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Primary productivity, sedimentation, and phosphorus cycling in a Lake Erie coastal wetland
Reeder, Brian Charles, Ph.D. The Ohio State Univenity, 1090
UMI 300 N. Zeeb Rd. Ann Aibor, MI 48106
PRIMARY PRODUCTIVITY, SEDIMENTATION, AND PHOSPHORUS CYCLING IN A LAKE ERIE COASTAL WETLAND DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of the Ohio State University by Brian Charles Reeder, B.S., M.A., M.S. a ****
The Ohio State University 1990
Dissertation Committee: Approved by W.J, Mitsch C.E. Herdendorf D.L. Johnson T.J. Logan Environmental/Biology Program ACKNOWLEDGEMENTS
i I would like to express my sinccrest thanks to the following people for their help and encouragement: Siobhan Fennessy and Julie Cronk for assistance in the field, lab, and office; Kim Baker fo r editorial assistance; Drs. Paul Colinvaux, Wendy Eisner, and Mark Bush for field and lal moratory aid with the pollen coring and analysis; Dr. C.E. Herdendorf for field assistance and geologic expertise; Dr. Terry Logan for advice on methodology and the fate and transport of phosphorus; the staff of Old Woman Creek, especially Dave Klarer and Gene Wright, for assistance and coordination of site activities; and finally. Dr. I William J. Mitsch, who taught me how to do research, and has assisted invaluably with every stage of this dissertation from conception to completion. VITA
March 31, 1962 ...... Bom-Youngstown, Ohio 1983 ...... B.S., Youngstown State University, Youngstown, Ohio 1985 ...... M.A. Marshall University, Huntington, West Virginia 1985,1986...... Naturalist, Columbus Metro Parks, Columbus, Ohio 1987-1989 ...... Teaching/Research Associate, The Ohio State University, Columbus, Ohio 1988 ...... M.S., The Ohio State University, Columbus, Ohio 1989-Present ...... Assistant Professor of Biological and Environmental Sciences, Morchead State University, Morehead, Kentucky PUBLICATIONS
Mitsch, W.J., B.C. Reeder, and D.A. Klarer. 1989 The role of wetlands in the control of nutrients with a case study of western Lake Erie. pp. 129-157 In: Mitsch, W.J. and S.E. Jorgensen (cds.) Ecological Engineering: an Introduction to Ecotechnology. J. Wiley, New York.
FIELDS OF STUDY Major Field: Environmental Biology Studies in Wetland Ecology and Systems Ecology
iii TABLE OF CONTENTS
ACKNOWLEDGMENTS...... ii VITA...... iii LIST OF TABLES...... vi LIST OF FIGURES...... vii
CHAPTER PAGE I. INTRODUCTION...... 1 1.1 Nonpoint pollution and Great Lakes Coastal wetlands ...... 1 1.2 Goals and objectives ...... 2 II. LITERATURE REVIEW...... 4 2.1 Wetlands as sources sinks and transformers of phosphorus ...... 4 2.2 Phosphorus cycling in Great Lakes coastal wetlands ...... 8 2.3 Environmental history of the western Lake Erie region ...... 9 2.4 Paleochemistry...... 11 2.5 Modelling phosphorus cycling and productivity in wetlands ...... 12 III. METHODS...... 15 3.1 Site description ...... 15 3.2 Water chemistry...... 18 3.3 Planktonic productivity based on diurnal metabolism ...... 22 3.4 Macrophyte productivity ...... 25 3.5 Plant nutrient analysis ...... 26 3.6 Solar insolation ...... 26 3.7 Hydrology ...... 27 3.8 Sediment core...... 28 3.8.1 Chemistry...... 29 3.8.2 Pollen ...... 31 3.8.3 Dating ...... 32 3.9 M odelling ...... 33 IV. RESULTS...... 36 4.1 Hydrology ...... 36 4.2 General water chemistry...... 39 4.2.1 pH ...... 41 4.2.2 Total suspended solids and turbidity ...... 41 4.2.3 Conductivity ...... 44 4.2.4 Phosphorus chemistry...... 45 4.3 Comparison to near shore water ...... 47 4.4 Primary productivity ...... 47 4.4.1 Water column productivity ...... 47 4.4.2 Chlorophyll...... 51 4.4.3 Macrophyte biomass ...... 52 4.5 Core stratigraphy...... 54 4.6 Ecosystem modelling ...... 63 4.6.1 Hydrology submodel ...... 65 4.6.2 Primary productivity submodel ...... 71 4.6.3 Phosphorus model...... 74 4.6.4 Other simulations ...... 76 4.6.4.1 1988 inflow; high Lake Erie levels ...... 80 4.6.4.2 Normal inflow; 1988 lake Erie levels ...... 83 4.6.4.3 Normal inflow; high Lake Erie levels ...... 86 4.6.4.4 High inflow; 1988 Lake Erie levels ...... 86 4.6.4.5 High inflow; high Lake Erie levels...... 89 V. DISCUSSION...... 95 5.1 Primary productivity ...... 95 5.2 Limiting factors to primary productivity ...... 98 5.3 Role of primary producers in phosphorus cycling ...... 102 5.4 Role of recent sedimentation in phosphorus cycling ...... 103 5.5 Geologic history of Old Woman Creek...... 105 5.6 Hydrology and phosphorus cycling ...... 107 5.7 Evidence that Old Woman Creek is a phosphorus sink...... 111 IV. CONCLUSIONS AND RECOMMENTATIONS...... 115 6.1 Conclusions ...... 115 6.2 Recommendations for future research ...... 116 LITERATURE CITED...... 118 APPENDICES...... 133 A. HYDROLOGIC AND CLIMATIC DATA FOR OLD WOMAN CREEK WETLAND...... 133 B. 1988 WATER CHEMISTRY DATA...... 140 C. DIURNAL DISSOLVED OXYGEN DATA AND PRODUCnVTTY CALCULATIONS...... 144 D. VEGETATION DATA...... 155 E. CHEMICAL DATA FROM SEDIMENT CORE OF OLD WOMAN CREEK, 158 F. CALCULATIONS FOR PHOSPHORUS BUDGET...... 160 v LIST OF TABLES
TABLE PAGE 1. Chemical concentrations for samples in Old Woman Creek Wetland ...... 40 2. Gross primary productivity of water column at Old Woman Creek wetland 48 3. Biomass and phosphorus concentrations of Nelumbo lutea for Old Woman Creek W etland ...... 53 4. State variables and differential equations for the models ...... 68 5. Model parameters, definitions, values and sources of the model ...... 69 6. Comparison of the phosphorus retention abilities of the various simulations 110 LIST OF FIGURES
FIGURE PAGE 1. Location of Old Woman Creek wetland and its watershed in northern Ohio ...... 16 2. Map of Old Woman Creek wetland ...... 17 3. Comparison of phosphorus concentrations using the persulfate and perchloric acid digestion method ...... 20 4. Representative diurnal oxygen curve and a sample productivity calculation 23 5. Diffusion dome used to estimate oxygen diffusion ...... 24 6. Precipitation, evapotranspiration, wetland level, outflow, and inflow components of hydrologic budget of Old Woman Creek wetland ...... 37 7. Estimated hydrologic budget for Old Woman Creek wetland ...... 38 8. Mean concentrations of total suspended solids, turbidity, and conductivity ...... 42 9. Correlation matrix of chemical parameters ...... 43 10. Mean concentrations of phosphorus species during the 1988 study period 46 11. Seasonal patterns of insolation, planktonic productivity, and ecological efficiency ...... 49 12. Comparisons of chlorphyll a concentrations and primary productivty ...... SO 13. Relationships of a) plant dry weight and b) phosphorus concentrations versus leaf diameter for Nelumbo lutea from Old Woman Creek wetland 55 14. Stratigraphy of sediment core ...... 56 15. Patterns of organic matter (LOI = loss on ignition), degradation products of chlorophyllous pigments (SCDP), iron, manganese, total phosphorus (TP) and bioavailable phosphorus (NaOH-P) ...... 57 16. Correlation matrix for chemical characteristics of sediment core ...... 58 17. Total pollen concentrations in sediment core from Old Woman Creek. 59 18. Concentration of pollen by species for Old Woman Creek wetland sediment core ...... 60 19. Percentage of pollen by species for Old Woman Creek wetland sediment core.. 61 20. Conceptual Odum model of phosphorus and energy cycling ...... 64
21. STELLA™ diagram of the hydrology and productivity submodels 66
22. STELLA™ diagram of the phosphorus submodel ...... 67 23. Actual water level in Old Woman Creek wetland in 1988 compared to simulated water level...... 70 24. Model simulations compared to field data ...... 72 25. Regression and equations used to calculate phosphoms concentrations during a given inflow ...... 75 26. Resuspension and sedimentation predicted by the calibration model 77 27. Simulated results showing phosphorus inflow, outflow, concentration, resuspension and sedimentation during 1988 hydroiogic conditions 78 28. Simulation results of inflow, outflow, planktonic biomass, and macrophyte biomass during a period with 1988 inflow rates and high Lake Erie levels. Middle plot indicates days which barrier beach was open ...... 81 29. Simulation results for phosphorus inflow, outflow, concentration, resuspension and sedimentation during a period of 1988 inflow rates and high Lake Erie levels...... 82 30. Simulation results of inflow, outflow, planktonic biomass, and macrophyte biomass during a period with normal inflow ...... 84 31. Simulation results for phosphorus inflow, outflow, concentration, resuspension and sedimentation during a period of normal inflow ...... 85 32. Simulation results of inflow, outflow, planktonic biomass, and macrophyte biomass during a period with normal inflow rates and high Lake Ene levels. 87 33. Simulation results for phosphorus inflow, outflow, concentration, resuspension and sedimentation during a period of normal inflow and high Lake Ene levels...... 88 34. Simulation results of inflow, outflow, planktonic biomass, and macrophyte biomass during a period with increased inflow ...... 90 35. Simulation results for phosphorus inflow, outflow, concentration, resuspension and sedimentation during a period increased inflow ...... 91 36. Simuladon results of inflow, outflow, planktonic biomass, and macrophyte biomass during a period with increased inflow and high Lake Erie levels.... 92 37. Simulation results for phosphorus inflow, outflow, concentration, resuspension and sedimentation during a period of increased inflow and high Lake Erie levels...... 93 38. Relationship between a) diurnal productivity and depth; b) diurnal productivity and turbidity; and c) depth and turbidity ...... 100 39. Suggested changes in the importance of macrophytes and plankton in Old Woman Creek under varying average annual depths ...... 101 40. Lake levels as hypothesized by this study, Herdendorf and Bailey (1989), and Coakley and Lewis (1985) ...... 108 41. Nutrient budgets for Old Woman Creek as calculatedby a) estimated loading rates and Richardson and Nichols (1985) b) field data estimate; c) sediment core data; and d) calibrated simulation results ...... 112 CHAPTER I
INTRODUCTION
A number of ecologists have found that wetlands have the ability to act as net
sinks for nutrients (e.g. Nixon etal. 1976; Mitsch 1977; Mitsch etal. 1979; Ewel and
Odum 1984; Richardson 1985; Jorgensen e ta l 1988). Because of this ability,
wetlands have been used to control point sources of pollution such as acid mine
drainage (Fennessy and Mitsch 1989) and sewage (Hartland-Rowc and Wright 1975;
Kadlec 1979; Ewel and Odum 1984). Once nutrients enter a wetland, they may be
. transformed from one chemical species to another by biotic and abiotic activities In the
sediments (Gambrell and Patrick 1978) and by scasonally-abundant primary producers
(Van der Valk et ah 1979). If overloaded with nutrients, wetlands may export more
nutrients to adjacent ecosystems than they receive (Richardson 1985). Theories have
been proposed that the ability of a wetland to act as nutrient sink ancVor transformer is
directly related to its productivity and hydrology (Gosselink and Turner 1976; Brinson
etal 1984; Mitsch and Gosselink 1986).
1,1 Nonpoint pollution and Great Lakes coastal wetlands
Lake Erie algal growth, is phosphoras-llmited during April-Octobcr stratification
(Lean etal. 1983). This limitation, combined with massive inorganic phosphorus
inputs, creates the well publicized problems associated with eutrophication. In recent 1 2 yean, point sources of phosphoms have been significantly controlled; however, nonpoint pollution (from agricultural watersheds) is more than sufficient to create water quality problems in the Great Lakes (Logan 1982; Baker 1988). A management strategy to reduce agricultural runoff Involves use of no-till and low-tlll agricultural techniques which minimize sediment runoff (and presumably the phosphorus associated with the sediments in the mnofT). However, since phosphorus selectively binds to smaller soil particles, which are more prominent In runoff from low-tlll fields,
this strategy may result in an increase in bioavallable phosphoms entering the lakes
(Logan 1982).
Along with limiting the phosphorus applied to agricultural soils, many of which
already contain higher levels of phosphoms than needed to increase crop yields r * (Logan 1982; Baker etal.1985), preservation and reclamation of Great Lakes coastal
wetlands may decrease nonpoint pollution. Although the western basin of Lake Erie
was once bordered by the Great Black Swamp, estimated to be more than 6400 km^ in
size, only 150 km^ of the original Lake Erie coastal marshes remain (Herdendorf
1987). Marshes bordering the Great Lakes could be excellent sinks of nutrients
resulting from nonpoint runoff. The majority of the phosphoms from nonpoint
sources is sorbed to incoming sediments, some of which are deposited when they
reach the slow moving waters of a wetland. The accompanying nutrients on these
sediments may be usedby the rooted macrophytes, or absorbed by the plankton In the
water. Thus, phosphoms is blotically bound and may enter food webs or become
permanently buried in the sediments.
1.2 Qot U and objectives The goals of my research are to evaluate temporal and spatial patterns of primary 3 productivity and phosphoms dynamics in a western Lake Erie coastal wetland and to estimate their interconnections. This is accomplished through the following objectives:
1) determine annual patterns of hydrology, primary production, and phosphoms cycling in relation to the present chemical and hydrologic regime;
2) integrate these data by developing a model of productivity and phosphoms
cycling that can simulate the effects of varying hydrology; and
3) estimate the fate of phosphorus over a post-glacial period and relate It to the past primary productivity, sedimentation rates, and the chemical and hydrologic conditions of the wetland.
Therefore, my study investigates the linkages among productivity, nutrient cycling and hydrology in a freshwater coastal wetland, taking into account annual patterns of
macrophyte and plankton productivity, phosphoms chemistry, and hydrodynamics.
Nutrient and water budgets are developed and models simulated to provide predictive capabilities. Since the key to long-term retention of nutrients lies in the sediments, geologically recent sediments are examined to determine historical linkages among hydrology, productivity, and phosphoms. CHAPTER n
LITERATURE REVIEW
2.1 Wetlands as sources, sinks, and transformers of phosphoms
Grant and Patrick (1969) investigated nutrient retention in a tidal freshwater marsh in Pennsylvania that received efTIuent from three sewage treatment plants. Even though they noted significant decreases in species dlveislty and water quality due to the sewage influx, they also found a 57% reduction in phosphoms as water passed though the marsh. This prompted other investigators to explore the use of wetlands as nutrient sinks for sewage effluent Florida cypress wetlands were subjected to intense systems analysis by Odum and his colleagues (Odum et al. 1977; Nessel et ah 1982; Ewel and
Odum 1984). These investigators believed that because cypress domes are normally unproductive, the nutrient enrichment would result not only in increased sedimentation, but also increased biomass. Indeed, the investigators discovered that cypress domes fertilized by sewage effluent had increased productivity and provided significant water quality benefits. As water passed through the cypress domes, the wetlands retained most of the nutrients in either biomass, water or sediments. The outflow waters then percolated through the sediments and were released with much lower nutrient concentrations. Similarly, Boyt etal. (1977) found that swamps in Florida were effective at reducing nutrient levels of waste water when it passed through a wetland system. Total phosphoms concentrations averaging 6.4 mg I’* at the sewage outflow
4 were reduced to 0.124 mg 1** after passing through about two miles of swamp.
These high nutrient losses were attributed to the productivity of the wetland vegetation.
The importance of biotic forces in nutrient cycling has been illustrated by a number of researchers. Kadlec (1979) investigated the addition of secondarily treated wastewater to a Michigan fen and found that the fen became a nutrient exporter when unproductive, or overloaded. Since Kaldec was working in a location with more dramatic seasonal shifts than Florida, he was able to better identify the seasonality of the wetland’s ability to take up nutrients. This suggests that primary producers serve an important role in nutrient removal. Van der Valk etal. (1979) discussed the seasonality of wetlands as sinks and transformers of nutrients and noted that nutrient uptake in wetlands is greatest during the growing season when primary producers and microbes are most active. They also suggested that inorganic forms of nutrients were taken up by biota, remobilized and exported upon the death of biota, or retained in the i t sediments. This suggests that the ability to transform nutrients is directly related to primary productivity.
The relationship between the ability to transform nutrients and primary productivity has been supported by a number of researchers working on nutrient removal in highly productive areas. In a central Florida lake with a notable seasonal pattern, Mitsdi (1977) found that water hyacinth (Eichhomla cmssipes) was responsible for the removal of 11% of the phosphorus input. Ma and Yan (1989) found that the harvesting of hyacinths in China removed 358 kg of phosphorus from each hectare of marsh throughout a seven-month growing period. Prentki et al.
(1978) discovered that 20% of the phosphorus taken up by the plants was retained in the sediments of a Typha marsh. In a birch bog, Rlcharson et al. (1978) noted that 6 almost all of the inflowing phosphoms was retained by vegetation, and only 25% was
returned to the soil.
Although primary producers may be an important component in the seasonal
retention and transformation of nutrients, sediments also play an important role in
removal of nutrients. Gambrell and Patrick (1978) explained how the anaerobic nature
of many wetland soils may result in a release of nutrients, enhancing productivity. By
analyzing the phosphoms inflow and outflow data for a number of wetland and
terrestrial soils, Richardson (1985) found that terrestrial soils were best at nutrient
retention. With Increasing inputs of nutrients, swamp (forested wetlands) soils became
quickly saturated, with bog soils showing a slightly higher capacity. Fen soils had the
highest capacity for a wetland, retaining phosphoms loads up to 200 kg h a 'l. Of the
soil characteristics examined, only extractable aluminum showed a correlation to
phosphoms retention. Other factors such as pH, organic matter, and extractable calcium
were inconclusive indicators of retention capacity. Melillo et al. (1984) found that the
microbial flora of the sediments may also be important in nutrient retention and
transformation. They found that soil decomposers contribute to the seasonal uptake and
release of phosphoms in the same way as the primary producers--by converting
nutrients into insoluble waste products.
Since wetlands are usually sediment accumulating systems, the chemical and
biological capacity of the sediments may not be as important as the sediment deposition
rate. Wetlands spread inflowing waters over a hydrologically low energy landscape,
allowing suspended materials to deposit. In a coastal Lake Erie watershed, agricultural
runnofT is estimated to be responsible for raising the sedimentation rate of Old Woman
Creek wetland an order of magnitude, when compared to prc*scttlcr rates (Buchanan
1982). In another agricultural watershed, Cooper e ta l (1987) found that since the 1940s, 80% of the labeled phosphoius from the watershed was deposited in associated
flood plain swamps. Mitsch etal. (1979) found that, in an alluvial swamp in southern
Illinois, 10 times more phosphoms was deposited in the wetland during floods than was drained away the remainder of the year. Even at the velocity of the flooding, 3% of the phosphoms that passed over the swamp was deposited in the marsh. They also
found that one-third of the annual sedimentation in the swamp occurred as a result of
flood events. These observations suggests that hydrology is important in regulating sediment deposition and hence, phosphorus retention and soil and vegetation types.
Gosselink and Turner (1978) reviewed the linkage between hydrology and the chemical and physical properties of a wetland's sediment and biotic systems. They concluded that all of these factors were indirectly linked, but that hydrology was the
single most important factor in determining ecosystem functions. Although
Richardson (1979) cautioned that no definitive linkage can be made between productivity and hydrology due to the great variability of wetland types and associated
hydrologic regimes, definable relationships among hydrology, productivity, and
nutrient cycling have been illustrated by a number of researchers. Brown (1981) found
that productivity in cypress wetlands was directly related to the rate of Inflowing, phosphorus-laden waters. Brinson etal. (1984) summarized the effects of hydrology
on net productivity in forested wetlands and concluded that there is a gradient between
flowing water systems (high productivity) and stagnant water systems (low
productivity). In the Netherlands, Verhoeven etal. (1988) found that the hydrology of a fen influenced nutrient avallabUty and species composition, hence nutrient deposition
capacity. Vegetation found in a mesotrophic fen, with high groundwater discharge, utilized 21% of available phosphoms. Conversely, vegetation found in an eutrophlc
fen with a net groundwater recharge utilized only 9% of available phosphoms. 8
2.2 Phosphoms cycling in Great Lakes coastal wetlands
Great Lakes coastal wetlands do not fit any standard hydrologic model. Inland freshwater marsh water levels can vaiy due to inflow differences from streams or riven or long and short term lake level fluctuations. These wetlands can gain or lose portions of their volume and/or area due to the rise and fall of lake levels or short term seiches (Lyon etal. 1986; Herdendorf 1987). Undemanding the hydrology of these areas is further complicated because many Great Lakes wetlands are seasonally, or intermittently, isolated from the lake influence by barrier beaches. Further, wetland types vaiy greatly, from dune-like to bog-like, and they may move and change with varying lake levels (Prince and DTtri 1985; Herdendorf 1987).
Effects of short term seiche events were monitored by Sager et at, (1985) in a wetland adjacent to Lake Michigan. They found fluctuations in every mqjor nutrient followed, directly, the fluctuations in water level. On a longer time scale, Lyon et al (1986) examined aerial photographs of wetlands in the Straits of Mackinac and found an 87% reduction in wetland area at high versus low lake levels. They also noted that short-term flooding in some areas was necessary to free nutrients and allow plant growth. Well-drained soils remained unproductive, whereas poorly drained soils
(which were anaerobic at some point) were productive. Kelly et al, (1985) studied
Pentwater Marsh, which is controlled by Lake Michigan water levels. They found that the wet meadow communities nearest to the lake were flooded more frequently and had lower nutrient concentrations and productivities. Emergent marshes further from the lake had higher product!vites and nutrient concentrations. Aerial photographs showed that prolonged low lake levels resulted in an increase in emergent wetland area and a decrease in wet meadow area. Marsh vegetation in Great Lakes coastal wetlands may also be reduced by high infestations of carp
(Cyprinus carplo), which disturb the substrate and overgraze vegetation (King and hL u 1967).
Phosphorus cycling has been investigated in a remnant wetland along Lake Erie’s
Western shoreline, Old Woman Creek wetland. Klarer (1988) has shown that the i wetland’s physical structure is conducive to the regulation of the amount of I phosphorus entering the lake. Most of the sediments remained in the marsh and were j npt exported to the lake even after strong storm events. In fact, up to 70% of the storm water orthophosphate was retained in the wetland. Klarer also found that orthophosphate was diluted during storm tunnofT and appeared to be associated with the sediment fraction of the water.
Heath {1987) discovered a significant seasonal reduction in the concentrations of total phosphoms from the inflow to the outflow in Old Woman Creek wetland. He noted that during the growing season bloavailable phosphoms decreased as water moved towards the outflow. Heath argued that phosphorus retention was dependent on planktonic activity, not on sediment absorption-desorption kinetics. Based on the nutrient availability, laboratory bioassay results, and the lack of phosphomonoester production, he concluded that the plankton were not phosphoms limited. Both Heath
(1987) and Klarer (1988) lacked critical data on flow rates necessary to calculate a mass balances.
2.3 Environmental history of the Western Lake Eric region
The western portion of Lake Erie is surrounded by Lake-Plain till (remnants of ancient lakes from previous glaciations and glacial retreat), whose gentle slopes are conducive to the formation of wetlands (Herdendorf 1987). The area was known as 10 the Great Black Swamp until agricultural ditching changed the hydrologic . characteristics of the landscape. The geologic history of the Old Woman Creek area, the study area of this research, has been well documented, with the most site specific study being that of Herdendorf (1963). The glacial history of the Old Woman Creek area has been described by Campbell (1955), and the depositions] history was described by Buchanan (1982) and Frizado etal. (1986), who noted a rapid sedimentation rate following deforestation.
The Old Woman Creek study site lies in the deepest portion of the preglacial
Huron River Valley (Buchanan 1982). Herdendorf (1987) and Brant and Herdendorf
(1972) describe Lake Erie coastal wetland formation in terms of the drowning of river mouths. After the Niagara outflow opened due to the Wisconsin glacial retreat
(maximum about 20,000 Y.B.P.), tributaries were cut deep into the glacial till because lake levels were low. As the Niagara outlet rebounded, the lake rose and stream velocities decreased. This formed the current deposits of alluvium in Old Woman
Creek.
Previous historic studies in the geographic region contain either incomplete stratigraphies or poor dates. Regional histories of vegetational changes along climatic gradients for the area are provided by Braun (1961) and Spear and Miller (1976).
Buchanan (1982) provides an indescript pollen diagram from a long sediment core taken in Old Woman Creek wetland. He also obtained a valid ^ C date, which he used to determine the deposition rate. He also found an increase in A m brosia pollen
(an indicator of Euopean habitation) with an Influx of till-plain and lake-plain sediments.
Mqjor studies of pollen and macrofossils in nearby areas include those done at
Sunbeam Prairie (Kapp and Gooding 1964), Silver Lake (Ogden 1966), Corry Bog 11
(Harrow etal. 1984), Nichols Brook (Calkin and McAndrews 1980), Refugee Road
(Garrison 1967), Pretty Lake (Williams 1974), and Ftains Lake (Kerfoot 1974).
Other stratigraphies are available for fossil pigments in Brown’s Lake (Sanger and
Crawl 1979) and diatoms at Summit Lake (Gray and Olive 1986). A complete pollen zone stratigraphy for the area was devised by Shane (1987) who analyzed the data from previous sites as well as data from six cores she collected (Brown's Lake,
Battaglia bog, Quillin, Stotzel-Lels, Carter, and Pyle). Shane noted that there was a warming and drying period after 10,300 B.P. She also noticed, at 8,000-4,000 B.P., a period of further warming and drying characterized by lower lake levels and the establishment of hardwood forest.
2.4 Paleochcmistrv
Analysis of a sediment core from a wetland could elucidate the hydrologic and blogeodiemical history of the area, if information on chemistry Is used in conjunction with knowledge about vegetational history. Sediment chemistry has been used successfully to gain insight into past biogeochemistry of lakes (Engstrom and Wright
1984; Davis etal, 1985; Engstrom etal. 1985) and could presumably be used in wetlands. For example, analysis of phosphorus from sediment cores has been used to determine past productivity and trophic status (Hutchinson and Wollack 1940;
Livingstone 1957; Livingstone and Boykin 1962; Williams eta l. 1971; 1976; 1980;
Holdrtn and Armstrong 1980). In addition to phosphorus, iron and manganese can be used to reconstruct past redox conditions because of their increased and differential solubility under reduced conditions (Macereth 1966; Pennington etal. 1972). Futyma
(1988) and Thompson (1988) used data on pollen, chemistry and geology to 12 reconstruct the environmental history of the Indiana Dune National Seashore wetlands.
2.5 Modeling phosphorus cycling and productivity In wetlands
Modelling has been used as a tool to provide answers for complex questions concerning ecological and physiological systems (Hall and Day 1977; Jorgensen
1988). It has been suggested that system approaches allow ecologists to evaluate ecosystem ’’health” (Schaefferetal. 1988). The sum effect of cumulative impacts on a wetland may only be resolved by applying systems theory and energetics approaches (Hemond and Benoit 1988). Reviews of models of freshwater wetlands are summarized by Mitsch etal. (1982; 1988). Jorgensen (1988) reviewed his highly refined model for the eutrophicatlon of a large shallow lake in Denmark known as
Lake Glumso. The perfection of the model required 16 years of study and 14 years of field work. The level of refinement in this model provides an excellent, and predictive, tool to study the nutrient and tropic status of Lake Glumso. Part of the success of Jorgensen’s model is attributable to the fact that the problems associated with the complex kinetics of shallow water sediments were resolved by the sediment exchange submodel developed by Kamp-Nielsen (1983). Wlegert etal. (1981) also developed a well refined model of productivity, decomposition, nutrient cycling, and hydrology for a tidal salt marsh. Wcigcrt’s model has also been extensively calibrated with field data, and represents one of the finest and all encompassing wetland simulations available.
The role of wetland hydrology in modelling was reviewed by Duever (1988). A model linking hydrology and nutrient behavior In wetlands was developed by Kadlec and Hammer (1988). They first developed an accurate hydrolgy simulation of 13
Houghten Lake wetland which took Into account the sheet flow dynamics of the wetland system (Kadlec etal. 1981). This model was calibrated by comparing simulation results using various flow equations with field data. They then created a nutrient model with nine solid compartments and three water compartments (Kadlec and Hammer 1988). Modeled nutrient variables included soli composition, soil water, and biotic factors, as well as surface water concentrations. Water concentrations and nutrient dynamics in the soil were determined directly by the hydrology submodel.
Extensive calibration was possible because of the abundance of field data. They found a high agreement between model and field results for nutrient concentrations in the surface waters and biomass.
Hopldnson and Day (1980a; 1980b) used the EPA Storm Water Management
Model (SWMM) to predict increases in nutrient mnofT into a Louisiana swamp. First, the effects of changing land use patterns on hydrology, and the results these would have on nutrient runoff were formulated (Hopldnson and Day 1988a), The mq)or forcing function in the model was overland flow, which was determined by both land use characteristics and rainfall. Nutrient concentrations were a function of water volume and land use. Further, each type of land use determined the quantity of nitrogen and phosphorus. Since the simulations were predictive, validation was done by static check using Soil Conservation Service parameters. They also used sensitivity analysis to Identify if the most uncertain parameters were significantly affecting the simulation results. The same hydrology model was used to predict the effects of runnoff as it passes through a swamp forest wetland (Hopklnson and Day
1980b). The submodel for the swamp Included the effects of anaerobic soils, primary productivity, and nutrient concentrations (as predicted by the land use model).
Calibration was done by comparing modelled hydrology results with field data 14 hydrology results. This model was capable of predicting how hydrologic parameters could be managed to maximize the productivity of the swamp, and therefore, Improve water quality.
Brown (1988) developed a wetland simulation that predicts water quality and nutrient cycling when factors such as the wetland type, inflow of water, and nutrient concentrations are provided. A hydrology submodel was developed independent from the nutrient model. The hydrology submodel predicted quantities of surface water, soil water, ground water runnoff, and rainfall. It also accurately described the
Interactions between the three state variables. Concentrations of nutrients were added to the calibrated hydrology model, and state variables added for nutrients in the biomass, soil, and solution. This also included a nutrient inflow from a sewage component. Calibration and verification were done by comparing the modelled results with field data results from a variety of other studies on nutrient mass balances in wetlands receiving sewage effluent.
Another recent model which links productivity to hydrology and nutrient cycling was developed by Mitsch (1988). This model quantifies the effects of varying hydrology on productivity in forested wetlands. This relatively simple model predicts nutrient concentrations in the sediments (available for plant growth) and water depth
(determined by hydrology), then combines the two factors to predict primary productivity. Although a preliminary model, it illustrates the importance of developing a proper hydrologic model as the first step in producing a productivity andfor nutrient mass balance simulation. CHAPTERm
METHODS
3.1. Site description
A Lake Erie coastal wetland site was sought which fufllled three criteria: 1) It should be a highly productive ecosystem with easily measurable primary productivity;
2) it should have a significant input of nutrients; and 3) it should have accumulated sediments throughout known climatic changes. Old Woman Creek State Nature
Preserve and National Estuarine Research Reserve (hereafter refered to as Old Woman
Creek) met the above-mentioned criteria. Preliminary data for the area had been collected, the area was relatively pristine, and research facilities were available on site.
Old Woman Creek is located adjacent to Lake Erie in Erie County, Ohio (Figures I and
2). Its hydrology is determined both by Lake Erie water levels and runoff from a 69 km watershed. The marsh itself is 56 hectares in size and extends about 1 km south of the Lake Erie shoreline. It is approximately 0.34 km wide at its widest portion. Depths may extend to 3 m in the inlet stream channel, but for the major portion of its area it is usually less than 0.5 m deep. The wetland has an outlet to Lake Erie that is often open but which can be closed for extended periods of time. Dramatic seiches on Lake Erie can reverse the normal lake inflow, causing lake water to spill into the wetland. Aquatic habitats within the wetland include open water planktonic systems and American lotus
(NcJumbo lutea) beds throughout a significant portion of the marsh. Not as common, 15 16
Old Woman Creek W etland
U.S. Hwy. 6 111111111 t Ohio Routo 2 Darrow Rd.
Approxim
Figure 1. Location of Old Woman Creek wetland and its watershed in northern Ohio 17
ONelumbo f Approximate Scale
Figure 2. Map of Old Woman Creek wetland study site showing sampling stations (num bers) and coring (+) location. 18 but found bordering the edges and Inlet streams axe white wateriillles (N ym phcac tuberosa), spattcrdock (Nupbar adusna), arrow aium (Pdtandra vfrginica), and cattails
( Typha spp.). Wooded wetlands (some recently created due to the high water levels) He in cmbayments. The present flora differ from the more divexse plant communities described by Marshall and Stuckey (1974) when the area was under the influence of lower lake levels.
Three geomorphlc provinces are found within the drainage basin. These are: 1) Lake
Plain, 2) Berea Encarpment, and 3) Till Plain, arranged respectively from the shoreline to the uplands (Buchanan 1982). The major land use (51%) within the 69 km^ watershed is agricultural. Old Woman Creek receives nonpoint pollution from these agricultural sources, In addition to sewage effluent from Berlin Heights’ (pop. 800) secondary waste treatment facility (Kreiger 1985). Due to Its status as a National
Estuarine Research Reserve, the wetland remains relatively undisturbed and is frequently used for nature education, recreation, and scientific study. Reserve facilities include a visitor's center, research dormitories, and a staffed aquatic ecology research laboratory.
3.2. Water chemistry
Water samples were taken at the ten sites shown in Figure 2, from early April through early November, 1988. Included in the sampling regime were an upstream site that received no influence from lake water, and a lakeshore water site. Sites were chosen which were near areas monitored by Old Woman Creek staff. Care was taken to Insure a variety of depths and flow regimes were represented. Samples were taken every two to four weeks with 500 ml acid washed polyethylene bottles, and the water levels were recorded. Overall, almost 1,500 water measurements were made on the 11 different parameters tested for throughout the course of the study. When the samples were taken, 19 different parameters tested for throughout the course of the study. When the samples were taken, temperature, pH (portable meter-calibrated with 4.01, 7.00, and 10.00
standards),.and conductivity (portable Hach meter) at each site were also measured.
Within two hours of collection 100-ml of each sample was Altered through a 0.45 pm
membrane filter, which had been soaked overnight in distilled water to remove any
traces of contamination. The filtered water was immediately placed in a freezer and
the filter and filtrant retained for chlorophyll a measurements. The samples were
placed on ice, in the field, and kept at temperatures between -5°C and 4 °C until analyzed. Samples were analyzed for all chemical species within 72 hours of collection.
Total suspended solids (TSS) were measured according to Standard Methods
(APHA 1985). One hundred ml of sample was vacuum filtered through a dry, pie-weighed 0.45pm glass fiber filter. The filter and filtrant were dried for at least 24
hours at 104°C, and the increase in weight determined. Twenty-five mis of the
sample were then tested for turbidity with a Hach colorimeter (Hach Chemical
Corporation 1984).
Bioavailability of phosphorus was ascertained by measurements of three phosphorus fractions following the guidelines of Logan e ta l, (1979) for Great Lakes tributaries. Soluble reactive phosphorus (SRP) was determined as molybdate reactive phosphorus (after APHA 1985) after the sample was passed through a 0.45 pm membrane filter. Total phosphorus in unfiltered (TP) and filtered (TDP) water was determined as othophosphate released after digestion with ammonium persulfate.
Particulate phosphorus (Part P) was considered the difference between TP and TDP.
The persulfate method of digestion was checked against the more rigorous perchloric acid digestion (after Sommers and Nelson 1972). Figure 3 shows a 20
600 500 ■ y - 1.054x-4,I9,r z-.987
TP by 400' persulfate digestion, 300 ' PC/I 200
100 '
0 100 200 300 400 500 600 TP by perchloric acid digestion, y g /1
Figure 3. Comparison of phosphorus concentrations using the persulfate and perchloric add digestion methods 21 comparison of the two methods for ten water samples from Old Woman Creek and nine samples taken from other western Lake Erie wetlands (samples courtesy of D.
Robb). Even with such a diverse array of samples, there was still less than 2% difference between the two methods.
The persulfate method of digestion was carried out as described In Standard
Methods (APHA 1985). Fifty ml of sample was treated with 1 ml sulfuric acid solution and 0.4 g ammonium persulfate. The solution was then autoclaved for 30 minutes at 98-137 kPa, cooled, neutralized to a faint pink phenolphthalein with SN sodium hydroxide then analyzed for orthophosphate.
To test for chlorophyll a , 50 ml of fresh sample were filtered through a 0.45 pm membrane filter. The filter was placed in a 50 ml centrifbge tube using 15 ml of 90% acetone as an extractant The solution was kept at a maximum of 4°C for at least 24 hours and centrifuged to clarity, afier which the top 3.5 ml was decanted into a 1-cm path-length spectrophotometer cell. Absorbances were read at 750 and 665 nm. The sample was then acidified in the spectrometer cell with 3 drops of 1 JVHC1 to correct for degradation and absorbance was read again. The percentage of native chlorophyll a was calculated using Lorenzen’s (1967) equation as:
Percent native chlorophyll ■ 665 - 665a 0.7 * 665
where,
665 “ absorbance at 665 nm, and
665a " aborbance at 665 nm afier acidification. 22 3.3 Planktonic productivity based on diurnal metabolism
Productivity and respiration were estimated on ten occasions during the growing
season over a nine month period by evaluation of the diurnal changes in open water
dissolved oxygen (Odum and Hoskin 1958). Measurements were taken every three to
six hours (taking care to get data near dawn and dusk) at sites 3,4, 5, 6, 7, and 9
(shown in Figure 2). Throughout the course of the study, over 800 dissolved oxygen
measurements were taken. Dissolved oxygen was measured with the azide
modification of the Winkler technique (APHA 1985) at dawn, dusk, and dawn, and
frequently in between with a YSI model 54 dissolved oxygen meter (calibrated by the
Winkler method). During winter, water temperatures were near or below 0°C and
planktonic activity was insignificant. No discemable change in dissolved oxygen was
observed during these periods.
Figure 4 shows a sample dissolved oxygen diurnal pattern and subsequent productivity calculation. Daily net production was determined by summing the
changes in oxygen concentration between sunrise and sunset. Day time respiration
was calculated as the mean nighttime respiration rate over daylight hours (assuming
that the daytime respiration rate was nearly equal to nighttime respiration rate). Gross
primary production was estimated by adding the daily net production to the day time
respiration.
Measurements were made with a floating dome to determine if it was necessary to correct productivty calcualtions for diffusion (Copeland and Duffer 1962). A 5-liter dome fitted with a YSI dissolved oxygen probe (Figure 5) was purged with nitrogen to a near zero dissolved oxygen reading. The rate at which the oxygen recovered was 23
27 Sept 1987
d .o. , i o : mg/L 9 ‘
15:30 18:30 21:30 2:30 6:30 9:30 12:30 15:30 Hour
Net Production
Rale of Change § Average Respiration —i » i Davtlmq ...f.p...).Repoirptlop ' i1 ■ i - 1.0 15:30 18:30 21:30 2:30 6:30 9:30 12:30 15:30 Hour A D.O. (g/m3) Rate of Change (g/m2 -hr) = A t (hours) * depth (m) For Net Productivity (g/m2-day), Integrate rate of change above0 for daytime hours For Total Respiration, find average nighttime respiration (R) (g/m2/hr) * 24 hours/day For daytime respiration. Integrate rate of change below 0 for daytime hours and above average respiration line Daytime Respiration + Net Productivity = Gross Primary Productivity (g/m2-day)
Figure 4. Representative diurnal oxygen curve and a sample productivity calculation. Dome Volume ■ 5.0 L i Temperature « 295 K
ii_m— 1^1 b Surface Area Covered •* 0.1521 m2 % Saturation on May 13,1988 ■ 99% % Increase of 0 2 in dome - 0.075 ml/hr
According to Odum and Hosldn (1958):
273 32g02 0.075 • ------‘ — — 295 2400 ml .00058 g 02/m2*hr 0.1521 * .99
Figure S. Diffusion dome used to estimate oxygen diffusion in Old Woman Creek wetland then used to calculate the diffusion rate. Although measured for at least five hours at numerous times during the course of the study, the highest rate of diffusion was 0.012 mg O2 m’2 h‘* at 100% oxygen deficit, a rate which could he attributable to leaks in the dome system. This rate does not contribute a significant error in metabolism calculations, even at low saturation. Therefore productivity numbers are presented uncorrected for diffusion.
3.4 Macroohvte productivity
Estimates of macrophyte productivity (primarily Nclunibo lutea) were obtained with a technique which minimized harvesting impact and provided an accurate estimate of Nclum bo productivity. During July and August or 1988 three 40-m transects were taken through the Nclum bo patches and the maximum diameter (dj) of each floating leaf head was recorded. Random measured plants were harvested and dried at 104°C overnight, then weighed. The area under the transect was determined by summing the areas of eadi leaf which allowed the calculation of biomass (B) by:
T. drv weights in transect (g) B " (ir/4) £ d ,2 (m2) <3*2)
The standard method of harvesting at peak biomass (Vollenwieder 1974) was also used to test the reliability of the new method. In April 1987, six randomly placed l-m quadrats were established in areas were Nclum bo was known to grow. These were harvested at peak biomass (based on flowering time) and the plants were dried at
104°C overnight and weighed. In 1988, twelve 2.25-m2 quadrats were randomly 26 chosen In a Nclum bo patch. Four quadrats were harvested in May, July, or at peak biomass In late August
The total area covered by Nclum bo was estimated from infra-red aerial photography of the wetland taken within 1 week of the August 1988 harvest by the
Ohio Department of Natural Resources. The slides were projected onto a map of the wetland, the Nclum bo patches drawn on the map, and the area calculated by a digital planimeter.
3.5 Plant nutrient analysis
To provide an estimate of total uptake of nutrients, twenty-flve randomly selected peak biomass Nclum bo plant samples were analyzed for chemical composition by the
Ohio Agricultural Research and Development Center (OARDC) laboratory. OARDC analyzes for nutrients by dry ashing the sample, bringing it into solution, then recording emmissions on a Inductively Coupled Plasma (ICP) Spectrometer. Metals are digested and aborbance or emmlsslon determined via atomic absorption spectrophotometry.
3.6 Solar insolation
Total radiation was obtained from a continuous recording pyroheliometer located about 35 km northwest of the site at the light house on South Bass Island (in Lake
Erie). Due to gaps In the data record, weekly average insolation was determined.
Yearly calculations were determined as the average of the weekly means for an entire year. 27 3.7 Hydrology
Hydrologic data were obtained from a variety of sources. Daily rainfall (P) was recorded at Old Woman Creek by reserve staff using a National Oceanographic and
Atmospheric Administration (NOAA) certified guage. Daily inflows (S|) at the Darrow
Road bridge, lake levels, and wetland levels (near the center of the marsh) were recorded by the United States Geologic Survey (USGS) using standard techniques.
Evaporation was recorded from a evaporation pan at Old Woman Creek by the staff
On days when the pan was not functioning properly, values from the next nearest pan in
Tiffin, Ohio, were used. Ken Krieger of Heldleburg College averaged the data to obtain monthly estimates. Daily evapotranspiration (ET) was determined by weighting the monthly averages by daily air temperatures, obtained from NOAA data at Cleveland,
Ohio, and multipling this value by 0.7 to correct for the effects of the pan (Chow 1967).
Using the known volumes at each water level as determined from a bathemetic map, the daily change in volume of water in the wetland (A V) was determined from USGS daily stage readings. The condition of the barrier beach was recorded daily by Old
Woman Creek staff. The outflow (S0) from the wetland was determined by the following equation:
S0 ■ -AV + P • ET + Sj (3-3)
The volume of water in the marsh was calculated using the following regression:
V-SL* 572,553 - 218,324 where,
V - volume of water in wetland (rrP) (3-4) SL - USGS stage level in wetland (m) 28 Stage level was taken from USGS data; volume was determined by analyzing frustum volumes on a bathemctric map.
The hydrology data used for the simulation submodels were designed using inflow data obtained from the USGS with the exception of October, when no field data was available. During October, inflow was estimated from rainfall by making it similar to the resultant inflow caused by the nearest available storm of similar magnitude and duration for which field data was available. Lake Brie water levels were assumed to equal those of the wetland when the barrier beach allowed free flow of water between the lake and wetland. When the barrier beach was closed, Lake Erie levels were estimated to be the same as the nearest operating USGS station. Since this data was only available through September, and since it is normal for the beach to be closed in
October, lake level was made constant after this point.
3.9 Sediment Core. Coring was done on 29 January 1988 using a modified Livingstone piston sampler
(Livingstone 1955). Parallel cores were extracted 30 meters directly north of the eastern "point” of star island (Figure 2). This location is near the location where a long core was drawn, analyzed, and dated by Buchanan (1982). Cores were x-rayed before opening to ascertain particle size fractionations which may not be visible to the human eye. The x-rays were taken on 35.5 cm x 43 cm film with an exposure time of 28 seconds, and developed on an automatic Industrial developer at the Buckeye Steel Company.
Analysis of the x-ray films revealed that the first core yielded approximately 2.5 m of sediment, the second core yielded 5.3 meters of sediment, and the depositlonal patterns of both cores seemed to be similar (in particle size). The first core (brought up 29 in 3 1-m casings) has remained unopened. The longer core (brought up in 7 I*m sections) was the subject of all subsequent analysis. When not under analysis cores were stored in a refrigeration chamber at a constant temperature of 4°C Once opened the cores were always kept wrapped in at least three standard width sheets of cellophane type cling wrap. Both cores are currently housed at the Old Woman Creek
Visitor's Center, where they are being analyzed for diatoms.
3.8.1 Chemistry
Fifty samples were taken for chemical analysis at 10 cm intervals, starting 5 cm from the bottom of each section of the core. Within 72 hours of the core sections being opened the sediments were analyzed for degradation products of the chlorophyllous pigments (SCDP) following the procedure of Sanger and Gorham
(1972). SCDPs were extracted from I-cc samples with 100 ml of 90% acetone (the acetone was added in 20-ml portions and shaken vigorously and extensively with each addition, then allowed to settle overnight before measuring absorbances) and measured at spectrophotometric absorbances of 660*670 nm in a 1 cnP cell. The values are expressed per grams organic matter in SCDP units (see Swain 1985 for a discussion of the units).
To estimate organic matter, a one cm^ sample was placed in a clean dry crucible, weighed, placed in a drying oven at about 105°C for at least 24 hours, reweighed (dry weight or water loss), then placed in a 550°C muffle furnace for one hour, and weighed again (organic matter loss) after the methodology outlined in Dean (1974).
Sediment particle size was analyzed for samples from the middle of each zone of differential organic deposition by the OARDC laboratory using suspension analysis.
Aliquots of dried sediment (0.8 g) were analyzed for bioavaitable phosphorus 30 (NaOH-P) after Chang and Jackson (1957) by placing them in 50-ml centrifuge tubes with 40 ml of 0.1 M sodium hydroxide. This was mixed mechanically for at least 24 hours, then centrifuged for 15 minutes at 2400 rpm. In samples with high organic matter (>10%), concentrated sulfuric acid was added dropwise to flocculate the organic matter. After 50-ml of sample were acidified with 5 N sulfuric acid to a phenolthalein end-point, the sample was analyzed for orthophosphate (APHA 1985).
Perchloric acid digestions for total phosphorus (TP) in sediments were carried out after Sommers and Nelson (1972). A 0.1 g dried sample was pie-treated with 5.0 ml of nitric acid and heated to dryness in a digestion tube to insure that no organic matter was available for explosive reactions. The sample was then digested with 3 ml of 70% perchloric acid at 203°C for 75 mln. The tube was cooled, diluted to 50 ml with distilled water, mixed, and allowed to settle overnight. Next, 3 ml of the supernatant were removed and neutralized with 5Arsodium hydroxide to a p-nitophenol end-point in a 50-ml volumetric flask, and brought to mark with distilled water. Standards were also carried through the digestion process so that an accurate standard curve could be obtained. The extracts and standards were then analyzed for orthophosphate (APHA
1985).
Digestion of samples for Fe and Mn was done with an Aqua Regia/HF mixture in
Teflon bombs similar to those described by Bumas (1967). Fifty mg of sample was taken using a Teflon coated spatula, taking care to get the sample from the very center of the core barrel. The sample was then placed in the Teflon vessel, and first completely saturated with 0.5 ml of Aqua Regia, and then next with 3.0 ml 48% HF.
The container was sealed and secured in the bomb, then placed in a 110°C oven for one hour. After cooling for at least 20 minutes in a -15°C freezer, the bombs were opened and 2.8 g of boric acid with 5ml distilled water were added and stirred. The 31 volume was taken up to 40 ml with distilled water, then taken up to 100-ml in a volumetric flask. Metal standards were made by mixing 0.5 ml Aqua Regia, 3.0 ml
HF, and 2.8 g of boric acid with a standard solution In a 100*ml volumetric flask.
Metal analysis was determined using a model 451 Instrumental Laboratory AA/AE
Spectrophotometer. The final concentration was determined by the average of three readings, with the standard error never exceeding 0.002. Mn was tun at a 0.5 bandwidth at 279.5 nm; Fe with a 0.03 bandwidth at 248 nm.
3.8.2 Pollen
Pollen was extracted by a modification of Faegrl and Iverson's (1975) methods from 0.5-cc of sediment at 20 cm intervals along the cote (adjacent to sites of chemical analysis), and at 5 cm intervals along the zone of Ambrosia intrusion. Samples were first washed with 9-ml of concentrated HC1 in a 15-ml centrifuge tube to remove all carbonates, and a known volume Ecalyptus pollen added. Each sample was then washed with 7-8-ml 10% NaOH, and heated at 90°C for 15 minutes. Then flve-ml of
0.1 M sodium pyrophosphate was added to flocculate the organic matter. The sample was then rinsed twice with 7-8-ml of distilled water to remove the traces of pyrophosphate, and dehydrated with a washing of 8-ml concentrated glacial acetic acid
(to prepare the pollen for acetolosls).
Acetolosls solution was prepared by very slowly adding 10-ml concentrated sulfuric acid to 90-ml acetic anhydride, then 7-8-ml of this solution carefblly stirred into the sample. This was heated in a digestion block until the solution either readied a "gummy orange" consistency or a 30-minute time limit. The pollen was washed with glacial acetic add, then water, and then three times with acetone. The pollen was then extracted into 3-ml of bromoform/acctone solution (specific gravity - 1.9) and 32 the supernatant placed in a clean centrifuge tube filled with 9 ml of acetone. The bromoform procedure was repeated to yield a solution with 6-ml of bromoform, 9-ml acetone and the cleaned pollen. The final pollen was centrifuged, rinsed with 5-ml of ethanol, and mixed with 1 to 2 drops of glycciW&aflorin solution and placed in a drying oven overnight.
Pollen was mounted on glass slides with glycerin and counted with the aid of a computerized pollen counting program (Eisner and Sprauge 1988). Identification of pollen was done at a 250 magnification on a light microscope. Counts were made until 300 grains/depth were counted (not including Eucalyptus grains) when possible.
In those samples with low concentrations of pollen, counts were made to 200 or 100
(dependent upon the amount present). The major keys used for pollen identification were McAndrews ef a/. (1973) and Kapp (1969).
3.8.3 Dating
Dating of the core was obtained for recent times from pollen analysis-the
Ambrosia intrusion considered to be a result of deforestation due to European settlement (forest clearance for ship building and agriculture occurring about 180 YBP
(Sears 1938)). Samples more than a thousand years old were taken from 1.96-2.01 m;
2.46-2.56-m; 2.83-3.03-m; 3.74-3.94-m; and the bottom of the core (5.13-5.33-m) and submitted to Beta Analytic Inc. for dating using international conventional techniques. Samples were pretreated with repeated washing of warm add, washed with distilled water to neutrality, sythesized to benzene and counted by Beta Analytic.
Low carbon samples were kept in extended counting to insure the smallest possible error. According to Beta Analytic, all information was recheckcd and no error was found, and the low carbon content did not cause undue difficulties. 33 3.9 Modelling
The first step in model development was to draw a conceptual model based on knowledge of ecological energy and nutrient flow. State variables were selected and an energese diagram (Odum 1983) developed using what is known about the parameters affecting the state variables. Model conceptualization continued on the microcomputer screen with the interactive simulation package STELLA™ (High Performance Systems
Inc. 1988) on a Macintosh microcomputer. Simulations used a fourth-order
Runge-Kutta technique and an integration interval of 0.1 day-selected because the turnover time of plankton is approximately one day. Simulation time runs for the 274 day period from March 1 to November 30,1988.
The model was calibrated using a step-wise calibration procedure. The hydrology submodel was developed using 1988 field data. Care was taken to make this submodel flexible enough to allow Lake Erie levels and inflows to be easily changed. The state variable selected for the hydrology model was volume of the wetland. The second submodel, primary productivity, was developed after the hydrology model was calibrated, and linked to it. State variables in this model were macrophyte biomass and plankton biomass. Calibration with 1987 and 1988 field data was performed for these two variables. After these two models were calibrated, the third submodel, phosphorus, was developed and calibrated. The phosphorus submodel was linked to the two preceding models prior to its calibration. State variables in this submodel include phosporus in the sediments and phosphorus in the water.
Several assumptions are implicit in the model:
-there is no built-in phosphorus limitation on the model (based on the work of
Heath 1987);
-one active layer of sediments is considered, with linear pathways of resuspension 34 and sedimentation;
•Since there is no phosphorus limitation, phosphorus is lumped as total
phosphorus, rather than dividing it into bioavailable and nonbioavailable
forms;
•phosphorus discharges into Lake Erie when the barrier beach is open and the
wetland level is higher than the lake level;
• no phosphorus discharges into Lake Erie when the barrier beach is closed;
• there is no autocatalytic feedback between plankton and its productivity. This
was done to increase model stability;
• macrophyte productivity is based on measurements of Nclumbo /urea, the
dominant macrophyte, and the only one for which calibration data were
available; and
• plankton biomass is converted to energy units with a constant ratio of 3.7 mg
chlorophyll a kcal‘1 for populations not limited by nutrients (Vollenwelder
1974).
Nclumbo productivity was a function of sunlight, as estimated from the field data.
Biomass, origanally calculated as energy units (kcal), were converted chlorophyll
according to Jorgensen (1982). Macrophyte growth was limited to a growing season
by the model in order to produce a proper pattern based on the productivity of
Nclumbo lutca as seasonally observed throughout the 1987 and 1988 growing periods.
Time of first frost was also programmed into the model to create a rapid decay rate of macrophytes in autumn.
The model calculates planktonic productivity as a function of sunlight, based upon
the extensive field data. Planktonic biomass was originally calculated as energy units
(kcal) are converted to chlorophyll according to Vollenwelder (1974), Trial 35 simulations using autocatalytic feedback reactions of plankton and macrophytes proved overly sensitive to variation. Both plankton and macrophytes contribute to sedimentation in the wetland.
After an accurate phosphorus simulation for the 1988 data was obtained (the calibration model), simulations were run to predict effects of varying watershed and
Lake Erie conditions on the ecosystem. As well as being predictive tools, these simulations also acted to test the stability of the model. Simulations included the effects normal and high inflow rates, increased lake levels, and varying barrier beach interactions. CHAPTER IV
RESULTS
4.1 Hydrology
The water budget for Match 1 through September 30,1988 for Old Woman Creek is summarized in Figures 6 and 7. A complete set of data is included in Appendix A. The precipitation pattern reflects a significant drought that occurred from eariy April through the middle of July throughout the mldwestem United States. Most of the surface inflow, which peaked near 300,000 m^ day* 1 in late Match, was completed by the end of April and did not resume through the rest of the study period. The barrier beach was open for most of Match, half of April, and fora short period during May. The wetland was open to Lake Erie for SO days, or 23 percent of the study period. It is a typical for the wetland to be opened during the spring and then closed during the summer. The water level of the wetland reached a high of 4.56 m above datum (datum "171m above sea level) on May 8 before a storm of 1.37 cm led to a breakthrough of the barrier beach.
When the beach opened on May 8 the water level dropped 0.55 m in two days. The barrier beach was closed by May 16 for the test of the study period, causing the water level to rise to 4.32 m before beginning a consistent drop during the drought until a 2.6 cm rain stoim in late August caused a slight rise.
The influence of Lake Erie on the wetland was most significant when the barrier beach was open in March through mid'May. Calculations revealed several peaks of 36 37
400000 300000
m3d‘l 200000 Inflow 100000
400000
300000
200000 Outflow 100000
Barrier Beach Goscd HE Barrier Beach Open 4.6
m above 4 ,4 Welland Level datum 4 .2 -
4 .0 -
0.010 0.008- Evapotranspiration m V 1 0.006- 0.004- 0 .002 *
Precipitation d *1 0 .0 2 '
J u ^ ii - L , 1 JLJL, 121 131 181 211 241 271 day
Figure 6. Precipitation, cvapotranspiration, water level, outflow, and inflow components of hydrologic budget of Old Woman Greek wetland for March 1 through September 30,1988. Middle plot indicates days which barrier beach was open. 38
Precipitation Evapotranspiration
1.0 1.8
i X i Old Woman Creek Surface Inflow Wetland
* * * * A * A * AV/At = +0.7 A A A * 15.2 '■■■■■■■II WWW"
units are 1,000 m3!day
Figure 7. Estimated hydrologic budget for Old Woman Creek based on field data for the period of January 1-September 30,1988 39 flow into the wetland, either from Lake Erie or as an error estimate in the hydrologic
budget, through the rest of the study period. These anomalies were not frequent. In
May the water level in the wetland increased 8 cm with no rainfall event and no Increase
in inflow due to the stream. I estimate that 44,000 m3 day*1 entered the wetland from
Lake Erie during that time. The wetland again had a slight increase in volume at the end
of August (9 cm) that suggests 24,000 m3 day 1 from sources other than those
measured.
During March and April storms, volume changed in direct proportion to inflow.
During the periods that the wetland was open to the lake, Lake Erie levels determined the wetland level, and therefore the volume. After the beach closed, volume increased proportionally to Inflows of precipitation and rainfall. As the summer progressed, lack of precipitation and inflow, coupled with high evapotransplration, caused the volume to
decrease. Volume was greatest when there was low evapotianspiration, high inflow, and a closed beach.
An estimate of the daily water budget for the study period of March through
September 1988 Is shown in Figure 7. Surface inflow from the watershed averaged
15,200 m3 day I while Lake Erie is estimated to provide 3,500 m3 day 1 on the average or 19 percent of the surface flow into the wetland. As expected, evapotranspiiatlon was
80 percent higher than precipitation during this summer of drought. The water level increased slightly during the study period by 7,000 m3 day I, even with the drought conditions. This was probably due to the barrier beach staying closed more often than usual in 1988. Outflow from the wetland to Lake Erie averaged 17,200 m3 day
4.2 General water chemistry
Overall water chemistry is summarized in Table 1. Mean concentrations of total Table 1. Chemical concentrations for samples in Old Woman Creek Welland, inflow stream, and Lake Erie shoreline for period of April I - November 6, 1988. Numbers indicate averages ± standard deviation (number of samples).
conductivity, tuibidity, total total P total soluble Station pH pmhoVcm FTU suspended pg-P/1 soluble reactive solids, mg/1 P, pg-P/1 P, pg-P/1 lake Erie Shoreline 1 8.010.7 (8) 285128 (12) 34125 (13) 35138(11) 1601128 (13) 30124 (13) 3.911.5 (9)
Old Woman Creek Welland 2 7.610.6 (8) 457188 (12) 88132 (13) 75121 (11) 2481147 (13) 45123 (13) 4.013.2 (9) 3 8.210.5 (8) 501196(11) 114150(13) 112152(11) 2671252(13) 46125 (13) 3.911.2 (9) 4 7.910.5 (8) 508190 (12) 1631138 (13) 1821186(11) 3781296 (13) 47131(13) 4.812.2 (9) 5 7.810.6 (8) 5281125 (12) 167183 (13) 1931108(11) 3091216(13) 50121 (13) 4.211.2 (9) 6 8.110.6 (8) 5341107 (12) 161180 (13) 142156(11) 3231225(13) 65125 (13) 4J+1.2 (9) 7 8.010 J (8) 520163 (12) 1821106 (13) 1821133(11) 3531329 (13) 56124 (13) 4.511.6 (9) 8 7.810.5 (8) 534182 (12) 139144 (13) 108141(11) 4301350(13) 66138 (13) 3.911.4 (9) 9 7.710.7 (7) 563142 (12) 143172 (13) 14H51 (11) 2781174 (13) 66137 (13) 4.712.1 (9) Inflow Stream to Wetland 10 8.010.4 (8) 6981102 (12) 75152 (13) 59150(11) 2471238 (13) 94163 (13) 7.512.7 (9) 41 suspended solids, turbidity, and conductivity at the inflow, outflow, and within the marsh are given in Figure 8. Statistical correlations are given in Figure 9. Appendix B presents all the water chemistty data. The overall averages (± standard deviation) of some of the chemical parameters are as follows: conductivity 510 (± 133) pmho cm’l; turbidity 128 (± 85) FTU; and total suspended solids 123 (± 100) mg 1*1. Throughout the majority of the study period surface outflows (station 2) and inflows (station 10) were at or near zero. Inflow, however, was significant for a much greater portion of the study period than outflow, since surface outflow was functionally halted when the barrier beach formed. Even given these restrictions, the water quality within the marsh tended not to have characteristics of either inflow or outflow area waters, suggesting that factors in the shallow zones played a role in manipulating water chemistry.
4.2.1 PH The pH of the wetland water remained circumneutral (annual mean of 7.910.7 SD) throughout the study period (Figure 8). The preponderance of limestone in the watershed caused relatively high alkalinity and some buffering. Diurnal shifts of almost one pH unit were noted during periods of highest planktonic productivity. Little difference was seen between inflow and outflow pH.
4.2.2 Total suspended solids and turbidity
Total suspended solids and turbidity were highly correlated (Figure 9), and showed some seasonal variability. Inflow and outflow concentrations shadowed each other, with outflow usually being slightly higher than inflow (suggesting that these hydrologic conditions were not conducive to rapid sedimentation rates). Inflow and outflow concentrations were highest at the beginning and end of the study period with the 42
400 ~w Upstream 300- Downstream -^W etland Tutbidity FTU 200"
1 00 -
-i— i— i— r i i— r l~'i I 1000 Upstream 800 Downstream -•* Wetland .f 00* pmohs cm 400
2 0 0 “ Conductivity
400
‘Upstream Total Suspended Solids 300- ‘Downstream -1 ‘Wetland 200
100
* * i ~ r™1 -t i I 50 100 150 200 250 300 350 tfay
Figure 8. Mean concentrations of total suspended solids, turbidity, and conductivity at the inflow (site 10), outflow (site 2), and within the marsh (sites 3-7; and 9). 43
pH Cond. FTU Chla TP SRP TSP TSS PartP
pH 1 Cond .17 1 FTU - .0 2 37 1 Chla -.18 29 39 1 TP .13 .36 36 .4 1 SRP .13 .37 -.09 - .1 2 -.06 1 TSP -.09 36 25 2 .27 .1 1 TSS -.09 .24 .94 .44 .28 -.18 .23 1 PartP .16 .29 31 .37 .97 -.09 .04 .24 1
Figure 9. Correlation matrix of chemical parameters measured in Old Woman Creek wetland in 1988. exception of a large increase at the end of July. The increases in the beginning and end
of the year coincide with increased inflow from the highly credible watershed.
Concentrations within the waters of the wetland were much higher than either the inflow
or outflow. As drought conditions began to dominate, concentrations in the wetland
increased to levels almost four times as high as the inflow, presumably due to stirring by
wind or biotic activity (e.g. caip).
Turbidity remained low as long as the lake water was the dominant inflow (Figure
8). In early June, stream inflows dominating and the beach closed, turbidity within the
marsh to reach as high as 600 FTU at station 4 (and a corresponding 710 mg 1* 1 total suspended solids). Concentrations remained about 300 FTU (200 mg 1* 1) throughout
July, but then fell to almost half that for the remainder of the year.
4.2.3 Conductivity
Conductivity followed a slightly different pattern than did turbidity and total suspended solids (Figure 8). Conductivity was generally highest at the Inflow, then decreased up to 50% as the water flowed through the wetland. Inflow concentrations steadily increased throughout the study period; conversely, concentrations at the outflow showed a steady and significant decrease. This may have been due to the activity within the wetland removing the chemical components of conductivity, such as primary producers removing dissolved nutrients. The drought conditions seemed to partially halt this decline at the outflow, corresponding to the same time that nutrient concentrations were Increasing in the wetland and resuspension of the sediments was increasing as the water level lowered. Conductivity was quite low within the marsh and at the outlet towards the end of the growing season. Overall, concentrations in the wetland remained relatively stable, despite the increased inflow and decrease outflow, further indicating 45 some process within the marsh maybe capable of eliminating dissolved lens from the
water. When Lake Erie is allowed to flow into the wetland, it dilutes all of the wetland
concentrations near the mouth.
Note that all three parameters, turbidity, conductivity, and total suspended solids,
show dl (Terences in their "flow” characteristics at the beginning of the study period.
This is when there was a significant inflow from the creek, and the beach was open to
allow passage of water to or from Lake Erie. Suspended solids and turbidity do not
change to any degree as they flow through the marsh, however conductivity (a measure
of dissolved ions) shows a linear decrease as it passes through and out to Lake Erie.
4.2.4 Phosphorus chemistry
Mean concentrations of phosphorus species as they pass through the marsh are
given in Figure 10. Soluble reactive phosphorus is not shown since It exhibited little or
no variability. The correlations of the various phosphorus species with the other chemical parameters measured are shown in Figure 9. Table 1 shows the average concentrations measured at each sampling station throughout the study period.
Overall, phosphorus concentrations tended to decrease as water flowed through the wetland. During periods where water flowed out to Lake Erie, total phosphorus concentrations decreased about 50% by the time it passed through the wetland, but the highest concentrations were usually within the marsh. Total phosphorus was the most variable of the phosphorus species in its retention In the marsh, and is oflen higher at the outflow than the inflow. However, during the periods of highest Inflow concentrations, outflow remained relatively low.
Total suspended phosphorus (TSP) usually dropped about 50-75 pg 1*1 from inflow to outflow, but this was not consistent. Differences in TSP between the inflow (site 10) 46
1000 TP marsh 800- TP downstream
W 1 1 600* TP upstream
400-
2 0 0 *
200 * downstream TDP upstream TDP marsh TDP p g l'1 100-
800' upstream Part P 600” downstream Part P • marsh Part P
Mgl -1 400-
2 0 0 "
T 50
days
Figure 10. Mean concentrations of phosphorus species during the’ 1988 study period. 47
and outflow (site 2) were greatest during the periods of highest productivity. Ail the
phosphorus species had low concentrations at the sites nearest to Lake Erie when the
barrier beach was open. Some of this was probably due to the dilution of the wetland
waters by the inflowing waters of Lake Erie, which had relatively low phosphorus
concentrations. When the beach closed concentrations of TSP in the marsh (sites 3,4,
5,6,7, and 9) increased.
4.3 Comparison to near shore water
Values for all water quality parameters in the marsh were in excess of those
concentrations found in the neaishore waters of Lake Erie adjacent to the marsh (Table
1). One exception to this was soluble reactive phosphorus, which was sometimes slightly higher in the lake (by 1-3 jig I'*). Total phosphorus in the shore waters was never greater than 300 p g l'l , with the exception of one time in late September, when it was 376 fig 1" 1. Turbidity and conductivity had low concentrations in the shore waters compared to the wetland. Shore turbidity averaged 34 FTU and conductivity averaged
285 pmhoscm’ l. In the wetland they average 145 FTU and 518 pmhos cm*l respectively.
4.4 Primary Productivity
4.4.1 Water column productivity
Results of planktonlc metabolism in Old Woman Creek are summarized in Table 2 and Figures 11 and 12. Complete data on dissolved oxygen readings and calculations are given in Appendix C. Solar insolation followed a typical annual pattern, although the Table 2. Gross primary productivity of water column at Old Woman Creek wetland. All values in g O^m^-day.
station weigh tod Ham 3 4 5 6 7 9 mean ±SD mean
June 27 87 1 0 .8 7.6 6 .1 5.4 6.4 7.2 ±11 6 .8 Sept 26 87 6.9 9.7 2 .8 - 3.2 2 .1 4.9 ±3.2 5.3 May 14 8 8 6 .2 7.7 7.7 6 .8 8 .1 8 .1 7.4 ±0.77 7.6 May 28 8 8 4.0 6 .0 4.1 3.0 4.1 4.4 4.3±0.98 4.1 June 19 8 8 7.1 7.7 9.1 6.5 1 0 .6 9.5 8.4±1.6 7.7 June 27 8 8 7.6 5.8 9.8 6 .8 7.8 9.0 7.8±1.4 7.4 July 12 8 8 13.8 7.4 7.8 7.2 6 .0 3.5 7.6 ±3.4 7.0 July 26 8 8 3.7 8 .1 2.7 5.2 7.8 5.9 5.6 ±2.2 6.4 Aug 25 8 8 5.9 5.8 4.5 4.9 8.9 2 .6 5.4 ±2.1 6 .1 Sept 24 8 8 8.4 5.3 7.7 2.5 9.9 6.3 6.7 ±2.6 6.7 meanlSD 7.1±3.2 6.7±1.1 6.7 ±2.6 5.4±1.8 7.9±2.1 6 .2 ±2 .6 49
7000 - 6000 “ Solar Iniolalton 5000 * - 4000 - kcalnr 3000 -
2000 “ 1000 -
•« - Silo 3 Gross Primary Productivity Site 4 ♦ SitcS A D.O., Site 6 g02 m'%ay *•* Site 7 Site 9
I q Solar Efficiency
% 0.6*
0.2
0 100 200 300 400 day
Figure 11. Seaonal patterns of solar insolation, planktonic productivity, and ecological efficiency. 120 50 a) GPP - 100 8- Chla g/m2 Chlrophyll a - 80 >1 AD.O. 6 - mgl D n + 1 60 g 0 2 m’^day 4 1 40
2A - 20
-« i-o- —r~ i B -|------r 0 100 200 300 400
Day
9 y ■ .15x + 5.62, r2 ■ .15 8
° S *>0’
5
Chlorophyll a mg in ‘2
Figure 12. Comparisons of chlorophyll a concentrations and primary productivity in Old Woman Creek wetland for 1988: a) average productivity compared to chlorophyll readings; b) regression of diurnal productivity at each site versus chlorophyll at each site. 51 lack of cloud cover may have resulted in values slightly higher than in normal yean.
Gross primary productivity was not discemable by the diurnal method until about 2,500 kcal m*2 d* 1 was available to the plankton for warmth and to drive the photosynthesis.
Because the diuranl method was used to estimate productivity, values represent the entire planktonic system, i.e. nanoplankton, picoplankton, other phytoplankton, protozoans, and zooplankton. Planktonic productivity peaked in late June and mid July, leveled off until late August, then fell in early September to a level that was no longer discernible by the diurnal method (during a brief cold spell accompanied by heavy rainfall). Productivity increased again in late September and continued until cold weather and low insolation became inhibitive.
Ecological (Lindeman) efficiency of the planktonic system was determined as the percentage of available light converted to gross primary production. Ecological efficiency was generally low to medium for aquatic ecosystems, averaging about 0.6% for the planktonic portion of the system. Annual gross planktonic productivity translates to a total water column productivity of976 g O 2 m*2 y r *. This Is equivalent to 366 g C m"2 yr* o r3,700 kcal m*2 yr*.
4.4.2 Chlorophyll
Individual chlorophyll a measurements did not correlate well with whole system metabolism measurements (Figure 12b); however, when average values for both whole system metabolism and chlorophyll a are plotted together, they follow the same pattern, and a correlation for the means Is significant (Figure 12a). Almost no chlorophyll a was detected in early April, when temperatures were still ranging near biological zero
(4°C). By late April the wetland exhibited a dramatic increase in concentrations of chlorophyll & Even the formerly depauperate shore zone showed traces of chlorophyll. 52
Values in the sites that usually have the greatest flow velocities (stations 2,8, and 10)
were about 60 percent less than those found within the shallow regions of the wetland
(stations 3,5,6 and 9). In early May, the lake waters (station 1) with their low
chlorophyll concentrations (averaging 21 mg 1*1), tended to dilute the waters near the
lakeside of the wetland (stations 2,3, and 4). During this same period, sites near the
railroad bridge (station 7,8, and 9) retained high concentrations, averaging neatly 225
mg 1* I, even throughout periods of significant flow through the wetland. By late May,
lack of lake inflow coincided with a rise in chlorophyll concentrations throughout the
marsh, and diurnal fluxes of pH and dissolved oxygen were measurable. Throughout the
remainder of the growing season, chlorophyll concentrations throughout the marsh average about 225 mg 1*1, ranging from lows in the inflow stream of 27 mg 1*1 to highs
of over 400 mg 1* 1. Concentrations in the outflow were usually less than 75 mg 1" 1.
4A3.Macrophyifi-bloma« Macrophyte productivity showed a similar seasonal pattern. Table 3 summarizes the
results of peak biomass measurements for Nclum bo /urea In the marsh (complete data arc in Appendix D). The 1987 values assumed the same area of plants as the 1988 values.
Quadrats harvested in 1987 resulted in 32% less biomass than those harvested in 1988.
Floating-leaf vegetation (Nclumbo lutca) began to appear In early May. Peak biomass occurred around late August, and by late September most of the plants were dead or decaying.
In 1988, two methods of harvest were used. The quadrat method suggested a peak biomass of 160 ± 30 g dry wt m*2 while the transect method yielded an average of 131 g dry wt m*2. The 1988 transects, which took into account a much larger sample size, produced values 18% smaller than those obtained from the 1988 quadrats, but 17% 53
Table 3. Biomass and phosphorus concentrations of Nelumbo lutea for Old Woman Creek wetland. date Quadrat Method Transect Method Phosphorus g dry/m^, mcanlSD g dry/m^, mean mg/gdiy wt
Sept 6 87 109 ±48 - -
May 14 8 8 1 0 ± 2 • -
July 12 8 8 101 ± 32 123 3.3
Aug 25 8 8 160130 131 (n-3) 3.4 (n-3) total/OWC 1987 (kg) 12,971 total/OWC 1988 (kg) 14,827 63.5 54 greater than those obtained from the 1987 quadrats. Macrophyte net productivity, conservatively estimated by biomass at peak harvest, is thus 75 g C m '^.yr * or 750 kcal m*2 yrlwithin theN dum bobed.
The transect method was advantageous for calculating biomass because it allowed the calculation of phosphorus in each plant. An inverse relationship between leaf diameter and phosphorus concentration was found and used to calculate the phosphorus stored In the Nclumbob\omass of the wetland (Figure 13). Phosphorus concentration of individual N clum bo ranged from 2.17 to 6.07 mg P g dry wt* * (average! SD - 3.41
± 1.07 rngPg*!, n - 13; data in Appendix D). Phosphorus in the biomass of the macrophytes averaged 0.34 g P m'2 in the N clum bo beds during July and August.
4iiCgis-gtntlftraphY The stratigraphy of the sediment core from Old Woman Creek is shown In Figure
14, which also shows the dates and their relative position in the core, and the particle size for three zones. The core contains three main zones: IV) a zone of intermediate organic content consisting of silty loam (according to dating this is recent sedimentation); III) a high organic matter peat zone (from about the time of (Inal glacial retreat to the era of industrialization); and I) a very low organic matter zone of silty clay
(throughout a series of glacial events). A fourth zone (II) was determined as an intermediate between zones I and IK. A diagram of the deposition of the chemical parameters tested for is shown in Figure 15. Additionally, a correlation matrix of all chemical data is shown in Figure 16. A complete set of data is included in Appendix E.
Pollen deposition is given in Figures 17 through 19.
Organic matter content is closely correlated to productivity as evidenced from data on sedimentary chlorophyllous degradation products. The highest productivities, as a) y **.552x * 8.124, R-squarcd: .76 M
GO
diameter (cm)
6000 y » -45.909x + 5090.824, R-squarcd: .591 b) 5000
OU£ 4000 2
3000
2000 0 10 20 30 40 50 60 70
diameter (cm)
Figure 13. Relationships of a) plant dry weight and b) phosphorus concentrations versus leaf diameter for Nclumbo lutea from Old Woman Creek wetland Years Before 56 Present
131 cm 1.13-1.17 m 180 ±20 4
196-201 cm 4,220 ±120
246-256 cm 5,040 2.51m ±170
283-303 cm 8,270 ±170
Sites for Dating - ► 374-394 cm v 12,650 - 4 □ Clay >4m ±280 f m Peat
Eza Pebbles
1^53 Sandy Clay with peat 513-533 cm . 18,750 -4 • 5m ±470 ri 5.3 m (bottom)
Figure 14. Stratigraphy of sediment cone from Old Woman Creek wetland, with carbon-14 dates and sediment composition. 0.4
0.3 SCDP 0.2
0.1 0.0
Depth, cm
Figure IS. Patterns of organic matter (LOI = loss on ignition), degradation products of chlorophyllous pigments (SCDP), iron, manganese, total phosphorus (TP) and bioavailable phosphorus (NaOH-P) versus depth for sediment Depth Age % LOI BD TP NaOHP Fe Mn
Depth 1
Age .983 1
% LOI -.358 -.359 1
BD .549 .515 -.847 1
TP .416 .436 .011 -.01 1
NaOHP .034 .015 -.355 .383 .159 1
Fc -.046 -.042 -.077 .042 .066 .015 1 O VJ 1 Mn .218 .184 -.181 .221 .288 * .382 1
SCDP -.655 -.642 .272 -.591 -.184 -.02 -.001 -.146
Figure 16. Correlation matrix for chemical characteristics of sediment core. Abbreviations as in Figure 15; BD = bulk density. YBP cm 0 0
1 90 66
180 131 n
4022 200
m 5040 251
5690 291
IV
7880 428
8090 492
9560 533
I I I I I I t I I I 1 1 »l I I 1 t t I I I I I M I 1 I I I 40 60 80 100 120 140 grains / cc * 10^
Figure 17. Total pollen concentration in sediment core from Old Woman Creek. 60
8
ilu S' YBP cm 0 0
I 90 66
180 131 D *
4022 200
m 5040 251
5690 291
IV
7880 428
8090 492
9560 533 0 30 30 grains/cc * 1(P
Figure 18. Concentration of pollen by species for Old Woman Creek wetland sediment core. Plus (+) denotes at least 3 grains counted. 61
X b, b i
YBP cm ill 0 0
I 90 66
180 131 n
4022 200 i n
5040 251
5690 291 IV
7880 428
8090 492
9560 533
0 25 50
Figure 19. Percentage of pollen by species for Old Woman Creek wetland sediment core. Plus (+) denotes at least 3 grains counted. 62 indicated by SCDP, or the time of maximal preservation of chlorophylls, Is at 223 cm.
Productivity remains relatively stable (about a 3- fold decrease from the Initial peak)
from 250 cm to the top of the core, with the exception of 2- fold peaks (each about a 2-
fold increase) at 123 cm and 100 cm. The latter coincides with a peak in phosphorus, as
does the only record of productivity in the lower portion of the core (at about 433 cm).
Phosphorus concentrations along the time gradient are quite variable. The
concentrations of bioavallable phosphorus (NaOH-P) decrease to near zero when
productivity (oiganic matter and SCDP) is highest. Peak values of NaOH-P correlate
closely with peak values for total phosphorus. Average concentrations of total
phosphonis (mg g‘ 1 (standard deviation)) for zones IV through I are: 1.8 (0.3); 2.0
(0.3); 2.0 (0.2); and 2.0 (0.3), respectively. Average concentrations ofNaOH*P (mg
g~l (standard deviation)) for zones IV through I are 0.2 (0.2); 0.03 (0.04); 0.06 (.04);
and 0.2 (0.2), respectively.
If manganese concentration rises relative to iron concentrations, it may be Indicative
of mildly reducing conditions (Mackreth 1966), thus providing a method of determining
paleoredox. Fc:Mn relationships show eras of mildly reduced conditions at about 503
cm, 438 cm, and at 368 cm. The increase in both iron and manganese at 63 cm is
indicative of a zone of migration due to oxidative conditions in the soil. Average
concentrations of iron (mg g~ I (standard deviation)) for zones IV through I are 42 (53);
33 (5);32 (3); and 36 (5), respectively. Average concentrations of manganese for zones
IV through I are: 0.35 (0.15); 0.27 (0.024); 0.25 (0.006); and 0.36 (0.22), respectively.
Pollen concentrations 6hown in Figure 17 were determined from the Eucalyptus spike. Zone in and IV pollen was deposited at concentrations of about 70,000 grains 63 cc"l; zone I and n pollen at roughly 15,000 grains cc**. The marked decrease In pollen deposition should coincide with either rapid sedimentation, poor preservation, or lack of pollen producing vegetation.
The pollen concentration and percentage diagrams (Figures 18 and 19) outline the environmental history of the area. The sharp increase in Ambrosia pollen due to deforestation is at approximately 131 cm (first appearing at 203 cm). There is also an increase of another disturbance indicator, Chcnopodlum, at the height of the rise (20*50 cm). Trees and shrubs begin to arrive in Zone II. Quercus, Ulmus, and C aiyaan the first to arrive, followed in Zone III by a sharp domination of Caiya, and the prevalence of B etula and Pious. In Zone IV, Quercus and S a llx dominate, and Ulmus, Juglans,
Carya, Fraxlnus, Plnus, and 77//aare all present.
The little pollen found in zone I is dominated by hydrophytes, such as Nyphaceae,
Typha, and Cyperaceae, along with some Lycopodium and Graminae. No trees are found in this zone. This is a contrast to Zone IV herbs, which are dominated by
Ambrosia, Graminae, Typha, Composltae, Artem isia, and Nyphaceae. Graminae and
Cyperaceae are prevalent throughout all zones. There is an interesting increase in the amount of Artemcsla, Rumex, and Lycopodium coinciding with the appearance of trees in Zone II and the beginning of Zone III.
4.6 Ecosystem modelling
The data generated by the field work on its own does not provide a description of ecosystem functioning. In order to synthesize the data and determine what it suggests about energy dynamics and wetland biogeochemistty, simulation models were created to mimic wetland functions. A conceptual diagram (Figure 20) of the simulation model was developed based on knowledge of the cycling of phosphorus and energy in wetland 64
Evapottanspiiation Direct Lake Precipitatioi Formation Erie of Barrier Water Beach > Level
water Water level Inflow Volume from exchange with Lake Erii
Macrophytes (Nelumbo lutca)
Solar Plankton (chlorophyll a)
Active > Sediment Layer J
Energy Phosphorus Permanent Sediments
Figure 20. Conceptual Odum model of phosphorus and energy cycling in Old Woman Creek wetland.
E" 65 ecosystems. Unique to this wetland model is the interaction of Lake Erie with the wetland. This portion of the hydrology submodel was formulated by examination of data on the wetlancfs hydrology. The conceptual submodels developed on STELLA™ are shown in Figures 21 and 22. The variables and coefficients programmed into the model, as well as descriptions of the mathematics, are given in Tables 4 and 5.
4.6.1 Hydrology submodel
The hydrology submodel is designed to depict the hydrologic budget described in section 4.1, and Is capable of tunning simulations without input from the other submodels»productivity and phosphorus cycling. The only state variable for this submodel is the volume of water in the marsh. Factors affecting the volume of water in the marsh include rainfall, inflow, evapotransplratlon, and outflow.
Figure 23 shows the results of the calibrated hydrology submodel. The outflow coefficient of 1.0 day* I when the barrier beach was open reproduces water levels nearly i the same as USGS data from 1988. When the flow was negative, water flowed from
Lake Erie into the wetland. The model indicates that this happened several times throughout the early part of the study period. Although the model shows a remarkably similar annual pattern, it does not make the dramatic changes in water level that the field data does-there are few times when the model data are not within 0.2 m of the field data.
Overall, the inflow and outflow values predicted by the model are in high agreement with the field data. Given the scarcity of data (evaporation pans not always operating on site, only one year of drought inflows, uncertainty of beach permeability), the hydrology submodel appears to be quite accurate. 66
ave_depth Lake Ena o p e n jo ja k e Wetland L £ 3
Dlrect_Preclp outflow
Volume of OW
chlorophyll_a outflow_plankton G \> »C3 Plankton Productivity Reaplratlon
entatlon
Solar_lnsolatlon G3 Macrophyte Mao Prod Mac_Resplratlon GrowlnglSeason mac fedlmentatlon perce nt_mac
Day ave_depth
Figure 21. STELLA™ diagram of the hydrology and productivity submodels. 67
Productivity
LUptake Respiration r oponJoJake Total P Inflow Outflow/Factor bC3
TPO utflo outflow
s1 ave_depth Resuspenslon Sodlmontatlon_TP Voluma_of_OWC Conc_TPJn_Watar
Plankton Sad
mac_sadlmenta1lon sedimentation o M c_Uptake\ Mac.Prod
Macjtasplratlon
Figure 22. STELLA™ diagram of the phosphorus submodel. Table 4. State variables and differential equations for the model. 68
W ater, Q dQ / dt a Pd(t) + Qi(t) - ET(t) - klQ (when b ■ 1 and L>Le ) + (Le *L)A (when b ■ I and Le >L) where, Q s water volume in wetland, m3 Pd(t) * direct precipitation, m3/day Qi(t)» surface inflow, m3/day ET(t) a cvapotranspiration, m3/day kl b outflow coefficient, day-1 b b 1 (when outflow is open); b 0 (when outflow is closed) L b wetland water level, m b f(Q) Le b Lake Erie water level, m A b wetland area, m2
Plankton Biomass, PI d P |/ d t b k2I- k3P] -sp P |-k IP i where. Pi b plankton biomass, kcal/m 2 k2 s GPP coefficient I b solar radiation, kcal/m2-day k3 b respiration coefficient, day-1 sp b plankton sedimentation coefficient, day -1
Macrophytes, M d M /d t» k41 % - k5M - k6 (l) M where, M b mocrophyte biomass, kcal/m2 k4 b GPP coefficient for macrophytes % b percent cover by macrophytes Bf(dcpth) kS b macrophytc respiration coefficient, day-1 k6 (t) b macrophytc sedimentation coefficient, day -1 b f(timc of year)
Total Phosphorus, P dP / dt = C(Qi) Qi(t) - klP - (sl/d) P - a (k2I - k3Pf) A + (s2/d) A where, P b total phosphorus, g C(Qi) b phosphorus concentration of inflow, gfri3 b f (inflow) si a sedimentation velocity, m/day s2 b resuspension velocity, m/day d ° wetland depth = f(watervolume) a b phosphorua/kcal ratio in plankton, gP/kcal
Phosphorus In Sediments, S dS / dt b a (k2I - k3Pj) A - (s2/d) A + a sp Pi A + B k 6 (t) M A + B (k4I % - lc5M) A where, S b phosphorus in sediments, gP B s phosphorus/kcal ratio in macrophytes, gP/kcal Table S. Model parameters, definitions, values and sources for the model.
Symbol Name Values/Units Source
State Variables Q water volume in wetland m3 field data P total phosphorus B field data P| plankton biomass kcal/m^ chlorophyll data M macrophytc biomass kcal/m^ biomass data P total phosphonts in water gP field data 5 phosphorus in sediments gP field data
Forcing Functions m) direct precipitation m3/day field data Qi(0 surface inflow m3/day USGS data ET(t) evapotranspiration m3/day field data
l e Lake Erie water level m USGS data i solar radiation kcalAn^-day field data
Parameters and Coefficients kl outflow coefficient 1 .0 day -1 calibration b wetland water level m Odd data A wetland area m2 field data si sedimentation velocity 0.03 m/day Henderson-Sdlers 198 s2 resuspension velocity 0.0025 gP/m-day calibration d wetland depth m lc2 GPP/solar 0.005 field data k3 respiration coefficient 1 .0 day -1 field data sp plankton sedimentation coefficient 0.25day-l calibration k4 GPP/solar for macrophytes 0.0025 estimate % percent cover by macrophytes = f(dcpth) variable Ic5 macrophytc respiration coefficient 0.015 day-1 calibration m) macrophytc sedimentation coefficient 0 .0 1 d a y l t<288 estimate 0 .1 d a y l t>288 estimate C(Q0 phosphorus concentration of inflow g/m3 Baker 1988 d wetland depth m field data a phosphorus/kcal ratio in plankton 0.001 gP/kcal Jftgensen 1982 8 phosphorus/kcal ratio in macrophytesO.00075 gP/kcal field data c chlorophyll/energy ratio 3.7 mg chaAcal Vollenwelder 1974 440000 ' 330000 ‘ Inflow m* 220000 ■ lioooo : • I • '...... I ■ 400000 UL. outflow 200000 m 0.0 KM •200000 openjojake h r ~ i a v 4.7 Old Woman Creek Water Level - Model Resulti
4.4
m above 4 ,1 datum
3.8
Old Woman Qcek Water LcvcMJSGS
m above datum
■ > i 130 198 267 Time, days I 77 I ! I ” 1 ' 1 ., T, I l 1 Mar Apr May Jun Jul Aug Sep Oct Nov
Figure 23. Actual water level In Old Woman Creek wetland in 1988 compared to simulated water level. Also shown are the inflow and outflow. Middle plot indicates days which barrier beach was open. 4.6.2 Primary productivity submodel
The second level of model calibration was with the primary productivity submodel.
This model was linked to the hydrology submodel, and the results were compared with
the field data. The state variables in this model arc macrophyte biomass and plankton biomass. These arc both a function of sunlight with the mqjor losses being respiration and sedimentation (Figure 20; Table 4).
The productivity submodel is linked to the hydrology submodel in two ways. First, plankton are exported to Lake Erie when water from the wetland flows into the lake and
the beach is open. This assumption is consistent with the field data. Although some chlorophyll may be brought into the wetland with incoming Lake Erie water, this quantity is negligible. Second, macrophytes are assumed to be more abundant when water levels are lower, and less abundant when water levels are higher. This Is based on observations of other Lake Erie coastal marshes (Herdendorf 1987). Since water level has an effect on the types and amounts of vegetation present, It was assumed that the percentage of macrophyte cover was a function of water level. Using the 25-30% coverage observed for N elum bo in 1988 and the average depth, the following equation was used to obtain percent coverage:
% cover - 1-7/2 * d, 0 -0, da 0.26 (4-1) where, d-avcragc depth, m Field measurements of gross primary productivity are in close agreement with the modelled results (Figure 24). Modelled results were either the same as, or within one standard deviation of, the field measurements 70% of the simulated time. One low field 72 a) 40.Q Gross Primary 30.0 Productivity Iccalm d 10.0 120 b) chlorophyll a 90.0. mg m 6 0 ,0 . 30.0. c) Macrophyte Biomass Nelumbo lutes 2 0 0 * 0.0 - d) 3.201 Total Phosphorus mg 1 1-60- 0.800* r T Mar Apr’ Muy ’ Jun’ Jul Aug' • Sep ' Oct ' Nov ' Figure 24. Model simulations compared to field data of Old Woman Creek wetland for 1988 for a) gross primary productivity of open water, b) chlorophyll a., c) Nelumbo lutea biomass, and d) total phosphorus. Range bars indicate one standard deviation of field data. Open circles on a) Indicate full dissolved oxygen diumals; open circles on c) indicate alternate biomass measurement method. 73 measurment of gross primary productivity in late May could be attributed to a factor not taken into account by the model, since it does not fit the pattern of either the modelled or the field results. Two field data points near the end of the growing season also do not agree exactly with the model, but they are just slightly outside the standard deviation range, and retain a similar seasonal pattern. A further check of plankton dynamics was possible by using the chlorophyll a data as an estimate of biomass. Using chlorophyll aas a measure of calibration, the model is in agreement with the field data 78% of the simulated time (Figure 24). This is similar to the calibration agreement achieved using gross primary productivity as a calibration factor. The chlorophyll a values exhibit the same seasonal pattern as the model results, although the model underestimates biomass in May and June. On the other hand, gross primary productivity values showed that during May and June the model was in agreement with field results. Conversely, the biomass calibration showed the September model results were almost in perfect agreement; however this was one of the periods of poor agreement with the gross primary productivity calibration. Given the differences in the two field measurements and the variability of energy/chlorophyll ratios in aquatic systems (Vollenweider 1974), the model accurately predicts seasonal patterns of productivity and biomass. Initial calibration tuns, such as the one shown in Figure 24, assumed 100% coverage by macrophytes (Nclumbo). Since only maximum biomass was estimated for macrophytes, it did not provide an especially good calibration comparison. The standard method of harvesting at peak biomass does not agree perfectly with the modelled results. The model predicts peak biomass at point earlier in August than the quadrat data does, but is still within range. The data for macrophyte biomass as predicted by the model is right between the field data of biomass as found in a quadrat. 74 The transect method, which took Into account a much larger sample size and was used to predict phosphorus concentrations, shows a much better agreement with the modelled results. Again, the model underpredicts peak biomass, but not to the extent it did when compared to the quadrat data. Overall, the macrophyte biomass as predicted by the model is within an acceptable range to allow it to be used in future simulations. 4.6.3 Phosphorus model The phosphorus submodel was developed based on a number of assumptions expressed in the Methods chapter. The phosphorus calibration submodel was coupled with both the hydrology and primary productivity submodels (Figure 22), and is incapable of running simulations without input from these models. Hydrology was added by making the incoming phosphorus a function of flow. This was determined from two Lake Erie tributaries of similar size and land use - Rock Creek (24% larger) and Upper Honey Creek (35% smaller) as shown in Figure 25. Phosphorus discharges to Lake Erie when the marsh outflow (as calculated by the hydrology submodel) is positive. Macrophyte primary productivity was linked to the phosphorus submodel using the values of phosphorus in the macrophytes determined in section 4.3 to calculate the amount of phosphorus uptake (productivity respiration) and release (productivity Planktonlc biomass productivity and respiration were converted to phosphorus uptake and release using Jorgensen’s (1982) estimate of 0.001 grams P kcal'l. Since 75 y ■ 0.0000137x * .062, r .87 Total Phosphorus, 100,000 ' 200,000 ' 300,000 ' 400,000 a .. a n m .< Figure 25. Regression and equation used to calculated phosphorus concentrations during a given inflow. plankton could discharge to the lake when outflow was positive and the beach was open, this provided another mode of exporting phosphoms. Plankton take phosphorus from the water storage, hold it in biomass, then release It to either the sediments or Lake Erie. This model utilizes one phosphorus storage in the waters of the wetland and another in the sediments, with a linear pathway between the two. The phosphorus model includes resuspension and sedimentation velocities as defined for a shallow lakes by Kamp-Nielsen (1983) and Henderson-Scllera (1984). Calibration was done by varying the resuspenslon coefficient (s2) - until the model predicted results similar to field data on phosphorus concentrations (Figure 25). Field phosphorus data results are compared to the model results in Figures 24d and 26. Data were not available for the high inflow times during March and April storms, but the simulated data are consistent with what is known about phosphorus flow in Lake Erie tributaries with agricultural watersheds (Baker 1988). Total phosphorus data was variable in 1988, but the average concentration follows the pattern predicted by the model (Figure 24d). Figures 26 and 27 summarize phosphorus dynamics for calibration simulations of 1988 conditions. Although resuspension and sedimentation have no field data check, if they were incorrect we would expect to find an anomaly in some other portion of the model. No such anomaly can be found. All other simulation results are consitent with the previously mentioned assumptions about phosphorus flow in the wetland. 4.6.4 Other simulations The hydrologic budget indicated that inflow, Lake Erie level, and the barrier beach are the most important factors determining the volume of the wetland. Therefore, it is appropriate to change these parameters to predict wetland functioning for a period other 77 40000 30000 1 resuspension 2 sedimentation g-P/day 20000 10000 130 198 267 33S Time, days 1 Mar * Apr * May * Jun * Jul * Aug * Sep * Oct * Nov ^ Figure 26. Resuspension and sedimentation predicted by the calibration model. 78 8 0 0 0 0 0 :, 600000 : 200000 : 600000 : g P d ‘ 400000 TP_Oulllow 200000 Conc_TPJn_Walcr gP m *3 2 80000 1 12000 1 Resuspension 2 20000 2 Scdimcntation_TP 1 3000 130 198 267 335 Time, days Figure 27. Simulation results showing phosphorus inflow, outflow, concentration, resuspension, and sedimentation during 1988 hydiologic conditions. 79 than the 198S drought year. Five additional simulations were run: 1) low inflow/high lake level • 1988 inflow with Lake Erie 0.25 meters higher than 1988 levels 2) normal inflow/average lake level • normal inflow with 1988 Lake Erie levels 3) normal Inflow/high lake level • normal inflow with Lake Erie 0.25 meters higher than 1988 levels 4) high inflow/average lake level -125 % of normal inflow with 1988 Lake Erie levels 5) normal inflow/high lake level - 125% of normal inflow with Lake Erie 0.25 meters higher than 1988 levels Since inflow had the greatest effect on volume, a number of the additional simulations were run with an increased inflow. Normal and high inflow conditions are not known because the USGS flow gauging station did not begin operation until October of 1987; therefore, flow was estimated from USGS data for Rock Creek in 1986. Based on watershed size, average flow In Rock Creek was used in the 125% of normal inflow simulations. Normal inflow was considered to be 75% of Rock Creek 1986 flows. In simulations 1,3, and 5, Lake Erie was raised 0.25 meters to make it representative of some historical high water years. Outflow was also varied from the calibration model, which utilized 1988 beach data. The level of the lake was assumed to have no effect on the opening or closing of the barrier beach (Dave Klarer, pers. comm.). Unlike 1988, when the beach closed in May, the beach usually stays open until mid-July-when it closes but can still be "blown” open by strong storms. Simulations with normal and high inflows were altered by opening the beach until mid-July, then leaving it open for the duration of storms, and closing it again within three days, to reflect the observed phenomenon. 80 4.6.4.1 Low inflow/high Lake Erie levels In this simulation, the inflow remained the same as in the calibration model, but Lake Erie levels were raised. This means that the inflow of phosphorus was exactly the same in both models. The results of this simulation are shown in Figures 28 and 29. The immediate c fleet was a raising of the annual average wetland water level about 0.1 meters above 1988 levels. This translates to almost 57,000 of extra water in the marsh, on average. Biomass of macrophytes was reduced 17% due to a decrease in suitable habitat Although the water levels were too high to allow the maximum growth of macrophytes, planktonic productivity and chlorophyll Increased because 62% less were exported to the lake. This was due to outflow being significantly reduced as it was less common for the level of the wetland to be higher than that of the lake (the only situation in which wetland water could be released). Although it might be assumed that these conditions would increase phosphorus concentrations in the marsh, since very little flowed out, this was not the case. More phosphorus did remain in the marsh (almost 8% more was retained than in the 1988 simulation), but this was diluted by the extra volume of water. Concentrations are closer to those In the lake diluting it, although the model does not attach any phosphorus to Lake Erie inflow. The deeper water was also not conducive to resuspension, which was less than half of the 1988 conditions, although it showed a similar seasonal pattern. Sedimentation was about 38% lower than in 1988. Most of the reduction in sedimentation was during the later part of the season, since it was almost the same as 1988 levels until mid-June. This was caused by lack of incoming phosphorus coupled with high water levels. 81 440000 ' 330000 ' mi 220000 110000 Inflow 400000 ' 200000 outflow m3 0.0 ‘ IJIM *200000 o p e n jo ja k c 1*2 5.00 2 Welland Level 1 3.13 1 Lake Erie 2 3.50 200 t2 150 Macrophytc_Biomass 120 mg m*^ 90.0 chIorophyll_a 198 Time, days ______ I Mar I Apr I May I Jun I Jul I Aug I Sep I Oct Inov I Figure 28. Simulation results of inflow, outflow, planktonic biomass, and macrophyte biomass during a period with 1988 inflow rates and high Lake Erie levels. Middle plot indicates days when barrier beach was open. 82 800000 ' 600000 * gP d 400000 ' 200000 ‘ Total_P_Inflow 800000 600000 gP d‘ TPjOulflow 400000 200000 gP m Conc_TP_in_Waicr 2 80000 I 12000 gP d 1 Resuspension 2 20000 1 3000 2 SedimentationJTP 130 267198 Time, days Figure 29. Simulation results for phosphorus inflow, outflow, concentration, resuspension, and sedimentation during a period with 1988 inflow rates and high Lake Erie levels. 83 4.6.4.2 Normal inflow/1988 Lake Erie levels This simulation utilized the same Lake Erie levels as the 1988 calibration simulation, but inflow was increased, and the barrier beach was open almost twice as long. This had dramatic changes on the functioning of the marsh (Figures 30 and 31). There are five large storm events instead of two, and inflow never falls to zero. Since phosphorus is linked to inflow, this resulted in over 2000 kg more phosphonu entering the marsh than under drought (1988) conditions. Most of this was input came during storm events. The simulated average depth is nearly the same as those of the calibration model during the beginning of the simulated season. Afler the beach closed, levels reached up to almost a meter above 1988 levels until the barrier beach opened and allowed water to flow out. This resulted in Increased water levels during the growing season, and subsequently caused a 14% decrease in macrophyte production. Planktonic productivity and chlorophyll decreased because 32% more plankters were exported to the lake during the periods that the beach was open. Twenty percent more phosphorus was exported to the lake than In 1988 because the outflow was open for a greater portion of the simulation season; however, total retention was much greater because of the increased quantity entering the marsh. On average, the concentration of phosphorus was twice as high. Resuspension was much more dramatic in its fluctuations because of the unstable water level changes that occurred during storms and when the beach opened and closed. Resuspension was almost as high as 1988 calibration levels during the beginning of the year, when water levels were similar. However, when the depth increased; resuspension values plummeted. The exception was during periods late in the year, when volume decreased afler storms blew 84 440000 Inflow 330000 m3 220000 I10000 jl >«brA 400000 A outflow 200000 0,3 0.0 i j h ^ : •200000 o p c n jo ja k e i _ a A 1 -2 5.00 2 WcuandLcvcl 1 3.13 I Lake Eric 2 3.50 Macrophytc_Biomass mg m 3 90.0 chlorophyll_a 198 Time, days ______I Marl Apr | May I Jun | Jul | Aug I Sep I Oct I Nov I Figure 30. Simulation results of inflow, outflow, planktonic biomass, and macrophyte biomass during a period with normal inflow. Middle plot indicates days when barrier beach was open. 85 800000 ] 600000 j TotaLPJnflow gPd*l 400000 1 200000 1 800000 1 600000 ' TP_OuUlow 400000 1 200000 • Conc_TP_in_Watcr A_ a _ 2 80000 1 12000 1 Resuspension 2 20000 Sedimentation.’ 61 130 198 267 335 Time, days ______ I Marl Apr I May I Jun I Jul I Aug I Sep I Oct Inov I Figure 31. Simulation results for phosphorus inflow, outflow, concentration, resuspension and sedimentation during a period with normal inflow. 86 open the beach. This initailly resulted in lower water levels, therefore resuspension would increase for the period of time that the levels were kept low. 4.6.4.3 Normal inflow/high Lake Erie levels This model simulates the combined effects of normal inflow and high Lake Erie levels. Like the previous model, inflows were increased and the barrier beach was left open much longer than in the calibration model. Further, the lake was raised 0.25 meters. The resultant simulations illustrate the combined efTects described in the previous two simulations (Figures 32 and 33). Marsh levels show a dramatic Increase throughout all portions of the simulated year. The average volume was nearly triple that of the calibration model. This resulted in a 29% decrease In macrophyte productivity. However, the amount plankton exported to the lake was 29% less than in the calibration model because the increased lake levels inhibited outflow more than the increased inflow raised the average depth in the marsh. Sedimentation averaged 18% less than in 1988, but during the periods the beach opened (later in the simulation year) it was able to meet 1988 levels. When the beach opened at the end of the simulation period there was a dramatic increase in sedimentation. Resuspension also Increased when the beach opened, but remained low during high water level periods. Total sedimentation was 35% less than the 1988 calibration simulation. 4.6.4.4 High inflow/1988 Lake Erie levels This model simulates the efTects of high inflows, similar to those that might be found during a year of high rainfall, coupled with normal lake levels. As with the normal inflow simulations, the barrier beach is lefl open to reflect the increased hydrologic 87 m 440000 1 m 330000 m3 m 220000 110000 A Inflow 400000 200000 outflow m 0.0 lA ' •200000 opcn_to_Iake \ f\ A 1*2 5.00 1 2 WctlandJxvd 4.38 4.50 m ■ 1 3.13 1 Lake_Eric 2 3.50 200 -2 150 g m Macrophylc_B iomass 100 50.0 120 mg m ' 90.0 60.0 30.0 61 130 198 335267 Time, days ______I Mar I Apr I May | Jun | Jul I Aug I Sep I Oct I Nov I Figure 32. Simulation results showing inflow, outflow, planktonlc biomass, and macrophyte biomass during normal inflow and high Lake Erie levels. Middle plot indicates days when barrier beach was open. 88 800000 600000 gPd-l 400000 TotalJ*Jnflow 200000 ..A, 8 0 0 0 0 0 « ^ 600000 \ 8?d 400000 1 TPjOutflow 200000 j 4 • 3 • Conc_TPJiuWaicr gP m*3 2 . 1 ■ 2 80000 1 12000 1 Rcsuspenslon 2 Scdimcnauion_TP 2 20000 1 3000 61 130 198 267 335 ______Time, days ______I Mar| Apr | May | Jun I Jul | Aug I Sep I Oct I Nov I Figure 33. Simulations results for phosphorus inflow, outflow, concentration, resuspension and sedimentation during normal inflow and high Lake Erie levels. 89 loading not accounted for in the drought simulations (Figures 34 and 33). This simulation had six substantial storm events. These were often during periods of not only increased inflow and phosphorus loading, hut outflow and plankton export as well. The total amount of phosphorus entering the marsh was 43% greater than during a normal flow simulation and almost 61% greater than 1988 calibration results. This was partially offset by the increased outflow, which was generally more than twice as great as in any of the previous simulations. While significant quantities of phosphorus are being imported and exported at the beginning and end of the growing season, a large quantity is being deposited during these same periods, as well as coincident with each storm. Sedimentation was twice as great as any of the previous simulations. Planktonic productivity was greatly reduced during the periods of high outflow. Almost 44% more planklcrs were exported than under the 1988 simulation model conditions. The high inflow created an average volume about the same as that of the calibration simulation under high lake levels. Similar to that simulation, macrophyte productivity was also reduced. 4.6,4.5 High inflow/high Lake Erie levels This simulation has high inflow conditions as with the previous simulation, coupled with high Lake Erie levels (Figures 36 and 37). The mean depth was almost 0.3 meters higher than that of the calibration simulation and was 0.03 meters higher than the any other simulation. The Increased marsh water levels left very little suitable habitat for rooted aquatic macrophytes, and the macrophyte biomass was 44% less than that In the calibration simulation. Although large quantities of phosphorus were brought in with the high inflow, these tended to be diluted by the enormous volume created by the combined effects of high lake levels and high inflow. Sedimentation and resuspension were similar 90 440000 * Inflow 330000 ' ra3 220000' 110000 ' 400000 ' 200000 1 m 0.0 ' pvw. i\ T ” J - A -K; •200000 4 opcnjojalcc \ f \ l\ 1 1-2 5.00 1 4.38 lWcdamUxvd a s A 4.50 * m 1 3.13 1 LakcJEric 2 3.50 ' ■ » 200 ' „ «*2 150 ■ Macrophylc_B iomass — 8 m 100 50.0 ■ 120 ' m g rn ^ 90*0 ' chlorophyll_a 6 0 0 ■ 30.0 ' 61 130 198 267 335 ______Time, days______fTtoTrA^T^>ta7T-juirT_Jui I Aug I Sep I Oct I Nov I Figure 34. Simulation results of inflow, outflow, planktonic biomass, and macrophyte biomass during a period of increased inflow. Middle plot indicates days when barrier beach was open. 91 800000 600000 400000 gPd* 200000 800000 600000 gPd* 400000 TPjOudlow 200000 4 3 gP m" 2 Conc_TP_in_Waicr 1 2 80000 1 12000 1 g P d ' 2 20000 1 3000 Sedimentation^ 61 130 198 267 335 ______Time, days ______I Mar I Apr I May I Jun I Jul I Aug I Sep I Oct I Nov I Figure 35. Simulation results for phosphorus inflow, outflow, concentration, resuspension and sedimentation during a period of increased inflow. 92 440000 , 330000 A 3 I Inflow m 220000 110000 i 400000 1 outflow 200000 ‘ m 0.0 IklUL J IfL: •200000 opcn_to_lakc L_/l A 1 -2 5.00 i 1 LakcJ-jic 1 3.13 2 3.50 •2 150 Macrophytc_B iomass 50.0 . mg m chlorophyllji 198 267 Time, days ______f M arl Apr | May I Jun | Jul [A u g I Sep I Oct I Nov I Figure 36. Simulation results of inflow, outflow, planktonic biomass, and macrophyte biomass during a period of increased inflow and high lake levels. Middle plot indicates days when barrier beach was open. 93 800000 600000 Total_P_lnflow g P d 400000 200000 800000 600000 g P d 400000 200000 Conc_TPJn_Watcr gP m‘ 2 80000 X 12000 1 Rcsuspcnsion 2 20000 2 Sedimcntation_TP 1 3000 130 267 335 Figure 37. Simulations for phosphorus inflow, outflow, concentration, resuspension and sedimentation during a period of increased inflow and high lake level. 94 to the other high inflow simulation, with the exception of being slightly lower in sedimentation and slightly higher in resuspension. Outflow was significantly reduced because of the high lake levels compared to the high inflow/normal lake levels simulation, but were still higher than that of the 1988 calibration model. This simulation retained more phosphorus of any of the simulations, but also had very low primary productivity values. CHAPTER V DISCUSSION 5.1 Primary productivity The high planktonlc productivities in Old Woman Creek, measured by field data and simulated in the models, can be attributed to high nutrient concentrations and optimal depths. Old Woman Creek has a relatively productive planktonlc population, with an annual average gross primary productivity or about 366 mg C m'^day**, and a peak average chlorophyll a content of almost 120 mg m’3. For comparison, an extremely productive aquatic ecosystem fixes about 1,000 mg C m^day* 1 and averages 125 mg m*3 of biomass measured as chlorophyll a, while a productive planktonlc community fixes about 500 mgCm’^dayl and averages 15 mg m’3 of chlorophyll a (Hall and Moll 1975; Wetzel 1983). Since the Old Woman Creek wetland usually remains deep enough to inhibit aquatic macrophytes, yet shallow enough to encourage resuspension of nutrients, it is well designed for algal growth. Unlike many other inland freshwater marshes, the wetland is not dependent on continuous inflows of nutrients, probably because of the extensive resuspension. The field results did not show a correlation between biomass measurements (as chlorophyll a) and whole system metabolism measurements of planktonlc productivity. The differences may be attributable to changes in community structure that occur as the 95 waters warm and cool, and as the nutrient and sediment loads change. Planktonlc productivity is high during the initial diatom blooms in Old Woman Creek wetland as the water begins to warm. Throughout the summer, productivity appears to be limited only by the length of the day, and the shallowness of the wetland. Since the waters are tuibid, photoinhibition is probably unimportant. Significant changes, however, must be occurring in the planktonlc community structure. For the majority of the growing season, the wetland is dominated be small green flagellates and Euglcnas, suggesting that climax communities never form, or that nutrients are in such great supply that reproduction continually exceeds losses. This would explain why chlorophyll a values do not correlate with whole system metabolism values. As the community moves from diatoms or cyanobacteria to green algae, the chlorophyll a concentration Increases, but the gross primary productivity may not. Community structure Is also affected by changing hydrologic conditions. For example, Kreiger(1985) noted dramatic changes in planktonlc population assemblages of Old Woman Creek wetland throughout the growing season, especially during storm events when the barrier beach was open to the lake. If open to the lake, the wetland could contain some lake species near the mouth. When strong storms surged through the wetland, most the plankton were exported, allowing new succesional species to dominate. Also, when the barrier beach was open, he found a large number of lake plankton species in the wetand water ajacent to Lake Erie. Klarer (1988) also found that during storms, the plankton populations of the wetland were almost completely flushed out into the lake, allowing the establishment of pioneer communities. This phenomenon was noted in my model simulations, which Illustrated that this planktonlc flushing lowered the overall chlorophyll content of the wetland, and increased the amount of phosphorus exported to the lake. 97 The presence of macrophytes did not appear to alter productivity in the water column, even though they covered a significant portion of the wetland (23%). Those sites In or near N dum bobcds did not vary greatly in their diurnal productivity from the other sites. In fact, site 5, which was in the edge of a patch of N c lumbo, was ofien the most productive. This site was in a relatively shallow portion of the marsh, and had abundant substrate for periphyton, especially diatoms and protozoans. It may be that epiphytic communities attached to the macrophytes were responsible for increased productivity at site 5. The model shows that a drop in the average water level of the wetland results in an increase in macrophyte biomass. If average water levels in the marsh drop and cause an increase in emergent macrophytes, it should also result in additional substrate for the periphyton, and could result in increased water column productivity. Although Old Woman Creek wetland is relatively productive on a planktonlc basis, it lacks the higher overall productivity values that can be obtained in marshes where different types of vegetation are prevalent. Typha, Sdrpus, and similar wetland plants may have up to 5 times more biomass at peak harvest than did the N dum bo harvested at Old Woman Creek (Westlake 1963, Good etaL 1982). This makes sense when one considers the nature of N d u m b oa large - flat photosynthetic surface oriented horizontally is not as efficient at gathering solar energy, per unit area, as a surface placed at an angle to the sun. The productivity for many common wetland plants usually averages around 500 g dry wt m’2 y r 1 (Westlake 1963; Good ctaL 1982). On the low end of the scale are water lilies, another large flat leaved plant, which ranges around 250 g dry wt m‘2yr*l (Good c t a l 1982). Old Woman Creek N dum bobcds arc approximately 60% as productive as this benchmark. A N dum bo- based wetland, presumably created by high water levels, will never have the macrophyte productivity 98 characteristic of many other types of wetlands where emergent plants with high biomass to area ratios, such as TyphamA Sdipus, dominate. Due to the extensive size of the Nclumbobcdx, and the variability of nutrient concentrations In different leaf size classes, macrophyte productivity was measured using both the standard method of harvesting at peak biomass (Vollenwelder 1974), and a new transect method. The transect method is more time consuming, but it has several advantages: 1) It is much easier to take into account a larger sample size; 2) It allows a more accurate determination of total nutrient retention by allowing the research to correct for different age and size classes of leaves; and 3) it is much less destructive to the ecosystem, especially if multiple sampling is to be done throughout the year. This method could be used for any wetland plant community where the leaf area index is known. 5.2 Limiting factors to primary productivity A number of assumptions have been made about what limits planktonlc productivity in Old Woman Creek. For instance, Heath (1987) examined phosphorus availability and found no evidence that it was ever in short enough supply to limit algal growth. Since there is abundant agricultural ninofT, nitrogen should also be in abundant. Some researchers have suggested informally that light is the limiting factor in Old Woman Creek wetland. Some evidence supports this theory; however, a number of other factor affect the amount of light In the euphoric zone. The shallow zones, especially those near macrophyte beds, tended to have moderate productivities. Productivity in the zones directly in the N dum bobcds was often low, suggesting that shading was inhibiting photosynthesis. It may be that depth and macrophyte shading are the limiting factors to planktonlc productivity. The effect of 99 shading is not discemable from my data because no samples were taken from the middle of a Nclumbobcd, only from the edges. The deepest zones showed the highest diurnal productivities (Figure 38a)t suggesting that productivity is limited by high tubldity since the most tuibid zones were shallow. This Is misleading, because the assumptions of productivity calcuatlons use depth as a factor. The importance of depth, light, and tubldity on limiting productivity cannot be scperated, since they are all Interrelated. The optimal tubldity for planktonlc productivity is between 250 and 450 FTU, which usually occurs at depths greater than 40 cm. Both high and low turbidities show a limiting effect (Figure 38b). There is an assumed Inverse relationship between depth and resuspension in the model (Kamp- Nielsen 1983), although the turbidity data do not support this (Figure 38c). However, turbidity does appear to affect productivity, because low tubldity limited productivity, perhaps a nutrient limitation (Figure 38b); however, this may be because the decreased volume at low depths limit the total number of plankters that con live In these zones. Perhaps photoinhibition is occuring at low tubldities, and at high turbidities no light can penetrate. On a volumetric basis, as measured by chlorophyll a, productivity is slightly limited in the deeper portions of the marsh. This supports the modeled assumption that rising and falling average depths would not signiflcantiy alter overall planktonlc productivity. However, if depths were increased greatly, turbidity and planktonlc productivity should decrease as the wetiand became more lake-like. Depth may be the ultimate limiting factor to macrophyte productivity (Figure 39). Since there are a number of wetlands nearby or adjacent to Old Woman Creek with aquatic macrophytes, such as Typha, Sdipus, Caicx, Pontedcria, and Sggittaiia, it can be assumed that there is a sufficient seed bank for these plants to establish if the proper 3 .4 depth cm b) <8 16 100 200 300 400 500 600 TUibidily, FTU c) £s 200 .3 .4 depth cm Figure 38. Relationship between a) diurnal productivity and depth; b) diurnal productivity and turbidity, and c) depth and turbidity. Lines on graphs represent the best fit of a second-order polynomial regression. 101 100 % Cover MACROPHYTE! 1988 198 0 0.2 0.4 0.6 0.8 0.9 1.0 averge depth, m Figure 39. Suggested changes in importance of macrophytes and plankton in Old Woman Creek wetland under varying average annual depths. 102 conditions existed. However, it is normal for the marsh to have average depths of almost one meter for the majority of the growing season. Since this is too deep for most of these plants, they do not germinate. Further, the constant stirring of the sediments by benthic fish and wind could hinder the establishment of macrophytes. When the marsh is shallower, more macrophytes do establish (Marshall and Stuckey 1974). This phenomenon was also evidenced in the sediment core. The zone of peat formation, mostly due to Scirpus, must have occured under lower lake levels. It could be concluded that low average depths favor macrophytes as the dominant primary producer, and that deep average depths favor planktonlc primary producers. There may also be inhibition from bloddes that come in with the non-point pollution. Krieger(1984) and Baker (1985; 1988) found high concentrations of herbicides in streams with similar agricultural watersheds in northwestern Ohio. However, due to their short half-life, It is unlikely that they persist in great enough quantities, or for a long enough time, to have an appreciable eflect on productivity. 5.3 Role of primary producers in phosphorus cycling The high productivity of Old Woman Creek suggests that it would act as a nutrient transformer. There Is oflen a significant decrease in conductivity and bioavailable phosphorus as water passes through the marsh. Some of this is due to dilution by Lake Erie waters when the beach is open; however, during the majority of the year this is attributable to direct sedimentation and the subsequent burial of nutrients. The mass balance and model show that a significant quantity must be taken in by the primary producers, then buried in the sediments. Low values of soluble reactive phosphorus during the growing season suggest most of this readily available form of phosphorus is bound in biomass. This is supported by the fact that the times of greatest biomass 103 (chlorophyll) arc the times of the largest reduction in total dissolved phosphorus. Although the models did not separate phosphorus into bioavailable and nonbioavailable forms, they do show some of the effects of the primary producers on nutrient retention. During 1988, more than 30% of the net sedimentation of phosphorus was estimated to be due to plankton cells. During times of greater hydrologic input, the importance of plankton to the permanent burial of phosphorus was diminished, but it always accounted for at least 27% of the gross sedimentation. This suggests that large quantities of the bioavailable phosphorus entering the marsh arc converted to plankton biomass. During times of low flow, it may be the most significant contributor to the burial of phosphorus. The model simulations also showed that a portion of the outflowing phosphorus was bound in plankton. However, since the marsh was usually closed to the lake by the barrier beach during the most productive periods, this amount was not very significant At best, it represented 4 % of the total phosphorus outflow. Macrophytes also took up a large quantity of phosphorus. Average uptake of phosphorus from all wetland sediments ranged from 0.15 mg P m '^yr 1 at low water levels to 0.10 mg P m*2yr 1 at high water levels. Most of this uptake was returned to the sediments. The mqjor contribution of the macrophytes may be to pump nutrients from the sediments, and release them back to the sediments during the death and decay process. This may also result in macrophytes releasing some of the mined phosphorus to the water. 5.4 Role of recent sedimentation in phosphorus cycling The key to the ability of wetlands to act as phosphorus sinks is not in their transforming abilities, but their ability to permanently bury incoming nutrients. In 104 wetlands where peat Is accumulated, the obvious mode of phosphorus removal is by phosphorus collection in the biotic matter. In systems where inorganic sediments are dominant, Incoming nutrients bound on sediment particles tend to be permanently burled. The sediment data show that Old Woman Creek is predominantly a sediment accumulating, not a sediment exporting, system. This is to be expected, since the ability of slow moving wetland water to suspend sediments Is much less than the rapidly moving Incoming stream water. For this area of the United States, the increase in concentrations of A m brosia pollen at a depth of 131 cm probably marks about 180 Years Before 1988 (YBP). This translates to an average sedimentation rate of 0.73 cm y r 1. Deforestation of the watershed had a drastic effect on the marsh. As marshes and forests upstream were channelized, the velocity of the Old Woman Creek increased due to increased (low and Intensity. In addition, the soils once held by vegetation were now being eroded and carried Into the fast flowing waters. As a result, the wetland began to fill with sediments which settled In the low energy waters of the marsh. The sedimentation rate Increased an order of magnitude over pre-settlement times. These changes, coupled with rising marsh levels (due both to lake level rise and increased inflow) changed the marsh from a Sc//pus dominated system (which deposited peat) to the current marsh communities. Lake levels must have been lower than present averages at the time of peat formation, and/br some barrier must have protected the marsh. Since deforestation, productivity in the wetland has remained high and the deposition rate of phosphorus and the percentage of phosphorus which is bioavailable has increased. During the time of peat formation, little bioavialable phosphorus is found. Presumably, the macrophytes and plankton were transforming almost all of the 105 bioavailable phosphorus into organic matter. As peat formation stopped and sediment loading increased, the ability of the marsh to work as a biotic transformer diminished, but its abiotic ability to permanently bury all the phosphorus forms Increased. In fact, on an annual basis, thirty times more phosphorus Is buried now (8.0 gP m*2 y r I) than when the marsh was forming peat (0.27 gP m*2 yr*). However, the peat zone of the core may not be a complete stratigraphy. Everett (1988) shows that the Scf/pus histosols, such as the one found in this core, should deposit at about 1 cm y r *-*more than an order of magnitude more than the rate found. If deposited in the same concentrations as the peat zone of the core, Everct’s depostion rate would translate into 6.1 gP m*2 y r * being deposited in a peat forming Old Woman Creek wetland. The low sedimentation rate found In the peat zone (0.27 gP m*2 y r *) could be explained If the lake level Increases periodically scoured portions of this peat from the marsh. This may have occured, since at one time the Lake Erie shoreline extended to the point where the sediment core was taken.. 5.5 Geologic history of Old Woman Creek The long sediment core allowed the examination of the Old Woman Creek area not only in terms of sedimetation rates, but also in terms of pollen rain, climate, and water level changes. The first part of the geologic study involved accurately defining time in order to determine sedimentation rates. The Am brosia rise is a definitive marker for recent sediments, but C*4 data was used for older material. Since glacial till was not reached during coring, it is presumed that the core data represents post glacial events. No erosional event, except for the possible scouring of the peat, is discernible from the core. C*4 dates show no inversions and line up to show an even sedimentation rate; however, the bottom 3 dates were taken from large samples (up to 350 g), and none 106 yielded more than O.S g of carbon. Buchanan (1982) came up with a sedimentation rate of0.076 cm y r * in a simitar zone with a date taken from a piece of wood. The sedimentation rate in the present study is much slower (0.02 cm y r I) and the cote is much older. However, the sedimentation rate obtained when only samples with a high carbon content are used for dating Is 0.064 cm y r 1, which is nearly the same as the rate rate obtained by Buchanan. The older dates may be in error since they suggest that pollen could be deposited during a number of glacial maxlma-when the area was covered by a glacier. Further, a fairly decent zonation pattern in vegetation described by Shane (1987) is completely absent. When placed in a standardized (low chart to determine the validity of C*4 dates in this area (King 1985), the dates fail to meet criteria for acceptance. A number of explanations for Inaccurate dates can be given: 1) with such a small amount of carbon, even a slight contamination from older carbon (it Is a limestone watershed) could significantly alter the results; 2) there is a probability that plankton were processing older carbon, which could skewed the results significantly; and 3) due to extensive glaciations in the area, the deposited sediments may have been old. Using the accurate dates, the bottom of the core Is about 9,560 radiocarbon years before present (RCYBP). The clay in the bottom portion of the core represents post glacial lake bottom. The sediments are very similar to Lake Erie's (Herdendorf, pets, comm.) and an oxidized shallow lake (near shore area) could account for the poor deposition of chlorophyll degradation products and pollen. It is obvious that the first trees to forest the area were Acer, Qucrcus, and Caiya. Conifers came in shortly afterwards, possibly due to some climatic cooling. The oldest zones (just after gtadation) are dominated by aquatic macrophytes, which would also be indicative of a shallow lake nearshore zone. 107 It could be surmised that the changes that occurred in ancient lake levels were not gradual, but fast and drastic. From this core I disagree with the post-glacial lake levels suggested by Coakley and Lewis (1985) and Herdendorf and Bally (1989) (Figure 40). If the interactions of the wetland and the barrier beach were better understood, the core may be shown not to be predicting lake levels, but showing an indication of some sort ofhydroiogic interaction between the lake and the wetland. An interesting phenomenon is that even under heavy sediment loading, the marsh remains a wetland and does not fill in. This has been observed under the drastic lake level fluctuations of the past 15 years. Some hydraulic equilibrium must be maintained as pollen shows it to remain wetland, and the steep eroded edges of the marsh indicate that it has existed under higher water levels (probably when drowned further by high Lake Erie levels). 5.6 Hydrology and phosphorus cycling The year of this study had a significant drought throughout the summer; however, it was the first year that inflow rates were measured. The availability of inflow data, fairly good data on evaporation, and knowledge of the hydrologic forcing functions in the wetland allowed the development of an accurate hydrologic budget and model. The most important part of the budget is determining the interactions of the beach with the wetland. I have observed periods when the level of the wetland was a meter or more above the level of the lake, yet still the beach held back the wetland water. This observation by me and others had resulted in a theory that the beach was nearly impermeable. However, even during a drought year, when the wetland level is not creating a large hydraulic head against the barrier beach, there may be some outflow through the primarily sandy beach. 108 225 Author Coakley and Lewis ■ 200 Meters above Sea Level 175 HenJendarf and Bailey 150 125 i i i i i i i i i —i i 10 9 8 7 6 5 4 3 2 10 3 Years Before Present X 10 Figure 40, Post glacial Lake Erie levels as determined by this study, Herdendorf and Bailey (1989), and Coakley and Lewis (1985). Modified Bom Herdendorf and Bailey (1989) 109 The beach does, however, act to keep water levels constant within the marsh. During 1988 the beach closed early In the year, allowing most of the inflow to be retained. This allowed the wetland to remain aquatic, even through a significant drought. During storms the beach opened for short periods of time, allowing the excess volume to be released to the lake, then it closed again to prevent desiccation. These processes may provide the key to why the area that is now Old Woman Creek wetland has remained a marsh despite rapid sedimentation rates over the past 200 years. The various model simulations provide an indication of how the wetland functions under various hydtologic loading rales. The model simulation reflecting the low inflow conditions of 1988 had the worst retention rate (Table 6). Raising the lake level has a positive effect on retention rate. When the lake is higher than the wetland, even if the beach is open, no water will flow out. The lake could be thought of as acting as a dam to inflowing water. Additionally, if the lake is higher than the wetland and the beach is open, the quantity of phosphorus in the wetland is diluted. This model prediction was observed in the field during March and April of 1988. Increasing the inflow also had a positive effect on retention rates of phosphorus to a point. This effect however was diminished if phosphorus inflow rates were increased above normal because the storms were of a magnitude beyond the capacity of the marsh to retain the water. This resulted In very rapid turnover times, and most of the inflow went quickly into the lake, without settling in the marsh. Again, this is consistent with what would be expected. The retention during both normal and high inflows could be increased by increasing the lake levels. During the situations where both phosphorus inflow and the lake level were increased, over 50% of the Incoming phosphorus was retained in the marsh. Table 6. Comparison of phosphorus retention abilities of the various simulation models. Values are in mgP m*2 day* 1. Simulation Total Total Sedimentation Retention Inflow Outflow net plankton % 1988 (calibration) 32.3 26.8 2.6 3.5 17 low inflow; high lake 32.3 20.6 4.6 3.6 36 normal inflow 45.4 33.1 4.7 3.3 26 normal inflow; high lake 45.4 23.6 8.2 3.4 48 high inflow 83.7 63.8 8.4 3.3 22 high inflow; high lake 83.7 39.9 12.4 3.4 51 I l l The model assumes that Increased water levels reduce macrophyte productivity. Lowering water levels should be beneficial, but since the macrophyte contribution to nutrient cycling is insignificant compared to sedimentation of plankton, this may be inconsequential. Overall, the changing water level had little effect on planktonlc productivity. More plankton are exported during strong storms when the lake is open to the wetland, but they recover quickly. 5.7 Evidence that Old Woman Creek is a phosphorus sink Figure 41 contrast rates of phosphorus retention in Old Woman Creek using an empirical model, the field data from this study, and the simulation model from this study. The balance using an empirical loading retention model of Richardson and Nichols (1985) (Figure 41a) predictions results in 8*13 mgP m '^dayl being permanently buried in the marsh sediments under standard loading rates for Lake Erie watersheds estimated from Johnson et al.(1978), UC (1980), and Novotony (1986). This estimate does not take into account any of the interactions between Lake Erie and the wetland, or any intrasystem interactions. The mass balance predicted from the field data (Figure 4 lb) has a much lower loading rate, because the flow rate did not affect the concentration of phosphorus coming into the marsh, and because the data reflect drought year conditions. However, retention was still 36%, which is nearly the same as predicted by the Richardson and Nichols (1985) model. This balance also indicates that the contribution of Lake Erie to phosphorus loading to the wetland is minimal (0.41%). The field data balance suggest that a large portion (64%) of the inflowing phosphorus Is released to the lake.The effect of the biota on transforming phosphorus into biomass before being exported to the lake 112 Inflow from Lake Erie from W atershed ifTT aedimenlatio flows In mg-P/m 2-day Sediment Accumulado i Inflow from Lake Edo from W atm hei to Lake Erie aedimenlatio flow* In mg-P/m2-day Sediment Accumuliiio t Figure 41. Nutrient budgets for Old Woman Creek as calculated by: a) estimated loading rates from Richardson and Nichols (1985); b) field data estimate for the March 1 - November 30 period of this study; c) sediment core data and d) calibrated simulation model. to Lake Erie Phot] ■vallal tacro] to lake 22 Inflow from W atm h ec \^V10,4 srocycltWT reiutpcnalo plankton ».S up tak e tedimenu ion ftciivX .Scdimjmt aedimentatii 3 . 5 flowa In ntK>P/m2*da]r Sediment Aocumulatioi Figure 41 (continued). 114 is not discernible in this balance; however, the significant uptake by primary producers suggests that some transformations should be occurring. Actual loading rates or retention must be higher than either the empirical or field data balances predict, because the sediment core shows that an average of 22 mgP m*2day*l has been deposited over the past 180 years (Figure 41c). However, the sediment coring site is in the area of the marsh with the highest sedimentation rate (Buchanan 1982), so this data represents maximum retention. The simulation model takes into account the effects of hydrology on loading rate and predicts the amount of transformation occurring due to the biota, as well as the permanent burial of phosphorus in the sediments (Figure 4 Id). The simulation model predicts that 2.9 mg P m*2 day* 1 is permanently retained-more than the field estimate suggests, but less than the empirical model or the sediment core predicts. As expected, the primary producers transform some bioavaiiable phosphorus into nonbloavailable forms, but this contribution is minimal (2.2%). Other simulations predicted that a maximum of 12.4 mgP m*2day* 1 could be retained in the marsh, especially under high water level conditions. The model estimates are reasonable considering the variability of the data used for comparison, and probably represent the best available estimate on phosphorus cycling in this Great Lakes coastal wetlands, albeit for a year of low precipitation. CHAPTER VI CONCLUSIONS AND RECOMMENDATIONS 6.1 Conclusions The following conclusions are made based on the fleld data and modelling results from this study: 1) Old Woman Creek wetland is sink for some phosphorus throughout the majority of the growing season, although a large portion of the phosphorus passes through the system. 2) Old Woman Creek wetland also serves, to a small extent, as a phosphorus transformer because the planktonic system cycles a portion of the phosphorus input, some of which is exported as plankton biomass. 3) The hydrology of Old Woman Creek optimizes its ability to act as a seasonal phosphorus sink. The outflow is barred from the lake for the majority of the growing season, when nutrient inputs to Lake Erie are of greatest consequence. 4) Paleoecological evidence suggest that the wetland underwent a change in community structure from a macrophytc dominated system to a planktonic system, but still retained the shallow water depths necessary to keep it a wetland for the past 4,000 years. 115 116 5) Long term nutrient retention rates and modelling suggest that Old Woman Creek can continue to function as a phosphonu sink as long as Lake Erie levels do not fall much below 1988 levels. 6) High Lake Erie levels enhance the ability of the wetland to act as a phosphorus sink by barring outflow. 6.2 Recommendations for future research The model and field results suggest that the most important factors for future study of Old Woman Creek lie in sediment dynamics. Determination of resuspension and sedimentation rates under a variety of hydrolpgic conditions would greatly aid in developing a more accurate simulation. Knowledge of the relationship between incoming suspended solid concentrations and inflow stream velocities during both storm events and at base flow would be the flist step to this research. This type of data could be added to the existing submodels to simulate ecosystem processes. The second stage of such a research project would entail the analysis of sediment cores at various portions of the marsh to examine spatial variations in deposition and scouring events since deforestation. The model also shows the importance of the planktonic community in the cycling of nutrients. Radiotracer studies of nutrients and plankton identification and enumeration would prove valuable to further elucidating this relationship. Further research is also needed on what factors limit planktonic productivity. As in any wetland study, a more accurate understanding of hydrologic functions could be beneficial. In Great Lakes coastal wetlands with barrier beaches, the 117 knowledge of the type of flow occurring through the barrier beach is important. It would also be valuable to have more data on the flow characteristics within the marsh. Further research is also needed on the exact mechanisms controlling the formation of the barrier beach and Its interaction with both lake and wetland levels, as well as the chemical and biological activities of the sedlment*water interface. One of the shortcomings of the model is that in its current state it does not accurately simulate the spatial considerations of changing water levels. For instance, the drying up of the wetland, as would occur with extended low inflow and Lake Erie levels, cannot be simulated by the model. This could be remedied if accurate spatial fleld data were available (i.e. GIS analysis), and Incorporated in a revised version of the existing submodels. Them model also does not take Into account the effects of nutrient limitation, 9 but this could also be easily programmed into it if the nature of the limiter and its effect on productivity were known. The model described in this study provides an excellent preliminary tool to aid in the design of wetlands that lie along large water bodies. Further refinement, with additional field data, would greatly aid in determining future freshwater coastal wetland research directives. The remaining coastal wetlands along Lake Erie may prove to be important for the mitigation of nonpoint pollution from agricultural runnoff. Accurate models will be required to determine how wetlands should be designed and built along Lake Erie for controlling nonpoint pollution. LITERATURE CITED American Public Health Association. 1985. 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APPENDIX A HYDROLOGIC AND CLIMATIC DATA FOR OLD WOMAN CREEK WETLAND 133 Dud Inflow R iinfill W etindLerd Mouth Radferioo Enpontfcn Lake Erie m3 3/1/88 31805.7 03000 3 3 9 1 2238 0.000 3 09 3/2/88 342523 0.0000 3.89 1 2209 OjOOO 309 3/3/88 366983 0.0000 4.05 1 2180 . 0.000 4 0 5 3/4/88 31805.7 0.0000 4.17 1 2221 0j000 4.17 3/5/88 342523 0.0000 4 3 2 1 2262 OJOOO 4 0 2 3/6/88 39145.4 0.0000 3.97 1 2303 0j000 3.97 3/7/88 513784 03000 3 3 9 1 2344 OJOOO 309 3/8/88 538253 0.0000 334 1 2385 OJOOO 3.94 3/9/88 538253 0.0048 3 3 9 1 2426 OJOOO 309 3/10/88 440383 0.0000 3.98 1 2467 OJOOO 3.98 3/11/88 31805.7 0.0000 3 3 4 1 2508 OJOOO 304 3/12/88 31805.7 0.0015 4.00 1 2550 OJOOO 4 3/13/88 31805.7 0.0005 3.83 1 2591 OJOOO 303 3/14/88 29359.1 0.0010 3.87 1 2632 OJOOO 3.87 3/15/88 269123 0.0025 3.98 0 2673 OJOOO 3.98 3/16/88 244653 0.0013 431 0 2714 OJOOO 4.01 3/17/88 29359.1 0.0000 4.07 0 2755 OJOOO 4.07 3/18/88 513784 0.0018 4.15 0 2796 OJOOO 4.15 3/19/88 489313 0.0010 4.17 0 2837 OJOOO 4.17 3/20/88 366983 0.0061 4.10 1 2878 OJOOO 4.1 3/21/88 342523 0.0000 4.01 1 2836 OJOOO 4.01 3/22/88 366983 03000 4.02 1 2794 OJOOO 4 0 2 3/23/88 464853 0.0000 3.98 1 2751 OJOOO 3.98 3/24/88 660573 0.0046 3.97 1 2709 OJOOO 3.97 3/25/88 318056.7 0.0226 4.03 1 2667 OJOOO 4.03 3/26/88 222639.7 0.0013 4.01 1 2647 OJOOO 4.01 3/27/88 83184.1 0.0003 3.90 1 2628 OJOOO 3 0 3/28/88 513784 0.0000 4.03 1 2608 OJOOO 4.03 3/29/88 415923 0.0000 4.03 1 2588 OJOOO 4.03 3/30/88 342523 0.0003 335 1 2568 OJOOO 3.95 3/31/88 269123 0.0000 4.06 1 2549 OJOOO 4.06 4/1/88 269123 0.0025 4.03 1 2529 0.003 4.03 4/2/88 269123 0.0000 4.04 1 2631 0.007 4.04 4/3/88 166368.1 03277 4 3 3 1 2733 0007 4.03 4/4/88 1883874 0.0000 4 3 1 1 2834 0 0 0 6 4.01 4/5/88. 636113 0.0000 4.04 1 2936 0008 4.04 4/6/88 415923 03041 4.03 1 3038 0008 4.03 4/7/88 2422114 0.0145 4 3 6 1 3140 0003 4 0 6 4/8/88 1859403 0.0000 4 3 0 1 3241 0.002 4 0 4/9/88 611643 0.0000 4.12 1 3343 0002 4.12 4/1Q/88 415923 0.0000 4.08 1 3445 0003 4.08 4/11/88 31805.7 0.0000 4.13 1 3547 0003 4.13 4/12/88 269123 0.0000 4.18 1 3648 0005 4.18. 4/13/88 234873 0.0000 4.09 1 3750 0005 40 9 4/14/88 198174 0.0003 4.05 1 3700 0 0 0 6 4.05 4/15/88 17126.1 03023 4.09 1 3650 0001 4.09 4/16/88 163923 0.0003 4.08 1 3600 0002 4.08 ro gsssssifjssisj^sissjjcisjssi^sjsussatss-asqsssjgisjsiisiqs^fjaafiasanfjas 5 1 E E Il8ll?ili§iii§lliii|||l8lllll§8iil§i§i|l§§|§i§§ oooooooooooooooooooooooooooooooooooooooooooooocSooo ft i •6 W"> N 1 ; 8 £ MpoOOOOOOOOOOOOOOOOOOOOO ooooooooooooooooooooo III §||3335^5S!^SiSi';Si5iSi=iti^!R^^S^3?aa!saaafifiqt)f!^5!Si^^s?^^^^^5; * E « 9 S : ^§l§ll8lk8888888S88888S8SS8SS8L8 ooooooooooooooooooooooooooooooooooooooooooociooooSS •6 1 I I Date Inflow Rainfall Wetland Level Month Ratation E v^ontkn Lake Erie m3d-l w m above datum l«qpcn kcald-1 m m above datum 6/6/88 1247.8 0.0000 4 2 0 0 5930 0X110 4.19 6/7/88 880.8 0X1000 4 2 0 0 6017 0209 4 2 6/8/88 685.0 0.0000 4 2 9 0 6104 0 206 4 2 8 6/9/88 513.8 0.0000 4 2 9 0 6191 0205 4 2 8 6/10/88 367.0 0.0000 4 2 9 0 6160 0205 4 2 2 6/11/88 2 2 0 2 0.0000 4 2 9 0 6129 0206 4.15 6/12/88 146.8 0.0000 4 2 9 0 6098 0208 4.15 6/13/88 97.9 0.0000 429 0 6066 0209 4;16 6/14/88 24.5 0.0000 4 2 7 0 6035 0210 4.15 6/15/88 0.0 0.0000 4 2 5 0 6004 0210 4.14 6/16/88 0.0 0.0015 4 2 4 0 5973 0207 4.17 6/17/88 0.0 0.0000 4 2 4 0 5942 0206 4.17 6/18/88 0.0 0.0000 4 2 3 0 5911 0 207 4.16 6/19/88 0.0 0.0000 423 0 5880 0209 4.13 6/20/88 0.0 0.0000 4 2 2 0 5848 0 210 4.11 6/21/88 0.0 0.0000 4 2 2 0 5817 0210 4.15 6/22/88 0.0 0.0008 421 0 5786 0211 4 2 5 6/23/88 0.0 0.0023 4 2 0 0 5755 0207 4.19 6/24/88 0.0 0.0000 4 2 0 0 5780 0207 4.18 6/25/88 0.0 0.0020 4.19 0 5805 0210 4.01 6/26/88 0.0 0.0000 4.18 0 5830 0 207 4.15 6/27/88 0.0 0.0000 4.17 0 5855 0 206 4.1 6/28/88 0.0 0.0003 4.17 0 5880 0207 4.03 6/29/88 0.0 0.0000 4.16 0 5905 0206 4.13 6/3Q/88 0.0 0.0000 4.16 0 5930 0205 4.12 7/1/88 0.0 0.0000 4.15 0 5832 0204 4.07 7/2/88 0.0 0.0000 4.15 0 5734 0205 4.07 7/3/88 0.0 0.0000 4.14 0 5636 0 206 4.07 7/4/88 0.0 0.0000 4.13 0 5538 0206 4 2 7/5/88 0.0 0.0000 4.12 0 5439 0207 4.14 7/6/88 0.0 0.0000 4.12 0 5341 0207 4.06 7/7/88 0.0 0.0000 4.11 0 5243 0207 4.05 7/8/88 0.0 0.0000 4.11 0 5145 0208 4.05 7/9/88 0.0 0.0000 4.10 0 5160 0208 4.02 7/1Q/88 0.0 0.0127 4.10 0 5174 0207 3.99 7/11/88 0.0 0.0005 4.11 0 5189 0207 3.99 7/12/88 0.0 0X1000 4.11 0 5203 0206 -4.02 7/13/88 0.0 0.0000 4.10 0 5218 0206 4.08 7/14/88 0.0 0.0000 4.10 0 5232 0208 3.92 7/15/88 0.0 0.0000 4.09 0 5188 0207 4.05 7/16/88 0.0 0.0000 4.08 0 5145 0208 4.01 7/17/88 0.0 0.0018 4.08 0 5101 0207 4.03 7/18/88 0.0 0.0264 4.08 0 5058 0207 4.07 7/19/88 0.0 0.0010 4.08 0 5014 0207 4.04 7/20/88 0.0 0.0109 *4.08 0 4970 0206 4.12 7/21/88 0.0 0.0064 4.08 0 4927 0206 4.04 7/22/88 0.0 0.0013 4.07 0 4883 0206 4.05 7/23/88 0.0 0.0018 4.08 0 4840 0206 4.08 7/24/88 0.0 0.0000 4.07 0 4796 0206 4.02 7/25/88 0.0 0.0041 4.07 0 4753 0206 4.01 Date Inflow Rainfall Wetland Level Mouth Radiation Evaporation Lake Erie m3d-l m m above datum l«otxn ItcaltH m m above datnm 7/26/88 0.0 0.0020 4.07 0 4709 0006 401 7/27/88 0.0 0.0000 4.06 0 4665 0006 4 0 2 7/28/88 .0.0 0.0000 4.06 0 4622 0006 308 7/29/88 0.0 0.0000 4.06 0 4578 0007 308 7/3Q/88 0.0 0.0180 4.06 0 4535 0007 305 7/31/88 8563 0.0000 4.08 0 4491 0006 4 0 2 8/1/B8 146.8 0.0000 4.07 0 4447 0005 308 8/2/88 0.0 0.0000 4.06 0 4404 0006 309 8/3/88 0.0 0.0000 4.06 0 4360 0006 4 8/4/88 0.0 0.0000 4.06 0 4317 0006 4 8/5/88 0.0 0.0033 4.05 0 4273 0005 304 8/6/88 0.0 0.0005 4.05 0 4148 0005 301 8/7/88 0.0 0.0000 4.04 0 4024 0005 309 8/8/88 0.0 0.0000 4.04 * 0 3899 0005 307 8/9/88 0.0 0.0000 4.03 0 3775 0005 303 8/10/88 0.0 0.0000 4.03 0 3650 0006 309 8/11/88 0.0 0.0053 4.02 0 3526 0006 307 8/12/88 0.0 0.0000 4.03 0 3401 0006 401 8/13/88 0.0 0.0000 4.03 0 3343 0006 309 8/14/88 0.0 0.0000 4.03 0 3285 0006 308 8/15/88 0.0 0.0000 4.04 0 3227 0005 401 8/16/88 0.0 0.0000 4.04 0 3168 0005 401 8/17/88 0.0 0.0000 4.03 0 3110 0006 4 8/18/88 0.0 0.0119 4.03 .0 3052 0005 4.05 8/19/88 0.0 0.0020 4.04 0 3087 0004 4.03 8/2Q/88 0.0 0.0000 4.04 0 3122 0004 4 8/21/88 0.0 0.0000 4.04 0 3157 0004 4.01 8/22/88 0.0 0.0089 4.04 0 3191 0004 4.01 8/23/88 0.0 0.0000 4.04 0 3226 0.004 4 8/24/88 0.0 0.0076 4.04 0 3261 0004 4 8/25/88 0.0 0.0000 4.03 0 3296 0004 309 8/26/88 0.0 0.0000 4.03 0 3331 0004 4 8/27/88 0.0 0.0008 4.02 0 3366 0004 309 8/28/88 4403.9 0.0213 4.06 0 3401 0.004 309 8/29/88 1174.4 0.0038 4.11 0 3436 0.004 4.01 8/3Q/88 293.6 0.0000 4.11 0 3470 0.003 309 8/31/88 0.0 0.0000 4.11 0 3505 0004 308 9/1/88 0.0 0.0000 4 .U 0 3540 0003 309 9/2/88 0.0 0.0000 4.11 0 3575 0004 308 9/3/88 415.9 0.0211 4.11 0 3712 0003 4 9/4/88 782.9 0.0076 4.12 0 3849 0003 3.98 9/5/88 3913 0.0081 4.12 0 3986 0002 4.06 9/6/88 146.8 0.0000 4.12 0 4123 0 002 309 9/7/88 0.0 0.0000 4.12 0 4260 0003 3.98 9/8/88 0.0 0.0000 4.12 0 4397 0003 3 08 9/9/88 0.0 0.0000 4.11 0 4534 0004 3 0 6 9/10/88 . 0.0 0.0000 4.11 0 4491 0003 308 9/11/88 0.0 0.0000 4.10 0 4447 0003 3.97 9/12/88 0.0 0.0069 4.10 0 4404 0003 3.99 9/13/88 0.0 0.0000 4.10 0 4360 0.003 309 ^n0000000000000000000000oQOO0OOOO'?'s'S'S'5'S's‘s'S'S'S'2^Sv'S's'S aaaasasaaaaasaaaaiaaaiaaaialaaaasaaaaaaaaaaaaaaaaa§l2g5S9SB SSfiB §Sg3|52B S2§|i|i|||i|i|i§ig|fii||||||S| s ppppppppppppppppp a ooooooooooooooooo a . ■ OOOOOOOOOOOOOOOOOOOOOOOOOOOOOQOOOOOOOOOOOOOOOOOOOO 8 Wr*OMUl88888 3 I o o w u n 322gg883'3 8888SSS3 ts: oooooooooooooooooooooooooooooooooooooooooooooooooo 1 % Ej 9* m oopopoooopoooopppopoppoooooooooooooooooooooooooooo uuuuuwuuuuuuuwuwuwwwwuuuwuuuuuu . S- V* . «<0«'0«'0«<0«<0«'0«'0t0>0v0!0'0«'0'0>0«'0>0>0'ol0'0'0 S2£lS !82S S S S S 3S '823 i u 00 Dub Inflow Rainfall Wetland Level Month Radiation Evaporation Lake Erie ______m 3d-l m m above datum l«opcn Vcald-1 m m above datum 11/3/88 0.0064 0 1963 0.000 3.9 11/4/88 0.0005 0 1881 OjOOO 3.9 11/5/88 0.0371 0 1800 0.000 3.9 11/6/88 0.0028 0 1719 . 0.000 3.9 11/7/88 0.0018 0 1638 0j000 3.9 11/8/88 0.0028 0 1557 0.000 3 S 11/9/88 0.0000 0 1476 OjOOO 3.9 11/10/88 0.0180 0 1395 0.000 3.9 UA1/88 0.0003 0 1420 0.000 3.9 11/12/88 0.0008 0 1445 0.000 3.9 11/13/88 0.0048 0 1470 OjOOO 3.9 11/14/88 0.0000 0 1495 0.000 3.9 11/15/88 0.0000 0 1520 0.000 3.9 11 AO/88 0.0025 0 1545 0.000 3.9 11/17/88 0.0000 0 1570 OXXX) 3.9 11A8/88 0.0000 0 1545 0.000 3.9 11/19/88 0.0020 0 1520 OjOOO 3.9 11/20/88 0.0295 0 1495 0.000 3.9 11/21/88 0.0000 0 1470 0.000 3.9 11/22/88 0.0000 0 1445 0.000 3.9 11/23/88 0.0000 0 1420 0.000 3.9 11/24/88 0.0000 0 1395 OjOOO 3.9 11/25/88 0.0000 0 1345 0.000 3.9 11/26/88 0.0000 0 1295 0.000 3.9 11/27/88 0.0028 0 1245 0.000 3.9 11/28/88 0.0005 0 1196 0.000 3.9 11/29/88 0.0000 0 1146 0.000 3.9 U/30/88 0.0015 0 1096 0.000 3.9 APPENDIX B 1988 WATER CHEMISTRY DATA 140 141 Sits jH conductivity turbidity chlorophylls ToulP SRP TSP TSS |imhos/cm FTU mg/nd |i f / L |n/L p * /L m |/ L 1*A pr-88 1 8 3 0 0 25 0 20 2 7 4 3 8 0 35 0 4 0 3 7 4 4 5 0 45 5 40 4 7 .7 4 6 0 65 4 80 5 7 .7 4 5 0 100 9 60 6 7 4 4 7 5 60 31 80 7 7.9 460 100 10 80 8 8 4 0 0 80 2 80 9 7 4 5 6 0 110 7 100 W 7 .9 5 0 0 50 0 50 2 4 -A pr-88 1 8 4 3 4 0 60 4 6 4 .9 6 20 2 8 4 5 4 0 120 35 68 12.0 29 80 3 8 4 5 4 0 100 169 195 3.1 48 80 4 8.7 600 160 165 203 7,6 57 80 5 8 5 6 0 0 170 145 231 54 68 100 6 8 .7 5 9 0 180 153 200 44 04 110 7 8 5 5 9 0 180 125 133 AA 34 110 8 8 3 6 4 0 160 24 156 3.0 44 90 9 8 .9 6 1 0 2 0 0 149 319 33 88 130 10 83 700 100 12 104 12.1 29 50 14-M ay-88 1 6 5 2 9 5 25 0 6 2.1 6 40 2 7 3 0 0 35 0 13 2 3 8 80 3 7 3 3 0 0 55 0 4 3 .7 4 80 4 7 3 0 0 60 8 9 8 3 8 80 5 6 .7 3 0 0 180 51 187 4.1 45 180 6 6 .9 4 0 0 2 0 0 2 1 9 280 3.1 64 200 7 6 .9 5 1 0 2 4 0 231 238 33 39 300 8 6 .7 5 4 0 150 239 138 24 31 140 9 6 4 5 6 0 125 263 155 34 49 120 10 7 4 6 5 0 60 4 70 73 27 80 30-M ay<88 1 8 2 7 0 15 0 47 6.1 52 20 2 8 3 4 0 70 161 240 14 62 80 3 8 5 4 4 0 100 39 254 23 67 100 4 8 5 4 4 0 130 90 259 24 57 120 5 8 5 4 6 0 135 47 288 23 75 140 6 8 4 4 6 0 105 82 2 3 9 AA 65 100 7 8 4 4 7 0 100 122 297 19 75 100 8 7 4 4 4 0 105 153 305 3.7 74 80 9 7 .7 5 2 0 165 141 383 3 .7 X 160 10 7 4 6 7 0 60 0 161 63 82 80 2 0 J u n -8 8 1 8 2 8 0 25 125 121 4.4 75 0 2 79 5 8 0 100 161 203 11 36 90 3 8.1 5 7 0 140 161 300 33 47 110 4 7 4 5 8 0 2 2 5 176 506 3.7 40 260 5 7 .1 8 2 0 1 90 149 464 3.9 56 180 6 79 5 8 0 2 0 0 149 545 44 61 200 7 8 600 180 161 392 4,7 SO 160 142 Sits pH conductivity turtridity chlorophyll T o ta l P SRP TSPTSS (imhos/cm FTU m g /m 3 W/L M/1- M/1- tn g/ L 8 8 6 2 0 140 169 3 9 0 4.1 60 80 9 8 6 2 0 2 0 0 19 2 5 6 8 3 .8 SO 180 10 8.1 5 4 0 50 51 118 6£ 83 SO 2 8 4 0 1 -8 8 1 8 .6 3 1 0 100 67 2 5 4 21 47 90 2 7 4 2 0 110 2 1 6 213 2 4 67 90 3 8 4 6 0 0 140 169 2 6 2 4 .9 85 120 4 7 4 6 0 0 6 0 0 25 5 4 4 0 3 3 13 7 1 0 5 8 2 6 0 0 3 0 0 188 2 2 4 3 .9 59 3 2 0 6 8 4 6 0 0 2 0 0 196 198 21 61 2 1 0 7 8 6 1 0 4 8 0 212 176 3.1 101 5 3 0 8 7 .9 5 0 0 2 1 0 212 451 2 .7 125 2 0 0 9 7 6 2 0 2 9 0 2 7 0 126 4 .1 103 2 7 0 K> 8.1 8 0 0 60 39 3 9 9 7 .7 179 20 1 3 4 u l-8 8 1 7 .7 2 9 0 60 35 2 8 3 5 5 SB n o 2 7 4 4 8 0 150 102 399 3 .8 75 110 3 8.1 6 0 0 2 4 0 145 166 31 71 22 0 4 7 .9 6 0 0 140 26 3 5 2 8 69 44 120 5 7 .9 5 9 0 3 7 5 2 1 9 247 5j6 60 3 7 0 6 7 .9 4 5 0 2 7 5 2 9 4 765 5.1 Q 180 7 8 5 8 0 2 7 5 2 5 9 461 61 53 2 2 0 8 7 .8 5 4 0 190 2 9 0 143 65 64 110 9 19 6 0 0 180 3 2 9 304 11 52 120 10 8 .7 7 4 0 70 67 471 99 « 60 2 6 -Ju l-8 8 1 8 .6 2 9 0 40 0 265 2 J6 14 0 2 7 5 8 0 95 133 3 76 3 4 71 SO 3 8 4 6 2 0 140 165 185 51 27 90 4 7 4 5 8 0 135 169 378 4j6 13 TO 5 8 2 5 6 0 160 192 3 4 2 53 14 120 6 8 4 5 8 0 180 4 0 8 215 6.1 120 7 8 5 5 0 2 0 0 251 3 27 7 4 33 140 8 7 .9 5 6 0 2 1 0 231 2 9 0 5 5 44 130 9 4 5 2 0 190 321 209 5 5 149 130 10 8.1 7 2 0 185 27 318 9 .9 192 190 9-A u g -8 8 1 20 19 18 5 ) 2 TO 5 4 4 3 9 .5 3 90 308 6 0 3 4 120 158 4 1 .7 5 n o 173 6 0 3 6 90 2 3 2 9 5 .9 7 90 2 8 6 5 8 .1 8 100 2 1 2 5 1 .0 9 80 156 4 3 4 10 50 25-A ug-88 1 3 0 0 18 0 227 2 3 56 10 2 5 0 0 95 133 2 1 0 21 4 6 90 3 120 90 31 4 71 2 4 67 1 9 143 S ite fH oonductrrity tub cUonphyO T o tilP SRPTSPTSS Itm h o c/ctn FTL m x/m 3 W/L J t|/L M/L R tf/ L 4 5 0 0 100 129 100 2.1 43 220 5 5 0 0 120 219 117 1 7 7 350 6 5 4 0 60 204 68 32 50 40 7 450 100 184 187 1 8 27 160 8 5 0 0 95 231 600 2 4 67 n o 9 520 90 133 44 1 2 24 140 10 700 60 145 142 3 4 106 90 9 -S e p 4 8 1 0 35 4 5 12 10 2 184 119 5 4 58 80 3 137 197 5 j0 16 100 4 278 152 5 4 S 100 5 200 238 4 4 48 90 6 172 229 32 40 150 7 102 266 33 83 90 8 188 335 43 113 69 9 2 27 4 0 2 8 .7 97 70 10 106 916 4 4 181 2D 2 4 -S cp -8 8 /. 1 2 6 0 20 0 376 4 70 2 4 5 0 100 180 3 5 2 8 80 3 4 8 0 100 S 1057 8 120 4 4 8 0 ISO 169 969 7 160 5 4 9 0 120 2 19 9 6 2 45 210 6 495 100 176 111 8 170 7 500 130 86 305 9 130 8 5 1 0 140 212 9 6 2 6 130 9 5 1 0 120 200 97 7 130 10 80S 60 0 45 15 0 1 2 -O ct'8 8 1 2 4 0 20 289 21 2 4 8 0 70 319 64 3 4 6 0 90 2 0 2 52 4 4 6 0 100 926 127 5 4 5 0 100 348 78 6 800 120 748 109 7 4 8 0 130 173 65 8 4 8 0 100 1324 132 9 540 80 609 © 10 7 0 0 60 182 149 6-N ov*88 2 5 0 20 138 25 4 4 0 100 179 2B 4 5 0 150 277 48 5 0 0 140 2 62 52 5 2 0 n o 2 02 40 4 4 0 3 2 0 368 81 4 4 0 165 1403 67 680 130 211 35 580 115 191 51 10 850 180 127 87 APPENDIX C DIURNAL DISSOLVED OXYGEN DATA AND PRODUCTIVITY CALCULATIONS 144 145 Diurnal Data July 27,1987 hour 14:00 18:00 21:30 1:00 4:00 7:00 11:00 14:00 D.O. Concentration in g/m3 3 14.20 14.40 14.00 9.70 7.90 530 9.80 1420 4 11.50 13.00 12.20 10.40 8.70 8.40 10.70 1120 5 13.90 1520 14.00 12.50 10.40 8.50 11.00 13.90 7 1120 13.20 1Z00 11.20 1020 830 10.40 1120 9 10.80 12.90 11.50 9.80 8.30 6.00 9.90 1030 Rate of Change in g/m3/hr 3 0.05 -0.11 -123 •0.60 •0.80 1.08 0.94 4 0.38 -023 -Oil - 0 i7 -0.10 0 3 8 0.16 5 0.33 -0.34 -0.43 -0.70 •0.63 0.63 0.58 7 0.50 *0.34 -023 -023 -0.57 0.48 0.16 9 0.53 -0.40 -0.49 -020 •0.77 0.98 0.18 Rate of change in g/m2/hr depth (m) 3 0.04 -0.08 -0.86 *0.42 •0.56 0.76 0.66 0.70 4 0.34 -0.21 -0.46 . -021 -0.09 032 0.14 0.90 5 0.17 -0.17 -022 -035 -032 0.32 0.29 0.50 7 0.30 -0.20 -0.14 •020 •0.34 0.29 0.10 0.60 9 027 *0.20 -025 -025 •0.39 0.49 0.09 0.50 Avg. Res. g/m2/hr /day GPP g/m2-day Kcal/m2-day 3 *0.48 •1132 10.88 39.17 4 -0.32 •7.68 7.66 27.58 5 -0.27 *6.48 6.21 22.36 7 -0.22 .-528 5.41 19.48 * 9 -027 •6.48 6.42 23.11 Avg, -0.31 -7.49 7.32 26.34 146 Diurnal Data 26 September 1987 Hour 15:30 18:30 21:30 2:30 6:30 9:30 12:30 15:30 D.O. concentration in g/m3 3 10.00 11.20 7.60 7.40 6 3 0 6.10 7.90 10.00 4 11.00 12.20 10.40 8.10 6.70 6.60 7.90 11.00 5 8.10 8.70 7.70 7.50 6.10 5.90 7.90 8.10 7 9.20 9.20 9.00 8.20 6.40 6.30 8.10 9 3 0 9 8.90 8.90 7.50 7.10 6.10 6.10 7 3 0 8.90 Rate of change in g/m3/hr 3 0.40 -1.20 -0.04 -030 41.03 0.60 0.70 4 0.40 -0.60 -0.46 4)35 41.03 0.43 1.03 5 030 -033 -0.04 -035 •0.07 0.67 0.07 7 0.00 *0.07 -0.16 -0.45 ■0.03 0.60 0.37 9 0.00 -0.47 -0.08 -035 0.00 0 3 7 0 3 7 Rate of change in gAn2/hr Depth (m) 3 032 <0.96 -0.03 4)34 •0.02 0.48 0.56 0.80 4 0.44 -0.66 -031 *039 •0.03 0.47 1.13 1.10 5 0.12 -030 -0.02 -032 •0.04 0.42 0.04 0.62 7 0.00 4J.05 -O.l 1 4)32 •0.02 0.42 036 0.70 9 0.00 4)31 -0.04 -0.11 0.00 0.17 0.26 0.45 Avg. Resp. g/m2/hr /day GPPg/m2-day Kcal/m2-day 3 4)31 -7.44 6.87 24.73 4 -0.40 -9.60 9.72 34.99 5 -0.12 -2.88 2.82 10.15 7 -0.12 -238 3.12 1133 9 -0.09 -2.16 2.10 7.56 Avg. -031 -4.99 4.93 17.73 147 Diurnal Oxygen Data for 14 May 1988 hour 5:45 9:45 16:45 21:00 1:45 5:45 D.O. Concentration in g/m3 3 5.80 830 9.80 11.00 8.60 5.80 4 6.10 8.40 8.90 11.00 8.60 6.00 5 3.60 5.90 7.10 10.20 5.20 3.10 6 3.10 5.90 6.00 10.80 4.90 2.90 7 3.70 9.20 11.00 13.90 9.00 4.00 9 4.20 8 3 0 11.40 10.00 8.90 3.70 Rate of change ingfm3/hr 3 0.60 0.23 0.28 *0,64 •0.70 4 0 3 8 0.07 0.49 *034 -0.65 5 0.58 0.17 0.73 -133 -033 6 0.70 0.01 1.13 -137 -0.50 7 138 0.26 0.68 •131 •135 9 1.08 0.41 -033 *039 -130 Rate of change on g/m2/hr Depth (m) 3 0 3 4 0.09 0.11 -036 •0.28 0.40 4 0.30 0.04 0.25 •033 -0.34 0.52 5 031 0.06 0.27 •0.49 -0.20 0.37 6 0.20 0.00 0.33 -0.46 •0.15 0.29 7 0.49 0.18 -0.15 -0.13 •0.59 0.45 9 0.49 0.18 -0.15 •0.13 -039 0.45 Avg. Resp. g/mZtor /lay GPP g/m2-day Kcal/m2-day 3 -037 -6.48 6.175 22.2 4 -0.34 -8.16 7.728 27.8 5 -0.34 ' -8.16 7.593 27.3 6 *0.30 -73 6.778 24.4 7 -0.36 -8.64 8.073 29.1 9 -0.36 -8.64 8.073 29.1 Avg. -033 -7.88 7.40 26.65 148 Diurnal Data 28 May 1988 Hour 5:30 11:30 20:45 5:30 D.O. concentration in g/m3 3 3.20 6.10 6.90 3.60 4 3.50 5.80 7.40 3.80 5 3.60 5.80 7.00 3.60 6 5.00 6.10 8.20 4.50 7 4.20 5.80 7.50 4.30 9 3.80 5.60 6.60 3.20 Rate of change in g/m3/hr 3 0.48 0.09 -038 4 0.38 0.17 *041 5 0.37 0.13 *039 6 0.18 0.23 -042 7 0.27 0.18 -037 9 0.30 0.11 -039 Rate of change in g/m2/hr Depth (m) 3 0.23 0.04 -0.15 0.40 4 0.22 0.10 -034 0.59 5 0.16 0.06 -0.17 0.44 6 0.07 0.07 -0.13 0.30 7 0.15 0.08 -0.17 0.45 9 0.15 0.06 -030 0.50 Repiration g/m2/hr /day GPP g/m2-day Kcal/m2-day 3 -0.15 -3.60 4.028 14.5 4 -0.24 -5.76 5.888 21.2 5 *0.17 -4.08 4.096 14.7 6 -0.13 -3.12 3.04 10.9 7 -0.17 -4.08 4.22 15.2 9 -0.20 -4.80 4.492 16.2 Avg. -0.18 -434 4.29 15.46 149 Diurnal Oxygen Data 19 June 1988 Hour 5:15 11:30 21.-00 5:15 D.O. concentration in g/m3 3 3.20 4.40 6.70 1.80 4 1.70 2.40 5.90 1.90 5 3.20 4.90 8.50 1.80 6 2.40 4.00 7.10 2.00 7 2.60 4.00 8.40 2.20 9 2.80 4.20 8.50 2.40 Rate of change in gAn3/hr 3 0.19 0.24 *0.59 4 0.11 0.37 -0/48 5 0.27 0.38 -0.81 6 0.26 0.33 -0.62 • 7 0.22 0.46 -0.75 9 0.22 0.45 -0.74 Rate of change in gAn2/hr depth (m) 3 0.10 0.13 •0.32 0.55 4 0.07 0.24 •031 0.65 5 0.14 0.19 -0.41 0.50 6 0.12 0.15 •038 0.45 7 0.13 0.28 •0.45 0.60 9 0.12 0.25 •0.41 0 3 5 Avg. Resp. g/m2/hr /day GPP g/m2-hr Kcal/m2-day 3 •0.32 •7.68 6.90 24.8 4 •0.31 *7.44 7.60 27.4 5 •0.41 •934 9.14 32.9 6•0.28 -6.72 6.59 23.7 7 •0.45 •103010.56 38 9 •0.41 * •934 9.58 34.5 Avg. •0.36 -8.72 8.40 30.22 150 Diurnal Oxygen Data 27 June 1988 Hour 5:15 11:30 20:30 5:15 D.O. concentration in g/m3 • 3 4.80 7.00 9.90 4.90 4 4.40 7.80 8.30 4.20 5 4.00 4.50 10.20 4.40 6 4.30 5.20 11.20 4.00 7 4.80 5.10 11.00 4.60 9 4.20 8.00 1230 430 Rate of change in g/m3/hr 3 0.35 0.32 -037 4 0.54 0.06 -0.47 5 0.08 0.63 -0.66 6 0.14 0.67 -0.82 7 0.05 0.66 -0.73 9 0.61 030 -0.94 Rate o f change in g/m2/hr depth (m) 3 0.19 0.18 -031 035 4 0.12 0.04 -031 0.65 5 0.05 0.38 -0.40 0.60 6 0.05 0.23 -029 0.35 7 0.02 0.30 4)33 0.45 9 0.24 0.20 -038 0.40 Avg. Resp. g/m2/hr/day GPP g/m2-day Kcai/m2-day 3 -031 -7.44 7335 27.1 4 -0.31 -7,44 5.838 21 5 -0.40 -9.6 9.833 35.4 6 -0.29 -6.96 6.805 243 7 4)33 -7.92 7.858 28.3 9 -038 -9.12 9.095 ' 32.7 Avg. -0.34 -8.08 7.83 28.18 151 Diurnal Oxygen Data 12 July 1988 Hour 6:30 9:30 1230 15:30 18:30 21:30 0:30 3:30 6:30 D.O. concentration in g/m3 3 1.65 5.65 7 3 5 10.20 12.25 1130 3.60 335 1.65 4 0.75 2.10 4.05 7 3 5 7.90 5.15 2.65 130 0.75 5 1.85 4.15 5.65 9.65 10.90 1135 5.75 3.65 1.85 6 3.28 5.80 7.70 13.50 15.20 1330 7.65 3.45 3 3 8 7 2.00 3.40 5.75 12.75 11.10 9.65 4.65 Z65 ZOO 9 2.10 3.95 6.15 13.05 8.00 4.85 4.70 3.00 Z10 Rale of change in g/m3/hr 3 133 0 3 3 0.98 0.68 ■035 -233 •0.08 4)37 4 0.45 0.65 1.10 0.18 •0.92 •0.83 -038 4)35 5 0.77 0.50 1.33 0.42 0.32 •2.03 ■0.70 -0.60 6 0.84 0.63 1.93 0 3 7 •0.67 -1.85 -1.40 -0.06 7 0.47 0.78 2 3 3 -035 •0.48 -1.67 -037 •032 9 0.62 0.73 2.30 -1.68 -1.05 •0.05 •037 -030 Rate of change in g/m2/hr Depth 3 0.86 0 3 4 0.64 0.44 •033 •1.64 •0.05 •037 0 3 5 4 0.23 0 3 4 0 3 7 0.09 •0.48 •0.43 •030 41.13 0 3 2 5 033 032 037 0.18 0.14 •0.87 -030 •036 0.43 6 035 0.19 038 0.17 •030 •036 -0.42 •0.02 0 3 0 7 0.16 0 3 6 0.77 •0.18 •0.16 -0.55 -032 •0.07 0.33 9 0.19 032 0.69 4)30 -0.32 •0.02 -0.17 •0.09 0.30 Avg. Resp. g/m2/hr /day GPP g/m2-day Kcal/m2- Diurnal Oxygen Data 26 July 1988 Hour 6:00 15:00 18:00 06:00 D.O. concentration in g/m3 3 4.00 720 8.60 3.90 4 2.10 1120 1250 2.60 5 3.00 5.80 7.40 2.80 6 3.10 7.80 1120 320 7 350 10.80 1200 350 9 4.00 1020 1120 3.60 Rate of change in g/m3/hr 3 026 0.47 -029 4 1.01 0.43 -023 5 0.31 053 -028 6 052 1.13 -0.67 7 0.81 0.40 -0.71 9 0.76 0.13 -0.63 Rate of change in g/m2/hr depth (m) 3 0.14 0.19 •0.16 0.40 4 0.40 0.17 •023 0.40 5 0.09 0.16 -0.11 0.30 6 0.17 0 2 6 •021 0.32 7 0 2 7 0.18 •023 0.46 9 0 2 0 0.05 •025 0.40 Avg. Reap. g/m2/hr May GPP& Kcal/m2-day 3 •0.16 •324 3.75 13.5 4 •0.33 -722 8.07 29.1 5 -0.11 -264 261 9.4 6 -021 -5.04 5.13 185 7 -0 2 3 -7.92 7.83 2 8 2 9 •025 •6.00 5.85 21.1 Avg. •023 -5 5 6 5 5 4 19.94 Diurnal Oxygen Data 25 August 1988 Hour 7:15 10:15 12:45 16:00 20:00 23:30 3:00 7:15 D.O. Concentration in gftn3 3 1.80 7.10 9.00 1320 830 7.00 3.70 1.80 4 1.50 3 4 0 5.00 8.70 6.80 4.80 3 3 0 1 30 5 0.60 5.80 6 3 0 8.40 7.00 1.40 130 0.60 6 1.00 9 3 0 10.40 11.80 7.60 4.00 2 3 0 1.00 7 0.90 4.20 5.00 8 3 0 7.60 3.00 130 0.90 9 1.20 5.00 6.00 8.00 7 3 0 4.10 2.70 1 30 Rate of change in gAn3/hr 3 1.77 0.76 0.98 *0.93 -0.43 •0.94 -0.45 4 0 3 0 1.04 1.14 •0 4 8 4)37 •0.46 -0.40 5 1.73 0.16 0.68 *035 -1.60 •0.06 -0.14 6 2.73 0.48 0.43 -1.05 -1.03 4)31 4)38 7 1.10 0.32 0.98 -0.15 •1.31 •0.49 -0.09 9 137 0.40 0.62 •030 •0.89 •0.40 4)35 Rate of change in g/m2/hr depth (in) 3 0 3 3 0 3 3 0 3 9 •038 •0.13 -0.28 -0.14 0 3 0 4 0.12 0.42 0.46 -0.19 •0.23 -0.18 -0.16 0.40 5 0 3 2 0.05 0.20 -0.11 •0.48 •0.02 *0.04 0.30 6 0.68 0.12 0.11 •036 -036 *0.13 •0.07 0.25 7 0.66 0.19 039 -0.09 •0.79 4)39 -0.05 0.60 9 0 3 5 0.08 0.12 -0,04 •0.18 •0.08 41.07 0 3 0 Avg. Resp. g/m2/hr /day GPPg/m2-day Kcal/m2-day 3 •0.21 •5.04 5.95 21.4 4 •0.19 -436 5.87 21.1 5 •0.16 •3.84 4.46 16.1 6 •0.18 -4 3 2 4.85 173 7 •031 -7.44 8.89 32 9 •0.09 •316 235 9.18 Avg. ■0.19 -4 3 6 5.43 1934 154 Diurnal Oxygen Data 24 September 1988 Hour 6:15 12:15 17:15 19:15 2:15 6:15 D.O. Concentration in g/m3 3 2.30 830 13.90 12.00 4.90 2.40 4 3.40 6.80 930 830 4.60 2.90 5 330 10.20 14.90 930 5.00 3.00 6 4.00 10.70 16.60 1230 4.80 3.60 7 3.60 1130 15.50 10.80 5.10 3.80 9 3.10 8.90 12.60 1030 5 3 0 3 3 0 Rate or change fat g/m3/hr 3 1.03 1.08 -0.95 •1.01 •0.63 4 037 034 -030 -033 -0.43 • 5 1.17 0.94 -2.70 •034 •0 3 0 6 1.12 1.18 -2JQ5 •1.10 -0.30 7 1.27 0.86 -235 -031 •0.33 9 0.97 0.74 -130 -0.71 -0.43 Rate of change in gftn2/hr depth (m) 3 0.41 0.43 -038 •0.40 -0.25 0.40 4 036 034 -037 •034 •0.19 0.45 5 035 038 -031 -0.19 •0.15 0.30 6 0.11 0.12 -031 -0.11 -0.03 0.10 7 031 0.34 -0.94 -032 -0.13 0.40 9 034 036 -0.42 -035 •0.15 0.35 Avg. Res. g/m2/hr /day GPP g/m2-day KcaUm2-day 3 -035 •8.40 8.46 30.46 4 -033 -5 3 2 5.29 19.04 5 -0.38 -9.12 7.68 27.65 6 -0.12 •238 2 3 8 9 3 9 7 -0.47 •1138 9.93 35.75 9 -0 3 7 -648 631 22.72 Avg. -0.30 -738 6.71 24.15 APPENDIX D VEGETATION DATA 155 Diameter of Nelumbo leaves in each trasect July Au-1 Au-2 Au-3 July Au-1 Au-2 Au-3 cm cm cm cm cm cm cm cm - 3 T 30 35 47 26 40 24 45 4 0 34 48 41 30 42 21 35 2 8 19 23 43 51 26 ■ 30 33 32 42 35 42 26 26 29 26 2 8 37 30 30 27 18 49 34 41 47 44 40 55 15 46 16 35 42 29 34 57 21 36 38 6 0 43 48 41 44 39 34 22 35 48 36 33 32 25 39 42 6 0 34 35 38 32 45 48 51 35 36 27 50 36 41 45 44 6 0 29 23 38 37 23 28 49 42 17 37 50 23 42 24 42 43 35 26 36 27 22 43 21 55 15 36 61 54 26 23 28 4 5 38 44 38 39 48 34 45 37 59 28 47 48 39 26 59 6 0 35 39 28 45 42 15 17 18 29 27 24 52 40 30 38 54 51 21 43 59 45 54 32 39 31 20 20 31 28 58 29 48 38 29 62 26 36 39 19 22 36 34 23 59 23 39 36 27 35 30 30 37 19 21 21 32 39 27 45 30 41 34 49 4 t 33 41 38 50 49 38 37 2 5 50 48 22 48 39 36 36 34 51 42 • 61 43 52 36 35 51 41 38 30 24 31 25 32 55 43 56 31 23 38 37 40 46 46 47 38 27 36 36 23 40 50 43 33 40 28 27 61 36 27 47 48 37 26 25 39 29 38 43 47 32 21 35 35 37 32 42 54 38 43 26 22 48 24 38 43 37 44 36 22 46 24 13 40 40 28 50 33 32 39 36 57 57 28 42 35 29 40 28 53 48 39 41 19 37 42 24 39 44 41 55 45 48 45 33 35 35 34 57 64 46 38 43 39 50 28 37 45 32 30 43 27 38 26 28 34 29 27 47 26 42 28 44 39 50 26 36 45 22 25 43 58 Diameter of Nelumbo leaves in each insect M y Au-1...... Au-2- Au-3 — July — Au-1 * ...... Au-2 Au-:' 157 cm cm cm cm cm cm cm cm " 1 5 " 48 42 24 44 31 37 33 55 42 44 21 33 54 46 10 53 49 39 50 26 26 19 30 53 40 17 34 17 39 42 47 52 53 49 39 33 44 46 45 32 40 31 28 Chemical Analysis micrognuns/g dry weight Sample diameter ...... P”"...... Fe Mn cm 33 2212 2432 744 13 6074 1986 366 42 3253 272 379 51 2728 151 316 31 3106 356 280 34 3771 288 312 37 3280 378 296 54 2175 80 149 51 2885 173 265 43 3051 1091 . 488 66 2941 388 278 APPENDIX E CHEMICAL DATA FROM SEDIMENT CORE OF OLD WOMAN CREEK 158 M » uc4Bp»o2Sfj5s!S3(28l3lo5S»w5«Hwjbiftcb«»*uis UbtOOtOvM OlOi Ot4k icJ2o!sJQi2S!28882S:£ <0 K»O, O S ^ S g ^ 85 S 85 2 a S {J s ^ s a S a S § IS S a t3 ^ ^ UiM«U|MnuM«UM nAwJ ■fl ft gfJAUOlAU^WSSS^SSJiJd^UMMWjo^uUMMMMMUUUAUMkUWkWUWWUMUkW # 5 0a««NN>4«)nUljJj;g52MWn8SniSSu” ” WU>'OHUl*‘H0t" 'lM*‘U',MW'4M',* O'°M^ ^ob«nMwfcM«j*waogo&woo<4SaoaMOWoo««iu(Joonau««uo&oouuo u w u pkVUOStAkttWAoJMMMWUMOlSkWW^MVwtfKlWWgeOtSMUSotMSMaltMUltl S S o o u 3 *w ^K)aoao^0K>bik>»btA[ooo^AMbsQibo‘A-a)}jba|ob\bt <7i k)(alojk ^ » Ank>M^bt S 3? OOOOOOOOOOOOOOOOOOOOOOOOOOOOOoOOOnOnOnOOOOOOOnOnac-. 3 M fekTiife& Sifcfe& fegkS& & fefcsrgfefcfefcf5‘5& kfefefcfcfe;fe& i,‘>fe<-i3‘-fe k ‘3feisii3sS**fc*-*-*- r PPPPPPPPpppPPPPPPppppopppppppppppppppppppppppppppo u u E58GS£SS2}3388nnr3GCi*ig8888888888888888888288888888 9 9 viuuUotoooia>KiCB 160 161 1) Sedimentation sedimentation rate = 0.73 cm/yr bulk density = 0.63 g/cm^ average phosphorus content - 1.76 mg P/g 0.73 cm/yr x 0.63 g/cm^ x 1.76 mg P/g x 10* cm2/m2 x 1 yr/365 days = 22 mg Pm -2 day* * 2) Macrophyte Uptake peak biomass = 64,000 g dry wt 64 kg/yr x lyr/365 days x 10® mg/kg /565.000 m2 = 0.3 mg P m '2 day** 3) Plankton Cycling gross primary productivity « 976 g O 2/ m2 yr 976g02/m^yrx 12gC/32gO2xlgP/40gCx 10^mg/g = 25 mg Pm*2 day* 1 respiration = 914 g O^J m2 yr 914g02/m2yrx 12gC/32g02XlgP/40gCxl(P mg/g = 23 mg Pm ’2 day* 1 4) Daily Inflow and Outflow of Phosphorus flow (nvtyday) x concentration (mgP/m^) /565.000 m2 = flux (mg P/ m2 day) It was assumed that the barrier beach would not allow transfer of phosphorus when it was closed. If the lake was flowing into the marsh (negative outflow), then the absolute value of the flow was multiplied by the Lake Erie phosphorus concentration, rather than by the outflow concentration. This provided the Lake Erie inflow value. Daily values from March 1,1988 - November 30,1988 were averaged for the mass balances.