Skip to main content

Advertisement

SpringerLink
Log in

Detecting hot and cold spots in a seagrass landscape using local indicators of spatial association

  • Research Article
  • Published:
Landscape Ecology Aims and scope Submit manuscript

Abstract

Eelgrass (Zostera marina) is an important feature of coastal ecosystems in Atlantic Canada, providing a suite of valuable ecosystem services. These services, and its sensitivity to stressors, have prompted efforts to characterize the spatial and temporal dynamics of eelgrass landscapes in order to facilitate management and monitoring of coastal ecosystem health. Current methods for broad-scale mapping of eelgrass rely on aerial remote sensing and may not be appropriate in certain types of landscapes, particularly in turbid waters and areas lacking distinct boundaries. This study takes a novel approach to the quantification and analysis of seagrass landscape structure at multiple spatial scales using acoustic data and local spatial statistics. Data from a single-beam acoustic survey in Richibucto, New Brunswick, Canada were analyzed with geostatistical techniques and the Getis-Ord G * i local spatial statistic in order to detect statistically significant zones of high and low cover in an estuarine seagrass bed. Results showed distinct and significant patterns in seagrass cover at multiple spatial scales within a region of apparently continuous spatial cover. Boundaries between areas of high and low cover were also detected. This study demonstrates how acoustic data and local spatial statistics can be used to quantify landscape pattern and to further the application of landscape techniques in the marine environment.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Anselin L (1995) Local indicators of spatial association—LISA. Geogr Anal 27:93–115

    Article  Google Scholar 

  • Barbier EB, Hacker SD, Kennedy C, Koch EW, Stier AC, Silliman BR (2011) The value of estuarine and coastal ecosystem services. Ecol Monogr 81:169–193

    Article  Google Scholar 

  • Bell S, Fonseca M, Stafford N (2006) Seagrass ecology: new contributions from a landscape perspective. In: Larkum AWD, Orth RJ, Duarte C (eds) Seagrasses: biology, ecology and conservation. Springer, Dordrecht, pp 625–645

    Chapter  Google Scholar 

  • Boots B (2002) Local measures of spatial association. Ecoscience 9:168–176

    Google Scholar 

  • Boström C, Jackson E, Simenstad C (2006) Seagrass landscapes and their effects on associated fauna: a review. Estuar Coast Shelf S 68:383–403

    Article  Google Scholar 

  • Boström C, Pittman S, Simenstad C, Kneib R (2011) Seascape ecology of coastal biogenic habitats: advances, gaps, and challenges. Mar Ecol Prog Ser 427:191–217

    Article  Google Scholar 

  • Costanza R, d’Arge R, de Groot R, Farber S, Grasso M, Hannon B, Limburg K, Naeem S, O’Neill R, Paruelo J, Raskin R, Sutton P, van den Belt M (1997) The value of the world’s ecosystem services and natural capital. Nature 387:253–260

    Article  CAS  Google Scholar 

  • Dekker A, Brando V, Anstee J, Fyfe S, Malthus T, Karpouzli E (2006) Remote sensing of seagrass ecosystems: use of spaceborne and airborne sensors. In: Larkum AWD, Orth RJ, Duarte C (eds) Seagrasses: biology, ecology and conservation. Springer, Dordrecht, pp 347–359

    Chapter  Google Scholar 

  • Duarte C (2002) The future of seagrass meadows. Environ Conserv 29:192–206

    Article  Google Scholar 

  • Duarte C, Fourqurean J, Krause-Jensen D, Olesen B (2006) Dynamics of seagrass stability and change. In: Larkum AWD, Orth RJ, Duarte C (eds) Seagrasses: biology, ecology and conservation. Springer, Dordrecht, pp 271–294

    Chapter  Google Scholar 

  • Fonseca M, Whitfield P, Kelly N, Bell S (2002) Modeling seagrass landscape pattern and associated ecological attributes. Ecol Appl 12:218–237

    Article  Google Scholar 

  • Fortin M, Dale M (2005) Spatial analysis: a guide for ecologists. Cambridge University Press, Cambridge

    Google Scholar 

  • Getis A, Ord J (1992) The analysis of spatial association by use of distance statistics. Geogr Anal 24:189–206

    Article  Google Scholar 

  • Goovaerts P (1997) Geostatistics for natural resources evaluation. Oxford University Press, New York

    Google Scholar 

  • Guan W, Chamberlain R, Sabol B, Doering P (1999) Mapping submerged aquatic vegetation with GIS in the Caloosahatchee Estuary: evaluation of different interpolation methods. Mar Geod 22:69–91

    Article  Google Scholar 

  • Guyondet T, Koutitonsky V, Roy S (2005) Effects of water renewal estimates on the oyster aquaculture potential of an inshore area. J Marine Syst 58:35–51

    Article  Google Scholar 

  • Harris B, Stokesbury K (2010) The spatial structure of local surficial sediment characteristics on Georges Bank, USA. Cont Shelf Res 30:1840–1853

    Article  Google Scholar 

  • Hinchey EK, Nicholson MC, Zajac RN, Irlandi EA (2008) Preface: marine and coastal applications in landscape ecology. Landscape Ecol 23:1–5

    Article  Google Scholar 

  • Hoechstetter S, Walz U, Dang L (2008) Effects of topography and surface roughness in analyses of landscape structure—a proposal to modify the existing set of landscape metrics. Landsc Online 1:1–14

    Article  Google Scholar 

  • Hufkens K, Scheunders P, Ceulemans R (2009) Ecotones in vegetation ecology: methodologies and definitions revisited. Ecol Res 24:977–986

    Article  Google Scholar 

  • Legendre P, Legendre L (1998) Numerical ecology, 2nd English edn. Elsevier, Amsterdam

    Google Scholar 

  • Lu L, Grant J, Barrell J (2008) Macrofaunal spatial patterns in relationship to environmental variables in the Richibucto Estuary, New Brunswick, Canada. Estuar Coast 31:994–1005

    Article  Google Scholar 

  • MacArthur RH, Wilson EO (1967) The theory of island biogeography. Princeton University Press, Princeton

    Google Scholar 

  • McGarigal K, Tagil S, Cushman SA (2009) Surface metrics: an alternative to patch metrics for the quantification of landscape structure. Landscape Ecol 24:433–450

    Article  Google Scholar 

  • McKenzie L, Finkbeiner M, Kirkman H (2001) Methods for mapping seagrass distribution. In: Short F, Coles R (eds) Global seagrass research methods. Elsevier, Amsterdam, pp 101–121

    Chapter  Google Scholar 

  • Nelson T, Boots B (2008) Detecting spatial hot spots in landscape ecology. Ecography 31:556–566

    Article  Google Scholar 

  • O’Neill R, Krummel J, Gardner R, Sugihara G, Jackson B, DeAngelis D, Milne B, Turner M, Zygmunt B, Christensen S (1988) Indices of landscape pattern. Landscape Ecol 1:153–162

    Article  Google Scholar 

  • Ord J, Getis A (1995) Local spatial autocorrelation statistics: distributional issues and an application. Geogr Anal 27:286–306

    Article  Google Scholar 

  • Orth R, Carruthers T, Dennison W, Duarte C, Fourqurean J, Heck KL Jr, Hughes A, Kendrick G, Kenworthy W, Olyarnik S, Short F, Waycott M, Williams S (2006) A global crisis for seagrass ecosystems. Bioscience 56:987–996

    Article  Google Scholar 

  • Paul M, Lefebvre A, Manca E, Amos CL (2011) An acoustic method for the remote measurement of seagrass metrics. Estuar Coast Shelf S 93:68–79

    Article  Google Scholar 

  • Philibert M, Fortin M, Csillag F (2008) Spatial structure effects on the detection of patches boundaries using local operators. Environ Ecol Stat 15:447–467

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Robbins BD, Bell SS (1994) Seagrass landscapes: a terrestrial approach to the marine subtidal environment. Trends Ecol Evol 9:301–304

    Article  PubMed  CAS  Google Scholar 

  • Sabol B, Melton RE Jr, Chamberlain R, Doering P, Haunert K (2002) Evaluation of a digital echo sounder system for detection of submersed aquatic vegetation. Estuar Coast 25:133–141

    Article  Google Scholar 

  • Sabol B, Kannenberg J, Skogerboe J (2009) Integrating acoustic mapping into operational aquatic plant management: a case study in Wisconsin. J Aquat Plant Manage 47:44–52

    Google Scholar 

  • Shao G, Wu J (2008) On the accuracy of landscape pattern analysis using remote sensing data. Landscape Ecol 23:505–511

    Article  Google Scholar 

  • Simes R (1986) An improved Bonferroni procedure for multiple tests of significance. Biometrika 73:751–754

    Article  Google Scholar 

  • Sleeman J, Kendrick G, Boggs G, Hegge B (2005) Measuring fragmentation of seagrass landscapes: which indices are most appropriate for detecting change? Mar Freshw Res 56:851–864

    Article  Google Scholar 

  • Turner M, Gardner R, O’Neill R (2001) Landscape ecology in theory and practice: pattern and process. Springer, New York

    Google Scholar 

  • Valley R, Drake M, Anderson C (2005) Evaluation of alternative interpolation techniques for the mapping of remotely-sensed submersed vegetation abundance. Aquat Bot 81:13–25

    Article  Google Scholar 

  • Wagner H, Fortin M (2005) Spatial analysis of landscapes: concepts and statistics. Ecology 86:1975–1987

    Article  Google Scholar 

  • Warren J, Peterson B (2007) Use of a 600-kHz acoustic Doppler current profiler to measure estuarine bottom type, relative abundance of submerged aquatic vegetation, and eelgrass canopy height. Estuar Coast Shelf S 72:53–62

    Article  Google Scholar 

  • Waycott M, Duarte C, Carruthers T, Orth R, Dennison W, Olyarnik S, Calladine A, Fourqurean J, Heck K, Hughes A, Kendrick G, Kenworthy W, Short F, Williams S (2009) Accelerating loss of seagrasses across the globe threatens coastal ecosystems. Proc Natl Acad Sci USA 106:12377–12381

    Article  PubMed  CAS  Google Scholar 

  • Wedding L, Lepczyk C, Pittman S, Friedlander A, Jorgensen S (2011) Quantifying seascape structure: extending terrestrial spatial pattern metrics to the marine realm. Mar Ecol Prog Ser 427:219–232

    Article  Google Scholar 

  • Wiens J (1989) Spatial scaling in ecology. Funct Ecol 3:385–397

    Article  Google Scholar 

  • Wu J, Hobbs R (2002) Key issues and research priorities in landscape ecology: an idiosyncratic synthesis. Landscape Ecol 17:355–365

    Article  Google Scholar 

  • Wulder M, Boots B (1998) Local spatial autocorrelation characteristics of remotely sensed imagery assessed with the Getis statistic. Int J Remote Sens 19:2223–2231

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Oceanography, Dalhousie University, 1355 Oxford St, PO Box 15000, Halifax, NS, B3H 4R2, Canada

    Jeffrey Barrell & Jon Grant

Authors
  1. Jeffrey Barrell
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jon Grant
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jeffrey Barrell.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Barrell, J., Grant, J. Detecting hot and cold spots in a seagrass landscape using local indicators of spatial association. Landscape Ecol 28, 2005–2018 (2013). https://doi.org/10.1007/s10980-013-9937-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10980-013-9937-2

Keywords

Search

Navigation