hotspots: Calculate roadkill hotspots

In AMBarbosa/DeadCanMove: Assess How Spatial Roadkill Patterns Change with Temporal Sampling Scheme

Description

This function identifies the hotspot regions in a dataset, or in a submatrix compared to the total dataset, using an adaptation of the method of Malo et al. (2004).

Usage

hotspots(dataset, submat = NULL, region.column, 
subsampl.columns = NULL, n.events.column = NULL, hotspots = TRUE, 
confidence = 0.95, min.total.events = 0, min.hotspot.threshold = 2)

Arguments

dataset	name of the matrix or dataframe containing the complete data
submat	name of the matrix or dataframe containing the data of the group and sampling window/gap for which to calculate hotspots
region.column	name or index number of the column containing the regions (road sectors, sites) to classify as hotspots or non-hotspots
subsampl.columns	index numbers of the consecutive columns of submat (or, if there is no submat, of the dataset) containing the (daily) sampling data, e.g. 4:180
n.events.column	alternatively to subsampl.columns, the name or index number of the column containing the number of events (e.g. individual deaths) in each row
hotspots	logical, whether to calculate the hotspots
confidence	confidence threshold to consider hotspots
min.total.events	minimum total number of events to calculate hotspots. Not totally implemented yet!
min.hotspot.threshold	minimum number of events for a region to be considered a hotspot. If the Malo method says that regions with less than this value are hotspots, the value returned is NA. The default threshold is 2.

Value

A list with elements threshold (an integer value indicating the number of deaths obtained as a threshold for considering a site a roadkill hotspot) and hotspots (a data frame showing the total number of deaths per region and whether or not it was considered a hospot.)

Author(s)

A. Marcia Barbosa, J. Tiago Marques, Sara M. Santos

References

Malo, J.E., Suarez, F., Diez, A. (2004) Can we mitigate animal-vehicle accidents using predictive models? J. Appl. Ecol. 41, 701-710 (doi: 10.1111/j.0021-8901.2004.00929.x)

See Also

sequential.hotspots

Examples

data(roadkills)

hs <- hotspots(dataset = roadkills, submat = NULL, region.column = "segment",
subsampl.columns = 4:ncol(roadkills), confidence = 0.95)

hs

AMBarbosa/DeadCanMove documentation built on Nov. 3, 2021, 10:03 a.m.