Effects Of Pollution On Water And Fish Production Using Macro Invertebrates As Bio-Indicators

Project and Seminar Material for Fishery and Aquaculture

Effects Of Pollution On Water And Fish Production Using Macro Invertebrates As Bio-Indicators


Abstract


The study was carried out on the effects of pollution on water and fish production using macro invertebrates as bio-indicators. The study was carried out in Numu pond, Niger state.Monthly sampling of the three study sites was carried out from November to December 2012 for the dry season and April to July 2013, for the wet season towards the end of every month, between 7am and 10.30am every sampling day. Macroinvertebrates samples were collected using a 3min Kick method with a D-frame net (800µm mesh) along an approximate 25m long wadeable stretch of the pond.

Three different samples were taken at each sampling site, which covered all different substrate and flow regime zones. After sampling, live sorting was carried out in the laboratory within a few hours of collection. All statistical test were based on  = 0.05 level of significance. Analysis of variance (ANOVA) was used for the statistical analysis of the physicochemical variables and Ephemeroptera and Odonata distribution.

The macroinvertebrates was sparse in Numu pond from the study result. This was due to the ephemeral and lentic nature of the pond. From the physicochemical parameters and macroinvertebrates sampled, it shows that the pond is becoming perturbed, probably due to various anthropogenic activities carried out along the course of the pond. The study recommended that more detailed research on the macroinvertebrates of Numu pond, especially their use as biological indicators of water quality.


Table Of Contents


Preliminary Page(s)

  • Title page
  • Certification page
  • Dedication
  • Acknowledgement
  • Abstract
  • Table of content

Chapter One

1.0 Introduction

  • 1.1 Background of the study
  • 1.2 Justification
  • 1.3 Aim
  • 1.4 Objectives

Chapter Two

2.0 Literature Review


Chapter Three

3.0 Material And Method

  • 3.1 Study Area
  • 3.3 Sampling Techniques
  • 3.4 Physicochemical Parameters
  • 3.4.1 Temperature
  • 3.4.2 Dissolved oxygen
  • 3.4.3 Biochemical oxygen demand (BOD)
  • 3.4.4 pH
  • 3.4.5 Nitrate-nitrogen:
  • 3.4.6 Phosphate-phosphorus:
  • 3.5 Collection And Analysis Of Macroinvertebrate Species
  • 3.6 Sorting and preserving the samples.
  • 3.7 Identification
  • 3.8 Data analysis
  • 3.8.1 Indices of species diversity
  • 3.8.2 Simpsons index

Chapter Four

4.0 Results

  • 4.1 Results
  • 4.1.1 Temperature
  • 4.1.2 pH:
  • 4.1.3 Conductivity:
  • 4.1.4 Dissolved Oxygen (DO):
  • 4.1.5 Biochemical Oxygen Demand (BOD):
  • 4.1.6 Nitrate:
  • 4.1.7 Phosphate:
  • 4.2 Composition, Distribution and Abundance of Macroinvertebrate in Numu Pond.
  • 4.3 Taxa richness, Evenness, Diversity indices of macroinvertebrates of the sampling sites of Numu Pond.

Chapter Five

5.0 Discussion, Conclusion And Recommendations

  • 5.1 Discussion
  • 5.1.1 Physicochemical Parameters
  • 5.1.2 Composition, Distribution and Abundance of Macroinvertebrate in Numu Pond.
  • 5.2 Conclusion and recommendations
  • References

Chapter One


1.0 Introduction

1.1 Background Of The Study

Although biologist have been studying the effects of human activities on aquatic systems and its effects on fish production for decades, their findings have only relatively recently being translated into methods suitable for monitoring the quality of water bodies. Mostly, bio-indicators such as benthic macro-invertebrates, phytoplankton and zooplankton are among the common bio-indicator organisms used during bio-monitoring of water to determine the suitability for fish production (Tassi, 2009). Artificial (and in some cases natural) changes in the physical and chemical nature of freshwaters can produce diverse biological effect ranging from the severe (such as a total fish kill) to the subtle (for example, changes in enzymes level or sub-cellular components of organisms) (Pagano et.al., 2006), changes like these indicates that the ecosystem and its associated organisms are under stress or that the ecosystem has become unbalanced (Masona, 2007).

Because flora and fauna of various trophic levels can integrate the effects of water quality or habitat changes over time, they become effective pollution indicators (Fernando, 2002). The concentration of a pollutant in an organism is the result of many variables such as the concentration of the pollutant in the water, the physical-chemical form of the pollutant, the membrane permeability of the organism, the type and quantity of food and its degree of contamination, the physiological state of the organism and the characteristics of the physical environment influencing the organism as well as the pollutant (Rose et.al., 2003). The response of biological communities or of the individual organism can be monitored in a variety of ways to indicate effects on the ecosystem. The co-existence and abundance of certain species at a particular location can indicate for example whether that habitat has been adversely altered (Pearl et al., 2003). The reactions of individual organisms such as behavioral, physiological or morphological changes can also be studied as responses to stress or adverse stimuli (for example caused by the presence of contaminants (Bailey et al., 2001).

If an environment receives a foreign pollutant, the organism living in it will start to take up the pollutant, from the water or food, and concentrate it in its body (Straskraba and Tundisi, 2008). Assuming that the pollutant concentration in the environment is constant overtime and the pollutant concentration in the organism body increases, death will occur after a long period. Conversely, a continuous decrease of the pollutant concentration in the medium produces a corresponding release of the pollutant form the organism, with some delay (Anmtage, 2008).

The kinetics of both pollutant uptake and release by the organism has the same pattern for any substance and animal species, whereas the uptake-and loss-rate are dependent on the characteristics of the organism as well as on those of the pollutant and the environmental conditions.

Bio-monitoring is measuring the conditions and integrity of various sources of water to ensure the health and fitness of the water body for the growth and production of fish species. For lotic (running) water systems, analysis of benthic macro-invertebrate communities provides the principal means of achieving this, particularly since macro-invertebrates are more stationary and less temporal than periphytic or attached microscopic communities (Relyea, 2008).

Biological monitoring refers to the collection and analysis of stream macro-invertebrate communities as indicators of water or habitat quality. Macro-invertebrates are larger than microscopic primary benthic (bottom dwelling) fauna, which are generally ubiquitous in fresh water and estuarine environments and play an integral role in the aquatic food web (Bernard et. al., 2003), they are the most commonly used bio-indicator of water quality among the community of indicator organisms because the presence or absence of certain pollution tolerant or intolerant species can be a great determining factor in ascertaining the level of pollution of the water available for fish production.

Total absence of pollution intolerant species, indicates bad water quality which may have adverse effect on fishes inhabiting such water bodies or in most cases, death of the fishes. They are insects and animals without backbone (invertebrates) that can be seen with unaided eye (without a microscope) that live in and on the bottom of streams, lakes, ponds, reservoirs, estuaries and oceans (Downing and Rigler, 2002). Insects (largely immature forms) are especially characteristics of freshwaters; other major groups include worms, mollusk (snails, clams) and crustaceans (scuds, shrimp etc.) (Lathrop and Markowitz, 2001). They are more readily collected and quantified than either fish or periphyton community. Species comprising the upstream communities occupy various niches, based on functional adaptation or feeding mode (e.g. predators, filter or detritus, feeders, scavenger); their presence and relative abundance is governed by environmental conditions (which may determine available food supply) and by pollution tolerance levels of the respective species (Cardoso et.al., 2006).

Benthic macro invertebrates are of great importance in assessing water quality available for fish culture because they have several characteristics that makes them easy to study and show clear responses when faced with adverse environmental conditions (Davis and Simon, 2005).

Aquatic Pollution

Degradable wastes are organic materials that can undergo decomposition through bacterial attack. The inputs that can be included under this category are urban sewage, agricultural waste, food processing waste distillery waste, paper-pulp mill waste, and organic discharge from chemical industry and oil spillages (Hutchinson, 2000). In addition, inputs like leaves and grass clippings and run-off from livestock feedlots and pastures also contributes to this. When natural bacteria and other micro-organisms in the water breaks down to organic materials, they use up the oxygen dissolved in water (Edington and Hildrew, 2003). Most of the fishes and bottom dwelling animals cannot survive when levels of dissolved oxygen drops too low. When this occurs, it kills fishes and other aquatic organisms in large numbers, which leads to disruption in food chain.

Fertilizers containing nutrients such as nitrates and phosphates could also have effects similar to those of organic wastes. In excess levels, nutrient over-stimulates the growth of aquatic plants and algae (Moore, 2000). Excessive growth of these clogs waterways, uses up dissolved oxygen as organisms decompose besides and thereby blocking light to deeper waters. The depletion of oxygen in turn, proves very harmful to aquatic organisms as it affects respiration of fish (Campaioli et. al., 2004) and other aquatic organisms that derive oxygen from water.

Heat, acids and alkalis and some chemicals such as cyanides can be considered as dissipating wastes as they lose damaging effects soon after they enter water bodies. Particulates like dredging spoil, fly-ash, China clay-waste, colliery waste and a variety of man-made materials like plastics are inert but they may clog feeding and respiratory structures of animals and may also reduce photosynthesis by reducing light penetration or may smother benthos (Simons, 2009). Conservative wastes like heavy metal, halogenated hydrocarbons and radioactive material are not subject to microbial attack and therefore, exist over a long duration and cause harm to plants and animal (Lampert and Sommer, 2004).

Sources of Pollution

The sources of pollution of a given water body, can be categorized as point and non-point. Point source of pollution occurs when polluting substances are emitted directly into water ways. A pipe channeling toxic chemicals directly into a river is an example. A non-point source occurs, when there is run-off of pollutants into a water way, for instance, when fertilizers for agricultural fields are carried into a stream by surface run-off. The common point sources of pollution are municipal and industrial waste effluent, run-off fields; discharge from vessels, storage tanks and piles of chemical, run-off from construction sites; and by passes from Sewers and sanitary pipes (Pollard, 2000).

The non-point sources include flow from agricultural field, and orchards, run-off from logging operations, urban run-off from logging operations, urban run-off from unsewed areas and septic tanks leachates, atmospheric deposition and rural runoff from roads, when toxic substances enter lakes, stream, rivers, oceans and other water-bodies, these get dissolved, i.e. suspended in water or get deposited on bed (Hynes, 2002). This results in water pollution thereby quality of water deteriorates, affecting aquatic eco-systems, pollutants can also seep down and affect ground water deposits. The most important sources of pollution are city sewage and industrial waste discharged into rivers by virtue of the quantities in which these are discharged. According to Lenat (2004), only about 10 percent of the waste water generated at present, is being treated, allowing about 90 percent of it to directly enter receiving water. Due to this, pollutants enter ground water, rivers and other water bodies and may even harbor pathogens. Agricultural run-off or the water from fields that drain into rivers is another major source of water pollution as it could be rich in the major nutrients like nitrogen, phosphorous and pesticides (Mecan, 2004).

Bio-Monitoring

Testing for chemical pollution in our nation’s water bodies, have traditionally meant using analytical chemistry. In recent years, environmental agencies have endorsed biological monitoring to enhance or replace chemical monitoring. The theory behind biological monitoring (bio-monitoring) is to use the organisms living in the aquatic system as a measure of water quality. These concepts have being applied to the study of so many water bodies and have proven effective in the determination of the water quality for fish production (Homing and Pollard, 2008).

Bio-monitoring an aquatic system uses the same theoretical approach. Aquatic organisms are subject to pollutants in the stream as if flows by day and night. Consequently, the health of organisms reflects the quality of water they live in. If the pollution levels reach a critical concentration, certain organisms will migrate; fail to reproduce or die, eventually leading to the disappearance of these species at the polluted site (Parker and Salansky, 2007). Normally, these organisms will return if conditions improve in the system.

Bio-monitoring involves the use of organisms to assess the health of the environment and is based on our understanding of how organisms interact with their environment. Bio-monitoring focuses on changes in community structure (distribution and abundance) (Cao et. al., 2007). The biological monitoring commonly used are based on the presence or absence of taxa indicators of environmental wellbeing (e.g. biotic indices) or on the complexity of the community identified with the level of environmental well-being (e.g. Diversity indices).

Biological monitoring (biotic and diversity indices) is not a direct measure of the biological effect produced by pollution, because the observed alterations may be due, in addition to the pollution, to other stress (e.g. natural or anthropogenic stress not caused by pollutants). Nevertheless, biological monitoring, when applied to the same community over time, may reflect some biological modifications, showing that the community, and then the physical environment have been stressed. As a consequence, biological monitoring may be considered a useful “warning signal” (Rundle et. al., 2002).


1.2 Justification of this Study

Niger State has a large proportion of freshwater bodies. This natural endowment, specifically Numu temporal pond, located in Numu quarters of Bosso Local Government Area of Minna, Niger State. Evaluating its pollution status by comparing various indicators will provide a good reference material on the pollution status of the pond.


1.3 Aim

To use macroinvertebrates as biological indicator of water pollution.


1.4 Objectives of the Study

Specific objectives are;

  1. To determine the physicochemical properties of the pond.
  2. To determine species composition and distribution of macroinvertebrates in the pond.
  3. To use the macroinvertebrates present in the pond to access the pollution status of the pond.

Chapter Five


Discussion, Conclusion And Recommendations

5.1 Discussion

5.1.1 Physicochemical Parameters

Numu pond showed two characteristics season, a dry and a wet season as earlier reported by (Imoobe & Oboh, 2003; Edegbene & Arimoro, 2012).

The physicochemical parameters were particularly high in the value of temperature, conductivity, DO and BOD (Edegbene et al. 2012).

Water temperature (28.3oC – 32.8oC) observed in this study is tropical of most tropical lotic water bodies in Nigeria as earlier reported by Arimoro et al. (2007). The range of temperature in the three sites studied showed no marked difference. Though site B recorded the highest water temperature of 32.8oC. This result is in consonant with the result of Arimoro & Ikomi (2008); Edegbene & Arimoro (2012). The absence of riparian vegetations may also results to high temperature of a particular water bodies (Arimoro & Ikomi, 2008; Edegbene et al. 2012).

The pH value in this study was slightly acidic. Site B was more acidic with a pH value of 6.1 when compared to others. The pH value ranged from 6.1 – 6.9 in the three sites. This value is in contrast with earlier report by Arimoro et al. (2008) in Warri River, Delta State. The acidic nature of this pond may be as a result of nearby farm settlement that uses some chemicals in their farming activities.

Conductivity measures the total ionic composition of water and overall chemical richness. It also quantitatively reflects the status of organic pollution and a measure of dissolved solids and ions in water (Jonnalagadda & Mhere, 2001). The conductivity value in the three (3) sites ranged from 102-987µ/cm, which is high. The conductivity value in River Borkena, Ethiopia, Abebe et al. (2009) recorded a conductivity value of 105 – 1200 µs/cm which was exceptionally higher than the one recorded in this present study. The conductivity recorded in this study may be due to the influence of dissolved solid from nearby farms, because the pond is an open type, which have no riparian vegetations and maybe somehow limited the influx of erosional process during raining season. The pond is an ephemeral and lentic type of water body which tends to have a high degree of dissolved solids because flow velocity is minimal.

The dissolved oxygen concentration of the sites sampled showed that it was well aerated sites. Dissolved oxygen ranged from 5.0 – 15mg/l. Similar to Ikomi et al. (2005); Edokpayi et al. (2004); Arimoro & Muller (2010); Edegbene & Arimoro (2012) in the Southern part of Nigeria. The high DO values recorded in this study may be an indication that the primary production of macrophytes is very high.

Biochemical oxygen demand (BOD) values indicate the extent of organic pollution in water quality (Jonnalagada & Mhere, 2001). Site 2 and 3 had relatively low mean BOD value (4.83 mg/l and 5.33 mg/l) which show these sites are still under control when compared to site 1 which had a mean BOD of 11.5 mg/l, showing that the site is fast deteriorating.

Nitrate, associated with algal growth and concentration of inorganic nitrogen greater than 0.3 mg/l can cause algae to grow in abundance (Nathanson, 2000). Nitrate in this study was high and range from 0.30 – 3.95 mg/l which may be attributed to algae growth in this water body. This range recorded compares favorably with other Nigerian water bodies; the values recorded include 0.08 mg/l to 3.39 mg/l in Orogodo River (Arimoro & Muller, 2010). This value of nitrate obtained in this study were however higher when compared to low titre value reported for similar natural unimpacted streams within Nigeria water body (Ogbeibu & Oribhabor, 2002; Edema et al., 2002; Edegbene & Arimoro, 2012).

Phosphate value range recorded in this study was between 3.37 mg/l – 4.99 mg/l. Contrarily, Arimoro et al. (2008) recorded a titre value of 0.09 – 1.88 mg/l; Edegbene (2012) recorded a value of 0.03 – 0.58 mg/l, in a river in southern Nigeria. This study area, phosphate value conforms favorably with the reports of Adakole & Anune (2003) who recorded a titre value of 0.03 – 5.89 mg/l in River Galma, Northern Nigeria. This report clearly shows that Numu pond is organically polluted which may be as a result of the incessant and indiscriminate use of fertilizers and other chemicals in farm settlements around the pond.

5.1.2 Composition, Distribution and Abundance of Macroinvertebrate in Numu Pond.

A total of 298 macroinvertebrates classified into 30 taxa was recorded in Numu pond. This study is in variance with earlier reports by Ogbeibu and Oribhabor, (2002) who recorded 46 taxa, Egborge et al., (2003), who recorded 62 taxa, 59 taxa reported by Ikomi et al., (2005). The paucity of macroinvertebrates in this study may be attributed to the Ephemeral and Lentic nature of the pond. Majority of the macroinvertebrates recorded in this study are widely distributed everywhere in Nigeria (Edakpoyi et al. 2010, Edema et al., 2002, Adakole & Anunne 2003, Edegbene & Arimoro, 2012) among others.

Coleoptera was represented by six (6) families, including Dyticidae, Notonectidae, Pleidae, Hydrophilidae, Cyprinidae and Elmidae. Edegbene (2012) recorded six families of Coleoptera in Owan River, Edo State. This shows that the Order Coleoptera is widely distributed in the aquatic system of Nigeria. The presence and abundance of Coleoptera in a water body has been affirmed to be related to clean water. But in this present study, the six (6) Coleoptera recovered were sparsely distributed based on the fact that the water is suffering from gross pollution (Edokpayi et al., 2000; Edema et al., 2002, Ikomi et al., 2005; Edegbene & Arimoro, 2012). Species of Coleoptera are very sensitive to reductions in dissolved oxygen levels.

The Order Ephemeroptera includes species that are tolerant as well as those that are intolerant to various forms of pollution (Menetrey et al., 2008). In accordance with this, the family Baetidae was represented by Cloeon dipterum, Cloeon annulata, Cloeon pallida, Cloeon marmoratum and Crassabwaspecies, showing that the pond is becoming stressed with organic pollution. This is in accordance with Arimoro (2009) report in Adofi River, Delta state, Edegbene & Arimoro (2012) in Owan River, Edo state. Other studies also reported that the genera Baetis are tolerant to organic pollution (Timm 1997; Menetrey et al., 2008). However, in this study these species were well represented in all the sites sampled except the paucity of Cloeon marmoratum and Crassabwa species.

Diptera recorded the highest number of individuals in the macroinvertebrates of Numu pond. This conforms favorably with similar study by Arimoro & Ikomi (2008) in River Orogodo, Niger Delta, Edegbene & Arimoro (2012) in Owan River, southern Nigeria, studies elsewhere (Ravera, 2001; Ruggiero et al., 2003 and Solimini et al., 2010) have revealed Diptera abundance to considerable level of organic particle from untreated sewage and livestock effluent. Chironomous specie was highly represented in the three sites. This is in accordance with the findings of Doisy & Rabeni (2001) who reported that Chironomus abundance is related to the amount of detritus, which in turn is negatively connected with flow velocity. This study area does not have flow regime because it is a lentic water body.

Hemiptera was represented by three families and three species but were poorly distributed except in site two, where Micronecta species was highly represented by 13 individuals. The paucity of Hemiptera in this study does not conform favorably with the reports of Ikomi et al (2005) and Edegbene & Arimoro (2012).

The Odonata was sparsely distributed in this study area, but were mostly collected in the macrophytes and riparian vegetation. Crachini et al. (2004) has earlier reported that the nymphs of Odonata are usually associated with macrophytes. This research further lead audience to the contribution of Edegbene & Arimoro (2012), who sampled more of the Odonata in aquatic submergent and emergent macrophytes in Owan River, Edo State, Nigeria.

The mollusca was scarce in distribution with only one family Lymnaeidae and specie (Lymnea species). Lymnea species was absent in site two and three but present in site one with five (5) individuals. This shows that site one was susceptible to the parasite Fasciola (hookworm), because the Mollusca, Lymnea species have been reported to harbor the parasite that causes fascioliasis or fasciolosis (Edegbene & Arimoro, 2012).


5.2 Conclusion and Recommendations

The macroinvertebrates was sparse in Numu pond from the study result. This was due to the ephemeral and lentic nature of the pond. From the physicochemical parameters and macroinvertebrates sampled, it shows that the pond is becoming perturbed, probably due to various anthropogenic activities carried out along the course of the pond.

Lending more credence to this is the presence of Ephemeroptera species that are tolerant to pollution. Chironomus which has been reported to dwell in heavily polluted water is also present in abundant form in the pond.

It is of this opinion that I would like to recommend more detailed research on the macroinvertebrates of Numu pond, especially their use as biological indicators of water quality.


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