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Aquatic Coleoptera \(Hydraenidae and Elmidae\) As Indicators of the Chemical Characteristics of Water in the Orbigo River Basin

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Aquatic Coleoptera \(Hydraenidae and Elmidae\) As Indicators of the Chemical Characteristics of Water in the Orbigo River Basin AnnlsLimnol. 31 (3) 1995 : 185-199 Aquatic Coleóptera (Hydraenidae and Elmidae) as indicators of the chemical characteristics of water in the Orbigo River basin (N-W Spain) F. Garcia Criado1 M. Fernandez Alaez Keywords : Hydraenidae, Elmidae, indicator species, León, Spain. The responses of 32 Hydraenidae and Elmidae species to six chemical parameters - alkalinity, CI", S04" ", COD, N03\ and to• tal P have been analysed in the Orbigo river basin. The study of the distribution in relation to these factors by means of elabora• ting their ecological profiles pointed out the indicator species for each one of these parameters, according to their reciprocal spe• cies-factor information. Hydraenidae et Elmidae (Coleóptera) indicateurs des caractéristiques chimiques de l'eau dans le bassin de la rivière Orbigo (N-O Espagne) Mots clés : Hydraenidae, Elmidae, espèces indicatrices, León, Espagne. Les réponses des 32 espèces d'Hydraenidae et d'Almidae à 6 paramètres chimiques - alcalinité, Cl", S04" ", DCO, N03" et P total - ont été analysées dans le bassin de la rivière Orbigo. L'étude de leur répartition en relation avec ces facteurs et la recherche de leurs profils écologiques ont mis en évidence les espèces indicatrices pour chacun de ces paramètres. 1. Introduction In the province of León (N-W Spain) there has been no previous research of this kind. We have presented Few studies have been reported on the families Hy• some preliminary data from our study carried out in draenidae and Elmidae in Spain. Furthermore, these the Orbigo basin (García Criado et al. 1994, García studies have been limited to general considerations Criado et al., in press), and pointed out the tolerance li• about habitat preferences. Only recently have authors mits of species for 10 physical and chemical parame• such as Puig (1983), Sáinz-Cantero (1985), Sáinz- ters. In this work we extend these studies through mo• Cantero & Alba-Tercedor (1991), Díaz Pazos (1991) re detailed investigation on the autoecology of species and Rico (1992) taken interest in determining the in• of both families. We aim at exposing the preferences fluence of physicochemical parameters on the distribu• of these species within the ranges of values found for tion of species of these families. several chemical factors. 2. Material and methods The Órbigo basin lies mostly on siliceous soil, which alternates with calcareous soil in the northern areas (ri• vers Luna and Torrestio). The depth of the water• 1. Departamento de Biología Animal. Facultad de Biología. courses prospected was seldom more than 50 cm. Universidad de León. 24071 León. Spain. Samples were taken seasonally over an annual cycle 2. Departamento de Ecologia, Genética y Microbiología. Facultad de Biología. Universidad de León. 24071 León. Spain. (from April 1991 to February 1992) and were collected Article available at http://www.limnology-journal.org or http://dx.doi.org/10.1051/limn/1995017 186 F. GARCIA CRIADO, M. FERNANDEZ ALAEZ (2) from 37 sites along the rivers of the basin (Fig. 1), al- were collected by five minutes kick-sampling. Only ways from lotie environmentsl(middlê~of~the river) presence/absence data of adults have been considered with pebble, cobble and boulder substratum. Beetles in this study. Fig. 1. Geographical situation of the Órbigo river basin and sampling sites. Fig. 1. Situation géographique du bassin de la rivière Órbigo et stations de récoltes. (3) AQUATIC COLEÓPTERA AND CHEMICAL CHARACTERISTICS IN A RIVER BASIN 187 All the 148 collected samples were taken into ac• Next the profile of absolute frequencies was arran• count together, regardless of their time of collection. ged, this is the number of samples in every class of Samples without Hydraenidae and Elmidae specimens describer in which each species is present. Although were excluded from statistical processing, so that 101 the pattern of this profile gives a preliminary idea of was the final number of analyzed samples. These how the taxon responds to environmental variables, it samples have been excluded as the lack of specimens may be misleading as the number of samples included is often due to causes other than chemical factors (high in every class (that is to say, the overall profile) is not water levels and difficulty of sampling, siltation...). uniform. Besides, it is necessary to take into account Besides their inclusion would have produced gaps in the frequency of each species in the sample lot to cor• the profiles making it difficult to interpret the results. rect the differences between the features of rare and Some factors likely to influence the distribution of frequent species. For these reasons, a profile of correc• Coleóptera or those positively correlated with the de• ted frequencies C(k) was calculated in order to produ• gree of organic pollution of water were considered in ce a more reliable image of the pattern of species dis• the analysis. Such selected factors are : alkalinity, CI", tribution in relation to the describer. For this purpose we used the formula of Daget & Godron (1982) : S04", chemical oxygen demand (COD), N03" and to• tal P. On the one hand, parameters such as pH and oxy• gen concentration were not included since their values C(k)- W • M> W throughout the basin were homogeneous and gave ve• R(k) ' NR ry little information on beetles distribution. Because conductivity is closely correlated with alkalinity, its in• where, besides the previous notation : clusion was considered redundant. C(k) = median frequencies of the species E in every class of describer. The data were analyzed as follows. Firstly, the ob• U(k) = number of sampling sites for every class of served range of values for each habitat parameter (des- describer in which species E is present. criber) was divided into a series of intervals (classes of U(E) = total number of sampling stations in which describer). The samples were assigned to intervals ac• species E is present. cording to their value for the describer. In this way, we established the number of samples occurring in each In order to select those taxa which give the most in• class of describer. Within each describer, care has been formation with regard to every parameter, and avoid taken for the amplitude of intervals to be as homoge• analysing all of them, the reciprocal species-describer neous as possible. However, it was not possible to es• information has been estimated. For this, we used the tablish perfectly even intervals since it is convenient formula put forward by Godron (1968) : that the number of sites included in each class is as uni• form as possible (Nakache 1973). Nk U(k) U(k) NR Nk V(k) V(k) NR Firstly, it is important to determine the sampling I(L,E) = I log2 . +1 log2 quality. We calculated the entropy linked to the descri• l NR R(k) U(E) l NR R(k) V(E) ber resulting from the sampling achieved by means of the following formula (Daget et al., 1972) : where, besides the previous notations : V(k) = number of sampling stations for each interval Nk R(k) NR in which species E is absent. H(L) = I log2 i NR R(k) V(E) = total number of sampling stations in which species E is absent. where : This value was taken as a measure of the indicator R (k) = number of sampling stations in every class of value of the species in relation to the describer. Since describer. we are working with 32 species and 6 parameters it is NR = total number of sampling stations (101). not useful to analyze such a high number of features. It Nk '= number of classes of describer taken into ac• is much easier to handle just those features of species count. which provide useful information. These are the ones By comparing this value with the one for maximum with highest I(L ; E), that is, the highest indicator value for the describer. For every parameter we have selec• entropy H(L)max = log2 (Nk) we obtained the sampling ted the ten species whose values of reciprocal informa• quality Q(L) = H(L)/H(L)max, which indicates the loss of information in the sampling. Higher is the value, lo• tion species-describer were highest ; their corrected wer is the loss of information. frequencies are represented by histograms (Figs. 2-7). 188 F. GARCIA CRIADO, M. FERNANDEZ ALAEZ (4) These are the species which are more highly linked to 3.2. Choride (Fig. 3) the factor under consideration. A sampling quality of 0.88 was obtained. Because of Finally, we calculated the barycenter which allows the small number of samples with a CI concentration us to summarize the information given by each one of exceeding 10 mg/1, all samples above this level were the ecological profiles by means of a single value. It included in a single interval, even though values ex• allows arrangement of the species along the ecological tended up to 23.2 mg/1. Only two species, Elmis mau- gradient and can be taken as a measure of its ecologi• getii and Esolus pygmaeus, occur in the site with maxi• cal optimum. For this calculation, the expression used mum chloride level. The most representative species was the following (Daget & Godron 1982) : for this parameter can be classified into : — Taxa from areas with a low concentration : Hy• 6 v m. draena inapicipalpis, Hydraena emarginata, Hydraena In 1 ibérica and Elmis aenea. With a wider range, Hydrae• where : na brachymera may also be included in this group. irij = index of frequency (value of corrected frequen• — Taxa from areas with a high concentration : Eso• cy for every class of describer in which the species is lus pygmaeus is closely linked to sites with high levels present).
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