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Dynamical Modeling of Phytoplankton Size Structure in the Gulf of Alaska: Do Copepods Relieve Grazing Pressure on Nano- and Picophytoplankton? Greg A.

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Presentation on theme: "Dynamical Modeling of Phytoplankton Size Structure in the Gulf of Alaska: Do Copepods Relieve Grazing Pressure on Nano- and Picophytoplankton? Greg A."— Presentation transcript:

1 Dynamical Modeling of Phytoplankton Size Structure in the Gulf of Alaska: Do Copepods Relieve Grazing Pressure on Nano- and Picophytoplankton? Greg A. Breed 1, Michael J. Dagg 2, and George A. Jackson 3. 1 Department of Biology, Dalhousie University, 1355 Oxford Street, Halifax, NS CANADA B3H 4J1 email: gbreed@dal.ca. 2 Louisiana Universities Marine Consortium, 8124 Hwy 56, Chauvin, LA, 70344 USA 3 Department of Oceanography, Texas A&M University, College Station, TX 77843-3146 USA Introduction: During GLOBEC cruises in the Gulf of Alaska in 2001 and 2003, chlorophyll concentrations of phytoplankton 20  m) (Fig. 1). In addition, high concentrations of small phytoplankton were often accompanied by large numbers of healthy Neocalanus spp. copepods. The combination of high concentrations of nano and picophytoplankton and high numbers of very large (>1 mm) copepods suggests the possible existence of a trophic cascade. Are large copepods consuming microzooplankton grazers of nano- and picophytoplankton, releasing the smallest phytoplankton from grazing pressure and allowing them to bloom? Methods: A simple 9 compartment nitrogen based NPZ type model was used to investigate the possible trophic cascade (Fig. 2). The dynamics of 4 compartments were of particular interest: Large phytoplankton (>20  m, essentially the diatoms), small phytoplankton (<20  m), copepods, and microzooplankton. Large and small phytoplankton differed in their ability to compete for nutrients. The grazer compartments were differentiated by the size structure of potential prey, as well as their half-saturation and maximum grazing rates. Grazing was regulated by an expanded Monod type saturation equation, and grazers preferred the most abundant prey item unless preference was otherwise specified. The model also included compartments for NH 4 +, NO 3 -, DON, bacteria, and detritus. It was initialized and forced using day length, mixed layer depth, temperature, and nutrient data from from recent (2001) GLOBEC cruises in the region, and spun up for one year. The coupled differential equations were largely taken from Fasham et al. (1990), modified to include two additional compartments and accommodate advances in parameterization (e.g. Steele and Henderson 1992; Edwards and Yool 2000). Two versions of the model were implemented. The first did not allow microzooplankton to consume large phytoplankton. The second allowed microzooplankton to consume large phytoplankton to varying degrees – with a lower maximum grazing rate and higher half- saturation constant than when grazing small phytoplankton. The models were integrated with Matlab 6.0 using the ode45 function – a numerical variable time step differential equation solver using a 5 th order Runge-Kutta method. Mid-Shelf (MS) Outer-Shelf (OS) Inner-Shelf (IS) July 2001 3-day average Kenai Peninsula Cook Inlet Prince William Sound Fig. 1. Primary Gulf of Alaska GLOBEC process stations.The model was forced using data from the 200 meter deep Mid-Shelf station, but conditions are often similar at the Outer-Shelf station. The inset graph shows 3-day average mixed layer chlorophyll concentration and size structure. Note the high concentration of small phytoplankton at mid and outer shelf stations. Similar results were found in April 2001 and in 2003. LPhyto (>20  m) SPhyto (<20  m) Copepods  zoo Bacteria Detritus NO 3 NH 3 DON mixing Fig. 2; Table 1. Basic model structure. Arrows indicate interactions included in the model, colored arrows indicate flow relevant to the trophic cascade, broad colored arrows are directly involved in the cascade. The red arrow, consumption of large phytoplankton by microzooplankton, was included in some models and not in others, and when included, the ability of microzooplankton to consume large phytoplankton was adjustable. Table 1 shows values of the most essential model parameters. Acknowledgements: We would like to thank Hongbin Liu, Jean Rabalais and Adriana Hashinaga for assistance and ideas in the development of this model. Suzanne Strom provided insights into the problem, as well as assistance in the field. The crew of the R/V Alpha Helix provided field support. This work was supported by NSF grant No. OCE-0102381. Results: A number of initial runs of both versions of the model revealed parameters related to grazers were most sensitive to adjustment (maximum grazing and half-saturation constants). Subsequent model runs focused on the effects of these parameters. Graphs indicate mixed layer concentrations in units of nitrogen. The models shown in figs 3 & 4 indicate the possibility that copepods are controlling microzooplankton after the initial spring diatom bloom, but before the onset of nutrient limitation. However, if microzooplankton are allowed a slightly higher maximum grazing rate, (2.5 vs. 2 d -1 ), microzooplankton effectively crop small phytoplankton (Fig 5). Increased grazing rates of both small phytoplankton and diatoms by microzooplankton has the opposite effect, increasing small phytoplankton populations (Fig. 6). ParameterValue   large phytoplankton 2.69 d -1   small phytoplankton 2.69 d -1 k NO3 small phyto 0.5  M k NO3 large phyto 1  M k NH3 small phyto 0.05  M k NH3 large phyto 0.5  M alpha (large & small phyto)0.025 (W m -2 ) -1 d -1 Max grazing - Copepods0.75 - 2.0 d -1 Max grazing –  Zoo 2 - 4.35 d -1 K grazing - Copepods 0.5 – 1.5  M K grazing –  Zoo*0.25 – 1.0  M Max grazing –  Zoo (on large phytoplankton) 0.5 – 1.25 d -1 K grazing –  Zoo (on large phytoplankton) 0.75 – 1.5  M Fig. 6. Grazing parameters  zoo max grazing = 2.5 d -1  zoo half sat (k) = 0.6  M  zoo max grazing (on Lphyto) = 1.25 d -1  zoo half sat (k) (on Lphyto) = 0.6  M Copepod max grazing = 1.0 d -1 Copepod half sat (k) = 0.9  M This run uses the same parameters as in fig. 5, but increases microzooplankton ability to consume large phytoplankton (lowered half saturation constant, and increased max grazing rate to 1.25). It produced the non-intuitive result of higher populations of small phytoplankton during mid-late summer, much greater than diatom populations. In addition, this produced a smaller spring diatom bloom and enhanced copepod populations. Conclusions: This model suggests a trophic cascade affecting the size structure of phytoplankton in the Gulf of Alaska. Under a number of model grazing scenarios, small phytoplankton are more abundant than diatoms during mid to late summer, when nutrients are limiting. The ability and preference of microzooplankton grazing on diatoms affects phytoplankton size structure. Higher  Zoo grazing rates on diatoms favor larger populations of small phytoplankton. Size structure is sensitive to grazing parameters. Caveats: Iron limitation may play a role in phytoplankton dynamics, but it has not been included in this model. Suggestions on how to improve this model, especially parameterization of grazing preferences, are welcome. References: Edwards, A.M., and A. Yool. 2000. The role of higher predation in plankton population models. J. of Plankton Res. 22(6):1085-1112. Fasham, M. J. R., H. W. Ducklow, and S. M. McKelvie. 1990. A nitrogen-based one-D model of plankton dynamics in the oceanic mixed layer, J. Marine. Res., 48, 591-639. Steele J. H. and E. W. Henderson. 1992. The role of predation in plankton models. J. Plankton Res. 14(1):157-172. Neocalanus spp. copepods collected at mid-shelf stations in May 2003. Fig. 5. Grazing parameters  zoo max grazing = 2.5 d -1  zoo half sat (k) = 0.6  M  zoo max grazing (on Lphyto) = 0.6 d -1  zoo half sat (k) (on Lphyto) = 1  M Copepod max grazing = 1.0 d -1 Copepod half sat (k) = 0.9  M This run allows microzooplankton to graze diatoms, and has a higher grazing rate on small phytoplankton. It suggests that with a 25% higher maximum grazing rate, microzooplankton can control small phytoplankton, despite pressure from copepods. Factors disturbing either copepod or microzooplankton grazing are likely to result in structure changes in this ecosystem. Fig. 3. Grazing parameters  zoo max grazing = 2.0 d -1  zoo half sat (k) = 0.6  M  zoo max grazing (on Lphyto) = 0.6 d -1  zoo half sat (k) (on Lphyto) = 1  M Copepod max grazing = 1.0 d -1 Copepod half sat (k) = 0.9  M This run included low rates microzooplankton grazing on large phytoplankton. The run produced damping limit cycles in the zooplankton and small phytoplankton, but not in the large phytoplankton. Limit cycles end at the onset of nutrient limitation at about day 170. Large spikes in small phytoplankton during early and mid summer, but not during the initial spring bloom, are similar to field observations. January 1 = day 1. Fig. 4. Grazing parameters  zoo max grazing = 2.0 d -1  zoo half sat (k) = 0.6  M  zoo max grazing (on Lphyto) = 0 d -1  zoo half sat (k) (on Lphyto) = 0  M Copepod max grazing = 1.0 d -1 Copepod half sat (k) = 0.9  M This run did not allow microzooplankton to graze large phytoplankton. The results are essentially the same as fig. 3, although microzooplankton grow in later allowing a slightly higher concentration of small phytoplankton to develop in the spring. Bold parameters are those changed relative to the results shown in figure 3.


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