biodecrypt: An algorithm to attribute unidentified occurrence data based...

In leondap/recluster: Ordination Methods for the Analysis of Beta-Diversity Indices

An algorithm to attribute unidentified occurrence data based on a subset of identified records

Description

biodecrypt uses the function ahull from package alphahull to construct concave hulls with custom concavity (alpha) for each taxon. This function can also remove sea or ground areas from the analysis based on a SpatialPolygonsDataFrame representing the area of interest. The main input is represented by: i) a matrix of longitude and latitude (decimal degrees of longitude and latitude, WGS84) for all occurrence records, ii) a vector indicating species membership of each record in the same order of the matrix (1,2..n for known species and 0 for cases to be attributed). By using spatial coordinates, the list of identified records and alpha values, biodecrypt computes a concave hull for each species based on known records. Then, the function attempts to attribute unknown cases to their most likely species based on the comparison of hull localtion, geometry and the location of occurrence data (see details).

Usage

biodecrypt(mat, id, alpha = NULL, ratio = 2.5, buffer = 90, polygon=NULL, checkdist = T, minimum = 7, plot=T, map = NULL, 
    xlim = NULL, ylim = NULL, main = NULL)

Arguments

mat	A matrix for longitude and latitude (in decimal degrees) for all records.
id	A vector indicating species membership of each record (in the same order of mat). Identified records are indicated with 1,2..n, unidentified records with 0.
alpha	A vector indicating an initial alpha value for each species. If NULL, the default value of 8 for all species is used.
ratio	The minimum ratio between the distance from the second distant hull compared to the closest hull to allow attribution. Default 2.5 times.
buffer	A distance buffer from hulls (metres).
polygon	A SpatialPolygonsDataFrame with area of interests (ground or sea). Typically obtained from Natural Earth (https://www.naturalearthdata.com/). If NULL no removal is applied
checkdist	Logical, if TRUE cases attributed to a given species based on relative distance from hulls but closer to an identified record of another species are not attributed.
minimum	The minimum number of specimens required to build alpha hulls. If the number of identified specimens is lower, convex hulls are calculated to improve procedure stability.
map	A map to be plotted during the procedure to show the separation progress.
plot	Flag to FALSE is plotting the result is not required
xlim	Longitude boudaries for the map.
ylim	latitude boudaries for the map.
main	The name to be plotted on the graph

Details

Once the hulls for species are drawn according to the distribution of known records, each unidentified record could be either: i) inside more than one hull, ii) inside a single hull, or iii) outside all hulls. - Cases inside more than one hull In this case, the function cannot attribute the unidentified records to a species and only the a priori identified records belonging to intersection areas are passed to the final vector as identified. - Cases inside a single hull The unidentified records falling inside a single hull are attributed to that species if their distance to any other hull is higher than a buffer value provided by the user. Unidentified records inside the buffer of another hull are not attributed. - Cases outside all hulls The unidentified records which do not fall inside any hull are attributed to the closest hull if: i) the distance from the second nearest hull is higher than the buffer and if ii) the ratio between the minimum distance to the second closest hull and to the closest hull is more than a value indicated by the user (ratio). - Check for distances from the nearest identified record As described above, the attribution of unknown records is strictly determined by the distance from the hulls. The biodecrypt function also contains an option (checkdist=T) to check if cases attributed to a given species based on relative distance from hulls are closer to an identified record of another species, which may occasionally occur. If this option is selected (as in the default settings) these cases are not attributed to any species. In general, alpha values <5 return small and fragmented hulls with low predictive power; moreover, depending on the topology of occurrence data, some low alpha values could return no hulls. In this cases, biodecrypt tries to increase alpha up the the lowest value for which a hull is obtained. The alpha values used is stored in the alphaused vector.

Value

type	"sep" an argument to be passed to biodecrypt.plot.
areas	The areas of hulls for all the species (in km squares).
intersections	The areas of intersections among hulls for each pair of species.
sympatry	The fraction of the overlap area compared to the total area of the two hulls.
NUR	The percentage of Non-attributed Unidentified Records (NUR).
table	The result table with Longitude and Latitude for each occurrence datum, its id after the biodecrypt procedure (id2, the result of the procedure) and its initial id (id).
hulls	The hulls in sf format.
hullspl	The hulls in alphahull format.
alphaused	The values of alpha used fopr each species (see details).

Author(s)

Leonardo Dapporto

References

Platania L. et al. Assigning occurrence data to cryptic taxa improves climatic niche assessments: biodecrypt, a new tool tested on European butterflies. Glocal Ecology and Biogeography (2020)

Examples

n1<-7
n2<-7
mat<-rbind(cbind(rnorm(n = n1, mean = 1, sd = 2),rnorm(n = n1, mean = 40, sd = 2)),cbind(rnorm(n = n2, mean = 7, sd = 2),rnorm(n = n2, mean = 45, sd = 2)))

id<-c(rep(1,n1),rep(2,n2))
id[sample(c(1:(n1+n2)))[1:round((n1+n2)/4,0)]]<-0


# Make the separation with custom parameters
attribution<-biodecrypt(mat,id, alpha=c(10,10))

#plot the results
plot(mat,type="n")
biodecrypt.plot(attribution)

#Group plots into pies
biodecrypt.plot(attribution, square=2, minsize=0.5)


# Make the separation with custom parameters
# With a lower fraction values the first hull (alpha equal to 1) can become more 
#concave. Excluded dots works as a punctiform sub-hull in the attribution. 
attribution<-biodecrypt(mat,id, alpha=c(1,5), buffer=20, ratio=2, minimum=5)

#plot the results
plot(mat,type="n")
biodecrypt.plot(attribution)
	
{record attribution}

leondap/recluster documentation built on Nov. 11, 2024, 7:11 a.m.