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CULTURAL EUTROPHICATION OF THREE MIDWEST URBAN RESERVOIRS: THE ROLE OF NITROGEN LIMITATION IN DETERMINING PHYTOPLANKTON COMMUNITIES Pascual, D. L., University of Michigan School of Public Health & Indiana University-Purdue University, (UM) Ann Arbor & (IUPUI) Indianapolis, USA Johengen, T. H., University of Michigan, Ann Arbor, USA Filippelli, G. M., Indiana University – Purdue University, Indianapolis, USA Tedesco, L. P., Indiana University – Purdue University, Indianapolis, USA Moran, D., Veolia Water, Indianapolis, LLC,1 USA ABSTRACT : The cultural eutrophication of three Midwest urban reservoirs has resulted in impaired water quality. Nutrient loading to these reservoirs has resulted in the formation of nuisance algal blooms, including possible toxin-producing and/or taste and odor causing, heterocyst-forming blue-green algae such as Anabaena, Aphanizomenon, and Cylindrospermopsis. However, while eutrophication models tend to utilize a single parameter, namely P, to predict potential algal standing stocks, data from three Midwest urban reservoirs showed that N was equally important in determining phytoplankton productivity and more important in determining phytoplankton succession from diatoms and greens to heterocyst-forming blue-green algae. Analysis of monthly nutrient concentrations (Total P, NO 3 - , NH 4 + ) taken from 1998 – 2000 for two southeastern Michigan reservoirs, Ford Lake and Bellville Lake, and weekly nutrient data taken from 1976 – 1996 and bi-weekly data collected in 2003 for Eagle Creek Reservoir, Indiana showed consistent annual trends of NO 3 - + NH 4 + depletion and P abundance from mid- to late summer, suggesting that phytoplankton production became seasonally N-limited in these reservoirs. Data from Eagle Creek Reservoir indicated that N concentrations were more strongly dependent on watershed inputs than was P, a trend not supported by Ford and Bellville Lake data sets. Blooms can lead to a shading effect, thereby, limiting the growth other competing algae. Warm temperatures High incident solar radiation + Quiescent water column Deep Photic Zone Growth of all algae in lake Diatoms Greens Blue-Greens C N P Si Si Silica Limiting N Nitrogen Limiting C N C Growth of specific algae in lake Bloom formation of HC blue-green algae Given Si abundance, diatoms will likely dominate as they are better competitors for N and P than greens and blue-greens. Given P abundance, HC blue-green algae will likely dominate as they are able to fix atmospheric N2. HC blue-greens such as Anabaena are known taste and odor causing algae. Growth of all algae in lake Diatoms Greens C N Si Blue-Greens N Nitrogen Limiting C Warm temperatures High incident solar radiation + Quiescent water column Deep Photic Zone Si High rates of N assimilation effectively deplete N. A B P P P P Given P and Si abundance, HC blue-green algae, which can fix atmospheric N 2 , and diatoms, which are better competitors than green algae for scarce N when Si is abundant, will likely dominate. INTRODUCTION : Since Vollenweider first developed input- output models to describe the relationship between phosphorus and eutrophication, empirical models have been employed as a way to understand how a single parameter can work to affect ecological changes such as changes in phytoplankton biomass (e.g. Dillon and Rigler, 1974). However, understanding the change from a diverse phytoplankton community to a specific nuisance algal bloom, i.e. heterocyst-forming (HC) blue-green algae capable of producing toxins and/or taste and odor causing compounds (e.g. MIB (2- methylisoborneol) and geosmin), requires a complex model which uses several parameters founded in mechanistic theory. These mechanism-based parameters include physical conditions necessary for nuisance algal growth, nutrient or chemical dynamics which promote nuisance algal growth, and biotic stresses, such as resource competition, which work to select specific nuisance algae for exponential growth (e.g. Sterner, 1989 and Tilman et al., 1982). Therefore, a mechanistic understanding of nuisance algal bloom formation could be used to predict phytoplankton abundance and seasonal phytoplankton succession to nuisance algae, specifically, HC blue-greens (Fig. 1). HYPOTHESES : Small urban reservoirs undergo a transition from nitrogen rich, P-limited growth conditions to nitrogen poor, P-abundant growth conditions. Given sufficient physical conditions for growth (i.e., water temperatures > 25 °C, abundant incident solar radiation, and quiescent water,) , this transition in the nutritive environment spurs the growth of nuisance algal blooms of heterocyst-forming blue-green genera such as Anabaena, Aphanizomenon, and Cylindrospermopsis. Figure 1 : Mechanistic model based on resource competition for limiting nutrients, describing seasonal phytoplankton succession to HC blue-green algae and possible MIB and geosmin production. A diagrams a successional pattern in which green algae dominate during mid-summer; B shows a successional pattern in which green algae are never able to become a significant portion of the phytoplankton community because Si abundance allows for high rates of N assimilation by diatoms which leads to N-limited phytoplankton growth, a condition in which HC blue- greens are ideally suited to thrive. METHODS : Nutrient data from three eutrophic Midwest, urban reservoirs of similar morphology were analyzed for trends in [Combined N] (NH 3 -N + NH 4 -N) and [Total P]. Nutrient and phytoplankton data from 3 stations in Ford Lake (1998-2000) and 3 stations in Eagle Creek Reservoir (ECR) (2003) were pooled then analyzed for empirical relationships between nutrient concentrations and phytoplankton growth as measured by [chlorophyll a] (Ford Lake) and phytoplankton counts (ECR). (See maps.) 2003 ECR nutrient and phytoplankton data were then analyzed in the context of the STUDY SITES : Both Ford Lake and Eagle Creek Reservoir have been documented as experiencing mid- to late Summer blooms of HC blue-green algae: Ford Lake having yearly Aphanizomenon blooms and Eagle Creek Reservoir having a mixed bloom including Anabaena, Aphanizomenon, and Cylindrospermopsis. Ford Lake, Michigan Eutrophic Impoundment of the Huron River Created in 1932 Area: 3.25 km 2 Volume: 15,151,000 m 3 Eagle Creek Reservoir, Indiana Eutrophic Impoundment of Big Eagle Creek Created in 1967 Area: 5.01 km 2 Volume: 20,820,000 m 3 (Tedesco et al., 2003) Belleville Lake, Michigan Eutrophic Impoundment of the Huron River Created in 1924 Area: 5.14 km 2 Volume: 21,923,000 m 3 1998-2000: M ean M onthly [T otalP ] -20 0 20 40 60 80 100 120 140 J F M A M J J A S O N D [Total P](ug/L) Ford Lake B elleville Lake 1998-2000: M ean M onthly [N O 3 - + N H 4 + ] -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 J F M A M J J A S O N D [N O 3 - + N H 4 + ](ug/L) Ford Lake B elleville Lake 1998 -2000 M onthly M ean S tream flow (U SG S G age #04174500,H uron R iver) 0 5 10 15 20 25 J F M A M J J A S O N D m 3 /s 1976 -1996 & 2003: M ean M ontlhy [N O 3 - + N H 4 + ] 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 J F M A M J J A S O N D [NO 3-+ N H 4+](m g/L) 2003 1990 -1996 1980 -1989 1976 -1979 1976 -1987 & 2003: M ean M onthly [TotalP ] -75 -25 25 75 125 175 225 275 325 J F M A M J J A S O N D [TotalP](ug/L) 2003 1980 -1987 1976 -1987 1976 -1987 M onthly M ean S tream flow (U SG S G age #03353200,E agle C reek) 0 1 2 3 4 5 6 7 J F M A M J J A S O N D m 3 /s 2003 Ford Lake [N O 3 -N + N H 4 -N ]vs [C hlorophyll a] [NO 3 -N + N H 4 -N](m g/L) 0 2 4 6 8 10 [C hlorophyll a]( g/L) 0 20 40 60 80 100 2003 Ford Lake: N -toP R atios vs [C hlorophyll a] N:P 0 100 200 300 400 500 [C hlorophyll a]( g/L) 0 20 40 60 80 100 2003 Ford Lake [TotalP]vs [C hlorophyll a] [Total P]( g/L) 0 20 40 60 80 100 120 140 160 [C hlorophyll a]( g/L) 0 20 40 60 80 100 2003 Eagle C reek R eservoir[Total P]vs [Phytoplankton] [Total P](m g/L) 0 50 100 150 200 250 300 [Phytoplankton](natural units) 0 10000 20000 30000 40000 50000 60000 70000 2003 Eagle C reek R eservoir[Total N ]vs [Phytoplankton] [Total N ](m g/L) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 [Phytoplankton](natural units) 0 10000 20000 30000 40000 50000 60000 70000 2003 Eagle C reek R eservoirN :P vs [Phytoplankton] N:P 0 50 100 150 200 250 300 [Phytoplankton](natural units) 0 10000 20000 30000 40000 50000 60000 70000 R 2 = 0.3849 R 2 = 0.5635 R 2 = 0.4875 R 2 = 0.5740 R 2 = 0.7089 R 2 = 0.5241 HC Form ing Non-HC Form ing Euglenophyta Chlorophyta C hrysophyta Total 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 natural units/m L RESULTS : All three reservoirs showed that surface water [Tot P] remained constant or slightly increased from June to October: Ford and Bellville Lake [Tot P] showed no significant change at =0.10; ECR [Tot P] increase was significant at =0.05 (Fig. 2A and 2B) . All three reservoirs showed that surface water [Combined N] (NO 3 -N + NH 4 -N) significantly decreased from June to August (Ford and Belleville Lakes at =0.10 and ECR at =0.05) (Fig. 2C and 2D). Historical mean monthly discharge from the major tributary to ECR correlated more strongly to [Combined N] (R 2 = 0.8892) than to [Total P] (R 2 = 0.1151) from April to October (Fig. 2H, 2D, and 2B): [Total P] significantly increased (=0.05) as stream discharge from Big Eagle Creek was decreasing (Fig. 2H and 2B). This was not seen in Ford Lake data sets, which showed that neither N or P correlated well with Huron River discharge (Fig. 2G, 2C, and 2A). 1998 – 2000 Ford and Belleville Lake molar N:P (NO 3 -N + NH 4 -N to Total P), as well as ECR’s 1980-1987 molar N:P (NO 3 -N + NH 4 -N to Total P) and 2003 molar N:P (TKN-N + NO 3 -N to Total P) significantly decreased (= 0.10 and 0.5, respectively) from mid- to late Summer (Fig. 2E and 2F). Ford Lake’s surface [Total P] was moderately positively correlated to [chlorophyll a] using a linear regression (R 2 = 0.5740) (Fig. 4A) ECR’s surface [Total P] was moderately positively related to total phytoplankton concentrations as natural units/mL using a linear regression (R 2 = 0.4875) (Fig. 4B). Ford Lake’s surface [Combined N] was moderately correlated to [chl a] using an exponential decay regression (R 2 = 0.5241) (Fig. 4C). ECR’s surface [Total N] (TKN+NO 3 -N) was weakly related to total phytoplankton concentrations using an exponential decay model (R 2 = 0.3849) (Fig. 4D). Ford Lake’s molar surface N:P (NO 3 -N + NH 4 -N to Total P) was strongly correlated to [chl a] using an exponential decay model (R 2 = 0.7089) (Fig. 4E). ECR’s surface molar N:P (TKN-N+ NO 3 -N to Total P) was moderately related to total phytoplankton counts using an exponential decay model (R 2 = 0.5635) (Fig. 4F). In July and September, 2003, ECR reached N:P minima of 27N:1P and 9N:1P, respectively (Fig. 3F). ECR’s 2003 phytoplankton community structure was dominated by diatoms throughout the year with HC blue-greens making up a large portion (34%) of the community on July 23 (Fig. 3). (Phytoplankton growth was disrupted by treatment with algaecide on April 30, June 11, July 25, and October 16). 1998-2000 Ford and B ellville Lakes: N -to-P R atios 0 10 20 30 40 50 60 J F M A M J J A S O N D Ford Lake B elleville Lake DISCUSSION AND CONCLUSIONS : All three reservoirs showed an annual trend of N depletion and P abundance during mid- to late Summer. This N scarcity compared to P occurred as phytoplankton production was increasing as seen exponential decay regressions. This seems contrary to growth kinetics as decreasing the availability of a limiting nutrient should adversely affect phytoplankton growth. However, Ford Lake (1998 – 2000) and ECR (2003) high phytoplankton biomass occurred when HC blue-green algae (Anabaena and Aphanizomenon) were present in the water column. 2003 ECR data show a successional pattern that could be explained by Figure 1B, whereby high diatom (Asterionella, Aulocoseira, Cyclotella, and Synedra) assimilation effectively depleted N. High N utilization compared to P by diatoms can be significant: Asterionella’s N per cell mmol requirement is 100x greater than P (Lehman et. al., 1975). On July 23, when N:P decreased below 22N:1P (Healy and Hendzel, 1980), a threshold for N-limited phytoplankton growth, the successional shift to HC blue-green algae occurred. This mechanistic explanation was supported by the moderately strong empirical relationship between N:P to phytoplankton counts. Variability in the model can be attributed to algaecide treatment in the reservoir which disrupted phytoplankton population growth and acted to redistribute N in the water column, as well as the lack of taxa specific thresholds for nitrogen limited growth: total phytoplankton counts represent many algal communities, whose growth limitation and optimal growth conditions may occur at different N:P. In conclusion, data from three Midwest, urban reservoirs showed that N-to-P ratios could provide a better empirical model for predicting phytoplankton productivity in these systems than P or N alone. These reservoirs showed a stronger relationship between phytoplankton growth and molar N-to-P ratios than to [P] or [N]. Furthermore, using resource competition theory, this model could also be used to predict phytoplankton succession to nuisance HC blue- green algae. As HC blue-green algae have an ecological advantage over non-N-fixing algae when N is limiting and P is abundant, they are ideally suited for exponential growth and bloom Works Cited : Dillon, P.J., and Rigler, F., 1974. The phosphorus-chlorophyll relationship in lakes. Limnology and Oceanography. 19(5): 767-773. Healy, F.P. and L.L. Hendzel. 1980. Physiological indicators of nutrient deficiency in lake phytoplankton. Can. J. Fish. Aquat Sci. 37: 442-453. Lehman, J.T., D.B. Botkin, and G.E. Likens. 1975. The assumptions and rationales of a computer model of phytoplankton population dynamics. Limnology and Oceanography. 20(3) 343-364. Sterner, R.W. 1989. Resource competition during seasonal succession toward cyanobacteria. Ecology 70:229-245. Tedesco, L.P., E.A. Atekwana, G. Filippelli, K. Licht, L.K. Shrake, B.E. Hall, D.L Pascual, J. Latimer, R. Raftis, D. Sapp, G. Lindsey, R. Maness, D. Pershing, D. Peterson, K. Ozekin, C. Mysore, and M. Prevost. 2003. Water Quality and Nutrient Cycling in Three Indiana Watersheds and Their Reservoirs: Eagle Creek/Eagle Creek Reservoir, Fall Creek/Geist Reservoir, and Cicero Creek/Morse Reservoir. Central Indiana Water Resources Partnership, CEES Publication 2003-01, IUPUI, Indianapolis, IN. 163 pp. Eagle Creek Reservoir: N-to-P Ratios 0 50 100 150 200 250 J F M A M J J A S O N D N:P 1980-1987 2003 Figure 4 : Empirical relationships between nutrients and phytoplankton biomass (Ford Lake - [chl a] and ECR – phytoplankton counts). Ford Lake (left) and ECR (right). Figure 2 : Mean monthly N, P, and N:P for Ford Lake, Belleville Lake, and ECR. 2003 ECR N:P are in timescale (F). Stream discharge for Huron River upstream of its inflow to Ford Lake and for Big Eagle Creek upstream of its inflow to ECR. Dashed lines corresponding to nutrient concentrations represent ±2 St.Dev. Horizontal red lines represent molar sestonic 22N:1P, Healy and Hendzel (1980) threshold for N- limited phytoplankton growth (E and F). A F E D C B H G A F D B E C Acknowledgements : Veolia Water Indianapolis, LLC White River Analytical Labs, especially D. Peterson. Center for Earth and Environmental Science • L. Shrake, Project Coordinator • B.E. Hall, Systems Engineer Ford and Belleville Lake research funded by a grant MDEQ (Michigan Department of Environmental Quality) and the University of Michigan Eagle Creek Reservoir research funded by the CIWRP (Central Indiana Water Resource Partnership) Figure 3 : 2003 ECR phytoplankton populations and community structure from May 29 – October 1, 2003. 500 0 500 1000 M eters N U S G S D O Q Q 1998 Sample Sites 500 0 500 M eters N IM A G IS 2002

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A. B. Warm temperatures High incident solar radiation + Quiescent water column Deep Photic Zone. Warm temperatures High incident solar radiation + Quiescent water column Deep Photic Zone. C. N. C. C. C. N. C. N. S i. S i. Si. S i. Growth of specific algae in lake. - PowerPoint PPT Presentation

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  • CULTURAL EUTROPHICATION OF THREE MIDWEST URBAN RESERVOIRS: THE ROLE OF NITROGEN LIMITATION IN DETERMINING PHYTOPLANKTON COMMUNITIESPascual, D. L., University of Michigan School of Public Health & Indiana University-Purdue University, (UM) Ann Arbor & (IUPUI) Indianapolis, USAJohengen, T. H., University of Michigan, Ann Arbor, USAFilippelli, G. M., Indiana University Purdue University, Indianapolis, USATedesco, L. P., Indiana University Purdue University, Indianapolis, USAMoran, D., Veolia Water, Indianapolis, LLC,1 USA ABSTRACT:The cultural eutrophication of three Midwest urban reservoirs has resulted in impaired water quality. Nutrient loading to these reservoirs has resulted in the formation of nuisance algal blooms, including possible toxin-producing and/or taste and odor causing, heterocyst-forming blue-green algae such as Anabaena, Aphanizomenon, and Cylindrospermopsis. However, while eutrophication models tend to utilize a single parameter, namely P, to predict potential algal standing stocks, data from three Midwest urban reservoirs showed that N was equally important in determining phytoplankton productivity and more important in determining phytoplankton succession from diatoms and greens to heterocyst-forming blue-green algae. Analysis of monthly nutrient concentrations (Total P, NO3-, NH4+) taken from 1998 2000 for two southeastern Michigan reservoirs, Ford Lake and Bellville Lake, and weekly nutrient data taken from 1976 1996 and bi-weekly data collected in 2003 for Eagle Creek Reservoir, Indiana showed consistent annual trends of NO3- + NH4+ depletion and P abundance from mid- to late summer, suggesting that phytoplankton production became seasonally N-limited in these reservoirs. Data from Eagle Creek Reservoir indicated that N concentrations were more strongly dependent on watershed inputs than was P, a trend not supported by Ford and Bellville Lake data sets.INTRODUCTION:Since Vollenweider first developed input-output models to describe the relationship between phosphorus and eutrophication, empirical models have been employed as a way to understand how a single parameter can work to affect ecological changes such as changes in phytoplankton biomass (e.g. Dillon and Rigler, 1974). However, understanding the change from a diverse phytoplankton community to a specific nuisance algal bloom, i.e. heterocyst-forming (HC) blue-green algae capable of producing toxins and/or taste and odor causing compounds (e.g. MIB (2-methylisoborneol) and geosmin), requires a complex model which uses several parameters founded in mechanistic theory. These mechanism-based parameters include physical conditions necessary for nuisance algal growth, nutrient or chemical dynamics which promote nuisance algal growth, and biotic stresses, such as resource competition, which work to select specific nuisance algae for exponential growth (e.g. Sterner, 1989 and Tilman et al., 1982). Therefore, a mechanistic understanding of nuisance algal bloom formation could be used to predict phytoplankton abundance and seasonal phytoplankton succession to nuisance algae, specifically, HC blue-greens (Fig. 1). HYPOTHESES:Small urban reservoirs undergo a transition from nitrogen rich, P-limited growth conditions to nitrogen poor, P-abundant growth conditions.Given sufficient physical conditions for growth (i.e., water temperatures > 25 C, abundant incident solar radiation, and quiescent water,) , this transition in the nutritive environment spurs the growth of nuisance algal blooms of heterocyst-forming blue-green genera such as Anabaena, Aphanizomenon, and Cylindrospermopsis.Figure 1: Mechanistic model based on resource competition for limiting nutrients, describing seasonal phytoplankton succession to HC blue-green algae and possible MIB and geosmin production. A diagrams a successional pattern in which green algae dominate during mid-summer; B shows a successional pattern in which green algae are never able to become a significant portion of the phytoplankton community because Si abundance allows for high rates of N assimilation by diatoms which leads to N-limited phytoplankton growth, a condition in which HC blue-greens are ideally suited to thrive.METHODS:Nutrient data from three eutrophic Midwest, urban reservoirs of similar morphology were analyzed for trends in [Combined N] (NH3-N + NH4-N) and [Total P]. Nutrient and phytoplankton data from 3 stations in Ford Lake (1998-2000) and 3 stations in Eagle Creek Reservoir (ECR) (2003) were pooled then analyzed for empirical relationships between nutrient concentrations and phytoplankton growth as measured by [chlorophyll a] (Ford Lake) and phytoplankton counts (ECR). (See maps.) 2003 ECR nutrient and phytoplankton data were then analyzed in the context of the proposed model. STUDY SITES:Both Ford Lake and Eagle Creek Reservoir have been documented as experiencing mid- to late Summer blooms of HC blue-green algae: Ford Lake having yearly Aphanizomenon blooms and Eagle Creek Reservoir having a mixed bloom including Anabaena, Aphanizomenon, and Cylindrospermopsis. Ford Lake, MichiganEutrophicImpoundment of the Huron RiverCreated in 1932Area: 3.25 km2Volume: 15,151,000 m3Eagle Creek Reservoir, IndianaEutrophicImpoundment of Big Eagle CreekCreated in 1967Area: 5.01 km2Volume: 20,820,000 m3(Tedesco et al., 2003)Belleville Lake, MichiganEutrophicImpoundment of the Huron RiverCreated in 1924Area: 5.14 km2Volume: 21,923,000 m3RESULTS:All three reservoirs showed that surface water [Tot P] remained constant or slightly increased from June to October: Ford and Bellville Lake [Tot P] showed no significant change at =0.10; ECR [Tot P] increase was significant at =0.05 (Fig. 2A and 2B) .All three reservoirs showed that surface water [Combined N] (NO3-N + NH4-N) significantly decreased from June to August (Ford and Belleville Lakes at =0.10 and ECR at =0.05) (Fig. 2C and 2D).Historical mean monthly discharge from the major tributary to ECR correlated more strongly to [Combined N] (R2 = 0.8892) than to [Total P] (R2 = 0.1151) from April to October (Fig. 2H, 2D, and 2B): [Total P] significantly increased (=0.05) as stream discharge from Big Eagle Creek was decreasing (Fig. 2H and 2B). This was not seen in Ford Lake data sets, which showed that neither N or P correlated well with Huron River discharge (Fig. 2G, 2C, and 2A).1998 2000 Ford and Belleville Lake molar N:P (NO3-N + NH4-N to Total P), as well as ECRs 1980-1987 molar N:P (NO3-N + NH4-N to Total P) and 2003 molar N:P (TKN-N + NO3-N to Total P) significantly decreased (= 0.10 and 0.5, respectively) from mid- to late Summer (Fig. 2E and 2F). Ford Lakes surface [Total P] was moderately positively correlated to [chlorophyll a] using a linear regression (R2 = 0.5740) (Fig. 4A)ECRs surface [Total P] was moderately positively related to total phytoplankton concentrations as natural units/mL using a linear regression (R2 = 0.4875) (Fig. 4B).Ford Lakes surface [Combined N] was moderately correlated to [chl a] using an exponential decay regression (R2 = 0.5241) (Fig. 4C). ECRs surface [Total N] (TKN+NO3-N) was weakly related to total phytoplankton concentrations using an exponential decay model (R2 = 0.3849) (Fig. 4D).Ford Lakes molar surface N:P (NO3-N + NH4-N to Total P) was strongly correlated to [chl a] using an exponential decay model (R2 = 0.7089) (Fig. 4E).ECRs surface molar N:P (TKN-N+ NO3-N to Total P) was moderately related to total phytoplankton counts using an exponential decay model (R2 = 0.5635) (Fig. 4F). In July and September, 2003, ECR reached N:P minima of 27N:1P and 9N:1P, respectively (Fig. 3F).ECRs 2003 phytoplankton community structure was dominated by diatoms throughout the year with HC blue-greens making up a large portion (34%) of the community on July 23 (Fig. 3). (Phytoplankton growth was disrupted by treatment with algaecide on April 30, June 11, July 25, and October 16). DISCUSSION AND CONCLUSIONS:All three reservoirs showed an annual trend of N depletion and P abundance during mid- to late Summer.This N scarcity compared to P occurred as phytoplankton production was increasing as seen exponential decay regressions. This seems contrary to growth kinetics as decreasing the availability of a limiting nutrient should adversely affect phytoplankton growth. However, Ford Lake (1998 2000) and ECR (2003) high phytoplankton biomass occurred when HC blue-green algae (Anabaena and Aphanizomenon) were present in the water column.2003 ECR data show a successional pattern that could be explained by Figure 1B, whereby high diatom (Asterionella, Aulocoseira, Cyclotella, and Synedra) assimilation effectively depleted N. High N utilization compared to P by diatoms can be significant: Asterionellas N per cell mmol requirement is 100x greater than P (Lehman et. al., 1975). On July 23, when N:P decreased below 22N:1P (Healy and Hendzel, 1980), a threshold for N-limited phytoplankton growth, the successional shift to HC blue-green algae occurred. This mechanistic explanation was supported by the moderately strong empirical relationship between N:P to phytoplankton counts. Variability in the model can be attributed to algaecide treatment in the reservoir which disrupted phytoplankton population growth and acted to redistribute N in the water column, as well as the lack of taxa specific thresholds for nitrogen limited growth: total phytoplankton counts represent many algal communities, whose growth limitation and optimal growth conditions may occur at different N:P.

    In conclusion, data from three Midwest, urban reservoirs showed that N-to-P ratios could provide a better empirical model for predicting phytoplankton productivity in these systems than P or N alone. These reservoirs showed a stronger relationship between phytoplankton growth and molar N-to-P ratios than to [P] or [N]. Furthermore, using resource competition theory, this model could also be used to predict phytoplankton succession to nuisance HC blue-green algae. As HC blue-green algae have an ecological advantage over non-N-fixing algae when N is limiting and P is abundant, they are ideally suited for exponential growth and bloom formation at low N:P. Therefore, rather than using P-only models to predict production in these systems, these reservoirs could be better modeled by utilizing N-to-P ratios and the mechanism by which HC blue-green algae would become dominant. This data could then be applied to create long-term management models aimed at preventing the occurrence of nuisance HC blue-green blooms in these eutrophic, urban reservoirs. Works Cited:Dillon, P.J., and Rigler, F., 1974. The phosphorus-chlorophyll relationship in lakes. Limnology and Oceanography. 19(5): 767-773.Healy, F.P. and L.L. Hendzel. 1980. Physiological indicators of nutrient deficiency in lake phytoplankton. Can. J. Fish. Aquat Sci. 37: 442-453.Lehman, J.T., D.B. Botkin, and G.E. Likens. 1975. The assumptions and rationales of a computer model of phytoplankton population dynamics. Limnology and Oceanography. 20(3) 343-364.Sterner, R.W. 1989. Resource competition during seasonal succession toward cyanobacteria. Ecology 70:229-245.Tedesco, L.P., E.A. Atekwana, G. Filippelli, K. Licht, L.K. Shrake, B.E. Hall, D.L Pascual, J. Latimer, R. Raftis, D. Sapp, G. Lindsey, R. Maness, D. Pershing, D. Peterson, K. Ozekin, C. Mysore, and M. Prevost. 2003. Water Quality and Nutrient Cycling in Three Indiana Watersheds and Their Reservoirs: Eagle Creek/Eagle Creek Reservoir, Fall Creek/Geist Reservoir, and Cicero Creek/Morse Reservoir. Central Indiana Water Resources Partnership, CEES Publication 2003-01, IUPUI, Indianapolis, IN. 163 pp.Tilman, D., S.S. Kilham and P. Kilham. 1982. Phytoplankton Community Ecology: The role of limiting nutrients. Annual Review of Ecology and Systematics. 13: 349-372.Figure 4: Empirical relationships between nutrients and phytoplankton biomass (Ford Lake - [chl a] and ECR phytoplankton counts). Ford Lake (left) and ECR (right).Figure 2: Mean monthly N, P, and N:P for Ford Lake, Belleville Lake, and ECR. 2003 ECR N:P are in timescale (F). Stream discharge for Huron River upstream of its inflow to Ford Lake and for Big Eagle Creek upstream of its inflow to ECR. Dashed lines corresponding to nutrient concentrations represent 2 St.Dev. Horizontal red lines represent molar sestonic 22N:1P, Healy and Hendzel (1980) threshold for N-limited phytoplankton growth (E and F).AFEDCBHGAFDBECAcknowledgements: Veolia Water Indianapolis, LLC White River Analytical Labs, especially D. Peterson.Center for Earth and Environmental ScienceL. Shrake, Project CoordinatorB.E. Hall, Systems EngineerFord and Belleville Lake research funded by a grant MDEQ (Michigan Department of Environmental Quality) and the University of MichiganEagle Creek Reservoir research funded by the CIWRP (Central Indiana Water Resource Partnership)Figure 3: 2003 ECR phytoplankton populations and community structure from May 29 October 1, 2003.

    Chart2

    JJJ

    FFF

    MMM

    59.4581.108254777337.791745222743.6552.879662326834.4203376732

    46.976.069224130317.730775869736.32551.417382184421.2326178156

    49.22595.99034366842.459656331637.094117647166.97040176917.217833525

    53.387597.66184923299.113150767159.77595.872254995123.6777450049

    61.2142857143131.4616226862-9.033051257655.980.439491980631.3605080194

    55.0687592.69864724517.43885275558.033333333382.764077296533.3025893702

    47.774.204037428321.195962571751.0708333333114.475485562-12.3338188954

    NNN

    DDD

    Ford Lake

    1

    -1

    Belleville Lake

    1

    -1

    [Total P] (ug/L)

    1998-2000: Mean Monthly [Total P]

    Ford 3-year

    Lake AveragesHuron BridgeMI. Ave.F-1F-2F-3F-4

    Tot PSRPNO3NH4Tot PSRPNO3NH4Tot PSRPNO3NH4Tot PSRPNO3NH4Tot PSRPNO3NH4Tot PSRPNO3NH4Tot PSRPNO3NH4

    Date(mg/L)(mg/L)(mg/L)(mg/L)Total Soluble NSRP:TSNDate(mg/L)(mg/L)(mg/L)(mg/L)Date(mg/L)(mg/L)(mg/L)(mg/L)Date(mg/L)(mg/L)(mg/L)(mg/L)Date(mg/L)(mg/L)(mg/L)(mg/L)Date(mg/L)(mg/L)(mg/L)(mg/L)Date(mg/L)(mg/L)(mg/L)(mg/L)

    5/29/9836.723.50.670.070.7469.785/29/98110.80.2189.95/29/9859.059.41.0956.65/29/9845.625.71.0394.7SBSBSBSBSMBSMBSMBSMBSMBSMBSMBSMB

    6/6/9853.7202.00.770.090.869.376/6/986/6/986/6/98102.6190.21.1970.35/29/9829.432.931.532.60.560.5778.4121.95/29/9839.033.959.213.314.742.60.560.580.5976.6112.3190.35/29/9832.833.644.523.321.535.50.530.530.5931.266.3175.2

    6/19/9855.823.00.660.050.7167.806/19/9823.00.3497.26/19/9814.21.1241.86/19/9872.841.21.1131.76/6/9844.667.8106.6~3200.550.7164.362.06/6/9841.629.440.3417.3~280113.30.600.590.64105.5140.7128.76/6/9825.961.625.793.764.772.40.720.620.56122.7118.2122.7

    7/17/9848.317.60.590.230.81102.097/17/987/17/987/17/9886.618.91.2686.26/19/9873.844.120.015.40.610.5043.356.86/19/9845.134.739.015.420.016.90.500.460.5546.354.5122.76/19/9831.339.333.215.419.212.40.420.510.5360.692.4122.7

    7/28/9853.97.00.740.110.85268.877/28/9869.24.20.2040.07/28/9871.312.21.3740.07/28/9863.58.21.327.57/17/9842.393.65.139.90.460.38140.3292.27/17/9835.645.844.24.43.55.20.370.370.39148.3162.2190.77/17/9828.640.9163.741.94.72.90.250.270.29531.9124.3109.8

    8/2/9886.33.00.700.040.74547.098/2/988/2/988/2/9878.63.81.3711.17/28/9845.268.62.74.40.650.6486.3170.07/28/9846.343.968.67.87.417.50.510.540.58157.5186.3337.57/28/9860.553.387.29.19.922.40.480.470.53170.0216.3348.8

    8/14/9854.01.80.400.010.41499.258/14/988/14/988/14/9865.72.31.165.28/2/9870.01.42.20.400.606.537.18/2/98142.2115.4111.11.63.14.30.490.550.5716.951.465.08/2/9838.242.352.25.17.57.00.540.540.53110.6142.4181.4

    8/19/985.80.380.030.42160.438/19/984.60.1564.48/19/989.71.1125.48/19/9816.51.0836.48/14/9850.61.77.40.030.026.5128.88/14/9864.974.557.31.61.32.30.190.220.264.627.385.88/14/9831.529.1153.01.62.480.40.220.310.469.878.774.1

    9/22/9850.76.30.610.060.67236.189/22/9820.12.30.0544.89/22/9860.015.71.5159.79/22/9873.612.91.5561.68/19/982.16.50.210.607.878.08/19/982.32.618.60.120.130.1656.696.2209.48/19/982.119.153.00.120.380.4438.4265.348.1

    9/30/9867.86.00.710.070.78285.039/30/989/30/989/30/9870.518.31.5730.69/22/9855.959.39.711.00.750.78176.2203.39/22/9840.844.150.01.71.11.10.130.120.135.30.80.89/22/9832.630.667.50.81.023.50.000.000.008.63.41369.4

    10/14/9845.011.20.800.331.13223.0810/14/9810/14/9810/14/9850.57.90.5232.99/30/9857.838.52.02.20.670.6944.264.99/30/9897.990.854.12.02.23.80.330.330.3351.3160.685.39/30/9844.937.044.91.82.27.70.250.250.29161.3185.2372.9

    10/20/9852.423.81.810.041.85171.5410/20/9815.23.80.1539.810/20/9844.526.21.7936.910/20/9852.423.81.8136.910/14/9846.848.913.314.10.960.99380.1381.510/14/9841.542.544.310.613.711.00.870.890.89439.7439.7428.310/14/9841.139.042.012.815.813.40.850.880.89448.2446.8448.2

    10/20/9841.143.610.812.21.081.0836.951.110/20/9837.836.9203.211.811.315.50.940.890.95371.6363.1385.810/20/9836.935.536.012.911.912.30.950.930.93377.3375.9374.5

    Huron BridgeMI. Ave.F-1F-2F-3F-4

    Tot PSRPNO3NH4Tot PSRPNO3NH4Tot PSRPNO3NH4Tot PSRPNO3NH4Tot PSRPNO3NH4Tot PSRPNO3NH4Tot PSRPNO3NH4

    Date(mg/L)(mg/L)(mg/L)(mg/L)Total Soluble NSRP:TSNDate(mg/L)(mg/L)(mg/L)(mg/L)Date(mg/L)(mg/L)(mg/L)(mg/L)Date(mg/L)(mg/L)(mg/L)(mg/L)Date(mg/L)(mg/L)(mg/L)(mg/L)Date(mg/L)(mg/L)(mg/L)(mg/L)Date(mg/L)(mg/L)(mg/L)(mg/L)

    4/29/9959.54.51.050.051.10546.294/29/9922.21.30.527.44/29/9955.02.50.931.44/29/9965.02.51.030.6SBSBSBSBSMBSMBSMBSMBSMBSMBSMBSMB

    5/26/9948.69.60.700.130.83190.795/26/99n/an/an/an/a5/26/9957.613.51.172.15/26/9962.910.81.071.34/29/9970.467.77.05.51.11.167.266.44/29/9956.952.053.35.55.34.11.11.11.265.661.562.44/29/9945.548.245.52.82.42.11.01.01.035.538.037.1

    6/15/9947.18.50.800.160.96251.196/15/9930.7


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