Skip to main content

Advertisement

Log in

Spatial Graphs: Principles and Applications for Habitat Connectivity

  • Published:
Ecosystems Aims and scope Submit manuscript

ABSTRACT

Well-founded methods to assess habitat connectivity are essential to inform land management decisions that include conservation and restoration goals. Indeed, to be able to develop a conservation plan that maintains animal movement through a fragmented landscape, spatial locations of habitat and paths among them need to be represented. Graph-based approaches have been proposed to determine paths among habitats at various scales and dispersal movement distances, and balance data requirements with information content. Conventional graphs, however, do not explicitly maintain geographic reference, reducing communication capacity and utility of other geo-spatial information. We present spatial graphs as a unifying theory for applying graph-based methods in a geographic context. Spatial graphs integrate a geometric reference system that ties patches and paths to specific spatial locations and spatial dimensions. Arguably, the complete graph, with paths between every pair of patches, may be one of the most relevant graphs from an ecosystem perspective, but it poses challenges to compute, process and visualize. We developed Minimum Planar Graphs as a spatial generalization of Delaunay triangulations to provide a reasonable approximation of complete graphs that facilitates visualization and comprehension of the network of connections across landscapes. If, as some authors have suggested, the minimum spanning tree identifies the connectivity “backbone” of a landscape, then the Minimum Planar Graph identifies the connectivity “network”. We applied spatial graphs, and in particular the Minimum Planar Graph, to analyze woodland caribou habitat in Manitoba, Canada to support the establishment of a national park.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1.
Figure 2.
Figure 3.
Figure 4.
Figure 5.
Figure 6.
Figure 7.

Similar content being viewed by others

REFERENCES

  • Adriaensen F, Chardon JP, De Blust G, Swinnen E, Villalga S, Gulinck H, Matthysen E. 2003. The application of “least-cost” modelling as a functional landscape model. Landsc Urban Plan 64:233–47

    Article  Google Scholar 

  • Andrén H. 1994. Effects of habitat fragmentation on birds and mammals in landscapes with different proportions of suitable habitat: a review. Oikos 71:355–66

    Article  Google Scholar 

  • Bélisle M. 2005. Measuring landscape connectivity: the challenge of behavioural landscape ecology. Ecology 86:1988–95

    Article  Google Scholar 

  • Bélisle M, Desrochers A. 2002. Gap-crossing decisions by forest birds: an empirical basis for parameterizing spatially-explicit, individual-based models. Landsc Ecol 17:219–31

    Article  Google Scholar 

  • Bélisle M, Desrochers A, Fortin M-J. 2001. Influence of forest cover on the movements of forest birds: a homing experiment. Ecology 82:1893–904

    Google Scholar 

  • Brooks CP 2003. A scalar analysis of landscape connectivity. Oikos 102(2):433–9

    Article  Google Scholar 

  • Brown WK, Theberge JB. 1990. The effect of extreme snowcover on feeding-site selection by woodland caribou. J Wildl Manage 54:161–8

    Article  Google Scholar 

  • Bunn AG, Urban DL, Keitt TH. 2000. Landscape connectivity: a conservation application of graph theory. J Environ Manage 59(4):265–78

    Article  Google Scholar 

  • Cain D, Riitters K, Orvis K. 1997. A multi-scale analysis of landscape statistics. Landsc Ecol 12:199–212

    Article  Google Scholar 

  • Calabrese JM, Fagan WF. 2004. A comparison shoppers’ guide to connectivity metrics. Front Ecol Environ 2:529–36

    Article  Google Scholar 

  • COSEWIC. 2001. Species at Risk. Environment Canada, Committee on the Status of Endangered Wildlife in Canada. Available at URL: http://www.speciesatrisk.gc.ca

  • Darby WR, Pruitt WO Jr. 1984. Habitat use, movements and grouping behaviour of woodland caribou, Rangifer tarandus caribou, in southeastern Manitoba. Can Field Nat 98:184–90

    Google Scholar 

  • Fahrig L, Merriam G. 1994. Conservation of fragmented populations. Conserv Biol 8:50–9

    Article  Google Scholar 

  • Fall A, Fall J. 2001. A domain-specific language for models of landscape dynamics. Ecol Model 141(1–3):1–18

    Google Scholar 

  • Getis A, Boots B. 1978. Models of spatial processes: an approach to the study of point, line and area patterns. Cambridge: Cambridge University Press

    Google Scholar 

  • Goodwin BJ, Fahrig L. 2002. How does landscape structure influence landscape connectivity? Oikos 99:552–70

    Article  Google Scholar 

  • Gustafson EJ. 1998. Quantifying landscape spatial pattern: what is the state of the art? Ecosystems 1:143–56

    Article  Google Scholar 

  • Harary F. 1972. Graph theory. Reading (MA): Addison-Wesley

    Book  Google Scholar 

  • Jaeger JAG. 2000. Landscape division, splitting index, and effective mesh size: new measures of landscape fragmentation. Landsc Ecol 15:115–30

    Article  Google Scholar 

  • Jelenski D, Wu J. 1996. The modifiable areal unit problem and implications for landscape ecology. Landsc Ecol 11:129–40

    Article  Google Scholar 

  • Keil JM, Gutwin CA. 1992. Classes of graphs which approximate the complete Euclidean graph. Disc Comput Geom 7(1):13–28

    Article  Google Scholar 

  • Keitt TH, Urban DL, Milne BT. 1997. Detecting critical scales in fragmented landscapes. Conservation Ecology [online] 1(1):4. URL: http://www.consecol.org/vol1/iss1/art4

  • McGarigal K, Marks BJ. 1995. FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. US Forest Service General Technical Report PNW 351

  • Manitoba Conservation. 2006. Manitoba’s conservation and recovery strategy for boreal woodland caribou (Rangifer tarandus caribou). Available at URL: http://www.manitoba.ca/conservation

  • Manly BJF, McDonald L, Thomas D, McDonald TL, Erickson WP. 2002. Resource selection by animals: statistical design and analysis for field studies, 2nd edn. Dordrecht: Kluwer Academic

    Google Scholar 

  • Manseau M, Fall A, O’Brien D, Fortin M-J. 2002. National Parks and the protection of woodland caribou: a multi-scale landscape analysis method. Res Links 10(2):24–8

    Google Scholar 

  • Manseau M, Rennie F, Mondor C. 2001. Determination of ecological boundaries for the establishment and management of Canadian National Park. In: Harmon D, Ed. Crossing Boundaries in Park Management. Proceedings of the 11th conference on research and resource management in parks and on public lands. Michigan: The George Wright Society, Hancock. pp 294–302

  • Marcot BG, Chinn PZ. 1982. Use of graph theory measures for assessing diversity of wildlife habitat. In: Lamberson R, Ed. Mathematical models of renewable resources. Proceedings of the 1st Pacific Coast conference on mathematical models of renewable resources. Arcata (CA): Humboldt State University. pp 69–70

  • O’Brien DT, Manseau M, Fall A, Fortin M-J. 2006. Testing the importance of spatial configuration of winter habitat for woodland caribou: an application of graph theory. Biol Conserv 130:70–83

    Article  Google Scholar 

  • Okabe A, Boots B, Sugihara K, Chiu SN. 2000. Spatial tessellations—Concepts and applications of Voronoi diagrams, 2nd edn. Chichester: Wiley

    Google Scholar 

  • Pickett STA, White PS, Eds. 1985. The ecology of natural disturbance and patch dynamics. Orlando (FL): Academic

  • Pither R, Manseau M, Clark J, Ball M, Wilson P. 2005. The relationship between landscape connectivity and genetic similarity among populations and individuals of woodland caribou in Manitoba. In: Ecological Society of America Conference, Montreal, August 2005

  • Qi Y, Wu J. 1996. Effects of changing spatial resolution on the results of landscape pattern analysis using spatial autocorrelation indices. Landsc Ecol 11(1):39–49

    Article  Google Scholar 

  • Reingold EM, Nievergelt J, Deo N. 1977. Combinatorial algorithms: theory and practice. Englewood (NJ): Prentice-Hall

    Google Scholar 

  • Ricotta C, Stanisci A, Avena GC, Blasi C. 2000. Quantifying the network connectivity of landscape mosaics: a graph-theoretical approach. Community Ecol 1(1):89–94

    Article  Google Scholar 

  • Schaefer JA. 1996. Canopy, snow and lichens on woodland caribou range in southeastern Manitoba. Rangifer Special Issue 9:239–44

    Google Scholar 

  • Schippers P, Verboom J, Knaapen JP, van Apeldoorn RC. 1996. Dispersal and habitat connectivity in complex heterogeneous landscapes: an analysis with a GIS-based random walk model. Ecography 19:97–106

    Article  Google Scholar 

  • Schumaker NH. 1996. Using landscape indices to predict habitat connectivity. Ecology 77(4):1210–25

    Article  Google Scholar 

  • Sutherland GD, Waterhouse FL, Fall A, O’Brien D, Harestad AS. 2006. A framework for landscape analysis of habitat supply and effects on populations of the northern spotted owl in British Columbia. Special Report, BC Ministry of Forests and Range, Research Branch, Victoria, BC

  • Taylor PD, Fahrig L, Henein K, Merriam G. 1993. Connectivity is a vital element of landscape structure. Oikos 68:571–2

    Article  Google Scholar 

  • Tischendorf L. 2001. Can landscape indices predict ecological processes consistently? Lands Ecol 16:235–54

    Article  Google Scholar 

  • Tischendorf L, Fahrig L. 2000. On the usage and measurement of landscape connectivity. Oikos 90:7–19

    Article  Google Scholar 

  • Urban D, Keitt T. 2001. Landscape connectivity: a graph-theoretic perspective. Ecology 82(5):1205–18

    Article  Google Scholar 

  • Wagner HH, Fortin M-J. 2005. Spatial analysis of landscapes: concepts and statistics. Ecology 86:1975–87

    Article  Google Scholar 

  • With KA, Gardner RH, Turner MG. 1997. Landscape connectivity and population distributions in heterogeneous environments. Oikos 78:151–69

    Article  Google Scholar 

Download references

ACKNOWLEDGEMENTS

This research was funded by Parks Canada Species at Risk Recovery Action and Education Fund, a program supported by the National Strategy for the Protection of Species at Risk and Parks Canada Western Canada Service Research Fund as well as GEIODE Strategic Initiative Program. Participating partners of this project were Manitoba Hydro, Manitoba Conservation, Tolko Ltd. and Natural Resources Institute of the University of Manitoba. We thank Jennifer Keeney for collating data and doing the GIS and mapping work. We also thank Richard Pither, Pasi Reunanen, Patrick James, Glenn Sutherland, Doug Steventon and two anonymous reviewers for helpful comments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrew Fall.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Fall, A., Fortin, MJ., Manseau, M. et al. Spatial Graphs: Principles and Applications for Habitat Connectivity. Ecosystems 10, 448–461 (2007). https://doi.org/10.1007/s10021-007-9038-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10021-007-9038-7

Key words

Navigation