Comparative responses of phytoplankton during chemical recovery in atmospherically and experimentally acidified lakes 1

COMPARATIVE RESPONSES OF PHYTOPLANKTON DURING CHEMICAL RECOVERYIN ATMOSPHERICALLY AND EXPERIMENTALLY ACIDIFIED LAKES1

Mark D. Graham2, Rolf D. Vinebrooke

Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada T6 G 2E9

Bill Keller, Jocelyne Heneberry

Ontario Ministry of the Environment, Cooperative Freshwater Ecology Unit, Laurentian University,

Sudbury, Ontario, Canada P3E 2C6

Kenneth H. Nicholls

S-15 Concession 1, RR#1, Sunderland, Ontario, Canada L0C 1H0

and David L. Findlay

Department of Fisheries and Oceans Canada, Freshwater Institute, 501 University Crescent, Winnipeg, Manitoba, Canada R3T 2 N6

Twenty lakes recovering from a century of atmo-spheric acid deposition over Northeastern Ontariowere resurveyed for phytoplankton following a20-year period and were compared with a 23-yearstudy of an experimentally acidified lake, L302S(Experimental Lakes Area, ON, Canada). Phyto-plankton species significantly tracked abioticchanges during both acidification and chemicalrecovery in all lakes based on concordance testing.However, ordination analyses showed that many phy-toplankton communities had not returned to theirpreacidification state. Significant explanatory vari-ables of taxonomic responses were pH, dissolvedorganic carbon (DOC), and inorganic nutrients(N, P), based on canonical correspondence analysis(CCA). Increases in DOC and pH influenced a sig-nificant taxonomic shift from acid-tolerant dinofla-gellates to a diverse assemblage of cyanobacteria,chlorophytes, and diatoms. Declining nitrogen levelsdefined a secondary environmental gradient, whichwas characterized by a decrease in filamentousgreen algal abundance. L302S remained remote inordination space from the more chronically andheavily polluted lakes in Northeastern Ontario, indi-cating that experimental acidification provided aconservative estimate of the true damage to atmo-spherically polluted lakes. However, L302S didincreasingly resemble lakes in Northeastern Ontario,suggesting that experimental acidification simulatedthe impacts of moderate levels of atmospheric pol-lution. Our findings demonstrate the importance ofecological history in understanding the responses byboreal lake ecosystems to environmental change.

Key index words: algal bioindicators; anthropo-genic acidification; boreal lakes; ecosystem recov-ery; phytoplankton

Abbreviations: Al, aluminum; Ca, calcium; CA,correspondence analysis; CCA, canonical corre-spondence analysis; Cu, copper; DOC, dissolvedorganic carbon; ELA, Experimental Lakes Area;Mg, magnesium; P, phosphorus; SRSi, solublereactive silica; TDN, total dissolved nitrogen;TDP, total dissolved phosphorus

Boreal lakes of the Canadian Precambrian Shieldhave experienced substantial environmental changeover the past century owing to anthropogenic aciddeposition (Schindler 1998, Jeffries et al. 2003a,b,Keller et al. 2003). However, reductions in industrialemissions of acidic sulfur oxides have resulted inimproved water quality (Dixit et al. 1992, Kelleret al. 1999a,b, Stoddard et al. 1999). As a result,some acidified lakes have also shown biologicalrecovery (Gunn and Keller 1990, Arnott et al. 2001,Keller et al. 2002, Findlay 2003, Holt and Yan 2003,Yan et al. 2004). However, many lakes remain tooacidic (i.e., pH < 6.0) to support many sensitive spe-cies of biota (Keller et al. 2003). Many lakes haveshown limited recovery, while some remain highlysensitive to drought-induced reacidification events(Keller et al. 1992, 2003, Yan et al. 1996, Arnottet al. 2001). The depletion of base cations in water-sheds of eastern North America has resulted inmany lakes having lost over 40% of their originalalkalinity (Schindler 1987). Further, concentrationsof metals (i.e., Al, Mn, Zn) associated with bothleaching of soils and particulate metal deposition(e.g., Cu, Ni) have stressed a majority of these acidi-fied lakes. These facts might explain why biologicalrecovery in acidified boreal lakes has been limited

1Received 3 June 2006. Accepted 7 May 2007.2Author for correspondence: e-mail [email protected].

J. Phycol. 43, 908–923 (2007)� 2007 Phycological Society of AmericaDOI: 10.1111/j.1529-8817.2007.00398.x

908

to a few cases in Northeastern Ontario (Jeffrieset al. 2003a).

Algal communities are considered to be amongthe earliest indicators of environmental change inlakes (Schindler 1987). For example, lake surveysand paleolimnological studies show that phytoplank-ton are highly responsive to environmental changesin acidified lakes (Dixit et al. 1992, Nicholls et al.1992, Vinebrooke et al. 2002). In general, anthropo-genic acidification results in decreased speciesrichness, taxonomic shifts toward deepwater phyto-flagellates and benthic filamentous green algae, andincreased total biomass (Schindler et al. 1991,Nicholls et al. 1992, Findlay et al. 1999, Vinebrookeet al. 2002).

However, phytoplankton have shown inconsistentresponses to recent environmental changes in bor-eal lakes. Some evidence suggests that phytoplank-ton assemblages show unexpected lag responses(>7 years) to chemical improvements in acidifiedlakes (Arnott et al. 2001, Vinebrooke et al. 2002).Similarly, paleolimnological investigations suggestthat the present-day diatom and chrysophyte assem-blages are significantly different from the preindus-trial period (Dixit et al. 2002). In other cases,phytoplankton assemblages shifted toward thosemore typical of circumneutral lakes within a fewyears of chemical recovery (Findlay 2003).

Phytoplankton responses in experimentally acidi-fied lakes in Northwestern Ontario are consideredto be predictive of other lakes that are being acidi-fied by atmospheric deposition (Schindler et al.1991). However, there has been no study examiningwhether phytoplankton recovery responses to chemi-cal recovery in experimentally acidified lakes cap-tures those occurring in acidified lakes. As a result,there is considerable interest in a comparison of therecovery of experimentally acidified lakes with recov-ering lakes in Northeastern Ontario, where sulfuroxide emissions have been decreased by 90% in thepast 35 years (Jeffries et al. 2003a,b).

In this study, we report on long-term taxonomicchanges in phytoplankton in atmospherically andexperimentally acidified boreal lakes. Many of theseregions have been well studied in the context ofphytoplankton responses to lake acidification(Schindler et al. 1991, Findlay and Kasian 1996,Findlay et al. 1999). However, in this study, we wereinterested in the regional specificity in phytoplank-ton responses to the chemical variables related toacidification as observed over much longer timeperiods of recovery than previously observed byNicholls et al. (1992). The objectives of our studywere as follows: (i) to determine if the phytoplank-ton communities in lakes that have experiencedlarge-scale regional chemical acidification stressorshave recovered over a 20-year period; (ii) to com-pare the phytoplankton responses in 20 Northeast-ern Ontario lakes with lakes that wereexperimentally acidified; and (iii) to determine

which of the measured environmental variablesexplained phytoplankton species variance withinand between the experimentally versus the atmo-spherically acidified lakes. We hypothesized thatboreal lakes across Ontario would show uniqueregional responses to acidification because of differ-ences in their ecological histories (Fischer et al.2001).

MATERIALS AND METHODS

Study lakes. Northeastern Ontario lakes: The response ofphytoplankton in these recovering boreal forest lakes wasquantified using the same protocol used in an earlier surveyconducted by Nicholls et al. (1992). The original survey,conducted in July of 1981, consisted of 111 lakes. We refinedour choice of lakes by only sampling those that displayedimprovements in water quality. Increases in pH, decreases insulfate, and increases in DOC defined the improvements inwater quality (see Table 1). As a result, 20 lakes located inNortheastern Ontario were sampled during the month of Julyin 1981 and 2002. These lakes had not been sampled forphytoplankton in the past 20 years. Therefore, this study wasthe first to provide information on the recovery responses ofphytoplankton over the last two decades. A majority of theselakes are within a 100 km radius of the city of Sudbury.However, most lakes were remote and required the use offloatplanes to complete the necessary sampling. This area liesnear the southern edge of the Precambrian Canadian Shield,just north of Lake Huron (Fig. 1). The bedrock consists ofgranite and orthoquartzite. The watershed contains vegetationconsisting of coniferous or mixed conifer-deciduous forest(Pearson and Pitblado 1995). The Sudbury smelters and otherNorth American sulfur emission sources caused substantialanthropogenic acidification and metal pollution during the20th century. For example, the Sudbury smelters emitted over2.5 million tonnes of sulfate into the atmosphere each yearduring the 1960s (Snucins et al. 2001). More recently,improvements in water quality have resulted from reducedindustrial emissions of sulfate. In fact, total North Americanemissions are now �40% less than in 1980 (Jeffries et al.2003b).

Several lakes in the survey were located southwest of Sudburyin Killarney Provincial Park (480 km2; Fig. 1). This wildernessarea is located �60 km southwest of Sudbury, ON (46�3¢ N,81�21¢ W), and has been impacted by industrial sources ofsulfur oxides (i.e., >2000 kg Æ m2 Æ year)1). Orthoquartziteridges of the La Cloche Mountains surround many of theseacid or acid-sensitive lakes, while the less acidified lakes arelocated on sandstone and limestone and are influenced bywetlands (Vinebrooke et al. 2002, 2003a, Keller et al. 2003).The selection of the Northeastern Ontario lakes was not biasedto include only those that showed the largest changes inchemistry similar to Lake 302S (L302S), an experimentallyacidified lake. First, the chemical histories of L302S versus theNortheastern Ontario lakes are quite distinct. The lakes ofNortheastern Ontario have experienced a century of anthro-pogenic pollution (acid rain, metal particulates, and metalsleaching from the watershed), while the area around L302S hasexperienced low rates of acid deposition and only 10 years ofwithin-lake acidification.

Swan Lake was chosen for this study due to its proximity tothe Sudbury smelters and the availability of 20 years ofphytoplankton and chemical data (1982–2001). Chemical andbiological recovery has been evident since the 1990s (Kelleret al. 1992, Yan et al. 1996, Arnott et al. 2001). Swan Lake is asmall lake (0.058 km2; 8.8 m maximum depth; Fig. 1). At�13 km from the smelting complexes in Sudbury, ON, Canada

PHYTOPLANKTON IN STRESSED BOREAL LAKES 909

(46�22¢ N, 81�04¢ W), this lake was the closest to the pollutionsource of our study lakes. Site descriptions of this lake can befound elsewhere (Yan et al. 1996, Arnott et al. 2001, 2003).Paleolimnological reconstructions indicate Swan Lake acidified50 years ago, with a pH of 4.0 in the late 1970s (Yan et al.1996).

Experimental Lakes Area (ELA)—Lake 239 (L239) and L302S:L302S is a small (0.109 km2, surface area) boreal headwaterlake located on the western edge of the Canadian PrecambrianShield, within the ELA (49�40¢ N, 93�45¢ W; Schindler et al.1991, Findlay 2003, Vinebrooke et al. 2003b; Fig. 1). Theunlogged catchment consists of jackpine (Pinus banksiana), redpine (Pinus resinosa), and black spruce (Picea mariana). Thedecade-long history of the experimental acidification of thisboreal forest lake has been described in detail elsewhere(Schindler et al. 1991, Turner et al. 1995a,b). Briefly, afterseveral years of premanipulation monitoring, L302S wasacidified using sulfuric acid from pH 6.8 in 1982 to 4.5 in1991 and allowed to recover from 1992 to present day(Schindler et al. 1997). L239 is an oligotrophic headwater lakeat ELA, in a region of low acid deposition. It was used as areference lake for this study. L239 has been used in severalstudies as a reference system due to its similarity with the lakesin the region of ELA. It has already been shown thatphytoplankton communities of L239 are comparable withseveral of the reference lakes at the ELA (Findlay et al. 2001;S. E. M. Kasian, D. L. Findlay, G. Regehr, K. G. Beaty, D. R.Cruikshank, and J. A. Shearer, unpublished data). As a result,we consider L239 to be representative of the lakes within theELA region and appropriate for comparison with the otheroligotrophic lakes in different regions, such as those found inNortheastern Ontario.

Water sampling and analyses. Northeastern Ontario lakes: Sincethe original survey was performed in July, we also conducted allof the collections during July in 2002 to make for moremeaningful comparisons. All samples were obtained withsupport from the Cooperative Freshwater Ecology Unit, basedin Sudbury, ON, Canada. A nonvolume weighted, epilimnionand metalimnion sample was collected from each of the 20survey lakes. Samples were collected for routine chemistry (i.e.,

pH, conductivity) and for analysis of sulfate (SO4)2), chloride

(Cl), sodium (Na), potassium (K), magnesium (Mg), calcium(Ca), soluble reactive silica (SRSi), dissolved organic carbon(DOC), total nitrogen (N), total phosphorus (P), and severalmetal elemental analyses (i.e., total aluminum [Al], totalcopper [Cu], total iron [Fe], total nickel [Ni], total zinc[Zn]). Water chemical analyses for Swan Lake were based on avolume-weighted depth integrated water sample 1982–2002.Standard Ontario Ministry of the Environment analyticaltechniques for determining water chemistry were performedon each of the samples and are outlined in Keller et al. (2004).

ELA (L302S, L239): Methods for collection of water forchemical analysis at the ELA (L302S, L239) are described inFindlay and Kling (1998). Samples for water chemistry wereobtained bimonthly throughout the ice-free season using anintegrated sampler from the deepest station of L239 andL302S. Water samples were collected from L239 and L302S,and chemical analyses were performed using methods fromthe Freshwater Institute (2006; http://www.umanitoba.ca/institutes/fisheries/Chemistry.html, last accessed on August7, 2007). The same chemical variables that were measured inthe Northeastern Ontario lakes survey were also determined inthe ELA lakes. Although water chemistry was determined bydifferent research groups, all analyses were performed basedon the standardized procedures originally derived from Amer-ican Public Health Association (APHA 1998).

Phytoplankton sampling and enumerations. Northeastern Ontariolakes: Phytoplankton samples were collected during the monthof July from the Northeastern Ontario lakes. Samples werecollected throughout the euphotic zone defined as twice thesecchi transparency plus 1 m. All samples were fixed withLugol’s solution. Aliquots (25 mL) from each of the sampleswere settled and enumerated using the Utermohl technique(Utermohl 1958), using phase-contrast illumination on a LeicaDM IRB inverted microscope at ·10 to ·1000 magnification.Enumerations were performed to the same level of resolutionas achieved in 1981. A minimum of 300–500 cells were countedin each of the samples. Biomass was calculated by measuringcell dimensions using OpenlabTM 4.0.1 (Improvision� Inc.,Lexington, MA, USA). Cell shape was approximated using up

Table 1. Overall changes in sulfate, dissolved organic carbon (DOC), and pH in 20 Northeastern Ontario lakes from 1981to 2002.

Lake Area of lake (km2) Sulfate, mg Æ L)1 (%) DOC (mg Æ L)1) pH

Annie 2.03 )5.9 (–; 45) +1.7 5.3–6.3 (+)Bell 2.81 )5.8 (–; 45) +0.6 5.4–6.3 (+)Bluesucker 1.45 )3.8 (–; 35) +0.6 5.1–5.3 (+)David 3.95 )3.5 (–; 37) +0.3 4.7–5.1 (+)Frederick 1.74 )5.7 (–; 39) +0.4 4.6–5.1 (+)George 3.95 )4.2 (–; 37) +0.4 5.4–6.1 (+)Helen 0.68 )5.0 (–; 45) +0.3 6.6–7.2 (+)Johnnie 3.95 )3.7 (–; 34) +1.4 5.1–5.9 (+)Killarney 3.57 )4.2 (–; 37) +0.2 4.9–5.1 (+)Klock 1.46 )3.8 (–; 39) +1.2 4.9–5.7 (+)Laundrie 3.64 )3.4 (–; 32) )0.6 5.2–5.5 (+)Nellie 9.49 )4.6 (–; 45) 0.0 4.5–4.7 (+)O.S.A. 2.92 )4.6 (–; 36) )0.1 4.7–4.9 (+)SansChambre 0.15 )7.5 (–; 60) +1.1 5.4–6.4 (+)Seagram 0.81 )4.2 (–; 36) 0.0 5.1–5.5 (+)Sunnywater 1.42 )2.0 (–; 19) )1.0 4.6–4.8 (+)Tyson 11.43 )6.0 (–; 44) +0.9 5.3–6.2 (+)Wabun 0.55 )4.1 (–; 41) 0.0 4.8–5.1 (+)Wavy 2.55 )4.7 (–; 38) +1.0 4.7–5.0 (+)Whitepine 0.78 )2.5 (–; 26) +0.7 4.8–5.2 (+)

Direction of change is indicated by either + or – before each of the values. Significant (P < 0.05) trend tests on all annual pHand sulfate values are indicated by + (increase) and – (decrease) after each unit in parentheses. Proportional decreases (%) insulfate since 1981 are also shown.

910 MARK D. GRAHAM ET AL.

to 50 individual cells and applying the geometric formula thatbest described the shape of the cell (Rott 1981, Hillebrandet al. 1999). Biovolumes were then converted to biomass byassuming a specific gravity of 1. Taxa were identified to specieswhen possible using Prescott (1982) and Findlay and Kling(1979).

Taxonomic procedures were performed exactly as in 1981(Nicholls et al. 1992). However, different taxonomists enu-merated the samples from 1981 and 2003. Lynda Nakamoto(Ministry of the Environment, ON, Canada) and Ken Nicholls(coauthor of this study) enumerated samples from 1981,while Mark Graham (lead author of this study) enumeratedsamples from 2003. In addition, the lead author analyzedarchived samples from 1981 to verify taxonomic identifica-tions. This procedure confirmed that different taxonomistscould produce similar results. Furthermore, every attempt wasmade to maintain quality control between taxonomists,including training sessions. We also enumerated severalarchived phytoplankton samples from various lakes during1980–1985 to determine whether different taxonomists couldproduce similar results. To compare the two results, we usedthe coefficient of community similarity index. Communitysimilarity was determined from species-level log-transformedbiomass data. These results indicated a high level of agree-ment among the various taxonomists in terms of theiridentification of preserved algal samples from various North-eastern Ontario lakes (David [1981: 86.2%]; SansChambre

[1981: 93.5%]; Wavy [1985: 92%]). Further, since all the samespecies were identified by both taxonomists, this difference inpercentage accuracy is likely attributable to subsamplingvariability.

ELA (L239, L302S): L239 and L302S phytoplankton werecollected every 2 weeks through the ice-free season from 1980to 2003. Samples were taken to a depth of 1% surface light, atthe deepest station of the lake, using an integrating sampler.Details of enumeration protocols for the ELA study lakes canbe found in Findlay and Kling (1998). Briefly, 10 mL aliquotsfrom each of the samples were settled. The same taxonomistanalyzed all samples. Samples were analyzed under phase-contrast illumination on a Zeiss IM35 inverted microscope(Carl Zeiss, Thornwood, NY, USA) at ·150 magnification. Also,phytoplankton biovolumes were measured using an ocularmicrometer (Leica Mikroskopie & Systeme GmbH Wetzlar,Germany).

Data analyses. Regional analysis of phytoplankton across atmo-spherically and experimentally acidified lakes: The phytoplanktonsurvey of the Northeastern Ontario lakes was conducted in July(1981, 2002). As a result, we only compared monthly (i.e., July)phytoplankton assemblages from the Northeastern Ontariolakes (including Swan Lake) with those assemblages foundduring July at the ELA (L302S and L239). A phytoplanktondata base was created to store all taxa abundances for each ofthe 20 Northeastern Ontario lakes (1981 and 2002), Swan Lake(1982–2001), and ELA lakes (L239, L302S: 1980–2003). The

Fig. 1. Study areas. Reference Lake 239 (L239), and the experimental Lake 302S (L320S) are located at the Experimental Lakes Area(ELA; which the circle encompasses). Twenty Northeastern Ontario lakes, including Swan Lake, located within the Sudbury area.


three data sets resulted in a matrix of 108 lake years by 240 taxa.However, each of the lake regions had different levels oftaxonomic resolution. For example, the ELA lakes wereenumerated at the species level, while a majority of theNortheastern Ontario lakes were enumerated at the genuslevel. Therefore, species determinations in the ELA lakes werelumped to genus level prior to analyses. Any shared speciesfound in all lakes were not combined into genera but, instead,were maintained as species prior to analysis. The grouping ofspecies into genera was advantageous since it controlled for thepotential under- or overestimation of species resulting from thedifferent taxonomists involved in this study. Misidentificationof genera is highly unlikely for most well-trained phycologists.During the preliminary analysis, rare species or genera werealso problematic because they resulted in a large number ofzeros in the matrix, which are considered outliers in corre-spondence analysis (CA) and canonical correspondence anal-ysis (CCA; ter Braak and Smilauer 2002). Therefore, only the51 genera ⁄ species that contributed >1% of the total biomass inat least one lake year were retained in the analysis. All biomassvalues were log transformed.

Changes in phytoplankton assemblages and environmentalvariables in all regions (i.e., ELA [L302S, L239], Swan Lake,and the Northeastern Ontario lakes) were examined usingCANOCO version 4.5 (Microcomputer Power, Ithaca, NY, USA;ter Braak and Smilauer 2002). Prior to CCA analysis, apreliminary CA was used to ordinate a species-by-sample matrixconsisting of log-transformed data for common phytoplanktonspecies (i.e., present in at least 1% of all samples from a givenlake year). Sample scores from the first two CA axes were usedas variables for the community-structure matrix. CA is thepreferred ordination technique for sparse data input matrices(Jackson 1993), and it was performed to determine if aunimodal species-response model was appropriate. CA revealedthat the gradient lengths were >2 SDs, and thus unimodalordination techniques were appropriate.

CCA was performed to determine the environmental vari-ables that best explained taxonomic changes in phytoplanktonduring acidification and chemical recovery in all study lakes.CCA is a community-level, multivariate analysis that capturesthe maximum amount of explainable variation in the taxo-nomic data set and maximizes its correlation with linearcombinations of measured environmental variables by con-structing a series of independent axes (ter Braak and Smilauer2002). CCA generates ordination plots, consisting of environ-mental variables depicted by solid-line vectors, and lake-yearscores and species for each region, depicted as points orderedalong each axis. The origin of the ordination diagramrepresents the mean for each of the environmental variables.Orientation of each environmental vector parallels its axis ofmaximum change, and vector length is indicative of the relativeimportance of that variable to the ordination, while theirorientation shows approximate correlations to the ordinationaxis. In the environmental-lake score biplot, the lake scores areweighted averages of the taxon scores. The positioning of lakesin relation to environmental arrows closely corresponds to thelimnological characteristics and associated regional patternsfor the study lakes. Proximity of species to each other, and lakescores, reflect the nature and strength of their association.

A preliminary CCA was performed using environmental andphytoplankton species data from each region (i.e., ELA,Northeastern Ontario, and Swan Lake). Taxonomic andchemical data were screened prior to the final CCA. Not allenvironmental variables were measured for each of the lakeswithin each of the regions. Therefore, only chemical variablesthat were consistent for all lakes were included in the finalanalysis. The complete chemical data set consisted of ammo-nium (NH4

+), TN, TP, SO4)2, Cl, Ca, Mg, pH, DOC, and a suite

of metals (Al, Cu, Mn, Ni, Fe, and Zn). Other variables

included surface temperature, total number of ice-free days,degree days (ºC), and annual precipitation (mm). Theseclimate variables were also considered important towardphytoplankton dynamics in an earlier study (Weyhenmeyeret al. 1999, Findlay et al. 2001), and therefore, we wanted todetermine if they were important on a regional scale.

Analysis of phytoplankton within the atmospherically and experi-mentally acidified lakes: Separate CCAs for L302S, Swan Lake,and the Northeastern Ontario lakes were performed usingCANOCO (version 4.5; Microcomputer Power, Ithaca, NY,USA) to determine the environmental variables that bestexplained temporal shifts in phytoplankton assemblages dur-ing acidification and recovery at each of these sites. Seasonalmean phytoplankton data were used for each of the separateL302S and Swan Lake CCA analyses. July (1981 and 2002)phytoplankton data were used for the CCA analyses of theNortheastern Ontario lakes. Taxonomic and environmentaldata were screened prior to each of the final CCAs. Taxa thatwere not present in at least 1% of all samples from a given lakeyear were defined as rare and removed from the species dataprior to CCA to negate their disproportional influence on theordination. To allow for proper comparisons, we choseenvironmental variables that were consistent among each ofthese study sites. The complete environmental data setconsisted of pH; conductivity; sulfate; the dissolved fractionof Ca, DOC, Fe, K, Mg, Mn, Na, SRSi, TN, and TP; severalmetals (Al, Cu, Ni, Zn); and climate variables (lake tempera-ture, precipitation). Hill’s scaling was used to equalize taxonvariances along all axes to generate site scores that wereweighted averages of taxon scores (ter Braak and Smilauer2002). We further determined if July phytoplankton assem-blages reflected seasonal composites. For this comparativeanalysis Swan Lake proved the most complete of the North-eastern lakes surveyed. We determined how Swan Lakemonthly (July) phytoplankton communities compared withseasonal composites (May–September) using the determina-tion of coefficient of community similarity index. Communitysimilarity was determined from species-level log-transformedphytoplankton biomass data. Results showed that >50% of theseasonal phytoplankton species were represented in the monthof July over the 4 years compared (56.4% [1977]; 51.5%[1982]; 69.0% [1983]; 69.3% [1984]).

The influence of environmental factors on phytoplanktonrelationships was investigated at each of the study regions usinga randomization Procrustes analysis. In this procedure,concordance between lake ordination scores from the two-dimensional multivariate summaries (i.e., CA) of the phyto-plankton taxa matrix, with respect to lake-year matrix andenvironmental variables, were compared. To statistically testthe degree of concordance between phytoplankton communitycomposition and environmental variables, a Procrusteanrandomization test [PROTEST: Jackson (1995)] was used.PROTEST estimates the significance of an observed m12

statistic, with the underlying null hypothesis being a randomassociation between the two data sets (e.g., phytoplanktoncommunity and lake environmental ordinations). In this study,9999 random permutations of the data were employed toensure the stability of the probability estimates. A significantconcordance between phytoplankton and environmentalmatrices would demonstrate that taxonomic changes werestrongly related to concurrent changes in the lakes environ-mental conditions.

Relationships between annual biomass and environmentalconditions were analyzed using backward stepwise multipleregression for L302S and the Northeastern Ontario lakes(including Swan Lake). Chemical conditions were defined bypH, DOC, TP and TN, SO4

)2, Al, and Cu. Here, we use DOCvalues as a surrogate measure of light limitation. DOCconcentrations have been shown to be significantly correlated


with light attenuation, as DOC adds color to freshwater lakes.Climatic variables included in the analyses were surface watertemperature (epilimnetic averages, �C), average precipitation(ice-free season, May–October for each study lake), and degreedays (�C). Climate was considered as a potential explanatoryvariable because several studies have shown significant rela-tionships between climate and phytoplankton communities(Weyhenmeyer et al. 1999, Findlay et al. 2001). All data wereverified for normality and homogeneity of variances prior tomultiple regression analysis. All data were log transformed tobetter meet the assumptions of normality. Analyses wereperformed using SYSTAT (version 10; Systat Software Inc.,San Jose, CA, USA).

RESULTS AND DISCUSSION

Regional responses of atmospherically and experimentallyacidified lakes. Our findings demonstrated the regio-nal specificity of responses by boreal lakes to chemi-cal change over a 25-year period in Ontario. Theindustrially impacted lakes of Northeastern Ontariowere discriminated significantly from the relativelypristine L239 based on CCA of the entire phyto-plankton species-environmental data matrix for 23lakes (Fig. 2). DOC (P < 0.025), TN (P < 0.01), TP(P < 0.01), and pH (P < 0.01) were the significantexplanatory variables associated with taxonomicchanges in phytoplankton during this period.Redundant and insignificant variables that wereexcluded from ordination analyses included SO4

)2,NH4

+1, Mg+2, Ca+2, and Cl). Monte Carlo unre-stricted permutation testing showed CCA axes 1 and2 were statistically significant (P = 0.01), capturing14% of the total taxonomic variance. Relative to theatmospherically and experimentally acidified lakes,the unperturbed L239 showed minimum taxonomicvariation over the 23-year period (Fig. 2).

Industrially impacted Ontario lakes differed fromthe L239 and L302S because of differences in pro-ductivity, water color, and acidity along CCA axis 1(Fig. 2a). Lakes located in Northeastern Ontariowere characterized by more productive conditions,lower concentrations of light-attenuating DOC, andhigher TP than found in L239 or L302S (preacidifi-cation years). L239 and L302S (preacidificationyears) remained remote in ordination space fromthe more heavily polluted Northeastern Ontariolakes (Fig. 2a). L302S (acidification years) occupiedthe same ordination space as several of the North-eastern Ontario lakes of 1981 (e.g., Nellie, O.S.A.,Whitepine, George, and Annie). Slight differencesamong the experimental and atmospherically acidi-fied lakes might be related to the degree of damageexperienced by each. Also, acidity (i.e., pH) reflect-ing within-lake neutralizing and watershed processes(i.e., rates of base cation export) was an importantfactor explaining these differences (Keller et al.2001). Regional differences are more attributable tohigh metal concentrations in the NortheasternOntario lakes that resulted from the direct atmo-spheric deposition of metals, mobilization from the

drainage basin, and leaching of metals from the sed-iments (sensu Dixit et al. 1989). Although weincluded trace-metal concentrations in our analyses,paleolimnological investigations have shown thatlake-water pH was the more important variableexplaining the distribution of chrysophytes and dia-toms, which were the dominant algal groups in thestudy lakes (Dixit et al. 1988, 2002). Differences inproductivity, acidity, and DOC can also be found ata smaller local scale, as neighboring lakes can showlarge differences among these variables dependingon the presence or absence of wetlands.

-8

4

-2 3

81 82

80

01

0099

02

03

988483

9697

95

94

9288

9089

9385

8687

9188

83

00 8784

89

97

958582 99

0198 8696

9491

9290 93

Wavy

LaundrieHelen

Tyson

Bluesucker Whitepine

Sans ChambreSeagram

Bell

Annie Johnnie

David

Sans Chambre

David

LaundrieHelen

Klock

Wabun George

Annie O.S.A.

SeagramJohnnie Sunnywater

Tyson

Nellie

NellieWhitepine

GeorgeBluesucker

KillarneyWabun

BellKlock

Frederick

O.S.A.

SunnywaterFrederick

L239L302S (acidification years)L302S (preacidification/recovery years)Northeastern Ontario lakes 1981Northeastern Ontario lakes 2002Swan Lake (1982 - 2001)

TN

TP

pH

DOC

WavyKillarney

-1.5

1.5

-1.5 1.5

12

34

56

78

91011 12

1314

15

16

1718

19

2021

222324

2526

TabellariaTetraedron

Anabaena

Radiocystis

Gomphosphaeria

Aulacoseira

Mougeotia

Chlorogonium Gymnodinium

ChlamydomonasKirchneriella

OocystisCryptomonas

Mallomonas

Scenedesmus

Asterionella

Gloeocystis

Coelastrum

Chromulina

Melosira

Chrysolokos

Synura

Pseudokephyrion

Cyanodictyon

Cyclotella

TN

TPpH

DOC

a

b

CCA axis 1

CC

A a

xis

2

Fig. 2. (a) Association of lake-year scores and environmentalvariables based on a canonical correspondence analysis (CCA) ofphytoplankton biomass and environmental conditions among theregional study lakes. Environmental vectors were increased 2· tobetter illustrate their associations with lakes and taxa. (b) Associa-tion of phytoplankton taxa and environmental variables based ona CCA of taxa biomass and environmental conditions amongeach of the regional study lakes. To reduce congestion, taxa wererepresented by number codes; the list of taxa is presented inTable 2. DOC, dissolved organic carbon; TN, total nitrogen; TP,total phosphorus.


Although the Northeastern Ontario lakes are stilloligotrophic (W. Keller, personal communication),the analysis suggests that TP has influenced the phy-toplankton communities. A potential explanationfor this result is human activity, such as cottagedevelopment, which has been shown elsewhere toalter nutrient loading and phytoplankton communi-ties (Kauppila and Valpola 2003). However, since amajority of the lakes are surrounded by wildernessand only a few have any substantial shoreline devel-opment, it is unlikely that this was a significantsource of phosphorus. Instead, airborne dust arisingfrom human disturbances of land surfaces and flyash is a more likely source of phosphorus to remotelakes (Reynolds et al. 2001). Aeolian nutrient inputsmight also explain the increase in postindustrialtotal algal abundance observed in other Northeast-ern Ontario lakes (Vinebrooke et al. 2002).

Northeastern Ontario lakes were further differen-tiated along CCA axis 2 based on sampling year andproximity to smelters (Fig. 2a). In general, lakessampled in 1981 were separated from lakes thatwere resurveyed in 2002. The lakes in 2002 werecharacterized by higher pH and lower TN, whichboth significantly (P < 0.05) defined CCA axis 2.Therefore, the second CCA axis represented a gradi-ent of recovering acidified lakes and phytoplanktoncommunities. In particular, less-acidic conditions

would have enabled increased nitrogen cycling(Rudd et al. 1988), thereby lowering TN. However,these lower TN values contrast with reportedincreases in nitrogen deposition over large areas ofNorth America, including the Northeastern Ontariostudy sites (Bergstrom and Jansson 2006).

A general taxonomic shift from cyanobacteriatoward chlorophytes occurred as pH and DOCdeclined in an eastward direction from the ELA tothe Northeastern Ontario lakes (Fig. 2b). Small cy-anobacteria (Anabaena, Chroococcus, Planktolyngbya,and Radiocystis) were common in circumneutralL239, while several chlorophytes (Chlamydomonas,Coelastrum, Kirchinerella, Oocystis, and Scenedesmus)were more abundant in Northeastern Ontario lakes.The abundance of acid-tolerant chlorophytes in themore productive Northeastern Ontario lakes mayreflect their ability to outcompete many other algalgroups under high phosphorus levels (Hall et al.2005). Also, several coccoid greens are more toler-ant than cyanobacteria of heavy metals (Lombardiet al. 2002, Mehta and Gaur 2005), which occur inhigher concentrations in Northeastern Ontario lakesthan in the ELA lakes.

L302S was severely acidified (pH < 5) during thelate 1980s and early 1990s. During these years,L302S increasingly resembled lakes in NortheasternOntario. This finding suggests that the L302S exper-iment mimicked the impacts of regional atmo-spheric pollution. However, the differences inrecovery responses among experimentally acidifiedand atmospherically polluted lakes are more diffi-cult to interpret. Many lakes in NortheasternOntario have either seen minimal change in phyto-plankton assemblages or have been altered to a dif-ferent community structure. Persistent metalcontamination and elevated SO4

)2 levels couldexplain this trend. Long water residency times andslow flushing rates would further enhance the per-sistence of these contaminants (Nriagu et al. 1998,Keller et al. 2003) and might explain the slowresponse of the phytoplankton communities in therelatively large George, Killarney, Nellie, and O.S.A.lakes. Climate change is also an important factorinfluencing phytoplankton community structure inboreal lakes (Findlay et al. 2001). However, we didnot find that the climatic variables were significantin the analysis; instead nutrients are considered ofgreater importance in determining phytoplanktondynamics than is temperature (Magnuson et al.1997, Findlay et al. 2001).

Phytoplankton responses to atmospheric acidification andrecovery. Phytoplankton biomass in the NortheasternOntario lakes during 1981 and 2002 averaged below400 mg Æ m)3, and a majority of these lakes weredominated by phytoflagellates (Fig. 3). However,diatom biomass increased in several lakes (e.g.,Annie, Sunnywater, Frederick, Whitepine, Bluesuck-er). Stepwise multiple regression analysis showedthat phytoplankton biomass increased significantly

Table 2. List of phytoplankton taxa used in the canonicalcorrespondence analyses (CCAs) of the 23 lakes.

No. Taxon Algal group

1 Chrysochromulina CH2 Katablepharis CR3 Tabellaria DI4 Botryococcus G5 Rhodomonas CR6 Synedra DI7 Rhabdoderma C8 Chroococcus C9 Aphanothece C

10 Gonyostomun CR11 Planktolyngbya C12 Ceratium DN13 Rhizosolenia DI14 Salpingoeca CH15 Stichogloea C16 Spiniferomonas CH17 Sphaerocystis G18 Monoraphidium G19 Staurodesmus DE20 Merismopedia C21 Spondylosium DE22 Dinobryon CH23 Pseudokephyrion CH24 Chrysosphaerella CH25 Uroglena CH26 Peridinium DN

Taxon identification numbers correspond to those used inthe CCA plots; cyanobacteria (C), desmids (DE), diatoms(DI), nonfilamentous green algae (G), dinoflagellates (DN),chrysophytes (CH), and cryptophytes (CR).


with increasing DOC concentrations (total bio-mass = 1.893 + 0.672DOC; r2 = 0.120; P = 0.025).Improved water quality (i.e., lower acidity) andreplenished DOC levels could help support thesenet heterotrophic systems, which consisted of mixo-trophic species such as chrysophytes (Bird and Kalff1989, del Giorgio et al. 1999).

Taxonomic shifts in the phytoplankton revealedthat the Northeastern Ontario lakes responded syn-chronously to chemical change over a 21-year period(Fig. 4). Further, phytoplankton species closelytracked environmental changes within the lakesbased on PROTEST analyses (forward selection andconcordance tests; m12 = 0.9292, P = 0.0008). Taxo-nomic shifts during this time best correlated with pH(P = 0.03), sulfate (P = 0.03), DOC (P = 0.03), andSRSi (P = 0.05) based on CCA with forward selec-tion. Redundant and insignificant variables that wereexcluded from ordination analyses based on MonteCarlo unrestricted permutation testing were chloride(Cl), sodium (Na), potassium (K), magnesium (Mg),calcium (Ca), manganese (Mn), and iron (Fe). CCAaxes 1 and 2 were statistically significant (P < 0.01),capturing 34% of the total taxonomic variance.

Lakes in Northeastern Ontario that displayed thegreatest improvements in pH were plotted in theupper left quadrat (e.g., Bell, Tyson, SansChambre,Johnnie, Klock) (Fig. 4a). Lakes that displayed rela-

tively minimal increases in pH were plotted ineither the right quadrat (e.g., O.S.A., Nellie, Freder-ick) or in the lower quadrats (e.g., Bluesucker,Wabun, Killarney, Wavy, Sunnywater, David, Laund-rie; Fig. 4a). Several factors may explain these differ-ences in the extent of recovery among the lakes.First, many lakes are still highly acidic or havehigher concentrations of sulfate (B. Keller, J. H.Heneberry, and J. M. Gunn, unpublished data). Thehigher sulfate concentrations might also be a conse-quence of lower microbial sulfate reduction in someof these lakes. This process can be dependent onthe environmental conditions of the lakes’ sedi-ments. For example, unusually slow rates of sulfate-reducing microbial activity have been related to

-4

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AnnieBell

Tyson

Wabun

Helen

David

Seagram

JohnnieKlock

SansChambre

Killarney

Bluesucker

Sunnywater

LaundrieWhitePine Wavy

O.S.A

GeorgeNellie

Frederick

pH Sulphate

Silica

DOC

a

-3

3

-2 2

Synedra

Pseudokephyrion

ArthrodesmusScenedesmus

Uroglena Staurodesmus

Tetraedron

Anabaena

ElakatothrixTabellariafl occulosa

Cryptomonas

Kirchneriella

Navicula

Dinobryonc ysts

Chrysosphaerellalongispina

Staurastrum

Dinoflagellate sp.A

picochlorophytes

Dinoflagellate cysts

Sphaerocystis

Mougeotia Synura

Smallc hrysophytes

Large chrysophytes ChrysochromulinaparvaMonoraphidium

GymnodiniumChlamydomonas

KephyrionAphanotheceCyclotella

Rhodomonas

Ankistrodesmus

Katablepharis

1 2 3 45

12345

Tabellariaf enestrata

ChromulinaBitrichiaChrysochromulinaCrucigeniaMelosira

a

bc d

ef g

h

i

jkl

Quadrigula

Chrysolokos

a Gloeocystisb Peridiniumc Botryococcusd Tabellariae Asterionellaf Dinobryong Cryptomonash Mallomonasi Oocystisj Merismopediak Chroococcusl Rhabdoderma

pHDOC

Silica

Sulphate

b

CCA axis 1

CC

A a

xis

2

Fig. 4. Biplot showing the association of phytoplankton andthe 20 Northeastern Ontario lakes based on a canonical corre-spondence analysis (CCA) of taxa biomass and environmentalconditions of the lakes during 1981 and 2002, respectively. (a)Lake years: open circles represent 1981; closed circles represent2002. (b) Taxa: to avoid congestion, taxa that were common andordinated more toward the centroid were coded with numbers orwith letters. Environmental vectors were increased 3· to betterillustrate their associations with lakes and taxa. DOC, dissolvedorganic carbon.

0

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400

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800

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Seag

ram

Kill

arne

y

Geo

rge

Sunn

ywat

er

Nel

lie

Fred

eric

k

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un

O.S

.A.

Dav

id

Wav

y

John

nie

Lakes

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ie

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mbr

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Lau

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ker

CyanophyceaeChlorophyceaeBacillariophyceaeChrysophyceaeCryptophyceaeDinophyceae

Phyt

opla

nkto

n bi

omas

s (m

g . m

-3)

Fig. 3. Phytoplankton composition from the 20 survey lakeslocated in Northeastern Ontario during the years 1981 (first bar)and 2002 (second bar). For comparative purposes, the lakes havebeen ordered from least to the greatest recovery responses asobserved in Figure 4.


poor supply of organic carbon to sediments (Ruddet al. 1988). Laboratory studies have also shown thatthe in situ rate of sulfate reduction is limited by sed-iment organic-matter content (Westrich and Berner1984). Further, heavy metals persist as potentialstressors in these systems. For example, analyses oflake sediments reveal elevated levels of phytotoxicCu and Al (Belzile et al. 2004). The factors affectingchemical and biological recovery around the Sud-bury area are still not clear (Keller et al. 1999a,b).

Evidence suggests that recovery is influenced by acombination of factors related to watershed buffer-ing and regeneration processes, which are depen-dent on export of base cations from thesurrounding catchment (Keller and Gunn 1995, Kel-ler et al. 1999b). For example, a majority of theselakes are on rocky drainage basins surrounded bypoorly buffered soils (Dixit et al. 1992). Conse-quently, the base cation calcium, which acts as abuffer against acidification, is much lower in theselakes than in previous years when acid depositionwas much higher (Keller et al. 2003). Also, thesedeclines in base cations will likely result in either lit-tle change in pH or alkalinity within these lakes(Driscoll et al. 1995, Stoddard et al. 1999, Kelleret al. 2001), thereby further impairing recovery byprimary producers.

A general taxonomic shift in the NortheasternOntario lakes occurred from 1981 to 2002, from anassemblage composed of chlorophytes (e.g., Kirch-neriella, Monoraphidium, Staurodesmus, Staurastrum,and Quadrigula) and cryptophytes (e.g., Cryptomonas)to an assemblage dominated by chrysophytes, espe-cially Synura (Figs. 3 and 4b). For example, chryso-phytes dominated phytoplankton biomass in Annie,O.S.A., George, Sunnywater, Wabun, David, John-nie, Killarney, Seagram, and SansChambre lakes in2002. In addition, similar increases in Synura havealso been observed in lakes within south-centralOntario, based on the paleolimnological (Patersonet al. 2001, 2004) and contemporary records (A. M.Paterson, unpublished data). The remaining lakeswere dominated by mixed assemblages of diatoms,cryptophytes, and dinoflagellates. These latterassemblages were associated with higher levels ofDOC and increased pH (Fig. 4b). This mixedassemblage was characterized by small r-strategistphytoflagellates, which have relative high rates ofgrowth and enhanced use of carbon under higherpH conditions (Reynolds 1993).

In general, overall phytoplankton biomass inSwan Lake was below 1000 mg Æ m)3 (Fig. 5). Dino-flagellates dominated in Swan Lake during 1982–1984 (Fig. 5). This was followed by a dominance ofchrysophytes during 1985–1987. A marked transitionwas observed in 1988 when the biomass was reducedto �300 mg Æ m)3 and was dominated by crypto-phytes. Since 1988, there has been a steady increasein overall biomass with an almost complete shifttoward chrysophytes, along with a persistent absence

of diatoms. Stepwise multiple regression modelsshowed that algal biomass significantly declined withboth increasing Al and sulfate concentrations(F = 13.38; r2 = 0.628, P < 0.001).

Swan Lake showed substantial taxonomic changesin its phytoplankton over a 20-year period (Fig. 6).Phytoplankton taxa significantly tracked chemicalchanges based on PROTEST analysis (concor-dance tests and forward selection; m12 = 0.5852,P = 0.0004, residual sum of squares = 0.7118). CCAsignificantly discriminated the early 1980s from theperiod of 1990 to 2002, with a marked transitionoccurring after 1988. This transition periodcorresponds to the reacidification event following1988–1989 (Yan et al. 1996, Arnott et al. 2001).Environmental variables that were significantly cor-related with phytoplankton assemblages during thistime were Al (P = 0.005), sulfate (P = 0.005), Cu(P = 0.02), and pH (P = 0.025), based on CCA withforward selection. Monte Carlo unrestricted permu-tation testing showed CCA axes 1 and 2 were statisti-cally significant (P = 0.015), capturing 29% of thetotal taxonomic variance.

The first CCA axis represented a significant(F = 2.647; P = 0.015) gradient of taxonomicresponses to increases in Al (P = 0.005) and Cu(P = 0.02), and lower pH levels (P = 0.025). Thisresult was driven mostly by the reacidification, whichresulted in the mobilization of heavy metals. CCAaxis 1 contrasted those taxa that were tolerant oflow pH and high Al and Cu concentrations, whichwere common during the 1983–1991 time period(e.g., Kircherinella, Chrysosphaerella longispina [seeTable 3 for taxonomic authors], and Peridinium),from the rare taxa that increased in abundance dur-ing 1992–2001 (Mougeotia, Botryococcus, Bambusinabrebissonii, and Merismopedia; Fig. 6b). CCA axis 2

Phyt

opla

nkto

n bi

omas

s (m

g . m

-3)


0

1000

2000

3000

4000

5000

6000

Year82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01

drought

reacidification event

Fig. 5. Seasonal composition of integrated phytoplankton forSwan Lake from 1982 to 2001. The drought years (1986–1987)and the reacidification event (1988) are marked.


explained 13.2% of the total taxonomicvariance and was positively correlated with sulfate(P = 0.005). CCA axis 2 contrasted acid conditionswith taxa belonging to Chrysosphaerella longispina andKircherienlla from a mixed assemblage of taxa char-acteristic of circumneutral conditions (Chromulina,Chrysochromulina breviturrita, Dinobryon, Synura, Katab-lepharis ovalis, Gymnodinium, and Tabellaria).

Swan Lake phytoplankton assemblages appearedto have been influenced by the cumulative impactof acid and metal deposition (Fig. 6). CCA axis 1was inferred to be an acid-metal-stressed gradient, asdefined by the variables of pH, Cu, and Al, while

CCA axis 2 was a less clearly defined sulfate gradi-ent. Swan Lake showed an extreme divergence oflake-year scores in ordination space between 1982and 2001. The most dramatic changes occurredfrom 1987 to 1992 following a drought event andsubsequent reacidification in 1988 (Yan et al. 1996,Arnott et al. 2001). From 1992 to 2001, Swan Lakeappeared to stabilize, as most years are ordinated inthe same space. Prior to the reacidification period(i.e., pre-1980), there was some evidence of phyto-plankton recovery, given that several alkaline indica-tor diatoms were present (e.g., Asterionella formosa,Achnanthes, and Actinella; Dixit et al. 1992). How-ever, dinoflagellates and Chrysosphaerella longispina,indicators of strongly to moderately acidic waters,dominated the phytoplankton assemblage (Dixitet al. 1988) during the reacidification period. Thislong-term record for Swan Lake is very similar tothat presented in Arnott et al. (2001). However, theanalyses expand the taxonomic resolution and timerecord for an additional 4 years.

It has been suggested that the first step towardthe recovery of primary producers within Swan Lakewould be the reestablishment of the diatom commu-nity, since it was once a natural component of thisacidified lake (Arnott et al. 2001). However, theestablishment of planktonic diatoms might not bepossible. First, Swan Lake is influenced by a signifi-cant littoral zone and is morphologically quite dif-ferent from the Northeastern Ontario lakes (i.e.,small, shallow, high DOC, short renewal times;Arnott et al. 2003). A greater littoral area wouldafford more habitats for benthic diatoms to colonizeand would give them a competitive advantage overplanktonic diatoms for available silica. Second, SwanLake still has moderate levels of mobilized Al, Cu,and other metals following the reacidification eventof 1988. The presence of metals can hinder theuptake of silica by planktonic diatoms, such as Aste-rionella formosa (Cattaneo et al. 2004), which was adominant member of the phytoplankton in SwanLake prior to the reacidification event. Third, thecurrent chrysophyte-dominated assemblage mightcompete with colonizing diatoms for Si. Severalmembers of the chrysophytes are able to assimilatephosphorus-rich bacteria and, therefore, may have acompetitive advantage over planktonic diatoms(Urabe et al. 1999, Lagus et al. 2004). In short, itmay take further improvements in water qualityand, most particularly, increased concentrations ofsilica and declines in metals for planktonic diatomsto thrive in Swan Lake.

Phytoplankton responses to experimental acidificationand recovery. L302S maintained an average annualalgal biomass of >1000 mg Æ m)3 throughout the 23-year study period (Fig. 7). Chrysophytes and dia-toms dominated L302S during preacidification(1980–1982). During the acidification and the earlyrecovery years, algal biomass increased to>2500 mg Æ m)3. Dinoflagellates (Dinophyceae)

-3

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SulphateCuAl

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19831984

19851986

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1994

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199920012000

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Chrysosphaerella longispina

Kirchneriella

Dinoflagellate (unknown)

Anabaena

Asterionella formosaBambusinaEuglena

ClosteriumBitrichiaArthrodesmus

PeridiniumPseudokephyrion

Merismopedia

Bambusina brebissoni

Mougeotia

BotryococcusChrysidiastrum

Uroglena

ActinellaAchnanthes

Carteria

Aphanocapsa

Peridinium inconspicuum

12 3

45

6

Chrysochromulina parva

OocystisScenedesmus, Cryptomonas

7

8 910

1=Chromulina2=Katablepharis3=Gymnodinium4=Tabellaria5=Synura6=Chrysochromulina breviturrita7=Dinobryon8,9=Chrysococcus, Chrysolykos10=Chlamydomonas

ChrysosphaerellaGloeocystis

EunotiaMallomonas

b

pH

SulphateCuAl

CCA axis 1

CC

A a

xis

2

Fig. 6. Biplot showing the association of phytoplankton spe-cies and Swan Lake year scores based on a canonical correspon-dence analysis (CCA) of taxa biomass and environmentalconditions of Swan Lake over 21 years. (a) Linear chi-squared dis-tance vectors representing recovery trajectories for the lake years.(b) Taxa. To avoid congestion, taxa that were common and ordi-nated more toward the centroid were coded with numbers.


Table 3. List of phytoplankton taxa used in the Lake 302S canonical correspondence analyses (CCAs).


1 Tabellaria fenestrata (Lyngb.) Kutz. DI2 Teilingia granulata (J. Roy et Bisset) DE3 Gomphosphaeria aponina Bourr. ex Compere Kutz. G4 Ceratium hirundenella (O. F. Mull.) Bergh DN5 Ankrya judayi (G. M. Sm.) Fott G6 Chrysostephanosphaera spp. CH7 Chrysococcus spp. CH8 Rhabdogloea gorskii Wołtosz. C9 Aulacoseira spp. DI

10 Merismopedia tenuissima Lemmerm. C11 Selenastrum minutum (Nageli) Collins G12 Staurodesmus spp. DE13 Cyclotella stelligera Cleve et Grunow DI14 Mallomonas duerrschmidtiae Siver, J. Hamer et H. J. Kling CH15 Staurodesmus cuspidatum Breb. et Ralfs DE16 Anabaena spp. C17 Synura spinosa Korshikov CH18 Spondylosium planum (Wolle) W. West. et G. S. West DE19 Mallomonas pseudocoronata Prescott CH20 Rhizosolenia eriensis H. L. Smith DI21 Mallomonas hamata Asmund CH22 Staurodesmus spp. DE23 Spiniferomonas serratus Nicholls CH24 Staurodesmus bullardii G. M. Sm. DE25 Stichogloea spp. C26 Small chrysophytes (Ochromonas-like) CH27 Dinobryon barvaricum O. E. Imhof CH28 Peridinium wisconsinense S. Eddy DN29 Katablepharis ovalis Skuja CR30 Chrysochromulina parva Lackey CH31 Peridinium willei Huitf.-Kaas DN32 Salpingoeca frequentissima (O. Zacharias) Lemmerm CH33 Sphaerocystis schroeteri Chodat G34 Chroococcus limneticus Lemmerm. C35 Chrysosphaerella longispina Lauterborn CH36 Chrysochromulina laurentia H. J. Kling CH37 Dinobryon mucronatum Nygaard CH38 Synura sphagnicola Korshikov CH39 Gonyostomun semen (Ehrenb.) Diesing CR40 Peridinium pusillum (Penard) Lemmerm. DN41 Dinobryon divergens O. E. Imhof CH42 Mallomonas crassisquama (Asmund) Fott CH43 Chlorocystis sp. G44 Peridinium limbatum (A. Stokes) Lemmerm. DN45 Synura petersenii Korshikov CH46 Arthrodesmus octocornis (Ehrenb. et Ralfs) W. West et G. S. West DE47 Dinobryon sociale Ehrenb. CH48 Oocystis borgei J. Snow G49 Dinobryon pediforme (Lemmerm.) Steinecke CH50 Gymnodinium helveticum Penard DN51 Xanthidium spp. DE52 Chrysochromulina breviturrita K. H. Nicholls CH53 Synura uvella Ehrenb. CH54 Cryptomonas marssonii Skuja CR55 Peridinium aciculiferum Lemmerm. DN56 Chlamydomonas spp. G57 Gymnodinium spp. DN58 Peridinium spp. DN59 Oocystis lacustris Chodat G60 Cryptomonas erosa Ehrenb. CR61 Small greens G62 Cryptomonas rostratiformis Skuja CR63 Merismopedia minima Beck C64 Cryptomonas ovata Ehrenb. CR65 Mougeotia spp. FG66 Dinobryon sertularia Ehrenb. CH67 Chromulina spp. CH


dominated during this period. There has been asteady decline in overall biomass while the lake wasallowed to recover from 1992 to present time.Chrysophytes and dinoflagellates showed equal rela-tive abundance during this recovery period. Step-wise multiple regression models showed that totalalgal biomass significantly increased with decreasingpH (algal biomass = )0.227 + 4.532 pH; r2 = 0.462,P < 0.001).

PROTEST analysis showed that phytoplanktonsignificantly tracked chemical changes during acidi-fication and chemical recovery in L302S (concor-dance tests and forward selection; m12 = 0.2937;P < 0.0001; residual sum of squares = 0.3192).Therefore, taxa did not show significant delayedresponse to acidification. CCA captured 40.4% ofthe total cumulative taxonomic variance with its firsttwo axes (Fig. 8). The first axis (k = 0.232) repre-sented a significant (P = 0.002) temporal gradientof taxonomic responses by species to chemicalchanges during experimental acidification between

1981 and 1990. CCA axis 1 was best defined bydeclines in pH (P = 0.002) and DOC (P = 0.002),along with increases in total dissolved nitrogen(TDN; P = 0.06) and SRSi (P = 0.042). CCA axis 1contrasted taxa that were common prior to theexperiment with originally rare taxa that increasedin abundance during acidification (Fig. 8b;Table 3). CCA axis 2 was best defined by increasesin DOC and TDP. This axis contrasted high DOClevels observed in the 1980–1984 period from thelow DOC concentrations observed during severeacidification years (1985–1991) and recovery years(1992–2003). Photobleaching of DOC, which is acommon phenomenon in acidified lakes, mightexplain these lower DOC levels (Findlay et al. 1999,Wu et al. 2005). However, we are also aware thatdecreases in DOC can also result from bacterialconversion to CO2 or incorporation into sedi-ments via precipitation processes (sensu Clair et al.1999).

Ordination of years showed that the taxonomictrajectories of the phytoplankton differed betweenacidification and recovery periods (Fig. 8b).Although lake scores during acidification (1981–1990) tracked primarily along CCA axis 1, they laterdiverged during recovery (1991–1999) along CCAaxis 2. In particular, differences between ordinationscores for certain acidification years (e.g., 1983 vs.1997, 1987 vs. 1992) indicated dissimilar phyto-plankton assemblages despite similar pH values.The ordination results corroborate the earlier find-ings of experimental acidification and early recoveryof L302S phytoplankton (Schindler et al. 1991,Findlay et al. 1999, Findlay 2003, Vinebrooke et al.2003b). The present study helps to extend theirtemporal scale of recovery and demonstrates the keyenvironmental factors affecting taxonomic changesin the phytoplankton of L302S.

We suggest that phytoplankton have not com-pletely recovered taxonomically because of lowDOC levels. Modest changes in DOC might stillbring about significant changes in the phytoplank-ton assemblage. For example, environmentalchanges occur when the DOC declines to1–2 mg Æ L)1, resulting in increased UV exposure

Table 3. (Continued)


68 Oocystis submarina Skuja G69 Chlorogonium spp. G70 Staurastrum paradoxum Meyen ex Ralfs DE71 Large chrysophytes (Ochromonas-like) CH72 Dinobryon sertularia var. protuberans (Lemmerm.) W. Krieg. CH73 Tabellaria flocculosa (Roth) Kutz. DI74 Rhodomonas minuta Skuja CR75 Mallomonas caudata Iwanoff CH

Taxon identification numbers correspond to those used in the CCA plots; cyanobacteria (C), desmids (DE), diatoms (DI), fila-mentous green algae (FG), nonfilamentous green algae (G), dinoflagellates (DN), chrysophytes (CH), and cryptophytes (CR).

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80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03

recoveryacidification

Phyt

opla

nkto

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omas

s (m

g . m

-3)

Fig. 7. Seasonal composition of epilimnetic phytoplankton forthe experimentally acidified Lake 302S (L302S). The experimen-tal acidification and recovery phases are marked.


and having potential effects on phytoplankton bio-mass (Schindler et al. 1996) and species composi-tion. Long-term paleolimnological studies alsosuggest that changes in species appear stronglylinked to changes in DOC in recovering acidifiedlakes (Monteith et al. 2005). We are not suggestingthat the phytoplankton assemblages are expected toreturn to their former state with increases in DOC.Instead, we believe that fluctuations in DOC con-

centration levels can affect the phytoplankton habi-tat. For example, DOC generally has a dominanteffect on lake transparency and overall thermalstructure (Snucins and Gunn 2000). In fact, DOC isconsidered the best individual predictor of late sum-mer epilimnion thickness (i.e., high DOC levelsequate to a reduced epilimnion) in NortheasternOntario lakes (Keller et al. 2006). Climate changesand associated variation in precipitation patternsaffect allochthonous inputs of DOC, which theninfluences absorption of solar irradiance and thethermal state of lakes (Schindler et al. 1996, Snucinsand Gunn 2000). Further, drought conditions alternutrient regimes, causing reductions in coloredDOC, thereby altering light availability (Schindleret al. 1985, 1990, Magnuson et al. 2000, Snucinsand Gunn 2000, Findlay et al. 2001, Pace and Cole2002). Understanding the recovery of stressed bor-eal lakes will involve an appreciation of the influen-tial role of climate variability. Presently, monitoringthe recovery of stressed boreal lakes is analogous totrying to catch a target (i.e., prestressed conditions)that is always moving in response to climaticchange.

CONCLUSIONS

There was strong agreement between phytoplank-ton responses to experimental acidification ofL302S during the 1980s and their community struc-ture in the chronically acidified lakes in Northeast-ern Ontario. Comparison of separate CCAs for theNortheastern Ontario lakes (Fig. 4) and L302S(Fig. 8) suggest that a potential explanation for thisfinding involved the same dominant generaresponding to the same set of environmentalchanges. Specifically, pH and DOC explained thetaxonomic similarities among phytoplankton inboth the Northeastern Ontario lakes and acidifiedL302S. In contrast, the taxonomic trajectories ofphytoplankton during chemical recovery from acidi-fication differed between the experimentally andatmospherically impacted lakes.

Taxonomic resilience (i.e., rate of recovery) wasgreater in L302S than in the Northeastern Ontariolakes, based on their relative movement in ordina-tion space. However, there remained a substantialamount of unexplained taxonomic variation by thephytoplankton during recovery in L302S, suggestingthat the community was also responding to otherunmeasured environmental variables. Therefore,despite other possible environmental changes (e.g.,climate warming) taking place during chemicalrecovery, the phytoplankton still responded moredynamically in L302S than in the eastern Ontariolakes. Further, phytoplankton community structureremains altered in L302S relative to its preacidifica-tion condition, suggesting that certain environmen-tal conditions have become altered within the lakeover the past 25-year period. Similarly, phytoplank-

Fig. 8. (a) Biplot showing the association of phytoplanktonspecies and Lake 302S (L302S). Lake-year scores based on acanonical correspondence analysis (CCA) of taxa biomass andenvironmental conditions of L302S over 23 years. (b) Linear chi-squared distance vectors represent recovery trajectories for thelake years. To avoid congestion, taxa were represented by numbercodes; full Latin binomials are shown in Table 3. DOC, dissolvedorganic carbon; SRSi, soluble reactive silica; TDN, total dissolvednitrogen; TDP, total dissolved phosphorus.


tons in Swan Lake have also not resumed their pre-vious taxonomic composition despite substantialchemical improvements. In comparison, the otheracidified lakes have exhibited more predictable, butalso less dynamic, responses to chemical improve-ments for the past two decades.

Our findings agree with other reports of delayedbiological responses to chemical recovery in acidi-fied lakes (Gunn and Keller 1990, Findlay et al.2001, Keller et al. 2002). Several possible explana-tions exist for delayed responses by phytoplanktonto recovery, which were more pronounced in theNortheastern Ontario lakes than in Lake 302S. Theecological history of a system can influence plank-tonic community responses to environmentalchange (Fischer et al. 2001). In this case, L302Swould be better able to show resistance to furtherperturbations, owing to its diverse assemblage of tol-erant species (Vinebrooke et al. 2003b). Long-termregional acidification of the Northeastern Ontariolakes may have generated more extreme abiotic con-ditions (e.g., trace-metal contamination) than didthe localized experimental acidification of Lake302S. Regional acidification and biological impover-ishment of Northeastern Ontario lakes may alsohave delayed the arrival of grazers that shouldincreasingly influence phytoplankton assemblagesduring chemical recovery (Vinebrooke et al. 2003b).It is already established that the fluctuations in her-bivorous grazing pressure can have significanteffects on phytoplankton compensatory dynamics(Vasseur et al. 2005). However, herbivorous cladoc-erans are not recovering in some of these chroni-cally stressed lakes (Yan et al. 2004). Ultimately,making predictions of the impact of further envi-ronmental changes on phytoplankton assemblages isdifficult unless we extend our research to considerthe possible interactive effects among multiple stres-sors, such as climate change and acidification.

This research was funded by the Natural Sciences and Engi-neering Research Council of Canada (NSERC) through aPGS-D scholarship to M. D. G., and NSERC Discovery Grantto R. D. V. Other funding sources included the EJLB Founda-tion and the Department of Fisheries and Oceans AcademicScience Subvention program.

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Comparative responses of phytoplankton during chemical recovery in atmospherically and experimentally acidified lakes 1