Creating a Resource Competition Model.

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In 2009, I developed and tested a resource competition model for phytoplankton using literature values and randomly generated data to test whether a dramatic change in form of nitrogen (from Ammonia to Nitrate) could have a similiar affect on phytoplankton competition as changes in nitrogen to phosphorus.

Note: All data is hypothetical and was used as preliminary exercise to show my intentions prior to beginning my experiment.

Abstract: The model was designed to make competition predictions for four species of phytoplankton that have changed in dramatically in abundance following upgraded wastewater treatment. Model predictions were compared to hypothetical competition experiments between the four species grown on treatments varying in both N:P and NH4+:NO3- to determine the ability of the model to capture the factors determining competition in a controlled laboratory experiment. Finally, the model was used to make predictions about the relative abundance of each of the four species in the lake since 2001 and compare with the actual data. This will not only indicate the validity of applying Tilman’s resource-ratio theory to natural systems but indicate whether the dominate N form as well as the N:P should be considered when estimating how resource competition structures phytoplankton assemblages.

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  • Over this period METRO loading to the lake  dropped by approximately 40%
    T-NH3 concentrations in the lake have decreased by ~75%
    But NOX concentrations have risen by ~45%.
  • Creating a Resource Competition Model.

    1. 1. CREATING A RESOURCE COMPETITION MODEL www.waterandwastewater.com http://cisbc.info/activities/PublishingImages/algae-2.jpg
    2. 2. OBJECTIVES
    3. 3. ONONDAGA LAKE o Historically oligo-mesotrophic o Flushes 4 times per year to Seneca River o Watershed 642 km2 , contains 450,00 people o Three tributaries = 70% of water input o (Onondaga, Ninemile and Ley Creeks o Morphometry o Maximum depth: 19.5 m o Surface area: 12.0 km2 o Volume: 131 X 106 m3
    4. 4. A HISTORY OF POLLUTION o Syracuse area was settled in the 1700s o Salt deposits spurred large scale production o Resulted in rapid industrial and population growth leading to… o Industrial pollution o Wastewater pollution Wastewater Effects on the Lake (timeline): 1890- Cold water fishery lost 1940- Swimming banned (fecal coliform, total phosphorus and clarity) 1994- Lake and sediment added to the EPA Superfund National Priority List
    5. 5. EFFECTS OF NUTRIENT LOADING Eutrophic Eutrophic o Large phytoplankton blooms o Anoxic bottom waters o Toxic levels of ammonium (NH4 + ) and nitrite (NO2 - ) o Loss of cold water fish Not actually Onondaga
    6. 6. NITROGEN IN WATER
    7. 7. CLEANING IT UP o METRO effluent o 80% of yearly TN load o 68% of TP o During summer Metro largest single inflow to the lake o 1998- Amended consent judgment against METRO o Decrease loading over 15 years o 3 phases ($380 mil)
    8. 8. CHANGING N LOADS o Tributary loads constant o Metro loading decreased by ~35% Now dominated by NO3 - o 283% increase in NO3 - (4x more) o 85% reduction in NH4 + (7x less) b) Metro Regime 3 4 5 YearlyAvergeNLoads(kgN/d) 0 1000 2000 3000 4000 5000 NH4 + NOx
    9. 9. CHANGING LAKE CONCENTRATIONS o [NH4 + ] and [NO3 - ] changed rapidly in lake o Ratio of NH4 + : NO3 - reversed between Regime 3 and 5 5:1 5:3 2:5NH4 + : NO3 - Regime 3 4 5 YearlyAvergeNConc(uM) 0 50 100 150 200 250 300 350 NH4 Nox
    10. 10. EFFECTS ON PHYTOPLANKTON ASSEMBLAGE  N Loading from Metro has decreased and changed since 1989  NH4 + : NO3 - is lower than ever before How will this change affect phytoplankton? Change in species? Toxicty? Food source?
    11. 11. N UPTAKE AND PREFERENCES Using NO3 - instead of NH4 + requires two additional steps
    12. 12. N UPTAKE AND PREFERENCES Diatoms prefer NO3 - Some Chlorophyta + Cyanobacteria prefer NH4 +
    13. 13. Year 98 99 00 01 02 03 04 05 06 07 08 09 10 11 RelativeBiomass 0.0 0.2 0.4 0.6 0.8 1.0 Charo- Zygnematophyceae Chloro- Chlorophyceae Mamiellophyceae Nephroselmidophyceae Trebouxiophyceae Ulvophyceae Crypto- Cryptophyceae Cyano- Cyanophyceae Dino- Dinophyceae Eugleno- Eulgenophyceae Ochro- Bacillarophyceae Chrysophyceae Synurophyceae Xanthophyceae Regime 3 Regime 4 Regime 5 PHYTOPLANKTON DIVISION TRENDS ↑ INCREASE ↓ DECREASE Charo. r2 = 0.051 p= 0.4 r2 = 0.11 p= 0.3 Dino. Crypto. r2 = 0.40 p= 0.01 Cyano. r2 = 0.85 p= <0.001 Chloro. r2 = 0.62 p= 0.5 r2 = 0.61 p= 0.001 Ochro. = No Significant Change
    14. 14. PREDICTED VS. ACTUAL COMMUNITY CHANGES o Recently evolved species increase o Diatoms o Distantly evolved species decrease o Cyanobacteria o Green Algae o What about Green Algae? o They have evolved over long period. o Lots of diversity.   Expected change in divisions over the study period…
    15. 15. Many changes since 1989… How can we partition out the effect of the NH4 + : NO3 - on the community structure?
    16. 16. OBJECTIVES  Onondaga Lake’s polluted past and long- term phytoplankton changes  Predicting resource competition  Testing model and results  Future research
    17. 17. RESOURCE COMPETITION The paradox of the plankton (Hutchinson 1961) o Why so many species? o What about competitive exclusion? ANSWER? o Nutrients, light, predation, turbulence etc.. vary! o Yearly, seasonally, daily and within seconds How to estimate the effect of these selective forces? o Develop model to estimate each and test it Falkowski, et al. 2004
    18. 18. RESOURCE COMPETITION o Measure growth rate for 4 species on TN, TP, NH4+ and NO3- � = �0��� W = conc. of phytoplankton W0 = conc. of phytoplankton (cells/ml) at time 0 µ = growth rate (d-1)
    19. 19. RESOURCE COMPETITION o Measure growth rate for 4 species on TN, TP, NH4+ and NO3- o At a range of 5 concentrations for each nutrient � = �0��� W = conc. of phytoplankton W0 = conc. of phytoplankton (cells/ml) at time 0 µ = growth rate (d-1) TN TP NH4 + NO3 - 1 20.00 1.00 0.50 0.50 2 63.33 2.35 3.00 12.71 3 94.86 4.34 8.81 18.67 4 195.03 6.30 20.89 25.72 5 246.79 20.59 115.13 115.00 Concentration (µM)
    20. 20. RESOURCE COMPETITION o Create growth curves (growth rate vs. nutrient concentration o Calculate µmax and Ks S = solute concentraiton µmax= maximum value of µ Ks = a constant, concentration where µ= ½ µmax o Calculate R* for each species when D = 0.1 o Rank species for each nutrient o R*1 < R*2 < R*3 < R*4 o Species 1 has the lowest nutrient requirement �∗ = � ∙ �� � 𝑚𝑎� ∙ � ↑ Vm  KS
    21. 21. CHOOSING STUDY SPECIES Present in Samples Data for every year Have trend with N or P loading Increased with time Decreased with time P driven? N driven? P driven? N driven?
    22. 22. AN EXCEL ADVENTURE: HYPOTHETICAL RESULTS Please Note: The following results from slide 20 to 28 were generated using my expectations and randomized data in excel as a preliminary exercise prior to beginning my experiment.
    23. 23. RESULTS: GROWTH RATE
    24. 24. RESULTS: R* VALUES Nutrient Species Vmax Ks R* R order Microcystis aeruginosa 0.45 7 2.00 2 Tetraedron spp. 0.45 22 6.29 4 Diatoma tenuis 0.50 10 2.50 3 Aphanizomenon flos-aquae 0.65 9 1.64 1 *Microcystis aeruginosa 0.25 0.19 0.127 3 *Tetraedron spp. 0.69 1.22 0.207 1 *Diatoma tenuis 0.48 0.15 0.0395 2 *Aphanizomenon flos-aquae 0.56 0.6 0.1304 4 Microcystis aeruginosa 0.38 6 2.14 2 Tetraedron spp. 0.51 15 3.66 4 Diatoma tenuis 0.61 13 2.55 3 Aphanizomenon flos-aquae 0.39 2 0.69 1 Microcystis aeruginosa 0.55 12.5 2.78 3 Tetraedron spp. 0.67 2 0.35 1 Diatoma tenuis 0.49 8 2.05 2 Aphanizomenon flos-aquae 0.41 14 4.52 4 TN TP NH4 + NO3 - �∗ = � ∙ �� � 𝑚𝑎� ∙ �
    25. 25. RESULTS: ZNGI GRAPHS Translating R* to Graphs
    26. 26. RESULTS:ZNGIGRAPHS N:P N:P ZNGI TP (uM) 0.0 0.5 1.0 1.5 2.0 TN(uM) 0 5 10 15 20 25 M.a T.spp D.t A.f TP (uM) 0.0 0.5 1.0 1.5 TN(uM) 0 5 10 15 20 TP (uM) 0.0 0.5 1.0 1.5 TP (uM) 0.0 0.5 1.0 1.5 TP (uM) 0.0 0.5 1.0 1.5 2.0 Microcystis aeruginosa Tetraedron spp. Diatoma tenuis Aphanizomenon flos-aquaeMicrocystisaeruginosa Tetraedronspp. Diatomatenuis Aphanizomenonflos-aquae TN(uM) 0 5 10 15 20 TN(uM) 0 5 10 15 20 TN(uM) 0 5 10 15 20 25
    27. 27. NH4 +(µM) 0 5 10 15 20 NH4 +:NO3 - ZNGI NO3 - (µM) 0 5 10 15 20 NH4 +(µM) 0 5 10 15 20 M.a T.spp D.t A.f NH4 +(µM) 0 5 10 15 NH4 +(µM) 0 5 10 15 NO3 - (µM) 0 5 10 15 NH4 +(µM) 0 5 10 15 NO3 - (µM) 0 5 10 15 NO3 - (µM) 0 5 10 15 NO3 - (µM) 0 5 10 15 20 Microcystis aeruginosa Tetraedron spp. Diatoma tenuis Aphanizomenon flos-aquae Microcystisaeruginosa Tetraedronspp. Diatomatenuis Aphanizomenonflos-aquae RESULTS:ZNGIGRAPHS NH4 + :NO3 -
    28. 28. OBJECTIVES
    29. 29. COMPETITION STUDY o Spike all four species into each treatment o A range of N:P and NH4 + :NO3 - concentrations (based on Onondaga Lake data since 1988) o Compare relative abundance between treatments N:P 8 6.16 0.81 0.25 83 1 5 9 13 45 2 6 10 14 27 3 7 11 15 15 4 8 12 16 NH4 + :NO3 - N:P NH4+:NO3- Min 24.05 0.26 Max 78.54 12.64
    30. 30. Species K/K Species K/K Aphanizomenon flos-aquae 15.00 Aphanizomenon flos-aquae 0.14 Tetraedron spp. 18.03 Microcystis aeruginosa 0.48 Microcystis aeruginosa 36.84 Diatoma tenuis 1.63 Diatoma tenuis 66.67 Tetraedron spp. 7.50 N:P NH4 + :NO3 - COMPETITION STUDY: PREDICTION N:P Dominant Species 83 Diat 45 Micro 27 Tetra 15 Aphan if N:P dominates trends NH4 + :NO3 - Dominant Species 8 Tetra 6.16 Diat 0.81 Micro 0.25 Aphan if NH4 + :NO3 - dominates trends
    31. 31. a) P limited N:P 020406080100 M.a T.spp D.t A.f b) N limited N:P 020406080100 A.fA.fM.aD.f T.sppA.fM.aD.f b) NO3 - limited NH4 + :NO3 - 0268 a) NH4 + limited NH4 + :NO3 - 0268 M.a T.spp D.t A.f A.fM.aD.tT.spp A.f M.a D.tT.spp WHICH SPECIES SHOULD DOMINATE WHEN A NUTRIENT IS LIMITING?
    32. 32. LONG-TERM TRENDS IN LAKE (PREDICTIONS) o How do the expected changes compare with the changes in the lake? if N:P dominates trends if NH4 + :NO3 - dominates trends Regime 3 65.34 ± 4.08 7.91 ± 0.54 Diatoma tenuis Aphanizomenon flos-aquae Regime 4 55.22 ± 2.58 3.16 ± 0.35 Microcystis aeruginosa Diatoma tenuis Regime 5 35.99 ± 2.35 0.81 ± 0.11 Tetraedron spp. Tetraedron spp. Dominate species of the 4 N:P NH4 + :NO3 - PREDICTIONS
    33. 33. RESULTS: LONG-TERM TRENDS IN LAKE if N:P dominates trends if NH4 + :NO3 - dominates trends Regime 4 55.22 ± 2.58 3.16 ± 0.35 Microcystis aeruginosa Diatoma tenuis Regime 5 35.99 ± 2.35 0.81 ± 0.11 Tetraedron spp. Tetraedron spp. Dominate species of the 4 N:P NH4 + :NO3 - o Actual trends in the lake don’t match up with predictions o Note: Used data generated from randomized models and literature values to make these predictions :-D PREDICTIONS 45 27 15 N:P NO3 = 8 M.a T.spp D.t A.f
    34. 34. DISCUSSION + CONCLUSIONS  Since I made up my own data to match my expectations... o Very useful to go through with the FAKE data o Found several bugs o Understand the models more o Better expectations of what will happen o Proves that I can make the predictions I hoped to make! What I Learned…?
    35. 35. DOGGIE BAG (I.E. TAKE HOME) o Since 1989 o NH4 + : NO3 - has decreased from 5:1 to 2:5 o Phytoplankton community has changed o NH4 + : NO3 - should be affecting phytoplankton community o World Wide o NH4 + loading decreasing + urea loading increasing o Stoichiometry is IMPORTANT o % toxic species and toxin production is correlated with changing ratio of N forms o Are we really solving the problem just decreasing TN loads?

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