Package 'redlistr'

Title: Tools for the IUCN Red List of Ecosystems and Species
Description: A toolbox created by members of the International Union for Conservation of Nature (IUCN) Red List of Ecosystems Committee for Scientific Standards. Primarily, it is a set of tools suitable for calculating the metrics required for making assessments of species and ecosystems against the IUCN Red List of Threatened Species and the IUCN Red List of Ecosystems categories and criteria. See the IUCN website for detailed guidelines, the criteria, publications and other information.
Authors: Calvin Lee [cre, aut] , Nicholas Murray [aut]
Maintainer: Calvin Lee <[email protected]>
License: GPL (>=3)| file LICENSE
Version: 1.0.4
Built: 2024-11-12 06:00:08 UTC
Source: https://github.com/red-list-ecosystem/redlistr

Help Index

Create empty Area of Occupancy (AOO) Grid.

Description

createGrid produces empty grid which can be used as the basis to help compute AOO.

Usage

createGrid(input.data, grid.size)

Arguments

input.data

Spatial object of an ecosystem or species distribution. Please use a CRS with units measured in metres.
grid.size

A number specifying the width of the desired grid square (in same units as your coordinate reference system)

Value

A regular grid raster with extent input.data and grid size grid.size. Each grid square has a unique identification number.

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

References

Bland, L.M., Keith, D.A., Miller, R.M., Murray, N.J. and Rodriguez, J.P. (eds.) 2016. Guidelines for the application of IUCN Red List of Ecosystems Categories and Criteria, Version 1.0. Gland, Switzerland: IUCN. ix + 94pp. Available at the following web site: https://iucnrle.org/

See Also

Other AOO functions: getAOOSilent(), getAOO(), makeAOOGrid()

Extrapolate Estimate

Description

extrapolateEstimate uses rates of decline from getDeclineStats to extrapolate estimates to a given time

Usage

extrapolateEstimate(A.t1, year.t1, nYears, ARD = NA, PRD = NA, ARC = NA)

Arguments

A.t1

Area at time t1
year.t1

Year of time t1
nYears

Number of years since t1 for prediction. Use negative values for backcasting
ARD

Absolute rate of decline
PRD

Proportional rate of decline
ARC

Annual rate of change

Value

A dataframe with the forecast year, and a combination of:

  • Values as extrapolated with absolute rate of decline (ARD)

  • Values as extrapolated with proportional rate of decline (PRD)

  • Values as extrapolated with annual rate of change (ARC)

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

References

Bland, L.M., Keith, D.A., Miller, R.M., Murray, N.J. and Rodriguez, J.P. (eds.) 2016. Guidelines for the application of IUCN Red List of Ecosystems Categories and Criteria, Version 1.0. Gland, Switzerland: IUCN. ix + 94pp. Available at the following web site: https://iucnrle.org/

See Also

Other change_functions: futureAreaEstimate(), sequentialExtrapolate()

Examples

a.r1 <- 23.55
a.r2 <- 15.79
decline.stats <- getDeclineStats(a.r1, a.r2, year.t1 = 1990, year.t2 = 2012,
                                 methods = 'PRD')
a.2040.PRD <- extrapolateEstimate(a.r1, a.r2, year.t1 = 1990, nYears = 50,
                                  PRD = decline.stats$PRD)

Future Area Estimate

Description

futureAreaEstimate is now deprecated, please use extrapolateEstimate instead

Usage

futureAreaEstimate(A.t1, year.t1, nYears, ARD = NA, PRD = NA, ARC = NA)

Arguments

A.t1

Area at time t1
year.t1

Year of time t1
nYears

Number of years since t1 for area prediction
ARD

Absolute rate of decline
PRD

Proportional rate of decline
ARC

Annual rate of change

Value

A dataframe with the forecast year, and a combination of:

  • Future area as estimated with absolute rate of decline (ARD)

  • Future area as estimated with proportional rate of decline (PRD)

  • Future area as estimated with annual rate of change (ARC)

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

References

Bland, L.M., Keith, D.A., Miller, R.M., Murray, N.J. and Rodriguez, J.P. (eds.) 2016. Guidelines for the application of IUCN Red List of Ecosystems Categories and Criteria, Version 1.0. Gland, Switzerland: IUCN. ix + 94pp. Available at the following web site: https://iucnrle.org/

See Also

Other change_functions: extrapolateEstimate(), sequentialExtrapolate()

Compute Area of Occupancy (AOO)

Description

getAOO determines the number of area of occupancy (AOO) grid cells occupied by a species or ecosystem. It includes capability for specifying whether at least one percent of the grid cell needs to be occupied before it is counted in the AOO. This functionality is important for assessing the IUCN Red List of Ecosystems Criteria B.

Usage

getAOO(input.data, grid.size, min.percent.rule = FALSE, percent = 1)

Arguments

input.data

Spatial object of an ecosystem or species distribution. Please use a CRS with units measured in metres.
grid.size

A number specifying the width of the desired grid square (in same units as your coordinate reference system)
min.percent.rule

Logical. If TRUE, a minimum area threshold must be passed before a grid is counted as an AOO grid.
percent

Numeric. The minimum percent to be applied as a threshold for the min.percent.rule

Value

The number of grid cells occupied by the ecosystem or species

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

References

Bland, L.M., Keith, D.A., Miller, R.M., Murray, N.J. and Rodriguez, J.P. (eds.) 2016. Guidelines for the application of IUCN Red List of Ecosystems Categories and Criteria, Version 1.0. Gland, Switzerland: IUCN. ix + 94pp. Available at the following web site: https://iucnrle.org/

See Also

Other AOO functions: createGrid(), getAOOSilent(), makeAOOGrid()

Examples

crs.UTM55S <- '+proj=utm +zone=55 +south +ellps=WGS84 +datum=WGS84 +units=m +no_defs'
r1 <- raster(ifelse((volcano<130), NA, 1), crs = crs.UTM55S)
extent(r1) <- extent(0, 6100, 0, 8700)
AOO <- getAOO(r1, 1000, min.percent.rule = TRUE, percent = 1)

Alternate function for getting AOO (with custom grid)

Description

getAOOSilent is identical to getAOO, but allows the custom input of the grid parameter. Used for gridUncertainty.

Usage

getAOOSilent(input.data, grid, min.percent.rule = FALSE, percent = 1)

Arguments

input.data

Spatial object of an ecosystem or species distribution. Please use a CRS with units measured in metres.
grid

Custom grid to be used to calculate AOO. Usually the output of gridUncertainty
min.percent.rule

Logical. If TRUE one percent of the grid cell must be occupied before it is counted in the AOO.
percent

Numeric. The minimum percent to be applied as a threshold for the min.percent.rule

Value

Value. The AOO calculated with the input distribution and grid.

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

See Also

Other AOO functions: createGrid(), getAOO(), makeAOOGrid()

Calculates the Area of a Raster.

Description

getArea reports the area of a RasterLayer object using the pixel counting method, or terra::expanse for SpatRaster and SpatVector objects, or the area of a SpatialPolygons or sf object using sf::st_area

Usage

getArea(x, ...)

Arguments

x

Either a RasterLayer or SpatialPolygons object. For a RasterLayer, no data value should be NA
...

Addition arguments based on input format

Value

The total area of the cells of interest in km2

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

See Also

Other Change functions: getArea.RasterLayer(), getArea.SpatRaster(), getArea.SpatVect(), getArea.SpatialPolygons(), getArea.sf(), getAreaLoss(), getDeclineStats()

Examples

crs.UTM55S <- '+proj=utm +zone=55 +south +ellps=WGS84 +datum=WGS84 +units=m +no_defs'
r1 <- raster(ifelse((volcano<130), NA, 1), crs = crs.UTM55S)
extent(r1) <- extent(0, 6100, 0, 8700)
a.r1 <- getArea(r1) # area of all non-NA cells in r1

Calculates the Area of a Raster from RasterLayer.

Description

getArea reports the area of a RasterLayer object using the pixel counting method.

Usage

## S3 method for class 'RasterLayer'
getArea(x, value.to.count, ...)

Arguments

x

Either a RasterLayer object. No data value should be NA
value.to.count

Optional. Value of the cells in a RasterLayer to be counted
...

Addition arguments based on input format

Value

The total area of the cells of interest in km2

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

See Also

Other Change functions: getArea.SpatRaster(), getArea.SpatVect(), getArea.SpatialPolygons(), getArea.sf(), getAreaLoss(), getArea(), getDeclineStats()

Calculates the Area of a Raster from sf object

Description

getArea reports the area of a sf object using sf::st_area

Usage

## S3 method for class 'sf'
getArea(x, ...)

Arguments

x

A sf object
...

Addition arguments based on input format

Value

The total area of the cells of interest in km2

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

See Also

Other Change functions: getArea.RasterLayer(), getArea.SpatRaster(), getArea.SpatVect(), getArea.SpatialPolygons(), getAreaLoss(), getArea(), getDeclineStats()

Calculates the Area of a Raster from SpatialPolygons.

Description

getArea reports the area of a SpatialPolygons object using sf::st_area

Usage

## S3 method for class 'SpatialPolygons'
getArea(x, ...)

Arguments

x

A SpatialPolygons object.
...

Addition arguments based on input format

Value

The total area of the cells of interest in km2

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

See Also

Other Change functions: getArea.RasterLayer(), getArea.SpatRaster(), getArea.SpatVect(), getArea.sf(), getAreaLoss(), getArea(), getDeclineStats()

Calculates the Area of a Raster from SpatRaster.

Description

getArea reports the area of a SpatRaster object using terra::expanse

Usage

## S3 method for class 'SpatRaster'
getArea(x, byValue, ...)

Arguments

x

SpatRaster
byValue

Logical. If TRUE, the area for each unique cell value is returned.
...

Addition arguments based on input format

Value

The total area of the cells of interest in km2

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

See Also

Other Change functions: getArea.RasterLayer(), getArea.SpatVect(), getArea.SpatialPolygons(), getArea.sf(), getAreaLoss(), getArea(), getDeclineStats()

Calculates the Area of a Raster from SpatVect.

Description

getArea reports the area of a SpatVect. object using terra::expanse

Usage

## S3 method for class 'SpatVect'
getArea(x, ...)

Arguments

x

A SpatVect object
...

Addition arguments based on input format

Value

The total area of the cells of interest in km2

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

See Also

Other Change functions: getArea.RasterLayer(), getArea.SpatRaster(), getArea.SpatialPolygons(), getArea.sf(), getAreaLoss(), getArea(), getDeclineStats()

Calculates area of the created EOO polygon.

Description

getAreaEOO calculates the area of the EOO polygon generated from makeEOO the provided data

Usage

getAreaEOO(EOO.polygon, unit = "km")

Arguments

EOO.polygon

An object of class SpatVect, usually the output from makeEOO.
unit

Character. Output unit of area. One of "m", "km", or "ha"

Value

The area of the EOO.polygon in km2

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

See Also

Other EOO functions: makeEOO()

Examples

library(terra)
crs.UTM55S <- '+proj=utm +zone=55 +south +ellps=WGS84 +datum=WGS84 +units=m +no_defs'
r1 <- rast(ifelse((volcano<130), NA, 1), crs = crs.UTM55S)
ext(r1) <- c(0, 6100, 0, 8700)
EOO.polygon <- makeEOO(r1)
EOO.area <- getAreaEOO(EOO.polygon)

Area change between two inputs in km2

Description

getAreaLoss reports the difference in area between two inputs. These can be RasterLayers, SpatialPolygons, SpatRaster, SpatVect, sf or numbers. Any combinations of these inputs are valid. If using number as input, ensure it is measured in km2

Usage

getAreaLoss(x, y)

Arguments

x

Spatial obect or numeric representing area in km2
y

Spatial object or numeric representing area in km2

Value

Returns the difference in area of the two inputs in km2

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

See Also

Other Change functions: getArea.RasterLayer(), getArea.SpatRaster(), getArea.SpatVect(), getArea.SpatialPolygons(), getArea.sf(), getArea(), getDeclineStats()

Examples

crs.UTM55S <- '+proj=utm +zone=55 +south +ellps=WGS84 +datum=WGS84 +units=m +no_defs'
r1 <- raster(ifelse((volcano<130), NA, 1), crs = crs.UTM55S)
extent(r1) <- extent(0, 6100, 0, 8700)
r2 <- raster(ifelse((volcano<145), NA, 1), crs = crs.UTM55S)
extent(r2) <- extent(0, 6100, 0, 8700)
a.dif <- getAreaLoss(r1, r2) # distribution rasters

Change statistics.

Description

getDeclineStats calculates the Proportional Rate of Decline (PRD), Absolute Rate of Decline (ARD) and Annual Rate of Change (ARC), given two areas at two points in time. Also provides the total area difference. Inputs are usually the results from getArea.

Usage

getDeclineStats(A.t1, A.t2, year.t1, year.t2, methods)

Arguments

A.t1

Area at time t1
A.t2

Area at time t2
year.t1

Year of time t1
year.t2

Year of time t2
methods

Method(s) used to calculate rate of decline. Either 'PRD', 'ARD', and/or 'ARC'. See vignette to see a more detailed explanation for each of them.

Value

A dataframe with absolute differences between the two inputs, and a selection of:

  • Proportional Rate of Decline (PRD)

  • Absolute Rate of Decline (ARD)

  • Annual Rate of Change (ARC)

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

References

Bland, L.M., Keith, D.A., Miller, R.M., Murray, N.J. and Rodriguez, J.P. (eds.) 2016. Guidelines for the application of IUCN Red List of Ecosystems Categories and Criteria, Version 1.0. Gland, Switzerland: IUCN. ix + 94pp. Available at the following web site: https://iucnrle.org/ Puyravaud, J.-P. 2003. Standardizing the calculation of the annual rate of deforestation. Forest Ecology and Management, 177, 593-596.

See Also

Other Change functions: getArea.RasterLayer(), getArea.SpatRaster(), getArea.SpatVect(), getArea.SpatialPolygons(), getArea.sf(), getAreaLoss(), getArea()

Examples

a.r1 <- 23.55
a.r2 <- 15.79
decline.stats <- getDeclineStats(a.r1, a.r2, year.t1 = 1990, year.t2 = 2012,
                                 methods = c('ARD', 'ARC'))

Function to compute AOO with grid uncertainty systematically with stopping rule

Description

gridUncertainty determines the number of area of occupancy (AOO) grid cells occupied by a species or ecosystem systematically. It will only stop when the AOO calculated does not improve (decrease) after a set number of split scenarios.

Usage

gridUncertainty(
  input.data,
  grid.size,
  n.AOO.improvement,
  min.percent.rule = FALSE,
  percent = 1
)

Arguments

input.data

Spatial object of an ecosystem or species distribution. Please use a CRS with units measured in metres.
grid.size

A number specifying the width of the desired grid square (in same units as your coordinate reference system)
n.AOO.improvement

Specifies the minimum number of rounds the calculated AOO is not improved before stopping the function.
min.percent.rule

Logical. If TRUE, a minimum area threshold must be passed before a grid is counted as an AOO grid.
percent

Numeric. The minimum percent to be applied as a threshold for the min.percent.rule.

Value

A list containing the following:

  • Data frame of results showing the minimum AOO calculated for each shift scenario

  • Single SpatialPolygonsDataFrame containing the AOO grid which would produce the minimum AOO calculated

Author(s)

Calvin Lee [email protected]

See Also

Other gridUncertainty functions: gridUncertaintyBase(), gridUncertaintyRandomManual(), gridUncertaintyRandom(), gridUncertaintyRestricted(), gridUncertaintySimulation()

Examples

crs.UTM55S <- '+proj=utm +zone=55 +south +ellps=WGS84 +datum=WGS84 +units=m +no_defs'
r1 <- raster(ifelse((volcano<130), NA, 1), crs = crs.UTM55S)
extent(r1) <- extent(0, 6100, 0, 8700)
x <- gridUncertainty(r1, grid.size = 1000, n.AOO.improvement = 5,
                           min.percent.rule = FALSE, percent = 1)

Base function to compute AOO with grid uncertainty systematically

Description

gridUncertaintyBase helps determine the minimum number of area of occupancy (AOO) grid cells occupied by a species or ecosystem. It varies the location of the AOO grid by shifting in systematically in both x- and y- axes, adding a small amount of random movement (five percent of the grid.size) at each point. It then returns summary statistics for the range of AOOs calculated, and the RasterLayer(s) containing the grids with the minimum AOO. It is the base function which is used by gridUncertainty, gridUncertaintySimulation, and gridUncertaintyRestricted

Usage

gridUncertaintyBase(
  input.data,
  grid.size,
  splits,
  min.percent.rule = FALSE,
  percent = 1,
  restriction = FALSE,
  min.grids.shift
)

Arguments

input.data

Spatial object of an ecosystem or species distribution. Please use a CRS with units measured in metres.
grid.size

A number specifying the width of the desired grid square (in same units as your coordinate reference system)
splits

Specifies the number of ways to split the grid in ONE axis.
min.percent.rule

Logical. If TRUE, a minimum area threshold must be passed before a grid is counted as an AOO grid.
percent

Numeric. The minimum percent to be applied as a threshold for the min.percent.rule.
restriction

Logical. If TRUE, allows user to specify areas to focus where grid search is done. Used in gridUncertaintyRestricted.
min.grids.shift

Dataframe object with two columns (x.shift and y.shift) specifying the coordinates to restrict the AOO grid placement.

Value

List containing the following:

  • Vector of length split*split of calculated AOO for each shifted grid

  • Data frame of summary statistics for the results create the AOO grid(s) which return the smallest AOO

  • Data frame of the shift(s) required to create the AOO grid(s) with the smallest AOO

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

See Also

createGrid() getAOOSilent()

Other gridUncertainty functions: gridUncertaintyRandomManual(), gridUncertaintyRandom(), gridUncertaintyRestricted(), gridUncertaintySimulation(), gridUncertainty()

Function to compute AOO with grid uncertainty randomly with stop rule

Description

gridUncertaintyRandom helps determine the minimum number of area of occupancy (AOO) grid cells occupied by a species or ecosystem. It varies the location of the AOO grid by shifting in randomly in both x- and y- axes, returning summary statistics for the range of AOOs calculated, and the RasterLayer(s) containing the grids with the minimum AOO. It automatically stops when the AOO no longer improves after a specified number of rounds.

Usage

gridUncertaintyRandom(
  input.data,
  grid.size,
  n.AOO.improvement,
  min.percent.rule = FALSE,
  percent = 1,
  max.n.rounds = 1000
)

Arguments

input.data

Spatial object of an ecosystem or species distribution. Please use a CRS with units measured in metres.
grid.size

A number specifying the width of the desired grid square (in same units as your coordinate reference system)
n.AOO.improvement

Specifies the minimum number of rounds the calculated AOO is not improved before stopping the function.
min.percent.rule

Logical. If TRUE, a minimum area threshold must be passed before a grid is counted as an AOO grid.
percent

Numeric. The minimum percent to be applied as a threshold for the min.percent.rule.
max.n.rounds

Specifies the maximum number of rounds to calculate AOOs. Generally unused except to limit computation time.

Value

List containing the following:

  • Data frame of summary statistics for the results

  • Data frame showing the distance shifted in x and y directions used to create the AOO grid(s) and their associated AOOs

  • List of RasterLayer(s) containing the AOO grid(s) which return the smallest AOO

Author(s)

Calvin Lee [email protected]. Nicholas Murray [email protected]

See Also

createGrid() getAOOSilent()

Other gridUncertainty functions: gridUncertaintyBase(), gridUncertaintyRandomManual(), gridUncertaintyRestricted(), gridUncertaintySimulation(), gridUncertainty()

Examples

crs.UTM55S <- '+proj=utm +zone=55 +south +ellps=WGS84 +datum=WGS84 +units=m +no_defs'
r1 <- raster(ifelse((volcano<130), NA, 1), crs = crs.UTM55S)
extent(r1) <- extent(0, 6100, 0, 8700)
x <- gridUncertaintyRandom(r1, grid.size = 1000, n.AOO.improvement = 50,
                           min.percent.rule = TRUE, percent = 1)

Manual function to compute AOO with grid uncertainty randomly

Description

gridUncertaintyRandomManual helps determine the minimum number of area of occupancy (AOO) grid cells occupied by a species or ecosystem. It varies the location of the AOO grid by shifting in randomly in both x- and y- axes, returning summary statistics for the range of AOOs calculated, and the RasterLayer(s) containing the grids with the minimum AOO. Requires manual input for the number of simulations to perform.

Usage

gridUncertaintyRandomManual(
  input.data,
  grid.size,
  n.sim = 10,
  min.percent.rule = FALSE,
  percent = 1
)

Arguments

input.data

Spatial object of an ecosystem or species distribution. Please use a CRS with units measured in metres.
grid.size

A number specifying the width of the desired grid square (in same units as your coordinate reference system)
n.sim

Specifies the number of random grids to be created and tested.
min.percent.rule

Logical. If TRUE, a minimum area threshold must be passed before a grid is counted as an AOO grid.
percent

Numeric. The minimum percent to be applied as a threshold for the min.percent.rule.

Value

List containing the following:

  • Data frame of summary statistics for the results

  • Data frame showing the distance shifted in x and y directions used to create the AOO grid(s) and their associated AOOs

  • List of RasterLayer(s) containing the AOO grid(s) which return the smallest AOO

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

See Also

createGrid() getAOOSilent()

Other gridUncertainty functions: gridUncertaintyBase(), gridUncertaintyRandom(), gridUncertaintyRestricted(), gridUncertaintySimulation(), gridUncertainty()

Function to compute AOO with grid uncertainty systematically with stopping rule and restrictions

Description

gridUncertaintyRestricted determines the number of area of occupancy (AOO) grid cells occupied by a species or ecosystem systematically. It will only stop when the AOO calculated does not improve (decrease) after a set number of split scenarios. The number of grids within each split is restricted to only include those which are already found nearby to ones already with the minimum AOO.

Usage

gridUncertaintyRestricted(
  input.data,
  grid.size,
  n.AOO.improvement,
  min.percent.rule = FALSE,
  percent = 1
)

Arguments

input.data

Spatial object of an ecosystem or species distribution. Please use a CRS with units measured in metres.
grid.size

A number specifying the width of the desired grid square (in same units as your coordinate reference system)
n.AOO.improvement

Specifies the minimum number of rounds the calculated AOO is not improved before stopping the function.
min.percent.rule

Logical. If TRUE, a minimum area threshold must be passed before a grid is counted as an AOO grid.
percent

Numeric. The minimum percent to be applied as a threshold for the min.percent.rule.

Value

A list containing the following:

  • Data frame of results showing the minimum AOO calculated for each shift scenario

  • Single SpatialPolygonsDataFrame containing the AOO grid which would produce the minimum AOO calculated

Author(s)

Calvin Lee [email protected]

See Also

Other gridUncertainty functions: gridUncertaintyBase(), gridUncertaintyRandomManual(), gridUncertaintyRandom(), gridUncertaintySimulation(), gridUncertainty()

Function to investigate behaviour of AOO under various split scenarios

Description

gridUncertaintySimulation returns the maximum and minimum number of area of occupancy (AOO) grid cells occupied by a species or ecosystem in incremental splits using gridUncertaintyBase.

Usage

gridUncertaintySimulation(
  input.data,
  grid.size,
  simulations,
  min.percent.rule = FALSE,
  percent = 1
)

Arguments

input.data

Spatial object of an ecosystem or species distribution. Please use a CRS with units measured in metres.
grid.size

A number specifying the width of the desired grid square (in same units as your coordinate reference system)
simulations

Specifies the maximum number of splits to be performed on the generated grid
min.percent.rule

Logical. If TRUE, a minimum area threshold must be passed before a grid is counted as an AOO grid.
percent

Numeric. The minimum percent to be applied as a threshold for the min.percent.rule.

Value

Data frame of results showing the minimum and maximum AOO calculated for each grid shift scenario.

Author(s)

Calvin Lee [email protected]

See Also

Other gridUncertainty functions: gridUncertaintyBase(), gridUncertaintyRandomManual(), gridUncertaintyRandom(), gridUncertaintyRestricted(), gridUncertainty()

Create Area of Occupancy (AOO) grid for an ecosystem or species distribution

Description

makeAOOGrid is a generic function that creates grids representing the area of occupancy for distributions based on the input spatial data. It includes capability for specifying whether a minimum percent of the grid cell needs to be occupied before it is counted in the AOO. This functionality is important for assessing the IUCN Red List of Ecosystems Criteria B.

Usage

makeAOOGrid(input.data, grid.size, min.percent.rule = FALSE, percent = 1)

Arguments

input.data

Spatial object of an ecosystem or species distribution. Please use a CRS with units measured in metres.
grid.size

A number specifying the width of the desired grid square (in same units as your coordinate reference system)
min.percent.rule

Logical. If TRUE, a minimum area threshold must be passed before a grid is counted as an AOO grid.
percent

Numeric. The minimum percent to be applied as a threshold for the min.percent.rule

Value

A shapefile of grid cells occupied by an ecosystem or species

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

References

Bland, L.M., Keith, D.A., Miller, R.M., Murray, N.J. and Rodriguez, J.P. (eds.) 2016. Guidelines for the application of IUCN Red List of Ecosystems Categories and Criteria, Version 1.0. Gland, Switzerland: IUCN. ix + 94pp. Available at the following web site: https://iucnrle.org/

See Also

Other AOO functions: createGrid(), getAOOSilent(), getAOO()

Examples

crs.UTM55S <- '+proj=utm +zone=55 +south +ellps=WGS84 +datum=WGS84 +units=m +no_defs'
r1 <- raster(ifelse((volcano<130), NA, 1), crs = crs.UTM55S)
extent(r1) <- extent(0, 6100, 0, 8700)
AOO_grid <- makeAOOGrid(r1, 1000, min.percent.rule = TRUE, percent = 1)

Creates Extent of occurrence (EOO) Polygon

Description

makeEOO is a generic function that creates a minimum convex polygon enclosing all occurrences of the provided spatial data. If the input provided is a raster layer, the points are taken from a buffer that has the radius of half of the shorter edge of the pixel around the centroid.

Usage

makeEOO(input.data)

Arguments

input.data

Spatial object of an ecosystem or species distribution. Please use a CRS with units measured in metres.

Value

An object of class SpatVect representing the EOO of input.data. Also inherits its CRS.

Author(s)

Nicholas Murray [email protected], Calvin Lee [email protected]

References

Bland, L.M., Keith, D.A., Miller, R.M., Murray, N.J. and Rodriguez, J.P. (eds.) 2016. Guidelines for the application of IUCN Red List of Ecosystems Categories and Criteria, Version 1.0. Gland, Switzerland: IUCN. ix + 94pp. Available at the following web site: https://iucnrle.org/

See Also

Other EOO functions: getAreaEOO()

Examples

library(terra)
crs.UTM55S <- '+proj=utm +zone=55 +south +ellps=WGS84 +datum=WGS84 +units=m +no_defs'
r1 <- rast(ifelse((volcano<130), NA, 1), crs = crs.UTM55S)
ext(r1) <- c(0, 6100, 0, 8700)
EOO.polygon <- makeEOO(r1)

Sequential extrapolation estimate

Description

sequentialExtrapolate uses rates of decline from getDeclineStats and generates a sequence of estimates at regular time-steps. Useful for generating a sequence for plotting graphs.

Usage

sequentialExtrapolate(A.t1, year.t1, nYears, ARD = NA, PRD = NA, ARC = NA)

Arguments

A.t1

Area at time t1
year.t1

Year of time t1
nYears

Number of years since t1 for prediction. Use negative values for backcasting
ARD

Absolute rate of decline
PRD

Proportional rate of decline
ARC

Annual rate of change

Value

A dataframe with the forecast year, and a combination of:

  • Sequence of values as extrapolated with absolute rate of decline (ARD)

  • Sequence of values as extrapolated with proportional rate of decline (PRD)

  • Sequence of values as extrapolated with annual rate of change (ARC)

Author(s)

Calvin Lee [email protected]

References

Bland, L.M., Keith, D.A., Miller, R.M., Murray, N.J. and Rodriguez, J.P. (eds.) 2016. Guidelines for the application of IUCN Red List of Ecosystems Categories and Criteria, Version 1.0. Gland, Switzerland: IUCN. ix + 94pp. Available at the following web site: https://iucnrle.org/

See Also

Other change_functions: extrapolateEstimate(), futureAreaEstimate()

Examples

a.r1 <- 23.55
a.r2 <- 15.79
decline.stats <- getDeclineStats(a.r1, a.r2, year.t1 = 1990, year.t2 = 2012,
                                 methods = 'PRD')
a.2040.PRD.seq <- sequentialExtrapolate(a.r1, a.r2, year.t1 = 1990, nYears = 50,
                                        PRD = decline.stats$PRD)