Variables used for the calculation of
Abstract
The Biological Monitoring Working Party (BMWP) is among the most used bioassessment indices for aquatic ecosystems quality assessment, which assigns scores to each macroinvertebrate taxa according to their sensitivity to organic pollution. However, BMWP scores must be calibrated to each geographical and ecological conditions. In this study, we obtain statistically derived scores of sensitivity for macroinvertebrates taxa from Neotropical Mexican rivers, Apatlaco and Chalma-Tembembe rivers, Balsas Basin. We obtained water samples and aquatic macroinvertebrates in four sampling campaigns (dry and rainy seasons). Physicochemical parameters and the abundances of the aquatic macroinvertebrates were used for the BMWP index calibration, which was performed in steps obtaining: the physicochemical quality index (Pcq), incorporation of abundances classes of macroinvertebrates taxa in the corresponding Pcq interval and the determination of bioindication values for each macroinvertebrate family. The BMWP calibrated index was validated and tested for the geographical range extension. The BMWP scores for Chalma-Tembembe River (located in agricultural areas) showed bad polluted to regular and moderated polluted categories. The urban river zone of Apatlaco River showed: bad, very polluted to very bad categories. The BMWP calibrated is a suitable biomonitoring tool, allowing the detection of those zones that needs urgently a management and recovery plan.
Keywords
- water quality assessment
- biomonitoring tool
- macroinvertebrate sensitivity
- land use
- bioindication values
- water quality categories
1. Introduction
In the framework of the World Economic Forum, the “Water Crisis” is positioned as the highest concern global risk for the next 10 years [1]. In this sense, water quality and management of freshwater ecosystems are one of the main challenges worldwide [2]. However, these ecosystems face impacts and degradation that are result of human population increase and agricultural and industrial development [3]. Consequently, freshwater ecosystems and their biota are considered as the most endangered and threatened worldwide [4]. In developing countries, there is an extremely high population growth, increasing industrialization and urbanization processes, with severe and constant changes in land use, whereby the freshwater ecosystems are highly impaired [5]. Rivers crossing different land uses (urban, industrial and agricultural) are the most threatened by anthropogenic activities [5]. The threat to freshwater systems, in particular in developing countries, make evident an urgent need for developing tools for the assessment and classification of aquatic conditions in order to manage water resources and bring them a sustainable management.
Biomonitoring is considered as the most appropriate method for environmental studies and for the control of water quality, due to that living organisms are excellent biosensors of the physicochemical and biological characteristics of water [6]. The aquatic macroinvertebrates have been used as bioindicators because they have a wide range of habitats and sensitivity to environmental pollution and other types of stressors, including sediment [7]. Thus, the macroinvertebrate assemblages change in response to environmental disturbances in predictable ways including a strong reduction in species and abundance in impacted areas and more tolerant species predominate; whereas, sensitive species are only present in environments with the least impact or un-impaired conditions. Moreover, biomonitoring integrate information over longer periods of time and better represent the responses of aquatic habitats providing information concerning the present state and the past trends in environmental conditions [8].
The Biological Monitoring Working Party (BMWP) is among the most used bioassesment index in Europe, which was originally developed in the UK in 1976 [9] and it has been used by the regulatory authorities in the UK as the basis of their river invertebrate status classification system since 1980. This index assigns scores to each macroinvertebrate taxon according to their responses to oxygen deficits caused by organic pollution. The analysis of these pollution-induced responses allows the calculation of sensitivity values by the different groups of organisms. Because of its ease of use and low cost, the BMWP index has been used in many other countries in Africa, Asia, Oceania and Latin America [10]. Nevertheless, the BMWP scores for each taxon must be calibrated to each ecological region since the taxonomic composition, ecological, zoogeographic and anthropogenic conditions promote important geographical differences.
Additionally, the scale to ranking water conditions must be adapted for each particular condition. In Latin America, attempts have been made to develop regional indices [5]. In México, the water quality indicators used by the National Commission of Water are fecal coliforms, biochemical oxygen demand, chemical oxygen demand and total dissolved solids [11]; unfortunately, biomonitoring is not included in the current legislation, while information on bioindication is scarce [12]. However, main urban zones of Mexico exert a high rate of changes in land use and deforestation for agricultural, industrialization and urban expansion provoking serious damages in water bodies [13]. Consequently, there is a need for a tool that considers both, biotic and abiotic variables and their relationships to assess the river water quality.
The aim of this study is to obtain the statistically derived scores of sensitivity for aquatic macroinvertebrates taxon for Neotropical Mexican rivers (Apatlaco and Chalma-Tembembe rivers, Balsas Basin). This chapter presents the calibration of the BMWP index based on Riss et al. [14] with some modifications, using physical, chemical and biological data from Apatlaco and Chalma-Tembembe rivers. This index, besides being an easy-to-use tool, allows for the implementation of a permanent biomonitoring network.
2. Materials and methods
2.1. Study area
Apatlaco and Chalma-Tembembe rivers are located in the Balsas Basin (Figure 1a), one of the largest catchment areas in Mexico (area of 117,405 km2) [15]. Both rivers are in the same zoogeographic region (Neotropical), which belongs to the Ecoregion Balsas Complex and belongs to the Biogeographic Province “Depresión del Balsas,” particularly to the “Alto Balsas” [15]. The Chalma-Tembembe River is formed by the Chalma and Tembembe rivers; the first has a length of 70 km and the second of 50.72 km. The Chalma River joins the Tembembe River at its lower reaches. The Chalma-Tembembe subbasin has a mean annual rainfall around 600 mm. The area consists of tropical deciduous forest (≈47% of landcover), with some areas of rain-dependent and irrigated agricultural use. The strong pressure from agricultural activities has favored land use changes and the loss of the original vegetation [15]. Six study sites were selected in Chalma-Tembembe: El Arco (I), La Loma (II), El Platanar (III), Casa de la Escuela (IV), Coatlán (V) and Hacienda de Cuautlita (VI) (Figure 1a). The Apatlaco River has a length of 63 km, with annual rainfall from 850 to 1500 mm. The natural vegetation has been highly fragmented and transformed, with only 27% of the original area of tropical deciduous, coniferous and oak forest remaining. Moreover, an important urban-industrial corridor (Cuernavaca corridor), runs alongside the river. The activities in the vicinity of the river include agriculture, lumber forestry, hunting and fishing [15]. Nine study sites along the main river channel (Apatlaco River) were selected: Las Truchas (VII), El Pollo (VIII), El Rayo (IX), El Encanto (X), Salida Panochera (XI), Xochitepec (XII), Alpuyeca (XIII), Xoxocotla (XIV) and Zacatepec (XV) and two more along the westerly tributary: Buenavista 1 (XVI) and Buenavista 2 (XVII), study sites located before and after the effluent of a wastewater treatment plant and three more along the easterly tributaries: El Texcal (XVIII), La Gachupina (XIX) and Las Juntas (XX), resulting in a total of 14 sampling sites (Figure 1a). In both rivers, four sampling campaigns were undertaken (the dry season in December 2012 and February-March 2013 and the rainy season in August-September 2012 and June 2013).
2.2. Water quality measurements and water quality index
For each site and sampling period, some variables were recorded: altitude (masl), water temperature (°C), conductivity (µS/cm), pH, salinity (PSU), dissolved oxygen (DO mg/L O2) and turbidity (NTU), using a Quanta® multiparameter probe. Air temperature was recorded with a 45118 EXTECH anemometer. Water samples were transported to the laboratory in refrigerated and dark conditions. Biochemical oxygen demand (BOD5 mg/L O2), chlorides (mg/L Cl), alkalinity (mg/L CaCO3) and total and fecal coliforms (MPN/100 mL) were determined according to [16]. Nitrite (mg/L NO2), nitrate (mg/L NO3), ammonia (mg/L NH3), total nitrogen (mg/L TN), orthophosphate (mg/L PO4), total phosphorus (mg/L TP), hardness (mg/L CaCO3), sulfates (mg/L SO42−) and color (U Pt-Co) were analyzed using a Hach DR 2500 spectrophotometer. Additionally, the DO saturation (%) was computed. The water quality index (WQI) proposed by Dinius [17] was calculated, which range from 0 to 100; 100 is excellent and 0 is strongly polluted.
2.3. Macroinvertebrate sampling
Aquatic macroinvertebrates were sampled at each sampling site and season with a multi-habitat monitoring system [18], along a section of 100 m length to incorporate local habitat variation (fast flowing riffles, pools, submerged vegetation and riparian vegetation). An area of 1 m2 was sampled for each type of habitat. Triplicate samples for each type of habitat, with a 10-min collecting effort, were collected and pooled for analysis. The samples were taken using a kick net for fast-flowing riffles and pools, while type-D nets for submerged and riverine vegetation, all nets with a mesh size of 500 µm. Organisms collected were preserved with 70% alcohol. Taxonomic identification at the family level was conducted using stereomicroscopes (Nikon C-Leds) and with the use of keys [19, 20].
2.4. BMWP index calibration
2.4.1. Data processing
The BMWP index is calculated by adding up the individual tolerance scores of aquatic macroinvertebrates at family taxonomic level present at a sample site. We calibrate the tolerance scores of the aquatic macroinvertebrates in several steps [14]: (1) obtaining a physicochemical quality index (
2.4.2. Mathematical formulation
The physicochemical quality index (
Each
The
2.4.3. BMWP scores for macroinvertebrates families
To assign bioindication values to the different macroinvertebrates families, a data matrix of sampling sites
For each family of macroinvertebrates, the abundance class data were pooled within each
2.5. Definition of BMWP water quality categories
The water quality category ranges for the BMWP values were assigned following [21]. The median value of the data set of the reference sites was calculated. Scores above this median value will correspond to the “Excellent” quality category, while values that fall between the median and the tenth percentile of that distribution are considered to be in the “Good, not sensible affected” quality category. Values below the tenth percentile were subdivided into four equal parts, which correspond to the categories “Regular,”“Bad, polluted,”“Bad, very polluted,” and “Bad, extremely polluted.” The names assigned to each of the water quality categories with some modifications were those proposed by Alba-Tercedor [29]. The selection of reference conditions included physical, chemical and biological criteria (WQI,
2.6. BMWP statistical validation
The validation process was performed using three approaches. First, a score prediction test, proposed by Armitage et al. [31], with the average per study site of BMWPobserved
For the second validation approach, the degree of fit of the model for the BMWPobserved
A third approach for the index validation and for the assessment of the geographical extension of the BMWP calibrated was performed with additional information that was obtained from the National Agency for Water in México (CONAGUA), data included aquatic macroinvertebrates collected in the county of Morelos. For the index validation, nine sites within the Apatlaco subbasin were considered: Arriba Chalchihuapan, Arroyo Chapultepec, water treatment plant (WTP) Acapatzingo, WTP Emiliano Zapata, WTP El Rayo, Apatlaco-Xochitepec, WTP Xochitepec, WTP Zacatepec and Tlaltenchi (Figure 1b). For the geographical extension, data from CONAGUA of seven sites in three subbasins were considered: Amacuzac subbasin, sites Chontalcoatlán, Amacuzac and Arroyo Salado; Cuautla subbasin, sites Barranca Santa María and Papayos; and Yautepec subbasin, sites Pedro Amaro and WTP Jojutla. These sites belong to the Balsas Basin and the last three subbasins are adjacent to the two rivers monitored in this study (Figure 1b). The monitoring team of CONAGUA used D-nets (mesh size of 500 µm), a multihabitat sampling and each habitat was sampled in 1 m2, with three replicates. Based on the calibrated scores for aquatic macroinvertebrates, the BMWP scores were calculated for each site of the data set from CONAGUA and these scores were included in the previous model generated with
2.7. Statistical analysis
WQI and BMWP values are presented as the mean values of each study site for the four monitoring campaigns. Mean values were also calculated for each study season taking into account the values of all the studied sites. Significant differences between sites and seasons were detected with a bivariate analyses of variance (ANOVA), followed by Student-Neuman-Keuls multiple comparison tests (if the data were normally distributed as well as homoscedastic), or Kruskal-Wallis test for nonparametric data, both
3. Results
3.1. Water quality index
For the Chalma-Tembembe River, mean values of WQI fluctuated from 52 to 74 (Figure 2), from slightly polluted to acceptable for human consumption; however, no significant differences between study sites (
3.2. Physicochemical quality and bioindication values
The factor analysis showed a total of 60.32% of explained variance for the first two axes. The parameters that showed a significant correlation, either positive or negative, in the first two axes of the factor analysis and which were considered as qualifying variables for this study,
The bioindication values for each aquatic macroinvertebrates family (obtaining the fifth percentile of the abundance class distributions along the
Variable | F1 (37.24%) | F2 (23.08%) |
---|---|---|
Nitrates (mg/L) | 0.207 | |
Nitrites (mg/L) | 0.195 | |
Ammonium (mg/L) | 0.297 | |
Total N (mg/L) | 0.600 | |
Total P (mg/L) | 0.392 | |
Sulfates (mg/L) | −0.525 | |
Color (Pt-Co) | 0.472 | |
Alkalinity (mg/L) | −0.203 | |
Chlorides (mg/L) | 0.166 | |
BOD (mg/L) | 0.516 | |
DO (mg/L) | −0.152 | |
Conductivity (μS/cm) | −0.522 | |
% DO | 0.024 | |
% Explained variance | 37.24 | 23.08 |
% Accumulated variance | 37.24 | 60.32 |
3.3. BMWP index and BMWP water quality classes
The BMWP values assessed with the calibrated bioindication values fluctuated from 2 to 109, but showed no statistical differences (
Taxon | Bioindication value | |
---|---|---|
Cordulegastridae Heptageniidae |
Lepidostomatidae Perlidae |
10 |
Caenidae Gyrinidae |
Scathophagidae | 8 |
Aeshnidae Blaberidae Cambaridae Helicopsychidae Hydrobiosidae Naucoridae |
Philopotamidae Pseudothelphusidae Ptilodactylidae Saldidae Scirtidae |
7 |
Corbiculidae Dixidae Dryopidae Ephydridae Glossosomatidae Gordiidae |
Hydrobiidae Hydroptilidae Leptophlebiidae Polycentropodidae Pyralidae Thiaridae |
5 |
Ancylidae Asellidae Calopterygidae Gomphidae Hirudinea Hyallelidae Hydropsychidae |
Leptohyphidae Physidae Planorbidae Psychodidae Sphaeriidae Stratiomyidae Turbellaria |
4 |
Corydalidae | Elmidae | 3 |
Belostomatidae Coenagrionidae Hebridae Staphylinidae |
Libellulidae Tabanidae Tipulidae |
2 |
Baetidae Chironomidae Corixidae Culicidae Dytiscidae Hydrophilidae Lestidae |
Muscidae Nepidae Notonectidae Oligochaeta Simuliidae Syrphidae |
1 |
The multiple linear regression equation of the quality test for predicting the BMWP scores is presented below (with
3.4. Index validation and regional extrapolation
The BMWP values for their validation and regional extrapolation (Figure 5) span the whole range of water quality classes: from “Very bad, extremely polluted” (Tlatenchi) to “Excellent” (Arriba Chalchihuapan).The observed and expected BMWP values for the nine index validation sites in the Apatlaco River and the seven regional in the neighboring river subbasins (Amacuzac, Cuautla and Yautepec) were calculated using the previously BMWP scores calibrated and the derived multiple linear regression model. Four sites of the BMWP values lay outside the confidence limits (
The index validation, adding nine independent sites, validated the regression model as a satisfactory indicator for river water quality in the Apatlaco River for the BMWP index (
4. Discussion
4.1. Water quality index
In Latin America, WQIs have been used to compare rivers in a country-wide dimension, the effect of a city discharge and also for a spatial and historical water quality assessment [13]. However, in Apatlaco and Chalma-Tembembe rivers, the WQI scores do not detect significant differences neither in the spatial nor in the temporal dimensions. In consequence, in this study, the WQI do not allow the detection of the most impaired portions of the rivers.
4.2. The BMWP index
Nowadays, the BMWP index is widely used in various countries of Europe (UK, Spain, Portugal, Turkey, Poland, among others) [8]. This index, also, has been used in some countries of Latin America [5, 14]. However, the procedure for calibrating the scores of the BMWP index has not been detailed. In the present study, we follow several steps for calibrating the BMWP values. The first step included the calculation of the minimum tolerance scores for each macroinvertebrate family from the study area. The
4.3. The BMWP index and BMWP water quality classes
While the WQI scores showed small differences among study sites, the BMWP index showed a wider variation, making evident that the latter has a higher level of sensitivity, as it was able to register fine and important differences between study sites, which were not evidenced by the WQI (Figure 5). The sensitivity of the BMWP index is related with the procedure to assign the values for the water quality classes. For this step, the reference sites are indispensable. The BMWP index was able to detect the pristine condition of “Las Truchas,” the clean river reference site, located inside an undisturbed oak forest, showing the highest richness score of this study site. Furthermore, this site showed the presence of the family Perlidae, a bioindicator of excellent water quality. Lakew and Moog [30] stated that a reference site must meet both abiotic and biotic requirements; the same authors consider a reference site as the least impaired site characterized by selected physical, chemical and biological characteristics. Las Truchas site reached the higher
The bioindication values of the aquatic macroinvertebrate families do not always match completely from one country to another, which can be due to the variations in taxonomic tolerances of each basin and biogeographic region and to the method of assigning bioindication values, which in most cases is unknown, generating some uncertainty in the scores assigned to each family. However, there are families of aquatic macroinvertebrates characteristic of very healthy environments, as is the case of the Perlidae with a score of 10; or in extremely hostile conditions, the midges and lumbriculids with score values of 1 [14]. In the present study, the wide distribution of families in different intervals of
Our results show that the BMWP index has a good discriminating capacity; nevertheless, doubtless, any index has to be adjusted, as demonstrated here, to the particular ecological conditions of each region in order to generate a powerful and representative biomonitoring tool.
4.4. Index validation and regional extrapolation
A third step in our procedure included the statistical index validation process, which produced multiple linear regression models for the BMWP index with good results in general. The obtained
For the index validation, we included a procedure with the addition of nine independent sites, validating the regression model as a satisfactory indicator for river water quality in the Apatlaco River for the BMWP index (
The fourth step in our procedure included the range extrapolation analysis, where the multiple linear regression model was extended to study sites from Amacuzac, Cuautla and Yautepec subbasins for BMWP index, in this case we obtained lower correlation and
Therefore, the calibrated BMWP scores and the proposed water quality classes of this study can be used as a tool for the biomonitoring of water quality in the Apatlaco and Chalma-Tembembe rivers and even the subbasins Cuautla, Yautepec and Amacuzac. Furthermore, our ranges for water quality class showed also a good fit for the qualification of study sites and the spectrum of the land use conditions [36]. The studied rivers showed that a great portion of the rivers Apatlaco and Chalma-Tembembe (nine study sites), with agriculture as the main land use, is qualified as: bad polluted to regular, moderated polluted, while another great portion of the Apatlaco River mainly located in urban zones is qualified as bad, very polluted to very bad. The BMWP calibrated and the water quality assignations resulted to be suitable to assess water categories in the studied rivers. Our results make evident that Apatlaco River needs urgently a management and recovery plan.
5. Conclusions
The procedure followed in this study, included four steps, resulted to be efficient, reliable, repeatable and suitable for the development of a robust index to assess the water quality for rivers in the Neotropical region of México.
The tolerance values of the BMWP index developed in this study and their respective water quality classes can be applicable without modification to the adjacent river subbasins of the Apatlaco River, such as the subbasins Cuautla, Yautepec and Amacuzac.
The aquatic invertebrates and the BMWP index calibrated proved to be excellent indicators of water quality, being very sensitivity to differentiate the degree of pollution, different land uses and degrees of perturbation and thus, assign a water quality class that is also strongly related with the land use of their surrounding area.
These results make evident that the BMWP index calibrated is a suitable tool for the biomonitoring in the Neotropical region, where changes in land use have exerted strong impacts on aquatic resources and where the assessment of ecological conditions in freshwater ecosystems is urgently needed in a relatively simple, effective, reliable, fast and economical way. The procedure followed in this study to calibrate the BMWP is recommended and can be extended to other Neotropical rivers.
Acknowledgments
We thank to the join Fund of the National Science and Technology Council (CONACyT) and the Morelos Government, Project FOMIX CONACyT 173996, as well as the Research and Postgraduate Studies Secretariat (SIP Instituto Politécnico Nacional SIP20121087).
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