Influence of environmental factors on the vertical distribution of phytoplankton in Lacamas Lake, WA

Kaitlin Perkins State University Vancouver Spring 2017 Gretchen Rollwagen-Bollens Aquatic Ecology Lab Abstract:

Urbanization in watersheds has led to nutrient enrichment () and dissolved oxygen depletion (hypoxia) in many freshwater systems. These conditions impact species diversity, availability of habitat, and organism behavior within these systems. Lacamas Lake is a managed in Camas, WA that experiences seasonal stratification, hypoxia in bottom waters, and is highly eutrophic, sometimes resulting in harmful algal blooms. Lacamas Lake also undergoes a drawdown for dam maintenance purposes each autumn. To better understand the impacts of hypoxia and management actions on the phytoplankton community in Lacamas, we pursued three research questions: 1) How is phytoplankton biomass vertically distributed in relation to dissolved oxygen levels? 2) Are there differences between day and night vertical distributions of phytoplankton? 3) How does phytoplankton vertical distribution vary before and after lake drawdown. 4) What is the relationship between phytoplankton size and vertical distribution? During August (pre-drawdown) and October (post-drawdown) 2015, phytoplankton biomass was measured at six depths from surface to bottom and a weighted mean depth was calculated for each sampling time. We found that phytoplankton biomass was consistently concentrated above the hypoxic zone, indicating these organisms were avoiding the low oxygen water. There was a significant difference in vertical distribution between day and night in one size fraction, as well as a significant difference in the vertical distribution between pre- and post-drawdown. These results highlight the need for strategies that manage run-off flowing into the watersheds in urban areas and further research into the ecological implications of the annual drawdown at Lacamas Lake.

Keywords:

Phytoplankton ecology, diel vertical distribution, hypoxia, eutrophication, reservoir

Introduction:

Urbanization and agriculture have altered the ecology of aquatic systems globally. Livestock grazing, the burning of fossil fuels, and paved surfaces increase pollutant loading, and dams have created where previously rivers and lakes dominated (Carpenter et al 2011).

Dams are most frequently constructed for power production, and their associated reservoirs often take on social significance as recreational sites (Lehman et al 2014). Reservoirs differ from other aquatic ecosystems in their hydrology, nutrient loading, and seasonal response, among other factors. In turn, they harbor phytoplankton communities with specific spatiotemporal dynamics and life strategies for success (Tornés et al 2014).

Approximately fifty percent of lakes in the United States are classified as eutrophic, meaning they are impacted by excess nutrients, primarily nitrogen and phosphorus (Smith et al

1999). Despite efforts to mitigate and prevent eutrophication through programs to eliminate nutrient runoff, internal phosphorus loading may still be a problem as nutrients stored in reservoir and lake sediments re-enter the water column. Phosphorus is typically released from sediments when the bottom of the lake becomes anoxic during periods of stratification

(Nurnberg et al 2013). Eutrophication is commonly linked to low phytoplankton community diversity, and often only one or two dominant species are seen in eutrophic system (Izaguirre et al 2012). Eutrophication is also linked to harmful algal blooms (Conley et al 2009) and hypoxia

(Vanderploeg et al 2009) in freshwater lake and reservoir systems. Harmful algal blooms (HABs) occur when water conditions spur the rapid reproduction of phytoplankton in marine or freshwater systems. In freshwater lakes, cyanobacterial blooms are the most common type of HAB and a sign of eutrophication (Conley et al 2009). HABs may be detrimental to human health, stocks, and ecosystem structure and function (Anderson et al

2002). Hypoxia is a common indicator of eutrophication as well (Vanderploeg et al 2009).

Hypoxia changes trophic dynamics in aquatic environments by altering migratory patterns of motile phytoplankton, as well as habitat availability (Zhang et al 2015). The stress of low oxygen levels leads to a decrease in trophic diversity and increases the populations of opportunistic organisms such as cyanobacteria (Friedrich et al 2012). Cyanobacteria are more adapted to low light conditions that often occur in turbid, eutrophic lakes, and therefore may dominate over other species or genera of phytoplankton (Sinistro et al 2015).

Nutrient and light availability, predation, and the mixing conditions in a lake system may directly and indirectly influence the composition of its phytoplankton community (Becker et al

2010). Higher latitude reservoirs are often thermally stratified in the summer, which coincides with vertical gradients of nutrients, light availability, and dissolved oxygen. Phytoplankton are impacted by thermal and density stratification, as it creates resource niches vertically in the water column (Cantin et al 2011). Access to these resources niches by phytoplankton is determined by their life strategies, such as size, motility, and buoyancy (Reynolds 2006). Small organisms such as cyanobacteria, for example, may capitalize on increased buoyancy to access light in the surface layer of the water column, while larger motile organisms such as flagellates may migrate deeper in the water column to access the nutrient-rich lower layers (Cantin et al

2011). Phytoplankton are plant-like organisms that are important globally, as they are responsible for approximately half of the world’s primary production (Kruk et al 2012). Phytoplankton communities are vertically heterogeneous, and their location in the water column informs their role as primary producers and a food source for other organisms (Mellard et al 2011). Their availability as a resource for grazing zooplankton can have bottom-up trophic cascade effects, and similarly zooplankton and fish community structure can impact phytoplankton community composition in a top-down manner (Reynolds 2006). Phytoplankton, due to their sensitive response to changes in abiotic factors such as nutrients, hydrology, and stratification, make them excellent indicators of ecological change (Paerl et al 2006). The visual appearance of water is impacted by phytoplankton, and knowledge of their community structure and function is a useful freshwater management tool (Kruk et al 2012).

Biomass and size aggregation estimates, in conjunction with vertical distributions, are useful tools for investigating phytoplankton ecological response to environmental conditions (Kruk et al 2002). Phytoplankton have a crucial role in determining the usability and public perception of recreational waterways due to nuisance algal blooms and poor water quality, and Lacamas Lake has a history of monitoring and restoration projects due to negative public opinion of its

“health” (Carlson 1985). Lacamas Lake has been monitored since the 1980s, and its seasonal hydrologic and nutrient dynamics are well documented, making it an ideal model reservoir system (Carlson 1985, Hutton and Schnabel 2004). The reservoir is managed through restoration programs and an annual drawdown, and is impacted by urbanization and upstream livestock grazing and agricultural land use practices (Hutton and Schnabel 2004). Reservoirs differ from lakes as they are often managed through controlled water release for maintenance, aquatic vegetation management, or water consumption (Cooke 1980). Water drawdown may have unintended effects, as water level reductions lead to soil desiccation, prompting nutrient release upon rewetting (Baldwin et al 2008). Drawdowns have also been linked to phytoplankton blooms, which occur when nutrients are released from the sediment

(Klotz and Linn 2001).

Increased urbanization means that anthropogenically-impacted lakes will become increasingly common, highlighting the importance of understanding their ecology and function.

Phytoplankton are an important indicator of the ecological status of a body of water, and can inform water quality in freshwater systems. Investigation into the vertical distribution, seasonal dynamics, and size structure of the phytoplankton in Lacamas Lake provides insights into its ecological status. More broadly, we seek to answer: how does the phytoplankton community in

Lacamas Lake respond to changes in season and resource availability?

Research Questions:

1) How is phytoplankton biomass vertically distributed in relation to dissolved oxygen levels?

2) Are there differences between day and night vertical distributions of phytoplankton?

3) How does phytoplankton vertical distribution vary before and after lake drawdown?

4) What is the relationship between phytoplankton size and vertical distribution?

We established a sampling program to measure phytoplankton biomass at multiple depths during the day and night in the summer and autumn 2015, both before and after the annual drawdown. The collections involved recording environmental factors that impact phytoplankton, including temperature gradients and dissolved oxygen levels.

Methods:

Study site:

Lacamas Lake is a small reservoir (1.3 km2) located in

Clark County, Washington

(45.37N, 122.25W) (Fig. 1). The lake, which is as deep as 19.8 meters and has an average depth of 7.8 meters, was dammed in 1938 (Deemer et al Figure 1 Map of Lacamas Lake, Washington. The red star represents the 2015). The lake is fed by five sample site, located in the deepest part of the lake. The dam is at the southeastern point. main tributaries, including

Lacamas Creek. These tributaries experience a wide variety of conditions at the headwaters.

Agricultural lands, urban development, and deforestation causes pollutant inputs that collect in

Lacamas Lake. These various inputs to the lake lead to a build-up of pollutants and sediments

(Schnabel and Hutton 2004). Influential inputs include nutrients from upstream dairy farms and storm-water runoff from the urban areas (Deemer et al 2011). The lake is strongly stratified between June and October, when it becomes eutrophic and experiences hypolimnetic hypoxia

(Deemer et al 2015). Since the 1980s the lake has a history of poor water quality, nutrient over- enrichment, and is classified as eutrophic or hypereutrophic (Carlson 1985). Lacamas Lake is drawn down annually in the fall for maintenance of the dam, which removes approximately fifty percent of the water (Deemer et al 2011).

Sample collection:

Water samples were collected from the deepest part of the lake (Figure 1) at mid-day and mid-night from six discrete depths below the surface (one, three, five, seven, nine, and fifteen meters) using a Van Dorn bottle. Water from each Van Dorn bottle was transferred to brown

250-mL bottles upon collection, stored on ice in a cooler, and returned to the laboratory. The samples were filtered as described below, and stored in the freezer within six hours. Dissolved oxygen concentration and temperature were measured throughout the water column with a

YSI85 probe, and transparency measured with a Secchi disk.

Size fractionation and measurement of chlorophyll biomass:

Upon return to the lab, the water samples from each date, time of day, and depth were processed and ultimately isolated into four size fractions: 0.7 – 250 µm, 0.7 – 2.7 µm, 2.7 – 35

µm, and 35 – 250 µm. The initial filtering process is diagrammed in Figure 2. First, each sample was passed through a 250 µm sieve to remove the majority of non-phytoplankton organisms.

Then the filtrate was split, and one half was set aside while the other half was poured over a second sieve of 35- µm mesh size. Next, thirty-five milliliters of the 35- µm sieved water and the

250- µm sieved water samples were further split and vacuum filtered over either a 0.7- µm filter (Whatman GF/F) to produce the 0.7 – 35 µm and the 0.7 – 250 µm fractions, or a 2.7-µm filter (Whatman GF/D) to produce the 2.7 – 35 µm and 2.7 – 250 µm fractions.

Figure 2. The filtration process applied to the water samples collected from Lacamas Lake.

For each sample, 35 mL of sample water was filter over either a Whatman GF/F or

Whatman GF/D filter. The filters were frozen for 24 hours, then extracted in 20 mL of 90% acetone for 24 hours. The concentration of chlorophyll-a in each sample was measured via fluorometric analysis using the acidification method of Strickland and Parson (1972).

The biomass of the 0.7 µm – 2.7 µm fraction was calculated by subtracting the concentration of chlorophyll-a in Size 2 from the concentration of chlorophyll-a in Size 3. This size fraction included the picoplankton, including cyanobacteria. The biomass of the 2.7 –

35 µm size range, which included nanoplankton-sized organisms such as flagellates, was simply the total chlorophyll-a concentration of Size 2. The biomass of the 35 µm – 250 µm Figure 3 A visualization of the size ranges used in the fraction was calculated by subtracting the chlorophyll-a difference calculations. concentration of Size 3 from that of Size 1, and included the largest phytoplankton organisms such as diatoms and ciliates. Finally, the biomass of the entire phytoplankton community fraction (0.7 µm – 250) µm was determined as the chlorophyll-a concentration measure in Size

1 (Figure 3).

Data and statistical analyses:

We calculated the weighted mean depths (WMD) of the chlorophyll-a biomass in each size fraction at each sampling time to allow for statistical comparison between samples. This allowed us to test for temporal differences in vertical distribution of phytoplankton biomass.

The WMDs are calculated according to Rollwagen-Bollens et al (2006) as follows:

∑ 퐴푖 ∙ 푍푖 푊푀퐷 = ∑ 퐴푖

Where A is the chlorophyll a concentration (µg/L) at each sampling depth (i)and Z is the midpoint depth (m) of each sampled depth range. The values for Z were calculated as follows:

퐷푒푝푡ℎ푛 − 퐷푒푝푡ℎ푛−1 퐷푒푝푡ℎ푛+1 − 퐷푒푝푡ℎ푛 1 퐷푒푝푡ℎ = ( + 퐷푒푝푡ℎ + + 퐷푒푝푡ℎ ) ∗ 푛 2 푛−1 2 푛 2

Where n is the discrete sampling depth that the midpoint is being calculated for.

The variances of the weighted mean depths were compared using the F test for equal variance. To analyze whether the weighted mean depths from different sampling dates or times were significantly different than each other, either the student’s two sample t-test for equal variance or Welch’s t-test for unequal variance was used.

Results:

Seasonal changes in environmental conditions: We observed distinct changes in the vertical structure of the water column in Lacamas Lake between summer and fall of 2015. The thermocline and oxycline both deepened from August to

October, and the surface temperature of the water was greater in August than October. Water transparency increased from August to October. Lacamas Lake was deeper before the water drawdown than after (table 1).

Table 1. Environmental data for August and October.

Phytoplankton biomass size distribution:

We did not observe a significant seasonal or day-night change in chlorophyll-a concentration size fraction distribution. The water column total chlorophyll-a for the 0.7 – 250

µm decreased from August mid-day to October mid-day (Figure 4). There was significant change in relative abundance, as the chlorophyll-a concentrations of each size fraction, 0.7 – 2.7 µm, 2.7 – 35 µm, and 35 – 250 µm, did not change relative to each other from August to October

(Figures 5 and 6).

Figure 4. Total chlorophyll-a concentrations for the 0.7 – 250 µm size fraction for August and October. The water column total chlorophyll-a was significantly different between August mid-day and October mid-day (p: 0.0056).

Vertical distribution of phytoplankton biomass: Figure 5. Relative abundance for total water Figure 6. Relative abundance for total water column chlorophyll-a for each of the three column chlorophyll-a for each of the three size size fractions in August. fractions in October.

Vertical distribution of phytoplankton biomass:

We observed significant changes in the vertical structure of chlorophyll-a biomass in

Lacamas Lake between August and October of 2015, while observing only one significant day- night change. The weighted mean depths of all size fractions, except the 0.7 – 2.7 µm range, were located in or above the oxycline. The chlorophyll-a concentrations for each size fraction were greater above the oxycline, except for the majority of sampling dates for the 0.7 – 2.7 µm range. The October 2.7 – 35 µm range had a greater weighted mean depth mid-day than mid- night (p-value: 0.0058) (Figures 7 and 8, Tables 2 and 3).

Figure 7. August mid-day and mid-night vertical distributions of chlorophyll-a concentrations. The blue bar represents the oxycline, and the circles represent the weighted mean depth for each size fraction.

**

Figure 8. August mid-day and mid-night vertical distributions of chlorophyll-a concentrations. The blue bar represents the oxycline, and the circles represent the weighted mean depth for each size fraction. The 2.7 – 35 µm size fraction weighted mean depth was significantly deeper in the water column mid- night than mid-day (p: 0.0058).

Table 2. Weighted mean depth values for August and October.

Table 3. Statistical comparison of August weighted mean depths to October weighted mean depths within the same size fraction.

Take home points:

 Total chlorophyll concentrations were greater in August than October.

 The chlorophyll-a concentration relative biomass did not change from August to

October.

 Chlorophyll-a biomass was concentrated above the oxycline and thermocline in both

August and October in all size fractions except 0.7-2.7 µm.

 Chlorophyll-a was concentrated deeper in the water column in October than in August.

 The 2.7 – 35 µm size fraction of chlorophyll-a was concentrated significantly deeper in

the water column mid-night than mid-day in October.

Discussion:

Lacamas Lake is a small reservoir created in the early 20th century when Lacamas Creek was dammed to support paper mill production in Camas, Washington (Deemer et al 2011). While

Lacamas Lake is no longer used for commercial purposes, this small reservoir has gained recreational and ecological importance in the community, and is popular for fishing, hiking, and boating (Schnabel and Hutton 2004). The dam that impounds the reservoir is presently managed by Georgia Pacific in Camas, Washington, who lower the water levels dramatically

(approximately 50%) each fall to maintain the dam structure (Deemer et al 2011). Lacamas Lake has been continuously designated as eutrophic since it was first monitored in the 1980s, and is considered impaired under EPA guidelines due to high phosphorus concentration (Schnabel and

Hutton 2004). The bottom layers of the reservoir are severely hypoxic in the summer months, limiting habitat availability. Additionally, the lake has displayed elevated levels of cyanobacteria in the summer, which are often the cause of harmful algal blooms (Schnabel and Hutton 2004).

We were interested in investigating how phytoplankton respond to low oxygen levels, and the impact of seasonal changes on phytoplankton biomass.

Seasonal changes in the Lacamas Lake vertical structure:

Lacamas Lake exhibits seasonal thermal stratification May through October, which occurs when solar energy heats the uppermost layers of the reservoir. Oxyclines and thermoclines represent the depth range over which oxygen concentration and temperature, respectively, change dramatically. The strength of the oxycline and/or thermocline, i.e. the magnitude of the change in either measure over a narrow depth range, is an indicator of the degree of stratification in the water column. Strong thermal stratification prevents vertical mixing of nutrients and passively floating plankton through the water column (Hutton and Schnabel

2004). Like other northern temperate lakes, in the summer Lacamas Lake exhibits a nutrient gradient that increases with depth, and oxygen, light, and temperature gradients that decrease with depth (Jobin and Beisner 2014). Reservoirs have physical and hydrological characteristics that are a hybrid of those seen in lakes and rivers (Leon et al 2016). Lakes and reservoirs contain comparable phytoplankton communities, which respond similarly to changes in environmental conditions (Becker et al

2010). This may be impacted, however, by the extreme drawdown that occurs each year in

Lacamas Lake. Water drawdown has been shown to impact stratification patterns, and reservoirs typically have decreased hydraulic residence times when compared to lakes

(Casamitjana et al 2003). Additionally, water drawdown in reservoirs has been linked to increased phosphorus availability due to soil desiccation on the shoreline, and changes in turbidity and light availability due to bottom sediment resuspension (Effler and Matthews

2004). Additionally, water drawdown may impact the community composition of phytoplankton, as disturbance-resistant phytoplankton species replace those that are more sensitive to large ecological changes such as drawdown (Turner et al 2005).

As solar energy input decreases in the fall, Lacamas Lake begins destratifying, which leads to increased vertical mixing potential. This seasonal change is evident in deepening of both the thermocline and oxycline, and decrease in surface temperature that occurs from August to

October in Lacamas Lake. Vertical stratification of the water column, as well as life strategies such as motility and feeding strategy, and predation, influence the location and concentration of phytoplankton (Reynolds 2006). Given the diversity in life strategy among plankton species, phytoplankton community composition varies as the vertical structure of the reservoir changes

(Cantin et al 2011). The ability to exploit resources differs among phytoplankton species, which leads to differential success rates among depths in a reservoir (Jobin and Beisner 2014).

Temporal variation in the vertical distribution of phytoplankton:

The concentration of chlorophyll-a is used as a proxy for phytoplankton biomass

(Reynolds 2006). The total water column concentration of chlorophyll-a decreased during mid- day in October when compared to August, however there was no significant change in mid- night chlorophyll-a concentrations. The October decrease in mid-day phytoplankton biomass may relate to decreased light availability in the fall, as light is a limiting factor in phytoplankton growth (Becker et al I 2010). This aligns with lack of change in chlorophyll-a during the mid- night samplings, as light is not available at that time.

There was a significant vertical redistribution of chlorophyll-a from August to October, as evidenced by deepening of the weighted means depths of nearly all size fractions except the smallest size fraction. The 0.7 – 2.7 µm size fraction did not exhibit deepening, which may be related to the relatively small chlorophyll-a values, and subsequent high variance among replicates and difficulty in statistical analysis. Phytoplankton biomass was concentrated in or above the oxycline and thermocline for all size fractions and sampling dates, except the 0.7 –

2.7 µm. Phytoplankton growth and concentration is related to access to light and nutrients, which is determined, in part, by mixing and density stratification in the water column (Becker et al 2010).

Strong stratification of the water column can lead to higher concentrations of chlorophyll-a in the epilimnion (Becker et al 2010), which may change as seasonal mixing (destratification) impacts light and nutrient availability. Additionally, phytoplankton species vary in life strategy, such as motility, buoyancy, and feeding strategy, and seasonal deepening of the thermocline may impact the ability of individual species to remain buoyant, and allow access to light and nutrients. Cyanobacteria, for example, maintain a position at the surface of the water to maximize light exposure, which is crucial to their success. Thermocline deepening, as seen in

Lacamas Lake in October, compromises the ability of cyanobacteria to remain near the surface due to mixing, thereby impacting their concentration in the water column (Cantin et al 2011). In addition, a strong oxycline creates a hypoxic layer in the deep waters. Deoxygenated water removes viable habitat for zooplankton, which are predators of phytoplankton. The depth of the oxycline also deepened from August to October, likely leading to a change in predator dynamics which thereby influenced phytoplankton distribution (Vanderploeg et al 2009).

The October 2.7 – 35 µm size fraction exhibited a change in vertical distribution from mid- day to mid-night, with the weighted mean depth decreasing mid-night. None of the other size fractions exhibited a significant mid-day to mid-night change in vertical distribution. This diurnal change in weighted mean depth may indicate vertical migration, as motile phytoplankton species remain in the upper layers during mid-day for light resources and migrate to the lower depths to take advantage of nutrient resources mid-night. The diurnal change in weighted mean depth may also indicate a change in phytoplankton community composition due to high turnover, or predation by other organisms (Liu et al 2011).

The August and October mid-night and October mid-day 35 – 250 µm size fractions were concentrated at a greater depth than the 2.7 – 35 µm size fraction. Phytoplankton have differential access in resources due to the diversity in life strategies, and many motile, mixotrophic organisms are found in the 35 – 250 µm size fraction. Mixotrophs are more successful at greater depths due to their decreased dependency on light, because they are able to acquire energy from consuming other organisms as well as from the sun via photosynthesis. Furthermore, residing at a greater depth enables these category of phytoplankton to take advantage of the greater concentration of nutrients found near the thermocline (Cantin et al

2011).

Conclusion:

Lacamas Lake exhibits seasonal dynamics, such as thermal and density stratification, like other temperate lakes in northern latitudes. The lack of oxygen in bottom depths of the lake, temperature gradient, and history of harmful algal blooms indicates the reservoir still exists in a eutrophic state, which persists even after successful efforts to reduce the input of phosphorus from upstream tributaries. The phytoplankton populations exhibited an interesting trend of concentrating deeper in the water column as the season progressed. Given the lack of biological activity existing below the oxycline, it is evident that hypoxia is impacting habitat availability in Lacamas Lake. The extent of this impact, however, requires more research.

List of references:

Anderson, D.M., Glibert, P.M., Burkholder, J.M. (2002). Harmful Algal Blooms and

Eutrophication: Nutrient Sources, Composition, and Consequences. Estuaries, 25(4b), 704-726.

Baldwin, D.S., Gigney, H., Wilson, J.S., Watson, G., Boulding, A.N. (2008). Drivers of water quality in a large water storage reservoir during a period of extreme drawdown. Water

Research, 42: 4711 – 4724. Becker, V., Caputo, L., Ordóñez, J., Marcé, R., Armengol, J., Crossetti, L.O., Huszar, V.L.M.

(2010). Driving factors of the phytoplankton functional groups in a deep Mediterranean reservoir. Water Research, 44: 3345 – 3354.

Becker, V., Cardoso, L., & Huszar, V. (2008). Diel variation of phytoplankton functional groups in a subtropical reservoir in southern Brazil during an autumnal stratification period. Aquat Ecol

Aquatic Ecology, 43: 285-293.

Cantin, A., Beisner, B.E., Gunn, J.M., Prairie, Y.T., Winter, J.G. (2011). Effects of thermocline deepening on lake phytoplankton communities. Canadian Journal of Fisheries and Aquatic

Science, 68: 260 – 276.

Carlson, K., Geiger, N.S., Waltz, T., Grant, M., Luzier, J., Anglin, D., Hough, G. (1985). Lacamas-

Round Lake Diagnostic and Restoration Analysis. Beak Consultants Incorporated and Scientific

Resources Incorporated, Portland, Oregon.

Carpenter, S. R., Stanley, E. H., & Zanden, M. V. (2011). State of the World's Freshwater

Ecosystems: Physical, Chemical, and Biological Changes. The Annual Review of Environment and

Resources, 36: 75-99. Retrieved February 22, 2016.

Casamitjana, X., Serra, T., Colomer, J., Baserba, C., Pérez-Losada, J. (2003). Effects of the water withdrawal in the stratification patterns of a reservoir. Hydrobiologia, 504: 21 – 28.

Conley, D. J., Paerl, H. W., Howarth, R. W., Boesch, D. F., Seitzinger, S. P., Havens, K. E., Lancelot,

C., Likens, G.E. (2009). Controlling Eutrophication: Nitrogen and Phosphorus. Science,

323(5917): 1014-1015. Cooke, G.D. (1980). Lake level drawdown as a macrophyte control technique. Water Resources

Bulletin, 16(2): 317 – 322.

Deemer, B.R., Harrison, J.A., Whitling, E.W. (2011). Microbial dinitrogen and nitrous oxide production in a small eutrophic reservoir: An in situ approach to quantifying hypolimnetic process rates. Limnology and Oceanography, 56(4): 1189 – 1199.

Deemer, B.R., Henderson, S.M., Harrison, J.A. (2015). Chemical mixing in the bottom boundary layer of a eutrophic reservoir: The effects of internal seiching on nitrogen dynamics. Limnology and Oceanography, 00: 1 – 24.

Effler, S.W. and Matthews, D.A. (2004). Sediment resuspension and drawdown in a water supply reservoir. Journal of American Water Resources Association, 40(1): 251 – 264.

Friedrich, J., Janssen, F., Aleynik, D., Bange, H. W., Boltacheva, N., Çağatay, M. N., Dale, A.W.,

Etiope, G., Erdem, Z., Geraga, M., Gilli, A., Gomoiu, M.T., Hall, P.O.J., Hansson, D., He, Y.,

Holtappels, M., Kirif, M.K., Kononets, M., Konovalov, S., Lichtschlag, A., Livingstone, D.M.,

Marinaro, G., Mazlumyan, S., Naeher, S., North, R.P., Papatheodorou, G., Pfannkuche, O., Prien,

R., Rehder, G., Schubert, C.J., Soltwedel, T., Sommer, S., Stahl, H., Stanev, E.V., Teaca, A.,

Tengberg, A., Waldmann, C., Wehrli, B., Wenzhöfer, F. (2014). Investigating hypoxia in aquatic environments: diverse approaches to addressing a complex phenomenon. Biogeosciences, 10(8), 1215-1259.

Hutton, B. and Schnabel, J. (2004). Lacamas Lake: Nutrient Loading and In-lake Conditions. Clark

County Public Works: Water Resources Section. Clark County, Washington. Izaguirre, I., Allende, L., Escaray, R., Bustingorry, J., Pérez, G., & Tell, G. (2012). Comparison of morpho-functional phytoplankton classifications in human-impacted shallow lakes with different stable states. Hydrobiologia, 698: 203-216.

Jobin, V.O., Beisner, B.E. (2014). Deep chlorophyll maxima, spatial overlap and diversity in phytoplankton exposed to experimentally altered thermal stratification. Journal of Plankton

Research, 36(4): 933 – 942.

Klotz, R.L., Linn, S.A. (2001). Influence of Factors Associated with Water Level Drawdown on

Phosphorus Release from Sediments. Lake and Reservoir Management, 17(1): 48 – 54. DOI:

10.1080/07438140109353972.

Kruk, C., Mazzeo, N., Lacerto, G., Reynolds, C.S. (2002). Classification schemes for phytoplankton: a local validation of a functional approach to the analysis of species temporal replacement. Journal of Plankton Research, 24(9): 901 – 912.

Kruk, C., Segura, A.M. (2012). The habitat template of phytoplankton morphology-based functional groups. Hydrobiologia, 698: 191 – 202.

Lehman, J.T. (2014). Understanding the role of induced mixing for management of nuisance algal blooms in an urbanized reservoir. Lake and Reservoir Management, 30(1): 63 – 71. DOI:

10.1080/10402381.2013.872739

León, J.G., Beamud, S.G., Temporetti, P.F., Atencio, A.G., Diaz, M.M., Pedrozo, F.L. (2016).

Stratification and residence time as factors controlling the seasonal variation and vertical distribution of chlorophyll-a in a subtropical irrigation reservoir. International Review of

Hydrobiology, 101: 36 – 47.

Liu, H., Song, X., Huang, L., Zhong, Y., Shen, P., & Qin, G. (2011). Diurnal variation of phytoplankton community in a high frequency area of HABs: Daya Bay, China. Chin. J. Ocean.

Limnol. Chinese Journal of Oceanology and Limnology, 29(4), 800-806.

Mellard, J.P., Yoshiyama, K., Litchman, E., Klausmeier, C.A. (2011). The vertical distribution of phytoplankton in stratified water columns. Journal of Theoretical Biology, 269: 16 – 30.

Nürnberg, G.K., Molot, L.A., O’Connor, E., Jarjanazi, H., Winter, J., Young, J. (2013). Evidence for internal phosphorus loading, hypoxia, and effects on phytoplankton in partially polymictic Lake

Simcoe, Ontario. Journal of Great Lakes Research, 39: 259 – 270.

Paerl, H.W., Valdes-Weaver, L.M., Joyner, A.R., Winkelmann, V. (2006). Phytoplankton indicators of ecological change in the eutrophying Pamlico sound system, North Carolina.

Ecological Applications, 17: 88 – 101.

Reynolds, C. (2006). Ecology of phytoplankton. Cambridge, Cambridge: Cambridge University

Press.

Rollwagen-Bollens, G., Bollens, S., & Penry, D. (2006). Vertical distribution of micro- and nanoplankton in the San Francisco Estuary in relation to hydrography and predators. Aquatic

Microbial Ecology, 44, 143-163.

Sinistro, R.S., Sánchez, M.L., Unrein, F., Schiaffino, M.R., Izaguirre, I., Allende, L. (2015).

Responses of phytoplankton and related microbial communities to changes in the limnological conditions of shallow lakes: a short-term cross-transplant experiment. Hydrobiologia, 752: 139

– 153.

Smith, V.H., Tilman, G.D., Nekola, J.C. (1999). Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environmental Pollution, 100: 179 – 196.

Strickland, J.D.H., Parsons, T.R. (1972). A Practical Handbook of Seawater Analysis. Fisheries

Research Board of Canada, 167.

Tornés, E., Pérez, M.C., Durán, C., Sabater, S. (2014). Reservoirs override seasonal variability of phytoplankton communities in a regulated Mediterranean river. Science of the Total

Environment, 475: 225 – 233.

Turner, M.A., Huebert, D.B., Findlay, D.L., Hendzel, L.L., Jansen, W.A., Bodaly, R.A., Armstrong,

L.M., Kasian, S.E.M. (2005). Divergent impacts of experimental lake-level drawdown on planktonic and benthic plant communities in a boreal forest lake. Canadian Journal of Fisheries and Aquatic Science, 62: 991 – 1003.

Vanderploeg, H.A., Ludsin, S.A., Ruberg, S.A., Höök, T.O., Pothoven, S.A., Brandt, S.B., Lang,

G.A., Liebig, J.R., Cavaletto, J.F. (2009). Hypoxia affects spatial distributions and overlap of pelagic fish, zooplankton, and phytoplankton in Lake Erie. Journal of Experimental Marine

Biology and Ecology, (381): S92 – S107.

Zhang, Y., Wu, Z., Liu, M., He, J., Shi, K., Zhou, Y., Wang, M., Liu, X. (2015). Dissolved oxygen stratification and response to thermal structure and long-term climate change in a large and deep subtropical reservoir (Lake Qiandaohu, China). Water Research, 75: 249 – 258.