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
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.92
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.00
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42
31
56
65
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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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