Help for package pciR

Type:

Package

Title:

Proactive Conservation Index

Version:

1.0.0

Description:

Calculates the Proactive Conservation Index, a new tool to prioritize species for conservation, which can incorporate information about future threats.

License:

GPL-3

Encoding:

UTF-8

LazyData:

true

Imports:

caret

Depends:

R (≥ 4.1.0)

Suggests:

rmarkdown, knitr

VignetteBuilder:

knitr

RoxygenNote:

7.3.2

NeedsCompilation:

Packaged:

2026-04-17 12:32:38 UTC; gabri

Author:

Gabriel Henrique de Oliveira Caetano [aut, cre], Uri Roll [aut], Shai Meiri [aut]

Maintainer:

Gabriel Henrique de Oliveira Caetano <gabrielhoc@gmail.com>

Repository:

CRAN

Date/Publication:

2026-04-21 19:32:24 UTC

Optimizes weighting for the calculation of Proactive Conservation Index

Description

optim_weights Optimizes weights for calculating Proactive Conservation Index,

Usage

optim_weights(
  sp,
  var_out,
  var_in = NULL,
  weight_out = NULL,
  weight_in = NULL,
  reference,
  type = "both",
  ...
)

Arguments

sp

character. Names of the taxa being evaluated.

var_out

numeric. Threat variables. higher values must indicate increased threat.

var_in

numeric. Interacting variables. Will modulate the effect of threat variables.

weight_out

numeric. Weights for threat variables

weight_in

numeric. Matrix of weights for the combination of interacting variables and threat variables.

reference

numeric. Threat reference towards which weights will be optimized.

type

character. Optimize weights for threat variables ("out"), for interacting variables ("in") or for both ("both").

...

additional arguments to be passed to function 'optim'.

Details

The Pearson correlation between the calculated pci and 'reference' is displayed as the weights are optimized.

Value

Vector ("out"), matrix ("in") or list ("both") with optimal weights.

Examples

# This function takes too long to run here.
#See vignette for a detailed explanation on how to use it.

Calculates Proactive Conservation Index

Description

pci Calculates the Proactive Conservation Index, a new tool to prioritize species for conservation, which incorporates information about future threats.

Usage

pci(sp, var_out, var_in = NULL, weight_out = NULL, weight_in = NULL)

Arguments

sp

character. Names of the taxa being evaluated.

var_out

numeric. Threat variables. higher values must indicate increased threat.

var_in

numeric. Interacting variables. Will modulate the effect of threat variables.

weight_out

numeric. Weights for threat variables

weight_in

numeric. Matrix of weights for the combination of interacting variables and threat variables.

Value

Data frame with PCI and rank.

Examples


# Invert variables that are negatively correlated with conservation priority

vert_df$inv_range_area <- 1/vert_df$range_area
vert_df$inv_brood_size <- 1/vert_df$brood_size
vert_df$inv_protected_area <- 1/((vert_df$protected_area*vert_df$range_area+0.0001))

# Select trait variables

traits_vertebrates <-
   vert_df[c("body_mass",
             "inv_range_area",
             "inv_brood_size",
             "inv_protected_area",
             "AHI")]

# Select threat variables for the year 2100, under scenarion SSP 5.85

threats_2100_585 <-
   vert_df[c("clim_2100_585",
             "landuse_2100_585",
             "popdens_2100_585",
             "inv_threat")]

# Calculate PCI

vertebrates_pci <-
   pci(sp = vert_df$binomial,
       var_out = threats_2100_585,
       var_in = traits_vertebrates)

Threat data for 33565 global terrestrial vertebrates.

Description

A data set containing data on threat correlates for 33565 global terrestrial vertebrates.

Usage

vert_df

Format

A data frame with 33565 rows and 21 variables:

binomial: character. Species binomial name
class: character. Taxonomic class
family: character. Taxonomic family
range_area: numeric. Area of distribution range, in km2
body_mass: numeric. Maximum body mass, in grams
brood_size: numeric. Maximum number of offspring per brood
protected_area: numeric. Proportion of species range overlapping with protected area under category I to IV
AHI: numeric. Artificial Habitat Intolerance, an index calculated from the IUCN Red List data on habitat use
iucn_cat: character. IUCN Red List threat category in July 2022
clim_2050_245: numeric. Proportion of species range lost due to climate change in 2050, under SSP 2.45 scenario
clim_2100_245: numeric. Proportion of species range lost due to climate change in 2100, under SSP 2.45 scenario
clim_2050_585: numeric. Proportion of species range lost due to climate change in 2050, under SSP 5.85 scenario
clim_2100_585: numeric. Proportion of species range lost due to climate change in 2100, under SSP 5.85 scenario
landuse_2050_245: numeric. Proportion of species range lost due to land use change in 2050, under SSP 2.45 scenario
landuse_2100_245: numeric. Proportion of species range lost due to land use change in 2100, under SSP 2.45 scenario
landuse_2050_585: numeric. Proportion of species range lost due to land use change in 2050, under SSP 5.85 scenario
landuse_2100_585: numeric. Proportion of species range lost due to land use change in 2100, under SSP 5.85 scenario
popdens_2050_245: numeric. Mean human population density in 2050, under SSP 2.45 scenario
popdens_2100_245: numeric. Mean human population density in 2100, under SSP 2.45 scenario
popdens_2050_585: numeric. Mean human population density in 2050, under SSP 5.85 scenario
popdens_2100_585: numeric. Mean human population density in 2100, under SSP 5.85 scenario
inv_threat: numeric. Proportion of species range under high or very high threat of biological invasion in 2100 under A3 scenario