Defi ning the ecological status of small forest lakes using multiple biological quality elements and palaeolimnological analysis
Janne Alahuhta1, 2, *, Kari-Matti Vuori2, Seppo Hellsten2, Marko Järvinen2,Mikko Olin3, Martti Rask4 and Arja Palomäki5
With 6 fi gures, 3 tables and 1 appendix
Abstract: A new classifi cation system compliant with the EU’s Water Framework Directive (WFD) was employed to assess the ecological status of six small forest lakes differently affected by catchment forestry. The classifi ca-tion is based on metrics involving four biological quality elements (phytoplankton, aquatic macrophytes, benthic macroinvertebrates and fi sh) and their nationally defi ned reference and class boundary values. The classifi cation evidence obtained from single metrics and quality elements, on the “One-out, All-out” principle, which establishes status according to the weakest measure, was compared with the integrated classifi cation system used in the Finnish national status assessments. The national classifi cation system harmonizes the individual measures by scoring and expresses overall status class as a median score across quality elements. In addition, because the amount of refer-ence data for this lake type was limited, palaeolimnological analyses were conducted to determine lake-specifi c changes during past decades. The results demonstrated that individual metrics and quality elements may result in highly variable classifi cations, and consequently pessimistic ecological estimates, if the One-out, All-out principle is applied. It is concluded that the integration of evidence from multiple quality elements evens out their variability and results in more realistic status assessments in small humic boreal forest lakes.
The European Water Framework Directive (WFD) sets strict environmental quality objectives for water bodies and demands integrated assessment of environmental pressures and risks of failing to meet these objectives
(European Communities 2000). The WFD quality objectives rely on ecological classifi cations based on biological quality elements: phytoplankton, aquatic macrophytes and phytobenthos, benthic macroinver-tebrates and fi sh. There have been a number of stud-ies that have considered lake classifi cations based on
Authors’ addresses:1 University of Oulu, Department of Geography, P. O. Box 3000, FIN-90014 University of Oulu, Finland.2 Finnish Environment Institute, Research Department, Research Programme for Integrated River Basin Management PO Box 413,
FIN-90014 Oulun yliopisto, Finland.3 University of Helsinki, Faculty of Biosciences, Department of Biological and Environmental Sciences, P. O. Box 56, FIN-00014
University of Helsinki, Finland.4 Finnish Game and Fisheries Research Institute, Evo Game and Fisheries Research Station, FIN-16970 Evo, Finland.5 University of Jyväskylä, Institute for Environmental Research, P. O. Box 35, FIN-40014 University of Jyväskylä, Finland.
single biological quality elements (e.g. White & Irvine 2003, Gassner et al. 2003, Lepistö et al. 2004, Stelzer et al. 2005), but classifi cations based on the integrated use of multiple quality elements have been less fre-quently studied (see e.g. Søndergaard et al. 2005, Free et al. 2007). There is an ongoing debate concerning whether WFD classifi cation status should be defi ned according to an integrated assessment of different bio-logical quality elements or on the “One-out, All-out” (OoAo) principle, which defi nes the status according to the weakest element or parameter. The Finnish sys-tem for assessment of the ecological quality (FinEQ) is based on integration of evidence from multiple qual-ity elements. Comparative studies on the performance of these two approaches are largely lacking, although signifi cant risks of misclassifi cation have been identi-fi ed when using the OoAo principle for Danish water bodies (Søndergaard et al. 2005).
According to the WFD, ecological status will be assessed using the reference condition approach (Eu-ropean Communities 2003), where reference condi-tions are defi ned separately for each lake type. How-
ever, because some lake types have low numbers of reference sites, reliable determination of such refer-ence conditions may be problematic. Also, the current lake typology may oversimplify the true variability in catchment and lake characteristics, so that inherently very different kinds of lakes may be grouped into a single lake type, resulting in high variability in the biological metrics within one type. The use of tem-porally limited data also makes the defi nition of refer-ence conditions more vulnerable to misinterpretation, due to year-to-year changes in biological variables. Studies of pristine small lakes show that biological communities may have high variability in biological metrics among lakes, even if they seem to be alike and belong to the same lake type (e.g. Magnuson et al. 2004 and references therein, Rusak et al. 2008). In such cases ecological classifi cation can be complex even under relatively pristine conditions and use of the site’s own palaeolimnological data could yield more realistic assessment results. Reconstruction of lake-specifi c reference status using diatoms is well justifi ed in palaeolimnology (Bennion & Battarbee 2007).
Fig. 1. Locations of the study lakes in the Oulujoki-Iijoki river basin district (dark grey) in the central part of Finland. A priorireference lakes are shown as black dots and impacted lakes as grey dots.
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205Ecological status of forest lakes
Small boreal forest lakes (< 5 km2) are potentially complex classifi cation cases, as lakes individual prop-erties, such as size, retention time, morphometrics, water colour and specifi c habitat characteristics of these systems, have a considerable infl uence on the ecological metrics. These natural factors may obscure the infl uence of anthropogenic impacts such as forest harvesting, drainage and soil preparation. These silvi-cultural activities are common sources of pressure on boreal headwater lakes, although their impact on the ecological status of these lakes appears to be variable. Impacts on individual water bodies depend on the na-ture and intensity of the forestry practices adopted, the magnitude and duration of nutrient loading, the response dynamics of the biological quality elements and the individual characteristics of the recipient lakes (e.g. Lepistö & Saura 1998, Rask et al. 1998, Turkia et al. 1998).
This case study is part of a wider research effort, examining the performance of different classifi cation practices in the Finnish water bodies. The aim of this study was to assess the ecological status of small hum-
ic boreal lakes subjected to catchment forestry and to compare the responses of multiple biological classifi -cation variables to the forestry-induced loading of nu-trients and organic matter. More specifi cally, our pur-pose was to compare the assessment evidence of single metrics and quality elements employed on the OoAo principle, with the integrated classifi cation system that is used in the Finnish national status assessments. Fur-thermore, because the classifi cation criteria for many small lake types are based on a limited number of ref-erence lakes, the applicability of palaeolimnological diatom analysis for supporting reference status defi ni-tions was also studied.
Material and methods
Classifi ed lakes and conducted surveys
We studied six small humic boreal lakes belonging to the Oulu-joki river basin in the Kainuu region of Eastern Finland in sum-mer 2005 (Fig. 1). These sites included two lakes considered to present reference conditions, i.e. to be close to pristine con-
Table 1. General properties of the study lakes and their catchments. The average depths of the impacted lakes are estimated from the depth gradients. Water chemistry properties are averages for the epilimnion in summer 2005 (3 samples: June, July, August–September). * = including drained peatland.
A priori reference lakes Impacted lakes
Saari-Kiekki Itäjärvi Iso Akonjärvi Pirttijärvi Roukajärvi Matalanjärvi
ditions, based on catchment land use data, water quality and expert judgements. Since thorough evidence on the land use history of these lakes is lacking, they are hereafter referred to as a priori reference lakes. The four other lakes were assessed to be affected by forestry practices such as peatland drainage and clear cutting (Table 1). The proportion of forest and peatland was as high as possible and other land cover types (e.g. agricul-tural land and settlements) were absent or minimal. Moreover, in all cases peatlands should make up at least 35 % of the catch-ment area. The lakes represent the type designated as “shallow, highly humic lakes” in the Finnish lake typology (surface area < 5 km2, colour > 90 mg Pt l–1, average depth < 3 m, Table 2). Whilst the estimated average depth of Lake Itäjärvi is slightly over 3 metres, the depth is less than this over the majority of the lake area. Classifi cation of the ecological status of the selected lakes was based on criteria established using the national refer-ence lake database (n = 6–173, depending on the metric used, Table 2). Selection of the reference lakes followed the criteria established in the EU intercalibration exercise (European Com-munities 2003). In Finland the main criteria included: catch-ment agricultural land less than 10 %, no major point source pollution, hydromorphological alterations or other signifi cant pressures affecting biotic communities.
We sampled phytoplankton, aquatic macrophytes, benthic macroinvertebrates and fi sh by standardized methods in each lake, and used a core-top-and-bottom technique for diatom-based palaeolimnological analysis (Hall & Smol 1995). The species composition of the phytoplankton was identifi ed from the pooled surface water samples (0–2 m) taken with a Ruttner sampler in June, July and at the end of August or beginning of September (CEN 15204). Aquatic macrophytes were surveyed at the end of August by a main belt transect method using 10 transects, according to Leka & Kanninen (2003). In addition to real hydrophytes, other growth forms such as helophytes and some shore plants were also included. A vegetation index (V), combining species abundances and frequencies (Toivonen & Huttunen 1995), was calculated based on Ilmavirta & Toivonen (1986). Five replicate samples of benthic macroinvertebrates were taken from the deepest points in the lakes at the end of Au-gust or beginning of September using an Ekman sampler (SFS 5076) at depths varying from 1.9 to 9.5 metres (Table 1). Chi-ronomids were identifi ed to species level based on Wiederholm (1983). Replicate samples were pooled and the Benthic Quality Index was defi ned according to Wiederholm (1980). For the fi sh data, stratifi ed random sampling with Nordic benthic gillnets (Olin et al. 2004) was performed in June or August. The total fi shing effort was 5 gillnet nights in each lake.
The palaeolimnological analysis was based on stratigraphic sediment samples taken from the deepest areas of the lakes with a Limnos gravity corer in April 2005. The average core length was 30–40 cm, and subsamples from the top and bottom 2 cm were analysed (Table 1). The samples were analysed for diatoms following standardized procedures (Battarbee 1986). Total phosphorus concentration (TP), pH and total organic car-bon (TOC) were reconstructed using most closely comparable calibration data in the European Diatom Database (pH: the Surface Waters Acidifi cation Programme, with data sets from Scandinavia and UK, employing the weighted averaging calcu-lation method; TP and TOC: combined TP and TOC data sets and LWWA calculation method). The distributions and compo-sitions of the diatom assemblages were analysed statistically by Detrended Correspondence Analysis (Hill 1979) and the simi-larity between the present and past diatom communities was
estimated according to Overpeck et al. (1985) and Flower et al. (1997). Sedimentation rates were estimated by soot particle analysis (Renberg & Wik 1984, Hynynen 2007), and the sedi-ment samples were dated to confi rm that the bottom subsamples represented a decade prior to the 1950s, which was considered to present a period before signifi cant increase in modern for-estry activities, particularly drainage of peatlands (see Peltomaa 2007). Lake Matalanjärvi was excluded from further analyses, because the sediment was non-stratifi ed due to the shallowness of the lake (maximum depth 1.9 m).
Classifi cation schemes and reference condition
Classifi cation metrics, reference values and class boundaries for each quality element are presented in Table 2. The WFD demands expression of the status class in terms of an Ecological Quality Ratio (EQR), i.e. a ratio between the observed biologi-cal metric value and the reference value (European Communi-ties 2000). The calculated EQR values are divided into classes: high, good, moderate, poor and bad. We calculated EQR values by dividing the observed metric values by the reference values, or vice versa if the metric values increase with anthropogenic pressure. For the phytoplankton metric, the proportion of harm-ful cyanobacteria, the class boundaries were partly derived from the European intercalibration results (European Commu-nities 2007).
The Finnish classifi cation system (FinEQ) is based on the integration of multiple metrics and biological quality elements. This integrated classifi cation system harmonizes the individual metrics and quality elements by scoring them and express-ing the overall calculated status class as a median score value across all quality elements. In the scoring system high status class (H) values are given a score of 0.9, good status (G) values 0.7, moderate (M) 0.5, poor (P) 0.3 and bad (B) 0.1, respective-ly. Medians of the scores across all metrics are then classifi ed according to the following class boundaries: high > 0.8, good ≤ 0.8, moderate ≤ 0.6, poor ≤ 0.4 and bad ≤ 0.2. This calculated status class is then further evaluated by using weight-of-evi-dence approach commonly used in ecological risk assessments (Lowell et al. 2000, Burton et al. 2002), in which quality ele-ments and monitoring results are weighted according to their relevance and reliability and the strength of their associations with environmental pressures.
Phytoplankton biomass (June–August), the concentrations of chlorophyll-a (June–September) and the proportion of harm-ful cyanobacteria (order Nostocales and the genera Microcystis, Planktothrix and Woronichinia) (July–August) were used as classifi cation metrics for phytoplankton. The number of ref-erence lakes was 173 for chlorophyll-a, but only 9 for phyto-plankton biomass and the proportion of cyanobacteria (Table 2). Also, the phytoplankton metric data represented in most cases only a limited number of measurements and all from a single year. Due to the shortage of reference lake data, the re-sults of the EU the WFD intercalibration work in the Nordic Geographical Intercalibration Group (NGIG) were used to de-fi ne class boundaries for a-chlorophyll and cyanobacteria in the lake type studied here (European Communities 2008).
Three classifi cation metrics were determined for aquatic macrophytes: the number of species specifi c to this lake type as a percentage of the total number of species (Leka et al. 2008), the reference index (RI) (Stelzer et al. 2005, Penning et al. 2008) and Percent Model Affi nity (PMA) (Novak & Bode 1992). The Finnish classifi cation of macrophytes is based on
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208 Janne Alahuhta et al.
data for a set of 773 lakes or ponds collected from the litera-ture by Leka et al. (2008). Due to the marked latitudinal pattern in macrophyte species distribution (Heino & Toivonen 2008), separate sets of reference conditions are defi ned for northern and southern lakes. North-south boundary is situated at Oulu-joki river basin, where all lakes situated more than 120 m a.s.l. belong to northern types and lakes situated less than 120 m a.s.l. belong to southern types. The classifi cation of our lakes was based on the reference set for northern Finland, which consists of 11 lakes (Table 2).
The benthic macroinvertebrate classifi cation was based on a modifi ed Bottom Quality Index (BQI, Wiederholm 1980), from which the value one was subtracted (BQI -1) to obtain the ra-tio. Because BQI was observed to be highly dependent on the sampling depth, the expected reference values were obtained using a regression model based on 141 reference lakes in the national zoobenthos database (Table 2, Jyväsjärvi et al., unpub-lished data)
The ecological classifi cation of fi sh included 5 metrics. To-tal biomass and number per unit effort (BPUE and NPUE), and biomass proportion of cyprinids and piscivorous (> 15 cm) per-cids (Cyprinid%, Piscivore%) were calculated from the gillnet data (Sairanen et al. 2007). The indicator species (Indicators) were based on expert judgements, according to the occurrence of natural populations of certain sensitive species or the nor-mality of the population structure of perch, pike and roach. The national reference data set covered the fi sh in 100 lakes rang-ing in area from 2 to 7900 ha, six of which were classifi ed as belonging to the shallow, highly humic lake type. These data were used to determine type-specifi c reference values and class boundaries for BPUE and NPUE, and Piscivore%. Due to the lack of Cyprinid% data, the reference lakes of three nearest types were combined to obtain a set of 12 lakes (Table 2).
Results
The biological surveys of the study lakes refl ected mostly a typical community structure of small humic and naturally acidic forest lakes. Chrysophytes, dia-toms and the raphidophyte Gonyostomum semen dom-inated phytoplankton community. The phytoplankton biomasses represented mainly oligo-mesotrophic con-ditions, with certain exceptions such as the blooms of the cyanobacteria Aphanizomenon yezoense in August in the Lake Roukajärvi. Macrophyte species varied in number between 22–31 with a predominance of oligo-mesotrophic (Carex lasiocarpa, Isoetes echinospora,Menyanthes trifoliata, Nymphae tetragona and Fonti-nalis antipyretica) and mesotrophic indicator species (Caltha palustris, Potamogeton gramineus, Sparga-nium gramineus, Calliergon cordifolium, Scapaniaundulata and Warnstorfi a exannulata) and indifferent species (e.g. Carex rostrata, Equisetum fl uviatile, Lysi-machia thyrsifl ora, Menyanthes trifoliata, Phragmites australis, Potentilla palustris). The macroinvertebrate species numbered between 8 and 14, except in the Lake Pirttijärvi, where the phantom midge Chaoborus fl avi-
cans was the only species found. The macroinverte-brate communities were dominated by the chironomid species Tanytarsus lugens, Zalutschia zalutschicola, Procladius spp., Chironomus anthracinus, C. sali-narius and Microtendipes pedellus, tubifi cid worms and Pisidium clams. The number of fi sh species varied between 4 and 6 and gillnet catches were dominated by perch (Perca fl uviatilis) and roach (Rutilus rutilus)in all the lakes.
The classifi cation results for individual metrics were highly variable both in the a priori reference and the impact lakes (Fig. 2, Appendix 1). When viewing the classifi cations across all the metrics and quality el-ements, a priori reference and impacted lakes were in less than good status in six cases out of the 24 and 12 cases out of 48, respectively. Hence, 25 % of the indi-vidual metrics indicated less than good status in both a priori reference and impacted lakes. One phyto-plankton metric (proportion of harmful Cyanophyta), two macrophyte metrics (percentage of type-specifi c species and PMA) and two fi sh metrics (NPUE and Piscivore%) indicated less than good status in the apriori reference lakes, as compared with one phyto-plankton metric (proportion of harmful Cyanophyta),
Fig. 2. Counts of classifi cation scores for different biological quality elements across all metrics (for the list of metrics, see Table 2) in the reference (black triangles) and impacted (grey triangles) lakes. The boundary between good and moderate sta-tus is a score of 0.6 (broken line).eschweizerbartxxx author
209Ecological status of forest lakes
two macrophyte metrics (percentage of type-specifi c species and PMA), the macroinvertebrate metric BQI-1 and one fi sh metric (BPUE) in the impacted lakes. Besides, the individual metrics based on the richness (proportion of type-specifi c macrophyte species, RI, BQI and indicator fi sh species) and abundance (incl. biomass) data did not vary between a priori reference and impacted lakes (Mann-Whitney U-test, p = 0.66, p = 0.1, respectively).
The element-specifi c classifi cation revealed mainly high or good status lakes (Fig. 3). There were no statis-tically signifi cant differences in the median classifi ca-tion score values between a priori reference and im-pacted lakes (Mann-Whitney U-test, p = 0.923). The most consistent exception was the macroinvertebrate BQI-1, which indicated poor or bad status for three impacted lakes (Fig. 4). Lake Pirttijärvi was scored as bad because of the total lack of sediment-inhabiting zoobenthos. The median macrophyte status score for apriori reference Lake Itäjärvi was moderate.
The integrated lake-specifi c status classifi cations based on the median status scores indicated good status in all the lakes except a priori reference lake Itäjärvi and impacted lake Iso Akonjärvi, which had a high ecological status based on all the quality elements ex-
cept for macrophytes (Appendix 1, Fig. 5). Although the element-specifi c scores varied substantially, the difference was evened out in the integrated assessment (median for all the lakes: 0.75). If the OoAo principle had been applied, the ecological status of a priori ref-erence lakes would have been poor (Saari-Kiekki) and moderate (Itäjärvi). The lakes Itäjärvi and Iso Akon-järvi would have been in moderate status (median for all the lakes: 0.2) and other impacted lakes would have been ranked as poor or bad (Fig. 5, Table 3).
The palaeolimnological samples yielded altogether 129 diatom taxa, with the number of taxa in each sub-sample varying from 42 to 63. In the studied lakes taxa varied between 50-70 (Table 1). Planktonic species (Aulacoseira sp., Fragilaria sp. and Tabellaria sp.) were dominant throughout, except in shallow Lake Matalanjärvi, where the sediment was non-stratifi ed and the epiphytic species dominated almost complete-ly. Therefore, Lake Matalanjärvi was excluded from the palaeolimnological analysis.
The palaeolimnological results indicated temporal changes in diatom community structure in all the lakes analysed (Fig. 6, Table 3). The bottom sediment sub-samples represented a time prior to the 1950s when the intensity of forest drainage was low in Finland
Fig. 4. Classifi cation scores across all metrics (for the list of metrics, see Table 2) for the study lakes: reference (black trian-gles) and impacted (grey triangles) triangles. The boundary be-tween good and moderate status is a score of 0.6 (broken line).
Fig. 3. Status score averages (± SE) for each quality elements in reference (black columns) and impacted lakes (grey columns). The boundary between good and moderate status is a score of 0.6 (broken line).
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210 Janne Alahuhta et al.
(Peltomaa 2007). However, the bottom samples of our study lakes did not cluster very close to each other in the DCA ordination space. One obvious pattern was that the bottom samples of the shallowest lakes (Saari-Kiekki, Iso Akonjärvi and Roukajärvi) clustered clos-est to each other, while the deepest lakes (Itäjärvi and Pirttijärvi) clustered on the opposite edge of the or-dination space. Of the two a priori reference lakes, major changes have occurred in Lake Itäjärvi, where the similarity between the bottom and surface diatom communities was less than 50 %. In the other a priori
reference lake, Saari-Kiekki, the diatom community had remained quite similar over the years (similarity 80 %). The similarity in the impacted lakes Iso Akon-järvi and Pirttijärvi was about 60 %, and that in Lake Roukajärvi was 70 %.
The diatom-based reconstructions indicated that the changes in the a priori reference lakes had been variable (Table 3). The TP level, pH and TOC in Lake Saari-Kiekki had been constant or slightly decreased from a prior 1950s to the present. In the other a pri-ori reference lake, Itäjärvi, the reconstruction results
Fig. 5. Cumulative median status scores for the study lakes. Status score value of each element is stacked for every study lake. Values above the bars are status score medians calculated for all the quality elements (left) and the status scores of the weakest quality element according to the “One-out, All-out” (OoAo) principle (right).
Fig. 6. DCA ordination of diatom spe-cies (no transformation, rare species reduced in importance). SK = Saari-Kiekki, IT = Itäjärvi, IA = Iso Akon-järvi, PI = Pirttijärvi and RO = Rouka-järvi. Surface refers to the core surface layer (present situation, 2005) and bot-tom to the core bottom layer (past situ-ation, before the 1950s). a) Cumulative percentage variance and b) length of gradient of species data of axis 1 and 2: a) 33.3 and 42.6, and b) 2.08 and 1.39, respectively. Sum of all unconstrained eigenvalues was 1.255. Lake Matalan-järvi was excluded from the ordination because non-stratifi ed sediment sample prevented reliable palaeolimnological analysis.
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showed increase in TP and TOC values. Diatom anal-yses in the lakes affected by catchment forestry re-vealed that the environmental status of Lake Iso Akon-järvi had improved (decreased values). The TP level, pH and TOC had increased in the lakes Pirttijärvi and Roukajärvi. We also tested the metrics of Omnidia programme (Lecointe et al. 1993) in our diatom-based assessments, but the results were ecologically unsound due to geographically limited data set (Central Eu-rope) and because the metrics are designed for river ecosystems.
Discussion
There was a striking difference between the integrated status assessments based on median scores calculated across the quality elements and the status class based on the weakest quality element as proposed according to the OoAo principle. The integrated Finnish national approach assessed the a priori reference lakes Saari-Kiekki and Itäjärvi to be of good or high ecological status, whereas with the OoAo principle they would have been classifi ed as only of moderate or good sta-tus, respectively. Moreover, the ecological status of all impacted lakes was good or high in terms of median status scores calculated across the quality elements, whereas with the OoAo principle their status would have been mainly poor or bad. Considering that, in general, our biological surveys indicated conditions typical of small humic boreal forest lakes, the OoAo assessment appears to be unrealistic for use in the as-sessment of these lakes. Also, the relatively good water quality in all lakes (Table 1) indicates that no dramat-ic environmental changes have taken place recently. However, the credibility and weight-of-evidence of
each classifi cation metric should be carefully assessed before defi ning the status class.
Shallowness, high water colour, acidity, reduced light penetration, organic sediment accumulation and consequent oxygen depletion during stratifi ed periods all have signifi cant effects on the biological communi-ties of humic lakes (e.g. Keskitalo & Eloranta 1999, Johnson & Goedkoop 2002). These characteristics dominated in the study lakes and infl uenced on the classifi cation process of single-metric categories. The biological assemblages that we found were typical of acid, humic boreal forest lakes (e.g. Ilmavirta 1982, Rintanen 1996, Rask et al. 2000, Willen 2003), sug-gesting that the impact of forestry activities was no more than moderate.
There are several problems with classifying the ecological status of shallow, highly humic lakes. First, the BQI metric, which downgraded the status of im-pacted lakes most sharply when the OoAo principle was adopted, may be considered inadequate and un-reliable for small shallow lakes (Johnson 1998). In such lakes oxygen depletion and dominance by the tolerant species Chironomus anthracinus and C. plu-mosus, which rank lowest in the scoring system of Wiederholm (1980), are natural phenomena, so that the low BQI values refl ect natural conditions rather than human impact in our lakes. The use of BQI for classifying macroinvertebrates in most shallow lakes is questionable, and alternative metrics based on lit-toral sampling should be developed.
Second, the proportion of type-specifi c macro-phyte species, PMA of macrophytes and NPUE of fi sh have inherent properties that impede status class interpretation. According to some preliminary results (e.g. Sutela et al. 2007, Leka et al. 2008), these fi sh and macrophyte-based metrics seem to be rather in-
Table 3. Summary of classifi cation outputs using the different approaches adopted here: “One-out All-out” (single metric, single quality element) and integrated classifi cation (FinEQ). Diatom-based reconstructions of TP (μg l–1), pH and TOC (mg l–1) are derived from European Diatom Database. See Methods for details of the European Diatom Database reconstruction data sets (EDDI 2008). Status abbreviations a) in ecological classifi cation: H = high, G = good, M = moderate, P = poor, B = bad, and b) in palaeolimnological reconstructions: S = surface subsample, B = bottom subsample. * Lake Matalanjärvi was excluded from the palaeolimnological analysis due to non-stratifi ed sediments.
Lake/method Single biol. Single FinEQ Diatom TP (μg l–1) pH
TOC(mg l–1)metric BQE similarity %
S B S B S B
Saari-Kiekki P G G 80 34.2 38.1 6.6 6.9 10.7 11.2Itäjärvi M M H < 50 33.8 4.3 6.2 6.1 10.8 6.9Iso Akonjärvi M G H 60 47.7 57.5 6.4 6.7 5.5 8.2Pirttijärvi B B G 60 23.5 8.5 6.2 6.0 9.8 8.7Roukajärvi B P G 70 39.6 15.9 6.8 5.9 9.1 7.5Matalanjärvi B B G * * * * * * *
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sensitive to changes induced in shallow highly humic lakes by catchment forestry. This may be due to the simple biological community structure of such lakes. The PMA index, for example, indicated the best status for Lake Roukajärvi among the study lakes, though the macrophyte assemblages of the lake had shown early signs of eutrophication in a separate bay area probably due to the local impact of a small farm (Ala-huhta, personal observation). Furthermore, PMA is the only macrophyte metric utilising also abundance estimates, which are vulnerable to erroneous reference values due to large variation between observers (Moe et al. 2008). The core species of both fi shes and mac-rophytes are tolerant of environmental fl uctuations, including hypolimnetic oxygen depletion and nutri-ent level changes, respectively (e.g. Willemsen 1980, Spence 1982, Toivonen & Huttunen 1995, Tammi et al. 1999). The core fi sh species also show considerable natural variations both in abundance and population structure, which may be refl ected in a corresponding variability in ecological classifi cation.
Third, shallow highly humic lakes represent a di-verse group of water bodies, and hence more profound research on factors affecting background variation of biological metrics is required within this lake type. The national reference data set may still be inadequate for establishment of reliable reference conditions es-pecially in the case of macrophytes (11 reference sites), phytoplankton biomass and species composi-tion (9 reference sites) and most of the fi sh metrics (6 reference sites). The limited number of reference lakes may result in biased reference values and class bound-aries. Division of this lake type into subtypes might be one solution. It is probable, however, that fi nding enough appropriate sets of reference conditions for each lake type will always be a problem (e.g. Moss et al. 2003, Stelzer et al. 2005). The most appropriate reference data set is achieved using several different lakes instead of extensive monitoring of few sites, be-cause large spatial components often overstep tempo-ral variation especially between different geographical regions (Rusak et al. 2002). However, assessment of temporal changes should also be appreciated.
All in all, given that the weigh-of-evidence of sin-gle metrics (BQI, PMA, NPUE) or quality elements may be questionable, the integrated classifi cation prin-ciple seems to provide more stable and reliable results than the OoAo principle in small boreal humic lakes. Søndergaard et al. (2005) have similarly suggested that if the natural variability in metric values is high, an integrated, generalized classifi cation principle is well justifi ed.
The palaeolimnological results indicated a high (natural) variability within the lake type, which was demonstrated especially between a priori reference lakes and bottom sediment samples representing ref-erence condition in all the study lakes. For example, the diatom communities have changed considerably in Lake Itäjärvi. The reference state of the study lakes may have been somewhat different from the beginning due to the inherent physiographic and limnological differences. Besides, we lack accurate information on the land use history of our study catchments, though, the general intensifi cation of forestry (drainages, clear cuttings) started generally only after the 1950s in Fin-land. However, the past utilization of forests for in-tensive tar production dates back to the 1700s in Fen-noscandia (Hjulström et al. 2006, van der Linden et al. 2008) and it was the major form of land use also in the Kainuu region until the early 1900s.
Implementation of palaeolimnological analysis in ecological classifi cation still faces several problems. First, shallowness of studied lake types and that of re-lated non-stratifi ed sediments often prevent the use of palaeolimnological evidence. We found, for instance, that the sediments of Lake Matalanjärvi were com-pletely non-stratifi ed. Second, calibration data sets are geographically limited and lack data on boreal humic lake types. In this study the diatom reconstructions yielded somewhat unrealistic results, demonstrated by higher reconstructed variable values compared to the observed ones (Table 3). These reconstructions were based on database including calibration data from Cen-tral Europe and the northernmost Finland (Lapland). Hence, there is a clear need for more calibration data from the highly humic lake type. In Finland separate diatom data sets are often in the possession of individ-ual researchers. These data sets should preferably be made available for public access, e.g. to current EDDI database (EDDI 2008), to improve the implementation of palaeolimnological methods in status assessment of our boreal humic lakes. Third, narrowly employed pal-aeolimnological analysis can hinder the weighting of gained evidence. For practical reasons, we were able to date our bottom sediment samples (soot particle analysis) only back to prior 1950s. We think that more thorough palaeolimnological studies, including the sediment layer chronology dating back to more than hundred years ago, would better reveal potential past changes due to human activities. Further, also pollen, cladoceran and chironomid analysis in addition to the diatom analysis would improve the usability of palae-olimnological analysis. Such studies may demonstrate sharp decadal changes in trophic status of small lakes
eschweizerbartxxx author
213Ecological status of forest lakes
as a response to recovery of forests from past land use activities (e.g. Alliksaar et al. 2005).
Considering the relation of palaeolimnological re-sults to the two classifi cation principles, the OoAo clas-sifi cation was more in line with the palaeolimnological evidence in Lake Itäjärvi, where diatom similarity (Ta-ble 3), diatom reconstructions and macrophyte OoAo classifi cations (Appendix 1) indicated lowered status. Hence, the status class of this lake should be down-graded to moderate or good. In two cases the OoAo classifi cations (single BQE) clearly disagreed (down-grading status to bad/poor) and FinEQ agreed (status good) with the palaeolimnological evidence on diatom similarity (Pirttijärvi and Roukajärvi, Table 3). Evi-dence from physical characteristics of sediment sup-port the results of OoAo classifi cation by indicating a peak in organic loading in lakes Itäjärvi and Pirttijärvi in the past (Palomäki 2005). However, considering the low weight-of-evidence of the weakest metrics and the current pressure-impact evidence, it seems exagger-ated that the OoAo classifi cation would have any fi rm causal relations to some past external loading taken place decades ago.
Concluding remarks
The present results support the use of an integrated, weight-of-evidence based approach for the ecological classifi cation of polyhumic boreal lakes rather than the OoAo system employing single biological quality ele-ments or metrics. The use of generalising approach is further emphasized by the challenges still to be over-come in the classifi cation process related to unsuit-ability of certain single-metrics for highly humic lake type, natural variation of biological groups within this lake type and lack of reference sites. The choice of the most relevant classifi cation method is a crucial ques-tion for practical water management, because of the demands for programmes of measures in water bodies defi ned to be less than good ecological status.
The use of palaeolimnological evidence can be benefi cial to assess the credibility of classifi cation evi-dence derived from biological surveys. These analyses may provide lake-specifi c evidence on the magnitude and trends of changes in the environmental condi-tions over several decades. However, non-stratifi ed sediments often prevent the use of palaeolimnological analysis in shallow lakes and the palaeolimnological evidence from deep lakes should be treated with care when the calibration data is geographically limited. It is sound to utilize a wide range of analyses and weight the importance and reliability of these results in the case of limited sampling. Furthermore, as our case of
the highly humic boreal lake type demonstrates, the palaeolimnological reconstructions may lack credibil-ity if the calibration database is poorly representative for the lake type in question.
Acknowledgements
This study was funded by the EU Watersketch project (Interreg IIIB, Baltic Sea Region). Janne Alahuhta has received personal grants from the Multidisciplinary Environmental Graduate Net School of the University of Oulu, the Finnish Cultural Foun-dation, the North Ostrobothnia Regional Fund of the Finnish Cultural Foundation and the Tauno Tönning Foundation. The authors thank three anonymous reviewers and Miska Luoto for their comments on the manuscript. The fi eld team of Kainuu Regional Environment Centre and especially Pekka K. Korho-nen are thanked for sampling most of the fi eld data. The English of this manuscript was revised by Malcolm Hicks.
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