CHAPTER – V LIMNOLOGICAL SIGNIFICANCE OF AQUATIC...

CHAPTER – V LIMNOLOGICAL

SIGNIFICANCE OF AQUATIC INSECTS

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LIMNOLOGICAL SIGNIFICANCE OF AQUATIC

INSECTS

Biodiversity is one of the most important corner stone of sustainable

development and represents the biological wealth of a given nation. The world, today

is facing its greatest ever biodiversity crisis. Flora and fauna are becoming extinct

because of habitat loss, overexploitation and the threat of global climate changes.

Aquatic biodiversity has enormous ecological, economical and aesthetic value and is

largely responsible for maintaining and supporting overall environmental health.

Humans have long depended on aquatic resources for food, medicine, and materials as

well as for recreational and commercial purposes such as fishing and tourism. Aquatic

organisms also rely upon the great diversity of aquatic habitats and resources for food

materials, and breeding grounds.

Factors including overexploitation of species, the introduction of exotic

species, pollution from urban, industrial and agricultural areas, as well as habitat loss

etc. contribute to the declining levels of biodiversity in both freshwater and marine

environments. As a result valuable aquatic resources are becoming increasingly

susceptible to both natural and artificial environmental change. Thus, conservation

strategies to protect and conserve aquatic life are necessary to maintain the balance of

nature and support the availability of resources for future generations.

Freshwater systems harbour diverse types of heterotrophic communities

specially the zooplankton, macro-invertebrates and fishes.They also act as an

indicator of trophic structure, water quality and eutrophication of the aquatic

ecosystems (Varma and Pratap, 2006). Moreover, biological indicators have the

advantage of monitoring water quality over a period of time, providing more exact

measures of anthropogenic effects on aquatic ecosystems, where physical and

chemical data provide momentary evidence (Camargo et al., 2004).

Aquatic insects make up only 3-5% of all insect species but are taxonomically

very diverse (Daly et al., 1998).These are insects in the order Ephemeroptera,

Odonata, Plecoptera , Hemiptera , Orthoptera, and Hymenoptera that spend at least

some stage of their lives under water. The Para insecta order collembola also has

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species that are closely associated with the water. Since aquatic insects are one of the

most important components of the aquatic ecosystems, they have both ecological and

economical value.

Aquatic insects are valuable tool for scientific research because of the rapid

reproduction, easy availability and ease of keeping them in laboratories. They have

been the primary tool for studying ecology, growth of population, evolution, genetics

and many other areas of biology.

Among the invertebrate taxa, aquatic insects form an important component of

food chains and energy flow pathways and comprise a high production of biomass in

freshwater. Various studies have shown that between 1% and 57% of biomass

produced by immature aquatic insect’s i.e. secondary production of aquatic insects

emerge from the aquatic systems in the form of adult insects. Thus, aquatic insects

constitute an important part of animal production within wetlands (Oertli, 1993), and

are tightly integrated into the structure and functioning of their habitats (e.g organic

matter processing, nutrient retention, food resources for vertebrates, such as

amphibians, fish or birds).In a given area, the spatial and temporal variability of

habitat types are key factors influencing the biodiversity of insect communities

(Hanquet et al., 2004) and are reflected in the ecological strategies and adaptations

exhibited by species (Townsend et al.,1997). Some of the aquatic insects are

responsible for breaking down the dead leaves and other plant parts that fall into the

bodies of water from land .This material provides the base of food chain in some

aquatic environments. Some scrape the algae that grow on all firm surfaces in water,

such as rocks, logs, leaves and stem of live rooted plants.This layer of algae, which

produces much oxygen and food for other organisms, is more productive if this is kept

thin by the grazing of aquatic insects and other invertebrates.

Some aquatic insects are specialized for filtering fine particles that are

suspended in water. This is useful as it helps to keep the water clean enough for light

to penetrate where algae and other plants are growing on the bottom. Others mix the

soft bottom sediments as they burrow in search of food. This makes the bottom

healthier for organisms because it puts oxygen from the water into the bottom.

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Predators such as Dytiscus reduce the number of other invertebrates and help to keep

the balance among the different kinds of organisms and the food that is available.

Nowadays biomonitoring is being much talked about and is rapidly expanding

fields particularly in case of limonological studies as biomonitoring gives an

aggregate of all environmental stresses, besides being a cost effective technique

(Zajic, 1971). Aquatic insects can reveal a great deal about the health of aquatic

ecosystems and many species are very sensitive to water quality.

Aquatic insects often make good indicators because they are present in some

capacity in almost every type of habitat and many are habitat specialists (Lewis and

Gripenberg, 2008).While a lack of data has historically excluded the use of many taxa

as possible indicators (Sahlen and Ekestubbe, 2001), a growing number of studies on

the habitats and distributional pattern of certain insects is making their use

increasingly suitable.

The order Odonata represents one set of insects that is being widely studied

for its potential in indicating environmental quality. Studies have included Odonata

relationship with water quality (Azrina, et al., 2006), biotope quality (Clark and

Samways, 1996; Clausnitzer,2003) and general species richness (Sahlen and

Ekestubbe, 2001, Briers and Biggs, 2003), and use of Odonata as indicators for

wetland conservation (Bried et al., 2007), riparian management needs (Samways and

Steytler, 1996), wetland buffer width requirements (Bried and Ervin, 2006) and

shallow lake restoration (D’Amico, et al., 2004). This is largely because many of

criteria of good indicator species, such as being taxonomically well known, relatively

easy to identify and having distinct habitat requirements (Krebs, 2001) are fulfilled by

odonates (Corbet, 1999).

As a group of species that are especially sensitive to the changes in their

habitat, Odonata population can also be indicative of the richness of other

invertebrates and macrophytes (Bried and Ervin, 2005). Furthermore, odonates have

became a focus of many conservation efforts as they tend to be very large, colourful,

and easily observable, making them an ideal subject of programmes that are largely

carried out by the public (Bybee, 2005).Through such conservation efforts, odonates

can also act as an umbrella species, facilitating the protection of habitat that is crucial

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for the survival of species (Bried and Ervin, 2005). While adult odonates in flight are

relatively easy to spot and identify, their movement among habitat limit their ability to

indicate changes in water quality (D’Amico et al., 2004).The odonate larva use as

energetic source in their diet the Anopheles larva, by maintaining the control over

their population numbers, which itself are responsible for spreading of the epidemic

illness like malaria (Mitra, 2002).

Odonates are characterized as an excellent habitat indicator of present and past

(long term) environmental conditions in aquatic habitats (Watson et al., 1982;

Steward and Samway, 1988). A feature of the odonate species is that they prefer to

live in freshwater, non-contaminated and well oxygenated habitats. Hence, they can

serve as valuable bio-indicators for environmental contamination studies (Needham et

al., 2000; Morin, 1984).

Though odonates were recorded in present study but they showed least

diversity and were very sparse in distribution, there by indicating their preference for

freshwater, non-contaminated and well oxygenated habitats.

In addition to the odonates, aquatic insects mostly sensitive to water pollution

are the Ephemeropterans (may flies), plecopterans (stone fly) and tricopterans

(caddisfly). nymphs caddisflies are integral component of benthic fauna of the most

relatively undisturbed streams (Hynes, 1960; Olive, 1976). The sparse distribution,

low numerical abundance and low species diversity in present study is therefore,

indicative of the ponds that have been severely disturbed. Thus, by cataloguing the

number and species composition in these derelict water bodies, it may be possible to

determine what type of pollutants may be present as well as the pollution levels in

water.

Aquatic Dipterans are the most ubiquitous of the entire macrobenthic

invertebrate group in tropics (Victor and Onomivbpri, 1996). Due to eutrophic nature

of Dipteran larvae, they have been used as reliable indicators of aquatic pollution and

related perturbation (Victor and Onomivbpri, 1996). The preponderance of

saprophilic insects (insects restricted to heavily enriched habits e.g. ‘bloodworm’

midge larva) at all the selected sites understudy clearly indicate that all these water

bodies are organically enriched. This further indicates that these water bodies are

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grossly polluted with poor water quality characterized by low oxygen and high

nutrient concentration (eutrophic).

Chironomid larvae are an important food source for fish and waterfowls

(Cibrowski and Corkum, 2003).The adults provide food for amphibians, bats and

martins and swallows (Smits et al., 2005).Chironomids can be important freshwater

indicator. The larvae of some specific species are sensitive to specific forms of

pollution, whereas others are quite tolerant. Because larvae feed on the dead plant and

animal debris in aquatic sediment, they are exposed to contaminants contained in the

organic matter. The fact that the chironomids live in such a wide variety of habitat

makes them especially useful indicators. Large numbers of pollution tolerant

chronomids are often indicative of poor water quality (characterized by low dissolved

oxygen and high nutrient concentrations). These species have a substance similar to

haemoglobin in their bloods which allow them to survive in places where the oxygen

has become depleted. Excellent water quality conditions are often characterized by

relatively low densities and high species diversity (50% or more of the species being

chironomids). Chironomids species diversity and their sensitivity to eutrophic

conditions have been used to create trophic classification of lakes into oligotrophic,

mesotrophic and eutrophic (Saether, 1975; Winnel and White 1985; Langdon et al.,

2006). The high abundance of Chironomus spp. in all the selected ponds in present

study indicates that these water bodies are highly eutrophic.

Dipteran flies are the most important arthropod vectors of disease in humans

and other animals. For example, malaria is believed to have killed more human beings

than any other known disease and is still a major cause of illness in many tropical

countries. Mosquitoes are vectors of filariasis (elephantiasis), malaria and viruses

including yellow fever and dengue fever. About 70 species of Anopheles mosquito

transmit an estimated 500,000 cases of malaria every year. Yellow fever is transmitted

by single mosquito, Aedes aegypti. Dengue or break bone fever, usually a non-fatal

disease leaves its victim debilitated for several weeks, is transmitted by Aedes aegypti

and A. albopictus. Filariasis, primarily a disease of people of Africa, the Orient and

the Pacific Islands, is caused by a minute round worm whose larvae are transmitted by

a few species of Anopheles, Culex and Aedes.

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The mosquito culex has been reported from grossly polluted shallow waters

(Hynes, 1960), and is presumably favoured by the rich supply of particulate organic

matter on which it feeds. The presence of Culex and Stratiomyids (Odontomyia

cincta) during present study also indicates that these water bodies are grossly

polluted.

Aquatic Hemiptera holds an important place in the ecology of fresh water

ecosystems. They are important food to many organisms including fish, amphibians,

water fowl and many other animals (Clarke, 1992). They generally have an

intermediate place in the food chain, apart from being eaten, are often important

predators too (Runck and Blinn. 1994). Hemipterans are exceedingly important in

relation to fish production. They are the primary food for many wild and cultivable

fishes, which make them valuable predators, are also occasional pests in the manmade

nursery ponds for fish culture where they feed on young fish. Certain families of bugs

may be utilized in the biological control of mosquito larvae (Ohba and Nakasuji.

2006; Saha et al., 2007).

The species of predatory aquatic bugs (Nepoidea, including Belostomatidae

and Nepidae) have been designated as threatened-vulnerable species in Red Book of

Japan (IUCN, 1990) and are regarded as effective predators of fresh water snails and

mosquito larvae (Ohba and Nakasuji, 2006). These insects are more voracious

predators and can fly to different bodies of water. This makes them more important

mosquito regulator than even the widely used mosquito-fish which cannot move out

of one body of water. Organizations’ as well as other researchers are looking into use

of predators for mosquito control (Neri- Barbosa et al., 1997), and there is even some

concern that insecticide run-off could be damaging to the population of these

important predators (Vasuki, 1996).

These insects are also highly important in relation to fish population, which

makes them important to humans. They are primary food of many wild fishes, which

make them valuable to sport fisheries. In fact, many fishing lures have been modeled

off of aquatic Hemipterans (Mc Cafferty, 1981). As a side note, these predators are

also occasional pests in the manmade fish hatcheries where they feed on the young

fish (Mc Cafferty, 1981).

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Environmental reclamation of aquatic habitats is aided by aquatic Hemipterans

which often can function as bio-indicators. These bugs, since they can survive in

heavily polluted areas, are often used to gauge the toxins in an environment (Papacek,

2001 and Wollmann, 2000).

Finally, in many cultures these insects are eaten and enjoyed. For example,

Mangdana, as species of giant water bug, that is enjoyed by Thailand people in

stirfiries and salads (Glausiusz, 2004). Because of large size of those insects, there is

presumably a lot of “meat” from one insect making them a good source of food.

Ephemeropterans (mayflies) are one of the most important herbivorous

invertebrate aquatic insects. They are insects of moderate size with an incomplete

metamorphosis. The immature stages of mayflies are aquatic. Ephemeroptera larvae

are recognized worldwide for their sensitivity to oxygen depletion, and are therefore

commonly used as bioindicators in many monitoring programmes. Mayflies are

considered as “keystone” species and their presence is believed to be an important

indicator of oligotrophic to mesotrophic (low to moderately productive) condition in

running waters (Barbour et al., 1999; Bauernifeind and Moog, 2000). A high

sensitivity of mayfly taxa to oxygen depletion, acidification, and various contaminants

including metals, ammonia and other chemicals was demonstrated in both

observational and experimental studies (Hubbard and Peters, 1978; Moog et al., 1997;

Hickey and clements, 1998).Various biological indices including mayflies to asses

water quality have been developed over the years (Lenat, 1988; Kerans and Karr,

1994). On contrary mayflies inhabiting lentic waters (e.g. lakes and ponds), have been

poorly used in biomonotoring programmes (Madenjian et al., 1998). Nevertheless, in

such environments, we would expect that mayflies also integrate some aspect of water

quality. Epemeroptera have also other advantages for monitoring; they are highly

visible, relatively easy to sample and are represented by a few species in such

habitats, which makes identification easier. The importance of Ephemeroptera as a

part of functioning aquatic ecosystem is recognized worldwide as shown by many

food studies; mayfly nymphs consume epiphytic algae and fine particulate organic

matter (Francis et al., 2010).

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The mayfly naiads are an important source of food for fish and other aquatic

wildlife. Anglers often use mayflies as bait, or tie “flies” that are made to resemble

imagos and subimagos. The larvae, as primary consumers, filter and remove large

amounts of nutrients from the water and are important as food for other aquatic

organisms. The winged stage facilitates nutrient and energy exportation from aquatic

to terrestrial ecosystems. A few larvae burrow in wooden structures, and when some

species that form massive swarms are attracted to town lights, they cause allergy-

related problems for some people.

In present study, Ephemeropterans were sparsely represented at all the

selected water bodies. The main reasons for their low population density and low

diversity in present study could be related to habitat degradation by pollution.

Plecoptera (stone flies) represents a very important component of ponds both

as biomass and as diversity of ecological roles, acting as primary or secondary

consumers and as prey for the other macro-vertebrates and fishes, including those of

economic importance. From a scientific point of view, they have been used as

biogeographical indicators and in evolutionary research. There importance as human

food is scarce, although some big species are consumed in the diet of some cultures.

Plecoptera (stoneflies) are a source of food for many game fishes. They have been

used for centuries in the sport of fly fishing, and fishermen have good knowledge of

them. They are used as biological indicators of water quality, especially dissolved

oxygen levels, thus deteriorating populations of stoneflies mean that poor water

quality threatens the health of aquatic ecosystem. Stone flies do not cause economic

damage to agricultural crops although some damage to fruit trees and ornamental

plants by adult Taeniopterygidae has been reported.

The absence of plecoptera during present study clearly indicates the water

quality degradation and physical alteration of these derelict water bodies under study.

Moreover, it is also clear from the study that Plecoptera is a sensitive order of aquatic

insects and is restricted to habitats where there is a little human interference, clear

water, and high dissolved oxygen content.

Aquatic insects are used as source of food by man, in addition of being a part

of food chain in aquatic ecosystems e.g. amongst aquatic insects Coleopterans are

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used as food in many countries of the world. The list of the edible insects of the world

(Elorduy et al., 2009) shows that the number of edible aquatic beetles is not very high

(6.58 %). However, it has been observed that in some Asian countries, such as Japan,

China, Thailand, Indonesia (Java and Bali) and Vietnam, the consumption of aquatic

insects is more common (Elorduy et al., 2009).

The genera of aquatic beetles commonly consumed in different countries of

the world are Cybister, Dystiscus, Hydrophilus, and Peltodytes etc. These genera

recorded in present study clearly show their nutritional importance. Beetles are highly

prized in the kitchen in many countries. They are prepared roasted or smoked and are

used in “tamales”, “quesadillas”, “sopes”, etc. Either they are boiled in salt water and

then combined with pepper and lemon, or they are dried in the sun. Some people eat

them alive.

In addition to their nutritional value, some economists have investigated the

potential for edible insects to provide income and generate jobs for rural population.

This income could be provided by capturing and preparing edible insects or even

raising them as “protocultures”. Different kinds of care is given by people in rural

areas to some species, in order to avoid falling stocks by predation, parasitism or lack

of food as well as change in temperature e.g., increasing the organic matter content in

the water where beetles and other aquatic insects are present or doing formal cultures,

which also then could be transported to urban cultures or semi-urban areas to sell.

Thus, they are highly prized and are also subject to national and international trade.

Trichoptera (caddisflies) are small to medium-sized insects, somewhat similar

to moths in general appearance. From an ecological perspective, Trichoptera are

important processors of organic matter. As processors of organic matter, collectively

known as functional feeding groups (FFG) of animals, they display the full array of

feeding modes (Cummins, 1973). In lotic water filter feeding, shelter constructing

species are important predators of black fly larvae and help to keep population levels

of the pest species at acceptable levels (De Moore, 1992). Trichopterans feed on

debris, cleaning the freshwater ecosystem in which they live besides being an

important source of food for fish.Trichoptera larvae, pupae and adults also form an

important link in the food chain and they have also been used extensively by trout

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fishing enthusiasts as models for “flies” (McCafferty, 1981). Although a few species

have been recorded as pests in rice paddies, most caddisflies have very little economic

importance.

Probably the most important aspect of ecological diversity among

Trichopterans is the ability to produce silk. Silk production has enabled caddisflies to

exploit a wide range of aquatic habitats. Silk utilization is different in most families

and has more or less defined the ecological role of caddisflies. According to Mackay

and Wiggins (1978), three modes of existence have resulted from silk utilization.

Some families such as caseless, predatory Rhyacophiloidea spin only a thin thread

while moving along the substrate. Other more sedentary larvae such as the

Hydropsychoidae spin nets or fixed shelters which serve as food capture device. The

third and probably most significant utilization of silk production is the construction of

mobile cases by such families as the limnephiloidae.

Five groups within the three superfamilies of Trichoptera have been identified

based on case - building behavior alone (Malick, 2010).This behavior has enhanced

defensive capabilities which have allowed subsequent improvements in habitat

selection and ecological diversity. Case-building behavior is usually species specific

although construction may vary depending upon available habitat. Cases function as

ballast camouflage, and mechanical defenses (Malick, 2010). The ability of larval

Trichoptera, therefore, to construct cases from silk and surrounding material has led to

their ecological diversification and utilization of habitats unavailable to other aquatic

macro -invertebrates.

Most case - building species construct cases of material from their immediate

surroundings. Malick (2010) divides case construction into organic and mineral

groups. The case size, shape, and material choice are usually species specific although

some modifications may occur due to limited resource availability. It has been

demonstrated (Otto, 1987b; Rowlands and Hansell, 1987) that caseless larvae are

preferentially preyed upon more than cased individuals and avoid cased and uncased

Trichopteran larva. Thus, case building caddisfly species have developed a defense

suitable for aquatic environments that allow them to utilize optimal microclimate

which other non-case building species cannot because of predation pressure. Case

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building species, therefore, may have an advantage in occupying feeding patches and

habitats which non-case building species would not inhabit for risk of predation.

Salmon and other fishes are attracted by caddisfly larvae, pupae, and adults,

leading to the creation of a series of sophisticated patterns for fly-fishing that imitate

the different stages of species from different regions. Some species gnaw on wood

structures in the water, while other species cause damage to rice fields and to aquatic

ornamental and commercial plants. Adults are often attracted to lights, where

thousands of them may appear simultaneously and cause damage to air conditioners

and other devices. Caddisflies also may reduce visibility when they lay eggs on roads;

apparently they confuse the shine of roads at night with water. The cementing

substance of the eggs and eggs broken by tires can be transformed into a gelatin that is

hazardous for drivers.

Although, caddisflies recorded during the present course of study are not

generally considered to be of great economic importance as pests, they are

beneficially important in the trophic dynamics and energy flow in aquatic ecosystems.

The larvae are also useful as biological indicator organisms for assessing water

quality. Extensive use of them has been made for this purpose because larvae of

different species vary in sensitivity to various types of pollution (Resh and Unzicker

1975, Resh 1993, Dohet 2002), and because the taxonomy of the group is relatively

well known.

Besides these Trichopterans (caddisflies) feed on debris, cleaning the

freshwater ecosystem in which they live besides being an important source of food for

fish.Trichoptera larvae, pupae and adults also form an important link in the food chain

and they have also been used extensively by trout fishing enthusiasts as models for

“flies” (McCafferty, 1981).Although a few species have been recorded as pests in rice

paddies, most caddisflies have very little economic importance.

Furthermore, it is probable that many of the aquatic insects of these derelict

water bodies under study might have gone extinct before their discovery as no study

have been documented in past and in fact, present study is the first of its kind in

Aligarh region.

Table - 1. Monthly variations in Air, Water temperature, Transparency and Conductivity in Ponds I, II, III, IV and V

from February 2009 to January 2010.

Air Temperature (ºC) Water Temperature (ºC) Transparency (cm) Conductivity (µ S cm-1) Parameters Months I II III IV V I II III IV V I II III IV V I II III IV V

Feb.2009 20 20 23 22 23 18 18 19 19 20 17.50 31.00 42.50 22.50 57.50 1484 1378 1398 1450 1308

Mar. 27 25 25 28 26 25 22 23 25 23 12.50 27.00 47.00 45.00 42.00 786 1221 1022 803 1248

Apr. 28 29 30 30 26 26 27 28 27 24 15.00 26.00 36.00 16.00 26.00 794 1022 974 890 1050

May 34 35 31 35 35 31 32 28 32 32 14.00 19.00 26.00 11.00 19.00 844 965 1033 832 1021

Jun. 38 38 37 34 35 34 34 34 31 32 14.00 22.00 25.00 17.50 19.00 925 1223 1147 955 978

Jul. 36 34 33 36 34 34 32 31 34 31 9.00 26.00 30.25 11.00 33.75 1461 1697 1860 1789 1625

Aug. 34 32 32 33 32 32 30 30 31 31 8.75 27.00 32.50 27.50 32.50 1958 1433 1735 1497 1505

Sep. 34 35 34 32 31 31 33 32 30 32 13.75 23.00 25.75 36.00 27.00 1635 1555 1960 1621 1334

Oct. 23 25 23 25 24 21 23 21 23 22 19.00 37.00 45.00 42.50 34.00 1789 1383 1545 1307 1095

Nov. 20 21 21 22 19 18 18 19 20 18 25.00 39.00 36.00 41.25 36.25 1861 1429 1497 1316 1377

Dec. 16 18 18 16 17 14 16 16 15 15 26.00 31.00 41.25 38.75 35.00 1960 1490 1508 1391 1547

Jan.2010 15 16 16 15 15 12 14 13 14 12 31.00 38.00 39.00 42.00 45.00 1963 1521 1543 1485 1678

Mean 27.08 27.33 26.92 27.33 26.42 24.67 24.92 24.50 25.08 24.33 17.13 28.83 35.52 29.25 33.92 1455.0 1359.8 1435.2 1278.0 1313.8

S.D. 8.14 7.51 6.80 7.28 7.06 7.90 7.29 6.90 6.86 7.20 6.94 6.49 7.68 13.12 10.91 487.5 216.1 331.4 329.4 242.2

Table - 2. Monthly variations in pH, Dissolved oxygen and Free carbon dioxide in Ponds I, II, III, IV and V


pH Dissolved oxygen Free CO2 (mg/L) Parameters Months I II III IV V I II III IV V I II III IV V

Feb.2009 8.5 8.0 8.0 9.0 8.3 7.6 6.8 6.4 6.0 6.2 0 11.0 10.0 0 22.0

Mar. 9.0 8.2 8.1 9.1 8.4 3.6 7.0 6.2 5.8 5.0 0 8.0 21.0 0 18.0

Apr. 9.0 8.0 8.5 9.1 8.0 4.6 5.0 3.2 4.0 4.2 0 12.0 18.0 0 24.0

May 9.2 8.2 7.8 9.3 8.8 4.0 3.8 4.8 4.0 3.8 0 16.0 19.0 0 22.0

Jun. 9.4 8.3 8.0 9.3 8.0 4.8 3.6 4.0 4.8 4.2 0 19.0 25.0 0 20.0

Jul. 9.4 8.2 8.3 9.5 8.2 10.0 6.0 5.0 5.0 4.6 0 23.0 45.0 0 24.0

Aug. 9.1 8.3 8.2 9.0 8.4 4.0 4.0 4.2 5.0 4.4 0 20.0 35.0 0 30.0

Sep. 8.6 7.8 7.9 8.7 8.8 5.0 4.0 3.8 3.6 3.4 0 20.0 35.0 0 0

Oct. 8.5 7.6 8.2 8.6 8.7 4.6 3.0 3.4 6.0 3.1 0 25.0 25.0 0 27.0

Nov. 8.9 8.0 8.2 8.8 8.6 6.0 3.0 3.6 5.8 6.0 0 35.0 32.0 0 0

Dec. 8.7 8.0 7.9 8.7 8.9 8.6 7.8 7.4 10.0 7.6 0 30.0 35.0 0 0

Jan.2010 8.8 8.2 8.2 8.5 8.8 12.0 8.6 8.2 8.0 8.0 0 28.0 30.0 0 0

Mean 8.9 8.1 8.1 9.0 8.5 6.2 5.2 5.0 5.7 5.0 0 20.6 27.5 0.0 15.6

S.D. 0.32 0.21 0.20 0.31 0.32 2.7 2.0 1.7 1.8 1.6 0 8.1 9.7 0.0 11.9

Table - 3. Monthly variations in Depth and Water colour in Ponds I, II, III, IV and V from February 2009 to January 2010.

Depth (cm) Water colour Parameters

Months I II III IV V I II III IV V

Feb.2009 76 65 87 73 119 Slight greenish Slight brown Slight brown Slight greenish Slight greenish

Mar. 73 61 83 70 113 Slight greenish Slight brown Slight brown Slight greenish Slight greenish

Apr. 57 51 67 60 95 Greenish Green yellowish Green yellowish Greenish Greenish

May 51 45 58 46 84 Greenish Green yellowish Green yellowish Greenish Greenish

Jun. 52 40 51 41 77 Greenish Green yellowish Green yellowish Greenish Greenish

Jul. 87 75 87 82 133 Greenish Brownish Brownish Greenish Greenish

Aug. 100 87 95 89 145 Greenish Brownish Brownish Greenish Greenish

Sep. 96 91 99 87 149 Greenish Brownish Brownish Greenish Greenish

Oct. 81 74 84 81 132 Slight greenish Slight brown Slight brown Slight greenish Slight greenish

Nov. 81 71 80 76 127 Slight greenish Slight brown Slight brown Slight greenish Slight greenish

Dec. 82 67 83 70 129 Slight greenish Brown Brown Slight greenish Slight greenish

Jan.2010 79 63 85 72 124 Slight greenish Brown Brown Slight greenish Slight greenish

Mean 76.3 65.8 79.9 70.6 118.9 - - - - -

S.D. 15.8 15.4 14.3 15.0 22.8 - - - - -

Table - 4. Monthly variations in Total solids, Total dissolved solids and Total suspended solids in Ponds I, II, III, IV and V


Total solids (mg/L) Total dissolved solids (mg/L) Total suspended solids (mg/L) Parameters Months I II III IV V I II III IV V I II III IV V

Feb.2009 1590 1400 1618 2100 1750 1000 740 1223 1720 1250 590 460 395 677 500

Mar. 1730 1360 1528 1600 1860 1169 760 965 1215 1300 561 600 563 385 560

Apr. 1800 1665 2040 2070 1980 1220 1100 1600 1510 1415 580 550 440 560 565

May 1765 1690 2610 1860 2200 1317 1123 2080 1400 1650 448 567 530 460 550

Jun. 1600 1960 2030 2100 1840 1060 1300 1203 1650 1200 540 660 827 450 640

Jul. 2720 2400 2680 2800 2970 1870 1400 2073 1880 1850 850 1000 810 920 1120

Aug. 2600 2590 2550 2900 2800 1600 1673 1800 1950 1600 1000 917 750 950 1200

Sep. 2460 2368 3050 2750 2500 1480 1250 2135 2010 1825 980 1118 915 740 675

Oct. 2000 1590 2584 2160 1820 1320 795 1900 1300 1310 680 795 684 860 510

Nov. 1660 1400 1218 1750 1460 1020 900 700 1200 1120 640 500 518 550 340

Dec. 1400 1360 1210 1600 1400 900 880 755 920 950 500 480 455 680 450

Jan.2010 1545 1230 1440 1650 1530 1145 800 840 136 1000 400 430 600 290 530

Mean 1905.8 1751.1 2046.5 2111.7 2009.2 1258.4 1060.1 1439.5 1407.6 1372.5 647.4 673.1 623.9 626.8 636.7

S.D. 443.4 468.1 637.8 470.8 511.9 279.7 298.3 553.2 521.7 301.3 196.9 230.2 170.3 214.1 259.4

Table - 5. Monthly variations in Total alkalinity, Carbonate, Bicarbonate and Hydroxides in Ponds I, II, III, IV and V


Total alkalinity (mg/L) Carbonate (mg/L) Bicarbonate (mg/L) Hydroxides (mg/L) Parameters Months I II III IV V I II III IV V I II III IV V I II III IV V

Feb.2009 300 292 306 350 309 80 – – 260 – 220 292 306 – 309 – – – 90 –

Mar. 250 350 330 180 410 10 – – 130 – 240 350 330 – 360 – – – 50 –

Apr. 350 307 320 320 500 300 – – 220 – 50 307 320 100 500 – – – – –

May 470 280 358 590 430 286 – – 480 – 184 280 358 110 430 – – – – –

Jun. 365 348 330 580 465 200 – – 500 – 165 348 330 80 465 – – – – –

Jul. 450 288 252 480 390 400 – – 380 – 50 288 352 100 390 – – – – –

Aug. 210 172 390 270 230 200 – – 160 – 10 172 390 110 230 – – – – –

Sep. 180 285 250 250 160 125 – – 200 140 35 285 250 50 20 – – – – –

Oct. 180 256 259 200 145 160 – – 100 – 20 265 259 100 145 – – – – –

Nov. 270 250 407 300 200 225 – – 220 140 45 250 407 80 60 – – – – –

Dec. 170 209 270 200 300 160 – – 140 100 10 209 270 60 200 – – – – –

Jan.2010 260 190 356 210 230 140 – – 150 160 120 190 356 60 70 – – – – –

Mean 287.9 268.9 319.0 327.5 314.1 190.5 - - 245.0 135.0 95.8 269.7 327.3 85.0 269.9 - - - 70.0 -

S.D. 102.3 56.6 53.4 146.0 122.6 104.4 - - 136.0 25.2 85.4 56.5 49.6 22.2 175.9 - - - 28.3 -

Table - 6. Monthly variations in Hardness, Calcium and Magnesium in Ponds I, II, III, IV and V


Hardness (mg/L) Calcium (mg/L) Magnesium (mg/L) Parameters Months I II III IV V I II III IV V I II III IV V

Feb.2009 110 124 100 168 164 64.12 72.00 65.73 56.00 89.77 25.05 39.55 26.37 21.09 25.05

Mar. 144 262 164 200 116 48.00 80.16 88.17 58.51 64.12 13.18 29.00 23.75 27.69 29.00

Apr. 182 110 120 260 112 56.00 52.90 67.33 48.00 60.12 26.37 32.90 27.69 32.94 36.92

May 220 126 188 224 118 66.53 36.07 72.14 64.12 58.51 38.24 35.60 30.32 43.51 27.69

Jun. 230 160 196 202 150 72.00 70.54 60.00 57.71 41.60 42.19 44.83 34.28 38.24 31.64

Jul. 212 140 180 174 170 62.50 48.00 64.00 56.00 48.00 32.94 18.46 25.05 22.41 26.37

Aug. 160 152 170 186 164 80.16 54.00 58.51 52.00 46.50 26.37 23.75 21.09 23.75 29.00

Sep. 142 130 116 180 134 40.00 42.48 52.00 55.31 38.47 23.75 19.77 22.41 32.94 25.05

Oct. 152 180 188 166 140 51.30 60.00 62.52 52.00 40.00 22.41 21.09 18.46 19.77 25.05

Nov. 180 220 240 150 156 60.12 68.13 72.14 44.88 48.00 19.77 32.94 30.32 29.00 27.69

Dec. 120 158 150 132 140 36.00 52.10 48.00 36.87 36.87 21.10 17.34 22.41 25.05 23.75

Jan.2010 164 120 116 124 112 49.69 56.00 66.53 52.10 52.10 17.14 23.75 15.82 22.41 18.46

Mean 168.0 156.8 160.7 180.5 139.7 57.20 57.70 64.76 52.79 52.01 25.71 28.25 24.83 28.23 27.14

S.D. 38.2 44.9 41.5 38.1 21.5 12.90 13.00 10.40 7.10 14.80 8.40 8.90 5.30 7.40 4.50

Table - 7. Monthly variations in Nitrate-Nitrogen (NO3–N), Phosphate-Phosphorus (PO4–P) and Chloride (mg/L) in ponds I, II, III, IV and

V from February 2009 to January 2010.

NO3–N (mg/L) PO4–P (mg/L) Chloride (mg/L) Parameters

Months I II III IV V I II III IV V I II III IV V

Feb.2009 0.112 0.088 0.081 0.056 0.092 0.420 0.290 0.584 0.460 0.550 199.0 142.0 135.0 326.0 142.0

Mar. 0.087 0.113 0.117 0.131 0.081 0.289 0.541 0.510 0.419 0.550 312.0 142.0 142.0 270.0 134.2

Apr. 0.131 0.153 0.131 0.175 0.122 0.950 0.941 0.867 1.425 0.785 326.0 156.0 156.0 397.0 142.0

May 0.170 0.141 0.151 0.131 0.157 0.919 0.785 0.950 0.867 0.707 482.0 244.0 184.0 495.0 200.0

Jun. 0.161 0.153 0.123 0.170 0.195 1.190 1.090 0.717 1.040 0.965 610.0 184.6 227.0 624.0 244.0

Jul. 0.240 0.237 0.182 0.156 0.267 0.570 0.785 0.549 0.761 0.686 364.0 156.0 198.0 298.0 156.0

Aug. 0.175 0.163 0.202 0.195 0.253 0.587 0.695 0.586 0.867 0.590 312.0 142.0 184.6 255.0 127.8

Sep. 0.240 0.151 0.278 0.161 0.195 0.761 0.635 0.761 0.695 0.541 276.9 169.0 156.2 127.8 170.4

Oct. 0.156 0.141 0.195 0.092 0.123 0.586 0.541 0.420 0.620 0.635 255.0 127.8 156.2 166.0 156.4

Nov. 0.117 0.141 0.122 0.156 0.161 0.420 0.321 0.510 0.586 0.541 269.8 142.0 142.0 170.0 123.5

Dec. 0.086 0.050 0.081 0.071 0.122 0.287 0.234 0.240 0.359 0.290 184.0 134.9 149.1 156.2 93.7

Jan.2010 0.056 0.096 0.051 0.092 0.081 0.240 0.191 0.289 0.390 0.226 227.0 113.6 184.6 127.0 99.4

Mean 0.144 0.136 0.143 0.132 0.154 0.602 0.587 0.582 0.707 0.589 318.1 154.5 167.9 284.3 149.1

S.D. 0.058 0.046 0.063 0.045 0.063 0.300 0.288 0.215 0.312 0.199 121.7 33.7 27.6 156.1 41.7

Table - 8a. Monthly Variations in aquatic insect population density (No./m2) in Pond I from February, 2009 to January, 2010

Months

Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Diptera Anopheles larva 5 7 6 10 14 12 18 15 11 10 19 12 Anopheles pupa – – – – 4 8 10 8 9 7 6 11 Chaoborus larva – 7 12 9 6 9 – 11 13 8 – – Chironomus larva 302 445 320 327 274 301 288 299 349 342 554 635 Chironomus pupa 22 28 31 – – – – – 27 25 39 51 Chrysops larva – – – – – – – – – – – – Culex larva 8 12 8 7 8 9 11 16 13 – 16 21 Culex pupa – – – – 4 5 7 5 9 – 12 8 Dictya pictipes (pupa) 9 7 8 6 7 8 – – – 5 – 13 Dixa larva – – – 7 9 7 7 14 8 5 11 – Eristalis larva – – 10 6 – 8 6 – 5 9 17 12 Helius larva – – – – – – – – – – – – Odontomyia cincta 5 7 – – 11 13 9 – 7 8 16 15 Pedicia larva 9 8 – – – 3 7 – – 10 13 12 Phalacrocera larva – 5 7 – 6 14 6 9 – – – 8 Pentaneura larva 6 7 6 – – – 3 – 8 15 9 Pilaria larva – – 3 8 – – – – 7 9 11 14 Tabanus larva – – 5 – – 6 10 7 11 – 10 15 Tipula larva 5 – – 7 6 – – – 7 9 8 14 Total 371 533 416 387 349 403 379 387 476 455 747 850

Continued …

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Hemiptera Belostoma sp. – – – 5 6 9 8 11 7 6 – – Buenoa sp. – 7 10 17 12 27 20 25 6 17 12 – Coroxid sp. – 9 12 8 10 22 28 21 – – 7 9 Gerris sp. – 6 5 6 8 7 8 12 7 – – – Hebrus sp. 5 8 7 – – – 14 – – 6 – 4 Hesperocorixa sp. 6 11 10 9 12 31 24 22 9 8 7 8 Mesovelia sp. – 3 – 6 7 11 – – 8 – – 5 Microvelia sp. 5 – – – – – – 6 7 9 6 – Nepa sp. – – 8 5 – 9 7 9 6 6 – – Neoplea striola 8 7 14 9 11 31 18 23 18 14 – – Notonecta insulata – 8 – – 9 14 15 21 12 – 9 – Pelocoris sp. – – – – 4 10 8 9 7 6 – – Ranatra sp. – – 7 5 7 9 – 8 10 5 – – Sigara sp. 5 – 3 6 5 10 14 11 9 – – – Total 29 59 76 76 91 190 164 178 106 77 41 26 Coleoptera Acilus larva – 5 9 8 6 4 5 7 – – – – Berosus larva 3 – 5 7 6 5 6 4 5 – – 3 Cybister larva 3 5 11 8 6 5 – – – 4 – – Coptotomus larva – – – – – – – – – – – – Dystiscus sp. – 7 6 7 8 5 – 6 – – 4 – Haliplus sp. 4 – 5 6 9 – 6 – – 5 – 5 Hydaticus sp. – 6 7 12 6 – 7 – – – – 5 Hydrochara sp. 5 4 – 8 9 7 5 5 – – 3 – Hydrophilus larva – 7 6 7 5 6 4 – 3 – – – Hydroporus larva – 8 14 9 7 5 6 – 6 – – – Peltodytes endentulus – 6 10 7 9 5 6 – – – 4 – Tropisternus larva 4 7 11 6 – – 5 – – 3 – 5 Total 19 55 84 85 71 42 50 22 14 12 11 18

Continued…

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Trichoptera Leptocella larva – 7 7 6 13 4 5 – – – 4 – Leuctorichia larva 6 3 7 9 7 8 4 – – 4 – – Limnephilus larva – 5 12 9 7 6 – 4 5 – – – Phryganaea larva 5 4 9 8 12 7 5 – – – – 6 Polycentropus larva – 4 7 11 6 5 4 – – – 3 – Ptilostomis larva case – – – – – – – – – – – – Trianodes larva 6 – 8 14 9 7 5 – – – 4 – Total 17 23 50 57 54 37 23 4 5 4 11 6 Odonata Aeschna nymph – – 7 8 12 6 6 8 4 – 5 – Argia nymph – – 6 14 9 5 4 5 10 – – 3 Coenagrion nymph 6 5 8 5 7 6 – 7 4 – – – Cordulia nymph – 4 9 6 8 – 7 5 6 – – 3 Enallagma nymph – 7 6 8 13 7 9 6 4 – – – Ischurna nymph 4 – – 5 14 8 6 5 – 3 4 – Total 10 16 36 46 63 32 32 36 28 3 9 6 Ephemeroptera Baetis hiemalis nymph – – 7 6 10 5 8 7 4 3 – – Caenis nymph – – – – – – – – – – – – Cinygmula nymph – 4 5 7 6 – – 5 5 6 – 3 Ephemerella nymph 3 5 4 8 7 9 5 – – – – 4 Heptageni nymph – 4 – – 8 5 7 6 4 5 3 – Total 3 13 16 21 31 19 20 18 13 14 3 7 G. Total 449 699 678 672 659 723 668 645 642 565 822 913

Table - 8b.

Monthly Variations in aquatic insect population density (No./m2) in Pond II from February, 2009 to January, 2010

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Diptera Anopheles larva 4 6 9 6 5 7 7 10 9 13 11 10 Anopheles pupa – – 3 4 6 – 4 6 5 5 7 6 Chaoborus larva 5 – 4 7 3 9 6 14 7 9 10 12 Chironomus larva 284 315 279 267 249 260 245 291 262 327 405 467 Chironomus pupa 26 20 – – – – 19 24 – 21 23 25 Chrysops larva – – – – – – – – – – – – Culex larva – 4 5 7 5 14 11 12 5 6 11 16 Culex pupa – – 6 3 7 – – 7 6 – 9 8 Dictya pictipes (pupa) – 6 – – 5 4 – – 5 7 8 8 Dixa larva 5 – – – 3 6 4 5 4 7 9 10 Eristalis larva – – – – – – – – – – – – Helius larva – – – – – – – – – – – – Odontomyia cincta – – – – – – – – – – – – Pedicia larva 6 – – – 3 – 6 4 7 7 9 – Phalacrocera larva – 3 4 – – – 7 – 6 8 13 12 Pentaneura larva 3 – 6 7 3 5 – – – – – 9 Pilaria larva – – – 3 5 – – – – – 10 8 Tabanus larva – 4 – 5 – – – – – 6 8 7 Tipula larva – – – – – – – – – – – – Total 333 358 316 309 294 305 309 373 316 416 533 598

Continued…

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Hemiptera Belostoma sp. – – – – – – – – – – – – Buenoa sp. 3 – 6 8 – 15 10 9 12 8 5 – Coroxid sp. – 6 7 12 9 13 16 11 8 7 – – Gerris sp. 5 7 – – 8 7 10 6 5 – 4 – Hebrus sp. – – – – – – – – – – – – Hesperocorixa sp. – – 5 7 6 13 11 12 9 5 7 4 Mesovelia sp. – – – – – – – – – – – – Microvelia sp. – – – 5 7 9 12 – – 4 – 3 Nepa sp. – – – – – – – – – – – – Neoplea striola – – – – – – – – – – – – Notonecta insulata – 3 – 6 9 13 12 9 – 5 4 – Pelocoris sp. – – – – – – – – – – – – Ranatra sp. 5 – 4 6 – 9 10 8 6 – – – Sigara sp. – – – – – – – – – – – – Total 13 16 22 44 39 79 81 55 40 29 20 7 Coleoptera Acilus larva 3 5 8 7 6 4 5 – – – 3 – Berosus larva – – – – – – – – – – – – Cybister larva 4 5 6 9 7 6 – – 4 – – 3 Coptotomus larva – – – – – – – – – – – – Dystiscus sp. 5 6 9 6 9 7 6 – – – – 4 Haliplus sp. – – 7 5 6 – 3 5 – 4 5 – Hydaticus larva – – – – – – – – – – – – Hydrochara larva – – – – – – – – – – – – Hydrophilus larva – – – – – – – – – – – – Hydroporus larva – – – – – – – – – – – – Peltodytes endentulus 5 4 9 5 6 7 – – 3 – – – Tropisternus larva – – 6 9 5 6 8 – 5 4 – – Total 17 20 45 41 39 30 22 5 12 8 8 7

Continued…

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Trichoptera Leptocella larva – – – – – – – – – – – – Leuctorichia larva – – 5 5 4 6 7 – – – – – Limnephilus larva – – – – – – – – – – – – Phryganaea larva 4 3 6 8 5 4 – – 3 – – – Polycentropus larva 6 5 4 7 9 – 5 – – 4 – 3 Ptilostomis larva case – – – – – – – – – – – – Trianodes larva 3 6 – 7 5 11 7 4 – – 4 – Total 13 14 15 27 23 21 19 4 3 4 4 3 Odonata Aeschna nymph 3 5 8 7 6 5 6 4 – – – – Argia nymph – – – – – – – – – – – – Coenagrion nymph – – – – – – – – – – – – Cordulia nymph – – – – – – – – – – – – Enallagma nymph – 4 7 5 9 6 7 – 6 5 3 – Ischurna nymph – – – – – – – – – – – – Total 3 9 15 12 15 11 13 4 6 5 3 0 Ephemeroptera Baetis hiemalis nymph – 3 6 5 5 4 7 6 – – 4 – Caenis nymph – – – – – – – – – – – – Cinygmula nymph – – – – – – – – – – – – Ephemerella nymph – – – – – – – – – – – – Heptageni nymph – – 6 5 4 – 6 4 5 3 – 4 Total 0 3 12 10 9 4 13 10 5 3 4 4 G. Total 379 420 425 443 419 450 457 451 382 465 572 619

Table - 8 c.

Monthly Variations in aquatic insect population density (No./m2) in Pond III from February, 2009 to January, 2010

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Diptera Anopheles larva 6 7 12 10 8 7 12 14 10 9 12 16 Anopheles pupa – – 5 – – 5 6 8 5 4 7 9 Chaoborus larva – – 6 5 9 14 11 7 6 10 16 11 Chironomus larva 402 398 304 295 267 288 315 198 195 329 545 501 Chironomus pupa 17 23 20 17 – – 24 28 27 29 41 55 Chrysops larva – – – – – – – – – – – – Culex larva – 5 7 6 8 13 12 9 8 11 17 20 Culex pupa – 6 5 – 3 4 7 – – – 9 14 Dictya pictipes (pupa) 6 – 3 4 – – – – – 8 10 9 Dixa larva 3 – 6 8 7 9 7 6 12 – – – Eristalis larva – 4 7 6 – – 8 9 7 6 12 15 Helius larva 5 6 – 3 5 4 – – – – 7 10 Odontomyia cincta 5 – – – – 7 6 5 8 – 9 14 Pedicia larva – – – – – – – – – – – – Phalacrocera larva 7 – – 6 8 7 6 3 7 6 10 9 Pentaneura larva – – – 4 7 6 – – – 10 7 9 Pilaria larva 8 6 3 – – – – – – 7 9 8 Tabanus larva – – 7 8 6 7 9 9 5 6 14 11 Tipula larva – – – – – – – – – – – – Total 459 455 385 372 328 371 423 296 290 435 725 711

Continued…

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Hemiptera Belostoma sp. 5 – – 4 7 6 8 – 7 – – – Buenoa sp. – – 14 20 14 25 24 22 15 12 9 7 Coroxid sp. – 9 15 12 11 19 16 17 11 – 5 – Gerris sp. 6 – 8 6 7 4 10 13 8 6 – 5 Hebrus sp. 7 5 6 8 – – – – 5 – 4 – Hesperocorixa sp. – 10 13 11 12 18 19 16 9 11 8 7 Mesovelia sp. – 4 – – 9 7 8 11 – – – 5 Microvelia sp. 6 7 5 – – 9 16 – – 5 – 3 Nepa sp. 4 8 – – 12 8 9 7 8 – – – Neoplea striola – – 9 12 – 21 17 24 12 5 – 4 Notonecta insulata – 9 12 9 11 15 12 14 9 – 3 – Pelocoris sp. – 5 9 6 7 – – 6 4 – – – Ranatra sp. 4 – 3 4 5 7 6 6 – – – – Sigara sp. – – 6 7 5 11 17 14 9 – – – Total 32 57 100 99 100 150 162 150 97 39 29 31 Coleoptera Acilus larva 4 5 6 4 12 8 – – 4 – – 3 Berosus larva – – 11 14 9 10 7 6 – – 5 – Cybister larva 6 4 9 8 6 4 5 – – 3 – – Coptotomus larva 5 3 – 7 9 8 – – – – 4 – Dystiscus sp. – 6 8 12 11 9 5 – 7 – – – Haliplus sp. – 9 10 9 6 7 6 7 – 5 – – Hydaticus larva 5 – 9 7 8 7 6 – 3 – – – Hydrochara larva 3 4 7 – – 4 5 – – – 3 4 Hydrophilus larva – 7 8 7 10 – – 4 – 5 – – Hydroporus larva 6 5 – 8 6 10 5 – – – 4 Peltodytes endentulus 5 – – – 8 5 7 4 5 – – 3 Tropisternus larva 6 8 11 10 9 6 – – – 5 – – Total 40 51 79 86 94 78 46 21 19 18 12 14

Continued…

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Trichoptera Leptocella larva 4 – 8 7 6 5 5 – – – – – Leuctorichia larva – 7 6 9 12 5 4 – – – – 5 Limnephilus larva – 5 8 9 7 – 6 5 – – 4 – Phryganaea larva 5 6 9 10 8 6 – – – – 4 – Polycentropus larva 3 5 7 4 6 4 – – – 5 – – Ptilostomis larva case – 4 8 7 4 3 5 – 4 – – – Trianodes larva 5 – – – 9 5 7 6 5 – – 4 Total 17 27 46 46 52 28 27 11 9 5 8 9 Odonata Aeschna nymph – 9 8 14 9 7 8 – – 5 – – Argia nymph – 7 9 7 6 – 7 8 4 – – – Coenagrion nymph 6 5 9 5 8 – – 7 5 – – 4 Cordulia nymph – 5 12 8 9 8 6 3 – – – – Enallagma nymph 3 – 6 7 – 6 5 8 5 4 – – Ischurna nymph – 6 5 7 9 10 12 – – – 3 4 Total 9 32 49 48 41 31 38 26 14 9 3 8 Ephemeroptera Baetis hiemalis nymph – 5 8 7 9 7 6 7 – 4 5 – Caenis nymph 3 4 – 8 6 4 7 5 – – – – Cinygmula nymph – 6 5 6 7 – 8 6 3 4 – – Ephemerella nymph – – 4 – 7 6 – 4 5 – 6 3 Heptageni nymph – 4 6 10 8 7 8 5 6 5 – – Total 3 19 23 31 37 24 29 27 14 13 11 3 G. Total 560 641 682 682 652 682 725 531 443 519 788 776

Table - 8 d.

Monthly Variations in aquatic insect population density (No./m2) in Pond IV from February, 2009 to January, 2010

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Diptera Anopheles larva 7 5 8 12 7 13 10 14 12 11 9 11 Anopheles pupa – – – 6 4 5 6 5 5 – 6 8 Chaoborus larva – 6 3 8 6 10 7 9 8 7 17 19 Chironomus larva 274 382 317 295 249 262 301 312 290 410 510 495 Chironomus pupa – – 27 23 – – 17 19 22 21 37 35 Chrysops larva – – – – 4 8 6 7 – – 12 10 Culex larva – 6 13 7 5 11 12 9 8 10 17 14 Culex pupa 5 7 – 3 – – – 6 5 10 8 Dictya pictipes (pupa) 6 5 – – – – 6 7 9 7 – – Dixa larva – – – 5 6 12 7 5 8 9 14 17 Eristalis larva 5 – 7 3 – – – – 6 8 11 9 Helius larva – 5 7 7 4 6 – – – 9 6 – Odontomyia cincta – 7 5 6 4 7 9 8 6 – 8 7 Pedicia larva – – – – – – – – – – – – Phalacrocera larva 7 6 7 – – – – – 4 7 15 9 Pentaneura larva – 7 6 8 7 – – – 3 – 9 7 Pilaria larva 5 4 – – 3 5 6 – – – – 8 Tabanus larva 4 7 9 – – – – 5 7 8 – – Tipula larva – – – – – – – – – – – – Total 313 447 409 383 299 339 387 400 394 512 681 657

Continued…

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Hemiptera Belostoma sp. – – – – – – – – – – – – Buenoa sp. – 7 – 10 17 21 25 19 14 10 4 – Coroxid sp. 8 15 11 8 16 20 22 26 10 – 5 – Gerris sp. – 3 5 7 6 8 8 7 5 6 – – Hebrus sp. – – – – – – – – – – – – Hesperocorixa sp. – 8 7 13 11 18 22 20 23 9 4 – Mesovelia sp. – 6 13 7 6 – – – 7 – 3 – Microvelia sp. 7 – – 10 7 14 11 13 – – 5 – Nepa sp. – – – 5 7 7 – 6 5 8 – 3 Neoplea striola – – 5 9 – 16 14 19 15 9 – – Notonecta insulata – – 5 7 9 12 20 15 – 6 – 4 Pelocoris sp. 3 6 – – – 8 12 9 5 – – 5 Ranatra sp. 7 4 7 – 8 6 14 8 – – – – Sigara sp. – 7 9 5 – 6 8 10 7 – 4 3 Total 25 56 62 81 87 136 156 152 91 48 25 15 Coleoptera Acilus larva 5 4 6 5 7 8 5 – – – – – Berosus larva – 6 9 11 10 7 6 7 – – – 5 Cybister larva 6 – – 8 6 12 7 – – 5 4 – Coptotomus larva 5 – 8 12 5 6 5 6 – – – 4 Dystiscus sp. – 5 7 9 8 6 – – – 5 4 – Haliplus sp. 7 6 11 10 9 – 7 – 5 – – – Hydaticus larva – 4 7 5 7 – 6 5 – – – – Hydrochara larva – – – – – – – – – – – – Hydrophilus larva – 3 6 14 9 5 4 4 – – – – Hydroporus larva 5 3 6 – – 7 6 5 – – – 4 Peltodytes endentulus 5 4 7 12 8 6 7 – – – 4 – Tropisternus larva – 6 8 7 6 4 – 4 3 – 5 – Total 33 41 75 93 75 61 53 31 8 10 17 13

Continued …

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Trichoptera Leptocella larva – – – – – – – – – – – – Leuctorichia larva 5 5 11 7 6 7 – 4 – – – – Limnephilus larva – 3 4 6 7 4 5 – – – – 4 Phryganaea larva 3 6 7 5 – 4 6 5 – – 4 – Polycentropus larva 3 – 10 14 6 7 5 – 4 3 – – Ptilostomis larva case 5 7 9 – 7 – 5 – – – 4 5 Trianodes larva – 3 7 5 8 4 – – – 5 – – Total 16 24 48 37 34 26 21 9 4 8 8 9 Odonata Aeschna nymph – – 8 6 9 7 6 5 – – – 4 Argia nymph – 5 6 9 8 – – 7 14 3 – – Coenagrion nymph 3 – – 15 10 8 7 9 5 – – – Cordulia nymph – – 11 7 9 9 8 6 34 – – Enallagma nymph 4 8 9 8 – – 6 7 4 – – 3 Ischurna nymph – 6 7 9 7 6 – 5 – – 4 – Total 7 19 41 54 43 30 27 39 57 3 4 7 Ephemeroptera Baetis hiemalis nymph – 5 10 8 11 7 10 9 – – 4 – Caenis nymph 3 6 – 5 7 – – 10 6 5 – – Cinygmula nymph – – 11 7 6 5 8 6 – – – 4 Ephemerella nymph – 4 7 11 – 7 6 – 4 3 5 – Heptageni nymph 3 – 9 12 8 10 9 5 8 5 – – Total 6 15 37 43 32 29 33 30 18 13 9 4 G. Total 400 602 672 691 570 621 677 661 572 594 744 705

Table – 8 e.

Monthly Variations in aquatic insect population density (No./m2) in Pond V from February, 2009 to January, 2010

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Diptera Anopheles larva 6 8 9 6 8 7 15 12 9 8 13 9 Anopheles pupa – 5 – – – – 7 5 4 5 6 6 Chaoborus larva – 4 6 9 6 9 8 10 6 9 – 11 Chironomus larva 510 481 390 367 306 381 478 482 565 402 685 701 Chironomus pupa 29 24 – – 19 25 – 31 25 29 41 39 Chrysops larva – – – – – – – – – – – – Culex larva 5 9 7 8 9 11 10 12 6 11 12 14 Culex pupa – – 5 5 4 – – 9 8 7 6 – Dictya pictipes (pupa) – 6 7 – 6 9 5 – – – 13 15 Dixa larva – – 3 9 7 6 9 7 – – 12 10 Eristalis larva 7 – – 6 5 – – – 7 8 16 11 Helius larva 5 8 3 6 – – – – – 7 11 15 Odontomyia cincta – – 6 8 7 8 9 7 11 8 16 12 Pedicia larva – – – – – – – – – – – – Phalacrocera larva 6 5 – – 3 5 8 – – 6 – 7 Pentaneura larva 8 6 5 7 8 – – – 6 3 13 9 Pilaria larva – – 3 – – – – 6 7 9 15 11 Tabanus larva – 5 8 3 6 7 6 11 – – – – Tipula larva 3 7 – – 5 6 – – – 7 8 11 Total 579 568 452 434 399 474 555 592 654 519 867 881

Continued…

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Hemiptera Belostoma sp. – – 7 5 6 15 12 10 8 – – – Buenoa sp. – 5 – – 13 17 15 18 12 10 9 9 Coroxid sp. – 7 12 15 9 29 27 32 14 11 – – Gerris sp. – 7 6 – – 11 10 9 3 – – 4 Hebrus sp. 4 5 8 7 6 – – – – 5 – 5 Hesperocorixa sp. – 10 12 9 15 24 19 29 16 13 11 – Mesovelia sp. – – 3 8 6 9 – – 7 – – 4 Microvelia sp. 3 6 – – 8 10 – 9 7 8 – – Nepa sp. – – – – – – – – – – – – Neoplea striola – 8 10 7 12 19 26 15 9 13 6 – Notonecta insulata – 5 9 12 8 13 9 14 – – – – Pelocoris sp. 7 3 8 6 9 14 8 – – – – – Ranatra sp. 4 7 – – 5 8 7 11 6 – – – Sigara sp. 7 – – 5 8 9 12 10 – – 3 7 Total 25 63 75 74 105 178 145 157 82 60 29 29 Coleoptera Acilus larva 5 4 8 14 7 5 8 – 4 – – – Berosus larva – 7 10 9 12 7 6 – – – – 5 Cybister larva – 6 7 14 8 8 6 – – 5 – – Coptotomus larva 7 – – – 7 6 8 – 6 5 4 – Dystiscus sp. 6 5 9 8 14 7 5 – – – – 3 Haliplus sp. 4 3 6 12 9 5 – 7 – – – – Hydaticus larva 3 – 12 9 7 – – – 5 – 5 – Hydrochara larva – – 14 8 9 7 6 5 – 4 – – Hydrophilus larva 6 7 11 – 7 5 8 5 – – – 4 Hydroporus larva 5 5 9 12 8 6 5 – – – 4 Peltodytes endentulus – 6 13 8 7 5 5 – – 3 – – Tropisternus larva 5 4 8 9 12 – – 5 – – 4 – Total 41 47 107 103 107 61 57 22 15 17 13 16

Continued…

Months Genera Feb.09 Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan.10 Trichoptera Leptocella larva 6 – 9 8 12 5 3 – – – 5 Leuctorichia larva 4 6 3 7 5 6 – – – – 4 – Limnephilus larva – – 10 9 11 6 7 6 – – 5 – Phryganaea larva 5 6 7 11 7 4 6 – – 5 – – Polycentropus larva – 4 8 7 6 7 4 – 5 – – 3 Ptilostomis larva case 6 5 – 12 – – 5 6 4 3 – – Trianodes larva – – – 8 11 4 – 5 – 4 3 4 Total 21 21 37 62 52 32 25 17 9 12 12 12 Odonata Aeschna nymph 4 – 6 8 7 5 7 – – – – 3 Argia nymph – 6 7 11 10 7 9 5 – – – – Coenagrion nymph – 4 8 7 14 8 5 7 6 – – – Cordulia nymph 4 – – 11 8 5 6 7 3 – – – Enallagma nymph – – 7 9 6 15 8 – – – 4 3 Ischurna nymph – 6 9 8 10 8 7 5 5 4 – – Total 8 16 37 54 55 48 42 24 14 4 4 6 Ephemeroptera Baetis hiemalis nymph – 5 8 12 7 8 7 6 6 4 – – Caenis nymph 4 – 6 5 6 – – 7 5 5 – – Cinygmula nymph – – 10 7 8 6 7 5 – – – 3 Ephemerella nymph 4 6 5 6 – 7 6 – 3 – 4 – Heptageni nymph – 6 – 13 7 6 9 7 – 3 – – Total 8 17 29 43 28 27 29 25 14 12 4 3 G. Total 682 732 737 770 746 820 853 837 788 624 929 947

Table - 9a. Statistical brief of various water quality parameters in Ponds I, II, III, IV

and Pond V.

Parameters Parameters Pond Correlation (r value)

Significant at P<0.05

Air Temperature Water Temperature I 0.997 II 0.996 III 0.995 IV 0.996 V 0.985 Water Temperature Transparency I -0.902 II -0.824 III -0.748 IV -0.654 V -0.653 Conductivity I -0.495 – II -0.206 – III 0.033 – IV -0.117 – V -0.400 – DO I -0.320 – II -0.589 III -0.662 IV -0.828 V -0.816 TS I 0.665 II 0.815 III 0.746 IV 0.681 V 0.800 TDS I 0.675 II 0.791 III 0.690 IV 0.772 V 0.832 TSS I 0.539 – II 0.707 III 0.656 IV 0.345 – V 0.612 NO3- N I 0.816 II 0.742 III 0.686 IV 0.746 V 0.736 PO4- P I 0.725 II 0.892 III 0.740 IV 0.645 V 0.743 Diptera I -0.764 II -0.745 III -0.761 IV -0.757



V -0.765 Hemiptera I 0.752 II 0.744 III 0.859 IV 0.830 V 0.814 Coleoptera I 0.661 II 0.609 III 0.713 IV 0.762 V 0.621 Trichoptera I 0.638 II 0.679 III 0.682 IV 0.593 V 0.670 Odonata I 0.846 II 0.748 III 0.813 IV 0.699 V 0.870 Ephemeroptera I 0.869 II 0.701 III 0.925 IV 0.892 V 0.892 Transparency DO I 0.348 – II 0.207 – III 0.416 – IV 0.532 – V 0.604 TDS I -0.668 II -0.576 III -0.507 – IV -0.524 – V -0.390 – TSS I -0.597 II -0.379 – III -0.581 IV -0.159 – V -0.169 – Conductivity TDS I 0.032 II 0.111 – III 0.284 – IV 0.142 – V -0.080 – pH Total alkalinity I 0.724 II 0.023 – III 0.110 – IV 0.784 V -0.645

Continued…

Continued…

Parameters Parameters Pond Correlation

(r value) Significant at P<0.05

TDS Total alkalinity I 0.270 – II -0.122 – III -0.388 – IV 0.381 – V 0.078 – Hardness I 0.336 – II -0.304 – III -0.053 – IV 0.496 – V 0.186 – Diptera I -0.384 – II -0.465 – III -0.703 IV -0.823 V -0.559 – Hemiptera I 0.879 II 0.876 III 0.854 IV 0.758 V 0.844 Coleoptera I 0.201 – II 0.407 – III 0.386 – IV 0.461 – V 0.338 – Trichoptera I 0.166 – II 0.560 – III 0.322 – IV 0.313 – V 0.379 – Odonata I 0.365 – II 0.640 III 0.557 – IV 0.423 – V 0.639 Ephemeroptera I 0.429 – II 0.734 III 0.559 – IV 0.608 V 0.750 Total alkalinity Hardness I 0.771 II 0.248 – III 0.365 – IV 0.447 – V -0.240 – NO3- N Diptera I -0.694 II -0.637 III -0.734 IV -0.392 – V -0.472 –

Continued…



Hemiptera I 0.915 II 0.785 III 0.861 IV 0.692 V 0.890 Coleoptera I 0.210 – II 0.450 – III 0.062 – IV 0.524 – V 0.263 – Trichoptera I 0.252 – II 0.485 – III 0.024 – IV 0.503 – V 0.309 – Odonata I 0.625 II 0.601 III 0.367 – IV 0.370 – V 0.658 Ephemeroptera I 0.618 II 0.382 – III 0.579 IV 0.741 V 0.576 – PO4- P Diptera I -0.667 II -0.756 III -0.691 IV -0.520 – V -0.913 Hemiptera I 0.335 – II 0.502 – III 0.510 – IV 0.399 – V 0.456 – Coleoptera I 0.713 II 0.831 III 0.717 IV 0.740 V 0.802 Trichoptera I 0.742 II 0.730 III 0.738 IV 0.807 V 0.725 Odonata I 0.931 II 0.917 III 0.828 IV 0.621 V 0.777

Continued…



Ephemeroptera I 0.820 II 0.699 III 0.696 IV 0.826 V 0.737 Chloride Diptera I -0.510 – II -0.500 – III -0.177 – IV -0.615 V -0.734 Hemiptera I 0.236 – II 0.284 – III 0.471 – IV 0.065 – V 0.406 – Coleoptera I 0.762 II 0.643 III 0.595 IV 0.858 V 0.673 Trichoptera I 0.816 II 0.714 III 0.579 IV 0.820 V 0.763 Odonata I 0.867 II 0.538 – III 0.483 – IV 0.460 – V 0.743 Ephemeroptera I 0.901 II 0.467 – III 0.620 IV 0.598 V 0.690

Table - 9b. Statistical brief of various water quality parameters in Ponds I, II, III, IV

and Pond V.



Water Temperature Shannon-Wiener index I 0.936 II 0.852 III 0.902 IV 0.948 V 0.849 Sorenson’s index I 0.853 II 0.736 III 0.836 IV 0.897 V 0.758 Berger-Parker’s index I 0.925 II 0.825 III 0.875 IV 0.930 V 0.812 Menhinick’s index I -0.216 – II -0.466 – III -0.090 – IV 0.033 – V -0.153 – Evenness I 0.939 II 0.870 III 0.887 IV 0.951 V 0.837 pH Shannon-Wiener index I 0.667 II 0.368 – III 0.131 – IV 0.648 V -0.556 – Sorenson’s index I 0.709 II 0.154 – III -0.037 – IV 0.792 V -0.627 Berger-Parker’s index I 0.659 II 0.395 – III 0.037 – IV 0.622 V -0.547 – Menhinick’s index I 0.187 – II 0.250 – III 0.007 – IV -0.180 – V 0.464 – Evenness I 0.645 II 0.348 – III 0.105 – IV 0.669



V -0.574 – D.O. Shannon-Wiener index I -0.310 – II -0.573 – III -0.708 IV -0.767 V -0.614 Sorenson’s index I -0.281 – II -0.714 III -0.343 – IV -0.709 V -0.641 Berger-Parker’s index I -0.183 – II -0.518 – III -0.708 IV -0.725 V -0.545 – Menhinick’s index I 0.380 – II 0.586 III 0.585 IV 0.198 – V 0.316 – Evenness I -0.315 – II -0.602 III -0.751 IV -0.776 V -0.606 NO3–N Shannon-Wiener index I 0.797 II 0.699 III 0.712 IV 0.693 V 0.665 Sorenson’s index I 0.563 II 0.583 III 0.380 – IV 0.629 V 0.457 – Berger-Parker’s index I 0.831 II 0.712 III 0.820 IV 0.667 V 0.660 Menhinick’s index I -0.271 – II -0.389 – III -0.448 – IV 0.274 – V 0.076 – Evenness I 0.810 II 0.718 III 0.770 IV 0.671 V 0.646 PO4–P Shannon-Wiener index I 0.823 II 0.791 III 0.689

Continued…



IV 0.762 V 0.820 Sorenson’s index I 0.778 II 0.825 III 0.663 IV 0.700 V 0.856 Berger-Parker’s index I 0.778 II 0.712 III 0.635 IV 0.733 V 0.812 Menhinick’s index I -0.246 – II -0.501 – III -0.169 – IV 0.120 – V -0.548 – Evenness I 0.831 II 0.813 III 0.674 IV 0.756 V 0.840

Continued…

Table - 10. Shannon-Wiener’s index in Ponds I, II, III, IV and V.

Months Pond I Pond II Pond III Pond IV Pond V

Feb.2009 1.630 1.210 1.521 1.623 1.371

Mar. 1.924 1.262 2.007 1.974 1.877

Apr. 2.622 1.722 2.778 2.637 2.454

May 2.612 1.979 2.835 2.842 2.682

Jun. 2.898 2.020 2.939 2.769 2.983

Jul. 2.808 1.986 2.841 2.782 2.686

Aug. 2.736 2.159 2.769 2.677 2.284

Sep. 2.511 1.647 2.800 2.549 2.111

Oct. 2.269 1.545 2.568 2.295 1.518

Nov. 1.945 1.460 1.789 1.585 1.801

Dec. 1.632 1.453 1.562 1.592 1.360

Jan.2010 1.534 1.224 1.728 1.494 1.385

Table - 11. Species evenness index in Ponds I, II, III, IV and V.


Feb.2009 0.285 0.214 0.254 0.289 0.220

Mar. 0.316 0.219 0.335 0.332 0.304

Apr. 0.455 0.306 0.486 0.458 0.411

May 0.451 0.354 0.499 0.500 0.454

Jun. 0.516 0.366 0.526 0.502 0.521

Jul. 0.492 0.357 0.502 0.500 0.452

Aug. 0.483 0.392 0.481 0.469 0.370

Sep. 0.440 0.290 0.529 0.444 0.342

Oct. 0.388 0.277 0.487 0.405 0.240

Nov. 0.333 0.252 0.309 0.263 0.300

Dec. 0.258 0.242 0.248 0.255 0.208

Jan.2010 0.238 0.199 0.278 0.241 0.211

Table - 12. Species dominance (Berger-Parker’s index) in Ponds I, II, III, IV and V.


Feb.2009 1.487 1.335 1.393 1.460 1.337

Mar. 1.571 1.333 1.611 1.576 1.522

Apr. 2.119 1.523 2.243 2.120 1.890

May 2.055 1.659 2.312 2.342 2.098

Jun. 2.405 1.683 2.442 2.289 2.438

Jul. 2.402 1.731 2.368 2.370 2.152

Aug. 2.319 1.865 2.302 2.249 1.785

Sep. 2.157 1.550 2.682 2.119 1.737

Oct. 1.840 1.458 2.272 1.972 1.395

Nov. 1.652 1.422 1.578 1.449 1.552

Dec. 1.484 1.412 1.446 1.459 1.356

Jan.2010 1.438 1.325 1.549 1.424 1.351

Table - 13. Menhinick’s index in Ponds I, II, III, IV and V.


Feb.2009 0.336 0.309 0.376 0.317 0.415

Mar. 0.524 0.342 0.430 0.478 0.445

Apr. 0.508 0.347 0.457 0.533 0.448

May 0.503 0.361 0.457 0.548 0.468

Jun. 0.494 0.342 0.437 0.452 0.453

Jul. 0.542 0.367 0.457 0.493 0.498

Aug. 0.500 0.373 0.486 0.537 0.518

Sep. 0.483 0.368 0.356 0.525 0.509

Oct. 0.481 0.311 0.297 0.454 0.479

Nov. 0.423 0.379 0.348 0.471 0.379

Dec. 0.616 0.466 0.529 0.590 0.565

Jan.2010 0.684 0.505 0.521 0.560 0.576

Table - 14. Percentage species Similarity (Sorenson’s index, 1948) in Ponds I, II, III, IV and V.


Feb.09 – Mar.09 57.14 63.16 52.17 57.58 61.97

Mar. – Apr. 78.05 62.22 75.86 80.95 73.56

Apr. – May 87.64 88.89 86.60 84.78 89.36

May – Jun. 88.17 88.14 87.76 86.96 88.24

Jun. – Jul. 90.53 83.64 87.76 85.06 91.26

Jul. – Aug. 85.71 76.92 86.32 84.71 90.32

Aug. – Sep. 70.00 80.85 79.52 80.49 70.00

Sep. – Oct. 79.45 68.29 78.87 68.49 68.66

Oct. – Nov. 62.69 71.43 52.46 71.19 67.74

Nov. – Dec. 55.17 74.42 54.55 54.55 59.65

Dec.09 – Jan.10 53.57 63.41 68.97 54.55 60.71

Jan.10 – Feb.09 60.38 48.65 53.33 42.31 53.33

Pond I

Air temperature (ºC)

10 15 20 25 30 35 40

Wat

er te

mpe

ratu

re (º

C)

10

15

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30

35

40Pond II


10 15 20 25 30 35 40

Wat

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C)

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Pond III


10 15 20 25 30 35 40

Wat

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10

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40Pond IV


10 15 20 25 30 35 40

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Pond V


10 15 20 25 30 35 40

Wat

er te

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C)

10

15

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35

Fig.1- Regression lines showing correlation between Air Temperature (ºC) and Water

Temperature (ºC) in Ponds I, II, III, IV and V.

Pond I

Water temperature (ºC)

10 15 20 25 30 35 40

Diss

olve

d O

xyge

n (m

g/L)

2

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6

8

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14Pond II


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Diss

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Pond III


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Diss

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9Pond IV


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Pond V


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9

Fig.2 - Regression lines showing correlation between Water Temperature (ºC) and

Dissolved Oxygen (mg/L) in Ponds I, II, III, IV and V.

Pond I


10 15 20 25 30 35 40

Tota

l Sol

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mg/

L)

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Pond V


10 15 20 25 30 35

Tota

l Sol

ids (

mg/

L)

12001400160018002000220024002600280030003200

Fig.3 - Regression lines showing correlation between Water Temperature (ºC) and Total Solids (mg/L) in Ponds I, II, III, IV and V.

Pond I


10 15 20 25 30 35 40

Tota

l Dis

solv

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olid

s (m

g/L)

800

1000

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2000Pond II


10 15 20 25 30 35

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l Diss

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d So

lids (

mg/

L)

020040060080010001200140016001800

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10 15 20 25 30 35 40

Tota

l Diss

olve

d So

lids (

mg/

L)

600800

10001200140016001800200022002400

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10 15 20 25 30 35

Tota

l Diss

olve

d So

lids (

mg/

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800

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Fig.4 - Regression lines showing correlation between Water Temperature (ºC) and Total

Dissolved solids (mg/L) in Ponds I, II, III, IV and V.

Pond I


10 15 20 25 30 35 40

NO

3-N (m

g/L)

0.00

0.05

0.10

0.15

0.20

0.25Pond II


10 15 20 25 30 35

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3-N (m

g/L)

0.00

0.05

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10 15 20 25 30 35 40

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3-N (m

g/L)

0.00

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10 15 20 25 30 35

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3-N (m

g/L)

0.00

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Pond V


10 15 20 25 30 35

NO

3-N (m

g/L)

0.05

0.10

0.15

0.20

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0.30

Fig.5 - Regression lines showing correlation between Water Temperature (ºC) and NO3-

N (mg/L) in Ponds I, II, III, IV and V.

Pond I


10 15 20 25 30 35 40

PO4-P

(mg/

L)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4Pond II


10 15 20 25 30 35

PO4-P

(mg/

L)

0.0

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0.4

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1.2

Pond III


10 15 20 25 30 35 40

PO4-P

(mg/

L)

0.0

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10 15 20 25 30 35

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(mg/

L)

0.0

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1.2

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Pond V


10 15 20 25 30 35

PO4-P

(mg/

L)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Fig.6 - Regression lines showing correlation between Water Temperature (ºC) and PO4-P

(mg/L) in Ponds I, II, III, IV and V.

Pond I


10 15 20 25 30 35 40

Dip

tera

(No.

/m2 )

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900Pond II


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(No.

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Pond V


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tera

(No.

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Diptera (No./m2) in Ponds I, II, III, IV and V.

Pond I


10 15 20 25 30 35 40

Hem

ipte

ra (N

o./m

2 )

020406080

100120140160180200

Pond II


10 15 20 25 30 35

Hem

ipte

ra (N

o./m

2 )

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Pond III


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Hem

ipte

ra (N

o./m

2 )

020406080

100120140160180

Pond IV


10 15 20 25 30 35

Hem

ipte

ra (N

o./m

2 )

020406080100120140160180

Pond V


10 15 20 25 30 35

Hem

ipte

ra (N

o./m

2 )

020406080

100120140160180200


Hemiptera (No./m2) in Ponds I, II, III, IV and V.

Pond I


10 15 20 25 30 35 40

Col

eopt

era

(No.

/m2 )

0

20

40

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100Pond II


10 15 20 25 30 35

Col

eopt

era

(No.

/m2 )

0

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Pond III


10 15 20 25 30 35 40

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eopt

era

(No.

/m2 )

0

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10 15 20 25 30 35

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eopt

era

(No.

/m2 )

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Pond V


10 15 20 25 30 35

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eopt

era

(No.

/m2 )

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Coleoptera (No./m2) in Ponds I, II, III, IV and V.

Pond I


10 15 20 25 30 35 40

Tric

hopt

era

(No.

/m2 )

0

10

20

30

40

50

60Pond II


10 15 20 25 30 35

Tric

hopt

era

(No.

/m2 )

0

5

10

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20

25

30

Pond III


10 15 20 25 30 35 40

Tric

hopt

era

(No.

/m2 )

0

10

20

30

40

50

60Pond IV


10 15 20 25 30 35

Tric

hopt

era

(No.

/m2 )

0

10

20

30

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Pond V


10 15 20 25 30 35

Tric

hopt

era

(No.

/m2 )

0

10

20

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40

50

60

70


Trichoptera (No./m2) in Ponds I, II, III, IV and V.

Pond I


10 15 20 25 30 35 40

Odo

nata

(No.

/m2 )

0

10

20

30

40

50

60

70Pond II


10 15 20 25 30 35

Odo

nata

(No.

/m2 )

0

2

4

6

8

10

12

14

16

Pond III


10 15 20 25 30 35 40

Odo

nata

(No.

/m2 )

0

10

20

30

40

50

60Pond IV


10 15 20 25 30 35

Odo

nata

(No.

/m2 )

0

10

20

30

40

50

60

Pond V


10 15 20 25 30 35

Odo

nata

(No.

/m2 )

-10

0

10

20

30

40

50

60


Odonata (No./m2) in Ponds I, II, III, IV and V.

Pond I


10 15 20 25 30 35 40

Ephe

mer

opte

ra (N

o./m

2 )

0

5

10

15

20

25

30

35Pond II


10 15 20 25 30 35

Ephe

mer

opte

ra (N

o./m

2 )

0

2

4

6

8

10

12

14

Pond III


10 15 20 25 30 35 40

Ephe

mer

opte

ra (N

o./m

2 )

0

5

10

15

20

25

30

35

40Pond IV


10 15 20 25 30 35

Ephe

mer

opte

ra (N

o./m

2 )

0

10

20

30

40

50

Pond V


10 15 20 25 30 35

Ephe

mer

opte

ra (N

o./m

2 )

0

10

20

30

40

50


Ephemerophtera (No./m2) in Ponds I, II, III, IV and V.

Pond I

Transparency (cm)

5 10 15 20 25 30 35

Diss

olve

d O

xyge

n (m

g/L)

2

4

6

8

10

12

14Pond II

Transparency (cm)

15 20 25 30 35 40

Diss

olve

d O

xyge

n (m

g/L)

0

2

4

6

8

10

Pond III

Transparency (cm)

20 25 30 35 40 45 50

Diss

olve

d O

xyge

n (m

g/L)

2

3

4

5

6

7

8

9Pond IV

Transparency (cm)

0 10 20 30 40 50

Dis

solv

ed O

xyge

n (m

g/L)

0

2

4

6

8

10

12

Pond V

Transparency (cm)

10 20 30 40 50 60

Dis

solv

ed O

xyge

n (m

g/L)

2

3

4

5

6

7

8

9

Fig.13 - Regression lines showing correlation between Transparency (cm) and Dissolved

oxygen (mg/L) in Ponds I, II, III, IV and V.

Pond I

Transparency (cm)

5 10 15 20 25 30 35

Tota

l Dis

solv

ed S

olid

s (m

g/L)

800

1000

1200

1400

1600

1800

2000Pond II

Transparency (cm)

15 20 25 30 35 40

Tota

l Diss

olve

d So

lids (

mg/

L)

020040060080010001200140016001800

Pond III

Transparency (cm)

20 25 30 35 40 45 50

Tota

l Diss

olve

d So

lids (

mg/

L)

600800

10001200140016001800200022002400

Pond IV

Transparency (cm)

0 10 20 30 40 50

Tota

l Dis

solv

ed S

olid

s (m

g/L)

0

500

1000

1500

2000

2500

Pond V

Transparency (cm)

10 20 30 40 50 60

Tota

l Diss

olve

d So

lids (

mg/

L)

800

1000

1200

1400

1600

1800

2000

Fig.14 - Regression lines showing correlation between Transparency (cm) and Total

Dissolved Solids (mg/L) in Ponds I, II, III, IV and V.

Pond I

Transparency (cm)

5 10 15 20 25 30 35

Tota

l Sus

pend

ed S

olid

s (m

g/L)

300

400

500

600

700

800

900

1000

1100Pond II

Transparency (cm)

15 20 25 30 35 40

Tota

l Sus

pend

ed S

olid

s (m

g/L)

0

200

400

600

800

1000

1200

Pond III

Transparency (cm)

20 25 30 35 40 45 50

Tota

l Sus

pend

ed S

olid

s (m

g/L)

300

400

500

600

700

800

900

1000Pond IV

Transparency (cm)

0 10 20 30 40 50

Tota

l Sus

pend

ed S

olid

s (m

g/L)

0

200

400

600

800

1000

Pond V

Transparency (cm)

10 20 30 40 50 60

Tota

l Sus

pend

ed S

olid

s (m

g/L)

200

400

600

800

1000

1200

1400

Fig.15 - Regression lines showing correlation between Transparency (cm) and Total

Suspended Solids (mg/L) in Ponds I, II, III, IV and V.

Pond I

Conductivity (µ S cm-1)

400 800 1200 1600 2000 2400

Tota

l Diss

olve

d So

lids (

mg/

L)

800

1000

1200

1400

1600

1800

2000Pond II


800 1000 1200 1400 1600 1800

Tota

l Diss

olve

d So

lids (

mg/

L)

020040060080010001200140016001800

Pond III


800 1200 1600 2000 2400

Tota

l Diss

olve

d So

lids (

mg/

L)

600800

10001200140016001800200022002400

Pond IV


400 800 1200 1600 2000

Tota

l Diss

olve

d So

lids (

mg/

L)

0

500

1000

1500

2000

2500

Pond V


800 1000 1200 1400 1600 1800

Tota

l Dis

solv

ed S

olid

s (m

g/L)

800

1000

1200

1400

1600

1800

2000

Fig. 16 - Regression lines showing correlation between Conductivity (µ S cm-1) and

Total Dissolved Solids (mg/L) in Ponds I, II, III, IV and V.

Pond I

pH

8.4 8.6 8.8 9.0 9.2 9.4 9.6

Tota

l alk

alin

ity (m

g/L)

150

200

250

300

350

400

450

500Pond II

pH

7.4 7.6 7.8 8.0 8.2 8.4

Tota

l alk

alin

ity (m

g/L)

0

100

200

300

400

Pond III

pH

7.6 7.8 8.0 8.2 8.4 8.6

Tota

l alk

alin

ity (m

g/L)

200

250

300

350

400Pond IV

pH

8.4 8.6 8.8 9.0 9.2 9.4 9.6

Tota

l alk

alin

ity (m

g/L)

0

100

200

300

400

500

600

700

Pond V

pH

7.8 8.0 8.2 8.4 8.6 8.8 9.0

Tota

l alk

alin

ity (m

g/L)

100

200

300

400

500

600

Fig. 17 - Regression lines showing correlation between pH and Total Alkalinity (mg/L)

in Ponds I, II, III, IV and V.

Pond I

Hardness (mg/L)

100 120 140 160 180 200 220 240

Tota

l alk

alin

ity (m

g/L)

150

200

250

300

350

400

450

500Pond II

Hardness (mg/L)

100 120 140 160 180 200 220 240 260 280

Tota

l alk

alin

ity (m

g/L)

0

100

200

300

400

Pond III

Hardness (mg/L)

80 100 120 140 160 180 200 220 240 260

Tota

l alk

alin

ity (m

g/L)

240260280300320340360380400420

Pond IV

Hardness (mg/L)

100 120 140 160 180 200 220 240 260 280

Tota

l alk

alin

ity (m

g/L)

0

100

200

300

400

500

600

700

Pond V

Hardness (mg/L)

100 110 120 130 140 150 160 170 180

Tota

l alk

alin

ity (m

g/L)

100

200

300

400

500

600

Fig. 18 - Regression lines showing correlation between Hardness (mg/L) and Total

Alkalinity (mg/L) in Ponds I, II, III, IV and V.

Pond I

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25

Dip

tera

(No.

/m2 )

200

300

400

500

600

700

800

900Pond II

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25

Dip

tera

(No.

/m2 )

0

100

200

300

400

500

600

700

Pond III

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25 0.30

Dip

tera

(No.

/m2 )

100

200

300

400

500

600

700

800Pond IV

NO3-N (mg/L)

0.04 0.08 0.12 0.16 0.20 0.24

Dip

tera

(No.

/m2 )

0

200

400

600

800

Pond V

NO3-N (mg/L)

0.05 0.10 0.15 0.20 0.25 0.30

Dip

tera

(No.

/m2 )

300

400

500

600

700

800

900

1000

Fig.19 - Regression lines showing correlation between NO3-N (mg/L) and Diptera

(No./m2) in Ponds I, II, III, IV and V.

Pond I

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25

Hem

ipte

ra (N

o./m

2 )

020406080

100120140160180200

Pond II

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25

Hem

ipte

ra (N

o./m

2 )

0

20

40

60

80

100

Pond III

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25 0.30

Hem

ipte

ra (N

o./m

2 )

020406080

100120140160180200

Pond IV

NO3-N (mg/L)

0.04 0.08 0.12 0.16 0.20 0.24

Hem

ipte

ra (N

o./m

2 )

020406080100120140160180

Pond V

NO3-N (mg/L)

0.05 0.10 0.15 0.20 0.25 0.30

Hem

ipte

ra (N

o./m

2 )

020406080

100120140160180200

Fig.20 - Regression lines showing correlation between NO3-N (mg/L) and Hemiptera


Pond I

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25

Col

eopt

era

(No.

/m2 )

0

20

40

60

80

100Pond II

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25

Col

eopt

era

(No.

/m2 )

0

10

20

30

40

50

Pond III

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25 0.30

Col

eopt

era

(No.

/m2 )

0

20

40

60

80

100Pond IV

NO3-N (mg/L)

0.04 0.08 0.12 0.16 0.20 0.24

Col

eopt

era

(No.

/m2 )

0

20

40

60

80

100

Pond V

NO3-N (mg/L)

0.05 0.10 0.15 0.20 0.25 0.30

Col

eopt

era

(No.

/m2 )

0

20

40

60

80

100

120

Fig.21 - Regression lines showing correlation between NO3-N (mg/L) and Coleoptera


Pond I

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25

Tric

hopt

era

(No.

/m2 )

0

10

20

30

40

50

60Pond II

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25

Tric

hopt

era

(No.

/m2 )

0

5

10

15

20

25

30

Pond III

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25 0.30

Tric

hopt

era

(No.

/m2 )

0

10

20

30

40

50

60Pond IV

NO3-N (mg/L)

0.04 0.08 0.12 0.16 0.20 0.24

Tric

hopt

era

(No.

/m2 )

0

10

20

30

40

50

60

Pond V

NO3-N (mg/L)

0.05 0.10 0.15 0.20 0.25 0.30

Tric

hopt

era

(No.

/m2 )

0

10

20

30

40

50

60

70

Fig.22 - Regression lines showing correlation between NO3-N (mg/L) and Trichoptera


Pond I

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25

Odo

nata

(No.

/m2 )

0

10

20

30

40

50

60

70Pond II

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25

Odo

nata

(No.

/m2 )

0

2

4

6

8

10

12

14

16

Pond III

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25 0.30

Odo

nata

(No.

/m2 )

0

10

20

30

40

50

60Pond IV

NO3-N (mg/L)

0.04 0.08 0.12 0.16 0.20 0.24

Odo

nata

(No.

/m2 )

0

10

20

30

40

50

60

Pond V

NO3-N (mg/L)

0.05 0.10 0.15 0.20 0.25 0.30

Odo

nata

(No.

/m2 )

0

10

20

30

40

50

60

Fig.23 - Regression lines showing correlation between NO3-N (mg/L) and Odonata


Pond I

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25

Ephe

meo

pter

a (N

o./m

2 )

0

5

10

15

20

25

30

35Pond II

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25

Ephe

meo

pter

a (N

o./m

2 )

0

2

4

6

8

10

12

14

Pond III

NO3-N (mg/L)

0.00 0.05 0.10 0.15 0.20 0.25 0.30

Ephe

meo

pter

a (N

o./m

2 )

0

5

10

15

20

25

30

35

40Pond IV

NO3-N (mg/L)

0.04 0.08 0.12 0.16 0.20 0.24

Ephe

meo

pter

a (N

o./m

2 )

0

10

20

30

40

50

Pond V

NO3-N (mg/L)

0.05 0.10 0.15 0.20 0.25 0.30

Ephe

meo

pter

a (N

o./m

2 )

0

10

20

30

40

50

Fig.24 - Regression lines showing correlation between NO3-N (mg/L) and Ephemeoptera


Pond I

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

Dip

tera

(No.

/m2 )

0

5

10

15

20

25

30

35Pond II

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Dip

tera

(No.

/m2 )

0

100

200

300

400

500

600

700

Pond III

PO4-P (mg/L)

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Dip

tera

(No.

/m2 )

200

300

400

500

600

700

800Pond IV

PO4-P (mg/L)

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

Dip

tera

(No.

/m2 )

0

200

400

600

800

Pond V

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Dip

tera

(No.

/m2 )

200

300

400

500

600

700

800

900

1000

Fig.25 - Regression lines showing correlation between PO4-P (mg/L) and Diptera


Pond I

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

Hem

ipte

ra (N

o./m

2 )

020406080

100120140160180200

Pond II

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Hem

ipte

ra (N

o./m

2 )

0

20

40

60

80

100

Pond III

PO4-P (mg/L)

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Hem

ipte

ra (N

o./m

2 )

20

40

60

80

100

120

140

160

180Pond IV

PO4-P (mg/L)

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

Hem

ipte

ra (N

o./m

2 )

020406080100120140160180

Pond V

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Hem

ipte

ra (N

o./m

2 )

020406080

100120140160180200

Fig.26 - Regression lines showing correlation between PO4-P (mg/L) and Hemiptera


Pond I

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

Col

opte

ra (N

o./m

2 )

0

20

40

60

80

100Pond II

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Col

opte

ra (N

o./m

2 )

0

10

20

30

40

50

Pond III

PO4-P (mg/L)

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Col

opte

ra (N

o./m

2 )

0

20

40

60

80

100Pond IV

PO4-P (mg/L)

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

Col

opte

ra (N

o./m

2 )

0

20

40

60

80

100

Pond V

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Col

opte

ra (N

o./m

2 )

-20

0

20

40

60

80

100

120

Fig.27 - Regression lines showing correlation between PO4-P (mg/L) and Coleoptera


Pond I

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

Tric

hopt

era

(No.

/m2 )

0

10

20

30

40

50

60Pond II

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Tric

hopt

era

(No.

/m2 )

0

5

10

15

20

25

30

Pond III

PO4-P (mg/L)

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Tric

hopt

era

(No.

/m2 )

0

10

20

30

40

50

60Pond IV

PO4-P (mg/L)

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

Tric

hopt

era

(No.

/m2 )

0

10

20

30

40

50

60

Pond V

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Tric

hopt

era

(No.

/m2 )

0

10

20

30

40

50

60

70

Fig.28 - Regression lines showing correlation between PO4-P (mg/L) and Trichoptera


Pond I

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

Odo

nata

(No.

/m2 )

0

10

20

30

40

50

60

70Pond II

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Odo

nata

(No.

/m2 )

024681012141618

Pond III

PO4-P (mg/L)

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Odo

nata

(No.

/m2 )

0

10

20

30

40

50

60Pond IV

PO4-P (mg/L)

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

Odo

nata

(No.

/m2 )

0

10

20

30

40

50

60

Pond V

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Odo

nata

(No.

/m2 )

-10

0

10

20

30

40

50

60

Fig.29 - Regression lines showing correlation between PO4-P (mg/L) and Odonata


Pond I

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

Ephe

meo

pter

a (N

o./m

2 )

0

5

10

15

20

25

30

35Pond II

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Ephe

meo

pter

a (N

o./m

2 )

0

2

4

6

8

10

12

14

Pond III

PO4-P (mg/L)

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Ephe

meo

pter

a (N

o./m

2 )

0

5

10

15

20

25

30

35

40Pond IV

PO4-P (mg/L)

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

Ephe

meo

pter

a (N

o./m

2 )

0

10

20

30

40

50

Pond V

PO4-P (mg/L)

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Ephe

meo

pter

a (N

o./m

2 )

0

10

20

30

40

50

Fig.30 - Regression lines showing correlation between PO4-P (mg/L) and Ephemeoptera


Feb.09

82.63

6.464.23

3.792.23 0.67

Mar.

76.25

8.44

7.873.29

2.29 1.86Apr.

2.36

61.3611.21

12.39

7.375.31

May3.13

57.59

11.31

12.65

8.486.85

Jun.

52.96

13.81

10.77

8.19

9.564.70

Jul.2.63

55.74

26.28

5.815.12

4.43

Aug.

56.74

24.55

7.49

3.444.792.99

Sep.2.79

60.00

27.60

3.410.62

5.58Oct.

74.14

16.51

2.180.78

4.36 2.02

Nov.

80.53

13.63

2.120.71

0.532.48

Dec.

90.88

4.991.34

1.34 1.09 0.36

Jan.10

93.10

2.851.97 0.66

0.66 0.77

93.10 2.851.970.660 660.77

Diptera Hemiptera Coleoptera

Trichoptera Odonata Ephemeroptera

Fig.31a - Monthly percent composition of different orders in total insect population

(No. /m2) in Pond I.

Feb.09

87.86

3.434.49

3.43 0.79 0.00Mar.

85.24

3.814.763.33

2.14 0.71Apr.

2.82

74.35

5.18

10.59

3.533.53

May

69.75

9.93

9.26

6.09

2.71 2.26Jun.

70.17

9.31

9.31

5.493.58 2.15

Jul.0.89

67.78

17.56

6.674.672.44

Aug.

67.61

17.72

4.814.162.84

2.84Sep.

82.71

12.201.11

0.89 0.892.22

Oct.

82.72

10.473.14

0.79 1.57 1.31

Nov.

89.46

6.241.72

0.861.08

0.65Dec.

93.18

3.501.40

0.70 0.520.70

Jan.10

96.61

1.131.13 0.48

0.00 0.65

96.61 1.131.130 480.000.65



Fig.31b - Monthly percent composition of different orders in total insect population

(No. /m2) in Pond II.

Feb.09

81.96

5.71

7.143.04

1.61 0.54Mar.

70.98

8.89

7.96

4.214.99 2.96

Apr.3.37

56.4514.66

11.58

6.74

7.18

May4.55

54.55

14.52

12.61

6.747.04

Jun.

50.31

15.34

14.42

7.98

6.295.67

Jul.3.52

54.4021.99

11.44

4.114.55

Aug.

58.34

22.34

6.343.72

5.244.00

Sep.5.08

55.7428.25

3.95

2.07

4.90Oct.

65.46

21.90

4.29

2.033.16 3.16

Nov.

83.82

7.513.47

0.961.73 2.50

Dec.

92.01

3.681.52

1.02 0.381.40

Jan.10

91.62

3.991.801.16 1.03

0.39

91.62 3.991.801.161 030.39



Fig.31c - Monthly percent composition of different orders in total insect population

(No. /m2) in Pond III.

Feb.09

78.25

6.25

8.25

4.001.75 1.50

Mar.

74.25

9.30

6.81

3.993.16 2.49

Apr.5.51

60.869.23

11.16

7.14

6.10

May6.22

55.43

11.72

13.46

5.35

7.81

Jun.

52.46

15.26

13.16

5.96

7.545.61

Jul.4.67

54.5921.90

9.82

4.194.83

Aug.

57.16

23.04

7.833.10

3.994.87

Sep.4.54

60.51

23.00

4.69

1.36

5.90Oct.

68.88

15.91

1.40

0.70

9.97 3.15

Nov.

86.20

8.081.68

1.350.51

2.19Dec.

91.53

3.362.28

1.080.54

1.21

Jan.10

93.19

2.131.841.28 0.99

0.57

93.19 2.131.841.280 99

0.57



Fig.31d - Monthly percent composition of different orders in total insect population

(No. /m2) in Pond IV.

Feb.09

84.90

3.676.01

3.081.17 1.17Mar.

77.60

8.616.42

2.872.19 2.32

Apr.3.93

61.3310.18

14.52

5.025.02

May5.58

56.36

9.61

13.38

8.05

7.01

Jun.

53.49

14.08

14.34

6.97

7.37 3.75Jul.

3.29

57.8021.71

7.443.90

5.85

Aug.

65.0617.00

6.682.93

4.923.40

Sep.2.99

70.73

18.76

2.632.03

2.87Oct.

82.99

10.411.90

1.141.781.78

Nov.

83.17

9.62

2.721.92

0.641.92

Dec.

93.33

3.121.40

1.29 0.430.43

Jan.10

93.03

3.061.69

1.27 0.630.32

93.03 3.061.691.270.630.32



Fig.31e - Monthly percent composition of different orders in total insect population

(No. /m2) in Pond V.

0100200300400500600700800900

F-09 M A M J J A S O N D J-10

Pop

ulat

ion

(No.

/m2 )

Ephemeroptera Odonata TricophteraColeoptera Hemiptera Diptera

Pond I

0

100

200

300

400

500

600


Pop

ulat

ion

(No.

/m2 )

Pond II

0

100

200

300

400

500

600

700

800


Pop

ulat

ion

(No.

/m2 )

Months

Pond III

Fig.32a - Histogram showing monthly variations in aquatic insect population

density (No./m2) in Pond I, Pond II and Pond III from February, 2009 to January, 2010

0

100

200

300

400

500

600

700


Pop

ulat

ion

(No.

/m2 )

Ephemeroptera Odonata TricophteraColeoptera Hemiptera Diptera

Pond IV

0100200300400500600700800900


Pop

ulat

ion

(No.

/m2 )

Months

Pond V

Fig.32b - Histogram showing monthly variations in aquatic insect population

density (No./m2) in Pond IV and Pond V from February, 2009 to January, 2010

TRICHOPTERA

CHAPTER – V LIMNOLOGICAL SIGNIFICANCE OF AQUATIC...

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