Application of Abundance Biomass Curve in Ecological...

* E-mail: [email protected]

Application of Abundance Biomass Curve in Ecological Health Assessment of Khure-Mussa

(Northwest of the Persian Gulf)

Dehghan-Madiseh, Simin1*; Nabavi, Seyed Mohammad Bagher2; Ghofleh-Marammazi, Jasem1; Jahani, Najmeh1; Koochaknejad, Emad1

1- Department of Ecology, South of Iran Aquaculture Research Center, Ahvaz, IR Iran 2- Deputy of Marine Environment, Department of Environment, Tehran, IR Iran

Received: May 2011 Accepted: December 2011

© 2012 Journal of the Persian Gulf. All rights reserved.

Abstract Khuzestan coastal waters have high fisheries potential and ecological importance. Since different sources of stress exist in this area, the present study was conducted to evaluate ecological quality and to determine health status in Khuzestan coastal sediments based on benthic communities and their biological parameters. Seasonal sampling was done from 20 creeks of Khur-e-Mussa area in Khuzestan coastal waters by 0.125 m2 Peterson grabsampler during winter 2008 to autumn 2009. Macro–invertebrates were separated, sorted and identified to the lowest possible taxon. In addition, biological parameters such as diversity, richness, biomass and abundance were calculated. The results were analyzed using univariate analysis method, ABC (Abundance–Biomass Curve). The most abundant groups were polychaets (58%), crustaceans (25%) and mollusk (9%), respectively. The ABC plots showed that majority ef creeks could be classified as moderately disturbed and polluted. The ranges of H' diversity index values in majority of stations indicated moderate ecological status.

Keywords: ABC (Abundance-Biomass Curve), Benthic communities, Khur-e-Mussa area, Khuzestan coastal waters

1. Introduction

Macrobenthic studies have achieved a fundamental

role in estuarine and marine impact assessment and

marine management. Because marine macrobenthic

invertebrates usually exhibit well-defined responses to

environmental change, especially those stressors which

influence the sediment structure (McLusky and

Elliott, 2004).

Many researches have been carried out attempting

to detect different stressors as result of environmental

deterioration by using benthic communities in the

coastal areas of the world (Gray and Wu, 2002;

Borja et al., 2000; Muxika et al., 2003; Simboura,

2003; Borja et al., 2004; Borja and Muxika, 2005). In last two decades, the study of marine

communities has benefited from the use of so-called

graphical/distributional representations (Warwick

and Clarke, 1991; Warwick, 1993), such as the

Abundance–Biomass Comparison (ABC method)

(Warwick 1986; Warwick et al. 1987). This method

is conceptually intermediate between univariate and

multivariate approaches, and in contrast with

multivariate analyses It has the advantage that a

value judgment can be compared with results

Journal of the Persian Gulf

(Marine Science)/Vol. 3/No. 7/March 2012/9/1-10

reg

(W

abu

dif

res

19

ass

pre

cur

lea

dis

of

ent

thr

com

and

tim

com

19

ma

(D

Do

sho

var

abi

pre

La

and

im

usi

Co

ma

Mu

20

eva

ind

qu

in

me

con

gardless of a

Warwick and

The ABC m

undance and

fferential pe

sponse to

93 and 198

sumption th

esence of la

rve lying ent

ast the first

sturbed comm

small indi

tirely above

ree species

mmunities.

d crossed fo

mes). Origin

mmunities o

86), it has

arine habitat

Dauer et al. 1

ozey et al. 1

ould be dete

rious biolog

ility to pre

eviously kn

ardicci and R

d Yamen an

mpact of fish

ing dominan

omparison (

acrobenthic

ussa creeks

00) but a

aluation in K

dices (Dehgh

The aim of

ality in twen

Khuzestan

ethod was u

ntaminant w

any compari

Clarke, 1991

method is a

d biomass d

erformance

environment

86). This m

hat in undis

arge organism

tirely above t

t three spe

munities, do

ividuals, th

the biomass

plotted i

These curve

or the first th

nally propos

on subtidal

subsequentl

ts, with var

993; Pencza

1999). The u

ermined in d

gical compo

edict change

nown (McM

Rossi 1998).

nd his collea

heries on de

nce curves

(ABC) curv

abundance

have been c

few studie

Khure-Mussa

han-Madiseh

this study w

nty tidal cree

coastal wate

used to deter

which induce

Dehghan-M

ison with co

1).

an internal c

distributions

of those di

tal conditio

method is b

sturbed com

ms results in

the abundan

ecies plotted

minated by

e abundanc

s curve for at

n moderate

es are close

hree species

sed for mac

soft substr

ly been app

rying degree

akand Kruk 1

utility of the

different hab

onents, acco

es in biotic

Manus and

Jouffre and

agues (2005)

emersal fish

and Abunda

ves. Severa

and diversi

carried out (

es were don

a by using d

h 2008; Dosts

was to evalu

eks in Khur-

ers. For this

rmine the sp

ed by prob

Madiseh et al.

ontrol locatio

comparison

based on th

istributions

ons (Warwic

based on th

mmunities, th

n the bioma

ce curve for

d; in gross

large numbe

ce curve li

t least the fir

ely disturbe

ely coincide

(one or mo

cro-zoobenth

ata (Warwic

plied to oth

es of succe

1999; Stento

e ABC mod

bitates and f

ording to i

c data seri

Pauly 199

d Inejih (200

) assessed th

h assemblag

ance Bioma

al studies o

ity in Khur

(Nabavi 199

ne on heal

different biot

shenas 2009)

uate ecologic

-e-Mussa are

reason, AB

patial sedime

able pollutio

/ Application

2

on

of

he

in

ck

he

he

ass

at

sly

ers

ies

rst

ed

ent

ore

hic

ck

her

ess

on-

del

for

its

ies

90;

05)

he

ges

ass

on

re-

97,

lth

tic

).

cal

ea,

BC

ent

on

sourc

and f

of m

2. M

Tw

North

Seas

autum

macr

organ

grab

Fig. (2008SemaShipp16-Kh19- K

FosieveorganseparusingCarpwere

A

Biom

Marg

of Abundanc

ces in this ar

fisheries activ

many types of

Materials and

wenty creek

hwest of the

onal samplin

mn 2009. T

robenthos stu

nic matter (

(0.125 m2).

1: The locatio8-09) 1-Ghanamaili 7-oil stationping station 13hure-mussa (1)

Khure-Mussa(4)

or macrobented through anisms wererated to the g: Barnes 1penter and Nie counted and

bundance (

mass (g/m2),

galef richnes

e Biomass Cu

rea such as, r

vity, several

industries.

d Methods

ks in Khu

e Persian Gu

ng was carried

Three replic

udying, grain

(TOM) were

on of studied m 2-Patil 3-Bihn 8-Odleh 9-Ja3-Ahmadi 14-P) 17- Khure-M 20- Khure-Mu

thos study, saa 0.5 mm me removedlowest anim987; Jones iem1998; Ste

d weighted.

(number of

diversity (S

ss indices w

urve in Ecolog

riverine inpu

out falls and

ure-Mussa a

ulf were stud

d out from wi

cates of ea

n size analy

e obtained

creeks in Khuhad 4-Ghazale afari 10-Zangi Petrochemy sta

Mussa(2) 18- Kussa(5)

amples were mesh screen . Macroben

mal taxonomic1986; Hutc

errer1986) an

f individual

Shannon-Wie

were calculate

gical Health…

uts, shipping

d discharging

area in the

died (Fig. 1).

inter 2008 to

ach site for

sis and total

by Peterson

ure-Mussa area5-Majidieh 6-

11-Doragh 12-ation 15-MaaviKhure-Mussa(3)

immediatelyand benthic

nthos werec groups (bychings 1984;nd all species

l per m2),

ener H') and

ed. For each

g

g

e

.

o

r

l

n

a --i )

y c e y ; s

,

d

h

station, do

biomass we

(Warwick 1

in order of

of abundan

using PRIM

the abundan

W-statistic (

and an even

for undistur

grossly dis

also were c

equation:

Where B

Ai is the rel

the number

using SPSS

3. Results

The orga

sediments

95.59%, res

Fig. 2: Variatiin Khure-Mus

The lo

KhureMuss

(10.90) and

ominance c

ere obtained

1986). In the

importance

nce or bioma

MER statistica

nce curve an

(Yemane et a

n abundance d

rbed, and the

sturbed. The

computed fo

Bi is the relati

lative abunda

r of species

14 software

anic matter

were 10.57

spectively (F

ion of total orgsa creeks

owest perc

sa 3 (10.57)

d the highes

curves for

d following t

e method, sp

based on pe

ass. The plot

al software.

nd the bioma

al., 2005). Bi

distribution g

e reverse case

e W-statistic

or each case

ive biomass

ance of the it

s. ANOVAs

e.

and silt-cla

7 to 29.75%

Fig. 2).

ganic matter and

centage va

), Patil (10.

st percentage

Journal

abundance

the ABC me

pecies are ra

ercent domin

ts were prod

The area bet

ass curve is c

iomass domin

gives a value

e a value of -

cs (Clarke 1

by applyin

of the ith spe

th species and

were calcu

ay percentag

% and 63.6

d silt-clay perc

alues were

80) and So

e values we

l of the Persia

3

and

ethod

anked

nance

duced

tween

called

nance

of +l

-1 for

1990)

ng the

ecies,

d S is

ulated

ge of

60 to

entage

e in

omaili

ere in

D

M

A

si

si

d

A

d

(P

b

id

C

N

S

ab

T

m

P

M

in

F

b

(p

Fi

in

an Gulf (Marin

Doragh (29.7

Majidie (21.5

ANOVA of

ignificant dif

ignificant d

ifferent cree

ANOVA sho

ifferent cre

P<0.05), how

etween seaso

In total, 28

dentified in

Crustacean (3

Nemertean,

eapens and

bundance an

Table 1. The p

macrobenthic fa

Taxa APolychaeta Crustacea Mollusca Seapen Others

Means of

n different s

Figures 3 and

Two way A

etween creek

p<0.05).

ig. 3: Variation

n different seaso

ne Science)/Vo

75), Ghazale

59) and Ship

f silt-clay

fference betw

differences

eks (P<0.05

wed no sign

eeks based

wever, there

ons (P<0.05)

8 faunal grou

ncluding Po

32 families)

Echinoderm

Bryozoans.

nd biomass (T

percentage of t

auna in Khure-M

Abundance (%58.06 24.82 9.35 5.24 2.53

macrobentho

seasons and

4, respective

ANOVAs sh

ks and season

n of macrobenth

ons (2008-2009

Vol .3/No. 7/Ma

eh (24.30),

pping-st. (19

percentages

ween season

were obse

5). In addit

nificant diffe

on total o

were signific

).

ups of benthi

olychaetes

), Mollusca

mata, Echiu

Each group

Table 1).

total biomass

Mussa creeks

%) Taxa Seapen

MolluscaPolychaetCrustacea

os abundanc

creeks are

ely.

howed signifi

ns based on m

hic means abun

9)

March 2012/9/1

Zangi (21.8

9.46). Two w

s showed

ns (P<0.05),

erved betw

tion, two w

erence betw

organic ma

cant differen

ic animals w

(25 famili

(23 famili

ura, Tunica

p differed in

and abundance

Biomass (%94.24

a 2.61 ta 2.08 a 1.07

ce and biom

represented

icant differen

mean abunda

ndance and biom

1-10

80),

way

no

but

een

way

een

atter

nces

were

ies),

ies),

ates,

its

e of

%)

mass

d in

nces

ance

mass

Dehghan-Madiseh et al. / Application of Abundance Biomass Curve in Ecological Health…

4

Fig. 4: Variation of macrobenthic means abundance and biomass in different creeks (2008-2009)

The creeks also showed significant differences based

on biomass (p<0.05). Figures 5a and 6a, show the

results of clustering of the stations using Bray-Curtis

index for similarities based on macrobenthic abundance

and biomass. MDS ordination confirmed the results of

cluster (Figs. 5b and 6b). Majority of creeks showed

above 85% similarity for abundance and above 80% for

biomass. The range of diversity and Richness indices

values were (1.95 to 3.58) and (14 to 33), respectively.

The range of Shannon diversity index was 1.95( in

Shipping-st) to 3.58 (for Patil).

Fig. 5: Cluster (a) and MDS (b) analysis based on Bray-Curtis similarity for macrobenthos abundance in different creeks

Journal of the Persian Gulf (Marine Science)/Vol .3/No. 7/March 2012/9/1-10

5

Fig. 6: Cluster (a) and MDS (b) analysis based on Bray-Curtis similarity for macrobenthos biomass in different creeks

The Shannon index value was above 3 in

Ghannam, Bihad, Odelleh, Jafary, Zangy, Ahmady,

Petrochem-st, Kh-Mussa (3), and Kh-Mussa (5).

Patil had the highest richness value (33) and the

lowest value (14) was in Oil station, Khure-Mussa

(3), and Kh-Mussa (4), and Kh-Mussa (5). Two-way

ANOVAs based on Richness and Shannon index

values, showed only significant differences for

Richness values (P<0.05). ABC curves were

obtained for all creeks. With few representative plots

of the environmental conditions observed in different

creeks presented in Figure 7. W index values were

positive and near zero for all creeks.

4. Discussion

According to the grain size analysis and TOM

content, it is clear that all creeks were characterized

by soft muddy bottom. The difference between

TOMs of different creeks was not significant.

However, the high amount of organic matter in

sediments (10.758-29.75) could be related to changing

seasonal condition. In addition, physical factors such

as prevailing water currents and instability of surface

sediments can also lead to variation of TOM.

Percentages of TOM sediments in all studied creeks

were above EPA standard (EPA, 2002). Studied creeks

showed significant differences between biological

parameters (abundance and richness) values due to

differences in benthic community structure. Significant

differences between seasons showed that there were

seasonal variations in macro-benthic communities in

this area. This temporal variation could have occurred

due to obvious seasonal changes in physico-chemical

and biological parameters in this area (Sabzalizadeh

and Nilsaz, 1996; Nilsaz et al., 2005).


6

Fig. 7: Selection of ABC plots of samples representatives of different conditions within the region. (a: Petrochemical

St; b: Zangy; c: Odelleh; d: Kh-mussa(4); e: Kh-mussa(5); f: Shipping St.) (□ biomass, Δ abundance)

Some biological characteristics like, longevity, reproduction strategy, depth of habitat, trophic level and also fishing pressure exert important influence in variation of frequency, succession and diversity of macrobiotic species (Little, 2000). The seasonal means of diversity index in the present study are less than its reported value in Khuzestan coastal waters (Nilsaz et al., 2005). It is probably due to dominance of opportunistic species such as Capitella sp,Cossura sp, and Chaetozone sp, which contributed to lower diversity index values. However, some evidence indicated that macrobenthic responses differed between metal contamination and organic enrichment. For example, metal contamination could detrimentally affect all taxa, whereas organic enrichment could only favor certain opportunistic taxa (Rygg, 1986; Wilson and Jeffrey, 1994).

Based on (H') diversity index values, all creeks are classified in poor and declining ecological status according to WFD (European Water Framework

Directive) water quality assessment classification (cited in Borja et al., 2003).

W index values in all creeks were positive and near zero, which suggested the moderate ecological status in all studied creeks. The low value of W and crossings between most of the curves led to classifying these stations as moderately perturbed. According to the abundance-biomass curves, some variations could be observed.

The creeks (Jafari, Zangi) and Petrochem stations showed more signs of disturbance condition, the creeks Bihad, Ghazaleh, Doragh, Semaili, Majidieh, Odleh, Ahmadi, Maavi, Oil station and Kh-mussa(4) showed moderate disturbed condition, and the Kh-mussa(1), Kh-mussa(2), Kh-mussa(3), Kh-mussa(5), Shipping station, Patil and Ghannam showed less disturbed condition. The last groups mostly were located in Khure-Mussa channel or placed outside the embayment of Mahshahr creeks. Mahshahr creeks could be affected by many probable pollution


7

sources. In general, according to ABC plots, the most creeks in Khure-Mussa area showed moderate pollution status.

The ABC curve is widely used for the detection of pollution effects on macrobenthos communities (Warwick, 1986; Warwick et al., 1987; Clarke, 1990). High similarity index values could emphasize the same ecological status based on macrobenthic animals in studied areas. In unpolluted systems, with a high evenness and several large-bodied species, the biomass curve will fall well above that for abundance, the reverse being true for heavily polluted situations dominated by high numbers of small species (Adams, 2002).

As a result of different types of exploitation,

industrial and shipping activities in Khure- Mussa

area, unbalanced and moderate ecological status for

sediment quality are expected. Khure-Mussa creeks

are characterized by sever water exchanges in their

base; This and with predominantly silt-clay sediment,

high rate of sedimentation might also be a major

factor in benthic animals fluctuation. For better

evaluation, chemical and biological monitoring is

necessary.

Adjusted SAB (Species-Abundance-Biomass)

relationships varied in their details with respect to

different classes of sediment contamination, but all

types of SAB stress appear to exhibit similar basic

characteristics. Moreover, rapid decrease in the B/A

ratio with increasing contamination supported the

concept that relatively long-lived, large-bodied,

equilibrium taxa decline markedly at high

concentration of toxicants (Rakocinski et al., 2000).

Acknowledgment

The authors are grateful for funding from

Department of Environment of Iran.

References

Adams, S. M., 2002. Biological indicators of aquatic ecosystem stress. American Fisheries Society,

Bethesda, Meryland, 644P.

Barnes, R.D., 1987. Invertebrate Zoology. Saunders

College Publishing, 5th ed.

Borja, A., Franco, J. and Muxka I., 2004. The biotic

indices and the water framework directive: the

required consensus in the new benthic

monitoring tools. Marine Pollution Bulletin. 48:

405-408

Borja, A, Franco, J. and Perez V., 2000. A marine

biotic index to establish the ecological quality of

soft bottom benthos within European estuarine

and coastal environments. Marine Pollution

Bulletin. 40: 1100-1114

Borja, A., Muxika, I. and Franko, J., 2003. The

application of a Marine Biotic Index to different

impact sources affecting soft bottom benthic

communities along European coasts. Marine

Pollution Bulletin. 46: 835-845

Borja, A. and Muxka, I., 2005. Guideline for the use

of AMBI (AZTIs Marine Biotic Index) in the

assessment of the benthic ecological quality.

Marine Pollution Bulletin. 50: 787-789

Clarke, K.R., 1990. Comparisons of dominance

curves. Journal of Experimental Marine Biology

and Ecology.138: 143 -157

Dauer, D.M., Luckenbach, M.W. and Rodi, A.J.,

1993. Abundance biomass comparison (ABC

method): effects of an estuarine gradient,

anoxic/hypoxic events and contaminated

sediments. Marine Biology. 116: 507–518

Dehghan-Madiseh, S., 2008. Identification of

sensitive and impacted area in Khuzestan creeks

by using of ecological and biological indices.

University of Marine Science and Technology

Khorramshahr, Ph.D thesis, (in Persian)

Dostshenas, B., 2009. Classification of Khur-e-

Mussa coastal waters by using sediment biotope

index to evaluation of biotic health. University of

Marine Science and Technology Khorramshahr,

Ph.D thesis, (in Persian)

FAO species identification guide for fishery

purposes, 1998. The living marine resources of


8

the Western Central Pacific. Cephalopods,

Crustaceans, holothuridians and sharks. Rome

Gray, J.S., Wu, R.S. and Or, Y.Y., 2002. Effects of

hypoxia and organic enrichment on the coastal

marine environment. Marine Ecology Progress

Series. 238: 249-279

Hutchings, P.A., 1984. An illustrated guide to the

estuarine Polychaete worms of new South Wales.

Coast and wetland society. Sydney NSW

2000.160p.

Jones, D.A., 1986. A field guide to the seashores of

Kuwait and the Persian Gulf. Bland ford Press.

191P.

Jouffre, D. and Inejih, C.A., 2005. Assessing the

impact of fisheries on demersal fish assemblages

of the Mauritanian continental shelf, 1987-1999,

using dominance curves. ICES Journal of Marine

Science. 62: 380-383

Lardicci, C. and Rossi, F., 1998. Detection of stress

on macro-zoobenthos: evaluation of some

methods in a coastal Mediterranean lagoon.

Marine Environmental Research. 45: 367–386

Little, C., 2000. The Biology of Soft Shores and

Estuaries. Oxford University Press, New York.

252P.

McLusky, D.S. and Elliott, M., 2004. The Estuarine

Ecosystem, Ecology, Threats and Management.3rd

ed. Oxford University Press, 216P.

McManus, J.W. and Pauly, D., 1990. Ecological

stress: variations on a theme by R. M. Warwick.

Marine Biology. 106: 305–308

Muxika, I., Borja, A. and Franco, J., 2003. The use

of a biotic index (AMBI) to identify spatial and

temporal impact gradient of benthic communities

in an estuarine area. ICES CM2003/Session J-01.

Tallinn (Estonia)

Nabavi, S.M.B., 2000. Macrobenthic study in

Mahshahr creeks with emphasis on its role on

aquatic food web. University of Marine Science and

Technology Khorramshahr (in Persian), 178P. Nabavi, S.M.B., Savary, A. Sakhaee, N., 1993.

Benthic survey in the Persian Gulf (Khuzestan

coastal waters). Faculty of Marine Science and

Technology, Shahid Chamran University, 73P.

Nilsaz, M.K., Dehghan-Madiseh, S., Mazreavy, M.,

Esmaily, F. And Sabzalizadeh, S., 2005.

Hydrological and hydrobiological study in the

Persian Gulf (Khuzestan coastal waters). Iran

Fisheries Research Organization.117 P.

Penczak, T. and Kruk, A. 1999. Applicability of the

abundance/biomass comparison method for

detecting human impacts on fish populations in

the Pilica River, Poland. Fish Research. 39: 229–

240

Rakocinski, C.F., Brown, S.S., Gaston, G.R., Heard,

R.W., Walker, W.W. and Summers, J.K., 2000.

Species- abundance- biomass responses by

estuarine macrobenthos to sediment chemical

contamination.Journal of Aquatic Ecosystems

Stress Recovery. 7: 201-214

Rygg, B., 1986. Heavy-metal pollution and log-

normal distribution of individuals among species

in benthic communities. Marine Pollution

Bulletin. 17: 31-36

Sabzalizadeh, S. and KhalfeNilsaz, M., 1999. Final

report of heavy metals pollution in water and

sediment in some creeks of Khuzestan coastal

waters. Iran Fish Reseach (in Persian).42P.

Simboura, N. 2003. Benthix index vs. Biotic Index in

monitoring: an answer to Borja et al., 2003.

Marine Pollution Bulletin. 46: 124-132

Stenton-Dozey, J., Jackson, F. and Busby, A.J.,

1999. Impact of mussel culture on macrobenthic

community structure in Saldanha Bay, South

Africa.Marine Pollution Bulletin. 39: 357–366

Sterreer, W., 1986. Marine fauna and flora of

Bermuda, a systematic guide to the identification

of marine organisms.John Willy and Sons, 742P.

Warwick, R. M., 1986. A new method for detecting

pollution effects on marine macrobenthic

communities. Marine Biology. 92: 557–562

Warwick, R.M. 1993. Environmental impact studies on

marine communities: pragmatically considerations.

Australian Journal of Ecology. 18: 63-80


9

Warwick, R.M. and Clarke, K.R., 1991. A comparison

of some methods for analyzing changes in benthic

community structure. Marine Biological

Association of the United Kingdom. 71: 225–244

Warwick, R.M., Pearson, T.H. and Ruswahyuni.,1987.

Detection of pollution effects on marine

macrobenthos: further evaluation of the species

abundance/biomass method. Marine Biology. 95:

193 -200

Wilson, J.G. and Jeffrey, D.W., 1994. Benthic

biological pollution indices in estuaries. In: K.J.M.

Kramer (ed.), Biomonitoring of coastal waters and

estuaries. CRC Press, Boca Raton, pp. 311-327

Yemane, D., Field, J.G. and Leslie, R.W., 2005.

Exploring the effects of fishing on fish

assemblages using Abundance Biomass

Comparison (ABC) curves. ICES Journal of

Marine Science. 62: 374-379



Journal of the Persian Gulf

(Marine Science)/Vol. 3/No. 7/March 2012/9/1-10

Application of Abundance Biomass Curve in Ecological...

Documents

Transcript of Application of Abundance Biomass Curve in Ecological...