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Primary productivity on Sturgeon Bank Ross, Lauren Ruth 1998

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PRIMARY PRODUCTIVITY ON STURGEON BANK by LAUREN RUTH ROSS B.Sc., The University of Western Ontario, 1993  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES Department of Earth and Ocean Sciences Oceanography Division  We accept this thesis as conforming to the required standard  THE UNIVERSITY OF BRITISH COLUMBIA April 1998 © Lauren Ruth Ross, 1998  In  presenting this  degree at the  thesis  in  partial  fulfilment  of  the  requirements  University  of  British  Columbia,  I agree that the Library shall make it  freely available for reference and study. I further agree that copying  of  department  this thesis for scholarly or  by  his  or  her  It  is  an  by the  understood  head of my  that  publication of this thesis for financial gain shall not be allowed without permission.  Department The University of British Columbia Vancouver, Canada  DE-6 (2788)  advanced  permission for extensive  purposes may be granted  representatives.  for  copying  or  my written  II  Abstract The Iona Island sewage treatment plant opened in 1963 and discharged primary treated wastewater onto the high intertidal area of Sturgeon Bank in the Fraser River estuary. In 1988, the effluent was diverted to the Strait of Georgia by the implementation of a deep sea outfall, intended to restore the ecological health of the intertidal area. This study investigated phytoplankton and benthic microalgal productivity on Sturgeon Bank, at a contaminated site adjacent to the sewage treatment plant and two reference sites further removed, to determine whether an effect of sewage pollution was present at the primary producer level of the food web. Primary productivity was determined by measuring the production and consumption of oxygen in benthic chambers over approximately 20 hour incubation periods, during 1995 and 1996. A variety of environmental parameters, each with a potential influence on primary productivity, was measured: nutrient concentrations, solar irradiance and attenuation, water turbidity, temperature, salinity and the biomass of primary producers. The contaminated site revealed the highest primary productivity, despite a lower biomass of benthic microalgae. These producers were more productive at this site, most likely due to the high level of organics from the sewage effluent, which enhanced nutrient availability. The low benthic biomass was most likely due to grazing by benthic macroinvertebrates in this area. The reference sites, however both supported a higher benthic microalgal biomass with lower productivity. Although the intermediate reference site, located approximately 2 km south of the previous sewage effluent outfall, exhibited the lowest benthic productivity, this may have been a consequence of surface freshwater used to inadvertently fill the incubation chambers during the summer months. However, the influence of the Fraser River is greatest at this site and may have been a factor controlling productivity. Correlations were not found between primary productivity and light, temperature or benthic biomass, although the effect of these environmental conditions may have been masked by other factors. Resultsfromcollaborating studies revealed information about the sediment composition, heavy and trace metal concentrations and organic content at the contaminated site that most likely did not impact productivity. As there is a lack of information regarding primary productivity in the Fraser River estuary, this study establishes baseline data useful for comparisons with future studies of benthic microalgal productivity.  iii  Table of Contents Abstract  ii  Table of Contents  iv  List of Tables  v  List of Figures  vi  List of Appendices  viii  Acknowledgments  ix  Introduction  1  The Fraser River Estuary  4  6  STURGEON BANK IONA ISLAND AND SAMPLING SITES Ecological importance of this area History of Iona Island sewage treatment plant Sewage pollution and its affects on an estuary Why measure primary productivity on Sturgeon Bank? Factors affecting primary productivity  LIGHT ENERGY TURBIDITY TEMPERATURE SALINITY NUTRIENTS PLANT BIOMASS ORGANIC MATTER BENTHICANIMALS Methods for the measurement of benthic primary productivity Overview of previous studies on Sturgeon Bank Objective  Materials and Methods Study site and station locations Tidal information Transportation  Laboratory and Field methods Sampling design and station orientation TERMINOLOGY TO DIFFERENTIATE BETWEEN SAMPLES Oxygen concentration determination Phytoplankton biomass Benthic microalgal biomass Primary producer identification Nutrient analysis Physical and chemical parameters TEMPERATURE AND SALINITY LIGHT INTENSITY AND ATTENUATION WIND SPEED AND TURBIDITY Calculations Statistical analysis  Results Nutrients Temperature Salinity  7 8 9 11 12  12 14 15 16 17 17 18 18 19 20 20  22 22 22 25  26 26 29 33 35 36 37 37 38 38 38 39 39 40  41 41 46 46  7  iv Turbidity and wind speed Sediment texture Primary producer biomass STATION AO STATION A12 Primary producer identification Primary productivity STATION AO Benthic microalgal productivity Phytoplankton productivity STATION A10 Benthic microalgal productivity Phytoplankton productivity STATION A12 Statistical results RELATIONSHIPS BETWEEN PRODUCTIVITY AND ENVIRONMENTAL FACTORS SPATIAL VARIATION - COMPARING STATIONS TEMPORAL VARIATION - SEASONAL TRENDS  Discussion ENVIRONMENTAL FACTORS RELATED TO PRIMARY PRODUCTIVITY The effect of temperature on primary productivity Was solar irradiance correlated with productivity? TURBIDITY EFFECTS ON LIGHT PENETRATION LIGHT AVAILABILITY, TIDAL VARIATION AND VERTICAL MIGRATION LIGHT ATTENUATION DUE TO RESUSPENSION OF MICROPHYTOBENTHOS Was benthic microalgal biomass a controlling factor for benthic productivity? Grain size and the effect on benthic diatom composition and production  ECOLOGICAL SPATIAL VARIATION ON STURGEON BANK THE CONTAMINATED SITE, AO Benthic productivity Phytoplankton productivity REFERENCE SITES Station A10 Station A12  50 50 54 54 56 59 59 61 61 63 65 65 68 68 73 73 75 78  80 80 80 81 82 83 86 86 88  92 92 95 98 101 101 106  Conclusions  110  Difficulties involved in primary productivity studies  111  General Recommendations  113  Bibliography  116  Appendices  122  V  List of Tables Table 1. Location coordinates, denomination and sediment types for sampling stations.  24  Table 2. Study sites and dates sampled.  32  Table 3. Phytoplankton and benthic rnicroalgae identified in water samplesfromfield sites on Sturgeon Bank.  60  Table 4. Statistical resultsfromregression analyses (p-values) of environmental factors against benthic rnicroalgae and phytoplankton net productivity (NP).  74  Table 5. ResultsfromANOVA (p-values) showing spatial variation between sites on Sturgeon Bank.  76  Table 6. Tukey test results (q-values) comparing gross and net productivity between study sites in total (chamber incubation), phytoplankton (bottle incubation), and benthic productivity.  77  Table 7. Summary of statistical results testing for seasonal differences in benthic microalgal biomass and benthic gross and net productivity.  79  Table 8. Benthic microalgal biomass in the top 1 cm of sedimentfromintertidal areas in various estuaries.  93  Table 9. A comparison of benthic microalgal productivity values (units in g C m' y' ) from other areas around the world. 2  1  Table 10. Comparison of sediment heavy metal concentrationsfromstation AO in 1979 and 1997 to the provincial sediment quality guidelines, and organic contentfrom1975 and 1997.  96  100  VI  List of Figures Figure 1. Typical food chains of the Fraser River Estuary with varying degrees of complexity.  3  Figure 2. Study area and sampling locations on Sturgeon Bank in the Fraser River Estuary.  5  Figure 3. A) An illustration of the sampling design and protocol involved to estimate benthic productivity, and B) ecological processes that occur within a benthic incubation chamber.  27  Figure 4. Photographs offieldsampling at station AO in July 1996.  30  Figure 5. Photographs offieldsampling at station A10 in July 1996.  31  Figure 6. A) Production and consumption of nutrients over the incubation period, and B) nitrate and ammonium concentrations (initial andfinal)at stations AO, from August 1995 to October 1996.  42  Figure 7. A) Production and consumption of nutrients over the incubation period, and B) nitrate and ammonium concentrations (initial andfinal)at station A10 from August 1995 to October 1996.  43  Figure 8. A) Production and consumption of nutrients over the incubation period, and B) nitrate and ammonium concentrations (initial andfinal)at station A12 from August 1995 to October 1996.  44  Figure 9. Porewater nitrate and ammonium concentrations at station AOfromMarch to November 1995.  45  Figure 10. A) Net increases and decreases in temperature and salinity in incubation chambers over the experiment, and B) initial andfinaltemperature and salinity values at station AO.  47  Figure 11. A) Net increases and decreases in temperature and salinity in incubation chambers over the experiment, and B) initial andfinaltemperature and salinity values at station A10.  48  Figure 12. A) Net increases and decreases in temperature and salinity in incubation chambers over the experiment, and B) initial andfinaltemperature and salinity values at station A12.  49  Figure 13. Average wind speed and water turbidity at station AOfromJuly 1995 to October 1996.  51  vii  Figure 14. Average wind speed and water turbidity at station A10fromJuly 1995 to October 1996.  52  Figure 15. Average wind speed and water turbidity at station A12fromJuly 1995 to October 1996.  53  Figure 16. A) Benthic microalgae and phytoplankton chlorophyll a concentrations, and B) percent changes in phytoplankton biomass over the incubation period in bottle incubations at station AO.  55  Figure 17. A) Benthic microalgae and phytoplankton chlorophyll a concentrations, and B) percent changes in phytoplankton biomass over the incubation period in bottle incubations at station A10.  57  Figure 18. A) Benthic microalgae and phytoplankton chlorophyll a concentrations, and B) percent changes in phytoplankton biomass over the incubation period in bottle incubations at station A12.  58  Figure 19. A) Gross and net benthic productivity, and B) phytoplankton productivity at station AO.  62  Figure 20. Primary productivity normalized to chl a for benthic microalgae and phytoplankton at station AO.  64  Figure 21. A) Gross and net benthic productivity, and B) phytoplankton productivity at station A10.  66  Figure 22. Primary productivity normalized to chl a for benthic microalgae and phytoplankton at station A10.  67  Figure 23. A) Gross and net benthic productivity, and B) phytoplankton productivity at station A12.  69  Figure 24. Primary productivity normalized to chl a for benthic microalgae and phytoplankton at station A12.  72  Figure 25. Annual values for both benthic microalgal biomass and benthic primary productivity at three sitesfromMarch to October 1996.  89  Figure 26. Comparison of heavy metal concentrations and organic content at AO from 1979 and 1997. Highlighted heavy metal concentrations in red represent values above the provincial standard guideline.  97  viii  List of Appendices Appendix 1.  Light intensity, incubation times and tide cycle charts.  122  Appendix 2.  Description of calculations following Winkler titrations for oxygen concentrations.  137  Appendix 3.  Oxygen results for comparison of the Azide modification and the standard Winkler titration.  138  Appendix 4.  Description for calculating productivity in chamber incubations.  139  Appendix 5.  Description for calculating productivity in bottle incubations.  143  Appendix 6.  Description for calculating productivityfromthe benthic microalgae community using the chamber and bottle values.  146  Appendix 7.  Description for calculating benthic microalgal biomass.  149  Appendix 8.  Comparison of benthic microalgal biomassfromsand troughs and crests.  151  Appendix 9.  Initial andfinaltemperature and salinity averages.  152  Appendix 10. Light attenuation with water depthfromlocations just offshorefromfield sites.  154  Appendix 11. Daily light intensity represented as the area under pyrheliometer curves.  159  Appendix 12. Adjustments to respiration valuesfromdark bottles and chambers.  160  Appendix 13. Summary of phytoplankton, benthic microalgae and other primary producers on Sturgeon Bank in 1974 and 1981.  164  ix  Acknowledgments I have been very fortunate to have had the opportunity to work with Paul J. Harrison and the students in his lab, who have provided an incredible atmosphere of learning, leadership and teamwork. I am especially grateful to Paul for his guidance and support throughout my time at UBC, and for his interest and encouragement in all of my endeavours. I would like to thank the other members of my committee, Dr. Ken Hall and Dr. Colin Levings, as well as Dr. Michael Healey for the use of his chambers. Thanks are in order to Environment Canada for funding and coordinating this project, especially Colin Gray and Janet Landucci. Great thanks are due to Dr. Michael Turner of DFO, Manitoba for assistance with the productivity calculations and to Dr. Jay Pinckney of the Institute of Marine Sciences, Chapel Hill, North Carolina for reviewing Appendices 4, 5, and 6. I greatly appreciated the constructive criticism Dr. Diana Varela provided of my work, her willingness to lend advice, and lessons for proper lab techniques. Shannon Harris was kind enough to help manipulate productivity calculations and acted as an intelligent and logical sounding board for ideas. Dr. Kedong Yin gave a critical viewpoint of the operations of the study and was always willing to assist in field work. Dr. Tony Larson was very generous in helping with conference and seminar talks. Terri Sutherland's insight was priceless in the final hours of the study. Mark Wen was very helpful and supportive, both as a friend and statistician. Dr. Charles Trick deserves a special thanks for his encouragement and thoughts throughout this project and for introducing me to the discipline of oceanography. There are a number of people to whom I am grateful, for their time and effort in both thefieldand laboratory, especially Mingxing Guo, Ramnarine Arjoon and Sarah Dudas. Hugh MacLean, Rachel Harrison and Joe Needoba were reliable and alertfieldassistants. Ken Jefferies provided ingenuity in engineering thefieldequipment. Dave Jones assisted with assembly and maintenance of the battery unit and microprocessor. I appreciated all the help and supportfromother members of the Harrison Lab group: David Crawford, Robert Strezpek, Catriona Hurd, Joe Arvai, Anthony Fielding, Graham Peers, Beth Bornhold, Nelson Sherry, Allen Milligan, Debbie Muggli, Nathalie Waser, and Michael Lipsen. The crew of the Canadian Coast Guard, Hovercraft Base was invaluable to the execution of the field experiments, as they provided both assistance and transportation. This project would not have been possible without the help of almost one hundred volunteers who gave up their time and priceless hours of sleep to assist in the collection of field samples. I would particularly like to acknowledge my parents for all they have done for me. Most importantly, they provided a foundation of strength and inspiration, and supported all of my endeavours. A very special thanks to people very dear to me, especially my sisters, Alexandra and Kathryn, and Mike, whose spirit and devotion is precious to me. Thank you to Ger, Johnny, Mezo, Vogel, Rick, Ali, Vicki, Shelley, Kami, and Nona Navin who made my experience at UBC so memorable.  1  Introduction Estuaries are among the most productive natural systems in the world. They are defined as a coastal body of water where a river meets the sea, mixingfreshwater and salt water with the influence of tidal action. As well as being highly productive, estuaries are also the dumping site for sediments, debris, and wastesfromhuman activity on neighbouring continental areas. Estuaries are natural navigable harbours and waterways that allow transportation of ships inland for commercial and industrial practices. In turn, any waste disposal operations occurring upriver will eventually end up in the estuary. Circulation is therefore very important toflushthe estuarine water of any pollution and maintain the integrity of the ecosystem.  The two most distinctive characteristics of estuaries are their unique circulation patterns and salinity gradients caused by the mixing of the two water sources (Knox, 1986). Water movement in estuaries is created by a combination offreshwateroutflow, saltwater intrusion, wind, waves and tides. This circulation contributes to a number of functions in the estuary: transportation of nutrients and plankton, distribution of suspended fish larvae and invertebrates,flushingwastes and cleansing the system of pollutants, controlling salinity patterns, movement of sediment and mixing the water masses (Knox, 1986). Storm events enhance and strengthen this circulation which has the greatest impact on the intertidal region of estuaries.  The estuarine intertidal area is alternately submerged and exposed by tides and is described by Kennish (1986) as a broad, gently sloping region of muddy or sandy sediment covering up to hundreds of square kilometers along the coast. These mudflats are subject to extreme and often rapid changes in sedimentation due to wind and storms, temperature changes due to solar  2 radiation over exposed or covered sediments, and salinity gradients depending on seasonal cycles in river discharge. Large fluctuations in environmental factors make estuaries a challenging place for plants and animals to live and therefore, species diversity is generally low. The euryhaline and eurythermal organisms found in estuaries are thus subject to lower competition, and therefore flourish, resulting in very high productivity. Phytoplankton, however, do not contribute to the majority of this production, as they might in pelagic systems (Pinet, 1992). A very complex network of autotrophs is involved in estuarine primary productivity involving macrophytes, micro- and macro-epiphytic algae, benthic micro- and macro-algae and phytoplankton. The diversity of these primary producers alone emphasizes the complexity and intricacy of a complete food web would be in an estuarine system. An illustration of a food web in the Fraser River Estuary is shown in Figure 1.  Although over 90% of the organic matter produced by macrophytes and macroalgae is processed by the detrital system, a much smaller percentage of the primary production by phytoplankton and benthic microalgae reaches this detrital part of the food web (Knox, 1986). A great proportion of this primary productivity is consumed by zooplankton, planktivorous fish, interstitial micro- and meiofauna, surface deposit-feeding mollusks, polychaete worms andfilter-feedinginvertebrates, before decomposition processes are initiated in the detrital system (Knox, 1986). The component of the organic matter that does reach this system is colonized by bacteria, fimgi, benthic microalgae and other microorganisms and provides food for primary consumers (e.g. zooplankton, benthic invertebrates, and some fish).  JUVENILE SALMON ft HERRING, BIROS  Figure I CLAMS,  BIROS, SEALS MAN  8  CRABS, ISOPOOS BENTHIC  MUSSELS, AMPHIPOOS, a  A SIMPLE F R A S E R ESTUARY FOOD CHAIN  OTHER  INVERTEBRATES  DEATH a OECAV PHYTOPLANKTON •  A SOMEWHAT MORE COMPLEX F R A S E R ESTUARY FOOO CHAIN  Figure 1. Typical food chains of the Fraser River Estuary with varying degrees of complexity (Hoos and Packman, 1974).  4  The Fraser River Estuary The Fraser River estuary, located on the western coast of Canada, at the delta of the Fraser River, Vancouver, BC, encompassing an area 115 km (Fig. 2) (Kistritz, 1978). It is a very dynamic and 2  complex system and is comprised of tidalflatson Sturgeon and Roberts Banks, brackish marshes in some areas along the high water level, and eelgrass beds on Roberts Bank and in Boundary Bay. The nature of the large salt-wedge type of stratification characteristic of this estuary is controlled by tides and the amount of freshwater discharge from the river (Pedersen, 1994). The salt-wedge is a two-layered system with a brackish surface layer and a bottom seawater intrusion (Hoos and Packman, 1974). The estuary is highly stratified with a strong halocline that is maintained out into the Strait of Georgia, only becoming partially mixed at times of very high river discharge (freshet) and significant tidal influence (Hoos and Packman, 1974).  The deltaic morphology of the Fraser estuary is more characteristic of estuaries on the eastern coast of North America than the typical fjords found in the west. Formation of the delta has occurred due to the large suspended load that drainsfromthe Fraser River and deposits in the estuary upon meeting seawater. Sediment deposition occurs with adequate sediment supply, which is definitely the case in the Fraser River, and when waves are modest in size and incapable of redistributing the sediments. Therefore, the rate of supply is greater than the rate of removal. Most of the sediment deposited in the last 9000 years (since Holocene deglaciation) has contributed to the growth and formation of the Fraser delta now 975 km in area with an average 2  thickness of 110 m (Milliman, 1980).  Figure 2. Study area and sampling locations on Sturgeon Bank in the Fraser River Estuary (from Yin et al., submitted).  Theriverdivides at the delta into a series of channels or arms. The North Arm empties approximately 16% of theriver(McLaren and Ren, 1995) between Point Grey and Iona Island and is bordered to the south by the Point Grey breakwater. Middle Arm separates Sea Island, the location of the Vancouver Airport and Lulu Island, now occupied by the Municipality of Richmond, and drains a less significant volume of the river. The Main Arm is the major waterway for industrial traffic as well as a world-class migration route for 5 species of salmon (Hoos and Packman, 1974; Anonymous, 1996). It also empties 70% of the river past Steveston (McLaren and Ren, 1995) and its flow is confined to Roberts Bank by the Steveston jetty to the north.  The Fraser River itself is the largestriverreaching the west coast of Canada, 1,375 km long and is one of the largestfreeflowingriversin North America draining more than 234,000 km of BC 2  (Milliman, 1980). Ecologically, theriverand estuary serve thousands of species, including the commercially-valuable salmon and trout that migrate along thisriverfor hundreds of kilometers.  STURGEON  BANK  Sturgeon Bank, an extensive intertidal, alluvial mud/sand bank, is mostly comprised of sand with mud found more in the North Arm area than further south (McLaren and Ren, 1995). This intertidal region is subject to a semi-diurnal tide, experiencing drying at low tide and up to a 4 m tidal rise at high tide (Fjarlie, 1950). The bank accepts the Fraser River through the North and Main Arms on either side of the bank as well as the Middle Arm that empties directly onto the flats. The Iona and Steveston breakwaters were built to direct theriverflowfromthe North and Main Arms off Sturgeon Bank. The Middle Arm thus has the greatest influence on the present study area and on Sturgeon Bank.  7 The foreshore of Sturgeon Bank is lined with a discontinuousfringeof brackish marsh that grows and contracts seasonally and covers approximately 9 km (from Point Grey to the southern end of 2  Sturgeon Bank) (Kistritz, 1978). Marsh vegetation includes sedges and bullrushes and provides an ecologically valuable habitat (Hoos and Packman, 1974; McGreer, 1979a). Benthic microalgae, or microphytobenthos, represent the dominant primary producers on the mudflats, accompanied by phytoplankton in the water column.  IONA ISLAND AND SAMPLING  SITES  Iona Island is located on the northern end of Sturgeon Bank between the North Arm and Sea Island and is the location of one of the major sewage treatment plants for the City of Vancouver. The Macdonald slough separates Iona IslandfromSea Island and was formed after the construction of a dike built to connect the two islands (Fig. 2). Details of the Iona Island sewage treatment plant (STP), regarding both effluent treatment and discharge will follow.  All three sampling sites used in this study are on Sturgeon Bank, rangingfromthe northernmost area adjacent to the Iona Island STP, to the southernmost region just north of the Steveston jetty. The distance between these sites measures approximately 10 km (Arvai, 1997). As the tidal height is very similar among the three sites, the flood tide arrives on site less than half an hour apart. This information was crucial in designing the sampling scheme. More specifics of the sampling sites will also follow in the Methods section.  Ecological importance of this area The Fraser River estuarine habitat is ecologically indispensable to wildlife, waterfowl and fisheries as it is used as a feeding ground and migration route, and a shelterfrompredators and rearing area by birds and fish. The estuary, and the Fraser River itself are both well known for the yearly  8 migration of over 800 million juvenile salmon and steelhead troutfromthe river, to the estuary and eventually out to the open ocean. As part of the behaviour of salmonid species, adults return to theirfreshwaterbirthplace to spawn. The great trek up the Fraser River is attempted by over 10 million adult salmon every year (Anonymous, 1993). The lower Fraser River also boasts home to over 87 species offishand shellfish; commercial crab and shrimpfisheriesare also present in the deeper waters of the estuary.  The estuary is also used as a staging area for the Pacific Flyway, one of the world's major migratory routes that rangesfromAlaska to South America (Anonymous, 1993). In an average year, up to 150 species of wintering waterfowl, shorebirds and birds of prey make use of the Fraser estuary. Approximately 1.5 million birds visit the estuary yearly, giving the Fraser delta the highest density of birds in Canada.  The importance to maintain the ecological integrity of the estuary becomes very obvious when considering not only the use of this area by hundreds of species, but also the economic value of variousfisheriesactive in the estuary and their dependence on a healthy environment. Municipal and industrial wastewater discharged into this estuary must therefore be done with minimal impact.  History of Iona Island sewage treatment plant The Iona Island sewage treatment plant processes both domestic and industrial wastewater from central Vancouver, Richmond and parts of Burnaby to primary treatment standards. During times of high precipitation, the wastewater volume plus the storm water runoff often exceed the maximum capacity of the treatment plant. The excess wastewater is discharged immediately onto the high intertidal area of Sturgeon Bank after receiving only the screening processes of primary  9 treatment. Although this bypass dumping onto the foreshore is somewhat infrequent and only 9 events occurred in 1994, the volume of effluent totalled 7.3 x 10 L during that year (Larson, 7  1995).  Since the operation of this treatment plant began in 1963, the location and nature of the receiving environment has undergone a number of changes. The effluent had been discharged immediately into the high intertidal zone of Sturgeon Bank via a dredged sewage channel (approximately 3 m deep and 40 m wide at low tide) that ran parallel to the Iona Jetty. The effluent was transported via this 7 km long open channel over the mudflat to deeper waters of the Strait of Georgia (Pomeroy, 1983). The discharged effluent was chlorinated for approximately 6 months of the year to comply to public health concerns, mostly between May and October when swimming activities were most prominent (McGreer, 1979a). During a flood tide, however, the rising water level brought the refuse back to shore and spilled it over the edges of the channel, onto the mudflat. In 1988, $40 million was spent to improve the plant operations, including an 8 km long deep-sea outfall that extended outfromthe Iona Jetty andfinallydischarged into 100 m of water. Effluent discharged at this depth and locationfromshore should be adequately dispersed and diluted by the circulation in the outfall area which would eliminate its effects in the near shore environment on Sturgeon Bank.  Sewage pollution and its affects on an estuary As this study examines ecological aspects of a previously sewage-polluted mudflat, it is important to both understand and consider the nature of the pollution itself and how it can affect the ecological health of the mudflat. The Iona Island STP provides primary treatment before releasing the effluent into the environment.  10  Primary treatment involves the removal of suspended or large solids (by 60%) and floating material through settling and screening processes and aeration to decrease the biochemical oxygen demand of the wastewater (by approximately 35%) (Anonymous and Group, 1995). The solids removed in this process have a very harmful long-term effect on the ecology of the receiving environment. Not only do they produce significant increases in turbidity, causing reductions in light penetration and subsequent photosynthesis inhibition, these solids eventually settle out of the water column where the organic content undergoes decomposition. This results in oxygen utilization and a detrimental modification of the benthic habitat (Waldichuk, 1984).  Pathogenic microorganisms represent the greatest potential health hazardfromsewage pollution, especially with inadequate treatment and improper disposal. Shellfish beds can become contaminated in the presence of sewage effluent asfilterfeeders bioconcentrate bacteria and viruses and this contamination can then be passed on to humans through consumption (or swimming in the contaminated area) (Waldichuk, 1984).  Other components of sewage effluent that impact the surrounding area include dissolved organic constituents, nutrients and metals. Although solid waste is removed in primary treatment, dissolved organic compounds are released into the environment and their resulting decomposition will use oxygen and potentially stress the aquatic system. High concentrations of nitrogen and phosphorus are also present in sewage effluent, especially urea, ammonia, nitrate and other nitrogenous forms (Waldichuk, 1984). These nutrients generate growth by primary producers and can induce undesired algal blooms such as cyanobacteria or toxic algal species that will eventually increase the demand for oxygen in the sediments after they die, sink and begin to  11 decompose. Trace metals (Hg, Zn, Pb, Cu, Cd, Ni, etc.) are also present in sewage effluent from industrial and commercial wastes and end up in the benthic environment as they are sequestered by particulate material and bioaccumulated by organisms. Such metals have the greatest effect, of any of the pollutants found in sewage refuse, on the benthos of the receiving environment (Waldichuk, 1984).  These effects of sewage pollution only make a significant impact on the receiving environment when both a substantial amount is discharged and when the receiving area is restrictedfromwater flow and volume. Strong currents dilute and disperse the pollution and suppress the environmental effect, as does a large volume of water to receive the effluent. The wastewater dischargedfromthe Iona Island treatment plant however, amounts to 5 x 10 m d' (Larson, 5  3  1  1995) or 53% of Greater Vancouver's sewage discharges, enough wastewater each year to fill BC Place stadium over 80 times (Anonymous, 1993)! The magnitude of this waste exemplifies the importance of proper treatment and disposal. From 1963-1988, the primary treated effluent from Iona Island was discharged directly onto the intertidal area of Sturgeon Bank rendering a momentous impact on the surrounding ecology.  Why measure primary productivity on Sturgeon Bank? Sewage pollution was discharged onto the intertidal region of Sturgeon Bank for decades, causing extensive environmental degradation of the area. A measurement of primary productivity will assess the influence of the sewage waste on two important rate processes, photosynthesis and respiration on microphytobenthos and phytoplankton. The rate of primary productivity is itself affected by a number of environmental factors such as light energy, temperature, salinity, nutrient concentrations, turbidity and grazing by benthic animals and zooplankton. Oxygen evolved from photosynthesis by primary producers is also affected by both respiration by plants and that of the  12 secondary producers, benthic animals and zooplankton. In order to interpret the rates of productivity on Sturgeon Bank, the mechanisms by which these factors influence productivity must be understood.  Factors  affecting  primary  productivity  The factors affecting primary productivity may be limiting, controlling or lethal to the growth and survival of these producers. Light energy and nutrients are considered limiting factors as they are essential for photosynthesis and control cell division. Physical factors, such as temperature, salinity and turbidity affect the rate at which primary producers utilize the available energy and nutrient supplies and are therefore labeled "controlling factors" (Rice and Ferguson, 1975). Lethal levels can be reached for many of these factors when environmental conditions surpass the tolerable range or intensity, or when the conditions change considerably in a short period of time and therefore cause stress.  LIGHT  ENERGY  Light energy (photosynthetically active radiation) is important in terms of duration, intensity and penetration into water, all of which vary considerably in the natural environment. Daylength varies, in temperate regions, with season, as does intensity. Light intensity variations occur not only seasonally, but also due to meteorological variations in sun and cloud, especially in an area such as the lower mainland where cloud and rain incidents are frequent.  Light penetration is inversely related to the turbidity of the water, where high river runoff carrying sediment-laden water allows for only very low penetration of light into the water. This sedimentladen freshwater, when mixing with seawater, causesflocculationand settling offineparticles. Although much of this settling occurs in the estuary, the water over the high intertidal area is  <  13 often murky and turbid as the flocculation process has not reached completion. Turbid river water thus influences photosynthetic activities through light attenuation in the intertidal area.  Penetration of light into sediments should also be considered when studying the productivity of the benthic environment. Many diatoms that live in these sediments migrate vertically through the interstitial spaces in the sediment in search for optimal environmental conditions. Paterson and Underwood (1990) describe the complex response these diatoms exhibit to tidal and diurnal rhythms, such that they place themselves at the surface at low tide when light energy is sufficient for photosynthesis. A day/night rhythm seems to override this tidal rhythm to prevent an upward migratory response during the night. Light is reduced in the sediment pores to 1% of the incident radiation at a depth of approximately 3 mm in sandy sediment (Admiraal, 1984). Nevertheless, as insolation increases on a mudflat, the depth of the photic zone in the sediment also increases, providing additional light for photosynthesis to both the buried microalgae and to cells on the sediment surface (Pinckney and Zingmark, 1993). The biomass attributable to productivity thus changes as a function of incident radiation.  Some studies have found that benthic microalgae are not generally photoinhibited by full sunlight on the sediment surfaces (Pamatmat, 1968). Different species, however, react differently to changes in light intensity which makes generalization difficult. Although photoinhibition is less likely to occur in experiments with very short incubation periods (e.g. 10 min), incubation periods were long in this study and totaled almost a day in length. Parsons et al. (1984b) reported that photoinhibition occurs more often with long exposures and it may also increase in magnitude with time. The possibility of photoinhibition in this study may therefore exist. Different species of microphytobenthos, however, prefer different light intensities (Admiraal, 1984) and thus some  14 species would be more susceptible to photoinhibition than others. Photoinhibition would only occur in summer months under clear skies on Sturgeon Bank, nevertheless, other factors, such as high turbidity, may have a stronger influence on productivity. This is especially possible, as estuaries such as the Fraser are commonly light-limited due to low light penetration in the turbid water (Paterson and Underwood, 1990). Rice and Ferguson (1975) reported that turbidity has a greater effect on light as a limiting factor than the light intensity changes experienced at the water surface over different seasons. Turbidity would therefore be another limiting factor for primary productivity and must also be given consideration.  TURBIDITY  Turbidity is a measurement of light transmittance in water and is related, in an intertidal area such as Sturgeon Bank, to suspended solids discharged in sewage effluent, sediment-laden river water and the resuspension of sediment on mudflats by wind, waves and tides. Both colloidal and residual suspended matter are present in sewage effluent, the former of which will absorb and scatter light (Metcalf and Eddy, 1991). A high sediment content, commonly found in the freshwater entering an estuaryfromthe river, prevents light transmittance by causing heightened turbidity. Light penetration in water is therefore dependent on the turbidity of the water, and thus affects the extent of primary productivity. As estuaries are typically turbid, light penetration and turbidity significantly influence primary productivity.  As shelterfromthe Fraser River differs between the three sampling sites in this study, due to their locations, one site may be more susceptible to high turbidity in the river discharge than the others. Peak dischargefromthe Fraser River occurs in late May and June (Harrison et al., 1983) with values as high as 10,000 m s"fromJune to mid-July, averaging 3,400 m s* over the year, and 3  1  3  1  therefore have the greatest influence on turbidity in May and June (McLaren and Ren, 1995). The  15 shallow and expansive nature of the intertidal region on Sturgeon Bank is conducive to high turbidity as wind and waves resuspend sediments. The extent of this resuspension by wind, waves and tides would vary between the three sites due to differing sediment types and grain sizes. The turbidity caused in this manner can dominate and override that generated by the river discharge. Due to the direct relationship between turbidity and both river discharge and wind speed (DeGroodt and de Jonge, 1990), high turbidity values can be assumed when these other factors are high.  TEMPERATURE  Temperature controls productivity by affecting the rate of cellular activities and severe increases or decreases in temperature can lead to cell death (Parsons et al., 1984b). Both photosynthesis and respiration in primary producers are driven by temperature and therefore subject to the seasonal and daily fluctuations that occur in and on intertidal sediments due to exposure to air and insolation (Admiraal, 1984). The optimal temperature for growth varies between species, although Colijn and Buurt (1975) concluded that the optimum for photosynthesis in mixed benthic diatom populations was between 20 and 22 °C. However, other studies have shown that optimal temperatures for growth or photosynthetic rates are very specific to each species and one species' optimum was as low as 18 °C (Admiraal 1977).  The temperature that would actually limit cell growth or division also varies, but it is generally above 22 to 25 °C (Eppley, 1972). Admiraal (1977) reported an optimum temperature of 25 °C for three benthic diatom species and 18 °C for a fourth. He also concluded that all test algae grew well between 4 and 25 °C and that the growth rate increased almost linearly for these four species with temperature increases, up to their respective optimum temperatures. Temperature changes  16 on intertidal mudflats can also be radical where the sediment can increase by 10 °C in only a matter of hours (Admiraal, 1984). This temperature change would also greatly influence the photosynthetic rate and survival of the microphytobenthos.  Although intertidal mud and sandflats experience both high temperatures and strong temperature fluctuations, the temperatures in the natural environment may not reach values high enough to promote maximum growth and photosynthetic rates in microphytobenthos (Admiraal, 1977). Therefore, temperature, as well as light, would limit productivity in the Fraser River estuary and its effect will be carefully explored during the interpretation of primary productivity rates.  SALINITY  Changes in the salinity of the estuarine environment affects the growth rate and cellular processes of phytoplankton andrnicroalgae.Phytoplankton cells react by adjusting the internal salt concentration such that it is less than the concentration in the growth medium (Rice and Ferguson, 1975). Similar to temperature, the reaction of phytoplankton and rnicroalgae to salinity changes is species specific. Some species prefer low salinities, while others display highest division rates at high salinities. Estuarine phytoplankton species are generally very tolerant to changes in salinity and only radical changes would affect the productivity of these euryhaline producers. These radical changes would, however, influence species diversity in the estuary. Hoos and Packman (1974) indicated that species diversity increasesfromthe head of the Fraser River estuary to the mouth and is a function of the distancefromthe source of freshwater entering the system. Most species present in the Fraser River estuary would presumably be euryhaline and salinity would therefore not be a factor dominating productivity.  17 NUTRIENTS  Nutrient concentration, such as that of nitrogen and phosphorus, is another major limiting factor controlling photosynthesis. Phytoplankton and bottom-dwellingrnicroalgaereact to low concentrations of these nutrients by lowering their rates of cell division, whereas nutrient depletion would terminate cell division altogether (Rice and Ferguson, 1975). Generally, only one nutrient will be limiting in an estuary at one time, nitrogen being more commonly limiting to algal growth in estuaries than phosphorus or silicate. Microphytobenthos, however, are rarely limited by nutrients because sediments arerichin nutrients, especially in polluted areas (Paterson and Underwood, 1990). The Fraser River acts as another source of nutrients to the estuary, especially for nitrogen that shows seasonal trends in concentration. The highest concentrations of nitrogen in the Fraser River occur during the low flow period (Jan-Mar) due to either less dilution or lower biological utilization, or both. Lower concentrations occur during the freshet period (June) and reach a minimum in late summer. As the low concentrations coincide with peak river discharge, dilution and biological uptake seem probable explanations. Concentrations of ammonium and nitrate rangefromsummer minima to winter maxima are 1-4 uM and 2-15 uM respectively (Harrison et al., 1983). High concentrations in theriverand estuary correspond to both leaching of plant nutrientsfromsoils and farmland, which is washed into theriverthrough land drainage, and by microbial regeneration of nutrients in estuarine sediments. Water movement back and forth over the sediments with the tidal cycle encourages the release of nutrientsfromthe sediments, especially during thefloodtide when the sediment is submerged.  PLANT  BIOMASS  The biomass and diversity of primary producers present in the environment can also greatly affect the primary productivity of a certain area. The chlorophyll (chl) content is important when  18 considering photosynthetic rates and this content is susceptible to changes in environmental or physiological conditions of the cell. Phytoplankton, for example, will often reduce their concentration of chl a under nutrient deficiency and the pigment that is present will be less active than normal (Rice and Ferguson, 1975). Other environmental conditions, as mentioned previously, can also potentially stress primary producers and therefore affect the biomass present in the estuary. The biomass, directly related to productivity, will then alter the rate of productivity in the area. This may, however, differ with species. Studies indicate that although primary productivity rates are similar within a species, they vary greatly between species (Admiraal, 1984).  ORGANIC  MATTER  Degradation of organic material by microorganisms, resulting in a reduction of dissolved oxygen, can drastically affect the environment of primary producers by causing hypoxia, if not anoxia in areas where oxygen replenishment is slow. Increased amounts of organic matterfromsewage pollution enhance and promote these low oxygen conditions.  BENTHIC  ANIMALS  Benthic animals or macroinvertebrates and zooplankton also impose an effect on the rate of primary productivity as intense grazing could greatly reduce the abundance of primary producers in the incubations and therefore restrain productivity itself. Although benthic animals are not addressed in this study, extensive research has been done in previous studies, including the measurement of secondary productivity on Sturgeon Bank by Arvai (1997) and early and inaugural work on species abundance and distribution by Bawden et al. (1973), Levings and Coustalin (1975) and Otte and Levings (1975).  19 Methods  for the measurement  of benthic  primary  productivity  Primary productivity was measured using changes in the oxygen concentration over the incubation period. The C method is also used to measure primary productivity and is the 14  preferred method for pelagic (water column) samples. Although the C method is able to detect 14  lower photosynthetic rates, giving a greater sensitivity than the oxygen method and therefore incubations can be remarkably shorter, it also has its problems - especially when it is used for benthic primary productivity. There are a number of ways by which the labeled carbon may escape measurement when using this method, including adsorption to sediments (especially small grain sediments) and interference of the sediments in counting the C radioactivity taken up by 14  cells. These problems render this method less appropriate for use on an intertidal mudflat.  The measurement of oxygen changes is an easier method than C for the determination of benthic 14  productivity in the intertidal zone (Hunding and Hargrave, 1973; Revsbech and Jorgensen, 1981). Oxygen concentrations are ordinarily measured using either an electrode or Winkler titrations. The conventional Winkler titration has been improved more recently by the use of colourimetric end points that increase the sensitivity of the test. This oxygen method, although rarely used for open ocean work, is commonly chosen for measurement in coastal benthic areas (Hunding and Hargrave, 1973). One problem, however that can occur is the presence of bubbles in incubations from supersaturation of oxygen in the water. This occurs in situations where the temperature and salinity are such that oxygen will come out of solution and form bubbles. As these bubbles are not measured during a Winkler titration, an underestimate of the oxygen concentration and therefore the productivity would result. This problem would generally only transpire on sunny days for light-exposed sediment, when primary productivity and oxygen production are high.  20 Overview  of previous  studies  on Sturgeon  Bank  A number of investigations were conducted between the mid-1970s and mid-1980s to assess the area on Sturgeon Bank for the deep-sea outfall construction. These surveys accumulated baseline environmental data regarding the impact of the sewage pollution on benthic organisms, sediment characteristics, water quality, bacteriology, levels of trace metals and organic compounds, the physical environment in the vicinity of the discharge, chemical and physical characteristics of the effluent and toxicity tofish(Birtwell et al., 1983; Pomeroy, 1983)  Pomeroy (1983) reported that the practice of releasing the effluent into the channel, which frequently spilled onto the mudflat, resulted in increased habitat degradation involvingfishkills due to depressed dissolved oxygen concentrations, changes in the diversity and composition of invertebrate species, accumulation of trace metals and organic compounds, and the consequent decomposition of these organics. Parsons et al. (1973) found that benthic animals collected from mudflats on Sturgeon Bank contained higher levels of mercury, cadmium and silver than animals from similar estuarine environments in British Columbia (e.g. Cowichan River Estuary, Kitimat Arm, Roberts Bank). These elevated levels were attributed to contaminationfromthe Vancouver City sewer outfall on Iona Island.  Objective  The main objective of this study was to measure primary productivity at designated sites on Sturgeon Bank, a previously sewage-contaminated mudflat, as well as the environmental factors, such as light, nutrients, tides, turbidity, temperature and salinity that influence these rates. Primary productivity was assessed both temporally and spatially. The data collected in this study  21 also served as a comparison with work in other areas of the world, especially those with similar pollution characteristics.  22  Materials and Methods Study  site and station  locations  Three sampling stations AO, A10 and A12 were chosen on Sturgeon Bank based on previous studies (Otte and Levings 1975; McGreer 1979a, 1979b) and were marked with concrete blocks (Fig. 2). Their exact station locations are given in Table 1. The station furthest north, AO, is located approximately 100 m seaward of the high tide line at the corner between Iona Island and the Iona Jetty. This station represents the area that received the greatest impactfromprimary treated sewage effluent from 1962 to 1988 and hence, it is referred to as the contaminated site. AO is located adjacent to the channel that was dredged parallel to the Iona Jetty for effluent disposal. The intermediate station, A10 is less than 100 m beyond the western end of the landing strip of the Vancouver International Airport and approximately 5 kmfromthe contaminated site (AO) (Fig. 2). The reference site, A12, also has a sandy sediments and is located in the intertidal area just north of the Steveston jetty.  Tidal  information  Neap tides were chosen for the sampling program in order to limit the exposure of the experiment to air and intense light and therefore heating in summer months during low tides. Canadian government tidal charts for Sand Heads were used to design the sampling program for each month. All three stations were at approximately the same tidal level, and subjected to semidiurnal tides. Station set-up was scheduled at the low flood tide such that incubation chambers at both stations could be assembled andfilledmanually before water reached the stations. Dismantling of the chambers occurred at the end of the ebb tide after a 16-22 h incubation depending on the tidal regime for that month. Maximum tidal heights during spring tides reach 5  23 m at Sand Heads with minimum tidal heights of 0.5 m during neap tides. The tidal regime for each sampling day can be found in Appendix 1 - Figures 1 to 14.  24  Table 1. Location coordinates, denomination, and sediment types for sampling stations (sediment information from Arvai, 1997). Location information was attained using the Canadian Coast Guard Global Positioning System on board the Hovercraft.  Site  Station Location  Denomination  Sediment Type  Station AO  49°12.899' N  Polluted  Fine-grained (Silt/ clay)  Station A10  123°12.488' W 49°11.50TN  Intermediate Reference  Fine and coarse grained sand  Station A12  123°13.292' W 49°09.14'N  Reference  Coarse silt and sand  123°12.598' W  Transportation The Canadian Coast Guard provided the use of their Hovercraft which was integral in the execution of thefieldexperiments because any other mode of transportation would not allow for two stations to be sampled during the same tidal cycle. Thefloodtide sweeps in so quickly over the expansive mudflats on Sturgeon Bank that moving between two sites with enough time to allow assembly of equipment at both stations before the water arrived on site would have been impossible without the use of a fast moving Hovercraft.  The pilots of the Hovercraft were careful to plan both the approach and departure of each station to avoid disturbing future sampling areas. Often, the experimental equipment was carried 30 m or morefromthe Hovercraft by foot to ensure the experimental area had not been previously disturbed. Each month, the location of the chambers was recorded relative both to land and the semi-permanent concrete blocks marking the stations and a new chamber incubation site was chosen each month.  Large wooden boxes securable to the outside of the Hovercraft were designed and built to hold the chambers during transport and to minimize the mess inside the cabin of the Hovercraft (the officers responsible for cleaning the Hovercraft after use appreciated the implementation of these boxes). A large metal barrelfilledwithfreshwaterwas also tied to the outside platform of the Hovercraft to rinse both equipment and volunteers.  26  Laboratory and Field methods Sampling design and station orientation The sampling program was designed such that two of the three stations, due to tidal and time constraints, were sampled either monthly or bimonthly. Six benthic chambers (Fig. 3) were employed at each station: three clear Plexiglas chambers to allow for photosynthesis and productivity measurements and three opaque or dark chambers for respiration rates. The cylindrical chambers were 30 cm tall and 30 cm in diameter with a totalfilled-volumeof 10 L. Flanges on the sides of each chamber indicated the 15 cm mark, the depth to which they were pushed into the sediment. Therefore, all chambers contained an equal volume of water for incubation. All six chambers were lined up randomly in a transect, approximately 20 cm apart, the order of which was assigned for each sampling trip by the roll of a die. Submersible bilge pumps (Rule 360 GPH Model 24) were mounted on the inside roof of each chamber, and powered by a 12 volt battery and a microprocessor programmed to trigger the pumps for 1 min every 0.5 h. The pumps were tested and set at an appropriate speed to circulate the chamber water without disturbing the sediment. This was done to mimic the water circulation in the natural intertidal environment and therefore keep the chamber waterfromstratifying. An on/off switch on the exterior of the battery case allowed the pumps to be restarted before samples were drawn from chambers to ensure homogeneity of the chamber water. Occasionally, the battery system posed problems and the pumps failed to operate. When this occurred, it is likely that some stratification occurred in the chambers, which have would impeded the exchange of oxygen between the sediments and the overlying water; this could have produced an underestimation of the respiration occurring in the sediments.  27  t i l l Rbonly  BOTTLES = pp + zp + bact  (water only)  CHAMBERS = pp + zp + bact + bma + ba (water + sediment) Total Productivity = Benthic microalgal productivity  + Phytoplankton Productivity  B  phytoplankton <+nutrients  pp = phytoplankton zp = zooplankton bact = bacteria bma = benthic rnicroalgae ba = benthic animals P = photosynthesis Rp = respiration from plants Rb = respiration from benthic animals and bacteria  benthic > rnicroalgae  benthic fauna bacteria  Figure 3. A) An illustration of the sampling design and protocol involved to estimate benthic productivity, and B) ecological processes that occur within a benthic incubation chamber.  28 The row of six chambers was secured by a system of rebar stakes to prevent uplifting (Figs. 4 and 5), which was found to occur (up to 5 cm vertically) with tidal changes. Rebar rods lying horizontally over the chambers were maintained by other rebar stakes hammered over 1.5 m into the sediment. As the set-up for the experiment took place at low tide, water was collected directly offshorefromeach station in carboys to fill chambers manually using a pouring system to ensure the sediment surface was not disturbed. These pouring tubes were designed to fit into the chimney of the chambers, reaching down to the sediment surface with a closed bottom and peripheral holes to drain water out the sides of the tube and avoid sediment resuspension. In the event that the tide arrived before the chambers were filled in this manner, they filled naturally by the incoming tide. The chambers remained empty until the flood tide reached the height at the top of the chimneys (approximately 50 cm), and the water then poured into the chambers, disturbing both the sediment and benthic diatoms living in and on the surface. Chambersfilledthis way are referred to as "tide-filled" The chimney of each chamber was then capped with a rubber stopper to hold the water in the chamber at low tide and prevent water drainage into the sediment.  Chamber water measurements included temperature, salinity, oxygen, nitrate and ammonium, chlorophyll a and turbidity. Light penetration was measured during the daylight period and light intensity was monitored continually during the experiment. Light and dark bottle incubations accompanied chamber incubations in order to estimate the primary productivity and respiration from the plankton alone. This water column primary productivity was subtractedfromthat in the chambers to calculate the benthic microalgal productivity.  As the three stations were at similar tidal heights and the tide flooded the stations very quickly, it was not possible to measure all three stations each month. Therefore, two stations were  29 measured each month on a rotating basis (Table 2). In the months in which battery failure occurred, a second sampling trip was scheduled two weeks later such that March and June 1996, as well as August 1995 have been labeled "early" and "late" or denoted with a I or II. Field data were not collected for the time period between December 1995 and February 1996 due to poor weather conditions and ice formation in the intertidal zone. Data collection resumed in March 1996.  TERMINOLOGY TO DIFFERENTIATE BETWEEN SAMPLES As samples were taken both at different times and from different containers (chambers and bottles) in the experiment, they are referred to in this thesis according to the time and container from which they were drawn. "Initial" refers to the samples drawn or measurements taken on the first day of the experiment, before the incubation and just after the completion of the station setup. The same measurements taken on day 2 of the experiment, just prior to the incubation termination, are referred to asfinalsamples. Many of the factors measured have been considered in terms of the difference between the initial (I) and final (F) samples (F-I), in the chamber over the incubation period (e.g. temperature, salinity, nutrient and oxygen concentrations).  30  Figure 4. Photographs of field sampling at station AO in July 1996. A) After equipment assembly was completed and chambers filled manually. Note: Iona Jetty and Iona Island STP in the background (on far right). Battery unit is shown in foreground (on left) with wires leading to each chamber to operate bilge pumps. B) Bottle incubations were suspended horizontally on rebar stakes, adjacent to the chamber incubations. Note: sediment texture at AO was very muddy.  31  Figure 5. Photographs of field sampling at station A10 on July 24, 1996. A) The design of the chambers is shown containing bilge pumps for circulation, PVC chimneys for accessibility and side flanges to ensure equivalent volumes. Ronalee Marsh and Scott Hughes work chambers into the sandy sediment at this site. B) Station set up is shown with rebar stakes to prevent uplifting over two flood tides. Stakes for bottle incubations are shown in background with marking flag.  32  Table 2. Study sites and dates sampled. Two stations were sampled on a monthly basis due to tidal and consequently time constraints. Experiments were repeated for months in which problems occurred with the sampling equipment (e.g. battery failure resulting in no water circulation in chambers). Stations visited  Date 1995  1996  July 19, 20  AO, A10  August 3, 4  A10, A12  August 16, 17  AO, A12  September 19, 20  AO, A10  October 19, 20  A10, A12  November 16, 17  AO, A12  March 11, 12  AO, A12  March 26, 28  A10, A12  April 9, 10  A10, A12  May 28, 29  AO, A10  June 13, 14  A10, A12  June 25, 26  AO, A12  July 24, 25  AO, A10  August 22, 23  A10, A12  September 17, 18  AO, A12  October 23, 24  AO, A10  33  Samples drawnfromthe benthic chambers are labeled "chamber water", where the chambers are specified as either clear or dark referring to their opacity. More specifically, the chamber water that lay directly above the sediment surface is referred to as "overlying water" and the water collected offshore to fill the chambers manually is "ambient water". The flood tide water that eventually surrounds thefilledchambers is referred to as "surrounding water". Therefore, due to the prevention of water movement by the rubber stopper in the chimney of the chamber, the ambient water inside the chambers did not exchange with the surrounding water outside the chambers. However, the surrounding water changed twice a day with the semi-diurnal tide.  Oxygen  concentration  determination  The production and consumption of oxygen in chamber incubations, the bell-jar technique, was the method chosen to estimate primary productivity. Samples were drawn, using a siphon-like system, to measure the oxygen concentration of chamber water at each site before the incubation and on the following day to terminate the incubation. The system used to draw the samples from the chambers was engineered such that two tubes emergedfromthe same rubber stopper that was fitted into the bottle neck to create suction. One tube leadfromthe chamber into the sample bottle and the otherfromthe sample bottle to a vacuum/ pressure bulb. Air displacedfromthe bottle by pumping the bulb was thus replaced by chamber water. The tube leading into the sample bottle emptied the water at the bottom of the bottle to avoid contamination by air. Sample bottles were overflowed and subsequently tapped on the side to dislodge any air bubbles before capping.  Another set of glass stoppered bottles, secured at the same depth as the chambers, measured net productivity and respirationfromthe phytoplankton community. These clear and dark bottles corresponded to the clear and dark chambers. The securing mechanism held the bottles by their neck such that they were suspended horizontally in the water column, and were either capped or  34 sealed with parafilm wax and elastics. These bottles were filled with the same water as the chambers and incubated simultaneously in identical environmental conditions as the chambers (i.e. same depth). They were analyzed for oxygen concentrations by Winkler titration at the end of the experiment.  Oxygen samples werefixedimmediately on board the Hovercraft with 3 ml of each of MnCl (3 2  M) and NaOH (8 N) solutions in 300 ml sample bottles, or 1 ml of each reagent in 125 ml bottles. Samples were shaken and placed in the dark until titration. Chamber and bottle water samples were analyzed within 48 h of the incubation using the Winkler titration method (Strickland and Parsons, 1968). Calculations are outlined in Appendix 2.  To confirm the accuracy of the titration method, a YSI dissolved oxygen meter (Model 57) was used in addition to the titration method in August 1996 (Appendix 3). An azide modification of the Winkler titration method (Greenberg et al., 1992), used to control the interference of nitrite when measuring oxygen, was tested and found not to be significantly differentfromthe standard Winkler titration (Appendix 3). Sediment in the water may have interfered with titrating samples from AO for a few of the sampling months. Some of the reagents added to stabilize the oxygen in the sample may have become bound to the sediment and would therefore produce an underestimate of the oxygen present in the sample.  Incubations in clear bottles represented the net oxygen evolved by phytoplankton in the water column, which incorporates any respiration by phytoplankton or zooplankton. Benthic chambers included the additional net production by benthic and planktonicrnicroalgaeas well as respiration by benthic and planktonic animals. All oxygen concentrations were calculatedfromthe titrations  35 (in ml L" ) and used to calculate primary productivity as described in Appendices 4, 5 and 6. All 1  productivity values were expressed as mg C m" h' or, for values normalized to chlorophyll a, as 2  1  mg C mg chl d h". x  Phytoplankton  1  biomass  Samples drawn for the measurement of chl a concentrations included waterfromeach chamber, the surrounding water and bottle incubations. A vacuumfiltrationapparatus was employed to filter 125 ml of each sample onto GF/Ffilters.In later months of the study, thefilterswere subsequentlyfrozenin plastic ziplock storage bags for later analysis, while earlier in the study, samples were processed immediately. This change was made for convenience due to the tightly scheduled sampling program. Extraction was completed by adding 10 ml of 90% acetone to each sample, shaking and sonicating for at least 20 min followed by overnight extraction in the refrigerator. Chl a was then determinedfromsamples diluted with 5 ml of 90% acetone for every 1 ml sample using a Turner 10-AU fluorometer and the following equation: chl a ( ug L" ) = 1.974 (F -F ) (1/0.9489) (v/V) 1  0  a  where F„ is thefluorescencebefore acidification, F is thefluorescenceafter acidification, a  v is the volume of solvent/acetone (ml) V is the volume of samplefiltered(ml)  (modifiedfromParsons et al., 1984a)  An initial reading (F ) was taken that measured the amount of both chl a and phaeopigment in the 0  sample. Three drops of 10% HC1 were then added to samples followed by inversion to mix the acid and a subsequent reading (F ) was taken to determine the amount of phaeopigment in the a  sample. The difference between these readings (F -F ), with additional conversions, gave the 0  a  active pigment concentration or "biomass as ug chl a L' or mg chl a m". l  3  36 Both phytoplankton and benthic microalgal biomass were reported in terms of chl a in addition to phytoplankton percent change values, or the phytoplankton growth in chamber water over the incubation period expressed as a percent. The term "growth rate" will be used to refer to this change in chl a over the incubation period. Phaeophytin was measured and subtractedfromchl a concentrations and therefore the chl a concentrations reported are assumed to be photosynthetically active and contributing to primary productivity.  Benthic microalgal biomass Benthicrnicroalgaein the sediment under each chamber were sampled using 3 topless 30 ml syringes. These syringes were pushed vertically into the sediment to a depth of more than 10 cm following the removal of the chamber at the end of the incubation. The top 4 cm of the core was used at station AO, while 8 cm was analyzed at both A10 and A12. These depths were chosen based on previousfieldwork which delineated the vertical distribution of chl a. The cores at each station werefrozenfor up to 3 weeks, then thawed and cut at 4 or 8 cm. They were then shaken in 150 ml of 95% acetone in either polypropylene or polyethylene 250 ml bottles and refrigerated overnight before fluorometric analysis as described above.  These sediment core depths (to 4 and 8 cm) were too deep as the photosynthetically active benthicrnicroalgaeresides within the top cm or less of sediment and chl a measured below this depth would overestimate the biomass contributing to primary productivity. Deep core depths (4 to 8 cm) would also not be comparable to published values because most studies use only the top 0.5 cm (Colijn and de Jonge, 1984; Sundback et al., 1991) to 1 cm (Varela and Penas, 1985; Rizzo and Wetzel, 1985b) of sediment for biomass measurements. To correct for these deep cores, an experiment was completed in May 1997 to determine the amount of chl a in the top 2, 5 and 10 mm sediment depths. Samples (n = 5) were scraped directlyfromthe sediment surface in  37 0-2, 2-5 and 5-10 mm sections using a flat aluminum sheet. Cores were cutfromthe sediment on this sheet using corers of the depths mentioned to ensure equal circumference and volume between replicates. To serve as a check, shallow cores (n = 2 or 3) were also taken with a topless syringe such that the sediment surface was not disturbed by the plunger or during transport. These cores were carefully cut into the depth sections mentioned above in order to obtain an estimate of the benthic microalgal biomass in each layer. The correction of biomass values with these new data is demonstrated in Appendix 7 as well as the initial calculations to obtain benthic microalgal biomass in units of mg chl a m' . Other samples were collected in the same trip to 2  study the distribution of microphytobenthos biomass in sediment surface ripples (sand ripple troughs versus crests). The resultsfromthis test are shown in Appendix 8.  Primary  producer  identification  Benthic microalgae and phytoplankton were identified to generafromoverlying chamber water and are shown in Table 3. Benthic microalgaefromthe sediment surface, were not analyzed due to improper preservation techniques.  Nutrient  analysis  Samples drawn for nutrient analyses werefilteredimmediately on board the Hovercraft into acidwashed polypropylene 30 ml wide-mouth bottles through pre-combusted (460 °C for 4 h) Whatman 25 mm GF/Ffiltersand kept on ice during transport to the lab. An acid-washed syringe and tube were used to draw the samples forfiltering.Nutrients measured included nitrate and ammonium and intentionally excluded both phosphate and silicate. Phosphate binds easily to sediment (K. Yin, pers. comm.) and therefore, it is difficult to measure. Silicate is in great abundance in this estuary and not limiting to primary productivity.  38 Ammonium concentrations were determinedfromfilteredwater samples immediately upon arrival in the lab using an adaptation of reagent and sample volumesfromthe manual spectrophotometry method (Parsons et al., 1984a). The remainder of the nutrient samples werefrozenfor subsequent nitrate analysis. After samples were thawed, nitrate (and nitrite) concentrations were analyzed on a Technicon AutoAnalyzer II using the cadmium column method of Wood et al. (1967). The 11  concentration of nitrite in these samples was so low that these nitrogen concentrations will be referred to hereafter as "nitrate" concentrations.  Physical  and chemical  parameters  TEMPERATURE AND SALINITY Temperature and salinity were measuredfromthe chamber water using a YSI temperatureconductivity meter (Model 33) both before the incubation and prior to disassembly of the chamber configuration. Appendix 9 contains chamber temperature and salinity averages before and after incubation.  LIGHT INTENSITY AND ATTENUATION Light penetration in water was determined by lowering a Li-cor Quantum meter (Model 185a), over the bow of the Hovercraft, eitherrighton station if the tide was in, or straight offshore where the deeper water was assumed to represent the water that wouldfloodthe station. Measurements were taken at 1 m intervals in 1995 and at 30 cm intervals in 1996, either on station at a sufficient tidal height, or directly offshore in deeper water (Appendix 10). These light measurements were taken during the daylight hours of the experiment and were used to calculate the extinction coefficient (k) as follows: k = 2.3(logI -L,)/Z-Z z  0  where I is the light intensity at a given depth Z z  l o is the light intensity at the surface or initial depth Z is the given depth Z is the surface or initial depth 0  A pyrheliometer, placed on the roof of the Coast Guard Hovercraft base prior to sampling, continuously recorded the variation in solar intensity over the course of the sampling period area under these light intensity curves is given in Appendix 11.  WIND SPEED AND TURBIDITY Turbidity of the water was determinedfromeach sampling trip in the Environmental Engineering laboratory at the University of British Columbia using a Hach turbidity meter (Model 2100a). Water samples for turbidity determination were collected in 250 ml polyethylene wide-mouth bottles and stored in the dark until analysis. Daily average wind speeds were acquired from Environment Canada's meteorological data index, published monthly.  Calculations A series of calculations were completed with the data, the most intricate of which were productivity rates and microphytobenthos biomass calculations. The productivity calculations were neither straightforward nor easily accessible in published literature and are thus detailed step-by-step in Appendices 4, 5 and 6. These computations are project-specific which, in this case, involved determining the rate of primary productivity for the chamber and bottle incubations separately and subsequently using these data to arrive at the benthic microalgal rate of productivity. This was done by subtracting the phytoplankton productivityfrombottle incubationsfromthe total productivity (phytoplankton plus benthic microalgal productivity) in chamber incubations. The difference between these two rates is the productivityfrombenthic microalgae alone.  40  Calculations were also completed to determine the primary productivity over the whole day, as incubation periods varied in length each month and did not necessarily incorporate the entire daylight period of the sampling day. The missing portion of daylight productivity was then backcalculated and added to the measured rate to achieve the total rate of primary productivity over the day.  Benthic rnicroalgae biomass was more straightforward and only became complex when the correction factor was incorporated to determine the biomass in the top 0.5 cm of sediment from the preexisting data of 4 to 8 cm depths. These calculations and corrections are outlined in Appendix 7.  Statistical  analysis  As productivity was influenced by an array of environmental factors, stepwise multiple regressions (Zar, 1996) were completed in an attempt to analyze the productivity results after the removal of these factors. More specifically, the relationships between productivity and light, temperature and biomass were determined. Analysis of variance (ANOVA) tests were also used to compare productivity at the 3 experimental sites. An assessment of temporal (seasonal) variation was also made for both benthic microalgal biomass and net benthic and phytoplankton primary productivity using ANOVAs and Tukey tests. Data were grouped for this assessment into spring (March I, March II, April and May), summer (June I, June II, July and August) and fall seasons (October and November 1995, September and October 1996). Tukey tests were applied, according to Zar (1996), to determine which of the three seasons (or the 3 stations for spatial variation) differed from each other.  41  Results Nutrients  Since most primary producers require a concentration of nitrate plus ammonium greater than 1-3 uM for photosynthetic activities (Syrett, 1981), nitrogen concentrations were saturating for growth in all months, at all stations except for the initial water samples in late June 1996 at station AO (Fig. 6B), July 1996 at A10 (Fig. 7B) and late June 1996 again at A12 (Fig. 8B). Nitrogen concentrations in June were, however, more than sufficient for growth on the final day of the incubation at AO and A12. On the other hand, July 1996 nitrogen concentrations remained low throughout the incubation and could potentially have limited productivity at A10. These very low concentrations may have been due to the incident of freshwater collected from the Fraser River discharge for the incubation. Nutrient values also changed minimally over the incubation period for most months (Figs. 6 to 8-A).  At AO, the porewater ammonium concentrations were extremely high (averagesfrom200-700 uM) relative to the overlying water (generally 0-60 uM) (Fig. 9). It is assumed that very high ammonium concentrations found in the water column, for example in September 1996 at station A12 (1,183 uM), were caused by sediment disturbance while placing the chambers, and the subsequent release of ammonium. Nitrate porewater concentrations (2-12 uM) did not, however, differ greatlyfromthe nitrate measured in chamber overlying water (generally 0-15 uM). Due to sandy sediments at A10 and A12, porewater samples could not be obtained.  42  Nutrient concentrations at station AO 60  A t  Station AO production  F- 40  F-  20  Q  T -20  a  consumption  - Nitrate - Ammonium  i r  —i—i  —i—i—i—r~n #  1995  ^  ^  ^  i  ^  ^  i ofi  h  -40  h  -60  r O*  1996  30  Nitrate Ammonium  170  Initial values  25 20 15 10 5  t  O 140  -«— Nitrate -o— Ammonium  0  t  20 15 10 r^5  1995  &^ ^ ^ ^ ^ 1996  Figure 6. Nitrate and ammonium concentrations at station AO expressed as: A) the  difference between initial and final nutrient concentrations over the incubation period, and B) actual initial and final nutrient values. Initial and final ammonium  concentrations were 170 uM +/- 56 and 140 uM +/- 52, respectively in September  1995 and final values of 92 uM +/-17 in July 1996. Error bars represent one standard  error with n = 3.  ~  » 1  Final values  #  c  o •••-» CD  O 92  5 -q  |  o  x"  Z  43  Nutrient concentrations at station A10 — A — Nitrate  A  Ammonium  Station A10  40  production I  60  *  I  20  v  0  no  P  -20  consumption  -40 -60  # 1995 Initial values  ^ ^ 1996  ^  ^  ^  Nitrate Ammonium / \  ^  o*  B  A  30 25 20 15 10 5  Final values  0  Nitrate Ammonium  25 20 15 F- 10  # &^ 1995  ^ ^  1996  Figure 7. Nitrate and ammonium concentrations at station A10 expressed as A) the difference between initial and final nutrient concentrations over the incubation period and, B) actual initial and final nutrient values. Ammonium initial concentrations were 52 pM +/- 28 in June 1996 and 39 u.M +/- 26 in August. Error bars represent one standard error with n = 3.  44  Nutrient concentrations at station A12  1995  1996  Figure 8. Nitrate and ammonium concentrations at station A12 expressed as A) the difference between initial and final nutrient concentrations over the incubation period and, B) actual initial and final nutrient values. Initial ammonium concentrations averaged 67 uM +/- 25 in June 1996 and 33 uM +/-15 in September 1996. The initial nitrate concentration in November 1995 averaged 30 uM +/- 14. Final ammonium values reached 48 uM +/-27 and 1183 uM +/-193 in August and September 1996, respectively. Error bars represent one standard error with n = 3.  45  Porewater nutrients at station AO  1995 Figure 9. Porewater nitrate (solid symbols) and ammonium (open symbols) concentrations at station AO from March to November 1995. Error bars represent +/- one standard error and n=3. (From Bendel-Young et al., in press).  46 Temperature  All stations showed seasonal changes in the chamber water temperature with a number of months reaching 20-23 °C (Figs. 10-12). As 25 °C has been determined as the upper limit above which temperature will inhibit productivity in temperate areas (Parsons et al., 1984b), it was assumed that temperature was not a limiting factor for primary productivity in this study. Nevertheless, all temperature measurements were scheduled around the tidal regime, and taken only at the beginning and end of the incubations, and therefore maximum temperatures may not have been measured. For example, chamber #6 at AO in July (Appendix 6k) was recorded at 23.5 °C in the mid-morning (10:00 am) and at 20.1 °C just before the termination of the incubation at 4:00 am the following morning. Since the low tide occurred at 6 pm, chambers would have been completely exposed to the intense mid-summer sunlight (and therefore extensive heating) as early as 3 pm. Therefore the water temperature in the incubation chamber could have risen upwards to 25 °C or higher during the late afternoon. Salinity  The salinity of the chamber, bottle and surrounding water generally stayed within a tolerable range for primary producers throughout the study (6-20 ppt) (Rice and Ferguson, 1975) (Figs. 10-12). The main exceptions occurred at station A10 in May, July and August of 1996 when the water collected offshore to manually fill the chambers had extremely low salinity because it was part of thefreshwatersurface layer formed by the Fraser River plume. The salinity in May and August was approximately 3 ppt and in July at almost 0 ppt with very little change over the incubation period. These low salinities would have likely stressed the benthicrnicroalgaein the chambers, or possibly even caused cell death. Therefore, low salinity was likely a major factor affecting  Temperature and salinity at station AO 1  A  E  Station AO £  4  *  4  a>  6  CD  S -C  O  o 0 -2  <D  2 a)  a.  E  2  2  I  O Q  S  n .  °  <  1  o  1  -2  _4  • O #  1995  0  ~  ^ ^ 1996  ^  Temperature Salinity  -4 -6  ^  20 16 12  8 £  4  1  o  ro i_  • O  Initial values  Temperature Salinity  20  E  0 16  CD  CL  4  16  12  CD  12  8  8 4  • O  ~3 Final values  0  i—r 1995  —m #  ^  i r~n ^  ^  ^  Temperature Salinity  i i ^ o f i  r  4 0  O*  1996  Figure 10. Temperature (solid symbols) and salinity (open symbols) at station AO expressed as: (A) changes during the incubation period (initial vs. final readings), and (B) actual initial and final values. Error bars represent +/-1 SE with n = 3.  Temperature and salinity at station A10 e -q  c  A E-  Station A10  4  F-  4  P  2  -2  =  -4q  ± A  -6 -q  —i—m—i—r 1995  & ^  -6  m—i—i—r  —m—i #  Temperature Salinity  &  V ^ c / O*  1996  20  1995  1996  Figure 11. Temperature (solid symbols) and salinity (open symbols) at station A10 expressed as: (A) changes during the incubation period (initial vs. final readings), and (B) actual initial and final values. Error bars represent +/-1 S E with n = 3.  49  Temperature and salinity at station A 1 2  Station A 1 2  A  M M  a n  „  n  7T  n  e  £ I  B  •  Temperature Salinity  T T T #  ^  ^  O*  ^ofi  ^  1996  1995  20  20 16  B h 16  H  12  12  8  8 4  H  a •  Initial values  Temperature Salinity  h  4  h 16 12 8  • •  Final values  —i 1995  m  i f  Temperature Salinity  —m—i—m—i #  ^  ^  ^  ^  ^ c f i  i  r O*  1996 Figure 12. Temperature (solid symbols) and salinity (open symbols) at station A12 expressed as: (A) changes during the incubation period (intial vs. final readings), and (B) actual initial and final values. Error bars represent +/-1 SE with n = 3.  50 primary productivity in these months. However, bottles were filled with this water for incubation and the phytoplankton in the water would not have experienced the same stress.  Turbidity  and wind  speed  Maximum water turbidity may not have coincided with the initial and final sampling times for each incubation. Therefore, daily average wind speeds were used in addition to the turbidity measurements to interpret the degree of turbidity each month, and hence, its effect on primary productivity. These values were acquired for the two sampling days and the day previous to sampling, in case a storm occurred prior to measurement (Figs. 13-15). Storm events can be seen in both May and July 1996 for stations AO and A12. A correlation was found between the average wind speed and turbidity at both stations, in both months, except for AO in May. This station, being more sheltered by the Iona Jetty, may have partly escaped the influence of the wind or, more probably, samples did not represent the maximum turbidity experienced that day. The spring freshetfromthe Fraser River also brings a large sediment load into the estuary and greatly enhanced turbidity in May and June. In November 1995, a storm occurred overnight during the experiment which is apparent in both the turbidity measurements at AO and A12 and the wind speed data (Fig. 15).  Sediment  texture  The sediment at AO was extremelyfine-grainedand muddy, and was black and anoxic 8 cm below the sediment surface. The intermediate site displayed a sandy and firm sediment type, and was encroached upon by the brackish marsh in the spring and summer months. The marsh, however, did not extend to the site during any part of this study. At station A12, large amounts of the diatom Melosira sp. were found during spring months, which trapped a small volume of water even at low tide. This caused sediments to loosen somewhat and become softer. A significant  Figure 13. Average wind speed (open diamonds) in km h" and water turbidity (solid circles) in nephelometric turbidity units (NTU) at station AO in 1995 and 1996. 1  52  Wind speed and turbidity at station A10  25  Station A10  h 20  Wind speed  \- 15  h 10  Turbidity  —i 1995  1—i—r  i  1  r~^i  i  i  r~  1996  Figure 14. Average wind speed (open diamonds) in km h" and water turbidity (solid circles) in nephelometric turbidity units (NTU) at station A10. 1  bz  Wind speed and turbidity at station A12  1995  1996  Figure 15. Average wind speed (open diamonds) in km h" and water turbidity (solid circles) in nephelometric turbidity units (NTU) at station A12. 1  54 population of large clams, Mya arenaria, was also found year round at this location within the top 20+ cm of sediment.  Primary  producer  biomass  Phytoplankton and benthic microalgal biomass are plotted, for each station, using axes of an equal scaling to show the relative differences between these two groups (e.g. from 0 to 200 for station AO; Fig. 16-Ai), and on adjusted scales to provide more detail (e.g. Fig. 16-A ). 2  STATION AO At station AO, phytoplankton chl a showed a strong seasonal trend with higher concentrations in summer months than spring and fall and an obvious bloom in late June 1996. Elevated phytoplankton biomass was also exhibited in November 1995 after a characteristic fall bloom. Generally, the phytoplankton biomass ranged between 1 and 6 mg chl a m" with the June 1996 3  bloom of 31 mg chl a m". The overall average was 5.6 mg chl a m' with the bloom included and 3  3  2.3 mg chl a m" without. Note that these values are "initial" pigment concentrations from before 3  the incubation (Fig. I6-A2). The percent change in chl a (an index of growth rate) ranged between 50 and 90% in most months, with one anomalous peak in September 1995 to almost 130%. However, the standard error around most of these percent change values is quite large and therefore, there is no definite seasonal pattern.  Benthic microalgal chl a was much higher (up to one order of magnitude higher) than that of phytoplankton in all months of 1996 (Fig. 16-Ai). A seasonal trend was less apparent in the microphytobenthos than the phytoplankton community as even the fall months, September and October 1996 displayed high benthic biomass values. Microalgae populations also experienced an early spring bloom in March, where values were equivalent to those in summer months.  55  Chl a concentrations at station AO IS c 0  p-  150  E  phytoplankton  (0  1 2  ° o. g> o c  100  j  31  H  1 'E  E- 100  in * O J=  z-  2 °  50  h  800  *  TO 600  h  phytoplankton  c  I  benthic rnicroalgae  £  2H ^  tU,Y ^  ^  o*  400  h  ^  E, in (0  E o  g co  -5.  150  V) in  o  E, in in as E  c: _ro a. o  200  <u E 1 0 0 0 CQ —  t  Station AO 8  j  LLJJ  50  0 10 E co  | A ^r-  benthic rnicroalgae  1 ^  CD =  200  CD  ^  ^  /  ^  c £  ^  O  f i  1996  1995  160  i—i—i ^ 1995  i r ^  # ^ ^ ^ ^ afi ^ n—i—m  i  i r  1996  Figure 16. Biomass (chl a) of primary producers in clear incubation chambers at station A O : A ) Phytoplankton (open bars) and benthicrnicroalgae(solid bars) chl a concentrations on equal scales (A.,) and adjusted scales (Aj). B) Phytoplankton percent change over the incubation period, where 100% represents a doubling of the chlorophyll a biomass. Error bars represent +/-1 standard error and n = 3.  56  STATION A10 In contrast to station AO, no phytoplankton bloom was measured at A10, although this station was not sampled in late June, the month of the bloom at AO. A seasonal pattern was apparent for chl a with higher values in summer months than spring or fall (Fig.  These values were so  I7-A2).  low (< 2 mg chl a m") in comparison to the microphytobenthos biomass that the contribution by 3  phytoplankton to the total primary productivity was insignificant (Fig. 17-Ai). The percent change in chl a over the incubation period (Fig. 17-B) also demonstrates the relatively inactive phytoplankton at this station, with a generally constant percent change between 35 and 65% across the sampling period. Overall, the growth rates at this station, or percent change in chl a values, were less than those at stations AO (Mean = 63%) and A12 (Mean = 50%) with an average of 47% in 1996.  Benthic chl a at A10 was higher than either of the other two stations, reaching values of 1,100 mg chl a m" or greater in April, June, July and August 1996 (Fig. 17- Ai and A ). Summer months 2  2  were generally higher than spring and fall values, with a spring bloom in April.  STATION A12 A seasonal trend was also apparent in both the benthic and phytoplankton chl a concentrations at station A12, the reference site, although the benthic component in July was lower than expected (Fig. I8-A1 and A2). Overall, this station exhibited lower benthic chl a concentrations than station A10, but higher than the polluted site, AO.  Phytoplankton at this station also bloomed in late June to greater than 30 mg chl a m' , which 3  coincides with the bloom at AO. All other months had generally low phytoplankton biomass,  Chl a concentrations at station A 1 0  ^  ^ ^  o* ^  ^  1995  ^ ^  ^  ^  ^  ^  1996  ^ 1995  ^  O*  ^  # ^ ^ ^ ^ ^ of 1996  Figure 17. Biomass (chl a) of primary producers in clear chambers at station A10: A) Phytoplankton (open bars) and benthic microalgae (solid bars) biomass. Concentrations of chl a in the benthic community exceeded 1000 mg m" in April, June, July and August 2  1996. B) Phytoplankton percent change over the incubation period, where 100% represents a doubling of the chl a pigment concentration. Error bars represent +/-1 standard error and n = 3.  58  Chl a concentrations at station A12 |  700 600 » 500 |«C 400 • 300 §•1 200 1 g> 100  I  benthic rnicroalgae  1  a £  E co  CO (A CO  E g in c  $  II  o  10  ,  I  U  phytoplankton  ii i n i  A,  t  Station A12  r  A„P 2L  31  8H  phytoplankton  h  700 600 8 500 If 400 .2 E 300 CO eg 200 I ^ 100 II 0 1000 800 600  6H  benthic rnicroalgae 400  I  200  Q.  ^ ^ of  Q. O  I I  ^  ^  I  ^  ^  ^ ^ ^ ^ ^ of n m i  O*  ^  Hi  r  1996  m i m i # ^ ^ ^ ^ ^  r ^  0  *  1996  1995  Figure 18. Biomass of primary producers in clear chambers at station A12: A) Phytoplankton and benthicrnicroalgaechlorophyll a concentrations. The phytoplankton in late June peaked at an average 31.1 mg chl a m' S E 1.8. B) Phytoplankton biomass percent change over the 3  incubation period. A percent change of 100% represents a doubling of the biomass. Error bars represent +/- 1 S E and n = 3.  f  CO O) CO  e  c JS  1995  CD  CD  4H  o  E !E o  g E o  JZ  c m  O*  59 ranging between <1 and 2 mg chl a m", except for higher values in early June and August (up to 3  4 mg chl a m' , not including the bloom in late June). The overall average phytoplankton biomass 3  was 4.6 mg chl a m", or 1.65 mg chl a m' without the bloom. Although this average was slightly 3  3  greater than that at A10, the distribution of the values over the months is skewed by the higher summer values. The biomass at A10 was more consistent. The percent change in chl a indicated phytoplankton growth in all months at A12, with values in early spring as low as 20%.  Primary producer identification Microphytobenthos and phytoplankton were identified to generafromthe water samples taken from the chambers (Table 3). Navicula spp., Nitzschia spp. and Cryptophyceae were found in abundance in water samples identified along with somefreshwaterphytoplankton. Surface sediment samples were spoiled due to improper preservation techniques. However, due to the sediment disturbance and resuspension of benthic microalgae that takes place upon station set-up, many benthic diatoms were found in the water column samples. Detailed accounts of the phytoplankton, benthic microalgae and other primary producers that exist in the Fraser River Estuary are given by Harrison (1981) and Hoos and Packman (1974) in Appendix 13.  Primary productivity Note that "net productivity" in this study was influenced by animal respiration, because the respiration that occurred in chamber incubations included both plant and animal respiration. Therefore, net productivity was assumed to be underestimated and respiration rates (by primary producers) overestimated, resulting in increased gross productivity rates. The animal respiration in the chambers could resultfromeither benthic invertebrates or zooplankton in the water or, more likely, both. Zooplankton respiration would typically be less than phytoplankton respiration  60  Table 3. Phytoplankton and benthic rnicroalgae identified in chamber water samplesfromthe study sites on Sturgeon Bank.  Marine genera  Freshwater genera  Chroomonas sp.  Amphora sp.  Coscinodiscus sp.  Cyclotella sp.  Cryptomonas sp. *  Cymhella sp.  Navicula spp. * Nitzschia spp. * Melosira sp. Skeletonema costatum Synedra sp. * most abundant  61 due to a lower biomass, where benthic animal respirationfromthe sediment would be substantial and could likely affect productivity.  Net productivity is also influenced by the array of environmental factors previously outlined, the most important of which are the availability of light energy, nutrients, and temperature. Wind speed is directly related to turbidity which, in turn, affects light penetration in the water column. Temperature, salinity and tidalfluctuationsare the other environmental parameters needed to interpret productivity results.  STATION AO Benthic microalgal productivity Gross productivity by the benthic microalgae community at the contaminated site, AO, showed a strong seasonal trend with lower fall and spring rates and higher summer productivity (Fig. 19-A; calculations shown in Appendix 6). These gross productivity rates, however, included both plant and animal respiration which also displayed higher activity in warmer summer months (shown as the difference between gross and net productivity on Figure 19-A). Net benthic productivity followed a similar seasonal pattern, but was more limited by other environmental conditions. In May, July and September 1996, for example, reduced light availability due to high turbidity in the water column hindered photosynthesis. This increase in turbidity was expected in May due to the Fraser River springfreshetthat causes a dramatic increase in river discharge. Some of the turbidity values measured during these three months were only moderately high (Fig. 13) because sample collection, most likely, did not coincide with peak turbidity values.  Primary productivity at station AO  1995  1996  Figure 19. Gross and net productivity in the: A) benthic community in chamber incubation and B) phytoplankton community in bottle incubations at station AO. The productivity of the benthic community was determined from the total productivity in the chambers minus the productivity of the water in the chambers (represented by the productivity in the bottles). Note: the rate of plant and animal respiration can be estimated from the difference between gross and net primary productivity. Error bars represent +/-1 SE and n = 3.  63 Although productivity in June was high, the response may still have been reduced by the turbidity from the springfreshet,as seen in May. Productivity in October 1996, on the other hand, was not affected by turbidity and was actually much higher than expected for late fall. A fall bloom is implicated for this high productivity as the benthic biomass remained high through to October. Lower temperatures in October would also facilitate lower respiration rates by plants and animals and consequently, the higher net productivity measured.  The normalization of productivity to chl a revealed a higher ratefromthe benthic producers in May than in June, when productivity was the highest (Fig. 20). This shows that the microbenthic biomass in May was actually more productive than the summer months (per unit chl a). October 1996 exhibited the highest benthic assimilation rate due to low biomass. Phytoplankton productivity The phytoplankton community at the polluted site showed similar productivity to benthic populations. During July and September 1996, productivity was lower than anticipated due, most likely, to turbid water. However, turbidity values reported in September were low, but peak turbidity probably did not coincide with the time of sampling. Although productivity in July fits the seasonal pattern, the response would have likely been greater if turbidity was lower.  Productivity per chl a values revealed very high productivity by the phytoplankton biomass in March, which coincides with a period of increased growth due to favourable environmental conditions in early spring. In May, the low productivity (both gross and net) may have been a consequence of zooplankton grazing in the bottle incubations as the abundance of the copepod Neocalanus plumchrus, for example, peaks in the Strait of Georgia around this time (Harrison et al., 1983). Thefreshetis also strong in May, favouring a reduction in net productivity because of  64  Productivity normalized to chl a 2.00  40  Station AO  35  Benthic rnicroalgae Phytoplankton  h  1.75  ^ o  30 H  1.50  §f  1.25  O o> E  o  E  25  I  20  h  1.00 "S 3  3  "O  o  o  0.75  o 22 | o •ss. °-*—' a>  i  Q.  \ - 0.50  10 5  h  0.25  &  co E •c c Q. CD  .O Q  •*—* CD  0.00  1995  1996  ^  ^  ^  Figure 20. Biomass-specific productivity for benthic rnicroalgae and phytoplankton communities, expressed as assimilation numbers (mg C mg chl a' h" ) at station AO. Note: any negative values are not shown. Error bars represent +/-1 SD and n = 3. Phytoplankton productivity in November 1995 displayed a very high average of 54.7 mg C mg chl a" h" +/- 22.8. 1  1  1  1  Z  65 the increase in water turbidity. Net productivity in June presented a duplicate situation to that in May, in which the freshet depressed productivity.  Unexpectedly, November 1995 exhibited the highest gross and net productivity in bottle incubations at this contaminated site. Assimilation numbers, or productivity per chl a, were also the highest in this month (Fig. 20). The phytoplankton biomass and nutrient concentrations favoured high productivity, whereas turbidity and weather conditions did not. A storm significant enough to warrant a marine storm warning occurred overnight during the November experimental period. This resulted in high turbidity and significantly reduced light conditions in the benthic environment. However, the biomass was very high, paralleling that in March 1996 and nitrate concentrations were high and actually surpassed ammonium. Therefore, although the environmental conditions do not provide an explanation, high productivity was observed in November.  STATION A10 Benthic microalgal productivity Net benthic primary productivity was highest in June at station A10 and coincided with substantial respiration rates, a result of the warm summer conditions (Fig. 21-A). Productivity expressed per chl a is also highest in this month (Fig 22). Other summer months with lower productivity suggest an interaction with environmental factors. The low salinity situation described for AO also affected A10 in May, July and August with salinity as low as zero parts per thousand (Fig. 11). This freshwater may have been the limiting factor during these months, although July also experienced nutrient concentrations that approached limiting concentrations, as well as possible high temperatures and turbidity.  Primary productivity at station A10  1995  1996  Figure 21. Gross and net productivity at station A10 from the: A) benthic community, and B) phytoplankton community in bottle incubations. April 1996 produced gross and net phytoplankton productivity rates of -0.157 mg C L' h' +/- 0.001 and -0.15 +/- 0.001 respectively. The productivity of the benthic community was determined from the total productivity in the chambers minus the productivity of the water in the chambers (represented by the productivity in the bottles). Error bars represent +/-1 standard deviation and n = 3. 1  1  67  Productivity normalized to chl a 0.50  40 .c 35 '<o o 30 —  Benthic microalgae  Station A10  |  :  | Phytoplankton  g  O cn E, 25  0.45  JO.  0.40  JE  0.35  "•8  20 —  =3 (J  o c o CD  a. o Ja.. *^ a)  Z  I  -  15  -  0.30  E  0.25  ••s  0.20  5  3  •D O i Q_  10  o o> E O O)  _  >  'co  0.15  -  0.10  -  0.05  -  CO  E  •c CL O c a>  .a  a>  Z  0.00  1*  ^  ^  ^  Figure 22. Biomass-specific productivity for microphytobenthos and phytoplankton communities, expressed as assimilation numbers (mg C mg chl a" h' ), at station A10. Note: any negative values are not shown. Error bars represent +/-1 SD and n = 3. 1  1  68 Benthic primary producers in April displayed moderately low productivity that was expected for this time of year. Typical low rates were also seen in October of 1995 and 1996, accompanied by lower ratios of respiration to net productivity than observed in warmer months. Although October 1996 yielded low productivity, the benthic microalgal biomass was particularly high (Fig. 17). Phytoplankton productivity The low salinity experienced in May did not decrease phytoplankton productivity as it did in July and August (Fig. 21-A). In fact, phytoplankton productivity in May was the highest at station A10. Phytoplankton productivity in July and August, nevertheless shadowed the low rates from the benthic community as they were correlated with these very low salinities. Negative gross and net productivity values were observed in both April and October 1996 because oxygen consumption exceeded production. Low light intensity was most likely the cause in October, while zooplankton grazing and respiration could have been significant in April. As mentioned earlier, copepods are especially abundant in the spring and could easily have affected the phytoplankton populations in the bottles givingriseto this high oxygen consumption and consequently negative productivity values.  Phytoplankton productivity per unit chl a was high in October of 1995. This demonstrates that although the productivity does not seem high (Fig. 21), it is very high relative to the biomass of primary producers present in the water at the time (Fig. 22).  STATION A12 A seasonal trend was also apparent in both gross and net productivity rates at the reference site, A12 (Fig. 23-A). Respiration rates were high in all months even though organic matter in the  69  Primary productivity at station A12 140  1995  1996  Figure 23. Gross and net productivity at station A12 from the: A) benthic community in chamber incubations, and B) phytoplankton in bottle incubations. The productivity of the benthic community was determined from the total productivity in the chambers minus the productivity of the water in the chambers (represented by the productivity in the bottles). Note: the rate of plant and animal respiration can be estimated from the difference between gross and net primary productivity. Error bars represent +/-1 SD and n = 3.  70 sediments was low. However, large bivalves were abundant in this area and, although their density and biomass were not measured, qualitative observations indicated that their abundance might partially be responsible for these high respiration rates. Zooplankton abundance in the estuary generally peaks in early spring and might have played a compounding role with the bivalves to produce the high benthic respiration found in March and April 1996 in chamber incubations.  In the bottle incubations, oxygen consumption exceeded oxygen production by phytoplankton in April and September 1996, and therefore, oxygen concentrations actually decreased in the clear bottles. Furthermore, this oxygen consumption in the light bottles exceeded that in the dark bottle incubations, and thus both gross and net productivity values remained negative (Fig. 23-B). The incidence of oxygen consumption in the light bottles could have been due to zooplankton grazing, which could have been greater than oxygen evolution in these months, and would have increased respiration and decreased phytoplankton biomass.  Respiration rates were also very high in early June and August in both the microphytobenthos and phytoplankton communities, and coincided with high summer temperatures; this resulted in lower net productivity values. However, respiration rates in the bottle incubations in late June were not high even with high temperatures.  Both gross and net productivity in early June deviatedfromthe typical high summer, low fall productivity trend as these rates were lower than anticipated. The environmental conditions experienced at station A12 in June did not reveal an obvious explanation for this depressed productivity. Battery failure over the incubation period resulted in a lack of circulation in the  71 chambers and might be responsible for the low productivity rates. This concurs with the events in bottle incubations as the battery does not affect these incubations and the phytoplankton productivity did not experience the same depression. Although one would assume an overestimated net productivity rate with a battery failure event, the intricacies of the chamber ecology cannot be clearly deciphered and one can only speculate on the processes that occurred.  Assimilation numbers revealed very high productivity by the phytoplankton biomass in March of 1996 (Fig. 24). This result was also seen at AO and was most likely a precursor of the spring bloom that was more obvious in April of 1996. In support of this, both the benthic biomass and primary productivity were high in April. A similar situation was found in November 1995 where both productivity and biomass values were higher than normal values at this time of year.  Insufficient solar irradiance was likely responsible for the low productivity in September 1996 from both the microphytobenthos and phytoplankton populations. The chambers were also tidefilled in this month, corresponding to high respiration rates. Although turbidity measurements in September were low, continuous samples were not taken during the incubation and relevant and significant fluctuations may have occurred. The increase in wind speed over the course of the experiment supports this possibility. The consumption of oxygen in clear bottles, detailed earlier for April 1996, occurred again in September and yielded negative values for both gross and net productivity. The interrelationship between high wind speed, turbidity and low light penetration facilitated the high oxygen consumption.  A surprisingly high productivity rate was measured in October 1995 for the benthic microalgal community. Favourable weather conditions were reported at this time along with high nutrient  Productivity normalized for chl a 1.0 Benthic rnicroalgae Phytoplankton  CO  1z  u  0.8  h  cn E O o> E  0.6  ••§  3 T3 O L-  0.4  Q.  Er CO  E  Q. O  0.2  'Jo  c  CD CD  0.0  1995 Figure 24. Biomass-specific productivity for microphytobenthos and phytoplankton communities, expressed as assimilation numbers (mg C mg chl a" h" ) at station A12. Phytoplankton productivity in March reached an average of 55.7 mg C mg chl a' h' SD 22.8. Negative values are not shown. Error bars represent +/-1 standard deviation and n = 3. 1  1  1  1  73 concentrations which support high productivity. Benthic microalgal biomass was quite low at this time, and was accompanied by low phytoplankton productivity at A12. In addition, low productivity for both the phytoplankton and microphytobenthos at A10 suggested that this high benthic primary productivity found at A12 was a result of analytical error. It is not uncommon, nevertheless, to find a very productive, low biomass of primary producers and the environmental conditions in this situation favoured higher productivity. Therefore, the possibility remains that the benthicrnicroalgaeat station A12 were the only community to respond to the favourable environmental conditions and yield high productivity values in October, 1995.  Statistical  results  RELATIONSHIPS BETWEEN PRODUCTIVITY AND ENVIRONMENTAL FACTORS The stepwise multiple regressions examined the productivity results once the environmental factors, with potential to influence primary productivity, were removed. However, the regressions showed that neither light energy (both penetration to 1 m and total light), temperature nor benthic microalgal biomass correlated with either benthic productivity or phytoplankton productivity (p-values on Table 4). The enormous amount of variation that occurs in the intertidal region could mask the effect of these ecological parameters. For example, one might have expected that light would limit primary productivity in early spring and late fall. However, the incubations on Sturgeon Bank were subject not only to seasonal changes in light intensity, but also daily variations in solar irradiance, cloud cover and rain, as well as tidal height variations; high water submerged the incubations resulting in light attenuation by both water and suspended solids. Therefore, in order to properly assess the relationship of light and primary productivity, each of these variables would require continual (perhaps hourly) measurement throughout the incubation period. A similar argument can be made for temperature, or any of the environmental  74  Table 4. Statistical results (p-values): Regression analyses of environmental factors (light penetration to 1 m water depth, total light, temperature, salinity and biomass) against benthic microalgae and phytoplankton net productivity (NP) at three stations. Productivity values (mg C m' daylight hr' ) involved the photoperiod only. Note: total light values were derivedfromlight intensity pyrheliometer curves (number of squares). 2  1  AO  Regression  A12  A10  Phytoplankton NP vs. light penetration tolm  0.52  0.89  0.41  Benthic microalgae NP vs. light penetration tolm  0.54  0.80  0.91  Phytoplankton NP vs. total light  0.21  0.49  0.63  Benthic microalgae NP vs. total light  0.20  0.68  0.19  Phytoplankton NP vs. temperature *  0.50  0.31  0.80  Benthic microalgae NP vs. temperature *  0.85  0.49  0.44  Phytoplankton NP vs. salinity *  0.60  0.32  0.04  Benthic microalgae NP vs. salinity *  0.61  0.39  0.13  Benthic microalgae NP vs. benthic biomass  0.25  0.57  0.94  * Net productivity values in mg C m" h'. 2  factors that varied greatly over the incubation period. Both temperature and oxygen changes would need to be monitored more frequently throughout the incubation period to determine their relationship with productivity.  SPATIAL VARIATION - COMPARING STATIONS In order to assess the differences between the threefieldsites, ANOVAs were executed on the gross and net productivity data both in units of "per daylight hour" (light period only) and "per hour" (Table 5). Using the raw data set, both gross and net productivity per daylight hour showed spatial variation for all of the chamber incubations, bottle incubations and benthic productivity estimations, with the exception that net daylight productivityfromthe chamber incubations did not differ significantly between the three sites. The productivity expressed "per hour" was similar to the daylight productivity. Although the graphical interpretation of the results was done in "per hour" productivity units, the statistics were completed for the productivity in the photoperiod only, in an attempt to uncover trends in the productivity without the added confusion of respiration at night.  Tukey tests results, comparing the productivity at the three sites, revealed significantly higher benthic gross productivity at the muddy, contaminated site (AO) than at the site with a sandier sediment texture, A10 (Table 6). This result was found regardless of what productivity units were used. The same result was presented both in terms of gross and net productivity for the phytoplankton community. Phytoplankton gross productivity at station A12 also outweighed that at A10, although this was found in terms of hourly productivity and not for the daylight period only. This suggests that the respiration was what differed between the two sites, not the productivity, as the hourly productivity has nighttime respiration incorporated into it. Estimated  76  Table 5. Results from ANOVA (p-values) showing the spatial variation in gross (GP) and net (NP) productivity in the chamber incubations (total productivity), and phytoplankton and benthic microalgae populations on Sturgeon Bank.  Total producers  Phytoplankton  Benthic microalgae  GP (photoperiod)  1.42 x lo *  0.0004 *  2.4 x 10" *  GP (hourly)  9.6 x lo *  0.001 *  5.6 xlO" *  NP (photoperiod)  0.195  0.003 *  0.0016 *  NP (hourly)  0.379  0.011 *  0.0002 *  ANOVA  -5  -5  * denotes a significant difference (p < 0.05) betweenfieldsites.  6  6  77  Table 6. Tukey test results (q-values) comparing gross and net productivity between the three sites in total (chamber incubation), phytoplankton (bottle incubation), and benthic productivity. Qcriticai = 3.57 (at a = 0.05, v = 21 and k = 3). Any value above q nticai shows a significant difference between the productivities at the two sites. C  Tukey test  Stations  Total producers  Phytoplankton  Benthic rnicroalgae  GP (photoperiod)  GP (hourly)  NP (photoperiod)  NP (hourly)  AO vs. A10  6.1 *  5.9 *  5.3 *  A10 vs. A12  0.5  3.0  2.0  AO vs. A12  0.9  2.7  7.8 *  AO vs. A10  5.4 *  5.4 *  4.3 *  A10 vs. A12  0.6  3.5 *  2.9  AO vs. A12  2.2  1.9  7.7 *  AO vs. A10  N/A  5.0 *  3.4  A10 vs. A12  N/A  2.4  1.4  AO vs. A12  N/A  2.5  5.2 *  AO vs. A10  N/A  4.4 *  3.06  A10 vs. A12  N/A  2.6  2.7  AO vs. A12  N/A  1.7  6.2 *  * q-value > q critical, so the null hypothesis was rejected, and a significant difference was found.  78 benthic productivity (as well as the productivityfromthe chambers) was also greater at the contaminated site than the reference site.  TEMPORAL VARIATION - SEASONAL TRENDS Seasonal trends were observed (Table 7) for both benthic microalgal biomass and benthic gross productivity where they were both more pronounced in summer months than in the fall (p = 0.002 and 0.011 respectively). These differences were found, specifically between June and September 1996, using ANOVA and Tukey tests on the raw data set (as opposed to averaged data). Differences between spring and summer or spring and fall were not significant for either the benthic microalgal biomass or its productivity.  79  Table 7. Summary of statistical resultsfromANOVAs and Tukey tests to determine seasonal differences in benthic microalgal biomass and benthic gross and net productivity. Chamber and bottle productivity values are not shown as there were no seasonal differences. Test Benthic gross productivity  ANOVA  Seasons all three  Tukey tests  spring & summer summer & fall  Result P = 0.011 * q = 2.07 q = 4.43 *  spring & fall  q = 1.87  Benthic photoperiod net prod.  ANOVA  all three  p = 0.82  Phytoplankton photoperiod NP  ANOVA  all three  p = 0.45  Benthic microalgal biomass  ANOVA  all three  p = 0.002 *  Tukey tests  spring & summer summer & fall spring & fall  represents significantly different values  q = 2.28 q = 5.24 * q = 2.96  80  Discussion ENVIRONMENTAL FACTORS RELATED TO PRIMARY PRODUCTIVITY In many studies involving primary productivity and community metabolism, estuarine ecologists attempt to discern patterns of primary productivity and its relationship with a series of environmental parameters, most notably temperature, light energy and algal biomass (Van Es, 1982; Hargrave et al., 1983; Varela and Penas, 1985). Although the requirement of nutrients (especially nitrate and ammonium) in photosynthetic processes are also widely accepted and well documented, coastal areas are generally nutrient-rich (especially polluted areas) due to the abundant and continual supply by sediments and riverine input, and are therefore rarely nutrientlimited (Paterson and Underwood, 1990). Tidal height is another factor affecting productivity as it dictates the length of time the tidal flats are exposed, and thus is especially important during the photoperiod. However, all three sites on Sturgeon Bank were at the same tidal height and therefore duration of exposure during low tides was similar. This eliminated tidal height as a source of variation and therefore, the effect of tidal variation on productivity was not explored. The effect of influential environmental factors on primary productivity was explored using regression analyses in order to interpret the productivity once these influences were removed.  The effect  of temperature  on primary  productivity  Temperature is often a controlling factor for estuarine community metabolism, including primary productivity and respiration. The use of bell-jar incubations to determine primary productivity provided the possibility of an even stronger influence by temperature due to the likelihood of heating in bottle and chamber incubations, especially when tidal exposure coincided with high light intensity. Although most benthic microalgal species show some tolerance to temperature  81 changes, water in the incubation chambers on Sturgeon Bank could easily have risen to lethal or intolerable temperatures for some species due to heatingfromair exposure and high incident radiation at low tide, especially in summer months (Admiraal, 1977). The event of overheating in both bottle and chamber incubations would also introduce supersaturation of oxygen and could cause oxygen to come out of solution and form bubbles. Although it was very difficult to discern this occurrence in the field, saturation limits were calculated for the warmest months and suggest that this phenomenon may have occurred in May and July.  Although there is a strong argument for a temperature effect on productivity, a correlation was not found between primary production and water temperature. Some studies have found a strong influence by temperature on productivity, whereas others have not. Van Es (1982), for example, reported weak correlations between primary production and abiotic parameters in the EmsDollard estuary, although community respiration showed the highest correlation with temperature. Varela and Penas (1985) examined the relationship between productivity and temperature in the water column, andfromthe sediment at both high and low tides. Once again, temperature was not found to directly regulate productivity during any of these conditions. Colijn and de Jonge, (1984) also support thesefindings.Therefore, although the controlling effect of temperature on productivity is well known, and the possibility of a direct correlation exists, it was difficult to discern this relationship in this study due to the interplay of other environmental factors.  Was solar irradiance correlated with productivity? Light availability, as a factor limiting primary productivity, is similar to temperature in that not only are the two factors directly related ecologically, but their impact on primary production is widely accepted and well studied (Admiraal and Peletier, 1979; Admiraal, 1984; Paterson and  Underwood, 1990). Light energy and its availability, however incorporates a number of other parameters which affect primary productivity. The availability of light to primary producers is primarily dictated by weather conditions (sun, cloud, rain, etc.), which influences light intensity and the photoperiod, which varies seasonally. Light energy is also attenuated in water due to refraction, absorption and scatter by water molecules and suspended solids in the water.  . TURBIDITY EFFECTS ON LIGHT PENETRATION Turbidity due to suspended solids and sediment in the water column reduces light penetration, and hence influences productivity. There are a number of ways by which turbidity can originate. Probably the most common generation of turbid water in estuaries results from the combination of wind, wave and tidal forces causing resuspension of sediment. Shallow intertidal areas such as Sturgeon Bank are especially well mixed during storm events. This situation often occurred during experimental periods with high winds forming large waves that resuspended sediment. Wind speed data reflected these storm events and are generally followed by increased turbidity. Turbidity samples were not taken continuously throughout the incubation period and some peak values were most likely unrecorded, such as in September 1996 at stations AO and A12. During this time, the wind speed data suggest the occurrence of sediment resuspension, but turbidity values were low. Furthermore, weather conditions were favourable, yet the productivity at AO and A12 was low in September. These variables and conditions imply that high turbidity inhibited light penetration and, in turn, productivity.  Increased turbidity also occurs on Sturgeon Bank during the spring freshetfromthe Fraser River that carries a substantial amount of sediment into the estuary. The effect of thefresheton turbidity was most prominent at station A10 which is more exposed to theriverdischarge than AO or A12 because it is closest to the Middle Arm of the river. The high average wind speed that  83 occurred during May at A10 may have resuspended sediment and added to the turbidityfromthe freshet. In this case, the two sources of turbidity were indistinguishable. However, the impact of thefresheton turbidity was obvious in June 1996 when the wind speed was almost zero, yet turbidity was very high. This suggests that thefreshetcaused more turbidity than the resuspension of sediments.  Elevated levels of particulate organic matterfromprimary treated effluent discharges, although not measured in this study, have been documented at the contaminated site (Bendell-Young et al., in press). Particulate organic matter is also prone to resuspension and decreases light penetration in addition to suspended sediments. Therefore, an increase in turbidity, whetherfromthe freshet, organic matter resuspension or sediment disturbance, plays a significant role in reducing light penetration and thus decreasing benthic productivity.  LIGHT AVAILABILITY, TIDAL VARIATION AND VERTICAL MIGRATION Although correlations were not found between irradiance and productivity (light penetration to 1 m or total irradiance), this does not eliminate light as a limiting factor in photosynthetic processes, but merely confirms the complexity of estuarine dynamics and the difficulty in teasing apart the influence of a single environmental factor in the intertidal region. Varela and Penas (1985) also reported no relationship between productivity and light (total solar radiation over their incubation period) on the sandflats of the Ria de Arosa, Spain. However, they did find a correlation between productivity and tidal variation which was directly related to the light available to benthic microflora. During the high tide period, productivity was only 30% of the total daily benthic productivity due primarily to particle size and water turbulence. On the other hand, Joint (1978) observed no productivity at high tide (cf Varela and Penas, 1985).  84 The study by Van Es (1982) in the Ems-Dollard estuary, which was remarkably similar to my study on Sturgeon Bank, did notfindthat solar radiation explained the productivity results in either the spring or fall, but a correlation was observed with tidal level in the spring (although a weak correlation) and winter. The tidal level of a station dictates the duration of sediment exposure at low tide and also corresponds to vertical migration behaviour by diatoms through interstitial spaces in the sediment. Paterson and Underwood (1990) have documented that epipelic (free-living) diatoms respond to tidal and diurnal rhythms such that they migrate down into the sediment at high tide and surface at low tide when light is sufficient for photosynthesis. Therefore, the epipsammic (attached)fractionof the microflora comprise the bulk of the benthic microalgae present for primary production during a flood tide. This phenomenon of vertical migration was also observed by Varela and Penas (1985) where 75% of their high tide production was attributable to epipsammic diatoms. Only 60% of the low tide productivity belonged to this benthic microalgalfraction,although both percentages are suspected to be underestimates of the total productivity due to the methodology used. On the other hand, both epipelic and epipsammic diatomfractionswere found to photosynthesize during exposed tides.  In addition to this vertical migration of diatoms, the drainage of porewater at low tide would also affect the vertical distribution of benthic microalgae and thus, their productivity. The epipelic diatoms that would normally migrate to the sediment surface at low tide, may have been unable to reach the surface to photosynthesize due to their transportation downwards with porewater drainage. Yin et al. (submitted) found that the sandy sediments at A10 and A12 resulted in more porewater drainage than the muddy sediment at the contaminated site and suggested that this drainage was responsible for the deeper distribution of chl a at station A10.  85 Although the tidal levels were approximately the same for the three sites on Sturgeon Bank, the tidal regime and sampling design may have resulted in underestimates of net productivity. All experiments were conducted during neap tides where the low tide does not ebb as far as it does during spring tides, and therefore exposure to direct light was reduced. Both the chamber and bottle incubations were sealed to prevent water leakage or exchange and therefore, any rnicroalgae in the chamber incubations were covered with water even at low tide. This would have mimicked a high tide and may have affected the vertical migration pattern of epipelic diatoms and consequently, the productivity. Therefore, the epipsammic proportion of the benthic diatoms would have been the predominant contributor to primary productivity and an underestimate of productivity could have resultedfromboth this "constant" high tide and the shorter exposure times associated with neap tides.  Penetration of light through closely packed sediment also affects the amount of light received by benthic rnicroalgae. Light sufficient to support photosynthesis only penetrates to approximately half a millimeter into the sediment (Paterson and Underwood, 1990). Therefore, migrating diatoms must place themselves within this depth to photosynthesize. Unfortunately, epipsammic diatoms cannot adjust their location with the photic zone in the sediment and in the event that they are buried by resuspended sediment or organic matter settling out of the water column, they will not be able to photosynthesize. This burial, as well as the vertical migration by epipelic diatoms, provides an explanation why active chlorophyll can be detected at depths greater than the sediment photic layer. High concentrations of chl a were found as deep as 10 cm in the sediment at station A10 on Sturgeon Bank (Yin et al., submitted).  86  LIGHT ATTENUATION DUE TO RESUSPENSION OF MICROPHYTOBENTHOS Benthic diatoms can also be resuspended into the water column, and thus contribute to phytoplankton productivity in the water column. This resuspended benthic microalgae would also be mistaken as phytoplankton biomass when measuring the chl a content of the water column. Resuspension could have occurred whenever the chambers were incidentally tide-filled upon the assemblage offieldequipment. The manualfillingof chambers was meant to avoid this disturbance, but during some experiments, it was unavoidable. It should be noted that resuspension would introduce some error into the productivity measurements, as well as the biomass values.  Resuspension of benthic microalgae, as well as the other factors mentioned, affects the penetration of light in the water column and these effects on light availability makes a definitive correlation with productivity difficult. The abundance of the benthic primary producers also usually affects productivity, as discussed in the next section.  Was benthic microalgal biomass a controlling factor for benthic productivity? It is generally accepted that plant biomass is related to productivity and thus, an increase in the abundance of primary producers should lead to an increase in production. However, there are ecological factors that may mask this seemingly direct correlation. Benthic chl a concentrations were not found to correlate with productivity at the study sites on Sturgeon Bank. One explanation for this result involves the use of chl a to determine the biomass. Plant pigments are present in the benthic environment in both active (chl a) and inactive (phaeopigments) forms and down to depths to which incident radiation never reaches. Therefore, much of the chl a existing in the top few centimeters of the sediment is not photosynthetically active. In fact, Varela and Penas (1985) reported that only 15% of the total chl a in the sediment was in the active form and  87 small amounts of this active pigment were as deep as 7 cm in the sediment. A similar result was found on Sturgeon Bank with the presence of chl a as deep as 10 cm (Yin et al., submitted). Light penetration through the water column affects the depth of penetration into the sediments and thus, the depth of active chl a. Therefore, the depth of benthic microalgae that are photosynthetically active in the sediment will vary as a function of light penetration through both the water and sediment.  In addition to the vertical variation in benthic diatom distributions, microalgae can also exhibit a heterogeneous or patchy horizontal spatial distribution. The phenomenon of "patchiness" has been reported to be prominent in the Fraser River Estuary and therefore, was considered in the arrangement of incubation chambers (Sewell, 1996). Patches of benthic microalgae could exist within one meter of sediment, or even less. The transect of chambers covered a distance of approximately 3 m of sediment in an attempt to reduce the effect of a heterogeneous spatial distribution.  Another complicating factor that should be considered when examining a correlation, between algal biomass and productivity is the diurnal vertical migration of microalgae. Epipelic diatoms migrate to the surface to photosynthesize during low tides and retreat back to depths in the sediment during high water. Therefore, their movement would add another source of variation to the productivity results.  Although Varela and Penas (1985) did not investigate the relationship between microbenthic biomass and gross primary productivity, Van Es (1982) reported a strong correlation between the two parameters, as would be expected, theoretically. These resultsfromVan Es (1982) do not  88 agree with the findings in this study. In my case, either the interaction of environmental factors on Sturgeon Bank disguised this relationship or productivity was simply independent of biomass.  Grain size and the effect on benthic diatom composition and production Light, temperature and nutrients have, until now, been the main focus as factors that affect primary productivity on Sturgeon Bank. The actual composition of the sediment can also play a significant role in defining the assemblage of benthic primary producers. In order to assess this influence, one mustfirstdefine the sediment textures at thefieldsites. Station AO is extremely muddy with more than 70% of the sediment in the 63 pm size fraction (coarse silt) or less (Fig. 25). A very small proportion of the sediment (less than 5%) represents the larger grain sizes of 180 um (fine sand) or larger. Similar to AO, station A10 also had a fairly homogeneous composition, with 75% representingfinesand and less than 5% of either the <63 um (clay) or 250 um (fine to medium sand) grain sizes. A bimodal distribution was evident in the sediment types from station A12, with the highest percentages in the 63 and 250 umfractions.Approximately 45% of the remaining sediment represented grain sizes between these two extremes, and less than 5% was <63 um. This location also had the largest representation in the medium and coarse sand categories. To summarize the sediment compositions at the three stations, AO and A12 exhibited the extremes of clay andfinesand respectively, with A10 somewhere in the middle, displaying evenfinersand.  Muddy sediment, with low porosity and thus little to no desiccation, has a high organic content, especially at a station like AO, with decades of sewage effluent input. Areas such as this generally  68  90 yield high benthic microalgal productivity. Sand, on the other hand presents a different situation. The mechanics of sand particle movement can damage algal cells and influence the growth and composition of benthic diatom assemblages. Delgado et al. (1991) studied this effect on sandflats in Spain and found that diatoms receive a varying degree of damagefromresuspension and turbulence of sandy sediments.  Furthermore, sediment grain size at a location is also a function of exposure and the input of organic material (Colijn and Dijkema, 1981). Currents and tides, that create water movement in exposed areas, easily cause the resuspension and distribution offinerparticles. Therefore, particulate organic material and sediment of the smallest sizefractionare only abundant in sheltered areas. A correlation also exists between the degree of exposure (indirectly related to organic content and directly related to tidal height) and the sediment chl a concentration. In a calm and protected area, we would then expect tofinda higher concentration of chl a, accompanied by a higher percentage of epipelic diatoms. Cadee and Hegeman (1977) confirmed that chl a increases with increasing clay content of the sediment (cf Colijn and Dijkema, 1981). Chl a is related to grain size due to the varying preferences of diatoms to specific sediment types. For example, Delgado et al. (1991) described that epipsammic diatoms (attached) predominate in exposed localities where epipelic diatoms are generally predominant in sheltered areas. Epipelic forms are more easily lifted and transported by currents and tidal resuspension, whereas the adhesive lifestyle and small size of epipsammic cells demonstrate a strategy to resist suspension forces. Therefore, this interconnected relationship between site exposure, organic content and the assemblage and chl a concentration of benthic algae also influences primary productivity.  91 After this investigation of the possible influences of numerous environmental factors in an intertidal region, some questions remain: how did primary productivity vary temporally on Sturgeon Bank and do these rates differ between the sewage-contaminated site and the other two locations examined on this mudflat?  92  ECOLOGICAL SPATIAL VARIATION ON STURGEON BANK The order of benthic primary productivity measured at the three study sites on Sturgeon Bank was AO > A10 > A12, while the benthic microalgal biomass was in the order A10 > A12 > AO. The following sections will address benthic and phytoplankton primary productivity at each site in detail, and examine the related factors to explain the results. However, although a comparison will be provided with valuesfromother estuaries, the sections will focus primarily on the between-site variation.  THE CONTAMINATED SITE, AO Station AO was subject to sewage pollution until the implementation of the deep sea outfall in 1988, and since then recovery has been proceeding. The observations made in this study, 7 and 8 years after the reduction of sewage pollution at AO, suggest that this previously "polluted" site could now be reclassified as a "fertilized" area. The detrimental effects of pollution, especially the heavy organic loading, have decreased. Decomposition activities have reduced the organic content of this area (Thomas, 1997), and these activities result in the subsequent release of available nutrientsfromthe porewater (Bendell-Young et al., in press). These nutrients are now likely responsible for the high levels of productivity.  Benthic algal biomass in the top cm of sediment, at AO, was the lowest of the three sites and averaged 102 mg chl a m" over the study period. However, these values were within the general 2  range of published values (Table 8). Pigment concentrations were fairly constant over the seasons, a result also observed by Varela and Penas (1985). High summer biomass values in 1996 continued into September and even October which corresponds to high fall biomass values  93  Table 8. Benthic microalgal biomass (chl a) reported in the top 1 cm of sedimentfromintertidal areas in various estuaries. Study  Benthic microalgal biomass (mg chl a m~) <424  Area  2  Bawden et al. (1973)  Sturgeon Bank  Otte and Levings (1975)  <1000 •  Sturgeon Bank  Colijn and Dijkema (1981)  < 100  Dutch Wadden Sea, Netherlands  Harrison (1981)  SAND  <250  Iona North, Fraser River Estuary  Harrison (1981)  MUD  <450  Iona North, Fraser River Estuary  Hargrave et al. (1983)  <500  Upper Bay of Fundy, NS, Canada  Colijn and de Jonge (1984)  <500  Ems-Dollard Estuary, Wadden Sea  Varela and Penas (1985)  < 103  Ria de Arosa, NW Spain  Rizzo and Wetzel (1986)  <236  York River, Virginia, USA  Pinckney and Zingmark (1993)  < 120  North Inlet, South Carolina, USA  Yin et al. (submitted)  <600  Sturgeon Bank  Present study  <200  Sturgeon Bank - station AO  Present study  < 1200  Sturgeon Bank - station A10  Present study  <450  Sturgeon Bank - station A12  • Values measured at a polluted site. * Note: valuesfromthe present study are for the top 5 mm of sediment only.  94 measured by Bendell-Young et al. (in press) on these mudflats and by Hargrave et al. (1983) in the Upper Bay of Fundy, Nova Scotia. Although no correlation was found between microphytobenthos biomass and productivity over the whole year, some monthly relationships are evident such as the coincidence of the fall bloom in October 1996 with a peak in productivity.  Neither the micro- nor macrofauna have been thoroughly investigated at this location since the implementation of the deep-sea outfall, although Arvai (1997) provided information on two benthic infaunal species, an amphipod, Corophium salmonis and a bivalve, Macoma balthica. He found a greater mean biomass and density of C. salmonis at the contaminated site than either of the reference sites. Under the assumption that recovery processes have started and are well underway at AO, both the density and diversity of the benthic fauna would be expected to increase from the lower levels typical of polluted areas to higher, more natural levels. Arvai (1997) has shown that this is indeed the case at AO, where C. salmonis abundance and biomass increased substantially between 1973-74 and 1994. Although C. salmonis feeds on detritus as well as microphytobenthos, other species of benthic macroinvertebrates were also found at this site and help explain the lower benthic microalgal biomass. The increase in biomass of these consumers, and their inevitable increase in grazing intensity will impact primary productivity.  Grazing by the micro- and macrofauna may be responsible for lower levels of benthic rnicroalgae at AO compared to A10 and A12. Previous studies have shown that benthic invertebrates, amphipods for example, graze on benthicrnicroalgae(Pomeroy and Levings, 1980). The larger abundance of C. salmonis, for example, at AO, would exert a higher grazing pressure on microphytobenthos (Arvai, 1997). These amphipods are primarily deposit feeders and scrape epipsammic diatoms and organic matter off particle surfaces, or gather epipelic diatoms and other  95 foodfromthe sediment surface. Therefore, their abundance and feeding behaviour may explain the low benthic microalgal biomass at this location. Arvai (1997) also reported a lower biomass of thefilterfeeder, Macoma balthica in this polluted area. If the density of this species is indicative of the entire population offilterfeeders at AO, then this would clearly explain the higher biomass of phytoplankton found at this site than the reference sites. The sediment composition is too fine for Macoma balthica, even considering the high organics available as food. Benthic productivity Primary productivity was high at AO, both in comparison to the other two sites and to published values. All polluted sites reviewedfromthe literature showed higher productivity than their controls or less polluted areas (Van Es, 1982; Hargrave et al, 1983; Colijn and de Jonge, 1984; D'Avanzo et al., 1996). The average gross benthic productivity at AO was 238 mg C m" h' over 2  1  the year and ranged between 30 and 408 mg C m" h' . Most values reportedfromother estuaries 2  1  using the oxygen method to measure primary productivity are much lower. However, this average from station AO does not incorporate the winter season and thus, would be overestimated. Table 9 summarizes annual primary productivityfromthis study, as well as published valuesfromdifferent estuaries. The high primary productivity at AO is supported further by high assimilation ratios of productivity to biomass. These ratios show that this contaminated site was not only more productive than the reference sites, but it was more productive per unit biomass; the productivity was the highest with the lowest biomass. Figure 26 clearly illustrates this relationship between benthic biomass and benthic primary productivity at AO and the two reference sites.  Respiration rates were also high at the contaminated site on Sturgeon Bank due to the abundant supply of organic matter present. Warm summer months related to very high rates of benthic  96  Table 9. A comparison of benthic microalgal productivity values (in g C m' y") from other areas (adapted from Varela and Penas, 1985). 2  1  Area  Pomeroy (1959) *  Annual production (gC m" yr ) 200  Pomeroy (1960) *  213  Boca Ciega Bay, Florida  Grontved (1960)  116  Danish fjords  Source  2  Pamatmat (1968) *  1  143-226  Duplin River Estuary, Georgia  Puget Sound, Washington  Leach (1970)  31  Ythan Estuary, Scotland  Marshall et al. (1971)  81  New England estuaries  Buntetal. (1972)  11-60  Florida and Jamaica estuaries  Cadee and Hegeman (1974)  101  Dutch Wadden Sea  Van Raalte et al. (1976)  105  Falmouth Bay salt marsh, Mass., USA  Cadee and Hegeman (1977)  85  Dutch Wadden Sea  Riznyketal. (1978) Joint (1978)  115-246 143  Bolsa Bay, California Lynher Estuary, England  Colijn and de Jonge (1984)  62-276  Ems-Dollard Estuary  Colijn and de Jonge (1984)  44-1314  Ems-Dollard Estuary -sewage polluted site  Varela and Penas (1985)  79  Ria de Arosa, NW Spain  Present study  88-2190 **  Sturgeon Bank - station AO  Present study  131-1300 **  Sturgeon Bank - station A10  Present study  44-438 **  Sturgeon Bank - station A12  * oxygen method ** overestimates because do not include lower winter values (March to October only)  "ANNUAL" BENTHIC MICROALGAL BIOMASS  AO  A10  A12  Station  "ANNUAL" BENTHIC PRIMARY PRODUCTIVITY  AO  A10  A12  Station Figure 26. A) Benthic microalgal biomass, and B) benthic primary productivity annual values for 1996 at stations AO, A10 and A12. Note: values represent averages between March and October only.  respiration, that were more than double the net productivity in June and July. These high respiration rates contributed to the very high gross benthic productivity that occurred in this area. Net primary productivity values were within the range of published data (approx. 10 -250 mg C m" h" with an average of 95 mg C m' h' over the year) and were very similar to those reported 2  1  2  1  by Colijn and de Jonge (1984) in the Ems-Dollard estuary (<10 -150 mg C m' h"). Note that 2  1  the range in net productivity reached a maximum of 250 mg C m" h" due to a peak in October 2  1  1996 in response, most likely, to the fall bloom. Phytoplankton productivity The phytoplankton community was generally affected by the same environmental factors as the benthic microalgae, except for the additional influence of grazing by zooplankton in May. This effect was far more prominent on phytoplankton than benthic productivity. A large peak in zooplankton abundance was, in all likelihood, responsible for this grazing. Neocalanus copepods, for example, are known to peak in April and May (Harrison et al., 1983). In comparison to microphytobenthos, phytoplankton productivity contributed a rather insignificant proportion of the total production. In fact, Varela and Penas (1985) found benthic productivity was approximately 10 times greater than phytoplankton productivity in the water column. Findings such as these substantiate and confirm the focus of intertidal productivity studies on the benthic community.  Productivity at AO was consistently higher than either of the other sites, regardless of the low benthic microalgae biomass, and most likely arosefromthe nutrient supply in the sediments. Porewater nutrient concentrations measured at this site confirmed that nutrient limitation was not a concern for cell growth. Ammonium porewater concentrations alone exceeded the nutrient  99 quota required for photosynthesis by over 40 times (values ranged between approximately 200 and 700 uM).  Turbidity in the water column and the subsequent decrease in light penetration to the sediment was the most influential factor affecting primary productivity at not only AO, but at all stations. Varela and Penas (1985) also observed that productivity was depressed due to water turbidity and therefore, their "high" values actually fell in the "normal" range of productivity. The effect of sediment grain size and the direct relationship with organic content also supported high productivity at AO. The protected nature of the contaminated site explains the high organic content found and domination of clay-like particles (in addition to the pollution source of organic matter). These environmental conditions contributed to high productivity at AO. It is also interesting to note that the organic content measured in July 1996 (2.4% L.O.I.) was almost onethird of the value reported by Otte and Levings in 1975 (7.3% L.O.I) at station AO. This implies that a considerable amount of organic matter degradation has occurred since the heavy organic loading has been greatly reduced. Today, the most obvious and substantial source of organics at this location is the episodic effluent bypass dumping that apparently still occurs (Arvai, 1997).  The present levels of heavy metals in the sediment, for example mercury and nickel that were found at concentrations above provincial sediment quality guidelines (Thomas, 1997), did not seem to adversely affect primary productivity. Furthermore, almost all of the heavy metals measured by Thomas (1997) showed decreased concentrations compared to past studies at station AO (McGreer, 1979b), including mercury, cadmium, lead, copper and zinc (Table 10). Burrowing behaviour of macroinvertebrates also revealed that the sediment was less toxic to these organisms than previous levels (cf Arvai, 1997). There is still a possibility that the heavy metal  100  Table 10. Summary of heavy metal concentrations in surface sedimentsfromstation AO in 1979 and 1997, in comparison to the provincial sediment quality guidelines (Lowest Observable Effects Level or LOEL (Nagpal, 1995)) (units in ug g"), and organic contentfrom1975 and 1997 as percent loss on ignition (L.O.L). 1  Metal Hg Ni Zn Cd Pb Cu  McGreer(1979) 0.9 46.0 264.0 3.0 166.0 234.0  Otte and Levings (1975) Organic content  7.3 % L.O.I.  Thomas (1997) 0.2 49.0 100.8 0.3 18.7 45.4  Thomas (1997) 2.4 % L.O.I.  L O E L (ug/g) 0.15 30 120 5 35 70  101 concentrations depressed primary productivity, but the high rates at this station suggest that they were not or only minimally affected.  In summary, station AO was highly productive in spite of the low biomass of benthic primary producers. What was once a very organic-rich, polluted location with reduced macrofauna species diversity, biomass and density and low oxygen levels (Otte and Levings, 1975), is now lower in organic matter and heavy metals, and higher in available nutrients and benthic fauna, which more closely resembles a fertilized area than polluted. This agrees with the high secondary productivity at the same location (Arvai, 1997), although the macrofauna and high productivity were mostly prominent in late fall. This occurred most likely in response to the fall bloom seen in October, both in terms of increased primary productivity and algal biomass. Although the degree of recovery for primary productivity cannot be estimated, (as previous studies in this area have not included primary productivity), one may speculate that the effects of sewage pollution at this site have been somewhat relieved and are not adversely affecting primary productivity.  REFERENCE SITES Station All) The habitat at A10 greatly differsfromAO in terms of sediment composition, organic matter content, and proximity to the Fraser River. This site has sandy sediments with a lower organic carbon content than the contaminated site, and a much greater benthic microalgal biomass. Microphytobenthos biomass values revealed an early spring bloom in March, as well as a fall bloom in November of 1995. This early response by benthic producers on intertidal mudflats is in accordance withfindingsby Pinckney and Zingmark (1993). Not only was chl a found as deep as 10 cm in the sediment, but the average biomass over the study period (in the top 1 cm of  102 sediment) was more than 7 times that found at AO (average of 728 mg chl a m"). This benthic 2  biomass exceeds any published values, except for other studies conducted in the same location (Bendell-Young et al., in press). Hargrave et al. (1983) reported a similarly high biomass at Pecks Cove in the Bay ofFundy (peaks > 500 mg chl a m"), although this was accompanied by 2  high productivity.  Phytoplankton chl a values in the water were low in comparison to published values. AO showed the highest overall average of 5.58 mg chl a m" and mostly ranged <l-6 mg chl a m", where A10 3  3  averaged 1.22 mg chl a m' . Values reported for the western Wadden Sea, by Veldhuis et al. 3  (1988) rangedfrom5 to more than 40 mg chl a m' with an average of approximately 15 mg chl a 3  m". My results agree with other studies on Sturgeon Bank that averaged between 2 and 4 mg chl 3  a m' , with peaks up to 10 mg chl a m" during flood tides (Bendell-Young et al., in press). 3  3  Even with an exceptionally high biomass, productivity was lower than expected. Productivity was actually the lowest of the three sites, and although the rates at A10 seem low in comparison to AO, they are actually very similar to published values. Gross benthic productivity generally ranged between 30 and 150 mg C m" h' , but the peak in June 1996, which was greater than 2  1  300 mg C m" h' , brought the overall average to 116 mg C m" h' . Shaffer and Sullivan (1988) 2  1  2  1  observed benthic productivity between 2 and 100 mg C m' h", while Jonsson's (1991) values 2  1  ranged between 20 and 120 mg C m" h". Rizzo and Wetzel (1985) found that gross productivity 2  1  of a sandflat ranges between 20 and 175 mg C m" h' with an average around 80 mg C m" h". 2  1  2  1  The average gross productivity at A10, excluding the bloom event (79.9 mg C m" h"), was very 2  1  close to this value. Our results showed that respiration was not high, and thus a greater  103 proportion of the gross productivity was attributed to the production of oxygen by primary producers than at station AO, where plant and animal respiration had a more significant effect.  As mentioned earlier, the high chl a in the sediments does not necessarily explain the lower productivity measured. Alternatively, the productivity values may not have accurately represented the actual production at this location, especially in summer months when productivity would be expected to be high. An underestimate may have occurred because incubations in May, July and August were all inadvertently executed with surface water which was determined later to be primarily freshwater (0-2 ppt), and below the level of tolerance by some estuarine organisms. Therefore, productivity in these months was clearly underestimated and the actual productivity might have correlated with the benthic biomass.  We can assume that grazing intensity and perhaps macrofaunal density must also be low to maintain such a high biomass. This suggestion is supported by datafromArvai (1997) who found that the biomass and density of the suspension feeder, Corophium salmonis, was low at station A10. Macoma balthica, a macroinvertebrate that uses bothfilterand deposit feeding processes (although preferablyfilterfeeding), was found in greater quantities, but the effect of its feeding behaviour on the benthic microalgae would have been minimal, especially relative to a strict deposit feeder. This animal would have had a greater impact on phytoplankton at station A10 than the microphytobenthos, which could explain the low phytoplankton biomass. Therefore, the presence of these macroinvertebrates, even in large abundance, does not directly suggest an intense grazing pressure on the benthic microalgae because phytoplankton is their food preference. However, there are a number of other reasons that portray A10 as a less favourable  104 environment for benthic macrofauna, and this would help to explain the high biomass of rnicroalgae at this location.  The influence of the Fraser River is the strongest at station A10 due to its proximity to the Middle Arm. The river water may create a less favourable environment for benthic infauna because they would experience very low salinities (especially when the springfreshetcoincides with a low tide), as well as large salinity gradients because the river discharge varies seasonally. The spring freshet resulted in lower productivity in May at A10, as well as high turbidity. The combination of a high river discharge with a greater exposure to wind, wave and tidal forces (enhancing sediment resuspension events), present a less favourable environment for benthos.  Another possibility to explain the high biomass and low productivity paradox involves the nature of the microphytobenthos, site exposure and the grain size. The majority of thernicroalgaemay have been comprised of epipsammic diatoms that are more easily buried and unable to photosynthesize. These diatoms are more common at exposed sites and the fact that active chl a was found as deep as 10 cm supports this idea. Another possibility is that the drainage of porewater at this site could have transported epipelic diatoms downwards into the sediment and thus reducing photosynthesis (Yin et al., submitted). This would have occurred when the benthic chambers werefilledwith water before the incubation and these diatoms may not have resurfaced during the incubation as the chamber water simulated afloodtide. This demonstrates that biomass is not always an accurate indicator of productivity.  At station A10, without the protection of a breakwaterfromcurrents as well as the exposure to the Fraser River, epipelic diatoms could also be carried away. Hence, epipsammic diatoms may  105 comprise the bulk of the photosynthesizing algal biomass at this location. The classification of this station as exposed is supported by the absence of fine particles that would also be removed by currents, as well as the presence of chl a to significant sediment depths, implying strong mixing forces. This movement of the smallest grain sizefractionfromA10 explains why the organic content is low in the winter (and much lower than the summer). According to Arvai (1997), the winter organic content (< 2% L.O.I) is also much lower than AO (> 4% L.O.I) (Fig. 25). Finegrained sediment and organic material would be more easily resuspended by thefrequentstorms that occur in winter months. Currents and tidal action, in addition to the Fraser River discharge, would transport the fine particles offshore. In the summer, this station sustains a very high biomass, which is most likely reflected in the high organic content (approx. 4.5% L.O.I.), and indicates the potential for high productivity. This suggests that my benthic productivity measurements are not valid, and thefreshwaterthat was used to fill incubations chambers in May, July and August 1996 acted to diminish benthic primary productivity.  A distinct result occurred in the phytoplankton community in July and August where net productivity in both months were actually negative and gross productivity was extremely low, especially for a summer month. Although both of these months involved the low salinity incubations described earlier, the phytoplankton was resident in the water collected for the incubations and therefore would not have been affected in the same manner as the microphytobenthos. They should be tolerant to the low salinity of the water, as they would most likely have beenfreshwaterspeciesfromthe Fraser River. One possibility for this low productivity is heating of the bottles during the incubation. This would occur faster in the bottles than the chambers due to the smaller volume. Temperatures in the chambers were initially 19°C, so bottle values could very likely have reached temperatures inhibiting to photosynthesis.  106 Nutrients were low in July, either due to its freshwater source or earlier phytoplankton growth in the estuary that resulted in nutrient depletion. The concentration of nitrate plus ammonium was less than 5 uM which borders on nutrient limitation.  In summary, station A10 displayed lower primary productivity than the polluted site, with a significantly greater biomass of benthicrnicroalgae.This paradox occurred primarily due to the incidence of freshwater incubations that resulted in very low productivity in summer months. A secondary, yet still very possible explanation involved the influence of the Fraser River and the resulting sandy sediment composition and low organic matter. The higher degree of exposure experienced at this site provides a less habitable area for benthic infauna and thus, a lower grazing pressure on benthic rnicroalgae. The productivity of these primary producers was most likely limited by high turbidityfromthe sediment load in the river water and wind, wave and tidal action causing resuspension of sediments. Station A12 The reference site, A12, also has a sandy sediment texture, similar to A10, and is even further removedfromIona Island. This station is more shelteredfromthe Fraser River than A10 due to its location north of the Steveston jetty that contains the flowfromthe Main Arm to the south. Benthic microalgal biomass measured in this area corresponded to, or was somewhat higher than published values. The overall average biomass was 260 mg chl a m' in the top cm of sediment, 2  where published values rangefrom5 to 500 mg chl a m" depending on the sediment 2  characteristics (e.g. sand vs. mud) and the depth sampled.  One dominant feature of this station was the overwhelming presence of very large clams, Mya arenaria. These macroinvertebrates arefilterfeeders and would impact productivity by both  107 grazing phytoplankton and by their respiration. Although the phytoplankton biomass did not seem to be greatly affected by these invertebrates, respiration rates were high and undoubtedly attributable to these clams. The overall average phytoplankton biomass at A12 was 4.6 mg chl a m' compared to 5.5 mg chl a m' at AO, where these invertebrates were not prominent. The 3  3  biomass at both of these sites exceeded that found closer to the mouth of the Fraser River, at A10, most likely due to the freshwater discharge. It is important to note though, that the phytoplankton biomass at any of the sites were not high relative to other estuaries (Veldhuis et al., 1988).  Gross productivity at A12 was the lowest of the three sites, ranging between approximately 15 and 120 mg C m" h' and differed (p< 0.05) from the contaminated site. Rizzo and Wetzel (1985) 2  1  found benthic gross productivity on a sandflat in the York River region of Chesapeake Bay to range between 20 and 175 mg C m" h". Van Es (1982) reported lower rates in a European 2  1  estuary between 15 and 75 mg C m* h". Although the values reportedfromSturgeon Bank 2  1  correspond to other studies, a few anomalies occurred that deserve explanation. For example, in early June, gross productivity was much lower than expected, accompanied by low net productivity and respiration rates. The entire community metabolism seemed depressed at this time, which cannot be easily explained by any of the abiotic or meteorological parameters. Benthic biomass values were high and suggest that primary productivity should also be high. Algal biomass values correspond with macroinvertebrate densities measured by Arvai (1997), who found that both Corophium salmonis and Macoma balthica were low as neither species prefers sandy sediments. Battery failure, however, occurred during the incubation in early June which might be an indication of the necessity of water movement in bell-jar incubations to accurately measure productivity, especially in wanner months. The issue of whether to stir or not  108 to stir chamber water has been well explored and debated, and there is no general agreement (Boynton et al. 1981; Hargrave et al., 1983; Rizzo and Christian, 1996). The choice was made to stir the chamber water in this study to mimic natural water movement and avoid stratification and any resulting hypoxia complications. The failure of pump operations would have presumably resulted in a reduced oxygen supply to the benthos, as the oxygen in the sediments would have become depleted through biological and chemical processes. Respirationfromthe benthos, would decrease, resulting in less oxygen consumption during the incubation. Net productivity (based on oxygen evolution during the incubation period) would thus be overestimated and respiration underestimated. An underestimate of respiration in early June may have occurred as values were low and high temperatures in the summer normally promote respiration. However, net productivity was lower than expected and was most likely not overestimated. The explanation for this occurrence is not obvious, nevertheless, processes in the chamber incubations were complicated, especially due to experimental difficulties associated with the chambers. One can merely speculate on the processes that occurred inside the chambers, especially during battery failure.  Although the chamber pumps operated according to plan in August, primary productivity mirrored the low values of early June. Difficulties with the sampling equipment might also be responsible for this anomaly. Productivity in late June was representative of the typical seasonal pattern of productivity exhibiting higher net production rates and respiration. Warm temperatures and sufficient light energy contributed to these high rates. Small blades of eelgrass inside the chambers most likely also contributed to this higher productivity. Respiration was also high during months in which the chambers were tide-filled (March and September) due to insufficient light and sediment resuspension.  109 Similar to gross productivity, net productivity at station A12 was also the lowest of the three stations, even though the average benthic biomass was more than double that at AO. Environmental factors investigated do not explain these low rates and a comparison with published values suggest that this site actually exhibits a normal rate of primary productivity, and the other sites are elevated. However, one possibility for low productivity at A12 involves the sediment texture of this station, which was sandy and possibly well sorted. The crushing capacity of sand is much higher than mud and, especially with thefrequentresuspension of sediment that occurs in intertidal regions, diatom survival could be jeopardized. Sediment composition data in Arvai (1997) revealed both a greater proportion of coarse-grained sand at A12 than AO or A10, as well as a significant amount of silt (> 20% in the silt sizefractionor smaller). This emphasizes the sheltered nature of this station and suggests that productivity is not low due to exposure, and therefore, a lower proportion of epipelic diatoms, but that the sediment texture creates a more difficult environment for diatom survival. Therefore, the higher benthic biomass found at this site would have a lower proportion of actively-photosynthesizing primary producers, and would not accurately represent the proportion of the community involved in primary productivity.  In summary, station A12 showed the lowest productivity of the three sites, although values correspond to primary productivity in other estuaries. This suggests that A12 does not necessarily have low productivity, but that AO and A10 are both highly productive. The reason that productivity at A12 varied spatiallyfromthe other two sites was most likely a consequence of the sandy sediment composition. The abundance of large clams in this area resulted in high respiration, but did not significantly reduce phytoplankton biomass. Several difficulties arose during the experimental periods at this site which may have masked the actual productivity due to increased variability.  110  Conclusions Primary productivity was highest at the contaminated site, despite a lower biomass of benthic microalgae. Assimilation ratios confirmed that this result occurred over the entire sampling period. The reduction of sewage pollution since the implementation of the deep sea outfall, has apparently allowed the progressionfroma heavily polluted state to a fertilized environment. Concentrations of heavy metalsfromthe previous sewage pollution have decreased substantially as confirmed by collaborative work, and did not affect primary productivity at this site.  Primary productivity at station A10 was low, especially in relation to the high benthic microalgal biomass, but, in all likelihood, was not an accurate representation of this productivity because the chambers were inadvertentlyfilledwith Fraser River discharge water in May, July and August 1996. The influence of the Fraser River and the sediment composition at this location may have created a less favourable environment for both benthic infauna and epipelic diatoms. Benthic microalgae, however, flourished possibly due to the absence of a strong grazing effect.  Productivity at A12 was the lowest of the three stations, but compares with published values on sandflats in other estuaries. The sandy sediments, and consequent abrasive action, may be responsible for the lower productivity due to decreased benthic microalgal survival. Battery failure occurrences and other difficulties with experimental equipment added variation to the results at this site. Correlations were not found between primary productivity and environmental factors, specifically light energy, temperature and benthic microalgal biomass. However, morefrequentsampling over the incubation period may have produced a relationship. The interplay of other environmental factors and marked spatial patchiness also caused difficulties in discerning a correlation.  The marked decrease in light penetration to the sediments by turbidity in the water was the largest limiting factor for primary productivity. Increases in turbidity were caused by both the Fraser River discharge, especially during the springfreshet,and resuspension of sediment and organic matter in the intertidal region.  A number of variables may have resulted in underestimates in productivity, including shorter exposure timefromthe use of neap tides, the occurrence of "tide-filled" chambers, and hence, increased turbidity, the use of Winkler titrations to determine oxygen concentrations in samples with high organic matter, the simulation of a high tide by the chamber incubations at low tide and thus, no productivity measurements during low tide.  Ill  Difficulties involved in primary productivity studies There are a number of reasons that made the measurement of primary productivity on Sturgeon Bank, and the comparison of these values with publishedfindings,difficult. This occurred primarilyfromthe use of benthic incubation chambers and the sources of variation involved with working in the intertidal region. Many on these difficulties are not unique to this project, but are widespread in the study of primary productivity. The problems or possible sources of variation most prominent in this study include: • • • • • • • • • • • • • •  chamber leakages oxygen supersaturation in bottles or chambers, or both overheating in bottle and chamber incubations during summer low tides chamber uplifting during incubations, resulting in volume changes stratification due to battery failure the possibility of hydrogen sulfide toxicityfromsediments exposure to air with sample extractionfromchambers underestimated oxygen concentrationsfromreagents binding to sediments in Winkler titrations river discharge andfreshwatereffects heterogeneity in benthic microalgal spatial distributions (patchiness) possible trampling of study sitesfromHovercraft use difficulty in estimating grazing effects undetected turbidity changes over the incubation period emergency landings at the Vancouver International Airport resulting in release of excess jet fuel over mudflats (albeit very infrequent, but did occur)  Differences also exist between studies which make comparisons to published valuesfromother estuaries difficult. Some of these differences include: • • • • • • • •  method for productivity measurements (e.g. oxygen vs. C radioisotopes) in situ experiments vs. transportation of "intact" cores to a laboratory chamber shapes and sizes circulation in chambers (to stir or not to stir?) tidal variations (neap vs. spring,floodvs. ebb) and a large tidal range sediment textures (mudflats, sandflats, etc.) depth of benthicrnicroalgaein sediments depth of sediment used for benthic microalgal biomass determination (generally ranges from 0.5-2 cm) 14  112 •  units chosen to express productivity values (unfortunately a universally accepted unit does not exist and units rangefrommmol O2 m' y" to mg C m' h' ) different procedures to calculate and express primary productivity (e.g. Was the daily productivity calculated by extrapolating the rate of net productivity to a 24 hour period, or was the respiration at night added to the net productivity?) 2  •  1  2  1  Variations therefore exist both within studies and between studies, especially involving the characteristics of the study area and the sampling design and equipment. These differences create difficulties for both interpretation of the results and comparisons with other work. It is important to consider these sources of variation before initiating the measurement of primary productivity.  113  General Recommendations A number of modifications could be made to the chamber design and sampling program to improve productivity measurements:  1) A smaller chamber size is recommended if patchiness is not prevalent. If the vertical distribution of benthic rnicroalgae is patchy, an increase in the number of replicate chambers is recommended to accompany a decrease in chamber size. Many studies have used chambers much smaller than the ones in this study. A smaller size would increase the ease of transportation, decrease the chance of lifting in the sediments during high tides, and therefore the necessity of a rebar securing system might be eliminated, or at least minimized. However, the water in small chambers would heat up faster during summer low tides, so incubations should be short.  2) Incubation times should be shorter than was used in this study, but modifications would also be necessary in the sampling design. In my case, shorter sampling times were not possible due to the inaccessibility to the sites, the semi-diurnal nature of the tide, and the large range in tidal height between high and low tides. If sites are easily accessiblefromshore, an effort should be made to shorten incubation times.  3) Assuming unlimited funds, oxygen meters should be mounted inside each chamber with an accompanying microprocessor or computer to record concentrations. Measurements should be taken at regular intervals throughout the incubations period (e.g. every hour or two, depending on the length of the incubation). It would be valuable to observe the switch between community metabolism during the photoperiod and at night. Oxygen measurements using a meter would also omit the process of transporting samples for Winkler titrations and any accompanying sources of  114 error. The use of Winkler titrations also requires sample exposure to air when transferring chamber water to sample bottles, and upon the addition of reagents. I recommend the use of a reliable and accurate oxygen meter over these titrations.  4) Light measurements (penetration into water) should, preferably, be taken on station if sampling times can be arranged to coincide with the flood or high tide. Our measurements were taken directly offshore, but the flood tide most likely increased turbidity in the upper intertidal and light measurements should reflect this.  5) Light availability to the sediment (or chambers) should also be measured using a light meter secured to one of the chambers. Measurements should be taken at regular intervals, in the same manner as the oxygen concentrations. This will allow for a comparison of the productivity and irradiance over time (P vs. I curves). The same frequency is recommended for temperature measurements to observe any problems due to overheating and oxygen supersaturation. Automated temperature sensors should be mounted inside chambers to monitor fluctuations and maximum and minimum temperatures over the incubation period.  6) More emphasis should also be placed on the value of frequent and spatially-distributed turbidity measurements. In the Fraser River Estuary, due to the high river discharge and its apparent effects on primary productivity, a good sampling design would incorporate turbidity samplesfromboth upriver and offshore. This would allow for greater distinction between turbidity caused by thefreshetand that causedfromwave and tidally-produced turbulence resulting in sediment resuspension. Turbidity could also be measured inside the chambers using automated turbidity monitors with OBS probes.  Some interesting experiments that have been conducted in other estuaries include the variation of primary productivity over tidalfluctuations(high vs. low tide) (Varela and Penas, 1985), photosynthesis in air (Einav and Beer, 1993), and productivity differences over tidal height variation.  116  Bibliography Admiraal, W. (1984). The ecology of estuarine sediment-inhabiting diatoms. In: Progress in Phycological Research, Round, F.E., and D.J. Chapman, (eds.) Biopress Ltd., Bristol, pp.269321. Admiraal, W. (1977). Influence of light and temperature on the growth rate of estuarine benthic diatoms in culture. Mar. Biol. 39: 1-9. Admiraal, W., and H. Peletier. (1979). Influence of organic compounds and light limitation on the growth rate of estuarine benthic diatoms. Brit, phycol. J. 14: 197-206. Anonymous. (1992). Greater Vancouver sewerage and drainage system. Greater Vancouver Regional District. Vancouver, B.C. Anonymous. (1993). State of the Environment Report for British Columbia. Environment Canada. Ministry of Environment, Lands and Parks. Vancouver.  Anonymous. (1995). Measuring the health of the river. Environmental Quality Technical Working Group. Fraser River Action Plan. Environment Canada. Vancouver. Anonymous. (1996). The Fraser River Estuary Environmental Quality Report. FREMP. Environment Canada. Vancouver. Anonymous. (1996). British Columbia Water Quality Status Report. BC Ministry of Environment, Lands and Parks. Environmental Protection Department. Water Quality Branch. Vancouver. Arvai, J. (1997). The population dynamics and production of Corophium salmonis (S.) and Macoma balthica (L.) on an estuarine mudflat in response to effluent diversion from a sewage plant, Sturgeon Bank, British Columbia. M.Sc. thesis. Department of Earth and Ocean Sciences. University of British Columbia. Vancouver. 234. pp Bawden, C. A., Heath, W.A., and A.B. Norton. (1973). A preliminary baseline study of Roberts and Sturgeon Banks. Westwater Research Center. Vancouver. Tech. Rep. 1. Bendell-Young, L., Harrison, P.J., Thomas, C , Feeney, T., Yin, K., Arvai, J., and L. Ross, (in press). Biogeochemistry of the intertidal area of the Fraser River Estuary. J. Luternauer, (ed.) Geological Survey of Canada. Vancouver.  117 Birtwell, I., Greer, G., Nassichuk, M., and I. Rogers. (1983). Studies of the impact of municipal sewage discharged onto an intertidal area within the Fraser River Estuary, British Columbia. Can. Tech. Rep. Fish. Aquat. Sci. No. 1170. Boynton, W.R., Kemp, W.M., Ostorne, C.G., Kaumeyer, K.R., and M.C. Jenkins. (1981.) Influence of water circulation rates on in situ measurements of benthic community respiration. Mar. Biol. 65: 185-190. Cadee, G.C. and J. Hegeman. (1977). Distribution of primary production of the benthic microflora and accumulation of organic matter on a tidal flat area, Balgzand, Dutch Wadden Sea. Neth. J. Sea. Res. 11:21-41. Colijn, F., and G. van Buurt. (1975). Influence of light and temperature on the photosynthetic rate of marine benthic diatoms. Mar. biol. 31: 209-214. Colijn, F., and K.S. Dijkema. (1981). Species distribution of benthic diatoms and distribution of chlorophyll-a on an intertidalflatin the Dutch Wadden Sea. Mar. Ecol. Prog. Ser. 4:9-21. Colijn, F., and de Jonge, V. N. (1984). Primary production of microphytobenthos in the EmsDollard Estuary. Mar. Ecol. Prog. Ser. 14: 185-196. D'Avanzo, C , Kremer, J., and S. Wainright. (1996). Ecosystem production and respiration in response to eutrophication in shallow temperate estuaries. Mar. Ecol. Prog. Ser. 141: 263-274. DeGroodt, E., and V.N. de Jonge. (1990). Effects of changes in turbidity and phosphate influx on the ecosystem of the Ems estuary as obtained by a computer simulation model. Hydrobiologia. 195: 39-47. Delgado, M., de Jonge, V.N., and H. Peletier. (1991). Experiments on resuspension of natural microphytobenthos populations. Mar. Biol. 108: 321-328. Einav, R., and S. Beer. (1993). Photosynthesis in air and in water of Acanthophora najadiformis growing within a narrow zone of the intertidal. Mar. Biol. 117: 133-138. Eppley, R. (1972). Temperature and phytoplankton growth in the sea. Fish. Bull. 70: 1063-1085. Fjarlie, R.L.I. (1950). The oceanographic phase of the Vancouver sewage problem. Joint Committee on Oceanography. Pacific Oceanographic Group. Nanaimo. B.C. File No. N7-18 Greenberg, A., Clesceri, L., and A. Eaton. (1992). Standard Methods: For the examination of water and wastewater. American Public Health Association. Washington.  118 Hargrave, B.T., Prouse, N.J., Phillips, G.A., and P.A. Neame. (1983). Primary production and respiration in pelagic and benthic communities at two intertidal sites in the Upper Bay of Fundy. Can. J. Fish. Aquat. Sci. 40:Suppl.l. 229-243. Harrison, B.J. (1981). The biological determinants of the structure of Harpacticoid copepod communities on an estuarine intertidal flat (Fraser River delta, B.C.). Ph.D. thesis. Department of Zoology. University of British Columbia. Vancouver. 455 pp. Harrison, P.J., Fulton, J., Taylor, F.J.R., and T.R. Parsons. (1983). Review of the biological oceanography of the Strait of Georgia: pelagic environment. Can. J. Fish. Aquat. Sci. 40: 10641094. Hoos, L.M., and Packman, G.A. (1974). The Fraser River Estuary: Status of environmental knowledge to 1974. Report of the Estuary Working Group. Department of the Environment. Regional Board. Pacific Region Special Estuary Series. No. 1. Environment Canada. Vancouver. 518 pp. Hunding, C , and B.T. Hargrave. (1973). A comparison of benthic microalgal production measured by C and oxygen methods. J. Fish. Res. Bd. Can. 30: 309-312. l 4  Joint, I.R. (1978). Microbial production of an estuarine mudflat. Estuar. Coast. Mar. Sci. 7: 185195. Kennish, M.J. (1986). Ecology of Estuaries: Physical and Chemical Aspects. Vol. 1. CRC Press. Boca Raton. 254 pp. Kistritz, R.U. (1978). An ecological evaluation of Fraser Estuary tidal marshes: The role of detritus and the cycling of elements. Technical Report of the Westwater Research Center. No. 15. Vancouver. Knox, G. (1986). Estuarine Ecosystems: A Systems Approach. Vol. 1. CRC Press Inc. Boca Raton. 289 pp. Larson, D. (1995). Iona foreshore monitoring project: sediment bioassays using the bivalve Macoma balthica. Integrated Resource Consultants Inc. Richmond. B.C. 67 pp. Levings, C D . , and J.B. Coustalin. (1975). Zonation of intertidal biomass and related benthic data from Sturgeon and Roberts Banks, Fraser River Estuary, British Columbia. Environment Canada. Fisheries and Marine Services Technical Report. No. 468. McGreer, E.R. (1979a). Studies of the bivalve Macoma balthica on a mudflat receiving sewage effluent and on an unpolluted mudflat, Fraser River Estuary, British Columbia. M.Sc. thesis. Department of Oceanography. University of British Columbia. Vancouver.  119 McGreer, E.R. (1979b). Sublethal effects of heavy-metal contaminated sediments on the bivalve Macoma balthica (L.). Mar. Pollut. Bull. 10: 259-262. McLaren, P., and P. Ren. (1995). Sediment transport and its environmental implications in the lower Fraser River and Fraser Delta. Fraser River Action Plan. Department of the Environment, Environment Canada. Vancouver. Metcalf and Eddy, Inc. (1991). Wastewater Engineering: Treatment, disposal and reuse. 3rd Edition, Tchobanoglous G. and F. L. Burton, (eds.) New York. McGraw-FIill Inc. 1334 pp. Milliman, J. (1980). Sedimentation in the Fraser River and its Estuary, southwestern British Columbia (Canada). Estuar. Coast. Mar. Sci. 10: 609-633. Nagpal, N.K. (1995). Approved and working criteria for water quality criteria. Water Quality Branch, Environmental Protection Department, Ministry of Environment, Lands and Parks. Otte, G., and C D . Levings. (1975). Distribution of macroinvertebrate communities on a mud flat influenced by sewage, Fraser River Estuary, British Columbia. Fisheries and Marine Service Technical Report. Environment Canada. Vancouver. No. 476. Pamatmat, M. (1968). Ecology and metabolism of a benthic community of an intertidal sandflat. Int. Rev. Gesamten Hydrobiol. 53: 211-298. Parsons, T.R., Bawden, C.A., and W.A. Heath. (1973). Preliminary survey of mercury and other metals contained in animalsfromthe Fraser River mudflats. J. Fish. Res. Bd. Can. 30: 1014-1016. Parsons, T.R, Maita, Y., and C M . Lalli. (1984a). A manual of chemical and biological methods for seawater analysis. Pergamon Press. Oxford. 173 pp. Parsons, T.R., Takahashi, M., and B.T. Hargrave. (1984b). Biological oceanographic processes. 3rd Edition: Pergamon press. Oxford. 330 pp. Paterson, D.M., and J.C Underwood. (1990). The mudflat ecosystem and epipelic diatoms. Proceedings of the Bristol Naturalists' Society. 50: 74-82. Pinckney, J., and R.G. Zingmark. (1993a). Modeling the annual production of intertidal benthic microalgae in estuarine ecosystems. J. Phycol. 29: 396-407. Pinckney, J., and R.G. Zingmark. (1993b). Biomass and production of benthic microalgal communities in estuarine habitats. Estuaries. 16: 887-897.  120  Pinet, P. (1992). Oceanography: An Introduction to the Planet Oceanus. West Publishing Company. St. Paul. 572 pp. Pomeroy, W.M. (1983). Receiving environment studies conducted in the vicinity of Iona Island sewage treatment plant, Vancouver, B.C. Canadian Environmental Protection Service Regional Report Program. No. 83-10. Environment Canada. Vancouver. Pomeroy, W.M., and C D . Levings. (1980). Association and feeding relationships between Eogammarus confervicolus (Amphipods, Gammaridae) and benthic algae on Sturgeon and Roberts Banks, Fraser River Estuary. Can. J. Fish. Aquat. Sci. 37: 1-10. Revsbech, N.P., and B.B. Jorgensen. (1981). Primary production ofrnicroalgaein sediments measured by oxygen microprofile, H C03* fixation, and oxygen exchange methods. Limnol. Oceanogr. 26: 717-730. 14  Rice, T.R., and R.L. Ferguson. (1975). Response of estuarine phytoplankton to environmental conditions. In: Physiological ecology of estuarine organisms. F.J. Vernberg. (ed.) University of South Carolina Press. Columbia. 397 pp. Rizzo, W.M., and R.L. Wetzel. (1985). Intertidal and shoal benthic community metabolism in a temperate estuary: Studies of spatial and temporal scales of variability. Estuaries. 8: 342-351. Rizzo, W.M., and R.L. Wetzel. (1986). Temporal variability in oxygen metabolism of an estuarine shoal sediment. In: Estuarine Variability. D.A. Wolfe (ed.). 227-239. Rizzo, W.M., and R.R. Christian. (1996). Significance of subtidal sediments to heterotrophicallymediated oxygen and nutrient dynamics in a temperate estuary. Estuaries. 19: 475-487. Sewell, M.A. (1996). Detection of the impact of predation by migratory shorebirds: an experimental test in the Fraser River estuary, British Columbia (Canada). Mar. Ecol. Prog. Ser. 144: 23-40. Shaffer, G.P., and M.J. Sullivan. (1988). Water column productivity attributable to displaced benthic diatoms in well-mixed shallow estuaries. J. Phycol. 24: 132-140. Stockner, J.G., Cliff, D.D., and K.R.S Shortreed. (1979). Phytoplankton ecology of the Strait of Georgia, British Columbia. J. Fish. Res. Bd. Can. 36: 657-666. Strickland, J., and T.R. Parsons. (1968). A practical handbook of seawater analysis. Fisheries Research Board of Canada. Ottawa.  121 Sundback, K., Enoksson, V., Graneli, W., and K. Pettersson. (1991). Influence of sublittoral microphytobenthos on the oxygen and nutrientfluxbetween sediment and water: a laboratory continuous-slow study. Mar. Ecol. Prog. Ser. 74: 263-279. Syrett, P.J. (1981). Nitrogen netabolism of microalgae. In: T. Piatt, (ed.). Physiological bases of phytoplankton ecology. Can. Bull. Fish. Aquat. Sci. 210: 182-210. Thomas, C.A. (1997). Linking sediment geochemistry in the Fraser River intertidal region to metal bioaccumulation in Macoma balthica. M.Sc. thesis. Department of Biological Sciences. Simon Fraser University. Vancouver. 103 pp. Van Es, F. (1982). Community metabolism of intertidalflatsin the Ems-Dollard Estuary. Mar. Biol. 66: 95-108. Varela, M and E. Penas. (1985). Primary production of benthic microalgae in an intertidal sand flat of the Ria de Arosa, NW Spain. Mar. Ecol. Prog. Ser. 25: 111-119. Veldhuis, M. J. W., Colijn, F., Venekamp, L.A.H., and L. Villerius. (1988). Phytoplankton primary production and biomass in the Western Wadden Sea (The Netherlands): A comparison with an ecosystem model. Neth. J. Sea Res. 22: 37-49. Waldichuk, M. (1984). Sewage pollution in British Columbia in perspective. Fisheries and Oceans Canada. Vancouver. Technical Report. 50 pp. Wood, E.D., Armstrong F.A.J., and F.A. Richards. (1967). Determination of nitrate in seawater by cadmium-copper reduction to nitrate. J. Mar. Biol. Ass. U.K. 47: 23-31. Yin, K. (1997). Personal communication. Vancouver, B.C. Yin, K., Harrison, P. J., and C D . Levings. (submitted). Pigments in the intertidalflatof Sturgeon Bank, British Columbia, Canada: Effect of tidal drainage for sandy and muddy sediments on chlorophyll abundance and distribution. Vancouver, B.C. Zar, J.H. (1996). Biostatistical Analysis. 3rd. Ed. Prentice-Hall, New Jersey. 661 pp.  122  Appendix 1 Light intensity and tidal regime Tidal regimes for each sampling trip are shown with light intensity traces measuredfroma pyrheliometer. The duration for each incubation period is indicated with initial (I) andfinal(F). Note that incubations include both daylight and night hours, and that the entire photoperiod was not incorporated into each incubation. The productivityfromthis missing part of the photoperiod was calculated and considered in thefinalprimary productivity values. These calculations are shown in Appendices 4-6.  o 3  SI  a v> a o o 3  cx  3  s» u. H> ~ 3  3  t=- o p £  II cr.  p  5" 5.  1 3 p  o  15 5*  0  fJ5' GO  3T g p o. < «  a to — o* P  J  7 1  2 i o o  2?.  3 o> < 3 O o IT > 3a 0 0 gp. c  g  ON  eg t Cu ~ J P -  "r= 00 •  I  921-  ON  I  3  ON  3  3  *T1 ON  I  3  •Z ^  o 3  cr CO B.Z a o o P3 , 3 n  ON  I  O.  a. 3  00  3  3  3  & f? 3 3  co  I*' S". J» q co  3*  <-•  •a  3  ON  3  I 5" 3"  O  It g  g  1 era  Cu co  co _  f» co  O  a  00  3  to  ON  n  I; 3 & 3  &  O  3  3  s > S3-  &:  co CTQ  8* « <S vo -  o 00  621-  ON  ON  g  137  Appendix 2 Oxygen  concentration  calculations  from Winkler  titrations  Winkler titrations give ml of oxygen per L of seawater. To obtain these units, a number of calculations must be completed to adjust for possible coloration in either the blank or standard used, or both. Stepl: Both the volume of the samples and standard used must first be corrected for the value of the blank. Whether the blank value is added or subtractedfromthe standard and samples depends on which value is higher. If the blank value is greater than the standard, for example, then the difference between the two (x) is subtractedfromthe standard volume to correct for premature coloration in the standard. If then  blank value > standard volume blank value - std volume = x vol (std)j - x = vol (stdL^  where vol (std)i is the initial standard volume and vol (std)^ is the corrected standard volume. However, if the blank value is less than the standard, then their difference is added to the standard. This corrected value is then used to determine the F Factor (Step 2). If then  blank value < standard volume std volume - blank value = y vol(std)+y = vol(std) i  axr  If there is no difference between the two values, no correction is necessary. The same process is done for the samples, as shown below: Vol (std)^ = Vol (std) j - Blank value The same equation is used tofindthe corrected volume of the sample, Vol (sample)Corr. Step 2: The f factor must then be determined as follows to calibrate the thiosulfate: / = 5.67568/Vol (Std)^ where Vol (Std)coiT is the volume of the standard corrected for the blank. Step 8:  The concentration of oxygen in the samples, in mL L' is found by: 1  Cone (Sample) =/x Vol (Sample) These oxygen concentrations were then used to calculate the various rates of productivity and respiration shown in Appendices 4, 5 and 6.  138  Appendix 3 A comparison of Winkler titrations and the azide modification When measuring oxygen concentrations by the Winkler titration method in a polluted area, organics can be problematic because they interfere with the reactions involved in the titration, and cause an underestimate of the oxygen concentration. The azide modification to the normal Winkler titration reduces this problem and it was used to determine whether organics were interfering at the study sites. The results showed an insignificant difference between the normal and azide treatments, and the modification was therefore discontinued.  Table 1. Oxygen concentrations in mL O2 L' seawater in: A) July, and B) August 1995, as measured by the normal Winkler titration and the modification to this titration with azide. Note: chamber colours define the opacity of the chambers and are represented by L (clear or light) or D (dark or opaque): 1  A) July 19 and 20,1995 chamber colour  W i n k l e r titration  Titration w i t h A z i d e  AO  L L D  6.76 7.04 3.97  6.35 6.71 3.49  A10  L L L D D D  6.97 6.88 6.96 6.57 6.61 6.53  6.24 6.30 6.49 6.44 6.78 6.43  chamber colour L  W i n k l e r titration  Titration w i t h A z i d e  6.27  6.08  L L D D  6.22 6.54 6.31 6.40  6.06 6.20 6.47 6.38  D  6.57  6.22  L  6.59  L L D D D  6.66 6.44 5.36 5.55 6.03  6.02 6.27 n/a 5.86 6.01  station  B) August 3 and 4, 1995 Station A10  A12  n/a  139  Appendix 4 Total Productivity calculations (from chambers) Example calculation is for clear chambers at station A10 on August 22 & 23, 1996.  Terminology. Gross productivity is the oxygen production over the incubation period before the consumption due to respiratory processes is deducted. It is determined as net productivity plus respiration. Net productivity is the oxygen production (which may at times be negative, and therefore actually consumption) after respiration has been deducted. It is the net oxygen production in the light. More specifically, this net production can be represented as: Daylight productivity is the net productivity, or rate of oxygen produced, over the photoperiod only. Hourly productivity is the rate of productivity per hour and incorporates both daylight and dark hours. It is the average hourly productivity over one day. Oxygen consumption is the use of oxygen by phytoplankton and benthic rnicroalgae. Respiration is the consumption of oxygen by organisms such as phytoplankton, benthic rnicroalgae, benthos and bacteria through degradation processes.  Stepl: Primary productivity was determined using the production or consumption of oxygen by benthic rnicroalgae and phytoplankton over an incubation period. The initial oxygen concentration of the sample, drawn before incubation, was subtractedfromthe final sample, collected at the end of the incubation (on Day 2 of the experiment). Initial andfinalsamples were therefore collectedfromthe same clear chamber. Final - Initial oxygen concentrations = 0.78 mL L"  1  Step 2: This change in the oxygen concentration was then adjusted for both the chamber volume and sediment surface area to attain the change in oxygen concentration in a clear chamber over the incubation period. Change in oxygen cone, per incubation period = (Final 0 cone. - Initial 0 cone.)(chamber volume) / (sediment sfc area) = (0.78mL L" x 10.6 L)/(0.07 m ) = 116.4 mL m" inc. period 2  2  1  2  z  1  Since all the incubations did not include the entire 24 hour day, productivity during the missing hours of the day must also be calculated. In order to calculate the production or consumption of oxygen during these missing daylight hours, it mustfirstbe determined in the "daylight-only" part of the incubation. In steps 3 and 4, oxygen consumption is calculated and removedfromthe equation to attain the daylight-only productivity value.  140  Step 8: An hourly rate of oxygen consumption during the incubation was first calculated in the dark chamber using a similar equation as in Step 2, applying the total incubation time. Dark chamber oxygen consumption rate = (Final 0 cone. - Initial 0 conc.)(chamber volume) / (sediment sfc area)(inc. hr) = (-0.52 mL I/ x 10.6 L) / (0.07 m x 18 hrs) = -4.3 m L m ^ h 2  2  1  2  1  This can also be expressed as the oxygen concentration change over the incubation period as a whole: Dark chamber change in 0 cone, per incubation period = (Final 0 cone. - Initial 0 conc.)(chamber volume) / (sediment sfc area) = (-0.52 mL L- x 10.6 L) / (0.070 m ) = -77.9 mL m" inc. period 2  2  2  1  2  2  1  Step 4: This hourly oxygen consumption rate was then used to determine the amount of oxygen consumption that would have occurred due to oxygen consumption, during the night incubation in the clear chambers, as follows: Amount of oxygen consumption at night in clear chambers = (Hourly oxygen consumption rate) x (# of night hrs in clear chamber incubations) = -4.3 m L m ' V x 7.75 hrs = -33.5 mL mJ  Step 5: Any oxygen consumption that occurred during the night in the incubation must therefore be added back to the oxygen production during the day, to arrive at the concentration of oxygen present in the chambers prior to night respiration activities. This yields the change in the oxygen concentration during the daylight part of the day only. Daylight-only 0 cone, change = Change in 0 cone. + ABS (Amt of night oxygen consumption) (Step 2 product) (Step 4 product) = 116.4 mL m* inc. period" +1-33.5 mL m' 1 = 149.9 mL m" 2  2  2  1  2  2  (where ABS = absolute value)  Step 6: Due to variations in weatherfrommonth to month and day to day, productivity values need to be normalized for light intensityfromsun and cloud variation. The area under the pyrheliometer curve, measuring light intensity, was determined in units of "squares". The rate of productivity was calculated on a "per square" basis by dividing the net productivity by the number of light intensity squaresfromthe incubation period. Daylight 0 cone, change per square = (Daylight-only 0 change). / (# incubation squares) = 149.9 m L n r / 255 squares = 0.6 mL m" incubation square' 2  2  2  1  141  Step I: The oxygen change that occurred before or after the incubation, and thus are "missing" hours of daylight, were then calculated by determining the area under the light intensity curve for those hours (in units of light squares): Missing daylight change in 0 cone. = (Daylight 0 change per square) x (# of squares in "missing" daylight hours) = (0.6 mL m" inc. sq' ) x 13 sqs missing = 7.6 mLrrf 2  2  2  1  2  Step 8: This, calculated "missing" change in the oxygen concentration was then added to the previously determined daylight-only oxygen concentration change to obtain a total of the oxygen change that occurred over the whole light period of the day. Total daylight 0 cone, change = Missing daylight change in 0 cone. + Daylight-only 0 cone, change = 7.6 mLrrf +149.9 mLm = 157.6 mL m' daylight period" = Amount of net productivity 2  2  2  2  -2  2  1  Step 9: The amount of gross productivity can then be calculated by adding the daily respiration back to the equation as Gross Productivity = Net Productivity + Respiration. Amount of gross productivity = Amt. of net productivity + |Daily respiration | = 157.6 mL m +1-103.8 mL r r i | = 261.4 mLrrf _2 2  Step 10:  PRODUCTIVITY UNITS  This final change in the oxygen concentration is in mL m-2 and is the amount of oxygen produced or consumed in the chambers over the incubation period. To obtain the productivity, this amount is adjusted depending on the desired units as either (1) the productivity per daylight hour (divide by the number of light hours in the day), or by (2) the productivity per hour (divide by 24 hr), or (3) simply expressed as productivity per day. (1)  Daylight gross productivity = Amt. of gross productivity/ # of daylight hrs = (261.4 mL nrf )/12.75 h = 20.5 mLrrf daylight h" 2  2  (2)  1  Hourly gross productivity = Amt. of gross productivity/ 24 hrs = (261.4 mLrrf )/ 24 h = 10.9mLm- rf 2  2  (3)  1  Daily gross productivity = Amt. of gross productivity/ day = 261.4mLrrf d2  1  142 Stent!:  C O N V E R S I O N FROM OXYGEN T O CARBON  All the above values are in units of mL oxygen per meter square of sediment surface per hour or day. As the literature often reports productivity in carbon units, I have made a conversion to mg carbon per meter square of sediment per hour, as shown below.  Unit conversion:  from mL 0 rrf h' to mg C rrf h' 2  1  2  1  2  = (31.9 g mol' 0 ) / (22400 mL mol' ) x (1000 mg g' ) = 31998 mg / (22400 mL) x (1 C11.2 0 ) x (12 g mol' / 31.9 g mol' ) = 0.45 conversion factor 1  1  1  2  1  2  Therefore, productivity in terms of carbon would be as follows: (1)  Daylight productivity = 20.5 mLO2m' h" x0.45 = 9.2 mg C m' h" 2  2  (2)  1  1  Productivity hourly = 10.9 mLm' h' x 0.45 = 4.9 mg C m" h" 2  1  2  1  1  143  Appendix 5 Phytoplankton Productivity calculations (from bottle incubations) Example calculation is for clear bottle incubations at station AO on March 11 & 12, 1996. Step 1: Primary productivity was determined using the production or consumption of oxygen by phytoplankton over an incubation period. The initial oxygen concentration of the sample, drawn before incubation, was subtracted from the final sample, collected at the end of the incubation (on Day 2 of the experiment). Initial and final samples were collected from the same clear-coloured bottle. Final - Initial oxygen concentrations = 1.63 mL L"  1  Step 2: This change in oxygen concentration occurred over the incubation period and is not expressed per meter squared as in the chamber productivity (Appendix 4). Change in oxygen cone, per incubation period = (Final O2 cone. - Initial 62 cone.) / inc. period = 1.63 mL O2 L" inc. period" 1  1  Since all the incubations took place such that they did not include the entire 24 hour day, the productivity during the missing hours of the day must also be calculated. In order to calculate the production or consumption of oxygen during the missing daylight hours, it must first be determined in the "daylight-only" part of the incubation. In steps 3 and 4, oxygen consumption is calculated as it must be removed before a daylight-only productivity value is achieved. Step 3: An hourly rate of oxygen consumption during the incubation was first calculated in the dark bottle applying the total incubation time. Dark bottle oxygen consumption rate = (Final O2 cone. - Initial 62 conc.)/(inc. period) = (1.093mLL"/18 hr) = 0.06 mLL" h" 1  1  1  Step 4: This hourly oxygen consumption rate was then used to determine the amount of oxygen consumption that would have occurred due to respiration, during the night incubation in the clear bottles, as follows: Amount of oxygen consumption at night in clear bottles = (Bottle oxygen consumption rate) x (# of night hr in clear bottle incubations)  = 0.06mLL"V x 13.25 hr = 0.8 mLL'  1  144 Step 5: Any oxygen consumption that occurred during the night in the incubation must therefore be added back to the oxygen production during the day, to arrive at the concentration of oxygen present in the bottles prior to night respiration activities. This yields the change in the oxygen concentration during the daylight part of the incubation period (NOTE: The incubation period does not always include the entire daylight period and the missing part is calculated in steps 6 and 7). Daylight-only O2 cone, change = Change in O2 cone. + ABS (Amt of night oxygen consumption) (Step 2 product) (Step 4 product) = 1.63 mL L- inc. period +10.8 mL L' 1 = 2.4mLL' 1  -1  1  1  where ABS = absolute value  Step 6: Due to variations in weather from month to month and day to day, productivity values need to be normalized for light intensity from sun and cloud variation. The area under the pyroheliometer curve, measuring light intensity, was determined in units of "squares". The rate of productivity was calculated on a "per square" basis by dividing the net productivity by the number of light intensity squaresfromthe incubation period. Daylight O2 cone, change per square = (Daylight-only O2 change) / (# incubation squares) = 2.4 mL L' /160 squares = 0.015 mLL' inc. square' 1  1  1  Step 7: The oxygen change that occurred before or after the incubation, and thus are "missing" hours of daylight, were then calculated by determining the area under the light intensity curve for those hours (in units of light squares): Missing daylight change in O2 cone. = (Daylight O2 change per square) x (# of squares in "missing" daylight hours) = (0.015 mL L' inc. sq' ) x 23 sqs missing = 0.4mLL" 1  1  1  Step 8: This, calculated "missing" change in the oxygen concentration was then added to the previously determined daylight-only oxygen concentration change to obtain a total of the oxygen change that occurred over the whole light period of the day. Total daylight O2 cone, change = Missing daylight change in O2 cone. + Daylight-only O2 cone, change = 0.4mLL" + (2.4 mLL" ) = 2.8 mL L' daylight period' = Amt. of net productivity 1  1  1  1  145 Step 9: The amount of gross productivity can then be calculated by adding the daily respiration back to the net productivity. Amt. of gross productivity = Amt. of net productivity + |Daily respiration | = 2.8 mLL +|1.5mLL- | = 4.2 mLL" day" -1  1  Step 10:  1  1  PRObUCTTVTry UNITS  Productivity is expressed either as the rate of productivity per daylight period, hour or day, as in Appendix 4 (Step 10). Stepn.  CONVERSION FROM OXYGEN TO CARBON  See Step 11 in Appendix 4 for the conversionfromoxygen to carbon.  146  Appendix 6 Productivity calculations for benthic rnicroalgae Note:  These calculations are identical to Appendix 4 with the exception of Steps 1 and 3. Example calculation is from station AO on March 11 & 12, 1996.  Stepl: Benthic rnicroalgae, present only in the chamber incubations, represents the main source of primary productivity. In order to determine the productivity by this group of producers, the two known values of productivity are subtracted: Benthic productivity = chamber productivity - bottle productivity As the bottle incubations do not contain sediment, or benthos, this represents: BMA productivity = (BMA +PP) productivity - (PP) productivity where BMA is benthicrnicroalgaeand PP is phytoplankton. Note that the oxygen concentration obtainedfromthe bottles represents the oxygen evolved into a 300 ml bottle, while the chambers are 10 liters in volume. To avoid this discrepancy, both concentrations were normalized for volume to reveal the amount of oxygen in the water in ml. For example, the oxygen concentrationfromthe chambers was 2.35 ml O2 L" . 1  Amount of oxygen per chamber incubation = 2.35 ml L x10.6L = 25.0 ml O2 chamber incubation' _1  1  The same calculation was done for bottle incubations and the two values were subtracted to yield a difference of differences: Note: these values arefromclear chambers. Benthic O2 volume evolved = chamber volume - bottle volume = 25.0 ml -17.31ml = 7.6 ml O2 chamber incubation' 1  Step 2: This change in the oxygen concentration was then adjusted for sediment surface area to attain the change in the oxygen concentration in a clear chamber over the incubation period. Change in oxygen cone, per incubation period = (Final 62 cone. - Initial O2 conc.)(chamber volume) / (sfc area) = (7.6 ml)/(0.07 m) = 108.1 ml m' inc. period" 2  2  1  Since all the incubations took place such that they did not include the entire 24 hour day, the productivity during the missing hours of the day must also be calculated. In order to calculate the production or consumption of oxygen during these missing daylight hours, it mustfirstbe determined in the "daylight-only" part of the incubation. In steps 3 and 4, oxygen consumption is calculated as it must be removed before a daylight-only productivity value is achieved.  147  Step 8: In order to calculate the hourly rate of oxygen consumption during the incubation in dark chambers, the (Final-Initial oxygen concentration) valuesfromthe dark bottles were subtractedfromthe chamber values, as was done for productivity in Step 1. Benthic O2 volume consumed = chamber volume - bottle volume = (-21.1 ml)-(-0.53 ml) = -20.6 ml O2 per incubation  The amount of oxygen consumed during the incubation over the given sediment surface area was then calculated. Amount of O2 consumed per chamber inc. = (Benthic O2 volume consumed)/ (sediment area) = (-20.6 ml)/(0.07 m ) = -291.4 ml m' 2  2  Step 4: This amount of oxygen consumption during the incubation period was then used to determine the amount consumed, due to respiration, during the night incubation in clear chambers, as follows: Amount of oxygen consumption at night in clear chambers = (Amt of oxygen in chamber) x (# of night h in clear chamber incubations) = -291.4 ml rrf x 13.25 h = -3861.3 ml m" in night incubation 2  2  Step 5: The amount of oxygen consumed over the course of the whole day could then also be calculated, and used later to determine gross productivity. Whole day amount of oxygen consumption = (Amt O2 consumption at night) x 24 h = (-291.4 ml rrf ] x 24 h = -6994.1 ml r r f V 2  Step 6: Any oxygen consumption that occurred during the night in the incubation must therefore be added back to the oxygen production during the day, to arrive at the concentration of oxygen present in the chambers prior to night respiration activities. This yields the change in the oxygen concentration during the daylight part of the day only. Daylight-only O2 cone, change = Change in O2 cone. + ABS (Amt of night oxygen consumption) (Step 2 product) (Step 4 product) = 108.1 ml m" +1-3861.3 ml m" | = 3969.4 ml m' 2  2  2  where ABS = absolute value  Step T. Due to variations in weatherfrommonth to month and day to day, productivity values need to be normalized for light intensityfromsun and cloud variation. The area under the pyroheliometer curve, measuring light intensity, was determined in units of "squares". The rate of productivity was calculated on a "per square" basis by dividing the net productivity by the number of light intensity squaresfromthe incubation period.  148 Daylight O2 cone, change per square = (Daylight-only O2 change). / (# incubation squares) = 3969.4 ml m' /160 squares = 24.8 ml m' / incubation square 2  2  Step 8: The oxygen change that occurred before or after the incubation, and thus are "missing" hours of daylight, were then calculated by determining the area under the light intensity curve for those hours (in units of light squares): Missing daylight change in O2 cone. = (Daylight O2 change per sq) x (# of sqs in "missing" daylight hours) = (24.8 ml m" inc. sq' ) x 23 sqs missing = 570.6 mlm" 2  1  2  Step 9: This, calculated "missing" change in the oxygen concentration was then added to the previously determined daylight-only oxygen concentration change to obtain a total of the oxygen change that occurred over the whole light period of the day. Total daylight O2 cone, change = Missing daylight change in O2 cone. + Daylight-only O2 cone, change = 570.6 ml m"+ 3969.4 mlm" = 4540 ml m* daylight period' 2  2  2  1  Step 16: The net change in the oxygen concentration per day can then be calculated by subtracting the change in the oxygen concentration at night (in the dark chambers) (absolute value;fromStep 3)fromthe total oxygen concentration change that occurred during daylight hours (from Step 9). Amount of gross primary productivity = Total daylight 02Conc. change - ABS (Dark chamber change in O2 cone.) = 4540 ml m"+1-6994.1 ml rr. | = 11534.2 mlm" 2  2  Stepll:  PRODUCT!VITY UNITS  Productivity is expressed either as the rate of productivity per daylight period, hour or day, as in Appendix 4 (Step 10). Step 12:  CONVERSION FROM OXYGEN TO CARBON  See Step 11 in Appendix 4 for the conversionfromoxygen to carbon.  149  Appendix 7 Benthic microalgal biomass calculations Example calculation is from a dark chamber at station A10 in August 1996.  Samples: Benthic cores were taken using 30 ml syringes with a diameter of 2.1 cm and a length of approximately 4 cm (at AO) or 8 cm (at A10 and A12). Stepl: Following the preparation forfluorometricanalysis, an aliquot was diluted with 95% acetone (usually 5 parts acetone with 1 part sample). Pre (F ) and post-acid (F ) readings were taken using thefluorometerand the chlorophyll a pigment content established with the following equation: G  a  Chl a biomass = 1.974 (Fo-Fa)(1/0.9489)(vW) = 1.974 (4848- 2316) (1/0.9489) (150 ml/ 29 ml) = 27244.8 ug chl a L' 1  where v is the volume of acetone in ml and V is the sediment volume in ml. The dilution ratio was factored into either the fluorometer readings directly (F and F ) or into the volume of acetone extract (v). In this example, the fluorometric readings were multiplied by a dilution factor of 6 and 29 cubic cm of sediment were taken for extraction. 0  a  Step 2: This value (27244.8 ug chl a L" ) represents the amount of chlorophyll a in one liter of sample. It must then be adjusted to the size of the core taken. 1  Amount of chlorophyll a per core = 27244.8 ug chl al' x 0.029 L = 790.1 ug chl a 1  Step 3: To express this value as a unit of surface area, the area of the core is calculatedfl|r2= 3.14(1.05)2) and the biomass normalized per unit surface area. Amount of chlorophyll a per square meter = 790.1 ug chl a/3.46 cm = 790.1 ugchl3/3.46x10- m = (2.28 x 106 ug chl am")(1 mg/1000 ug) = 2283.5mg chl am 2  4  2  2  2  Step 4:  Correction factor  This value now represents the biomass of chlorophyll a pigment in a square meter of sediment, down to a depth of 4 cm (as coresfromAO were processed to this depth), and therefore overestimates the photosynthetically-active microalgal biomass. A correction was then needed to adjust all the 1995 and 1996 core sample values to an appropriate depth that would represent the microalgae contributing to primary productivity. Based on literaturefindingsand recommendations, a sediment depth of 5 mm was chosen for this purpose.  150 A supplementary experiment was designed and executed in May 1997 to correct the existing benthic microalgal values for core depth, such that the microalgal biomass in only the top 5 mm of sediment was determined. In this experiment, both whole-core and sectioned samples were taken, the latter at intervals of 0 - 2, 2 - 5 and 5-10 mm. The amount of chlorophyll a pigment in the top 5 mm layer was thenfluorometricallydetermined for 5 replicates at each station, as well as the percentage that this amount represented of the whole core (56.5% at A10). The average percentage, of thefivereplicates, was then applied to the pre-existing data (1995 and 1996 values) tofindthe chlorophyll a content in the top 5 mm of those samples. Microphytobenthos biomass in top 5 mm of sediment = (amt. chl a to 4 cm depth) (% of total chl found in top 5 mm) = (2283.5mg chl am ) (0.554) = 1265.1 mg chl am" 2  2  This value is reported as the benthic microalgal biomass at station A10 in August 1996 and is found in Figures lOa-c. Step 5: The amount of chlorophyll a in the top 5 mm of sediment under the chambers was also determined, and later used to calculate assimilation numbers. Amount of chlorophyll a under chamber = benthic biomass x sediment surface area = (1265.1 mg chl a m")(7.07x10- m) = 89.4 mg chl a 2  2  2  151  Appendix 8 Sediment trough and crest biomass Sand ripple samples were collected to determine any difference between the microphytobenthos biomass in sediment troughs and crests from natural cellular aggregation as caused by biological population dynamics or external forces such as waves or mixing.  Figure 1. Biomass of microphytobenthos in sediment troughs vs. crests at station A10 in May 1997. Error bars represent SE with n = 5.  152  Appendix 9 Initial and final temperature and salinity averages  Table 1. Initial temperature (°C) and salinity averagesfromdark (D) and light (L) incubations chambers at three sampling stations (n = 3). Note: unavailable data are represented by n/a. AO J u l y 1995 Aug I A u g II Sept Oct Nov M a r l 1996 M a r II Apr May J u n II July Aug Sept Oct  D L D L D L D L D L D L D L D L D L D L D L D L D L D L D L  A10 salintiy  temp  salintiy  temp  21.4 21.2  16.3 16.7  20.5 20.1 n/a n/a  12.0 10.1 n/a n/a  18.8 18.9 11.4 11.6  7.7 7.9 5.4 5.4  7.5 7.7 9.5 9.4 16.0 16.3  8.0 9.4 7.8 8.3 2.0 2.3  16.6 16.7 18.2 18.7  7.7 7.7 9.0 9.0  15.1 15.9 20.4 20.5 19.5 23.0  14.4 14.7 8.3 8.0  12.8 12.7 14.5 14.7  12.8 12.4 14.5 15.5  8.0 7.9 7.3 7.6 8.5 9.0  11.6 10.4 14.5 15.0  20.8 20.6 17.2 17.9  0.1 0.1 2.8 2.5  8.9 9.0  10.4 10.0  A12 temp  salintiy  18.4 18.5 15.9 16.3  14.9 14.8 14.1 14.1  10.3 10.8 7.1 7.0 10.0 9.9 9.7 9.4 11.0 11.0  12.3 12.0 8.2 9.8 15.5 15.6 n/a n/a 16.8 18.0  18.8 19.7  6.7 7.5  18.1 19.8 n/a n/a  7.7 8.5 n/a n/a  153  Table 2. Final temperature and salinity averages from dark (D) and clear (L) incubation chambers at three sampling sites (n = 3). Note: unavailable data are represented by n/a. AO J u l y 1995 Aug I A u g II Sept Oct Nov M a r l 1996 M a r II Apr Jun I J u n II July Aug Sept Oct  D L D L D L D L D L D L D L D L D L D L D L D L D L D L D L  A10  A12  temp  salintiy  temp  salintiy  20.0 20.1  16.8 17.1  19.2 19.1 19.5 19.7  12.6 12.2 16.0 17.1  17.9 17.8 17.8 17.8  9.0 9.1 11.2 15.3  13.8 13.8 17.8 17.6 20.3 20.4  17.7 18.0 8.9 8.9  13.0 13.2 7.9 8.1  17.5 17.4 10.9 10.9  13.2 13.7 7.0 6.1  12.6 12.6 13.7 14.6  7.6 7.5 8.0 7.7 9.6 9.4  10.7 9.6 14.3 14.9  n/a n/a 10.6 12.0 12.8 12.9  n/a n/a 8.5 7.4 2.3 2.1  17.4 17.5 17.7  0.6 0.7 2.5 3.2  8.6 8.6  10.5 9.9  17.3  temp  salintiy  n/a n/a 17.5 17.5  14.2 15.4  10.9 10.9 8.7 8.7 11.1 11.5 11.2 14.2 11.8 14.5  12.3 12.5 9.7 9.6 17.1 17.5 n/a n/a 17.3 16.9  16.6 16.8  7.1 7.5  19.0 19.0 15.3 16.7  8.2 8.2 12.5 12.1  154  Appendix 10 Light attenuation with water depth Light attenuation with water depth is displayed for monthsfromAugust 1995 to October 1996. Light intensity was measured with a Li-cor quantum meterfromthefrontof the hovercraft (see Methods). Months in 1995 were measured to a water depth of 6 m, while 1996 months used smaller increments to a depth of 2 m. Each figure shows datafromtwo of the three sampling sites AO, A10 and A12. Light intensity scales generally rangefrom0 - 500 umol photons m-2 s-1 or 0 - 1500 umol photons m-2 s-1 except November 1995 and October 1996, both of which range from 0-75 p,mol photons m-2 s-1.  155  Figure 1. Light attenuation with water depth in: A) August, B) September, and C) November 1995 at stations AO (circles), A10 (triangles) and A12 (squares). Data from October were not available. Note different quantum light scale for November. All measurements were taken 1-5 km seaward of field sites during flood tides.  156  Light Intensity 0.1 nl  0.00 0.25  1 i i  I  (umol photons m" s" ) 2  10  100  I  I  • i  0.1 • • IT"  B  March I  -3  1 i i  1  1  10  I  100  il—i i 11 mil—•—i—i—L  M a r c h II  0.50 ~ 0.75 E, ; £ 1.00 Q. H  Q  1.25  -3  1.50 1.75  Station A10 Station A12  Station AO Station A12  -3  2.00 Light Intensity 0.1 q go  1 "I  (umol photons m" s' ) 2  10  1  100  i i i mill—i i i mill—iA 'i 1  April  0.25 0.50 *  0.75 -  E  \  £ 1.00 Q. CD  °  1.25  -E  1.50 1.75  Station A10  2.00 Figure 2. Light attenuation with water depth in A and B) March and C) April 1996. A12 data was not available for April. All measurements were taken 1-5 km seaward of the field sites during flood tides.  157  2.00  Figure 3. Light attenuation with water depth in A) May, B) June I, and C) June II 1996. Note: Light intensity scales differ from Figures 1 and 2. All measurements were taken 1-5 km seaward of the field sites during flood tides.  Light Intensity (umol photons m' s' ) 2  1  Figure 4. Light attentuation with water depth in A) July, B) August and C) October 1996. September data was not available. Note: light intensity scale differs for October. All measurements were taken 1-5 km seaward of the field sites during flood tides.  159  Appendix 11 Light intensity over incubation period Light intensity, including variation in both seasonal solar radiation and daily sun and cloud, was measured with a pyrheliometer. The curve traced by this instrument displays these variations. The area under the curve therefore represents the amount of light energy experienced during that day and is determined by the number of squares on the grid under the curve. These traces can be found in Appendix 1. The table below shows the total number of squares during the photoperiod (and incorporates both intensity and duration) and the number of squares for the incubation period.  Sampling month  Station  Daily light intensity (#sqs)  Incubation light intensity (# sqs)  September 1995  AO A10  150  not available  October  A10 A12  120  90 90  November  AO A12  11  10 11  March I 1996  AO A12  181  160 134  March II  A10 A12  225  181 209  April  A10 A12  146  91  May  AO A10  260  182  June I  A10 A12  342  131 148  June II  AO A12  354  215 247  July  AO A10  334  256  August  A10 A12  268  255  September  AO A12  196  196  October  AO A10  15  4 5.5  110 195  287  223 196  160  Appendix 12 Dark bottle and chamber respiration adjustments Several months revealed oxygen production in dark bottle or chamber incubations. As these values are used in the calculation of primary productivity, they were therefore adjusted before use to ensure the integrity of the productivity values. In these cases, the station average was used, in place of the positive value, if other replicates showed oxygen consumption in dark incubations. If not, the seasonal average was calculated using the remaining valuable data and applied to the outliers.  o o o »  c  3 2 2 Zz n, 2 o 0) a , o, at o  < ~ a s *"S "s •< < •< 2 *< •<«< tt  m G) m  00  <  -i -i -i <  o  II  0000^-»-- O - 03 Lt(ilUUU''<J(D'o<I)^ i  r  i  -j ro  o p o b P " 0  (D Mi  o  Q) (D  3  S  « 0)  <t> D) W O O -»• O O CO CO O - s i CO * 4 U l «D CO CO  c  IS-  <  i"8"  is 3 Q. e »  M  fi  7) A  3 o < <t>  a. •a  o w  •  I  I  DO -  -  o  J  -  o  a b b ) 4> o o  3" 3 S. s-  <D  |  vl N O NJ - » .  i  C (D W  B> S Q. O C  3  »" 3 < CO  o b  O  b  SL -o  o  5 3-  o  to IQ  o  o  b> b b) 4> o o  i f  -4 ro r o 4>  i-n  6 Op p ^^  c »  00 ( d U U U - s i J> 4> O) O) O) ">1  o o o o ^ ^ p ^ p .  (0  -»• o o o o o p p o o b b b bo co O O J  Ol  ocn  cn u i A  2  3  s  <"  I  © p o p _ _ >| Ju u u u *. 0 ) O) 0 )  a.  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C.  £-222 2 > > > O O CO —  m  u> co cn cn  o  o m  -A  o 2 » 0) C  3 a  oooooooooPPPPPPr^cnwuioo ( j j u o i u i v i u o o  CO  CO  < C (D  (0  7) »  3  o % a. •o  o  CO I  I  I  I  I  I  I  I  I  I  o o o o op p p o o  o o  a o  <  CO  S i" (0 CQ  <  o o o o o o ^ ^ k> Kj to k> ~j --j to tn  ro  c  M 10 CD  e o o o h i O M CO • * CO <o o  < os SL  CO  o o o o o o o o o o o o p o o o o o o o p i o i o w ^ ^ M i o w k j M f o k j b ' o b b b b b j i o O i D O ^ ^ I - ^ N l C i i c n u u u c n c n u i c i i c n u i c n u ^  1  TI  CA  CP ^ Q.  CO  co to > > c  m  OO  > >2 2 2 Z  C 3  CD ID c C C • D - D (Q (Q 3  Q>  £U  aa  6> O  -I -I -I <  J?"  o  o m  ro  II  2 i  i  i  i  i  i  i  « ~  •  to ro to p o o ^ o o o o o o o o P ^ w 'u; S5 o io ^ w b b) In » M " oo -J -si o K —»• o o to o - J —J 0 ) A ( O O I > l ( O M - '  CD D) (A C  Poo  3  iois  Q.  < »  0  C CD (0  3) CD  3 o <  CD Q.  •a  o co  •  i  i  i  i  •  «  »  © o o o o o o o 1*1 j*. b i 'oo b> cn co 'to cncn^cocn-^icoto  o  oo - J - J ->• - 4 - J  to  o  < CD <  S " CD W  0) 3 Q. O  < 01  5§  o o  o to  4*.  CA CQ  <  O O OO  00  b> cn co to O) - J CD to  CO "D  H  -4 —J  c  3  CD CO CD  < o o o o b > cn bo W CD A CC  •  i  i  i  o o ro cn  n » =  CA  I  I  I  I  I  OOOOpppO;-*  I  o> * . cn bo oo cn 'co tofabo  I  o I T o o o o o o o o o fafa'o fa - J S * . ro M M A * 3t £ 8  <  I  4 > 0 3 J ^ C D O ) - - J C D K ) C O - » - ~ N I ~ J ^  £91  » c CD  31  Q.  CA CD Q.  164  Appendix 13 Phytoplankton, benthic rnicroalgae and other primary producers as summarized in Hoos and Packman in 1974, and identified by Pomeroy and Levings (1980) and Brenda Harrison in 1981. The listfromHoos and Packman (1974) details species found in the Fraser River Estuary, whereas the primary producers identified by Harrison (1981) were collectedfromher study sites north of the Iona jetty and would be very similar to the composition on Sturgeon Bank. Species from Pomeroy and Levings (1980) include macroalgae and diatomsfromSturgeon Bank, south of the Iona jetty.  From Hoos and Packman (1974) DIATOMS 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46.  Asterionella japonica Bacteriastrum delicatulum Biddulphia aurita B. laevis B. longicruris Chaetoceros affinis C. brevis C. concavicornis C. costrictus C. convolutus C. curvisetus C. deo///s C. decipiens C. didymus C. lacinosus C. lorenzanus c. radicans C. s/m///s C. teres C. vanheurcki Corethron hystrix Coscinodiscus excentricus C. wailesii Ditylum brightwellii Eucampia zoodiacus Fragilaria crotonensis F. straitula Grammatophora manna Leptocylindrus danicus Melosira moniliformis M . sulcata Navicula sp. Nitzschia spp. Pleurosigma spp. Rhizosolenia delicatula R hebetata forma semispina R stolterfothii R styliformis Skeletonema costatum Stephanopyxis nipponica Thalassionema nitzschioides Thatassiosira condensata 7. decipiens T. nordenskioldii Thalassiothrix firauenfeldii miscellaneous collonial forms  Benthic macrophytes and algae 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.  17. 18. 19. 20. 21.  Acrochaetium densum Enteromorpha intestinalis E. linza E. tubulosa Fucus distichus Gracilaria verrucosa Laminaria saccharina Lola lubn'ca Microcleus spp. Monostroma fuscum Phormidium spp. Porphyra sanjuanensis Prasiola meridionalis Rhizoclonium reparium Smithora naiadum IZ/va scagellii a sp. Urospora mirabilis Zostera latifolia Z. marina Z. nana  From Pomeroy and Levings (1980) Primary producers on south side of Iona 1. 2. 3. 4. 5. 6.  Enteromorpha linza Ulva lactuca Monostroma fuscum Prasiola meridionalis Fucus distichus Porphyra spp.  167  From Harrison (1981)  Primary producers found in surface SAND Date  Composition  Comments  March 1979  60 um pennates Bodonids other pennates photosynthetic coccoids  different species from mud colourless flagellates  April 1979  palmelloid green cells Cryptomonas aff profunda Navicula spp. Amphidinium Amphidinium testudo Nitzschia paradoxa  12 um 15-20 nm 18-24 um; some 50 um rare rare  small Cryptomonas Amphidinium asymmetricum coccoids Navicula sp. Cryptomonas profunda Cylindretheca closterium Amphiprora Prasinophytes Prorocentrum Katodinium sp.  6-10 nm  September 1,1978  Amphidium testudo Amphiprora sp.  30 um and extremely abundant  September 28,1978  Navicula sp. Amphiprora (abdulens?) Amphora sp. Cylindrotheca closterium Cryptomonads Prorocentrum limum Amphidinium testudo  20-25 um with high diversity 70 um 40 um 120 um 16 um 45 um 32 um (species crashed in one month)  November 1978  everything very sparse pennates large pennates Bodonids ciliates Cryptomonas profunda  ~ 20 um > 20 um 10-15 um 30-5- um  December 1978  Nitzschia (Bacillaria) paradoxa Bodonids  1 small colony; almost no other diatoms few  July 1978  30-36 um fewer  168  Primary producers found in surface MUD Date  Composition  March 1979  nearly all 30-60 um Naviculoids Bodonids  July 1978  Cylindrotheca fusiformis (1.75 um) Navicula sp. (10-15 um) Cylindrotheca closterium Melosira moniliformis Anisonema Euglena sp. Amphidinium testudo  September 1,1978  small Navicula sp. (20 um)  September 29,1978  Navicula sp. (20-26 um) larger pennates (50-80 um)  November 1978  small pennates (mostly Navicula) larger pennates Bodonids  Comments  dominant dominant few few few few few extremely abundant bloom-like < 20 um < 20 um  


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