2015 Baseline Algae Monitoring Report

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1 2015 Baseline Algae Monitoring Report March 21, 2016 Amanda Pratt Colin Holme Lakes Environmental Association 230 Main Street Bridgton, ME

2 Summary Recognizing the importance of understanding algae population dynamics in lakes, LEA began monitoring epilimnetic algae in We hoped to take monthly samples from June to September, however equipment took longer than expected to acquire, meaning that samples were not able to be collected until July. The first year was in many ways a trial run, but nevertheless did result in some good data. Algae samples were collected from surface waters on ten different lakes, filtered, then counted under magnification. The genus of each algae and the number of cells present were recorded. Multiple samples were taken from a number of lakes, allowing for comparison of algae populations over time. Studying these seasonal changes in the makeup of algae populations is important to understanding lake ecology. This study focused on planktonic algae, which are those that are free-floating in the water, rather than attached to rocks or other material. Summaries of individual lakes results are available in LEA s 2015 Water Testing Report or on the online lake information pages, both available on our website, Collecting a core sample from the upper portion of a lake using a Tygon core tube. The water collected will be filtered and counted for algae. 2

3 Introduction and Background Algae are a key metric in the assessment of water quality. They are the foundation of lake food webs, meaning that they are the food source that directly or indirectly supports much of the animal life existing in a lake. Of course, algae are also the source of algal blooms, which result from an over-abundance of nutrients or a lack of algae-eating organisms. Either way, algal blooms are often a sign of a water quality problem, a situation that is bad for people and for the lakes themselves. The goal of LEA s algae testing program is to identify the various kinds of algae present in the lakes of the Lakes Region of western Maine, quantify them, and study how they change over time. Algae populations change in a predictable way over the course of a year, and understanding which algae are present at certain times can tell us about lake conditions. For example, diatoms are common in the early spring because they prefer colder water and well mixed lake conditions. Large diatoms tend to settle out in the summer when waters are calmer. There are 6 main groups of algae found in our lakes: green algae, cyanobacteria, dinoflagellates, cryptomonads, golden algae, and diatoms. Green algae are a very diverse group; their common characteristic is their dominant pigments, chlorophyll-a and chlorophyll-b, which give them a deep green color. Cyanobacteria are the most liable to form blooms and are also known for producing toxins. They are more closely related to bacteria than to other algae, and are also known as blue-green algae. Dinoflagellates are a group made up of large, motile algae. This group includes only a few species. Cryptomonads are one-celled algae with two flagella which allow them to move through water. None were identified during sampling although they are likely present in the lakes studied. The Golden algae category contains relatively few species, though they are often common in low nutrient lakes such as the ones in this study. Golden algae are a group distinguished by their brown or yellow color. Finally, diatoms are readily identified by their hard, silica-based outer shells which make them unique from other types of algae. They are most common in the spring and fall when lakes mix. LEA is particularly interested in learning more about the relative quantity of cyanobacteria in each lake, and how this number changes over time. This is because cyanobacteria concentrations can tell us the most about the water quality status of a lake. High levels of cyanobacteria are often correlated with high phosphorus levels, and cyanobacteria such as Aphanizomenon, Anabaena, and Microcystis are the most common cause of algal blooms. Cyanobacteria tend to be most common in the later part of the summer, when temperatures are warmest. While cyanobacteria do exist naturally in all lakes and their presence is generally not a problem, changes in the amount of cyanobacteria over the course of a year can be a water quality indicator. 3

4 Methods Algae samples were collected from ten lakes one or more times between July 17th and September 15, 2015 (Table 1). The samples were taken from epilimnetic core samples, meaning they contained a composite of water from the top layer (ranging from 3-10 meters deep) of the water column. The depth of the core was determined by temperature and dissolved oxygen profiles. A total of 36 samples were collected. Samples were not preserved, but stored in the refrigerator for a maximum of three days before analysis. Samples were filtered through sand and a concentrated 1-mL subsample was mounted on a gridded Sedgwick-Rafter slide. Ten squares on the grid were counted at 200x magnification. The number of algal cells and the genus (the taxonomic rank above species level, plural genera) of algae they belonged to were recorded. Finally, the number of cells per milliliter (cells/ml) was calculated for each sample. Table 1. Lakes sampled for algae and the number of samples collected from each. Lake Name Number of Samples Hancock Pond 4 Highland Lake 1 Keoka Lake 4 Long Lake 1 from each basin for a total of 3 McWain Pond 4 Moose Pond 4 from the Main Basin and 4 from the South Basin Peabody Pond 2 Sand Pond 4 Trickey Pond 2 Woods Pond 4 4

5 Results A total of 49 different algae genera were identified across the 10 lakes sampled. Of these, there were 21 green algae genera, 16 cyanobacteria (blue-green algae), 9 diatoms, 5 golden algae, and 2 dinoflagellates. The average sample contained 22 unique genera. Overall, Green algae were most common type of algae seen in the samples, followed by cyanobacteria, diatoms, golden algae, dinoflagellates, and cryptomonads. Among the most common genera identified were Westella (green algae), Tabellaria (diatom), Dinobryon (golden/yellow algae), Asterionella (diatom) and Merismopedia (cyanobacteria) (Table 2). The ponds with the highest average percentage of cyanobacteria were Woods Pond and Moose Pond (Table 3). Trickey Pond was the only lake in which green algae did not make up the majority of algae counted on average. Instead, diatoms made up 44% of samples on average and green algae accounted for 39%. Sand Pond and Trickey Pond had relatively high average levels of golden algae compared to the other lakes, mainly due to high Dinobryon counts. The total number of algae cells counted in a particular lake fluctuated over time, though there was no clear pattern in algae abundance across all lakes. The relative amount of algae in each of the six categories also varied over time in each lake (Figure 1). The average number of cells/ml in a sample was 155 cells/ml with a range of cells/ml (Table 2). McWain Pond and Highland Lake had the highest average levels of algae and Woods Pond, Hancock Pond, and Trickey Pond had the lowest levels. Figure 1. Graph showing changes in the relative amounts of different types of algae in Hancock Pond between July and September of

6 Results (continued) Table 2. Number of cells/ml counted in an average sample and most commonly counted algae genera in the samples collected from each lake. Common genera are listed in chronological order of sample collection (first genus listed was the most common in the first sample taken, etc.) (G = Green algae, C = Cyanobacteria, D = Diatom, GO = Golden algae) *Long Lake statistics are an average of 1 sample from each of the three basins (North, Middle, and South). Lake Average cells/ml Most Commonly Counted Genera Hancock Pond 108 Westella G, Tetraspora G, Tabellaria D, Tabellaria D Highland Lake 234 Westella G Keoka Lake 215 Westella G, Westella G, Westella G, Dinobryon GO Long Lake* 160 Asterionella D, Dinobryon GO, Rhabdoderma G McWain Pond 225 Tabellaria D, Tabellaria D, Tabellaria D, Tabellaria D Moose Pond (North) 149 Westella G, Asterionella D, Merismopedia C, Merismopedia C Moose Pond (Main) 151 Westella G, Merismopedia C, Merismopedia C, Aphanocapsa C Peabody Pond 141 Westella G, Merismopedia C Sand Pond 156 Tabellaria D, Tabellaria D, Dinobryon GO, Dinobryon GO Trickey Pond 118 Asterionella D, Westella G Woods Pond 89 Westella G, Merismopedia C, Eucapsis C, Tabellaria D Table 3. Average percentage of each type of algae in each lake, as well as on average across all lakes. *Long Lake statistics are an average of 1 sample from each of the three basins Green Algae Cyanobacteria Diatoms Golden Algae Dinoflagellates Cryptomonads AVERAGE 62% 16% 14% 7% 1% 0% Hancock Pond 58% 10% 25% 3% 4% 0% Highland Lake 77% 16% 6% 1% 0% 0% Keoka Lake 82% 10% 4% 4% 0% 0% Long Lake* 61% 16% 19% 4% 0% 0% McWain Pond 57% 17% 18% 8% 0% 0% Moose Pond (North) 69% 21% 7% 3% 0% 0% Moose Pond (Main) 51% 40% 4% 5% 0% 0% Peabody Pond 68% 18% 7% 7% 0% 0% Sand Pond 59% 7% 13% 19% 2% 0% Trickey Pond 39% 1% 44% 16% 0% 0% Woods Pond 55% 32% 10% 3% 0% 0% 6

7 Discussion The results of algae sampling in 2015 give LEA a baseline of algae conditions in 10 lakes over the months of July, August, and September. This baseline sampling is important because it provides a record of conditions to which future data can be compared. This data will help in assessing changes over time and determining what a normal algae population looks like in each lake. Because these lakes currently have good water quality, knowing which algae are present, and in what concentrations, is especially important. Any water quality changes in the future will he easier to assess if current water quality conditions are understood. One of the main findings was that green algae were the most counted type of algae. Green algae are certainly a diverse category, with about 2,400 freshwater species. Although they are often counted, green algae do not generally contribute much to the biomass of algae present in a lake. This highlights an important point the number of cells/ml counted does not correlate to the amount of algal biomass (or chlorophyll concentration) in a lake. This is because a large, relatively heavy single algae cell is counted as one cell, whereas a tiny colony of algae may have all of its individual cells counted. The biomass (and chlorophyll levels) of the tiny colony may well be lower than the one large algal cell, but the colony would contribute much more to the calculated number of cells/ml. The unit of cells/ml does not measure cell size or chlorophyll level. Therefore, we can t directly compare the results from this study to chlorophyll-a concentrations measured in the lakes tested. Similarly, Table 2 shows that a number of the most common algae genera were not green algae, despite the fact that green algae were the most counted group. This can also be explained by the diversity of the green algae. High green algae counts were often due to the combined total of multiple genera, whereas other groups contributed less to the overall amount of algae but were made up of only one or two genera. For example, in a sample with 100 green algae and 20 diatoms, green algae are the most common group. However, if you look at the genera that make up that sample, there may be 10 different types of green algae (10 of each) but there is only one type of diatom, of which there are 20 making the most common genus of algae a diatom. Reported cell counts in low-nutrient lakes generally range from 0 to 1,000 cells/ml, although there are no established guidelines that define lake status based on cell counts. Lakes within this range are considered oligotrophic to oligo-mesotrophic. Average cell counts in this study were low at an average of 155 cells/ml. While the lakes studied are low in nutrients, the counts are probably underestimates based on reports from similar lakes. This likely has to do with zooplankton grazing during holding times, and is in part due to the variability inherent in the process of manually counting algae, which is affected by equipment and experience level. 7

8 Discussion (continued) The following are descriptions of ideal water conditions for the five most common genera found in the lakes tested. The dominance of these algae can be used to infer what lake water quality conditions were like when the samples were taken. However, it should be noted that the environmental preferences of individual species within these genera may differ. Information presented are based on findings from Morabito and Curradi (1997) and Taylor et al. (1979). Asterionella is a diatom which is found throughout the spring, summer, and fall in low-nutrient lakes. It prefers cooler temperatures, high oxygen levels, and high water clarity, and will be most common in lakes with those characteristics. Dinobryon is a golden algae that is most common in the spr ing and fall, often after diatom population peaks. This genus is found in abundance in similar conditions as Asterionella: cooler, low-productivity lakes with high clarity and oxygen levels. They are also associated with high N:P ratios. Merismopedia is a type of cyanobacteria (blue-green algae). Its individual cells are very small and form colonies, so although it is common in cell counts, it has relatively low biomass. This genus is most common in summer and fall. It is tolerant of low oxygen and low clarity conditions and higher nutrient levels. It grows well in warm water and is associated with low N:P ratios and higher lake productivity. Tabellaria is a diatom that is found throughout the spring, summer, and fall. It is common in low nutrient, clear waters with high secchi readings. It often dominates in moderately acidic lakes with low alkalinity that also have low phosphorus and chlorophyll levels. Westella is a type of green algae that is associated with moderate nutrient levels and is tolerant of pollution and low ph levels. It can be found in the spring, summer and fall, however it tends to dominate when lakes are unstratified or in stratified lakes with large mixing zones. 8

9 Discussion (continued) Many of the most common algae present when the lakes were sampled in 2015 are indicative of good water quality. In addition, cyanobacteria levels were low in most of the lakes. While it is difficult to draw conclusions based on only a couple of months of sampling, the dominant algae and the percentage of cyanobacteria can be useful in making generalizations about lake condition. Moose Pond s main basin and Woods Pond had the highest average cyanobacteria levels. They were also two of the four basins (along with Moose Pond s north basin and Peabody Pond) where Merismopedia was the dominant genus in at least one sample. These facts in and of themselves do not mean that these lakes are in trouble, but it means they are of particular concern for further testing. Merismopedia is a very small colonial algae, so the counts are often high even though there is relatively little of it present in terms of biomass. These high counts then correlate to high percentages of cyanobacteria. The role that Merismopedia (and the other algae identified) plays in the algae communities in these lakes will become more clear once we have multiple years worth of algae data to compare with Sampling LEA will continue sampling algae monthly between May and September of Beginning the sampling earlier in the season will help us better understand shifts in algae populations over time. We will also be able to compare samples from July, August, and September to the samples taken in 2015 to gain insight into how populations may change from year to year. We are also looking to increase and improve our algae identification capabilities. We are hoping to get a microscope camera, which we will use to photograph unknown algae. This allows us the flexibility to identify algae at a later date. The pictures can also be used to make an algae identification guide unique to our lakes. References Morabito, G., & Curradi, M Phytoplankton community structure of a deep subalpine Italian lake (Lake Orta, N. Italy) four years after the recovery from acidification by liming. Internationale Revue der gesamten Hydrobiologie und Hydrographie, 82(4), Taylor, W. D., Hern, S. C., Williams, L.R., Lambou, V. H., Morris, M. K., and Morris, F. A Phytoplankton Water Quality Relationships in U.S. Lakes. United States Environmental Protection Agency. 9

10 Acknowledgements We gratefully acknowledge the help and support of the Portland Water District, who showed us their filtering and counting methods and provided much assistance and advice with materials and equipment. Thank you to the following sponsors who helped to fund this project: An Anonymous Foundation Hancock and Sand Ponds Association Keoka Lake Association McWain Pond Association Moose Pond Association Peabody Pond Assocation Residents of Woods Pond Trickey Pond Association Lastly, thank you to all LEA members: You made this project and all of LEA s work possible. 10

11 Lakes Environmental Association 230 Main Street Bridgton, ME

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