD. Implemented indicators are N, LNN, S, D, SN, SNA, H, L, AMBI, ITI, PIE, N2 (see package vignette).

The format of the habitat reference file is documented in the BEQI2-package vignette.

Functions

• validate_ref(): validator for REF-format

References

Van Loon, W, 2013. Loon2013-BEQI2-Specs-Ecotopes-27nov.doc

---

Read and Validate Taxa Data

Description

This function reads files in the taxa format.

Usage

read_taxa(filename)

get_taxa()

validate_taxa(x)

Arguments

filename	name of taxa file
x	table in taxa-format

Details

Taxa files have the following format:

group

taxonomic group

provided

provided taxon name

accepted

accepted taxon name

level

taxonomic level

Other columns are allowed, but silently ingored.

Functions

• get_taxa(): get default taxa list (TWN list extended with species Southern North Sea)

• validate_taxa(): validator for taxa-format

---

Read and Validate Taxa Waterbeheer Nederland (TWN) Data

Description

This function reads files in the Taxa Waterbeheer Nederland (TWN) format.

Usage

read_twn(filename)

get_worms()

validate_twn(x)

Arguments

filename	name of TWN file (character)
x	table in TWN-format

Details

The function adds a new column taxon. Its contents depending on TWN-status:

status = 10

taxonname

status = 20

prefername

status = 80

parentname

Value

a tibble with four columns:

GROUP

TWN/WoRMS taxon group

LEVEL

TWN/WoRMS taxon level

FROM

taxon name to convert from

TO

taxon name to convert to

Functions

• get_worms(): get default WoRMS list (TWN list extended with species Southern North Sea)

• validate_twn(): validator for TWN-format

References

https://taxainfo.nl/

---

Rygg's Index of Diversity

Description

Rygg's index of diversity is given by

$SN = \frac{\ln(S)}{\ln(\ln(N))}$

Usage

rygg(taxon, count, adjusted = FALSE)

Arguments

taxon	taxa names (character)
count	counts (numeric)
adjusted	(defaults to FALSE)

Details

The adjusted version of Rygg's index which gives more consistent values for smaller S=2, N=2, N=3 and S=3, N=3 is

$SN = \frac{\ln(S)}{\ln(\ln(N+1)+1)}$

Value

Rygg's index of diversity (numeric vector of length 1)

Note

Rygg's index is not defined for $N=exp(1)$. For $N \leq exp(1)$, rygg returns NA_real_.

References

Rygg, B. (2006). Developing indices for quality-status classification of marine soft-bottom fauna in Norway. Norwegian Institute for Water Research, Oslo, Norway. NIVA Report SNO 5208-2006.

Examples

rygg(
     taxon = c("Euspira pulchella", "Nephtys cirrosa"),
     count = c(4, 6)
 )

---

Shannon's Index or Entropy

Description

Compute entropy according to Shannon (1948)

Usage

shannon(taxon, count, base = 2)

Arguments

taxon	taxa names (character)
count	counts (numeric)
base	the base with respect to which logarithms are computed. Defaults to 2 (unit: bits).

Value

Shannon's entropy

References

Shannon, C. E., 1948. A Mathematical Theory of Communication. Bell System Technical Journal 27: 379-423.

Examples

shannon(
     taxon = c("Euspira pulchella", "Nephtys cirrosa"),
     count = c(4, 6)
 )

---

Simpson's Measure of Concentration

Description

The probability that two individuals selected at random (with replacement, Hurlbert, 1971, p.579) from a sample will belong to the same species. For an infinite sample Simpson's Index is given by (Peet, 1974):

$\lambda = \sum_{i=1}^S p_i^2$

For a finite sample by:

$L = \sum_{i=1}^S \frac{n_i (n_i-1)}{N (N-1)}$

where $p_i$ the proportion of the individuals in species $i$, $n_i$ the number of individuals in species $i$ (relative abundance), and $N$ the total number of individuals (total_abundance). The finite sample case has been implemented in function simpson (and simpson_).

Usage

simpson(taxon, count)

Arguments

taxon	character vector containing taxa
count	numeric vector containing counts

Value

The probability that two individuals selected at random from a sample will belong to the same species.

References

Peet, R. K. 1974, The Measurement of Species Diversity. Annual Review of Ecology and Systematics 5:285-307.

See Also

hpie

Examples

simpson(
         taxon = c("Euspira pulchella", "Nephtys cirrosa"),
         count = c(6, 12)
     )

---

Species Richness

Description

Species richness ($S$) is defined as the number of taxa (lowest identification level possible) per sampling unit (data pool or box core sample).

Usage

species_richness(taxon, count = NULL)

Arguments

taxon	taxa names (character)
count	number of individuals for each taxon (numeric)

Value

species richness (integer vector of length 1)

Examples

species_richness(
     taxon = c("Euspira pulchella", "Nephtys cirrosa"),
     count = c(4, 6)
 )

---

Remove Redundant Spaces

Description

This function removes redundant spaces from character vectors

Usage

strip_spaces(x)

Arguments

x	character vector

Value

character vector without trailing or multiple spaces

---

Convert Taxon Names to Comply with WoRMS

Description

Taxon names are standardized according to the World Register of Marine Species (WoRMS) database. The conversion is case-insensitive. For this conversion, the TWN-list (Taxa Water management the Netherlands) is used, extended with species of the Southern North Sea. See references below for download locations.

Usage

to_worms(taxon, worms = NULL)

is_worms(.data = NULL, taxon)

is_worms_(.data, taxon)

is_accepted(taxon)

Arguments

taxon	character vector, containing taxon names
worms	an optional table usually created with read_twn.
.data	data in a data.frame, tibble, data.table, database etc.

Value

character vector with WoRMS compliant species names

TRUE for WoRMS compliant species names, FALSE otherwise.

TRUE for WoRMS/TWN compliant species names, FALSE otherwise.

Functions

• is_worms(): check if a taxon complies with WoRMS

• is_worms_(): as is_worms but suitable for calling from a function (see package lazyeval).

• is_accepted(): check if a taxon complies with WoRMS/TWN

References

https://www.marinespecies.org/

https://taxainfo.nl/

---

Total Abundance

Description

The total number of individuals.

Usage

total_abundance(count, na.rm = FALSE)

lnn(count, na.rm = FALSE)

Arguments

count	counts (numeric)
na.rm	Should missing values (including NaN) be removed? (logical)

Value

total number of individuals (integer)

Functions

• lnn(): natural log of total abundance + 1

Examples

total_abundance(count = c(4, 6))

---