Connectivity Analysis Toolkit License Version history Getting Started Overview of Methods Three Methods for Connectivity Analysis Subset Centrality: Mapping Linkages All-pairs Centrality: Mapping Landscape Connectivity Network Flow Analysis of Time Series Input files Output files Running the Toolkit from the GUI Hexmap Tab Graphs Tab Connectivity Tab Output Tab Running the Toolkit from the Command Prompt Flowchart of analysis process Examples Example 1: Shortest-path betweenness centrality (BC) Example 2: Shortest-path betweenness subset centrality Example 3: Comparison of subset and all-pairs current flow BC Example 4: Comparison of shortest-path and current flow BC Tutorial Exercise 1 - Mapping linkages with min-cost-max-flow subset centrality Exercise 2 - Mapping linkages with shortest-path subset centrality Exercise 3 - Mapping landscape connectivity with all-pairs centrality Exercise 4 - Mapping connectivity under climate change: analysis of time series Troubleshooting Related Resources System requirements Contacts & Credits
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# Related Resources Publications using the Connectivity Analysis Toolkit Carroll, C., B. McRae, and A. Brookes. 2012. Use of Linkage Mapping and Centrality Analysis Across Habitat Gradients to Conserve Connectivity of Gray Wolf Populations in Western North America. Conservation Biology 26:78-87. Related software resources Circuitscape (website) is a software designed for analyzing current flow between two or more source locations on high-resolution raster surfaces (habitat maps). Both the CAT and Circuitscape calculate current flow as a measure of connectivity, but Circuitscape is designed to calculate current flow between a subset of nodes or core areas on raster datasets, whereas the CAT is better suited to current flow centrality calculations. While Circuitscape can be used to calculate current flow centrality by summing currents between all pairs, it is not optimized for this purpose. Because Circuitscape is designed to calculate current, voltage, and resistance, it does not calculate other connectivity measures employed by the CAT, such as least-cost paths. It does, however, accommodate very large raster datasets (with millions of nodes, depending on availability of RAM). Hexsim (website) is a software designed to perform spatial population viability analysis. CAT functionality such as hexmap generation was derived from Hexsim. Users who are interested in exploring more complex and realistic simulations of functional connectivity (e.g., dispersal barriers) may be interested in using Hexsim. UNICOR (website) is a software that allows calculation of a metric that is similar to approximate shortest-path betweenness centrality on high-resolution rasters. Publications cited in this documentation Adriaensen, F., J. P. Chardon, G. D. Blust, E. Swinnen, S. Villalba, H. Gulinck, and E. Matthysen. 2003. The application of ‘‘least-cost’’ modeling as a functional landscape model. Landscape and Urban Planning 64:233–247. Ahuja, R. K., T. L. Magnanti, and J. B. Orlin. 1993. Network flows: theory, algorithms, and applications. Prentice Hall, Englewood Cliffs, New Jersey. Beier, P., D. R. Majka, and W. D. Spencer. 2008. Forks in the road: choices in procedures for designing wildland linkages. Conservation Biology 22:836–851. Bodin, O., M. Tengö, A. Norman, J. Lundberg, and T. Elmqvist. 2006. The value of small size: loss of forest patches and ecological thresholds in southern Madagascar. Ecological Applications 16:440–451. Borgatti, S. P. 2005. Centrality and network flow. Social Networks 27:55-71. Borgatti, S. P., and M. G. Everett. 2006. A graph-theoretic perspective on centrality. Social Networks 28:466–484. Brandes, U. 2001. A faster algorithm for betweenness centrality. Journal of Mathematical Sociology 25:163-177. Brandes, U. and D. Fleischer. 2005. Centrality Measures Based on Current Flow. Proceedings of the 22nd Symposium Theoretical Aspects of Computer Science 533-544. Brandes, U., and C. Pich. 2007. Centrality estimation in large networks. International Journal Of Bifurcation And Chaos (Special Issue On Complex Networks’ Structure And Dynamics) 17:2303-2318. Bunn, A. G., D. L. Urban, and T. H. Keitt. 2000. Landscape connectivity: a conservation application of graph theory. Journal of Environmental Management 59:265–278. Chetkiewicz, C. L. B., C. C. St Clair, and M. S. Boyce. 2006. Corridors for conservation: integrating pattern and process. Annual Review of Ecology, Evolution, and Systematics, 37:317-342. Cushman, S. A., K. Gutzweiler, J. S. Evans, and K. McGarigal. 2010. The gradient paradigm: a conceptual and analytical framework for landscape ecology. Pages 83-108 in S.A. Cushman and F. Huettmann, editors, Spatial Complexity, Informatics, and Wildlife Conservation. Springer, New York, New York. Dijkstra, E. W., 1959. A note on two problems in connexion with graphs. Numerische Mathematik 1:269-271. EGRES. 2010. LEMON, Library for Efficient Modeling and Optimization in Networks. Egervary Combinatorial Optimization Research Group, EGRES, Budapest, Hungary. Available at http://lemon.cs.elte.hu. Estrada, E., and O. Bodin. 2008. Using network centrality measures to manage landscape connectivity. Ecological Applications 18: 1810–1825. Freeman, L. C. 1977. A set of measures of centrality based on betweenness. Sociometry 40:35-41. Freeman, L.C., S. P. Borgatti, and D. R. White. 1991. Centrality in valued graphs: a measure of betweenness based on network flow. Social Networks 13:141–154. Hagberg, A., D. Schult, and P. Swart. 2008. Exploring network structure, dynamics, and function using NetworkX. Pages 11–16 in G. Varoquaux, T. Vaught, and J. Millman, editors, Proceedings of the 7th Python in Science Conference, Pasadena, California. Lee-Yaw, J. A., A. Davidson, B. H. McRae, and D. M. Green. 2009. Do landscape processes predict phylogeographic patterns in the wood frog? Molecular Ecology 18:1863-1874. Long, R., P. MacKay, J. Ray, and W. Zielinski, editors. 2008. Noninvasive survey methods for carnivores. Island Press, Washington, D.C. McRae, B.H., and P. Beier. 2007. Circuit theory predicts gene flow in plant and animal populations. Proceedings of the National Academy of Sciences of the USA 104:19885-19890. McRae, B. H., B. G. Dickson, T. H. Keitt, and V. B. Shah. 2008. Using circuit theory to model connectivity in ecology and conservation. Ecology 10: 2712-2724. Moilanen, A., H. Kujala, and J. Leathwick. 2009. The Zonation framework and software for conservation prioritization. Pages 196-210 in A. Moilanen, K. A. Wilson, and H. P. Possingham, editors. Spatial conservation prioritization: Quantitative methods and computational tools. Oxford University Press, Oxford, UK. Newman, M. E. J. 2005. A measure of betweenness centrality based on random walks. Social Networks 27: 39-54. Phillips, S. J., P. Williams, G. Midgley, and A. Archer. 2008. Optimizing dispersal corridors for the Cape Proteaceae using network flow. Ecological Applications 18:1200–1211. Possingham, H. P., I. R. Ball, and S. Andelman. 2000. Mathematical methods for identifying representative reserve networks. Pages 291–306 in S. Ferson and M. Burgman, editors. Quantitative methods for conservation biology. Springer-Verlag, New York, New York, USA. Pressey, R. L., M. Cabeza, M. E. Watts, R. M. Cowling, and K. A. Wilson. 2007. Conservation planning in a changing world. Trends in Ecology and Evolution 22:583-592. Schumaker, N. H., T. Ernst, D. White, J. Baker, and P. Haggerty. 2004. Projecting wildlife responses to alternative future landscapes in Oregon’s Willamette basin. Ecological Applications 14:381–400. Schwartz, M. K., J. P. Copeland, N. J. Anderson, J. R. Squires, R. M. Inman, K. S. McKelvey, K. L. Pilgrim, L. P. Waits, and S. A. Cushman. 2009. Wolverine gene flow across a narrow climatic niche. Ecology 90:3222-3232. Spencer, W.D., P. Beier, K. Penrod, K. Winters, C. Paulman, H. Rustigian-Romsos, J. Strittholt, M. Parisi, and A. Pettler. 2010. California Essential Habitat Connectivity Project: A Strategy for Conserving a Connected California. Prepared for California Department of Transportation, California Department of Fish and Game, and Federal Highways Administration. Theobald, D. M. 2006. Exploring the functional connectivity of landscapes using landscape networks. Pages 416–443 in K. R. Crooks and M. A. Sanjayan, editors. Connectivity conservation: maintaining connections for nature. Cambridge University Press, Cambridge, UK. Urban, D. L., E. S. Minor, E. A. Treml, and R. S. Schick. 2009. Graph models of habitat mosaics. Ecology Letters 12:260–273. Urban, D., and T. Keitt. 2001. Landscape connectivity: a graph-theoretic perspective. Ecology 82:1205-1218. van Rossum, G. and Drake, F. L., editors. 2006. Python reference manual. Python Software Foundation. Available at http://docs.python.org/ref/ref.html. Young, A. G., and G. M. Clarke. 2000. Genetics, demography and viability of fragmented populations. Cambridge University Press, Cambridge, UK.
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