APPLICATION OF BIOTIC INDEXING IN FRESHWATER QUALITY ASSESSMENT: A CASE OF BOMPAI-JAKARA - PowerPoint Presentation

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  APPLICATION OF BIOTIC INDEXING IN FRESHWATER QUALITY ASSESSMENT: A CASE OF BOMPAI-JAKARA CATCHMENT, KANO, NORTHERN NIGERIA

1

IMAM, T.S* and

2

BALARABE, M.L.

1

Applied Biology Department, Bayero University, Kano, PMB 3011, Kano, Nigeria.

2

Department of Biological Sciences,

Ahmadu

Bello University, Zaria, Nigeria.

*Corresponding Author’s E-mail:

tijjanimam70@gmail.com

, GSM: 08133382562

Paper Presented During

International Conference on the Future of Energy use in Nigeria’s

Dryland

: Challenges and Opportunities

Held at Department of Geography

,

Bayero University Kano

P.M.B. 3011, Kano, Nigeria

September 21, 2012

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INTRODUCTIONBiodiversity index (Biotic index) is the degree which measures the presence of flora and fauna in the environment ,

or

Is a scale which shows the quality of an environment (i.e. water, land, air etc).

Zooplankton have long been used as indicator of water quality, because they respond to environmental factors

S

uch

as water chemistry, shoreline disturbances and watershed land use, as well as levels of vertebrate and invertebrate

predation

Bompai-Jakara

Catchment Basin

is part of the north-eastern watershed of the Kano metropolis, which carries urban domestic wastewater as well as industrial effluents from the

Bompai

industrial estate

.

Studies have shown that the river system is highly contaminated with both organic and inorganic pollutants (

Binns

et al

., 2003;

Bichi

and

Anyata

, 1999).

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AIM OF THE STUDYThis study aimed at applying Biotic Indexing in Freshwater Quality Assessment using zooplanktonic

fauna in the

Bompai-Jakara

Catchment Basin, Kano.

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MATERIALS AND METHODSStudy Area Bompai-Jakara

catchment Basin consists of two major tributaries i.e.

River

Jakara

which carries mostly domestic wastewater from the ‘Kano Old City’ and

Getsi

River that carries industrial effluents from

Bompai

industrial estate (one of the major three industrial estates in the state).

The two rivers meet at a confluence (

Magami

) and the water drains into the

Wasai

reservoir.

Wasai

reservoir is utilized for fishing as well as for Urban and

Peri

-urban Agriculture (UPA) along the catchment.

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Sampling Site A: Jakara RiverThis is located on Jakara

River, at

Nomansland

off

Zungeru

road (11

0

58.822N, 008

0

28.412E) in a high density residential area. Substantial vegetable production takes place on both banks of Jakara River, and crops are irrigated by water from the Jakara channel.

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Sampling Site B: Getsi RiverThis site is located 100m away from Kwana

Hudu

Bridge on the River

Getsi

(12

0

05.930N, 008

0

37.807E). The river receives effluents from the Bompai industrial Estate. A significant proportion of the factories in operation at the industrial estate are tanneries and textile mills.

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Sampling Site C: Magami (Confluence)The site is located within 5 meters away from the confluence of

Jakara

and

Getsi

rivers

(12

0

03.159N, 008

0

32.689E). Where industrial effluents from the River Getsi as well as domestic wastewater from the Jakara River mix.

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Sampling Site D: Bela (Entry Point into Wasai reservoir)This site is the entry point (inlet) of which wastewater from the tributaries drain into the reservoir, located on 12

0

05.932N, 008

0

37.806E.

It is an important fishing station and the banks are utilized for informal irrigation.

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Sampling Site E: Barwa (Spillway)This site is situated 5m away from the spillway of the dam, located on 12

0

07.742N, 008

0

41.235E.

It is an important fishing station; the banks are used for informal irrigation.

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Sampling Site F: Wasai (Outlet)This site is situated 5m away from the regulated outlet of the dam, Is a fishing station and the banks are used for informal irrigation farming.

Located on 12

0

08.766N, 008

0

40.848E.

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Figure 1: Study Area: Bompai-Jakara Catchment Basin, Kano State, Nigeria and Sampling Sites (Source: Google Earth, 2012).

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Zooplankton Samples CollectionZooplankton samples were collected using plankton net mesh size 70µm.

The net is tied to metal rod, and was immersed into the water, pulled vertically for 1meter, and hauled out of water.

The water (containing plankton) that is collected in the plastic bottle at the end of the net was emptied into a sample bottle and preserved with 4% formalin;

The volume of water that passed through the net was then estimated by using the following formula:

V=

π

r

²

Where v=volume of water filtered by net,

r= radius of the mouth of the net.

d= length of the haul (APHA, 2005).

 

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Zooplankton Sample Collection using Plankton Net

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Determination of Zooplankton Composition and DistributionThe zooplanktons collected were condensed by sedimentation in the laboratory for 48hours, and later 10ml of the concentrated samples (which was the sediment obtained after decantation of the sample) was taken for sorting and counting

Identification to species level was performed using Kolb (1986) and Yamaguchi and Bell (2007) protocols.

Zooplankton population density was computed using the following formula (APHA, 2005):

No./m³= C x V´/V´´ x V´´´

Where:

C= Number of organisms counted

V

I

= Volume of concentrated sample (

mL)VII= Volume counted (mL)V

III

= Volume of Grab sample

NB: To obtain organism per

litre

(org/L) = Divide No./m

3

by 1000

 

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Estimation of Biodiversity IndexingZooplanktons diversity indexing was computed by means of the following biodiversity indices:1.

Saprobic

Index

(

Zladaçek

and Tuçek,1975)

:

 

S= ∑

sh/ ∑h

Where:

s=

saprobity

class (1-4),

h= abundance of spp (1-9)

NB:It

estimates level of organic loading of the water.

 

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ii. Jaccard Similarity Index(JSI) (Allaby,1999): 

JSI= C/ N

1 +

N

2

Where:

C=Number of

taxa

shared between a pair of site

N1

and N

2

: Number of spp in each of the two sites

NB: It correlates two sites in terms of similarity.

 

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iii. Margalef Index (Margalef, 1958; Maiti, 2004; SDR-IV, 2010):

D= S-1/

lnN

Where:

S=Number of spp,

ln

= Natural log of total number of individuals.

NB: It increases with increase in number of spp.

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iv. Berger-Parker or Community Dominance Index (Maiti, 2004):CDI= Y

1

+ Y

2

/ Y

Where:

Y

1

= abundance of the most dominant spp; Y

2

= abundance of the 2nd most dominant spp;

Y= total abundance of all species at the site.

NB: The higher the value the greater the dominance of 1 or 2 spp in the habitat.

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Statistical AnalysisSPSS statistical software version 15 was employed in the analysis of data obtained, which include variables of zooplanktonic

fauna.

One-way ANOVA was used to test for

significant difference between the variables.

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RESULTS Table 1: Percent Composition of Zooplankton Taxonomic Group (2009 and 2010)

2009

Zooplanktonic

group

Sampling

Site

Percent

Composition

A

B

C

D

E

F

∑

Protozoa

9

5

5

4

6

3

13

39.4

Insecta

2

3

3

-

-

1

7

21.2

Annelida

3

2

3

2

2

2

3

9.09

Cladocera

221-1139.09Copepod a21--1-39.09Nematoda-1--1-13.03Trematoda 1-111113.03Rotifera 1----113.03Mysida -----113.03Spp Richness2014137121033% Total100

B. 2010

Protozoa

5

5

4

4

5

5

7

33.33

Insecta

4

3

3

2

3

3

4

19.05

Annelida

3

3

2

2

3

3

3

14.29

Cladocera

1

1

1

1

1

1

1

4.76

Copepoda

1

-

-

1

1

1

1

4.76

Nematoda

1

2

-

1

2

2

2

9.53

Tunicata

1

-

-

-

-

-

1

4.76

Chaetognatha

1

1

1

1

1

1

1

4.76

Rotifera

1

-

-

1

1

1

1

4.76

Spp Richness

18

15

11

13

16

17

21

100

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Table 2: Zooplankton Mean and Maximum Abundance (Density) in Dry and Wet seasons in the Jakara-Getsi River System and Wasai

Reservoir, 2009 and 2010.

Jakara

-

Getsi

Wasai

Overall

Range

2009

2010

2009

2010

2009

2010

Mini

Maxi

Dry

Mean

53.53±6.710

NS

26.11±11.0

NS

45.06±24.4

NS

43.07±0.47

NS

45.9±15.12

NS

36.96±0.48

NS

35.23

59.62

Maximum

199.12

93.6

117.9

85.46

317.02

179.06

85.46

317.02

Wet

Mean

24.05±0.481

NS

25.78±4.80 NS26.0±9.10 NS45.09±9.11 NS26.99±1.44 NS35.91±1.54 NS25.9737 Maximum81.277.3265.0497.67146.24174.9965.04174.99Annual Mean38.21±15.17 NS31.33±13.4 NS33.6±16.71 NS39.18±11.9 NS36.45±13.3 NS36.44±0.74 NS35.7256.8 Maximum199.1293.6117.997.67317.02191.2793.6317.02Key: NS= There is no significant deference at P≤0.05.

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Table 3: Biotic Indices Estimation of the Bompai-Jakara Catchment Basin according to Sampling Sites, 2009 and 2010.

Sampling Site

A

B

C

D

E

F

2009

2010

2009

2010

2009

2010

2009

2010

2009

2010

2009

2010

Saprobic index

3

cd

3.2

cd

2

bc

2.2

bc

2.5

cd

2.6

cd

2

bc

2

bc

2.4

c

2.2

bc

2

bc2 bcMargalef's index2.91c2.46 c2.24 c2.36 c1.97 bc2 bc1.09ab2.14 bc1.74 bc2.42 c1.59 bc2.53 cJaccard's Similarity index0.75a0.42 a0.29 a0.4 a0.25 a0.13 a0.6 a0.4 a0.44 a0.2 a0.33 a0.43 aBerger-Parker

Dominance index

0.62

a

0.36

a

0.74

a0.58 a0.76 a0.62 a0.87 a0.51 a0.77 a0.57 a0.8 a0.36 a

Numbers with the same superscript are not significant at P≤0.05.

NB:

Values of JSI increase with increase in similarity between sites;

values of CDI increase with increase in dominance of certain species in a given site;

values of D increase with increase in evenness between sites.

Interpretation of

Saprobic

Values:

1-1.5=

oligosaprobic

1.6-2.5= beta-

mesosaprobic

2.6-3.5= alpha-

mesosaprobic

3.6- above=

polysaprobic

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Figure 1: Comparing Total Zooplankton Density (org/L) in Surface Water of Bompai- Jakara Catchment Basin, Kano State in 2009 and 2010.

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A

B

C

E

D

Plate I: Photomicrograph of Zooplanktons, A:

Trachelomonas

sp.(Protozoa) ; Nauplius larva (Copepoda);

Brachionus

sp. (Rotifera);

Diaptomus

sp. (Copepoda);

Hemicycliophora

sp. (Nematoda); F:

Daphnia

sp.(Cladocera).

F

Plate I: Photomicrograph of Zooplanktons, A:

Trachelomonas

sp.(Protozoa) ; Nauplius larva (Copepoda);

Brachionus

sp. (Rotifera);

Diaptomus

sp. (Copepoda);

Hemicycliophora

sp. (Nematoda); F:

Daphnia

sp.(Cladocera).

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CONCLUSIONS AND RECOMMENDATIONSThis study highlights the state of the catchment in terms of zooplanktonic

fauna composition and distribution, and their utilization for water quality

assessment

The overall abundance of zooplanktons was observed to be low both spatially and temporally.

There is the problem of maintaining the balance of the aquatic

ecosystem,

bearing

in mind

that the study area is important for fishing, also urban and

peri

-urban

agrciculture

(UPA) is

practised

.

Thus, effort of monitoring as well as government enforcement of FEPA effluent and sewage discharge regulation limits need

to

be effected

.

This is in order to improve the health of the aquatic biodiversity which will be ecologically and socio-economically beneficial to Kano populace and the nation in general.

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Thanking You for Listening!!