Assessment of environmental suitability for growth of Zostera marina L. (eelgrass) in San Francisco Bay

Zimmerman, Richard C.; Reguzzoni, John L.; Wyllie‐Echeverria, Sandy; Josselyn, Michael; Alberte, Randall S.

doi:10.1016/0304-3770(91)90009-t

Cited by 92 publications

(56 citation statements)

References 24 publications

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“…Of the possible factors that can directly influence the survival of transplanted eelgrass, poor site-selection (Harrison 1990, Fonseca 1992 has been identified as the major limitation: often sites with insufficient light associated with poor water quality (Zimmerman et al 1991, 1995, Reid et al 1993) are selected. Excess inorganic nitrogen can contribute to reduced light conditions or smothering by macroalgae (Costa et al 1992, Short et al 1995.…”

Section: Resale or Republication Not Permitted Without Written Consenmentioning

confidence: 99%

Site-selection model for optimal transplantation of eelgrass Zostera marina in the northeastern US

Short¹,

Davis²,

Kopp³

et al. 2002

Mar. Ecol. Prog. Ser.

113

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Section: Resale or Republication Not Permitted Without Written Consenmentioning

confidence: 99%

Site-selection model for optimal transplantation of eelgrass Zostera marina in the northeastern US

Short¹,

Davis²,

Kopp³

et al. 2002

Mar. Ecol. Prog. Ser.

113

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“…Estuaries are vulnerable to anthropogenic alteration of water quality, particularly with regard to light availability. Increased turbidity caused by eutrophication, chronic upstream erosion and periodic dredging has dramati-cally reduced light penetration in many estuarine water columns, thereby reducing the depth distnbution, density and productivity of SAM (Zieman 1975, Orth & Moore 1983, Cambridge & McComb 1984, Shepherd et al 1989, Carter & Rybicki 1990, Larkum & West 1990, Zimmerman et al 1991, Monroe et al 1992.…”

Section: Introductionmentioning

confidence: 99%

“…(Onuf 1991, Dennison et al 1993, Dunton & Tomasko 1994. In addition, different mean light requirements have been reported for the same species growing in different habitats (Ostenfeld 1908, Borum 1983, Dennison 1987, Kenworthy et al 1991, and the apparent light requirement of a single species growing within a single estuary appears to increase as the variance in light availability increases (Zimmerman et al 1991). Thus, the correlation between mean light attenuation and maximum colonization depth appears to require extensive site-and population-specific calibration in order to generate a useful predictor of environmental suitability.…”

Section: Introductionmentioning

confidence: 99%

Modeling daily production of aquatic macrophytes from irradiance measurements: a comparative analysis

Zimmerman¹,

Cabello‐Pasini²,

Alberte³

1994

Mar. Ecol. Prog. Ser.

100

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The importance of submerged aquatlc macrophytes to coastal ecosystems has generated a need for knowledge of minlmum l~g h t levels that wlll support the m a~n t e n a n c e and restoration of healthy populations Our goals were (1) to evaluate the s e n s~t~v~t y to natural, non-sinusoidal fluctuatlons in irradiance I of analytical integration techniques for calculating daily carbon gain (2) to evaluate the H,,, (the daily period of I-saturated photosynthesis) model of daily production relat~ve to models based on Instantaneous photosynthesis vs Irradiance ( P v s I ) and (3) to provlde some guidance for the temporal d e n s~t y of Irradiance data r e q u~r e d for accurate estimation of dally carbon gain Monthly measures of the P v s I response of an eelgrass Zostera m a n n a L population were used to p~e d l c t rates of dally carbon galn from continuous in sjtu recordings of I Dally ~n t e g r a t e d I was not a reliable predictor of daily product~on Numencal (iterative) integration of H,,, was much more r e l~a b l e but r e q u~r e d repeated measures of I within a day as did numencal integrat~on of P vs I Analytical (non-iterative) models based only on observations of l,, (noon) could not p r e d~c t daily production accurately Analyt~cal models of P v s I and H,,, agreed with each other, however, indicating that the analyt~cal models may be useful where the daily pattern of I is sinusoidal Given the h~g h degree of temporal vanability in coastal 11ght environments continuous monltonng of hght a v a~l a b~l i t y may be required for calculation of daily production and rehable management of aquatlc macrophyte populations

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“…In most cases, these complex models are designed for estimating general trends in seagrass growth under scenarios of changing environmental conditions, rather than for directly assessing SAV habitat suitability at specific sites based on water quality measurements. Simple empirical correlations (Nielsen et al 2002) have been used to predict depth of maximum SAV biomass or colonization from routine water clarity measurements (Rørslett 1987;Zimmerman et al 1991;de Jonge and de Jong 1992). Although the widespread availability of water clarity data (e.g., Secchi disk depth) makes this a potentially useful approach, it does not account for light attenuation by epiphytes on SAV leaves, often a dominant factor in regulating plant growth (Twilley et al 1985;Sand-Jensen 1990).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2004

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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 min ) and as a percentage of light reaching leaves through the epiphyte layer (PLL 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 min and PLL 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 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.

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Assessment of environmental suitability for growth of Zostera marina L. (eelgrass) in San Francisco Bay

Cited by 92 publications

References 24 publications

Site-selection model for optimal transplantation of eelgrass Zostera marina in the northeastern US

Site-selection model for optimal transplantation of eelgrass Zostera marina in the northeastern US

Modeling daily production of aquatic macrophytes from irradiance measurements: a comparative analysis

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

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