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A substance which is present at concentrations which cause harm or

A substance which is present at concentrations which cause harm or. exceed an environmental standard is considered to pollute the environment. In. disturbances. reality any change or. in the environment due to human activity.

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A substance which is present at concentrations which cause harm or

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  1. A substance which is present at concentrations which cause harm or exceed an environmental standard is considered to pollute the environment. In disturbances reality any change or in the environment due to human activity may affect the mean abundance of populations or may not, at least at some temporal scale, but are exctremely important for the long-term persistence or conservation (rates of reproduction or mortality) of a species (Underwood 1991) or the spatial dispersion of the organisms. DISTURBANCES

  2. Types of disturbances pulse disturbances There are (pollutant: pathogens, heavy metals, organic pollution, suspended solids, nitrate pollution, eutrophication, acidification, thermal pollution, pesticides, environmental oestrogens) (fig.1)which are acute, short-term episodes of disturbance which may create a temporary pulse of change in a population, although a short-term change may itself cause long-term press disturbance (Table I) consequences. There is a which is a sustained or chronic interference with a natural population which would provoke long-term and usually non-recoverable changes in the populations. Finally, there exist catastrophes which are major, often planned, destructions of habitat, under which organisms can not recover because their habitat is actually removed. The time course of the first two disturbances is intimately related to the life cycle and longevity of the potentially affected organisms.

  3. BIOMONITORING • Biomonitoring is the measurement of effects of pollutants on natural aquatic test organisms ranging from bacteria to fish. Effects include mortality, growth inhibition, cancers and tumours, genetic alteration and reproductive failure. Effects can also be measured in the field by measuring species diversity. Biomonitoring also includes the measurement of pollutants that are accumulated in tissue and other organs of biological organisms.Biomonitoring must lead to an integrated strategy for surveillance, early warning and control of freshwater ecosystem, which will be able to respond to the different impacts in the time and space. The conception “monitoring” is a specific information system for an assessment of the anthropogenic character of changes and the environmental fluctuations on a background of natural ones. As an element of the global environment monitoring, the biological monitoring is a permanent registration of the biodiversity, the structure and the living system functioning (Socolov & Smirnov, 1978).The toxic effect must be monitored for different levels of the biological material organization molecular, cellular, individual and population.

  4. Pollution and season Mediterranean running water ecosystems exhibit seasonal peculiarities, concerning their hydrological conditions. During summer period temperature is greatly increased, while humidity decreases in a varying degree. The result is a decrease of water discharge, causing the rivers to get sometimes completely dry. The above process ultimately affects the structure of benthic macroinvertebrate communities (fig.2). On the other hand, rivers are largely used for the irrigation of agricultural activities. In order to meet the increased water demands for the irrigation of fields, large ammounts of water are removed from the rivers via dams , thus aggravating the reduced water discharge. The decreased discharge provokes the concentration of nutrients or/and some heavy metals (fig.3) and ultimately affects the structure and synthesis of benthic macroinvertebrate communities. Recolonization. In the mediterranean region streams are also dried during summer. Recolonization happens in these streams or creaks in the beginning of the autumn or winter depending on the climatic conditions of a country. The first stages of recolonization usually include tolerant taxa and this may result to inaccurate assessment of water quality (fig.4).

  5. Chronobiologicalimplications A major problem concerning any biological sampling is that temporal and spacial patterns are not simple to separate. Understanding the natural temporal changes in populations is, however, essential for any interpretation of their ecology and, particularly, for any programme of management and conservation. It is impossible to make realistic predictions about future abundunces if temporal changes are notunderstood. For example, the assessment of water quality based on biotic indices can be proved inaccurate if the chronobiology and life cycles of benthic organisms is not taken into consideration. Thepresence or absence of several taxa from a site may be related to their life cycles (e.g.Plecoptera fig.6)and thus can modify the values of the biotic indices providing misleading results to whether these changesare related to a source of pollution or not. On the other hand, pollution events may influence various developmental or behavioural stages affecting the abundance of the organisms resulting to controversialconclusions. So much more thought is required about the processes by which detection, interpretation andprediction of environmental threats can be made. Additionally good environmental programmes ofsampling (sampling sites, sampling frequency, sampling methodology) (see 5.1.1) and a good knowledgeof the biology of organisms is needed for monitoring any type of the environment.

  6. Physical or Biological implications

  7. Standards and Toxicity testing environmental standards A key tool in monitoring is the use of . Many standards are set to protect human health, but there are also a range of other standards for the natural environment (as a particular type of fishery). For many substances there is no threshold for effect. In this case a risk assessment is undertaken and a value is derived which is considered "reasonable". For example, the air quality standard for particulates for human health is not set at a level below which it is thought that there is no effect, but at a level below which the effects are thought to be minimal. The simplest type of development of standards is to examine data for thresholds for significant effects and then use this number as the standard ( e.g. critical levels of air pollution, phosphate standards for freshwater ecosystems e.t.c.). In toxicology, such as threshold is commonly referred to as the no effect level (NOEL), either measured directly or estimated by a statistical analysis of response data to pollutant exposure.

  8. Directives There exist directives which demand from the Member States of the E.U. to establish monitoring networks to follow the quality of the air (92/72/EEC for ozon pollution) or of fresh water (C184/20/17.6.97). Many countries of the E.U. have specialized organisations or institutions to undertake the regular monitoring. One of the biggest obstacles to good information from monitoring is that a wide range of organisations undertake monitoring, although not always in relation to each other. It is sometimes difficult, therefore, to compare information and thus form a more holistic view of the environment. The Environment Agency in the U.K. is currently attempting to rectify this. By building a common framework and overcome problems of data sharing etc. land-use management decisions can be aided, and better informed policy and legislation can be produced. : .

  9. Environmental monitoring and surveillance of water bodies Water quality monitoring However, all water quality monitoring techniques and sampling chemical approach methodologies introduce some bias. The advantages of (discrete or automatic samplers) are the smaller variability between replicates and the highly specific nature of the data obtained in terms of which pollutants /toxins are present and at which concentrations. But they must be continuous in order to be more representative and this is possible only for some determinands such as pH, ammonium,temperature, dissolved oxygen, turbidity and chlorophyll- biological monitoring a (currently it is developed for others too). Whereas encompases the ecological quality and uses the responses of biota to changes in water quality as a method of assessing such changes. Water quality impact community status may be monitored at a number of different levels, from (e.g. fish/invertebrate indices), through population effects (which take into account fecundity and age-specific survivorship), to the presence/absence of indicator species (individual species of mayfly or caddis-fly larvae have different tolerances to water acidification) and effects on the individual which range from whole organism mortality to sub-lethal tests at the cellular or tissue level. This behavioural techniques last group includes , pathology, developmental biochemical assays tests(e.g. the oyster embryo development bioassay), (e.g. the induction of cholinesterase enzyme activity), physiological tests bioaccumulation studies (respiratory activity, ventilation rate, e.t.c.) and (Calow and Petts 1995). The best and the most integraded method of monitoring though is the one that takes into consideration both biological aspects and physicochemical parameters of the environment.

  10. In nature many factors determine whether a species are present or not. When human activity introduce a change in a water quality or in habitat structure, different species react differently. Some will increase in numbers, new species may appear, other species may be reduced or disappear. The exercise of analysing the situation is then the important part. Sometimes the reasons for differences and changes is clear, but often there might be various causes. To struggle with complex problems, as environmental problems generally creates discussions and hopefully a better understanding of conflicts and problems. Water is a resource in itself and its quality is reflected by the organisms that live in it. The best pictures appears when you know the complete species composition, the conditions of the individuals, the structure of populations and have additive information about the chemical and physical environment. However, even with limited information about the species and only a few simple observations about the waterbody, the water chemistry and the surroundings, one can get a very informative picture.Monitoring over time, from year to year, will give an information about a stable situation or a situation under change. Whether a species is present or not in a waterbody dependes on eventually geographical barriers. Geographical barriers appear in all aquatic ecosystems, but particularly in freshwater habitats. Freshwaters are often aquatic "islands" in a terrestrial "ocean", and many species are not able to colonize them. If, however, an organism has been able to reach an area, a further success depends on the selective forces acting there. Those will decide whether a certain species or form will survive and reproduce or go extinct. These forces can be biotic or abiotic.

  11. Design of sampling and analysis Despite the enormous and widespread need to be able to identify and, where possible, predict the effects of human disturbances in natural ecosystems, there is still insufficient attention paid to the basic requirements of design of sampling and analysis of quantitative data from field surveys (Calow anf Petts, 1995). It is vital that the effort given to monitoring is properly targeted, otherwise the data collected will have limited value. Collecting data is no substitute for clear analytical thinking. It is perfectly possible to be "data tich and information poor". Monitoring and environmental sampling for eventual management and conservation of habitats and species must operate within a framework of logic and design around specific anticipated processes and results. If not sampling is clearly confounded and any effect of the disturbance cannot be distinguished from natural variation between locations or time. The design of monitoring programmes involves decision-making with regard to four major factors: 1. Sampling sites (there must always exist a sampling site before the source point pollution and one after). 2.Sampling frequency (see 1.5.1, 1.5.1.2). 3. Sampling methodology (the same method must be always used for comparison reasons)(see 1.4.2). 4. Choise of appropriate analytical methodology (including analytical quality control (AQC) procedures e.t.c.).

  12. Indices- scores or other • Saprobiotic • Diversity indices • Biological indices • Predictive models leading to an biologic index

  13. Trent Biotic Index (TBI, Αγγλία, 1964) France (ΙΒ, 1968) Extended B.I (ΕΒΙ, Αγγλία, 1978) Chandler index (1970, Σκωτία) France (IGB, Γαλλία, 1982) G.B.(BMWP) (M. Βρετανία, 1978) Extended B.I.Italy (ΙΒΕ Ιταλία, 1980) Global (IGB, Γαλλία, 1985) Modified BMWP (1979, M. Bρετανία) Belgium ΒΒΙ, 1983 Saprobic Index(Q-index, ΒΕΟL, Κ 135) (Holland,Germany, E. Europe) Lincoln (ASPT+BMWP) Iberian BMWP’ (1988, Ισπανία)

  14. Ευρύτερη περιοχή μελέτης Studied rivers Β Rivers Aliakmon, Axios , Almopeos, Aggitis and the creeks of Skouries and Olympiada (Chalkidiki)

  15. Ελληνικό Σύστημα Αξιολόγησης Ταξινομικές ομάδες Παρούσες Κοινές Άφθονες (0 - 1%) (1.01 - 10%) (>10%) α) β) Capniidae , Chloroperlidae , Siplonuridae , γ ) δ ) Aphelocheiridae, , Blephariceridae ε ) Phryganceidae, Molanidae, Odontoceridae, Bareidae, 10 10 10 Lepidosto matidae, Thremmatidae, Brachycentridae, Helicopsychlidae α ) Leuctridae, Perlodidae, Perlidae, 9 9.5 10 β ) γ ) Sericostomatidae, Goeridae, Neoephemeridae α ) Nemouridae, Taeniopterygidae, β ) Ephemeridae, Heptageniidae, Leptophle biidae, γ ) Leptoceridae, Polycentropodidae, Psychomyidae, Philopotamidae, Limnephilidae, Rhyacophilidae, 8 8.5 8.8 Glossosomatidae, Ecnomidae, δ ) Aeshnidae, Lestidae, Corduliidae, Libeliidae, ε ) Athericidae, Dixidae, στ ) Helodidae, Gyrinidae, Hydraenidae, ζ ) η ) θ ) Si alidae, Brachyura, Astacidae α ) β ) Potamanthidae, Calopterygidae, Cordulegasteridae 7 7.5 7.8 γ ) δ ) Stratiomyidae, Hydrobiidae α ) Platycnemididae, Gomphidae, β ) Tabanidae, Ceratopogonidae, Empididae, 6 6 6 γ ) δ ) Elminthid ae, Viviparidae, Neritidae, ε ) στ ) Unionidae, Corophidae α ) Caenidae, Oligoneuriidae, Polymitarcidae, Isonychiidae, β ) γ ) δ ) Hydropsychidae, Ancylidae, Gammaridae, ε ) Planariidae, Dendrocoelidae, Dugesiidae, 5 5 5 στ ) Dryopidae, Hel ophoridae, Hydrochidae, Clambidae α ) β ) Ephemerellidae, Baetidae, Hydroptilidae, γ ) Tipulidae, Dolichopodidae, Anthomyidae, Limoniidae, 4 3.8 3.5 δ ) Haliplidae, Curculionidae, Chrysomelidae, ε ) Hydracarina α ) β ) Coenagriidae, Chironomidae ( όχι τα κόκκινα ), γ ) Dytiscidae, Hydrophilidae, Hygrobiidae, δ ) Corixidae, Hebridae, Veliidae, Mesoveliidae, Hydrometridae, Gerridae, Nepidae, Pleidae, Naucoridae, Notonectidae, 3 2.5 2 Belostomatidae, ε ) Asellidae, Ostrac oda, στ ) Physidae, Bythiniidae, Bythinellidae, Acroloxidae, Malaniidae, Ellobiidae, ζ ) η ) Hirudinidae, Sphaeriidae θ ) Oligochaeta ( εκ . Tubificidae) HELLENIC BIOTIC INDEX α ) Chironomidae ( τα κόκκινα ), Rhagionidae, Culicidae, Muscidae, Thaumaleidae, Ephydridae , Ephemeridae, Heptageniidae, 2 1.5 1 Leptophlebiidae, β ) γ ) Lymnaeidae, Planorbidae, Erpobdellidae α ) β ) γ ) Tubificidae, Valvatidae, Syrphidae 1 0.8 0.5

  16. δείγματα που συλλέχθηκαν από πολλούς τύπους ενδιαιτημάτων samples collected from many types of habitat E λληνικό σύστημα Υ Μέσος Όρος Δείκτη Χ αξιολόγησης ανά ταξινομική Ομάδα 151+ 7 6.0+ 7 121 - 150 6 5.5 - 5.9 6 91 - 120 5 5.1 - 5.4 5 61 - 90 4 4.6 - 5.0 4 31 - 60 3 3.6 - 4.5 3 15 - 30 2 2.6 - 3.5 2 0 - 1 4 1 0 - 2.5 1 Δείγματα που συλλέχθηκαν από λίγους τύπους ενδιαιτημάτων Samples collected fron few types of habitat E λληνικό σύστημα Υ ΜΟΔΤ Χ αξιολόγησης ΕΣΑ 121+ 7 5.0+ 7 101 - 120 6 4.5 - 4.9 6 81 - 100 5 4.1 - 4.4 5 51 - 80 4 3.6 - 4.0 4 25 - 50 3 3.1 - 3.5 3 10 - 24 2 2.1 - 3.0 2 0 - 9 1 0 - 2.1 1 T ελική τιμή Σύντομη ερμηνεία E ρμηνεία 6+ A ++ Άριστη ποιότητα 5.5 A + Άριστη ποιότητα 5 A Άριστη ποιότητα 4.5 B K αλή ποιότητα 4 Γ K αλή ποιότητα 3.5 Δ M έτρια ποιότητα 3 E M έτρια ποιότητα Hellenic ASPT HELLENIC BMWP Final value Index Interpretation excellent good moderate poor 2.5 Z K ακή ποιότητα 2 H K ακή ποιότητα Very poor 1.5 Θ Πολύ κακή ποιότητα 1 I Πολύ κακή ποιότητα

  17. Number of taxa IBMWP score Hellenic BMWP

  18. Number of taxa Units of decrease in relation to the first grading Units of increase in relation to the first grading

  19. Προσθήκη νέων ταξινομικών ομάδων στο ΕΣΑ Added taxonomicv groups Number of taxa Scores Trichoptera Ephem. Diptera Hemiptera Gastropoda

  20. Biological monitoring: Animal community changes The use of changes in community structure to monitor pollution commonly involve benthic invertebrates and this group is considered the most appropriate biotic indicators of water quality in EU countries (Metcalfe 1989), including Greece (Anagnostopoulou et al ., 1994). The biotic indices are based on the tolerance of benthic macroinvertebrates or other organisms to low oxygen conditions and the effects of organic pollution on community structure. Nevertheless, as it has been mentioned the application of biotic indices combined with measurements of physical and chemical parameters provide more integrated results concerning water pollution.

  21. In the last decades, industrial, agricultural and urban development has caused an extended degradation of the natural environment both on a local and on a global scale. Pollution of water bodies is one of the major issues that have to be seriously taken under consideration since they are the main final receptors of all kinds of pollution. chemical methods Water quality assessment based only on has been proved less accurate than the combination of biotic and abiotic approaches, since chemical measurements represent the instantaneous situation of the river body, at the time of sampling. On the other hand, organisms integrate environmental conditions over long periods of time and thus they are more informative concerning the water quality before and during sampling. Concerning biotic indices the , their performance in slow flowing water courses displays some problems, since sensitive to lack of oxygen taxa naturally occur only in fast flowing courses rather than in slow ones, despite the presence or absence of pollution sources.

  22. Benthic macroinvertebrates as biotic indicators Benthic macroinvertebrates are the most appropriate biotic indicators for the following reasons: (1) These organisms are relatively sedentary and are therefore representative of local conditions. (2) Macroinvertebrate communities are very heterogeneous, consisting of representatives of several phyla. The probability that at least some of these organisms will react to a particular change in environmetal condtitions, is therefore high (Hellawell, 1977; De Pauw & Vanhooren, 1983; Metcalfe, 1989; Mason 1991). Other groups of organisms (fish, phytoplakton, etc) possess some, but not all, of these important attributes. (3) Macroinvertebrates are differentially sensitive to pollutants of various types, and react to them quickly; also, their communities are capable of a gradient response to a broad spectrum of kinds and degrees of stress. (4) Their life spans are long enough to provide a record of environmental quality. (5) Macroinvertebrates are ubiquitous, abundant and relatively easy to collect. Furthermore, their indentificaton and enumeration is not as tedious and difficult as that of microorganisms and plankton.

  23. Modelling A wide range of techniques, including standard survey procedures and modelling software for analysis of the results, are now available for the pollution manager, and these are proving very robust for a wide range of purposes.Many policy decisions are nationally based, and country-wide monitoring networks are essential to inform future decisions. Finally, of course, international cooperation on monitoring is essential, as much pollution crosses national frontiers, e.g. monitoring acid rain across Europe, the transfer of pollutants in marine waters or the movement of radionuclides from the Chernobyl accident. International cooperation in the European Union was enhanced by the recent formation of the European Environment Agency (EAA) based in Copenhagen. Currently, the work of the EAA has focused on establishing "topic centres" in each member state to coordinate the supply of environmental monitoring data to produce a clearer picture of the state of the environment within the EU and how this might be used to aid production of future EU legislation.

  24. predictive model The use of a , which take into consideration both the biotic and physicochemical approach for the detection of water pollution and monitoring of the water quality, is probably the best tool for the management and improvement of water resources, and especially of rivers. A predictive model, applied on data collected with a standard sampling method, can also produce a classification scheme according to the degree of pollution that rivers receive. This may allow inter and intra site comparisons, which could lead to an effective conservation strategy. For the establishment of these models, one approach is to identify the "best achievable community" which can occur under a particular set of physical, chemical, geological and geographical conditions. So the surveyed community can then be compared with the above one and hence the degree of change objectively assessed.

  25. During the 70's, multivariate analytical techniques have been introduced as a new tool for the assessment of water quality. Between 1978 and 1988, in the UK a biological classification of unpolluted freshwater sites (483 sites on 80 rivers, 700 have been assessed up today) was developed based on macroinvertebrate fauna (see 5.1.3.). It was attempted to assess whether the type of macroinvertebrate community at a given site maybe predicted using physicochemical parameters. This proved to be feasible and led to the formation of RIVPACS (River InVertebrate Prediction And Classification System). Two main techinques are used for RIVPACS: Twinspan and Decorana.

  26. Twinspan (two way indicator species analysis) classifies organisms at each site into an hierarchy on the basis of their taxonomic composition. At the same time, species are classified on the basis of their occurrence in site groups (sites are classified into 10-25 groups). It also identifies indicator species that show the greatest difference between site-groups in the frequency of occurrence (Figure 1). A common problem in community ecology and ecotoxicology is to discover how a multitude of species respond to external factors such as environmental variables, pollutants and management regimes. For this, data are collected (species and external variables) at a number of points in space and time. Decorana (detrended correspondence analysis) is an ordination technique which arranges sites into a subjective order, those sites with similar biota being placed close together. It also relates community type to physicochemical parameters. In a survey which took place over the whole of the United Kingdom in the 1970's, Decorana revealed 11 key variables which produced 58% chance of correct first prediction of one of 10-25group-sites. These parameters were: 1) distance from the source (1-10), 2) discharge (1-10), 3) latitude, 4) longitude, 5) altitude, 6) slope, 7) width, 8) depth, 9) substrate (% 5 categories), 10) alkalinity 11) chloride.

  27. From the above information the following predictions can be made about a site: 1) presence/absence of families, 2) presence/absence of species, 3) BMWP score (Biological Monitoring Working Party), 4) ASPT score (Average Score Per Taxon). If a site has a probability of less than 5%, one does not proceed. For site classification, three seasons data per year (3 samples per site) are requested, while for fauna prediction one season's data is adequate. From the original survey, the ASPT was predicted in the U.K. for a site directly using a suite of 5 variables in a multiple regression equation, which explains 68% of the total variation (there have been used 118 families and 578 taxa at the species level). The equation of ASPT prediction was the following: ASPT=7.331-0.00269A-0.876C-0.133Too-0.05395S-0.051D (where A: alkalinity, C: log10 chloride, Too: log10 total oxidized oxygen, S: mean substratum, D: log10 distance from the source).

  28. Extension of Twinspan and Decorana Statistical analyses available so far have either assumed linear relationships (but relationships may be unimodal, like a bell shaped Gaussian curve) or were restricted to regression analyses of the response of each species seperately. CANOCO has been mainly developed to overcome the above problem: The CANOCO program is an extension of Decorana. It escapes the assumption of linearity and is able to detect unimodal relationships between species (Figure 2) or/and sites (Figure 3) and external variables. It is particularly good for a forward selection of environmental variables in order to determine which variables best explain the species data. It selects a linear combination of environmental variables, while it maximizes the dispersion of the scores of the species and allows us to see whether species are related to environmental variables (This uses the Monte Carlo permutation test). CANOCO can analyse 1,000 samples, 700 species, 75 environmental variables and 100 covariables (total data size < 80,000).

  29. The other problem was the classification of communities at each site into an hierarchical way on the basis of their taxonomic composition. Species are classified simultaneously on the basis of their occurrence in site groups. FUZZY overcame this problem. FUZZY is an extension of Twinspan. Species are classified as well as samples. Both ordination and classification are done. In the results, there is no clearcut transition from one class to another and many intermediate situations may occur. It does not assume the existence of discrete benthic populations between the various streches of a river system, but identifies the continuum and gradual change in their faunal composition. The maximum Fuzzy membership values are usually low (0.5-0.7) and they rarely exceed the value of 0.9, which agrees with the fact that communities are formed along gradients, without sharp boundaries, except in cases of pulse or chronic disturbances (Figure 3). The number of clusters (groups) are decided according to a parameter which is an integer number between 2-30: the largest the partition coefficient the best except if the number is very high. If convergence fails then we start from the beginning with a different number of clusters.

  30. Biodiversity in the Water programme The water-programme is centered around biodiversity. That is first of all because biodiversity is an adequate tool to characterise the environment. Biodiversity means in general all aspects of variety in the living world, but more specifically it can be expressed as: 1) the collection of species present in an area, 2) the amount of genetic variation or 3) the number of community types. In this context we are talking about biodiversity as the assembly of species. Both the collection of species that are present and those that are absent, will say something about the water itself and the water habitat. Comparisons of biodiversity between localities, and variation over time, will give information about the environmental status and indicate eventual qualitative changes. Other reasons for using the biodiversity in this porgramme are the educational aspects. Many species can be identified with small resources without expensive apparatus. To some extent it can be done by the students and their teachers. In addition are environmental problems normally complex problems.

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  32. De Pauw N. & Vanhooren G. (1983). Method for biologicalquality assessment of water courses in Belgium. Hydrobiologia, 100, 153-168. European Union Commission. (1978). Directive on the quality of fresh water for the protection and improvement of fish life. Official Journal of the European Communities , No 222/1/ 14.8.78. European Union Commission. (1980). Directive on the quality of drinking water. Official Journal of the European Communities , No 80/778/15.07.80 European Union Commission (1997). Proposal for a Council Directive establishing a framework for Community action in the field of water policy . Official Journal of the European Communities , No C 184/20, 17.6.97. Extence C.A., Bates A.J., Forbes W.J. and Barham P.J. (1987). Biologically based water quality management. Environmental Pollution 45, 221-236. Farmer, A. (1997). Managing environmental pollution. Routledge Environmental Management Series. Ford J., Yfantis G., Artemiadou V., Lazaridou-Dimitriadou M., White K. N. (1998). Ecological evaluation of water quality in river Mavrolakkas (Olympiada, Halkidiki), from May to August 1997. Proceedings of the International Conference "Protection and Restoration of the Environment IV" , 1-4 July, Sani Halkidiki, 144-152. Goldman G.R. & Horne A.J. (1983). Limnology. McGraw - Hill Book Company. Harper, D.M. and Ferguson, A.J.D. (eds) (1995). The ecological basis for river management. John Wiley & Sons. Haslam, S.M. (1995). River Pollution: An Ecological Perspective. John Wiley & Sons. Hellawell J.M. (1986). Biological indicators of freshwater pollution and environmental management . Elsevier Applied Science Publishers, London. Hill M.O. (1979). DECORANA - A Fortran program for detrended correspondence alalysis and reciprocal averaging. Ecology and Systematics, Cornell University, Ithaca, New York. Hynes H.B.N. (1970). The Ecology of Running Waters. Liverpool University Press. Jeffries M. & Mills D. (1990). Freshwater Ecology, Principles and Applications. Belhaven Press, London and New York. Karr J.R. & Chu E.N. (1999). Restoring life in running waters. Better Biological Monitoring. Island Press. U.S.A. Krenkel P.A. & Novotny V. (1980). Water quality management. Academic Press Inc. Langrick J.M., Artemiadou V., Yfantis G., Lazaridou-Dimitriadou M., White K. N. (1998). An integrated water quality assessmentof the river Axios, Northern Greece. Proceedings of the International Conference "Protection and Restoration of the Environment IV" , 1-4 July, Sani Halkidiki, 135-143. Lazaridou-Dimitriadou M., Artemiadou V., Yfantis G., Mourelatos S. and Mylopoulos J. (1998). Contribution to the ecological quality of running waters in the river Aliakmon (Macedonia, Hellas). A multivariate approach. Submitted. Mason C.F. (1991). Biology of freshwater pollution. Longman Group U.K. Ltd. Metcalfe L.J. (1989). Biological water quality assessment of running waters based on macroinvertebrate communities : History and present status in Europe. Environmental Pollution 60, 101-139. Metcalfe L.J. & Smith M. (1994). Invertebrates ecology and survey methods, in The Rivers Handbook, Hydrological and ecological principles. Vol. 2, edited by Calow P. & Petts G.E., Blackwell Scientific Publications. Ter Braak C.J.F. (1988). CANOCO - a FORTRAN program for canonical community ordination (version 2.1).Tecnical report: LWA-88-02. Wright J.F., Hiley P.D., Cameron A.C., Wigham M.E. and Berrie A.D. (1983). A quantitative study of the macroinvertebrate fauna of five biotopes in the river Lambourn, Berkshire, England. Arch. Hydrobiol. 96, 271-292.

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