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Predictive modelling of seabed habitats: case study of subtidal kelp forests on the coast of Brittany, France

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Abstract

Predictive modelling to map subtidal communities is an alternative to “traditional” methods, such as direct sampling, remote sensing and acoustic survey, which are neither time- nor cost-effective for vast expanses. The principle of this modelling is the use of a combination of environmental key parameters to produce rules to understand species distribution and hence generate predictive maps. This study focuses on subtidal kelp forests (KF) on the coast of Brittany, France. The most significant key parameters to predict KF frequency are (1) the nature of the substrate, (2) depth, (3) water transparency, (4) water surface temperature and (5) hydrodynamics associated with the flexibility of algae in a flow. All these parameters are integrated in a spatial model, built using a Geographical Information System. This model results in a KF frequency map, where sites with optimum key parameters show a deeper limit of disappearance. After validation, the model is used in the context of Climate Change to estimate the effect of environmental variation on this depth limit of KF. Thus, the effects of both an increase in water temperature and a decrease in its transparency could lead to the complete disappearance of KF.

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References

  • Bajjouk T, Guillaumont B, Populus J (1996) Application of airborne imaging spectrometry system data to intertidal seaweed classification and mapping. Hydrobiologia 327:463–471

    Article  Google Scholar 

  • Belsher T (1986) Etude bibliographique de quelques espèces planctoniques et benthiques de la Manche. In: Phytobenthos, vol. 4. Ifremer, Brest

  • Boller ML, Carrington E (2006) The hydrodynamic effects of shape and size change during reconfiguration of a flexible macroalga. J Exp Biol 209:1894–1903

    Article  Google Scholar 

  • Brinkman AG, Dankers N, van Stralen M (2002) An analysis of mussel bed habitats in the Dutch Wadden Sea. Helgoland Mar Res 56:59–75

    Article  Google Scholar 

  • Brown CJ, Cooper KM, Meadows WJ, Limpenny DS, Rees HL (2002) Small-scale mapping of sea-bed assemblages in the eastern English Channel using sidescan sonar and remote sampling techniques. Estuar Coast Shelf S 54:263–278

    Article  Google Scholar 

  • Buck BH, Buchholz CM (2005) Response of offshore cultivated Laminaria saccharina to hydrodynamic forcing in the North Sea. Aquaculture 250:674–691

    Article  Google Scholar 

  • Cardoso PG, Raffaelli D, Lillebø AI, Verdelhos T, Pardal MA (2008) The impact of extreme flooding events and anthropogenic stressors on macrobenthic communities’ dynamics. Estuar Coast Shelf S 76:553–565

    Article  Google Scholar 

  • Castric-Fey A, Girard-Descatoire A, Gentil F, Davoult D, Dewarumez JM (1997) Macrobenthos des substrats durs intertidaux et subtidaux. In: Dauvin JC (ed) Les Biocénoses Marines et Littorales Françaises des Côtes Atlantiques, Manche et Mer du Nord.—Synthèse, menaces et perspectives. Museum National d’Histoire Naturelle, Paris, pp 83–95

    Google Scholar 

  • Combe JP, Launeau P, Carrere V, Despan D, Meleder V, Barille L, Sotin C (2005) Mapping microphytobenthos biomass by non-linear inversion of visible-infrared hyperspectral images. Remote Sens Environ 98:371–387

    Article  Google Scholar 

  • Dayton PK, Tegner MJ, Parnell PE, Edwards PB (1992) Temporal and spatial patterns of disturbance and recovery in a kelp forest community. Ecol Monogr 62:421–445

    Article  Google Scholar 

  • de Jonge VN, de Jong DJ (2002) ‘Global change’ impact of inter-annual variation in water discharge as a driving factor of dredging and spoil disposal in the river Rhine system and of turbidity in the Wadden sea. Estuar Coast Shelf S 55:969–991

    Article  Google Scholar 

  • De Oliveira E, Populus J, Guillaumont B (2006) Predictive modelling of coastal habitats using remote sensing data and fuzzy logic. EARSeL eProc 5:208–223

    Google Scholar 

  • Denny M (1995) Predicting physical disturbance: mechanistic approaches to the study of survivorship on wave-swept shores. Ecol Monogr 65:371–418

    Article  Google Scholar 

  • Denny M, Gaylord B (2002) The mechanics of wave-swept algae. J Exp Biol 205:1355–1362

    Google Scholar 

  • Ferrat L, Pergent-Martini C, Roméo M (2003) Assessment of the use of biomarkers in aquatic plants for the evaluation of environmental quality: application to seagrasses. Aquat Toxicol 65:187–204

    Article  CAS  Google Scholar 

  • Freitas R, Rodrigues AM, Quintino V (2003) Benthic biotopes remote sensing using acoustics. J Exp Mar Biol Ecol 285–286:339–353

    Article  Google Scholar 

  • Freitas R, Sampaio L, Oliveira J, Rodrigues AM, Quintino V (2006) Validation of soft bottom benthic habitats identified by single-beam acoustics. Mar Pollut Bull 53:72–79

    Article  CAS  Google Scholar 

  • Gaylord B, Denny M, Koehl MAR (2003) Modulation of wave forces on kelp canopies by alongshore currents. Limnol Oceanogr 48:860–871

    Article  Google Scholar 

  • Gohin F, Loyer S, Lunven M, Labry C, Froidefond J-M, Delmas D, Huret M, Herbland A (2005) Satellite-derived parameters for biological modelling in coastal waters: illustration over the eastern continental shelf of the Bay of Biscay. Remote Sens Environ 95:29–46

    Article  Google Scholar 

  • Greve TM, Krause-Jensen D (2005) Predictive modelling of eelgrass (Zostera marina) depth limits. Mar Biol 146:849–858

    Article  Google Scholar 

  • Guillaumont B, Callens L, Dion P (1993) Spatial-distribution and quantification of fucus species and Ascophyllum-Nodosum beds in intertidal zones using spot imagery. Hydrobiologia 261:297–305

    Article  Google Scholar 

  • Guillaumont B, Bajjouk T, Talec P (1997) Seaweed and remote sensing: a critical review of sensors and data processing. In: Round FE, Chapman DJ (eds) Progress in phycological research. Biopress, Bristol, pp 213–282

    Google Scholar 

  • Hurd CL (2000) Water motion, marine macroalgae, physiology, and production. J Phycol 36:453–472

    Article  CAS  Google Scholar 

  • IPCC (2001) Climate change 2001: the scientific basis, contribution of working group I to the third assessment report of the Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press, Cambridge

    Google Scholar 

  • Kelly NM, Fonseca M, Whitfield P (2001) Predictive mapping for management and conservation of seagrass beds in North Carolina. Aquat Conserv 11:437–451

    Article  Google Scholar 

  • Koutsikopoulos C, Beillois P, Leroy C, Taillefer F (1998) Temporal trends and spatial structures of the sea surface temperature in the Bay of Biscay. Oceanol Acta 21:335–344

    Article  Google Scholar 

  • Lundblad ER, Wright DJ, Naar DF, Donahue BT, Miller J, Larkin EM, Rinehart R (2004) Classifying deep water benthic habitats around Tutulia, America Samoa 24th annual ESRI conference, San Diego, CA

  • Marchalot C, Diner N, Berger L (2003) MOVIES + documentation: echo-integration by depth layers using MOVIES + software. IFREMER/DNIS/ESI, Plouzané

    Google Scholar 

  • Markager S, Sand-Jensen K (1992) Light requirements and depth zonation of marine macroalgae. Mar Ecol-Prog Ser 88:83–92

    Article  Google Scholar 

  • McRea JE, Greene HG, O’Connell VM, Wakefield WW (1999) Mapping marine habitats with high resolution sidescan sonar. Oceanol Acta 22:679–686

    Article  Google Scholar 

  • MEDD (2005) Plan d’actions stratégique du MEDD pour les milieux marins. Tome 1—diagnostic et orientations. Ministère de l’écologie et du développement durable, Paris

    Google Scholar 

  • Méléder V, Launeau P, Barillé L, Rincé Y (2003) Microphytobenthos assemblage mapping by spatial visible-infrared remote sensing in a shellfish ecosystem. C R Biol 11:437–451

    Google Scholar 

  • Méléder V, Populus J, Rollet C (2007) Mapping seabed substrata using Lidar remote sensing. MESH—mapping European seabed habitats. http://www.searchmesh.net/PDF/GMHM3_Mapping_Substrata_using_LIDAR.pdf

  • Ménesguen A, Piriou JY, Dion P, Auby I (1997) Les “Marées vertes”, un exemple d’eutrophisation à macroalgues. In: Dauvin J-C (ed) Les biocénoses marines et littorales françaises des côtes atlantiques, Manche et Mer du Nord. Synthèse, menaces et perspectives. MNHN, Paris, pp 212–218

    Google Scholar 

  • Norderhaug KM, Christie H, Rinde E (2002) Colonisation of kelp imitations by epiphyte and holdfast fauna; a study of mobility patterns. Mar Biol 141:965–973

    Article  Google Scholar 

  • Piazzi L, Acunto S, Cinelli F (2000) Mapping of Posidonia oceanica beds around Elba Island (western Mediterranean) with integration of direct and indirect methods. Oceanol Acta 23:339–346

    Article  Google Scholar 

  • Pope ND, Widdows J, Brinsley MD (2006) Estimation of bed shear stress using the turbulent kinetic energy approach. A comparison of annular flume and field data. Cont Shelf Res 26:959–970

    Article  Google Scholar 

  • Riegl BM, Moyer RP, Morris LJ, Virnstein RW, Purkis SJ (2005) Distribution and seasonal biomass of drift macroalgae in the Indian River Lagoon (Florida, USA) estimated with acoustic seafloor classification (QTCView, Echoplus). J Exp Mar Biol Ecol 326:89–104

    Article  Google Scholar 

  • Roff JC, Taylor ME (2000) National frameworks for marine conservation—a hierarchical geophysical approach. Aquat Conserv 10:209–223

    Article  Google Scholar 

  • Rosso PH, Ustin SL, Hastings A (2006) Use of lidar changes associated with Spartina invasion in San Francisco Bay marshes. Remote Sens Environ 100:295–306

    Article  Google Scholar 

  • SHOM (1994–2005) Cartes sédimentologiques (G). SHOM

  • Sivertsen K (1997) Geographic and environmental factors affecting the distribution of kelp beds and barren grounds and changes in biota associated with kelp reduction at sites along the Norwegian coast. Can J Fish Aquat Sci 54:2872–2887

    Article  Google Scholar 

  • Steneck RS, Graham MH, Bourque BJ, Corbett D, Erlandson JM, Estes JA, Tegner MJ (2002) Kelp forest ecosystems: biodiversity, stability, resilience and future. Environ Conserv 29(4):436–459

    Article  Google Scholar 

  • Stevens T, Connolly RM (2004) Testing the utility of abiotic surrogates for marine habitat mapping at scales relevant to management. Biol Conserv 119:351–362

    Article  Google Scholar 

  • Toms JD, Lesperance ML (2003) Piecewise regression: a tool for identifying ecological thresholds. Ecology 84:2034–2041

    Article  Google Scholar 

  • Udden JA (1914) Mechanical composition of clastic sediments. Bull Geol Soc Am 25:655–744

    Google Scholar 

  • Vaslet D, Larsonneur C, Auffret J-P (1979) Carte des sédiments superficiels de la Manche. BRGM/CNEXO

  • Vogel S (1994) Life in moving fluids, 2nd edn. Princeton University Press, Princeton, 467 pp

    Google Scholar 

  • Wentworth CK (1922) A scale of grade and class terms for clastic sediments. J Geol 30:377–392

    Google Scholar 

  • Zacharias MA, Roff JC (2001) Explanations of patterns of intertidal diversity at regional scales. J Biogeogr 28:471–483

    Article  Google Scholar 

  • Zacharias MA, Morris MC, Howes DE (1999) Large scale characterization of intertidal communities using a predictive model. J Exp Mar Biol Ecol 239:223–242

    Article  Google Scholar 

Download references

Acknowledgments

We acknowledge F. Gohin and B. Saulquin from Ifremer Brest for images traitement.

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Correspondence to Vona Méléder.

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Communicated by F. Bulleri.

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Méléder, V., Populus, J., Guillaumont, B. et al. Predictive modelling of seabed habitats: case study of subtidal kelp forests on the coast of Brittany, France. Mar Biol 157, 1525–1541 (2010). https://doi.org/10.1007/s00227-010-1426-4

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  • DOI: https://doi.org/10.1007/s00227-010-1426-4

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