Chesapeake Bay Submerged Aquatic Vegetation Water Quality ...total suspended solids. These SAV...

Chesapeake Bay Submerged Aquatic Vegetation Water Quality

and Habitat-Based Requirements and Restoration Targets:

A Second Technical Synthesis

August 2000

Printed by the United States Environmental Protection Agencyfor the Chesapeake Bay Program

Printed on recycled paper

A Watershed Partnership

Chesapeake Bay Program

The loss of submerged aquatic vegetation, or SAV,from shallow waters of Chesapeake Bay, which wasfirst noted in the early 1960s, is a widespread, well-documented problem. Although other factors, such asclimatic events and herbicide toxicity, may have con-tributed to the decline of SAV in the Bay, the primarycauses are eutrophication and associated reductions inlight availability. The loss of SAV beds are of particularconcern because these plants create rich animal habitatsthat support the growth of diverse fish and invertebratepopulations. Similar declines in SAV have been occurringworldwide with increasing frequency during the lastseveral decades. Many of these declines have been attrib-uted to excessive nutrient enrichment and decreases inlight availability.

The health and survival of these plant communities inChesapeake Bay and other coastal waters depend on suit-able environmental conditions that define the quality ofSAV habitat. These habitats have been characterized previ-ously for Chesapeake Bay using simple models that relateSAV presence to medians of water quality variables. InChesapeake Bay Submerged Aquatic Vegetation HabitatRequirements and Restoration Targets: A Technical Syn-thesis, published in 1992, SAV habitat requirements weredefined in terms of five water quality variables: dissolvedinorganic nitrogen, dissolved inorganic phosphorus, water-column light attenuation coefficient, chlorophyll a andtotal suspended solids. These SAV habitat requirements(Table 1, last five columns) have been used in conjunctionwith data from the Chesapeake Bay Monitoring Programas diagnostic tools to assess progress in restoring habitatquality for SAV growth in Chesapeake Bay. Attempts to

use these habitat requirements to predict SAV presence orabsence in Chesapeake Bay and elsewhere, however, havemet with mixed success.

REVISING THE HABITAT REQUIREMENTS

Although the 1992 SAV habitat requirements have proveduseful in factoring SAV restoration into nutrient reductiongoal-setting for Chesapeake Bay, the original habitatrequirements contain several limitations:

• It is unclear how many of the five requirements mustbe met to maintain existing SAV beds or establishnew ones.

• The requirements ignore leaf surface light attenua-tion, which can be high enough to restrict SAVgrowth where there is a high epiphytic and sedimentload on the leaf surface.

• There is no way to adjust the water-column lightattenuation coefficient (Kd) requirement for varia-tions in tidal range, or to adjust it for different SAVrestoration depths.

For these reasons, we undertook this revision of the orig-inal habitat requirements.

The principal relationships between water quality condi-tions and light regimes for growth of SAV are illustratedin Figure 1, which represents an expansion of a similarconceptual diagram presented in the first SAV technicalsynthesis. Incident light, which is partially reflected at thewater surface, is attenuated through the water columnabove SAV by particulate matter (chlorophyll a and totalsuspended solids), by dissolved organic matter and by

Executive Summary iii

Executive Summary

water itself. In most estuarine environments, the water-column light attenuation coefficient is dominated by con-tributions from chlorophyll a and total suspended solids.This was the only component of light attenuation consid-ered in the original habitat requirements.

Based on this conceptual model and an extensive reviewof the scientific literature, the original Kd habitat require-ments were validated and reformulated as the “water-

column light requirements” (Table 1). The attainment ofthe water-column light requirements at a particular sitecan be tested with the new “percent light through water”parameter (PLW), which is calculated from Kd and water-column depth and can be adjusted for both tidal range andvarying restoration depths (Figure 2).

Light that reaches SAV leaves also is attenuated by theepiphytic material (i.e., algae, bacteria, detritus and

iv SAV TECHNICAL SYNTHESIS II

TABLE 1. Recommended habitat requirements for growth and survival of submerged aquatic vegetation(SAV) in Chesapeake Bay and its tidal tributaries.

# Regions of the estuary defined by salinity regime, where tidal fresh = 5-18 ppt and polyhaline = >18 ppt.

* Medians calculated over this growing season should be used to check the attainment of any of these habitatrequirements, and raw data collected over this period should be used for statistical tests of attainment (see Chapter VII). For polyhaline areas, the data are combined for the two growing season periods shown.

† Minimum light requirement for SAV survival based on analysis of literature, evaluation of monitoring and research findings and application of models (see Chapters III, V and VII). Use the primary requirement, or minimum lightrequirement, whenever data are available to calculate percent light at the leaf (PLL) (which requires light attenuationcoefficient [Kd] or Secchi depth, dissolved inorganic nitrogen, dissolved inorganic phosphorus and total suspended solids measurements).

**Relationships were derived from statistical analyses of field observations on water quality variables in comparison toSAV distributions at selected sites. The secondary requirements are diagnostic tools used to determine possible reasonsfor non-attainment of the primary requirement (minimum light requirement). The water-column light requirement canbe used as a substitute for the minimum light requirement when data required to calculate PLL are not fully available.

Primary Secondary Requirements**Requirements† (Diagnostic Tools)

Tidal April- >9 >13

Executive Summary v

LightTransmission

LightAttenuation

Reflection

PlanktonChlorophyll a

TotalSuspended

Solids

DIN

DIP Epiphytes

Grazers

SAV

• Water

• Particles

• Color

• Algae

• Detritus

PLW (% Light through Water)

PLL (% Light at the Leaf)

WaterColumn

(Kd)

Epiphyte(Ke)

FIGURE 1. Conceptual Model of Light/Nutrient Effects on SAV Habitat. Availability of light for SAV is influenced by water column and at the leaf surface light attenuation processes. DIN = dissolved inorganic nitrogen and DIP = dissolved inorganic nitrogen.

sediment) that accumulates on the leaves. This epiphyticlight attenuation coefficient (called Ke) increases expo-nentially with epiphyte biomass, where the slope of thisrelationship depends on the composition of the epiphyticmaterial. Dissolved inorganic nutrients in the water col-umn stimulate growth of epiphytic algae (as well as phy-toplankton), and suspended solids can settle onto SAVleaves to become part of the epiphytic matrix. Becauseepiphytic algae also require light to grow, water depth andKd constrain epiphyte accumulation on SAV leaves, andlight attenuation by epiphytic material depends on themass of both algae and total suspended solids settling onthe leaves. An algorithm was developed to compute thebiomass of epiphytic algae and other materials attached toSAV leaves, and to estimate light attenuation associatedwith these materials. This algorithm uses monitoring datafor Kd (or Secchi depth), total suspended solids, dissolvedinorganic nitrogen and dissolved inorganic phosphorus to

calculate the potential contribution of epiphytic materialsto total light attenuation for SAV at a particular depth(Figure 2).

The SAV water-column light requirements were largelyderived from studies of SAV light requirements, in whichepiphyte accumulation on plant leaves was not controlled.Therefore, light measurements in those studies did notaccount for attenuation due to epiphytes. To determineminimum light requirements at the leaf surface itself,three lines of evidence were compared:

1. Applying the original SAV habitat requirementsparameter values to the new algorithm for calculat-ing PLL (Figure 2), for each of the four salinityregimes;

2. Evaluating the results of light requirement studiesfrom areas with few or no epiphytes; and

vi SAV TECHNICAL SYNTHESIS II

Percent Light through Water (PLW) Percent Light at the Leaf (PLL)

Inputs•Kd measured directly or•Kd calculated from Secchi depth

Inputs•Kd •Total suspended solids•Dissolved inorganic nitrogen•Dissolved inorganic phosphorus

Approach followed when only Secchi depth/direct light attenuation data areavailable

Recommended approach forbest determination of the amount of light reaching SAV leaves

Calculation

EvaluationPLW vs. Water-Column

Light Requirement

Calculation

•Ke = Epiphyte attenuation•Be = Epiphyte biomass

EvaluationPLL vs. Minimum Light

Requirement

WaterColor

Total SuspendedSolids

Algae

PLWEpiphyteAttenuation

Leaf Surface PLL

100% Ambient Light of Water Surface

PLW=e(Kd)(Z)100 PLL=[e-(Kd)(Z)][e-(Ke)(Be)]100

FIGURE 2. Calculation of PLW and PLL and Comparisons with their Respective Light Requirements. Illustrationof the inputs, calculation and evaluation of the two percent light parameters: percent light through water and percentlight at the leaf.

3. Comparing median field measurements of theamount of light reaching plants’ leaves (estimatedthrough the PLL algorithm) along gradients of SAVgrowth observed within Chesapeake Bay and itstidal tributaries.

Minimum light requirements of 15 percent for mesohalineand polyhaline habitats and 9 percent for tidal fresh andoligohaline habitats resulted from the intersection of thesethree lines of evidence (Table 1). The attainment of the min-imum light requirement at a particular site is tested by com-paring it with the calculated PLL parameter (Figure 2).

VALIDATING THE REVISED REQUIREMENTS

The algorithm described above was applied to analyzeSAV habitat suitability for some 50 sites in ChesapeakeBay and its tidal tributaries using data collected over 14years (1985-1998) of environmental monitoring. For eachmonitoring site, values were calculated for PLW and PLLat 0.5-meter and 1-meter depths, adding half of the tidalrange to those values. There was considerable variation inthe relationship between PLL and PLW among sitesthroughout Chesapeake Bay, but clear patterns were evi-dent (Figure 3). Light attenuation by epiphytic materialappears to be generally important throughout ChesapeakeBay, contributing 20 to 60 percent additional attenuation(beyond that due to water-column light attenuation) in thetidal fresh and oligohaline regions, where nutrient and totalsuspended solids concentrations were highest, and con-tributing 10 to 50 percent in the less turbid mesohaline andpolyhaline regions. These findings are consistent with the30 percent additional light reduction expressed in the PLLvalue, which was calculated using the 1992 SAV habitatrequirements, compared to the PLW parameter value,which was extracted from the same 1992 requirements.

We tested the robustness of this analysis by relating cal-culated values for PLL at 0.5-meter and 1-meter waterdepths to SAV presence (over a 10-year record) in areasadjacent to water quality monitoring stations. Five quanti-tative categories of SAV presence were defined based onSAV areas recorded over all years within the ChesapeakeBay and tidal tributaries’ 70 segments. These categorieswere: always abundant (AA); always some (AS); some-times none (SN); usually none (UN); and always none(AN). The observed patterns of percent light at the leafsurface versus SAV presence were then compared with theapplicable minimum light requirement.

Executive Summary vii

FIGURE 3. Percent Light at Leaf vs. Percent LightThrough Water Column by Salinity Regime.Comparing values for percent surface light at SAV leafsurface (PLL) and percent surface light through waterjust above the SAV leaf (PLW) calculated for Z = 1 mfrom the model described in this report (Table V-1) forwater quality monitoring stations in Virginia portion ofChesapeake Bay for 1985-1996 in three salinity regimes.Lines indicate position of points where epiphyte attenua-tion reduced ambient light levels at the leaf surface by 0, 25, 50 and 75 percent.

We assumed that water quality adequate to support SAVgrowth would be found in segments that fell in the AS andSN categories, since they always or usually had mappedSAV. Thus, we predicted that median PLL values for seg-ments in those categories should be near the minimumlight requirement. For the mesohaline and polyhalineregions of the Bay, we found excellent agreement (Figure4) between the median PLL values calculated (at 1-meterdepth plus half tidal range) for sites categorized as AS andSN (ranging from 13 to 18 percent) and the minimumlight requirement value for these higher salinity areas (15percent). The agreement was not as close, however, for thetidal fresh and oligohaline regions of the Bay. MedianPLL values in these regions ranged from 5 to 8 percent forsites categorized as AS and SN, only exceeding the mini-mum light requirement value of 9 percent for segments inthe AA category at the 0.5-meter restoration depth. Forlower salinity segments in the AS or SN categories at the1-meter restoration depth, the median PLL value was only1 to 3 percent–far less than the expected 9 percent. SAVspecies that inhabit shallow waters (0.25 meters or less,even up to the intertidal zone) in the fresh and brackishreaches of the upper Bay and tidal tributaries are predom-inantly canopy-forming species that grow rapidly untilthey reach the water’s surface. This appears to allow themto grow in low salinity sites where the estimated lightlevel at the leaf at the restoration depth (e.g., 1 meter) ispredicted to be inadequate to support SAV growth.

NEW ASSESSMENT ANDDIAGNOSTIC CAPABILITIES

An important advancement in this report was the develop-ment of an SAV habitat assessment method that explicitlyconsiders water depth requirements for SAV restoration.As SAV is generally excluded from intertidal areasbecause of physical stress (waves, dessication and freez-ing), the upper depth-limit for SAV distribution is usuallydetermined by the low tide line. The maximum depth ofSAV distribution, in turn, is limited by light penetration. Arelatively small tidal range results in a larger SAV depthdistribution (Figure 5A), whereas a large tidal rangeresults in a smaller SAV depth distribution (Figure 5B).This is because the upper depth-limit for SAV distributiontends to be lower in areas with larger tidal range. Further-more, the lower depth-limit tends to be reduced at sites

viii SAV TECHNICAL SYNTHESIS II

FIGURE 4. Comparison of PLL Values for DifferentRestoration Depths Across Salinity Regimes by SAVAbundance Category. SAV growing season medianpercent light at the leaf (PLL) calculated using 1985-1998 Chesapeake Bay Water Quality MonitoringProgram data by SAV relative abundance category. AN = Always None, UN = Usually None, SN =Sometimes None, AS = Always Some, AA-AlwaysAbundant. The applicable minimum light requirement(MLR) for each salinity regime is illustrated as a dashedline. The number with a plus symbol within parenthesesafter PLL indicates the restoration depth adjusted fortidal range.

with larger tidal range because of increased light attenua-tion through the longer average water column. Thus, theretends to be an inverse relationship between tidal range andthe range of SAV depth distribution. When the PLW orPLL parameters are calculated, half the mean diurnal tidalrange is added to the target SAV restoration depth value(Z) to reflect this relationship.

A management diagnostic tool was developed for quanti-fying the attenuation of light within the water column thatis attributable to light absorption and scattering by dis-solved and suspended substances in water and by wateritself. Water-column attenuation of light measured by Kdwas divided into contributions from four sources: water,dissolved organic matter, chlorophyll a and total sus-pended solids. The basic relationships were thusdescribed by a series of simple equations, which werecombined to produce the equation for the diagnostic tool.The resulting equation calculates linear combinations ofchlorophyll a and total suspended concentrations that justmeet the water-column light requirement for a particulardepth (Figure 6) at any site or season in Chesapeake Bayand its tidal tributaries. This diagnostic tool can also beused to consider various management options for improv-ing water quality conditions when the SAV water-columnlight requirements are not currently met.

This report defines SAV habitat requirements in terms oflight availability to support plant photosynthesis, growthand survival. Other physical, geological and chemical fac-tors may, however, preclude SAV from particular siteseven when minimum light requirements are met. Theseeffects on SAV are illustrated (Figure 7) as an overlay tothe previous conceptualization (Figure 1) depicting inter-actions between water quality variables and SAV lightrequirements. Some of these effects operate directly onSAV, while others involve inhibiting SAV/light interac-tions. Waves and tides alter the light climate by changingthe water-column height over which light is attenuated,and by resuspending bottom sediments, thereby increas-ing total suspended solids and associated light attenua-tion. Particle sinking and other sedimentologicalprocesses alter texture, grain-size distribution and organiccontent of bottom sediments, which can affect SAVgrowth by modifying availability of porewater nutrientsand by producing reduced sulfur compounds that are phy-totoxic. In addition, pesticides and other anthropogenicchemical contaminants tend to inhibit SAV growth. Anextensive review of the literature revealed that certainSAV species and functional groups appear to have alimited range in their ability to tolerate selected physical,sedimentological and chemical variables (Table 2).

Executive Summary ix

FIGURE 5. Tidal Range Influence on Vertical SAV Depth Distribution. The vertical range of distribution of SAVbeds can be reduced with increased tidal range. The minimum depth of SAV distribution (Zmin) is limited by the lowtide (T), while the maximum depth of SAV distribution (Zmax) is limited by light (L). The SAV fringe (arrow) decreasesas tidal range increases. A small tidal range results in a large SAV depth distribution (A), whereas a large tidal rangeresults in a small SAV depth distribution (B). Mean high water (MHW), mean tide level (MTL) and mean low water(MLW) are all illustrated.

The original tiered SAV distribution restoration targets forChesapeake Bay, first published in the 1992 SAV techni-cal synthesis, have been refined to reflect improvementsin the quality of the underlying aerial survey database anddepth contour delineations, based on an expanded bay-wide bathymetry database (Table 3). The previous targetsdid not include Tier II, which is potential habitat to 1-meter depth at mean lower low water, because this con-tour was not available in 1992. As of 1998, baywide SAVdistributions covered 56 percent of the areas in the Tier Irestoration goal and 16 and 10 percent of the tiers II andIII restoration target areas, respectively.

One question raised in the original SAV technical synthe-sis, which continues to be relevant to this analysis, is theextent to which water quality monitoring data collectedfrom midchannel stations in the Bay and its tidal tributar-ies represent conditions at nearshore sites where SAVpotentially occurs. Several studies conducted by stateagencies, academic researchers and citizen monitors since1992 provided the basis for more comprehensive analysisof this question using data from the upper mainstemChesapeake Bay and 12 tidal tributary systems. Resultsrevealed that SAV habitat quality conditions are indistin-guishable between nearshore and adjacent midchannelstations 90 percent of the time, when station pairs wereseparated by less than two kilometers.

SUMMARY

The present report provides an integrated approach fordefining and testing the suitability of Chesapeake Bayshallow water habitats in terms of the minimum lightrequirements for SAV survival. It incorporates statisticalrelationships from monitoring data, field and experimen-tal studies and numerical model computations to producealgorithms that use water quality data for any site to cal-culate potential light availability at the leaf surface forSAV at any restoration depth. The original technical syn-thesis defined SAV habitat requirements in terms of fivewater quality parameters based on field correlationsbetween SAV presence and water quality conditions. Inthe present approach, these parameters are used to calcu-late potential light availability at SAV leaves for anyChesapeake Bay site. These calculated percent light at theleaf surface values are then compared to minimum lightrequirements to assess the suitability of a particular site asSAV habitat. Values for the minimum light requirementswere derived from algorithm calculations of light at SAV leaves using the 1992 SAV habitat requirements,

x SAV TECHNICAL SYNTHESIS II

Chlorophyll

Medianconditions

Target

TargetTarget

N/A

N/A

TS

S

TS

S

TS

S

TS

S

N/A

N/A

Habitatrequirement

Target

Medianconditions

Medianconditions

Medianconditions

Chlorophyll Chlorophyll

ChlVS

D. Chlorophyll Reduction OnlyC. TSS Reduction Only

B. Normal ProjectionA. Projection to Origin

Chlorophyll

FIGURE 6. Illustration of Management Optionsfor Determining Target Concentrations ofChlorophyll and Total Suspended Solids.Illustration of the use of the diagnostic tool tocalculate target growing-season median con-centrations of total suspended solids (TSS) and chlorophyll for restoration of SAV to a given depth. Target concentrations are calculated as the intersection of the minimum light habitatrequirement, with a line describing the reduction of median chlorophyll and TSS concentrationscalculated by one of four strategies: (A) projectionto the origin (i.e. chlorophyll=0, TSS=0); (B)normal projection, i.e. perpendicular to the mini-mum light habitat requirement; (C) reduction in total suspended solids only; and (D) reduction inchlorophyll only. A strategy is not available (N/A)whenever the projection would result in a ‘negativeconcentration'. In (D), reduction in chlorophyll alsoreduces TSS due to the dry weight of chlorophyll,and therefore moves the median parallel to the line (long dashes) for ChlVS, which describes the minimum contribution of chlorophyll to TSS.

Executive Summary xi

Light Transmission

Waves Tides



DIN

DIP Epiphytes

Grazers

Organic matter Sulfide

N

P

Contaminants

Biogeo-chemicalprocesses

Settlingof

OrganicMatter

SAV

PLL

PLW

Currents

FIGURE 7. Interaction between Light-Based, Physical, Geological and Chemical SAV HabitatRequirements. Interaction between previously established SAV habitat requirements, suchas light attenuation, dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus(DIP), chlorophyll a, total suspended solids (TSS) and other physical/chemical parametersdiscussed in this chapter (waves, currents, tides, sediment organic matter, biogeochemicalprocesses). P = phosphorus; N = nitrogen; PLW = percent light through water; PLL =percent light at the leaf.

xii SAV TECHNICAL SYNTHESIS II

TABLE 2. Summary of physical and chemical factors defining habitat constraints for submersed aquaticplants.

Executive Summary xiii

TABLE 3. Chesapeake Bay SAV distribution targets and their relationships to the 1998 SAV aerial surveydistribution data.

extensive review of the scientific literature and evaluationof monitoring and field research findings. These calcula-tions account for regionally varying tidal ranges, and theypartition total light attenuation into water-column and epi-phyte contributions; water-column attenuation is furtherpartitioned into effects of chlorophyll a, total suspendedsolids and dissolved organic matter. This approach is usedto predict the presence of suitable water quality conditionsfor SAV at all monitoring stations around the Bay. Thesepredictions compared well with results of SAV distribu-tion surveys in areas adjacent to water quality monitoringstations in the mesohaline and polyhaline regions, whichcontain 75 to 80 percent of all recent mapped SAV areasand potential SAV habitat in the Bay and its tidaltributaries.

The approach for assessing SAV habitat conditionsdescribed in this report represents a major advance overthat presented in 1992. At the same time, areas requiring

further research, assessment and understanding have beenbrought into sharper focus. The key relationships withinthe algorithm developed for calculating epiphytic contri-butions to light attenuation can be strengthened andupdated with further field and experimental studies. Par-ticular attention needs to be paid to the relationshipsbetween epiphyte biomass and nutrient concentrationsand between total suspended solids and the total mass ofepiphytic material, and to a better understanding of therelationships in lower salinity areas. Detailed field andlaboratory studies are needed to develop quantitative,species-specific estimates of minimum light requirementsboth for the survival of existing SAV beds and for reestab-lishing SAV into unvegetated sites. Although this reportalso provides an initial consideration of physical, geolog-ical and chemical requirements for SAV habitat, morework is needed to develop integrated quantitative meas-ures of SAV habitat suitability in terms of physical,geological and chemical factors.

xiv SAV TECHNICAL SYNTHESIS II

Richard A. BatiukU.S. Environmental Protection AgencyChesapeake Bay Program OfficeAnnapolis, Maryland

Peter BergstromU.S. Fish and Wildlife ServiceChesapeake Bay Field OfficeAnnapolis, Maryland

Michael Kemp, Evamaria Koch, Laura Murray,J. Court Stevenson, and Rick BartlesonUniversity of Maryland Center for Environmental StudiesHorn Point LaboratoryCambridge, Maryland

Virginia Carter, Nancy B. Rybicki,and Jurate M. LandwehrU.S. Geological SurveyWater Resources DivisionReston, Virginia

Charles GallegosSmithsonian InstitutionSmithsonian Environmental Research CenterEdgewater, Maryland

Lee Karrh and Michael NaylorMaryland Department of Natural ResourcesResource Assessment Service, Tidewater EcosystemAssessmentAnnapolis, Maryland

David Wilcox and Kenneth A. MooreCollege of William and MaryVirginia Institute of Marine ScienceGloucester Point, Virginia

Steve AilstockAnne Arundel Community CollegeArnold, Maryland

Mirta TeichbergChesapeake Research Consortium, Inc.Edgewater, Maryland

Principal Authors xv

Principal Authors

The development of this second technical synthesiswas made possible by the efforts of authors of the ini-tial technical synthesis and numerous investigators, fieldand laboratory technicians, program managers and manyother people over the past three decades.

Technical comments and suggestions provided by the fol-lowing independent peer reviewers are fully acknowl-edged: John Barko, U.S. Army Corps of Engineers Water-ways Experimental Station; Ryan Davis, Alliance for theChesapeake Bay; Kellie Dixon, Mote Marine Laboratory;Ken Dunton; University of Texas Marine Science Insti-tute; Mike Durako, University of North Carolina Centerfor Marine Science Research; Mark Fonseca, NOAANational Marine Fisheries Service Science Center-Beau-fort Laboratory; Jim Fourqurean, Florida InternationalUniversity; Brian Glazer, University of Delaware Collegeof Marine Studies; Holly Greening, Tampa Bay EstuaryProgram; Dick Hammerschlag, U.S. Geological Survey;Will Hunley, Hampton Roads Sanitation District; W.Judson Kenworthy, NOAA National Marine FisheriesService Science Center-Beaufort Laboratory; HilaryNeckles, U.S. Geological Survey; Harriette Phelps, Uni-versity of District of Columbia; Kent Price, University ofDelaware College of Marine Studies; Fred Short, Univer-sity of New Hampshire Jackson Estuarine Laboratory;Michael Smart, Lewisville Aquatic Ecosystem ResearchFacility; John Titus, Binghamton University; DaveTomasko, Southwest Florida Water Management District;Robert Virnstein, St. Johns Water Management District;

Lexia Valdes, University of Delaware College of MarineStudies; and Richard Zimmerman, Hopkins MarineStation.

The technical editing skills of Robin Herbst, University of Maryland Eastern Shore, drew together the work of 17 authors into a single, integrated technical synthesis.

The Chesapeake Bay Program's Living Resources Sub-committee has contributed directly to this second techni-cal synthesis through their funding support of the researchneeds identified through the 1992 synthesis and continuedfunding of the annual baywide SAV aerial survey pro-gram. This management commitment to funding researchsupported a second synthesis cycle: synthesis of availabledata and information; identification of unmet manage-ment information needs; funding of required research;continued commitment to long-term monitoring followedby another round of synthesis and management applica-tion of new findings.

Funding for the compilation of this second technicalsynthesis was from the U.S. Environmental ProtectionAgency through a cooperative agreement with theChesapeake Research Consortium. Funding for theresearch and monitoring results reported here came froma wide variety of dedicated agencies whose contributionsto Chesapeake Bay SAV research, distribution surveys,and long term water quality monitoring programs arehereby acknowledged.

Acknowledgments xvii

Acknowledgments

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii(Kemp, Batiuk, and Bergstrom)

Principal Authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii

CHAPTER IIntroduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1(Batiuk and Bergstrom)

Technical Synthesis Objectives, Content, and Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2Synthesis Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2Synthesis Content and Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

CHAPTER IISAV, Water Quality, and Physical Habitat Relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3(Kemp, Batiuk, and Bergstrom)

CHAPTER IIILight Requirements for SAV Survival and Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11(Carter, Rybicki, Landwehr, Naylor)

Discussion of Literature Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11Photosynthesis-irradiance Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11Field Observations of Maximum Depth and Available Light . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15Light Manipulation Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15Light Availability Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Determination of Minimum Light Requirements for Chesapeake Bay . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27Factors to be Considered in Determining Minimum Light Requirements . . . . . . . . . . . . . . . . . . . . . . 27Chesapeake Bay Research and Monitoring Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Water-Column Light Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Contents xix

Contents

CHAPTER IVFactors Contributing to Water-Column Light Attenuation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35(Gallegos and Moore)

Water-Column Light Attenuation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35Partitioning Sources of Water-Column Light Attenuation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36Diagnostic Tool Coefficients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Water Alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37Dissolved Organic Carbon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37Phytoplankton Chlorophyll . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Total Suspended Solids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Evaluation of the Kd Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43Components of Total Suspended Solids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45Summary of the Diagnostic Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47Application of the Diagnostic Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Suspended Solids Dominant Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47Phytoplankton Bloom Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47Light-limited Phytoplankton Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49Generation of Management Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Sensitivity of Target Concentrations to Parameter Variations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Directions for Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

CHAPTER VEpiphyte Contributions to Light Attenuation at the Leaf Surface . . . . . . . . . . . . . . . . . . . . . . . . 55(Kemp, Bartleson, and Murray)

Approach and Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55Model Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Computing Epiphytic Algal Biomass (Be) from Nutrient Concentration . . . . . . . . . . . . . . . . . . . . . . . 56Epiphyte Biomass-Specific PAR Attenuation Coefficient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61Estimating the Ratio of Epiphyte Biomass to Total Dry Weight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Sensitivity Analysis of the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

CHAPTER VIBeyond Light: Physical, Geological and Chemical Habitat Requirements . . . . . . . . . . . . . . . . . . 71(Koch, Ailstock, and Stevenson)

Feedback Between SAV and the Physical, Geological and Chemical Environments . . . . . . . . . . . . . . . . . . 71SAV and Current Velocity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Positive Effects of Reduced Current Velocity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73Negative Effects of Reduced Current Velocity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74Epiphytes and Current Velocity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74Current Velocity SAV Habitat Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

SAV and Waves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75Effects of High Wave Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77Wave Mixing Depth Effects on SAV Minimum Depth Distributions . . . . . . . . . . . . . . . . . . . . . . . . . 79Wave Exposure Habitat Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

SAV and Turbulence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81SAV and Tides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

Minimum Depth of Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81Maximum and Vertical Distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

xx SAV TECHNICAL SYNTHESIS II

SAV and the Sediments It Colonizes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85Grain Size Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86Sediment Organic Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

SAV and Sediment Geochemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Nutrients in Sediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Microbial-Based Phytotoxins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90

Chemical Contaminants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92Physical and Geological SAV Habitat Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

CHAPTER VIISetting, Applying and Evaluating Minimum Light Requirements for Chesapeake Bay SAV . . . . 95(Bergstrom)

Defining and Applying the Minimum Light Requirements and Water-Column Light Requirements . . . . . . 95Water-Column Light Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96Minimum Light Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96Primary and Secondary Habitat Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99Calculating Percent Light Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99Adjusting Percent Light Parameters for Tidal Range and Different Restoration Depths . . . . . . . . . . . 101Recommendations for Applying Percent Light Variables and Other Habitat Requirements . . . . . . . . . 102

Evaluating Minimum Light Requirements Using Chesapeake Bay Water Quality Monitoring Data and SAV Survey Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

Comparing Water Quality Medians Over Categories of SAV Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

Identifying Segments with Persistent Failure of the Minimum Light Requirements and Checking them for SAV Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

Comparing Different SAV Habitat Requirements as Predictors of SAV Area . . . . . . . . . . . . . . . . . . . . . . . 111Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

Correlating SAV Depth With Median Water Quality for Habitat Requirement Parameters . . . . . . . . . . . . . 116Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119

CHAPTER VIIIChesapeake Bay SAV Distribution Restoration Goals and Targets . . . . . . . . . . . . . . . . . . . . . . . 121(Batiuk and Wilcox)

Distribution Targets Development Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121Tiered SAV Distribution Restoration Goals and Targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122

Contents xxi

CHAPTER IXComparing Nearshore and Midchannel Water Quality Conditions . . . . . . . . . . . . . . . . . . . . . . . . 131(Karrh)

Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132Station Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132Statistical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133

Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133Tributary Comparisons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137Attainment of Habitat Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145

Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156

CHAPTER XFuture Needs for Continued Management Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159(Moore, Kemp, Carter, Gallegos)

Minimum Light Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159Water-Column Contribution to Attenuation of Light . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159Epiphyte Contribution to Light Attenuation at the Leaf Surface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159Physical, Geological, and Chemical Habitat Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160SAV Distribution Restoration Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161

APPENDICES

Appendix A. Light Requirements for Chesapeake Bay and other SAV Species . . . . . . . . . . . . . . . . . . . . . . . . . . 175

Appendix B. The Role of Chemical Contaminants as Stress Factors Affecting SAV . . . . . . . . . . . . . . . . . . . . . 189

Appendix C. SAS Code Used to Calculate PLL from Kd, TSS, DIN, and DIP . . . . . . . . . . . . . . . . . . . . . . . . . . 195

Appendix D. SAV Depth, Area, and Water Quality Data Used and Details of Statistical Analysis Performed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197

Appendix E. Spearman Rank Correlations between Chesapeake Bay Water QualityMonitoring Program Data and Measures of SAV Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205

xxii SAV TECHNICAL SYNTHESIS II

Underwater grasses, or submerged aquatic vegeta-tion (SAV), represent a conspicuous and impor-tant component of shallow estuarine and coastal envi-ronments worldwide, because SAV species are key-stone species in these ecosystems. Their many rolesinclude providing habitat for juvenile and adult fishand shellfish and protecting them from predators;providing food for waterfowl, fish and mammals;absorbing wave energy and nutrients and producingoxygen; improving water clarity and settling out sedi-ment suspended in the water; and stabilizing bottomsediments. The rich estuarine habitats created by SAVsupport growth of diverse populations of living estu-arine and marine resources.

Health and survival of these plant communities inChesapeake Bay and other coastal waters depend onmaintaining environmental conditions that effectivelydefine the suitable habitat for SAV growth. SAVestablishment and continued growth depends princi-pally on light availability but also on several other fac-tors, including the availability of propagules; suitablewater quality, salinity, temperature, water depth andtidal range; suitable sediment quality, wave action andcurrent velocity; and low enough levels of physical dis-turbance and toxic substances.

Suitable SAV habitats were characterized previouslyfor Chesapeake Bay and its tidal tributaries by relat-ing observations of SAV presence or absence to meas-urements of five water quality variables (Batiuk et al.1992, Dennison et al. 1993). This comparative tech-nique was used to define critical levels for dissolvedinorganic nitrogen and phosphorus, water columnlight attenuation coefficient, chlorophyll a and total

suspended solids. Growing season median values ofthese water quality parameters were compared at sitesclassified according to the degree of SAV growthnearby. Habitat requirements for each parameterwere chosen that were near the highest (worst)median values found at sites that had SAV growth ineach of four salinity regimes. Where growing seasonmedian water quality values were lower (better) thanthese medians, the habitat requirements were metand SAV growth should be possible (although SAVcould still be absent from a site with good water qual-ity due to lack of propagules, high wave energy orother causes).

While these five water quality variables relate to manyaspects of SAV physiology, their influence on theplant’s light climate appears to be of primary impor-tance in determining whether SAV can grow at a site.Attainment of these SAV habitat requirements wasused to predict SAV presence or absence at specificsites in Chesapeake Bay and its tidal tributaries(Batiuk et al. 1992, Dennison et al. 1993) . These pre-dictions were accurate in a majority of cases but sev-eral problems remained, especially that of decidinghow many of the four or five requirements had to bemet to permit SAV growth; how to account for the pri-macy of the light requirements; and how to explainwhy some areas had SAV but consistently failed manyof the SAV habitat requirements.

In the 10 years since work was first initiated on thefirst SAV technical synthesis, there have beenrenewed investments in more focused research,expanded monitoring and ecosystem modeling,prompted, in part, by gaps in understanding that were

Chapter I – Introduction 1

CHAPTER II

Introduction

brought to light after synthesizing the vast quantitiesof information available through the late 1980s.Prompted by the accumulation of these new data andby insights and advances in ecosystem processes mod-eling, and driven by management needs for the nextgeneration of habitat requirements, a team of scien-tists and managers assembled to produce this secondtechnical synthesis.

TECHNICAL SYNTHESIS OBJECTIVES, CONTENT AND STRUCTURE

Synthesis Objectives

The SAV Technical Synthesis II has seven majorobjectives:

1. to establish scientifically defensible minimumlight requirements for Chesapeake Bay SAVspecies;

2. to develop a set of models for determining lightavailability through the water column and at theleaf surface under a variety of water qualityconditions and at varying restoration depths;

3. to provide the management and scientific com-munities with a set of diagnostic tools necessaryto better interpret not only the relative degreeof achievement of the light requirements, butalso to understand the relative contributions ofdifferent water quality parameters to overalllight attenuation;

4. to recognize and quantify the many other physi-cal, geochemical and chemical habitat require-ments, pointing out the need for furtherresearch where the data necessary to developspecific requirements are lacking;

5. to document refinements to the ChesapeakeBay Program’s tiered distribution restorationgoals and targets;

6. to provide an in-depth assessment of the appli-cability of midchannel monitoring data for eval-uating the water quality in adjacent shallow-water habitats; and

7. to produce a concise list of research needsrequired to improve our ability to define a holis-tic picture of habitat quality suitability for SAV.

Synthesis Content and Structure

Interactions among SAV, water quality and physicalhabitat, which are quantified in the rest of the techni-cal synthesis, are laid out within their respective con-texts (Chapter II). Water column-based light require-ments for SAV survival and growth are determinedthrough an extensive review of the literature and anevaluation of experimental results from research andmonitoring conducted in Chesapeake Bay (ChapterIII). The scientific basis for developing diagnostictools for defining water quality necessary to meetwater-column conditions supporting restoration andprotection of SAV are documented. This is followedby an illustration of the management applications ofthe diagnostic tools (Chapter IV). A model isdescribed for calculating light at the leaf surface ofplants at given restoration depths under specific waterquality conditions (Chapter V). Physical, geologicaland chemical factors affecting the suitability of a sitefor SAV survival and growth are discussed with spe-cific quantitative requirements established where sup-ported by scientific data (Chapter VI). Two types ofSAV light requirements are defined, along with expla-nations of how to test their attainment (using two newpercent-light parameters calculated from water qual-ity data) and how to account for tidal range. The rela-tionships are tested among the percent-light parame-ters, SAV area and the average depth at which SAV isgrowing in Chesapeake Bay (Chapter VII). Refine-ments to and expansions of the original tiered restora-tion goals and targets are then documented (ChapterVIII). An expanded, in-depth analysis of midchanneland nearshore water quality measurements is laid out,along with recommendations for site-specific applica-tion of midchannel data in characterizing nearshorehabitats (Chapter IX). Drawn from the precedingchapters, the technical synthesis concludes with adetailed list of follow-up monitoring and researchneeded to provide the basis for further quantificationof a more expanded set of SAV habitat requirements(Chapter X). The appendices include copies of moreextensive tables and methodological documentationreferred to within the technical synthesis.

2 SAV TECHNICAL SYNTHESIS II

The loss of SAV beds since the early 1960s (Orth andMoore 1983, Kemp et al. 1983), primarily becauseof eutrophication and associated reductions in lightavailability (e.g., Twilley et al. 1985), is of particularconcern because these plants create rich animal habi-tats that support the growth of diverse fish and inver-tebrate populations (Lubbers et al. 1990). They alsosignificantly influence bio-geochemical (e.g., Caffreyand Kemp 1990) and sedimentological (e.g, Ward et al.1984) processes in the estuary. Similar declines in SAVhave been occurring worldwide with increasing fre-quency during the last several decades (e.g., Short andWyllie-Echeverria 1996), and many of these have beenattributed to excessive nutrient enrichment andincreases in turbidity (e.g., Cambridge and McComb1984, Borum 1985, McGlathery 1995, Tomasko et al.1996).

Although the 1992 SAV habitat requirements haveproved useful in factoring SAV restoration into nutri-ent reduction goal-setting for Chesapeake Bay(Chesapeake Executive Council 1993, 1997), a numberof serious limitations have been noted in attempting toapply this approach. First, it was unclear how many ofthe five habitat requirements needed to be met for aparticular site to be suitable for maintaining the healthof existing SAV beds or for revegetation of denudedsites. Many examples, particularly in the tidal freshand oligohaline regions of the estuary, have beenencountered in which water quality at sites withhealthy SAV beds met only three or four of the habitatrequirements (Table II-1). On the other hand, in other

sites, no SAV was present, despite the fact that most ofthe habitat requirements were met. An obvious taskwas to determine which of these variables were mostimportant and how they interacted to define SAVgrowth requirements. In addition, it was difficult to seehow these habitat requirements, as established in theoriginal SAV technical synthesis (Batiuk et al. 1992),would be used to accommodate different depth targetsfor SAV restoration (e.g., 1 meter for Tier II restora-tion versus 2 meters for Tier III restoration).

Even though light requirements were suggested to beof primary importance for defining SAV habitats withthis approach (Dennison et al. 1993), explicit relation-ships between these water quality variables and lightavailability were, in general, poorly defined (Batiuk etal. 1992). The one exception is that light attenuation inthe water column can be calculated directly from theexponential coefficient, Kd. In the first SAV technicalsynthesis, values for Kd, chlorophyll a and total sus-pended solids were set as separate components of thewater quality conditions defining SAV habitats,despite the fact that the three variables are highlyinterdependent (e.g., Gallegos 1994). Finally, there isan implied relationship between SAV habitat require-ments for the dissolved inorganic nitrogen and phos-phorus concentrations and light attenuation attributa-ble to epiphytic materials on plant leaf surfaces, butthis relationship was not explained. In fact, althoughepiphyte growth and associated light attenuation havebeen clearly related to estuarine nutrient levels (e.g.,Borum 1985, Twilley et al. 1985), we are aware of no

Chapter II – SAV, Water Quality and Physical Habitat Relationships 3

CHAPTER IIII

SAV, Water Quality andPhysical Habitat Relationships


TABLE II-1. Comparison of SAV Habitat Requirements with median levels of water quality variablesamong SAV growth categories within salinity regimes in Chesapeake Bay.

* SAV were usually present, even though the habitat requirements were not met (horizontal line is assumed to separate vegetated from unvegetated sites). Note that there are 11 of 50 cases in this category (= 22%disagreement); all of these were in tidal fresh and oligohaline regimes. Dissolved inorganic nitrogen medianswere not counted where there was no habitat requirement.** SAV were usually not present, even though the habitat requirements were met (horizontal line is assumedto separate vegetated from unvegetated sites). Note that there are 7 of 31 cases in this category (= 23%disagreement); there were some in each salinity regime. There are many reasons other than water quality why SAV might be absent, however, including physical conditions and lack of propagules.

quantitative descriptions of such relationships basedon field or experimental data. Such relationships canbe derived, however, from numerical simulation mod-els, which have successfully described dynamic interac-tions among nutrients, epiphytic algae, light fields andSAV growth (e.g., Fong and Harwell 1994, Kemp et al.1995, Madden and Kemp 1996, Buzzelli et al. 1998).

This report synthesizes new information into a revisedapproach for establishing SAV habitat requirementsfor Chesapeake Bay and its tidal tributaries. At theoutset, we decided that this revision should focus onhow water quality conditions interact to control lightavailable for supporting SAV growth. An additionaleight years of monitoring SAV presence and waterquality variables at sites throughout the Bay provideda rich data base for further relating SAV occurrence tohabitat conditions beyond the original 1992 habitatrequirements (Batiuk et al. 1992). We used a combina-tion of model simulations and statistical analyses todevelop an algorithm that explicitly relates nutrientconcentrations and turbidity with epiphyte attenuationof light. The revised approach also develops empiricalfunctions derived from monitoring data to partitionthe total water-column light attenuation coefficient(Kd) into contributions from phytoplankton biomass,inorganic suspended solids and colored dissolvedorganic matter. This new approach requires establish-ing a set of target values of “minimum light require-ments” for SAV survival. These are derived from anextensive review of the scientific literature, applicationof these algorithms to calculate available light underwater quality conditions corresponding to the originalSAV habitat requirements, and from an evaluation offindings of field water quality conditions along gradi-ents of SAV growth.

The principal relationships between water quality con-ditions and the light regime for the growth of sub-mersed plants are illustrated in a conceptual diagram(Figure II-1), which represents an expansion from asimilar conceptualization presented in the first SAVtechnical synthesis (Figure 1, Batiuk et al. 1992).Incident light, which is partially reflected at the watersurface, is attenuated through the water column over-lying submersed plants by particulate material (phyto-plankton chlorophyll a and total suspended solids), bydissolved organic matter and by water itself. In mostestuarine environments, water-column attenuation,which is characterized by the composite light attenua-

tion coefficient, Kd, is dominated by contributionsfrom chlorophyll a and total suspended solids.

Light is also attenuated by epiphytic material (i.e.,algae, bacteria, detritus and sediment) accumulatingon SAV leaves. This epiphytic light attenuation is char-acterized by the coefficient Ke, which increases in lin-ear proportion with increases in the mass of epiphyticmaterial, where the slope of this relationship dependson the composition (e.g, chlorophyll a/dry weight) ofthe epiphytic material. Dissolved inorganic nutrientsin the water column stimulate the growth of both phy-toplanktonic and epiphytic algae, and suspendedsolids can settle onto SAV leaves to become part of theepiphytic matrix. Thus, the percent of surface lightreaching SAV leaves depends on water depth and onthe five water quality variables—dissolved inorganicnitrogen, dissolved inorganic phosphorus, chlorophylla, total suspended solids and water-column light atten-uation coefficient—that define the original SAV habi-tat requirements (Batiuk et al. 1992). Because epiphyt-ic algae also require light to grow, water depth and Kdconstrain its accumulation on SAV leaves, and lightattenuation by epiphytic material (Ke) depends on themass of both algae and total suspended solids settlingon the leaves.

This approach to defining SAV habitat requirements,therefore, explicitly considers water-column depth.Thus, for any site, the minimum water quality condi-tions needed for SAV growth and survival will tend tovary with depth. Chesapeake Bay and many of its tidaltributaries are characterized by broad shoals flankinga relatively narrow channel, such that relatively largeincreases in bottom area will accompany small changesin depth-range between 0 to 8 meters (Kemp et al.1999). As a consequence of the estuary’s bottom mor-phology, the doubling of SAV depth penetration fromthe Tier II (1 meter) to the Tier III (2 meters) distri-bution restoration targets results in more than a 33percent increase in potential bottom area of SAV cov-erage (see Table VIII-1, from 408,689 to 618,773acres). As of the 1998 aerial survey, however, actualSAV coverage represented only 10 percent and 16 per-cent of the Tier III and Tier II targets, respectively.

In this report we have used mean tidal level—themean depth over all tidal cycles during the year—asthe reference point from which mean water-columndepth is measured. Chesapeake Bay tidal amplitudes



LightTransmission

LightAttenuation

Reflection


TotalSuspended

Solids

DIN

DIP Epiphytes

Grazers

SAV

• Water

• Particles

• Color

• Algae

• Detritus

PLW (% Light through Water)

PLL (% Light at the Leaf)

WaterColumn

(Kd)

Epiphyte(Ke)

FIGURE II-1. Conceptual Model of Light/Nutrient Effects on SAV Habitat. Availability of light for SAV is influenced by water column and at the leaf surface light attenuation processes.DIN = dissolved inorganic nitrogen and DIP = dissolved inorganic nitrogen.

vary considerably from approximately 90 cm at themainstem Bay mouth to 25 cm on the western side ofthe upper mesohaline region; tidal ranges on the east-ern shoals of the Bay tend to be higher by 10 cm to 15cm than those on the western side, and ranges are gen-erally 40 cm to 50 cm higher in the tidal fresh regionsof tributaries than at their mouths (Hicks 1964). SAVis generally excluded from intertidal areas because ofphysical stress (waves, desiccation and freezing), andthe upper depth-limit for SAV distribution, therefore,tends to be lower in areas with higher tidal range.Furthermore, the deeper depth limit tends to bereduced at sites with greater tidal range because ofincreased light attenuation through the longer averagewater column (Koch and Beer 1996). Thus, theretends to be an inverse relationship between tidal rangeand the range of SAV depth distribution.

In general, there is a strong positive relationshipbetween water clarity and the maximum water-columndepth to which plants grow for virtually all SAVspecies in both freshwater and marine environments(e.g., Dennison et al. 1993). Numerous statistical mod-els have been reported describing relationshipsbetween Kd (or Secchi depth) and maximum SAV col-onization depth. Virtually all of these models are sim-ilar in shape and trajectory, and two representativeexamples are given for freshwater plants (Chambersand Kalff 1985) and seagrasses (Duarte 1991) (FigureII-2, upper panel). There is a suggestion here thatfreshwater plants tend to survive better than sea-grasses in relatively turbid waters (Kd

-1 < 2 meters),whereas seagrasses grow deeper in clear waters (Kd

-1

> 3 meters). Realistically, however, the two relation-ships are quite similar, and the percent of surface lightreaching the sediments at the maximum SAVcolonization depth (Zmax) can be calculated (= exp (- Kd Zmax)) to range from approximately 10percent to 30 percent for both habitats. Assuming thatlight limits the water depth penetration for SAV inmost instances, this calculation represents an estimateof the minimum light (as a percent of surface light)required for SAV survival. Results from various shad-ing experiments with different SAV species (primarilywith seagrasses) suggest a similar range of minimumlight values (10 percent to 35 percent of surface irradi-ance) at which plants can survive (see Chapter III).These estimates of SAV light requirements, however,don’t consider the shading effects of epiphytesaddressed in detail in Chapter V.


Maximum Plant Colonization Depthversus Water Transparency

Light at Plant Depth Limitversus Light Attenuation

Freshwater PlantsZc = [1.71-1.33 (log Kd)]2

PAR

at M

axim

um D

epth

(I z

c/I o

), %

Max

imum

SA

V C

olon

izat

ion

Dep

th (

Zc)

Transparency (1/Kd), m

Light Attenuation Coefficient (Kd), m-1

Marine PlantsZc = 1.82-1.07 (Kd)

Meadow-Forming Plants

Canopy-FormingPlants

8

6

4

2

0

40

30

20

10

0

0 1 2 3 4

0 1 2

FIGURE II-2. Maximum Plant Colonization Depth.Illustrations of the relationships between water trans-parency and light attenuation, and maximum depth ofSAV growth from fresh water versus marine plants(upper panel) and meadow-forming versus canopy-forming plants (lower panel), respectively.

Whereas seagrasses tend to be meadow-formingspecies with blade-shaped leaves that grow from theirbase, most freshwater plants are canopy-formers, withleaves growing out from the tips of stems. Under low-light conditions, these canopy-forming species oftenexhibit rapid vertical growth by stem-elongation andretain only their uppermost leaves near the water sur-face (e.g., Goldsborough and Kemp 1988). Canopy-formation and stem-elongation are two shade-adaptation mechanisms that allow these species,which dominate the tidal fresh and oligohaline regionsof the Bay, to survive considerably better thanmeadow-forming seagrasses in turbid shallow environ-ments (Middleboe and Markager 1997) (Figure II-2lower panel).

This report defines SAV habitat requirements in termsof light availability to support plant photosynthesis,growth and survival. Other physical, geological andchemical factors may, however, preclude SAV fromparticular sites even when light requirements are met.These effects on SAV are illustrated (Figure II-3) as an overlay on the previous conceptualization (FigureII-1), depicting interactions between water qualityvariables and SAV light requirements. Some of theseeffects operate directly on SAV, while others involveinhibition of SAV-light interactions. Waves and tidesalter the light climate by changing the water-column

height over which light is attenuated and by increasingtotal suspended solids and associated light attenuationby resuspending bottom sediments. Particle sinkingand other sedimentological processes alter texture,grain-size distribution and organic content of bottomsediments, which can affect SAV growth by modifyingavailability of porewater nutrients (Barko and Smart1986) and by producing reduced sulfur compoundsthat are phytotoxic (Carlson et al. 1994). In addition,there are diverse pesticides and other anthropogeniccontaminants that tend to inhibit SAV growth.

This revised approach for assessing SAV habitatrequirements is completely consistent with theChesapeake Bay Water Quality Model, as the samemodel structures were used for both calculations. Thus,the Chesapeake Bay Water Quality Model can be usedto predict how SAV habitat conditions respond to sce-narios for reducing nutrient and sediment loads to theBay, while the revised SAV habitat assessmentapproach uses monitoring data to define in quantita-tive terms recent trends and changes in the suitabilitythe of sites for supporting SAV growth. Although werecognize that factors other than light (including waves,tidal currents, sediments and toxic chemicals) also limitSAV distribution in both pristine and perturbed coastalhabitats, we have not yet devised a scheme to explicitlyand quantitatively account for them.



Light Transmission

Waves Tides



DIN

DIP Epiphytes

Grazers

Organic matter Sulfide

N

P

Contaminants

Biogeo-chemicalprocesses

Settlingof

OrganicMatter

SAV

PLL

PLW

Currents

FIGURE II-3. Interaction between Light-Based, Physical, Geological and Chemical SAV HabitatRequirements. Interaction between previously established SAV habitat requirements, suchas light attenuation, dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus(DIP), chlorophyll a, total suspended solids (TSS) and other physical/chemical parametersdiscussed in this chapter (waves, currents, tides, sediment organic matter, biogeochemicalprocesses. P = phosphorus; N = nitrogen; PLW = percent light through water; PLL =percent light at the leaf.

Chapter III – Light Requirements for SAV Survival and Growth 11

CHAPTER IIIIII

Light Requirements for SAV Survival and Growth

This chapter addresses the identification of lightrequirements for SAV survival and growth asdetermined by an extensive search of the pertinent lit-erature and examination of experimental results fromresearch and monitoring conducted in ChesapeakeBay. As part of the revision and update of Batiuk et al.(1992), emphasis was placed on refining the lightrequirements, as it is widely recognized that growth,spatial distribution and survival of SAV is ultimatelylimited by the availability of light to support photosyn-thesis (Dennison 1987; Duarte 1991a; Middleboe andMarkager 1997). Based on available information fromfour localities in the Bay, Batiuk et al. (1992) set habi-tat requirements for Chesapeake Bay SAV. Lightrequirements for the various salinity zones of Chesa-peake Bay were expressed as light attenuation coeffi-cients (Kd), based primarily on observed Kd maxima orSecchi depth minima at sites with SAV. These lightrequirements were intended to promote potentialrecovery of SAV to a depth of 1 meter; that is, plantswould be able to colonize all suitable habitats 1 meterin depth.

This chapter also provides a systematic review of theliterature on light requirements for SAV, consideringthe relative utility of information derived from a rangeof different approaches. Where possible, the informa-tion is interpreted in terms of possible differences inlight requirements for species and growth forms occur-ring in the four major salinity zones of ChesapeakeBay. The chapter is divided into three sections: adiscussion and evaluation of the literature; factorsaffecting determination of light requirements forChesapeake Bay and research and monitoring results

from the Patuxent and Potomac rivers; and the water-column light requirements for Chesapeake Bay SAV.

DISCUSSION OF LITERATURE VALUES

Information found in an extensive literature searchand review of the light requirements for SAV falls intofour general categories: (1) physiological studies ofphotosynthesis/irradiance relationships; (2) results offield observations of the maximum depth of SAV colo-nization and available light at that depth; (3) experi-ments involving the artificial or natural manipulationof light levels during long- or short-term growth stud-ies; and (4) statistical models intended to generalizelight requirements. These four categories are dis-cussed in the order of their perceived utility for thepurpose of determining light requirements, with mod-els and shading experiments being the most useful.The literature reviewed in this chapter includes lakeand estuary studies throughout the world.

Photosynthesis-Irradiance Measurements

Numerous studies have presented photosynthesis-irradiance (PI) curves for SAV. Photosynthesis-irradiance curves are generated by exposing wholeplants, leaves, or leaf or stem sections to varying lightintensities and measuring the photosynthesis ratebased on generation of oxygen or consumption of car-bon dioxide (CO2). Most PI measurements are madein the laboratory, although some studies use ambientlight and environmental conditions with plants suspended in bottles at different water depths. Photosynthesis-irradiance curves generally provide

information on: (1) species light compensation point(Ic), where respiration balances photosynthesis; (2)light saturation (Ik), or the minimum irradiance atwhich photosynthesis rates are at a maximum; (3) max-imum photosynthesis rate (Pmax); and (4) the half-sat-uration constant Km, which is the irradiance at whichone-half the maximum photosynthesis rate (½ Pmax) isachieved. Such PI data provide the basis for determin-ing the effects of temperature, CO2 concentration, pH,light conditions during growth of the plant, tissue age, etc., on photosynthesis and its relationship toirradiance. They may also be useful for comparingspecies if experiments are conducted under similarconditions and/or if plant material comes from thesame environment.

These studies show that variables such as light adapta-tion, water temperature, species, pH, tissue age, CO2concentration and nutritional status can all affect ratesof photosynthesis and respiration as well as Ic and Ik,making generalizations difficult. Table A-1 in Appen-dix A is a compilation of literature values for PI stud-ies of freshwater-oligohaline species, most of whichare found in Chesapeake Bay and its tidal tributaries.1

Table A-2 in Appendix A is a summary of literaturevalues from PI studies of mesohaline-polyhalinespecies, with Zostera marina and Ruppia maritimabeing the two species found in Chesapeake Bay and itstidal tributaries. Table III-1 is a summary of the mate-rial contained in Appendix A, tables A-1 and A-2, byspecies.

Photosynthesis-irradiance measurements show thatSAV photosynthesis is almost always saturated (Ik) atirradiances from 45-700 µmol m-2 s-1. This represents2.3 to 35 percent of full sunlight (assuming a full sun-light value of 2000 µmol m-2 s-1) and indicates thatSAV species are adapted to low light regimes ratherthan surface irradiance. Light compensation points fornet photosynthesis (Ic ) are very low, generally below50 µmol m-2 s-1 (2.5 percent surface light). Light com-pensation points for overall growth would be higherthan those for net photosynthesis, as they wouldinclude respiration by above- and below-groundbiomass. The half-saturation irradiance Km rangesfrom 20-365 µmol m2 s-1 and lies between Ic and Ik foreach species.

In considering the utility of PI curves for determiningminimum light requirements for restoration of Chesa-peake Bay SAV, the following was observed fromreviews of the PI values reported in the literature andsummarized in Table III-1 and documented in Appen-dix A, tables A-1 and A-2.

1. Ik depends on temperature and is, therefore,generally lower when temperature is lower(Harley and Findlay 1994; Fair and Meeke 1983;Madsen and Adams 1989; Orr 1988; Marsh et al.1986; Penhale 1977; McRoy 1974; Evans et al.1986; Wetzel and Penhale 1983).

2. Ic generally underestimates the amount of lightnecessary for growth or survival because it doesnot take into account the whole plant, includingunderground biomass. Photosynthesis-irradi-ance measurements from leaf incubations of Z.marina tend to be lower than those for in situincubations or whole plants. However, compar-isons are difficult because of the variety of exper-imental temperatures used and the possibilitythat whole plants include epiphytes. Likewise, Ikdiffers according to the experimental conditions.For example, Drew (1979) found Z. marina leafsections to have an Ik of 208 µmol m-2 s-1 at 15°C,whereas Zimmerman et al. (1991) measured Ik at35 ±17 µmol m-2 s-1 at the same temperature.Wetzel and Penhale (1983) found whole plantsof Z. marina at 17.5°C to have an Ik of 312 µmol -2 s-1 and at 10°C, an Ik of 231 µmol m-2 s-1.Furthermore, Ic and Ik measured in the field maybe much higher than Ic and Ik measured in thelaboratory (Dunton and Tomasko 1994).

3. Ik and Ic vary with in situ light intensity gradients,previous daily light history, plant species and leafand tissue age (Mazzella and Alberte 1986;Goldsborough and Kemp 1988; Bowes et al.1977a; Titus and Adams 1979; Madsen et al.1991; Goodman et al. 1995).

Although there are estimates of Ik or Ic for mostChesapeake Bay species, the estimates are so variabledepending on experimental conditions, and so fewhave actually been done in the Chesapeake Bayregion, that most studies are not directly applicable for


¹Freshwater or tidal fresh refers to aquatic habitats with salinities ranging from zero to 5 to 18 ppt; and polyhaline, to salinities >18 ppt.


TABLE III-1. Summary of photosynthesis-irradiance measurements for freshwater, oligohaline, mesohaline and polyhaline SAV species.

Species Ik Km Ic References(µmol m2 s-1) (µmol m2 s-1) (µmol m2 s-1)

(Ic = compensation point; Ik = irradiance at saturation; Km = 1/2 saturation constant or 1/2 Pmax)continued


TABLE III-1. Summary of photosynthesis-irradiance measurements for freshwater, oligohaline, mesohaline and polyhaline SAV species (continued).

Species Ik Km Ic References(µmol m2 s-1) (µmol m2 s-1) (µmol m2 s-1)

1. Corrected for respiration

(Ic = compensation point; Ik = irradiance at saturation; Km = 1/2 saturation constant or 1/2 Pmax)

setting light requirements for survival and growth of Chesapeake Bay SAV. As suggested by Zimmermanet al. (1989), it is questionable to use short-termphotosynthesis-light experiments to estimate light-growth relationships and depth penetration, particu-larly when plants are not pre-acclimated to experi-mental conditions. In addition to the balance betweenphotosynthesis and respiration, estimates of light re-quirements must consider other losses of plant organiccarbon through herbivory, leaf sloughing and frag-mentation as well as reproductive requirements. Thatbeing said, consider the two studies done in theChesapeake Bay region (Wetzel and Penhale 1983;Goldsborough and Kemp 1988). The Ic required for the polyhaline species Z. marina was as high as 417µmol m2 s-1 (or about 30 percent, assuming 2000 µmolm2 s-1 light at the surface). For the oligohaline species,P. perfoliatus, Ic of 25-60 µmol m2 s-1 (3 percent) wasmeasured in an incubator.

Field Observations of Maximum Depth and Available Light

There have been numerous studies around the worldin which observations of the maximum depth to whicha species grows (Zmax) have been linked to the avail-able light (Im) at that depth (tables A-3 and A-4 inAppendix A). Determinations of available light areusually made once at midday on a clear day, generallyin midsummer, with the available light expressed asthe percent of surface or subsurface illumination.These studies are summarized in Table III-2. Some ofthese studies discuss the problems inherent in deter-mining the percent of surface light needed to restoreSAV under various management scenarios.

Individual maximum depth of colonization studieswere not particularly useful for setting up minimumlight requirements for Chesapeake Bay environments.Most studies were of freshwater and oligohalinespecies in freshwater lakes, where water was exceed-ingly clear and the percent of surface light in the mid-dle of the summer on a good day was not reallyindicative of the seasonal light environment of theplant. All determinations were of the maximum depthat which the plants were rooted, disregarding whetherchance fragments or propagules might have estab-lished outlier populations that might not survive awhole growing season (e.g., Moore 1996). Measure-ment frequency is a major problem that needs to be

considered with these studies. However, taken in theaggregate, they serve as a basis for models that predictmaximum depths of colonization or minimum lightrequirements (see “Light Availability Models”).

With the exception of Sheldon and Boylen (1977),most references in Table III-2 suggested that at thegreatest depth where freshwater and oligohalinespecies were found growing, light was 10 percent ofsurface light. Sheldon and Boylen (1977) were workingin Lake George where the water clarity was excel-lent—Secchi depths were 6 to 7 meters. This implies aKd of about 0.19 and a conversion constant of 1.15 to1.34. They estimated about 10 percent light at 12meters, the deepest depth at which the plants werefound. Compared to the freshwater and oligohalinespecies, the mesohaline-polyhaline species Z. marinarequired 4.1 to 35.7 percent light at maximum depth;no field observation studies of R. maritima were foundreported in the literature.

Light Manipulation Experiments

Light requirements for growth and survival of SAVhave been investigated directly using short- to long-term studies under experimentally manipulated lightconditions (Table III-3). These studies were done insitu, in mesocosms where plants receive a measuredpercentage of ambient light, or in the laboratory whereplants are grown under constant light and temperatureregimes. Most field studies were done with polyhalineand mesohaline species. In the case of prolonged fieldexperiments, recovery of the plants was sometimesmonitored. Some studies did not involve actual manip-ulation of light levels; e.g., Dunton (1994) involvednatural shading by an algal bloom and continuousmonitoring of light in Texas coastal bays, whereas Kim-ber et al. (1995) and Agami et al. (1984) suspendedplants in buckets at specific depths and observed sur-vival. Some studies were included in Table III-3 to pro-vide examples of the various types of experiments, butwere not sufficiently robust to be considered directlyrelevant to determining light requirements for Chesa-peake Bay SAV.

Laboratory and mesocosm experiments under highlycontrolled light, temperature and flow conditions maysubstantially underestimate natural light requirementsbecause of the absence of natural light variability, her-bivory, fragmentation losses and tidal or riverine cur-rents. For example, laboratory shading experiments



TABLE III-2. Summary of percent light at maximum depth of growth for freshwater, oligohaline,mesohaline and polyhaline SAV species from field observations1. “Other” refers to species not found in Chesapeake Bay.

Chapter III – Light R

equirements for S

AV

Survival and G

rowth

17

TABLE III-3. Results of SAV light manipulation experiments.

continued

18S

AV

TEC

HN

ICA

LS

YN

THE

SIS

II

TABLE III-3. Results of SAV light manipulation experiments (continued).

continued

Chapter III – Light R

equirements for S

AV

Survival and G

rowth

19

TABLE III-3. Results of SAV light manipulation experiments (continued).

with the freshwater species Hydrilla verticillata and Val-lisneria americana (Carter and Rybicki, unpublisheddata, not included in Table III-3) showed that survivalfor several months was possible under very low lightconditions (12 µmol m-2 s-1)(< one percent of full sun-light 2000 µmol —2 s-1), however, tuber formation wasseverely affected. In this same experiment, survivaland tuber production was good at a light level of only45 µmol m-2 s-1 (2.3 percent of full sunlight). However,these experiments involved a simulation of growingseason photoperiod, rather than the continuously fluc-tuating daily light environment of the field. Many lab-oratory/mesocosm studies are of relatively shortduration (e.g., Goldsborough and Kemp 1988; Sand-Jensen and Madsen 1991). Agami et al. (1984) did notmeasure or estimate percent light, but merely sug-gested minimum light for survival or reproduction.

Long periods of dense shading were sufficient toreduce standing crop and below-ground biomass of allspecies to almost zero. For the mesohaline to polyha-line species, including R. maritima, without regard toexperimental conditions, the critical percent lightranged from 9 percent to 37 percent, or a mean of 17.9 percent ±2.97 standard error (SE). For Z. marinaand R. maritima (Chesapeake Bay species), the meanwas 24 percent ±5.55 SE. In the case of the freshwa-ter-oligohaline species, V. americana was able to pro-duce replacement tubers at 9 percent light (94-daygrowing season) while Potamogeton pectinatus wasseverely impacted when exposed to only 27 percentlight (Kimber et al. 1995). Pond experiments with V. americana by Kimber et al. (1995) showed thatplants held under 9 percent shading for 94 days underambient light conditions produced replacement-weight tubers (tubers sufficient to replace the popula-tion the following year), however, if the growingseason was increased to 109 days, plants producedreplacement weight tubers at 5 percent light.

Unfortunately, shading experiments do not provideprecise numbers useful for developing light require-ments for Chesapeake Bay SAV. If plants die at 10 per-cent surface light and survive at 20 percent surfacelight, the actual threshold lies between 10 and 20 per-cent. Means of light manipulation experiments doneunder markedly different experimental conditions arenot sufficiently accurate to provide guidance forsetting light requirements. Reasons for lac

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