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The pink shrimp Farfantepenaeus duorarum,its symbionts and helminths as

bioindicators of chemical pollution inCampeche Sound, Mexico

V.M. Vidal-Martınez1*, M.L. Aguirre-Macedo1,R. Del Rio-Rodrıguez2, G. Gold-Bouchot1, J. Rendon-von Osten2

and G.A. Miranda-Rosas3

1Laboratories of Parasitology and Marine Geochemistry, Centro deInvestigacion y de Estudios Avanzados del IPN (CINVESTAV-IPN)Unidad Merida, Carretera Antigua a Progreso Km. 6, 97310 Merida,

Yucatan, Mexico: 2Centro de Ecologıa, Pesquerıas y Oceanografıa del Golfode Mexico, Universidad Autonoma de Campeche, Av. Agustın Melgar

S/N Campeche, Campeche, Mexico: 3Gerencia de Seguridad Industrial yProteccion Ambiental- RMNE PEMEX Exploracion y Produccion, Calle 31

S/N, Edificio Complementario 1, Col. Sta. Isabel, Cd. del Carmen,Campeche, Mexico

Abstract

The pink shrimp Farfantepenaeus duorarum may acquire pollutants,helminths and symbionts from their environment. Statistical associationswere studied between the symbionts and helminths of F. duorarum andpollutants in sediments, water and shrimps in Campeche Sound, Mexico. Thestudy area spatially overlapped between offshore oil platforms and naturalshrimp mating grounds. Spatial autocorrelation of data was controlled withspatial analysis using distance indices (SADIE) which identifies parasite orpollutant patches (high levels) and gaps (low levels), expressing them asclustering indices compared at each point to produce a measure of spatialassociation. Symbionts included the peritrich ciliates Epistylis sp. andZoothamnium penaei and all symbionts were pooled. Helminths includedHysterothylacium sp., Opecoeloides fimbriatus, Prochristianella penaei and anunidentified cestode. Thirty-five pollutants were identified, includingpolycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs),pesticides and heavy metals. The PAHs (2–3 ring) in water, unresolvedcomplex mixture (UCM), Ni and V in sediments, and Zn, Cr and heptachlorin shrimps were significantly clustered. The remaining pollutants wererandomly distributed in the study area. Juvenile shrimps acquired pesticides,PAHs (2–3 rings) and Zn, while adults acquired PAHs (4–5 rings), Cu and V.Results suggest natural PAH spillovers, and continental runoff ofdichlorodiphenyltrichloroethane (DDT), PCBs and PAHs (2–3 ring). Therewere no significant associations between pollutants and helminths. However,there were significant negative associations of pesticides, UCM and PCBs

*Author for correspondence:Fax: Tel: þ52 (999) 9812334E-mail: [email protected]

Journal of Helminthology (2006) 80, 159–174 DOI: 10.1079/JOH2006358

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with symbiont numbers after controlling shrimp size and spatial auto-correlation. Shrimps and their symbionts appear to be promisingbioindicators of organic chemical pollution in Campeche Sound.

Introduction

It is a matter of current debate whether parasites(metazoans and protozoans) are effective indicators ofanthropogenic environmental impact in aquaticecosystems (Kennedy, 1997; Lafferty, 1997; Yeomanset al., 1997; Marcogliese & Cone, 2001; Vidal-Martinezet al., 2003; Khan, 2004; Sures, 2004a). Theoreticalthinking on this question is based on field evidencelacking experimental support (Vidal-Martinez et al.,2003; Khan, 2004; but see Khan & Payne, 2004), orlaboratory evidence with no supporting field data(Siddall & des Clers, 1995; Marcogliese et al., 1998; Mor-ley et al., 2001), and data on metazoan parasitesas heavy metal sinks (Zimmermann et al., 1999,2005; Qian & Pin, 2000; Sures, 2003, 2004a,b; Sureset al., 2005).

The debate has centered on whether parasites of fish areat least as useful for environmental monitoring as free-living organisms or other kinds of biochemical bioindi-cators (Kennedy, 1997; Schmidt et al., 2003). Recentreports, however, support the view that aquatic hostssuch as fish, crabs and shrimps, as well as their symbiontsand metazoan parasites, are good indicators of environ-mental impact (Schuwerack et al., 2001a,b; Bergey et al.,2002; Schuwerack & Lewis, 2003a,b; Lewis et al., 2003 andreferences therein; Schmidt et al., 2003; Williams &MacKenzie, 2003; Sures, 2004a).

One as yet unresolved problem with using parasitesas pollution bioindicators is the high temporal andspatial variability of parasite communities in aquaticorganisms (Kennedy, 1997). This author pointed outthat even within a single locality a parasite species canappear and disappear over time without manifesting anapparent trend, or a species can be present in onelocality but absent in a neighbouring one, i.e. a lack oftemporal or spatial repeatability. This caveat is linkedto the influence of geographical distance on therepeatability of parasite community compositionbetween different localities (see Vidal-Martınez &Poulin, 2003). Recent research has addressed theimportance of geographical distance as a factoraffecting structure and similarity (and thus repeat-ability) in the parasite communities of freshwater andmarine hosts (Poulin, 1997, 2003; Poulin & Morand,1999; Karvonen & Valtonen, 2004). Theory suggests thatrepeatability increases as geographical distance betweensampling points decreases. However, it also means thatsamples collected from one place are not necessarilyindependent from samples collected in neighbouringlocalities, i.e. they are spatially autocorrelated. With oneexception (Bengtsson & Ebert, 1998), the possibleinfluence of autocorrelation in aquatic parasitologicaldata has not been addressed. This is a vital aspectfor mobile coastal or marine species, like fish orshrimps, since they naturally migrate within their homeranges.

During research on shrimp (a mobile species) healthstatus for the Mexican national petroleum companyPetroleos Mexicanos (PEMEX) in Campeche Sound (Gulfof Mexico), we collected data on pollutants and parasitesin the pink shrimp Farfantepenaeus duorarum, as well as onpollutants in water and sediments in areas with andwithout offshore oil platforms. Data included symbiontand metazoan parasite species and individuals, andpollutants (heavy metals, pesticides, polycyclic aromatichydrocarbons (PAHs) and polychlorinated biphenyls(PCBs)). However, the sampling design proposed byPEMEX imposed a high degree of contiguity betweensampling points, resulting in autocorrelation in the pinkshrimp data (Castrejon et al., 2004). To deal with the data’sspatial structure and control for autocorrelation we usedspatial analysis using distance indices (SADIE) (Perryet al., 1999). Originally used in insect ecology, thistechnique identifies areas of significant clustering andgroups them into patches (in this case, areas of highparasite density or high pollutant concentrations), or gaps(areas of low density or low concentration) by producingan index that quantifies the degree to which each localitycontributes to clustering. Furthermore, SADIE determinesthe extent to which cluster indices ‘agree’ at each point,thus providing a measure of spatial association.

Given that agriculture and offshore oil extraction aresignificant economic activities in the state of Campeche,Mexico, high pesticide concentrations in sediments andwaters near the coast, and high PAH concentrations insediments and waters near offshore platform zones can beexpected. Consequently, the study objectives were: (i) todetermine if the pink shrimp acquires organic pollutants(i.e. PAHs, PCBs, heavy metals and pesticides); and (ii) todetermine if the number of symbionts and metazoanparasites in shrimp have significant statistical associ-ations with pollutant concentrations in sediments, waterand shrimp pools.

Materials and methods

Study area and sampling techniques

The study area encompassed 20 points in CampecheSound, Gulf of Mexico (fig. 1). Shrimps were collectedbetween 17 and 22 October 2002 using 0.5–1 h trawls atdepths of 12.2 to 50 m undertaken from a ship (Cetmar II)equipped with two shrimp trawl nets. After each trawl(indicated by letters in fig. 1) surface sediments werecollected with a 1 m2 van Veen grab and frozen, whilewater samples were taken at 5 m depth intervals using1-gallon amber glass bottles closed under water to avoidcontamination with surface mixtures. Water sampleswere extracted with hexane, and constantly agitated for5 min. Processed sediment and water samples weretransported to CINVESTAV-Merida for further analysis.All trawls are shown in fig. 1, but only those (15)containing pink shrimps are shown in table 1.

160 V.M. Vidal-Martınez et al.





A total of 248 pink shrimps were obtained from alltrawls. These were identified on board and dissectedsagittally. The right half of each specimen was stored fordetermination of pollutant concentrations. The left halfwas fixed in Davidson’s AFA solution for four days thentransferred to 70% ethanol for histological examination.These samples were then embedded in paraffin, and threesagittal sections, 5mm thick, cut from each specimen.Tissue slides were stained with hematoxylin and eosin,and fixed to glass slides. The left sagittal slides ofindividual shrimps were examined to determine thenumber of individuals for each symbiont or metazoanparasite species, following the procedures of Khan (2004)for fish.

Chemical analysis

Hydrocarbon, pesticide and PCB levels were deter-mined according to Sericano et al. (1990) and Wade et al.(1993). Shrimp samples were extracted in a Soxhletapparatus for 8 h with hexane, and for another 8 h withdichloromethane. These extracts were concentrated in aKuderna-Danish system, purified and divided into twofractions using column chromatography with alumina-silica gel. Lipids were removed from the second fractionin an HPLC system with a size-exclusion column, andorganic compounds were quantified using gas chroma-tography (Hewlett-Packard 5890 Series II) with flameionization detection for hydrocarbons, and electron

capture detection for organochlorines. Internal standards(PCBs 103 and 198 for organochlorines and n-C23 anddihydroanthracene for hydrocarbons) were added forquality control. Concentrations of these pollutants insediments and water were measured using the sameprocess. Metals in water were extracted using Chelex 100resin, and sediments were extracted with 0.1 M HCl(simultaneously extracted metals fraction). Organismswere digested with nitric acid and hydrogen peroxide.Final measurements were taken in a Perkin Elmerinductively coupled plasma (ICP) spectrometer.

Statistical analysis

Rather than describing parasite and symbiont infectionparameters, our interest was in determining any possibleassociations between the number of symbionts andparasites identified in the shrimp slides with sedimentand water pollutant concentrations. Consequently, theterms prevalence and mean abundance as suggested byBush et al. (1997) were not used. Instead, the percentage ofinfected shrimp (number of shrimps infected withsymbionts or a metazoan parasite species/number ofshrimps examined per trawl) and the mean number ofindividuals (number of individual symbionts or individ-uals of a metazoan parasite species/ number of shrimpsexamined per trawl) were calculated. An ‘all parasites’category was created to include all symbionts andparasites in the shrimps per trawl. Because symbionts

93˚W

19˚N

N

United States

Gulf ofMexico

Pacific Ocean

92˚W 91˚W

93˚W 92˚W 91˚W

19˚N

80M100M

90M 70M

60M50M

40M

30M

20MPlatformsZone

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Lagoon

Campeche

10M

K

I J

C

FE

B

A

H

G D

L

N

O

M

SR

P

T

Q

Fig. 1. Sampling points in Campeche Sound, Gulf of Mexico, where sediment and water samples were taken. Shrimps were caught intrawls between each sampling point. Points A–J were near offshore platforms, and points K–T near the coast.

Shrimps, their symbionts and helminths and pollution 161





Tab

le1.

Hel

min

ths

and

sym

bio

nts

of

the

pin

ksh

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pFarfantepenaeusduorarum

(n¼

248)

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pec

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een

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er,

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wl

Init

ial

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de

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ud

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um

ber

of

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ng

th(0^

SD

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ln

um

ber

of

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asit

es

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ths

and

sym

bio

nts

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yst

Op

ecP

roc

Sy

mb

*

A19

831

009

819

831

013

713

11.3

8^

3.19

18–

––

126

918

460

228

918

480

140

0.12

^0.

340.

44^

1.71

B19

826

003

5198

260

743

1712

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3.28

6–

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1718

918

530

981

918

510

570

0.83

^2.

180.

82^

2.13

C19

820

087

3198

210

041

511

.84^

3.8

60–

––

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918

550

673

918

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635

0.6^

0.55

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825

046

0198

260

689

3113

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2.78

173

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136

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487

918

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242

0.74

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1.31

1.70

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47E

198

320

418

198

300

139

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940.

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476

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144

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36^

1.14

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198

250

476

198

230

629

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100

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800.

08^

0.39

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819

032

2198

180

437

2414

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3.37

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2012

928

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837

928

150

385

0.08

^0.

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6^

1.44

0.68

^2.

81J

198

170

378

198

160

668

10.5

8^

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918

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589

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330.

5^

1.33

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805

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8198

040

235

1010

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1.91

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3.1^

4.95

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1.58

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804

029

6198

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296

2710

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1.18

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918

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839

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03^

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802

006

2198

000

604

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19–

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510

660

918

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320

0.19

^0.

750.

19^

0.75

N19

800

095

6198

010

673

139.

59^

1.39

23–

0.08

^0.

288

238

918

580

695

928

010

677

0.08

^0.

280.

61^

1.32

0.08

^0.

28R

188

510

500

188

520

262

58.

8^

0.54

1–

––

100

4091

844

075

3918

470

753

1.2^

0.45

0.8^

1.09

S18

852

051

3188

520

958

99.

87^

1.4

11–

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1111

918

480

439

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544

0.22

^0.

672.

44^

7.33

Tra

wls

wit

hn

op

ink

shri

mp

sar

en

ot

sho

wn

.En

trie

sfo

rp

aras

ites

are

the

per

cen

tag

eo

fin

fect

edsh

rim

ps

(up

per

val

ue)

and

mea

nn

um

ber

of

ind

ivid

ual

s(l

ow

erv

alu

es).

Ces

t,u

nid

enti

fied

inte

stin

alce

sto

de;

Hy

st,H

ysterothylacium

sp.;

Op

ec,O

pecoeloides

fimbriatus;

Pro

c,Prochristianellapenaei;

Sy

mb

,th

esu

mo

fal

lsy

mb

ion

tsfo

un

d;

ind

epen

den

to

fsp

ecie

s.T

he

mo

stp

rob

able

spec

ies

inth

isg

rou

pw

ereZootham

nium

penaei

andEpistylis

sp.,

bas

edo

nV

idal

-Mar

tın

ezet

al.

(200

2).






could not be identified to species level, they were groupedin a single ‘symbionts’ category.

Possible associations between the percentage and meannumber of individuals of symbionts or metazoan parasitespecies and pollutant concentrations in shrimp tissuefrom the same trawl were determined. However, due totechnical restrictions on the amount of shrimp tissueneeded for pollutant analysis, the sagittal right halves ofevery 3–5 shrimps from each trawl were pooled. For eachpool associations between the percentage, total and meannumber of symbionts and parasites identified in the slidesof the left half of the shrimps were determined, and thepollutant concentrations recorded in the right half of thesame shrimps. A total of 39 pools were obtained from alltrawls. Associations between the percentage and meannumber of symbionts and parasites in the shrimps, andthe sediment and water pollutant concentrations fromeach of the 15 trawls in which shrimps were caught werealso studied. Data on the potential associations betweenpollutants and shrimp histology produced from thesesamples are to be published elsewhere.

The sampling design originally proposed by PEMEXproduced autocorrelation in the data, and a clearbathymetric pattern in pink shrimp size (fig. 1) (Castrejonet al., 2004), with shrimp size increasing with depth. Thetechnique of Moles & Wade (2001) was used tocompensate for the effect of shrimp size and then thenumber of parasites in each shrimp was divided by thatshrimp individual’s length.

SADIE (Perry et al., 1999) was used to determine ifpollutants and parasites were randomly distributed orsignificantly clustered in the study area. SADIE detectsspatial patterns in the form of patch clusters, rather thancharacteristics of local population densities or concen-trations. In this sense, its purpose differs from geostatis-tics, which estimates local density (Perry & Dixon, 2002).Mathematical details of SADIE are presented at http://www.rothamsted.bbsrc.ac.uk/pie/sadie. Briefly, spatialpatterning in SADIE is measured at each sampled unit,using a clustering index. This algorithm is based on themovement of individuals to a new location (similar totransmission). In any case, an individual’s movementsbetween sampling units are expressed as distances. Arandomization procedure randomly and independentlyreassigns each of the total individuals in the sample to oneof the n sample units. The randomization process is thenrepeated 5000 times to build a frequency distribution ofthese values that relates to an initially random spatialdistribution of individuals in the sample. The computedvalue of the sample is compared with this frequencydistribution, and the proportion (Pr) of the values that areequal to, greater or smaller than the observed value isrecorded (Perry, 1995). Therefore, the null hypothesis thatthe observed sample originated in a spatially randompopulation is rejected at a 0.05 level for a two-tailed test ifthe indices values are equal to, greater or smaller than theobserved value.

The Ir index, based on the average distance ofrandomized rearrangements, is Ir ¼ D=Er where D is thedistance of the actual sample, and Er is the distance ofrandom rearrangements. A unity value represents aspatially random sample. Each unit with a count greateror smaller than the overall mean is assigned to a patch

(positive) or gap (negative) cluster index. Clusterindices for each sample were contoured in maps usinginterpolation procedures (e.g. kriging). We used Surfer ver.7 software to produce maps with three region types: valuesnear zero were random; areas with indices $1 were patchclusters; and areas with an indices #1 were gap clusters.

To determine spatial association using SADIE, it wasassumed that parasite and pollutant cluster indices ateach sample unit are measures of their local spatialpattern (patches or gaps) at that point. The extent towhich the parasite and pollutant cluster indices inshrimps, sediments or water ‘agree’ or ‘disagree’ at eachpoint provide a measure of local spatial association ordissociation. For the two data sets and clustering indicesof set one zk1 (combining patch and gap data) with meanq1, and those of set two zk2, with mean q2, the measure oflocal spatial association for unit k is:

Xk ¼ nðzk1 2 q1Þðzk2 2 q2Þ=½Skðzk1 2 q1Þ2Skðzk2 2 q2Þ

2�1=2

The overall spatial association is the mean of these localvalues, X ¼ S iXi, where X is the correlation coefficientbetween the clustering indices of each set. Assessment ofthe significance of X was tested against Xrand with arandomization test in which the clustering indices of eachset are randomly reassigned to each set of units:K ¼ 1; 2; 3. . .:n. Critical values for the test statistic wereestimated using the Xrand randomization distributionquantiles, derived from the null hypothesis of noassociation. Local spatial association values were alsomapped and contoured.

When a set of cluster indices is spatially autocorrelated,then the amount of information in that set is reduced inproportion to the degree of autocorrelation. Hence, whentesting a statistic that estimates the association betweentwo data sets, such as X, the test and critical values mustbe adjusted to allow for any reduction in effective samplesize caused by the autocorrelation. SADIE employs theadjustment proposed by Dutilleul (1993). This functionsby computing the effective size of the combined sets,allowing the test’s degrees of freedom to be adjusted.Since SADIE uses randomizations to build frequencydistributions, it is essentially a distribution-free pro-cedure. The significance of all statistical analyses wasestablished at P ¼ 0.05, unless otherwise stated.

Results

From 15 trawls in which pink shrimps were recovered(table 1), a total of four metazoan parasite species werefound, namely an unidentified intestinal cestode, thenematode Hysterothylacium sp. in muscle, metacercariaeof Opeocoeloides fimbriatus in muscle, and the cestodeProchristianella penaei in hepatopancreas. All recordedsymbionts were found in the gills of the pink shrimp. Useof histology, rather than full parasitological examinationof fresh specimens, precluded the identification ofsymbionts to species or detection of low-prevalencespecies like gregarines. However, it is highly probablethat symbionts in the histological slides were Zootham-nium penaei and Epistylis sp. as these are the most frequentand abundant symbiont species on the Yucatan Peninsula






(Vidal-Martinez et al., 2002), the Texas and Georgia coastsand in the Mississippi Sound (Overstreet, 1973).All metazoan parasites were at the larval stage, and allsymbionts were adults. Prochristianella penaei was themost frequent and abundant parasite, followed by thesymbionts (table 1).

Detected sediment and water pollutant concentrationsfrom the 15 trawls showed that significantly clusteredpollutants were the 2–3 ring PAHs in water, theunresolved complex mixture (UCM), and the heavymetals Ni (nickel) and V (vanadium) in sediments(table 2). The remaining pollutants were randomlydistributed in the study area.

Pollutant concentrations from 39 pink shrimp poolsfrom all trawls which had both pollutants and parasitesshows the presence of four PAHs metabolites, five heavymetals, 11 pesticides, and seven PCBs (table 3). Mostpollutants in table 3 were not significantly clustered in thestudy area, for example, all the PAHs. Also, apart from Cu(copper) and Fe (iron), all heavy metals were randomlydistributed. Of the pesticides, only heptachlor wassignificantly clustered. None of the PCBs was signifi-cantly clustered in the SADIE randomization process.Also, none of the parasites, symbionts, or the sum of bothwas significantly clustered in the shrimp pools. Finally,the sum of P. penaei, the symbionts plus all less-abundantparasites did not cluster significantly.

Figures 2 and 3 show the concentrations of selectedpollutants from tables 2 and 3 that were significantlyclustered in the study area. Each map shows the clusterindices for each pollutant in individual shrimps, sedi-ments and water. In fig. 2A heptachlor in shrimp hadsignificantly higher concentrations in the coastal zone thanin the platforms zone, while the clustering values of Cu,UCM (fig. 2B and C), Ni and V in sediments (fig. 3A and B)were higher in the platforms area. Finally, the overalldistribution for 2–3 ring PAH concentrations in water,even when the local cluster values were not significantlydifferent from a random distribution, was significantlyclustered in the coastal zone in comparison with theplatforms zone (table 2; fig. 3C).

Shrimp size had a substantial influence on the data.Shrimps from trawls around offshore platforms werelarger than those from near the coast (one-way ANOVA;F15,510 ¼ 17.68; P , 0.0001). There were also significantcorrelations between mean total length and depth(Kendall’s rank correlation Tau ¼ 0.70; n ¼ 15; P , 0.01),and between individual shrimp size and total number ofparasites (Kendall’s Tau ¼ 0.19; n ¼ 37; P ¼ 0.04). Therewas a negative but statistically non-significant correlationbetween the number ofP. penaei and shrimp size (Kendall’sTau ¼ 20.11; n ¼ 37; P . 0.10). This is why P. penaei, andother parasite species in table 1 that were not abundantenough for correlation analysis, were not included infurther analyses. There were also no correlations betweenthe percentage of shrimps infected with symbionts or ametazoan parasite species and pollutants from water,sediments or the shrimp hosts. Consequently, they werealso not considered for further analyses. Symbiontsnumerically dominated in the histological slides through-out the study area. There was a significant positivecorrelation between symbiont clustering values and thetotal number of parasites (X ¼ 0.87;n ¼ 37;P ¼ 0.001), and

thus all the following figures showed associations betweensymbionts and pollutants.

Figures 4A to C and 5A to C show local values of thecorrelation coefficients (Xk) of the cluster indices ofsymbionts and pollutants from table 2, after shrimp sizeand autocorrelation were controlled for in the trawl data.In fig. 4A and B, negative correlation values mean that thehigher the pesticide concentration, the lower the numberof symbionts. Furthermore, there were overall significantnegative associations between the clustering indices ofsymbionts and the pesticides alpha-HCH (X ¼ 20.69;n ¼ 15; P ¼ 0.99) and HCH (X ¼ 20.52; n ¼ 15; P ¼ 0.98).In contrast, there was a significant positive correlationbetween symbionts and heptachlor (X ¼ 0.53; n ¼ 15;P ¼ 0.03), especially near the coast (fig. 4C). In fig. 5A andB, the higher the clustering indices values of UCM insediments from the platforms zone (X ¼ 20.54; n ¼ 15;P ¼ 0.98) and water (X ¼ 20.59; n ¼ 15; P ¼ 0.99), thelower the symbiont values become. Finally, fig. 5C showshigh Ni clustering indices where high symbiont cluster-ing indices (X ¼ 0.51; n ¼ 15; P ¼ 0.03) were recorded,especially near the coast.

Figures 6A to C and 7A to C show the correlationcoefficients (X) of the symbiont clustering indices withselected pollutants from table 3 after controlling forshrimp size and autocorrelation for the 39 shrimp pools.Figure 6A shows a positive significant correlationbetween symbionts and phenanthrene (X ¼ 0.38; n ¼ 39;P ¼ 0.008), with higher correlations in the coastal area. Incontrast, fig. 6B has a significant negative correlationbetween symbionts and alpha-HCH (X ¼ 20.39; n ¼ 39;P ¼ 0.9918) with positive correlations in the platformsarea (top of the figure). In fig. 6C, high local and overallnegative correlations between symbionts and heptachlor(X ¼ 20.76; n ¼ 39; P ¼ 0.9999) were found in the coastalarea. Figure 7A shows significant negative local corre-lation values for both symbionts and PCB1016, which inturn produced a positive overall correlation (X ¼ 0.64;n ¼ 39; P ¼ 0.0001). In contrast, there were significantnegative local and overall correlation values betweensymbionts and PCB1242 (X ¼ 20.77; n ¼ 39; P ¼ 0.9999)(fig. 7B). Finally, significant positive local and overallcorrelation values between symbionts and zinc (X ¼ 0.32;n ¼ 39; P ¼ 0.0244) were found near the coastal area(fig. 7C).

Discussion

The results show that the pink shrimp acquiredpollutants from the environment, and that there weresignificant statistical associations between chemicalpollutants and symbionts, once the effect of shrimplength and autocorrelation were controlled. However,there were unexpected results such as the randomdistribution of some pollutants. No correlations wereobserved between metazoan parasites or their percen-tages of infection and pollutants from water, sedimentsor the shrimp hosts. The results suggest thathistological slides were useful in detecting statisticalassociations between symbionts and pollutants and thatthis is a useful technique when dealing with mobilehosts as bioindicators of environmental impact.






Tab

le2.

Po

llu

tan

tsd

etec

ted

inse

dim

ents

and

wat

erfo

rea

cho

f15

traw

lsin

Cam

pec

he

So

un

d,

Gu

lfo

fM

exic

o.

Po

lycy

clic

aro

mat

ich

yd

roca

rbo

ns

Hea

vy

met

als

Pes

tici

des

Po

lych

lori

nat

edb

iph

eny

ls

Ali

ph

aP

AH

2–

3P

AH

4–

5U

CM

Ba

Fe

Ni

VP

bZ

nH

CH

sM

eto

xD

DT

sP

CB

s

I rS

edim

1.12

1.29

0.99

1.95

1.13

1.12

1.58

2.07

–1.

04–

–0.

990.

96P

val

ue

0.27

0.09

0.48

0.00

080.

250.

30.

030.

001

–0.

42–

–0.

480.

46I r

Wat

er–

1.38

–0.

69–

0.81

0.56

11.

171.

290.

930.

86–

0.51

Pv

alu

e–

0.03

–0.

94–

0.74

0.97

0.41

0.25

0.14

0.61

0.68

–0.

98

Tra

wl

AS

0.95

0.11

0.18

26.9

02.

522.

5412

.72

45.0

74N

DN

DN

DN

D0.

471.

80W

ND

ND

ND

4.90

ND

28.7

43.

984.

730.

176.

40–

0.28

ND

0.9

BS

0.83

ND

5.03

34.7

2N

D8.

8015

.15

49.4

2N

DN

DN

DN

DN

D63

.06

WN

DN

DN

D2.

33N

D91

.10

3.78

57.0

90.

236.

390.

75N

DN

D0.

9C

S0.

69N

D6.

2038

.21

2.57

ND

13.2

247

.38

ND

ND

ND

ND

ND

46.5

6W

ND

ND

ND

5.40

ND

110.

344.

1749

.75

0.60

15.9

30.

750.

50N

D0.

9D

S0.

58N

D0.

1023

.65

3.23

51.7

014

.32

57.1

0N

DN

DN

DN

DN

D1.

8W

ND

0.06

ND

6.82

ND

72.7

43.

8249

.46

0.22

15.5

89.

00N

DN

D1.

25E

S0.

50N

D0.

6722

.36

ND

6.44

13.3

455

.77

ND

ND

ND

ND

ND

35.9

2W

ND

0.20

ND

3.57

ND

49.2

34.

2950

.84

0.24

8.55

ND

ND

ND

0.9

FS

1.21

0.03

0.40

32.7

43.

0215

1.12

16.5

243

.18

ND

ND

ND

ND

ND

ND

WN

DN

DN

D2.

64N

D58

.15

4.17

38.0

90.

1413

.62

ND

0.46

ND

0.9

GS

0.41

0.01

0.04

20.9

42.

9219

8.93

15.4

756

.23

ND

ND

ND

ND

ND

1.8

WN

DN

DN

D48

.76

ND

34.7

73.

9838

.14

0.13

2.87

ND

0.32

ND

0.9

HS

1.38

0.02

0.44

81.3

63.

5073

0.10

19.3

955

.44

ND

3.36

ND

ND

ND

0.90

WN

DN

DN

D36

.88

ND

39.0

54.

0554

.07

0.14

6.90

ND

ND

ND

0.9

JS

0.90

0.01

0.67

10.0

5N

DN

D9.

9743

.23

ND

ND

ND

ND

ND

8.10

WN

DN

DN

D17

7.29

ND

27.7

73.

7739

.97

0.53

6.34

ND

0.37

ND

ND

KS

0.52

ND

0.89

0.03

2.70

ND

6.91

35.5

2N

DN

DN

DN

DN

D26

.65

WN

DN

DN

D22

.38

ND

20.9

64.

5049

.89

0.12

7.47

ND

0.30

ND

0.9

LS

0.35

ND

20.

053.

993.

023.

521.

5834

.03

ND

ND

ND

ND

ND

32.3

4W

ND

ND

ND

24.2

1N

D78

.76

4.20

48.0

70.

188.

78N

D0.

28N

D1.

80M

S0.

90N

D0.

98N

D3.

1569

.98

6.54

32.7

2N

DN

DN

DN

DN

DN

DW

ND

ND

ND

23.5

7N

D55

.56

3.84

48.8

90.

117.

81N

D0.

36N

DN

DN

S0.

55N

D0.

93N

D2.

6411

.32

8.54

37.0

3N

DN

DN

DN

DN

D2.

00W

ND

ND

ND

18.6

8N

D32

.67

3.69

54.5

80.

163.

86N

D0.

25N

D0.

9R

S0.

26N

DN

DN

D2.

598.

078.

5736

.91

ND

ND

ND

ND

0.43

3.81

WN

D3.

94N

D24

.88

ND

48.5

93.

9733

.65

0.12

3.08

ND

ND

ND

0.9

SS

0.96

ND

0.36

ND

3.18

584.

2017

.98

41.6

5N

D2.

40N

DN

DN

D2.

22W

ND

0.13

ND

23.0

9N

D65

.03

4.17

40.0

30.

105.

49N

DN

DN

D0.

9

Up

per

val

ues

are

sed

imen

t(S

)co

nce

ntr

atio

ns

(mg

g2

1fo

rp

oly

cycl

icar

om

atic

hy

dro

carb

on

s,h

eav

ym

etal

san

dp

esti

cid

es,p

gg2

1fo

rp

oly

chlo

rin

ated

bip

hen

yls

)an

dlo

wer

val

ues

are

wat

er(w

)co

nce

ntr

atio

ns

(mg

l21).

I rS

edim

,se

dim

ents

clu

ster

ing

ind

exv

alu

e;I r

Wat

er,

wat

ercl

ust

erin

gin

dex

val

ue;P

val

ue,

sig

nifi

can

cele

vel

;N

D,

no

td

etec

ted

.






Tab

le3.

Po

llu

tan

ts,

hel

min

ths

and

sym

bio

nts

of

39p

ink

shri

mpFarfantepenaeusduorarum

po

ols

fro

mC

amp

ech

eS

ou

nd

,G

ulf

of

Mex

ico

.

Po

lycy

clic

aro

mat

ich

yd

roca

rbo

ns( m

gg2

1)

Hea

vy

met

als

(mg

g2

1)

Pes

tici

des

(mg

g2

1)

Po

lych

lori

nat

edb

iph

eny

ls(m

gg2

1)

Hel

min

ths

and

sym

bio

nts

(nu

mb

ero

fin

div

idu

als)

BA

Pir

Pir

Nap

hP

hen

aC

uF

eN

iV

Zn

Hep

taP

esti

PC

Bs

Ap

roA

sym

bA

ll

I r0.

840.

760.

800.

141.

761.

371.

231.

220.

581.

450.

890.

841.

001.

201.

11P

val

ue

0.69

0.84

0.78

0.28

0.01

0.04

0.18

0.18

0.98

0.02

0.64

0.67

0.47

0.25

0.27

Sh

rim

pA

524

.61

15.4

412

1.25

256.

315

.52

2.24

2.46

33.1

331

.9N

D0.

460.

061

45

A10

0.57

0.21

11.3

15.

2913

.93

5.87

13.4

334

33.8

7N

D2.

90.

010

11

A11

18.8

89.

1919

.89

274.

111

.77

39.0

523

.19

39.4

32.0

7N

DN

D0.

131

01

B17

11.5

53.

235

.85

181.

512

.43

22.2

115

.55

34.7

338

.11

ND

ND

0.01

12

3B

183.

933.

1375

.61

253

13.8

823

.91

12.7

132

.94

29.9

ND

ND

ND

08

9B

190.

570.

259.

125.

318.

7725

.19

36.3

678

.03

35.6

2N

D0.

060.

011

45

B20

2.75

0.41

6.68

166.

110

.417

.65.

0370

.52

28.8

5N

DN

D0.

020

00

C38

41.3

30.

8711

1.88

546

15.2

422

.56

4.74

79.2

934

.75

ND

ND

ND

00

0D

403.

3437

.06

7.35

133.

217

.02

13.2

95.

2980

.11

29.7

4N

D0.

950.

120

1313

D44

5.14

0.61

4.85

143.

819

.31

18.1

76.

7973

.51

30.6

6N

D0.

04N

D0

00

D45

1.94

0.45

8.43

123.

616

11.2

713

.02

32.8

836

.55

ND

ND

0.01

00

0D

4739

.18

31.4

259.

4641

6.3

24.5

221

.54

4.9

76.6

35.9

4N

DN

DN

D1

4041

D49

14.9

47.

2334

.618

0.2

20.8

435

.12

10.8

574

.97

33.1

8N

D0.

10.

010

00

D76

110.

2315

.395

3.41

602.

314

.13

74.9

133

.05

47.9

134

.2N

D0.

070.

010

00

D84

12.8

612

.37

133.

920

9.5

10.7

710

9.5

29.5

17.8

832

.42

ND

1.24

ND

116

17D

8912

.87

7.47

164.

522

6.4

16.0

349

2.4

149

74.7

339

.39

ND

ND

ND

14

5D

9043

.86

33.8

139

6.06

377.

713

.09

61.6

413

.31

33.3

130

.13

ND

ND

ND

114

15F

9812

.94

4.79

14.9

926

2.1

13.1

77.

519

.67

33.4

329

.7N

D0.

110.

010

77

F10

141

.69

23.6

721

4.2

234.

610

.611

.39

16.5

638

.66

30.4

2N

D4.

060.

010

015

F10

40.

460.

276.

296.

0819

.33

26.1

16.

1977

.28

35.7

6N

D11

.4N

D1

01

G11

74.

51.

4236

.35

271.

723

.116

.16.

1579

.71

34.8

2N

DN

D0.

021

910

G12

26.

632.

8429

.88

197.

716

.521

.69

4.96

75.6

833

.17

ND

8.56

0.03

00

0G

123

9.42

5.69

76.2

820

6.3

47.6

631

.716

.25

214

34.8

8N

DN

D0.

031

01

G12

86.

633.

5548

.31

233.

714

.12

9.42

12.8

33.1

537

.33

ND

0.22

ND

30

3H

157

5.59

4.05

72.1

911

3.2

13.4

621

.31

39.3

370

.63

35.5

ND

1.01

0.04

00

0H

182

18.6

511

.64

143.

3224

6.9

11.7

547

.59

64.8

312

642

.26

ND

0.12

ND

042

42J1

854.

42.

8387

.19

111.

215

.27

49.2

826

.12

152.

930

.12

ND

0.06

ND

20

7K

194

1.85

1.1

49.9

762

.42

13.6

616

.99

10.2

872

.33

26.4

3N

D1.

77N

D0

00

L20

65.

112.

4227

.514

1.9

18.9

339

.39

12.6

36.

0330

.48

ND

1.5

ND

00

0L

230

12.8

94.

9923

.58

193.

636

.49

111.

250

.09

214.

730

.7N

DN

D0.

020

00

M24

30.

970.

4824

.16

18.2

916

.62

32.3

410

.31

71.3

631

.77

ND

0.29

ND

00

0N

244

1.78

1.09

39.1

331

.81

6.12

122

36.5

658

.76

29.7

8N

D0.

45N

D3

16

N15

824

.26

16.6

421

9.78

242.

310

.63

24.5

514

.23

31.5

528

.8N

D30

.20.

180

00

R25

616

.54

7.7

153.

1117

4.7

9.65

10.8

213

.95

33.5

730

.41

ND

2.71

ND

10

1R

255

14.7

58.

4312

2.22

261

11.4

142

.57

24.5

453

.23

34.9

8N

DN

D0.

121

23

R25

716

.93

12.2

717

3.67

417.

58.

2525

.627

.91

62.3

132

.42

0.02

ND

ND

12

3R

258

104.

9363

.47

33.4

121

.81

11.8

118

.31

26.9

55.6

932

.31

ND

ND

ND

10

2R

259

59.4

745

.56

538.

3816

2.6

1426

.67

53.4

866

.14

34.9

0.22

ND

ND

20

2S

261

7.29

4.34

82.1

111

5.3

ND

79.0

746

.58

90.9

31.0

5N

D0.

320.

045

28






Due to the geographical proximity of CampecheSound to the US Gulf Coast and the sharing of shrimpspecies between these areas, the symbionts andmetazoan parasites of Campeche Sound can beexpected to be similar to those reported in US waters(Overstreet, 1973, 1985; Couch, 1978). Indeed,F. duorarum species composition in the study zone(table 1) was similar to that described by Overstreet(1973) and Vidal-Martınez et al. (2002).

We are aware of the limitations of histological slidesfor detecting total number of parasites and symbiontsin an individual host, and for this reason traditionalinfection descriptors such as prevalence or meanabundance were not used. Use of histology wasjustified because we were interested in describingpossible associations between the parasites/symbiontsidentified in the slides and pollutants from the sameindividual host rather than describing infectionparameters of each parasite species. Though thismethod can produce an underestimate of the numberof symbionts and metazoan parasites, it is the onlyway to guarantee detection of both parasites andpollutants from the same sample or pool. Given thepositive results, histological slides appear to be usefulin determining associations between symbionts andorganic chemical pollutants in mobile hosts like theshrimp. This histological approach has also beensuccessfully applied in determining the possibleassociation of environmental impact on fish parasites(Overstreet, 1997; Marcogliese & Cone, 2001; Khan,2004).

Sediment, water and shrimp pollutant concentrations(tables 2 and 3) suggest that shrimps were exposed toand acquired different pollutants depending on theenvironment in which they lived. When pink shrimpjuveniles inhabit the Terminos Lagoon, they acquirepesticides, 2–3 ring PAHs (from petroleum) andprobably heavy metals (like Zn). En route to, andonce in their mating grounds, the shrimps are in thevicinity of offshore platforms (see Garcıa-Cuellar et al.,2004), where they acquire 4–5 ring PAHs or heavymetals such as vanadium or copper.

The results suggest natural PAH spillovers throughoutthe study area (table 2), which is further supported bydata from Garcıa-Cuellar et al. (2004) and Soto et al. (2004)on natural PAH spillovers in Campeche Sound. The UCMin sediments were significantly clustered in the platformzone (table 2; fig. 2C), which is probably associated withoil drilling taking place on the platforms. However, lowconcentrations of UCM were present in both water andsediments throughout the study area (table 2), probablydue to distribution by ocean currents. Available data areinsufficient to unequivocally determine if these concen-trations are associated with petroleum extraction ornatural seeps.

Overall the levels of PAHs, PCBs, heavy metals andpesticides recorded here were within permitted levels,with some exceptions (UCM; DDTs), and could not beclearly linked to the presence of oil drilling platforms. Thisdoes not mean, however, that they pose no potential risk tohumans and shrimps. The PAH concentrations in water(0.12 to 177.29mg l21) were below the EPA criterion(4,600,000mg l21) (EPA, 1999), but UCM exceeded theI r

¼cl

ust

erin

gin

dex

val

ue;

Pv

alu

e¼

sig

nifi

can

cele

vel

.O

nly

par

asit

esan

dsy

mb

ion

tsin

fect

ing

mo

reth

anfo

ur

ho

sts

wer

ein

clu

ded

,th

atis

,Prochristianella

penaei

(Ap

ro)

and

sym

bio

nts

(Asy

mb

).A

ll¼

sum

of

all

met

azo

anp

aras

ite

spec

ies

ind

ivid

ual

s,in

clu

din

gHysterothylacium

sp.,Opecoeloides

fimbriatus,

and

anu

nid

enti

fied

inte

stin

alce

sto

de.

Cap

ital

lett

ers

inth

efi

rst

colu

mn

are

traw

lsfr

om

wh

ich

shri

mp

po

ols

wer

em

ade;

ND

,n

ot

det

ecte

d.

BA

Pir

,Ben

zo(a

)p

yre

ne;

Pir

,py

ren

e;N

aph

,Nap

hth

alen

e;P

hen

a,P

hen

antr

ene;

Cu

(ran

ge

0.0

–7.

8m

gg2

1;I

r¼

0.96

;Pv

alu

e¼

0.50

);P

esti¼

pes

tici

des

,th

esu

mo

fh

exac

hlo

rocy

clo

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val

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Hep

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].






National Oceanic and Atmospheric Administration(NOAA) limit (70mg g21). However, shrimps from alltrawls possessed PAHs (table 3), though at levels deemednon-toxic for humans (0.11 to 253.97mg g21). Nevertheless,the ubiquitous presence of these compounds deservesattention since many (e.g. benzo (a) pyrene) are knowncarcinogens in humans (ATSDR, 1999). For heavy metals,Cu, Fe, Ni, V and Zn concentrations were all belowinternational regulations for sediments or water (e.g.O’Connor, 1990; ATSDR, 2004), though again they were

present throughout the study area. Pesticide levels werelow in the coastal and platform areas, only heptachlor wassignificantly clustered in the study area and DDT wasclearly present in the shrimp. The occurrence of the lattertwo is cause for some concern as both are known to be toxicto shrimps and humans. The a and d hexachlorocyclohex-anes and heptachlor are considered carcinogenic inhumans, while the g isomer produces liver and kidneytoxicity in humans (http://cfpub.epa.gov/iris). While therecorded concentrations may not exceed limits for humans

19˚31´

19˚26´

19˚20´

19˚15´

Lati

tud

e N

19˚10´

19˚04´

18˚59´

18˚54´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´ 91˚45´

19˚31´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

Longitude W

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´ 91˚45´

19˚31´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´ 91˚45´

E

F

G

H

D

C

J

B

A

–2

–2

–1.5

–1

–0.5

–0.5

–0.5

0

0

KL

M

S

N

R

1

–1

–1.5

EF

G

2

D B

C

K

M

R

L

–1

–1N

S

J

1

1

0

0

2

1

2

A

H

AE

F

2.5D B

1.5

1.5

–1.5

0.5

J

0.5

–0.5

–0.5

C

K

NM

SR

L

G

H

a b c

Fig. 2. Cluster indices of selected pollutants in shrimp pools, sediments and water in the study area. The coastal zone is located on thebottom margin and the platform zone on the top margin in all figures. A. Heptachlor in shrimp; B, copper in shrimp; C, unresolved

complex mixture (UCM) in sediments. The letters in circles refer to the sampling points shown in fig. 1.

Lati

tud

e N

19˚31´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´ 91˚45´

19˚31´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´ 91˚45´

19˚31´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´ 91˚45´

a b c

2

1

1

0

J

K

M

L

N

0

–1

–1

–1

2

G

H

F

D B

C

EA

0

SR

G

H

FE

A

B

C

J

K

NM

L

SR

D

1.5

1.5

0.5

0.5

–0.5

–0.5

1.5

1.5

1.5

Longitude W

2.5

G

F

EA

D

C

J

KL

MN

SR

H

B

–2

–2

–1.8

–1.8

–1.6 –1.6

–1.4

–1.4–1.2

–0.8 –0.6 –0.5–0.4

–1

–1

Fig. 3. Cluster indices of selected pollutants in shrimp pools, sediments and water in the study area. The coastal zone is located on thebottom margin and the platform zone on the top margin in all figures. A, nickel in sediments; B, vanadium in sediments; C, polycyclic

aromatic hydrocarbons (PAHs) in water. The letters in circles refer to the sampling points shown in fig. 1.






(3mg g21 [300 ppb] for heptachlor, ATSDR, 1993; 15–17 mgkg21 body weight for HCH, WHO, 1991), little is knownabout what effect the concentrations found in the shrimpmay have (LD50 for F. duorarum is 0.17mg l21; Schimmelet al., 1977). Most DDT concentrations recorded in theshrimp (1.85–1110.88mg g21) (table 3) exceeded levelsknown to cause adverse responses in benthic organisms(WHO, 1991). Finally, PCB concentrations in the shrimp

were below NOAA limit for benthic organisms(200mg g21) (WHO, 1993) and the limit for humanconsumption (0.2–3 ppm) (ATSDR, 2000), though levelsas low as 0.9–4.0 ppb are known to kill F. aztecus (Nimmoet al., 1975). Even though most compounds here werewithin permitted concentrations, caution must be takenwhen interpreting these data since extensive research isstill needed to definitively determine damaging levels in

19˚26´

19˚20´

19˚15´

Lati

tud

e N

19˚10´

19˚04´

18˚59´

18˚54´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´

19˚31´19˚31´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

Longitude W

91˚45´ 92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´ 91˚45´

19˚31´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´ 91˚45´

a b cE

FA

BDG

CH

J

K

MN

RS

L

0

0

–1

–1.4

–1.6

–2.2

–1

–1

–0.4

–0.4

–0.4

–0.4

–0.4

–1

FE

A AE

F

G

H

KL

MN

1.5

SR

D B

C

J

H

G D B

C

J

KL

MN

SR

–0.2

–0.2

–0.2

–1–0.6

–0.6

–0.6–1

0.6

–0.6–1.8–1.4

–0.5

–0.5 –0.5

–0.61.5

–0.5

–2.5

Fig. 4. Local values of correlation coefficients (Xk) of clustering indices of symbionts with selected pollutants from trawl data, aftercontrolling for shrimp size and autocorrelation. The coastal zone is located on the bottom margin and the platform zone on the top marginin all figures. A, alpha-HCH (X ¼ 20.69; n ¼ 15; P ¼ 0.99); B, HCH (X ¼ 20.52; n ¼ 15; P ¼ 0.98); C, heptachlor (X ¼ 0.53; n ¼ 15;

P ¼ 0.03). The letters in circles refer to the sampling points shown in fig. 1.

19˚26´

19˚20´

19˚15´

Lati

tud

e N

19˚10´

19˚04´

18˚59´

18˚54´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´

19˚31´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

Longitude W

19˚31´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

19˚31´

91˚45´ 92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´ 91˚45´ 92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´ 91˚45´

a b cE

F

G

H

KL

MN

SR

D B

C

J

A

0

0

–0.4

–0.4

–0.5

0.5

–0.4

–0.6

–0.6

–1.8

FE

A

G D B

C

J

H

KL

MN

SR

–1

–1

–1

–1.4

–1.4

–1.8

–1.6

–0.2

F0

00.4

0.4

0.6

0.6

0.6

0.401.2

1.82

EA

D BG

H

C

J

KL

NM

SR

Fig. 5. Local values of correlation coefficients (Xk) of clustering indices of symbionts with selected pollutants from trawl data, aftercontrolling for shrimp size and autocorrelation. The coastal zone is located on the bottom margin and the platform zone on the top marginin all figures. A, unresolved complex mixture (UCM) in sediments (X ¼ 20.54; n ¼ 15; P ¼ 0.98); B, UCM in water (X ¼ 20.59; n ¼ 15;

P ¼ 0.99); C, nickel in water (X ¼ 0.51; n ¼ 15; P ¼ 0.03). The letters in circles refer to the sampling points of fig. 1.






shrimps or humans, and some of them (e.g. PCBs)bioaccumulate (WHO, 1993), meaning exposure to themfor any length of time holds potential risks to humanhealth.

The available data do not permit attribution of thepresence of the studied compounds in shrimps, sedi-ments and water solely to petroleum extraction on theplatforms. Low molecular-weight PAHs probably resultfrom road runoff or oil leaks (WHO, 2003) into coastal

zones, heavy metals and pesticides likely enter the marineenvironment from river runoff, and PCBs come fromelectrical capacitors, transformers, marine paint and rustprotection for marine structures (EPA, 1999). Thoughbanned, DDT is still used in agricultural pest control, andso continues to enter the Gulf of Mexico (Benıtez &Barcenas, 1996).

The influence of total shrimp length as a covariable is tobe expected since as shrimps grow, and ‘sample the

19˚26´

19˚20´

19˚15´

Lati

tud

e N

19˚10´

19˚04´

18˚59´

18˚54´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´

19˚31´

91˚45´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

19˚31´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´ 91˚45´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´

19˚31´

91˚45´

a b c

G

F

EA A A

E

F

G

H

D B

C

J

K

SR

NM

L

EF

G D B

J

K

NM

L

SR

CH

D

J

K

NM

L

SR

B

H

0.1

0.3

0.3

0.5

0.5

0.7

0.30.6

0.1

0

0

0

Longitude W

0

0

0.5

–0.2

–0.6–1.2–1.6

–0.6

–0.4

–0.4

–0.4

Fig. 6. Local values of correlation coefficients (Xk) of the clustering indices of symbionts with selected pollutants from 39 shrimp pools,after controlling for shrimp size and autocorrelation. The coastal zone is located on the bottom margin and the platform zone on the topmargin in all figures. A, Phenanthrene (X ¼ 0.38; n ¼ 39; P ¼ 0.008); B, alpha-HCH (X ¼ 20.39; n ¼ 39; P ¼ 0.9918); C, heptachlor

(X ¼ 20.76; n ¼ 39; P ¼ 0.9999). The letters in circles refer to the sampling points of fig. 1.

19˚26´

19˚20´

19˚15´

Lati

tud

e N

19˚10´

19˚04´

18˚59´

18˚54´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´

19˚31´

91˚45´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

Longitude W

19˚31´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´ 91˚45´

19˚26´

19˚20´

19˚15´

19˚10´

19˚04´

18˚59´

18˚54´

92˚14´ 92˚08´ 92˚02´ 91˚57´ 91˚51´

19˚31´

91˚45´

a b c

F

EA

G

H

D B

C

J

K

M

L

N

SR

–0.4 –0.4

–0.4 –0.4

–0.8

–0.8

–1.2

FE

A AE

F

G

H

KL

NM

SR

D B

C

J

D

C

BG

H

J

N

KL

M

SR

–0.4 –0.4

–0.4 –0.4

–0.6

–0.6–1.2

–1.2

0.6

0.6

0.2

0.2

1

Fig. 7. Local values of correlation coefficients (Xk) of the clustering indices of symbionts with selected pollutants from 39 shrimp pools,after controlling for shrimp size and autocorrelation. The coastal zone is located on the bottom margin and the platform zone on the topmargin in all figures. A, PCB1016 (X ¼ 0.64; n ¼ 39; P ¼ 0.0001); B, PCB1242 (X ¼ 20.77; n ¼ 39; P ¼ 0.9999); C, zinc (X ¼ 0.32; n ¼ 39;

P ¼ 0.0244). The letters in circles refer to the sampling points shown in fig. 1.






environment’ while finding food, they accumulate anincreasing number of symbionts and metazoan parasites.This is supported by data for the same phenomenon in avariety of fish species and other vertebrates thataccumulate larval-stage metazoan parasites as theygrow (Hudson & Dobson, 1995). The influence of depthis also predictable because shrimps are migratory, movingfrom shallow coastal lagoon waters to mate in the deeperopen sea (Ramırez-Rodrıguez et al., 2003). This migrationoccurs when they have reached adult stage, explainingthe correlation between host length and depth.

Once shrimp size and autocorrelation were controlledfor, useful patterns emerged between the symbiont andpollutant cluster indices values in both trawl and shrimppool data. Negative correlations in figs 4A, B and 6Bsuggest that the sampling points with high cluster valuesfor alpha-HCH and HCH had low symbiont values,especially near the coast. The apparent contradictionbetween overall values and correlations for heptachlor andsymbionts cluster values (figs 4C and 6C) in trawls andshrimp pools near the coast does not exist. Figure 4Cshows that the positive overall value is due to lowconcentrations of both symbionts and pesticides, whilefig. 6C, with an increase in sampling size (39 shrimp pools),presents a clear pattern where high and low indices occurfor heptachlor and low symbionts respectively. Lowsymbiont clustering values in the presence of HCH maybe related to an inhibitory effect since lethality due to HCHin Amphidinium carteri (dinoflagellate) is attained at2 mg l21 and in Tetrahymena pyriformis (ciliate) at.10 mg l21 (Jeanne-Levain, 1974). A similar situation canbe expected for heptachlor since this pesticide is reportedto cause a drop in cell density in the marine dinoflagellateExuviella baltica at 50mg l21 (Magnani et al., 1978).

The phenanthrene and symbiont correlation values (X)were higher near the coast than in the platform zone,which may be explained by organic productivity beinghigher in Terminos Lagoon due to the dumping ofuntreated sewage from Ciudad del Carmen. This in turnmay cause an increase in the number of symbionts, aswell as in the amount of PAHs.

The UCM in sediments and water, and symbiontscorrelation values were negative at most points (fig. 5Aand B). High UCM clustering values were associated withlow symbiont values suggesting that this mixture ofcompounds seems to be toxic to symbionts. This is furthersupported by data showing that species that do notmetabolize PAHs, like algae, oligochaetes, molluscs andprotozoans, can accumulate high UCM concentrationsthat eventually become harmful to them (James, 1989).

The PCB 1016 and 1242 and symbiont local correlationvalues were negative near the coast (fig. 7A and B),suggesting that these concentrations were harmful tothese protozoans. These pollutants presumably origi-nated in Ciudad del Carmen, and are produced by thevapourization of plasticizers or incineration, industrialfluid leaks and dumping, or disposal in dumps andlandfills. Accumulation of PCBs varies depending on thelength of exposure and concentration in the water. Forexample, a diatom exposed to PCB 1242 had anaccumulation factor of 1100 (Keil et al., 1971), whileciliated protozoan exposed to PCB 1254 in water had anaccumulation factor of 60. However, growth in certain

marine diatoms is inhibited by PCB 1254 levels as low as10–25mg l21 (Cooley et al., 1972).

For heavy metals, nickel in water from trawls (fig. 5C)and zinc in the shrimp pools (fig. 7C) had positivecorrelation values, especially near the coast. Again, alikely explanation is that high organic productivity inTerminos Lagoon from the dumping of untreated sewagemay cause an increase in the number of symbionts, aswell as in Ni and Zn concentrations.

The data indicate that different pollutants havedifferent statistical associations with symbionts. Apossible explanation for this is that these pollutantshave different effects on symbionts since they arechronically exposed to them due to their position on thegills or cuticle of shrimps.

The F. duorarum catch has been declining since the late1970s (Ramırez-Rodrıguez et al., 2003), and, though thepresent results are not shown as an explanation for all orpart of this decline, they do indicate that the presence ofpollutants and parasites probably has an additive effecton the Campeche Sound shrimp population’s generalcondition. If this is true, then highly polluted andparasitized shrimps are being removed from thepopulation through chronic exposure to a combinationof deleterious agents present in the environment. It canalso be expected that shrimps affected by pollutants,symbionts and metazoan parasites are unable to deal withenvironmental stresses (e.g. changes in temperature,salinity, oxygen concentration) that would have no effecton healthy shrimps.

Based on the present field data, both shrimps and theirsymbionts seem to be promising bioindicators of theenvironmental status of Campeche Sound (but see EPA,2000). Furthermore, data suggest that the origin ofpollutants found in the water, sediments and shrimps ofCampeche Sound is not exclusively linked to PEMEXactivities. Government authorities and people of coastalcities and towns also contribute by freely dumpingsewage charged with PAHs (mainly petroleum products)and PCBs into Terminos Lagoon, as do farmers upstreamwho continue to use banned pesticides that eventuallywash into the sea (Botello et al., 1996). The problem isextremely complex and its mitigation will requireextensive preventative measures such as sewage proces-sing plants and natural pesticide use, among others.

Acknowledgements

This paper was presented at the Black ForestSymposium entitled “Environmental and ecologicalparasitology: the impact of global change” held inFreudenstadt, Germany, Spring 2005. The authors thankthe Gerencia de Seguridad Industrial y ProteccionAmbiental RMNE, PEMEX Exploracion y Produccionfor financial support through contracts no. 4120028470and 4120038550, ‘Impactos antropogenicos sobre elrecurso camaron en la Sonda de Campeche I y II’. Theyalso thank Ana Maria Sanchez-Manzanilla, Clara Vivas-Rodrıguez, Gregory Arjona-Torres, Abril Rodrıguez-Gonzalez, Trinidad Sosa-Medina and Reyna Rodrıguez-Olayo of CINVESTAV-Merida, and Dr Rasul A. Khan forhis comments on an earlier version of this paper.






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(Accepted 10 February 2006)q CAB International, 2006






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