Water quality in the Mondego river basin : pollution and habitat heterogeneity

INTRODUCTION The increase in water necessities for domestic, industrial and agricultural use has led to an increase in water consumption and contributed to the degradation of the water quality. Since water degradation results mainly from chemical changes in water, early standard methods for assessing quality relayed on water chemistry. According to Metcalfe (1989), biological assessments offer important advantages over chemical assessments: (1) they are more sensitive than chemical methods under conditions of toxic, intermittent or organic pollution; (2) they detect the more subtle disruptions as well as non-source pollution; (3) they measure actual effects on 295 Water quality in the Mondego river basin: pollution and habitat heterogeneity Verónica Ferreira*, Manuel A.S. Graça, Maria João Feio & Claúdia Mieiro IMAR - Centro Interdisciplinar de Coimbra, Departamento de Zoologia, Universidade de Coimbra, 3004517 Coimbra, Portugal * Author for correspondence: [email protected] ABSTRACT The “IMARDepartamento de Zoologia, Universidade de Coimbra” and “Direcção Regional de Ambiente e Ordenamento do Território” started a partnership with the objective of establishing bases for the assessment of water quality in the Mondego river basin. Here we present the preliminary results of the study. We sampled 75 sites covering the Mondego river basin. At each site we took 18 physical and chemical measurements and sampled macroinvertebrates with a hand net. Site quality was assessed by the application of a biotic index (BMWP’), water chemistry and habitat heterogeneity. Fifty two percent of the sites had good biological water quality (based on BMWP’ index). The strongly polluted sites were concentrated in the Lower Mondego region. Thirty three percent of sites had bad chemical water quality and 45% of the sites had low habitat complexity. Only 40% of the sites with low biological quality also had low chemical water quality. We concluded that (1) in general, the waters on the Mondego river basin do not suffer from strong water pollution and (2) low BMWP’ values can be explained by low water quality or low habitat heterogeneity (natural or man-made). Key words: biological water quality, chemical water quality, habitat heterogeneity, BMWP’. RESUMEN El “IMARDepartamento de Zoologia, Universidade de Coimbra” y la “Direcção Regional de Ambiente e Ordenamento do Território” iniciaron una colaboración con el objetivo de establecer las bases para la evaluación de la calidad del agua en la cuenca hidrográfica del Río Mondego. En esta publicación presentamos los datos preliminares de ese estudio. Se muestrearon 75 localidades, repartidas por toda la cuenca del Mondego. En cada localidad se midieron 18 parámetros químicos y físicos y se muestreó la comunidad de macroinvertebrados acuáticos con una red de mano. La calidad ambiental fue calculada mediante la aplicación del índice biótico BMWP’, por las características químicas del agua y por la heterogeneidad del hábitat. Un 51% de las localidades muestreadas tenían una buena calidad ambiental, de acuerdo con el índice BMWP’. Los sitios fuertemente contaminados estaban concentrados en la zona del Bajo Mondego. Un 33% de los locales tenían una calidad química mala, mientras que el 45% tenían una baja heterogeneidad del hábitat. Solamente un 40% de las localidades con baja calidad biológica también tenían baja calidad química. Concluimos que (1) en general, las aguas de la cuenca del río Mondego no sufre de contaminaciones fuertes, y (2) que los bajos valores de BMWP’pueden ser explicados por la baja calidad del agua o bien por una baja heterogeneidad del hábitat (por causas humanas o naturales). Palabras clave: calidad biológica del agua, calidad química del agua, heterogeneidad del hábitat, BMWP’. Limnetica 23(3-4): 295-306 (2004) © Asociación Española de Limnología, Madrid. Spain. ISSN: 0213-8409 biota, whereas chemical methods must be interpreted on a biological basis; and (4) organisms integrate environmental conditions over long periods of time, whereas chemical data are instantaneous and therefore require large numbers of measurements for an accurate assessment. Biotic indices are numeric expressions that classify water quality based on the ecological sensitivity of the taxa present and on the taxa richness. Many biotic indices are based on macroinvertebrates because they occupy a central role in the aquatic ecosystem by participating in the decomposition of organic matter and by constituting the major food source for other aquatic invertebrates, fishes and some birds (Callisto et al., 2001). An example of a biotic index based on macroinvertebrates is the BMWP index, originally developed in Great Britain (Armitage et al., 1983) and then adapted to the Iberian Peninsula (Alba-Tercedor & Sánchez-Ortega, 1988; Alba-Tercedor, 1996). This index requires only qualitative data and macroinvertebrates are identified only to family level. Although the index is expected to respond negatively with an increase in organic pollution, low values may also reflect low habitat heterogeneity (Armitage et al., 1983; Blijswijk et al., 2005; Oliveira et al., 2001). The goals of this study were (1) to elaborate a map of biological quality of the Mondego river basin, the largest single basin located entirely in Portugal, and (2) to estimate the effect of pollution and habitat heterogeneity on the BMWP’scores values. METHODS Study area The source of the Mondego River is located in the “Serra da Estrela” mountain (Central Portugal), at 1547 m above sea level. The river flows along 227 Km into the Atlantic Ocean, draining a hydrological basin of about 6670 Km2, the largest single basin located entirely in Portuguese territory (Marques et al., 2002). It is possible to divide the Mondego basin into 3 areas, according with hydro-morphologic characteristics; the Upper Mondego region, which comprises the mountainous region drained by the upper Dão and Alva tributaries and the upper part of the Mondego river, is mainly composed of granite; the Middle Mondego region, which comprises the area between the base of Serra da Estrela Mountain and the city of Coimbra, is mainly schistose. This section contains the final parts of the Dão, Alva and Ceira tributaries; and the Lower Mondego region that spans from the city of Coimbra to the sea (Figueira da Foz), and where the main tributaries are Pranto, Arunca and Ega, is calcareous (Marques et al., 2002). In this basin, land is mostly used for coniferous forest plantations (22%), mix forest plantations (21%), agriculture (25%) and furze-field and pasture (15%) (INAG, 2003). The Lower Mondego region is comprised of 15,000 hectares of good agricultural land where the main crops are rice (60% of the valley), corn, and beans (18% of the valley), which require the use of great amounts of fertilizers and pesticides. Another important economic activity is wood extraction for pulp production for which there are large extensions of Eucalyptus globulus plantations in the central part of the basin (Marques et al., 2002; DGF, 2003). The main sources of pollution in this basin are collective sepias ditches (75%), wastewater treatment plants (18%), and direct discharges of urban sewage (7%) (INAG, 2003). We sampled a total of 75 sites distributed all over the basin and covering altitudinal, geological, and stream size gradients. The lowland main channel of the river was avoided due to sampling methodology restrictions and because its artificial configuration. Sampling, sorting, and identification of macroinvertebrates Samples were taken between June and September, 2001, by kick sampling with a hand net (0.3 x 0.3 m opening and 0.5 mm mesh size) covering a transept of approximately 6 meters in 296 Ferreira et al. 3 minutes. The transept was perpendicular to the riverbanks and was set to cover all major microhabitats. In addition, invertebrates were obtained from 10 different stones randomly retrieved from the streambed at each site. The stones were inspected in situ and invertebrates removed and placed in plastic bags. This is a modification of the methodology described by Alba-Tercedor & Sánchez-Ortega (1988). The handnet and “stone” samples were stored individually. Samples were conserved in 4% formalin until they were sorted. In the lab, each sample was washed through a sieve series (0.51.02.0 mm) to increase sorting efficiency. The macroinvertebrates were sorted and stored in 70% ethanol for further identification. Identification was made to family level except for mites (Hydracarina), Oligochaeta, and Hydridae. Particulate organic matter After removing the invertebrates, we determined the particulate organic matter of each sample (total area of approximately 6 x 0.3m) and fraction: fine fraction (FPOM: 0.5 - 1mm) and coarse fraction (CPOM: > 1 mm). Each fraction was dried in a stove at 70ºC for 24 h, weighed, placed in a muffle at 550ºC for 4 h and reweighed, to obtain ash free dry mass (AFDM). Environmental parameters and habitat characterization Variables measured at sampling sites included river width, mean depth (n=3 or 6/site), mean current velocity (n=3 or 6/site; VALEPORT 15277), dissolved oxygen (% and mg/L; WTW OXI 92), pH (JENWAY 3310), conductivity and total dissolved solids (WTW LF 330), temperature, and mean substrate size (9 or 18 substrate particles from the substratum/site). Habitat assessment was made based on habitat complexity - heterogeneity: a site with a variety of types (logs, branches, boulders and aquatic vegetation) and sizes of material was considered an optimal site; a site where structural types or sizes of material were less than optimum but where adequate cover was still provided was considered a sub optimal site; a site dominated by only one or two structural components was considered a marginal site; and a site with homogeneous, simple habitats (where silt and sand dominate) was considered a poor site. Pool quality was also assessed into 4 classes: optimal (river bed with all 4 possible combinations of depth (shallow / deep) and current velocity (low / high)), sub-optimal (river bed with 3 of the 4 possible combinations), marginal (two combinations) and poor (homogeneous pool) (EPA, 1999). Water chemistry At each site 600 mL of water were collected into acid washed plastic bottles. Water samples were transported to the laboratory in an ice chest. Water was analyzed for ammonia, nitrate, nitrite, sulfate, phosphate and chloride, using an ion analyzer (Dionex DX-120). We also measured alkalinity by titration to an end pH of 4.5 (A.P.H.A., 1995). The chemical water quality index was determined based on concentrations of the 6 ions. We considered a site to have bad chemical water quality if at least one ion was in excess, according with the Decree-law nº 236/98 of August 1st (Rocha & Vieira, 1998), which gives the threshold values for the different ions in water for human consumption. BMWP’ index For the application of the BMWP’index, we considered a family as present, when more than one individual was counted. The family Calamoceratidae (Trichoptera) is not considered in the original or adapted version of the index. However, in this study we found the Calamoceratidae family in 9 sites (> 1 individual), 3 of which with very high abundances. In consequence we included this family in the table and gave it a score of 6. This score is arbitrary and was achieved by looking at the most polluted site where the Calamoceratidae family appeared (Louriçal) and giving it the same Water quality in the Mondego basin 297 value as the most intolerant family present (Ancylidae), knowing that this can be over scoring this family. Based on BMWP` score we used the 5 biological water quality classes: I (BMWP’> 100), pollution free waters or high quality; II (BMWP’: 61-100), good quality; III (BMWP’: 36-60), moderate quality; IV (BMWP’: 16-35), poor quality and V (BMWP’< 15), strongly polluted or bad quality. The ASPT’value for each site was computed by dividing the BMWP’value of each site by the total number of BMWP’families present at the considered site (Alba-Tercedor, 1996). RESULTS Ninety-eight “families” of macroinvertebrates were identified. Fifty six percent of the total individuals were members of the families Chironomidae, Hydrobiidae and Baetidae. Forty-one families were very rare, together contributing with less than 1000 individuals (<1%) for a total of 137,000. Ten families were present at almost all sites, whereas 20 families were rare, having appeared in less than 5 sites (Table 1). The sites with higher number of individuals (> 4000) were Tentúgal (17711), Anobra (6807), 298 Ferreira et al. Table 1. Presence of macroinvertebrate “families” in the Mondego River basin. Presencia de “familias” de macroinvertebrados en la cuenca del río Mondego. Taxa Nº of sites Taxa Nº of sites Taxa Nº of sites Hydridae 2 Heptageniidae 42 Ecnomidae 13 Dugesiidae 26 Leptophlebiidae 55 Glossosomatidae 19 Planariidae 16 Oligoneuridae 3 Goeridae 15 Nemathelmintha 12 Leuctridae 60 Helichopsychidae 1 Ancylidae 47 Nemouridae 16 Hydropsychidae 55 Hydrobiidae 38 Perlidae 7 Hydroptilidae 13 Lymnaeidae 5 Aeshnidae 22 Lepidostomatidae 23 Physidae 16 Calopterygidae 17 Leptoceridae 41 Planorbidae 8 Cordulegasteridae 24 Limnephilidae 22 Valvatidae 2 Gomphidae 41 Philopotamidae 19 Corbiculidae 2 Lestidae 2 Phryganeidae 13 Sphaeriidae 11 Platycnemidae 11 Polycentropodidae 44 Unionidae 1 Aphelocheiridae 3 Psychomyiidae 39 Echytraeidae 11 Corixidae 20 Rhyacophilidae 35 Haplotaxidae 5 Gerridae 27 Sericostomatidae 35 Lumbricidae 31 Hydrometridae 9 Uenoidae 3 Lumbriculidae 56 Nepidae 6 Athericidae 38 Naididae 39 Notonectidae 6 Anthomyiidae 7 Tubificidae 26 Vellidae 3 Blephariceridae 2 Erpobdellidae 30 Dryopidae 15 Ceratopogonidae 22 Glossophoniidae 12 Dytiscidae 6 Chironomidae 75 Acari 63 Elmidae 64 Dixidae 8 Ostracoda 5 Gyrinidae 8 Dolichopodidae 1 Copepoda 6 Haliplidae 8 Ephydridae 4 Asellidae 5 Hydraenidae 23 Empididae 29 Cambaridae 6 Hydrochidae 11 Limoniidae 17 Atyidae 11 Hydrophilidae 27 Psychodidae 10 Gammaridae 1 Hydroscaphidae 2 Rhagionidae 5 Colembolla 1 Scirtidae 3 Sciomyzidae 1 Baetidae 71 Sialidae 16 Simuliidae 50 Caenidae 51 Beraidae 4 Tabanidae 10 Ephemerellidae 39 Brachycentridae 2 Tipulidae 12 Ephemeridae 10 Calamoceratidae 14 Vimieiro (5240), Porto da Carne (5161), Miranda do Corvo (5084), Ribamondego (4777), Carqueijal (4711), S. Miguel de Vila Boa (4612), and Louriçal (4454). The sites with lower number of individuals (< 200) were Liceia (35), Vila Moinhos (48), Nascente do Catarredor (83), Campizes (97), Casal Ermio (101), Vila Nova do Ceira (120), and Tondela (158) (see table 2). Six sites presented more than 50 different taxa: Ribamondego (61), S. Miguel de Vila Boa (59), Nespereira (59), Casal Mundão (58), Carqueijal (57), and Sabugueiro (53), and 10 sites presented less than 20 different taxa: Soure (8), Vila Moinhos (10), Liceia (13), Campizes (14), Nascente do Catarredor (15), S. Paio do Mondego (16), Casal Ermio (18), Foz do Alva (19), Tondela (19), and Casal da Rola (19). The sites with the lower number of individuals were also the ones presenting lower number of taxa, however the opposite didn’t happen for sites with higher number of individuals. This may be explained by the fact that in some sites there’s a high number of individuals, but most of them belonging to the same family. Water quality in the Mondego basin 299 Table 2. Stream name, total number of individuals, number of BMWP’taxa, number of intolerant taxa (sum of BMWP’taxa with a score of 7, 8 and 10), BMWP’value and ASPT’value for the 75 sites sampled in the Mondego river basin, in summer 2001. Nombre del río, número total de individuos, número de familias para BMWP’, número de taxa intolerantes (suma de taxa con valores de 7, 8 y 10 para BMWP’), valores de BMWP’y ASPT’para las 75 localidades muestreadas en la cuenca del río, en verano de 2001. Number Site Stream name No. No. BMWP’No.Intolerant BMWP’ASPT individuals taxa taxa 1 Botão Ribeira do Botão 1393 15 7 92 6.13 2 Lorvão Ribeira do Lorvão 2929 20 2 87 4.35 3 Rebordosa Ribeira do Lorvão 1293 26 8 150 5.77 4Tábuas Ribeira da Nossa Sra. da Piedade 931 14 7 100 7.14 5 Ponte do Espinhal Rio Dueça 551 19 8 119 6.26 6 Miranda do Corvo Rio Dueça 5084 13 3 67 5.15 7 Tourigo Ribeira de Marruge 423 19 10 128 6.74 8 Vila Moinhos Ribeira da Fraga 48 5 1 20 4.00 9 Vila Gozendo Ribeira da Fraga 493 18 5 99 5.50 10 Póvoa Ribeira de Mortágua 493 13 4 69 5.31 11 Vendas de Ceira 1 Rio Ceira 730 16 6 87 5.44 12 Vendas de Ceira 2 Rio Dueça 385 12 4 65 5.42 13 Foz de Arouce Rio Ceira 879 20 7 113 5.65 14 Casal de Ermio Rio Ceira 101 7 2 45 6.43 15 Múceres Rio de Múceres 981 25 14 168 6.72 16 Carqueijal Ribeira do Farreco 4711 32 12 172 5.38 17 Vila Nova de Ceira Rio Ceira 120 9 3 36 4.00 18 Góis Rio Ceira 407 15 4 81 5.40 19 Cabreira Rio Ceira 780 25 10 148 5.92 20 Candosa Ribeira do Carvalhal Sapo 1186 23 8 129 5.61 21 Lousã Ribeira de S.João 1604 21 10 140 6.67 22 Candal Ribeira do Candal 865 16 7 102 6.38 23 Nascente do Catarredor Ribeira do Catarredor 83 6 3 36 6.00 24 Golpilhares Ribeira Barroca da Tijosa 353 16 9 109 6.81 25 Santa Eulália Ribeira do Esporão 3018 17 2 72 4.24 26 Arrifana Ribeira do Vodra 1668 13 5 69 5.00 27 S.João da Boa Vista Ribeira da Tábua 841 27 13 166 6.15 28 Ançã Ribeira de Ançã 1468 16 3 69 4.31 29 Tentúgal Ribeira de Moinhos 17711 21 6 105 5.00 30 Liceia Rio do Fojo 33 7 1 25 3.57 31 Ferreira-a-Nova Ribeira das Barreiras 460 12 2 53 4.42 32 Fornos de Algodres Rio Mondego 646 13 6 80 6.15 The BMWP’index classified 14 sites (19%) as being moderately to highly polluted (classes IIIV), 22 sites (29%) as being of good quality (class II) and 39 sites (52%) as lightly or not polluted (class I) (Table 2 and Fig. 1). The BMWP’values are explained by both the type and number of taxa present in each site; so, a site with a high number of intolerant taxa (score: 7-10) will present a high BMWP’value (for example, Caldas de S. Paulo with 64% of intolerant taxa has an index value of 155); on the other hand, a site with a low number of intolerant taxa will present a low BMWP’value (for example, Soure and Campizes with 0% of intolerant taxa have an index value of 10 and 9, respectively). However, a site with a low number of 300 Ferreira et al. Table 2. (Continuation.) 33 Vila Franca de Serra Ribeira de Linhares 786 20 8 119 5.95 34 Ribamondego Ribeira do Freixo 4777 34 16 206 6.06 35 Vila Cortêz da Serra Ribeira do Paço 1056 26 10 153 5.88 36 Nespereira Ribeira de Gouveia 3748 27 6 126 4.67 37 Sandomil Rio Alva 741 19 8 114 6.00 38 Caldas de S.Paulo Rio Alva 1172 22 14 155 7.05 39 Alvoco das Várzeas Ribeira do Alvoco 409 16 7 100 6.25 40 Avô 1 Rio Alva 2263 20 8 113 5.65 41 Avô 2 Ribeira da Moura 1189 20 9 117 5.85 42 Foz do Alva Rio Alva 412 10 3 50 5.00 43 Vimeiro Rio Alva 5240 16 7 92 5.75 44 S. Paio do Mondego Ribeira de S.Paulo 825 8 2 40 5.00 45 Folques Ribeira de Folques 2615 29 13 177 6.10 46 Côja 1 Rio Alva 3743 18 9 114 6.33 47 Côja 2 Ribeira da Mata 2421 26 9 150 5.77 48 Vinhó Ribeira do Casal 2186 23 13 156 6.78 49 Porto da Balsa Ribeira da Castanheira 2026 21 10 134 6.38 50 Pombal Rio Arunca 1446 20 6 110 5.50 51 Ponte de Assamaça Ribeira de Valmar 1285 16 3 65 4.06 52 Louriçal Ribeira das Castelhanas 4454 12 0 45 3.75 53 Casal da Rola Ribeira de Carnide 462 10 1 41 4.10 54 Soure Rio de Anços 705 3 0 10 3.33 55 Vale dos Azares Ribeira da Cabeça Alta 2602 26 11 159 6.12 56 Trinta Rio Mondego 1289 19 12 131 6.89 57 Porto da Carne Rio Mondego 5161 20 6 102 5.10 58 Minhocal Ribeira dos Tamanhos 2199 21 8 119 5.67 59 Cardal Ribeira Quinta das Seixas 808 26 11 157 6.04 60 Muxagata Ribeira de Muxagata 1134 15 2 71 4.73 61 Póvoa da Rainha Rio Mondego 374 16 7 99 6.19 62 Sabugueiro Ribeira de Fervença 3954 27 12 162 6.00 63 Campizes Ribeiro do Gaio 97 4 0 9 2.25 64 Anobra Ribeira de Arzila 6807 15 3 77 5.13 65 Vila da Barba Ribeiro do Poto 472 24 11 146 6.08 66 Várzea Ribeira da Mata 1277 11 4 61 5.55 67 Travanca de S.Tomé Ribeira de Cabanas 809 20 9 120 6.00 68 Tondela Rio Dinha 158 8 2 43 5.38 69 Casal de Mundão Ribeira da Fraga 1686 31 10 171 5.52 70 Alcafache Rio Dão 572 16 6 90 5.63 71 Fail Rio Paiva 3999 11 1 46 4.18 72 Antas Ribeira do Carrapito 2255 19 8 115 6.05 73 Penalva do Castelo Rio Dão 332 16 9 105 6.56 74 S.Miguel da Vila Boa Ribeira de Satão 4612 31 14 183 5.90 75 Senhorim Rio do Saldo 412 14 2 61 4.36 intolerant taxa, but with a high total number of taxa may present a high BMWP’value (for example, Nespereira with only 22% of intolerant taxa, but with 27 BMWP’taxa, has an index value of 126); on the other hand, a site with a high percentage of intolerant taxa, but with a low total number of taxa can present a low BMWP’value (for example, Nascente do Catarredor with 50% of intolerant taxa, but with only 6 BMWP’taxa, has an index value of 36). However, it seems like the BMWP’values are more related to the total number of BMWP’taxa considered in the index calculation (R2= 0.9255) than to the type of taxa (number of intolerant taxa, R2= 0.8982). There was no relationship between the BMWP’values and the ASPT’values (R2= 0.4565). Also, there was no relationship between the number of individuals and the BMWP’values (R2= 0.0371). This could be explained by the fact that in some sites there was a large number of individuals (>4000) but most of them belonging to the same family; for example, in Tentúgal, Anobra and Louriçal, 98, 84 and 58 % of the individuals belong to the Hydrobiidae family; in Vimieiro, 81% of the individuals belong to the families Leuctridae, Hydropsychidae, Philopotamidae, Chironomidae; in Miranda do Corvo and Fail, 81 and 51% of the individuals belong to the Chironomidae family and in Porto da Carne 72% of individuals belong to the Simullidae family. The ASPT’values are more independent from the number of taxa than the BMWP’ values, but depend more on the type of taxa (% of intolerant taxa). Because the ASPT’values reflect the percentage of intolerant taxa (in general, increasing with the increase in the % of these taxa), it makes it possible to compare sites with similar BMWP’values, but that differ in the percentage of intolerant taxa (which could reflect differences in ambient conditions). For example, Nascente do Catarredor and Vila Nova de Ceira have the same BMWP’value (36) and the same number of intolerant taxa (3), but the 1st one has 6 BMWP’taxa and the 2nd one has 9 BMWP’taxa. This leads to a higher % of intolerant taxa in Nascente do Catarredor (50%) than in Vila Nova de Ceira (33%), which explains the Water quality in the Mondego basin 301 Figure 1: Biological water quality based on BMWP` index in the Mondego river basin. Calidad Biológica del agua en la cuenca hidrográfica del río Mondego, de acuerdo con el índice BMWP’. different ASPT’values (6 in the 1st one and 4 in the 2nd one), and is in agreement with the chemical water characteristics. Another example, is the case of Minhocal, Vila Franca da Serra, and Ponte do Espinhal, all with the same BMWP’ value (119) and the same number of intolerant taxa (8), but differing in the total number of BMWP’taxa (21, 20 and 19, respectively), which leads to a higher % of intolerant taxa in Ponte do Espinhal, followed by Vila Franca da Serra and Minhocal, which explains the different ASPT’values (6.26, 5.95 and 5.67 respectively). This tendency to find higher ASPT’ values in sites with the same BMWP’value but that only differ in the % of intolerant taxa, can be observed in all the cases were the sites have the same BMWP’value (see table 2). Polluted sites were located mainly in the Lower Mondego region, at low altitudinal sites (< 100m asl; just 29% of sites in class I), at > 50 Km from the source (just 21% of sites in class I), in river sections with a width superior to 10 m (just 42% of sites in class I) and lower amounts of CPOM (< 5g AFDM/kick sample; 50 % of sites in class I). Conversely, sites with high quality were located in altitudes superior to 400 m asl (87% of sites in class I), at < 10 Km from the source (64% of sites in class I), in river sections with a width inferior to 3 m (64% of sites in class I) and higher amounts of CPOM (>10g AFDM/kick sample; 67% of sites in class I). Biological water quality was also low at sites with fine sediment (sand; 0% of sites in class I), low pool quality (just 29% of sites in class I), and low habitat heterogeneity (33% of sites in class I). The Lower Mondego region is characterized by fine sediment, low pool quality, and low habitat heterogeneity. Globally, 44% of sites had low habitat heterogeneity and were distributed through the whole area. In terms of water chemistry (Table 3), polluted sites, according to the BMWP’, were the ones that had an alkaline pH (just 39% of sites in class I) and alkalinity superior to 20 mg/L (just 302 Ferreira et al. Table 3. Geographic (altitude and distance to the source), structural (mean substrate size and CPOM) and chemical (pH, alkalinity, conductivity, ammonia, nitrate, nitrite, chloride, phosphate and sulfate) parameters for the 75 sites sampled in the Mondego river basin, in summer 2001. *The critical threshold (Decreto-Lei 236/98) for the 6 ions is: NH4+: 0.05mg/L; NO3-: 25mg/L; NO2-: 0.01mg/L; Cl-: 25mg/L; PO42-: 0.4mg/L; SO42-: 5mg/L. Parámetros geográficos (altitud y distancia al nacimiento del río), estructurales (tamaño medio del sustrato y CPOM) y químicos (pH, alcalinidad, conductividad, amonio, nitratos, nitritos, cloro, fosfatos y sulfatos) para las 75 localidades muestreadas en la cuenca del río Mondego, en verano de 2001. *El límite máximo (Decreto-Lei 236/98) para los 6 iones es: NH4+: 0.05mg/L; NO3-: 25mg/L; NO2-: 0.01mg/L; Cl-: 25mg/L; PO42-: 0.4mg/L; SO42-: 5mg/L. Number Site Altitude Distance Width Mean CPOM pH Alkalinity Conductivity NH4+*NO 2-*NO 3-*Cl -*PO 42-*SO 42-* (m) to the (m) substrate (>1mm, g/ (mg CaCO3/L) (mS/cm) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) source (Km) size (mm) kick sample) 1 Botão 80 85.442 4.20 109.2 4.99 7.70 40 190.2 6.9 0 3.59 14.88 0 5.61 2 Lorvão 183 4.701 3.25 93.3 5.45 6.82 21 123.2 36.6 0.05 6.02 13.53 0 2.37 3 Rebordosa 82 8.819 2.00 94.8 3.44 6.60 18 140.7 18.8 0 6.50 16.76 0 2.58 4Tábuas 310 3.433 2.50 105.6 5.56 7.35 11 52.4 0.9 0 0.82 8.96 0 1.01 5 Ponte do Espinhal 181 15.174 6.90 171.7 3.98 7.97 82 498.0 0 0 0.00 14.34 0 30.24 6 Miranda do Corvo 118 33.271 10.50 90.6 2.87 7.76 87 407.0 1626.4 0.01 0.96 16.62 0.19 14.25 7 Tourigo 300 5.792 2.60 128.3 2.20 6.53 3 42.7 33.6 0 2.05 6.40 0 1.10 8 Vila Moinhos 107 12.346 3.90 134.2 6.36 7.05 23 81.9 11.8 0 1.36 9.01 0 1.58 9 Vila Gozendo 111 16.865 6.00 92.8 7.25 7.02 7 87.2 45.9 0 1.73 9.08 0 2.61 10 Póvoa 115 19.785 6.00 99.2 4.44 7.12 15 87.8 12.2 0 3.01 9.75 0 3.44 11 Vendas de Ceira 1 115 102.970 12.10 53.9 2.94 7.57 27 123.1 32.6 0 3.40 10.62 0 3.18 12 Vendas de Ceira 2 115 63.635 6.50 28.1 1.00 8.06 99 410.0 5.4 0 4.21 18.12 0 18.76 13 Foz de Arouce 84 86.560 26.80 77.2 2.96 7.90 14 102.9 5.1 0 4.35 8.73 0 2.87 14 Casal de Ermio 71 81.975 13.00 79.2 4.04 8.31 9 90.6 10.9 0 3.75 10.20 0 2.48 15 Múceres 71 0.834 5.70 74.7 5.21 6.71 7 60.8 0 0 3.29 8.01 0.09 1.44 16 Carqueijal 166 4.244 5.00 129.2 7.14 6.27 7 73.5 0 0.04 7.69 11.11 0.07 1.48 17 Vila Nova de Ceira 138 69.472 12.60 144.2 2.00 7.23 11 76.3 8.1 0 4.01 7.42 0 2.49 18 Góis 201 63.170 6.50 164.3 6.83 7.41 15 63.6 18.2 0 1.67 6.00 0 1.88 Water quality in the Mondego basin 303 Table 3. (Continuation.) 19 Cabreira 290 31.407 6.50 118.1 1.50 7.32 11 55.5 0 0 1.77 5.75 0 1.79 20 Candosa 330 6.500 2.70 91.1 16.05 8.24 12 43.5 0 0 0.51 5.59 0 0.90 21 Lousã 260 5.806 3.95 96.0 5.54 7.07 8 53.3 0 0.05 1.09 9.43 0 1.12 22 Candal 620 1.502 2.00 98.9 3.32 7.09 5 31.0 0 0 0.44 4.75 0 0.76 23 Nascente do Catarredor 730 0.546 2.60 83.3 4.69 6.82 6 34.9 0 0 1.01 5.45 0 0.69 24 Golpilhares 219 0.809 2.10 91.1 1.16 7.76 17 70.2 0 0 0.58 8.96 0 1.48 25 Santa Eulália 392 7.627 1.85 94.4 6.71 7.07 24 134.7 724.2 0.09 4.03 15.75 0 0.247 26 Arrifana 437 5.179 1.80 105.6 2.68 6.89 14 115.0 33.0 0 7.67 10.86 0 4.71 27 S.João da Boavista 309 3.268 1.55 76.7 1.70 7.27 12 98.2 0 0 4.19 16.20 0 2.08 28 Ançã 30 16.902 4.10 16.0 10.22 7.79 164 813.0 16.9 0 12.96 19.94 0 4.47 29 Tentúgal 36 6.415 2.30 18.9 2.83 8.04 141 559.0 0 0 13.69 22.46 0 5.26 30 Liceia 22 7.380 2.25 sand 1.46 7.92 43 421.0 38.3 0 4.82 28.02 0 6.24 31 Ferreira-a-Nova 27 6.601 3.95 25.6 3.74 7.25 31 223.0 16.8 0 6.90 25.76 0 9.17 32 Fornos de Algodres 345 78.993 5.70 138.9 2.37 8.03 21 83.0 0 0 0.09 7.85 0 1.38 33 Vila Franca de Serra 350 19.090 3.67 35.0 9.44 6.84 14 86.4 229.4 0.01 3.90 9.20 0.20 1.91 34 Ribamondego 337 16.763 6.40 115.3 10.15 7.01 16 77.9 15.1 0 2.66 9.55 0.54 1.83 35 Vila Cortêz da Serra 446 4.018 3.20 100.0 6.35 6.89 11 77.2 0 0 2.50 9.98 0 1.66 36 Nespereira 488 10.188 2.60 9.6 5.61 7.21 31 161.8 6.6 0.05 18.60 20.20 0.67 4.22 37 Sandomil 318 25.873 27.00 136.9 3.19 7.31 9 24.1 7.2 0 0.99 3.38 0 0.40 38 Caldas de S.Paulo 287 32.741 16.00 165 4.51 7.15 5 31.9 4.4 0 1.55 4.31 0 0.65 39 Alvoco das Várzeas 279 30.409 8.00 144.2 2.78 7.22 13 47.0 14.7 0 2.20 5.31 0 0.99 40 Avô 1 237 42.097 6.37 167.2 1.53 7.86 9 45.1 13.4 0 2.15 7.19 0 0.85 41 Avô 2 237 11.374 7.90 133.3 3.79 7.62 13 63.2 7.4 0 2.64 6.39 0 1.52 42 Foz do Alva 232 115.447 8.40 81.9 2.08 7.41 10 50.1 21.7 0 0.93 4.28 0 0.82 43 Vimeiro 97 108.625 30.00 135.6 2.18 7.32 10 49.0 11.9 0 1.46 5.44 0 1.04 44 S. Paio do Mondego 129 5.936 3.20 118.4 5.17 7.07 12 88.0 0 0 0 15.30 0 1.82 45 Folques 180 7.239 3.60 126.5 1.41 7.47 21 96.8 21.6 0 0.67 9.51 0 3.42 46 Côja 1 178 56.291 29.00 95.6 2.78 7.33 9 49.2 0 0 2.75 6.01 0 1.10 47 Côja 2 191 15.896 3.85 106.7 3.31 6.97 13 77.6 0 0 2.56 8.59 0 2.12 48 Vinhó 306 4.282 1.75 38.3 1.57 7.05 15 75.5 0 0 1.05 9.76 0 2.00 49 Porto da Balsa 634 5.573 2.50 83.3 0.73 7.61 5 38.2 0 0 0.64 5.81 0 0.83 50 Pombal 68 21.592 8.60 81.4 2.49 7.98 94 405.0 42.9 0.13 3.83 23.49 0 4.38 51 Ponte de Assamaça 97 11.708 3.00 101.7 3.50 7.63 170 542.0 49.5 0 0.22 13.58 0 2.59 52 Louriçal 17 6.562 3.00 47.6 1.01 7.87 56 362.0 15.7 0.06 20.56 40.80 0.41 10.48 53 Casal da Rola 19 23.900 5.70 sand 1.20 7.5 61 306.0 29.2 0.14 11.72 43.60 0 4.64 54 Soure 27 24.391 14.00 sand 0.07 7.88 126 598.0 36.0 0.08 9.77 39.40 0 5.80 55 Vale dos Azares 473 14.718 2.80 65.0 7.37 6.57 15 55.5 0 0 0.55 6.46 0 1.37 56 Trinta 800 33.609 5.00 150.6 1.10 7.10 7 25.7 48.2 0 0.35 2.94 0 0.36 57 Porto da Carne 455 51.188 14.90 121.7 4.51 6.76 8 51.4 23.5 0 1.07 3.97 0 1.17 58 Minhocal 460 15.044 3.50 58.9 5.35 6.61 26 101.1 0 0 0.71 63.71 0.37 19.00 59 Cardal 437 7.503 3.00 100.0 3.12 6.87 13 58.8 51.3 0 2.62 5.80 0 1.26 60 Muxagata 380 14.738 6.50 97.8 2.21 6.45 20 83.1 0 0 0.13 8.86 0 1.12 61 Póvoa da Rainha 260 99.152 10.20 173.3 2.12 7.41 22 87.2 0 0 0 8.22 0 1.14 62 Sabugueiro 1040 5.277 2.70 111.1 1.57 6.90 5 19.2 43.5 0 0.59 2.62 0 0.26 63 Campizes 30 5.924 4.70 sand 2.19 7.50 119 682.0 0 0.02 5.06 30.28 0 12.45 64 Anobra 25 13.318 1.80 53.3 11.17 8.05 16 762.0 36.8 0.12 15.54 21.94 0 42.71 65 Vila da Barba 229 6.748 2.85 16.1 7.91 5.96 15 185.7 0 0 19.35 21.37 0 4.14 66 Várzea 136 23.969 2.75 122.2 3.54 6.53 12 111.2 15.7 0 8.22 15.34 0 2.58 67 Travanca de S.Tomé 247 11.000 2.20 128.9 9.22 6.01 17 156.0 18.7 0.03 0 17.05 0 5.69 68 Tondela 250 22.072 7.30 51.9 6.32 6.49 9 81.3 36.6 0 5.32 10.58 0 1.31 69 Casal de Mundão 547 2.445 1.90 63.3 9.76 6.61 21 104.4 3.0 0 1.64 6.02 0 0.87 70 Alcafache 238 50.579 7.00 221.4 1.38 7.04 19 114.5 10.1 0 0.58 6.59 0 1.50 71 Fail 325 19.548 3.00 60.6 4.26 7.27 68 593.0 5631.3 0.21 10.36 81.00 5.31 10.78 72 Antas 538 18.337 4.50 112.8 0.04 6.89 15 66.7 0.2 0 0.76 9.96 0 0.72 73 Penalva do Castelo 388 27.474 2.00 105.5 4.32 6.76 8 78.6 4.4 0 0 10.05 0 0.46 74 S.Miguel da Vila Boa 405 15.114 3.00 74.4 110.40 7.07 22 136.6 0 0 5.28 15.19 0 2.02 75 Senhorim 369 19.533 3.30 126.4 3.51 6.19 25 136.6 19.4 0 0.50 21.11 0 11.24