Landscape Ecology

, Volume 28, Issue 10, pp 1949–1959 | Cite as

Identifying functionally connected habitat compartments with a novel regionalization technique

  • Peng Gao
  • John A. Kupfer
  • Diansheng Guo
  • Ting L. Lei
Research article


Landscape ecologists have increasingly turned to the use of landscape graphs in which a landscape is represented as a set of nodes (habitat patches) connected by links representing inter-patch-dispersal. This study explores the use of a graph-based regionalization method, Graph-based REgionalization with Clustering And Partitioning (GraphRECAP), to detect structural groups of habitat patches (compartments) in a landscape graph such that the connections (i.e. the movement of individual organisms) within the groups are greater than those across groups. Specifically, we mapped compartments using habitat and dispersal data for ring-tailed lemurs (Lemur catta) in an agricultural landscape in southern Madagascar using both GraphRECAP and the widely-used Girvan and Newman method. Model performance was evaluated by comparing compartment characteristics and three measures of network connectivity and traversability: the connection strength of habitat patches in the compartments (modularity), the potential ease of individual organism movements (Harary index), and the degree of alternative route presence (Alpha index). Compartments identified by GraphRECAP had stronger within-compartment connections, greater traversability, more alternative routes, and a larger minimum number of habitat patches within compartments, all of which are more desirable traits for ecological networks. Our method could thus facilitate the study of ecosystem resilience and the design of nature reserves and landscape networks to promote the landscape-scale dispersal of species in the fragmented habitats.


Ecoregionalization Graph theory Habitat connectivity Fragmentation Ring-tailed lemur 



This work was supported by a Dean’s Dissertation Fellowship from the College of Arts and Sciences at the University of South Carolina to the lead author. This work was also supported in part by the National Science Foundation under Grant No. 0748813. The lead author would like to thank Hai Jin’s help with programming. The authors would especially like to thank Dr. Örjan Bodin for the generous offer of the dataset of his published work.


  1. Bellisario B, Cerfolli F, Nascetti G (2010) Spatial network structure and robustness of detritus-based communities in a patchy environment. Ecol Res 25(4):813–821CrossRefGoogle Scholar
  2. Benton TG, Vickery JA, Wilson JD (2003) Farmland biodiversity: is habitat heterogeneity the key? Trends Ecol Evol 18(4):182–188CrossRefGoogle Scholar
  3. Bodin Ö, Norberg J (2007) A network approach for analyzing spatially structured populations in fragmented landscape. Landscape Ecol 22:31–44CrossRefGoogle Scholar
  4. Bodin Ö, Tengö M, Norman A, Lundberg J, Elmqvist T (2006) The value of small size: loss of forest patches and ecological thresholds in southern Madagascar. Ecol Appl 16(2):440–451PubMedCrossRefGoogle Scholar
  5. Borgatti SP, Everett MG, Freeman LC (2002) Ucinet forwindows: software for social network analysis. Analytic Technologies, HarvardGoogle Scholar
  6. Brooks CP (2003) A scalar analysis of landscape connectivity. Oikos 102(2):256–278Google Scholar
  7. Chen J, Yuan B (2006) Detecting functional modules in the yeast protein–protein interaction network. Bioinformatics 22(18):2283–2290PubMedCrossRefGoogle Scholar
  8. Clobert J, Le Galliard JF, Cote J, Meylan S, Massot M (2009) Informed dispersal, heterogeneity in animal dispersal syndromes and the dynamics of spatially structured populations. Ecol Lett 12(3):197–209PubMedCrossRefGoogle Scholar
  9. De Nooy W, Mrvar A, Batagelj V (2012) Exploratory social network analysis with Pajek, 2nd edn. Cambridge University Press, New YorkGoogle Scholar
  10. Devi BSS, Murthy MSR, Debnath B, Jha CS (2013) Forest patch connectivity diagnostics and prioritization using graph theory. Ecol Model 251:279–287CrossRefGoogle Scholar
  11. Dunn R, Dudbridge F, Sanderson CM (2005) The use of edge-betweenness clustering to investigate biological function in protein interaction networks. BMC Bioinformatics 6:1–14CrossRefGoogle Scholar
  12. Economo EP, Keitt TH (2010) Network isolation and local diversity in neutral metacommunities. Oikos 119(8):1355–1363CrossRefGoogle Scholar
  13. Foltête J-C, Clauzel C, Vuidel G (2012) A software tool dedicated to the modelling of landscape networks. Environ Modell Softw 38:316–327CrossRefGoogle Scholar
  14. Forman RTT (1995) Land mosaics: the ecology of landscapes and regions. Cambridge University Press, CambridgeGoogle Scholar
  15. Fortunato S (2010) Community detection in graphs. Phys Rep 486(3–5):75–174CrossRefGoogle Scholar
  16. Freeman LC (1977) Set of measures of centrality based on betweenness. Sociometry 40(1):35–41CrossRefGoogle Scholar
  17. Galpern P, Manseau M, Fall A (2011) Patch-based graphs of landscape connectivity: a guide to construction, analysis and application for conservation. Biol Conserv 144(1):44–55CrossRefGoogle Scholar
  18. Gilarranz LJ, Bascompte J (2012) Spatial network structure and metapopulation persistence. J Theor Biol 297:11–16PubMedCrossRefGoogle Scholar
  19. Girvan M, Newman MEJ (2002) Community structure in social and biological networks. Proc Natl Acad Sci USA 99(12):7821–7826PubMedCrossRefGoogle Scholar
  20. Glover F (1990) Tabu search: a tutorial. Interfaces 20(4):74–94CrossRefGoogle Scholar
  21. Guo D (2009) Flow mapping and multivariate visualization of large spatial interaction data. IEEE Trans Vis Comput Graph 15(6):1041–1048PubMedCrossRefGoogle Scholar
  22. Guo D, Jin H (2011) iRedistrict: geovisual analytics for redistricting optimization. J Vis Lang Comput 22(4):279–289CrossRefGoogle Scholar
  23. Hanski I (1997) Metapopulation dynamics from concepts and observations to predictive models. In: Hanski I, Gilpin M (eds) Metapopulation biology: ecology, genetics, and evolution. Academic Press, San Diego, pp 69–91CrossRefGoogle Scholar
  24. Hanski I, Gilpin M (1991) Metapopulation dynamics: brief-history and conceptual domain. Biol J Linn Soc 42(1–2):3–16CrossRefGoogle Scholar
  25. Holvorcem CGD, Tambosi LR, Ribeiro MC, Costa S, Bernardo Mesquita CA (2011) Anchor areas to improve conservation and increase connectivity within the Brazilian “Mesopotamia of Biodiversity”. Nat Conserv 9(2):225–231CrossRefGoogle Scholar
  26. Jordán F, Baldi A, Orci KM, Racz I, Varga Z (2003) Characterizing the importance of habitat patches and corridors in maintaining the landscape connectivity of a Pholidoptera transsylvanica (Orthoptera) metapopulation. Landscape Ecol 18(1):83–92CrossRefGoogle Scholar
  27. Kerr JT, Deguise I (2004) Habitat loss and the limits to endangered species recovery. Ecol Lett 7(12):1163–1169CrossRefGoogle Scholar
  28. Kupfer JA (1995) Landscape ecology and biogeography. Prog Phys Geogr 19(1):18–34CrossRefGoogle Scholar
  29. Kupfer JA (2012) Landscape ecology and biogeography: Rethinking landscape metrics in a post-FRAGSTATS landscape. Prog Phys Geog 36(3):400–420CrossRefGoogle Scholar
  30. Laita A, Mönkkönen M, Kotiaho JS (2010) Woodland key habitats evaluated as part of a functional reserve network. Biol Conserv 143(5):1212–1227CrossRefGoogle Scholar
  31. McIntyre NE, Strauss RE (2013) A new, multi-scaled graph visualization approach: an example within the playa wetland network of the Great Plains. Landscape Ecol 28(4):769–782CrossRefGoogle Scholar
  32. Mertl-Millhollen AS, Blumenfeld-Jones K, Raharison SM, Tsaramanana DR, Rasamimanana H (2011) Tamarind tree seed dispersal by ring-tailed lemurs. Primates 52(4):391–396PubMedCrossRefGoogle Scholar
  33. Minor ES, Urban DL (2007) Graph theory as a proxy for spatially explicit population models in conservation planning. Ecol Appl 17(6):1771–1782PubMedCrossRefGoogle Scholar
  34. Minor ES, Urban DL (2008) A graph-theory frarmework for evaluating landscape connectivity and conservation planning. Conserv Biol 22(2):297–307PubMedCrossRefGoogle Scholar
  35. Newman MEJ (2006) Modularity and community structure in networks. Proc Natl Acad Sci USA 103(23):8577–8582PubMedCrossRefGoogle Scholar
  36. Newman MEJ, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69(2):1–15CrossRefGoogle Scholar
  37. O’Brien D, Manseau M, Fall A, Fortin MJ (2006) Testing the importance of spatial configuration of winter habitat for woodland caribou: an application of graph theory. Biol Conserv 130(1):70–83CrossRefGoogle Scholar
  38. Ono N, Fujiwara Y, Yuta K (2005) Artificial metabolic system: An evolutionary model for community organization in metabolic networks. In: Capcarrère MS, Freitas AA, Bentley PJ, Johnson CG, Timmis J (eds) Proceedings on Advances in artificial life, 8th European Conference, ECAL 2005, Canterbury, U.K., September 5–9, 2005, Lecture Notes of Computer Science, vol 3630. Springer, Berlin, pp 716–724Google Scholar
  39. Pimm SL (1979) The structure of food webs. Theor Popul Biol 16(2):144–158PubMedCrossRefGoogle Scholar
  40. Rayfield B, Fortin MJ, Fall A (2011) Connectivity for conservation: a framework to classify network measures. Ecology 92(4):847–858PubMedCrossRefGoogle Scholar
  41. Reunanen P, Fall A, Nikula A (2012) Spatial graphs as templates for habitat networks in boreal landscapes. Biodivers Conserv 21(14):3569–3584CrossRefGoogle Scholar
  42. Rezende EL, Albert EM, Fortuna MA, Bascompte J (2009) Compartments in a marine food web associated with phylogeny, body mass, and habitat structure. Ecol Lett 12(8):779–788PubMedCrossRefGoogle Scholar
  43. Ricotta CA, Stanisci A, Avena GC, Blasi C (2000) Quantifying the network connectivity of landscape mosaics a graph theoretical approach. Community Ecol 1(1):89–94CrossRefGoogle Scholar
  44. Rubio L, Saura S (2012) Assessing the importance of individual habitat patches as irreplaceable connecting elements: an analysis of simulated and real landscape data. Ecol Complex 11:28–37CrossRefGoogle Scholar
  45. Saura S, Rubio L (2010) A common currency for the different ways in which patches and links can contribute to habitat availability and connectivity in the landscape. Ecography 33(3):523–537Google Scholar
  46. Theobald DM, Reed SE, Fields K, Soulê M (2012) Connecting natural landscapes using a landscape permeability model to prioritize conservation activities in the United States. Conserv Lett 5(2):123–133CrossRefGoogle Scholar
  47. Urban DL, Minor ES, Treml EA, Schick RS (2009) Graph models of habitat mosaics. Ecol Lett 12(3):260–273PubMedCrossRefGoogle Scholar
  48. Vergara PM, Perez-Hernandez CG, Hahn IJ, Soto GE (2013) Deforestation in central Chile causes a rapid decline in landscape connectivity for a forest specialist bird species. Ecol Res 28(3):481–492CrossRefGoogle Scholar
  49. Ziolkowska E, Ostapowicz K, Kuemmerle T, Perzanowski K, Radeloff VC, Kozak J (2012) Potential habitat connectivity of European bison (Bison bonasus) in the Carpathians. Biol Conserv 146(1):188–196CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Peng Gao
    • 1
  • John A. Kupfer
    • 1
  • Diansheng Guo
    • 1
  • Ting L. Lei
    • 1
  1. 1.Department of GeographyUniversity of South CarolinaColumbiaUSA

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