Quantifying the network connectivity of landscape mosaics: a graph-theoretical approach

Connectivity determines a large number of ecological functions of the landscape, including seed and animal dispersal, gene flow and disturbance propagation, and is therefore a key to understanding fluxes of matter and energy within land mosaics. Several approaches to quantifying landscape connectivity are possible. Among these, graph theory may be used to represent a landscape as a series of interconnected patches, where flows occur as a result of structural and/or functional patch connectivity. Within this context, we propose the use of a graph-theoretic index (i.e., the Harary index) as a measure of landscape connectivity. Results derived from the analysis of the vegetation map of Palmarola (central Italy) show that, from a statistical and ecological viewpoint, the Harary index may be a better measure of landscape connectivity than more traditional indices derived from transportation geography.

[1]  Marinus J. M. Smulders,et al.  Dispersal patterns of Lonicera periclymenum determined by genetic analysis , 1998 .

[2]  Monica G. Turner,et al.  Predicting the spread of disturbance across heterogeneous landscapes , 1989 .

[3]  David G. Green,et al.  Connectivity and complexity in landscapes and ecosystems , 1994 .

[4]  C. Allen,et al.  Viewpoint: Sustainability of pinon-juniper ecosystems - A unifying perspective of soil erosion thresholds , 1998 .

[5]  N. Trinajstic,et al.  On the Harary index for the characterization of chemical graphs , 1993 .

[6]  Carlo Blasi,et al.  Spatial connectivity and boundary patterns in coastal dune vegetation in the Circeo National Park, Central Italy , 2000 .

[7]  V. R. Magnuson,et al.  Topological indices: their nature, mutual relatedness, and applications , 1987 .

[8]  Nathan H. Schumaker,et al.  Using Landscape Indices to Predict Habitat Connectivity , 1996 .

[9]  Jesús Molinari,et al.  A calibrated index for the measurement of evenness , 1989 .

[10]  David W. Roberts,et al.  Analysis of forest succession with fuzzy graph theory , 1989 .

[11]  Bruce T. Milne,et al.  Detecting Critical Scales in Fragmented Landscapes , 1997 .

[12]  K. McGarigal,et al.  FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. , 1995 .

[13]  Timothy H. Keitt,et al.  Detection of Critical Densities Associated with Pinon‐Juniper Woodland Ecotones , 1996 .

[14]  Jana Verboom,et al.  Dispersal and habitat connectivity in complex heterogeneous landscapes: an analysis with a GIS based random walk model , 1996 .

[15]  P. Beier,et al.  Do Habitat Corridors Provide Connectivity? , 1998 .

[16]  Carlo Blasi,et al.  Spatial connectivity and boundary patterns in coastal dune vegetation of Central Italy , 2000 .

[17]  C. Grashof-Bokdam,et al.  Forest species in an agricultural landscape in The Netherlands: effects of habitat fragmentation , 1997 .

[18]  H. Wiener Structural determination of paraffin boiling points. , 1947, Journal of the American Chemical Society.

[19]  N. Trinajstic,et al.  Information theory, distance matrix, and molecular branching , 1977 .

[20]  Helen Couclelis,et al.  Cellular Worlds: A Framework for Modeling Micro—Macro Dynamics , 1985 .