Project Title: Modeling the effects of changes in turbidity on light available for submerged aquatic vegetation

Project Coordinator:

Roger I. E. Newell
Professor, Horn Point Laboratory, University of Maryland Center for Environmental Science
PO Box 775, Cambridge, MD 21613
Phone:410-221-8410
Fax:410-221-8490
email: newell@hpl.umces.edu

Additional Principal Investigators:
Raleigh R. Hood
Assistant Professor, Horn Point Laboratory, University of Maryland Center for Environmental Science
PO Box 775, Cambridge, MD 21613
Phone:410-221-8434
Fax:410-221-8490
email: raleigh@hpl.umces.edu

Evamaria W. Koch
Assistant Professor, Horn Point Laboratory, University of Maryland Center for Environmental Science
PO Box 775, Cambridge, MD 21613
Phone:410-221-8418
Fax:410-221-8490
email: koch@hpl.umces.edu

Raymond E.Grizzle
Associate Professor
Jackson Estuarine Laboratory
85 Adams Point Road
Durham, NH 03824
Phone: 603-862-2175
Fax: 603-862-1101

Work Accomplishments

Scheduled Tasks for Year One

1. Undertake experimental work in the laboratory to measure changes in light extinction coefficients associated with oyster and clam feeding over a range of seston concentrations at 15, 20, and 25oC water temperatures.
2. Perform two-week field studies to quantify sediment resuspension in SAV beds 1) when they have maximum shoot density in mid-summer and 2) as shoot densities decline during plant senescence in the Autumn.
3. Develop a mathematical model in STELLA relating bivalve feeding to light penetration and seagrass abundance. Parameterize the model using our own field and laboratory data.
   

Work Plan to Accomplish Tasks

1. The influence of eastern oysters (Crassostrea virginica) and hard clams (Mercenaria mercenaria) on turbidity and light penetration was evaluated in1 m deep tanks filled with estuarine water. These tanks have a continuous mixing systems consisting of rotating, reversing paddles, with speed, direction, and duration controlled by computer to simulate mixing in nature. This system ensures homogeneous mixing of the water column without resuspending sediment from the bottom. Light was provided by 4 ft high output flourescent tubes which produced irradiance of ca 200 (µmol photons m-2 s-1) just below the water surface.
   
   We used adult oysters (8 to 10 cm shell height) collected from the Sandy Hill oyster bar in the Choptank River. Mercenaria mercenaria (shell height of 5 to 6 cm) were grown in Plantation Creeks, VA and provided by Dr. Mike Peirson of Cherrystone Aquafarm. Both species of bivalve were collected in March and held in the lab for 14 to 20 d acclimation prior to use in the feeding studies. Oysters were held in flowing ambient estuarine water salinity (salinity 15 ppt) with a natural seston complement. Clams were held in non-flow through aerated tanks with 20 ppt water made by mixing estuarine water with full strength seawater with 20% of the water exchanged every second day. Clams were fed algal paste at 2% of dry body weight per days as a maintenance ration. Clams were put into 12 cm deep plastic beakers containing coarse sand into which the deeply buried during the acclimation period prior to use in the feeding studies. In March one group of each species was held at the field ambient water temperature of 15oC and one group was acclimated to 20oC.
   
   In separate experiments, oysters and clams were placed on the bottom of the tanks and allowed to feed undisturbed for 2 h. Oysters were placed in 2 cm deep plastic pots to facilitate retention of both feces and pseudofeces and clams were placed directly in the tank while still buried in the sand-filled plastic beakers. At intervals for between 14 and 24 h the diffuse attenuation coefficient for photosynthetically available light, Kpar was measured using a 4B Li-Cor light meter positioned just beneath the water surface (0) and at 0.5 m (z) beneath the surface. The flourescent tubes were only switched on for the 10 min period required to make readings and were then turned off to reduce any phytoplankton growth during the experimental runs. Due to slight variations in light output from the high intensity flourescent tubes we measured light levels (µmol photons m-2 s-1) haphazardly 3 times in each of the 3 tanks. The 3 light readings were then used to calculate the extinction coefficient :
   
   Kd = [ln (light z /Light 0)] / z
   
   from which an average Kd was calculated. In order to estimate the loss in light intensity associated with distance from the light source, rather than attenuation by material in the water, we also measured in tanks without water the light at the usual position of the water surface and 0.5 m further into the tank. This Kd value for air was subtracted away from all of the experimental Kd values. Regression equations of Kd against time were calculated for each data set and used to calculate the absolute change in Kd (increase in light penetration) for a 24 h period. The change in Kd for the control tank associated with particle settlement was then subtracted away from the experimental values
   
   
2. We performed in early June 2000 the first of two field studies of the influence of seagrasses on sediment resuspension in Duck Point Cove at Bishop’s Head Point at the entrance to Monie Bay, Maryland. In this same cove we selected two sites, one densely vegetated by the seagrass, Ruppia maritima, and one unvegetated. At each site, a small platform was mounted to hold the necessary equipment to monitor environmental conditions over a 10-d period. We used an ISCO automated water sampler at each site to collect 1 l of water every 2 h to determine total suspended solids (TSS), grain size distribution, and salinity. Additional abiotic parameters recorded included water temperature, light availability (4B LiCor sensors) and wave characteristics. At the end of the experiment, seagrass density, canopy height, and photosynthesis x irradiance curves were measured. Samples are in the final stages of being analyzed and all data will be analyzed before the October deployment. Additionally, the critical erosional threshold of the sediments at each site is being quantified using microcosms under controlled conditions.
   
   
3. We have made substantial progress in the development of our mathematical model predicting the interrelationships between seagrasses and suspension feeders on light penetration.
   

Concerns or Difficulties

No major difficulties have been encountered so far in the development of this project.

Anticipated Success in Meeting Project Objectives in Scheduled Project Period

We have met all the objectives we set out for the first year of this project

Preliminary data

The preliminary data from the oyster and clam feeding studies show that there were clear and measurable changes in the light attenuation coefficient (Kd) over the course of the 24 feeding period.(Table 2). These data indicate that as we expected the removal of suspended particles by bivalves increase the amount of light that can penetrate through the light column. These data will then be used to parameterize the simulation model described below.

Table 1. Increase in light penetration, as measured by change in Kd due to particle removal by oyster and clams over a a 24 h period (Data not yet corrected for biomass of bivalves in each tank which was greater for oysters than clams)

There were differences in water temperature and light availability between the Ruppia maritima meadow and the surrounding unvegetated sediments. Different patterns in temperature fluctuations were also observed inside and outside the seagrass bed. During the initial warming trend (June 7 to 11), the water temperatures in the vegetated area tended to be warmer during the day as well as at night than in the unvegetated area (Figure 1). This pattern changed after the passage of a storm. The temperatures shortly after the storm (between June 15 and 19) fluctuated less in the seagrass meadow than at the unvegetated site (i.e. highs were less high and lows less low) after which they resumed the same pattern of warmer temperatures in the vegetated than in the unvegetated area (Figure 1).


Figure 1: Water temperature within the Ruppia maritima sea grass meadow and the surrounding unvegetated sediments during June 2000.

The light data show that in the vegetated area more light is available to the plants than in the vegetated area (average and maximum light levels are higher in vegetated than in unvegetated areas, independent of the depth at which the data have been collected; Figures 2 and 3, Table 2). This is possibly due to the lower resuspension of particles in vegetated areas but this remains to be confirmed by the TSS data currently being processed. As a result, light attenuation in the vegetated area is significantly lower than in the unvegetated area (Table 2).

Figure 2: Light availability (µmol photons m-2 s-1) at the top of the water column within and outside a Ruppia maritima sea grass meadow (June 2000).

Figure 3: Light availability (µmol photons m-2 s-1) at the close to the sediment surface within and outside a Ruppia maritima sea grass meadow (June 2000).

Table 2. Average and maximum (in parenthesis) light availability (µmol photons m-2 s-1) within and outside a Ruppia maritima bed (June 2000).

F. Preliminary Model Development:
We have formulated the basic model, and we have determined the approach that we will use to analyze and implement it. The basic model is composed of two equations, one which describes the rate of change in SAV biomass (Bsav):

1) dBsav /dt = um(1-e^(-Ib/Ik))Bsav - rBsav, where Ib = Ioe^(-KdZb), and Kd = m1S + b1

And a second which describes the rate of change of suspended seston concentration (S):

2) dS/dt = M(Tb-Tc) + wsS – CbSBb


In (1) um is the maximum growth rate of SAV, Ib is the irradiance at the bottom, Ik is the light saturation parameter and r is coefficient characterizing respiratory losses. Io is the irradiance at the water surface, Kd is the diffuse attenuation coefficient for photosynthetically active radiation, and Zb is the depth of the bottom. In (2) M is the erosion rate, Tb and Tc are the bottom shear stress and the critical shear stress for resuspension, respectively. Both Tb and Tc will be specified as a function of SAV bed density using data collected in the field studies. In addition, in (2) ws is the sinking rate of seston, Cb is the filtration rate of bivalves, and Bb is the biomass of bivalves (the latter is specified, i.e., not dynamically modeled).

The model is cast in a vertically integrated form and with spatial units of m2. Equation (2) feeds back on (1) through S, which determines the diffuse attenuation coefficient in (1). The form of this feedback suggests that the model has two stable equilibrium states, one with low S and high Bsav and a second with high S and low Bsav. In between these two stable states the model will likely exhibit unstable and possibly even chaotic dynamics. The existence of these stable states, and the parameter ranges which give rise to them will be characterized using STELLA’s sensitivity analysis tools. Spatial modeling will be carried out by recoding the model in FORTRAN and specifying a grid of cells over the actual topography in Monie Bay, with intercell exchanges provided via horizontal diffusion and specified advective flows.

Tasks and activities for next reporting period

Tasks for the next reporting period

1. Complete our field studies of sediment resuspension in SAV beds at a lower shoot density that the summer study we just completed.
   
   
2. Complete the laboratory studies to measure changes in light extinction coefficients associated with oyster and clam feeding at 25oC.
   
   
3. Implement and analyze the mathematical model in STELLA and FORTRAN as described above, and incorporate functional relationships and parameters derived from the field and laboratory studies
   

Work plan to accomplish tasks

1. We will complete in late August 2000 the experimental work in the laboratory to measure changes in light extinction coefficients associated with oysters and clams feeding at 25oC.
   
   
2. We will undertake in October 2000 the second of the two proposed field studies in the Monie Bay NERR to quantify sediment resuspension in SAV beds when, due to normal senescence, the seagrass shoot density will be lower that during the June study period.
   
   
3. We will complete the development and testing of our mathematical model in STELLA, and implement the spatially explicit version of the model in FORTRAN. Our first goal will be to predict, on theoretical grounds, the interactions between seagrasses and suspension feeders through their effects upon suspended sediment concentrations and light penetration. We plan to do this before we start our second summer of field work in 2001 so the results can be used to help guide our field studies. The model will incorporate the data from the two field studies of the seagrass beds at Bishops head and the laboratory bivalve feeding studies described above. We will test our model predictions of the influence of bivalve feeding on light penetration and seagrass growth at clam aquaculture farms on the lower eastern shore of Virginia on the Chesapeake bay.
   

Concerns or difficulties

At this point we anticipate no major difficulties regarding the future progress of this project.

Expenditures

In all budget categories no expenditures are exceeding estimates. All of the equipment for which we requested funding has been delivered and is performing satisfactorily.