Habitat Requirements for Submerged Aquatic Vegetation in Chesapeake Bay: Water Quality, Light Regime, and Physical-Chemical Factors
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...
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Published in | Estuaries Vol. 27; no. 3; pp. 363 - 377 |
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Main Authors | , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Lawrence, KS
Estuarine Research Federation
01.06.2004
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
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Abstract | 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 through the water column to the depth of SAV growth (PLWmin) and as a percentage of light reaching leaves through the epiphyte layer (PLLmin). Values were computed by applying, as inputs to this algorithm, statistically derived values for water quality variables that correspond to thresholds for SAV presence in Chesapeake Bay. These estimates of PLWminand PLLmincompared well with the values established from a literature review. Calculations 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 chlorophyll a (chl a), 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 exceeded PLLmin. Predictions closely matched results of aerial photographic monitoring surveys of SAV distribution. Correspondence between predictions and observations was particularly strong in the mesohaline and polyhaline 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. |
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AbstractList | 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 ^sub min^) and as a percentage of light reaching reaching leaves through the epiphyte layer (PLL ^sub 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 ^sub min^ andPLL ^sub 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 ^sub 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.[PUBLICATION ABSTRACT] 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 through the water column to the depth of SAV growth (PLW sub(min)) and as a percentage of light reaching leaves through the epiphyte layer (PLL sub(min)). Values were computed by applying, as inputs to this algorithm, statistically derived values for water quality variables that correspond to thresholds for SAV presence in Chesapeake Bay. These estimates of PLW sub(min) and PLL sub(min) compared well with the values established from a literature review. Calculations 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 chlorophyll a (chl a), 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 exceeded PLL sub(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 polyhaline 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. 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 sub(min)) and as a percentage of light reaching reaching leaves through the epiphyte layer (PLL sub(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 sub(min) andPLL sub(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 sub(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. 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 through the water column to the depth of SAV growth (PLWmin) and as a percentage of light reaching leaves through the epiphyte layer (PLLmin). Values were computed by applying, as inputs to this algorithm, statistically derived values for water quality variables that correspond to thresholds for SAV presence in Chesapeake Bay. These estimates of PLWminand PLLmincompared well with the values established from a literature review. Calculations 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 chlorophyll a (chl a), 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 exceeded PLLmin. Predictions closely matched results of aerial photographic monitoring surveys of SAV distribution. Correspondence between predictions and observations was particularly strong in the mesohaline and polyhaline 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. |
Author | Carter, Virginia Koch, Evamaria W. Wilcox, David J. Hunley, William Kemp, W. Michael Landwehr, Jurate M. Rybicki, Nancy B. Moore, Kenneth A. Murray, Laura Naylor, Michael Bartleson, Richard Karrh, Lee Stevenson, J. Court Bergstrom, Peter Batiuk, Richard Gallegos, Charles L. |
Author_xml | – sequence: 1 givenname: W. Michael surname: Kemp fullname: Kemp, W. Michael – sequence: 2 givenname: Richard surname: Batiuk fullname: Batiuk, Richard – sequence: 3 givenname: Richard surname: Bartleson fullname: Bartleson, Richard – sequence: 4 givenname: Peter surname: Bergstrom fullname: Bergstrom, Peter – sequence: 5 givenname: Virginia surname: Carter fullname: Carter, Virginia – sequence: 6 givenname: Charles L. surname: Gallegos fullname: Gallegos, Charles L. – sequence: 7 givenname: William surname: Hunley fullname: Hunley, William – sequence: 8 givenname: Lee surname: Karrh fullname: Karrh, Lee – sequence: 9 givenname: Evamaria W. surname: Koch fullname: Koch, Evamaria W. – sequence: 10 givenname: Jurate M. surname: Landwehr fullname: Landwehr, Jurate M. – sequence: 11 givenname: Kenneth A. surname: Moore fullname: Moore, Kenneth A. – sequence: 12 givenname: Laura surname: Murray fullname: Murray, Laura – sequence: 13 givenname: Michael surname: Naylor fullname: Naylor, Michael – sequence: 14 givenname: Nancy B. surname: Rybicki fullname: Rybicki, Nancy B. – sequence: 15 givenname: J. Court surname: Stevenson fullname: Stevenson, J. Court – sequence: 16 givenname: David J. surname: Wilcox fullname: Wilcox, David J. |
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CODEN | ESTUDO |
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ContentType | Journal Article |
Copyright | Copyright 2004 Estuarine Research Federation 2004 INIST-CNRS Estuarine Research Federation 2004 |
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ISSN | 0160-8347 1559-2723 |
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Issue | 3 |
Keywords | Marine environment Brackish water environment Light Water quality Vegetation Estuaries Environmental factor Habitat Bay Habitat selection |
Language | English |
License | CC BY 4.0 |
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PublicationDate | 2004-06-01 |
PublicationDateYYYYMMDD | 2004-06-01 |
PublicationDate_xml | – month: 06 year: 2004 text: 2004-06-01 day: 01 |
PublicationDecade | 2000 |
PublicationPlace | Lawrence, KS |
PublicationPlace_xml | – name: Lawrence, KS – name: Stony Brook |
PublicationTitle | Estuaries |
PublicationYear | 2004 |
Publisher | Estuarine Research Federation Springer Nature B.V |
Publisher_xml | – name: Estuarine Research Federation – name: Springer Nature B.V |
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Snippet | We developed an algorithm for calculating habitat suitability for seagrasses and related submerged aquatic vegetation (SAV) at coastal sites where monitoring... |
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SubjectTerms | Algorithms Animal and plant ecology Animal, plant and microbial ecology Aquatic habitats Aquatic plants Biogeochemistry Biological and medical sciences Brackish Brackish water ecosystems Coastal environments Environmental monitoring Epiphytes Estuaries Fundamental and applied biological sciences. Psychology Habitats Leaves Literature reviews Moorings Plant growth Plants Sediments Submerged aquatic plants Synecology Tidal range Total suspended solids Transcriptional regulatory elements Vegetation Water column Water depth Water quality |
Title | Habitat Requirements for Submerged Aquatic Vegetation in Chesapeake Bay: Water Quality, Light Regime, and Physical-Chemical Factors |
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