1 seiyaboh, e.i. and 2sikoki, f.d 1* 2 · 2018. 5. 8. · s e iy ab oh nd s k proceedings of 6th...

Seiyaboh and Sikoki

Proceedings of 6th NSCB Biodiversity Conference; Uniuyo 2018 (328 - 340pp)

328

The Impact of Dredging on the Balance of Nature and Biodiversity of Igbedi Creek,

Niger Delta, Nigeria

1*SEIYABOH, E.I. and 2SIKOKI, F.D 1*Department of Biological Sciences, Niger Delta University, Wilberforce Island, Bayelsa State, Nigeria.

Email: [email protected], [email protected] Tel: 08035485910 2Department of Animal & Environmental Biology, University of Port Harcourt, Rivers State, Nigeria.

Email: [email protected]

Abstract: The impact of dredging on the balance of nature and biodiversity of Igbedi Creek, Niger Delta, Nigeria

was investigated from June, 2009 to May, 2011. The study was conducted at two locations along the river channel

representing a dredged (Ogbobiri) and an un-dredged (Agoro-Gbene) stretches. The physico-chemical

characteristics of the water,aspects of the biology, and relative abundance of fish species were studied using

routine limnological techniques and standard methods in eight stations (five dredged and three un-dredged).The

results showed significant differences (P˂0.05) between the dredged and un-dredged stretches except for

dissolved oxygen(DO), temperature and pH. Similarly,there were more fish species in the un-dredged stretch,(28)

than in the dredged area (23species). In the dredged area, all the fish species exhibited negative allometric growth

except for one species (Shilbe uranascopus) which showed isometric growth while in the un-dredged area, three

species exhibited isometric growth. Condition factor of the fish were also significantly different in the two

stretches with the fish from the un-dredged area having generally higher values. Based on the results, it is

concluded that dredging had significantly impacted on the balance of nature in Igbedi Creek.

INTRODUCTION

As established in literature, dredging is a process

involving the abyssal excavation of water bodies in

order to get rid of sediments, pollutants, shellfish and

other anthropogenic agents (Seiyaboh, 2012). The

applied techniques and mechanism in dredging vary

widely, and can be artisanal or mechanized.

Mechanized dredging can be done by ships towing a

dredge along the water bed, or byself-standing dredges

with pumping stations. It is executed for drainage

improvement, land reclamation, sea buffering or as a

cleanup in the environment (Bray et al., 1998).A

dredge, which is the catch all term for the different

types of machinery that perform dredging, can cut

away sediment, scoop materials out like a back hoe or

suction them through a large pipe to be deposited into

a ship.

According to Stolpe (2001), the direct impacts of

dredging are often established, they are seldom

quantified, and their “downstream” consequences are

less compared to upstream (Ellery and McCarty,

1994). Dredging pose beneficial and adverse impacts

on the environment, depending on the approach.

Ideally, dredging activities should not pose adverse

effects on the environment if meticulously carried out

(CIRI, 1997). In terms of benefits, it improves the

navigability of water and even dredged sand can serve

as materials for backfilling or construction purpose.

Dredging activities pose adverse effects on aesthetic

value of water bodies (Balchand and Rasheed, 2000),

including vegetation acidification (Abam, 2001), and

increased water turbidity, with aftermath

anthropogenic or lithogenic effects on all forms of

aquatic biodiversities, especially fish. In addition,

dredging can cause the introduction of foreign species

to the affected ecosystem (Reine et al., 1998).

Notwithstanding, not much research have been carried

out on the effects of dredging at population-level of

mobile epi-benthic biota and dermal species (Ault et

al., 1998). In the Niger Delta region, dredging have

also heightened intrusion of saline water to freshwater

or low brackish water areas (Nwankwo, 1996).

According to Su et al., (2002), the dissolution and

mobility of polluted sediments induce ecological

impacts beyond the advent of physical effects of

mechanical disturbances provided the contaminants

are persistent and bioavailable (Su et al., 2002).

Dredging activities pose adverse effects on

biodiversity, as such it impacts are hereby

investigated.

MATERIALS & METHODS

Study Area

The study was carried out in Igbedi Creek, a tributary

of the Upper Nun River in the Niger Delta located

between latitude 50N011 and 60171E. The stretch of the

river is a long and wide meander whose outer concave

bank is relatively shallow with sandy point bars

(Abowei, 2000). The depth and width of the river vary

slightly at different points (Sikoki et. al., 1998). The

minimum and maximum widths are 200 and 250

meters respectively. The river is subjected to tidal

influence in the dry season. Water flows rapidly in one

direction during the flood (May – October). At the

peak of the dry season, the direction of flow is slightly

reversed by the rising tide. At full tide the flow is

almost stagnant.The riparian vegetation is composed

of a tree canopy made up of Raphia hokeri, Nitrogena

sp, Costons afer, Bambosa vulgans, Alchomia cordifolla, Alstonia boonei, Antodisinia sp and

submerged macrophytes which includes; Utricularia

sp, Nymphea lotus, Lemna sp, Salvinia sp, Cytosperma senegalensis, Ludwigia ewrects,

mailto:[email protected]



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Cyclosorus sp, Commelia sp and Hyponea sp (Sikoki

et. al., 1998)

Collection of Water Samples

Water samples were collected from three (3) points on

each of the stations in each study location. Water

samples were collected as subsurface water samples at

a depth of about 15-20cm below surface. The water

samples were collected using DO bottles, BOD bottles

and 1 litre containers for the measurement of other

water quality parameters respectively. The sampling

bottles/containers were rinsed three times with the

water at the specific sampling spots before the

collection of samples. Generally, the samples were

collected by lowering the containers by hand below

the surface level. The containers were completely

immersed in water, and were corked (stoppered) under

water. The water samples were fixed and preserved on

the site. Winkler 1 & 11 solutions were added into the

water samples for DO; the samples for BOD were

stored in ice-cold containers and taken to the

laboratory.The water samples were subsequently

taken to the laboratory, Department of Animal and

Environmental Biology, University of Port Harcourt,

for analysis.

Collection of Fish Samples

Sampling was carried out forth nightly between June

2009 and May 2011 using gillnets, long lines, traps

and stakes. The researcher fished for himself and also

employed the services of fishers for sampling. Catches

were isolated and conveyed in thermos cool boxes to

the laboratory on each sampling day. Fish specimens

were identified using monographs, descriptions,

checklists and keys (Daget, 1954; Alfred Ockiya,

1983; Loveque et al., 1991).

Total length and weight of fish specimens were

measured to the nearest centimetre and grammes

respectively, to obtain data for length-weight

relationship. The total length (TL) of the fish was

measured from the tip of mouth to the caudal fin using

meter rule calibrated in centimetre. Fish samples were

measured to the nearest centimetre. The weight of

each fish was obtained after draining water from the

buccal cavity and blot drying samples with a piece of

clean hand towel. Weighing was done with a tabletop

weighing balance to the nearest gram.

Length – Weight Relationship

The relationship between the length (L) and weight

(W) of the various fish species were expressed by the

exponential equation (Pauly, 1983):

W=aLb (Eqn. 1)

Where

W=Weight of fish in (g) L= Total Lenght of fish in (cm)

a= Constant (intercept)

b= The Length exponent (Slope)

The “a” and “b” values were obtained from a linear

regression of the length and weight of fish. The

correlation (r) that is the degree of association between

the length and weight was computed from the linear

regression analysis.

Condition Factor

The condition factor (K) of the experimental fish was

estimated from the relationship:

K=100W/L3 (Eqn. 2)

Where;

K= Condition Factor

W= Weight of Fish (g)

L= Length of Fish (cm)

Surface Water Analysis

Analysis for water quality parameters such as;

biochemical oxygen demand (BOD) using Winkler’s

method. The pH and dissolved oxygen (DO), were

evaluated using portable field kits (Hach’s CO 150

and JK-OXY-006 meters respectively). Turbidity was

measured using digital TB400 EXTECH portable

meter.

Nitrates

Determination of Nitrates (NO3) in water was by

Brucine method. Nitrate level in the water samples

was determined following the procedure described in

standard methods of water and wastewater analysis

(APHA, 1975, Section 410D). The principle of this

determination was based on the reaction of nitrate and

brucine to produce a yellow coloured complex. The

intensity of the colour depends on the concentration of

Nitrates (NO3-) present and was measured

spectrophotometrically with Spectonic 20 (B & L) at

420nm.

Nitrite

This is a rather direct reading without the reduction

process using the diazonium compound and -

naphthyl-amine product of a red azo-dye read on the

spectrophotometer. The concentration in mg/l was

extrapolated from the nitrite chart.

Sulphate(Turbidimetric Method)

Water samples was treated with 5ml of 10% BaCl2

solution and read at 425nm. The water samples were

acidified with HCl.

Chloride: (Mohr Method)

Using potassium chromate as indicator, 100ml of

water samples was titrated against a 0.0257M AgN03

solution previously standardized against a 0.0282M

NaCl solution.

Statistical Analysis

The contaminant concentrations found in each of the

aquatic media were compared to World Health

Organization (WHO) acceptance limits for drinking

water (WHO, 2000). The following statistical tools

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were used to analyzed the data obtained – Analysis of

Variance (ANOVA) for water and sediment data

analysis; Regression and Correlation Analysis

(RECA) for linear regression of length and weight of

fish, Microsoft Excel (2010) for computation of means

and standard deviation; Statistical Package for Social

Sciences (SPSS) and FISAT (Gayando and Pauly,

1997) for descriptive statistics, length-weight

relationship and condition factor of fish.

RESULTS

In dry and wet season the depth of ranged from 2.49 -

13.01 and 3.58 – 15.35m across the locations and

stations respectively. The highest depth was recorded

in the month of October at the dredged station in

Ogobiri as opposed to undredged station in

Agorogbene which recorded the lowest depth was

recorded in March. Furthermore, the highest depth

was recorded at the peak of the wet season, while the

lowest depth was recorded in the dry season. The

mean depths were significantly different (p<0.05)

across the stations. There were significant differences

(p<0.05) in mean depth in Ogobiri and Agoro-Gbene

locations. There was no significant (p>0.05) variation

in depth between the locations for dry and wet

seasons.

In dry season, the pH values ranged from 6.31 - 8.64

across the locations and stations, compared to 7.05 –

8.64 in wet season. The highest pH was recorded in

September (AGO1MD3); October (AGO1MD3) while

the lowest pH was recorded in February (AGO1DS1).

The highest pH was recorded in wet season, while the

lowest pH was recorded in the dry season. The mean

pH were significantly different (P<0.05) across the

stations. There was no significant difference (p>0.05)

in mean pH in Ogobiri (7.17±0.01) and Agoro-Gbene

(7.26±0.01) locations There was no significant

(p>0.05) variation in pH between the locations for dry

(6.89±0.06, 6.88±0.08) and wet (7.44±0.06,

7.65±0.08) seasons (Tables 1 and 2).

The seasonal water temperature values ranged

between 26.95 - 28.890C and 26.99 - 29.110C across

the locations and stations. Highest temperatures of

29.110C were recorded in June (OGO1DS3), June

(OGO1DA2, OGO1DA3), July (OGO1DA2) and

August (OGO1DS1, OGO1DS3); lowest temperatures

of 26.990C were recorded in September (OGO1DA3)

and January (OGO1DA2). The highest temperature

was recorded in the wet season, while the lowest

temperature was recorded in the dry season. The mean

temperatures were significantly different (p<0.05)

across the stations. There was no significant difference

(P>0.05) in mean temperature in Ogobiri (27.9±0.02)

and Agoro-Gbene (28.20C 2±0.02 locations. There

was also no significant (p>0.05) variation in

temperature between the locations for dry (27.40C

±0.08, 28.30C±0.10) and wet (28.30C±0.08,

28.20C±0.10) seasons (Tables 1 and 2).

The water turbidity values ranged between 27.61 –

78.64 and 42.01 – 79.89 NTU in dry and wet seasons

respectively, across the locations and stations. The

highest turbidity of 79.89NTU was recorded in

September (OGO1DA1); lowest turbidity of

22,15NTU was recorded in February (AGO1DS2).

The highest turbidity was recorded in the dry season,

while the lowest turbidity was also recorded in the dry

season. The mean turbidity were significantly

different (p<0.05) across the stations. There was

significant difference (P<0.05) in mean turbidity in

Ogobiri (62.54NTU±0.64) and Agoro-Gbene

(44.25NTU±0.81) locations. There was significant

(p<0.05) variation in temperature between the

locations for dry (50.76NTU±1.50, 36.59NTU±1.94)

and wet (73.91NTU±1.55, 51.99NTU±1.96) seasons.

The seasonal conductivity values ranged between

52.24 – 98.65 and 50.76 – 120.90 μS/cm1 across the

locations and stations. The highest conductivity was

recorded in August (OGO1DA1) while the lowest

conductivity was recorded in April (AGO1MD2).

There was significant difference (P<0.05) in mean

conductivity in Ogobiri (76.23hmoscm-1 ±2.60) and

Agoro-Gbene (65.44hmoscm-1±3.29) locations.

There was significant (p<0.05) variation in

conductivity between the locations for dry

(85.00hmoscm-1±4.30, 76.91hmoscm-1±5.56) and

wet (64.47hmoscm-1±4.44, 54.02hmoscm-1±5.61)

seasons.

The DO values ranged between 2.79 – 4.79 and 2.91 -

3.59mg/l across the locations and stations. The highest

DO was recorded in February (OGO2US3); lowest DO

was recorded in October (AGO1DS1), November

(OGO1DA1, OGO1DS3 and AGO1DS2). The highest

DO was recorded in the dry season, while the lowest

DO was also recorded in the dry season. The mean DO

were significantly different (p<0.05) across the

stations. There was no significant difference (p>0.05)

in mean DO in Ogobiri (3.7mg/l±0.03) and Agoro-

Gbene (3.4mg/l±0.04) locations. There was also no

significant (p>0.05) variation in DO between the

locations for dry (4.2mg/l±0.07, 3.6mg/l±0.09) and

wet (3.2mg/l±0.07, 3.1mg/l±0.09) seasons (Tables 1

and 2).

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Figure 1: Map of the Study Area.

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Table 1: Physicochemistry of Surface water in Ogobiri and Agorogbene during dry season

Parameter LOC. January February March November December

Depth(m) OGO 7.57±1.71 5.26±1.71 3.57±1.71 13.01±1.71 10.23±1.71

AGO 6.66±2.20 4.36±2.20 2.49±2.20 11.68±2.20 9.29±2.20

pH OGO 6.67±0.04 6.67±0.04 6.69±0.04 7.36±0.04 6.66±0.04

AGO 6.33±0.05 6.31±0.05 6.58±0.05 8.64±0.05 6.34±0.05

Temp oC OGO 26.98±0.07 27.05±0.07 27.76±0.07 27.42±0.07 26.95±0.07

AGO 28.41±0.08 28.34±0.08 28.10±0.08 28.89±0.08 28.37±0.08

Turb.

NTU

OGO 42.93±2.14 42.01±2.14 43.12±2.14 78.64±2.14 42.88±2.14

AGO 27.83±2.77 27.61±2.77 32.59±2.77 59.67±2.77 27.89±2.77

Cond.

μS/cm1

OGO 98.30±8.76 98.59±8.76 94.51±8.76 52.24±8.76 98.65±8.76

AGO 92.97±11.31 92.78±11.31 72.43±11.31 59.58±11.31 92.93±11.31

DO mg/l OGO 4.72±0.11 4.79±0.11 4.57±0.11 2.79±0.11 4.67±0.11

AGO 3.72±0.14 3.88±0.14 3.62±0.14 2.94±0.14 3.79±0.14

BOD5

mg/l

OGO 5.77±0.09 5.90±0.09 5.97±0.09 2.45±0.09 5.60±0.09

AGO 11.62±0.12 11.91±0.12 5.34±0.12 1.78±0.12 11.49±0.12

TDS mg/l OGO 49.24±1.32 48.79±1.32 48.59±1.32 25.95±1.32 49.23±1.32

AGO 45.93±1.70 45.84±1.70 35.23±1.70 29.72±1.70 45.97±1.70

NO3- mg/l OGO 0.075±0.005 0.072±0.005 0.073±0.005 0.245±0.005 0.074±0.005

AGO 0.343±0.007 0.347±0.007 0.198±0.007 0.267±0.007 0.356±0.007

NO2- mg/l

OGO 0.074±0.002 0.076±0.002 0.074±0.002 0.131±0.002 0.074±0.002

AGO 0.104±0.003 0.105±0.003 0.083±0.003 0.074±0.003 0.105±0.003

Cl- mg/l OGO 0.34±3.65 0.34±3.65 0.32±3.65 0.30±3.65 0.71±3.65

AGO 0.22±4.72 0.21±4.72 0.42±4.72 0.31±4.72 0.22±4.72

SO42- mg/l

OGO 7.92±0.21 7.89±0.21 7.79±0.21 7.53±0.21 7.82±0.21

AGO 6.74±0.27 6.66±0.27 7.68±0.27 7..95±0.27 6.52±0.27

Table 2: Physicochemistry of Surface water in Ogobiri and Agorogbene during wet Season

Parameter LOC. Apr. May Jun. Jul. Aug. Sep. Oct.

Depth(m) OGO 4.54±1.71 5.36±1.71 6.27±1.71 7.39±1.71 9.74±2.16 13.67±1.80 15.35±1.71

AGO 3.58±2.20 4.32±2.20 5.12±2.20 6.93±2.20 6.88±2.38 11.08±2.20 13.92±2.20

pH OGO 7.30±0.04 7.43±0.04 7.51±0.04 7.52±0.04 7.51±0.05 7.34±0.04 7.36±0.04

AGO 7.05±0.05 7.14±0.05 7.12±0.05 7.13±0.05 7.15±0.05 8.63±0.05 8.64±0.05

Temp oC OGO 28.31±0.07 28.71±0.07 29.11±0.07 28.99±0.07 29.05±0.08 26.99±0.07 27.21±0.07

AGO 27.54±0.08 27.70±0.08 27.80±0.08 27.87±0.08 27.84±0.09 28.84±0.08 28.94±0.08

Turb.

NTU

OGO 53.98±2.14 61.76±2.14 72.74±2.14 73.45±2.14 78.65±2.71 79.89±2.25 79.39±2.14

AGO 43.93±2.77 46.69±2.77 48.15±2.77 48.26±2,77 48.92±2.99 59.72±2.77 59.76±2.77

Cond.

μS/cm1

OGO 67.63±8.76 60.88±8.76 59.01±8.76 58.99±8.76 120.90±11.08 52.46±9.19 52.57±8.76

AGO 50.76±11.31 50.98±11.31 51.09±11.31 51.11±11.31 51.22±12.21 59.64±11.31 59.74±11.31

DO mg/l OGO 3.59±0.11 3.37±0.11 3.41±0.11 3.29±0.11 3.18±0.14 3.11±0.11 2.91±0.11

AGO 3.49±0.14 3.17±0.14 3.28±0.14 3.16±0.14 2.95±0.15 3.29±0.14 3.04±0.14

BOD5

mg/l

OGO 3.27±0.09 2.45±0.09 1.99±0.09 2.21±0.09 2.23±0.11 2.377±0.09 2.46±0.09

AGO 2.16±0.12 1.37±0.12 0.98±0.12 1.18±0.12 1.38±0.13 1.66±0.12 1.87±0.12

TDS mg/l OGO 37.55±1.32 33.20±1.32 29.50±1.32 29.67±1.32 29.85±1.66 26.23±1.38 26.35±1.32

AGO 26.50±1.70 25.50±1.70 25.54±1.70 25.58±170 25.90±1.70 29.84±1.70 29.84±1.70

NO3- mg/l OGO 0.106±0.005 0.113±0.005 0.114±0.005 0.116±0.005 0.117±0.007 0.233±0.006 0.249±0.005

AGO 0.113±0.007 0.077±0.007 0.076±0.007 0.077±0.007 0.077±0.007 0.256±0.007 0.272±0.007

NO2- mg/l

OGO 0.075±0.002 0.076±0.002 0.079±0.002 0.079±0.002 0.080±0.003 0.128±0.002 0.132±0.002

AGO 0.064±0.003 0.052±0.003 0.051±0.003 0.051±0.003 0.052±0.003 0.075±0.003 0.075±0.003

Cl- mg/l OGO 0.54±3.65 0.71±3.65 0.83±3.65 0.83±3.65 0.87±4.62 0.18±3.83 0.19±3.65

AGO 0.56±4.72 0.57±4.72 0.59±4.72 0.59±4.72 0.59±5.09 0.31±4.72 0.31±4.72

SO42- mg/l

OGO 6.05±0.21 5.39±0.21 5.40±0.21 5.41±0.21 5.43±0.27 7.64±0.22 7.64±0.21

AGO 9.14±0.27 9.46±0.27 9.78±0.27 9.77±0.27 9.7333±0.30 8.02±0.27 8.06±0.27

The BOD5values ranged between 1.78 – 11.91 and

0.98 – 3.27 mg/l in dry and wet seasons, across the

locations and stations. Meanwhile, the highest BOD5

was recorded in February at Agorogbene station;

lowestBOD5 was also recorded in June. The highest

BOD5 was recorded in the dry season, while the

lowest BOD5 was recorded in the wet season. The

mean BOD5 values were significantly different

(P<0.05) across the stations. There was significant

difference (P<0.05) in mean BOD5 in Ogobiri

(3.6mg/l±0.27) and Agoro-Gbene (4.4mg/l±0.34)

locations. There was also significant (p<0.05)

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variation in BOD5 between the locations for dry

(4.8mg/l±0.24, 7.4mg/l±0.30) and wet (2.3mg/l±0.24,

1.4mg/l±0.31) seasons.

Across the locations and stations; in dry season, TDS

values ranged from 25.95 – 49.24mg/l, compared

to25.50 – 37.55mg/l values of wet season. The highest

TDS was recorded in December (OGO1DA1); lowest

TDS was recorded in June (AGO1MD2). The highest

TDS was recorded in the dry season, while the lowest

TDS was recorded in the wet season. The mean TDS


stations. There was significant difference (p<0.05) in

mean TDS in Ogobiri (36.18mg/l±0.39) and Agoro-

Gbene (32.62mg/l±0.04) locations. There was also

significant (p<0.05) variation in TDS between the

locations for dry (43.23mg/l±0.83, 38.20mg/l±1.07)

and wet (29.13mg/l±0.86, 27.06mg/l±1.08) seasons.

The seasonal NO3- values ranged between 0.072 –

0.347 mg/l and 0.076 – 0.272 mg/l across the locations

and stations in dry and wet seasons respectively. The

highest NO3- was recorded in February (AGO1DS1);

lowestNO3- was recorded in March (OGO1DS1). The

highest NO3- was recorded at the end of the wet

season, while the lowest NO3- was recorded in the dry

season. The mean NO3- values were significantly

different (P<0.05) across the stations. There was

significant difference (p<0.05) in mean NO3- in

Ogobiri (0.132mg/l±0.22) and Agoro-Gbene

(0.205mg/l±0.22) locations. There was also

significant (p<0.05) variation in NO3- between the

locations for dry (0.107mg/l±0.01, 0.271mg/l±0.01)

and wet (0.159mg/l±0.01, 0.142mg/l±0.01) seasons.

The NO2-values ranged between 0.074 – 0.131 mg/l

and 0.051 – 0.132 mg/l across the locations and

stations in dry and wet seasons. The highest NO2- was

recorded in October (OGO2DS2) and November

(OGO1US1); lowestNO2- was recorded in August

(AGO1MD1). The highest NO2- was recorded at the

end of the wet season and the beginning of the dry

season, while the lowest NO3- was recorded in the wet

season. The mean NO2- values were significantly

different (p<0.05) across the stations. There was

significant difference (p<0.05) in mean NO2- in

Ogobiri (0.090mg/l±0.001) and Agoro-Gbene

(0.074mg/l±0.001) locations. There was also

significant (p<0.05) variation in NO2- between the

locations for dry (0.084mg/l±0.003,

0.089mg/l±0.003) and wet (0.096mg/l±0.003,

0.059mg/l±0.003) seasons.

The monthly Cl-values ranged between 0.21 – 0.71

mg/l in dry season and 0.18 – 0.87 mg/l in wet season

across the locations and stations. The highest Cl- was

recorded in August (OGO1DA1); lowestCl- was

recorded in February (AGO1US1). The highest Cl-

was recorded in the wet season, while the lowest Cl-

was recorded in the dry season. The mean Cl- values


stations. There was significant difference (p<0.05) in

mean Cl- in Ogobiri (0.48mg/l±1.09) and Agoro-

Gbene (0.41mg/l±1.37) locations. There was no

significant (p>0.05) variation in Cl- between the

locations for dry (0.36mg/l±2.46, 0.32mg/l±3.17) and

wet (58.81mg/l±2.53, 49.33mg/l±3.20) seasons.

The values of SO42- ranged between 6.52–7.89 mg/l

and 5.39 – 9.78 mg/l across the locations and stations.

The highest SO42- was recorded in June (AGO1US3);

lowestSO42- was recorded in December (AGO1DS2).

The highest SO42- was recorded in the wet season,

while the lowest SO42- was recorded in the dry season.

The mean SO42- values were significantly different

(P<0.05) across the stations. There was significant

difference (p<0.05) in mean SO42- in Ogobiri

(6.83mg/l±0.06) and Agoro-Gbene (8.29mg/l±0.08)

locations. There was also significant (p<0.05)

variation in SO42- between the locations for dry

(7.50mg/l±0.14, 7.45mg/l±0.18) and wet

(6.16mg/l±0.15, 9.12mg/l±0.19) seasons.

Table 3: Condition factor fish in Ogobiri station during dry Season

S/N Fish Species Nov. Dec. Jan. Feb. Mar.

1. B. nurse 1.20±0.03 1.19±0.04 1.14±0.03 1.22±0.04 1.21±0.03

2. B. macrolepidotus 1.15±0.07 1.06±0.05 1.23±0.07 1.11±0.07 1.02±0.05

3. S. batensoda 1.19±0.03 1.15±0.04 1.13±0.04 1.11±0.04 1.19±0.03

4. S. membranaceous 0.87±0.02 0.84±0.02 0.90±0.03 0.81±0.04 0.87±0.02

5. C. furcatus 0.88±0.04 0.89±0.03 0.87±0.03 0.90±0.04 0.91±0.04

6. P. quadrifilis 2.25±0.03 2.21±0.04 2.22±0.04 2.23±0.03 2.21±0.04

7. O. mento 1.17±0.03 1.24±0.02 1.21±0.03 1.16±0.03 1.22±0.04

8. P. pellucida 1.30±0.03 1.25±0.04 1.20±0.03 1.22±0.03 1.31±0.04

9. C. senegalensis 0.78±0.04 0.80±0.03 0.76±0.03 0.84±0.04 0.78±0.03

10. H. brevis 0.78±0.04 0.62±0.03 0.77±0.03 0.69±0.04 0.61±0.03

11. L. coubie 1.22±0.03 1.28±0.04 1.21±0.03 1.27±0.04 1.26±0.03

12. L. senegalensis 1.51±0.04 1.42±0.05 1.41±0.03 1.52±0.04 1.40±0.04

13. G. abadii 0.78±0.03 0.81±0.03 0.78±0.03 0.90±0.04 0.92±0.03

14. D. brevipinnis 1.28±0.03 1.30±0.03 1.44±0.03 1.25±0.03 1.41±0.03

15. S. uranoscopus 0.74±0.04 0.70±0.03 0.82±0.03 0.77±0.04 0.80±0.03

16. S. mystus 0.76±0.01 0.81±0.01 0.84±0.01 0.74±0.01 0.75±0.01

17. C. citherus 1.44±0.03 1.46±0.03 1.32±0.03 1.49±0.03 1.42±0.03

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18. H. odoe 1.16±0.04 1.26±0.04 1.15±0.04 1.24±0.05 1.29±0.03

19. C. laticeps 1.08±0.04 1.11±0.04 1.06±0.04 1.22±0.04 1.12±0.04

20. A. baremose 0.20±0.01 0.15±0.01 0.09±0.01 0.11±0.01 0.12±0.01

21. P. bovei 1.48±0.02 1.51±0.03 1.43±0.04 1.44±0.04 1.51±0.04

22. E. senegalensis 2.74±0.06 2.78±0.05 2.68±0.05 2.70±0.05 2.71±0.06

Table 4: Condition factor of fish in Agorogbene station during dry Season

S/N Fish Species Nov. Dec. Jan. Feb. Mar.

1. B. nurse 2.90±0.06 3.02±0.05 3.04±0.05 3.10±0.05 3.09±0.05

2. B. macrolepidotus 4.11±0.05 3.98±0.06 4.19±0.05 4.20±0.05 4.09±0.05

3. S. batensoda 1.58±0.03 1.52±0.03 1.59±0.03 1.59±0.03 1.69±0.03

4. S. membranaceous 1.90±0.04 1.78±0.05 1.80±0.04 1.86±0.05 1.88±0.04

5. C. furcatus 2.20±0.95 2.24±0.94 2.15±0.95 2.10±0.94 2.25±0.94

6. S. nigrita 1.50±0.03 1.59±0.03 1.64±0.03 1.57±0.02 1.61±0.03

7. P. quadrifilis 3.20±0.07 3.14±0.08 3.06±0.07 3.08±0.07 3.12±0.08

8. O. mento 1.65±0.03 1.71±0.03 1.75±0.03 1.62±0.03 1.70±0.03

9. P. pellucid 2.14±0.03 2.00±0.03 1.98±0.03 2.18±0.03 2.07±0.03

10. C. senegalensis 1.60±0.04 1.58±0.03 1.64±0.03 1.72±0.03 1.77±0.03

11. H. brevis 3.18±0.03 3.21±0.03 3.26±0.03 3.23±0.04 3.17±0.03

12. L. coubie 1.35±0.03 1.25±0.03 1.31±0.04 1.36±0.03 1.28±0.03

13. L. senegalensis 1.55±0.03 1.58±0.03 1.46±0.04 1.49±0.03 1.51±0.03

14. G. abadii 2.34±0.04 2.39±0.03 2.41±0.03 2.44±0.03 2.48±0.03

15. D. brevipinnis 5.61±0.05 5.62±0.05 5.72±0.06 5.74±0.05 5.68±0.05

16. S. uranoscopus 0.92±0.03 0.84±0.04 0.90±0.04 0.81±0.03 0.79±0.05

17. S. mystus 1.09±0.03 1.12±0.03 1.15±0.03 1.16±0.03 1.07±0.03

18. C. citherus 2.70±0.03 2.51±0.03 2.64±0.03 2.71±0.03 2.69±0.04

19. H. bdoe 1.16±0.03 1.15±0.03 1.22±0.04 1.24±0.03 1.20±0.03

20. C. laticeps 2.16±0.03 2.15±0.03 2.22±0.04 2.28±0.03 2.19±0.03

21. A. Baremose 1.71±0.04 1.78±0.03 1.72±0.03 1.80±0.03 1.65±0.04

22. P. bovei 2.06±0.03 2.10±0.03 2.08±0.03 1.92±0.04 2.01±0.03

23. E. senegalensis 2.66±0.48 2.65±0.49 2.54±0.48 2.56±0.49 2.68±0.48

24. D. engycephalus 1.32±0.03 1.36±0.04 1.25±0.03 1.38±0.04 1.28±0.03

25. H. faciatus 2.31±0.03 2.36±0.03 2.42±0.04 2.36±0.03 2.44±0.03

26. P. ansorgii 0.66±0.01 0.70±0.01 0.72±0.01 0.56±0.01 0.61±0.01

27. P. afer 1.20±0.03 1.22±0.03 1.25±0.04 0.12±0.03 1.08±0.04

28. X. nigri 1.26±0.46 1.21±0.45 1.18±0.46 1.36±0.45 1.34±0.46

Table 5: Condition factor fish in Ogobiri station during wet Season

S/N Fish Species Jun. Jul. Aug. Sep. Oct. Apr. May

1. B. nurse 1.17±0.03 1.18±0.04 1.18±0.05 1.18±0.05 1.24±0.03 1.16±0.03 1.21±0.04

2. B. macrolepidotus 1.09±0.08 1.35±0.11 1.07±0.08 0.92±0.03 1.19±0.06 1.22±0.07 1.14±0.07

3. S. batensoda 1.11±0.05 1.22±0.04 1.12±0.05 1.16±0.06 1.17±0.04 1.16±0.04 1.10±0.04

4. S. membranaceous 0.84±0.03 0.84±0.03 0.87±0.03 0.86±0.03 0.83±0.03 0.83±0.02 0.87±0.03

5. C. furcatus 0.86±0.04 0.89±0.04 0.91±0.03 0.90±0.03 0.86±0.03 0.88±0.04 0.89±0.04

6. P. quadrifilis 2.20±0.03 2.22±0.03 2.24±0.03 2.20±0.03 2.23±0.04 2.28±0.03 2.26±0.03

7. O. mento 1.18±0.03 1.17±0.03 1.18±0.04 1.22±0.03 1.20±0.03 1.17±0.04 1.23±0.04

8. P. pellucida 1.29±0.03 1.23±0.03 1.32±0.04 1.23±0.03 1.29±0.05 1.20±0.03 1.31±0.04

9. C. senegalensis 0.84±0.03 0.85±0.04 0.81±0.03 0.82±0.03 0.80±0.04 0.09±0.03 0.82±0.03

10. H. brevis 0.70±0.03 0.68±0.03 0.72±0.04 0.69±0.03 0.74±0.03 0.68±0.03 0.66±0.03

11. L. coubie 1.28±0.03 1.28±0.04 1.26±0.03 1.30±0.03 1.32±0.03 1.18±0.04 1.21±0.03

12. L. senegalensis 1.40±0.05 1.48±0.04 1.50±0.06 1.54±0.04 1.48±0.04 1.39±0.05 1.38±0.05

13. G. abadii 0.80±0.03 0.82±0.02 0.88±0.03 0.86±0.03 0.81±0.02 0.89±0.03 0.91±0.04

14. D. brevipinnis 1.32±0.03 1.40±0.04 1.34±0.03 1.42±0.03 1.35±0.03 1.30±0.04 1.33±0.03

15. S. uranoscopus 0.75±0.03 0.71±0.03 0.70±0.0o4 0.84±0.03 0.88±0.03 0.71±0.03 0.81±0.03

16. S. mystus 0.62±0.01 0.78±0.01 0.68±0.01 0.70±0.01 0.74±0.01 0.70±0.01 0.77±0.01

17. C. citherus 1.42±0.03 1.44±0.03 1.38±0.04 1.36±0.03 1.48±0.04 1.43±0.03 1.47±0.03

18. H. odoe 1.22±0.04 1.28±0.05 1.25±0.04 1.18±0.03 1.15±0.04 1.22±0.04 1.28±0.04

19. C. laticeps 1.08±0.04 1.05±0.04 1.14±0.03 1.16±0.04 1.20±0.04 1.02±0.04 1.24±0.04

20. A. baremose 0.08±0.01 0.07±0.01 0.15±0.01 0.11±0.01 0.18±0.01 0.15±0.01 0.18±0.01

21. P. bovei 1.42±0.04 1.48±0.04 1.52±0.03 1.58±0.04 1.61±0.04 1.55±0.04 1.47±0.04

22. E. senegalensis 2.75±0.06 2.62±0.05 2.77±0.06 2.61±0.05 2.66±0.05 2.69±0.05 2.71±0.05

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Table 6: Condition factor of fish in Agorogbene station during wet Season

S/N Fish Species Jun. Jul. Aug. Sep. Oct. Apr. May

1. B. nurse 3.05±0.06 3.11±0.05 3.01±0.06 3.18±0.05 3.06±0.05 3.07±0.05 3.16±0.05

2. B. macrolepidotus 4.08±0.04 4.05±0.04 4.10±0.05 4.10±0.04 4.05±0.05 4.15±0.05 4.02±0.06

3. S. batensoda 1.55±0.02 1.56±0.03 1.54±0.03 1.60±0.03 1.61±0.04 1.66±0.03 1.68±0.03

4. S. membranaceous 1.76±0.05 1.77±0.04 1.82±0.04 1.88±0.05 1.89±0.04 1.92±0.05 1.93±0.04

5. C. furcatus 2.22±0.94 2.24±0.95 2.30±0.94 2.28±0.95 2.19±0.94 2.11±0.95 2.28±0.94

6. S. nigrita 1.55±0.03 1.56±0.02 1.58±0.03 1.60±0.03 1.63±0.03 1.52±0.03 1.55±0.03

7. P. quadrifilis 3.10±0.07 3.15±0.08 3.11±0.07 3.05±0.08 3.14±0.07 3.15±0.07 3.18±0.07

8. O. mento 1.66±0.03 1.68±0.03 1.70±0.02 1.72±0.03 1.60±0.03 1.71±0.02 1.74±0.03

9. P. pellucid 2.08±0.04 2.10±0.03 2.05±0.03 2.06±0.04 2.11±0.03 2.10±0.03 2.13±0.03

10. C. senegalensis 1.66±0.03 1.70±0.04 1.72±0.03 1.75±0.03 1.65±0.03 1.62±0.04 1.64±0.03

11. H. brevis 3.20±0.04 3.25±0.04 3.30±0.03 3.32±0.03 3.28±0.04 3.21±0.03 3.28±0.03

12. L. coubie 1.28±0.03 1.30±0.03 1.26±0.03 1.27±0.03 1.32±0.04 1.29±0.04 1.31±0.03

13. L. senegalensis 1.48±0.04 1.50±0.04 1.46±0.03 1.42±0.03 1.54±0.03 1.52±0.04 1.53±0.04

14. G. abadii 2.40±0.05 2.38±0.04 2.42±0.03 2.36±0.03 2.32±0.03 2.38±0.04 2.42±0.03

15. D. brevipinnis 5.68±0.06 5.65±0.05 5.70±0.05 5.60±0.05 5.66±0.05 5.69±0.05 5.61±0.06

16. S. uranoscopus 0.88±0.03 0.80±0,04 0.82±0.03 0.89±0.03 0.90±0.04 0.78±0.05 0.89±0.05

17. S. mystus 1.05±0.03 1.08±0.02 1.10±0.03 1.01±0.03 1.11±0.03 1.12±0.02 1.10±0.03

18. C. citherus 2.50±0.04 2.58±0.03 2.00±0.03 2.60±0.04 2.66±0.03 2.51±0.03 2.59±0.03

19. H. bdoe 1.22±0.04 1.28±0.03 1.26±0.04 1.25±0.04 1.18±0.03 1.32±0.03 1.31±0.03

20. C. laticeps 2.10±0.04 2.12±0.03 2.20±0.03 2.26±0.04 2.30±0.03 2.21±0.03 2.32±0.04

21. A. Baremose 1.77±0.03 1.68±0.03 1.62±0.04 1.66±0.03 1.76±0.03 1.74±0.04 1.69±0.03

22. P. bovei 1.91±0.04 1.90±0.03 1.99±0.04 2.00±0.03 2.08±0.03 2.07±0.03 1.94±0.03

23. E. senegalensis 2.55±0.49 2.58±0.48 2.60±0.48 2.62±0.49 2.61±0.49 2.70±0.48 2.51±0.49

24. D. engycephalus 1.24±0.03 1.28±0.04 1.22±0.03 1.23±0.04 1.30±0.03 1.31±0.03 1.33±0.04

25. H. faciatus 2.30±0.04 2.38±0.04 2.32±0.03 2.40±0.03 2.42±0.04 2.28±0.04 2.30±0.03

26. P. ansorgii 0.55±0.01 0.32±0.01 0.54±0.01 0.60±0.01 0.64±0.01 0.63±0.01 0.64±0.01

27. P. afer 1.10±0.04 1.12±0.03 1.15±0.03 1.18±0.03 1.18±0.03 1.06±0.03 1.21±0.03

28. X. nigri 1.20±0.46 1.21±0.45 1.28±0.46 1.30±0.46 1.30±0.46 1.31±0.45 1.29±0.45

The seasonal and spatial Condition Factor of the

various fish species in both Ogobiri (Dredged) and

Agoro-Gbene (Un-dredged) Locations are shown in

Tables 3 - 6 respectively. The monthly Condition

Factor for the various fish species in both locations are

shown in Tables 3 - 6 respectively. The graphical

presentations of the mean Condition Factor of all the

various fish species studied in both locations are

shown in Figs. 24 & 25, while the monthly Condition

Factor for 22 representative fish species from both

locations are shown in Figs. 26 – 47 respectively.

The mean condition factor ranged from 0.10±0.003

(Alestes baremose) to 2.24±0.03 (Polydactylus

quadrifilis) in Ogobiri location and 0.58±0.003

(Polypterus ansorgii) to 5.64±0.05 (Distochodus

brevipinnis) in Agoro-Gbene location. There were

significant differences using t-test at 95& level in the

mean condition factor for the combined fish species

and the monthly Condition Factor for each fish

species studied between Ogobiri and Agoro-Gbene

locations.

DISCUSSION

The depth values ranged between 0.50m and 29.50m in this study. The highest depth was recorded in

October which is the peak of the wet season, while the

lowest depth was recorded in March which is towards

the end the dry season. The higher values recorded in

the wet season is as a result of high floods influenced

by high amount of rainfall. Water levels rose steeply,

spreading into the floodplains therefore the .height of

the flood. The rise was fastest after the first rains and

believed to be influenced by discharges transmitted

from upstream and aided by local rains. Welcome

(1979) had earlier observed this trend and noted that

the flood curve at any point in a river was derived

from discharges transmitted from upstream, input

from local tributaries and precipitation in the

immediate area. These values compare favorably

with results obtained in other studies in the Nun River.

Water depth correlated significantly with Current

Velocity, but was inversely related to temperature,

turbidity, conductivity and fish species abundance

(Otobo, 1993). The mean depth in Ogobiri location

was significantly higher than values obtained in

Agoro-Gbene location; this can be attributed to the

dredging operation in Ogobiri resulting in much

higher depths than usual as a result of excessive

extraction of sand from the river bottom.

The pH range of 5.50 – 8.72 obtained in this study

shows an acidic to alkaline condition for the study

locations. The mean values of 7.17±0.01 and 7.26±0.01 obtained in Ogobiri and Agoro-Gbene

locations exhibited slightly alkaline conditions. This

agrees with earlier findings from tropical aquatic

ecosystems (Welcome, 1986) and Otobo (1995b) who

Seiyaboh and Sikoki


336

also recorded a pH of 7.3. The pH level in rivers,

lakes, and streams is an important biological indicator

because low pH levels are harmful to most living

organisms. If pH changes to beyond the preferred

range for an organism, physiological processes may

be adversely affected. This is especially true for most

organisms if the ambient pH drops to below ~7 or rises

to above 9. Physical damage to the gills, skin and eyes

can also occur when pH is sub-optimal for fish, and

skin damage increases susceptibility to fungal

infections such as red spot disease. When pH values

are driven to greater extremes under eutrophic

conditions, algal species with tolerance to extreme pH

levels grow and dominate communities, and

potentially form algal blooms. The effects of high pH

on fish may include: death; damage to outer surfaces

like gills, eyes, and skin; and an inability to dispose of

metabolic wastes. The seasonality in pH observed in

this study with higher values in the dry season than the

wet season, has been recorded for many African

Rivers (Adebisi, 1987 for Ogun River; Akpan and

Offem, 1993 for Cross River; Courant, et. al., 1985 for

Niger Delta; Welcome, 1985 for River Tony, Sierra

Leone; Dublin-Green, 1990 for Bonny River; Ekeh

and Sikoki, 2003 for the New Calabar River; Ansa,

2005 for Andoni flats of the Niger Delta area). The

mean pH values recorded in the locations were within

the preferred pH of 6.5 – 9.0 recommended for

optimal fish production (Boyd and Lichktopller,

1979). However, the pH in the dredged location was

generally acidic ranging from 6.69 – 6.93, acidic

sediment can have an adverse effect on fisheries

distribution.

The range of surface water temperature in this study

(26.1oC – 29.8oC) is in agreement with Otobo (1995d)

who reported a range of 26 oC - 30 oC for the Nun

River. The temperature range is also typical of 25 oC -

30 oC in African Rivers (Macan, 1963). It is also

within the reported range of 21 oC - 30 oC in the Niger

Delta (Ewa, 1988; Hutchinson, 1957). These findings

agree with earlier works in the Niger Delta waters by

Chindah et. al ., (1998) who reported temperature

range of between 26 oC - 30.5 oC; Zabbey (2002)

between 26.3 oC – 30.4; Braide et al., (2004) 26.64 oC

– 30.8 oC; Ansa (2005) 25.9 oC – 32.4 oC; Hart and

Zabbey (2005) 25.8 oC – 27.8 oC; Sikoki and Zabbey

(2006) 26 oC – 27.8 oC; Dibia (2006) 25 oC - 27 oC;

Seiyaboh et al., (2007) 26 oC and Jamabo (2008) who

reported a temperature range of 27 oC - 30 oC in the

Upper Bonny River of Niger Delta. The highest

temperatures were recorded in the wet season months

of May, June, July and August. This trend is similar

that reported in Andoni River in the brackish water

environment (Francis, 2003). There was a slight drop

in temperature observed in December and January which may be attributed to a drop in air temperature

during the hamattan period. Positive correlation

between air and surface water temperatures has been

reported by Welcome (1985). According to Hynes

(1970), tropical stream temperatures increase

downstream until they reach equilibrium with the air

temperature.

The turbidity range of 22.15NTU – 125.80NTU

observed in this study showed a gradual increase in

turbidity values from the upstream stations to

downstream stations along the creek. These values

were higher than the values obtained by Seiyaboh et. al., (2007) ranging from 5NTU – 64NTU in the Nun

River. The highest turbidity values were recorded at

the dredged location and gradually declined further

downstream. The mean turbidity value of 62.54NTU

recorded in Ogobiri (Dredged) location was

significantly higher than 44.25NTU recorded in

Agoro-Gbene (Undredged) location. This can be

attributed to the dredging operation in the area. The

highest turbidity was recorded at the peak of the wet

season (October) during the heavy rains which were

accompanied by increased water current velocity. The

results also showed much higher values for Turbidity

in the station immediately downstream of the dredged

area and steadily declined further downstream. The

dredging operation and in addition, increased

sediment load from surface run-offs (Lucinda and

Martin (1999) and those picked up by the accelerated

water flow during this period may explain this trend.

According to Welcome (1985), acceleration of flow

causes rivers to pick up sediments hence, waters in the

rising flood are heavily charged with silt load. High

turbidity reduces light penetration and visibility,

which in turn limits plant growth, fish movements and

the ability of predatory fish and birds to see their prey.

When sediments from turbid water settle, they may

smother organisms living on the bottom of waterways

and alter aquatic habitats. High levels of suspended

solids can make water unsuitable for a range of

environmental needs and human uses. For instance,

high levels of suspended solids reduce the efficacy

(and therefore increase costs) of disinfectants used to

treat water for drinking purposes, by shielding

pathogens from the action of the disinfectant. On the

other hand, high turbidity levels allow higher

phosphorus and nitrogen levels to be tolerated without

triggering algal blooms because they reduce the

availability of light to the algae (EPA, 1996a). During

dredging, resuspension of sediment in the water

column is likely to occur as a result of dredging action

at the sediment-water interface (Seiyaboh et. al., 2007), transfer of the sediment to a transporting

vessel, slop or leakage from the vessel, and disposal

of the sediment. Resuspension of the sediments causes

increased turbidity which may adversely affect

aquatic life by clogging gills, decreasing visibility,

and preventing oxygen diffusion. However, since the increased turbidity is expected to be short term and

only cover a limited area, the impact should not be

significant (Richard, et al., 1997). Resuspension of

sediments may result in release of constituent

Seiyaboh and Sikoki


337

pollutants such as heavy metals from the sediment

into the water. Therefore, water quality parameters,

such as turbidity, heavy metals, and nutrients could be

affected during the dredging operations.

The conductivity range (50hmoscm-1 -

167hmoscm-1) obtained in this study compares

favorably with the range of 89 hmoscm-1 -

110hmoscm-1 recorded for the Nun River around

Tombia by Seiyaboh et. al., (2007). However, these

values are higher than the range of 30hmoscm-1 -

71hmoscm-1 recorded for the Niger Delta and Otobo

(1995b) range of 42hmoscm-1 - 68hmoscm-1 in the

Nun River around Polaku. Distinct seasonality in

conductivity was evident in this study as there was a

significant difference between the wet and dry season

conductivity values. This assertion collaborated with

other works in different water bodies within the Niger

Delta (Dublin-Green, 1990 in Main Bonny River;

Mallin et. al.,1999; Dibia, 2006 in Mini-Chinidah

Stream, Port Harcourt; Davies et. al., 2008 in Trans-

Amadi (Woji) Creek, Niger Delta). Bishop (1973) had

earlier explained higher conductivity values in the dry

season as resulting from the concentration of ions by

evaporation and increased mineralisation of organic

matter. The results from this study compares

favorably with the results of Dublin-Green (1990) and

Zabbey (2002) in Woji Creek. The reduction in

conductivity with rising flood in this study may be

attributed to the dilution effect of the increased water

volume within the river system (Otobo, 1995b).

According to Welcome (1985) conductivity could

also be affected by local conditions such as washing

out of nutrient rich grounds during rain. The mean

conductivity value of 76.23hmoscm-1 in Ogobiri

(Dredged) location was significantly higher than

65.44hmoscm-1 recorded in Agoro-Gbene

(Undredged) location. This may be indicative of the

impact of dredging in the study area.

The DO values ranged between 2.1mg/l – 6.5mg/l and

is close to that obtained by Seiyaboh et. al., (2007) in

the Nun River (3.8mg/l – 7.2mg/l). The higher DO

values recorded in the dry season did not agree with

the findings of Egborge (1971) who reported that DO

is generally higher in the wet season in the tropics.

The lowest DO value was recorded at the peak of the

wet season and in the dredged location. A possible

explanation for the lower DO values in the wet season

could be as a result of turbidity of the water at this

period; possibly due to dredging, inflows from run-off

and decomposition of organic matter in the water.

Braide et al., (2004) also had similar results in their

study of the water quality of Miniweja stream in

Eastern Niger Delta, Nigeria.

The TDS range of 22.00mg/l – 85.60mg/l with higher

values in the dry season than the wet season is in

agreement with Otobo (199b5). The richness or

fertility of a river is determined by its nutrient load.

The mean TDS value of 36.18mg/l in Ogobiri


32.67mg/l recorded in Agoro-Gbene (Un-dredged)

location. This may be attributed to the release of

nutrients as a result of re-suspension of sediments

during dredging operations.

Nitrate values ranged from 0.023mg/l – 0.550mg/l and

were lower than that obtained by Seiyaboh et. al.,

(2007) in the Nun River (0.32mg/l – 4.15mg/l). The

mean NO3- value of 0.132mg/l in Ogobiri (Dredged)

location was significantly lower than 0.205mg/l

obtained in Agoro-Gbene (Un-dredged) location.

Nitrate levels were higher in the wet season than in the

dry season; this may be attributed to influx from run-

off, domestic waste and other organic materials

discharged into the river system during the flood

period.

Nitrite values ranged between 0.021mg/l –

0.168mg./l. Highest nitrite was observed in both wet

and dry season. High nitrite in the wet season can be

attributed to higher nutrient load from run-off and

domestic waste discharged into the river system. High

concentration of nitrite in the aquatic environment can

lead to fish toxicity. The mean NO2- value of

0.090mg/l in Ogobiri (Dredged) location) was

significantly higher than 0.074mg/l obtained in

Agoro-Gbene (Un-dredged) location. The results

showed higher values for NO2- in the station

immediately downstream of the dredged area which

steadily declined further downstream. This is

indicative of impact of dredging on NO2- level.

Chloride values ranged from 0.10mg/l – 1.09mg/l.

The highest Cl- value was recorded in the wet season,

while the lowest Cl- value was recorded in the dry

season. The mean Cl- value of 0.48mg/l in Ogobiri


0.40mg/l obtained in Agoro-Gbene (Un-dredged)

location.

The sulphate values ranged from 3.3mg/l – 12.50mg/l

with highest value recorded in the wet season and

lowest value recorded in the dry season. This may be

attributed to influx from run-off into the river system

during the flood period. The mean S042-value of

6.83mg/l in Ogobiri (Dredged) location) was

significantly lower than 8.29 mg/l obtained in Agoro-

Gbene (Un-dredged) location.

Alkalinity values ranged from 7.00mg/l – 128.00mg/l

and values for wet and dry seasons varied

significantly with wet season having the highest

alkalinity values. This can be considered to be influenced by presence of domestic waste and tidal

action which has a flushing and diluting effect on

dissolved constituents as well as carbonates capable

of increasing alkalinity levels.

Seiyaboh and Sikoki


338

The BOD5 values ranged from 0.7mg/l – 12.7mg/l and

these values varied considerably from 1.97mg/l –

2.69mg/g recorded by Abowei & George (2009) in

Okpoka Creek, Niger Delta, Nigeria. The higher

BOD5 load recorded in the month of February could

be attributed to increased degradable organic waste

load as noted by McNeely et. al., (1979) and Clerk

(1986)

This study identified a total of 22 species belonging to

13 families caught in Ogobiri (Dredged) Location;

and a total of 28 species belonging to 16 families

caught in Agoro-Gbene (Un-dredged) Location. This

species composition was lower than the results of

studies in other water bodies: Lowe-McConnel,

(1964) encountered 44 species in the Riepennime

River; Okereke (1990) observed 46 species of 20

families in Otamiri River; Alfred-Ockiya (1998)

observed 41 species in Kolo creek; Sydenham, (1979)

observed 85 species in Ogun River; Nwadiaro (1989)

identified 89 species in Oguta Lake; Reid and

Sydenham (1979) 120 species from the Lower Benue

River; Victor and Tetteh (1988) 58 species from

Ikpoba River; Imevbore and Okpo (1975) 70 species

from River Niger; Sikoki, et. al., (1998) 34 species

from the Nun River; Nweke, (1984) 29 species in Aba

River. However, the 22 & 28 species recorded in both

locations in this study were higher than that reported

by Sydenham (1975) 13 species in Odo-Ona stream;

Ekeh (1990) 19 species in Nworie River.

This study showed that of the 22 & 28 species

recorded in both Ogobiri (Dredged) and Agoro-Gbene

(Un-dredged) locations, Shilbe uranoscopus was the

most dominant in both locations accounting for 7.5%

and 6.8% respectively. The result of seasonality of the

catch composition showed that the mean catch in the

dry season was relatively higher than the rainy season.

The increase in catch during the dry season may be

attributed to lower water levels which favored the

effective use of most fishing gear in the study

location. This is in agreement with the findings of

Turner, (1970) who on using experimental gill net

data observed that the catch rate was inversely related

to the water level. Bazigos (1972) also observed a

significant correlation between the commercial

catches and water level fluctuations in the Kainji

Lake. According to APHA (1980) distribution and

abundance of fish is determined by water depth,

shoreline activity, sediment type and other factors.

Chindah and Osuamkpe (1994) caught a higher

proportion of adult sized fish in the late dry season

than in the wet season in the creeks which was

attributed to spawning aggregation.

The effect of season on catch composition was tested

using the Analysis of Variance by Ita (1978). The

variations were not statistically significant, but when

variations were reclassified in reaction to water level

fluctuations, a definite trend was observed with the

lowest mean catch during the high water mark.

Bazigos (1972) attributed this to increased fishing

effort and greater investment in fishing gears by local

fishers during the period of low water.

The result of the respective percentage composition in

number and total weight of fish caught in the various

locations showed that the following: Ogobiri

(Dredged) location - 26,988 (44.8%); 1000.57

(31.5%) and Agoro-Gbene Un-dredged) location -

33,275 (55.2%); 2175.51 (68.5%). This study

revealed that Agoro-Gbene location recorded the

highest values both in total number and weight of

55.2% and 68.5% respectively. This may be attributed

to the relatively better environmental condition in

Agoro-Gbene (Un-dredged) location as revealed by

this investigation when compared to Ogobiri

(Dredged) location, which may be a direct

consequence of the dredging in this location. The

values obtained in Agoro-Gbene (Un-dredged)

location are significantly higher (p<0.05) than those

obtained in Ogobiri (Dredged) location.

The mean Condition Factor of the various fish species

in this study ranged from 0.10 – 2.24 in Ogobiri

(Dredged) location for 22 fish species and 0.58 – 5.64

in Agoro-Gbene (Undredged) location for 28 fish

species. For most species in the present study,

condition factor values were higher than the 0.917 –

0.985 recorded by Abowei and George (2009) for 5

fish species from Nkoro River, Niger Delta; 0.92 –

0.98 recorded by Hart and Abowei (2007) for 10 fish

species in the Lower Nun River; 0.64 – 1.99 recorded

by Fafioye and Oluajo (2005) for 5 fish species in Epe

Lagoon, Nigeria; 0.12 – 16.29 recorded by Kumolu-

Johnson and Ndimele (2010) for 21 fish species in

Ologe Lagoon, Lagos.

The values obtained for mean Condition Factor and

monthly Condition Factor for the various fish species

in Agoro-Gbene (Un-dredged) location were

significantly higher (p<0.05) than values obtained for

Ogobiri (Dredged) location. The statistical analysis of

twenty-two (22) representative organisms occurring

in both locations clearly shows this trend. The mean

Condition Factor of the various fish species in Ogobiri

(Dredged) location were lesser than those values (2.9

– 4.8) documented by Bagenal and Tesch (1978) for

mature fresh water fish. This suggests that the

condition of Igbedi creek, upper Nun River around

Ogobiri location in comparison to other fresh water

bodies is unfavorable to fishes irrespective of season.

The results of the Physico-Chemical characteristics of

water samples from this location further confirms this

assertion.

From the results obtained in this study, we can

conclude that the fish species in Agoro-Gbene were

relatively in a better condition than those in Ogobiri

Seiyaboh and Sikoki


339

location. This might not be unconnected with the

dredging operation in Ogobiri location.

CONCLUSION

The impact of dredging on the Balance of Nature and

Biodiversity of Igbedi Creek, upper Nun River in

Central Niger Delta was investigated from June 2009

– May 2011. The study investigated the

physicochemical characteristics of the water, length-

weight relationships, condition factor, catch

composition, relative abundance and growth pattern

of the fish species in Ogobiri (Dredged) and Agoro-

Gbene (Un-dredged) location. There were significant

spatial differences (P<0.05) between the locations in

all the water parameters measured except for DO,

Temperature and pH. In addition, there were

significant temporal variations between the locations

for the following parameters: Temperature, Turbidity,

Conductivity, N03-, NO2

-, S042-, and BOD5. The results

also showed higher values for Turbidity and NO2- in

the station immediately downstream of the dredged

area which steadily declined further downstream. In

the Dredged location, all fish species exhibited

negative allometric growth with length exponent.

There were significant spatial and temporal

differences in the condition factor for the fish species

between the Dredged and the Un-dredged locations.

The results also indicate that the fish species in the

Un-dredged location were generally in a better

condition than those in the Dredged location. From the

above information, it is concluded that there has been

an impact of dredging on the Balance of Nature and

Biodiversity of Igbedi Creek, Upper Nun River.

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