Calculation on network metrics a.k.a centralities.

These are functions under the igraph package adapted to calculate habitat connectivity. In the context of habitat connectivity, the functions can be interpreted as follows:

• [nn_sum()]: Calculates the sum of nearest neighbors igraph::graph.knn().

• [node_strength()]: Calculates the sum of edge weights of adjacent nodes igraph::graph.strength().

• [betweeness()]: Calculates the node betweenness based on the number of shortest paths. Because the igraph::betweenness() function in igraph interprets link weights as distances to calculate the shortest paths, the betweenness() function in geohabnet transforms the link weights (or the relative likelihood of pathogen or pest movement) in the adjacency matrix so that higher link weight values will be the shortest (or more likely) paths for pathogen or pest movement.

• [ev()]: Calculates the eigenvector centrality of positions within the network igraph::evcent().

• [closeness()]: measures how many steps is required to access every other vertex from a given vertex igraph::closeness(). Because the igraph::closeness() function in igraph interprets link weights as distances to calculate the shortest paths, the closeness() function in geohabnet transforms the link weights (or the relative likelihood of pathogen or pest movement) in the adjacency matrix so that higher link weight values will be the shortest (or more likely) paths for pathogen or pest movement.

• [degree()]: number of adjacent edges igraph::degree().

• [pagerank()]: page rank score for vertices igraph::page_rank().

Usage

nn_sum(crop_dm, ...)

node_strength(crop_dm, ...)

betweeness(crop_dm, ...)

ev(crop_dm, ...)

degree(crop_dm, ...)

closeness(crop_dm, ...)

pagerank(crop_dm, ...)

Arguments

crop_dm

A square adjacency matrix, in which rows and columns names represent nodes (or locations) and each entry indicate the relative likelihood of pathogen or pest movement between a pair of nodes. In the internal workflow, the adjacency matrix comes as a result of operations within sean() function. This weight represents the importance of the network metric in the habitat connectivity analysis.

...

arguments to corresponding igraph fun

Value

SpatRaster. Representing connectivity of each node or location.

See also

Other metrics: supported_metrics()