findSite: Delineating sites of potential importance to conservation

In track2KBA: Identifying Important Areas from Animal Tracking Data

Delineating sites of potential importance to conservation

Description

findSite uses the core areas (based on utilization distributions) of individual animals to identify areas used regularly used by a significant portion of the local source population (i.e. the tracked population).

Usage

findSite(KDE, represent, popSize = NULL, levelUD, thresh, polyOut = FALSE)

Arguments

KDE	estUDm or SpatialPixels/GridDataFrame. If estUDm, as created by estSpaceUse or adehabitatHR::kernelUD, if Spatial*, each column should correspond to the Utilization Distribution of a single individual or track.
represent	Numeric (between 0-1). Output value provided by repAssess which assesses how representative the tracking data are for characterising the space use of the wider population.
popSize	Numeric, the number of individuals breeding or residing at the origin location from where animals were tracked, quantifying the population that the tracking data represent. This number will be used to calculate how many animals use the delineated areas of aggregation. If no value for popSize is provided then output will be as the proportion of the population.
levelUD	Numeric (percentage). Specifies the quantile used for delineating the core use (or home range) areas of individuals based on the kernel density estimation (e.g core area=50, home range=95).
thresh	Numeric (percentage). Threshold percentage of local source population needed to be found using a location for it to be considered part of a 'potentialSite'. Default is set based on degree of representativeness.
polyOut	Logical. (Default TRUE) Should the output be a polygon dataset (TRUE) or grid of animal densities (FALSE). See 'Value' below for more details.

Details

findSite estimates the proportion of the local source population using an area based on the proportion of overlap among individual core areas and the degree of representativeness as quantified by repAssess). This value is then compared to a threshold of importance (i.e. a certain the population) to delineate areas as 'potentialSites'. Thresholds area either set automatically set on the representativenss of the sample (lower rep==higher threshold), or set manually by the user.

The areas identified are sites of ecological relevance to the populations, which may be significant for the wider region or entire species, which cane be assessed using global (or regional) criteria, such as those of the Key Biodiversity Area program.

The KBA criteria for site assessment are published in the KBA standard, which may be found here: http://www.keybiodiversityareas.org/.

If grid used for estimating core areas (i.e. KDE) is very memory-heavy (e.g. >10,000 cells) use polyOut = FALSE to speed things up.

Value

if polyOut = TRUE function returns an object of class sf containing polygon data with three data columns: Column N_IND indicates the number of tracked individuals whose core use area (at levelUD) overlapped with this polygon.

Column N_animals estimates the number of animals from the represented population that predictably use the polygon area during the tracked season. If no value for (at popSize) is provided, this number is the proportion of the represented population using the area.

Column potentialSite indicates whether the polygon can be considered a potential Site (TRUE) or not (FALSE).

if polyOut = FALSE function returns a gridded surface of class SpatialPixelsDataFrame, with the same three aforementioned columns as cell values.

If polyOut = TRUE the user may choose to automatically produce a plot of the result using plot=TRUE. The map produced displays the areas which hold aggregations above a certain threshold proportion of the population. If there are no areas displayed on the map, then either the species doesn't aggregate, the Scale is too small to identify aggregations in this species, or the tracked sample aren't representative enough to meet the thresholds.

Examples

KDE <- track2KBA::KDE_example

## identify potential sites
pot_site <- findSite(KDE, represent = 90, levelUD = 50)

track2KBA documentation built on July 3, 2024, 5:10 p.m.