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Annls

Limnol.

28 (2) 1992 : 147-156

Comparison of several biological indices based on river macroinvertebrate benthic community for assessment of running water quality E. Rico* A . Rallo" M . A . Sevillano M X . Arretxe

1

1

Keywords Nine

: Biological indices, water quality, macroinvertebrates,

biological indices based

on the macroinvertebrate

rivers.

community

inhabiting rivers have been

calculated

t o f i n d o u t w h i c h o f t h e m is m o r e a p p r o p r i a t e t o e v a l u a t e t h e q u a l i t a t i v e s t a t u s o f t h e r u n n i n g w a t e r f o r p u b l i c mental authorities. T h e B M W P ' score (Alba-Tercedor & Sânchez-Ortega rate a n d

precise, a n d easy to calculate. S o m e problems

derived

from

sampling

C o m p a r a i s o n d e p l u s i e u r s i n d i c e s b i o l o g i q u e s b a s é s sur la c o m m u n a u t é é v a l u e r la q u a l i t é d e s e a u x

in

order

environ-

1 9 8 8 ) h a s b e e n c h o s e n b e c a u s e it is b o t h strategies are

macroinvertébrée benthique des rivières

macroinvertébrés,

fleuves.

N e u f i n d i c e s b i o l o g i q u e s d ' é v a l u a t i o n d e la q u a l i t é d e s e a u x f l u v i a l e s b a s é s s u r l ' é t u d e d e s m a c r o i n v e r t é b r é s q u e s s o n t c o m p a r é s . P a r sa simplicité et sa p r é c i s i o n , l'indice B M W P '

(Alba-Tercedor & Sânchez-Ortega

benthi-

1988)

ê t r e l ' i n d i c e le p l u s p r a t i q u e p o u r ê t r e e m p l o y é p a r les o r g a n i s m e s p u b l i c s d e g e s t i o n d e s e a u x . Q u e l q u e s p r o b l è m e s v a l e u r s o b t e n u e s p a r les i n d i c e s à c a u s e d e s s t r a t é g i e s d ' é c h a n t i l l o n n a g e

1. Introduction The saprobien-system (Kolkwitz & Marsson 1902, 1908, 1909) was the first proposed way t o evaluate the quality and status of fresh waters by biological m e t h o d s . It has been revised and u p d a t e d several times since, a n d a d a p t e d to different taxocenosis (Liebmann 1951, 1962 ; Sladecek 1961, 1967, 1973 ; Fjerdingstad 1964) a n d specially used in central and eastern E u r o p e . Also, there are other methods based on t h e study of the faunistic c o m m u n i t y , such as the assessment of taxonomic richness and diversity or trophic structure. M o s t popular in West Europe are t h e Biotic indices that rely on the presence of diverse taxons chosen for their specific sensitivity t o w a r d s pollu-

1. U n i v e r s i d a d d e l P a i s V a s c o . F a c u l t a d d e C i e n c i a s . D e p a r t a m e n t o de Biologia A n i m a l y Genética, Zoologia. A p d o . 644. E-48080 Bilbao,

Espafia.

pour

courantes

M o t s clés : Indices b i o t i q u e s , qualité d e l'eau,

tifs a u x

accu-

discussed.

suivies sont

paraît rela-

commentés.

tion. Several indices of this kind have been p r o p o sed, each of them widely applied t o most rivers in any specific geographical area. So, in Great Britain the TBI, the CBS and the EBI indices (see a h e a d for definition) are the most commonly used, whereas in France the VT and IBG are generally preferred. Actually it seems very interesting to compare their different results when applied t o the same biological entity (Balloch et al. 1976 ; Ghetti & Bonazzi 1977 ; T o l k a m p 1985 ; Mesanza et al. 1988), specially in order to choose one o f t h e m and adjust it t o a particular fluvial system. The major part of the fluvial system of the Basq u e Country (northern Spain) is seriously polluted and spoiled. In order to evaluate this situation, several studies — supported by the Administration —, have been carried out t o get a general map of river water quality a n d to propose a management strategy. A preliminary problem is choosing a suitable biotic index, both accurate a n d workable. A t h e o retical m e t h o d of comparison between indices has

Article available at http://www.limnology-journal.org or http://dx.doi.org/10.1051/limn/1992013

148

E. RICO, A. R A L L O , M.A. SEVILLANO, M X .

been designed a n d tested with data from basque rivers, b o t h in analytical and holistic ways.

2. Methods T h e biotic indices calculated and c o m p a r e d are : TBI : T r e n t Biotic Index (Woodiwiss 1964) EBI : Extended Biotic Index (Woodiwiss 1978) V T : Indice Biotique (Verneaux & T u f f e r y 1967) IBG : Indice Biologique de Qualité Générale (Verneaux et al. 1982) B M W P ' : Biological Monitoring W o r k i n g Party, a d a p t e d t o Iberian Peninsula (Alba-Tercedor & Sanchez-Ortega 1988) A S P T : Average Score per T a x o n ( A r m i t a g e et al. 1988) derived from B M W P ' C B S : C h a n d l e r ' s Biotic Score (Chandler 1970) A C B S : Average Chandler's Biotic Score (Balloch et al. 1976) RVI : River of V a u d Index (Lang et al. 1989). T h e c o m p a r i s o n between t h e m is m a d e by theoretical considerations (see results), and by Pearson product-moment correlation analysis (Sokal & Rohlf 1969). T h e scores are categorised by hierarchic clustering analysis, evaluating square euclidean distances a n d g r o u p i n g the results by the U P G M A algor i t h m (Sneath & Sokal 1973). T h e d a t a were obtained from 65 fluvial stations in A l a v a a n d G u i p û z c o a (Basque C o u n t r y , Spain (Fig. 1), w h o s e rivers are short, shallow a n d turbulent a n d with a fluctuating streamflow u p o n a pred o m i n a n t l y calcareous lithology. Samples were t a k e n by a « kicker » handnet (500 0 ) in lotie system, looking for the biggest spatial heterogeneity ; over whole, a m i n i m u m of 4500 c m area were sampled each time. Faunistic analysis included A n n e l i d a , Mollusca, Crustacea, E p h e m e r o p t e r a , P l e c o p t e r a , O d o n a t a , Heteroptera, Coleoptera, M e g a l o p t e r a , T r i c h o p t e r a a n d Diptera. 2

3. Results and discussion W h e n choosing a biological method t o evaluate the q u a l i t y of r u n n i n g water, two considerations m u s t be b o r n e in mind (Verneaux 1982) : firstly, the accuracy a n d precision, that is t o say, t h e adjustment of t h e o b t a i n e d results t o the real fluvial condition t h a t is being studied, and secondly, the practicality a n d simplicity in the use a n d application of the method.

ARRETXE

(2)

The exigencies of these t w o methodological aspects are, in some way, contradictory : accuracy requires a carefully, time-consuming and detailed identification up to the species level, because species is the unquestionable ecological unity (unambiguously linked to the ecological niche concept on which bioindication takes r o o t ) . It is evident t h a t this exigence is neither simple nor practical, a n d practicality and simplicity are required because of the large n u m b e r of samples which have t o be p r o cessed as fast as possible and with a m i n i m u m of taxonomic analysis dedication. So we have to choose the method that, being simple and practical enough, shows the highest correlation with the most accurate index which is that which uses the species level as the taxonomic unity. The biotic indices applied in our work could be classified in three groups, according t o the t a x o n o mical level required. The simplest ones, IBG, B M W P ' and A S P T , only require the taxonomic family level to be worked out. More exigent are T B I , EBI, VT and RVI, that need identification u p to families and genera, and the most difficult are those that require identification at the genera and species level, as CBS and its derivated ACBS d o , so that only trained taxonomists can do the work. But when looking for precision and accuracy the CBS index must be preferred, as not only the theoretical considerations we have already m a d e but also practical results have shown (Balloch et al. 1976, W a s hington 1984, Domezain et al. 1987, Mesanza et al. 1988). All the above mentioned indices have been applied to the d a t a from the rivers of Alava and Guipûzcoa : the results are shown in Table II, that also include their taxons' number and the values of Shannon-Weaver faunistic diversity index in each sample. Comparisons have been established between all these values which have been referred to CBS index (Fig. 2) that has been chosen because of its aforementioned accuracy in order to evaluate the behaviour of the other more practical indices. T h e interrelation between the indices is also studied by Pearson linear correlation analysis (Table 1). CBS index has been shown t o be very sensitive t o small variations in water quality. T h e range of the obtained values is wider for each value of the other indices, specially the highest T B I , EBI and VT values.

COMPARISON O F SEVERAL BIOLOGICAL

Silas

Oi D2 D3 04 D5 DAI D01 DEE Ul U2 U3 U4 UU1 Orl 02 03 Or* Ort.1 OrU Ort-3 Ort.4 0>A1 OA2 Of A3 Lift Ur2 Ur3 Ur4 Oil 0>2 OiAi 6.5 B.2

Rivar

Altitude (mt

OaOa 4SQ Oaoa 280 O u 270 DM» 120 Oaba 20 Aramaiona 340 Onare 275 Onaia 210 530 Urol* Urola 420 Droit 210 20 Uneairilla 2*0 Ona 620 Oria 100 O.» 30 Ona 15 Lai la ran 540 Lain ran 4*0 Lwiaran 240 Laiiaran 70 Afuai 2&0 Araies t40 Araxu 10O Urumaa 550 Urumaa 140 Urum«a 40 Urumaa 5 Oyarmn 100 Oyirain 40 AiuiDar 70 60 B-îasca 5

Distance from sourca (Km) 3-5

to

20. S 30.5 50.5 3 1.5 E t.5 65 20.5 46.5 2.5 3 26 41 57 5.5 11.5 26.5 35 3 13 19 25 14.5 29.5 4V5 S 11 5 42 5 55 5

Locality

Salinas da Lena Eskonaua San Prudenoo Metcoiaida Puenta SasoU Otabirriaia ZutxKaga Mirandaoia Ailzpunjtxo AitamaiaDal Aratz Mat* vanta Zsgama Legorrata (rurj.Anoaw Zub-ata LARTZA Laitza Laiia'an Andoain Betaki Uiarua Tu/ama LaitularnH Gaiuaia UgaUotxo Ergo&a Arionjiaça UgaMttao Kamka Vanta Yand Endanaua

INDICES

S-tas

Rivar

BTI Pt 0ML Om2 Om3 OmHl Byt By! By3 By4 AYS Z1 22 23 Z* Z5 25 Z7 ZU1 ZU2 ZB1 ZZt ZAl ZA2 ZA3 Int In2 Egl EGA Eg3 EgSi EgB2

Tximistra Puffin Omeàno Omadlo Omecrlk) Humeciilo Bayas Baya» Bayai Bayas Baya* Zadcxrj Zadorra Zadona Zadorra Zadorra Zadorra Zadorra UfiucMa Ufhaola Zu&izabaU Barnjndia Ayuda Ayuda Ayuda Inglares ingiarw EA» ES> Egt Barron

JJtnuda (

Locality *oorc« (KmJ

•00 750 620 520 490 570 700 590 380 520 475 640 580 560 520 500 480 450 650 560 580 560 650 540 470 840 505 708 660 550 820 600

5 75 1 28 38 9 4. S 16.5 235 38.5 535 3.5 5-5 15 30 52 64 77 0.2 6 3.5 15 3 20.5 36 25 235 2.2 13.8 27.8 1.5 15.5

F i g . 1. L o c a l i s a t i o n e t c a r a c t é r i s t i q u e s d e s p o i n t s d ' é c h a n t i l l o n n a g e . F i g . 2. L o c a t i o n a n d characteristics o f s a m p l i n g sites i n t h e s t u d y a r e a .

Erxalar Rifcara KO TO Vanta BUnca BargùarWa Osma SA m'a Lukiano KILATJIANO Subijana-Pjbaï MUNAIN Satvatierra Elura Arroiaba ViHodas Puacla d« Arganzon Area Urtwla Ctxancl'O UtMaa Ozaeta Sasaia Vanta Armenia Escartana Pipaôn COQ Lagiân ArigcaBna Sta C/uz di Camoaio Atacata AntoAana

E. R I C O , A. R A L L O , M . A . S E V I L L A N O , M.L.

Indices 10 -j •i °„1

T



i

T S ! y CBS 1. •

• ...

.

m

•J , 1 ° "I

?

coroiradosi

ARRETXE

-.

" •

-

* p -

:r

.

0

4

3

12

io

20 «

Indices

convaradcsî

24 100)

E S ! y CBS

F i g . 2 . R e p r é s e n t a t i o n des v a l e u r s des différenis indices b i o l o g i q u e s en fonction des celles d u C B S . Fig. 2. R e l a t i o n s h i p b e t w e e n t h e C B S and t h e o t h e r biological indices.

COMPARISON OF SEVERAL BIOLOGICAL

INDICES

J j

Indicss

Indices 180

T

B M

c o ! ! î p î r a d c s ! !B'l

~s CBS

CQII>j»arados! I B I i J ? -.f

CP?

-

150

-

120

-

90

-

60

-

30

-

• %

IL

Indices



V

a

csmparaiosiASPT

-s CBS

O

s

J J J J

/]

1

-

"

-

m m *

-m



-

V

i i J

J

A J 0

4

8

12

15

20 (X

24 00)

Fig. 2. R e p r é s e n t a t i o n des v a l e u r s des d i f f é r e n t s indices b i o l o g i q u e s en f o n c t i o n des celles d u Fig. 2. Relationship between t h e C B S a n d the other biological indices.

CBS.

E. R I C O , A. R A L L O , M.A. SEVILLANO, M.L.

"•ii-res ccrffl?=rïios:

ARRETXE

9CBS v s CBS

24 (X 1005

Indices

comparâmes!

FÎVflUD v s CBS

F i g . 2 . R e p r é s e n t a t i o n d e s v a l e u r s d e s d i f f é r e n t s indices b i o l o g i q u e s e n f o n c t i o n des celles d u C B S . Fig. 2. R e l a t i o n s h i p b e t w e e n the C B S a n d the o t h e r biological indices.

Tableau

1. V a l e u r s d e s coefficients d e c o r r é l a t i o n linéaire e n t r e les d i f f é r e n t s i n d i c e s b i o l o g i q u e s (n = Table

1. L i n e a r c o r r e l a t i o n v a l u e s b e t w e e n t h e b i o l o g i c a l i n d i c e s (n

TBI TBI EBI VT IBG BMWP ' ASPT CBS ACBS RVI

EBI

VT

IBG

BMWP '

.000 9335 8665 9404 8162 8606 8326

1.000 .9138 .9317 . 8523 .8560 .8956

1.000 .8897 .8959 .7880 .9405

ASPT

CBS

=

127).

ACBS

RVI

1.000 . . . . . . . .

9 9 9 8 9

865 668 378 608 240 8174 8751 8317

1 . . . . . . .

.000 9542 9453 8984 9174 8475 8574 8744

1 . . . . . .

1.000 .8105 .8779 .8413

1.000 .8510 .8743

1.000 .7568

1.000

1

(7)

COMPARISON OF SEVERAL BIOLOGICAL

These three indices h a v e a very similar design, and consequently show a high degree of linear correla­ tion between them (r > 0.95, g.f. = 125 ; p ^ 0.001 - T a b l e 1 -) and t h e lowest with CBS. T h e great variability in the highest values reached by the three indices makes the relation to C B S to fit m o r e t o a logarithmic model than a linear o n e . So, in our case, they work well in polluted waters but fail to eva­ luate adequately t h e quality of good water. It is important t o notice that VT is, so far, the most com­ monly used index in previous studies in Spanish rivers, so that its calculation would be interesting for a short period in order to compare with histori­ cal situations. T h e highest linear correlation with CBS is reached by B M W P ' (r = 0.8959), RVI (r = 0.8743) and IBG (r = 0.8523) indices (in all cases, with g.f. = 125 and p ^ 0.001, T a b l e 1). The RVI is a very recently proposed index ( L a n g 1989) t o evaluate the quality of rivers in the V a u d c a n t o n , Switzerland, and is based u p o n the total n u m b e r of taxons in a sample and the number of t h e m which are intolerant to pol­ lution. The range of variation of CBS against RVI is very wide in all cases, even those corresponding to waters of the lowest quality. S o , RVI is not able to discern, in our country, small variations in water quality.

INDICES

153

requires a taxonomic analysis only d o w n t o the family level. The other index, A S P T , is a modifica­ tion of the B M W P (in the same way that A C B S is of the CBS) to correct the values obtained from a very particular fluvial conditions : when the faunis­ tic scarcity is not an effect of pollution b u t of t h e small biogenic capacity of the ecosystem (as it actually happens near the river sources). S o , these indices are contempled only as auxiliaris t o be applied only when such conditions are p r e s e n t . T h e B M W P ' and the IBG have already been applied to a few b a s q u e rivers (Lea, Oria a n d Bidasoa) by Rodriguez & Wright (1988), who o b t a i n e d values remarkably higher than ours (in O r i a a n d Bidasoa rivers). As the biological condition of both rivers have not change, this effect can be a t t r i b u t e d to the m e a n of sampling, as these authors t o o k fauna not only from lotie but from lentic a n d m a r ­ ginal zones, also. It is obviously known t h a t lentic and marginal sampling raises the number of t a x o n s , as also has been proved by Rodriguez & Wright (1991) ; Mesanza et al. (1988) have got results simi­ lar to ours in the Lea river.

IBG (Verneaux et al. 1982) seems to be more sen­ sible a n d accurate t h a n its antecesor V T , a n d by its application a really g o o d , extensive and complete characterization of the fluvial section is achieved. Nevertheless, its estimation requires a well-trained and skilled staff a n d d e m a n d s a very rigourous and complex sampling protocol which is difficult to fol­ low when a large fluvial net must b e studied against time. T h e sampling m e t h o d in the present work did not fit that protocol, so the values of the index obtai­ ned must be accepted only as approximations. Also, the laboriousness a n d t h o r o u g h n e s s of the method is far from being simple, so this index is not suita­ ble for our p u r p o s e .

T h e normalised d a t a in Table 2 (indices, n u m b e r of taxons a n d diversity values for each sample) have been analysed by clustering methods. W e have found six well defined groups of sampling stations that correspond to six correlative ranges of B M W P ' values (Table 3), substantially similar to those deter­ mined by Alba-Tercedor & Sanchez-Ortega (1988) according t o Ghetti et al. (1983). To classify the results of Rodriguez & Wright (1988) in these cate­ gories would give way to an overvaluation of the real quality of the water. This is the outcome of t h e methodological discrepancies again : Alba-Tercedor & Sânchez-Ortega (1988) included lotie a n d lentic zones in their sampling strategy ant the concordance with our results m a y be a consequence of t h e n a t u r e of their faunistic d a t a , from Sierra Nevada ( A n d a lucfa) rivers, poorer than ours (we have personally discussed all these items with Dr. Alba-Tercedor).

T h e B M W P ' is an index derived from the british B M W P (National W a t e r Council 1981), a d a p t e d to the faunistic peculiarities of the iberian peninsula by Alba-Tercedor & Sânchez-Ortega (1988). It is able t o detect small variations in water-quality (see Fig. 2), and shows a very high linear correlation with CBS (r = 0.8959 ; d.f. = 125 ; p ^ 0.001). It is o n e of the simplest indices t o calculate, since it

O t h e r iberian rivers looked more like Basque t h a n Andalucian ones : the B M W P ' range values are very similar t o ours in the Tietar river (western Spain) (Garcia-Avilés, pers. c o m m . ) , in the J u c a r basin (eastern Spain) a n d in Gredos Mountains (central Spain) fluvial systems (Dr Gonzalez, in litt.). So we wonder if a unique way of application of the B M W P ' for all the iberian peninsula is a l l o w e d .

154

E. RICO, A. R A L L O , M.A. SEVILLANO, M.L.

(8)

ARRETXE

T a b l e a u 2 . V a l e u r s d e s i n d i c e s d e q u a l i t é d e s e a u x , d e la d i v e r s i t é de S h a n n o n - W e a v e r ( H ) et n o m b r e d e t a x o n s ( N ) . S p : P r i n t e m p s , Au : Automne. T a b l e . 2. Values of water quality indices, diversity index o f S h a n n o n - W e a v e r (H) a n d n u m b e r of taxa (N). Sp : Spring, Au : A u t u m n .

TBI Sp Au Dl D2 D3 04 D5 DAI DOl D02 Ul 02 U3 U4 UU1 Orl 0r2 Or3 Or4 OrLl OrL2 0rL3 OrL4 OrAl OrA2 0rA3 Url Ur2 Ur3 Ur4 Oil Oi2 OiAl Bil Bi2 BiTl PI Oral Om2 Om3 OmHl Byl By2 By3 By4 By5 Zl

22 Z3 Z4 Z5 Z6 Z7 ZU1 ZU2 ZB1 ZZ1 ZA1 ZA2 ZA3 Inl In2 Egl Eg2 Eg3 EgBl EgB2

10 2 2

2 3 9 10 6 10 9 5 9 10 10

e 4 3 10 9 10 9 9 9 9 10 9 9 3 9 7 B 10 9 10 10 10 9 9 9 10 9 10 S

9 2 2 3 2 9 8 3 10 8 3 7 9 10 8 3 4 10 9 9 10 7 8 9 10 10 9 3 10 2 9 10 8 10 10 9 10 8 9 10 9 10

e9

7

0' 2

0 1 9 3 4 6 8 9 10 9 10 8 8 3 8

e

4 5

e9 8 6 9 10 9 9 S

7 10

-

6 5 1 0 10 9 9

e9

EBI Sp Au 10 2 2 2 3 9 10 6 11 9 5 9 12 10 8 4 3 12 10 10 9 9 9 10 11 9 10 3 9 7 8 10 10 11 10 10 9 9 11 12 10 11 8 8 9 0 1 9 3 4

9 2 2 3 2

i 8 3 10 8 3 7 10 11 S 3 4 11 9 9 10 7 8 9 10 10 9 3 10 2 9 11 B 10 10 9 10 B 9 11 9 10

7

}

3 8 2 5 5 9 9 10 10 10 8

6 8 9 10 9 10 8 8 3 4 8 9 10 . 8 6 11 S 10 1 2 9 9

e

VT Sp Au 10 9 2 2 2 2 2 4 3 2 9 10 10 9 5 4 10 10 9 9 4 5 9 6 1 0 10 1 0 10 7 7 2 5 2 5 1 0 10 3 10 10 9 9 10 9 8 9 9 9 9 1 0 10 9 10 9 10 5 4 9 10 6 4 7 9 1 0 10 9 8 1 0 10 1 0 10 1 0 10 9 10 9 9 9 9 10 1 0 9 9 10 1 0 7 7 9 0 0 2 2 8 11 4 2 5 4 8 6 9 10 8 11 6 10 9 11 1 1 14 9 12 9 12 E 2 7 9 10 6 5 9 5 10 10 9 9

a

IBG Sp Au 14 13 2 2 2 2 2 3 2 2 1 4 11 1 4 11 5 3 16 14 1 1 10 3 3 11 5 16 15 16 15 10 6 2 3 1 5 17 15 1 1 13 13 12 13 14 12 10 13 11 11 9 16 13 14 14 15 14 2 3 15 14 9 3 14 13 12 12 13 1 1 1 5 12 16 14 1 5 12 12 12 11 10 14 14 16 15 14 12 14 13 8 11 9 13 0 0 3 2 8 8 4 3 6 9 7 9 9 12 B 13 7 9 9 14 10 15 9 13 9 11 3 9 7 11 12 8 9 13 4 14 16 14 14

BMWP' Sp Au 101 3 1 3 7

93 89 10 127 85 5

51 3 3 9 3 82 88 6 102 61 16 25 153 131 31 12 21 141 92 94 92 40 83 93 85 112 98 9 84 12 75 119 69 91 92 85 106 60 109 117 120 100

53 143 133 40 6 3 149 83 69 108 88 85 81 132 76 117 14 126 38 86 92 44 119 10S 104 107 69 146 163 108 125 48 75 32 107 0 0 S 3 62 93 12 9 30 29 39 29 77 93 80 88 22 81 76 98 93 99 89 83 61 49 68 11 39 52 70 40 50 121 32 82 1 3 8 93 81

ASPT Sp Au 7 .21 1 .. 5 0 1 .00 1 .50 2 ,. 3 3 6. . 2 0 5 ., 9 3 3 ., 3 3 6, . 6 8 6. , 0 7 2,,50 4 ..07 5 ,.96 6. . 3 3 4 ..44 2 ..00 1 .,50 6 . 48 4 . 88 4 . 93 5 .. 6 8 5 ., 5 0 5 ., 0 0 5 ..06 6..60 5 ,,43 6..16 2 ..80 6,.30 S, . 4 3 6..14 5 ;. 4 1 5 .. 5 0 6. . 2 6 6. . 5 6 6.,50 5 .. 6 3 5 .31 5 .. 4 1 7. . 0 8 5 .. 6 8 5 .95 5 .. 3 3 5 .35 5 . . 94 0 .00 2 .00 4 .43 3 .00 3 .00 3 .54 6 .64 5 .71 4 .40 5 .06 6 .60 5 .56 4 .08 4 .00 4 .87 5 .00 3 .63 5 .04 5 .85 5 .47

.64 1 .50 1 .50 2 -2S 1 .50 S .66 S .28 2 .00 6 .37 5 .54 3 .20 3 .57 6 .65 i .55 3 .44 2 .40 2 .62 6 .71 5 .75 E .27 5 .75 5 .00 5 .93 5 .17 £ .07 7 .00 6 .12 2 .25 6 .00 3 .00 S .77 5 .95 4 .93 5 .69 5 .75 5 .67 5 .89 5 .45 5 .45 6 .50 6 .00 5 .88 4

5 .00 0 .00 3 .00 5 .17 2 .25 3 .22 3 .62 6 .42 5 .87 6 .23 5.44 6 .20 5.53 5 .08 2 .75 4 .33

3 .85 3 .55 6 .27 5 .78

Sp 946 54 19 38 32 1019 1327 119 996 2070 71 532 1935 1727 543 46 34 1704 1171 1245 1257 1132 1146 867 1414 787 1259 59 1240 403 659 1864 504 1348 1290 740 1300 889 1301 1392 1133 1234 826 650 725 0 73 670 62 201 489 1124 860 368 1361 1896 1407 979 736 852 570 361 1659 1604 1591

CBS Au 529 30 31 99 26 1016 847 43 1546 547 36 319 2390 1740 316 67 103 1560 1010 632 972 302 927 868 1151 1193 956 84 797 64 1007 1425 604 1021 1190 827 1102 277 873 1510 1262 1218

432

0 7 919 62 136 367 848 1131 844 1293 1351 1010 611 115 700

423 223 1820 1184

ACB£ Au Sp 67 . 7 4 18 . 0 0 9 .50 19 . 0 0 10 . 6 0 67 . 9 0 69 . B4 29 . 7 5 58 . 5 8 121 . 7 6 23 . 6 0 38 . 0 0 62 , 4 1 70 . 0 8 49 , 3 6 11 . 5 0 11 . 3 3 65 . 5 0 53 . 2 2 65 . 5 2 57 ., 1 3 62 , 8 8 6 0 .. 3 1 54 . 1 8 64 . 2 7 65 . 5 8 62 . 9 5 14 . 7 5 59 . 0 4 57 . 5 7 65 . 9 0 103 . 5 0 56 . 0 0 67 . 4 0 64 .SO 49 . 3 3 65 . 0 0 55 . 5 6 59 . 1 3 58 . 0 0 49 . 2 6 56 . 0 9 48 . 5 8 65 . 0 0 60 . 4 1 0 .00 24 . 3 3 47 . 8 5 12 . 4 0 16 . 7 5 44 . 4 5 62 . 4 4 66 . 1 5 40 . 8 8 54 . 4 4 72 . 9 0 63 . 9 5 54 . 3 8 49 . 0 6 56 . 8 0 43 . 8 0 36 . 1 0 57 . 2 0 61 . 6 9 63 , 6 4

48 15 10 16

.09 .00 .33 .50 .66

e

56 . 4 4 65 . 1 5 21 . 5 0 67 . 2 1 60 . 7 7 12 . 0 0 45 . 5 7 64 , 5 9 64 . 4 4 35 . 1 1 13 . 4 0 17 . 1 6 67 , 8 2 53 ., 1 5 49 . 6 1 57 . 1 7 5 0 .. 3 3 54 . 5 2 51 . 0 5 67 . 7 0 62 . 7 8 5 6 .. 2 3 21 . 0 0 56 . 9 2 12 . 8 0 67 . 1 3 49 . 1 3 46 . 4 6 48 . 6 1 59 . 5 0 51 . 6 8 50 . 0 9 30 . 7 7 54 . 5 6 68 . 6 3 52 . 5 8 60 . 9 0 43 . 2 0 0 7 48 12 27 36 70 66 64 58 67 56 47 23 50

.00 .00 .36 .40 .20 .70 .66 .52 .92 .77 .55 .11 .00 .00 .00

42 31 56 65

.30 .85 .87 .77

RVI Sp Au 5 0 0 0 0 4 6 0 6 3 0 3 7 6 1 0 0 8 5 5 6 6 5 5 6 4 6 0 5 1 5 3 4

6 6 4 5 3 S 9 5 4

2 3 6 0 0 3 0 1 2 5 4 0 4 7 6 2 3 2 4 1 6 5 5

3 0 0 0 0 3 3 0 7 4 0 0 7 8 1 0 1 9 5 3 4 2 3 4 5 6 5 0 5 0 4 5 3 4 5 4 6 2 5 8 5 4 2 0 0 4 0 1 1 3 5 4 4 5 2 3 0 4 2 1 8 5

H Sp 3 .03 0 .46 1 .36 2 .24 2 .60 3 .15 2 .94 2 .62 4 .01 3 .41 2. . 2 7 2. , 4 1 3. , 7 7 3 .22 1 .95 2 .07 2 .24 4 ,36 2 .33 3. , 3 0 3. , 4 2 2 .87 3. . 5 4 3 ,42 3 ,70 2 .04 3 .78 2 .73 3 .60 2 .91 2 .47 3 .29 3 .12 3 .17 3 .08 3 .37 3 .73 3 .42 3 .69 4 .52 3 .33 2 .68 2 .93 2 .98 1 .98 0 .00 2 .18 3 .23 2 .09 2 .99 3 .07 3 .58 2 .49 3 .39 3 .39 3 .15 2 .95 2 .18 2 .62 2 .84 3 .58 3 .40 3 .82 2 .55 2 .80

Au 2. . 4 9 1. . 4 1 1. . 4 7 2. . 0 1 1. . 4 4 0. . 9 2 2. . 0 5 1., 8 4 3. . 9 4 3, , 8 1 2,,59 2. . 2 3 4 ..70 3. . 8 9 3. . 5 8 0. . 9 6 3. . 1 0 3. . 6 1 1. . 2 6 2 , 35 4 ..07 1. . 9 7 2. . 5 5 3. . 7 6 2 . 96 2. . 6 2 2 ..69 0. . 9 6 1. . 8 6 2, . 8 0 2. . 1 0 3, . 8 6 2. . 7 2 3. . 4 2 2. . 5 8 2. , 8 5 3. . 3 5 2. . 7 2 2. . 8 7 3. . 6 3 3. . 7 9 3 .59 3. . 0 8 0. . 0 0 0. . 0 0 0. . 4 2 2 .19 2 .46 2 .59 2 .82 3 .30 3 .93 3 .48 3 .16 3 .23 2 .54 1 .90 2 .46 0 .58 2 .92 3 .97 1.89

N Sp A 26 6 4 7 15 29 29 8 31 32 7 24 47 29 19 15 10 40 36 29 41 21 22 27 33 18 35 13 32 19 20 27 26 30 26 25 26 28 40 41 29 30 19 19 17 0 6 19 11 15 28 28 23 17 30 35 34 27 25 21 22 22 42 33 27

1B 8 6 9 7

22 19 11 28 21 13 13 45

39 22 8 18 36 22 20 35 11 21 26 21 23 24 9 20 12 20 38 15 32 25 25 29 18 29 24 33 23

-

20

0 1 32 7

11 IB 16 25 25 32 25 22 21 14 23

-

12 18 38 22

(9)

COMPARISON

OF SEVERAL BIOLOGICAL

155

INDICES

T a b l e a u 3 . C l a s s e s d e q u a l i t é , r a n g s d e s v a l e u r s d u B M W P ' ( A : d ' a p r è s A l b a - T e r c e d o r & S â n c h e z - O r t e g a 1988, B : d ' a p r è s les d o n n é e s d e la p r é s e n t e é t u d e ) et c o u l e u r s à utiliser d a n s les r e p r é s e n t a t i o n s

cartographiques.

T a b l e 3 . Quality classes, r a n g e of B M W P ' values (A : a c c o r d i n g to A l b a - T e r c e d o r & S â n c h e z - O r t e g a 1988, B : a c c o r d i n g t o g r o u p i n g w i t h d a t a of s t u d y ) a n d c o l o u r s t o u s e in c a r t o g r a p h i c r e p r e s e n t a t i o n s .

Class

Values A

I I II III IV V

of

>13 5 95-135 65-94 45-64 20-44 <2Ù

>150 101-120 61-100 36-60 16-35 <1S

Colour

Significance

BMWP' B

Blue Blue GreenYellow Orange Red

Very c l e a n waters Clean waters Waters w i t h some d i s t u r b a n c e Polluted waters Seriously polluted waters Grossly polluted waters

Also it would be necessary t o extend the list of t a x o n s p r o p o s e d by A l b a - T e r c e d o r & SânchezO r t e g a (1988) including o t h e r iberian g r o u p s , a n d t o modify the scores of water quality depending on the peninsular a r e a where the samples came from.

Ghetti

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methods.

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