FINAL REPORT ON THE RELEVANT SYSTEM OF INDICATORS AND CRITERIA FOR EVALUATING THE ECOLOGICAL STATUS OF A VERY LARGE NONSTRATIFIED LAKE AND ITS RIVER BASIN IN WFD CONTEXT
Compiled by
Tiina Nõges
Tartu University Estonia
Deliverable D3b July, 2003
Integrated Strategies for the Management of Transboundary Waters on the Eastern European fringe – The pilot study of Lake Peipsi and its drainage basin
Title: Final report on the relevant system of indicators and criteria for evaluating the ecological status of a very large nonstratified lake and its river basin in WFD context Authors: Tiina Nõges, Peeter Nõges, Kalle Olli, Meelis Tambets, Markus Vetemaa, Taavi Virro (Tartu University, Estonia) Enn Loigu,Ülle Leisk, Kristjan Piirimäe, Tiiu Alliksaar, Atko Heinsalu (Tallinn Technical University, Estonia) Külli Kangur, Juta Haberman, Marina Haldna, Andu Kangur, Peeter Kangur, Reet Laugaste, Anu Milius, Helle Mäemets, Tõnu Möls, Henn Timm, Rein Järvekülg, Peeter Pall, Malle Viik, Kai Piirsoo, Sirje Vilbaste, Tiiu Trei (Estonian Agricultural University, Estonia)
Report No. No. of pages Sponsor Dissemination Contract No.
D3b 96 pages level:
public +2 The European Commission under the Fifth EVK1-CT-2000- Framework Programme and contributing to the Appendixes implementation of the Key Action ’Sustainable 00076 Management and Quality of Water’ within the Energy, Environment and Sustainable Development
ABSTRACT: The ultimate goal of the present work is to establish an indicator system for rivers in L. Peipsi watershed and the lake itself which is in line with the requirements of the WFD. The typificaiton of rivers was based on type of baserock, size of watershed, and flow velocity of the water, giving 20 potential types. Alltogether 41 river samples (108 samples for macrozoobenthos) were considered as in undisturbed state with respect to biological variables. 32 potential biological indicators (quality elements) were evaluated. Reference values were finally proposed for 20 biological indicators. These reference values are interpreted as the demarkation line between high and good status. After intercalibration, which is necessary to find the values for good and satisfacotry classes, the reference values will be assigned a relative value 100%, against which all lower qualtiy classes will be related to find type specific comparison data for some classes of Estonian rivers. The status of rivers is best described by combined hydrochemical subindex system, which, by applying different weights, takes into account biological oxygen demand, pH, oxygen saturation, ammonium, total P and N. The biological indicator systems are more complex and a single index is not available at the moment to summerize the ecological status. Thus, the available data is divided into subchapters, which each gives an overview on the presnent state of art in asessing the ecological status based on individual biological indicators. Following changes of Estonian national river monitoring programme were suggested: (a) implementation of Polluter Pays Principle; (b) better monitoring of small rivers; (c) development of background monitoring; (d) content of dissolved oxygen, content of ammonia, biochemical oxygen demand, total nitrogen and total phosphorus should be constantly measured within the surveillance- monitoring programme aiming at evaluating the ecological status of the water body; (e) monitoring should focus on rivers where chemical quality is below “good”; (f) if changes in significant pollution factors have appeared then additional monitoring is necessary to estimate long-term changes as well as spatial and temporal variability; (g) suggested methodology for monitoring of flux stations would maintain the total number of 12 samples per year but springtime requires 4–6 samples, autumn flood period 3 – 4 while summer and winter time low water periods require only 1 – 2 samples per year; (h) including the routine calculation of nutrient loading into the river monitoring program. For L. Peipsi increased phosphorus loading was considered the most serious anthropogenic pressure to the ecosystem of. To calculate the reference conditions for total phosphorus concentration we used the morpho-edaphic index (MEI). As a quality objective for L. Peipsi we set the reference TP concentration multiplied by 1.5 that corresponded to the lower quartile of long-term TP measurements. Similar approach was used to set the quality class borders for biological quality criteria based on phytoplankton, which were selected on the basis of having significant correlations with TP. According to present hydrochemical and phytoplankton data the ecological quality of L. Peipsi is mainly moderate. According to the macrophyte and fish indices the status is intermediate between good and moderate while zooplankton and benthic macroinveretbrates indicate ‘good’ ecological status. The following suggestions for adjustment of L. Peipsi monitoring program should be made: (a) including the monitoring of macrovegetation; (b) including the monitoring of abundance, biomass and age structure of all fish species; (c) the current monitoring program of macrozoobenthos in open-water areas should be continued. It gives valuable data for estimation of fish food and enables to watch year- to-year variability of abundance and biomass that is not possible to achieve in another way. A simple reorganisation of open-water sampling sites could give us both the data of fish food (at the same level), and also the estimation of ecological quality of different parts of lake. Studies of shallow areas with handnet samples are recommended for the last purpose.
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CONTENTS
1. REVIEW OF THE REQUESTS OF EC WATER FRAMEWORK DIRECIVE (P. NÕGES)...... 5 2. SHORT REVIEW OF ENVIRONMENTAL INDICATORS APPLIED IN LAKES AND RIVERS (T. NÕGES)...... 8 3. ASSESSMENT OF THE REFERENCE CONDITIONS ...... 11 3.1. ASSESSMENT OF REFERENCE CONDITIONS FOR THE RIVERS IN LAKE PEIPSI REGION (E. LOIGU, K. PIIRIMÄE, Ü. LEISK)...... 11 3.2. ASSESSMENT OF THE REFERENCE CONDITIONS FOR LAKE PEIPSI (P. NÕGES) ...... 12 3.3. PALEOLIMNOLOGICAL STUDIES OF LAKE PEIPSI (A. HEINSALU & T. ALLIKSAAR)14 4. INDICATORS AND CRITERIA TO ASSESS THE ECOLOGICAL STATUS OF RIVERS IN THE LAKE PEIPSI CATCHMENT AREA (K. OLLI, E. LOIGU, Ü. LEISK, K. PIIRIMÄE, H. TIMM)...... 18 4.1. TYPOLOGY OF THE RIVERS IN LAKE PEIPSI REGION...... 18 4.2. INDICATORS AND CRITERIA FOR ASSESSMENT OF ECOLOGICAL STATUS OF RIVERS...... 20 4.2.1. CRITERIA OF CHEMICAL AND HYDROMORPHOLOGICAL STATUS...... 22 4.2.2. CRITERIA OF ECOLOGICAL STATUS...... 24 5. ECOLOGICAL STATUS OF RIVERS IN L. PEIPSI BASIN ACCORDING TO THE REQUESTS OF WFD (K. OLLI, E. LOIGU, Ü. LEISK, K. PIIRIMÄE, H. TIMM)...... 29 5.1.HYDROCHEMISTRY...... 30 5.1.1. POINT SOURCES...... 30 5.1.2. NON-POINT SOURCES...... 33 5.1.3. SOURCE APPORTIONMENT...... 34 5.1.4. CHEMICAL STATUS...... 35 5.1.5. POLLUTION LOAD TO L. PEIPSI...... 36 5.2. BIOLOGICAL STATUS OF L. PEIPSI RIVER BASIN...... 37 5.2.1. BACTERIA...... 37 5.2.2. PHYTOPLANKTON AND CHLOROPHYLL...... 38 5.2.3. BENTHIC DIATOMS...... 39 5.2.4. MACROZOOBENTHOS...... 39 5.2.5. MACROVEGETATION...... 41 6. INDICATORS AND CRITERIA FOR ASSESSMENT OF ECOLOGICAL STATUS OF LAKE PEIPSI...... 42 6.1. CHEMICAL AND PHYSICAL PROPERTIES AND PHYTOPLANKTON (P. NÕGES, R. LAUGASTE, T. NÕGES)...... 42 6.2. ZOOPLANKTON (T.VIRRO & J.HABERMAN)...... 46 6.3. ZOOPLANKTON/PHYTOPLANKTON RATIO (J. HABERMAN & R.LAUGASTE)...... 48 6.4. MACROPHYTES (H. MÄEMETS)...... 50 6.5. BENTHIC INVERETEBRATES (H. TIMM & K. KANGUR)...... 52 6.6. FISHES (A. JÄRVALT, A. KANGUR, P. KANGUR, M. VETEMAA, M. TAMBETS)...... 56 7. ECOLOGICAL STATUS OF L. PEIPSI ACCORDING TO THE REQUESTS OF WFD...... 64 7.1. WATER QUALITY ASSESSMENT (K. KANGUR, A. KANGUR, J. HABERMAN, M. HALDNA, P. KANGUR, R. LAUGASTE, A. MILIUS, H. MÄEMETS, T. MÖLS)...... 64 7.2. EXPERT JUDGEMENT OF ECOLOGICAL QUALITY (P. NÕGES, J. HABERMAN, A. JÄRVALT, K. KANGUR, A. KANGUR, R. LAUGASTE, H. MÄEMETS, T. NÕGES)...... 68 8. SUGGESTIONS FOR ADJUSTMENT OF NATIONAL MONITORING PROGRAM OF THE RIVERS IN LAKE PEIPSI REGION ACCORDING TO WFD REQUIREMENTS...... 70 8.1. PRESENT SITUATION OF ESTONIAN RIVER MONITORING (T. NÕGES)...... 70 8.2. SUGGESTIONS OF THE GROUP OF HYDROCHEMICAL MONITORING OF ESTONIAN RIVERS AT TALLINN TECHNICAL UNIVERSITY (E. LOIGU)...... 70 8.2.1. MONITORING OF POINT SOURCE POLLUTION 72 8.2.2. MONITORING OF THE ECOLOGICAL STATUS OF RIVERS...... 74 8.2.3. MONITORING OF FLUX STATIONS...... 75 8.3. TYPOLOGY OF RIVERS IN L. PEIPSI-VÕRTSJÄRV RIVER BASIN, SUGGESTED BY RIVER BIOLOGY WORKING GROUP (R. JÄRVEKÜLG, P. PALL, K. PIIRSOO, H. TIMM, S. VILBASTE, T. TREI & M. VIIK)...... 76 9. SUGGESTIONS FOR ADJUSTMENT OF NATIONAL MONITORING PROGRAM OF LAKE PEIPSI ACCORDING TO WFD REQUIREMENTS (T. NÕGES, H. TIMM)...... 82 10. LITERATURE ...... 84 APPENDIX 1...... 92 APPENDIX 2...... 96
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1. REVIEW OF THE REQUESTS OF EC WATER FRAMEWORK DIRECIVE (P. NÕGES) In December 2000 the Official Journal of European Community published a document entitled “Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the field of water policy” that is widely known as the Water Framework Directive (WFD). This Directive aims at maintaining and improving the aquatic environment in the European Community. The objective of achieving good water status should be pursued for each river basin, so that measures in respect of surface water and groundwaters belonging to the same ecological, hydrological and hydrogeological system are coordinated. Key elements of the Directive are: • Protecting of all waters. The WFD covers all waters including inland waters (surface water and groundwater), transitional waters and coastal waters up to one sea mile. For the chemical status WFD covers also territorial waters which may extend up to 12 sea miles from the territorial baseline of a Member State. • Good quality of all waters to be achieved by 2015. Artificial and heavily modified waters should achieve a good ecological potential by that time. • Use of a combined approach for the control of pollution, setting emission limit values and water quality objectives. • Involvment of citizens and stakeholders in making decisions on water management.
The concept of the WFD is to coordinate all other measures included in earlier directives on drinking and bathing water, urban waste water, nitrates, industrial discharges and hazardous substances. In order to achieve this, also economic instruments like economic analysis and the principle “polluter pays” will be used to promote prudent use of water. The WFD has set ambitious objectives and a demanding timetable for implementation: 2003 - transposition of the WFD into national legislation; 2003 - identification of river basin districts (RBD); 2004 - analysis of waters within the RBD-s including • analysis of its characteristics, • designation of heavily modified and artificial waterbodies, • registers of protected areas, • a review of the impact of human activity on the status of surface waters and on groundwater, • an economic analysis of water use, 2006 - monitoring programs for all waterbody categories should be operational and giving information on • flows and levels of surface waters, • ecological and chemical quality of surface waters, • amount and quality of groundwaters. 2006 - intercalibration of reference conditions, quality criteria and standardisation of methods for sampling and analysis; 2009 - the River Basin Management Plans should be published; 2012 - program of measures for pollution control in RBD-s should be operational; 2015 - the environmental objectives of WFD should be achieved.
Common principles are needed in order to coordinate Member States' efforts to contribute to the control of transboundary water problems. Most river basins in Europe are shared river basins (Fig.1.1). Several large river basins such as Danube, Elbe and Odra river basins are shared between a number of Member States.
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For river basins extending beyond the boundaries of the Community, Member States should endeavour to ensure the appropriate coordination with the relevant non-member States1. This Directive is to contribute to the implementation of Community obligations under international conventions on water protection and management, notably the United Nations Convention on the protection and use of transboundary water courses and international lakes, approved by Council Decision 95/308/EC (1) and any succeeding agreements on its application.
Fig. 1.1. International river basins in In order to avoid wrong applications because of the complexity of requirements EC has worked out a number of guidance documents, which will be examined in 14 pilot river basins in Europe: • Identification of water bodies • Water and Economics • Analysis of pressure and impacts • Heavily modified and artificial water bodies • Coastal and transitional waters - ecological assessment • Intercalibration - site selection and process • Monitoring • Geographic Information System - GIS • Public participation
Three more guidance documents are under preparation and will be finalised during the first half of 2003: • Rivers and lakes - ecological assessment • Planning process • Wetlands.
The WFD was not part of the "aquis communautaire" negotiated for accession in 2004 but for later accessions (i.e. Bulgaria, Romania and others). However, all 10 Candidate Countries will
1Article 35
6 implement the WFD without a transitional period, that means, in accordance to the timetable given in the Directive. In parallel, the existing water legislation is transposed and implemented in the accession process.
One of the key working areas for 2003 and 2006 will be the intercalibration of quality criteria for waterbodies that is planned simultaneously with the development of typology and monitoring system. Intercalibration is aimed to achieve consistent interpretation of the class boundary definitions, i.e. to show how 'slight', 'moderate', 'major' and 'severe' alterations from reference conditions should be quantified.
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2. SHORT REVIEW OF ENVIRONMENTAL INDICATORS APPLIED IN LAKES AND RIVERS (T. NÕGES)
The most widely accepted framework for environmental indicators is based on PSR (Pressure- State-Response) chains. Chosen indicators reflect the relationship between environmental effects, and/or their causes and measures taken. A more sophisticated version is called DPSIR (Driving Forces-Pressure-State-Impact-Response). PSR/DPSR systems are used by OECD, Nordic Council of Ministers, United Nations, World Bank, EU Environmental Agency etc. (Wiederholm, 2000).
The environmental status can be assessed in 2 ways (Wiederholm, 2000): • Assessment of current conditions. Usually a 5-level scale is used where Class 1 indicates conditions at which there are no known negative effects on the environment and/or human health. The remaining classes indicate effects of increasing magnitude. Class 5 includes conditions leading to the most serious negative effects. Wherever possible, the scale is correlated with effects on the ecosystem (‘effect-related classification’); in some cases the ‘statistical classification’ is applied, based on a statistical distribution of national data. In latter case there is no well- defined relationship between effects and class limits. • Deviations from reference values The extent of human impact is estimated by calculating deviations from reference values. Deviation=Measured value/reference value Extent of deviation is usually classified on a 5-level scale. Class 1 includes conditions with little or no deviation, Class 5 indicates very significant impact from local sources.
Macrophytes Aquatic plants play an important role in lake metabolism and form an essential part of the habitat of many organisms. The diversity and abundance of plants is affected by eutrophication, acidification and other changes in the environment. Both individual species and entire types of plant community can serve as indicators of the state of ecosystem (Wiederholm, 2000). In general, macrophytes are regarded as sensitive to important anthropogenic pressures like physical deterioration and disturbances. Macrophytes are also long-lived sessile organisms and may therefore integrate anthropogenic pressures over long time periods.
Periphyton Periphytic algae are of limited value in assessing the ecological status of lakes. They reflect not just the general properties of the lakes (what is needed), but also local habitat environment in the littoral (Eloranta, 2001).
Phytoplankton Phytoplankton is an essential part of lake food chains as a producer of organic matter and oxygen. Planktonic algae serve as food for zooplankton, benthic fauna and fish and excrete dissolved organic matter which is consumed by microbes. Algae respond rapidly to changes in water quality because of their rapid reproduction rate. Changes in the physical and chemical status of the water can be identified after only a week or so in the form of changes in the balance of species and species abundance. Lasting water quality changes can be discerned in the plankton community from one vegetative period to another (Wiederholm, 2000).
Macroinvertebrates Benthic macroinvertebrate species are differentially sensitive to many biotic and abiotic factors in their environment. Consequently, macroinvertebrate community structure has
8 commonly been used as an indicator of the condition of an aquatic system. Biotic index systems have been developed, which give numerical scores to specific indicator organisms at a particular taxonomic level (Armitage et al., 1983; Skriver et al., 2001). Such organisms have specific requirements in terms of physical and chemical conditions. Changes in presence/absence, numbers, morphology, physiology or behaviour of these organisms can indicate that the physical and/or chemical conditions are outside their preferred limits. Presence of numerous families of highly tolerant organisms usually indicates poor water quality. For temperate zone, there exist several well-developed guides how to use macroinvertebrates as bioindicators (Johnson, 1999, Gerritsen et al., 1998, Barbour et al., 1998, Mandaville, 2001).
Fish As a considerable amount of information is known about the life cycles and habitat requirements of individual fish species, the structure and function of fish communities is a useful tool for assessing the changes in the habitat. In Sweden lake and river assessment is based on the following parameters, which are weighed together to give an overall index (Wiederholm, 2000).
Parameter Lakes Water- courses Number of native fish species X* X* Species diversity of native fish species based on weight X* Relative biomass of native fish species (weight/effort) X* Relative number of individuals of native fish species X* (number/effort) Proportion of piscivorous percids out of the total catch based on X* weight Proportion of cyprinids out of the total catch based on weight X Presence of species and stages sensitive to acidification X Proportion of biomass of species tolerant to low oxygen X concentrations Proportion of biomass of alien species X X Biomass of native fish species X* Number of individuals of native fish species X* Proportion of salmonids based on number X* Reproduction of native salmonids X* Proportion of alien species based on number X X* - parameters used to assess current conditions X - parameters used to assess deviation from reference values
Finding a reference value. In many cases good reference values are lacking in the literature. The reference values for different parameters are obtained in different ways, depending on the availability of data. In some cases it is possible to use the reference stations. In others, collated data from environmental monitoring or from specific studies have been used. As regards fish, in Sweden calculations have been made using national or supra-regional data bases in their entirety (Wiederholm, 2000). For some parameters it is impossible to set any reference values at all. Here, assessments can only be made using a state scale (current conditions). A range of measures from paleolimnology to modelling and expert judgement has been suggested (e.g. Jeppensen et al., 2001). Even more, new terms like "ecological potential" have been
9 introduced, partly to replace the more demanding "ecological status". In parallel, the goals have shifted from good ecological status to "optimal ecological condition", particularly in heavily populated countries like the Netherlands.
An overview how the existing national monitoring systems in EU member states fit with the requirements of the WFD is available on the web page: http://www- nrciws.slu.se/REFCOND/document.htm. This document includs graphic information on following topics: • Chosen classification system in member states (system A or B, decided or probable); • Preliminary number of water body types in member states for lakes and rivers; • Elements included in existing classification systems for lakes and rivers; • Existing national or international standard methods for lakes and rivers; • Methods compatible with WFD for lakes and rivers; • Methods for establishing reference conditions for lakes and rivers.
A detailed literature review of indicators and criteria applied in assessment of ecological status of rivers and lakes is given in MANTRA-East working paper by Nõges et al. (2001) For lakes, the review includes the methodology of the calculation of pristine phosphorus concentration; pristine phytoplankton biomass and chlorophyll concentration values for a variety of lakes; assessment tables for determining the lake status using the measured nutrient concentrations as well as phytoplankton, zooplankton, macroinertebrate and fish indices. For rivers, the review includes assessment tables for determining the river status using the measured nutrient concentrations, macroinvertebrate and fish indices.
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3. ASSESSMENT OF REFERENCE CONDITIONS
3.1. ASSESSMENT OF REFERENCE CONDITIONS FOR RIVERS IN LAKE PEIPSI REGION (E. LOIGU, K. PIIRIMÄE, Ü. LEISK) Establishing values for the reference conditions will be one of the major tasks in implementing the WFD. The reference conditions were derived directly from the national monitoring data collected from rivers without direct human impact. For determination of reference values in polluted rivers we may use the relation between an indicator and runoff. If there is a statistically significant correlation between a pollutant (BOD, phosphorus etc.) and runoff, the correlation can be described as hyperbolic curve y = a/Q + b, where a – amount of pollutant in river (g), Q – runoff (m3/s), y - concentration of indicator (g/m3) and b - reference value (g/m3) (Fig. 3.1). During increasing runoff conditions the concentration of pollutant decreases constantly due to dilution and approaches asymptotically, the reference value of the water quality indicators (Loigu & Leisk, 1989).
Emajõgi, Kavastu, BOD , 1992-1996 Emajõgi - Kavastu, 1992-1996 7
7.0 100% 6.0 y = 42.11/x + 2.57 r = 0.64 80% /l
2 5.0 4.0 60% , mgO
7 3.0 40% b
BOD 2.0 20% 1.0 0% 0.0 01234567 0 50 100 150 mgO /l Q, m³/s 2
Fig. 3.1. Relationship between runoff and Fig. 3.2. Cumulative curve of BOD7 in BOD7 concentration in Emajõgi River Emajõgi River If correlation between runoff and water quality parameters is absent, we recommend to charecterise pristine water quality on the basis of the data of the ‘reference’ rivers that are considered not to be influenced by human activities. Another method is used to find reference values for indicators, which are not strongly correlated with runoff, e.g. nitrogen. In these cases, the reference value can be estimated based on cumulative curve of all measured values of the water quality parameter in the region (Fig. 3.2.) Depending on whether the concentration of a substance is increased or decreased by human activity, the 10th or 90th percentile of values will characterize background condition of the parameter in the region. The percentile distribution of a parameter can be estimated with additional field investigations.
For dissolved oxygen concentration, percentiles are most reliably calculated assuming a normal distribution. For normal distribution the percentiles are calculated according to the National Rivers Authority (1994): q = m −1.2816s where: q - 10th percentile m - mean s- standard deviation For BOD7, ammonium, total phosphorus and nitrogen concentrations percentiles are most reliably calculated assuming a log-normal distribution. The values of m and s are thus converted to the values for the logarithm of the data (M and S respectively) using the method of moments:
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m M = ln 1+ sm22/
Ss=+ln(1 22/ m) where M and S are estimates of the mean and standard deviation for the logarithm of the data. The estimate of the 90-percentile (q) is calculated using:
q = e(.)MS+ 12816
3.2. ASSESSMENT OF THE REFERENCE CONDITIONS FOR LAKE PEIPSI (P. NÕGES) There are five principal ways how type-specific reference conditions can be derived. In case there is large number of lakes of the same type available in the area, reference conditions can be derived on a spatial basis choosing some of the best preserved sites as the reference. If it is impossible, reference conditions can be found using either historical records or paleolimnological data from the site. If the pressure-response relationships are well formalised, reference conditions for minimum pressure conditions can be modelled. Finally, if none of these methods is applicable, reference conditions can be established on the basis of expert opinion. Problems with large lakes According to Estonian national lake typology worked out by Mäemets (1974) and complemented by Ott & Kõiv (1999), Lake Peipsi belongs to large, well-mixed, hard-water eutrophic type. Increased nutrient loading is clearly the most important anthropogenic pressure to L. Peipsi. As the ecosystem is phosphorus-limited (nitrogen limitation can be easily overcome by nitrogen fixers providing a nitrogen source also for nitrogen non-fixing species) the increase of P loading can be considered as the most dangerous anthropogenic impact. That is why looking for potential quality parameters we focused on variables correlating with phosphorus loads. The commercial fisheries has also a specific impact on species composition and age structure of fishes that affects in a specific way also the composition of lower trophic levels like zooplankton and benthic invertebrates. However, in the present study the overall effect of fisheries has not been considered in water quality parameters. The number of lakes of a comparable size to that of L. Peipsi is small. Other large lakes in the region, lakes Ladoga and Onega, are incomparably deeper. Large lakes in Sweden have a totally different catchment geology and ionic composition. Among European large lakes of the same latitude range L. Ilmen is may be the most similar to L. Peipsi, but is much more shallow (mean depth 2.8 m). The location outside EU and the rather poor level of investigation also complicates the use of this lake as a reference. That means that there are no reference sites available for L. Peipsi and other approaches should be used to work out reference conditions. L. Peipsi is undoubtedly among the best investigated lakes in Estonia. The first picture of the ecosystem was given already by K. E. von Baer who studied the fishery of the lake already in 1851-52. The first overview of plankton of the lake was given by N. Samsonov (1914) whos work describes the plankton community in 1909 and 1912. Recent paleolimnological studies (Heinsalu et al., 2003) characterise the changes in the lake during the last 130 years. As there have been agricultural activities in the catchment for centuries and overfishing was considered a serious threat to the fish stock already by Baer it rises the question, how far in history one should go to find reference conditions. As increased phosphorus loading was considered the most serious and most direct anthropogenic pressure,
12 we tried to find out reference conditions first of all for this element and parameters correlating with it. Most of chemical and biological parameters of lakes that are used for quality assessment have a more or less established seasonal regularity with values changing often more than by one order of magnitude. These seasonal differences should inevitably be taken into account while working out quality criteria. Another question arises in connection with natural water level fluctuations that may have a similar effect to the ecosystem as changes in anthropogenic nutrient loading. In the 1930s, zebra mussel (Dreissena polymorpha) invaded L. Peipsi. According Timm et al. (2001) zebra mussel is now spread over the major part of the lake bottom and has become the species of the highest biomass (≈ 700 g/m2) in the lake exceeding even that of the whole phytoplankton. As the spreading of zebra mussel has been probably facilitated by human, it rises the question how the exotic species should be handled, as a natural phenomenon that could be included also to reference conditions or as a kind of anthropogenic pressure?
Reference conditions for total phosphorus concentration To find out reference conditions for total phosphorus concentration, we used the morpho- edaphic index (MEI) by Vighi & Chiaudani (1985) calculated as the ratio between alkalinity (in meq/l) and mean depth of the lake (in m). We obtained the following value of MEI for L. Peipsi: MEIalk = 2.51/ 8.3 = 0.30
For comparison, the corresponding value was calculated for L. Võrtsjärv:
MEIalk = 3.04/ 2.8 = 1.07
The above mentioned authors found a highly significant correlation between the MEI and total P concentrations in lakes practically not affected by anthropogenic phosphorus input. That allows to use this relationship to calculate the reference concentration of TP for the lakes: Log TPref = 1.48 + 0.33 (±0.09) log MEIalk
Based on this relationship, the reference TP level for L. Peipsi is between 18 and 23 mg/l and for L. Võrtsjärv equal to 31 mg/l. Comparing these values to the trophic scale of OECD (Eutrophication …, 1982) one can see that both large lakes of Estonia fall into the mesotrophic range (Table 3.2.1)
Table 3.2.1 OECD fixed boundary values for trophic classification (Eutrophication …, 1982) Trophic category TP, Average Maximum Average Minimum mg/m3 Chl, Chl, Secchi Secchi mg/m3 mg/m3 depth, m depth, m Ultra-oligotrophic < 4 < 1 < 2.5 > 12 < 6 Oligotrophic < 10 < 2.5 < 8 > 6 > 3 Mesotrophic 10-35 2.5-8 8-25 6-3 3-1.5 Eutrophic 35-100 8-25 25-75 3-1.5 1.5-0.7 Hyper-eutrophic > 100 > 25 > 75 < 1.5 < 0.7
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3.3. PALEOLIMNOLOGICAL STUDIES OF LAKE PEIPSI (A. HEINSALU & T. ALLIKSAAR)
Paleolimnological techniques provide means to study the past shifts in the aquatic ecosystems outside the instrumentally documented range and evaluating natural background conditions and long-term variability in lakes (e.g. Battarbee, 1991, Smol, 1992). For paleolimnological studies of L. Peipsi s.s. a 70-cm long sediment core was taken from the central part of L. Peipsi s.s. at a water depth of 9.2 m in February 2002. Sampling was performed from the ice using a rectangular freeze corer. The recovered in situ frozen undisturbed sediment core was sliced at continuous 1-cm increments for different sediment analysis. Sediment samples were analysed for 210Pb, and 226Ra by direct gamma assay in the Radiometric Laboratory of the Ukrainian Hydrometeorological Research Institute using low background germanium detector (Appleby et al., 1986) and the chronology of the sediment core was established on the basis of 210Pb dating. Spherical fly-ash particle counting was used to check the accuracy of 210Pb dates. A temporal sediment record of these particles, which are derived from fossil fuel burning, serves as a useful dating tool for the post-industrial era (Renberg & Wik, 1985). North from Lake Peipsi lies the region of the largest commercially exploited oil shale deposit in the world and the main energy production area for Estonia. The well-documented history of oil-shale industry and fly-ash emissions enables to use these particles stored in the uppermost lake sediment layers as an indirect chronological tool (Alliksaar, 2000). For the spherical fly-ash particle analyses dried sediment samples were subjected to sequential treatment with 30% H2O2, 3M HCl and 0.3 M NaOH in order to remove organic matter, carbonates and biogenic silica respectively. For diatom analysis the weighed samples were treated with 30% H2O2 (Battarbee et al., 2001). Diatom concentration was determined by adding a known number of commercially available Lycopodium spores to the cleaned sediment slurry (Kaland & Stabell, 1981). Slides were mounted with Naphrax and analysed for microfossils using a Zeiss Axiolab microscope (oil immersion, phase contrast, 1000x magnification, numerical aperature – 1.30). A minimum of 450 diatom valves was counted for each sediment sample.
Eutrophication history of Lake Peipsi according paleolimnological evidence Of the range of biological remains preserved in lake sediment, diatoms (Bacillariophyceae) a re microscopic unicellular algae that are increasingly being utilised as particularly good indicators of environmental change because they are abundant in all aquatic environments and are highly sensitive to water quality changes (Stoermer & Smol, 1999). They have very rapid replication and immigration rates, which leads to a short time lag between an environmental change in the aquatic system and the diatom response. Diatoms are well preserved within lake sediment, because their external structure is composed of silica which is very resistant to decay. The estimation of diatom concentration (the number of valves per unit weight, here also referred to as absolute diatom abundance) is an important component in paleolimnological investigations. Diatom concentration data from core samples can be applied to the reconstruction of diatom paleoproductivity. Of course different factors like diatom preservation status, i.e. dissolution and diatom fragmentation during grazing, as well as rate of sediment accumulation make interpretation of diatom concentration results more or less tentative.
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Figure 3.3.1. Diatom diagram of the core from L. Peipsi s.s. In the graph to the right black bars show concentration of planktonic diatoms and white bars concentration of littoral diatoms in the sediment. The age scale left to the lithology column is based on 210Pb dates and sperical fly-ash stratigraphy
Diatom analysis was carried out within the 0–40 cm core-depth interval for the timespan 1870–2001, and the stratigraphy was divided into four diatom assemblage zones (DAZ; Table 3.3.1; Fig. 3.3.1). Diatom were not perfectly preserved in the sediment, although there was no signs of frustules dissolution, diatom breakage possibly related to grazing was a common feature.
Table 3.3.1. Diatom assemblage zones (DAZ) in the uppermost sediment sequence of Lake Peipsi Depth, DAZ Age Description of the diatom Environ- cm assemblage ment 0–8 DAZP–1990s– Importance of Stephanodiscus parvus Stoermer & slight 4 2001 Håkansson is decreasing towards the upper boundary of the recovery zone. Aulacoseira granulata (Ehrenberg) Simonsen, and A. ambigua (Grunow) Simonsen are continuously present in high number. A. islandica (O. Müller) Simonsen is increasing distinctly. Fragilaria crotonensis Kitton, Asterionella formosa Hassall, Aulacoseira granulata var. angustissima (O. Müller) Simonsen, Tabellaria flocculosa agg. and Nitzschia fonticola Grunow have their maximum values. Littoral diatoms are present in low values. 8–20 DAZP–1970s– Stephanodiscus parvus dominates and reaches the eutrophic 3 1980s maximum values in the top of the zone. Planktonic diatoms lake Aulacoseira granulata, A. islandica and A. ambigua are continuously present in high number. Fragilaria crotonensis, Asterionella formosa and Aulacoseira granulata var. angustissima are slightly increasing and some new planktonic taxa appear in low numbers. Values of littoral diatoms are still decreasing towards the upper boundary of the zone. 20–23 DAZP– mid Planktonic diatoms Aulacoseira granulata, A. islandica and gradual 2 1950s– A. ambigua predominate. Small planktonic diatom typical eutrophi- 1960s for eutrophic lakes Stephanodiscus parvus starts to increase. cation of Some new eutrophic planktonic diatoms like Fragilaria the lake crotonensis, Asterionella formosa and Aulacoseira
15
granulata var. angustissima appear. The proposition of littoral diatoms is decreasing. 23–40 DAZP– 1870– Planktonic diatoms typical to large lakes Aulacoseira natural lake 1 mid granulata, A. islandica, and A. ambigua predominate and 1950s planktonic taxa make up 50–63% of the diatoms. Planktonic taxa, like A. cf. muzzanensis (Meister) Krammer, Stephanodiscus neoastraea Håkansson & Hickel, S. alpinus Hustedt, Puncticulata bodanica (Grunow) Håkansson and Tabellaria flocculosa agg. are also present in lower values. Littoral diatoms are common (up to 50% of the diatoms), mostly small-size taxa of the family Fragilaria occur. Of those epipsammic diatoms species such as Fragilaria brevistriata Grunow and F. heidenii Oestrup are the most common. Large lake littoral diatom Gyrosigma attenuatum Kützing (Rabenhorst) is also present.
Hereby we present an attempt to trace changes in the ecology of Lake Peipsi s.s. during the last 130 years based on microfossil succession in sub-recent sediments: Pre 1950s The earliest zone DAZ P–1 represent a period when the aquatic ecosystem was extremely stable for at least 70 years and human activity in the catchment and environmental change in general had little influence on the ecology of the lake. Therefore we defined as time of natural baseline conditions in Lake Peipsi a period before mid 1950s. Diatom assemblages typical for large alkaline mesotrophic lakes occur in the sediment accumulated prior to mid-1950s. On the evidence from longer cores, planktonic diatoms Aulacoseira granulata, A. islandica, and A. ambigua together with Stephanodiscus neoastraea as well as littoral small-size Fragilaria species and Gyrosigma attenuatum existed in smaller sub-basins of Lake Peipsi, i.e. Lake Lämmijärv and Lake Pihkva throughout the Holocene (Davydova, 1999). Similar diatom composition characterises also post-glacial development of Lake Ladoga and Lake Onega (Davydova, 1985). There are no diatom based studies on the Holocene paleoenvironmental development of Lake Peipsi s.s. However it seems fairly possible that no or only small changes in the ecological character of the lake have taken place during the last 10,000 calendar years, i.e. after the end of the so called Small Peipsi stage with water level at least 10 m lower than at present (Hang, 2001). If so, Lake Peipsi has been resistant to considerable population expansion, forest clearance and agricultural activity in the catchment during several thousands of years. This interpretation is rather speculative and further sediment studies are needed.
Relatively high proportion of epipsammic diatoms of the genus Fragilaria and epipelic Gyrosigma attenuatum in sediments suggests well illuminated water column, either light reached the bottom because of better water transparency or the zone where periphytic diatoms might survive was much closer to the surface. The water transparency (measured with a Secchi disc) has been relatively low in Lake Peipsi s.s. during last years fluctuating between 1.0 and 3.4 m (Starast et al., 2001). Total diatom abundance ranged between 390 and 670 × 106 valves per 1 g of dry sediment with planktonic species concentrations slightly exceeding that of littoral diatoms. The abundance of chrysophyte cysts was low. Our data indicate low productivity of the lake compared to that of the 1980s, particularly low in plankton communities.
Mid-1950s–1960s A modification in diatom flora is registered at a transitional DAZ P–2. It is characterised by a marked increase in the values of Stephanodiscus parvus although ‘pristine associations’ for Lake Peipsi, Aulacoseira granulata, A. islandica, and A. ambigua are still dominating. An
16 introduction of new species associated with eutrophic lakes such as Fragilaria crotonensis, Asterionella formosa, Synedra tenera and Aulacoseira granulata var. angustissima occurred, indicating a first step of eutrophication. One interesting but still unproven hypothesis is that some of those species were not part of the original flora of Lake Peipsi. These planktonic diatoms are very common in small nutrient-rich lakes in southern Estonia. In lakes with considerable silica supply (like Lake Peipsi) Fragilaria crotonensis may react immediately and earlier than other species to rising phosphorus loading (Alefs & Müller, 1999). It is likely that this change, following a long period of stability, reflects the beginning of antropogenic impact on the lake ecosystem. The amount of littoral diatoms reduced, perhaps because of a decrease in the area of the lake bottom receiving light as the growth of larger plankton crops diminished the illumination. An increase in absolute abundance of planktonic diatoms supports that suggestion.
1970s–1980s Further changes in the diatom flora took place during the 1970s and represent a new influence on the ecology of the lake. Sedimentary diatom evidence indicate that the eutrophication of the lake took place remarkably fast, in only ca. 15 years. The diatom assemblage in DAZ P–3 is mainly composed of planktonic forms. The relative abundance of plankton (80–90% of the total) reflects both the high productivity of the diatom phytoplankton and the restrictions of periphytic (epiphytic and benthic) diatoms due to low transparency of the water column in the photic zone. The littoral forms found in the sediment have therefore been transported to the deeper parts of the basin from considerable distances before incorporated in the sediment. The planktonic component of the assemblage on the other hand reflects progressive nutrient enrichment. Lake Peipsi changed since the 1970s from Aulacoseira granulata, A. islandica and A. ambigua dominated assemblage to a Stephanodiscus parvus dominated diatom assemblage. This taxon seems to be a good indicator of eutrophic conditions. Owing a small size and thin frustule, Stephanodiscus parvus flourishes in the aquatic system with high phosphorus loadings and low Si:P ratios because of their better competitive ability for Si when phosphorus availability is very high (Interlandi et al., 1999). Also some new eutrophic diatoms like Diatoma tenuis appear. The timing and direction of diatom assemblage changes in the sediments compare well with the hydrochemical observations from the lake and an increase in the trophic status of the lake. In terms of nutrient effects on diatoms, these considerations indicate that phosphorus is the prime nutrient controlling primary production in freshwater lakes. The most striking change is an overall increase in absolute abundance of diatoms caused by increased nutrient, particularly phosphorus loading from 900 to 3100 × 106 valves g dry sediment with a maximum in late-1980s.
Post-1990s A slight recovery of the ecosystem took place at least as the sedimentary diatom flora is concerned. Both the relative and absolute abundances of Stephanodiscus parvus decrease substantially during 1990s. Probably during the S. parvus dominance the total phosphorus load to Lake Peipsi was the highest and the period of maximum S. parvus may therefore reflect the period of maximum productivity in the lake. Decline of S. parvus thus can indicate a reduction of phosphorus loading to Lake Peipsi. Absolute abundance of planktonic diatoms varies in a broad range. The same pattern occur with many planktonic diatoms, e.g. Fragilaria crotonensisi, Aulacoseira granulata and A. var. angustissima, which implies that ecosystem is still rather unstable.
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4. INDICATORS AND CRITERIA TO ASSESS THE ECOLOGICAL STATUS OF RIVERS IN THE LAKE PEIPSI CATCHMENT AREA (K. OLLI, E. LOIGU, Ü. LEISK, K. PIIRIMÄE, H. TIMM)
4.1. TYPOLOGY OF THE RIVERS IN LAKE PEIPSI REGION According to the EU WFD all surface water bodies must achieve good ecological status by the year 2015. The good ecological status is determined by hydro-morphological, physical, chemical and biological quality criteria that should guarantee functioning of the aquatic ecosystem and good water quality for different users. The classification of rivers into five classes according to their ecological status is based on the determination of reference conditions. To determine reference conditions, sites of no or only a slight human impact for each type of water body should be selected. Typology is mainly based on hydro- morphological and physical-chemical parameters. The proposals for typology and classification are based on long-term monitoring data and results of extensive research. Leading experts in hydrology, hydrochemistry and biology have been involved in the project. The hydrology and chemistry of Estonian rivers have been well investigated for a long time to enable a comparison with biological and ecological data. The WFD offers a choice between two typology systems (system A and system B). System B was chosen by us as being more flexible and allowing local conditions to be taken into account. According to this system, river types were created using obligatory factors: altitude, latitude and longitude, geology, size and selected optional factors. By altitude Estonian rivers belong only to one class of lowland (< 200 m) rivers. By size the rivers are divided in the following way: • small < 100 km2 (779 rivers in Estonia); • medium 100 to 1000 km2 (120 rivers); • large 1000 to 10 000 km2 (14 rivers); • the largest > 10 000 km2 (River Narva only). The EU Water Framework Directive requires considering rivers with catchment size over 10 km2. Usually small rivers and streams with a size of 10-100 km2 are influenced by human activity via drainage. Many of them have been straightened and deepened during melioration works in the end of the 1960s and in the beginning of the1970s. At the same time, these rivers may play an important ecological role. According to geological conditions and hydrochemistry Estonian rivers can be divided into 4 categories: • calcareous rivers (carbonate rocks dominating, water with high content of Ca and Mg), • siliceous rivers (siliceous rocks dominating, water with low content of Ca and Mg), • organic (humic) rivers (strong impact of bogs, water with high content of humic substances, Fe and COD ), • clay rivers (high turbidity, high content of P). Most of the Estonian rivers belong to the calcareous and siliceous types. Rivers characterised by the domination of clay and organic soils have, as a rule, small catchment areas. Acidification is not a problem for Estonian rivers as the water has a high acid neutralizing capacity. The content of calcium in soils is high and calcium-carbonate buffers the effect of acidity. Rivers are generally alkaline with pH values usually higher than 7.5. Because of high pH of soils there is no significant leakage of heavy metals to the water. High alkalinity of rivers (>3 meq/l) commonly eliminates the impact of the base rock type (Table 4.1.1). Table 4.1.1. Average concentrations of selected water quality parameters in 2001-2002.
Alkalinity Ca pH Colour meq/l mg/l Calcareous area 3.29 62.3 7.90 124 Siliceous area 3.75 62.7 7.93 74
18
West-Estonia 3.34 50.2 7.87 103 Rivers in wetlands 3.62 61.8 7.87 158
More than the base rock, land cover determines the ecological type of rivers in Estonia. Natural wetlands (bogs, swamps) have often a prominent impact on water quality, providing a wealth of humic compounds, while natural oxygen content remins low (Fig. 4.1.1).
45 70 y = 0.5474x - 10.594 40 60 2 R = 0.6918 35 50 30 y = 0,1228x + 4,3287 40 25 R2 = 0,7879 30 20
, 90%, 1997-2001 20 15 Mn , average in 1997-2001 D
Mn 10 10 CO 5 0 COD 0 0 20406080100 0 100 200 300 400 natural land (forest, wetland etc), % colour, average in 1997-2001
Fig. 4.1.1. Correlation between CODMn and proportion of wetlands in the catchment area and colour of the water in the monitoring stations.
Proposed threshold between high and low content of humic compounds is equivalent to chemical oxygen demand (COD) of 20 mg/l and colour of 120 Pt units (Fig. 4.1.1). Hydro-morphological elements used to typologise Estonian rivers are the flow regime (minimal runoff – sanitary flow; natural, modified), riparian zones (width, % of cover along the river etc.), and sinuosity (meandering). According to standard definitions of the WFD, no or very minor human alterations to the hydro-morphological quality elements are allowed to classify a site to 'high' status class. For 'good' status and lower status classes, the permitted degree of deviation of hydro-morphological quality elements from their reference conditions is not defined Lower quality classes are defined only by the deviation of the biological elements from the reference conditions. In case of 'good' ecological status, also the physical-chemical quality elements should be considered. Hydro-morphological regime of Estonian rivers has been altered by amelioration, drainage, deepening, straightening and damming. Slight reduction of river lengths and substrate variability (0.8 – 0.95 EQI) also occurs. Estonian legislation requests water protection belts and buffer zones (riparian areas) for all rivers with catchment area over 25 km2. These belts protect biodiversity and water against non-point pollution. The width of the belt depends on the catchment area of the river. Water flow has significant impact on flora and fauna as well as on ecosystem processes. Ecological status of small rivers is critically dependent on the low-water period when fish migration is hindered. Thus, for flow, EQI of good status should exceed 0.9.
The proposed typology of Estonian rivers: 1. small (< 10 – 100 km2) humic rivers 2. small (< 10 – 100 km2) rivers with low humic content 3. small (< 10 – 100 km2) eutrophic rivers in clay areas 4. middle-size (100 – 1000 km2) humic rivers 5. middle-size (100 – 1000 km2) rivers with low humic content 6. large rivers (1000 – 10000 km2) humic rivers 7. large rivers (1000 – 10000 km2) with low humic content 8. very large rivers (> 10000 km2) with low humic content
19
According to the WFD, it is necessary to intercalibrate the values of quality parameters characterising the thresholds between 'high' and 'good' but also between 'good' and 'moderate' status classes. Therefore the following rivers are proposed for intercalibration (Table 4.1.2).
Table 4.1.2. Recommended river types for intercalibration River Characteristic Catchment Geology Flow regime area, km² 1. Reiu medium lowland, 548 siliceous humic-rich 2. Ahja medium lowland, 336 siliceous low humic content 3. Vihterpalu medium lowland, 474 calcareous humic-rich 4. Võhandu large lowland, low 1144 siliceous humic content 5. Navesti large lowland, 1008 siliceous humic-rich 6. Jägala large lowland, 1572 calcareous humic-rich
4.2. INDICATORS AND CRITERIA FOR ASSESSMENT OF ECOLOGICAL STATUS OF RIVERS
At the present time Estonia lacks a well established consensus on biological criteria to assess the ecological status of running waters. The work is in progress under the coordination of Estonian government (Department of Environment), involving experts in the fields of aquatic bacteria, aquatic botany, phytoplankton, macrozoobenthos and benthic diatoms. Therefore, the following criteria have to be considered preliminary. Even more, much of the present progress is based on a relatively limited sample size of rivers and streams with natural or nearly natural conditions. As the sample size most likely increases in the future, we expect tuning up of the criteria. To fulfill the present objectives, long-term hydrological, physical and hydro-chemical data of L. Peipsi river basin were collected. The database contains data on flow rates, precipitation, and on about 30 chemical parameters for Estonian side of Lake Peipsi basin since 1987. As a first step we selected representative indicators of chemical status. The next step was the selection of specific measurable parameters to represent these indicators. These parameters enabled to work out a classification for selected indicators. In selecting indicators following criteria were considered: • the indicator must be widely and cost-effectively measured in different monitoring programs; • the indicator must be officially accepted as good indicator of water quality; • the indicator must characterize the main water protection problems; • the indicator must describe common types of pollution in the country; • the indicator requires valid water quality standards; • standard method for analytical measurement must be available (guarantees reliability and comparability of data); • precision and accuracy of analysis must be maintainable to ensure validity of results; • the indicator must measure specifically only water quality; • chemical indicators must complement biological indicators; • the indicator must suit to the general indicator system;
20
• the indicator must well describe the health and functioning of the ecosystem. The biological indicators and criteria are largely based on the database of the River Biology Working Group of the Institute of Zoology and Botany (Estonian Agricultural University). As much as possible, published international and national sources were used. Macrozoobenthos data were collected separately by H. Timm through various contracts, or originate from the database of the Võrsjärv Limnology station (Estonian Agricultural University). The drawback of this approach is that the data were not collected with the FWD requirements in mind. On the other hand, this is the only extensive complex investigation of Estonian rivers. The database structure and value has been discussed in previous MANTRA- East documents and will only shortly been reviewed here. The database includes 737 rows of data, corresponding to river samples. The spatial coverage includes all watersheds in Estonian; approximately half of the samples come from L. Peipsi watershed. Only the shortest streams are represented by only one sample; in most cases up to half a dozen stations were spread over the course of the river (from headwaters to lower course). In most cases the rivers (read: stations) were revistied once or twice during the survey period (1989 – 2000), usually with 3- to 5-year intervals. Hydrochemical data are most complete in the database, with only a few missing values. However, the completeness of biological data is only moderate at best. Even more, species specific community structure can not be revealed from the database; in most cases the included parameters are the number of taxa, dominant species, or biomass level (or equivalent) on an ordered categorical scale. The biological quality elements (phytoplankton, macrovegetation, benthic macrofauna, benthic diatoms, fish) were mainly pre-determined by the WFD. To assess the type specific reference conditions for the indicators, 41 river samples were judged by a group of experts in each field as being in undisturbed condition. This is a relatively low number of samples, and not all types of rivers are even represented. That is not surprising, as some types, e.g. the largest watersheds, are relatively rare, and the lower courses of these largest rivers can by no means be considered undisturbed. The criteria to reject a river sample from an undistrubed category were as follows: (i) presence of bioindicators of eutrophication or pollution; (ii) concentrations of total N and P in river water, which exceed the levels set by national quality standards; (iii) direct influence of artificial water reservoirs; (iv) location close to towns or smaller settlements; (v) changes in landscape and melioration works. Based on the 41 river samples, the variation of indicator values were evaluated and reference values proposed, taking into account type specific variation is present. The key surface water problems in Estonia are: • Organic pollution due to insufficiently treated sewage waters entering to rivers • Excessive eutrophication • Harmful substances – specific pollutants • Natural problems – high content of organic substances, turbidity, color, etc. Content of dissolved oxygen, ammonia and biochemical oxygen demand (BOD7) has been selected as parameters showing organic pollution. Total nitrogen and phosphorus indicates the eutrophication and trophic level of waters. Dissolved oxygen is important for successful functioning of aquatic vertebrates such as fish community. Over-saturation and oxygen deficit may significantly influence ecosystem. The other indicators of the oxygen balance of rivers are BOD and ammonia-nitrogen. Organic compounds, consuming oxygen for degradation, put dissolved oxygen work as an indicator of organic pollution. Biochemical oxygen demand (BOD) measures the oxygen demanding capacity of discharged wastewaters. Rivers that are recipients of sewage effluent can often contain high concentrations of organic substances. Small rivers and streams can suffer from high BOD, when large quantities of sewage effluent combined with very low runoff in the low-water period does not provide adequate dilution of the waste-water. Wastewater management bases mainly on BOD7. Ammonia is also toxic for
21 fish and must be the important water quality indicator. Phosphorus is the main nutrient limiting primary production in freshwaters. Therefore, reduction of phosphorus emission should remain the main target in water protection. Still, in coastal waters and in few other exceptional cases (including L. Peipsi), nitrogen may limit primary production. While nitrogen / phosphorus concentration ratio drops below 16 then nitrogen starts to limit primary production favoring cyanobacteria with atmospheric nitrogen fixation capacity. Most cost- effective management measures in reducing nitrogen emissions to improve water quality are in sustainable agricultural practice. Dissolved oxygen, biochemical oxygen demand (BOD), total ammonia and total nitrogen and phosphorus are widely used as indicators of water quality in many European countries.
4.2.1. Criteria of chemical and hydromorphological status
Chemical status classification has been worked out on the basis of long-term national river monitoring data. The new grades are defined in terms of the 90 percentile for BOD and ammonia and the 10 percentile for dissolved oxygen; in other words, the river reach should contain less than the specified levels of BOD and ammonia at least 90 percent of the cases, whilst the level of dissolved oxygen must not fall below the prescribed level in more than 10 percent of the cases. Several authors have proposed to use combine method to give the general assessment to river water quality (Ventilla, House, Green 1989; House, 1989; Bascombe, House, Ellis, 1989; Vesistöjen Laadullisen Käyttökelpoisuuden Louittaminen, 1988) To combine several parameters, the method for estimating the general status - the Sub-Index method - has been adapted for the Estonian rivers. The sub-index (SI) is calculated to give common base for different indicators and bases on the principle: the border value between class I and II will have an SI of 100. The border value between class II and III will have SI value of 75. The demarcation limit between the third and fourth class is set on SI 40. The value between class IV and V will have SI 5. Figure 4.2.1.1. indicates the estimations of sub- index values for main water quality parameters.
Sub-Index for Ammonia 100 90 80 70
x 60 50 40 Sub-Inde 30 20 10 0 0 0.10.20.30.40.50.60.7 Ammonia (mg N/l)
Figure 4.2.1.1. Estimation of sub-index for ammonia On the basis of expert assessment following weighting factors for different indicators are estimated.
Table 4.2.1.1. The weighting factor (SI) for indicators is following: Indicator Weighting factor (SI) Dissolved oxygen 0.15
22
Biochemical oxygen demand 0.3 Ammonia 0.1 Total nitrogen 0.2 Total phosphorus 0.25
The weighting factor values of the parameters have to be combined in one value for characterizing the general status of water quality (GS). 01..5 03 0.1 0.2 0.25 GS =×()SIO2% (SI BOD74)×(SI NH )×(SI Ntot )×(SI Ptot ) The water quality indices range from zero to 100. The following classes have been set for the general classification of the rivers. Class I: High chemical status, GS ranges from 100 to 90; Class II: Good chemical status, GS ranges from 90 to 75; Class III: Fair chemical status, GS ranges from 75 to 55; Class IV: Poor chemical status, GS ranges from 55 to 35; Class V: Bad chemical status, GS ranges from 35 to 0.
For the bases of the distribution of the first quality class i.e. water with high quality parameters typical for Estonian natural water has been taken which express background values of river water not influenced directly by human activity. For the second class (II) is allowed certain anthropogenic impact but quality still good and suitable for the river ecosystem. Rivers which are moderately, significantly or strongly influenced by human activities and corresponding to pollution situation belongs to third, fourth or fifth class. The proposed water quality classification of Estonian rivers based on chemical indicators is presented in Tables 4.2.1.2 and 4.2.1.3.
Table 4.2.1.2 Water quality classification of Estonian rivers for rivers of low organic- humic content Ingredient Unit Class I Class II Class III Class IV Class V High Good Fair Poor Bad pH 6-9 6-9 6-9 6-9 <6-9> Saturation of % >70 70-60 60-50 50-40 <40 dissolved oxygen BOD7 mgO/l <3.0 3.0-5.0 5.0-8.0 8.0-10.0 >10.0 + NH4 mgN/l <0.1 0.1-0.3 0.3-0.45 0.45-0.6 >0.6 Ntot mgN/l <2.0 2.0-3.0 3.0-4.0 4.0-5.0 >5.0 Ptot mgP/l <0.05 0.05-0.08 0.08-0.12 0.12-0.16 >0.16
Table 4.2.1.3 Water quality classification of Estonian rivers for rivers of high organic- humic content Ingredient Unit Class I Class II Class III Class IV Class V High Good Fair Poor Bad pH 6-9 6-9 6-9 6-9 <6-9> Saturation of % >60 60-50 50-40 <40 <40 dissolved oxygen BOD7 mgO/l <3.0 3.0-5.0 5.0-8.0 8.0-10.0 >10.0 + NH4 mgN/l <0.1 0.1-0.3 0.3-0.45 0.45-0.6 >0.6 Ntot mgN/l <2.0 2.0-3.0 3.0-4.0 4.0-5.0 >5.0 Ptot mgP/l <0.05 0.05-0.08 0.08-0.12 0.12-0.16 >0.16
23
The biochemical oxygen demand of natural river water not affected by human activity is as a rule less than 3.0 mgO/l. BOD7 3-5 mgO/l indicates moderate human impact and the values generally more than 5 mgO/l indicate obvious pollution. The critical content of total nitrogen as minimal requirement to avoid eutrophication of rivers is 2.5 mgN/l (Loigu, 1992). The mean concentration in the background rivers was 1.5 mgN/l and in 98% of all samples the content of total nitrogen was lower than the critical value. The main element limiting primary production in Estonian surface waters is phosphorus. The highest permissible value of total phosphorus preventing eutrophication is 0.10 mgP/l (Loigu, 1993). Mean content of total phosphorus and phosphates in background rivers in 1992-1999 was correspondingly 0.05 mgP/l and 0.025 mgP/l. The classification is based on the principle that class I or High quality is characterised by ingredients of natural background water in our region i.e. not influenced by human activity. For the class II, water of Good quality, some human impact is allowed but water corresponds to the requirements of Good quality. The overview of the chemical status of rivers of L. Peipsi basin according to water quality classes in 2002 is given in figures 6-10. The water protection management plan for improvement of water quality should be worked out for those waterbodies not corresponding to the requirements of the Good status. According to national monitoring data, the BOD7 level in Estonian rivers in generally is low. Only in one river (Emajõgi River) in 2002 water quality by BOD7 didn’t correspond to water quality standard (good status). Emajõgi River is polluted due to discharge of sewage water from Tartu town. The other rivers in spite of that they are also affected by sewage waters, the fluctuation of BOD is low and correspond to standards. The main problem in Estonia is still high level of nitrogen and phosphorus in the rivers discharging into L. Peipsi (Fig. 4.2.1.2.).
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a e a agula äpina st vast geva e u e ääpa T a e islepa e a u gi gi gi a ō u a a a P av t t T gi t j v o a ku gi ō Av uu Al v na
rv u kasilla rv i rv K ō J iidjär ō ō st mmiste a s r s rt a i s j Po ō i r ō Tõlliste m - Ta epa i - Na r V ō ō aav R j l ltsamaa O sknar i l llist J silla a K i t jä Lääniste es r Mustj m K a Tarv Tagaj gev va st s T P õ äpi õgi ō a g S s nar T H ō Piusa Avij rv ō Alaj hne - k ō gi - e peakr Kääpa J P rv mmi sa aj Por j - Na T agaj i - Ta V t gi - edja - ja - Mustajõgi J i Tänassilma Oo Vagul ō lt R ja - a - Ka a a j gi - Mus - T annu- Ta Kiid Lääni ō Pika Õ i g h ō P j Sui h H - a ō Na edja - i - - hne - änas annapunger rv e peak g a - ō - j a - P A hne - a i isiku peakr Vas R A u peak g a v ō T P a Mus handu - ja handu - R aj g Em ō er k r Õ annu- ō Pedj Õ i ō Na ō aj astver ō a - a handu - l s V annapunger tv aj i Em gi - Ah hne - Ahj V v R V Pedj aj ō Em N A R handu - r ō handu - ō V-Em - as Õ j Em ō a V ō V handu - Em a V-Em gi V Al Em N V ō V- ō V V- aj Em Em 90% max average min 10% 90% max average min 10% 0,3
0,25
0,2
0,15 Figure 4.2.1.2. Dissolved oxygen 0,1 0,05 Total phosphorus, mgP/l 0
e u e e saturation and content of BOD , e a gi gi gi t a u t a t gi v ja tu gi ku uu v rva rve st rva ō ō ō rt aav illa ō j j j 7 s ō ri r a aav ō j ō lepa us llis s ri a ilma t r es i maa va gev st T agula õ a ääpa s is nar ō T a P Avi rva ō Al k k iidjär u J i K ajõgi Po T - N agaj - Ta t s i V J Oo lts Räpina Mus T K Ta Läänis P a g ō S - Ka Himmis i hne - e peak änas rva gi - ō P j V u peak edja - g a ō T Mus ja - ja - gi - j a ammonium-nitrogen, total nitrogen er ō Õ ik P j h N h ō a edja - a - j tv a is hne - A A Rannu- v P a Em handu - Rannapunger ō handu - Õ as ō l ō V handu - Em gi - V A V Nar ō V-Em ō j V V-Em and total phosphorus in the a Em monitored river stations in 2002 90% max average min 10%
24
4.2.2. CRITERIA OF ECOLOGICAL STATUS
Out of several potential indicators based on bacterioplankton, the abundance of saprobacteria, and also the abundance of coliform bacteria appear to be most informative and easy to interpret. In Estonian rivers saprobacteria originate mainly from allothonous sources (Pall, 2001), but can grow also autothonously. High concentration indicates pollution and lowest concentrations were found close to springs. Concentration of saprobacteria have proven to be a good indicator of organic pollution, being high in rivers with elevated levels of total phosphorus and ammonium. In Estonian rivers the concentration of saprobacteria correlates with other indicators of pollution: BOD5 – r=0.28; NH4 – r=0.35; Ptot – r=0.44; PO4 – r=0.43, but not so with NO3 – r=0.06. One of the most widely used bacteriological water quality indicators is the concentration of coliform bacteria, indicating pollution with faecal material (both, from municipal and agricultural sources), but also organic pollution. In Estonian rivers, concentrations of sparobacteria have also been widely used as indicators of general bacteriological contamination. As a relatively new indicator, concentration of thermo- tolerant coliform bacteria, which is supposedly more reliable indicator of faecal contamination, has been used since 2002. Most likely the criteria for bacteriological contamination of inland waters will be regulated by future EU directives. The present requirements (76/160/EEC) are most likely out-dated and the future norms will be more strict. As a general guidance, the perspective norms in the 76/160/EEC directive have been followed in Estonia: maximum concentrations of coliform bacteria <500 cells/100ml, and for thermo- tolerant coliform bacteria <100 cells/100ml. These criteria should be used to delimit good and satisfactory states of the water. To demarcation of good and high status is less certain; provisionally 150 cells/100ml for coliform bacteria has been suggested. Thus, the proposed natural reference value for coliform bacteria in Estonian rivers is <150 cells/100 ml, the proposed boundary between good and moderate status is 500 cells/100 ml (Lokk, Laugaste & Leinsalu, 1988). According to Lokk et al, (1988) the concentrations of saprobacteria in Estonian rivers should be grouped as follows – low: < 1000 cells/ml; moderate: 1000 – 5000 cells/ml, high: 5000 – 10000 cells/ml, and very high > 10000 cells/ml,. The natural reference value of saprobacteria in Estonian rivers is set to 1000 cells/ml, which coincides with the oligosaprobic class boundary and is probably too stringent. As low concentration of saprobacteria (<1000 cells/ml) are truly rare in Estonian rivers, the river biology experts have suggested to use 1500 cells/ml, to demark the boundary between good and high status. The boundary between good and moderate status should be set to 3000 cells/ml. It deserves attention that bacterioplankton based indicators in Estonian rivers have proven to be relatively independent of type specific parameters, such as area of drainage basin, type of bedrock, and flow velocity of the river. Phytoplankton has been used as an ecological indicator in several large lowland rivers (Dokuli, 1996; Hindrak & Makovinska, 1999; Kiss & Schmidt, 1996). However, the methods to use phytoplankton based indicators in small rivers and brooks are not well developed. The short residence time of the water does not permit the development of true potamoplankton, and phytoplankton is usually dominated by epiphytic and benthic species (Piirsoo, 2001). Higher vegetation on the river banks and exposure to light has more influence on phtoplankton than water quality parameters. Phytoplankton biomass (mg/l), abundance (cells/ml), number of taxa in quantitative sample, biomass dominants, and general phytoplankton index (FKI) have all been considered as potential indicators of water quality. FKI has been developed to assess the biological quality in small Estonian lakes (Ott & Kõiv, 1999; Ott & Laugaste, 1996), and is expressed as a ratio of eutrophic and oligotrophic indicator species:
Cyan + Chl + Cent + Eugl + Cryp
25
FKI= —————————————— Zygn + Chr + 1,
Cyan – cyanobacteria, Chl – Chloorococcales green algae, Cent – centric diatoms, Eugl – euglenophytes, Cryp – cryptophytes, Zygn – Zygnematales green algae, Chr – crysophytes. At the present time, FKI is considered as the most informative phytoplankton based indicator for Estonian rivers. It correlates reasonably well with the trophic state of the water (Spearman correlation coefficient r = 0,33; p < 0,001), BOD5 (r = 0,21; p < 0,001) and rank of the river sensu Strahler (r = 0,27; p < 0,001). The cirteria to demark the reference value for Estonian rivers according to FKI indicator has been proposed as follows - ≥ 6 (drainage basin <100 km2), ≥ 9 (drainage basin 100-2500 km2) and ≥ 15 (drainage basin >2500 km2). At the moment there are no agreed numeric values to demark good and moderate status. Various benthic diatom indexes provide a promising perspective to assess various water quality properties (Kelly & Whitton, 1995; Kelly & Whitton, 1998; Prygiel, 2002). As sessile organisms, diatoms respond directly to changes in the river water quality and can not change their habitat. Several European countries have developed national indicator systems to use benthic diatoms as water quality criteria (Van de Vijver & Beyens, 1998; Prygiel, 2002). European Union has adopted a standard method to use benthic diatoms in qater quality assessment (Water quality – Guidance standard for the routine sampling and pretreatment of benthic diatoms from rivers CEN/TC 230). Diatoms are the most diverse group of microalgae in Estonian rivers (Piirsoo, 2001; Vilbaste, 2001) and the development of benthic diatom based indicator system for Estonian rivers is currently under progress (Vilbaste, 2001). The following indicators were considered: number of diatom taxa in qualitative sample, H (Shannon diversity index), SPI (Specific Pollusensitivity Index) (Cemagref, 1982) GDI (Generic Diatom Index) (Coste & Ayphassorho, 1991), CEC (Diatom index by Descy & Coste, 1991) IDAP (Artois-Picardie Diatom Index) (Prygiel, Whitton & Bukowska, 1999), TDI (Trophic Diatom Index) (Kelly & Whitton, 1995). At the present moment the criteria system for water quality assessment for Estonian rivers is under development. In the following we provide preliminary suggestions of the numerical values of diatom based indexes to deliniate the reference state for Estonian rivers. Number of taxa in qualitative sample does not reveal clear pattern in different types of rivers. The only notable positive correlation was with the size of the drainage basin of fast-flowing rivers on limestone bedrock.The proposed reference value is 30 taxa per sample for limestone bedrock, > 250 km2 drainage basin, and 25 taxa for all other types. Shannon diversity index has a reference value of 3.0, except in limestone bedrock rivers with < 250 km2 drainage basin, where it should be 2.5. SPI (reciprocal of organic pollution) appeared to be indiferent with type; reference value proposed as 16. GDI (general water quality) was related to flow velocity and less to size of the drainage basin. Reference value 12 applies to rapidly flowing rivers with < 2500 km2 drainage basin, 10 to rapidly flowing rivers > 2500 km2 drainage basin, 11 and 10 to slow flowing rivers with drainage basins < 1000 km2 and > 1000 km2, respectively. CEC (general quality) index was indifferent with respect to types, reference value is proposed as 15. IDAP (general quality) index was also indifferent with respect to types, reference value is proposed as 14. TDI index (organic pollution, larger values correspond to higher pollution, not to improved quality as is the case with other indexes) was again indifferent with respect to types, reference value is proposed as 75. Potentially suitable macrozoobenthos based criteria for small running waters (Table 4.2.2.1) are abundance, or number of organisms per unit of bottom surface, number of taxa, Shannon diversity index H’, Average Score Per Taxon - ASPT index, DSFI - Danish Stream Fauna Index, number of taxa of Ephemeroptera, Plecoptera, Trichoptera in a sample – EPT index, Swedish acidity index. All these are successfully in use e.g. in central and southern Sweden.
26
Table 4.2.2.1. Scales of quality macrozoobenthos based quality criteria for small running waters. Abundance Number EPT Shannon H’ ASPT DSFI Acidity index of taxa (Johnson, 1999) Very high - - - 3.71 >6.9 7 >10 High - - - 2.97-3.71 6.1-6.9 6 6-10 Moderate - - - 2.22-2.97 5.3-6.1 5 4-6 Low - - - 1.48-2.22 4.5-5.3 4 2-4 Very low - - - <1.48 <4.5 <4 <2 Reference - - - 1.97 4.7 5 6 value
Medin et al. (2001) Very high >3000 >50 >29 >4.15 >6.9 7 >10 High 1500-3000 40-50 22-29 3.85-4.15 6.1-6.9 6 6-10 Moderate 500-1500 25-40 12-22 2.95-3.85 5.3-6.1 5 4-6 Low 200-500 18-25 7-12 2.35-2.95 4.5-5.3 4 2-4 Very low <200 <18 <7 <2.35 <4.5 <4 <2 Reference - - - 2.95 6.1 5 6 value
Abundance tends to be higher on stony bottoms, compared to sandy bottoms, and thus the former should be preferred as sampling sites. However, abundance seems to be quite site specific and with high natural variability. Even more, it is not unambiguously clear how abundance relates to changes is water quality. Number of taxa is based on predetermined identification level and list of over 500 taxa (Johnson, 1999). This indicator is not overly dependent on bedrock type. The proposed border between high and good status could be 30 taxa; for rivers with < 100 km2 watersheds 25 taxa. It is likely that the number of taxa can vary based on flow velocity of the river, but the relationship is unclear at the moment. Shannon diversity index should have a border between good and high at 2.5 (watersheds < 100 km2 and > 1000 km2), or 2.75 (waterseds 100 – 1000 km2). ASPT index (Armitage et al., 1983) is relatively less dependent on type of river. Values > 6 should indicate high, 5 – 6 good, 4 – 5 moderate and < 4 poor conditions. In < 100 km2 watersheds, the reference value between high and good should be 5.5. DSFI (Skriver, Friberg & Kirkegaard, 2000) indicates organic pollution, and can vary with flow velocity (as the number of taxa; these indicators are partly inter-related). Proposed criteria for Estonian rivers are: 6 - 7 high, 5 good, 4 moderate, < 4 poor. In rivers with > 2500 km2 watersheds the index value 5 should be considered high. EPT (Lenat, 1988) values in Estonian rivers are low, possibly because of the nature of Estonian rivers (lacks mountain rivers), as compared to Sweden or North-America (where the original criteria were developed). In rivers with 100 – 1000 km2 watersheds, EPT values ≥ 15 should be considered high; for watersheds < 100 km2 and > 100 km2 the corresponding value should be 12. In low flow velocity and < 100 km2 the boundary between good and high should be 10, otherwise 12. More than other criteria, EPT varies with flow velocity. High values of Acidity index (Johnson, 1999) indicate low levels of acidity. In general, acidity is not a problem in Estonian rivers. Proposed cirteria for Acidity index are as follows: on carbonate bedrock < 250 km2 watershed: ≥ 10, watersheds >250 km2: ≥12. Rivers on sandy deposits: watersheds < 100 km2: ≥ 7, watersheds > 100 km2: ≥ 9. In cases acidity index can be misleading when indicator species are missing due to secondary factors, as low flow velocity of strong impact of springs. Macrophytes embrace several taxonomic groups of organisms: macro-algae, liverworts and mosses, ferns, and flowering plants. Macrophytes are the prime structural element in the open water column of rivers and lakes. Numerous groups of organisms make
27 use of the considerable enhancement of spatial diversity provided by the surface of the plant organs and the spaces in between. The life-form of macrophytes determines their sensitivity to water quality. Sumberged floating leaf and surface living plants tend to be more prone to changes in water chemistry. Reeds and other helophytic species, although closely related to the aquatic environment, are rather to be dealt with under the element of hydro-morphology (Janauer, 2001). During the investigation of Estonian rivers, the recorded macrophyte parameters within a 50 – 100 (200) m stretch of river included determination of species richness, percentage cover, dominant species, occurrence of red algae (rhodophytes), occurrence of filamentous algae, occurrence of algal mats. There were no significant differences in the dominant species between types (of rivers), i.e. the between types variability did not exceed the within types variability. Similarly, the percentage of cover was independent of type. However, species richness was related to drainage basin size and type of bedrock. The proposed reference values for calcareous drainage basins > 1000 km2 and < 1000 km2 is 15 and 12, respectively. For sandy drainage basins > 1000 km2 and < 1000 km2 the respective values are 15 and 7. The macrophyte community structure, types of communities and ecological parameters which determine the occurrence of dominant species in Estonian rivers has been analyzed by Paal and Trei (2003). The authors used data from 109 river stretches (37 rivers) and 210 community descriptions, and separated 23 community types by using cluster analysis. Using generalized linear models (GLIM) and discriminant analysis, they found that the most important ecological gradients, determining the macrophyte community structure, were (1) the bottom substrate type, (2) BOD5 and to some extent N/P ratio of the water, (3) mud accumulation and water transparency. The second gradient, which is most obviously related to pollution and water quality, was characterized by the occurrence of communities dominated by Sagittaria sagittifolia and Nuphar lutea, with Equisetum fluviatile, Sparganium spp, and Lemna minor as common co-dominants. In Estonian rivers S. sagittifolia is a species, which tolerates the highest trophic levels. The work of Paal and Trei (2003) had an high analytical and descriptive quality, but it did not lead to proposals of numerical values to quality criteria.
28
5. ECOLOGICAL STATUS OF RIVERS IN L. PEIPSI BASIN ACCORDING TO THE REQUESTS OF WFD (K. OLLI, E. LOIGU, Ü. LEISK, K. PIIRIMÄE, H. TIMM)
The satus, or quality of river water is an intriquing topic. As municipal wastes start to become under control in Estonia, i.e. conventional sewage treatment plants with biological and chemical treatment become commonplace, more attention is directed towards agricultural diffuse sources. Here, again, we have witnessed an unprecedended drop in the use of mineral fertilizers as the economic system of the country shifted. It is even suggested that at present more nutrients leave the fields annually with harvested crop, than is returned with fertilization. Clearly, this situation cannot last for prolonged periods. Consequently, the nutrient load to rivers and lakes in Estonia at the present time is likely to be lower than ever during the past decades, but also, during the decades to come. The ultimate question is: has the biological system of the rivers and lakes responded? And if yes, then how? It is therefore of utmost importance to record the present state of rivers and lakes in great detail, as a reference status to compare future changes against. Formation of water quality status of Peipsi river basin depends on natural processes and human activities. The latter influence water quality via river basin (cultivation, fertilization, drainage, use of pesticides etc.) and via direct wastewater inputs to water bodies. Pollution load from point sources (industries, municipalities) are relatively easy to measure, control and regulate. Implementation of purification measures enables to significantly reduce pollution load. Non-point pollution, at the same time, comes from entire river basin area, thus, assessment of its impact is complicated and the reduction of pollution requires a combination of different measures such as legislative, institutional, technical, economical and informational measures. Nutrients, especially nitrogen, originate from non-point sources. The following text gives an overview on the types and sources of pollution in the L. Peipsi watershed. Where the data is sufficiently detailed (e.g. hydrochemical monitoring data), comparisons with recent years are given and possible trends discussed. Finally, the present hydrochemical status of the rivers in L. Peipsi watershed is given. The biological status is refers to published and unpublished criteria, and is based on years of intensive work on Estonian rivers. Whenever usable criteria were available, the existing data were evaluated against these. In other cases, a more general account is given on the status of rivers based on different biological indicator systems. The biological interpretation is based on data collected by the River Biology Working Group of the Institute of Zoology and Botany (IZB, Estonian Agricultural University), unless otherwise noted. The field work was done in July and August (1989 – 2000) during a low flow period when stabilization of aquatic biological regime and the maturity of the biota have reached full development, bioproduction is at a maximum, and water quality parameters are the most stable (Järvekülg, 2001a). Included are 218 streams (a total of 737 sampling stations) representing all major watersheds; particular focus is on rivers in L. Peipsi basin (77 rivers and brooks; 317 sampling stations). Apart from the shortest streams, several sampling stations per river were covered, most of which were visited several times during the investigation period. A different approach was used to sample macrozoobenthos, where most of the samples were taken during spring, not summer. It has been agreed that the summer low flow period is not optimal for macrozoobenthos sampling. Namely, by summer many of the insect larvae, which often hava a good indicative value, are missing from the water, while during autumn they can be in such a premature state that identification is not feasible. Thus, macrozoobenthos sampling scheme differs from the rest of the biological indicators.
29
5.1. Hydrochemistry
5.1.1. Point sources
Large amount of nutrients and the other pollutants are discharged into the Lake Peipsi by rivers via direct discharges from coastal settlements, industries and the atmosphere. Many rivers work as recipients of municipal and industrial wastewaters. Surface water of the L. Peipsi basin area also affected by mining activities, fish farming and cooling waters. As a rule, there is a combined sewage system of wastewater treatment in Estonia and in Russia. Both, industrial and municipal wastewater is purified by common plants. Pollution load data was assessed and evaluated possible changes during the last decade on the basis of national statistics kept by the Data and Information Centre of the Estonian Ministry of Environment. Since 1999, L. Peipsi has not received non-treated wastewaters. However, 89000 m3 purified wastewater discharges directly to L. Peipsi, which is equivalent to 1.6 tons of P and 1.2 tons of N. Compared to 1992, direct wastewater discharges has decreased by 32%. The coastal water quality in the vicinity of local outlets has been improved, giving opportunities to recreational use. Based on the national statistics, in 2001 about 60 million m3 of wastewater were discharged annually into the rivers. Besides, 915 000 m3 of polluted wastewater are discharged annually without any treatment. The share of biological treatment with phosphorus removal is still moderate while mechanical treatment still dominates (Fig. 5.1.1.1.). A great amount of wastewaters form mining waters directly depends on precipitations. Mining waters form ca 90% of the wastewaters of Peipsi river basin. In the same time, mining waters do not significantly impact to organic and nutrient pollution. Still, mining waters are impure, containing much solid substances, phenols and even hydrocarbons. Mining waters are treated mechanically in sedimentation ponds. Table 5.1.1.1. The amount of wastewater, pollution load of mechanically organic substances and nutrients in treated L. Peipsi catchment area 1992-2001 75% Amount of Pollution load (tons wastewater per year) 3 Year (10 m3) BOD7 Ntot Ptot 1992 51735 4583.4 537.7 82.3 1993 39489 1973.5 367.9 59.4 Untreated biologically biological- 2% 9% 1994 49585 1500.2 352.1 69.1 chemically 14% 1995 58003 1295.2 471.2 79.8 1996 44743 1120.1 451.5 73.4 1997 55421 1044.4 417.1 73.6 1998 53344 804.3 339.7 56.5 1999 59802 528.6 390.6 58.1 2000 57938 518.9 351 53.2 Figure 5.1.1.1. Share of different wastewater 2001 59358 437.9 336.8 46.5 treatment technologies in L. Peipsi basin in 2001
The amount of wastewater, pollution load of organic substances and nutrients are given in the Table 5.1.1.1. In 2001, wastewaters transported to Peipsi drainage basin water bodies accounted for over 400 tons organic substances, ca 340 tons of nitrogen and below 50 tons of phosphorus. The major part of the load was directed to R. Emajõgi (Table 5.1.1.2). Approximately 68% of BOD7 load and 56% of phosphorus load to R, Emajõgi comes from town of Tartu. From the Estonian side, the two largest rivers, Emajõgi and Võhandu, channel 80% of the total BOD and P load to L. Peipsi. The largest point source pollution in the area comes from the municipal wastewater of Tartu with its ca 105 000 inhabitants, which is directly discharged into R. Emajõgi.
30
Table 5.1.1.2. Load of point pollution sources of Peipsi drainage basin in 2001
Amount of wastewater that requires BOD7 (tons Ntot (tons Ptot (tons Source treatment (103 m3 per year) per year) per year) per year) Total catchment area 59358 438 337 46 R. Emajõgi 10569 278 203 32 Tartu town 7579 190 152 18
The second largest town in the catchment area is Võru (15 000 inhabitants). The recipient of its sewage waters is R. Võhandu. Following largest towns are Põlva (6500 inhabitants) that directs its wastewaters through R. Ahja to R. Emajõgi. Total BOD, P and N load from 3 biggest towns (Tartu, Võru and Põlva) was approximately equal to load from other sources such as small settlements and household plots (Fig. 5.1.1.2).
100% 90% 80% 70% Others 60% Põlva 50% Võru 40% 30% Tartu 20% 10% 0% BOD Tot-N Tot-P
Figure 5.1.1.2. Relative distribution of direct discharges into recipient of organic matter and nutrients from Data analysis indicates that the dynamics of pollution load has changed. Despite of that, the total amount of wastewaters has increased slightly. In 1992, less than 52 million m3 while in 2001 ca 59 million m3 of wastewater was directed to the river system. The reason for such a change is that Tartu has improved its sewage treatment capacity while more people have been connected to the treatment plant. Figure 5.1.1.3 indicates that load of BOD7 from municipal and industrial wastewater treatment plants in L.Peipsi catchment area has steadily decreased long-term. The pollution load of organic substances has been reduced during the period 1992 to 2001, from 4583 tons to 448 tons per year. It can be seen that the BOD decline was faster during economic crises period in 1992-1993. In 1998, biological waste water treatment plant was installed to Tartu causing increase of discharges due to increased population number connected to the sewage system. The general decrease of amount of organic pollution can be explained by economical depression in the beginning of 1990s then many industries were closed. Also, wastewater treatment efficiency has increased. Several new wastewater treatment plants have been constructed. In addition, several old plants have been reconstructed. It can be partly explained by the national policy: water consumption and pollution taxes have increased. Thus, sustainable use of water resources has been better implemented. The total nitrogen and phosphorus load from point sources have significant variations from year to year and in different waster water outlets. During the period 1999-2001 the annual total nitrogen and phosphorus discharges from municipal and industrial outlets to rivers was about of 360 tons of nitrogen and 52 tons of phosphorus. Despite of the fact that
31 wasterwater treatment efficiency has improved, the total phosphorus point source load high, and the removal of phosphorus is still an major problem in Estonia.
5000 12000 Peipsi basin 4500 Tartu town 10000 4000 Amount of wastewater (10 3 m3 /yr) 3500 8000 3000 2500 6000 2000 4000 1500 1000 2000 500 0 0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
Fig. 5.1.1.3. Organic pollution (BOD7, tons per year) and amount of wastewater in 1992- 2001 The effluent concentration of nitrogen from Tartu wastewater treatment plant varied greatly, purification efficiency was low. It was approximately 30-60%, although the national standard requires at least 80% removal of nitrogen. Thus, concentration exceeded limit standards that is 10 mgN/l (Fig. 5.1.1.4). Effect of phosphorus purification in Tartu wastewater treatment plant was about 82% but despite of that the effluent concentration of phosphorus did not correspond to the maximum permissible level (1.0 mgP/l, Fig. 5.1.1.4) Problem deriving from this was extremely high influent concentration of phosphorus (12.5 mgP/l). High content of phosphorus describes all Estonian small towns and villages. Water price and cost for wastewater treatment has increased during recent years. Pollution charges have also increased significantly. Due to that, industries and private owners, lacking finances, sustain more water. Water use per capita has decreased significantly and rapidly. While in the end of 1990s water consumption was 200-250 liters per capita then today in several small towns and villages the number remains only ca 70-80 liters per capita. These numbers in one hand indicate sustainable use and management of water resources but simultaneously the concentration of P and N in municipal water has increased. Highly concentrated municipal sewage waters fail to purify under the treatment of modern technologies, while the amount of wastewater is low. Therefore, in future it may appear necessary to use additional treatment options such as artificial wetlands etc. As inland waters are especially sensitive to phosphorus load, nitrogen removal from wastewater remains less important. Estonian water policy pays attention on nitrogen removal in coastal towns. Investigations in Peipsi drainage basin have shown significant decrease of N/P ratio in the beginning of 1990s. It dropped from 80-100 in 1987 to 12-15 in 1991 (Iital et al., unpublished, Figure 5.1.1.5). Low N/P ratio can increase probability that nitrogen will limit primary production instead of phosphorus. Due to that it is important to reduce P load from wastewater treatment plants and P level in surface water bodies. Rural settlements have often old treatment plants that function badly causing high P concentration in small rivers. Even, if HelCom requirements of less than 1.5 mgP/l was achieved, the ecological state of small streams would have been still bad because in summer and winter time low flow rates can not guarantee required dilution for sewage waters. It means that in future it is necessary to pay more attention to P removal. Sparse settlements and household plots impact to small rivers and streams. Due to biochemical transformation processes, much of that emission fails to
32 reach L. Peipsi. In the same time, small rivers offer close contact with the local people requiring achievement of good ecological status there too.
40,0 4,5 35,0 4,0 )
/ l) 3,5 l
30,0 g 3,0 (m Ptot 2001 25,0 Ntot 2001 n 2,5 Ptot 2002 on (mg / 20,0 Ntot 2002 atio 2,0 tr limit value
15,0 Limit value en 1,5 c
n 1,0
10,0 co
concentrati 0,5 5,0 0,0 0,0 I II III IV V VI VII VIII IX X XI XII I II III IV V VI VII VIII IX X XI XII Figure 5.1.1.4. Effluent concentration of nitrogen and phosphorus from Tartu waste water treatment plants
Future development can be made by establishing new and more efficient wastewater treatment plants especially to reduce significantly phosphorus load to avoid pollution.
5.1.2. Non-point sources Non-point pollution load are caused by human activities or have natural origin. Therefore, pollution prevention methods may be the most cost-effective. In calculations of the natural background load earlier data about load from forests, swamps and natural grasslands were used. As fertilizers are practically not used at all in Estonian forests, the load from the forests was regarded to be equal to the natural background load. For estimation of anthropogenic non-point load from agriculture the state hydrological and chemical monitoring data for the river Porijõgi discharging to the river Emajõgi were used. The agricultural land constitutes 55% of the catchment area (241 km2) of the river. The figures were compiled with the data collected via special monitoring program carried out in small agricultural catchment of River Räpu. The river Räpu catchment (25.5 km2) is a typical agricultural production area in central part of Estonia in Pärnu Bay catchment area. Landuse data for the catchment area of L. Peipsi was obtained from the CORINE landcover of Estonia The results of the nutrients load calculations for the rivers Porijõgi and Räpu are presented in the Table 5.1.2.1.
Table 5.1.2.1. Nutrients load from the rivers Porijõgi and Räpu Year Losses of nutrients, kg/ha (Räpu) Losses of nutrients, kg/ha (Porijõgi) - 3- - 3- NO3 -N Ntot PO4 -P Ptot NO3 -N Ntot PO4 -P Ptot 1995 3.29 4.4 0.02 0.07 2.21 3.40 0.06 0.12 1996 2.12 2.9 0.03 0.09 1.89 3.07 0.08 0.11 1997 5.59 7 0.04 0.11 2.48 3.93 0.08 0.13 1998 4.06 6.2 0.03 0.09 2.06 3.74 0.07 0.15 1999 2.26 3.9 0.05 0.17 2.14 3.31 0.07 0.15 2000 2.59 3.7 0.04 0.07 1.84 2.49 0.04 0.10 2001 4.38 5.9 0.04 0.19 1.84 2.71 0.05 0.11 2002 4.49 5.8 0.04 0.23 3.24 4.29 0.06 0.11
The mean total nitrogen and total phosphorus losses in the river Porijõgi catchment area in 1995-2002 were 3.4 and 0.12 kg/ha*yr, respectively (Fig. 5.1.2.1). The average losses of nitrogen from the Räpu basin in 1995 – 2002 were somewhat higher - 5.0 kg/ha*yr but losses of phosphorus were on the same level, 0.12 kg/ha*yr, respectively. The nitrogen run-off ranged in Porijõgi between 2.5 to 4.3 kg/ha*yr and in river Räpu between 2.9 to 7.0 kg/ha*yr.
33
The average total nitrogen content in 59 monitored rivers in Estonia in 1992-2001 with 90% probability does not exceed 4.0 mg/l (Leisk and Loigu, 2001). It means, that nitrogen concentrations in agricultural rivers are fairly close to the observed values in other monitored rivers. No remarkable change has been observed in nitrogen runoff during the monitoring period.
8 NO3-N Räpu 0.25 PO4-P Räpu TOT-N Räpu TOT-P Räpu 7 NO3-N Porijõgi 0.2 6 TOT-N Porijõgi PO4-P Porijõgi TOT-P Porijogi
5 a 0.15 h 4 / kg
kg/ha 0.1 3 2 0.05 1 0 0 1995 1996 1997 1998 1999 2000 2001 2002 1995 1996 1997 1998 1999 2000 2001 2002 Year Year
Figure 5.1.2.1. Annual nitrogen and phosphorus runoff in two agricultural catchments in 1995-2002
Based on the data from two monitoring sites the total yearly nutrient load from agricultural areas of Estonian side of L. Peipsi catchment area was 2835 tons of nitrogen and 34 tons of phosphorus. Nutrient losses from agriculture in recent years are low to compare with recorded results in 1980-ies, when annual losses were 10 – 32 kg/ha and 0.22-0.55 kg/ha for nitrogen and phosphorus respectively (Loigu and Velner, 1985). Nutrient losses in Estonia are relatively low also to compare with measured losses in similar meteorological conditions in the Nordic countries where it ranges roughly from 10-70 kg N/ha*yr (Gustafson, 1995, Kronvang et al., 1993; Rekolainen, 1989; Rekolainen et al., 1995; Vagstad, 1994; Vagstad et al., 2001). It is much higher than observed losses in Estonia in 1990is and indicates major differences in leaching regimes between different countries. One important factor could be difference in fertilizers application rates. Relatively low nutrient runoff to compare with Nordic countries can be explained also by low animal density, with prevailing natural and cultural grasslands in land use and by differences in hydrological conditions, i.e. longer water residence time and high nutrient buffering capacity and retention within catchments. The maintenance of main ditches has been not sufficient during the last decade and watercourses are overgrown with bushes and macrophytes that support nitrogen losses by denitrification. Also in condition of calcareous soils the pH value is high and ammonia (NH3) volatilization takes place. It means that interaction between basin properties (soil, climate, hydrology, topography) and agricultural management and their relative influence are of critical importance for nutrient losses from the basins. Forced by the limited agricultural productivity, nutrient load is very low but improvement of economic environment can lead to the increased leaching of nitrogen. In study plot experiments, conducted in the 2 demonstration catchments (R. Räpu and R. Rägina), expert assessment concludes that nitrogen average content in intensive agricultural areas can reach 5 mgN/l. Considering that Estonian runoff is 270-290 mm yr-1, it can be concluded that nitrogen losses from arable land form 14 to 15 kg/ha*yr. Applying water management and protection measures on L. Peipsi, these conclusions should be considered.
5.1.3. Source apportionment
34
Estimation of different emissions indicates that background load from natural areas is relatively high. Background load forms 47% of N and 45% of P total inputs (Fig. 5.1.3.1.). It can be explained by the low intensity and high extensity of agricultural land use characterised by low fertilisation rate. The aim of water management should be the reduction of human load, not natural load. Non-point N pollution from agriculture is responsible for 44% of total N input. The eutrophying role of natural nitrogen input is, however, much smaller than that of anthropogenic point and non-point source nitrogen, because natural nitrogen is tightly bound in organic compounds (humic acids) which are very stable in water. N load from point sources contributes only 6% to the total load. N deposition to the surface water is 3%. Wastewater treatment plants emit 29% of total P inputs. Also, P agricultural input is significant (19%). The contribution of P from agricultural land includes load from sparse population areas because these cannot be separated. In reducing N pollution, the most cost- effective is to reduce agricultural load while reduction of P load requires better purification and minimisation of wastewaters. Combating eutrophication of L. Peipsi requires to start with the reduction of phosphorus inputs to the lake.
Nitrogen Phosphorus 7%
3% 6% 45%
47% 29
19% 44% Point sources Agriculture Background load Atmospheric deposition
Figure 5.1.3.1. Share of N and P river inputs from different sources
5.1.4. Chemical status The main water quality indicators which characterize the ecological status of surface waterbodies are: 1. Biochemical oxygen demand 2. Nutrient (nitrogen and phosphorus) contents The biochemical oxygen demand of natural river water not affected by human activity is a rule less than 3.0 mgO/l. BOD7 values 3-5 mgO/l indicates low human impact and values generally more than 5 mgO/l indicate obvious pollution. Estonian environmental monitoring data indicate continuous improvement of water quality. Somewhat higher BOD level was observed in R. Emajõgi and in R. Narva (Fig. 5.1.4.1). Increased BOD level of these rivers does not indicate direct pollution but they characterize secondary pollution derived from intensive phytoplankton bloom. That explains high variability of BOD content in R. Narva characterizing also the trophic state of L. Peipsi. The main element limiting primary production in Estonian surface waters is phosphorus. The highest permissible value of total phosphorus preventing eutrophication is 0.10 mgP/l (Loigu, 1993). Mean content of total phosphorus and phosphates in background rivers in 1992-1999 was correspondingly 0.05 mgP/land 0.025 mgP/l. Increased content of phosphorus appears in rivers that receive municipal wastewaters (R. Võhandu, R. Tarvastu, R. Emajõgi, R. Ahja, R. Narva). As a rule, despite of impact of wastewaters, content of total phosphorus has remained below 0.15 mgP/l (Fig. 5.1.4.1).
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Narva-Vasknarva Õhne Emajõgi-Kavastu Tänassilma Emajõgi-Rannu-Jõesuu Tarvastu Tarvastu Ahja Rannapungerja Pedja-Tõrve Alajõgi Emajõgi-Kavastu Avijõgi Võhandu Kääpa Piusa Väike-Emajõgi Emajõgi-Rannu-Jõesuu Porijõgi Väike-Emajõgi Pedja-Tõrve Porijõgi Õhne Avijõgi Tänassilma Narva-Vasknarva Põltsamaa Alajõgi Ahja Kääpa Võhandu Rannapungerja Piusa Põltsamaa 0123456789 0 0.05 0.1 0.15 0.2 0.25 0.3
BOD7, 90% values, mgO2/l Total phosphorus, 90% value, mgP/l Classes I II III IV Classes I II III IV V
Alajõgi Avijõgi Rannapungerja Tarvastu Pedja-Tõrve Põltsamaa Emajõgi-Kavastu Figure. 5.1.4.1. Variability of Narva-Vasknarva Tänassilma Õhne annual value (by 90-percentile) Väike-Emajõgi Kääpa Emajõgi-Rannu-Jõesuu of BOD , total phosphorus and Porijõgi 7 Ahja Piusa total nitrogen concentration in Võhandu rivers of L. Peipsi basin in 0123456789 Total nitrogen, 90%-value, mgN/l 1992-2001. Classes IIIIIIIVV
The mean concentration of N in reference rivers not affected by human activity is 1.1 mgN/l. Extremely high N content was in Alastvere main ditch that situates in nitrate-sensitive area influenced by intensive farming.
5.1.5. Pollution load to L. Peipsi From 2000 - 2002 L. Peipsi received about 240 tons of phosphorus and more than 6700 tons of nitrogen. These two nutrients are main substances responsible for eutrophication. Pollution load values correlated highly with water runoff (Fig. 5.1.5.1.). The biggest river Emajõgi contributes 74% of BOD and N load. Load of phosphorus from R. Emajõgi formed 67% of total phosphorus load from Estonian side to L. Peipsi. Year 1996 was extremely dry and water runoff formed only ca 60% of average long-term runoff. Especially low flow rates were observed in summer time when minimal runoff values remained below 95 percentile. In the same time, year 1998 characterises wet period. Of total nitrogen 63% and of total phosphorus 35% were phosphate and nitrate, respectively. Our nutrient load estimates well confirm the results of Stålnacke et al., 2002. Between 1984 and 1987 annual load of nitrogen from Estonian side to L. Peipsi was ca 9000 tons while phosphorus load was more than 300 tons. Thus, the loads have decreased during 1990s. Flow weighted concentrations of nitrogen, phosphorus and BOD7 fluctuated (Fig. 5.1.5.1.). High concentrations were observed in dry years when the direct impact of wastewaters was higher due to low dilution capacity. During recent years, concentration of nitrogen has been increasing. According to classification of chemical status of water quality the annual BOD concentration is below 3.0 mgO/l characterising high quality. Phosphorus concentration fluctuates around the threshold between good and moderate quality class. Nitrogen concentration was between 1.5 and 2.5 mgN/l characterising good status.
36
NO3 14000 A 6000 10000 N-t ot 6000 BOD7 9000 B 12000 5000 W W 8000 5000 10000 4000 7000 4000 r 6000 8000 /yr ³ r 3000 5000 3000 m³/y m t/y t/yr 6 6000 4000 6 10 2000 2000 10 4000 3000 2000 2000 1000 1000 1000 0 0 0 0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 PO4 3.5 0.1 350 P-tot 6000 D 0.09 3 W 300 C 5000 0.08 2.5 0.07 250
4000 l 2 0.06 200 0.05 P/ 3000 m³/yr t/yr 1.5 mg 150 6 0.04 10 2000 1 N/W BOD7/W P/W 0.03 100 BOD7, N, mg/l 0.02 1000 0.5 50 0.01 0 0 0 0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Figure 5.1.5.1. Load of biochemical oxygen demand (BOD7, left axis: A), total nitrogen (Ntot, left axis: B), nitrates (NO3, left axis: B), total phosphorus (Ptot, left axis: C), phosphates (PO4, left axis: C) and water runoff (W, right axis: A, B, C) into L. Peipsi, and D: runoff adjusted
concentrations of nitrogen (N/W), BOD7/W and phosphorus (P/W).
5.2. BIOLOGICAL STATUS OF L. PEIPSI RIVER BASIN
5.2.1 BACTERIA Table 5.2.1.1. summarizes status of rivers in L. Peipsi basin according to saprobacterial abundance. By far most of the samples (83%) fall into β-mesosabrobic category. According to Lokk et al, (1988) the natural reference value of saprobacteria in Estonian rivers is 1000 cells/ml, which coincides with the oligosaprobic class boundary and is probably too stringent. River biology experts have suggested to use 1500 cells/ml, as a natural reference value for Estonian rivers, which gives a frequency of 71 (38%) samples from the L. Peipsi basin as in near-natural state.
Table 5.2.1.1. Assessment criteria of sabrobity of Estonian rivers based on the classical 4 categories: O – oligosaprobity, β-M - β-mesosaprobity, α-M - α-mesosaprobity, P – polysaprobity based on sparobacterial concentrations in river water. Frequency of river samples in different saprobic classes in L. Peipsi basin (77 rivers, 187 river samples), percentage of distribution in parenthesis (after Pall, 2001). O β-M α-M P Saprobacteria (cells/103ml) < 1 1-5 5-10 > 10 Frequency of occurrence 17 (9.1) 155 (82.9) 9 (4.8) 6 (3.2)
The requirements for coliform bacteria are met by most of the studied Estonian rivers in near- natural state, apart from a few exceptions where slight faecal contamination was likely (two sations in Põltsamaa river). The proposed natural reference value for coliform bacteria in Estonian rivers is < 150 cells/100ml, the proposed boundary between good and moderate status is 500 cells/100ml (Lokk et al., 1988). Based on the proposed criteria for coliform bacteria in Estonian rivers (reference value < 150 cells/100ml, boundary between good and moderate status 500 cells/100ml), 190 river samples were below the natural reference value and 260 (82%) were within at least good status. The frequency distribution of river samples in L. Peipsi basin according to commonly used concentration classes is given in Table 5.2.1.1.
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Table 5.2.1.1. Concentration of coliform bacteria in river samples (n=317) of L. Peipsi basin. Abundance scale according to Pall (2001). The frequency of occurrence is followed by percentage of distribution in parenthesis. Fit for swimming Not fit for swimming Coliform bacteria (cells/100ml) < 5 5-240 240-700 > 700 Frequency of occurrence 24 (7.6) 175 (55.2) 61 (19.2) 57 (18)
5.2.2. PHYTOPLANKTON AND CHLOROPHYLL The phytoplankton of Estonian rivers is quite heterogeneous (Piirsoo, 2001; Piirsoo, Trei & Laugaste, 1997). It should be reiterated that phytoplankton based indicators should not be used as universal in Estonian rivers. They are applicable only in lareger river systems where true potamoplankton develops, like Emajõgi, Narva, Väike Emajõgi, Võhandu, Põltsamaa, Piusa, Elva, etc. Only in such river basins the small discharge and reduced flow velocity lead to elevated water temperature and phytoplankton abundance can be very high. The phytoplankton in such rivers is dominated by cryptophytes Cryptomonas spp, Rhodomonas spp., chlorophytes from the genera Monoraphidium and Scenedesmus, planktonic diatoms from the genera Cyclotella and Stephanodiscus. In these rivers and river reaches, the biomass of phytoplankton is in good correlation with the concentration of nutrients and organic pollution (Piirsoo et al., 1997). Abundance of cyanobacteria (e.g. Planktothrix agardhii), frequently accompanied by Euglena viridis, indicates strong pollution, as in the case of Väike Emajõgi (Piirsoo, 2001; Piirsoo et al., 1997). Due to the short residence time, the majority of the first and second order streams in Estonia do not develop well-defined phytoplankton assemblages. The planktonic forms are dominated (in number and biomass) by small difficult to identify flagellates (including Cryptomonas cf. erosa, C. cf. obovata, C. cf. ovata and C. cf rostratiformis and unidentified small flagellates). The majority of algae in these rivers are benthic diatoms re-suspended from bottom or macrophytes (e.g. Cocconeis pediculus, C. placentula, Nitzschia acicularis, Achnanthes minutissimum, Synedra ulna, Meridion circulare, Rhoicosphenia curvata Melosira varians are found in over 50% of the investigated rivers). Phytoplankton abundance is positively correlated with the area of the drainage basin of the river. Planktonic diatoms prevail in big river systems and non-planktonic diatoms in small rivers. Generally, diatoms and chlorophytes prevail in species number, diatoms and cryptomonads in biomass. In large rivers phytoplankton biomass and composition is a good indicator of the water quality; in small rivers the water quality is better characterized by benthic and epiphytic diatoms. In most rivers, hydrological regime has a far stronger effect on phytoplankton than chemical properties of the water. In most rivers nutrient supply (P and N) is sufficient and has no direct limiting effect on phytoplankton. More importantly, river banks are often bordered with trees and shrubs, and phytoplankton growth and nutrient uptake is limited by light. Chlorophyll summer concentrations in Estonian rivers indicates that generally the level of phytoplankton is less what is considered eutrophic or hypertrophic in lakes. High levels of phytoplankton does not interfere with the functioning of the river system itself (e.g. turbidity, high daily variance of oxygen content), with consequences for other groups of organisms (zoobenthos, fish). Apart from a relatively few exceptions Estonian rivers cannot be considered plankton dominated (sensu Behrendt & Opitz, 2001). The quartile values of summer time chlorophyll a concentrations (measured after Jeffrey-Humprey) in L. Peipsi basin river samples (n=257) were 1.6, 2.5, and 4.7 mg/m3. However, in the high end the chlorophyll concentration increased rapidly: in 5% of the river samples chlorophyll a concentrations > 18 mg/m3 (max 58 mg m3 as) indicated strong phytoplankton development. These can be considered low values compared to chlorophyll a concentrations in large European river systems like Elbe and Oder, where most of the values
38 are > 10 mg/m3 (Behrendt & Opitz, 2001). Based on transfer functions from phosphorus to chlorophyll concentrations, the reference state of the latter, calculated for German rivers, is 38 mg m3, and good ecological status can be assigned to rivers with < 55 mg/m3 (Behrendt & Opitz, 2001). From these figures it becomes apparent that in the majority of Estonian rives the phytoplankton does not fulfill the whole production potential, and with a few extreme exceptions, the status is good.
5.2.3. BENTHIC DIATOMS The composition of soft bottom diatom assemblages from Estonian rivers and association with environmental variables has been analysed by Vilbaste and Truu (2003). In this study out of the total of 205 diatom taxa as much as three-quarters were regarded sproradic (encountered once or twice), and approximately 50 constant taxa comprised 90% of the total cell counts. The most common species were Achnanthidium minutissimum, Martyana martyi, Meridion circulare, Cocconeis placentula, Planothidium lanceopatum and Amphore pediculus (Vilbaste & Truu, 2003). The benthic diatom assemblages were significantly influenced by the trophy of the water (12% of the variation in the data), but also by the order of the stream, which largely determines the trophy. Headwaters and first order streams with oligo- or mesotrophic water are characterized by small non-motile diatoms: Martyana martyi, Planothidium delicatulum, Staruosira cf. construens var. venter, Staurosirella leptostauron, and S. pinnata. In higher order stream reaches with eutrophic or hypertrophic waters the benthic diatom assemblages are characterized by Amphora pediculus, Cocconeis placentula and Navicula spp. (e.g. N. tripunctata, N. gregaria, N. cryptotenella) (Vilbaste & Truu, 2003). This pattern is in accord with a more general ecological gradient in lotic systems, where obligate epipsammic species, attached to sand grains (Round, 1965), can tolerate erratic turbulent environments and colonize headwaters. In lower courses and plain lowland rivers where current is slower and habitats are more sheltered the diatom assemblages change to motile epipelic associations with frequent occurrence of Amphora, Navicula, Nitzschia, etc. (Brown, Gibby & Hickman, 1972). Judged upon the concentration of mineral N and P in Estonian waters, it is assumed that nutrients do not limit the algal primary production (Järvekülg, 2001a). However, the trophic state of the water has a notable effect on the composition of the benthic diatom assemblages (Vilbaste & Truu, 2003). This effect is combined with the change in assemblage composition from headwaters to lower courses. The actual forcing factor is difficult to discern, as the trophy tends to be generally higher in higher order rivers (correlation between the order of the stream and trophic level r=0.35, p<0.05), but quite variable in the first order stream reaches (Vilbaste & Truu, 2003).
5.2.4. MACROZOOBENTHOS Macrozooplankton of Estonian rivers was intensively investigated by A. Järvekülg (Järvekülg, 2001a). The status of rivers in the L. Peipsi basin, based on summertime (July – August) samples is given in Tables 5.2.4.1 and 5.2.4.2.
Table 5.2.4.1. Criteria to classify Estonian rivers according to the number of taxa, abundance of organisms, and biomass of benthic invertebrate fauna (after Järvekülg, 2001b). Very low Low Medium High Very high Number of taxa ≤ 10 11-30 31-40 41-50 >50 Abundance < 1 1-5 5-10 10-20 > 20 (103specimen/m2) Biomass (g/m2) < 1 1-10 10-25 25-50 >50
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Table 5.2.4.2. Distribution of river samples of the L. Peipsi basin between the classes defined in Table 6. Number in parenthesis denotes the percentage in the particular class out of the total 180 river reaches (after Järvekülg, 2001b). Very low Low Medium High Very high Number of taxa 1 (0.5) 48 (26.7) 43 (23.9) 55 (30.6) 33 (18.3) Abundance 17 (9.4) 42 (23.3) 75 (41.7) 34 (18.9) 12 (6.7) Biomass 2 (1.1) 24 (13.3) 80 (44.4) 55 (30.6) 19 (10.6)
According to an alternative approach, the most suitable time for macrozoobenthos sampling is spring. E.g. many sensitive insect larvae are already not present in summer and are not fully developed in autumn making identification impossible. During 1985-1999 qualitative macroinvertebrate samples were collected from Estonian Rivers by H. Timm (Võrtsjärv Limnological Station, IZB). To assess the quality status of the rivers, the British Average Score Per Taxon (ASPT) was used. The method (Armitage et al., 1983) lists macroinvertebrate families present in the sample and determines the score of each family. ASPT Index is the mean score of all the scoring families. ASPT values are positively correlated to organic pollution and/or general ecological quality (Armitage et al., 1983; Johnson, 1999). Table 5.2.4.2 shows the investigated rivers from the L. Peipsi catchment, the corresponding ASPT score and associated quality status (Johnson, 1999). Polluted and unpolluted sites within a stream are not separated in calculations, as well as the upper and lower reaches of small streams.
Table 5.2.4.3. Mean ASPT values and quality estimates (after Johnson, 1999, for small streams). Stream n mean Quality ASPT Piusa 16 6.0 intermediate Võhandu (upstream of Lake Vagula) 17 6.5 high Võhandu (downstream of Võru Town) 10 5.9 intermediate Võhandu (Räpina) 2 5.1 low Väike Emajõgi (upper) 12 6.4 high Väike Emajõgi (Tõlliste) 2 7.0 very high Väike Emajõgi (Pikasilla)* 2 4.7 low Õhne (upper) 5 6.4 high Õhne (Roobe) 2 6.8 high Õhne (Suislepa) 1 6.5 high Tarvastu 3 5.7 intermediate Emajõgi (upstream of Tartu Town) 30 5.2 low Emajõgi (downstream of Tartu Town) 29 4.1 very low Pedja (upstream of Jõgeva Town) 6 5.9 intermediate Pedja (downstream of Jõgeva Town) 6 5.5 intermediate Preedi 3 5.7 intermediate Põltsamaa (upstream of Endla Nature 58 4.4 very low Reserve) Põltsamaa (downstream of Endla Nature 4 5.8 intermediate Reserve) Oostriku 1 5.6 intermediate Porijõgi 18 6.0 intermediate Ahja (upper) 11 5.6 intermediate Ahja (Lääniste) 1 6.3 high Kääpa 11 5,5 intermediate Avijõgi 8 6,0 intermediate Rannapungerja 4 5,3 intermediate
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Tagajõgi 3 5,9 intermediate Alajõgi 1 5,3 intermediate Total number of samples 266 Mean ASPT 5,7 intermediate
In most cases, ASPT index revealed medium biological quality. The Emajõgi River (downstream of Tartu) and the upper course of Põltsamaa River showed very low quality, probably caused by human activities. Possibly the quality status in the Table 5.2.4.3 can be somewhat underestimated due to smaller sample size naked eye sorting of the animals in the field, as compared to laboratory stereomicroscope sorting in Johnson (1999).
5.2.5. MACROVEGETATION The vascular plants in Estonian rivers tend to form monodominant stands. The most frequent dominants are Schoenoplectus lacustris, Nympha lutea, Sparganium erectum, and Equisetum fluviatile. On stones Fontinalis antipyretica was a frequent dominant. The dominant filamentous macroalgae in Estonian rivers are chlorophytes Gladophora glomerata, C. rivularis, Ulothrix zonata, and tribophycean Vaucheria spp. (Piirsoo et al., 1997). Mass occurrence of filamentous algae indicates high trophic levels. During the years of the survey (1994 – 1999) the biomass of filamentous algae had dropped, which could be a response to the diminished use of agricultural fertilizers (Piirsoo et al., 1997). Notable occurrence of filamentous algae was recorded in only one case out of 41 rivers of near-natural state. Rhodophytes, Chantransia chalybea, Hildenbrandia rivularis and Batrachospermum grow in natural, undisturbed envirionments in Estonian rivers. However, their absence in many pristine rivers (rhodophytes were found only in 8 out of 41 rivers of near-natural state) is most probably related to absence of suitable habitats, not to compromised quality of the water. Algal mats, which are formed by microscopic cyanobacteria and/or diatoms, indicate strong organic pollution. Algal mats were not found in any of the 41 rivers considered as in near-natural condition. One of the conclusions is that in Estonian rivers, macrovegetation as a life-form depends on several naturally occurring conditions, which are not considered in the Water Framework Directive. E.g. light conditions have an instrumental role in determining the macrophyte community structure and species composition.
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6. INDICATORS AND CRITERIA FOR ASSESSMENT OF ECOLOGICAL STATUS OF LAKE PEIPSI
6.1. CHEMICAL AND PHYSICAL PROPERTIES AND PHYTOPLANKTON (P. NÕGES, R. LAUGASTE, T. NÕGES)
According to the EU Water Framework Directive (WFD; Directive, 2000/60/E) , the class boundaries in quality classification are set using ecological quality ratios (EQR). EQR is a numeric index showing the degree of deviation of any studied parameter from the initial reference value. As a quality objective for L. Peipsi we set the reference TP concentration multiplied by 1.5 that is close to the EQR suggested by Premazzi et al. (2003) for mesotrophic Italian lakes to meet the ecological quality objectives.The estimated TPref and EQR for the ‘good’ - ‘moderate’ boundary enable to calculate the actual TP values characterising this boundary for L. Peipsi:
3 3 TPgood = 1.5 * 23 = 34 mg/m (present average 44 mg/m )
As the present TP concentration in L. Peipsi exceeds the set goal, the water quality can be considered ‘moderate’. Considering the actual TP values measured in L. Peipsi since 1982 (from 8 to 172 mg/m3), they range clearly from ‘high’ to ‘bad’. As the average value characterises the lake quality as ‘moderate’, we used the 10th and 90th percentiles to delimit reference conditions and/or bad conditions (depending whether the parameter is positively or negatively correlated with quality) and the 25th and 75th percentile for the boundaries between ‘good’-‘moderate’ and ‘moderate’-‘poor’ conditions. In order to eliminate the effect of seasonality, class boundaries were calculated separately for each month (Table 6.1.1.).
Table 6.1.1. Seasonal quality class boundaries for L. Peipsi based on monthly total phosphorus concentrations Month High/good Good/mod Mod/poor Poor/bad Feb 0.021 0.029 0.035 0.053 Mar 0.017 0.023 0.040 0.058 Apr 0.009 0.013 0.042 0.052 May 0.024 0.027 0.047 0.055 Jun 0.020 0.022 0.034 0.043 Jul 0.018 0.028 0.049 0.060 Aug 0.022 0.039 0.062 0.076 Sep 0.024 0.033 0.064 0.072 Oct 0.031 0.040 0.067 0.077 Nov 0.029 0.040 0.060 0.066
Other ecological water quality indicators were selected on the basis of having significant correlation with TP as the main pressure factor. In the analysis we used monthly splitted data set from 1982 to 2002. This allowed us, besides of selecting the appropriate variables, decide also upon their seasonal applicability as quality parameters (Table 6.1.2.).
Table 6.1.2. Variables correlating with TP in Lake Peipsi, general correlation coefficient (all data included) and the periods of significant (p<0.05) relationship Parameter r Months Secchi depth -0.60 3-9 BOD7 0.23 3-6; 8; 11 Chl a 0.40 3-4; 6-10 Car/Chl a (carotenoid/chlorophyll ratio) -0.31 5-8; 10 BAC (biomass of diatoms) 0.30 4; 9
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Cy% (% of cyanobacteria in phytoplankton biomass) 0.19 8 ZB/FB (zooplankton/phytoplankton biomass ratio) -0.29 4-6; 9-11
We used similar percentiles (10, 25, 75 and 90) as in case of TP for class boundaries for other quality parameters (Tables 6.1.3- 6.1.9).
Table 6.1.3. Seasonal quality class boundaries for L. Peipsi based on Secchi depth (m) Month High/good Good/mod Mod/poor Poor/bad Mar 4.0 3.2 1.4 0.7 Apr 2.9 2.5 2.0 1.5 May 2.6 2.3 1.8 1.4 Jun 3.0 2.7 1.9 1.5 Jul 2.4 2.0 1.7 1.4 Aug 2.5 2.0 1.5 1.2 Sep 1.9 1.6 1.0 0.9
Table 6.1.4. Seasonal quality class boundaries for L. Peipsi based on biochemical oxygen demand (BOD7, mgO/l) Month High/good Good/mod Mod/poor Poor/bad Mar 1.00 1.00 1.80 2.80 Apr 1.60 1.80 3.00 3.30 May 1.60 1.80 2.60 3.00 Jun 1.30 1.45 2.15 2.50 Aug 1.10 1.40 2.50 4.10 Nov 1.30 1.40 2.00 2.80
Table 6.1.5. Seasonal quality class boundaries for L. Peipsi based on Chl a concentration Month High/good Good/mod Mod/poor Poor/bad Mar 0.8 1.3 4.8 9.8 Apr 9.4 9.8 35.5 55.9 Jun 5.0 7.4 15.4 19.9 Jul 7.2 9.5 19.3 24.2 Aug 10.7 15.7 27.8 35.9 Sep 16.8 19.5 30.9 37.0 Oct 11.2 14.2 30.4 39.9
Table 6.1.6. Seasonal quality class boundaries for L. Peipsi based on carotinoid/chlorophyll a ratio (mg/mg) Month High/good Good/mod Mod/poor Poor/bad May 61 57 39 28 Jun 68 56 36 31 Jul 56 49 32 21 Aug 55 47 27 20 Oct 39 35 18 1
Table 6.1.7. Quality class boundaries for L. Peipsi based on April and September biomass values of diatoms (mgWW/l) Month High/good Good/mod Mod/poor Poor/bad Apr 1.1 1.7 7.6 8.1
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Sep 1.6 2.3 5.6 8.5
Table 6.1.8. Quality class boundaries for L. Peipsi based on cyanobacteria percentage in phytoplankton biomass (mgWW/l) in August Month High/good Good/mod Mod/poor Poor/bad Aug 12.5 41.5 71.9 82.0
Table 6.1.9. Seasonal quality class boundaries for L. Peipsi based on zooplankton/phytoplankton biomass ratio (mg/mg) Month High/good Good/mod Mod/poor Poor/bad Apr 0.18 0.15 0.02 0.01 May 1.92 0.82 0.08 0.01 Jun 2.92 1.42 0.35 0.21 Sep 0.52 0.17 0.07 0.03 Oct 0.68 0.39 0.08 0.03 Nov 0.23 0.09 0.03 0.02
According to the expert opinion, the ecological status of L. Peipsi improved after heavy loading of the 1980s but deteriorated again in the second half of the 1990s and in the 2000s. Although the quality parameters were selected on the basis of their correlation with TP, they show rather different patterns (Fig. 6.1.1.) The improvement of the ecological quality in the first half of the 1990s is most evident from the quality indices calculated on the basis of Chl a, carotenoid/chlorophyll ratio and Secchi depth. The following deterioration of the lake quality is well seen in the quality indices calculated on the basis of Chl, zooplankton/phytoplankton biomass ratio and, especially, cyanophyte percentage, while Secchi depth, carotenoid/chlorophyll ratio and diatom biomass show even an improvement. The chlorophyll-based quality index achieved the best fit with the expert opinion and with the common understanding of the lake quality. As this index can be calculated nearly for all months from spring to autumn, we recommend to use this index as the best quality descriptor for L. Peipsi. According to this index, the lake reached a ‘poor’ quality by the end of the 1980s. There was a clear improvement of the quality until 1996 while in several years the average ecological quality could be evaluated as ‘good’. Since 1997 there has been a continuous and even accelerating deterioration in the lake quality, which reached in 2002 the ’poor’ quality class again.
44
5.0 5.5 Bad Bad 4.5 Poor 4.5 4.0
a Poor l
Ch 3.5 r/ 3.5
Ca 3.0 Moderate y Moderate
ss b 2.5 a 2.5
y cl Good t i l 2.0 Good a
Qu 1.5 1.5 High High
1.0 Quality class by blue-green % in August 1983 1986 1988 1992 1994 1996 1998 2000 2002 0.5 1983 1986 1988 1992 1994 1996 1998 2000 2002 1985 1987 1991 1993 1995 1997 1999 2001 1985 1987 1991 1993 1995 1997 1999 2001 Year Year
5.5 5.0 Bad Bad 4.5 4.5 Poor Poor 4.0 ass ratio 3.5 3.5 Moderate Moderate 3.0 2.5 2.5
Good 2.0 Quality class by Chl a 1.5 Good 1.5
High uality class by Zp&Fp biom High 0.5 Q 1.0 1983 1986 1988 1992 1994 1996 1998 2000 2002 1983 1986 1988 1992 1994 1996 1998 2000 2002 1985 1987 1991 1993 1995 1997 1999 2001 1985 1987 1991 1993 1995 1997 1999 2001 Year Year
5.5 5.0 Bad Bad 4.5
4.5 Poor 4.0 Poor
P 3.5 l a 3.5 t Moderate o 3.0 Moderate 2.5
2.5 ass by t
y cl 2.0 t
i Good Good 1.5 1.5 Qual Quality class by Secchi depth High 1.0 High
0.5 0.5 1983 1986 1988 1992 1994 1996 1998 2000 2002 1983 1986 1988 1992 1994 1996 1998 2000 2002 1985 1987 1991 1993 1995 1997 1999 2001 1985 1987 1991 1993 1995 1997 1999 2001 Year Year
5.0 5.0 Bad Bad 4.5 4.5
4.0 Poor 4.0 Poor
3.5 7 3.5 D O 3.0 Moderate 3.0 Moderate
2.5 2.5
2.0 Good 2.0 Good
1.5 1.5 Quality class by B
1.0 1.0 High High Quality class by Fp species number 0.5 0.5 1983 1986 1988 1992 1994 1996 1998 2000 2002 1983 1986 1988 1992 1994 1996 1998 2000 2002 1985 1987 1991 1993 1995 1997 1999 2001 1985 1987 1991 1993 1995 1997 1999 2001 Year Year
Figure 6.1.1. Long-term changes in the ecological quality of L. Peipsi as estimated according to different quality parameters 45
6.2. Zooplankton (T.Virro & J.Haberman)
The present analysis is based on zooplankton samples from 3 observation periods: 1965– 1966, 1985–1987 and 1992–2001. It is generally accepted that during these years L. Peipsi has changed from oligo-mesotrophic in 1960s to meso-eutrophic state in 1990s. In 1970s, an intensive anthropogenic eutrophication began which lead to higher trophy. In 1980s, the lake was nearly eutrophic. Sharp decrease in nutrient level was observed in early 1990s. After critical analysis of existing data 25 potential zooplankton indicators were selected for further evaluation. Long-term changes of these indicator parameters were analysed in relation to the general trends of the trophic state of L. Peipsi, and then a tentative set of most suitable zooplankton indicators for assessment of ecological status was distinguished (Table 6.2.1). Analysing the present dataset it seemed reasonable to distinguish 3 periods reflecting different ecological states in the lake succession: 1965–1966, 1985–1992 and 1993–2001. The assessment of the present ecological status of L. Peipsi is based here on the following assumptions: • The oligo-mesotrophic period 1965–1966 is considered as reference state. In fact, this is the only available reference state so far. • The eutrophic period (1985–1992) is considered as undesirable state for L. Peipsi ecosystem. According to the selected zooplankton parameters and the WFD water quality classes the present ecological status of L. Peipsi can be summarily evaluated as ‘good’ or ‘good’/‘moderate’ (Table 6.2.2). The eutrophic period can be labelled as ‘moderate’ status. Preliminary criteria for distinguishing ‘good’ and ‘moderate’ statuses in the case of L. Peipsi are proposed in Table 6.2.3.
The set of indicators used: • N Zpl – Total zooplankton number (103 ind/m3). General trend: increasing with lake trophy. No significant (at p<0.05) correlation with Trophic State Index based on Chl a concentrations (TSI(Chl)) occurred in the present material. • B Zpl – Total zooplankton biomass (g/m3). General trend: increasing with lake trophy. No correlation with TSI(Chl). Significantly correlated with TSI based on water transparency (TSI(SD)) (r=0.60, p<0.05). • B/N – Mean zooplankter weight (µg). General trend according to the present data: increasing with lake trophy. This is contradictory with most of the literature data: mean zooplankter weight should decrease during eutrophication. It seems probable that B/N reflects rather cahnges in food web structure than changes in trophic state. B/N should be strongly affected by fish predation. Medium positive (but not significant at p<0.05) correlations with TSI(Chl) and TSI(SD), and medium negative correlation (also n.s.) with planktivorous fish catch were detected in the present material. • N Rot – Number of Rotifera (103 ind/m3). General trend: increasing with lake trophy. No significant correlation with TSI(Chl). • B Rot – Biomass of Rotifera (gWW/m3). General trend: increasing with lake trophy. No significant correlation with TSI(Chl). • RotN% – Percentage of Rotifera in total zooplankton number. Expected general trend: increasing with lake trophy. No significant correlation with TSI(Chl) but a significant positive correlation with planktivorous fish (r=0.57, p<0.05). • RotB% – Percentage of Rotifera in total zooplankton biomass. General trend: increasing with lake trophy. No significant correlation with TSI(Chl) but a significant positive correlation with planktivorous fish (r=0.56, p<0.05).
46
• B Cop – Biomass of Copepoda (g/m3). General trend: decreasing with lake trophy rise. No significant correlation with TSI(Chl). • B Daph / B Cru – Percentage of Daphnia in crustacean biomass. General trend: decreasing with lake trophy rise. No significant correlation with TSI(Chl). The indicator values are highly variable. The values of RotN%, RotB% and B Zpl are less dispersed. B/N behaved contradictory. It seems probable that B/N and many other zooplankton indicators (e.g. B Cop, B Daph / B Cru, etc.) reflect rather changes in food web structure than changes in trophic state. These indicators should be strongly affected by fish (or invertebrate) predation. Relative indices (e.g. RotN%, B/N) cannot be used without monitoring the dynamics of absolute values of the parameters involved. Changes in these parameters may have different speeds.
Table 6.2.1. Selected zooplankton indicators and their parameters for L. Peipsi in different periods. Quart1 = lower quartile; Quart3 = upper quartile. Min Max Median Quart1 Quart3 Average SD N Zpl (103 ind/m3) 1965-2001 12.53 2752.20 510.28 183.62 1029.39 706.44 644.30 1965-1966 58.57 1257.27 189.33 114.59 545.62 422.69 439.26 1985-1992 12.53 2752.20 930.58 373.16 2060.00 1178.89 971.52 1993-2001 37.14 1608.83 537.25 238.94 978.17 618.34 420.64 B Zpl (gWW/m3) 1965-2001 0.035 6.344 1.475 0.718 2.310 1.661 1.307 1965-1966 0.035 2.931 0.270 0.088 1.460 0.893 1.005 1985-1992 0.088 6.344 1.692 1.214 2.817 2.104 1.494 1993-2001 0.047 6.153 1.537 0.802 2.311 1.757 1.232 B/N (µg) 1965-2001 0.4528 55.7995 2.5148 1.5495 5.5485 4.4664 6.7108 1965-1966 0.4528 9.3210 1.2132 0.6392 2.4363 2.3009 2.6677 1985-1992 0.6714 55.7995 2.1101 1.3533 4.8891 6.2274 12.7778 1993-2001 0.7244 16.9353 3.8474 2.1525 5.7428 4.5320 3.3688 RotN% (%) 1965-2001 23.0 105.1 77.7 63.6 90.5 75.7 18.7 1965-1966 57.4 105.1 96.7 82.2 98.6 88.8 14.5 1985-1992 30.2 98.6 85.1 74.0 93.9 80.3 17.5 1993-2001 23.0 97.8 72.0 61.3 82.6 69.2 17.7 RotB% (%) 1965-2001 1.6 92.0 25.9 8.6 45.8 31.8 26.7 1965-1966 1.8 86.9 53.7 9.2 74.5 43.3 34.5 1985-1992 1.6 92.0 32.4 17.5 60.9 38.3 29.4 1993-2001 1.9 86.3 19.8 7.1 32.3 25.1 20.3 N Rot (103 ind/m3) 1965-2001 9.59 2688.63 391.87 167.82 817.04 577.82 593.89 1965-1966 56.68 1033.29 187.62 86.60 496.19 348.42 353.68 1985-1992 9.59 2688.63 857.22 253.58 1787.92 1054.64 914.14 1993-2001 33.29 1475.03 391.87 187.25 634.00 468.65 367.97 B Rot (gWW/m3) 1965-2001 0.010 1.846 0.163 0.080 0.457 0.373 0.470 1965-1966 0.010 0.198 0.083 0.033 0.123 0.087 0.056 1985-1992 0.017 1.846 0.486 0.148 1.224 0.754 0.689 1993-2001 0.018 1.716 0.217 0.091 0.453 0.322 0.340 B Cop (gWW/m3) 1965-2001 0.003 2.267 0.484 0.195 0.784 0.552 0.459 1965-1966 0.003 1.298 0.098 0.020 0.678 0.337 0.409
47
1985-1992 0.007 1.649 0.349 0.196 0.640 0.489 0.414 1993-2001 0.027 2.267 0.588 0.347 0.801 0.653 0.471 B Daph./B Cru (%) 1965-2001 0.0 73.2 21.6 6.2 34.8 23.2 18.2 1965-1966 1985-1992 0.0 24.8 22.6 11.3 23.7 15.8 13.7 1993-2001 0.0 73.2 21.5 6.2 35.9 23.7 18.5
Table 6.2.2. Evaluation of the present ecological status of L. Peipsi on the basis of selected zooplankton indicators. Indicator Assessment N Zpl good B Zpl moderate/good B/N good RotN% good RotB% good N Rot good B Rot good B Cop moderate/good B Daph / B Cru moderate
Table 6.2.3. Preliminary criteria for distinguishing ‘good’ and ‘moderate’ statuses in the case of L. Peipsi (as mean for the vegetation period). Indicator Status ‘moderate’ Status ‘good’ N Zpl (103 ind/m3) > 1000 (1000–2000) < 1000 B Zpl (g/m3) > 2 (2–3) < 2 B/N (µg) < 2 > 2 RotN% (%) > 80 (80–100) < 80 RotB% (%) > 40 (50–60) < 40 N Rot (103 ind/m3) > 700 (700–2000) < 700 B Rot (gWW/m3) > 0.5 (0.5–1.2) < 0.5 B Cop (gWW/m3) < 0.4 > 0.4 B Daph/B Cru (%) 10–25 > 25
6.3. Zooplankton/Phytoplankton ratio (J. Haberman & R.Laugaste)
When the trophic level of a waterbody increases, the phytoplankton will be dominated by large filamentous algae, particularly cyanobacteria, which are not suitable food for zooplankters (Augusti et al., 1991). As a result, larger zooplankters, feeding on algae, start to disappear gradually from the water body, and zooplankton will be dominated by small forms (rotifers and small cladocerans) feeding on bacteria and detritus. Consequently, the biomass of phytoplankton rises, while that of zooplankton decreases. In moderatly eutrophic Lake Peipsi summer biomasses of phytoplankton and zooplankton are about 10 gWW/m3 and 3 gWW/m3, respectively (Figure 6.3.1). The ratio BZp/BPhyt has been considered a highly informative index of eutrophication process (Avinski et al., 1995). It reflects adequately the trophic state af a water body, decreasing with increasing trophy (Andronikova, 1996; Jeppesen et al., 1999, 2000). A study of Danish lakes of different trophy showed that a rise in trophic level (total phosphorus content from <0.05 to 0.4 mg P/l) was accompanied with a decrease in BZp/BPhyt from 0.46 to 0.08, and in WZp from 5.1 µg to 1.5 µg. This was caused by a decline in the abundance of large-sized zooplankters (Daphnia, copepods). The share of Daphnia species in the biomass of the cladoceran group decreased from 63-73 % to 30 % (Jeppesen et al., 2000).
48
Non-Outlier Max 16 1992-2001 Non-Outlier Min 0.8 14 ZP 75% FP 0.7 25% -3 12 1997-2001 0.6 Median 10 0.5
, gWW m 8 0.4 Zp
, B 6 0.3 t , gWW/gWW t y Phy 0.2
B 4 Ph
/B 0.1 2 Zp 0.0 0 B -0.1 IIIIVVVIVIIVIIIIXXXI L. Peipsi s.s. L. Lämmijärv L. Pihkva
Non-Outlier Max ±1.96*Std. Err.
2.6 Non-Outlier Min ±1.00*Std. Err. 75% 0.8 Mean 2.2 25% 0.7 Median 1.8 0.6 1.4 0.5 0.4
, gWW/gWW 1.0 t , gWW/gWW t y
y 0.3 Ph
0.6 Ph 0.2 /B /B
Zp 0.2 Zp 0.1 B B -0.2 0.0 Winter Spring Summer Autumn L. Peipsi L. Võrtsjärv
Figure 6.3.1. Biomassses of metazooplankton and phytoplankton and their ratio in lakes Peipsi and Võrtsjärv in 1992-2001. Upper border good/moderate, lower border moderate/poor
In L. Peipsi BZp/BPhyt is the highest in the northern moderately eutrophic part, diminishing southward towards the strongly eutrophic southern part, L. Pihkva. The average values of BZp/BPhyt are lower than 0.5 for all lake parts (0.49, 0.30 and 0.14 for the northern, middle and southern parts, respectively). Maximum values (about 2–3) occur commonly in the northern part in June and slightly lower values (1–2) in May. In L. Lämmijärv, this index commonly did not exceed the value of 0.5. BZp/BPhyt had quite strong Spearman correlations with biomass of copepods (r = 0.65), with biomass and production of herbivorous zooplankton (r=0.64 and 0.59, respectively) and with average zooplankter weight (r=0.52). All correlations with the phytoplankton parameters were negative. Only weak correlations were revealed between BZp/BPhyt and nutrient content. Among hydrological and hydrochemical parameters, temperature alone displayed a weak correlation (r = 0.37) with this ratio. Significant differences in BZp/BPhyt values between the two lake parts were lacking on the basis of Student’s criteria, but were revealed with ANOVA (p-level 0.002–<0.0001 for the years 1997-2001). In moderately eutrophic L. Peipsi BZp/BPhyt was clearly higher than in strongly eutrophic L. Võrtsjärv (Fig. 6.3.1). The values of BZp/BPhyt fluctuated in a wide range. The ratio was rather stable in summer 0.6–0.7 in July–August for L. Peipsi and 0.1–0.2 for L. Võrtsjärv) when ecosystem is balanced and the diversity is the largest. In L. Peipsi BZp/BPhyt was significantly higher than in L. Võrtsjärv also in winter: 0.26 and 0.16, respectively. Andronikova (1989) has established that BZp/BPhyt was ≥4 for oligotrophic water bodies, 1 for mesotrophic water bodies, and ≤0.5 for eutrophic water bodies. In oligo-mesotrophic (clear-water) Dutch lakes, BZp/BPhyt fluctuated between 0.45 and 0.78, while in eutrophic (turbid) lakes, it fluctuated between 0.13 and 0.32 (Jeppesen et al., 1999). On the basis of materials from 71 lakes, Jeppesen et al. (2000) followed changes in this ratio simultaneously with changes in the total phosphorus content of water (from <0.05 to >0.4 mgWW/l). Mean summer BZp/BPhyt decreased from 0.46 to 0.08. In the oligo-mesotrophic water bodies of the Netherlands, this ratio was 0.4 for oligo-mesotrophic lakes and 0.05 for hypertrophic lakes (Gulati, 1983). In
49 the eutrophic Vasikalampi pond (Finland) the mean annual BZp/BPhyt was 0.4 (Eloranta, 1982), in the eutrophic L. Müggelsee 0.49 (Nixdorf & Arndt, 1993), in the eutrophic L. Okeechobee 0.12 (Havens, 1998), and in the eutrophic Neva Bay 0.4 (Telesh et al., 1999). In the bays of the oligo-mesotrophic L. Ladoga the ratio was 0.5-0.7 (Ogorodnikova, 1995; Letanskaya & Protopopova, 1995), in the Bay of Bolshoe Onego 2.8 (Kulikova, 1982). Consequently, BZp/BPhyt characterises both the trophy and the whole ecosystem of the water body quite adequately. Indirectly, they characterise dominating groups in phytoplankton and zooplankton, feeding relationships between phyto- and zooplankton and between zooplankton and fish, as well as the pressure of fish on zooplankton. The mean summer values can be used as a marker characteristic in the qualification of state and the ecosystem of the water body. Particularly, it is essential in the case of permanent monitoring of water bodies.Considering BZp/BPhyt, the state of L. Peipsi can be evaluated as follows: reference >3; high 1-3; good 0.6-1; moderate 0.3-0.6; poor 0.1-0.3; bad <0.1
6.4. Macrophytes (H. Mäemets)
Macrophyte criteria are formed on the basis of the data of the last 40 years (Tuvikene, 1966; Nedospasova, 1974; Sudnitsyna, 1990; Mäemets & Mäemets, 2001). During this period the eutrophication has expanded step by step from southern part of L. Peipsi to north. Presently the (presumably) primary emergent and amphibious vegetation has preserved mainly on scattered stretches. Main changes in macrovegetation are connected with expanding reeds, shading the water and forming sheltered habitats for accumulation of organic sediments. Decrease in maximum growth depth of submerged plants is not remarkable. Regarding the criteria, elaborated in Water Framework, we must assert some differences, connected with characteristics of L. Peipsi: • Although sparse stands of Potamogeton perfoliatus reach in L. Peipsi the depth of four meters (locally), the share of littoral in lake area is relatively small. • The quantitative characteristics used for small lakes, e.g. the percentage volume infested by macrophytes (PVI), are not always suitable for large lakes. The distribution of macrophytes in large lakes is impeded by the action of currents, wind, waves and removal of fine-grained sediments. In some shore areas (northern coast) the growth conditions are unfavourable due to steep slope and moving sand. In such areas subject to hard mechanical impacts the estimation of ecological quality on the basis of macrophytes is evidently meaningless. • Certain problems are connected with determination of limits of observation area (=ecotone). On the coast of L. Lämmijärv the reed belt in lake goes over to reed fen, containing numerous small water bodies. Usually in such places we restrict to the zone of wave impact. More questionable is distinguishing of observation area on the stretches where eutrophication obviously has caused the increase of reeds during last decades, e.g. between Praaga and Varnja, at northwestern coast of L. Peipsi s.s. etc. There reeds form sheltered and organic-rich habitats for nutrient-demanding floating and weakly-rooted species, which were earlier lacking from these lake parts. To ignore them seems unjustified. By the clearance from reed the species of the good state occur in the temporary open stretches but do not establish for longer time. So the actual state of a shore stretch depends on the direct human activity too. Restricting the estimates only to submerged plants seems to be impoverishing, as in submerged vegetation Potamogeton perfoliatus has been prevailing permanently. Investigations of submerged stands in 1999-2002 were carried out to estimate possible changeability of its state, depending on weather conditions or other natural factors. Without such knowledge we can not decide, how significant are observed differences between years in regard of trophic state of the lake. The results have been used for the estimation of the criteria for open water (Table 6.4.1.). However, these criteria are preliminary and need further
50 revision, as the abundance of epiphyton and large algae (on higher plants) seems to be very different in subsequent years. The presented criteria compromise between different characteristics of vegetation. Most difficult problem related to estimation of the state of the lake is segregation of real trends and natural oscillations, obviously connected with cosmic cycles.
Table 6.4.1. Macrophyte indicators and criteria for L. Peipsi Plant groups/ HIGH GOOD MODERATE POOR and/or Estimates BAD EMERGENT Undersized In some stretches Extensive reed Undersized plants PLANTS species undersized belt hundred absent, in reed Eleocharis, species replaced meters wide, sheltered creeks Juncus etc. by Phragmites reach water depth with thick mud australis and (in of 1 m and more, and litter south) stands of Typha Schoenoplectus angustifolia, lacustris undersized species rare Amphibious Ranunculus Frequent and/or mainly in cleared absent plants reptans, abundant in open stretches Eleocharis stretches without acicularis, reed Potamogeton gramineus frequent and abundant Alisma gramineum frequent Submerged Fertile. Stands of Charophytes lacking or plants Potamogeton Charophytes lacking, P. unrooted perfoliatus Fertile P. perfoliatus with (Ceratophyllum dominate, P. perfoliatus with P. pectinatus and demersum) in filiformis P. pectinatus; P. P. lucens. In (reed) canals and frequent on filiformis occur some places creeks, vegetative stony shallows infertile. in open water (depth 2-3 m) Floating- in bays, in bays, scattered Abundantly in Abundantly in leaved plants scattered bays, at inflows bays, at inflows sheltered by reed sheltered by reed Floating Absent scattered, in scattered, in In sheltered plants sheltered places sheltered places places in masses Epiphyton invisible by eye non-smearing smearing, large thick, smearing, filamentous algae opulent large in places algae
Macrophyte rarities in L. Peipsi Several rare (for Estonia or whole region) species grow in the littoral of L. Peipsi, e.g. Potamogeton filiformis, Alisma gramineum, Cyperus fuscus, Scirpus radicans. Their survival is depending on several factors. Most important factors affecting rare species are overgrowing by reeds, which shade the habitats and favour the accumulation of organic sediments, and epiphyton, Despite suppressing impact of reeds we do not recommend the extensive removal, as their role in retention of nutrients and denitrification is remarkable.
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Regular clearance of shore stretches used for recreation by local settlement favours survival of rare species. Strong recreational stress, boat traffic and pollution by oil or wastewater may cause the extinction of rarities.
Epiphyton on macrophytes The biomass and the chorophyll a content (Chla) of the epiphyton increased southward together with trophic state of L. Peipsi. Both the epiphyton biomass and Chla revealed reliable and quite strong negative Spearman correlations (P <0.05) with wind index and transparency, and positive with abundance of host plant, both reed and pondweed. Epiphyton values claculated per area of the host plant are more suitable for assessment than these per mass unit of dried host plant since the dry matter content is very different in plant species. Criteria of the ecological state are different for epiphyton values in the large and small lakes: Chla about 50 µg cm-2 notes a ‘poor’ state for L. Peipsi (Tab. 6.4.2) but ‘moderate’ status of Estonian small lakes.
Table 6.4.2. Status criteria of epiphyton for L. Peipsi Reed Epiphyton P. australis Chla, µg/cm2 Chla, µg/g dry weight High <15 <50 Good 15-30 50-100 Moderate 30-50 100-150 Poor >50 >150
Pondweed Epiphyton Potamogeton Chla, µg/cm2 Chla, µg/g dry weight High <15 <500 Good 15-30 500-1500 Moderate 30-50 1500-2500 Poor >50 >2500
6.5. Benthic inveretebrates (H. Timm & K. Kangur)
The use of macroinvertebrate communities for determining the structural and functional integrity of surface waters is widespread (Wiederholm1980; Johnson, 1999). Determination of the structure and dynamics of the benthic community is a key to understanding the state of a freshwater ecosystem and how it works. According to Reice & Wohlenberg (1993), the benthos is an high biotic indicator of ecosystem change for several reasons: • Life history of benthic macroinvertebrates, especially length of their life cycles, provides a long term exposure to toxic substances, relative to other system constituents such as zooplankton • Benthic macroinvertebrates live in intimate contact with the sediments, which enhances their contact with many pollutants. Benthic macroinvertebrate populations and the benthic community display far greater sensitivity to several types of environmental disturbance than single organisms (e. g. fish) or single processes (e. g. primary productivity). Profundal communities, in particular chironomid species assemblages, have long been used for determining the degree of pollution and trophic classification (eutrophication) of temperate lakes (Saether, 1979; Aagaard, 1986; Gerstmeier, 1989; Johnson et al., 1993; Lods-Crozet & Lachavanne, 1994; Lindegaard, 1995).
Macrozoobenthic animals as biological indicators for lakes are used in two main directions:
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• Lakes of different types or with a different impairment status can be compared on the basis of the profundal species. In addition, paleolimnological studies, using cores of profundal sediment, enable to monitor the history of pollution. Systematical studies of macrozoobenthos in Estonian small lakes, collected with Ekman-type samplers, started in 1951. In Lake Peipsi, a similar sampling program was initiated in 1964 and repeated yearly until now. In addition, several special programs, operating with Ekman-type box samplers or square frames by divers have been conducted. They comprise littoral transects all over the basin (1970, 1980, 1990), or on Estonian side only (2000-2002), production studies (1984-1986), and mapping the distribution of zebra mussel (1985-1988). Several papers are published in order to describe Estonian lake types and/or lake status on the basis of open-water samples (Estonian lakes, 1968; T. Timm et al., 1982; T. Timm et al., 1996 (for Lake Peipsi); Kangur et al., 1998). For Lake Peipsi, a description of limnological type according to macroinvertebrates is given in separate chapter in a monograph (T. Timm et al., 2001). • The animal communities of the lake littoral can be studied as indicators using handnets and relative techniques. In North America, several multimetric indices have been elaborated on the basis of single metrics of littoral macroinvertebrates. In Estonia, special studies in this field started in 1994 as a part of small lake monitoring. An attempt to separate limnological lake types on the basis of qualitative samples was done by H. Timm et al. (1999). In Lake Peipsi, the first few handnet samples according to standard EN 27828 (European…, 1994) were collected in 2002.
WFD confirmed macroinvertebrates as a key group of biological indicators in lakes. Composition and abundance of benthic invertebrate fauna were considered significant biological quality elements and their ranges must be classified according to natural conditions and pollution levels. Box and frame samples enable to estimate both abundance and species composition, but they do not work well on the hardest substrates, such as stones or dense vegetation. Therefore, most of them are distributed on the relatively homogeneous areas with soft bottom, where, however, the majority of species do not occur. Handnet samples, on the other hand, can be used only in shallow waters. They occupy much wider area than the quantitative samples, covering all local substrates and vegetation types (except the fluid mud). They give an incomplete estimate of the total abundance, but usually incorporate much more species than that in open-water areas. Hence, the combination of the shallow-water and open- water samples only can give the complete status estimation in lake.
Biological criteria for abundance and species composition of macroinvertebrates in lakes • Abundance Although abundance is a metric, which is estimated very often, in limnological studies, its use as a bioindicator has several considerable disadvantages. First, it is greatly variable compared with taxa richness, diversity, or pollution indices. Increasing the number of observations should compensate the high natural variability. In the profundal, 10 replications, containing at least 100 individuals is considered a minimum effort required to get the confident estimation of abundance (Veijola et al., 1996). The sublittoral and littoral are even more variable. In practical monitoring (including the Estonian side of Lake Peipsi), 3-5 replications per site (irrespective of the habitat type) have been used as a standard. Abundance depends to a great extent on substrate type. For example, if one of the three replicates falls into dense patch of zebra mussel, a ten- or even hundredfold difference in abundance and biomass of animals between such observations can occur. A scale of abundance of macroinvertebrates for small lakes (ind./m2) was proposed by Õ. Tõlp in the monograph “Estonian Lakes” (1968) as follows: <600 – very low; 600-1600 – low; 1600-3000 – moderate; 3000-7000 – high; >7000 – very high. No relationships with lake type, substrate type, or pollution level were presented. Therefore, speaking about the
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“mean abundance of macroinvertebrates in a lake” must be taken with caution, until the proportion of different bottom habitats, as well as the location of sampling sites is not known. Johnson (1999) analysed different metrics in lake littoral, in order to detect their natural variance and also ability to distinguish impaired and unimpaired sites. He found that compared with all other indices, abundance for handnet samples was the most variable. At the same time, its discriminative power regarding to polluted sites was one of the lowest. Therefore, abundance in lake littoral was considered a second-rate indicator, for which quality classes were not established. According to Medin et al. (2001), for handnet samples there are the following classes of abundance:
Abundance (ind./m2) Very high >1000 High 700-1000 Intermediate 300-700 Low 150-300 Very low <150 Reference value -
It should be considered that the abundance values, obtained by handnet are naturally much lower than those collected with bottom samplers. Abundance of macrozoobenthos is a valuable metric for estimation of fish food. Nevertheless, no good quality classes on the basis of macroinvertebrate abundance are available. There are also problems to distinguish type-specific conditions, because abundance is related much more to physical conditions than to slight pollution effects.
• Taxonomic composition One way is to concentrate on one or two most abundant taxonomical units (for example, chironomid larvae or oligochaetes), identifying them all to species level and assigning tolerance values to each species. This method requires high-experinced taxonomist, able to identify these groups. Second, a detailed list of pollution tolerances for all species is needed. Such lists usually exist only for single lakes and cannot well adjusted to other lakes belonging to different climatic zones and limnological types. Although historically popular, quite few indices for lake profundal are currently used in contemporary practice. Johnson (1999) presents two indices for soft-bottom profundal of Swedish lakes, with corresponding quality classes – the Benthic Quality Index (based on sensitivity to eutrophication of few chironomid species), and the ratio of oligochaetes and sedentary chironomids. The last ratio presumes that with nutrient enrichment some tolerant oligochaete species tend to increase in abundance relative to the chironomids. Neither proved itself as reliable method to estimate the quality of Estonian lakes. Otherwise, all groups present in sample could be taken into consideration but the taxonomical resolution used at this approach is usually somewhat lower than species level. Taxa diversities and percentage ratios represent combinations of abundance and taxonomical composition. The groups, considered indicators usually differ in open-water areas and in shallows. Chironomids and oligochaetes are preferred indicators in the profundal and in the deep sublittoral, because few other groups inhabit these zones, even in natural conditions. In shallow areas, attention is often concentrated on other groups, even though chironomids and oligochaetes are abundant. Rich occurrence of these two groups in littoral is often considered an evidence of impairment. For the hard-bottom littoral, the classification criteria for total taxa richness (with fixed sample size), Ephemeroptera, Plecoptera and Trichoptera taxa richness (EPT), Shannon taxa diversity, British Average Score Per Taxon (ASPT, general ecological quality), and acidity index are available (Johnson, 1999; Medin et al., 2001) (Table 6.5.1). All these indices are also concurrently used in Swedish
54 streams. The Swedish examples, however, do not distinguish natural limnological types, concentrating on soft-water waterbodies with high transparency.
Table 6.5.1 Some quality criteria for macroinvertebrate indices in the hard-bottom lake littoral according to Johnson (1999) and Medin et al. (2001) Total taxa EPT Shannon ASPT Acidity richness richness diversity index Very high >35 >17 >4.00 >6.4 >8 High 30-35 14-17 3.80-4.00 5.8-6.4 6-8 Intermediate 20-30 10-14 2.85-3.80 5.2-5.8 3-6 Low 15-20 8-10 2.45-2.85 4.5-5.2 1-3 Very low <15 <8 <2.45 ≤4.5 ≤1 Reference value - - 2.85 5 6
These indices described above have been tested in Estonian conditions for different lake types and bottom substrates (Timm, 2002). The elaboration of corresponding quality classes for several of them (ASPT, total taxa richness, EPT, Shannon taxa diversity, acidity index) is also in progress (Ott et al., 2003). The study methodology for shallow-water animals was elaborated in streams but it was successfully carried onto hard-bottom littoral of lakes (e.g. Johnson, 1999). The indices suitable for Estonian lakes are taken from Swedish examples (Johnson, 1999; Medin et al., 2001), except the Danish Stream Fauna Index, which does not work here properly. For Estonian different lake types and bottom substrates, a package of type-specific index values, as well as quality classes is in elaboration (Ott et al., 2003). The corresponding values are given in Table 6.5.2. To obtain the border between “good” and “moderate”, 80% of the reference value is proposed by Medin et al. (2001). We have too little experience to judge the reliability of this number for Lake Peipsi.
Table 6.5.2. Some quality elements with reference values for some lake types and bottom substrates in Estonia (Ott et al., 2003) Variable (quality Reference value for Estonian lakes (the Reference value element) border between “very good” and “good” according to other status sources ASPT ≥ 6 (humic lakes) 5 ≥ 5.5 (transparent soft-water lakes) ≥ 5 (other lakes) Taxa richness (taxa list ≥ 25 (small eutrophic and mixotrophic - according to Johnson lakes) (1999)) ≥ 20 ( transparent soft-water lakes) ≥ 15 (humic lakes) Shannon diversity ≥ 3.5 (small eutrophic and mixotrophic 2.85 lakes; quagmire edge) ≥ 2.5 (small eutrophic and mixotrophic lakes, stones or sand; transparent soft-water lakes and lagoon lakes) ≥ 1.8 (humic lakes)
EPT ≥ 10 (small eutrophic and mixotrophic - lakes, sand) ≥ 7 (small eutrophic and mixotrophic lakes stones and quagmire edge; transparent soft-
55
water lakes) ≥ 4 (humic lakes, lagoon lakes) Acidity index ≥ 8 (small eutrophic and mixotrophic lakes, 6 sand and stones) ≥ 6 (small eutrophic and mixotrophic lakes, quagmire edge) ≤ 5 (transparent soft-water lakes) ≤ 2 (humic lakes)
In Lake Peipsi, only two compound handnet samples, according to the standard EN 27828 (European…, 1994) have been collected from the western shore of the main lake basin in 2002. Both areas were considered type-specific: well-aerated stony littoral at the least influenced basin of the whole lake, far of point pollution sources. The sampling time was October (baseflow) and the sampling depth was 0.3-0.5 m. According to Table 6.5.2, the sites of Lake Peipsi revealed moderate taxa richness (16 or 17), medium (1.54, the northern site) or low (0.44, the southern site) Shannon diversity, relatively high ecological quality according to ASPT index (4.7 or 4.9) and EPT index (7 or 5). Acidity level in lake was considered low (acidity indices 8 or 9). It must be underlined that these numbers are still based on few measurements and should be adjusted as soon as possible. Anyway, the results show that the shallow-water methodology gives results well comparable with other lakes both in Estonia and in Sweden. In future, other parts of lake shallow areas with different substrates and eutrophication level should be tested.
6.6. Fishes (A. Järvalt, A. Kangur, P. Kangur, M. Vetemaa, M. Tambets)
When assessing the quality of fish fauna of a lake, the whole work must be based on so-called reference conditions. However, since in the Baltic province ecoregion there are no lakes comparable to L. Peipsi, the type-specific reference conditions do not exist yet and they should be established. Further, in aim to analyse how far is the state of the fish fauna of L. Peipsi from the initial state (type-specific reference conditions) it is important to concentrate to such changes, which have resulted from human impact. When listing the factors that should be considered in this process, the text of WFD names human activity in broad sense. However, the Annex V specifies human impact on fish communities only as “an impact on physicochemical or hydromorphological quality elements”. The difference is huge, since the last approach allows to exclude the effect of fishing, which is the most important human impact on the fish communities in many lakes including L. Peipsi.
Species composition of fishes as indicator of ecological quality Fish fauna of the L. Peipsi and the lower reaches of its inflow and outflowing rivers comprise 37 species (Table 6.6.1). • The species composition today is practically the same as it was centuries ago. Only one species, zope (Abramis ballerus), which existed in the L. Peipsi according to the literature in 19th century (Dybowski 1862), is today extinct. However, there are no data available which could link this extinction to human impact. Further, last specimens were got long before the serious human impacts such as eutrophication become observable. Finally, zope is a cyprinid species not very sensitive to human impact. • Another extinct species is eel. This species inhabits L. Peipsi today but this is just an effect of artificial introduction taking place in the water basin of L. Peipsi (mainly in L. Võrtsjärv). The reason for extinction was the damming of R. Narva for hydroelectric power production. Eel is a native fish in Estonian inland water bodies. Upstream migration of young eel from the Atlantic Ocean into the basin of L. Peipsi is complicated. It proceeds along the North Sea, the Gulf of Finland of the Baltic Sea, and the Narva River. Therefore, natural eel stocks have never been very dense in Estonian large lakes.
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The annual catch of eel in 1939 was only 3.8 tons from L. Võrtsjärv and 9.2 tons from L. Peipsi (Kint, 1940). This means that the natural annual eel yield in L. Võrtsjärv was 0.014 kg/ha and in L. Peipsi 0.026 kg/ha at that time. The construction of the Narva hydropower station in 1955--56 (Mishchuk & Jaani, 2000) blocked almost totally the natural route of eel from the Baltic Sea to the water bodies of the L. Peipsi basin, including L. Võrtsjärv. With the purpose to restore the eel population and to use better the production capacity of L. Võrtsjärv, stocking measures were started in 1956. Unfortunately, no stocking program of eel in transboundary L. Peipsi has yet been adopted (Kangur et al., 2002). • Vendace was one of the main commercial fishes in L. Peipsi until the late 1980s. The stock and catches of this fish displayed a rising trend from 1931 to 1990 (Fig. 6.6.1). According to Yefimova (1966), stopping the catch of spawning vendace in the 1960s contributed greatly to the increase of its abundance in the lake. On the other hand, an increase in the catch of vendace was achieved by the introduction of a new modification of fishing gear _ a gigantic vendace trap net (Yefimova, 1966). At the end of the 1980s vendace produced annual catches of 1957-3271 tons. From 1990, the abundance of vendace decreased sharply and in 1991-1994, vendace was not caught at all. Sharp decline in the stock of vendace Coregonus albula (L.) in L. Peipsi is probably irreversible owing to the eutrophication of the lake. According to Winfield et al. (1996), the increasing eutrophication may in itself be responsible for the inconsistent recruitment of vendace through the siltation of its eggs on spawning grounds. In L. Peipsi, the grazing- resistant cyanobacteria have become more dominating (Kangur et al., 2002b) and are mainly involved in matter cycling via detritus food chain. The resulting siltation deteriorates the aquatic environment and hence also the spawning areas of fish (e.g. vendace). The predatory influence of pikeperch, (whose abundance increased concurrently with the decrease of vendace), could also contribute to the sharp decline in the abundance of vendace as well as prevent recovery of its stock in L. Peipsi (Kangur et al., 2002a). • The population dynamics of several fishes, particularly pikeperch Stizostedion lucioperca (L.) and perch Perca fluviatilis L., are to a large extent controlled by fishery policy, although climatic factors are also of importance. Pikeperch is one of the key species in the fish community of L. Peipsi as the main regulator of the abundance of coarse fish (Kangur & Kangur 1998). The population dynamics of top predators, first of all pikeperch and perch are to a large extent influenced by fishing pressure. Continuous eutrophication of the lake and decrease of water transparency seems to be favourable to pikeperch, since this fish prefers biotopes of relatively warm, productive waters which have high turbidity. Catches of perch have decreased last years due to overfishing (Saat et al., 2002). Older age classes of top predators are rare, particularly that of pikeperch and perch. In conclusion, according to the existing data the list of L. Peipsi fish species should include 38 species (species in Table 6.6.1 and zope). Today, only two species are extinct (zope and “natural” eel). So, the status of L. Peipsi fish fauna based on this criteria cannot be lower than “good”. However, all signals of extinction (or the state near to the extinction) of additional species taking place in future should be considered as very alarming.
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3500 3000 2500 2000 Tons 1500 1000 500 0 1931 1937 1951 1957 1963 1969 1975 1981 1987 1993 1999
Figure 6.6.1. Catches of vendace from Lake Peipsi
The usability of single fish species as indicators In order to be used as indicators of the ecological status of the lake, different species have very different value. Like in the other groups of biota, also in fish fauna the indicator species should have two main important characters: 1) such species must be sensitive to the ecological changes taking place in the lake ecosystem, and 2) the species should be observable using routine and comparatively cheap sampling methods. Last demand includes also the need for historical data (existing series of key data reaching back in time for as long as possible). First of all, some of the species presented in Table 6.6.1are only visitors in the lake, e.g. have very low abundance (4 species). Further, several fish species are small in size and/or live close to bottom in the shallow littoral zone (mud loach, sunbleak, spined loach, bullhead, gudgeon etc.). Such species are usually not catchable using the commercial fishing gears, which means that the fishing statistics is not providing any data on them. Additionally, scientific fish monitoring program as it is built up today, is also not providing any regular data on such small specimens. Even if the fish monitoring routines could be changed, the future data could not be compared to the historical data. So, both visitors and small-sized species are not very suitable as indicators of the ecological status of the lake. However, it must be pointed out that some above-mentioned species could be theoretically very usable as indicators. Bullhead, for example, is a species inhabiting stony and gravely sandy areas. Therefore, the decrease in the total territory of areas covered by stones and gravel (as a result of eutrophication and sedimentation) should be reflected in decreasing abundance of bullhead. Additionally, this species is sensitive to low content of oxygen. Oxygen depletion in the lake occurs as a result of algal boom in summer and could be linked to human impact to chemical conditions in the lake. This feature increases the suitability of bullhead as indicator species. In Table 6.6.1 the suitability of the different species (i.e. the abundance of the species) as indicators of the ecological status of the L. Peipsi and the changes taking place is evaluated (Table 6.6.1, third column). The suitability valuation presented is in accordance in the guidance given in WFD, i.e. based mainly on the sensitivity of the species in relation to physicochemical or hydromorphological quality elements. Even if the WFD calls to treat river basins as a whole, the present formulation of the WFD (Annex V) gives an opportunity to evaluate the status of ichthyofauna based only on factors impacting fish in lakes itself. Our analysis suggests that this approach is too narrow and that human impact in whole tributary should be taken into account. Several species (like
58 vimba bream, asp) are more impacted by physicochemical or hydromorphological quality elements in the spawning areas than in L. Peipsi itself. (Further, it is sometime more sensible to monitor such species also in the spawning areas, where they are more abundant). Therefore, Table 6.6.1 is taking into account both the L. Peipsi and its tributaries. In conclusion, when assessing the changes in the lake ichthyofauna created by human impacts other than fishery in first order the species marked as “VS” and “S” should be taken into account. Based on the above-mentioned species, the status of L. Peipsi could be today evaluated as “good”, i.e. human impact on physicochemical or hydromorphological quality elements of the lake and its tributaries has caused only rather slight deviation from the “natural” or “pristine” state.
Table 6.6.1 The abundance (Abu.: vis – visitor; I – rare, II common, – III - abundant IV - very abundant) of fish species of L. Peipsi-Pihkva, and their dependence rates on the tributaries (Dep.: 1 - spawning only outside from lake; 2 - spawning mostly outside from lake; 3 – spawning mainly in lake; 4 – spawning only in lake; vis - visitor). ? – data not available. Suitability as indicators of the ecological status is given as “Suitabl.” (VS – very suitable, S – suitable; - not suitable). Species Abu. Suitabl. Dep. Brook lamprey Lampetra planeri (Bloch) vis - vis Brown trout Salmo trutta fario L. vis - vis Vendace Coregonus albula (L.) III VS 4 Whitefish Coregonus lavaretus maraenoides Poljakow III VS 3-4 Grayling Thymallus thymallus (L.) vis - vis Smelt Osmerus eperlanus eperlanus Pallas III - 4 Pike Esox lucius L. III S 2 Eel Anguilla anguilla (L.) II VS 1 Carp Cyprinus carpio I - 3 Roach Rutilus rutilus (L.) III S 2 Rudd Scardinius erythrophthalmus (L.) III - 3 Dace Leuciscus leuciscus (L.) I S 1 Ide Leuciscus idus (L.) II S 2 Mud loach Misgurnus fossilis (L.) I - 4 Sunbleak Leucaspius delineatus (Heckel) ? - 4 Riffle minnow Alburnoides bipunctatus (Bloch) vis - vis Wels Siluris glanis (L.) I - 1-2 Spined loach Cobitis taenia L I - 4 Asp Aspius aspius L I VS 1 Vimba bream Vimba vimba (L.) I S 1 Tench Tinca tinca (L.) II - 4 Minnow Phoxinus phoxinus (L.) vis - vis Stone loach Barbatula barbatula (L.) vis - vis Perch Perca fluviatilis L. III S 3-4 Bullhead Cottus gobio L. I VS (?) 4 Burbot Lota lota (L.) III S 3 Gudgeon Gobio gobio (L.) I - 3 Nine-spined stickleback Pungitius pungitius (L.) I - 4 Bream Abramis brama (L.) III S 3 Silver bream Blicca bjoerkna (L.) III S 3 Chub Leuciscus cephalus (L.) I S 1 Bleak Alburnus alburnus (L.) II - 2 Three-spined stickleback Gasterosteus aculeatus L. ? - ? Ruffe Gymnocephalus cernuus (L.) III S 4 Crucian carp Carassius carassius (L.) II - 4 Gibel carp Carassius gibelio (Bloch) I - 3-4 Pikeperch Stizostedion lucioperca (L.) III S 3
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Occurrence of fish kills during strong cyanobacterial bloom in summer Commercially caught smelt and the commercially non-valuable ruffe have been mostly suffering of the effect of summer water blooms. The catches of smelt have been very variable, depending on hydrometeorological conditions during the short fishing period (Fig. 6.6.2). A sharp decrease in the stock of smelt, caused by summer fish-kill is usually followed by a quick recovery (Pihu & Kangur, 2001) because of its short life cycle and fast reproduction. In the hot and dry summer 2002, blooming of cyanobacteria Gloeotrichia echinulata started in L. Peipsi s.s. in early June. Strong cyanobacterial bloom led to fish-kill, which was induced by synergistic effect of several unfavourable conditions: high temperature, low water level, great spatial and temporal variations in oxygen (saturation 25%–165%) and ammonium ion (up to 0.33 mgN/l) content as well as in pH (7.7–9.5). Ruffe suffered most seriously (Kangur et al., 2003).
10000 9000 8000 7000 6000 5000 Tons 4000 3000 2000 1000 0 1931 1933 1935 1937 1939 1951 1953 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001
Figure 6.6.2. Catches of smelt from L. Peipsi.
Indicative value of the relative abundance of fish species The abundance, biomass and production of different fish species could be used as indicator of the ecological status of a water body. Further, the species could be distributed into groups based on their feeding pattern: predators, plankton-eaters etc. The ratio of the different groups and all changes taking place in this could theoretically serve as rather sensitive indicators of the ecological status. However, the real usage of this criterion is occasionally problematic, because the abundance of the different species (and groups of the species) is (at least in L. Peipsi) much more impacted by fishing pressure than by the human activities changing physicochemical or hydromorphological conditions. Even the species not targeted by the commercial fishery are in L. Peipsi often more impacted by fishery (through food web) than by other human activities. The evaluation of ecological status of the lake in different periods on the basis of official catch data is not reliable, because of changes in catch limits, in type of fishing gears and in fishery statistics in long-term scale. For assessment of ecological status we analysed the ratio of the different group of fishes in 1986 and 1998-2002: piscivores, nonpiscivores, planctivores, benthivores, coregonids, percids, cyprinids. Concerning the amount of catches main commercial fishes are lake smelt (average annual catch 1700-3700 t), perch (600-1800 t), vendace (60-1720 t), bream (250-850 t), pike (200-400 t) and pikeperch (20-1060 t). During the last decade the abundance of vendace in L. Peipsi diminished to the extremely low values while the stock of pikeperch increased remarkably. In 1990s annual catches of pikeperch reached over the thousand tons. The second-rate commercial fishes are whitefish and burbot. Roach, which is rather numerous fish
60 species in L. Peipsi has not so great commercial importance in value, but the amount of catch is still high (570-1100 t). Catch of inferior small fishes, mainly small roach and ruff made up one third from the total catches, except previous decade. In 1935-2000 total annual fish catch from L. Peipsi was 9000-11000 t or 25-30 kg/ha. Due to unreliable fishery statistics, especially at the beginnig of 1990s, registered annual fish catches decreased to 6000 t or 16 kg/ha. During the two different investigation periods 1986 and 1998-2002 catches of the experimental bottom trawl were rather unstable, but relationship between species in 1998- 2002 (in weight and number) was stable enough. According to our calculations the total biomass of fishes in the open part of L. Peipsi in 1998-2002 was 110 kg/ha. The population density of pikeperch was very high, 40 kg/ha or 36% of total biomass. In the second place was roach (12.7%), following by bream (11.4%), smelt (10.8%), perch (10.4%) and ruffe (9.3%). The biomass of pike in the pelagic zone was 5.8 kg/ha. The most productive fish species in L. Peipsi is smelt 45 kg/ha*yr or 46% from total fish production (98.9 kg/ha*yr). Smelt is one of the main food object for pikeperch and other piscivores fishes and at the same time smelt gives 30% from total annual catch. The production of pikeperch and roach is quite similar (14%). The average annual yield during our latest period of investigations was 22 kg/ ha or 22% from total fish production. Presently the biomass of piscivorous fishes in L. Peipsi is extremely high (54.7%) but the production constitutes one fifth of total (18.2%) (Table 6.6.2). The main piscivores are pikeperch, perch (SL >10 cm) and pike. The production of most abundant benthophagous fishes, bream and ruff, was rather low (10%). The production of planktivores made up more than half of total (68%). Due to the high amount of vendace, in 1970s and 1980s the role of the planktivoruos fishes in L. Peipsi was much higher, than during last ten years. In comparison with other Estonian large lake Võrtsjärv, the total biomass of fish in L. Peipsi is rather similar (accordingly 120 kg/ha and 110 kg/ha). Fish production in L. Peipsi (98.9 kg/ha*yr) is up to two times higher as in L. Võrtsjärv (62.2 kg/ha*yr). The same proportion characterises annual yield, accordingly 22 kg/ha and 12 kg/ha. In L. Peipsi planktivorous and piscivorous fish species dominate while in L. Võrtsjärv benthivorous bream and ruffe form the majority. Table 6.6.2. Relative contribution (%) of different fish groups by their food item and most significant fish families in L. Peipsi (1998-2002) and in L. Võrtsjärv (1978-2001) Lake L. Peipsi L. Võrtsjärv CPUE B P CPUE B P total kg/h kg/ha kg/ha kg/h kg/ha kg/ha 204 110 99 241 120 62 % piscivores 54.7 48.1 18.2 24.4 25.6 17 % nonpiscivores 45.3 51.9 81.8 75.6 74.4 83 % planktivores 20.1 29.9 68.1 12.8 11.6 32.7 % bentivores 21.5 22.9 10.1 62 61.8 49.1 % coregonids 3.2 10.9 45.4 0.4 1.7 12.2 % percids 59.9 56.1 24 35 41.9 34.2 % cyprinids 30.3 27.7 28 58.3 46.2 48.5 % smelt 3.2 10 45.3 0.4 1.7 12.2
Fish criteria applicable for assessment of ecological status of L. Peipsi According to experimental trawling the fish community composition in 1980s and in last years was different (Tables 6.6.3 & 6.6.4). The same tendency appeared in commercial catches. During the known history the fish stocks of L. Peipsi have been influenced by rather intensive fishery. Already in 1930s the quantitative composition of catches was similar to present days, when the abundance of predatory fishes and coregonids were both high. Due to extremely intensive fine mesh trawling in 1950s--1980s, the abundance of predatory
61 fishes (first of all pikeperch) was depressed but stocks of vendace and smelt remained on high level. It is well known, that high abundance of piscivores indicates the good quality class. However, in L. Peipsi it is not so straightforward. The main predator, pikeperch prefers waters with higher trophic status and, at the same time, it is pressing down vendace, which prefers clear and less eutrophic water. During the last decades the decrease of cyprinids indicates reduced eutrophication of lake.
Table 6.6.3. Species composition, CPUE of experimental trawl, biomass and production of fishes in L. Peipsi in 1986 and 1998-2002 CPUE g/trawl*h B kg/ha P kg/ha 1986 1998-2002 1986 1998-2002 1986 1998-2002 Smelt Osmerus eperlanus 15882 6442 29.4 11.9 111.8 45.33 Vendace Coregonus albula 26902 32 24.9 0.03 49.8 0.06 Whitefish Coregonus lavaretus 1113 40 0.5 0.02 0.2 0.01 Pike Esox lucius 6315 12609 2.9 5.8 1.0 2.0 Roach Rutilus rutilus 40514 30258 18.8 14.0 18.8 14 Bleak Alburnus alburnus 858 4222 0.8 3.9 1.7 8.6 Bream Abramis brama 169704 27248 78.6 12.6 31.4 5.0 Burbot Lota lota 956 817 0.2 0.2 0.07 0.06 Perch Perca fluviatilis 92110 18567 56.9 11.5 22.7 4.6 Pikeperch Sander lucioperca 5361 86825 2.5 40.2 0.9 14.1 Ruffe Gymnocephalus cernuus 28052 16593 17.3 10.2 8.7 5.1 Total 387767 203653 233 110.4 247.1 98.9
Table 6.6.4. Relative contribution (%) of different feeding groups of fish and most significant fish families in L. Peipsi in 1986 and 1998-2002 1998-2002 1986 1998-2002 1986 1998-2002 1986 CPUE CPUE B B P P total kg/ha 204 388 110 233 99 247 piscivores ** % 54.7 17.5 48.1 17.9 18.2 4.5 nonpiscivores % 45.3 82.5 51.9 82.1 81.8 95.5 planktivores % 20.1 22 14.4 32 54.6 73.8 bentivores % 21.5 50.1 22.9 41.2 10.1 16.2 coregonids % 3.2 11.3 10.9 23.6 45.4 65.5 percids % 59.9 32.4 56.1 32.9 24 13 cyprinids % 30.3 54.4 27.7 42.2 28 21 smelt % 3.2 4.1 10 12.6 45.3 45.2
** pikeperch, pike, burbot and perch >10cm (60% in B and 40% in P)
On the basis of criteria worked out in EC project ECOFRAME (Moss et al, 2003), L. Peipsi is turned from moderate to good status during the last 15 years (Table 7.5, Figures 7.4-7.6).
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Table 6.6.5. The quality classes and status of L. Peipsi by fish composition in experimental trawl catches in 1986 and 1998-2002. Upper section – fish indices and criteria according Moss et al. (2003) where Pipre indicates presence of locally characteristic native piscivores, Abex absence of artificially introduced species that are not native and Altd, either an absence of locally characteristic piscivores or the presence of introduced species. Lower section – status of L. Peipsi according the criteria above. Criteria Fish Fish Piscivore/ Piscivore/ Benthivore/ Cyprinid/ according community biomass zoopalnktivore nonpisciv total total Moss et al., (g/m2) biomass ratio ore biomass biomass 2003 biomass ratio ratio ratio High Pipre, Abex >0<20 >1 Good Pipre, Abex >0<20 >1 >0.3 <0.3 <0.3 Moderate Altd >0<30 0.5-1.0 <0.3 >0.3 >0.3 Poor Altd >30 <0.5 Bad Altd >30 <0.5 Status of L. Peipsi 1986 Pipre, Abex: 23: 0.6: moderate 0.2: 0.4: 0.4: good-high moderate moderate moderate moderate 1998-2002 Pipre, Abex: 11: good- 3.3: good-high 0.5: good 0.2: good 0.3: good good-high high
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7. ECOLOGICAL STATUS OF L. PEIPSI ACCORDING TO THE REQUESTS OF WFD
7.1. WATER QUALITY ASSESSMENT (K. KANGUR, A. KANGUR, J. HABERMAN, M. HALDNA, P. KANGUR, R. LAUGASTE, A. MILIUS, H. MÄEMETS, T. MÖLS)
The water quality in L. Peipsi was preliminary assessed according to the classification of water quality in Estonian light-coloured eutrophic lakes (Table 7.1.1).
Table 7.1.1. The classification of water quality in Estonian light-coloured eutrophic lakes (Eesti Vabariigi keskkonnaministri määrus nr.33, 20. juuni 2001) Characteristics I Class II Class III Class IV Class V Class high good moderate poor bad Water transparency, m >3 2-3 1-2 <1 <1 pH at surface 7-8 8-8.3 8.3-8.8 8.8-9; 6-7 9>; <6 3 Ptot, mg/m <30 30-60 60-80 80-100 >100 3 Ntot, mg/ m <500 500-700 700-1000 1000-1300 >1300 Chemical oxygen demand by <15 15-30 30-40 40-50 >50 dichromate oxygen consumption (KHTCr), mgO/l Sulfate concentration, mg/l <10 10-50 10-50 10-50 >50 Chlorophyll a mg/m3 <10 10-20 20-40 40-50 >50
The water of L. Peipsi is rich in dissolved oxygen (O2) during the ice-out period (Table 7.1.2). However, in spring-winter time (data from 4 March 2002) under the ice cover the O2 content decreased and reached a critical level (2…3 mg/l, 17%) in the near-bottom water layer in the middle of L. Peipsi s.s. At the same time the surface water was oversaturated with O2 up to 123%. The water of L. Peipsi is slightly alkaline (overall mean 8.3 in 1992–2002). During strong cyanobacterial bloom in summer 2002 an increase in pH values was observed. Proceeding from the classification of water quality criteria for Estonian eutrophic lakes (rule nr.33 of Ministry of Environment of Estonia) by water pH mean values, the quality of water of L. Peipsi s.s. is moderate.
Table 7.1.2. Chemical, physical and plankton parameters in L.Peipsi and in its parts in 1992-2002. Variable Unit n Geom. 95% tolerance L. Peipsi At L. L. limits s.s Emajõgi Lämmijärv Pihkva mean n mean n mean n mean n mean
HCO3 meq/l 475 2.45 1.88 3.21 313 2.45 69 2.80 75 2.24 18 2.20
SO4 mg/l 503 14.8 8.8 25.0 330 15.2 74 15.5 81 12.6 18 16.1 Cl meq/l 504 0.21 0.13 0.33 331 0.21 74 0.21 81 0.19 18 0.24 Ca meq/l 502 2.06 1.58 2.69 329 2.06 74 2.35 81 1.88 18 1.78 Mg meq/l 503 0.92 0.54 1.56 330 0.93 74 1.01 81 0.82 18 0.84 3 Ptot mgP/m 515 46.5 18.8 115.4 336 41.2 76 53.3 84 60.2 19 72.3 3 PO4P mgP/m 507 10.3 2.0 53.4 331 9.7 75 10.4 83 12.6 18 14.5 3 Ntot mgN/m 505 712 282 1798 331 633 75 931 81 843 18 929 3 NO3N mgN/m 496 73.2 11.5 467.6 327 59.6 71 140.6 80 91.1 18 89.2 3 NO2N mgN/m 484 2.1 0.3 13.8 316 1.7 75 4.6 79 2.1 14 1.8
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3 NH4N mgN/m 485 22.1 2.1 234.7 317 17.7 75 38.4 79 27.1 14 54.7 Ntot/Ptot mg/mg 474 15.4 4.9 48.2 312 15.3 69 17.3 75 14.4 18 13.1 Si mg/l 476 0.64 0.10 4.08 311 0.60 74 0.74 77 0.62 14 1.28 Fe mg/l 484 0.12 0.03 0.58 316 0.10 75 0.19 79 0.16 14 0.29
CODCr mgO/l 517 29.60 14.81 59.17 338 28.25 76 33.17 84 33.37 19 25.37
O2 mg/l 485 10.56 7.44 14.99 319 10.67 76 10.11 77 10.63 13 10.18
O2 % 466 101 76 134 307 101 73 99 74 104 12 99 pH 499 8.32 7.56 9.07 326 8.32 77 8.28 82 8.34 14 8.32 Secchi m 418 1.7 0.8 3.4 268 1.9 55 1.3 79 1.3 16 1.1 ChlaJH mg/m3 434 16.9 3.6 79.5 277 14.5 58 20.8 81 22.4 18 22.9 FBM gWW/m3 442 5.24 0.70 39.22 283 4.44 58 7.15 83 6.90 18 7.28 FLA 442 46 21 98 283 43 58 53 83 46 18 60 CY gWW/m3 442 0.76 0.02 36.14 283 0.60 58 1.62 83 0.99 18 0.73 BAC gWW/m3 442 2.19 0.12 38.72 283 1.91 58 2.15 83 3.03 18 4.66 CHL gWW/m3 441 0.14 0.02 1.01 282 0.12 58 0.20 83 0.15 18 0.21 CHR gWW/m3 441 0.007 0.000 0.342 283 0.007 58 0.011 82 0.007 18 0.023 CRYP gWW/m3 442 0.10 0.00 2.68 283 0.10 58 0.17 83 0.07 18 0.13 DINO gWW/m3 441 0.01 0.00 1.39 283 0.02 58 0.01 82 0.00 18 0.01 ZA 103.ind./m3 365 391 38 3992 238 423 48 277 69 313 10 1440 ZB gWW/m3 365 1.21 0.16 9.00 238 1.15 48 1.11 69 1.44 10 1.84 TCB 106cells/ml 359 2.50 0.91 6.85 222 2.28 54 3.06 68 2.80 15 2.77 TA ind./l 148 2759 374 20387 91 2034 30 4192 27 4849 TB µg/l 148 49 4 555 91 33 30 72 27 126 Secchi - water transparency by Secchi disk; ChlaJH - chlorophyll a content according to Jeffrey and Humprey equations; FBM- phytoplankton biomass; FLA- phytoplankton species number per sample; CY-biomass of cyanobacteria; BAC-biomass of diatoms; CHL -biomass of chlorophytes; CHR-biomass of chrysophytes; CRYP-biomass of chryptophytes; DINO- biomass of dinophytes; ZA-abundance of zooplankton; ZB-biomass of zooplankton; TA- abundance of planktonic ciliates; TB-biomass of planktonic ciliates; TCB-total count of bacteria; SAPRONA- plate count of saprophytic bacteria
Water transparency (Secchi) is mostly in the range of 0.9–3.4 m (overall mean 1.7 m in 1992-2002). The Secchi depth was about two times higher in L. Peipsi s.s. in comparison with L. Pihkva. In L. Lämmijärv, the water transparency decreased significantly since 1999. According to the data of water transparency, the state of L. Peipsi may be estimated moderate. According to the content of total phosphorus (Ptot) and total nitrogen (Ntot) the state of L. Peipsi may be estimated as good, L. Lämmijärv and L. Pihkva moderate. A clear decline in Ptot has been registered in L. Peipsi s.s. in 1995–98, but an increase was observed during last years (Fig. 7.1.1). The most significant increase of Ptot in last years was observed in L. Lämmijärv, which is influenced by water of L. Pihkva. The course of PO4P in 1992– 2002 was similar to that of Ptot. A clear decrease of total nitrogen (Fig. 7.1.2) and ammonium ion (NH4N) content in L. Peipsi s.s was observed during 1992–1996.
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Fig. 7.1.1. Changes in total phosphorus concentration (Ptot) in L. Peipsi s.s. and in L. Lämmijärv on 19 July.
Fig. 7.1.2. Changes in total nitrogen concentration (Ntot) and Ntot/Ptot ratio in L. Peipsi on 19 July.
The Ntot/Ptot ratio decreased significantly in L. Peipsi s.s. at the beginning of the observation period (Fig. 7.1.2). The lowest Ntot : Ptot ratio (about 11-13) was registered in 1995-1996. 1996 was the year of a very low water level in the lake. Dissolved silicon (Si) concentration decreased in the lake during observation period. The total content of organic matter is characterized by chemical oxygen demand (CODCr). According to CODCr, the water quality of L. Peipsi s.s. is good, however, the state of L. Lämmijärv and the influence area of Emajõgi R. is moderate. A clear increase in CODCr has been observed during last years (Fig. 7.1.3).
Fig. 7.1.3. Changes in chemical oxygen demand (CODCr) and sulphate concentration (SO4) in L. Peipsi s.s. on 19 July.
Strong anthropogenic impact on the lake, reflected by the increase in sulphate and chloride ions from 1950s up to the late 1980s (Starast et al., 2001), was diminishing in all lake parts during the 1990s (Fig. 7.1.3). The danger to form a toxic H2S during anoxia is decreased in L.
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Peipsi due to a significant decrease in sulphate concentration. According to this parameter, the water quality is good. Phytoplankton biomass (FBM), especially the biomass of cyanobacteria, and chlorophyll a (Chl a) content did not follow the dynamics of nutrients but showed an increasing trend (Fig. 7.1.4).
Figure 7.1.4. Changes in Chlorophyll a content (Chl a), biomass of phytoplankton (FBM) and cyanobacteria (CY) in L. Peipsi s.s. and in L. Lämmijärv on 19 July.
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Strong and long-lasting (up to October-November) algal blooms were noted in the lake. In phytoplankton groups that demand less nutrients as cyanobacteria (blue-green algae) have become more dominating. Cyanobacteria are favoured because many of them are able to accumulate P supply into cells and to fix N2. All major dominants in blooms in L. Peipsi (Aphanizomenon flos–aquae, Anabaena flos–aquae, Gloeotrichia echinulata) are effective N- fixers (Laugaste et al., 2001). As a rule, cyanobacteria demand for a lower Ntot:Ptot ratio compared with other algae. Weather conditions appear to be a very important factor in development of algal blooms in L. Peipsi. In the hot and dry summer 2002, blooming of cyanobacteria Gloeotrichia echinulata started in L. Peipsi s.s. In early June which is a month earlier than usually. At the beginning of August 2002, the water temperature reached 26oC. Due to blooms the water transparency by Secchi disk near the western shore of the lake at the depth of 0.8-1.0 m has decreased to 0.3-0.4 m. Shore of the lake was in several places covered with the carpet of Gloeotrichia globules. On the shore were collections or stripes of dead fishes and blue areas of decomposing cyanobacteria. Among dead fishes dominated ruffe but on the shore and in the water were also big dead pikeperch, perch, burbot, pike, bream and roach. We counted dead fishes in several regions along the Estonian shoreline of the lake. The maximum number of dead ruffe was 460 specimens per 1 m of shoreline at Nina village. A relationship between the fish-kill and cyanobacterial bloom is very evident. Probably, fish-kill was induced by synergistic effect of several unfavourable conditions. Low water level, high water temperature, strong bloom of cyanobacteria and resulting great diurnal changes of oxygen and ammonium ion content as well as in pH evidently surpassed tolerable level for fish and led to fish-kills in the lake. Measurements at 10 stations along the shore and diurnal observations at two stations showed great spatial and temporal variations in oxygen (saturation 25%-165%) and ammonium ion (up to 330 mgN/m3) content as well as in pH (7.7- 9.5). High level of cyanotoxins in the water is also possible.
7.2. EXPERT JUDGEMENT OF ECOLOGICAL QUALITY (P. NÕGES, J. HABERMAN, A. JÄRVALT, K. KANGUR, A. KANGUR, R. LAUGASTE, H. MÄEMETS, T. NÕGES)
Phytoplankton dominants of L. Peipsi have generally remained the same since the first profound investigations made in 1909 (Samsonov, 1914). A summer water bloom caused by the cyanobacterium Gloeotrichia echinulata was noticed in L. Peipsi already in 1895 by Spindler and Zengebusch (Kullus, 1964). Mass development of Anabaena flos-aquae and Microcystis aeruginosa in L. Peipsi was observed already in August 1912 (Samsonov, 1914). Yearly water blooms from July to September with a maximum in August were a common phenomenon in the lake already in the 1930s (Vinkel-Voore, 1935). Taking into account the persistance of the phytoplankton community structure in general but also the observed slight changes the ecological status of the lake can be considered as ‘good’. Although the intensity of water blooms seems to be increasing during a last couple of years, there have been no significant differences observed in the frequency, or bloom causing species compared to the earlier documented period. In L. Peipsi the dominating zooplankton complex has been the same for the last 40 years. Increasing eutrophication is generally accompanied by a decrease in the mean individual weight of zooplankters (Haberman, 1997; Haberman & Künnap, 2002). In moderately eutrophic L. Peipsi zooplankton mean individual weight of has decreased since 1965 from 6.0 to 4.4 µg. Slight changes in zooplankton species composition and mean weight do not result in undesirable disturbance to the balance of organisms present in L. Peipsi and the ecological status of the lake can be evaluated as ‘good’. The first profound description of the macrovegetation of L. Peipsi made by H. Tuvikene in 1961-62 (Tuvikene, 1966) has been the reference for further comparisons (investigations by Nedospasova in 1966-70, by A. Mäemets in 1970-71 and 1980, by Sudnitsyna in 1988-89, and by H. Mäemets in 1997-2001 (Mäemets & Mäemets, 2001). The
68 most significant change is the expansion of the reed belt surrounding L. Peipsi s.s. during the last 20 years. Flora of L. Peipsi s.s. has supplemented in the 1970s by species earlier spread only in L. Pihkva. The biomass of reed has considerably increased during the last 30 years while that of Potamogeton perfoliatus has decreased. The abundance of filamentous green algae has significantly increased. Basing on aquatic macrophytes, the ecological quality of L. Peipsi can be estimated as ‘good’/‘moderate’. The community of benthic macroinvertebrates dominated by Chironomus plumosus and Potamothrix hammoniensis (Tubificidae) has inhabited the bottom areas of L. Peipsi presumably during hundreds of years, since the formation of muddy bottoms after the last glaciation. 4. Several oxyphilous species characteristic of mesotrophic or oligotrophic lakes or flowing waters, as larvae of Monodiamesa bathyphila, Potthastia longimana gr. and Paracladopelma rolli, are also present. However the introduction/invasion of alien species has irreversably changed the benthic invertebrate community. The zebra mussel Dreissena polymorpha invaded L. Peipsi in 1935 (Mikelsaar & Vinkel, 1936) but forms now the most significant animal population of the lake. Despite the negative nature of the invasion as such, good acclimatization of this clean water species indicates high water quality. Another exotic species, a Baikalian gammaridean amphipod Gmelinoides fasciatus was introduced accidentally in L. Peipsi in the early 1970s (Timm & Timm, 1993) during attemts to acclimatize Gammarus lacustris from a Siberian population. By 1990 G. fasciatus has completely replaced the native population of G. lacustris. According to the fact that the benthic fauna of L. Peipsi has been strongly modified, the overall ecological quality with respect of the reference conditions can be evaluated not higher than ‘moderate’. On the other hand, high species diversity, stability of the abundance and survival of sensitive clean water species demonstrates high quality features of L. Peipsi. The fish stock of L. Peipsi is heavily exploited. Already Baer (Ber, 1852) showed that overfishing was the main reason of decreasing of bream cacthes in this lake. In recent years sharp decrease of intolerant species like vendace and whitefish; episodic fish kills; older age classes of top predators, particularly that of pikeperch, becoming rare; sharp decrease of stocks of top predators and the abundance of omnivores and habitat generalists like ruffe allow to evaluate the ecological quality of L. Peipsi with the respect of fish community not higher than ‘moderate’. However, of 38 species, only two species are extinct from L. Peipsi (zope and “natural” eel) indicating only minor changes. High abundance of piscivores also indicates good ecological quality. Nevertheless, all signals of extinction (or the state near to the extinction) of additional species taking place in future should be considered as very alarming.
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8. SUGGESTIONS FOR ADJUSTMENT OF NATIONAL MONITORING PROGRAM OF THE RIVERS IN LAKE PEIPSI REGION ACCORDING TO WFD REQUIREMENTS
8.1. PRESENT SITUATION OF ESTONIAN RIVER MONITORING (T. NÕGES)
Estonian river monitoring is presently performed by four institutions. Hydrology and discharges are measured by Estonian Institute of Hydrology and Meteorology; hydrochemical monitoring is the responsibility of the Department of Environmental Engineering at Tallinn Technical University; biological indices are mainly monitored by the River Biology Working Group of the Institute of Zoology and Botany at Estonian Agricultural University, and macrozoobenthos is observed separately by H. Timm at Võrsjärv Limnological station at Estonian Agricultural University. All three groups work and reports separately. As WFD requires a complex estimation of ecological quality of waters involving biological, chemical and hydromorphological aspects, a big attempt was made in frames of MANTRA-East project to achieve better integration and common understanding of separate groups. Present report involves the results and attitudes of all these groups. Though, the achievement of necessary integration and full common understanding was generally failed and will remain the further subject of Estonian ministerial authorities in the process of implementation of WFD. The main problem why the integration of views was not achieved was the claim of the researchers of the River Biology Working Group that the presently approved river typology enables to develop type-specific indicators and criteria for chemical, and partly for plankton indices but does not meet the requirements for development of type- specific indicators/criteria system for the higher levels of river ecosystem (e.g. macrovegetation and fishes) which are also the subject of WFD and reflect ecosystem integrity. An alternative typology scheme proposed by River Biology Working Group is presented below in Chapter 8.3.
8.2. SUGGESTIONS OF THE GROUP OF HYDROCHEMICAL MONITORING OF ESTONIAN RIVERS AT TALLINN TECHNICAL UNIVERSITY (E. LOIGU)
Environmental monitoring is important for estimation of environmental status, different human pressure impacts and base information for decision makers in applying environmental protection measures, and for estimation of cost-effectiveness of used measures. Therefore, monitoring requires comparable, reliable and representative data. Estonian National River Monitoring Programme started to investigate the chemical status of rivers in 1992. That programme has developed according to (1) EU directives and other international agreements including convention of transboundary water bodies, and (2) intra-national requirement. Sampling frequency and objectives has been given in table 8.2.1.
Table 8.2.1. Monitoring stations of physico-chemical quality of rivers Nr. Type of Size of the Legal Analysis River Distance Catchment the station basis package Sampling Station from the area station frequency in a mouth, km F, km2 year
1. Piusa, 16 503 R/F L km, rF I5) 12 Värska-Saatse road. 2. Võhandu , 93 495 R L km, rR II 6 outlet of lake Vagula 3. Võhandu, 57,5 848 R L km, rR II 6 Himmiste
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Nr. Type of Size of the Legal Analysis River Distance Catchment the station basis package Sampling Station from the area station frequency in a mouth, km F, km2 year
4. Võhandu, 6 1144 R/F/I XL rF I5) 12 downstram of Räpina 5. Väike-Emajõgi, 35.7 1054 R XL rR I 12 Tõlliste 6. Väike-Emajõgi, 1.1 1270 R/F XL KD rF I8) 12 Pikasilla bridge 7. Õhne, 6 577 R/I L rF I 12 downstream of Suislepa 8. Õhne 38 266 B M km, rB II 6 upstream of Tõrva, Roobe 9. Tarvastu, 0.5 108 R/F M rF I 12 mouth 10. Tänassilma, 0.5 454 R/F L rF I 12 Oiu 11. Emajõgi, 101 3374 R/F XXL P, rR II2)9) 6 Rannu-Jõesuu 12. Emajõgi, 45.2 7828 R/F XXL rR II 6 Tartu (Kvissental) 13 Emajõgi, 16 8539 R/F/I XXL/MI P, I2)6)8)9)11) 12 Kavastu FD,rF 14. Pedja, 71 665 R/I L rI II 6 Jõgeva 15. Pedja, 45.6 776 R L rR II 6 Tõrve 16. Preedi, 39.8 34.8 B S ND, II 6 Varangu rB 17. Põltsamaa, 64.5 861 R L km, rR II 6 Rutikvere 18. Mustjõgi, 7.6 16.2 B S rB II 4 Tulijärve 22. Oostriku, 6 29.7 B S ND, II 4 Oostriku rB 23. Porijõgi, 12.6 241 R M rR I 12 Reola 24. Ahja, 54.4 336 B L rB II 6 Kiidjärve 25. Ahja, 18 930 R L km, rR I 12 Lääniste 26. Kääpa, 6.2 282 R M km, rF I5) 12 outlet from Kose storage lake 27. Avijõgi, 4.6 366 R/F L km, rF I5) 12 Mulgi 28. Rannapungerja, 27.0 214 R/F M P, rF I5) 12 Iisaku-Avinurme road. 29. Tagajõgi, 3.7 252 R/F M km, P II 6 Tudulinna 30. Alajõgi, 3.5 140 R/F M P, rF I5) 12 Alajõe 31. Narva, 76 47815 R/F XXL/MI P II2)9) 6 Vasknarva
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Nr. Type of Size of the Legal Analysis River Distance Catchment the station basis package Sampling Station from the area station frequency in a mouth, km F, km2 year
32. Narva, 7 56060 R/F/I XXL/MI FD I2)3)4)7)8)9) 12 Narva HEL, P 1)Type of the station, on the basis of EUROWATERNET (ETC/W Ref: PO31/98/1, Annex 3): P- station on a transboundary water body according to the convention of tranboundary water bodies, paragraph 7; B- background station; R – representative station; F- force station; I- pollution impact station 2)Size of the station, on the basis of EUROWATERNET (ETC/W Ref: PO31/98/1, Annex 3): S- small catchment area (<50 km²); M- medium catchment area (50-250 km²); L- large catchment area (250-1000 km²); XL – very large catchment area (1000-25000 km²); XXL – excessive catchment area (>25000 km²); XXL/MI – station of national importance Legal basis: B- background station (EUROWATERNET (ETC/W Ref: PO31/98/1, Annex 3); rR - representative station EUROWATERNET (ETC/W Ref: PO31/98/1, Annex 3); rF – charge station (EUROWATERNET (ETC/W Ref: PO31/98/1, Annex 3); rI - pollution impact station (EUROWATERNET (ETC/W Ref: PO31/98/1, Annex 3); FD – basestation of EU Freshwater Fish Directive (78/659/EEC, 6.1); ND – basestation of EU Nitrates Directive (91/676/EEC; 5.6); HEL – HELCOM pressure station (3.5;5.1) Parameters, elements analysed (2 main packages and 11 directive differences): I package - temperature, suspended solids, pH, O2, BOD7, COD, NH4, NO2, NO3, Ntot, PO4, Ptot, SO4, Cl, Si, conductivity (recommendable), colour; II package - temperature, suspended solids, pH, O2, BOD7, COD, NH4, NO2, NO3, Ntot, PO4, Ptot, HCO3, SO4, Cl, Ca, Mg, Na, K, Si, hardness, Fe, conductivity (recommendable), colour 2) According to the protocol of Estonian-Russian commission of transboundary water bodies as an obligatory parameter also chlorophyll-a 3) Heavy metals (Hg, Cu, Pb, Cd, Zn) are analysed once a years in the autumn rainperiod, according to HELCOM Conversation (5.3) and Dangerous Substances Directive (6.3) 4) Oil products are analysed six times a year according to HELCOM Conversation (5.3) and Dangerous Substances Directive (6.3) 5) Oil products are analysed once a year according to Transboundary Water Body Treaty (ch. 7) and Dangerous Substances Directive (6.3) 6) According to the protocol of Estonian-Russian commission of transboundary water bodies, obligatory indicators are in addition to the monitoring programme package (I) dangerous substances Hg, Cu, Pb, Cd, Zn, phenols, oil products six times a year on different hydrological periods 7) Phenols are analysed 12 times a year according to Dangerous Substances Directive (6.3) 8) In rivers of salmonids and cyprinids according to EU Freshwater Fish Directive (78/659/EEC, Annex 1) there must be additionally determined ammonia (NH3) and total residual chlorine (HOCl) once a month 9) According to the requirements of EUROWATERNET to determine chlorophyll-a 12 times a year for classification 10) Pesticides are analysed twice a year, according to Dangerous Substances Directive (6.3) 11) In rivers of salmonids and cyprinids according to EU Freshwater Fish Directive (78/659/EEC, Annex 1) must be additionally analysed heavy metals 6 times a year
According to EU Freshwater Fish Directive (78/659/EEC) Estonian river monitoring has been organized in following rivers: R. Kunda (salmonids), R. Selja (salmonids), R. Pirita (salmonids), R. Keila (salmonids), R. Pärnu (salmonids), R. Narva (salmonids), R. Kasari (cyprinids), R. Emajõgi (cyprinids), R. Väike-Emajõgi (cyprinids). The directive requires that rivers with important fishery fall under analysis of all water quality indicators. We do not give additional proposals for the monitoring of rivers with important fishery. The first priority should be to implement measures to ensure required water quality for fishery. The main problem is increased total ammonia, nitrites and non-ionised ammonia values which fall within the mandatory (imperative) standards but fail to fulfill future guide values.
8.2.1. SUGGESTIONS FOR THE MONITORING OF POINT SOURCE POLLUTION
According to EU Urban Wastewater Treatment Directive (91/271/EEC, 98/15/EC) rivers of Table 8.2.1.1 require monitoring.
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Table 8.2.1.1. Requirements for end-of-pipe and operational monitoring of settlements
Discharge from Treatment Frequency Surface water body – outlet, Frequency No Settlement River Plant, parameters in year parameters in year
1 Abja-Paluoja Halliste river BOD7; COD; Ptot, NA 12 pH; dis.O2; BOD7; NH4+; Ntot, Ptot 12
2 Antsla Leese stream BOD7; COD; Ptot, NA 12 pH; dis.O2; BOD7; NH4+; Ntot, Ptot 12
3 Elva Kavilda river BOD7; COD; Ptot, NA 12 pH; dis.O2; BOD7; NH4+; Ntot, Ptot 12
4 Jõgeva Pedja river BOD7; COD; Ptot, NA 12 pH; dis.O2; BOD7; NH4+; Ntot, Ptot 12
5 Karksi-Nuia Halliste river BOD7; COD; Ptot, NA 12 pH; dis.O2; BOD7; NH4+; Ntot, Ptot 12
6 Mustvee Peipsi jlake BOD7; COD; Ptot, NA 12 pH; Ptot; Ntot; chlorofyll- a 12
pH; dis.O2; BOD7; NH4+; Ntot, Ptot; 7 Narva Narva river BOD7; COD; Ntot Ptot, NA 24 phenols 24
pH; dis.O2; BOD7; NH4+; Ntot, Ptot; 8 Narva-Jõesuu Narva river BOD7; COD; Ptot, NA 12 phenols 12
9 Otepää Elva river BOD7; COD; Ptot, NA 12 pH; dis.O2; BOD7; NH4+; Ntot, Ptot 12
10 Põltsamaa Põltsamaa river BOD7; COD; Ptot, NA 12 pH; dis.O2; BOD7; NH4+; Ntot, Ptot 12 pH; dis.O2; BOD7; NH4+; Ntot 11 Põlva Oraj river BOD7; COD; Ptot, NA 12 12 pH; dis.O2; BOD7; NH4+; Ntot 12 Räpina Võhandu river BOD7; COD; Ptot, NA 12 12 pH; dis.O2; BOD7; NH4+; Ntot 13 Tartu Ema river BOD7; COD; Ntot Ptot, NA 24 24 pH; dis.O2; BOD7; NH4+; Ntot 14 Tõrva Õhne river BOD7; COD; Ptot, NA 12 12 pH; dis.O2; BOD7; NH4+; Ntot 15 Valga Pedeli river BOD7; COD; Ntot Ptot, NA 12 12 pH; dis.O ; BOD ; NH +; Ntot Tänassilma river, 2 7 4 16 Viljandi Raudna river BOD7; COD; Ntot Ptot, NA 12 12 pH; dis.O ; BOD ; NH +; Ntot Kubija stream, 2 7 4 17 Võru Koreli stream BOD7; COD; Ntot Ptot, NA 12 12 pH; dis.O2; BOD7; NH4+; Ntot 18 Väike-Maarja Põltsamaa river OD7; COD; Ptot, NA 12 12
The municipal wastewater should be observed proportionally with runoff or at fixed time in one point of the outlet. Minimal number of sampling is defined by the size of the treatment plant. Monitoring of point emission sources need improvement to evaluate impact of pollution to aquatic environment and to assess its ecological status. That requires implementation of Polluter Pays Principle – self-monitoring of polluters to increase the responsibility of polluting enterprises for environmental damages. Although Estonian Law of Environmental Monitoring (RTI 1999, 10, 154) requires self-monitoring of enterprises, it does not still function sufficiently. Water and environmental permit require national approval of water quality parameters that describe pollution and sampling frequency that enterprise must organize, and impart the data to the national database. Also, the enterprise must guarantee that the samples are analyzed in an accredited water chemistry laboratory that successfully participates in comparison tests.
8.2.2 SUGGESTIONS FOR THE MONITORING OF THE ECOLOGICAL STATUS OF RIVERS
The surveillance monitoring of rivers is funded by the state budget under the item of the environmental monitoring and implemented within the structure of the national programme (Table 8.2.2.1.).
Table 8.2.2.1. Rivers of surveillance monitoring: rivers of 1 order with a catchment area over 100 km² No. of the National Monitoring Station Code River Catchment Area, km² 1 10002 Piusa 796 2, 3, 4 10030 Võhandu 1420 11, 12, 13 10236 Emajõgi 9740
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- 10511 Koosa 205 - 10526 Kullavere 627 - 10551 Mustvee 180 - 10563 Piilsi 103 27 10569 Avijõgi 393 28, 29 10587 Rannapungerja 601 30 10613 Alajõgi 150 5, 6 10082 Väike-Emajõgi 1380 7, 8 10137 Õhne 573 9 10165 Tartvastu 108 10 10180 Tänassilma 454 31, 32 10622 Narva 56200
Estonia is a typical country of short rivers with small catchments, relatively poor of water with fluctuating water regime, thus sensitive to human activities such as agricultural, industrial and municipal pressures. Small rivers, however, can be important from ecological point of view (high biodiversity etc.) offering close touch with local inhabitants. Although, national monitoring pays main attention to bigger rivers and their reaches. Small streams have not received necessary attention. Of Estonian rivers with catchment area of 10 – 100 km2 monitoring covers only 7 rivers of 779 (Table 8.2.2.2.). Thus, we recommend better monitoring of small rivers.
Table 8.2.2.2. Number of rivers and number of monitoring stations in relation with size categories of rivers Size category Size (km2) Number of rivers Number of monitoring stations Small 10 – 100 779 7 Medium 100 – 1000 120 35 Large 1000 – 10000 14 12 The largest > 10000 1 2
According to EU Water Framework Directive the estimation of biological and chemical values of reference values is important because it is the basis of classification and assessment of human impact. This requires each river basin districts to select background areas that are not influenced by direct human activities and to organize water monitoring in these background areas. In different river basin districts climatic, hydro-geological and landscape conditions differ, thus each sub-district should find at least one reference area. It requires in Estonia to develop background monitoring. A reference area should contain homogeneous characteristics in a small catchment. These small rivers should not receive wastewaters; agricultural lands should remain below 10%. Population should be dense to eliminate potential load from sparse population. This requires additional river catchments to be involved into national monitoring programme to evaluate reference conditions. These suitable catchments can be easily found in Estonia. Estonian National River Water Monitoring Programme should reduce number of stations in the major rivers but in the same time the number of stations in small rivers and reference sites should be increased. One of the objectives of EU Water Framework Directive is to achieve good ecological status of rivers by 2015. On that basis, we propose following additional monitoring programme from 2004 till 2015. Mantra-East working paper ”Indicators and Criteria for Assessment of Ecological Status of Rivers” has concluded 3 parameters showing organic pollution which is the main pollution problem in the region: (1) content of dissolved oxygen, (2) content of ammonia and (3) biochemical oxygen demand (BOD7). According to that report, parameters indicating the eutrophication and trophic level of waters, which is the main consequence of human impacts to water bodies in the region, are (1) total nitrogen and (2)
74 total phosphorus. These parameters should be constantly measured within the surveillance-monitoring programme aiming at evaluating the ecological status of the water body. Monitoring should focus on rivers where chemical quality is below “good” because these rivers require immediate environmental measures to achieve good quality. These measures require plannings and financial investments. Thus, the monitoring of status is necessary to evaluate the effectiveness and sufficiency of implemented environmental measures. If changes in significant pollution factors appear (changes and trends in agriculture, land use, waste water treatment, new industries etc), then additional monitoring is necessary to estimate long-term changes as well as spatial and temporal variability. Improvement of the monitoring total organic carbon (TOC) is necessary to characterize the content and origins of different organic compounds in rivers. Today, TOC is measured only 6 times per year in some selected rivers. Pollution of environment with 33 priority substances listed in the Water Framework Directive should be avoided with preventive and technology-based water protection measures. Estonia should develop ecotest-based pesticide control system within the river monitoring programme to evaluate the toxic impact of their biological accumulation. In case of toxic waste waters ecotests are also needed to evaluate the effect of each toxic emission source and synergy of several sources.
8.2.3. SUGGESTIONS FOR MONITORING OF FLUX STATIONS
One important task of monitoring is to determine pollution load of different substances discharging to the coastal waters and seas in Europe and entering to the transboundary water bodies. In Baltic region, river flow fluctuated remarkably during the seasons. The maximum flow rates occur in spring snowmelt time and during the autumn floods. It means that the main load discharging to the lakes and seas appear in the periods of high flow rates. In point of view of measuring fluxes of different pollutants it is necessary to increase sampling frequency during high flow periods. Better results come from flow-proportional sampling but that is complicated requiring expensive specific equipment. Thus, in evaluating pollution load it is suggested to increase sampling frequency while high water periods (spring, autumn) while decreasing the frequency in low water periods (summer, winter). Until now, in flux stations give water monthly samples 12 times per year.
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Alajõgi 14 3 12 10 2 8
m³/s 6 1 4 sampling frequency 2 0 0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Flow, 1996 Flow, 2001 sampling 2001 sampling, 1996
Figure 8.2.3.1 Sampling frequency and water runoff in R. Alajõgi.
Figure 8.2.3.1 illustrates present sampling frequency that does not consider flow rate. For example, during the spring and autumn floods that give half amount of total runoff, only 2–3 samples are taken. Such a sampling principle hardly succeeds to estimate the real pollution load because the concentration of pollution compounds correlates positively with runoff and short flood periods may be missed at low sampling frequency. Our suggested methodology would maintain the total number of 12 samples per year but springtime requires 4–6 samples, autumn flood period 3–4 while summer and winter time low water periods require only 1–2 samples per year.
We suggest following changes to Estonian National River Monitoring Programme: • Implementation of Polluter Pays Principle – self-monitoring of polluters to increase the responsibility of polluting enterprises for environmental damages. • We recommend better monitoring of small rivers. • Development of background monitoring. • Content of dissolved oxygen, content of ammonia, biochemical oxygen demand, total nitrogen and total phosphorus should be constantly measured within the surveillance- monitoring programme aiming at evaluating the ecological status of the water body. • Monitoring should focus on rivers where chemical quality is below “good” • If changes in significant pollution factors have appeared then additional monitoring is necessary to estimate long-term changes as well as spatial and temporal variability. • Our suggested methodology for monitoring of flux stations would maintain the total number of 12 samples per year but springtime requires 4–6 samples, autumn flood period 3 – 4 while summer and winter time low water periods require only 1 – 2 samples per year. • Inclusion of total organic carbon into the monitoring programme as parameter indicating origin and content of organic substances • Estonia should develop ecotest-based pesticide control system. • As an important factor determining the risk of cyanobacterial blooms in lakes, N/P ratio in river water should be routinely calculated.
8.3. TYPOLOGY OF RIVERS IN L. PEIPSI-VÕRTSJÄRV RIVER BASIN, SUGGESTED BY RIVER BIOLOGY WORKING GROUP (R. JÄRVEKÜLG, P. PALL, K. PIIRSOO, H. TIMM, S. VILBASTE, T. TREI & M. VIIK)
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Up to now several attempts have been made to create a typology of rivers corresponding to the requirements of the EU Water Framework Directive. In 2001 the first step was made while the act of the Minister of Environment No 33 (Pinnaveekogude…, 2001) established quality classes on the bases of hydrochemical parameters for Estonian surface water bodies, incl. for rivers. During the preparation of the act it was found, that chemical and physical quality elements of rivers do not need any typification of rivers in Estonia. (For example in case of lakes 3 types were separated: brown water dystrophic lakes, eutrophic lakes, and lakes which are neither dystrophic nor eutrophic). It was obvious already at that time, that in Estonia all running waters can not be treated as one type and the implementation of the Water Framework Directive needs the separation of different river types. After discussions (Baltic Environmental Forum seminars related to the implementation of the WFD in 2001-2002) it was generally accepted, that typology of rivers is needed in Estonia. In late 2001 and early 2002 the first effort to create a typology of Estonian rivers corresponding to the needs of the WFD was made in Estonia (Timm, 2002). The following typology of rivers was used in the project: 1. Ecoregion - all Estonia belongs to the Baltic ecoregion. 2. Altitude - practically all Estonian rivers are situated on lowland on altitude 0-200 m from sea level. 3. Geology - rivers running on the limestone and sandstone area were distinguished. Rivers with great natural organic impact were also mentioned, but not handled due to the lack of information; 4. River size - according to the size of the catchment area the following types of rivers were separated: Catchment area of the river reaches < 100 km2 Catchment area of the river reaches 100-250 km2 Catchment area of the river reaches 250-1000 km2 Catchment area of the river reaches 1000-2500 km2 Catchment area of the river reaches >2500 km2; 5. Two types of river reaches were separated according to the average current velocity: Slowly running rivers - average current velocity <0.2 m/s Fast running rivers - average current velocity >0.2 m/s
Totally 20 types of rivers were separated and attempt was made to determine the reference conditions and quality classes of both biological elements and supporting them hydromorfological and physico-chemical elements for all types. Unfortunately the results of the project were not fully acceptable, as the used typology did not take into account the needs of all biological elements. Different components of river biota have different demands to the environmental factors. The typology was mainly worked out by specialists working on the field of chemical and physical and hydromorfological parameters of rivers. Recommendations of biologists were considered only partly. In general, the concentration of nitrogen and phosphorus compounds in the water does not have direct impact on the level of primary production in river water. In the rivers, contrary to the lakes and sea, the autotrophic organisms (macro- and microalgae) are not able to utilize the whole amount of biogenes in the water. In Estonian rivers primary production is mainly limited by the light conditions. Important factors are also the bottom character to the macrophytes (to find places to anchor) and water residence time to phytoplankton (to have time to develop along a river).The most of problems appeared when fish fauna of rivers was analyzed, but there were also evident problems dealing with macrophytes. During the long- term investigations we found that the most sensitive component of river biota is fish fauna (the number of effective environmental factors was thirteen) (Timm, 2002). For vascular plants and macrozoobenthos the number of factors was nine and six, respectively (Timm, 2002).
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The aim of the current work was to develop and compile earlier typologies of rivers and to create the typology practically usable in the process of the implementation of the WFD in case of all biological elements, especially fish fauna, zoobenthos and macrophytes. On the other hand the lack of information concerning certain river types (especially in the case of rivers on organic soil) was evident. There was no possibility to complement the existing data during the project. Due to the limited time for analyses the current typology should be treated as a preliminary. Also it should be mentioned, that the typology was created mainly having regard to rivers of the catchment area of the L. Peipsi-Võrtsjärv. Therefore some changes may be necessary when to wide the typology to the whole Estonia. The base of the preliminary typology of rivers of the L. Peipsi-Võrtsjärv catchment area were biological, hydromorphological, and hydrochemical data gathered during complex hydrobiological fieldwork in 1992-2002. All in all 140 river reaches from 67 rivers were taken into consideration. As the material was collected on the other purposes not all parameters were determined for all studied river reaches and of course, not all the existing data were usable. The WFD offers choice between two classification systems (system A and system B). We have chosen the system B as a more flexible classification system giving possibility to take into account the local conditions. There was no need for longitudinal and altitude differentiation of rivers of the L. Peipsi-Võrtsjärv catchment area. But the size of the river is certainly very important for fauna and flora of the river. We analyzed three different river size characteristics - water discharge, river order and the size of the catchment area. Finally we agreed, that although minimum water discharge in low water period and river order are rather good characteristics, the most reasonable way to describe the river size would be to use the size of the catchment area of the river.
After analyses we separated 5 size groups of rivers/river reaches in the L. Peipsi- Võrtsjärv river basin: • Very small to small rivers/river reaches - catchment area < 75 km² • Small to medium size rivers/river reaches - cathment area 75 to 300 km² • Medium size rivers/river reaches - catchment area 300 to 1000 km² • Large rivers/river reaches - catchment area 1000 to 5000 km² • Very large rivers - catchment area >5000 km²
The thresholds between different types are preliminary and they need to be tested and analyzed also in other watersheds of Estonia. We have chosen these size categories mainly on the bases of fish data, as the fish fauna is the most sensible component of the river ecosystem what concerns the river size. Other biological elements (zoobenthos, benthic vegetation, phytoplankton, bacterioplankton) are less influenced by the size of the river.
According to the geological conditions we divided the rivers into two classes (Järvekülg et. al., 2003): • calcareous and siliceous type with low concentration of humic compounds in water (CODCr <35 mgO/l, light water), • organic soils type with high concentration of humic compounds in water (CODCr >35 mgO/l, brown water).
It is evident, that rivers beginning and running mainly through extensive bog and swamp areas are rich in humic compounds and there are specific living conditions for fauna and flora. Although there was a lack of data concerning brown water humic rich streams we considered very important to differentiate brown and light water rivers. The composition and structure of zoobenthos depend on the bottom character (muddy, sandy, gravelly, stony) of the river reach. But it also appeared, that the alkalinity of water could be important factor for
78 zoobenthos (Timm, 2002). Subsequent and more precise analyses must find out is it necessary to differentiate also the rivers running mainly on limestone or sandstone areas. The natural hydromorphological character of river greatly influences both the fauna and flora of the river. Therefore, it is important to take into consideration also the main hydromorphological conditions of a river site.
According to the hydromorphological characteristics we divided the river reaches into three classes: • rhitral river reaches (high slope, high flow velocity, no extensive sedimentation processes, mainly stony or gravelly bottom, e. g. riffles - living conditions for potamal species are poor or absent); • potamal river reaches (low slope, slow flow velocity, sedimentation is considerable, soft bottom (sand, mud, clay) prevails - living conditions for rhitral species are poor or absent); • intermediary character of the river reach (both rhitral and potamal species may occur)
For fish fauna the most important environmental factors influencing the species composition are the temperature regime of the river and amount of flow rate (Järvekülg, 1994; Keskminas & Virbickas, 1999; Järvekülg et.al., 2001, etc.). The former is characterized well by maximum water temperature in midsummer the latter by the minimum amount of water flow in the summer low-water period. In Estonian rivers there are clearly differentiated fish communities of cold water streams and warm water streams. There is also a temperate water region where both cold and warm water fish species may occur. Therefore, we found important to distinguish following 3 groups of rivers: • river reaches with cold water (maximum water temperature in summer <16ºC, warm water species are absent) • river reaches with temperate water (maximum water temperature in summer 16- 21ºC, both cold and warm water species may occur) • river reaches with warm water (maximum water temperature in summer >21ºC, cold water species are absent) The temperature regime of the river may essentially influence beside the fish fauna also the zoobenthos and macrophyte communities, but until now there is few particular data on that in Estonia. The potential number of river reaches was 90 by this kind of typification. Really the number of different types of river reaches in the L. Peipsi-Võrtsjärv river basin was 28 (Figures 8.3.1- 8.3.5, Appendices 1-2).
<75 75-300 300-1000 1000-5000 >5000
Cal/sil. Org.
Rith. Rith/Pot. Pot. Rith. Rith/Pot. Pot.
Cold-water Warm water
Moderate water
Figure 8.3.1. Preliminary typology of rivers on the basis of data in the L. Peipsi-Võrtsjärv river basin. 79
<75 km2 n=52
Cal/sil. Org. n=44 n=8
Rith. Rith/Pot. Pot. Rith. Rith/Pot. n=15 n=21 n=2 n=3 n=3
Moderate Moderate Cold-water Cold n=3 n=3 Warm Cold n =6 n=11 n=3 n =1
Warm Moderate n=1 n=12
Moderate water Figure 8.3.2. Number of river reaches with catchment n=4 area <75 km2 in the L. Peipsi-Võrtsjärv river basin.
75-300 km2 n=50
Cal/sil. Org. n=39 n=11
Rith. Rith/Pot. Pot. Rith. Rith/Pot. Pot. n=11 n=19 n=5 n=2 n=5 n=1
Warm Moder Warm Moderate Cold-water Warm n=3 n=3 n=2 n=2 n=2 n=5 Moderate Moderate Moderate n=1 n=16 n=3
Moderate water Figure 8.3.3. Number of river reaches with catchment n=6 area 75-300 km2 in the L. Peipsi-Võrtsjärv river basin.
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300-1000 km2 n=31
Cal/sil. Org. n=30 n=1
Rith. Rith/Pot. Pot. Rith/Pot. n=5 n=17 n=8 n=1
Warm Warm Moderate n=10 n=6 n=1
Warm water Moderate Moderate n=7 n=2 n=2 Figure 8.3.4. Number of river reaches with Moderate 2 water catchment area 300-1000 km in the L. Peipsi- n=3 Võrtsjärv river basin.
1000-5000 km2 n=7
Cal/sil. n=7
Rith/Pot. Pot. n=2 n=5
Warm Warm n=2 n=5
Figure 8.3.5. Number of river reaches with catchment area 1000-5000 km2 in the L. Peipsi-Võrtsjärv river basin.
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9. SUGGESTIONS FOR ADJUSTMENT OF NATIONAL MONITORING PROGRAM OF LAKE PEIPSI ACCORDING TO WFD REQUIREMENTS (T. NÕGES, H. TIMM)
As Lake Peipsi is a transboundary water body, it creates many problems of monitoring of the lake and catchment basin as an integrated system. It is, however, the responsibility of the countries implementing Water framework Directive to establish coordinated management of transboundary basins. Regular investigation of L. Peipsi started in 1960s and up to now about 35 year dataseries on water chemistry and biology have been gathered. The sampling frequency per year and the number of sampling stations has varied from 3 to 8 times and from 4 to 24 stations. As L. Peipsi is the largest transboundary water body in Europe (shared by Estonia and Russia) its monitoring and management is an object of regulation of Estonian-Russian Commission of Transboundary Waterbodies. On non-govermental level various activities are carried out by NGO Center of Transboundary Cooperation. In Estonia the research of L. Peipsi involves mainly (1) state monitoring, the framework established in 1992; (2) state fishery research; (3) target-financed research at Universities; (4) research projects of Estonian Science Foundation, European Commission, NATO. Hydrochemistry of L. Peipsi is presently monitored by Tartu Environmental Research Ltd. and hydrobiological indices by Võrtsjärv Limnological Station of Institute of Zoology and Botany at Estonian Agricultural University. State fishery research is made by Institute of Zoology and Hydrobiology at Tartu University. These studies are mainly targeted to establishing of catch limits and considers mainly commercial fish species. Therefore the collected data are only partly applicable for tha analysis of the status of the whole ecosystem. In frames of Estonian national monitoring programme the following indices are monitored in large lakes in 1992-2000 1. General indices: Water temperature, dissolved oxygen content (mg/l), Secchi depth (m) 2. Hydrochemistry Water color (o), pH, alcalinity (mmol/l), conductivity (uS/cm) Suspended solid concentration (mg/l) Biochemical oxygen demand, chemical oxygen demand by permanganate (mgO/l) Ammonium, nitrite, nitrate, total N (mgN/l) Soluble reactive P and total P (mgP/l) Chlorides, sulphates, iron, sodium, potassium, silicon (mg/l) Calcium and magnesium (mmol/l) Oil products and heavy metals (Cd, Cu, Hg, Pb ja Zn) 3. Phytoplankon Total biomass (gWW/m3), number of species, list of dominant species Biomasses of blue-greens, diatoms, chlorophytes, chrysophytes and pyrrophytes Concentration of chlorophyll a (mg/m3) 4. Zooplankton Total abundance (ind/l) and biomass (gWW/m3) of metazooplankton List of species dominating by abundace and by biomass Percentage of copepods, cladocerans and rotifers in total abundance and biomass Total abundance (ind/l) and biomass (gWW/m3) of ciliates (since 1995) 5. Bacteria Total count (millions of cells/ml), plate count (cells/ml) 6. Benthic macroinvertebrates Abundance (ind/m2) and biomass (g/m2) of chironomids, oligochaets, small molluscs other small inverebrates and big clams List of species dominating by abundace and by biomass
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Estonian national monitoring program of Lake Peipsi is quite well integrated between different disciplines. Considering the linkages between river and lake monitoring, it should be noted that the routine calculation of nutrient loading should be added into the river monitoring program to allow better interpretation of the lake ecosystem changes. There are, however several shortcomings considering the requests of Water Framework Directive, e.g as fish and macrophyte monitoring is not included into the program. Also the present monitoring strategy of bottom macroinvertebrates seems not to reflect the changes of ecological status. Regularly monitored macroinvertebrate metrics contain some elements, which enable to use them to estimate ecological status in limited way. They serve quite well as fish food estimation measures (abundance, biomass, proportion of the especially valuable groups). In order to explain, how macroinvertebrate indices couple with depth and substrate combinations in different lake parts, the location of some sampling sites should be changed. The current sites overlap with water monitoring stations in which bottom substrate and water depth are not taken into consideration. Monitored macroinvertebrate metrics is generally not changing concurrently with hydrochemical and phytoplankton metrics. This is not so much a shortcoming of the current monitoring program but is caused by the specific character of bottom animals. They do not react to changes so rapidly as chemical and plankton indices. Therefore, in principle it is reasonable to establish quality classes for some currently estimated macrozoobenthos metric in Lake Peipsi but such classes tell us very little. Alternative metrics of macrozoobenthos for Lake Peipsi could be the shallow-water handnet method, used in Sweden and having established quality classes for several metrics tested in small lakes of Estonia (2000-2002) and also in Lake Peipsi (northwestern part, October 2002).
The following suggestions for adjustment of L. Peipsi monitoring program should be considered: 1. Including the routine calculation of nutrient loading into the river monitoring program. 2. Including the monitoring of macrovegetation. 3. Including the monitoring of abundance, biomass and age structure of all fish species. 4. The current monitoring program of macrozoobenthos in open-water areas should be continued. It gives valuable data for estimation of fish food and enables to watch year-to- year variability of abundance and biomass that is not possible to achieve in another way. A simple reorganisation of open-water sampling sites could give us both the data of fish food (at the same level), and also the estimation of ecological quality of different parts of lake. Moreover, studies of shallow areas with handnet samples are recommended for the last purpose. However, there is an objection against this suggestion from Dr. Külli Kangur who is responsible for the biological monitoring of L. Peipsi. She consideres suggested changes of macrozoobenthos sampling stations unjustified as it will break long- term data series at fixed stations, and may disturb analyses of the data of hydrochemistry, plankton, macrozoobenthos and fishes from the same stations to find out common trends and interactions. She also stresses that the data gathered since now do not give information only about fish food but are also important for analysis of biodiversity at species level.
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Vagstad, N.1994. Changes in agricultural practices and possible effects on nutrient run-off. Proceedings of the NorFa seminar, November 10-12, 1994. Jelgava, 52 p. Vagstad, N. et al. 2001. Nutrient Losses from Agricultura in the Nordic and Baltic Countries. Measurements in small agricultural catchments and national agroenvironmental statistics. TemaNord 2001:591, Nordic Council of Ministers, Copenhagen, 74 p. Veijola H., Meriläinen J.J., Marttila V., 1996. Sample size in the monitoring of benthic macrofauna in the profundal of lakes: Evaluation of the precision of estimates. - Hydrobiologia 322: 301- 315. Ventilla R., House M.A., Green C.H. 1989. Expert systems as an aid to water quality assessment. Proceedings of IAWPRC Conference held in Rovaniemi, Finland, 1989. River Basin Management – V, pp. 47-58. Vesistöjen Laadullisen Käyttökelpoisuuden Louittamien. Vesi- ja Ympaäristöhallitus. Helsinki 1988. Vighi, M., Chiaudani, G., 1985. A simple method to estimate lake phosphorus concentrations resulting from natural background loadings. Water Res. 19: 987-991. Vilbaste S, and Truu J. 2003. Distribution of benthic diatoms in relation to environmental variables in lowland streams. Hydrobiologia in press. Vilbaste S. 2001. Benthic diatom communities in Estonian rivers. Boreal Environmental Research 6: 191-203. Vinkel-Voore, R. 1935. Vee õitsemine Peipsi järvel. - Eesti Loodus 1: 24. Wiederholm, T. (ed.) 2000. Environmental Quality Criteria. Lakes and Watercourses. SEPA Report 5050. ARALIA, Lemnanders, Kalmar. Wiederholm, T. 1980. Use of benthos in lake monitoring. J. Wat. Pollut. Control Fed. 52: 537-547. Winfield, I. J., Adams, C. E. & Fletcher, J. M., 1996. Recent introductions of the ruffe (Gymnocephalus cernuus) to three United Kingdom lakes containing Coregonus species. Annales Zoologici Fennici 3-4, 459-466. Yefimova, A. I., 1966. Vendace in Lake Peipsi. In: E. Pihu, A. Mäting (Eds.), Hydrobiology and fisheries of Lake Peipsi-Pskov, pp. 140-174. Tallinn.
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APPENDIX 1. THE NAMES OF THE RIVER/RIVER REACHES IN THE L. PEIPSI- VÕRTSJÄRV RIVER BASIN. THE NUMBER OF RIVER REACHES IS GIVEN IN PARENTHESES.
1. Catchment area < 75 km2 (52)
1.1. Calcareous/siliceous (oligohumic: CODCr concentration < 35 mgO/l) (44). 1.1.1. Rhitral (15). 1.1.1.1. Cold water (maximum water temperature in summer <16 /C) (11): 1. R. Ahja 1 - Ropso 2. R. Avijõgi 1- Alekvere 3. R. Avijõgi 2- Paasvere 4. R. Luutsna 1- Rookse 5. R. Meeksi - Vahtseliina 6. R. Nõmme - Punamäe 7. R. Oostriku 8. R. Pedja 1- Simuna 9. R. Põltsamaa 1- Kiltsi 10. R. Raudoja - Illi 11. R.Võllinge- the lower reach 1.1.1.2. Temperate water (maximum water temperature in summer 16-21 /C) (4): 1. R. Hilba - Möksi 2. R. Kavilda 5 - Kavilda 3. R. Laguja 2 - the lower reach 4. R. Tagajõgi 1- Oonurme2 1.1.1.3. Warm water (maximum water temperature in summer > 21 /C) (absent). 1.1.2. Rhitral-potamal (21). 1.1.2.1. Cold water (maximum water temperature in summer <16 /C) (6): 1. R. Ahja 2 - Tilleorg 2. R. Ahja 3 - Aarna 3. R. Illi - Illi 4. R. Nõo 2 - the lower reach 5. R. Pedja 2 - Mällo 6. R. Tatra - Aarike 1.1.2.2. Temperate water (maximum water temperature in summer 16-21 /C) (12): 1. R. Amme 2 - Ehavere 2. R. Haavakivi 2- the lower reach 3. R. Kavilda 4- Kobilo 4. R. Laeva 1 - Pirusi 5. R. Orajõgi - Himmaste 6. R. Peeda 2 - S_Kambja 7. R. Piusa 1- Vana-Saaluse 8. R. Umbusi - Umbusi 9. R. Visula - Koljaku 10. R. Voika 2 - the lower reach 11. R. Võhandu 1 - Ritsike 12. R. V-Emajõgi 2 - Märdi 1.1.2.3. Warm water (maximum water temperature in summer > 21 /C) (3): 1. R. Amme 1- Järvepera 2. R. Kavilda 3 - Aru 3. R. V-Emajõgi 1- Sihva 1.1.3 Potamal (2). 1.1.3.1. Cold water (maximum water temperature in summer <16 /C) (1):
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1. R. Kavilda 2 - Krasna 1.1.3.2. Temperate water (maximum water temperature in summer 16-21 /C) (absent). 1.1.3.3. Warm water (maximum water temperature in summer > 21 /C) (1): 1. R. Kavilda 1- Elva traffic circle.
1.2. Organic soil type (polyhumic: CODCr concentation 35 mgO/l) (8). 1.2.1. Rhitral (3). 1.2.1.1. Cold water (maximum water temperature in summer <16 /C) (absent.) 1.2.1.2. Temperate water (maximum water temperature in summer 16-21 /C (3): 1. R. Aksi 2. R. Avinurme - Avinurme 3. R. Karja - Venevere 1.2.1.3. Warm water (maximum water temperature in summer > 21 /C) (absent). 1.2.2. Rhitral-potamal (3). 1.2.2.1. Cold water (maximum water temperature in summer <16 /C) (absent.). 1.2.2.2. Temperate water (maximum water temperature in summer 16-21 /C (3): 1. R. Elva 2 - Kintsli 2. R. Leevi - Põrste 3. R. Õhne 1 - Ala 1.2.2.3. Warm water (maximum water temperature in summer > 21 /C) (absent). 1.2.3. Potamal (absent). 2. Catchment area 75-300 km2 (50)
2.1. Calcareous/siliceous (oligohumic: CODCr concentration < 35 mgO/l) (39). 2.1.1.Rhitral (11). 2.1.1.1. Cold water (maximum water temperature in summer <16 /C) (5): 1. R. Avijõgi 3 - Arukse 2. R. Helme - Helme 3. R. Onga - Onga 4. R. Piusa 2 - Vahtseliina 5. R. Preedi - Rõhu 2.1.1.2. Temperate water (maximum water temperature in summer 16-21 /C (6): 1. R. Avijõgi 4- Kaasiksaare 2. R. Avijõgi 5 - Kõveriku 3. R. Piigaste - Punaku 4. R. Pikknurme - Pikknurme 5. R. Piusa 3 - Tellaste 6. R. Võhandu 2 - Vihtla 2.1.1.3. Warm water (maximum water temperature in summer > 21 /C) (absent). 2.1.2. Rhitral-potamal (19). 2.1.2.1. Cold water (maximum water temperature in summer <16 /C) (absent). 2.1.2.2. Temperate water (maximum water temperature in summer 16-21 /C (16): 1. R. Ahja 4 - Koorvere 2. R. Amme 4 - Igavere 3. R. Elva 4 - Uderna 4. R. Elva 5 - Elva 5. R. Jõku - Rulli 6. R. Luutsna 3 - Melliste 7. R. Pedja 3 - Reastvere 8. R. Porijõgi 4- Reola 9. R. Purtsi - Purtsi 10. R. Võhandu 3 - Utita
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11. R. Võhandu 4 - Sõmerpalu 12. R. V-Emajõgi 3 - Restu 13. R. V-Emajõgi 4 - Sangaste 14. R. Õhne 3 - Koorküla 15. R. Õhne 4 - Patküla 16. R. Ärnu - Iigaste 2.1.2.3. Warm water (maximum water temperature in summer > 21 /C) (3): 1. R. Amme 3 - Lilu 2. R. Antsla - Liiva 3. R. Laeva 4 - Kärevere 2.1.3. Potamal (5). 2.1.3.1. Cold water (maximum water temperature in summer <16 /C) (absent). 2.1.3.2. Temperate water (maximum water temperature in summer 16-21 /C (3): 1. R. Laatre - Laatre 2. R. Lutsu - Arnike 3. R. Piilsi 3- the lower reach 2.1.3.3. Warm water (maximum water temperature in summer > 21 /C) (2): 1. R. Mädajõgi - S_Veerks. 2. R. Sillaotsa 2.2. Organic soil type (polyhumic: CODCr concentation 35 mgO/l) (11): 2.2.1.Rhitral (2). 2.2.1.1. Cold water (maximum water temperature in summer <16 /C) (absent). 2.2.1.2. Temperate water (maximum water temperature in summer 16-21 /C (2): 1. R. Elva 3 - Palu 2. R. Tagajõgi 2 - Tagajõe 2.2.1.3. Warm water (maximum water temperature in summer > 21 /C) (absent). 2.2.2. Rhitral-potamal (5). 2.2.2.1. Cold water (maximum water temperature in summer <16 /C) (absent). 2.2.2.2. Temperate water (maximum water temperature in summer 16-21 /C (3): 1. R. Luutsna 2- Võnnu 2. R. Luutsna 4 - Kaagvere 3. R. Põltsamaa 2 - Piibe 2.2.2.3. Warm water (maximum water temperature in summer > 21 /C) (2): 1. R. Kääpa 3 - Koseveski 2. R. Mõra 3 - Haaslava 2.2.3. Potamal (1). 2.2.3.1. Cold water (maximum water temperature in summer <16 /C) (absent). 2.2.3.2. Temperate water (maximum water temperature in summer 16-21 /C (1): 1. R. Õhne 2 - Holdre Warm water (maximum water temperature in summer > 21 /C) (absent).
3. Catchment area 300 - 1000 km2 (31).
3.1. Calcareous/siliceous (oligohumic: CODCr concentration < 35 mgO/l) (30). 3.1.1. Rhitral (5). 3.1.1.1. Cold water (maximum water temperature in summer <16 /C) (absent). 3.1.1.2. Temperate water (maximum water temperature in summer 16-21 /C (3): 1. R. Avijõgi 7 - Vadi village 2. R. Pedja 4 - Rohe 3. R. Õhne 5 - Härma 3.1.1.3. Warm water (maximum water temperature in summer > 21 /C) (2): 1. R. Avijõgi 6 - Vadi ford
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2. R. Pedja 6 - Tõrve 3.1.2. Rhitral-potamal (17). 3.1.2.1. Cold water (maximum water temperature in summer <16 /C) (absent). 3.1.2.2. Temperate water (maximum water temperature in summer 16-21 /C (7): 1. R. Ahja 5 - V-Taevaskoja 2. R. Ahja 6 - Porgandi 3. R. Amme 5 - Metsküla 4. R. Amme 6 - Haava 5. R. Piusa 4- Piusa 6. R. Põltsamaa 3 - Jõeküla 7. R. Võhandu 9 - Reo 3.1.2.3. Warm water (maximum water temperature in summer > 21 /C) (10): 1. R. Amme 7 - Kärkna 2. R. Avijõgi 8 - Sepera 3. R. Elva 8 - Mosina 4. R. Pedja 5 - Härjanurme 5. R. Pedja 7 - Puurmanni 6. R. Pedja 8 - Utsali 7. R. Põltsamaa 5 - Pajusi 8. R. Võhandu 8 - Leevi 9. R. V- Emajõgi 5 - Tagula 10. R. V-Emajõgi 6 - Iigaste 3.1.3. Potamal (8). 3.1.3.1. Cold water (maximum water temperature in summer <16 /C) (absent). 3.1.3.2. Temperate water (maximum water temperature in summer 16-21 /C (2): 1. R. Õhne 6 - Leebiku 2. R. Õhne 7 - Suislepa 3.1.3.3. Warm water (maximum water temperature in summer > 21 /C) (6): 1. R. Ahja 7 - Vanamõisa 2. R. Elva 9 - Ulila 3. R. Kullavere 6 - Omedu 4. R. Võhandu 5 - Võru 5. R. Võhandu 6 - Kirumpää 6. R. Võhandu 7 - Kääpa 3.2. Organic soil type (polyhumic: CODCr concentation 35 mgO/l) (1). 3.2.1.Rhitral (absent) 3.2.2. Rhitral-potamal (1). 3.2.2.1. Cold water (maximum water temperature in summer <16 /C) (absent). 3.2.2.2. Temperate water (maximum water temperature in summer 16-21 /C (1): 1. R. Põltsamaa 4 - Rutikvere 3.2.2.3. Warm water (maximum water temperature in summer > 21 /C) (absent). 3.2.3. Potamal (absent). 4. Catchment area 1000 - 5000 km2 (7)
4.1. Calcareous/siliceous (oligohumic: CODCr concentration < 35 mgO/l) (7). 4.1.1. Rhitral (absent.) 4.1.2. Rhitral-potamal (2): 4.1.2.1. Cold water (maximum water temperature in summer <16 /C) (absent). 4.1.2.2. Temperate water (maximum water temperature in summer 16-21 /C (absent). 4.1.2.3. Warm water (maximum water temperature in summer > 21 /C) (2): 1. R. Põltsamaa 6 - V- Kamari 2. R. Võhandu 11 - Räpina
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4.1.3. Potamal (5). 4.1.3.1. Cold water (maximum water temperature in summer <16 /C) (absent). 4.1.3.2. Temperate water (maximum water temperature in summer 16-21 /C (absent). 4.1.3.3. Warm water (maximum water temperature in summer > 21 /C) (5): 1. R. Põltsamaa 7 - Lalsi 2. R. Võhandu 10 - Toolamaa 3. R. V- Emajõgi 7 - Sooru 4. R. V- Emajõgi 8- Jõgeveste 5. R. V- Emajõgi 9- Pikasilla 4.2. Organic soil type (polyhumic: CODCr concentation 35 mgO/l) (absent).
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APPENDIX 2. NUMBER OF RIVER REACHES IN DIFFERENT TYPES OF RIVERS IN THE L. PEIPSI-VÕRTSJÄRV RIVER BASIN.
Geol. Hydromorphol. Character <75 75-300 300- 1000- conditions character of water km2 km2 1000 5000 temp. n=52 n=50 km2 km2 n=31 n=7 Cal+Si 44 39 30 7 Rhitral 15 11 5 0 Cold 11 5 0 0 Temperate 4 6 3 0 Warm 0 0 2 0 Rhitral-Potamal 21 19 17 2 Cold 6 0 0 0 Temperate 12 16 7 0 Warm 3 3 10 2 Potamal 258 5 Cold 1 0 0 0 Temperate 0 3 2 0 Warm 1 2 6 5 Organic 811 1 0 Rhitral 320 0 Cold 0 0 0 0 Temperate 3 2 0 0 Warm 0 0 0 0 Rhitral-Potamal 351 0 Cold 0 0 0 0 Temperate 3 3 1 0 Warm 0 2 0 0 Potamal 010 0 Cold 0 0 0 0 Temperate 0 1 0 0 Warm 0 0 0 0
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