Estuaries and Coasts

, Volume 37, Issue 6, pp 1467–1489 | Cite as

Evaluating Light Availability, Seagrass Biomass, and Productivity Using Hyperspectral Airborne Remote Sensing in Saint Joseph’s Bay, Florida

  • Victoria J. HillEmail author
  • Richard C. Zimmerman
  • W. Paul Bissett
  • Heidi Dierssen
  • David D. R. Kohler


Seagrasses provide a number of critical ecosystem services, including habitat for numerous species, sediment stabilization, and shoreline protection. Ariel photography is a useful tool to estimate the areal extent of seagrasses, but recent innovations in radiometrically calibrated sensors and algorithm development have allowed identification of benthic types and retrieval of absolute density. This study demonstrates the quantitative ability of a high spatial resolution (1 m) airborne hyperspectral sensor (3.2 nm bandwidth) in the complex coastal waters of Saint Joseph’s Bay (SJB). Several benthic types were distinguished, including submerged and floating aquatic vegetation, benthic red algae, bare sand, and optically deep water. A total of 23.6 km2 of benthic vegetation was detected, indicating no dramatic change in vegetation area over the past 30 years. SJB supported high seagrass density at depths shallower than 2 m with an average leaf area index of 2.0 ± 0.6 m2 m−2. Annual seagrass production in the bay was 13,570 t C year−1 and represented 41 % of total marine primary production. The effects of coarser spatial resolution were investigated and found to reduce biomass retrievals, underestimate productivity, and alter patch size statistics. Although data requirements for this approach are considerable, water column optical modeling may reduce the in situ requirements and facilitate the transition of this technique to routine monitoring efforts. The ability to quantify not just areal extent but also productivity of a seagrass meadow in optically complex coastal waters can provide information on the capacity of these environments to support marine food webs.


Remote sensing Seagrass Hyperspectral Spatial patterns Submarine landscape 



We thank D. Ruble, J. Cousins, M. Stoughton, C. Buonassissi, I. Nardello, J. Godfrey, and A. Branco for assistance in data collection. We also acknowledge the staff and facilities at the Preserve Center, St. Joseph’s Bay State Buffer and Aquatic Preserves, Office of Coastal and Aquatic Managed Areas and the crew at Daly’s Dock and Dive Centre, Port Saint Joe, FL. This work was supported by funding from NASA project NNG04GN84G and Florida DNR Coastal Aquatic Managed Areas.


  1. Akula, R., R. Gupta, and M.R. Vimala Devi. 2012. An efficient PAN sharpening technique by merging two hybrid approaches. Procedia Engineering 30: 535–541. doi: 10.1016/j.proeng.2012.01.895.CrossRefGoogle Scholar
  2. Bell, S.S., B.D. Robbins, and S.L. Jensen. 1999. Gap dynamics in a seagrass landscape. Ecosystems 2(6): 493–504. doi: 10.1007/s100219900097.CrossRefGoogle Scholar
  3. Bell, S.S., M.S. Fonseca, and N.B. Stafford. 2006. Seagrass ecology: New contributions from a landscape perspective. In Seagrasses: Biology, ecology and conservation, ed. A.W.D. Larkum, 625–645. the Netherlands: Springer.Google Scholar
  4. Bissett, W.P., R.A. Arnone, C.O. Davis, T.D. Dickey, D. Dye, and D. Kohler. 2004. From meters to kilometers—a look at ocean color scales of variability, spatial coherence, and the need for fine scale remote sensing in coastal ocean optics. Oceanography 17(2): 32–43.CrossRefGoogle Scholar
  5. Bissett, P., R.A. Arnone, S. DeBra, D. Deterlie, D. Dye, G. Kirkpatrick, O. Schofield, and J. Walsh. 2005. Predicting the inherent optical properties and colored dissolved organic matter dynamics on the West Florida Shelf. Marine Chemistry 95: 199–233.CrossRefGoogle Scholar
  6. Brando, V.E., J.E. Anstee, M. Wettle, A. Dekker, S.R. Phinn, and C. Roelfsema. 2009. A physics based retrieval and quality assessment of bathymetry from suboptimal hyperspectral data. Remote Sensing of Environment 113: 15.CrossRefGoogle Scholar
  7. Buonassissi, C. J. and H. M. Dierssen. 2010. A regional comparison of particle size distributions and the power law approximation in oceanic and estuarine surface waters. Journal of Geophysical Research 115. doi: 10.1029/2010JC006256.
  8. Congalton, R. G. 2005. Thematic and positional accuracy assessment of digital remotely sensed data classification accuracy. Seventh Annual Forest Inventory and Analysis Symposium.Google Scholar
  9. Cummings, M.E., and R.C. Zimmerman. 2003. Light harvesting and the package effect in the seagrasses Thalassia testudinum Banks ex König and Zostera marina L.: Optical constraints on photoacclimation seagrass. Aquatic Botany 75: 261–274.CrossRefGoogle Scholar
  10. Davis, C.O., J.H. Bowles, R.A. Leathers, D. Korwan, T.V. Downes, W.A. Snyder, W.J. Rhea, W. Chen, J. Fisher, P. Bissett, and R.A. Reisse. 2002. Ocean PHILLS hyperspectral imager: Design, characterization, and calibration. Optics Express 10(4): 210–221.CrossRefGoogle Scholar
  11. Dekker, A., V. Brando, J. Anstee, S.K. Fyfe, T. Malthus, and E. Karpouzli. 2006. Remote sensing of seagrass systems: Use of spaceborne and airborne systems. In Seagrasses: Biology, ecology and conservation, ed. A.W.D. Larkum and C.M. Duarte, 347–359. Dordrecht: Springer.Google Scholar
  12. Dekker, A., S.R. Phinn, J. Anstee, P. Bissett, V.E. Brando, B. Casey, P. Fearns, J. Hedley, W. Klonowski, Z.P. Lee, M. Lynch, M. Lyons, and C.D. Mobley. 2011. Intercomparison of shallow water bathymetry, hydro-optics, and benthos mapping techniques in Australian and Caribbean coastal environments. Limnology and Oceanography: Methods 9: 396–425.CrossRefGoogle Scholar
  13. Dierssen, H.M., R.C. Zimmerman, R.A. Leathers, T.V. Downes, and C.O. Davis. 2003. Ocean color remote sensing of seagrass and bathymetry in the Bahamas Banks by high-resolution airborne imagery. Limnology and Oceanography 48(1, part 2): 444–455.CrossRefGoogle Scholar
  14. Dierssen, H.M., R.C. Zimmerman, L.A. Drake, and D.J. Burdige. 2010. Benthic ecology from space: Optics and net primary production in seagrass and benthic algae across the Great Bahama Bank. Marine Ecology Progress Series 411: 1–15. doi: 10.3354/meps08665.CrossRefGoogle Scholar
  15. Duarte, C.M., and C.L. Chiscano. 1999. Seagrass biomass and production: A reassessment. Aquatic Botany 65: 159–174.CrossRefGoogle Scholar
  16. Ferwerda, J.G., J. De Leeuw, C. Atzberger, and Z. Vekerdy. 2007. Satellite-based monitoring of tropical seagrass vegetation: Current techniques and future developments. Hydrobiologia 591: 59–71.CrossRefGoogle Scholar
  17. Fyfe, S.K. 2003. Spatial and temporal variation in spectral reflectance: Are seagrass species spectrally distinct? Limnology and Oceanography 48(1): 15.Google Scholar
  18. Gao, B.-C., M.J. Montes, Z. Ahmad, and C.O. Davis. 2000. Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space. Applied Optics 39(6): 887–896.CrossRefGoogle Scholar
  19. Gao, B.-C., M.J. Montes, and C.O. Davis. 2004. Refinement of wavelength calibrations of hyperspectral imaging data using a spectrum-matching technique. Remote Sensing of the Environment 90(4): 424–434.CrossRefGoogle Scholar
  20. Garzelli, A., Nencini, F., Alparone, L., Aiazzi, B. and S. Baronti. 2004. Pan-sharpening of multispectral images: A critical review and comparison. Geoscience and Remote Sensing Symposium. 1.Google Scholar
  21. Gillanders, B.M. 2006. Seagrasses, fish and fisheries. In Seagrasses: Biology, ecology and conservation, ed. A.W.D. Larkum, R. Orth, and C.M. Duarte. the Netherlands: Springer.Google Scholar
  22. Han, L., and D. Rundquist. 2003. The spectral response of Ceratophyllum demersum at varying depths in an experimental tank. International Journal of Remote Sensing 24(4): 859–864.CrossRefGoogle Scholar
  23. Harwell, M.C., and R.J. Orth. 2001. Influence of a tube-dwelling polychaete on the dispersal of fragmented reproductive shoots of eelgrass. Aquatic Botany 70: 1–7.CrossRefGoogle Scholar
  24. Hemminga, M.A., and C.M. Duarte. 2000. Seagrass ecology seagrass. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  25. Hovel, K.A., and R.N. Lipcius. 2001. Habitat fragmentation in a seagrass landscape: Patch size and complexity control Blue Crab survival. Ecology 82(7): 1814–1829. doi: 10.1890/0012-9658(2001) 082[1814:HFIASL]2.0.CO;2.CrossRefGoogle Scholar
  26. Kendrick, G.A., B.J. Hegge, A. Wyllie, A. Davidson, and D.A. Lord. 2000. Changes in seagrass cover on success and Parmelia Banks, Western Australia between 1965 and 1995. Estuarine, Coastal and Shelf Science 50(3): 341–353. doi: 10.1006/ecss.1999.0569.CrossRefGoogle Scholar
  27. Kirk, J.T.O. 1994. Light and photosynthesis in aquatic ecosystems photosynthesis. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  28. Kishino, M., M. Takahashi, N. Okami, and S. Ichimure. 1985. Estimation of the spectral absorption coefficients of phytoplankton in the sea. Bulletin of Marine Sciences 37: 634–642.Google Scholar
  29. Klonowski, W., P.R.C.S. Fearns, and M.J. Lynch. 2007. Retrieving key benthic cover types and bathymetry from hyperspectral imagery. Journal of Applied Remote Sensing 1: 1–21.CrossRefGoogle Scholar
  30. Kohler, D., P. Bissett, R.G. Steward, and C.O. Davis. 2004. A new approach for the radiometric calibration of spectral imaging systems. Optics Express 12(11): 2463–2477.CrossRefGoogle Scholar
  31. Kohler, D., Bissett, P., Steward, R. G., Kadiwala, M. and R. Banfield. 2006. Hyperspectral remote sensing of the coastal environment. Proceeding of Ocean Optics, XVIII, Montreal.Google Scholar
  32. Kurdziel, J.P., and S.S. Bell. 1992. Emergence and dispersal of phytal-dwelling meiobenthic copepods seagrass. Journal of Experimental Marine Biology and Ecology 163: 43–64.CrossRefGoogle Scholar
  33. Kutser, T., I. Miller, and D. Jupp. 2006. Mapping coral reef benthic substrates using hyperspectral space-born images and spectral libraries. Estuarine Coastal and Shelf Science 70: 449–460.CrossRefGoogle Scholar
  34. Lee, Z.P., K.L. Carder, S.K. Hawes, R.G. Steward, T.G. Peacock, and C.O. Davis. 1994. Model for the interpretation of hyperspectral remote-sensing reflectance. Applied Optics 33(24): 5721–5732.CrossRefGoogle Scholar
  35. Lee, Z.P., K.L. Carder, C.D. Mobley, R.G. Stewart, and J.S. Patch. 1999. Hyperspectral remote sensing for shallow waters: 2. Deriving bottom depths and water properties by optimization. Applied Optics 38(18): 3831–3843.CrossRefGoogle Scholar
  36. Lee, Z.P., K.L. Carder, F.R. Chen, and T.G. Peakcock. 2001. Properties of the water column and bottom derived from Airborne Visible Infrared Imaging Spectrometer AVIRIS. Journal Geophysical Research 106(C6): 11639–11651.CrossRefGoogle Scholar
  37. Lesser, M.P., and C.D. Mobley. 2007. Bathymetry, water optical properties, and benthic classification of coral reefs using hyperspectral remote sensing imagery. Coral Reefs 26: 819–829. doi: 10.1007/s00338-007-0271-5.CrossRefGoogle Scholar
  38. Louchard, E.M., R.P. Reid, F.C. Stephens, C.O. Davis, R.A. Leathers, and T.V. Downes. 2003. Optical remote sensing of benthic habitats and bathymetry in coastal environments at Lee Stocking Island, Bahamas: A comparative spectra classification approach. Limnology and Oceanography 48(1): 511–521.CrossRefGoogle Scholar
  39. Mantoura, R. F. C., Jeffrey, S. W., Llewellyn, C. A., Claustre, H., Morales, C. E. and S. W. Wright. 1997. Comparison between spectrophotometric, fluorometric and HPLC methods for chlorophyll analysis fluorometric. In: Phytoplankton pigments in oceanography, eds. S. W. Jeffrey, et al., 361–380. Paris: UNESCO.Google Scholar
  40. Marba, N., and C.M. Duarte. 1995. Coupling of seagrass (Cymodocea nodosa) patch dynamics to subaqueous dune migration. Journal of Ecology 83: 381–389.CrossRefGoogle Scholar
  41. Marbá, N., M. Holmer, E. Gacia, and C. Barron. 2006. Seagrass beds and coastal biogeochemistry. In Seagrasses: Biology, ecology and conservation, ed. A.W.D. Larkum, R. Orth, and C.M. Duarte. the Netherlands: Springer.Google Scholar
  42. Maritorena, S., A. Morel, and B. Gentili. 1994. Diffuse reflectance of oceanic shallow waters: Influence of water depth and albedo. Limnology and Oceanography 39(7): 1689–1703.CrossRefGoogle Scholar
  43. Matarrese, R., Acquaro, M., Morea, A., Tijani, K. and Chiaradia. 2008. Application of remote sensing techniques for mapping Posidonia oceanica meadows. Proceedings of the IGARSS.Google Scholar
  44. Mateo, M.A., J. Cebrian, K. Dunton, and T. Mutchler. 2006. Carbon flux in seagrass ecosystems. In Seagrasses: Biology, ecology and conservation, ed. A.W.D. Larkum, R. Orth, and C.M. Duarte. the Netherlands: Springer.Google Scholar
  45. McNulty, J. K., Lindall, W. N. and Sykes, J. E., 1972. Cooperative Gulf of Mexico estuarine inventory and study, Florida: Phase I, area description. NOAA Technical Report NMFS CIRC-368, 126 p.Google Scholar
  46. McPherson, M.L., V.J. Hill, R.C. Zimmerman, and H.M. Dierssen. 2011. The optical properties of Greater Florida Bay: Implications for seagrass abundance seagrass Florida. Estuaries and Coasts 34: 1150–1160. doi: 10.1007/s12237-011-9411-9.CrossRefGoogle Scholar
  47. Meehan, A.J., R.J. Williams, and F.A. Watford. 2005. Detecting trends in seagrass abundance using aerial photograph interpretation: Problems arising with the evolution of mapping methods. Estuaries 28(3): 10.CrossRefGoogle Scholar
  48. Mitchell, B. G., Kahru, M., Wieland, J., Stramska, M., Mueller, J. L. and G. S. Fargion. 2002. Determination of spectral absorption coefficients of particles, dissolved material and phytoplankton for discrete water samples. In: Ocean optics protocols for satellite ocean color sensor validation, eds. G.S. Fargion, J.L. Mueller, C.R. McClain, 231–257. Greenbelt: NASA.Google Scholar
  49. Mobley, C.D. 1994. Light and water: Radiative transfer in natural waters. San Diego: Academic.Google Scholar
  50. Mobley, C.D., L.K. Sundman, C.O. Davis, J.H. Bowles, T.V. Downes, R.A. Leathers, M.J. Montes, P. Bissett, D. Kohler, R.P. Reid, E.M. Louchard, and A.C. Gleason. 2005. Interpretation of hyperspectral remote-sensing imagery by spectrum matching and look-up tables. Applied Optics 44(17): 3576–3592. doi: 10.1364/AO.44.003576.CrossRefGoogle Scholar
  51. Morel, A., and J.L. Mueller. 2003. Normalized water-leaving radiance and remote sensing reflectance: Bidirectional reflectance and other factors, 32–59. Greenbelt: Goddard Space Flight Center.Google Scholar
  52. Moriarty, D.J.W., R.L. Iverson, and P.C. Pollard. 1986. Exudation of organic carbon by the seagrass Halodule wrightii Aschers and its effect on bacterial growth in the sediment. Journal of Experimental Marine Biology and Ecology 96(2): 115–126.CrossRefGoogle Scholar
  53. Mumby, P.J., and A.J. Edwards. 2002. Mapping marine environments with IKONOS imagery: Enhanced spatial resolution can deliver greater thermatic accuracy. Remote Sensing of Environment 82: 9.CrossRefGoogle Scholar
  54. Mumby, P.J., E.P. Green, A.J. Edwards, and C.D. Clark. 1997. Measurement of seagrass standing crop using satellite and digital airborne remote sensing. Marine Ecology Progress Series 159: 51–60.CrossRefGoogle Scholar
  55. Nelson, N.B., C.A. Carlson, and D. Stephenson. 2004. Production of chromophoric dissolved organic matter by Sargasso Sea microbes. Marine Chemistry 89: 273–287.CrossRefGoogle Scholar
  56. Orth, R.J., M.C. Harwell, E.M. Bailey, A. Bartholomew, J.T. Jawad, A.V. Lombana, K.A. Moore, J.M. Rhode, and H.E. Woods. 2000. A review of issues in seagrass seed dormancy and germination: Implications for conservation and restoration. Marine Ecology Progress Series 200: 277–288.CrossRefGoogle Scholar
  57. Orth, R., Wilcox, D. J., Nagey, L. S., Owens, A. L., Whiting, J. R. and A. K. Kenne. 2006. Distribution of submerged aquatic vegetation in Chesapeake Bay and Coastal Bays Virginia Institute of Marine Science. Special Scientific Report #150.Google Scholar
  58. Pasqualini, V., C. Pergent-Martini, G. Pergent, M. Agreil, G. Skoufas, L. Sourbes, and A. Tsirika. 2005. Use of SPOT 5 for mapping seagrasses: An application to Posidonia oceanica. Remote Sensing of Environment 94: 6.CrossRefGoogle Scholar
  59. Pegau, W. S., Zaneveld, R. V. and J. L. Mueller. 2002. Volume absorption coefficients: Instruments, characterization, field measurements and data analysis protocols. In: Ocean optics protocols for satellite ocean color sensor validation, revision 4, volume IV, eds. J. L. Mueller, G. S. Fargion, C. R. McClain. Greenbelt: National Aeronautical and Space Administration.Google Scholar
  60. Phinn, S.R., C. Roelfsema, A. Dekker, V. Brando, and J. Anstee. 2008. Mapping seagrass species, cover and biomass in shallow waters: An assessment of satellite multi-spectral and airborne hyper-spectral imaging systems in Moreton Bay (Australia). Remote Sensing of Environment 112: 3413–3425.CrossRefGoogle Scholar
  61. Pu, R., S.S. Bell, C. Meyer, L. Baggett, and Y. Zhao. 2012. Mapping and assessing seagrass along the western coast of Florida using Landsat TM and EO-1 ALI/Hyperion imagery. Estuarine, Coastal and Shelf Science 115: 234–245. doi: 10.1016/j.ecss.2012.09.006.CrossRefGoogle Scholar
  62. Ralph, G.M., R.D. Seitz, R.J. Orth, K.E. Knick, and R.N. Lipcius. 2013. Broad-scale association between seagrass cover and juvenile blue crab density in Chesapeake Bay. Marine Ecology Progress Series 488: 51–63. doi: 10.3354/meps10417.CrossRefGoogle Scholar
  63. Robbins, B.D. 1997. Quantifying temporal change in seagrass areal coverage: The use of GIS and low resolution aerial photography. Aquatic Botany 58(3–4): 259–267.CrossRefGoogle Scholar
  64. Robbins, B.D., and S.S. Bell. 2000. Dynamics of a subtidal seagrass landscape: Seasonal and annual change in relation to water depth. Ecology 81(5): 1193–1205.CrossRefGoogle Scholar
  65. Rose, C.D., W.C. Sharp, W.J. Kenworthy, J.H. Hunt, W.G. Lyons, E.J. Prager, J.F. Valentine, M.O. Hall, P.E. Whitfield, and J.W. Fourqurean. 1999. Overgrazing of a large seagrass bed by the sea urchin Lytechinus variegatus in outer Florida Bay. Marine Ecology Progress Series 190: 212–222.CrossRefGoogle Scholar
  66. Sagawaa, T., E. Boisniera, T. Komatsu, K.B. Mustaphab, A. Hattourb, N. Kosakac, and S. Miyazakic. 2010. Using bottom surface reflectance to map coastal marine areas: A new application method for Lyzenga’s model. International Journal of Remote Sensing 31(12): 3051–3064.CrossRefGoogle Scholar
  67. Savastano, K.J., K.H. Faller, and R.L. Iverson. 1984. Estimating vegetation coverage in St. Joseph Bay, Florida with an airborne multispectral scanner. Photogrammetric Engineering and Remote Sensing 50(8): 1159–1170.Google Scholar
  68. Sfriso, A., and P.F. Ghetti. 1998. Seasonal variation in biomass, morphometric parameters and production of seagrasses in the lagoon of Venice. Aquatic Botany 61: 207–223.CrossRefGoogle Scholar
  69. Short, F.T., and S. Wyllie-Echeverria. 1996. Natural and human-induced disturbance of seagrasses. Environmental Conservation 23(1): 17–27.CrossRefGoogle Scholar
  70. Silva, T.S.F., M.P.F. Costa, J.M. Melack, and E.M.L.M. Novo. 2008. Remote sensing of aquatic vegetation: Theory and applications. Environmental Monitoring and Assessment 140: 131–145.CrossRefGoogle Scholar
  71. Stewart, R.A., and D.S. Gorsline. 1962. Recent sedimentary history of St. Joseph Bay, Florida. Sedimentology 1: 256–286.CrossRefGoogle Scholar
  72. Thorhaug, A., A.D. Richardson, and G.P. Berlyn. 2007. Spectral reflectance of the seagrasses: Thalassia testudinum, Halodule wrightii, Syringodium filiforme and five marine algae. International Journal of Remote Sensing 28(7): 1487–1501.CrossRefGoogle Scholar
  73. Vahtmae, E., T. Kutser, G. Martin, and J. Kotta. 2006. Feasibility of hyperspectral remote sensing for mapping benthic macroalgal cover in turbid coastal waters—a Baltic Sea case study. Remote Sensing of Environment 101: 342–351.CrossRefGoogle Scholar
  74. van Tussenbroek, B.I. 1998. Above- and below-ground biomass and production by Thalassia tesudinum in a tropical reef. Aquatic Botany 61: 69–82.CrossRefGoogle Scholar
  75. Warren, M.A., R.S. Gregory, B.J. Laurel, and P.V.R. Snelgrove. 2010. Increasing density of juvenile Atlantic (Gadus morhua) and Greenland cod (G. ogac) in association with spatial expansion and recovery of eelgrass (Zostera marina) in a coastal nursery habitat. Journal of Experimental Marine Biology and Ecology 394(1–2): 154–160.CrossRefGoogle Scholar
  76. Waycott, M., C.M. Duarte, T.J.B. Carruthers, R. Orth, W.C. Dennison, S. Olyarnik, A. Calladine, J.W. Fourgurean, K.L. Heck, A.R. Hughes, G.A. Kendrick, W.J. Kenworthy, F.T. Short, and S.L. Williams. 2009. Accelerating loss of seagrasses across the globe threatens coastal ecosystems. Proceedings of the National Academy of Sciences 106(30): 5. doi: 10.1073/pnas.0905620106.CrossRefGoogle Scholar
  77. Wetherell, V. 1997. St. Joseph Bay aquatic preserve management plan. Washington, DC: U. S. Government Printing Office.Google Scholar
  78. With, K.A., and T.O. Crist. 1995. Critical thresholds in species responses to landscape structure. Ecology 76: 2446–2459.CrossRefGoogle Scholar
  79. Yangab, C., D. Yanga, W. Caoa, J. Zhaoab, G. Wanga, Z. Suna, Z. Xuab, and M.S.R. Kumarb. 2010. Analysis of seagrass reflectivity by using a water column correction algorithm. International Journal of Remote Sensing 31(17–18): 4595–4608.CrossRefGoogle Scholar
  80. Zieman, J.C., J.W. Fourgurean, and R. Iverson. 1989. Distribution, abundance and productivity of seagrasses and macroalgae in Florida Bay. Bulletin of Marine Sciences 44(1): 292–311.Google Scholar
  81. Zimmerman, R.C. 2003. A biooptical model of irradiance distribution and photosynthesis in seagrass canopies. Limnology and Oceanography 48(1, part 2): 568–585.CrossRefGoogle Scholar

Copyright information

© Coastal and Estuarine Research Federation 2014

Authors and Affiliations

  • Victoria J. Hill
    • 1
    Email author
  • Richard C. Zimmerman
    • 1
  • W. Paul Bissett
    • 2
    • 3
  • Heidi Dierssen
    • 4
  • David D. R. Kohler
    • 2
    • 3
  1. 1.Department Ocean, Earth and Atmospheric SciencesOld Dominion UniversityNorfolkUSA
  2. 2.Florida Environmental Research InstituteTampaUSA
  3. 3.WeoGeo, Inc.PortlandUSA
  4. 4.Marine Sciences/Geography, Department of Marine SciencesUniversity of ConnecticutGrotonUSA

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