pelagic and benthic algal responses in eastern canadian boreal shield lakes following harvesting and...

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Can. J. Fish. Aquat. Sci.57(Suppl. 2): 136–145 (2000) © 2000 NRC Canada

Pelagic and benthic algal responses in easternCanadian Boreal Shield lakes following harvestingand wildfires

Dolors Planas, Mélanie Desrosiers, S-Raphaëlle Groulx, Serge Paquet, andRichard Carignan

Abstract: Pelagic and benthic algal biomass and pelagic algal community structure were measured in Boreal Shieldlakes impacted by forest harvesting and wildfires (Haute-Mauricie, Québec). Sixteen reference lakes in which the wa-tershed has been unperturbed for at least 40 years, seven harvested lake watersheds (logged in 1995), and nine lakewatersheds burnt in 1995 were sampled for 3 years following harvesting or wildfires. From 1996 to 1998, repeated-measures ANOVA showed significant effects between treatment and sampling years for pelagic chlorophylla (Chl a)and biomass, but for 1997–1998 benthic Chla, repeated-measures ANOVA showed only significant treatment effects.Chl a concentrations increased 1.4- to 3-fold in perturbed lakes as compared with reference lakes. Areal pelagic Chla(milligrams per square metre) was lower than estimated littoral Chla in perturbed lakes. The pelagic algal communitywas dominated by mixotrophic nanoflagellates in reference lakes. Watershed perturbation induced differential changesin pelagic algal communities: mixotrophic nanoflagellates increased in harvested lakes and photoautotrophic diatoms inburnt lakes. Considering only perturbed lakes, algal biomass was proportional to the fraction of the catchment area per-turbed divided by the surface area of lakes in the catchment.

Résumé: La biomasse des algues pélagiques et benthiques ainsi que la structure de la communauté pélagique ont étémesurées dans 32 lacs de la forêt boréale (Haute-Mauricie, Québec) : seize lacs de référence non perturbés depuis aumoins 40 ans, sept lacs ont été perturbés par des coupes forestières (1995) et neuf lacs dont les bassins versants ontsubi des feux de forêt (1995). Pour la chlorophyllea (Chl a) et la biomasse pélagique (1996–1998), l’ANOVA en me-sures répétées montre un effet significatif du traitement et de l’année alors que seul le traitement est significatif pour laChl a benthique (1997–1998). La concentration du Chla augmente de 1,4 à 3 fois dans les lacs perturbés par rapportaux lacs de référence. Dans les lacs perturbés, la Chla pélagique par unité de surface (milligrammes par mètre carré)est plus faible que la Chla benthique. La communauté pélagique est dominée par les nanoflagellés mixotrophes dansles lacs de référence. Cependant, les perturbations du bassin versant induisent des changements différentiels dans lacommunauté d’algues pélagiques : les nanoflagellés mixotrophes augmentent dans les lacs de coupes alors que ce sont lesdiatomées phototrophes qui augmentent lors d’un feu. Lorsque l’on considère uniquement les lacs perturbés, la biomassedes algues est proportionnelle à la fraction du bassin versant perturbé divisée par la surface des lacs dans ce bassin.

Planas et al. 145

Introduction

Aquatic ecosystems and wetlands occupy almost a third ofthe boreal ecoregion. More than 600 000 lakes larger than4 ha are found in the Canadian Shield boreal region, southof 52°N latitude and east of the Manitoba–Ontario border

(Minns et al. 1992). Timber harvesting in the Canadian bo-real forest has increased in the last two decades and con-cerns have been raised over its potential impact on aquaticecosystems. In the province of Québec, approximately 1%of the boreal forest is harvested annually (Ministère Res-sources Naturelles Québec 1996).

The disturbances expected after logging are an increase inthe watershed export of suspended solids, base cations, nu-trients, and dissolved organic C (DOC) (e.g., Nicolson et al.1982; Rask et al. 1998). In the boreal forest, similar distur-bances in watershed exports occur naturally, mainly follow-ing wildfires, which also increase flow, silt loads, andchemical concentrations in waters (Bayley et al. 1992). As aconsequence of these perturbations, nutrients may increaseand light penetration may decrease, thereby modifying thewater quality and productivity of impacted watersheds (e. g.,Wright 1976; Carignan et al. 2000).

Studies on the effects of forestry practices are more com-mon on running waters than on lakes (e.g., see Holopainen

Received September 2, 1999. Accepted April 28, 2000.J15344

D. Planas,1 M. Desrosiers, S-R. Groulx, and S. Paquet.Groupe de Recherche Interuniversitaire en Limnologie(GRIL), Département de Sciences Biologiques, Université duQuébec à Montréal, C.P. 8888, Succursale Centre-Ville,Montréal, QC H3C 3P8, Canada.R. Carignan. GRIL, Département de Sciences Biologiques,Université de Montréal, C.P. 6128, Succursale Centre-Ville,Montréal, QC H3C 3J7, Canada.

1Author to whom all correspondence should be addressed.e-mail: [email protected]

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and Huttunen 1992). The few previous studies on the conse-quences of forest harvesting on lakes have only consideredthe response of pelagic organisms (Rask et al. 1998). How-ever, benthic algal communities can be responsible for a sig-nificant fraction of the primary production in lakes, either inshallow systems or in deep oligotrophic lakes, and their im-portance in whole-lake metabolism is often neglected (Loebet al. 1983; Wetzel 1996). Furthermore, the littoral zone isthe main feeding area of many freshwater fish species.

The objectives of this study were to analyse changes inbiomass and community structure of phytoplankton in borealeastern Canadian Shield lakes disturbed by fire and harvest-ing and to compare the responses of pelagic and littoral al-gae with these disturbances.

Material and methods

The study area (-50 000 km2) is centered on Gouin Reservoir(47°52¢–48°59¢N, 73°19¢–76°43¢W) (Fig. 1) at the transition zonebetween the boreal mixed and the boreal conifer forest (seeCarignan et al. 2000). Thirty-two thermally stratified lakes wereselected on the basis of several criteria (Carignan et al. 2000). Ini-tially, the experimental design consisted of 16 lakes located withinunperturbed watersheds, defined as a watershed untouched by fireor anthropogenic influences for a minimum of 40 years and, ingeneral, for more than 70 years (reference lakes, N in Fig. 1). Ofthe harvested lakes, seven had approximately 9–73% of their wa-tershed logged in 1995 (C in Fig. 1) and one was harvested twice,once in 1995, and once in 1997 (C9 in Fig. 1). Nine lakes had 50–100% of their watershed area severely burnt in 1995 (burnt lakes,FP and FBP in Fig. 1).

SamplingPhytoplankton were sampled three times per year, in spring

(within 2 weeks of ice-out), summer, and fall, from 1996 to 1998.Duplicate integrated samples from the euphotic zone (depth of 1%light penetration, between 2 and 5 m) were taken near the deepestpart of the lake. Benthic algae were sampled using artificial sub-strates (70-mm Teflon® mesh; D. Planas et al., unpublished data) inreference lakes (four for the summers of 1997 and 1998 and six forwinter), burnt lakes (five in 1997 and 1998), and cut lakes (four forthe summers of 1997 and 1998 and six for winter). We used artifi-cial substrates to minimize the heterogeneity of communities andto facilitate comparisons between systems. Benthic biomass aschlorophylla (Chl a) was measured at two to four stations per lakeon quadruplicate substrates placed at a depth of 1 m and left in thefield for 3 months during the summers of 1997 and 1998 (summerbenthic algae) and during 9 months from September 1998 to May1999 (winter benthic algae).

Phytoplankton and benthic algal biomass measurementsWater samples for pelagic algae were transported to the labora-

tory on ice and Chla was concentrated within 12 h by filtering aknown amount of water (750–1000 mL) on Whatman GF/C filters.The filters were immediately frozen and kept at –40°C until extrac-tion. Phytoplankton Chla was extracted using hot 90% ethanol andabsorbance was measured spectrophotometrically, before and afteracidification (Sartory and Grobbelaar 1984). For measurements ofbenthic algal Chla, the Teflon® substrates were transported to thelaboratory on ice and kept frozen at –40°C until analysis. Chlawas extracted directly from artificial substrates by immersing themin hot 95% ethanol for 5 min.

A portion of the pelagic sample was preserved with acid Lugolsolution for taxonomic analyses. Algae were identified, measured,and counted with an inverted interferential microscope. Phyto-

plankton counts were converted to wet weight biomass (biomass)using average species dimensions (mean of 40 cells) and corre-sponding geometric shapes and assuming a specific density of 1(Lewis 1976). Species were assigned to one of three fractions ac-cording to the longest cell dimension: picoplankton, <2mm; nano-plankton, 2–20mm; microplankton, >20mm.

Data analysesIn order to compare the relative importance of pelagic and ben-

thic algae, phytoplankton biomass per unit volume was trans-formed to unit area of photic zone as phytoplankton biomass(milligrams per cubic metre) × photic zone depth (metres). Thebenthic to pelagic biomass ratio was estimated as average benthicbiomass per lake (milligrams per square metre) × littoral area(square metres)/average phytoplankton biomass per lake (milli-grams per square metre) × area of the pelagic euphotic zone(square metres). The littoral area was defined as the surface area ofbottom sediments receiving more than 1% of the light extinctioncoefficient (ePAR). For benthic algae, we assumed that the biomassat 1 m corresponded to maximum biomass, since the substrateswere at a fixed depth in all lakes. This coarse approach probablyunderestimated benthic algal Chla, since typical epilithic algalprofiles in oligotrophic Shield lakes show maximum Chla concen-trations below the 10% surface incident light depth (D. Planas etal., unpublished data), and artificial substrates after a 3-month col-onization period have, in general, lower algal biomass than naturalsubstrates (D. Planas et al., unpublished data). We could not ex-clude the possibility that our calculations overestimated benthic al-gal biomass, since factors other than depth and irradiance alsoregulate littoral algal biomass in lakes.

Statistical analyses were performed on log10-transformed datawhen necessary using SAS 6.14 and JMP 3.2.5 statistical packages(SAS institute Inc., Cary, N.C.). For pelagic Chla and biomass andfor summer benthic Chla, univariate repeated-measures ANOVA(RMA) were applied to examine changes in Chla and biomassmeasurements over time (1996, 1997, and 1998 for pelagic algaeand 1997 and 1998 for benthic algae) for each treatment (refer-ence, burnt, and harvested). One-way ANOVA was performed onwintering benthic Chla (1998–1999). When an effect was signifi-cant, a Dunnett one-tailedt test was applied to compare referenceand treated lakes. Differences among treatments and among yearswere tested using Tukey’s honestly significant difference test formultiple comparisons. Thet tests were used for benthic data (twoyears sampled) and for pelagic and benthic comparisons.

Multiple regressions were performed with a stepwise variableselection (p < 0.05 as an entering and keeping level) using Mal-low’s Cp as a model selection criterion, and colinearity betweenvariables was accounted for by using a variance inflation factor.Normality of the predicted–observed residuals was verified with aShapiro-Wilk W test. Correlations between phytoplankton taxonand physical and chemical variables were calculated using thePearson product-moment pairwise method. Finally, we usedANCOVA (covariance on intercept and heterogeneity of slopes forregression coefficients) to test if the regression relationships be-tween Chla and total P (TP) (data from Carignan et al. 2000) andthe ratio of Chla to TP andePAR (data from Carignan et al. 2000)were different among groups of perturbed lakes.

Results

Response of pelagic algal biomassRMA on pelagic Chl a and biomass concentrations

showed significant effects between treatments (burnt andharvested lakes with more than 10% catchment perturbed)and years (within treatments). The interaction term was sig-nificant for Chl a, indicating that temporal changes are de-

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Fig. 1. Location of the 32 study lakes in the Haute-Mauricie (Québec). N, reference lakes; FP and FBP, burnt lakes; C, harvested lakes (cut in 1995). The circles mark thelakes in which benthic algae were sampled.

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pendent on lake watershed treatment (Table 1). Over the 3-year period, perturbed lakes had higher mean Chla and bio-mass than reference lakes (p < 0.05, Dunnett’s test) (Figs. 2and 3). Regardless of treatment, 1996 had higher Chla andbiomass than 1998 (p < 0.05, Tukey’s test) and values in1997 were intermediate (p > 0.05) between 1996 and 1998.A comparison within years found higher Chla and biomassin perturbed lakes as compared with reference lakes in 1996(p < 0.05), and these differences persisted only in burntlakes for 1997 and 1998. Burnt lakes had higher Chla in1997 than in 1998 (p < 0.05, Tukey’s test).

A highly significant relationship (r 2 = 0.69, p < 0.0001)was found between pelagic algal Chla and biomass whendata for all years and treatments were combined. However,when regressions were performed by treatment, the strongestrelationship was found in burnt lakes (r 2 = 0.66,p < 0.0001)and the weakest in harvested lakes (r 2 = 0.40, p < 0.002).

The relationship was also weak in reference lakes (r 2 = 0.42,p < 0.0001) (Fig. 4). ANCOVA indicated nonsignificant dif-ferences between slopes (p > 0.05) and intercepts (p > 0.05)among treatments.

Phytoplankton communities were dominated by thenanoplankton fraction, which represented between 76 and91% of the total biomass. Nanoplankton increased in burntand harvested lakes 1 year after perturbation and, in compar-ison with reference and harvested lakes, remained high 2and 3 years after perturbation in burnt lakes (p < 0.05). Inharvested and reference lakes, nanoplankton biomass tendedto decrease from 1996 to 1997 (p < 0.05). Picoplankton bio-mass represented between 3 and 13% of the total biomass

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Type III SS df F p > F

Phytoplankton ChlaTreatments 0.48 2 13.33 0.0001Years 0.07 2 11.01 0.0001Treatments × years 0.06 4 4.77 0.0022

Wet weight biomassTreatments 2.36 2 17.08 0.0001Years 0.33 2 10.9 0.0001Treatments × years 0.11 4 1.83 0.1384

Summer benthic ChlaTreatments 0.72 2 6.25 0.0174Years 0.04 1 0.04 0.1119Treatments × years 0.02 2 0.02 0.5636

Winter benthic ChlaTreatments 2.44 112 18.36 <0.0001

Table 1. Results of univariate RMA for phytoplankton Chla(mg·m–3), wet weight biomass (mg·m–3), and summer benthicChl a (mg·m–2, 3-month colonization) and one-way ANOVA forwinter benthic Chla (mg·m–2, 9-month colonization).

Fig. 2. Average summer means ± SE of pelagic algal Chla forreference (open bars,n = 16), harvested (grey bars,n = 7), andburnt lakes (black bars,n = 9). Different letters indicate meandifferences (p < 0.05, ANOVA) within sets of lakes.

Fig. 3. Annual average total biomass of pelagic algae taxa. R,reference lakes (n = 16); H, harvested lakes (n = 7); B, burntlakes (n = 9).

Fig. 4. Regression plot between pelagic algal Chla concentra-tions and pelagic algal biomass (wet weight) for reference lakes(circles), harvested lakes (diamonds), and burnt lakes (squares)(log(Chl a) = –0.745±0.085 + 0.389±0.027log(biomass);r 2 =0.69, p < 0.0001,n = 96). The dotted line, dashed line, andsolid line indicate the linear fit for reference, harvested, andburnt lakes, respectively.



and was higher in reference than in harvested and burntlakes (p < 0.05). In reference lakes, picoplankton increasedbetween 1996 and 1998 (p < 0.05). Microplankton biomassrepresented between 8 and 18% of the total biomass increasein harvested lakes in 1997 and was higher than in referenceand burnt lakes (p < 0.05).

The dominant communities in the nanoplankton fractionswere Chrysophyceae and Cryptophyta taxa. This associationis characteristic of oligotrophic boreal lakes (Kling andHolgrem 1972; Willén et al. 1990). Cyanobacteria communi-ties, the most important taxa within the picoplankton frac-tion, were dominated by small chroococcales, which wereabundant in terms of numbers but of minor importance whenconverted to biomass. Cyanobacteria species found in ourstudy are typical of temperate, nutrient-poor, dark watersand are abundant in eastern Canadian Shield lakes in themiddle of summer, often associated with small green chloro-coccales (D. Planas et al., unpublished data). Harvestingbarely changed the phytoplankton community compositionin lakes; some taxa increased, such as Chrysophyceae,Cryptophyceae, and dinoflagellates, or decreased, as was thecase for cyanobacteria. More drastic changes in communitycomposition were measured in burnt lakes 1 year after per-turbation; diatoms became the dominant taxa and Crypto-phyceae also increased in these perturbed lakes (Fig. 3).

Response of benthic algal biomassIn the littoral zone, algal communities also had higher Chl

a in perturbed lakes compared with reference lakes. RMA onbenthic summer Chla showed only significant treatment ef-fects (Table 1). Among perturbed lakes, burnt lakes had thehighest concentrations of Chla (p = 0.0025) (Fig. 5). Forboth years, Chla concentrations were threefold higher inburnt lakes than in reference lakes, and in 1997, burnt lakeshad twofold higher Chla concentrations than harvestedlakes (data not shown). A one-way ANOVA on wintering

benthic algae also showed differences among treatments(p < 0.0001) (Table 1). Mean wintering algal Chla concen-trations in lakes impacted by harvesting (23.30 mg·m–2) andwildfire (29.06 mg·m–2) were higher than in reference lakes(14.57 mg·m–2), but the difference between harvested andburnt lakes was not significant (p < 0.05, Tukey’s test) (Ta-ble 1). In 1998, mean Chla concentrations in the littoralzone were higher in winter than in summer, for any treat-ment (reference,p = 0.0008; harvested,p = 0.0001; burnt,p = 0.0014;t test).

Biomass budgetIn the subset of 16 lakes for which littoral algae were

sampled, the comparison of littoral versus pelagic algal bio-mass (Chla) per unit area of photic zone was estimatedfrom the average summer biomass of 1997 and 1998 com-bined. When both communities were compared, differenceswere only found in perturbed lakes in which littoral Chlawas higher than pelagic Chla (Fig. 5). The means of the ra-tios of benthic to pelagic algal biomass were 1.31 in refer-ence lakes, 2.56 in harvested lakes, and 2.74 in burnt lakes(Fig. 5).

Physical and chemical variables influencing algal ChlaPelagic algal Chla could be predicted by TP, which ex-

plained 48% of the partial variance, followed byePAR anddissolved inorganic N (DIN = NO3 + NO2 + NH4) (datafrom Carignan et al. 2000), which explained 6 and 4% of thevariance, respectively (Table 2). The same variables enteredinto the biomass regression model, but the predictive powerin this model was slightly weaker for TP, but not forePARand DIN, than contribute slightly more to the total variance(Table 2). The relationship between TP and Chla in per-turbed lakes is shown in Fig. 6A, and for the same set oflakes, the relationship between the ratio of Chla to TP andePAR is shown in Fig. 6B.

Catchment characteristics as well as the area of cut orburnt watershed that predicted the physical and chemicalwater changes in our lakes (Carignan et al. 1999), also pre-dicted changes in pelagic biomass (Fig. 7). For phyto-plankton biomass, the fraction of the watershed perturbedover the sum of lake surface areas in the watershed ex-plained 57% of the variance in Chla.

TP was the best predictor of benthic algal Chla concen-trations in summer, explaining 34% of the variance, fol-lowed by NO3 and DOC, which accounted for 17 and 11%of the variance, respectively (Table 2). TP as well as DOCalso showed a relationship with winter benthic algal Chla,but total N (TN) explained a stronger percentage of the vari-ance (Table 2).

Variables influencing algal taxon compositionIn general, correlations between phytoplankton taxon

composition and environmental variables were significant,although correlation coefficients were low. Cryptophyta andBacillariophyceae (diatoms) showed weak positive correla-tions with TP (r 2 = 0.29, p = 0.0038 andr 2 = 0.34, p =0.0007, respectively). Bacillariophyta was also correlatedwith DIN (r 2 = 0.5070,p < 0.0001) and Cryptophyta withePAR (r 2 = 0.3998, p = 0.0001). Chrysophyceae, cyano-bacteria, and Chlorophyceae showed weakly negative rela-

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140 Can. J. Fish. Aquat. Sci. Vol. 57(Suppl. 2), 2000

Fig. 5. Average summer means ± SE of benthic algal (solid bars)and pelagic algal (open bars) Chla concentrations per unit areain reference and perturbed lakes. Different letters indicate meandifferences (p < 0.05; t test) within sets of lakes.



tionships with nutrients, including both TP (r 2 = –0.20,p =0.0472,r 2 = –0.42,p < 0.0001, andr 2 = –0.22,p = 0.0289,respectively) and DIN (r 2 = –0.39,p = 0.0001,r 2 = –0.21,p = 0.0417, andr 2 = –0.22,p = 0.0344, respectively). Thenegative correlations of these taxa with water column nutri-ents suggests that they were not directly controlled by nutri-ents.

Discussion

Algal responses to watershed perturbationsPhytoplankton biomass (Chla and biomass) as well as the

dominant taxa in the reference lakes of our study regionwere characteristic of pristine oligotrophic Canadian Shieldlakes (Armstrong and Schindler 1971; Kling and Holgrem1972). Within perturbed watersheds, and particularly inburnt lakes, volumetric biomass increased to mesotrophiclevels (Chla > 3 mg·m–3, biomass > 3000 mg wet weight·m–3) with maximum Chl a concentrations greater than5 mg·m–3. Moreover, increases in taxa such as diatoms,which are more characteristic of boreal enriched environ-ments (Eloranta 1986), only occurred in burnt lakes. Benthicalgal biomass responses to watershed perturbations followedthe same pattern as for phytoplankton; the response was,however, magnified relative to the pelagic community, par-ticularly in burnt lakes. In burnt lakes, benthic algal Chla ashigh as 100 mg·m–2 was measured 2 years after perturbation,while in references lakes, the highest Chla measured wasapproximately 30 mg·m–2. Other studies have also reportedconsiderable increases in benthic algal biomass followingboreal forest disturbance ranging from 21- to 46-fold inrivers and from two to fourfold in lakes compared with ref-erence systems (Holopainen and Huttunen 1992; Rask et al.1998). In our study, benthic algal Chla in the perturbedlakes was only two to three times higher than in the refer-

ence lakes and is thus comparable with boreal lakeresponses (Rask et al. 1998).

Even 3 years after perturbations, algal communities in thelakes may not have reached a steady state. Long-term re-sponses to disturbances have been reported in aquatic eco-systems following watershed perturbations, such as wildfires(Wright 1976; Minshall et al. 1997). During our 3-yearstudy, the greatest response was measured in the second yearfollowing disturbances, and the sign of the response was dif-ferent in relation to the type of disturbance. Biomass in-creased and major taxa shifts were observed in burnt lakes,whereas biomass decreased in harvested lakes. These inter-annual differential changes in algal biomass and (or) speciescomposition in lakes with perturbed watersheds could be ex-plained by variability in chemical fluxes and light penetra-tion. Higher runoff was measured in 1997 compared with1996 and 1998 in the region of the Gouin Reservoir(Lamontagne et al. 2000). Nutrient loading was equivalent inboth types of perturbations for 1996 and 1998, and it was50% higher than in reference lakes. The increase in P load-ing in 1997 was 25% higher in burnt lakes than in harvestedlakes (S. Lamontagne, GRIL, Université de Montréal, C.P.6128, Montreal, QC H3C 3J7, Canada, personal communica-tion). However, the large difference in chemical loading be-tween harvested and burnt lakes was a result of the largeincrease in DOC (50–80%) in harvested watersheds, whichwas not observed in burnt watersheds (S. Lamontagne,GRIL, Université de Montréal, C.P. 6128, Montreal, QCH3C 3J7, Canada, personal communication). Higher DOCconcentrations in harvested lakes strongly influenced lightpenetration in our study lakes (Carignan et al. 2000). Thus,low light transmission could explain, for any year, the smallresponse of algal biomass in harvested lakes as comparedwith burnt lakes, and this in spite of similar nutrient load-ings. Moreover, light differences between treatments could

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(a) log10(Chl a) = –0.168±0.061 + 0.700±0.090log(TP) – 0.322±0.113log(ePAR) + 0.074±0.022log(DIN)r 2

partial 0.48 0.06 0.04

SSE = 0.75 r 2adjusted= 0.565 F = 42.1 p < 0.0001 n = 96

(b) log10(biomassa) = 1.951±0.139 + 1.270±0.204log(TP) – 0.925±0.255log(ePAR) + 0.220±0.053log(DIN)r 2

partial 0.31 0.10 0.07


(c) log10(Chl a) = –0.414±0.320 + 0.650±0.320log(TP) + 0.169±0.068log(NO3) + 0.847±0.517log(DOC)r 2

partial 0.34 0.17 0.11


(d) log10(Chl a) = –0.109±0.288 + 1.320±0.275log(TP)

SSE = 0.16 r 2 = 0.622 p = 0.0003 n = 16(e) log10(Chl a) = –3.414±0.856 + 1.931±0.353log(TN)

SSE = 0.15 r 2 = 0.681 p < 0.0001 n = 16(f) log10(Chl a) = 0.095±0.225 + 1.407±0.303log(DOC)

SSE = 0.16 r 2 = 0.606 p = 0.0004 n = 16

Note: Physical and chemical data from Carignan et al. (2000).p = p > F; biomass is wet weight;ePAR is the availableradiation light extinction coefficient.

Table 2. Multiple or simple regression models of yearly averages of algal biomass and physical and chemicalvariables of lakes (independent variables): (a) phytoplankton Chla, (b) phytoplankton wet weight biomass,(c) summer benthic algal Chla, and (d–f) winter benthic algal Chla.



explain the lack of difference in pelagic algal Chla per unitarea between treatments. Low light, when nutrients areavailable, could limit algal primary production and hencebiomass (Petersen et al. 1997). For a similar increase in nu-trients in perturbed lakes, differences inePAR could also ex-plain differences in the algal taxa responses, which arediscussed below.

Relationship between algal responses and physical andchemical lake characteristics

TP was the best predictor of pelagic algal biomass in thestudy lakes. For a given P concentration, lakes in burnt wa-tersheds produced more Chla per unit TP than harvestedlakes. It is well known that P limits phytoplankton produc-tion in boreal Canadian Shield lakes (Schindler 1974) and,as mentioned before, watershed perturbation in our study in-creased TP export by twofold as compared with referenceslakes (Lamontagne et al. 2000). Nitrogen also seemed tohave had some control on pelagic algal biomass responses. Itis known that N plus P additions yielded the greatest bio-mass response as compared with additions of one or the

other alone (Axler et al. 1994). Thus, in our burnt lakes, in-creases in P and N loading increased algal biomass per unitvolume. Harvesting increased TP concentration but not inor-ganic N concentrations (Carignan et al. 2000), and thus,lower N could explain the lower algal biomass in harvestedlakes as compared with burnt lakes. However, lower lightpenetration could also explain the lower Chla concentra-tions per unit biomass in harvested lakes in relation to burntlakes.

The fact than N showed stronger relationships with ben-thic rather than pelagic algal Chla could be explained by thedifferences in nutrient availability in the littoral as comparedwith the pelagic zones. Phosphorus release from littoralepilimnetic sediments could support benthic algal growth,while pelagic algae rely on P dissolved in the water column(Carlton and Wetzel 1988). While the export of N increasedin both harvested and burnt watersheds, N was primarily ex-ported as NO3 in burnt lakes and probably as dissolved or-ganic N in harvested lakes (Lamontagne et al. 2000). HigherNO3 fluxes into the lakes could thereby help to explain thehigher algal benthic biomass in burnt lakes. The positive re-lationship between DOC and benthic algae biomass seen inour study suggests that DOC could enhance littoral algalgrowth, as was observed in an experimental study by Vine-brooke and Leavitt (1998). In our lakes, DOC regulates un-derwater spectral irradiance, but we do not know if it alsoinfluences lake chemistry. DOC can complex metals and en-zymes that regulate P availability (Boavida and Wetzel1998) or, conversely, can act as a source of labile organicsubstrates, such as P and dissolved inorganic C (Moran andZepp 1997). DOC is also a vector for nutrients such as Nand P (Lamontagne et al. 2000). Although in our study, wedid not determine the proportion of nutrients that enter thelake in the dissolved organic form, it is possible that in bo-real catchments, it is the more important form of nutrients(Lamontagne et al. 2000). In our multiple regressions, P ex-

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Fig. 6. (A) Relationship between 3-year average pelagic algal Chlain perturbed lakes (harvested (diamonds) and burnt (squares)) and TP(log(Chl a) = –0.407±0.233 + 0.789±0.224log(TP);r 2 = 0.47,F =12.38,p > F = 0.0034,n = 16). (B) Relationship between the Chla/TP ratio in perturbed lakes andePAR (Chl a/TP = 0.135±0.014 –0.107±0.036log(ePAR); r 2 = 0.38,F = 8.60,p > F = 0.0109,n = 16).

Fig. 7. Relationship (solid line) and 95% confidence intervals(dotted lines) between phytoplankton Chla in perturbed lakes(harvested (diamonds) and burnt (squares)) and the fraction ofthe watershed perturbed over the sum of lake surface areas in thewatershed (FA) (log(Chla) = 0.412±0.036 + 0.024±0.006FA;r 2 = 0.570,F = 18.53,p > F = 0.0007,n = 16).



plained a greater percentage of benthic algal biomass insummer as compared with winter. The wintering algae wereexposed to spring runoff, which contributes a high percent-age of the annual runoff in our lakes, as, in general, in tem-perate regions (Likens 1985). Thus, in spring, when UVradiation is higher than in late summer, photolysis of DOCcould reactivate the alkaline phosphatase binding withhumic substances, thereby promoting P availability for litto-ral algae (Boavida and Wetzel 1998).

It has been observed that catchment variables can explainthe variability of Chla almost as well as that of TP (Duarteand Kalff 1989). In our study lakes, some of the easily mea-sured catchment characteristics, such as the area of cut orburnt watershed, predict the physical and chemical changesin our lakes (Carignan et al. 1999) as well as changes in pe-lagic biomass. The highest Chla concentrations occurred inburnt lakes (p = 0.001,t test), particularly in the FP regionwhere the 1995 wildfire hit more severely the lake’s shore-line. This relationship allowed for the prediction of eitherlake water quality or the response of primary producers andcould be a useful tool for managers.

Changes in pelagic algal community associated withenvironmental variables

Moderate enrichments, such as those observed in the per-turbed lakes, may also explain increases or changes in algalcommunity taxa (Eloranta 1986; Willén et al. 1990). Diatomincreases in burnt lakes could be expected as a result of Pand, to a lesser extent, N augmentations in these lakes(Jansson et al. 1996; Watson et al. 1997). Cryptophyta andChrysophyceae also increased in perturbed lakes, but theseincreases cannot be explained by nutrients with which thebiomass of these two taxa were weakly or negatively corre-lated. Weak correlations of these taxa or curvilinear re-sponses with TP increases have been reported and attributedto morphological diversity, differential herbivory, and mix-ing regime (Watson et al. 1997). In our study, the relativelystrong correlation of nutrients with diatoms and the weak orabsent relationship of nutrients with Cryptophyta andChrysophyceae cannot be explained by differential grazingor mixing. Thus, in all taxa, the species present in our lakeswere edible, and no strong relationship was found betweenphytoplankton and herbivorous zooplankton (Patoine et al.2000), and the thermal characteristics of these lakes did notdiffer (Carignan et al. 2000).

Dominance of Cryptophyta and Chrysophyceae, repre-senting almost 90% of the biomass, has been found in borealbrown-water lakes (Kling and Holgrem 1972; Willén et al.1990), and Cryptophyceae increases have been measured inbrooks of harvested watersheds (Holopainen and Huttunen1992; Lepistö and Saura 1998). In our study, the negative re-lationship between nutrients and Chrysophyceae and lightpenetration and Cryptophyta suggests that the species pres-ent in our lakes are capable of obtaining their energy viameans other than photoautotrophy, e.g., phagotrophy, hetero-trophy, or photoheterotrophy (Pick and Caron 1987). In Ca-nadian Shield lakes, stronger phagotrophic particle uptakehas been demonstrated in some Chrysophyceae species, andphagocytosis was the dominant path for energy flow whenphotosynthesis was light limited (Bird and Kalff 1987).Mixotrophy has also been reported in Cryptophyta (Tranvik

et al. 1989). Thus, the different responses of taxa observedin our study in relation to the type of perturbation, namelythe increase in photoautotrophic algae in burnt lakes but notin harvested lakes, may be associated with differences inlight penetration.

Biomass budgetThe littoral versus pelagic biomass (Chla) per unit of sur-

face area indicated a stronger response of littoral communi-ties to pertubations. Since no other studies investigating theimpact of watershed disturbance on lakes have simulta-neously measured the response of pelagic and benthic algae,no comparisons with the literature were possible. However,it is known that in humic oligotrophic lakes, phytoplanktonand benthic algae compete for nutrients (Hansson 1990).Nutrient loading in the littoral zone is less diluted than in thepelagic water column, and the efficiency of nutrient utiliza-tion, retention, and recycling is much greater among closelyaggregated benthic algal–microbial communities than in thepelagic zone (Wetzel 1996). These littoral characteristicslead to maximal resource utilization and productivity per ar-eal unit. In nine perturbed lakes, in which benthic algal bio-mass was measured, nutrients in the water column wererelatively abundant compared with unperturbed lakes, sug-gesting that competition for nutrients between littoral andpelagic zones was weaker in relation to reference lakes.However, due to differences in the concentration of DOC,the amount of light reaching the substrates differed betweentreatments (Carignan et al. 2000), with 25% of surfaceirradiance (ePAR) in reference lakes, 14% in harvested lakes,and 10% in burnt lakes. Low light penetration in perturbedlakes could increase the Chla content of cells (Ahlgren1970), but mean Chla per algal cell in phytoplankton wasequal in reference and harvested lakes. For benthic algae,however, Chla per unit cell was higher in burnt lakes (p <0.05) than in harvested or reference lakes (D. Planas et al.,unpublished data). Consequently, we cannot exclude the pos-sibility that higher Chla concentrations in benthic algae inburnt lakes are related to lower light conditions as comparedwith reference lakes. For the burnt lakes in which benthic al-gae were studied, the 1997 and 1998 mean euphotic zone tomixing depth ratio (Zph/Zmix) was lower than 1 (Zph/Zmix =0.796 ± 0.106) and less (p < 0.05) than in the reference lakes(Zph/Zmix = 1.31 ± 0.101), while it was intermediate in har-vested lakes (Zph/Zmix = 0.992 ± 0.106).

In conclusion, increases in nutrient loading as a conse-quence of watershed perturbation may modify algal biomassand induce changes in the pelagic algal community struc-ture. The littoral algae showed a greater response to pertur-bations than pelagic algae. Responses were somewhatdifferent for lakes on harvested watersheds as compared withlakes in burnt watersheds. Lack of riparian vegetation insome burnt watersheds may explain why biomass and algalcomposition responses were greater in burnt lakes than inharvested lakes. Three years after perturbation, algal bio-mass may still have not reached a steady state. At present,results indicate that TP is the main nutrient driving thesechanges, although total pelagic productivity in the perturbedlakes could be impaired by low light penetration. Changes inspecies composition among perturbed lakes did not inducethe development of inedible algae in the pelagic zone. How-

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ever, because N seems to play some role and if N exportdecreases through time and P continues to leach from thewatershed, we can expect the development of toxic cyano-bacteria. Decreases in biomass associated with light limita-tion or changes in algal quality due to changes in N/P ratioscould negatively affect fish communities in these pristineboreal lakes. Although we could not discount the influenceof natural interannual variability on our results because pre-perturbation data from these lakes were not available, ourstudy does indicate that simple empirical models incorporat-ing perturbation scenarios and variables such as lake area,which is easily measured from maps, could be used in thedevelopment of sustainable harvesting practices.

Acknowledgments

The project was supported by a research grant from theSustainable Forest Management Network of Centers of Ex-cellence and the Natural Sciences and Engineering ResearchCouncil of Canada. The Ministry of Natural Resources ofQuébec, Cartons Saint-Laurent, Donohue, and Kruger pro-vided land use information. We thank P. D’Arcy (Universitéde Montréal) for coordination of the field activities and N.Armstrong, S. Lamontagne, S. Montgomery, and C. Vis fortheir valuable comments on the manuscript.

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