, Volume 27, Issue 3, pp 363–377 | Cite as

Habitat requirements for submerged aquatic vegetation in Chesapeake Bay: Water quality, light regime, and physical-chemical factors

  • W. Michael Kemp
  • Richard Batleson
  • Peter Bergstrom
  • Virginia Carter
  • Charles L. Gallegos
  • William Hunley
  • Lee Karrh
  • Evamaria W. Koch
  • Jurate M. Landwehr
  • Kenneth A. Moore
  • Laura Murray
  • Michael Naylor
  • Nancy B. Rybicki
  • J. Court Stevenson
  • David J. Wilcox


We developed an algorithm for calculating habitat suitability for seagrasses and related submerged aquatic vegetation (SAV) at coastal sites where monitoring data are available for five water quality variables that govern light availability at the leaf surface. We developed independent estimates of the minimum light required for SAV survival both as a percentage of surface light passing though the water column to the depth of SAV growth (PLW min) and as a percentage of light reaching reaching leaves through the epiphyte layer (PLL min). Value were computed by applying, as inputs to this algorithm, statistically dervived values for water quality variables that correspond to thresholds for SAV presence in Chesapeake Bay. These estimates ofPLW min andPLL min compared well with the values established from a literature review. Calcultations account for tidal range, and total light attenuation is partitioned into water column and epiphyte contributions. Water column attenuation is further partitioned into effects of chlorophylla (chla), total suspended solids (TSS) and other substances. We used this algorithm to predict potential SAV presence throughout the Bay where calculated light available at plant leaves exceededPLL min. Predictions closely matched results of aerial photographic monitoring surveys of SAV distribution. Correspondence between predictions and observations was particularly strong in the mesohaline and polythaline regions, which contain 75–80% of all potential SAV sites in this estuary. The method also allows for independent assessment of effects of physical and chemical factors other than light in limiting SAV growth and survival. Although this algorithm was developed with data from Chesapeake Bay, its general structure allows it to be calibrated and used as a quantitative tool for applying water quality data to define suitability of specific sites as habitats for SAV survival in diverse coastal environments worldwide.


Total Suspended Solid Light Attenuation Submerge Aquatic Vegetation Marine Ecology Progress Series Dissolve Inorganic Phosphorus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Estuarine Research Federation 2004

Authors and Affiliations

  • W. Michael Kemp
    • 1
  • Richard Batleson
    • 2
  • Peter Bergstrom
    • 3
  • Virginia Carter
    • 4
  • Charles L. Gallegos
    • 5
  • William Hunley
    • 6
  • Lee Karrh
    • 7
  • Evamaria W. Koch
    • 1
  • Jurate M. Landwehr
    • 4
  • Kenneth A. Moore
    • 8
  • Laura Murray
    • 1
  • Michael Naylor
    • 7
  • Nancy B. Rybicki
    • 4
  • J. Court Stevenson
    • 1
  • David J. Wilcox
    • 8
  1. 1.Horn Point LaboratoryUniversity of Maryland Center for Environmental Science (CES)Cambridge
  2. 2.Chesapeake Bay Program OfficeU.S. Environmental Protection AgencyAnnapolis
  3. 3.U.S. Fish and wildlife ServiceAnnapolis
  4. 4.U.S. Geological SurveyReston
  5. 5.Smithsonian Environmental Research CenterEdgewater
  6. 6.Hampton Roads Sanitation DistrictVirginia Beach
  7. 7.Maryland Department of Natural ResourcesAnnapolis
  8. 8.Virginia Institute of Marine SciencesGloucester Point

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