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RESEARCH ARTICLE
Contents Vol 56(6)

Measuring fragmentation of seagrass landscapes: which indices are most appropriate for detecting change?

Jai C. Sleeman A , Gary A. Kendrick B , Guy S. Boggs A and Bruce J. Hegge C
+ Author Affiliations
- Author Affiliations

A Charles Darwin University, Casuarina, NT 0909, Australia.

B School of Plant Biology, University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia.

C Oceanica Marine and Estuarine Specialists, 99 Broadway, Nedlands, WA 6009, Australia.

D Corresponding author. Email: jai.sleeman@cdu.edu.au

Marine and Freshwater Research 56(6) 851-864 https://doi.org/10.1071/MF04300
Submitted: 20 December 2004  Accepted: 26 May 2005   Published: 27 September 2005

Abstract

Many indices are available for assessment of spatial patterns in landscape ecology, yet there is presently no consensus about which ones effectively quantify habitat fragmentation. Research that has been carried out to date has evaluated indices primarily using computer-simulated models of terrestrial environments, but how they perform when applied to real landscapes, particularly in the marine environment, has received little attention. Eleven indices that are commonly used for quantifying habitat fragmentation were assessed for their abilities to measure different levels of fragmentation in 16-ha landscape windows of mapped seagrass. The landscape windows were grouped into five categories, from highly fragmented to continuous seagrass landscapes. Nested within the fragmentation categories were high and low levels of seagrass cover. Hierarchical analysis of variance techniques were used to differentiate between the different fragmentation categories and levels of seagrass cover within the fragmentation categories. Principal component analysis was also employed to determine strong correlations between the indices. The results suggest that (1) landscape division and (2) area-weighted mean perimeter to area ratio were the most appropriate indices for differentiating between independent levels of seagrass fragmentation. The splitting index may also be useful when the detection of small differences in cover is important.

Extra keywords: habitat fragmentation, indices, landscapes, metrics, patchiness, seagrass.


Acknowledgments

This research was funded by an Australian Research Council Discovery Grant (DP345856) to GAK at the University of Western Australia. DAL Science & Engineering enabled the supply of the aerial photography and seagrass mapping data. We thank two anonymous reviewers for their helpful comments.


References

Bell, S. S. , and Hicks, G. R. F. (1991). Marine landscapes and faunal recruitment a field test with seagrasses and copepods. Marine Ecology Progress Series 73, 61–68.
Forman R. T. T. (1995). ‘Land Mosaics, The Ecology of Landscapes and Regions.’ (Cambridge University Press: Cambridge, UK.)

Frost, M. T. , Rowden, A. A. , and Altril, M. J. (1999). Effect of habitat fragmentation on macroinvertebrate infaunal communities associated with the seagrass Zostera marina L. Aquatic Conservation: Marine and Freshwater Ecosystems 9, 255–263.
| Crossref | GoogleScholarGoogle Scholar | Hegge B. J., and Kendrick G. A. (2000). ‘Seagrass Mapping Owen Anchorage and Cockburn Sound 1999.’ (D.A. Lord & Associates Pty Ltd, Botany Department, UWA, Alex Wyllie & Associates Pty Ltd, NGIS Australia, Kevron Aerial Surveys Pty Ltd: Perth.)

Hovel, K. A. , and Lipcius, R. N. (2001). Habitat fragmentation in a seagrass landscape: patch size and complexity control blue crab survival. Ecology 82, 1814–1829.
McGarigal K., and Marks B. J. (1995). FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. General Technical Report Pnw 0, US Forest Service, Washington, DC.

McGarigal K. (2002). Landscape pattern metrics. In ‘Encyclopedia of Environmentrics, Vol. 2’. (Eds A. H. El-Shaarawi and W. W. Piegorsch.) pp. 1135–1142. (John Wiley and Sons: Sussex, UK.)

Newman, D. (1939). The distribution of range in samples from a normal population, expressed in terms of an independant estimate of standard deviation. Biometrika 31, 20–30.
Opdam P., Van Apeldoorn R., Schotman A., and Kalkhoven J. (1993). Population responses to fragmentation. In ‘Landscape Ecology of a Stressed Environment’. (Eds C. C. Vos and P. Opdam.) pp. 147–171. (Chapman & Hall: London.)

Rasheed, M. A. (1999). Recovery of experimentally created gaps within a tropical Zostera capricorini (Aschers) seagrass meadow, Queensland Australia. Journal of Experimental Marine Biology and Ecology 235, 183–200.
| Crossref | GoogleScholarGoogle Scholar |

Reed, R. A. , Johnson-Barnard, J. , and Baker, W. (1996). Fragmentation of a forested rocky mountain landscape, 1950–1993. Biological Conservation 75, 267–277.
| Crossref | GoogleScholarGoogle Scholar |

Riitters, K. H. , O’Neill, R. V. , Hunsaker, C. T. , Wickham, J. D. , Yankee, D. H. , and Timmins, S. P. (1995). A factor analysis of landscape pattern and structure metrics. Landscape Ecology 10, 23–39.
| Crossref | GoogleScholarGoogle Scholar |

Robbins, B. D. , and Bell, S. S. (2000). Dynamics of a subtidal seagrass landscape: seasonal and annual change in relation to water depth. Ecology 81, 1193–1205.


Saunders, D. A. , Hobbs, R. J. , and Margules, C. R. (1991). Biological consequences of ecosystem fragmentation: a review. Conservation Biology 5, 18–32.
| Crossref | GoogleScholarGoogle Scholar |

Saura, S. (2002). Effects of minimum mapping unit on land cover data spatial configuration and compostition. International Journal of Remote Sensing 23, 4853–4880.
| Crossref | GoogleScholarGoogle Scholar |

Saura, S. (2004). Effects of remote sensor spatial resolution and data aggregation on selected fragmentation indices. Landscape Ecology 19, 197–209.
| Crossref | GoogleScholarGoogle Scholar |

Saura, S. , and Martínez-Millán, J. (2000). Landscape patterns simulation with a modified random clusters method. Landscape Ecology 15, 661–678.
| Crossref | GoogleScholarGoogle Scholar |

Saura, S. , and Martínez-Millán, J. (2001). Sensitivity of landscape pattern metrics to map spatial extent. Photogrammetric Engineering and Remote Sensing 67, 1027–1036.


Schumaker, N. H. (1996). Using landscape indices to predict habitat connectivity. Ecology 77, 1210–1225.


Smith, K. A. , and Suthers, I. M. (2000). Consistent timing of juvenile fish recruitment to seagrass beds within two Sydney estuaries. Marine and Freshwater Research 51, 765–776.
| Crossref | GoogleScholarGoogle Scholar |

Trzcinski, M. K. , Fahrig, L. , and Merriam, G. (1999). Independent effects of forest cover and fragmentation on the distribution of forest breeding birds. Ecological Applications 9, 586–593.


Turner, M. G. (1989). Landscape ecology: the effect of pattern on process. Annual Review of Ecology and Systematics 20, 171–197.
| Crossref | GoogleScholarGoogle Scholar |

Turner, M. G. , and Ruscher, C. L. (1988). Changes in landscape patterns in Georgia, USA. Landscape Ecology 1, 241–251.
| Crossref | GoogleScholarGoogle Scholar |

Vidondo, B. , Duarte, C. M. , Middelboe, A. L. , Stefansen, K. , Luetzen, T. , and Nielsen, S. L. (1997). Dynamics of a landscape mosaic: Size and age distributions, growth and demography of seagrass Cymodocea nodosa patches. Marine Ecology Progress Series 158, 131–138.


Walker, D. I. , Hillman, K. A. , Kendrick, G. A. , and Lavery, P. (2001). Ecological significance of seagrasses: Assessment for management of environmental impact in Western Australia. Ecological Engineering 16, 323–330.
| Crossref | GoogleScholarGoogle Scholar |

Williams, S. L. (1990). Experimental studies of Caribbean seagrass bed development. Ecological Monographs 60, 449–469.