dwi candra pratiwi

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1 國立中山大學 海洋生物研究所 碩士論文 Institute of Marine Biology National Sun Yat-sen University Master Thesis 高雄港廢汙水排放區底棲生物之群聚結構及四種底棲動物蛋白質表 現之研究 The study of benthic community structure and protein expression pattern of four benthic species in effluent areas of sewage treatment plants (STP) in Kaohsiung, Taiwan 研究生 : 白緹薇撰 (Dwi Candra Pratiwi) 指導教授: 劉莉蓮博士 (Dr. Li-Lian Liu) 中華民國 100 8 August 2011

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1

國立中山大學 海洋生物研究所

碩士論文

Institute of Marine Biology

National Sun Yat-sen University

Master Thesis

高雄港廢汙水排放區底棲生物之群聚結構及四種底棲動物蛋白質表

現之研究

The study of benthic community structure and protein expression pattern

of four benthic species in effluent areas of sewage treatment plants

(STP) in Kaohsiung, Taiwan

研究生 : 白緹薇撰 (Dwi Candra Pratiwi)

指導教授: 劉莉蓮博士 (Dr. Li-Lian Liu)

中華民國 100 年 8 月

August 2011

2

I

高雄港廢汙水排放區底棲生物之群聚結構及四種底棲動物蛋白質表

現之研究

摘要

本研究探討高雄港廢汙水排放區底棲生物之群聚結構及四種底棲動物蛋白質表現是

否受廢汙水排放之影響。分別於2009年12月(冬季)及2010年7月(夏季)在中洲廢汙水處

理廠汙水排放區附近3個採樣點,中山大學廢汙水處理廠汙水排放區附近2個採樣點,及其

北方2公里處之對照樣點進行底拖網採樣。冬季及夏季之水溫分別為26.8、33.7oC; 鹽度分

別為32.2、31.5‰;酸鹼度分別為8.1、8.0。二季六個測站共捕獲底棲動物5門31科48種;

季節間與測站間之環境參數與物種組成無顯著差異。以一維蛋白質電泳檢測三種魚類(Lei-

ognathus splendens, Apogon fasciatus, Engyprosopon multisquama)及一種螃蟹(Portunus

hastatoides) 之蛋白質表現,此三種魚類及一種螃蟹之蛋白質表現在季節間與測站間亦

無顯著差異。依據相關文獻及本研究結果推測高雄港內存在多元之污染物也包含本研究之

六個測站8公里以上, 而造成測站間之底棲生物群聚結構及四種底棲動物蛋白質表現相似。

關鍵字: 一維蛋白質電泳、Leiognathus splendens、 Apogon fasciatus、 Engyprosopon

multisquama、Portunus hastatoides

II

The study of benthic community structure and protein expression pattern

of four benthic species in effluent areas of sewage treatment plants in

Kaohsiung, Taiwan

Dwi Candra Pratiwi

Advisor: Dr. Li-Lian Liu

Institute of Marine Biology, National Sun Yat-sen University, Kaohsiung, Taiwan,

R.O.C.

Abstract

In order to gain better understanding on the impacts of sewage treatment plant (STP)

effluent on marine environment, the present study was undertaken to investigate the structure of

benthic community and protein expression patterns of 4 benthic species in STP effluent areas in

Kaohsiung, Taiwan. Six sites were selected, 3 near Jhong Jhou STP, 2 near NSYSU STP and

one reference site. Samples were collected in December 2009 (winter) and July 2010 (summer)

by bottom trawling. In winter, temperature was 26.8oC; salinity and pH were 32. 2‰ and 8.1. In

summer, environmental data were 33.7oC, 31.5‰ and 8.0, respectively. In all, 5 phyla, 31

families and 48 different species were captured in two seasons. Proteomic approach by one-

dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (1D SDS-PAGE) was

conducted on 3 fishes, Leiognathus splendens, Apogon fasciatus, Engyprosopon multisquama,

and one crab Portunus hastatoides. Environment characteristics and structure of benthic

community had no significant difference among the 6 sampling sites. Protein expression patterns

based on the four examined species also indicated no significant difference among sites. The

complexity of pollutants in Kaohsiung Harbor is probably the main reason affecting all sampling

sites. In other words, contaminated area in Kaohsiung Harbor may cover a wide range, at least

III

over the present sampling distance, i.e. 8km which causes no difference in community structure

and protein expression pattern among control, Jhong Jhou STP and NSYSU STP sites.

Key words: 1D SDS-PAGE, Leiognathus splendens, Apogon fasciatus, Engyprosopon

multisquama, Portunus hastatoides

IV

Acknowledgments

Foremost, I would like to express my sincere gratitude to my advisor Dr. Li-Lian Liu for

the continuous support of my master study and research, for her patience, motivation,

enthusiasm, and immense knowledge. Her guidance helped me in all the time of research and

writing of this thesis. Besides my advisor, I would like to thank the rest of my thesis committee:

Dr. Hin-Kiu Mok, Dr. Kuoh-Sun Chiu and Dr. Eddy Suprayitno for their encouragement,

insightful comments, and hard questions. My sincere thanks also goes to Dr. Liliek Sulistyowati

for giving me opportunity to get this scholarship and Dr. Endang Yuli for supports and advices

you gave to me.

I thank to all my labmates, Frank Lin, Rui Ouyang and Helena Chan for proteomics

lesson and guidance, Sandy Chuang, Jin-Ying Wu, Yalan Chou, Steven Chan, Yi-Ting Fang, Jia-

Qi Lu, Mu-Ting Tang, Chih-Hsien Chang, for supports, happiness and friendship in this past two

years.

Last but not the least, I would like to thank my family, my parents, Bapak Agus

Sudarmadi, ibu Sri Wihadiati for giving birth to me at the first place and supporting me

spiritually throughout my life. To my sister Endah and her husband Agus, my little brother,

Waskito and my niece Basith Ar-Rahman for their love and supports.

V

Contents

Abstract in Chinese……………………………………………………………………… I

Abstract in English………………………………………………………………………. II

Acknowledgments………………………………………………………………………… IV

Contents…………………………………………………………………………………. V

List of Tables…………………………………………………………………………… VI

List of Figures……………………………………………………………………………. VII

List of Appendix……………………………………………………………………….. VIII

Introduction…………………………………………………………………………….. 1

Materials and methods……………………………………………………………………. 6

Results…………………………………………………………………………………… 9

Discussion………………………………………………………………………………… 12

Conclusion……………………………………………………………………………….. 16

References…………………………………………………………………………………. 17

Tables……………………………………………………………………………………. 22

Figures……………………………………………………………………………………. 33

Appendix……………………………………..………………………………………….. 48

VI

List of Tables

Table 1. Geographic coordinates of the sampling sites…………………………………… 22

Table 2. Environmental data of the sampling sites ………………………………………. 23

Table 3. Species composition in the winter and summer samples…..….…………………. 24

Table 4. Phyla composition community index of the winter and summer samples……….. 30

Table 5. Results of Principal Component Analysis of environmental and biological data

composition………………………………………………………………………………… 31

VII

List of Figures

Fig. 1. Map of the Sampling sites ………………………………………………………. 32

Fig. 2. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices

using square-root transformed overall environmental characteristics of winter and

summer samples. ………………………………………………………………………. 33

Fig. 3. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices

using square-root transformed overall biological characteristics of winter and summer

samples ………………………………………………………………………..…….…. 34

Fig. 4. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices

using square-root transformed overall environmental and biological characteristics of

winter and summer sample..………………………………………………………….. 35

Fig. 5. Principal Component Analysis of environmental and biological characteristic

data of winter and summer samples…………………………………………………….. 36

Fig. 6. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices

using square-root transformed overall environmental and biological characteristics of

winter samples………………………………………………………………………… 37

Fig. 7. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices

using square-root transformed overall environmental and biological characteristics of

summer samples……………………………………………………..………………….. 38

Fig. 8. Gel electropherogram results from the fish Leiognathus splendens…………. 39

Fig. 9. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices

using square-root transformed overall protein bands of fish Leiognathus splendens……. 40

Fig. 10. Gel electropherogram results from the fish Apogon fasciatus ………………… 41

Fig. 11. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices

using square-root transformed overall protein bands of fish Apogon fasciatus ………. 42

Fig. 12. Gel electropherogram results from the fish Engyprosopon multisquama ………. 43

Fig. 13. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices

using square-root transformed overall protein bands of fish Engyprosopon multisquama.. 44

Fig. 14. Gel electropherogram results from the crab Portunus hastatoides ………………. 45

Fig. 15. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices

using square-root transformed overall protein bands of crab Portunus hastatoides .…. 46

VIII

List of Appendix

Appendix 1. Correlation between summer and winter samples of environmental

characteristics…………………………………………………………………………….. 47

Appendix 2. Correlation between summer and winter samples of biological

characteristics…………………………………………………………………………….. 48

Appendix 3. Correlation between summer and winter samples of environmental and

biological characteristics………………………………………………………………… 49

Appendix 4. Similarity matrix of summer sample………………………………………… 50

Appendix 6. Correlation between proteomic bands of fish Leiognathus splendens………. 51

Appendix 7. Correlation between proteomic bands of fish Apogon fasciatus………….. 52

Appendix 8. Correlation between proteomic bands of fish Engyprosopon multisquama... 53

Appendix 9. Correlation between proteomic bands of crab Portunus hastatoides……….. 54

1

1. Introduction

Marine contamination takes place when the concentration of a waste substance in

seawater, sediments or organisms exceeds background level without causing measurable

damaging effects. It is usually coupled to human activities that modify properties of

environmental condition or the availability and quality of resources over a given space range

and/or time interval (Kennish, 1997).

Biological concerns of wastewater loading in marine environments have focused on four

main points (Kennish, 1997), firstly, the accumulation and transfer of metals and/or xenobiotic

compounds in marine food webs, including commercial resources. Secondly, toxic effects of

contaminants from population level, e.g. the survival and reproduction of marine organisms to

the level of ecosystem. Thirdly, uptake and accumulation of pathogenic organisms in

commercially harvested species destined for human consumption. Fourthly, the release of

degradable organic matters and nutrients to the ocean which results in localized eutrophication

and organic enrichment. Contaminations of biological concern are largely associated with

particulate waste materials and sediments which derived from hazardous wastes commonly pose

potential threat to marine communities and human through food web biomagnification.

Effectively environmental management requires biological indication to assess the status

of resources of interest. Benthic fauna have been used extensively as indicators of

environmental status. Many studies have demonstrated that benthos respond predictably to

various types of natural and anthropogenic stresses (Pearson and Rosenberg 1978, Dauer 1993,

Tapp et al. 1993, Wilson and Jeffrey 1994, Weisberg et al. 1997). Benthos have many

characteristics that make them useful as indicators, e.g. high exposure potential to stresses.

2

Because benthic organisms have limited mobility and cannot avoid adverse conditions, they are

exposed to contaminants accumulated in sediments. As a result, benthic assemblages, unlike

most pelagic fauna, reflect local environmental conditions (Gray, 1979). Another advantage of

using benthic fauna as biological indicator is their taxonomic diversity. Benthic organisms have

a wide range of physiological tolerances, feeding modes, and trophic interactions, making them

sensitive to a wide array of environmental stresses (Pearson and Rosenberg 1978, Rhoads et al.

1978, Boesch and Rosenberg 1981).

Use benthic fauna as bioindicator generally falls into two categories. Single community

attribute measures, including species diversity and abundance vs. biomass ratio, have been used

to summarize data beyond the level of individual species (Warwick and Clarke 1993, 1994).

Alternative approach is the multi-metric index, which combines multiple measures of community

response into a single index it is more effective to capture different types of response that occur

at different levels of individual stress (Engle et al. 1994, Weisberg et al, 1997).

1.1. Pollution source of aquatic environments

Sewage treatment plants (STPs) are the common source of chemicals entering into

aquatic environment. Effluent from STPs has been shown to contain complex mixtures of

chemicals, including PAHs, organic solvents, heavy metals, pharmaceuticals, and flame

retardants, originating from household use as well as industry (Paxeus, 1996; Halling-Sorensen

et al., 1998). Studies conducted on the effects of STP effluents have shown, for example,

vitellogenin effects, immune responses, and biomarker responses in fish caged/caught outside

STPs (Larsson et al., 1999; Oakes et al., 2004). Heat shock proteins (LISPs) can also be induced

by a variety of stressors, including heavy metals and organic and organo-metallic compounds

(Guven, 1994).

3

Sewage treatment generally involves three stages, called primary, secondary and tertiary

treatment (Kennish, 1997). Primary treatment consists of temporarily holding the sewage in a

quiescent basin where heavy solids can settle to the bottom while oil, grease and lighter solids

float on the surface. The settled and floating materials are removed and the remaining liquid

may be discharged or subjected to secondary treatment. Secondary treatment removes dissolved

and suspended biological matter. It is typically performed by indigenous, water-borne micro-

organisms in a managed habitat. Secondary treatment may require a separate process to remove

micro-organisms from the treated water prior to discharge or tertiary treatment. Tertiary

treatment is sometimes defined as anything more than primary and secondary treatment in order

to allow rejection into a highly sensitive or fragile ecosystem. Treated water is sometimes

disinfected chemically or physically (for example, by lagoons or microfiltration) prior to

discharge into stream, river, bay, lagoon or wetland. And it can be used for the irrigation of a

golf course, green way or park. If it is sufficiently clean, it can also be used for groundwater

recharge or agricultural purposes.

1.2. Response of organisms to pollution stress

Individual organisms display multiple responses to pollutant stress. Physiological

responses depend on bioavailability, uptake, detoxification, accumulation and disposition of

pollutants in the body. Chief among the negative physiological changes are those directly

affecting on organism’s growth, reproduction and survival. For instance, sublethal toxic effects

of pollution commonly alter energy supply for growth and reproduction of marine organisms

(Almroth, 2008).

Proteomic techniques, in particular, offer great potential for insight into chemical modes

of toxic action and are useful tools in biomarkers discovery (Snape, 2004). Although measuring

4

specific protein has been used extensively in aquatic toxicology to monitor organism exposure

and effect, the analysis of whole proteomes enables one to examine potentially unforeseen

responses (Brian, 2010). The proteome is highly dynamic and continuously responding to

numerous intra ad extra cellular signaling (Barrett, 2005). It is recognized that all living

organisms respond to even the most subtle environmental changes through alteration in the

expression of multiple genes and proteins (Monsinjon, 2007).

Stress-induced changes at the gene/protein level occur earlier and at lower doses than

those causing alteration at organism level (Aaderma, 2002). Therefore, research focusing on

proteomic alteration can help to unravel the early molecular events involved in toxicant response

(Miracle, 2005).

In Kaohsiung City, Jhong Jhou STP is the biggest waste water treatment facility which is

located in Chi-jin Island (KCG, 2006). This secondary STP was built in 1987 and treats up to

30% of domestic waste water from all over the city, including domestic, hospital and industrial

discharge with 1.5 million population (Yang, 1995). Moreover, there are several industrial parks

(e.g., chemical manufacturing plants, paint and dye industries, metal processing factories,

electronic industries, paper and board mills, motor vehicle plating and finishing plants, and

foundries) located in or around Kaohsiung City (Chen and Wu, 1995). Research on Kaohsiung

harbor pollution caused by industrial waste dumping and shipping activity has been conducted.

However, study relates to impact of STP effluent on local fauna in Kaohsiung harbor is still

unavailable. Additionally, effluent of National Sun Yat-sen University (NSYSU) STP with

secondary treatment facility also flows into Kaohsiung harbor. In order to gain better

understanding on the impact of STP effluent on marine environment, the present study was

5

undertaken to investigate the benthic community structure and proteomic profiles of fishes living

in effluent areas of Jhong Jhou and NSYSU STPs in Kaohsiung, Taiwan.

6

2. Materials and methods

2.1 Sample collections

Samples were collected by bottom trawling at six locations, in December, 2009 (winter)

and June, 2010 (summer) (Table 1). Locations of AC AS and AN were near Jhong Jhou STP

effluent (Fig. 1). Site AC locates right in front of the outlet of Jhong Jhou STP which is about

10 km offshore. Site AS is in the south of AC and AN is in the north of AC. All three sites

were <2 km away from each other. Two sites were around NSYSU STP. They are C5 and C10.

Site C5 is in front of the STP outlet which is about 1 km offshore. Site C10 is in front of C5 at

10m in depth. Site D site is the reference site. All of the three sites were < 2km away from

each other. Environmental characteristics, such as temperature, salinity, pH and depth were

recorded. Collected samples were sealed in zip bags and saved in iced box on board until

further storage in -20oC freezer.

2.2 Study on benthic community structure

I calculated univariate measures of the benthic assemblages, including total abundance,

number of species and Shannon diversity indices. Population structures were analyzed by Bray-

Curtis similarity test using square-root transformed data. And, significance computations were

performed by SIMPROF tests. A 'similarity profile' (SIMPROF) test is described, in which the

biotic similarities from a group of a priori unstructured samples are ordered from smallest to

largest, plotted against their rank (the similarity profile), and this profile compared with that

expected under a simple null hypothesis of no meaningful structure within that group. Repeated

application of this test generates a stopping rule for a posteriori division of the samples into ever

smaller subgroups, as in hierarchical cluster analysis (Clarke, 2008). The Principal Component

7

Analysis (PCA) was calculated to characterize the weighting of each variable. All analyses were

performed using the software package PRIMER6 developed at the Plymouth Marine Laboratory

(Warwick and Clarke, 1994).

2.3 Proteomic study

2.3.1 Sample preparation

Species found in all sampling sites were selected for proteomic analysis. Samples were

homogenized individually at 5oC with 500 μL homogenization buffer (250 mM sucrose, 1 mM

EDTA, 30 mM Tris, Ph 7.4), using 2 mL eppendorf tube. Each sample was maintained for 10

min on ice for protein release. Soluble protein fraction was harvested by centrifugation at 13,000

rpm for 30 min at 4 o

C and the pellet was discarded. The supernatant was aliquoted into 2 mL

new eppendorf and protein concentration was determined using the BCA protein assay (Thermo

Fisher Scientific Inc., Rockfeller, USA). At least three individuals were analyzed from each site

excluding the sites without enough specimens. A sample containing approximately 400 μL

protein was then stored at -70 o

C freezer for one-dimensional sodium dodecyl sulphate-

polyacrylamide gel electrophoretic (1-D SDS-PAGE) protein analysis.

2.3.2 1-D SDS-PAGE

For gel electrophoresis, the sample was mixed with 2X sample buffer (1M Tris-Cl (pH

6.8) DTT, SDS, Bromophenol blue, Glycerol, DDH2O) to a concentration of 40 μg protein each

sample per well of the gel, vortexed the sample for 30 seconds. For protein annealing process, it

was heated at 95 oC for 5 min and quickly removed to iced and rested for 3 min to deanneal. The

sample was loaded to 12% gel consisting of Acrylamide-Bis (30%T, 2.6%C), 1.5M Tris (pH 8.8

8

for resolving and pH 6.5 for stacking gel (storage at 4oC, 10% SDS, 10% APS, TEMED and

DDH2O). Isopropanol was applied over the resolving gel solution to prevent oxidation before

stacking gel solution loaded. Gels were run at two steps, firstly constant 15 mA for 30 min and

secondly, 40-45 mA for 4 to 4.5 hrs. Afterward, gels were stained with colloidal commassie blue

(200 mL methanol, 50 mL Acetic acid, commassie blue for 0.5 g and DDH2O) for 15 min and

destaining over night with DDH2O, then scanned the gel by Amersham bioscience gel scanner.

2.3.3 Image acquisition

Bands detection and matching were performed using Fuji film Multi Gauge V2.02 software

(Fuji Photo Film Co., Ltd). The reference gels were used as standard to determine the relative

intensity of test bands. Then, the data were analyzed by Bray-Curtis similarity test using square-

root transformed data and the significance computations were performed by SIMPROF tests. All

of the analyses were conducted by the software package PRIMER6 developed at the Plymouth

Marine Laboratory (Warwick and Clarke, 1994).

9

3 Results

3.1 Study on benthic community structure

In winter, the average salinity, temperature and pH were 32.17‰, 26.8oC, and 8.1,

respectively (Table 2). On the other hand, the average values of environmental characteristics

were 31.5‰, 33.8 o

C, and 8.0, respectively, in summer. Cluster dendrogram using the Bray-

Curtis similarity indices showed no significant difference in environmental characteristics among

sites and between seasons (Fig. 2) and the correlation matrix was shown in Appendix 1.

A total of 5 phyla, 31 families and 48 species with 5661 individuals were collected during

the study period (Table. 3). Among them, 2755 individuals were from winter samples and 2906

were from summer samples. The most abundant family was Penaidae. Seven species were

included in this family, i.e., Metapenaeopsis palmensis, M. provocatoria longiroitris,

Parapenaeopsis cornuta, Portunus argentatus, P. sanguinolentus, P. pelagicus and P.

hastatoides, respectively. Hermit crab is the most abundance species in both winter (2419

individuals) and summer (1194 individuals). There were only 4 species founded in all sites,

three fishes (Leiognathus splendens, Apogon fasciatus and Engyprosopon multisquama) and one

crab (Portunus hastatoides).

In summer, the highest richness was 2.59 at site D and the lowest is 0.69 at site C10, both

in winter (Table 4). Evenness and diversity index have the highest values in winter samples;

they were sites D and C5. Evenness was 0.93 at site D and 0.26 at site C5. For the diversity

index, it was 1.93 at site D and 0.415 at site C5.

Cluster dendrogram using the Bray-Curtis similarity indices showed no significant

difference in species composition among sites and between seasons (Fig.3). When combined

both environmental and biological data together, the cluster dendrogram showed significant

10

difference among some sites (Fig. 4). Both correlation matrix were shown in Appendix 2 and 3.

Most sites in winter season were grouped together except site DW. In order to determine the

variables which contributed to the separation, the data were further analyzed by PCA. As shown

in Fig. 5. PC1 was the major component to separate site DW from others which explained 97.6%

of the variation (Table 5). The sample sites were divided into 3 groups, first group was site D in

winter (DW), second was site AC in summer (ACS) and the third including the rest of the sites

(Fig. 5). The most important coefficient in the linier combination of variables making up this

separation was hermit crab with the value of -1.00 (Table 5). It is known that hermit crab was

the most abundant species in our samples at site D in winter and at site AC in summer (Table 3).

To examine site variation within season, cluster dendrograms using the Bray-Curtis

similarity indices showed no significant difference in neither environmental characteristics,

species composition nor both combined in winter and summer (Figs. 6 and 7). The similarity

correlation matrix were shown in Appendix 4 and 5.

3.2 Proteomic study

Species founded in all sites were used for proteomic study. They were three fishes

(Leiognathus splendens, Apogon fasciatus and Engyprosopon multisquama) and one crab

(Portunus hastatoides) (Table 3). Fish Leiognathus splendens with 18 individuals were used in

this study. There were 24 bands determined in each sample (Fig. 8). Significant difference

among individual was shown without site variation (Fig. 9). The individual of 13AC was

significantly different from others at similarity level of 83% (Appendix 6). Fish Apogon

fasciatus with 15 individuals were used in this study. There were 24 bands determined in each

sample (Fig.10). Significant difference among individual was shown without site variation (Fig.

11

11). Two individuals 21AS and 45AS were significantly different from others at similarity level

of 94% (Appendix 7). Fish Engyprosopon multisquama with 16 individuals was used in this

study. There were 29 bands determined in each sample (Fig. 12). Significant difference among

individual was shown without site variation (Fig. 13). Similarity correlation matrix among

samples was shown in Appendix 8. The 17 individuals of crab Portunus hastatoides were used.

It had 27 protein bands (Fig. 14). Two individuals were significantly different from others (Fig.

15) with the correlation matrix shownl in Appendix 9. However, there was no site correlation in

the cluster results.

12

4 Discussion

Environmental characteristic was insignificant difference among the sampling sites. In

other words, environmental variation is not the major factor affecting on the structure of benthic

communities in the sampling area. Increasing habitat complexity will generally result in an

increase of diversity and a change in the community structure (Friedlander and Parrish, 1998;

Ohman and Rajasuriya, 1998). However, sites at Jhong Jhou STP, NSYSU STP and control site

are sandy bottom. It is suggested that sandy substrate are unstable in nature, which are rolled,

dispersed and buried constantly by various currents. Thus, population expansion by benthic

dwelling rock-affiliated species like decapods is very difficult (Chou and Fang, 2005).

Previous monitoring on decapods in Kaohsiung Harbor during 1990 – 1998 showed

insignificant difference between control and slag dumping sites (Chou and Fang, 2005). They

separate the monitoring data into three stages. Stage I was conducted in 1990 - 1992, stage II

was 1993 - 1995 and stage III was 1996 - 1998. None of the three stages have significant

difference in decapods species number. As in their diversity index, the p values were 0.180,

0.988 and 0.781, respectively. As to individual numbers, insignificant p values showed for stage

I and II, i.e. 0.150 and 0.485. For stage III, significant difference (p<0.01) was caused by

typhoon Gloria hit the study area in July 1996 (Chou and Fang, 2005).

In the present study, Leiognathus splendens, Apogon fasciatus, Engyprosopon

multisquama and Portunus hastatoides are four species found in all sampling sites. These

species are typically coastal species. Study on Benthic community monitoring in Kaohsiung

Harbor founded that the most captured species were families of callionymidae, Mullidae (in

control site) and Bothidae, Scorpaenidae, Platycephalidae, Leiognathidae, Apogonidae and

Synanceiidae (in dumping area) (Chou and Fang, 2005).

13

Fish Leiognathus splendens is widely distributed in the eastern Indian and western Pacific

oceans, from India to Papua New Guinea, and from southern Japan to northern Australia

(www.seabase.com). Fish Apogon fasciatus is Reef-associated; at depth ranges between 2 - 128

m and distributes in Indo-West Pacific: Red Sea and Persian Gulf south to Mozambique and east

to the western Pacific from Japan to Sydney. Fish Engyprosopon multisquama distributes from

northwest pacific: Japan to Taiwan. It is a demersal fish in temperate area (Goren et al, 2009).

Proteomic analyses conducted on the 4 species and none shows cluster related to site difference.

The distance among the sampling sites was in the range of 2 – 8 km. It is possible that the target

species moved across sites frequently.

Moreover, the complexity of various pollutants in Kaohsiung Harbor also can be one

reason causing no site difference in this study. Coastal and offshore regions of southwestern

Taiwan receive ~35 million tons per year (Mt/year) of chemically weathered sediments from the

high mountains of Taiwan and the upper crust of the Yangtze Craton (UC-YC, China), mainly

through river input and substantially by aeolian pathways. With nearly 36,000 km² of land,

about 1.6 Mt of domestic and industrial wastes were generated, primarily from factories, farming

activities, hospitals and other major business organizations, which increased heavy metals and

organics loads in natural environments (Tsai and Chou, 2004). The China Steel Corporation, the

largest producer of steel in Taiwan, uses offshore region of southwestern Taiwan as their solid

waste dumping site during 1984 - 1995. During this time period, 2 Mt of slag were dumped in

the site located approximately 14 km from Kaohsiung Harbor (Chou et al., 2002).

Another study (Lee et al, 2000) measured heavy metal concentrations in sediments of

Kaohsiung Harbor. Three groups of their sampling sites were closest to my sampling sites. First

group was T3 (in 5, 7.5, 10 and 15m depth) close to my control site D. Second group was T4

14

close to my NSYSU STP sites and the third group was T5 close to Jhong Jhou STP. The study

reported eight heavy metals, i.e. Cu, Zn, Pb, Ni, Cr, Cd, Mn and Fe. In T3-5m, the

concentrations of Cu, Zn, Pb, Ni, Cr, Cd and Mn were 17.5, 90.0, 23.8, 18.8, 28.8, 0.05 and

345mg/kg sediments, respectively. The concentration of Fe was 2.74% of surface sediments.

The listed heavy metals at site T4-5m (near NSYSU STP) were lower than that of T3-5m. They

were 7.5, 78.8, 16.3, 23.8, 27.5, 0.12 and 287.5mg/kg sediments. The site T5-5m was close to

my Jhong Jhou STP sites. The sediments contained heavy metals in concentrations between sites

T3-5m and T4-5m. Metal concentrations of Cu, Zn, Pb, Ni, Cr, Cd and Mn were 8.8, 75.0, 25.0,

36.0, 26.3, 0.04 and 252.5mg/kg sediments and Fe was 2.79% of surface sediments. It is

suggested that the sediments of my study sites also contain various heavy metals with high

concentration.

Study in metal enrichment in surface sediments off southwestern Taiwan was also

conducted in 1995 (Chen and Selvaraj, 2008). Twenty sites in coastal Kaohsiung Harbor were

chosen, three of them were close to my sampling sites. They were KN12, K1 and S1,

respectively. Nine metals were detected in all sites, i.e., As, Cd, Cr, Cu, Mn, Ni, Pb, V and Zn.

Site KN12 was 2km away from my control site. Metal concentrations were 17.8, 1.2, 76.0, 30.0,

368.0, 37.0, 53.0, 74.0 and 143.0 µg/g sediments, respectively. Site K1 located 1 and 0.5km

away from sites C5 and C10. Metal concentrations were 7.2, 0.2, 64.0, 26.0, 357.0, 36.0, 42.0,

68.0 and 163µg/g sediments. Site S1 was 0.5km away from my AN and AS sites. Its metal

concentrations were below detection limit for As, and 0.3, 56.0, 14.0, 390.0, 26.0, 21.0, 87.0, and

85µg/g sediments for metals of Cd, Cr, Cu, Mn, Ni, Pb, V and Zn. These two studies indicated

that my control site is also a polluted site in Kaohsiung Harbor with high concentrations of heavy

metals as my other 5 sampling sites near NSYSU and Jhong Jhou STP.

15

Local current in Kaohsiung Harbor were another possible reason causing insignificant

difference among my six sampling sites. Longshore currents off Chi-jin Island are dominated by

seasonal tidal pattern (Liu, 1997). In summer, the prevailing wind directs sediments transport in

northward direction, and vice versa in winter. However on long-term basis, the northward

transport dominates (Kaohsiung Institute of Marine Technology, 1998). Another study also

mentioned that both tidal and subtidal currents are strong in the Taiwan Strait with semidiurnal

tide dominant (Chuang, 1985). The subtidal current flow in the Taiwan Strait is usually

northward in both winter and summer with summer northward current being stronger (Chuang,

1985). Thus sediment transport by currents might result in movement or/and mixing small-scale

environmental conditions and it makes the analysis shows no sites correlation.

16

5. Conclusions

Environment characteristics are not the major factor affecting the structure of benthic

communities. Protein expression patterns based on the four examined species also indicated no

significant difference among sites. The complexity of pollutants in Kaohsiung Harbor may be

the main reason affecting all sampling sites. In other words, contaminated area in Kaohsiung

Harbor seems to cover a wide range, at least over the present sampling distance, i.e. 8km which

causes no difference in community structure and protein expression pattern among the control,

Jhong Jhou STP and NSYSU STP sites.

17

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22

Winter Summer

Sites Latitudes Longitudes Latitudes Longitudes

D 22° 38.994’N 120° 14.191’E 22° 38.994’N 120° 14.191’E

C5 22° 37.467’N 120° 15.124’E 22° 37.467’N 120° 15.152’E

C10 22° 37.783’N 120° 14.474’E 22° 37.730’N 120° 14.417’E

AN 22° 34.677’N 120° 15.350’E 22° 35.967’N 120° 14.587’E

AS 22° 34.203’ N 120° 16.086’E 22° 34.098’N 120° 15.633’E

AC 22° 34.809’N 120° 14.389’E 22° 32.808’N 120° 15.548’E

Table 1. Geographic coordinates of the sampling sites

23

Sites Salinity ‰ Temperature °C pH Depth (m)

D 27.3±0.6 30.3±0.6 8.2±0.0 11.4

C5 27.2±0.3 30.3±0.6 8.1±0.0 3.2

C10 27.7±0.5 30.7±0.6 8±0.0 10.6

WINTER AC 25±0 34.7±0.6 8.1±0.0 25.5

AS 25.2±0.3 34.7±0.6 8.1±0.0 20.4

AN 27.6±0.1 33.3±0.6 8.2±0.0 18.7

D 30±0.0 34.0±0.3 8.1±0.0 11.2

SUMMER C5 30.3±0.6 33.7±0.2 8.02±0.0 3.9

C10 30.7±0.6 33.4±0.3 8.1±0.0 11.4

AC 32.7±1.2 32.9±0.5 8.01±0.0 27

AS 32.7±2.1 34.1±0.0 8.05±0.0 21.8

AN 34.3±0.6 34.2±0.1 7.97±0.0 19.6

Table 2. Environmental data of the sampling sites. (mean±SD) check and correct the decimal point by yourself.

24

Winter Summer

Species D C5 C10 AC AS AN D C5 C10 AC AS AN

Cnidaria

Sea pen 0 0 0 0 0 0 7 0 4 0 6 4

Molusca

Family : Personidae

Distorsio reticularis 0 0 0 0 0 0 0 0 3 2 1 1

Family : Nassariidae

Nassarius clathratus 0 0 0 0 0 0 1 0 0 1 13 1

Family : Muricoldea

Rapana rapiformis 0 0 0 0 0 0 0 0 0 0 0 1

Family : Veneridae

Dosinorbis bilunulata 0 0 0 0 0 0 0 0 0 0 1 0

Paphia amabilis 0 0 0 0 0 0 0 0 0 0 0 1

Family : Philinidae

Philine vitrea 0 0 0 0 0 0 0 0 5 0 0 1

Table 3. Species composition of the winter and summer samples.

summer.

25

Winter Summer

Species D C5 C10 AC AS AN D C5 C10 AC AS AN

Family : Octoodidae

Octopus aegina 0 0 0 0 0 0 0 0 0 0 1 0

Family : Loliginidae

Sepioteuthis lessoniana 0 0 0 13 19 3 0 0 0 0 5 1

Arthropod

Family : Calappidae

Calappa philargius 0 0 0 0 0 0 0 0 0 1 0 0

Matuta victor 2 1 1 0 0 0 0 5 0 0 0 0

Family : Paguroidae

hermit crab 2419 26 0 0 0 0 0 1 0 1194 38 11

Family : Leucoslidae

Arcania septemspinosa 0 0 0 0 0 0 0 0 0 0 1 0

Family : Penaidae

Metapenaeopsis palmensis 0 0 0 14 0 0 0 0 0 4 1 2

26

Winter Summer

Species D C5 C10 AC AS AN D C5 C10 AC AS AN

M. provocatoria longiroitris 0 0 0 0 0 0 0 0 1 0 0 0

Parapenaeopsis cornuta 0 0 1 0 0 0 0 0 0 0 0 0

Portunus argentatus 0 0 0 1 0 0 2 0 10 17 3 1

P. sanguinolentus 4 2 5 0 0 0 0 2 0 0 0 0

P. pelagicus 0 0 0 0 0 0 0 1 0 0 0 0

P. hastatoides 0 0 0 6 18 4 16 2 12 164 50 24

Echinodermata

Family Astropectinidae

Astropecten scoparius 0 0 0 0 0 0 0 0 0 21 0 0

Echinodea 0 0 0 0 0 0 0 0 0 25 49 11

Family Majidae

Phalangipus longipes 0 0 0 0 0 0 0 0 0 0 1 0

27

Winter Summer

Species D C5 C10 AC AS AN D C5 C10 AC AS AN

Chordata

Family : Haemulidae

Diagramma pictum 0 0 0 0 0 0 0 0 0 2 0 0

Family : Gabiidae

Oxyurichthys

ophthalmonema 1 0 0 0 0 0 0 0 0 0 0 0

Family : Platycepalidae

Onigocia spinosa 0 0 0 0 0 0 0 0 0 91 0 0

Family : Apogonidae

Apogon fasciatus 0 0 0 0 2 0 7 1 2 18 33 23

Family : Plotosidae

Plotosus lineatus 0 0 0 0 0 0 1 106 4 0 0 0

Family : Tetraodontidae

Chelonodon patoca 1 0 0 0 0 0 0 0 0 0 1 6

28

Winter Summer

Species D C5 C10 AC AS AN D C5 C10 AC AS AN

Family : Leiognathidae

Leiognathus splendens 1 73 21 0 0 0 106 106 295 222 15 11

Family : Bothidae

Engyprosopon multisquama 0 0 0 0 0 0 3 2 1 53 25 17

Family : Synanceiidae

Inimicus japonicus 0 0 0 0 0 0 0 0 0 1 0 0

Family : Paralichtyidae

Pseudorhombus

quinquocellatus 0 0 0 1 0 0 0 0 0 0 0 0

Family :Soloeidae

Liachirus melanospilos 0 0 0 0 0 0 0 0 1 0 0 0

Family : Leucosioidae

Philyra platychira 0 0 0 0 0 0 1 0 0 1 6 0

29

Winter Summer

Species D C5 C10 AC AS AN D C5 C10 AC AS AN

Family : Synodontidae

Saurida elongata 0 0 0 0 0 0 1 0 2 0 1 3

Trachinocephalus myops 0 0 2 0 0 0 1 3 15 0 0 3

Family : Uranoscopidae

Uranoscopus chinensis 0 0 0 0 0 0 0 0 0 1 0 0

Family : Sillaginidae

Sillago parvisquamis 0 0 0 0 0 0 0 0 0 0 1 1

Family : Monacanthidae

Stephanolepis cirrhifer 1 0 0 0 0 0 0 0 0 0 0 0

Family : Triacanthidae

Tripodichthys blochii 0 0 0 0 0 0 0 1 0 0 0 0

Family : Mullidae

Upeneus bensasi 3 2 0 2 8 2 0 0 4 0 0 1

30

Table 4. Community index of the winter and summer samples.

Winter Summer

Species D C5 C10 AC AS AN D C5 C10 AC AS AN

Cnidaria (Sea pen) 0 0 0 0 0 0 7 0 4 0 6 4

Molusca 0 0 0 13 19 3 1 0 8 3 21 6

Arthopoda 2525 29 7 21 18 4 18 11 23 1380 93 38

Chordata 7 73 23 3 8 2 120 219 324 389 82 65

Echinodermata 0 0 0 0 0 0 0 0 0 46 50 11

Σ Species 8 5 3 5 5 8 10 8 10 10 7 8

Margalef Richness* 2.59 0.91 0.6 0.84 1.5 1.44 1.8 1.28 1.54 1.96 0.97 1.39

Pielouf Evenness** 0.93 0.26 0.57 0.53 0.69 0.89 0.46 0.5 0.31 0.79 0.64 0.87

Diversity index (Log e)*** 1.93 0.415 0.63 1.43 1.42 0.85 1.07 1.04 0.71 1.25 1.8 1.82

31

Eigenvalues

PC Eigenvalues %Variation Cum.% Variation

1 5.59E+05 97.6 97.6

2 1.03E+04 1.8 99.4

3 2.29E+03 0.4 99.8

4 837 0.1 99.9

Eigenvectors

(Coefficients in the linear combinations of variables making up PC's)

Variable PC1 PC2 PC3 PC4

Apogon fasciatus 0.001 0.011 -0.163 0.019

Arcania septemspinosa 0 0 -0.002 0

Astropecten scoparius -0.003 0.035 -0.082 0.027

Calappa philargius 0 0.002 -0.004 0.001

Callionymus planus 0.001 -0.004 -0.045 0.014

Chelonodon patoca 0 -0.004 -0.007 -0.002

Diagramma pictum 0 0.003 -0.008 0.003

Distorsio reticularis 0 0.008 -0.003 -0.008

Dosinorbis bilunulata 0 0 -0.002 0

Echinoidea -0.001 0.017 -0.226 0.048

Engyprosopon multisquama -0.005 0.073 -0.276 0.084

hermit crab -1 -0.008 0.02 0.001

Inimicus japonicus 0 0.002 -0.004 0.001

Leiognathus splendens -0.002 0.95 0.273 -0.107

Liachirus melanospilus 0 0.002 0.003 -0.004

Matuta victor 0 -0.001 0.015 0.042

Metapenaeopsis palmensis 0 -0.004 -0.024 -0.006

Metapenaeopsis provocatoria longiroitris 0 0.002 0.003 -0.004

Nassarius clathratus 0.001 -0.004 -0.036 0.003

Octopus aegina 0 0 -0.002 0

Onigocia spinosa -0.013 0.151 -0.354 0.119

Oxyurichthys ophthalmonema 0 -0.001 0.002 -0.001

Paphia amabilis 0 0 -0.001 0

Parapenaeopsis cornuta 0 0 0 -0.001

Penaeus marginatus 0 0.002 -0.004 0.001

Penaeus monodon 0 0.002 0 0.02

Phalangipus longipes 0 0 -0.002 0

Philine vitrea 0 0.009 0.013 -0.019

Philyra platychira 0 0 -0.018 0.002

Table 5. Results of Principal Component Analysis of environmental and biological data

32

Plotosus lineatus 0.006 0.038 0.229 0.964

Portunus argentatus -0.002 0.045 -0.045 -0.017

Portunus hastatoides -0.018 0.25 -0.75 0.156

Portunus pelagicus 0 0 0.002 0.009

Portunus sanguinolentus -0.001 -0.005 0.015 0.008

Pseudorhombus quinquocellatus 0 -0.001 0 -0.001

Rapana rapiformis 0 0 -0.001 0

Saurida elongata 0 0.002 0.001 -0.009

Sepioteuthis lessoniana 0.002 -0.024 -0.029 -0.023

Sillago parvisquamis 0 -0.001 -0.003 0

Stephanolepis cirrhifer 0 -0.001 0.002 -0.001

Thalamita sima 0 0 -0.002 0

Tiarinia cornigera 0 0.006 0.009 -0.011

Trachinocephalus myops 0.001 0.027 0.046 -0.031

Tripodichthys blochii 0 0 0.002 0.009

Upeneus bensasi 0 -0.003 0.012 -0.028

pH 0 0 0 -0.001

Salinity 0.001 -0.006 -0.018 -0.011

Temperature 0 0.023 -0.009 0.037

Depth 0 -0.013 -0.122 -0.06

33

Fig. 1. Map of the Sampling sites 1: Jhong jhou STP, 2: NSYSU STP. AC: outlet pipe dumping

of JJ STP. AN: North side of AC. AS: South side of AC. C5: outlet pipe dumping site of NSYSU

STP at depth of 5 meter depth. C10: outlet dumping site of NSYSU STP at depth of 10 m. D

control site.

2

1

34

Fig. 2. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices using

square-root transformed environmental data in winter and summer. Dash lines represent

insignificant difference between sites. S: summer; W: winter.

35

Fig. 3. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices using

square-root transformed biological data in winter and summer. Dash lines represent insignificant

difference between sites. S: summer; W: winter.

36

Fig. 4. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices using

square-root transformed environmental and biological data in winter and summer. Solid lines

represent significant difference between sites; Dash lines represent insignificant difference

between sites. S: summer; W: winter.

37

Fig. 5. Plot of PC1 and PC2 based on environmental and biological data in winter and summer.

S: summer; W: winter.

38

Fig. 6. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices using

square-root transformed data in winter. A. Environmental characteristics B. Biological

characteristics, C. Environmental and biological characteristics. Solid lines represent significant

difference between sites; Dash lines represent insignificant difference between sites. W: winter.

A

B

C

39

Fig. 7. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices using

square-root transformed data in summer. A. Environmental characteristics B. Biological

characteristics, C. Environmental and biological characteristics. Solid lines represent significant

difference between sites; Dash lines represent insignificant difference between sites. S: summer.

A

B

C

40

Fig. 8. Gel electropherogram with molecular markers results from fish Leiognathus splendens.

~130 kDa ~170 kDa

~10 kDa

~17 kDa

~26 kDa

~34 kDa

~43 kDa

~55 kDa

~72 kDa ~95 kDa

41

Fig. 9. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices using

square-root transformed protein expression data of fish Leiognathus splendens. Solid lines

represent significant difference between individuals; Dash lines represent insignificant difference

between individuals.

42

Fig. 10. Gel electropherogram with molecular markers results from fish Apogon fasciatus.

~170 kDa ~130 kDa ~95 kDa

~72 kDa

~55 kDa

~43 kDa

~34 kDa

~26 kDa

~17 kDa

~10kDa

43

Fig. 11. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices using

square-root transformed protein expression data of fish Apogon fasciatus. Solid lines represent

significant difference between individuals; Dash lines represent insignificant difference between

individuals.

44

Fig. 12. Gel electropherogram with molecular markers results from fish Engyprosopon

multisquama.

~170 kDa ~130 kDa

~95 kDa

~72 kDa

~55 kDa

~43 kDa

~26 kDa

~34 kDa

~17 kDa

~10 kDa

45

Fig. 13. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices using

square-root transformed protein expression data of fish Engyprosopon multisquama. Solid lines

represent significant difference between individuals; Dash lines represent insignificant difference

between individuals.

46

Fig. 14. Gel electropherogram with molecular markers results from crab Portunus hastatoides.

~170 kDa

~130 kDa

~95 kDa

~72 kDa

~55 kDa

~43 kDa

~26 kDa

~34 kDa

~17 kDa

~10kDa

47

Fig. 15. Dendrogram following cluster analysis of Bray-Curtis similarity (BCs) indices using

square-root transformed protein expression data of crab Portunus hastatoides. Solid lines

represent significant difference between individuals; Dash lines represent insignificant difference

between individuals.

48

Appendix 1. Correlation matrix of environmental characteristics in summer and winter.

ASW ACW ANW C5W C10W DW ASS ACS ANS C5S C10S DS

ASW

ACW 96.80

ANW 97.64 94.53

C5W 84.50 82.13 86.86

C10W 89.83 87.45 92.38 93.36

DW 90.25 87.13 92.77 92.93 97.69

ASS 93.06 91.69 93.52 82.64 89.10 89.37

ACS 91.31 94.10 91.77 81.09 87.55 87.18 96.34

ANS 94.34 91.47 95.65 82.63 89.14 89.38 97.75 94.15

C5S 82.06 79.63 84.67 94.57 91.29 90.81 87.90 85.12 87.93

C10S 87.80 85.55 90.27 89.78 96.28 95.25 92.74 90.29 92.74 94.29

DS 86.95 84.47 89.43 89.92 95.20 95.59 92.60 89.50 92.59 95.21 98.72

49

Appendix 2. Correlation matrix of biological characteristics in summer and winter.

ACW ASW ANW C5W C10W DW ACS ASS ANS C5S C10S DS

ACW

ASW 49.41

ANW 38.30 32.14

C5W 2.82 2.65 3.54

C10W 0.00 0.00 0.00 35.56

DW 0.16 0.24 0.16 2.52 0.49

ACS 1.29 2.14 0.44 10.28 2.37 56.18

ASS 9.49 16.45 5.26 22.71 11.11 2.98 17.41

ANS 13.79 24.04 8.28 19.17 16.77 1.09 10.21 58.52

C5S 1.47 2.14 1.65 45.56 20.38 0.45 11.19 9.37 11.89

C10S 4.53 8.87 3.26 32.40 12.31 0.29 22.93 11.69 14.55 39.80

DS 8.94 19.15 5.33 59.59 26.74 0.08 14.06 24.12 31.05 61.33 50.80

50

Appendix 3. Correlation matrix of environmental and biological characteristics in summer and winter.

ACW ASW ANW C5W C10W DW ACS ASS ANS C5S C10S DS

ACW

ASW 81.74

ANW 85.29 79.93

C5W 45.82 43.84 52.20

C10W 63.62 60.17 74.64 65.73

DW 5.91 5.91 6.17 7.52 6.34

ACS 9.66 10.45 9.08 16.04 9.91 57.51

ASS 41.53 46.73 41.38 41.39 40.45 8.27 24.29

ANS 55.47 58.49 57.53 45.16 53.91 6.78 18.16 70.48

C5S 31.97 31.36 35.39 60.31 46.57 5.45 17.19 29.48 36.24

C10S 29.87 32.25 31.23 46.68 37.08 5.56 28.31 29.88 35.58 51.45

DS 47.32 50.91 50.51 71.26 60.04 5.79 20.73 44.88 55.45 71.51 62.90

51

Appendix 4. Similarity matrix of summer samples. A. Environmental data, B. Species

composition and C. Combined Environmental and Species composition data.

AS AN AC C5 C10 D

AS

AN 97.9

AC 96.73 94.71

C5 87.98 88.19 85.09

C10 92.71 92.88 90.12 94.81

D 92.53 92.7 89.29 94.99 99.1

AS AN AC C5 C10 D

ACS

ASS 17.41

ANS 10.21 58.52

C5S 11.19 9.37 11.89

C10S 22.93 11.69 14.55 39.8

DS 14.06 24.12 31.05 61.33 50.8

ACS ASS ANS C5S C10S DS

ACS

ASS 24.24

ANS 18.13 70.59

C5S 17.13 29.81 35.53

C10S 28.25 30.02 35.04 51.46

DS 20.65 45.42 54.29 71.36 62.89

B.

C.

A.

52

Appendix 6. Correlation matrix of protein expression pattern between individuals of fish Leiognathus splendens

1AC 2AN 3AS 4C5 5C10 6D 13AC 14AN 15AS 16C5 17C10 18D 37AC 38AN 39AS 40C5 41C10 42D

1AC

2AN 93.88

3AS 96.61 93.05

4C5 94.75 92.06 92.97

5C10 94.55 91.67 93.87 91.71

6D 95.08 91.69 94.66 92.38 97.77

13AC 84.43 87.35 84.51 84.72 83.90 84.23

14AN 93.36 96.85 91.57 91.80 92.42 92.21 87.35

15AS 95.48 91.56 95.16 91.54 97.10 96.86 83.58 91.67

16C5 94.59 91.70 93.12 98.01 92.00 92.34 84.84 91.39 91.84

17C10 94.33 91.33 93.89 91.31 99.06 97.41 83.75 91.89 96.97 91.52

18D 94.80 91.07 93.95 91.12 95.62 96.34 83.93 92.37 94.61 91.36 95.30

37AC 94.38 91.69 94.98 90.37 95.42 94.63 83.17 91.16 95.81 90.00 95.44 92.82

38AN 95.43 92.14 94.78 91.88 93.60 93.71 83.85 91.11 94.65 91.39 93.84 92.21 96.55

39AS 96.02 92.28 96.77 91.92 94.41 94.14 83.94 91.03 95.73 91.57 94.48 92.92 96.61 96.72

40C5 96.44 93.15 95.83 93.11 92.97 93.31 84.10 92.02 94.29 92.66 92.97 92.40 95.84 96.83 96.45

41C10 93.72 90.73 94.25 90.79 96.11 94.99 83.49 90.60 95.67 90.75 96.46 92.82 95.93 93.80 94.89 93.05

42D 93.08 90.60 93.26 90.52 96.29 95.58 83.32 90.33 95.74 90.19 96.32 92.88 95.54 93.41 94.56 92.91 96.09

53

Appendix 7. Correlation matrix of protein expression pattern between individuals of fish Apogon fasciatus.

43AN 44AC 45AS 46D 19AC 20AN 21AS 23C10 24D 7AC 8AN 9AS 10C5 11C10 12D

43AN

44AC 98.11

45AS 94.12 93.33

46D 96.28 97.42 91.64

19AC 87.88 88.59 84.60 89.45

20AN 85.50 85.92 82.74 86.88 96.00

21AS 84.60 85.30 82.86 86.43 93.84 95.40

23C10 87.61 88.12 84.89 88.81 97.16 96.73 94.15

24D 84.44 84.98 83.31 86.41 94.43 96.24 93.65 95.42

7AC 91.59 91.99 90.77 93.04 91.28 89.77 89.73 91.31 89.06

8AN 90.08 90.05 86.24 90.63 94.32 92.30 90.95 93.77 90.55 93.14

9AS 88.02 89.08 90.29 90.21 89.93 88.42 89.31 90.62 89.06 93.61 90.30

10C5 86.79 87.58 90.89 87.91 85.80 83.85 84.28 86.31 84.59 90.72 86.49 93.56

11C10 80.92 82.01 85.35 83.11 84.09 83.75 83.82 84.16 83.65 86.28 84.06 92.35 91.18

12D 90.32 91.18 88.63 91.36 93.24 91.43 90.04 93.61 90.14 93.64 94.53 93.11 90.73 87.55

54

Appendix 8. Correlation matrix of protein expression pattern between individuals of fish Engyprosopon multisquama

47AN 48AC 49AS 50C10 51D 31AC 32AN 33AS 35C10 36D 25AC 26AN 27AS 28C5 29C10 30D

47AN

48AC 91.25

49AS 94.61 89.04

50C10 91.76 86.82 92.77

51D 91.49 86.53 92.37 94.31

31AC 91.42 88.80 89.82 87.17 86.38

32AN 88.55 86.35 87.60 88.51 87.82 91.14

33AS 90.09 88.19 90.40 88.74 86.55 88.24 85.12

35C10 86.63 85.38 86.78 85.72 85.40 88.92 86.22 85.91

36D 91.30 85.47 90.60 92.03 91.38 89.08 85.63 88.02 87.75

25AC 83.37 86.85 80.99 79.99 78.91 85.75 86.98 81.34 86.11 78.39

26AN 88.21 86.42 84.73 84.59 82.71 84.23 81.75 88.00 83.04 83.73 87.09

27AS 88.36 86.63 87.22 86.26 84.24 87.27 83.28 89.76 84.09 85.73 85.24 93.89

28C5 86.85 86.37 85.32 84.35 84.86 85.99 85.05 84.17 88.56 83.96 88.44 87.07 87.76

29C10 85.24 85.85 83.51 86.66 85.09 87.54 87.61 81.98 86.51 83.62 87.67 83.95 85.65 87.80

30D 84.57 84.67 82.66 84.71 85.98 85.07 86.41 79.98 86.51 81.89 87.46 82.48 82.67 90.86 93.39

55

Appendix 9. Correlation matrix of protein expression pattern between individuals of crab Portunus hastatoides

58AN 59AC 60AS 61C5 62C10 63D 52AN 53AC 54AS 55C5 56C10 57D 64AN 65AC 66AS 67C10 68D

58AN

59AC 95.50

60AS 96.29 94.87

61C5 95.72 94.31 93.19

62C10 95.04 94.60 92.50 97.13

63D 91.82 88.27 88.81 93.65 92.83

52AN 92.22 93.18 90.94 91.89 91.52 88.92

53AC 90.67 91.17 89.22 92.16 92.06 91.10 95.43

54AS 86.66 89.52 88.70 85.49 86.29 80.23 90.85 88.39

55C5 89.66 92.64 89.22 91.12 92.00 85.96 92.56 91.49 91.01

56C10 91.94 94.95 93.32 90.63 91.50 85.47 95.17 92.25 93.87 93.95

57D 93.86 94.82 94.52 91.59 91.73 87.16 94.26 92.04 91.56 91.50 95.22

64AN 93.79 93.34 91.61 93.94 93.32 91.29 94.93 94.91 87.06 90.97 92.65 93.74

65AC 93.75 93.95 94.03 91.35 90.60 86.50 91.08 88.36 90.20 89.53 92.68 95.01 91.63

66AS 96.27 95.42 96.26 93.53 93.04 89.81 92.06 90.14 89.28 90.29 93.82 95.50 93.04 95.78

67C10 95.87 94.78 94.14 94.30 93.53 90.94 93.34 91.37 86.73 90.20 92.53 94.01 94.64 93.67 95.65

68D 96.14 95.14 95.54 93.26 92.56 89.21 91.91 89.98 88.88 90.05 93.73 95.81 93.06 95.86 97.47 96.23