Ecological assessment of Portoviejo river basin (Ecuador) [PDF]

Faculty of Bioscience Engineering Academic year 2015 – 2016

Ecological assessment of Portoviejo river basin (Ecuador)

Juan Antonio Dueñas Utreras Promotor: Prof. dr. ir. Peter L.M. Goethals Tutor: MSc. Marie Anne Eurie Forio

Master’s dissertation submitted in partial fulfillment of the requirements for the degree of Master of Science in Environmental Sanitation

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COPYRIGHT PAGE

I, JUAN ANTONIO DUEÑAS UTRERAS, herewith declare that this dissertation is the result of my own work and the submission of this dissertation is only made here in this university. Other studies used here have been duly acknowledged through references of the authors and served as information resources.

The author and the promoter give authorization to consult and copy parts of this dissertation for personal use only. Any other use of this dissertation is subject to copyrights laws, and the source should be specified after having received the written permission from the author and the promoter.

Laboratory for Environmental Toxicology and Aquatic Ecology Department of Applied Ecology and Environmental Biology Faculty of Bio-engineering Sciences, Ghent University Jozef Plateaustraat 22, B-9000 Gent (Belgium) Tel. 0032 (0)9643765 Fax. 0032 (0) 9 2644199

………………………………………… 19/08/2016 Prof. Dr. ir. Peter L.M. Goethals (Promoter) Email: [email protected]

…………………………………………… 19/08/2016 Juan Antonio Dueñas Utreras (Master thesis author) Email: [email protected]

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ACKNOWLEDGMENTS

First at all, I want to thanks God who has given to me the strength to remain firm in my convictions and who holding me in my moments of sadness. To my Promotor Prof. Peter Goethals and my tutor Marie Anne Eurie Forio, who have contributed to my training, thanks for all your help in the realization of this thesis. Special thanks to the Ministry of Higher Education, Science and Technology and Innovation (SENESCYT) of Ecuador for the scholarship that was awarded in 2014 that made me able to realize my dreams of studying abroad. The Technical University of Manabí, institution where I work, thank you very much for the trust. To my beloved Erika for giving me unconditional love and constant support at all times, my little Lina for giving me their love and happiness when I needed it. My mother, who provide their prayers and affection throughout my life, to each of the members of my family, my grandfather, uncles, sisters, nephews, nieces and cousins. To my friends in Ghent, who tolerated my jokes, for his words of encouragement and especially for his sincere friendship in these two years where they became my family in foreign land. To Anne-Marie and Guy for accepting me into your home and make me feel at home. My eternal gratitude.

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TABLE OF CONTENT

COPYRIGHT PAGE .............................................................................................................................. i ACKNOWLEDGMENTS ...................................................................................................................... ii TABLE OF CONTENT ......................................................................................................................... iii LIST OF ABBREVIATIONS ................................................................................................................... v ABSTRACT ....................................................................................................................................... vii 1. INTRODUCTION ............................................................................................................................ 1 2. LITERATURE REVIEW..................................................................................................................... 3 2.1 Water Quality in freshwater ecosystems .............................................................................. 3 2.2 Quality indices ....................................................................................................................... 3 2.2.1 Biological Indices ............................................................................................................ 3 2.2.2 Physicochemical water quality ....................................................................................... 6 2.3 River Continuum Concept (RCC) ............................................................................................ 8 2.4 Impacts of pollution............................................................................................................. 11 3. MATERIALS AND METHODS............................................................................................... 13 3.1. Study area ........................................................................................................................... 13 3.2 Data collection ..................................................................................................................... 14 3.2.1 Macroinvertebrates ...................................................................................................... 14 3.2.2. Physicochemical characteristics .................................................................................. 14 3.2.3. Hydromorphological characteristics............................................................................ 15 3.3. Chemical and ecological assessment.................................................................................. 15 3.3.1. Chemical indices .......................................................................................................... 15 3.3.2. Ecological indices ......................................................................................................... 16 3.4. Scatter plots and boxplots .................................................................................................. 17 3.5. Data analysis ....................................................................................................................... 18 4. RESULTS ......................................................................................................................................19 4.1 Physicochemical results ....................................................................................................... 19 4.2. Macroinvertebrates ............................................................................................................ 20

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4.3 Water Quality Indices .......................................................................................................... 23 4.4. Gradients of environmental variables from mouth to source. .......................................... 25 4.5. Impacts of dams ................................................................................................................. 29 4.6. Impact of Land use ............................................................................................................. 31 4.7 Effect of municipal waste water treatment plants ............................................................. 34 5. DISCUSSION ................................................................................................................................36 5.1 Water quality ....................................................................................................................... 36 5.2 River continuum/ Gradients from source to mouth ........................................................... 37 5.3 Impacts ................................................................................................................................ 39 5.3.1 Impact causes by dams in Portoviejo river ................................................................... 39 5.3.2 Impact of Portoviejo river cause by land use ............................................................... 40 5.3.3 Effects of municipal wastewater treatment plant in the Portoviejo river basin .......... 41 6. CONCLUSIONS AND RECOMMENDATIONS ................................................................................43 6.1 Conclusions .......................................................................................................................... 43 6.2 Recommendations............................................................................................................... 44 REFERENCES ...................................................................................................................................45 APPENDICES....................................................................................................................................54

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LIST OF ABBREVIATIONS BMWP:

Biological Monitoring Working Party

BOD:

Biological Oxygen Demand

BOD5:

Five days Biological Oxygen Demand

COD:

Chemical Oxygen Demand

CPOM:

Coarse Particulate Organic Matter

DO:

Dissolved Oxygen

DOM:

Dissolved Organic matter

DOsat:

Dissolved Oxygen Saturation

EC:

Electrical Conductivity

EIFA-WP:

European Inland Fishery commission Working Party

EPT:

Ephemeroptera, Plecoptera and Trichoptera

FFG:

Functional Feeding Groups

FISRWG:

Federal Interagency Stream Restoration Working Group

INAMHI:

Instituto Nacional de Meteorología e Hidrología

INEC:

Instituto Nacional de Estadística y Censos

MAGAP:

Ministerio de Agricultura, Acuacultura y Pesca.

MMIF:

Multimetric Macroinvertebrate Index for Flanders

PCBs:

Poly-Chlorobiphenols

PHCs:

Poly Aromatic Hydrocarbons

RCC:

River Continuum Concept

SENAGUA:

Secretaria Nacional del Agua

TOC:

Total Organic Carbon v

Advisory

Ganadería,

WATQI:

Water Quality Index

CF :

Coliform fecal

ATP :

Adenosine triphosphate

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ABSTRACT Water is essential for life of organisms and necessary in civilization. However, the fast growth of the human population, changes in land use and rapid urbanization damage natural ecosystems and reduce their value for delivering goods and services for human societies. Around the world, various researches determine how ecosystems respond to external stressors. However, some regions are hardly investigated and characterized. For instance, the water and ecological quality of the Portoviejo river basin is unknown. Thus, the present study assesses the water quality of the Portoviejo River in Ecuador. Furthermore, the evolution of various environmental variables was determined along the disturbance gradient within the river. Additionally, the impacts of irrigation dams, agriculture, urbanization, wastewater discharge on water and ecological quality was assessed. For this, physical, chemical and biological (macroinvertebrates) characteristics of the rivers were sampled at 31 sampling sites along the main river, some tributaries and within the reservoir. Ecological quality, expressed as Biological Monitoring Working Party-Colombia (BMWP-Col), and chemical indices (the Dutch and LISEC methods) were calculated. Majority of sampling sites (45%) had poor quality. The good ecological quality was associated with high flow velocities, low temperatures, low conductivity, low chlorophyll a content, low biological oxygen demand (BOD5) and low nutrient concentrations. Additionally, good water quality was also associated with the presence of sensitive taxa and high diversity. Bad quality, mainly at the downstream of the river, is related to urbanization and inputs of untreated domestic wastewater. In general, there was an increase in conductivity, chlorophyll a, available nutrients, and total organic carbon along the gradient from source to the mouth. This observation was related to changes in land use. Predators and collectors were dominant at upstream, more scrapers were found at the midstream and collectors dominated near to the mouth. Deviation from the prediction of the River Continuum Concept (RCC) can be explained by the presence of a series of dams along the river and differences in food availability in tropical zones. Flow velocity, pH and temperature are low before dams. While, turbidity is relatively high after dams. Chlorophyll a is higher in residential areas than in forest and arable land. While conductivity and nutrients in forest areas are relatively low compared with arable land. Conversely, BOD5 in forest areas is relatively higher than in arable and residential zones. Physicochemical variables are not statistically affected by the presence of a municipal WWTP in the Portoviejo River. Nonetheless, chlorophyll a, BOD5, TOC, total phosphorus and total nitrogen after WWTP are relatively higher than before WWTP. Probably, the WWTP is insufficient in organic and nutrients removal or an overload of waste is present. In general, Portoviejo River follows the pollution gradient typical by the presence of anthropogenic perturbations. Based on the findings, a sustainable management of the river catchment is necessary, combining the reduction of inflow of pollutants via wastewater treatment, and minimizing the habitat alteration of banks, and restoring flows affected by hydropower dams. vii

1. INTRODUCTION Water is essential for life of organisms. It is necessary for development of natural ecosystems, for human well-being and for progress of cities (Virha et al., 2011; Haldar et al., 2014). Around the world, freshwater is mainly obtained from natural streams which are exposed to external pressure that could influence its water quality. Water quality, in most cases, is caused by human activities such as water pollution, modification of natural hydrology, river impoundments and land-use changes (Geist, 2011). Assessment of water quality is crucial to determine the health of ecosystems, control of environmental pollution and hence to maintain human safety (Bilotta et al., 2008). Nowadays, water quality is assessed by measuring environmental variables and by freshwater organisms in order to determine the environmental status of the ecosystem (Sundermann et al., 2015). The use of macroinvertebrates together with physicochemical variables has been used worldwide to assess water quality. Some adaptations were made to allow its use in all regions including South America (Damanik-Ambarita et al., 2016). Macroinvertebrates are broadly used because it provides an easy and less costly tool to monitor freshwater ecosystems, which make it the best option in developing countries (Pander and Geist, 2013). In Ecuador, a number of investigations on water quality and ecological status on freshwater ecosystems based on macroinvertebrates were implemented (Alvarez-Mieles et al., 2013, Damanik-Ambarita et al., 2016). However, this method is not yet spread along the whole country, such as the case of the Portoviejo River. The Portoviejo River is an important source of water for the inhabitants of the region for drinking water and irrigation. To know its water quality status is crucial in order to take actions for reducing sources and impacts of pollution. However, the water and ecological quality of the Portoviejo river basin is unknown. It is currently monitored based on physicochemical variables by the water secretariat (Secretaría del agua SENAGUA), a government organization which is also in charge to assure the access to good quality freshwater for human consumption, irrigation and other uses. Furthermore, the conservation of natural environment is in charge of the ministry of environment (Ministerio del ambiente MAE), which is in charge to ensure sustainable management of strategic natural resources. Together, both agencies are making good effort to assure water supply in the region but the rapid population grow, urbanization, changes in land use, together with limited budget make it challenging to control and continuously monitor the freshwater streams. Furthermore, the municipal government is putting a great effort to recover the water quality of the river but positive results are not yet obtained. Portoviejo river consists of a series of dams. The impacts of irrigation dams in water and ecological quality are unknown. Furthermore, little is known on the impact of a series of dams along a tropical river on the functional feeding groups (FFG). In the same way, limited knowledge exists in how the nutrients, organic matter and others physicochemical variables evolve in this system. The Portoviejo offers an interesting advantage for study as it is a small catchment (system) and thus it is easy to explore and be investigated. As various land uses such as agriculture, and urbanization and the presence of dams are found along the Portoviejo river impacts of these land uses can be easily studied. Thus, changes in land use and other anthropogenic activities could be 1

anticipated in order to reduce pollution to the river. Findings of this study can be used as a baseline on the effects of these anthropogenic activities in a similar tropical river system worldwide. For reasons cited above, an ecological monitoring based on macroinvertebrates is proposed to identify multiple stressors in freshwater stream to help decision makers to take actions for management and control pollution. For this research, it is aimed (1) to assess the ecological water quality in the Portoviejo River (Ecuador) based on macroinvertebrates community, (2) to analyze the environmental gradients along the river based on the river continuum concept and (3) to estimate different impacts caused by land use, dams and waste water treatment plants within the Portoviejo River.

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2. LITERATURE REVIEW 2.1 Water Quality in freshwater ecosystems Water is essential for the life in the planet (Virha et al., 2011). Freshwater streams support the natural ecosystem (Haldar et al., 2014). People use freshwater mainly from rivers for their daily activities. Utilization of water resources is indispensable for humans and its use has allowed the development of cities and countries (Geist, 2011; Kaushal et al., 2015; Pander et al., 2013). Water quality is important for sustaining development of both human and ecological communities (Srebotnjak et al., 2012). Water quality could be defined as a group of chemical and physical characteristics of any stream that could be used as indicator of ecosystem health and useful for deducting environmental pollution (Bilotta et al, 2008). To assess water quality, environmental measurements are needed. These values are usually contrasted with a reference point that has previously been considered as good water quality site (De Rosemond et al., 2009). The sources of pollutants are different and are present in many forms. Diffuse and point source pollution affects streams in distinct ways. They may degrade various aquatic habitats through accumulation. For instance, major intensity usually occurs in the lower section of a stream, impoverishing the water quality and results to a decrease in diversity of aquatic fauna (Snook and Whitehead, 2004). Furthermore, other types of river alteration, such as modification of natural hydrology of a stream, also leads to the detriment of water quality (Castello and Macedo, 2016). European Inland Fishery Advisory commission Working Party (EIFA-WP) defined parameters for water quality in 1969. They demarcated safe pH range for fish, which is between 5 and 9. Furthermore, they also established healthy temperature and ammonia ranges for aquatic animals (EIFA-WP, 1969). In various studies, freshwater quality is derived from physicochemical, biological and microbiological parameters (Antonietti et al., 1996; Da Silva and Sacomani, 2001; Reisenhofer et al., 1998). These include pH, COD, orthophosphates, conductivity, dissolved oxygen, total plating count, ammonia, nitrate, alkalinity, coliform fecal CF, adenosine triphosphate ATP, carbohydrates and macrobenthos composition (Antonietti et al., 1996). In 2008, a Water Quality Index (WATQI) was developed based on five parameters: dissolved oxygen, electrical conductivity, total phosphorous, total nitrogen and pH (Srebotnjak et al., 2012). 2.2 Quality indices 2.2.1 Biological Indices Several studies revealed that biota depends on water quality. Mostly, water quality is influenced by anthropogenic pressures such as urbanization and agriculture (Kail et al., 2012). Organisms in freshwater bodies seem to suffer multiple stressors from human activities and therefore these organisms serve as indicators for pollution (Sundermann et al., 2015). Globally, freshwater organisms are used to assess water quality and determine the environmental status of an ecosystem.

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Fish, invertebrates, algae and macrophytes are commonly used to assess quality of aquatic environments. They provide an easy and less costly tool to monitor the ecological status of freshwater ecosystems (Southerland et al., 2007; Pander et al., 2013). But some of them have limitations. For instance, fish monitoring cannot be applied to very small streams due to the impairment of space to their developing (Southerland et al., 2007). Additionally, stream quality classifications are usually based on the presence of expected fauna from a reference site (pristine location). In this way, the absence of fauna means presence of stressors. Nevertheless, it needs to take into account that these variations could depend on other physical characteristics, such as landscape and flow velocity (Skoulikidis et al., 2009). Macroinvertebrates are broadly used in environmental assessment as they are sensitive for a wide range of pollutants. They have a broad variety of taxonomic groups whose responses towards environmental variations are very valuable to evaluate freshwater ecosystems (Carlisle et al., 2007; Smith et al., 2007). Cao et al., (1997) found as water quality was reduced along the stream, some species loses their average quantity. On the other hand, the number of some tolerant species increased in the contaminated sites. Furthermore, they measure the cumulative response to habitat changes due to their long life cycle (Azevedo et al., 2015). Macroinvertebrates has been used as water quality indicators since early 1950s (Gabriels, 2007) and several assessment methods has been developed worldwide to evaluate water quality (Skoulikidis et al., 2009). As an example a Multimetric Macroinvertebrates Index for Flanders (MMIF) was developed by Gabriels et al. (2010) to assess quality in rivers and lakes within Belgium. In Bulgaria and Vietnam, freshwater quality was determined with macroinvertebrates (Lock et al., 2011; Nguyen et al., 2014). Furthermore, hydromorphological quality on surface water was also examined in Estonia based on invertebrates (Timm et al., 2011). 2.2.1.1 Common indices based on Macroinvertebrates There is an ample quantity of indices based on macroinvertebrates communities to assess freshwater quality (Gabriels, 2007). Some of them used in the present study are discussed in the following paragraphs. Biological Monitoring Working Party (BMWP) The Biological Monitoring Working Party (BMWP) (Armitage et al., 1983) developed in UK and revised by the National Water Council, is based in a score system (Couto-Mendoza et al., 2015). The BMWP score provides a suitable classification for monitoring and assessing quality in freshwater ecosystem (Armitage et al., 1983). Zamora-Muñoz et al. (1995) demonstrated that BMWP is negatively related to pollution. Their study also indicates that BMWP is not seasonally dependent (Zamora-Muñoz et al., 1995) making it suitable for monitoring campaign during all seasons. Some adaptations to BMWP index were made in Europe. For example, the Iberian Biological Monitoring Working Party (IBMWP) for Spain (Alba-Tercedor 2000; Alba-Tercedor et al., 2004) 4

was developed. According to Couto-Mendoza et al. (2015), IBMWP was more used during the last two and a half decades in Spain to determine ecological status in freshwater. Several adaptations from BMWP have been developed in Latin America. For instance, in Costa Rica, the Biological Monitoring Working Party Costa Rica (BMWP-CR) is employed (Gutiérrez and Lorion, 2014). In Colombia, Roldán (2003) established Biological Monitoring Working Party Colombia (BMWP/Col) to make an approximation on the ecological status of water bodies in Colombia (Roldán, 2003). Some researches were conducted applying BMWP-Col in Colombia (Montoya et al., 2011; Forero and Reinoso, 2013) and in Ecuador (Alvarez-Mieles et al., 2013; Damanik-Ambarita et al., 2016) to assess freshwater quality and wetland ecosystems. Diversity indices Shannon-Wiener (Shannon and Weaver, 1949) and Margalef index (Margalef, 1958) are nontaxonomic metrics (Gabriels, 2007), also referred as diversity indices. Both metrics make use of richness, evenness and abundance on macroinvertebrate community. In an unpolluted environment, high richness, even-spreading and abundant organisms is expected (Metcalfe, 1989). Metcalfe (1989) describes some advantages of diversity indices. They are exclusively quantitative, independent of the proportions of the sample, no suppositions about tolerances are needed and can measure biomass instead count individuals. Criticism against it includes values rely on the equation used, there are variations depending on the standard used, some species are neglected, it considers response to pollution as linear, and there is few testing in middle range pollution (Metcalfe, 1989). Taxonomic species richness Freshwater invertebrate richness in pristine locations is influenced by environmental factors such as geology, ecosystem productivity, competition and predation. Interactions of these factors determine the gradients of species richness (Compin and Céréghino, 2003). The richness along the stream is influenced by anthropogenic interference (Céréghino et al. 2003). The number of taxa reduced (Brittain and Saltveit as cited by Compin and Céréghino, 2003) and expected gradient is disrupted (Ward and Stanford as cited by Compin and Céréghino, 2003) as a result of human activities. Because Ephemeroptera, Plecoptera and Trichoptera (EPT) have an extensive distribution, they are highly associated with tendencies in richness and vastly related with ecological variations (Shah et al. 2015). Thus, EPT is a good indicator of stream disturbances (Céréghino et al. 2003). EPT taxa were used to assess stream ecosystem health in Burkina Faso in Africa (Kaboré et al. 2016) and in Latin America and the Caribbean (Soldner et al. 2014). The number of macroinvertebrate families are also used as an indicator of pollution in freshwater streams (Carlisle et al. 2007). Carlisle et al. (2007) found that genera and families are strongly correlated to road density as a result of urbanization. The total number of taxa is also utilized to derive the multimetric index in Belgium (Gabriels, 2010) and in Vietnam (Nguyen et al. 2014). 5

2.2.2 Physicochemical water quality Physical and chemical properties depict water of a stream (Bilotta et al. 2008) and are essential determining the stream’s quality (Virha et al. 2011). As the population grows, the needs of freshwater increase as well. Furthermore, as a result of the increase of anthropogenic activities, biological and physicochemical conditions of rivers deteriorate (Forero-Céspedes and ReinosoFlórez, 2013). Pollution caused by chemicals is the main stressor in freshwater ecosystems (Berger el al. 2016). Berger el al. (2016) found that some chemical affects ecosystems in lower concentration than expected from laboratory analysis. They suggest that chemical pollution is an important factor in the distribution of macroinvertebrates which are widely used as indicators of water quality (Smith et al. 2007). There are numerous physicochemical indicators used for determining water quality. Several studies worldwide characterized water quality in freshwater streams based exclusively on physicochemical parameters (Da Silva and Sacomani 2001; Reisenhofer et al. 1998) and others in combination with biological and microbiological components (Charalampous et al. 2015; Haldar et al. 2014; Antonietti et al. 1996). In 2008 a first approach named Water Quality Index (WATQI) intended to be worldwide used was published. WATQI was based on measurements of dissolved oxygen, electrical conductivity, total phosphorous, total nitrogen and pH (Srebotnjak et al., 2012). 2.2.2.1 Physicochemical water quality indicators Physicochemical indicators are briefly deliberated below. pH pH can be easily measured in the field. Natural pH in rivers ranges between 6.7 and 8.6 which could vary due to direct discharges, runoff, heavy rainfall events or mine drainage (Lloid et al 1969). With relation to the aquatic biota, Lloid et al. (1969) reported that pH range in between 5 to 9 is not directly harmful to fish. Nitrogen and phosphorous Nitrogen and phosphorous determine the trophic status and eutrophication in freshwater ecosystems (Jarvie et al. 2002). The main sources of these nutrients are application of fertilizers and combustion of fossil fuel (Smith et al. 2007). Nevertheless, eutrophication in the river also depends on interacting elements along the stream (Honty 2015). Suspended solids It is clear that suspended solids are very important in the assessment of water quality in a river ecosystem. Suspended solids not only affect the light availability within the water column and in the visual effect of the river but also interfere negatively with the ecological life, e.g. reduction in primary production and temperature change because of reduction of light penetration and, 6

chemical alterations by release of contaminant into the water column from absorption places in sediments (Bilotta et al., 2008). Moreover, Xia et al. (2004) revealed that the presence of suspended solids could also enhance the process of nitrification. Dissolved Organic matter (DOM) The dissolved organic matter present in streams is connected with human interactions. Williams et. al. (2016) established that DOM composition is strongly related with human activities. It is also associated with land cover and human density. The DOM composition is different between urbanized watershed and natural land cover and agricultural places. Ecosystem with low human densities have DOM composition more similar to clear water ecosystem. So, highly populated areas strongly alter the quality of DOM (Williams et al., 2016). Stream Flow Barreto et al. (2014) indicate that the flow rate is strongly related with other parameters. They described that flow rate is positive correlated with total dissolved solid and salinity, while pH is inversely correlated with flow rate. On the other hand, phosphorus that phosphorus increased exponentially as flow rate increased (Barreto et al., 2014). Temperature Water temperature in freshwater ecosystems is a key element for subsistence of aquatic organisms (Verones et al. 2010) and regulation of its compartment (Whitehead et al., 2009). Thermal emissions (Verones et al. 2010), hydrological alterations (Olden and Naiman, 2010) and climate change are increasing freshwater temperature (Dietrich et al. 2014). This increment has negative ecological consequences as it accelerates kinetic reactions of some chemicals and pollutants (Whiteheaed et al., 2009). For example, Laetz et al. (2014) found that some insecticide mixtures increased its relative toxicity for Pacific Salmon with increasing temperature. Electrical Conductivity (EC) The electrical conductivity (EC) measures the total dissolved ions in freshwater ecosystems as an indicator for pollution by human activity (Srebotnjak et al., 2012). It is frequently associated with sewage discharge (Ribeiro de Sousa et al., 2014). However, Srebotnjak et al., (2012) indicates that measurements of EC could be influenced by meteorological conditions, geology, water body size, evaporation and metabolism of bacteria community. EC is inversely related with aquatic life (Thompson et al., 2012). Furthermore, EC has been used together with other physicochemical parameters to determine freshwater quality in rivers (Cicek and Ertan 2012; Akkoyunlu et al., 2012), its effects in aquatic organisms (Patnode et al., 2015; Haddaway et al., 2015) and impact of mining activities on water chemistry (Wright et al., 2015) Indices based on chemical water variables Below the LISEC index developed based on chemical water quality parameters. 7

LISEC index The LISEC Index is commonly used to evaluate quality in surface waters. It uses classification (5 classes) of 4 parameters (% O2 saturation, BOD, ammonium and orthophosphate). The LISEC Index is then the sum of each individual variable class. Since it sums up pollution produced by individual parameters, LISEC index classifies water quality with low scores as “very good”, and high scores as “very bad”, (Lamia and Hocine 2012). This index was used to measure freshwater streams quality in Congo (Bagalwa et al., 2013) and in Algeria (Lamia and Hocine 2012; Chaoui et al., 2013). 2.3 River Continuum Concept (RCC) The river continuum concept (RCC) (Figure 2.1) proposed by Vannote et. al. (1980) attempt to explain a continuous gradient of physical conditions from source to mouth within a river system. It also indicated that structures of biotic communities and functional characteristics are adapted in function of energy inputs along the river (e.g. organic matter). So, the RCC offers a probable composition in its functional feeding groups FFG, for example, at headwater, the organisms are dominated by shredders as the organic matter debris are bigger, and collectors due to food source as fine particulate organic matter (FPOM) from fragmented leafs (coarse particulate organic matter (CPOM)) within a river ecosystem (Vannote et. al.,1980). The RCC was conceived based on “existing data” from geomorphology, hydrology, biogeography, and natural history (Resh and Kobzina 2003). The RCC defines a unidirectional transport of materials and organisms in watercourses resulting in longitudinal variations along the stream gradient (Barquin and Death 2011; Minton et al., 2008). It predicts biotic diversity from little streams to big rivers (Dettmers et al., 2001). Furthermore, RCC indicates that changes in physical conditions and food availability in rivers leads to a longitudinal pattern of macroinvertebrates and fishes conditioning the trophic group compositions of aquatic community (Ibanñez et al 2009; Wolff el al. 2013). However, Dettmers et al., (2011) indicated that the RCC predicts a highest diversity in rivers of middle order (4–6) but does not predict arrangements for fishes of large rivers (>6th order). The longitudinal arrangements within the stream ecosystems in the RCC are dominant in early ecological studies (Lamberti et al., 2010) producing a new paradigm and motivating a good deal of discussion (Resh and Kobzina 2003). The RCC is widely applied in many studies. Wolff el al. (2013) found that fish assemblages follow the pattern expected by the River continuum concept. It was also used to describe the freshwater-saltwater interface in estuarine ecosystems (Dame et al., 1992), the zooplankton in a reservoir, river and estuary pathway (Akopian et al. 2002) and the bacterial diversity along the river (Savio et al., 2015). The RCC was also employed to investigate the gradient in infection level produced by fish parasites (Blasco-Costa et al., 2013), to predict linear gradients in two fish species (Schaefer et al., 2011) and quantified phenotypic gradients in freshwater snails (Minton et al., 2008). From a water basin protection perspective, Saunders et al. (2002) indicated that following the RCC, headwater streams are more vulnerable to changes in land use as a result of changes in energy input. On the other hand, downstream riparian

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vegetation is required for shading, smoothing hydrological fluctuation, regulating nutrient loads and avoiding erosion. Nevertheless, Newson and Newson (2000) found that macroinvertebrate biological patterns respond to longitudinal zonation like the RCC, but there is a noticeable secondary indicator controlled by local habitat patterns. In addition, Greathouse and Pringle (2006) indicated that macroinvertebrates distribution in a tropical island normally follow RCC however, additional studies are needed to polish the influence of functional feeding groups distribution caused by trophic regulators. Furthermore, Covich et al. (2009) indicated that the RCC do not consider impediment related with neither sloped basin nor dissimilarities between streams that controls predation and macroinvertebrate spreading. The RCC also considers a strong influence of coarse particulate organic matter (CPOM) from terrestrial sources as primary energy input on headwater, whereas downstream internal production rises generating its own energy sources (Saunders et al. 2002). Additionally, some deviations to the RCC are found in literature. In a comparison between tropical and temperate fish assemblages, Ibañez et al. (2009) found some differences in the expected predictions of the RCC that can be linked to differences in energy availability between temperate and tropical systems. Covich et al. (2009) indicated that for a diadromous shrimp, complexity in tropical insular drainages combined with temporal variability and land use induces dissemination and abundance of this shrimp in tropical stream ecosystems, which do not meet the RCC. They also stated that geomorphic obstacles can influence the plenty of shrimps and impede the spreading of their predatory fishes (Covich el al., 2009). Blanco et al. (2013) found that in short coastal streams (1 to 10 km) do not follow the principles of the RCC because of the steep gradient and the presence of waterfalls and cascades. Thus is consistent with the typology observed in volcanic oceanic islands in the Caribbean and the Pacific. They also indicated that low order (5.0

The index was derived by the addition of each individual score. A color code was assigned to the total score: blue, green, yellow and red as indicated in Table 3.2. 15

Table 3.2: Water quality assessment according to Dutch Method Class 1 2 3 4 5

Color code blue green yellow orange red

Score 3 – 4.5 4.6 – 7.5 7.6 – 10.5 10.6 – 13.5 13.6 - 15

Quality Excellent, very pure Good, pure Moderate, doubtful Bad, polluted Very bad, heavily polluted

The LISEC method The LISEC method was derived using 4 parameters, one variable more than the Dutch method. For LISEC index orthophosphate was used with a score of 1 for values lower or equal to 0.05, a score of 2 from 0.5 to 0.25, score of 3 from 0.25 to 0.9, score of 4 from 0.9 to 1.5 and score of 5 for values bigger or equal to 1.5. The parameters and scores are presented in Table 3.3. Table 3.3: Score system based on 4 parameters – LISEC method Score 1 2 3 4 5

%O2 saturation BOD (mg/l) NH4+-N (mg N/l) t.an. PO43-P (mg P/l) 91 –100 71 – 90 111 – 120 51 – 70 121 – 130 31 – 50 131 – 150 150