Computes several landscape metrics, mostly derived from graph theory or assuming a graph representation of the landscape.
Usage
metrics.graph(rl, metric)
Arguments
rl
Object of class 'landscape'.
metric
one of the following connectivity metrics:
'NC' - Number of components,groups of connected patches, in the landscape graph (Urban and Keitt, 2001).
'LNK' - Number of links connecting the patches (considering that the maximum distance is t
Value
Returns a numeric value, which corresponds to the value of the chosen connectivity metric for the given landscape.
Details
These metrics assume different types of links between nodes (patches). Some assume probabilistic connections between nodes (e.g. PC) while others assume binary connections (e.g. NC, SLC, LNK, IIC). Some of these metrics are very simple, while others are more complex. From the simpler ones (such as NC and LNK) to the more complex (such as IIC and PC). Some of these measures of connectivity are purely structural; the same landscape has the same index whatever the species, while others are measures of functional, where the connectivity of a given landscape is dependent on the species. Precaution must be taken when looking at the outputs produced by some of these metrics (particularly the simpler, structural ones). Regardless of being simpler to compute, the outputs might be misleading. This metrics can however be used as exploratory tools.
References
Bunn, A. G., Urban, D. L., and Keitt, T. H. (2000). Landscape connectivity: a conservation application of graph theory. Journal of Environmental Management, 59(4): 265-278.
Fall, A., Fortin, M. J., Manseau, M., and O' Brien, D. (2007). Spatial graphs: principles and applications for habitat connectivity. Ecosystems, 10(3): 448-461.
Ivanciuc, O., Balaban, T. S., and Balaban, A. T. (1993). Design of topological indices. Part 4. Reciprocal distance matrix, related local vertex invariants and topological indices. Journal of Mathematical Chemistry, 12(1): 309-318.
Minor, E. S., and Urban, D. L. (2007). Graph theory as a proxy for spatially explicit population models in conservation planning. Ecological Applications, 17(6): 1771-1782.
Minor, E. S., and Urban, D. L. (2008). A Graph-Theory Framework for Evaluating Landscape Connectivity and Conservation Planning. Conservation Biology, 22(2): 297-307.
O'Brien, D., Manseau, M., Fall, A., and Fortin, M. J. (2006). Testing the importance of spatial configuration of winter habitat for woodland caribou: an application of graph theory. Biological Conservation, 130(1): 70-83.
Pascual-Hortal, L., and Saura, S. (2006). Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation. Landscape Ecology, 21(7): 959-967.
Plavsic, D., Nikolic, S., Trinajstic, N., and Mihalic, Z. (1993). On the Harary index for the characterization of chemical graphs. Journal of Mathematical Chemistry, 12(1): 235-250.
Ricotta, C., Stanisci, A., Avena, G. C., and Blasi, C. (2000). Quantifying the network connectivity of landscape mosaics: a graph-theoretical approach. Community Ecology, 1(1): 89-94.
Saura, S., and Pascual-Hortal, L. (2007). A new habitat availability index to integrate connectivity in landscape conservation planning: comparison with existing indices and application to a case study. Landscape and Urban Planning, 83(2): 91-103.
Urban, D., and Keitt, T. (2001). Landscape connectivity: a graph-theoretic perspective. Ecology, 82(5): 1205-1218.