Longitudinal and seasonal variation of the benthic macroinvertebrate community and biotic indices in...

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Longitudinal and seasonal variation of the benthicmacroinvertebrate community and biotic indicesin an undisturbed Pyrenean river

Pedro M. Leunda *, Javier Oscoz, Rafael Miranda, Arturo H. Arino

Department of Zoology and Ecology, University of Navarra, P.O. Box 177, E-31080, Pamplona/Iruna, Navarra, Spain

1. Introduction

Benthic macroinvertebrate communities and biological

indices based on them have a number of features that

promoted being widely used to assess water quality. Basically,

(1) they are relatively easy to sample qualitatively or semi-

quantitatively (Zamora-Munoz et al., 1995), (2) there is an

extensive range of identification keys available (e.g., Tachet

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 2 – 6 3

a r t i c l e i n f o

Article history:

Received 26 August 2007

Received in revised form

27 January 2008

Accepted 31 January 2008

Keywords:

Macrozoobenthos

Seasonality

Spatial variation

Temporal variation

Erro River

Iberian Peninsula

a b s t r a c t

The present work aims to analyze the spatio-temporal variability in benthic macroinverte-

brate assemblages and biotic indices in an undisturbed and unpolluted Pyrenean river.

Samples were collected seasonally over 2 year-cycles (2001–2002) at fifteen sampling sites

along the Erro River (Ebro River Basin, Spain) during a exhaustive biomonitoring program

following the IBMWP–IASPT scoring system protocol routinely applied in Iberia. Despite

absolute values of the biotic indices showed high spatio-temporal variation, the IBMWP–

IASPT scoring system proved useful because water quality classes were consistent throughout

seasons and years as well as along-river. The original macroinvertebrate families’ presence/

absence data matrix was reduced in a number of ways to conduct different statistical

procedures in order to detect and separate the underlying near-natural spatial and temporal

gradients of the assemblage composition in the Erro River. Along-river, spatial variation of the

macroinvertebrate community composition was well assessed by similarity analysis, which

clearly detected physical features on the river (drought-affected reach, gorge, towns and flow

gauging weirs). Categorical principal component analysis (CATPCA) synthesized and jointly

ordered macroinvertebrate samples in a spatio-temporal gradient in the factorial map defined

by the first two principal components providing a parsimonious way to assess the assem-

blages’ variation. These two variation gradients throughout the macroinvertebrate families’

occurrence data were subsequently confirmed separately by several correspondence analyses

and revealed additional information, as the representative families for each sampling site

group and season could be identified. Furthermore, these spatio-temporal gradients were

discussed and put in relation with changes in the aquatic habitat (water temperature,

conductivity, total dissolved solids, water velocity, channel width, canopy cover, etc.). The

near-natural functioning of the Erro River promoted us to emphasize that conservation efforts

should aim to maintain the free-flowing as a permanent source of variability.

# 2008 Elsevier Ltd. All rights reserved.

* Corresponding author. Present address: GAVRN – Gestion Ambiental Viveros y Repoblaciones de Navarra S.A., C/Padre Adoain 219 Bajo, E-31015 Pamplona/Iruna, Navarra, Spain.

E-mail addresses: [email protected], [email protected] (P.M. Leunda).

avai lable at www.sc iencedi rec t .com

journal homepage: www.e lsev ier .com/ locate /ecol ind

1470-160X/$ – see front matter # 2008 Elsevier Ltd. All rights reserved.doi:10.1016/j.ecolind.2008.01.009


et al., 2000), (3) the tolerance to pollution of many macro-

invertebrate taxa is well documented allowing biological

indices to be developed (Mason, 1981; Hellawell, 1986; Jeffries

and Mills, 1990), and (4) the sampled macroinvertebrate

community integrates the state of the environment over the

previous months (Rosenberg and Resh, 1993). The IBMWP

(originally BMWP’, Alba-Tercedor and Sanchez-Ortega, 1988) is

the adaptation for the Iberian Peninsula of the British

Biological Monitoring Working Party Score (BMWP, Armitage

et al., 1983) and is extensively used as the standard biological

index in water quality biomonitoring programs throughout

the Iberian water-systems (Alba-Tercedor and Prat, 1992).

However, the marked temporal (diel and seasonal) (e.g.,

Murphy, 1978; Chesters, 1980; Armitage et al., 1983) and spatial

(between and within rivers, basins or ecoregions) (e.g.,

Hellawell, 1978; Washington, 1984) variability of the macro-

invertebrate communities and biological indices hindering

comparability has constituted their main criticism (Rosenberg

and Resh, 1993). Therefore, biotic indices are now commonly

accompanied by multivariate approaches that may provide

different and/or complementary information about the aqua-

tic environment depending on the experimental design, the

collected data and the subsequent choice for analysis (Doledec

and Chessel, 1991; Cao et al., 1996). But variation in macro-

invertebrate communities and biological indices is a result of

the natural functioning of aquatic ecosystems. Rivers in

particular, are mostly characterized by a high degree of spatio-

temporal variability (Elosegui and Pozo, 1994). As a result, the

concurrently occurring spatial and temporal variability in the

absence of disturbances must be first described and then

understood before possible anthropogenic impacts and dis-

turbance effects can be distinguished from natural variability.

At this point, the multivariate approaches offer their com-

plementary information thanks to their ability for detecting

and understanding spatio-temporal trends in the benthic

macroinvertebrate assemblages. The key advantage of these

techniques is the reduction of multidimensional data with a

minimum loss of information allowing the detection of

variability directions hidden in the data (Rosenberg and Resh,

1993).

There is an increasing need for detailed scientific informa-

tion on near-natural river systems both to ensure their

conservation as well as to better inform the restoration of

those rivers that are polluted or altered (e.g., Rosenberg and

Resh, 1993). It seems impossible to direct appropriate

restoration efforts for a disturbed reach or at least to measure

their effectiveness, if information regarding the target condi-

tions to be achieved is lacking. In order to overcome the

uncertainty in establishing control sites in field-oriented

biomonitoring studies of water quality the ‘‘reference-condi-

tion approach’’ was developed. With the reference-condition

approach, test sites are compared with the condition that is

representative of a group of minimally disturbed sites

organized by selected physical, chemical, and biological

characteristics (Reynoldson et al., 1997; Bonada et al., 2006).

An array of reference sites act as replicates for a given region to

evaluate natural variability, enabling a more reliable biomo-

nitoring of human impact on test sites. This important

principle is now more widely appreciated since the European

Community Water Framework Directive (WFD, 2000/60/CE)

was endorsed, because it states that the ecological status of a

water body must be defined by mathematically comparing the

observed (O) biological community composition with the

particular near-natural reference conditions (E, expected) for

that type of watercourse by calculating the ecological quality

ratios for a biotic index (EQR = O/E). According to the WFD,

these type-specific biological reference conditions must be

based on a physical and chemical typology of surface water

bodies in each European ecoregion, developing for this

purpose a type-specific reference network containing a

sufficient number of sites of high ecological status to provide

a sufficient level of confidence about the values for the

reference condition (Furse et al., 2006).

The Erro River in northern Spain is a near-natural Pyrenean

catchment within the Ebro River Basin. Studies have confirmed

its good ecological status based on its aquatic habitats, its

hydrochemical parameters and the biological communities it

supports (Leunda et al., 2004; Oscoz et al., 2005). The latter

study, in particular, pointed out that many reaches of the

Erro River could be used as reference sites for Pyrenean rivers

within the Ebro River Basin. As a result, and attempting

to enhance the dialogue between biomonitoring programs

and ecological research, the aim of this paper was to quantify

the temporal – seasonal – and spatial – longitudinal, along-

river – variation in macroinvertebrate assemblages and derived

biotic indices (IBMWP and IASPT) in the Erro River. Common

statistical methods were used to carry out these analyses, but

also theusefulness of a newlydeveloped multivariate statistical

tool such as the categorical principal component analysis

(CATPCA) for assemblage composition studies was tested.

2. Material and methods

2.1. Study site

The Erro River is a 48.5 km-long tributary of the Ebro River

(Spain) and is characteristic of the western Pyrenean Valleys. It

flows, north to south, through the Erro valley (Navarra) draining

an area of approximately 214 km2 (Fig. 1). The river’ source is at

1125 m a.s.l. and meets the Irati River at 460 m a.s.l. The greatest

discharge period runs from November to April with winter

maximums related to oceanic rains. These progressively

decrease in volume during spring, being replaced by melt-

water. Population density in the Erro valley is low, with scatte-

red settlements which are administratively attached to the

villages of Erro (pop. 759), Lizoain (pop. 238) and Urroz (pop. 369).

Fifteen sampling sites (E01–E15) were selected along the

river, according both to an equidistant distribution and

accessibility (Fig. 1). The sites E01 to E03 are in the headwaters

where 54% of the land is covered by deciduous forests, 17% by

scrubland and 27% by pastures. The catchment area in the

upper-middle Erro from E03 to E06 is mainly covered by

deciduous (25%) and coniferous (39%) forests while pastures

(25%) and scrublands (10%) occupy the remaining land. A

similar forest- and scrubland-cover is found in the lower-

middle Erro (E07–E12) but crop fields (24%) replace pastures

(4%). Crop fields (57%) and scrublands (18%) dominate the

lower Erro (E13–E15) while deciduous (14%) and coniferous

(5%) forests and pastures (5%) occupy the rest. E02 is located

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 2 – 6 3 53


70 m upstream from the Sorogain flow gauging weir (FGW).

The lack of sampling sites between E03 and E04 is due to the

summer drought affecting this reach where the water

infiltrates to flow through substrate interstices and the

subsurface. E15 was selected as reference for E14 (570 m

upstream) which is affected by a channelized stretch and the

Villaveta FGW. A more detailed description of the sampling

sites is available elsewhere (Leunda et al., 2004).

2.2. Field sampling and sample analysis

Qualitative samplings of macroinvertebrates were performed

seasonally, completing 2 year-cycles (2001–2002) in each

sampling site. Macroinvertebrates were collected using a

hand-net (25 cm � 25 cm aperture, 100-mm-mesh size) by

kicking and sweeping in all microhabitats present at the site

in accordance with the CEN standard (UNE-EN 27828:1994).

The kick-net contents were checked and deposited periodi-

cally in 2-l plastic jars to avoid losing organisms by overflow

from the nets. The samples were fixed in 5% buffered

formaldehyde for later identification in the laboratory.

Additional information on associated hydrochemical para-

meters can be found elsewhere (Oscoz et al., 2005).

Macroinvertebrate samples were successively filtered at

the laboratory with 4-mm to 0.4-mm-mesh size sieves to

remove fixative and fine sediments. Since samples taken with

a 0.5-mm-mesh size are adequate for exhaustive biological

surveillances (UNE-EN 27828:1994), sieving up to 0.4 mm also

Fig. 1 – Maps locating the Ebro River Basin and Navarra in the Iberian Peninsula (a), the Erro River in Navarra (b), and the

sampling site distribution along the Erro River (c).



allowed us to discard smaller macroinvertebrates. Large

organic material (whole leaves, algae or macrophytes) not

removed in the field were rinsed, visually inspected for

macroinvertebrates, and discarded. Then, all macroinverte-

brates were examined under a stereomicroscope (7�–45�) and

identified to family-level (Appendix A) using Tachet et al.

(2000). With the presence/absence data water biological

quality was assessed using the IBMWP (formerly BMWP’,

Alba-Tercedor and Sanchez-Ortega, 1988). Simultaneously,

the IASPT (Iberian Average Score Per Taxon, formerly ASPT’)

was calculated by dividing the IBMWP score by the number of

families in each sample.

2.3. Statistical procedures

Our sampling design provided 120 measurements (2 years � 4

seasons � 15 sites) for each biotic index (IBMWP and IASPT). In

order to check the difference of both biotic indices between

years Wilcoxon Matched-Pairs Signed-Ranks Tests were

performed on the pooled data of seasons and sites (2

years � 60 data). Seasonal differences in the biotic indices

were tested with Friedman analysis of variance (ANOVA)

followed by Wilcoxon Matched-Pairs Signed-Ranks Tests on

the pooled data of years and sites (4 seasons � 30 data). The

relation between IBMWP and IASPT values as well as between

these indices (seasonal, intra- and inter-annual means) and

river distance from source (DFS) were also tested by means of

Spearman’ rank correlation coefficient (rs). Since the biotic

indices are discrete quantitative variables, the non-parametric

way was chosen and the tests were carried out using the SPSS

11.0.1 statistical software package.

The original presence/absence data matrix of 78 famil-

ies � 120 samples was reduced in a number of ways to conduct

different statistical procedures following Doledec and Chessel

(1991) and references therein. First of all, very rarely occurring

(<5%) macroinvertebrate families were removed. A hierarch-

ical cluster analysis was performed on the 75 families � 15

sampling sites frequency table (i.e., counts of the presence/

absence data of years and seasons) in order to detect spatial

patterns in the macroinvertebrates community composition

of the Erro River. The Simple Matching coefficient was used as

qualitative similarity measurement between each pair of

sampling sites; the resulting similarity matrix was clustered

by the Unweighted Pair-Group Method using Arithmetic

Averages algorithm (UPGMA) (Sneath and Sokal, 1973; Krebs,

1999).

In order to simultaneously quantify our categorical variables

(presence/absence) while reducing the dimensionality of the

data a Categorical Principal Component Analysis (CATPCA) was

performed (Meulman and Heiser, 2001) with the transposed

original presence/absence data matrix (i.e., 120 samples � 78

families) with SPSS 11.0.1. Our original presence/absence data

matrix was nothing but a three-dimensional data matrix of 78

families sampled at 15 sites 8 times (2 year � 4 season).

Therefore, amongst the various analytical choices illustrated

by Doledec and Chessel (1991) and references therein, con-

ducting two Correspondence Analyses (CA) separately elim-

inating the temporal and the spatial effects was chosen. The

first CA was performed on a frequency data matrix cumulated

by sites (75 families � 15 sites) while in the second CA a

frequency data matrix cumulated by dates (75 families � 8

sampling seasons) was used as input table. These allowed

detecting the most characteristic families for the seasons and

the sampling sites, respectively. NTSYSpc Version 2.11s (Rohlf,

2002) was used to carry out the clustering and the CAs.

3. Results

3.1. Biotic indices

Throughout both years the IBMWP scores fall almost always in

the quality Class I defined for unpolluted waters (>100) (Fig. 2).

The IASPTvaluesvarying between 4.82 and 6.82 (Fig.2) were also

consistently indicative of good (4.5–5.5) and very good (>5.5)

water quality over the 2-year study period. Highest IBMWP

scores could be obtained anywhere along the river but were

generally more common in E02 and in middle reaches. The

negative significant correlation between DFS and the inter-

annual IBMWP scores was consistent neither in intra-annual

means nor in seasonal scores (Table 1). On the contrary, IASPT

valuesalwaysshoweda strongprogressive decreasefromupper

to lower reaches, being slightly weaker in spring (Table 1).

Neither the IBMWP scores (Z = �0.593, p = 0.553) nor the IASPT

(Z = �0.677, p = 0.498) were significantly different between

years. However, highly significant seasonal differences were

detected in both IBMWP scores (x2ð3;30Þ ¼ 13:600, p = 0.004) and

IASPT (x2ð3;30Þ ¼ 14:800, p = 0.002). Pair-wise comparisons

detected that the summer IBMWP scores were higher and

significantly different to all other seasons, which in turn did not

differ significantly from each other (i.e., summer> (spring �winter� autumn), Table 2). All the pair-wise comparisons of

the seasonal IASPT were statistically significant except for the

winter vs. autumn and summer vs. spring pairs, showing that

IASPT values detected in winter and autumn where signifi-

cantly higher than those from summer and spring (i.e.,

(summer � spring) > (winter� autumn), Table 2). The biotic

indices were significantly positively correlated (rs = 0.525,

p < 0.001).

3.2. Macroinvertebrate community

The similarity analysis of the macroinvertebrate community

composition clustered the 15 sampling sites into six groups

along the Erro River (Fig. 3). The first main division separated

sites upstream (E01–E12) and downstream (E13–E15) of Urroz

town with a similarity of approximately 36%. The upstream

from Urroz cluster could be further split into four groups at the

42% similarity level. The river reach affected by the summer

droughts and the Erro town segregated upstream E01 and E03

(first) and downstream E02 and E04–E06 (second). E02 appears

in this second group and not in the first one, as was a priori

expected. The third (E07–E10) and fourth (E11 and E12) groups

are located between the gorge and Urroz town. The down-

stream Urroz cluster could be further split into two groups at

the 40% similarity level – sites E13–E15 made up the fifth group

while site E14 constitutes the sixth group on its own.

The CATPCA analysis of the macroinvertebrate families

extracted two dimensions with eigenvalues >1.0 that

together explained 16.1% of the total variance between all



the 120 samples. Factor scores of the samples in the first two

dimensions are plotted in Fig. 4. The first dimension, and

principle gradient of variation throughout the macroinverte-

brate families occurrence data, is that associated with the

spatial – longitudinal – change from source to mouth along

the river. The second dimension conveys the seasonality of

the assemblage composition. Summer and winter samples

were most distinct from each other while spring and autumn

samples tended to be closer, midway between the former two

seasons.

The CAs confirmed these patterns separately and revealed

additional information, as the representative families for each

sampling site group and season could be identified. Fig. 5

intends to visualize the longitudinal distribution of the

taxonomic groups in the first two dimensions (48.6% of the

variance) obtained from the temporal-effect-free CA. Numbers

correspond to macroinvertebrate families in Appendix A.

Within some taxonomic groups some families appeared all

along the river whereas others were characteristic of certain

reaches. This was the case of Molluscs where Bythinellidae (4)

were representative of headwaters, Lymnaeidae (6) were of

middle reaches, Physidae (7) and Planorbidae (8) were

representative of lower reaches, while Ancylidae (3) was

distributed all along the river. Also within mayflies (Ephemer-

optera), families such as Potamanthidae (24) and Caenidae (19)

were limited to the lower reaches while Ephemeridae (21) and

Leptophlebiidae (23) were more faithful to upstream sites.

Similar tendencies could be found in Odonata, Coleoptera,

Trichoptera and Diptera families. Most stonefly families

(Plecoptera) were restricted to headwaters—Chloroperlidae

(29), Perlodidae (33), Nemouridae (31) and Perlidae (32), but

Taeniopterygidae (34) could be found in lower reaches. Due to

these distribution preferences the sampling sites followed a

characteristic ordination in the factorial map as indicated by

the arrow (Fig. 5). The site ordination by the CA was mostly in

agreement with the groups identified by the cluster analysis.

Fig. 6 shows the most representative families for each

season in the first two dimensions (57.0% of the variance)

obtained from the spatial-effect-free CA. This factorial map

shows how within a given taxonomic group families appear in

a certain season of the year. This occurred with aquatic beetles

(Coleoptera) where families such as Dryopidae (38) and

Haliplidae (42) were detected in autumn–winter, and Helodi-

dae (43) and Helophoridae (44) were found in spring, whereas

Dytiscidae (39) and Hydrophilidae (46) appeared in summer.

Similar situation was displayed for caddisflies (Trichoptera),

from which Brachycentridae (48) and Goeridae (51) occurred in

autumn–winter, Beraeidae (47) and Glossosomatidae (50)

occurred in spring, but most of the families were detected

in summer (49, 53–59). Alike tendencies were found for Diptera

or Plecoptera. But within some taxonomic groups most

Fig. 2 – Seasonal IBMWP scores (*) 2001; (*) 2002 and IASPT (^) 2001; (^) 2002 values along the Erro River. Dashed lines show

the limits of the biological water quality Class I (IBMWP value >100, unpolluted) and Class II (IBMWP value 61–100, good).

Table 1 – Correlation tests between biotic indices(seasonal values, intra- and inter-annual means) anddistance from source (DFS) in the Erro River (rS, Spear-man’ rank correlation coefficient, *p < 0.05, **p < 0.01,***p < 0.001).

DFS vs. IBMWP DFS vs. IASPT

rS p rS p

2001 Winter �0.195 0.486 �0.800 <0.001***

Spring �0.243 0.383 �0.629 0.012*

Summer �0.415 0.124 �0.839 <0.001***

Autumn �0.384 0.157 �0.864 <0.001***

Mean �0.293 0.289 �0.882 <0.001***

2002 Winter �0.536 0.040* �0.804 <0.001***

Spring �0.702 0.004** �0.600 0.018*

Summer �0.345 0.208 �0.832 <0.001***

Autumn �0.679 0.005** �0.850 <0.001***

Mean �0.743 0.002** �0.843 <0.001***

Mean �0.683 0.005** �0.836 <0.001***



families were representative of a certain season, e.g. Mollusca

in autumn–winter, Hemiptera and Odonata in summer, or

Ephemeroptera in spring. This seasonality was summarized

by the circular sequence displayed by the location of the

seasons in the factorial map as showed by the arrows (Fig. 6).

The ordination shows that spring and summer benthic

macroinvertebrate assemblages were clearly different from

other seasons’, whereas autumn and winter were more

similar to each other.

4. Discussion

Although many researchers since Murphy (1978) have

observed seasonal variability in biotic indices, they considered

these differences to be relatively small compared with

differences between sites (Armitage et al., 1983; Zamora-

Munoz et al., 1995). Previous works in British (Armitage et al.,

1983; Pinder et al., 1987) and Basque rivers (Rodrıguez and

Wright, 1991) have shown the ASPT/IASPT to be less sensitive

to seasonal changes than the BMWP/IBMWP, and therefore

Armitage et al. (1983) recommended the ASPT rather than the

BMWP. However, Zamora-Munoz et al. (1995) showed that in

the case of riverheads with clear waters from a Mediterranean

river, the IASPT was more dependent on temperature and

therefore seasonality. Additionally, in view of the difficulty of

giving IASPT values a specific meaning with regard to

biological quality, Zamora-Munoz et al. (1995) considered

the IBMWP valid. This could account for the case of Erro River,

an unpolluted Pyrenean river, where our pair-wise compar-

Table 2 – Wilcoxon Matched-Pairs Signed-Ranks Test values and their significance (*p < 0.05, **p < 0.01, ***p < 0.001) for thecomparisons of the seasonal IBMWP scores and IASPT values

Winter Spring Summer

Z p Z p Z p

IBMWP

Spring �0.833 0.405 – –

Summer �3.096 0.002** �3.353 0.001*** – –

Autumn �0.072 0.943 �1.049 0.294 �2.859 0.004**

IASPT

Spring �2.746 0.006** – –

Summer �2.828 0.005** �0.216 0.829 – –

Autumn �1.347 0.178 �2.211 0.027* �1.964 0.049*

Fig. 3 – Dendrogram resulting from the cluster analysis of the macroinvertebrate assemblage composition of the fifteen

sampling sites (E01–E15) and their distribution along the Erro River ( : weir; FGW: flow gauging weir). The rectangles

highlight the sites-pairs located nearby FGW that did not fit the a priori expected groups.



isons between seasonal biotic indices showed more significant

differences in the IASPT (i.e., (summer � spring) > (win-

ter � autumn)) than in the IBMWP (i.e., summer > (spring -

�winter � autumn)). In any case, Armitage et al. (1983)

suggested that samples taken in any of the three seasons

(winter was not considered) are likely to provide consistent

estimates of BMWP and ASPT. In the same way, Zamora-

Munoz et al. (1995) pointed out that the different classes of

water quality established for the IBMWP correspond to wide

intervals of the score, making it robust even when pronounced

peaks and troughs are found in the graphics tracing its

evolution as long as they do not go beyond these intervals.

Regarding along-river variation of the biotic indices, our

results are in accordance with previous studies (Armitage

et al., 1983; Rodrıguez and Wright, 1991). Highest IBMWP

scores could be obtained anywhere along the length of the

river but were generally more common in middle reaches

whereas IASPT values always showed a clear progressive

decrease in a downstream basis. A more detailed discussion of

possible causes and management implications of the local

changes is available elsewhere (Oscoz et al., 2005). Summing

up and putting this in practice, for a routine biomonitoring

program using the IBMWP–IASPT scoring methodology, we

would conclude that the biological quality of the Erro River

waters was almost always above the original limits of the Class

I (Alba-Tercedor and Sanchez-Ortega, 1988) defined for

unpolluted waters (>100) and even very clear (>150). The lack

of spatio-temporal variation in the classes obtained, despite

the changes of the macroinvertebrate community composi-

tion and therefore the resulting IBMWP–IASPT absolute

values, is a key feature of the usefulness of this scoring

system after the WFD water quality classification require-

ments. Following the criteria given by the WFD, the IBMWP

quality classes are being readjusted and defined for each

ecoregion/ecotype within the Ebro River Basin; the Erro River

was included in the ‘‘Humid (Pyrenean) Mountains’’ ecoregion

and therefore the biological quality of its waters still remain

conveniently in the Class I (>100).

The methodology for the calculation of the IBMWP score

requires the elaboration of families’ presence/absence charts

while samples are being analyzed. Until recently there was no

multivariate statistical method to work with these categorical

raw data (78 families � 120 samples). However, the Data

Theory Scaling System Group (DTSS) of the Leiden University

implemented the CATPCA module for SPSS, which is mainly

an exploratory application rather than confirmatory in nature

(Meulman and Heiser, 2001). The utilization of this technique

allowed us to reduce the multidimensionality of the macro-

invertebrate assemblage composition data while graphically

displayed the two most relevant components affecting the

Fig. 4 – Categorical principal component analysis ordination diagram of the macroinvertebrate assemblage composition

samples. Samples (n = 120) are represented by rectangles, which are colored in a grayscale basis according the sampling

site location along the Erro River and rotated differently for each season.



possible relations between samples, i.e., position along the

river and season. As far as the authors know, this is the first

time that such ordination technique has been applied for

these purposes.

These two principal gradients of variation throughout the

macroinvertebrate families’ occurrence data were subse-

quently confirmed separately by several CAs and revealed

additional information, as the representative families for each

sampling site group and season could be identified. The

factorial map jointly representing the factor scores of the

macroinvertebrate families and the sampling sites in the two

main dimensions obtained from the temporal-effect-free CA

clearly displayed the along-river gradient (Fig. 5). Based on

this, we showed that within most taxonomic groups (i.e.,

Mollusca, Ephemeroptera, Odonata, Coleoptera, Trichoptera

and Diptera) given families appear all along the river whereas

others are characteristic of upper, middle or lower reaches. On

one hand, for example, we showed that Ancylidae is one of the

Mollusca families ubiquitous in the Erro River, something that

has been also pointed at larger spatial scales in the Ebro River

Basin (Oscoz et al., 2004) and nearby Basque rivers (Bargos

et al., 1990) at species-level (Ancylus fluviatilis). On the other

hand, most stonefly (Plecoptera) families are restricted to the

upper reaches of the Erro River (E01–E03), probably related to

fast-flowing clear waters with pebbles and boulders (Armitage

et al., 1983; Bargos et al., 1990; Vivas et al., 2002), while

Taeniopterygidae was the only family occurring in lower

reaches seemingly due to a preference for sand and gravel

substrates (Taeniopteryx schoenemundi according to Oscoz and

Duran (2004)).

Compressing all the spatial distribution preferences

showed by the benthic macroinvertebrate families, the

sampling sites follow a characteristic ordination which is

mostly in agreement with the groups identified by the cluster

analysis. Both statistical approaches resulted to be useful and

complementary tools segregating the sampling sites in a

longitudinal basis along the Erro River, since the former

identifies the families responsible of the site ordination while

the latter quantifies the similarity/dissimilarity level between

sites (Cao et al., 1996). The sampling sites groups were

segregated due to natural and/or artificial influences. Sam-

pling sites located nearby the FGW (E02 and E14) did not fit

within the a priori expected groups, indicating that the benthic

macroinvertebrate assemblage was altered (Fig. 3, rectangles).

Alteration in E02 and E14 sites was due to widened channel,

reduced canopy cover and water velocity, resulting in

increased water temperature (Leunda et al., 2004; Oscoz

et al., 2005). It is noticeable that the FGW located between

E04 and E05 apparently did not alter the communities of these

points, since they were far enough from it.

Fig. 5 – Correspondence analysis ordination diagram of the macroinvertebrate families (numbers, Appendix A) and

sampling sites (E01–E15), accompanied by a graph representing the decreasing percentage of the explained variance by the

eigenvalues of the successive dimensions.



Seasonal change of the benthic macroinvertebrate

families was evidently displayed by the location of the

seasons in a circular fashion in the factorial map obtained

from the spatial-effect-free CA (Fig. 6). The cyclical ordination

pattern as the seasons progress furthermore shows that

autumn and winter benthic macroinvertebrate assemblages

were more similar while spring and summer were clearly

different (Armitage et al., 2001). The observed seasonal

succession results from the fact that within a given

taxonomic group different families appear in certain season

of the year (e.g., Coleoptera, Plecoptera), but moreover,

because within other taxonomic groups most (even all)

families are characteristic of a season. This is the case of

mainly summer-occurring Trichoptera, Diptera, Hemiptera

and Odonata, the Mollusca in autumn–winter or Ephemer-

optera in spring (Coimbra et al., 1996; Rieradevall et al., 1999;

Vivas et al., 2002).

It is widely accepted that the presence of an organism at a

specific site is the result of the constraining action of a

number of nested historical and ecological filters at

successively smaller spatio-temporal scales, as well as that

the relative importance of each filter may vary according to

the spatio-temporal scale of the study (e.g., Bonada et al.,

2005). Nearly all facets of the life-history of benthic

macroinvertebrates, and consequently their distribution

and abundance, are influenced by temperature (Wetzel,

2001; Vivas et al., 2002; Hieber et al., 2005), substrate – type

and composition – (Allan, 1995; Hieber et al., 2005), hydraulic

conditions (Allan, 1995; Vivas et al., 2002) and food

availability (Basaguren et al., 1996; Gonzalez et al., 2003),

combined and acting in various spatio-temporal scales and

gradients (Cortes, 1992; Graca et al., 2004; Murphy and Davy-

Bowker, 2005). In natural water courses, these parameters

(and others, e.g., altitude, slope, channel stability, width,

depth, pH, conductivity, salinity) vary seasonally and/or

over downstream gradients, and their relative importance

affecting benthic macroinvertebrates differs among studies

suggesting considerable inter-habitat and inter-climatic

variation (Graca et al., 2004).

In the Erro River, Leunda et al. (2004) pointed out that

factors such as river width, presence of aquatic vegetation,

water temperature, conductivity and total dissolved solids

(TDS) increased downstream, while depth, discharge, current

velocity and temperature were seasonally more variable. It is

therefore plausible to explain the gradual spatio-temporal

replacement of the benthic macroinvertebrate assemblage

observed in this study with the spatio-temporal patterns in the

aquatic habitat described by Leunda et al. (2004). The latter

study did not show noticeable variation in the substrate type

and composition between reaches, so the variation of the

Fig. 6 – Correspondence analysis ordination diagram of the macroinvertebrate families (numbers, Appendix A) and seasonal

samples (Wi: winter, Sp: spring, Su: summer, Au: autumn; 01: 2001, 02: 2002), accompanied by a graph representing the

decreasing percentage of the explained variance by the eigenvalues of the successive dimensions.



macroinvertebrate communities along the river could be

related to the downstream increase of habitat features such

as river width, conductivity and temperature (Vivas et al.,

2002; Bonada et al., 2005). The cyclical pattern of the samples

reflects macroinvertebrate life-cycles in response to the

seasonal changes of habitat characteristics such as tempera-

ture (Hieber et al., 2005) and discharge (Coimbra et al., 1996;

Armitage et al., 2001; Vivas et al., 2002), and its surrogate

variables, depth and current velocity. Despite we have been

able to detect and describe spatio-temporal variations of

benthic macroinvertebrate assemblages identified to family-

level, it is sure that more subtle changes only would became

apparent as the taxonomic identification resolution increases

to genus- or species-level (Doledec et al., 2000).

In conclusion, we showed that data on presence/absence of

benthic macroinvertebrate families, as is commonly collected

in routine biomonitoring programs for the calculation of the

IBMWP index, is further useful for the understanding of spatial

and temporal trends of macrobenthic assemblages in rivers.

Possibly, the main criticism to this approach is that the

differences among assemblages are based on taxa presence or

absence, instead of relative abundances, but optimizes the

cost–benefit trade-off since reduces sampling effort and

sorting time (Doledec et al., 2000). As can be seen in the study

carried out by Sporka et al. (2006) in a stream in the Carpathian

Mountains, quantitative surveys in combination with species-

level identification do not per se ensure a better than ours

separation of the seasonal macroinvertebrate samples in the

multivariate ordination space (i.e., spring and summer

assemblages clearly different from other seasons’, whereas

autumn and winter were more similar to each other).

However, family-level abundance data is recommended as

the best resolution for resolving spatial patterns in macro-

invertebrate assemblages in harsh dryland river system in

Australia based on cost/benefit analysis (Marshall et al., 2006).

Apart from all this, it is always worthwhile highlighting that

the near-natural spatio-temporal variations described in this

study are favored by the lack of severe anthropogenic

alterations in the Erro River. We talk in terms of ‘near-

naturalness’ since nowadays nearly all river systems suffer at

least some degree of anthropogenic pressure that subse-

quently promote faunistic changes. Therefore, conservation

efforts in the Erro River should aim to preserve this near-

natural functioning.

Acknowledgements

Authors gratefully acknowledge the people that collaborated

in field samplings. We are very grateful to John F. Murphy

(Centre for Ecology and Hydrology, Winfrith Technology

Centre), Arturo Elosegi (University of the Basque Country) and

Sergi Sabater (University of Girona) and two anonymous

reviewers for their valuable comments on an earlier version

of the manuscript, and to Marıa Dıez-Leon (University of

Guelph) for improving the English. This research was

financially supported by means of a project funded by

C.S.I.C./Government of Navarra and a predoctoral grant from

the Asociacion de Amigos – University of Navarra to Pedro M.

Leunda.

Appendix A

Macroinvertebrate families found in the analyzed samples

from the Erro River followed by their code number

Platyhelminthes

Dugesiidae (1)

Planariidae (2)

Mollusca

Ancylidae (3)

Bythinellidae (4)

Hydrobiidae (5)

Lymnaeidae (6)

Physidae (7)

Planorbidae (8)

Sphaeridae (9)

Annelida

Oligochaeta (10)

Hirudinea

Erpobdellidae (11)

Glossiphoniidae (12)

Arthropoda

Arachnidae

Hydracarina (13)

Crustacea

Asellidae (14)

Atydae (15)

Gammaridae (16)

Ostracoda (17)

Insecta

Ephemeroptera

Baetidae (18)

Caenidae (19)

Ephemerellidae (20)

Ephemeridae (21)

Heptagenidae (22)

Leptophlebiidae (23)

Potamanthidae (24)

Odonata

Aeschnidae (25)

Calopterygidae (26)

Cordulegasteridae (27)

Gomphidae (28)

Plecoptera

Chloroperlidae (29)

Leuctridae (30)

Nemouridae (31)

Perlidae (32)

Perlodidae (33)

Taeniopterygidae (34)

Hemiptera

Corixidae (35)

Gerridae (36)

Hydrometridae (37)

Coleoptera

Dryopidae (38)

Dytiscidae (39)

Elmidae (40)

Gyrinidae (41)

Haliplidae (42)

Helodidae (43)

Helophoridae (44)

Hydraenidae (45)



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Hydrophilidae (46)

Trichoptera

Beraeidae (47)

Brachycentridae (48)

Ecnomyidae (49)

Glossosomatidae (50)

Goeridae (51)

Hydropsychidae (52)

Hydroptilidae (53)

Leptoceridae (54)

Limnephilidae (55)

Odontoceridae (56)

Philopotamidae (57)

Polycentropodidae (58)

Psychomyiidae (59)

Rhyacophilidae (60)

Sericostomatidae (61)

Megaloptera

Sialidae (62)

Diptera

Anthomyidae (63)

Blephaceridae (64)

Ceratopogonidae (65)

Chironomidae (66)

Dixidae (67)

Ephydridae (68)

Limoniidae (69)

Muscidae (70)

Psychodidae (71)

Simuliidae (72)

Stratiomyidae (73)

Tabanidae (74)

Tipulidae (75)

Brachycera

Athericidae (76)

Dolichopodidae (77)

Empididae (78)



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