Estuarine, Coastal and Shelf Science (1985) 2lr 5ll-537

I1

I

i

Annual Variation in the Nocturnal NektonAssemblage of a Tropical Estuary

NormanJ. Quinno and Barbara L. KoiisDFisheries Departmento and Department of Chemical Technologgb, Papua NewGuinea Unioersity of Technology, Lae, Papua New Guinea

Receiaed 23 October 1983 and in revisedform 4 March 1985

Keywords: Oceanography; Fourier analysis; time-series; salinity; fish; watertemperature; regression analysis; Papua New Guinea

A nocturnal demersal nekton assemblage was sampled fortnightly for two yearsat five sites in the Labu estuary using a 3 m beam trawl with a3.2 cm mesh net.Forty-eight species were caught, totalling 31 458 individuals with the five mostabundant species comprising over 950,1 of the catch. Using multiple regressiontechniques with Fourier transformations, the mean number of species, S, themean abundance, N, and mean weight, W, wete found to conform to a regularannual cycle with maxima in April and May. Seven of the 11 most abundantspicies demonstrated regular annual cycles of abundance. S, N and W weregreatest in the wider, middle sites and lowest in a shallow, stagnant side branchof the estuary. Catch weights and abundances were significantly correlated withphysical data.

Salinity and temperature values in the estuary exhibited an annual cycle withmaxima occurring in February/March. The annual thermal variation of surfacewater outside the estuary followed a similar cycle. The salinity at the mouth ofthe Markham River is lowest during January/February, which correspondswith the rainy season in the Markham River catchment. Significant annual vari-ation existed between years in estuarine bottom salinity and salinity values inLabu Bay.

Several species exhibited a greater variation in abundance and mass betweenyears than within years. This supports the hypothesis that in the tropicsbetween-year variation in coastal marine biotic communities is greater thanwithin-vear variation.

Introduction

Knowledge of the fish inhabiting Papua New Guinea estuaries is largely confined to listsof species (Munro, 1967; Liem & Haines, 1977; Haines, 1979; Berta et al., 1975;Collette, 1983), taxonomic descriptions (Collette, 1982) and studies of the biology ofbarramundi, Lates calcarifer (Moore, 1982; Moore & Reynolds, 1982; Reynolds &Moore, 1982). Studies of fish of the Huon Gulf and seasonality of Papua New Guineaestuarine fish are non-existent. There are only a few published accounts of the fishfaunas of the tropical estuaries of this region, e.g. Singapore (Thia-Eng,1973) and NorthQueensland (Blaber, 1980).

The importance of estuaries as feeding and nursery grounds for fish and the need toassess the effects of existing or potential alterations by man have resulted in increased

027 2-77 14185 I 1005r l + 27 $03.00/0

5ll@ 1985 Academic Press Inc. (London) Limited

512 N. J. Quinn {s B. L. Kojis

attention to these areas throughout the world. Recently interest in mangrove communi-ties in Papua New Guinea has been stimulated by the prospects of three major develop-ment schemes - the Purari hydroelectric power scheme, proposals by Japanesecompanies to develop the large unexploited mangrove resources of the Papuan Gulf andthe Lae port expansion.

Mangrove and coastal ecosystems in Papua New Guinea are relatively undisturbed.Local villagers use mangroves as a source of building material and firewood, butthe population density is low and the effect is small. Industrial use of mangroves isalso limited; only 19400 tons of mangrove bark were exported from I89l to 1970(unpublished report of the Office of Forestry, undated, entitled Mangroae Stands:Papua New Guinea). There has been no recent increase in mangrove exploitation.The only full-time commercial fishery is in the Gulf of Papua where increases incatches are recent (1981:. 32.8 tonnes fis}e, 4-7 tonnes crabs; 1982: 68'7 tonnes fish,3'0 tonnes crab) (Anon., 1983). As utilization of these virtually untouched coastalecosystems is inevitable, a baseline of information is necessary from which comparisonscan be made.

This study describes the trawlable demersal fish and crustacean communities of theLabu estuary adjacent to the proposed expansion of the Lae wharf and discusses spatialand temporal changes in abundance and seasonality in relation to variations in abioticparameters.

Additionally, the fauna from the estuary is compared with that of a subtropical estuary(Serpentine Creek, Brisbane, Queensland, Australia) (Figure l).

lVorkhom

t40 "E

PopuoNewGuineo Loe

t

I

Queenslond

Auslro lio

Bri s bo ne

140"8

expo ns ion

Vrl qqe

HuonGui f

AI

North

ltlkm

Figure l. (a) Regional map showing Lae, Papua New Guinea and Brisbane, Australia.(b) Labu estuary trawling sites. Trawl sites are numbered. Sites where hydrologicaldata were collected are indicated with X.

Porl

N octurnal nekton assemblage aariation 513

Materials andMethods

Physical data samplingSampling was carried out fortnightly from June 1980 to May 1982 from 17.00 to 23.00hat seven sites. Dissolved oxygen, temperature and salinity were measured in situ using a'Kahlisco' conductivity meter with thermistor and a dissolved oxygen meter at each site.Measurements were taken on the surface and near the bottom at the completion of each

trawl. S7ater tr€ursparency was measured using a 20 cm diameter Secchi disc. Rainfalldata for the years 1973 to 1982 were obtained from the Civil Engineering Department atthe Papua New Guinea University of Technology.

Biological samplingOn the basis of a pilot survey from March to June 1980 five sites were sampled on a

fortnightly basis from June 1980 to May 1982. A 3 m beam trawl with a stretched meshof 3'2cm, identical to that used by Quinn (1980), was trawled heading upstream forabout 300m at each site for 15 min at approximately one knot. The beam trawl waschosen because it is an active fishing gear that yields quantitative results which can becompared with work done at lower latitudes in Queensland, Australia.

All sampling methods are biased because any one type of equipment is more suitablefor catching some species than others. For example, in this study the beam trawl caughtmostly bottom fish while surface feeding (e.g. gar) and schooling (e.C. mullet) fish werenot caught at all, although they were present in the estuary.

Sampling was carried out on 4l out of a possible 48 dates. Inclement weather andother difficulties account for the missing sampling sets. $Tithin each sampling date not allsites were trawled owing to snags, the presence of too many jellyfish (Catostylus sp.) andrequests by villagers to forego trawling a site when numerous gill nets had been set.Approximately 97o/, of sites were trawled within the sampling dates.

To reduce collecting variability, trawling began at Site I about l-2 h after sunset.Replicate trawls were not taken owing to time limitations imposed by a suspected dielvariation in the fauna. This is discussed in greater detail in Quinn & Koiis (1983). Lunarphase was considered a controlled variable since sites were trawled each fortnight duringnew and full moons (Quinn & Kojis, 1984).

Captured fish were counted, standard length (S.L.) measured to the nearest centi-metre and returned to the water. Samples of 12 species comprising the most abundanttaxa were collected and brought back to the laboratory for length/weight measurements.From these data a power curve equation for the length/weight relationship was derivedusing a Texas Instruments power curve programme. Veight estimates were made bytaking the median value for a species' size class and using the length/weight equation forthat species.

Unfamiliar fish were preserved for subsequent identification. The genus Upeneas hadtwo morphologically similar 'species' that were difficult to separate in the field; one isprobably a new species (Johnson, personal communication). Authorities used in theidentification of fish were Munro (L967) and Carcasson (1977). Specimens were lodgedwith the Queensland Museum, Brisbane, Australia.

Analysis

D escriptia e statisticsThe mean total number of individuals per trawl is designated by N, the mean total

514 N. J. Quinn {x B. L. Kojis

weight by lV and total number of species by S and are termed sample parameters. Theabundance and weights of individual species are identified by n and z{, respectively. Intemporal analyses the means were determined across sites, while for spatial analysesmeans were calculated through time. The amplitude of the coefficient of variation (C.V.)was used as an index of the degree of heterogeneity of the estuarine water and biota.

H armonic r egr e s sion p erio di ci tyIn ecological studies two types of non-random time-series patterns can occur. The firstmay involve a series of observations which show repetition although no apparent regu-larity. These are difficult to characterize and often reflect randomly fluctuating orirregular hydrological conditions. The second, and the one considered here, involves a

series of observations with regular repetition through time. Biotic cycles of this form are

believed to be caused by regular variation in abiotic and/or biotic factors and usuallypersist for extended periods.

\Ve fitted our data to a Fourier transform model using sine and cosine terms, becausethey provide a powerful tool for describing periodic phenomena. Bliss (1958) has pro-vided a comprehensive description of harmonic regression analysis with examples fromagriculture. A similar type of analysis was used by Maddock & Swann (1977) to investi.-gate trends in sea temperature and climate, by Hamon & Kerr (1968) to investigatethe time variation in the EaSt Australian current and by Quinn (1980) for the hydrologyof a sub-tropical estuary. Only regressions over the 95o/o confidence level were acceptedand plotted.

Studies of periodicity using mathematical models are uncommon and relatively recentin marine ecology. Platt & Denman (1975) in their review of spectral analysis in ecologycited only I I studies, of which seven dealt with marine organisms. Bulmer (197 4) used amixed model, which included periodic terms, to analyse a l0-year cycle in Atlanticsalmon angling records. Recently these techniques have been applied to the Australianmarine fauna (Stephenson, 1978, 1980a, 1981; Stephenson & Burgess, 1980; Stephensonet al.,l982a,b; Gilmour & Stephenson, 1983).

Multiple regressions

Studies analysing the effect of several abiotic parameters on fish (Risk, 1972; Oviatt &Nixon, 1973; Quinn, 1980) and prawn (Stephenson, 1980b; Stephenson & \Tilliams,1981) populations have only recently been analysed using statistical methods.

As the composition of the nekton may be the result of physical conditions during theprevious several months, regressions were also performed on lagged physical data. Inthis analysis only temperature and salinity are used to estimatey values, the abundanceor weight of nekton populations. The lagging interval used ranged from one to fivefortnights. As the lag increases, the number of valid observations declines. Given thelimitations of the existing data set, five fortnights (2.5 months) was the longest lagexamined. If more biological knowledge about the populations had been available,further analyses with increased lags might have indicated which stages of the life cycleare most affected by certain abiotic factors (Stephenson & \Tilliams, 1981).

V ariations betw een y ear s

Using a paired r-test, variations in physical and biological data between years wereinvestigated. Similar lunar phases from June 1980 to May 1981 were compared withJune 1981 to May 1982. Owing to missed sampling dates in either of the years, a subsetof 15 lunar pairs were available for comparison.

Nocturnal nekton assemblage aariation 515

Results

Phgsical data

Estuarine sites

The mean salinity and coefficient of variation for the five trawl sites per sample time are

plotted in Figure 2. The highest recorded bottom salinity was 30'5%o in February 1981,

while the lowest was 3'9%o in October 1981 (range 28'6%o; annual mean over all times :18.2%o; C.V.:28'60/.; N:38). Surface and bottom salinities followed annual cycles

which peaked in February (Table l). Mean surface salinity varied from 0'6%o to 26'6%o

(range 26'0%'; r : 8'0%; C.V. : 75'7o/"; N : 39). The salinity range between sites was

greatest in August/September.Bottom temperatures averaged over sites for each date were lowest in August 1980

(26'5 "C) and highest in November 1980 (32'3 "C), a range of 5'8 "C (Figure 3)' Both the

surface and bottom temperatures followed an annual cycle that peaked in February. Thesurface temperatures ranged from a maximum of 32'l 'C in November 1980 to a

minimum of 24'4 'C in August 1980 (range 7'7 "C; x : 29'2 'C; C.V. : 7'0'/.; N : 40).

Bottom water temperature was slightly warmer (x : 29'6 'C; C.V. : 4'9'A;N : 39).

Dissolved oxygen values followed no annual cycle (Figure 4). Mean surface values

ranged from 2'6mgl-1 to saturated at about 6'2mgl-1 at 30'C (range 3'6mgl-1;i:3'7 mgl-1; C.V.: 23'5'/,; N:24). Bottom readings varied from 0'2mgl I to

3'8mgl-1 (range 3'6mgl-1; x :2'lmgl-1; C.V. :45'7'/Lt N:24.). r$fater trans-parency varied from 0'9 to l'7m G: l'2m; C.V.: l3'l%) with no annual cycle(P>0.05) (Figure 5). Hydrological differences between sites were calculated from the

o

o\

=.:oU)

c.9

,oo

o

c9.9

oO

ASONt980

J JAI 98r

JFMA1982

Figure 2. Times series of surface and bottom salinity mean values for five sites in theLabu estuary. -, predicted salinity values;

-, observed values; -----, coeffrcient

of variation.

516 N. J . Quinn Cx B. L. Kojis

TABLE 1. Regression coeffcients for hydrological observations from Labu estuary - hvesite mean

PR2iAoMBA

Month ofmaximum

N value

Surface temperature, oC

Bottom temperature,'CSurface salinity, %o

Bottom salinity, %o

Surface dissolved O, mg I t

Bottom dissolved O, mg l-lTransparency, m

-1.67 0.01 29.061.26 -0 0l 29.97

- 6.98 -0.12 11.67

-5.76 -0'22 t:u

- 1.13

-0 6l-2.38-0.47

0.53 <0.0010.41 < 0'0010.61 < 0.0010.56 < 0.0010.17 N.S.0.r2 N.S.0.13 N.s.

Early Feb.Feb.Feb.Late Feb.

39383838232337

Where l, B, Mo and constant are variables in the equation:

Y -- \A^ + Asin( zn-J-\ * r.o, ( r"=! \ *r,,t\ 25.64) \ 25.64 )

Trigonometric functions are in radians.

O

+odE

F

co;.9o

o

.9

;ooO

80

60

Figure 3. Time series of surface and bottom water temperature mean values for fivesites in the Labu estuary. -, predicted temperature valuesl

-, observed values;

----, coefficient of variation.

mean over time (Table 2). As expected the site nearest the mouth of the estuary had thehighest mean bottom salinity, 20'0%o, while sites further upstream had lower salinitieswith site 5 having the lowest at L7.2%o. Mean surface salinities followed a similar patternranging from9'60/oo at the mouth to 6'6%o at site 5. Coefficients of variation were similarfor all sites with the surface salinities coefficients being over twice as high as bottomsalinities.

N octurnal nekton assemblage aariation 517

c.oa'ao

o

.o

.9

oU

ioE

co0

0Eo

o

i5

JJ A SOND J FMAMJ J ASONDJ FMA1980 r98t t982

Figure 4. Time series of surface and bottom dissolved oxygen mean values for five sitesin the Labu estuary.

-, observed valuesl - - - -, coefficient of variation.

J J A S O N D J F M A M J J A S O N D J F MAt980 l98r t9 82

Figure 5. Time series of water transparency mean values for five sites in the Labuestuary.

-, observed valuesl - - - -, coefficient of variation.

Mean surface temperatures were approximately uniform (29.5'C) for all sites (Table2). Mean bottom temperature for site 4 was about I 'C higher than the other sites. Thissite was furthest upstream and in an isolated section of the estuary with no tributaries.The coefficient of variation was less for bottom than surface temperatures.

Mean surface dissolved oxygen readings were uniform around 34mgl-r (Table 2).Sites I and 2 had similar mean dissolved oxygen readings of about 3 mg I - 1, while sites 3

and 5 were slightly lower. Site 4 had the lowest dissolved oxygen readings and occasion-ally hydrogen sulphide odours were present. Bottom reading were more variable thansurface readings.

Mean transparency ranged from l'1 to l'3 m (Table 2). Turbidity was slightly greaterat site I than at the other sites, probably owing to the increased effect of tidal mixing.

There was greater variability in the hydrological observations through time thanthrough space (Table 2). The bottom temperature C.V. was l'3o1" between sites and

c,9

40 _eo

200c.9

ni;ooO

E2

coolocoFo

J

518 N. J. Quinn €s B. L. Kojis

T tstn 2. Summary of hydrological data for five sites in Labu estuary

Physical data Mean C.V. N

Site 1

Surface temperature,'CBottom temperature, oC

Surface salinity, %o

Bottom salinity, %o

Surface dissolved oxygen, mg I 1

Bottom dissolved oxygen, mg I 1

Transparency, m

Site 2Surface temperature,'CBottom temperature, oC

Surface salinity, %o

Bottom salinity, %o

Surface dissolved oxygen, mg I - 1

Bottom dissolved oxygen, mg I - I

Transparency, m

Site 3Surface temperature,'CBottom temperature, oC

Surface salinity, %o

Bottom salinity, %o

Surface dissolved oxygen, mg I 1

Bottom dissolved oxygen, mg l- 1

Transparency, m

Site 4Surface temperature, oC

Bottom temperature,'CSurface salinity, %o

Bottom salinity, %o

Surface dissolved oxygen, mg I I

Bottom dissolved oxygen, mg l- 1

Transparency, m

Site 5Surface temperature, "CBottom temperature,'CSurface salinity, %o

Bottom salinity, %o

Surface dissolved oxygen, mg I - 1

Bottom dissolved oxygen, mg I 1

Transparency, m

29.329.5

9.519.84.13.41.1

29.429.58.3

182372.91.2

29.4295

8.318.23.72.9r.2

30.030.4

6.61873.80.97.3

28729.46.7

17.2))t.47.3

6.45.3

9t.724.9229738t7.4

7.85.5

87933.726.561.815.5

40383835232337

4l393936)72338

5

5

55

5

5

5

7.9 4l5.6 39

64.3 4025.7 3727.6 2049.8 2026.0 37

66 41

5.5 397t.5 4032.4 37222 2357.1 2375.5 37

6.6 4t5.5 39

71.5 4032.4 3722.3 23571 2315.6 37

Mean ztalues through sitesSurface temperature,'C 29.2 1.4Bottom temperature, 'C 29.6 1.3Surface salinity, %o 7.9 l3'9Bottom salinity, %o 18.4 4.6Surface dissolved oxygen, mg 1- 1 3.7 4.6Bottom dissolved oxygen, mg I - 1 2.3 42.1Transparency,m 1.2 62

N octurnal nekton assemblage aariation 519

TABLE 3. Comparison between years of hydrological observations in Labu estuaryusing a paired l-test

Year One Year Two

Physical data MeanStandard

ertorStandard Degrees of

Mean error freedom

Surface temperature,'CBottom temPerature, oC

Surface salinity, %o

Bottom salinity, %o

Dissolved O, surface, mg l-tDissolved O, bottom, mg 1- 1

Transparency, m

29.229.6

6.215.84.2241.2

0.400.230.980'840.590.320.05

29.029.9

8.820.93.62'0t-3

0.670.512.08r.330.300.470.04

t4t3t3t2

5

5

t3

N.S. 0.50N.S. -0.74<0.09 - 1.87<0.01 -3.49N.S. O.75N.S. 0.56N.S. -O.49

EE

c'ot

JFFigure 6. Weekly rainfall for 1973-81with 95%, confidence limits.

about 5.51o through time. Salinity was similar with over six times the variability overtime as space. Bottom dissolved oxygen was the only parameter with nearly equal varia-bility in space and time. Both surface dissolved oxygen and transparency had a greater

temporal than spatial variability.Comparisons between years using a paired t-test demonstrated significant differences

for surface and bottom salinity values (Table 3). The mean surface salinity during year

one was 6.2%o and rose to 8'8%o during year two. Similarly, for bottom salinity the secondyear mean was higher (21'0%,) than for year one (15'8%0).

RainfallThe mean weekly rainfall for the 10 years 1973-1982 is plotted in Figure 6 (I:74'5 mm;C.V. : 20'2o/o; N : 519). The mean weekly rainfall for 1981 and 1982 was 7l'6 mm and58.9 mm, respectively. The annual rainfall varied between 260 and 520 cm during the

lO-year period. The recorded rainfall from June 1980 to May 1981 was significantlygreater than from June 1981 to May 1982 (N : 12, t:3'21, P<0'01). Neighbouring

ro t5 ?o ?5 30 35 40 45 50M A M J J A SO N D

520

Tesrr 4. Analysis of variance of mean weekly rainfall

Source ofvariance

Degrees of Mean sumfreedom ofsquares

1.2r4

r.773

localities such as the Siassi Islands (120 km north-east of Lae) and stations up theMarkham Valley reported drought conditions during these latter months.

There was a significant difference in mean weekly rainfall between years (P<0.02),but there was no significant difference in mean weekly rainfall (P>0.05) between weeks(Table 4). Rainfall was variable and could be considerable during any week of the year!(Figure 6).

Biological ob serzt ations

D es uiptizt e statistics

In 4l trawling sets from June 1980 to May 1982 (24 months) 3L 458 individuals,weighing over L77 kg, from 38 fish species, nine crustacean species and a scyphozoanwere caught. Over 95o/o of the individuals belonged to five species (Table 5) while 25bony fish species were represented by more than l0 individuals. Most of the fish caughtwere juveniles. These were typically brackish water forms capable of tolerating a widerange of salinity by secreting a thick mucous layer over the skin (Equula), by possessinglarge scales (Gerres, Lactarius) or by having other modifications to minimize osmoticchanges (Thia-Eng, L973). Laryer fish were relatively few.

No truly freshwater fish were caught. Scatophagus argus, Toxotes jaculator andAnodontostoma chacunda, which could tolerate fresh and estuarine conditions, were col-lected occasionally. The common marine fish that entered the estuary were the anchovy(Stolephorus), the snapper (Lutjanus), the grunter (Pomadasys) and the carangid(Caranx). Only large individuals of some of the less common species were caught, suchas Arothron reticularis.

The length/weight equations for 12 fish species were very highly significant (Table 6)and were used to estimate catch weight. Eleven species of fish and prawns, each with aweight greater than lo/o of the total, account for about 97t/o of the total mass caught(Table 7).

The overall mean number of individuals caught per night (1.25h total trawling time)was 796 individuals weighing 4'3kg with a mean of 14.0 species and a catch rate of3'4 kg h- 1 trawling.

From interviews with the natives it was found that 31 of the 38 fish species and fivecrustacean species caught in the beam trawl were eaten. The Appendix contains thescientific names of the catch and an indication of those locallv eaten.

By yearYearResidualTotal

By weekrVeek

ResidualTotal

8

458466

5l335386

12855.5854000.1 I I4152 136

4927.2974t99.8704279.189

Nocturnal nekton assemblage aariation 521

TABLE 5. Rank order and per cent abundance for species trawled in the Labu estuary.Authors of species are given in Appendix along with an indication of which specieswere eaten

Rankorder

Number ofindividuals

%oftotal

CumulativeSpecies

1 Equulaequula2 Metapenaeus demani3 Secutor ruconius4 Gazza achlamys5 Ambassis interruptus6 Polydactylusmicrostomus7 Pseudosciaena weberi8 Apogon amboinensis9 Lactarius lactarius

l0 Caranx sexfasciatusI I Gerres filamentosus12 Apogon hyalosoma13 PalaemonidaeL4 Lutjanusjohnil5 Pomadasys argyreus16 Upeneus sp.17 Anodontostomachacundal8 Stolephorusbataoiensisl9 Upeneus oittatus20 Setipinna papuensis2l Lutjanus ehrenbergi20 L. maxweberi23 Eleotris c.f. macrolepis24 Archamiaburoensis25 Arothronreticularis26 Lutjanusargentimaculatus

for each of the remaining species, fewer than tenindividuals were caught

Total 31458

H armoni c p erio di city analy si s

As with the abiotic data, multiple regression incorporating the Fourier transformationwas performed on each of the 1l most abundant and massive species to ascertain theirconformity to an annual cycle and to determine the period of peak abundance or mass.

Seven species had annual cycles of abundance (Table 8). Five of these species were mostcommon in the five months ]une to October. Pseudosciaena ueberi had no cycle, but sig-nificantly increased in abundance through time. The most abundantfish, Equula equula)

is most abundant in July (Figure 7). Secutor ruconius, rank order 2,was most abundant inFebruary/March while Metapenaeus demani peaked in November/December.

Five species had changes in the weight of the catch that corresponded to annualchanges (Table 8). Three of these species also had maximum peaks from June to August.The most massive population, Equula equula, has its greatest catch of individuals and

mass in July/August. Similarly, the largest catches of prawns are in November/December. Catches of Arothron reticularis, weight rank order 2,were too infrequent andirregular to fit the model.

2210632592860I 199584190186169t2tt02l0l83756461

37373t3t28)')2ll8l7l5ll

70.310.39.13.81.90.6060.5o.40.30.30-30.20.20-20.10.10.10.10.1

<0.1<0.1<0'1<0.1<0.1<0.1

70.380'689.793.595.496.096.697.197.597.898.198.498.598'798.999.099.199.299.399'4

>99'4

522 N. J. Quinn U B. L. Kojis

Tenrr 6. Length/weight relationships for Labu estuarine fish

Species NP

Ambassis interruptusAno dont o s toma chacundaApogon hyalosomaEquula equulaGazza achlamysGerres filamentosusLactarius lactariusP o ly d a c ty lus mi cr o s t omusPomadasys argyreusPseudosciaena weberiSecutor ruconiusS tolephorus bataztiensis

l'50 x 10-s1.03 x l0-s6.82 x l0 6

5'75 x 10 s

6'13 x 10 s

3.48 x l0-s3 01 x lO-s3.48 x 10 s

1.74 x l0-s1 96 x l0-s4.53 x 70-s5.57 x l}-s

3.193.223.382-892.792.952952'923133012.30).61

o.9920.995o.9540.9770.9650.9940.9920.974a 9960.9700'7800.986

<0.001< 0.001< 0.001< 0.001< 0'001<0.001<0.001<0.001< 0.001< 0.001< 0.001< 0.001

t72530

248112

12

421022346418

Tesrt 7. summary statistics for estuary nekton populations with the highest weights

Species

Rankorder

numberby

weight

Numberof

samplingtimes

trawled

Meancatchper

sampleddate (g)

Catchweight

(g)

o/

oftotal

weight

Equula equulaArothron reticularisMetapenaeus demaniGazza achlamysSecutor ruconiusPolydacty lus microstomusAmbassis interuptusLurjanus johniLutjanus maxweberiLactarius JactatiusPomadasys argyreusApogon hyalosomaHimantura granulataApogon amboinensisGerres filamentosus

I2345

6

78

Ii0t1T2

13

I475

411l413237333822

5

2923

I)624

469.7115.535.641.528.527.4r8.877.43l .l908.17.25.85.25.2

96280232073t06850583043853865357026901855I 660r495r20010751070

59 1

14.5454.23.62.72.4

1.71.1

1.00.9o.70.7o.7

The total weight of the catch, total number of fish and number of species had anannual cycle with the grearest carch occurring in June/July (Table g).

In parametric statistical testing, the most basic assumptions are: (l) that data arenormally distributed, and (2) thar variances are homogeneous (Sokal & Rohlf, 1969). Forsignificance testing in cyclical regressions it is necessary that the raw data be normallydistributed since significance testing involves paramerric distributions (Bliss, 1970).Recently, Gilmour & Stephenson (1983) specifically noted that: (l) residuals, or rheunexplained proportion of the variation in data after cyclical regression, should benormally distributed, and (2) that the magnitude of residuals should be independent ofpredicted (explained) components. The reason for transforming the data was that for the

N o cturnal nekton as s embl ag e a ari ati on 523

Tenrr 8. Regression coefficients for annual cycles in Labu estuary nekton

SpeciesPeak

month BA M ll2Ai P

Catch weightEquula equulaArothron reticularisMetapenaeus demaniGazza achlamysSecutor ruconiusP o ly da c ty lu s mi cr o s t omu s

Ambassis interruptusLutjanus johniL, maxwebeiLactarius lactariusPomadasys argyreus

Number of individualsEquula equulaMetapenaeus demaniSecutor ruconiusGazza achlamysAmbassis interruptusPolydacty lus microstomusPseudosciaena weberiApogon amboinensisLactarius lactariusCarnax sexJasciatusGerres fi,lamentosus

Summary parametersll/sN

Jul/Aug 275'0

Nov/Dec 17'1

f"t7tr{",ry:'Y-

Jul/Aug 56.6Nov/Dec -7 1

Feb/Mar

Iun 0'8

Jr'rr/errgJuVAug 0'4

Aug/Sep

Jul 123 5

Jul 15Iun 25'8

2u4 y

-r, rj' r43.4 r.3

11.9

0.5 -0.104

0.3

t33 0t.7

269.7 < 0.001 0.68N.S. 0.20

t5.7 <0.01 o.42N,S. 0.13

30.4 < 0.01 0.4021.8 <0.05 0.38

N.S. 0.24N.S. 0.10N.S. 0.16

8 6 N.S. 0.40N.S. O.23

74.0 <0.001 0.7515.7 < 0.01 O'4214.8 < 0.05 0.32

N.S. o.t4N.S. 0.19

0.1 < 0'001 0.55

-0.8 <0.001 0.64t-7 < 0.001 0.620.6 <0.001 0 61

N.S. 0.180.5 <0.05 0.31

427.8 < 0.01 O.5412.8 <0 001 0.5880 I <0.01 0.50

ooj!.=!.=

o

oEfz

_erayv.\o

200

too

A, B are the cyclic coefficients in the Fourier equation, M is the linear coefficient in theFourier equation, and ll2Aoisthe constant value in the equation.Peak month is the period of predicted maximum values.There were 25 64 sampling periods in a year.Where 1,8, M and constant are variables in the equation:y : I 12 Ao + A cos(2t 125'64) + B sin(2t125'64) + M (t).Trigonometric functions are in radians.

--a

s

JJ Ar980

JF M

I 981DJ F

r982

Figure 7. Time series of the mean number of individuals of Equula equula for five sitesintheLabuestuary.-,meannumberofindividualspersite;--------,predictednunber of individuals.

524 N. J. Quinn €c B. L. Kojis

Tesrp 9. Regression coefficient for catch weight of ,Equula equula and transformed data

Transformation

Month ofmaximumoccurrence iAoM

Square root4th rootlog (N+ 1)

None

JulJul/Aug

JulJu1/Aug

t5.43 0 738 <0.0013.87 0.762 < 0.0013.32 0-776 < 0.001

269.7 0.683 <0.001

most effective use of this technique the data should be normally distributed. A furtherdesirable feature of the transformation used was that the explained variation in datashould be as great as possible, i.e. r should approach 1.0 (Gilmour & Stephenson, 1983).

The fourth root and log (n -t 1) transformations reduced the skewness and kurtosis tothat approximating a normal distribution and, hence, were used here. It is appreciatedthat the choice of transformations is somewhat arbitrary and that other transformationsmight have been used, such as those described by Box and cox (1964). However, rhechosen transformations were considered reasonable in meeting the assumptions of themathematical models.

Recently, Gilmour & Stephenson (1983) investigated two approaches for selectingBox-Cox transformations to apply to data used in cyclical regressions, but neglected todetermine experimentally the effect the transformation had on the period of greatestoccurrence (commonly termed phase angle or I-u"). Since the primary purpose in theuse of cyclical regressions in ecological studies is to elucidate periods of greatest occur-rence) extended investigations of various transformations to increase r without know-ingly increasing the certainty of the phase angle are likely to be of marginal use and werenot pursued.

Equula equula catch weights were used to assess the effect of transformed data on thedetermination of annual cycles. The use of any of the transformations, square root,fourth root and log(n -t 1), resulted in increasing the correlation coefficient withoutappreciable changes in the month of maximum occurrence (Table 9). Transformed dataenhanced the fit to the cycle (increasing r) without altering the phase angle. By increasingthe correlation coefficients, several smaller populations exhibited annual cycles. As thesespecies are uncommon, the use of the transformations does little to increase ourknowledge of the estuary fauna.

Multiple regressions with catch dataStepwise, forward inclusion regressions between N, S and IZ resulted in several signifi-cant relationships. S was correlated with bottom salinity, N with surface temperatureand W with surface salinity (Table l0).

Four species abundances had a significant relationship with unlagged hydrologicalvalues (Table ll), with a mean r of 0'61. Equula equula, the dominant species, andLactarius lactarius were highly significantly correlated with surface water temperature.Apogon amboinensis correlated well with bottom water temperature and Pseudosciaenaweberi with bottom salinity. All of the regressions included only one hydrologicalvariable as a predictor.

6.479 5'229 0.1890.733 0.604 0.0220.295 0.245 0.009

275-0 275-0 7.7

Nocturnal nekton assemblage oariation

TABLE 10. Catch summary values regressed against physical data

Surfacetemperaturecoefficient

Bottom Surface Bottomtemperature salinity salinity Linearcoefficient coefficient coefficient coefficient Constant r

Number of speciesNumber of individualsTotal weight

-81 89

-169.5

The weight of each species was related to hydrological values (Table l2). Equulaequula weight, rank order l, was negatively correlated with surface salinity whileLutjanus johni, rank order 8, was positively correlated. Surface temperature was a weakindicator of Metapenaeus demani (rank order 3) and Lactarius lactarius (rank order l0)weight, with only 11076 and 20o/o of the variance explained respectively. The mean rvalue was 0'47, explaining 22"1; of the variance, about 15 f,u less than that explained withregressions on species abundances. Both the catch weight and number of individuals ofL. lactarius were correlated with the same hydrological observation. The only otherspecies with correlations for both weight and abundance was E. equula, but it wascorrelated with different variables.

There are three types of complications to be expected in effecting regressions betweena given time set of hydrological data and a given time set of catch data:

(1) The relationship may not be linear, and if not, exponential, logarithmic or powercurve fitting may be required.(2) The data may not be normally distributed and may require transformations whichmay in turn convert a non-linear to a linear relationship.(3) The catches may be influenced by several climatic conditions at an earlier time, andthis is referred to as the lag effect.

Hydrological observations lagged at fortnightly intervals were regressed against thenumber of individuals of commonly caught species (Table I l). Bottom and surface watertemperatures were the most common significantly correlated hydrological variables - l0and nine times respectively. Then followed surface (seven times) and bottom (twice)salinity. It is curious to note that the variable with the greatest temporal homogeneity(C.V., 4'9o/o), bottom temperature, was the most common significantly correlatedhydrological variable. In other words, the 'best' hydrological parameter from whichabundances can be predicted is the parameter that varies least throughout time andwhich probably reflects the small range in abundance. The model lag was threefortnights with eight significant correlations. A single fortnight lag had six correlations,two fortnights had three, four and five fortnights, five correlations. There is no apparentconsistency in hydrological variables ofprevious fortnights affecting abundances.

The transformed catch weights of Equula equula and Metapenaeus demani wereregressed on lagged hydrological variables (Table 13). Correlations with bottom salinity(lagged five fortnights) and surface salinity (lagged three) and bottom temperaturerecurred in each regression for E, equula. Two regressions were significant with trans-formed catch weights of M. demani and both included surface temperature. As suspected

-0.19 r6.33137.55580.5

<0.05<0.01<0.01

0.350.450.44

TenrE I I . Regression coefficients between numbers of individuals and hydrological variablesuN)

SpeciesPhysical Surface Bottomdata lag' temperature temperature

Bottom Linearsalinity coefficient Constant

Surfacesalinity P

Eguula equula

Secutor ruconius

Metapenaeus demani

Gazza achlamys

Ambassis interruptus

P o ly d a c tjt lu s mi cr o s tomu s

Apogon ambionensis

Gerres filamentosus

Lactarius Iactarius

Caranx sexfasciatusPseudosciaena ueberi

01

3

45

2

3

45)3

45

3

45

0I23

451

3

0I

0I3

- 17.02

-rt:o

- 0.98

-t.42

-o'28027

-0 39

-0.31-o.26

- 0.38*0 23

8.58r0.5410.26

-2.61-412-4.80-3.83

_ ru

-5',

-o.21yu

0.910.85r.200.38

0.19

-0 05

0. l50.29

- 0.10

-0.24-0.18

-0'04

-0.06

601 3465.3

-237.7-295.9-287-5

96.6138.5159.9t28.5

-l.t- 0.1,3.2

1.816.743.r40.6

10.I86

12.l10.59.98.47.00.97.2l.l

1.04.O

-4.5

0.55 < 0.01o.35 <0.05o'45 <0.020.50 <0.0t0.51 <0.010.35 <0.05o.43 < 0.050.55 < 0.010.62 <0.010.48 <0.010.45 < 0.050.65 < 0.01o.52 <0.010.40 <0.050.71 < 0.0010.58 < 0.001

N.S.0 56 <0.0010.52 <0.010.64 <0.0010.41 <0.05o.54 <0.010'45 < 0.010.41 < 0.050.59 <0.050.63 < 0.0010.41 < 0.05

N.S.0.65 < 0.0010.60 < 0.0010.68 < 0.001

3:.?ro

a5

l-x,o

'Each lag represents one fortnight.

TABLB 12. Regression coefficients between catch weight and hydrological variables

SpeciesPhysical Surface Bottom Surfacedata lag temperature temperature salinity

Bottom Linearsalinity coefrcient Constant P

Equula equulaArothron recticalnris

Metapenaeus demani

Secutor ruconius

Gazza achlamysP o ly d acty lus mi cr o s t or/tusLutjanusjohni

Pomadasys argyreus

Ambassis intenuptus

Lactarius lactarius

Lutjanus maxuteberi

0235

045,345400I2335

45

0I

-rs.n

3.6

--9 5

-1.4-7.4

-2.5-2.6

-57.4

- 91.9

-t.t- 10.3

16.820-918.7

2-4

-2.2

-9.5

:

-3t.4

l'-4-2

1.6

17.9

0.6

- l.lJt.o

716.6t799'2t275.82521.8

-7t.5299'l344'5

6'6466.5

- 585.5

-520.r5.5

36.935.1

-22.6-23.7270.2

70.845.6

238.3303.r

82.O85.4

2.22.L

0.65 <0.001o.?7 <0.050.41 <0.05o.54 <0.01o-34 <0.050.41 <0.050.05 <0.01o'37 /<0.050.46 f .o.os0.54 / <O.010.50 <0.010'67 <0.0010.34 <0.050.57 <0.0010.4r <0.050.46 <0.010.65 <0.0010.51 <0.010.17 <0.050.64 <0.0010.59 <0.0010.35 <0.010.51 <0.001

N.S.

2:rI

s:hr

N6

sI6sI

ois

utt\){

iJli\)00

Tesrr 13. Regression coefficents between carch weights and lagged hydrological variables

Species a'LaE Transformation Variable Constant P

Equula equula

Metapenaeus demani

square rootsquare rootsquare root4th root4th root4th rootlog(n + 1)

log(n + 1)

log(rz+ 1)

4th root4th rootlog(zf 1)

bottom salinitybottom salinitybottom temperaturesurface salinitybottom salinitybottom temperaturesurface salinitybottom salinitysurface salinitybottom temperature

surface temperaturesurface salinitysurface temperature

o.57 < 0.05

0.84 < 0.001

05

235

235

34

0I3I

37.16t.2t

-3.71-0.62

0.14

-0 41

-0.070.06

-0.03-0.16

0. 15

0.030.09

- 13r.83

116.50

15.13

6'66

-183- l.l8

0.89

091

0.36

0.700.54

<0.001

<0.0001

N.S.

<0.05< 0.05

3:-?o

rn

F!-X,o

"Q is the coefficient for the hydrological variables

Nocturnal nekton assemblage z;ariation 529

the relationship is clearly complex. It is postulated that hydrological parameters along

with interactions of other species, such as the presence of predators, need to be con-

sidered in the models. This analysis was not attempted owing to small catches of knownpredators of the dominants.

V ariation betw een y ear s

The data from similar lunar phases for two years (June 1980 to May 1981 and June 1981

to May 1982) were compared using a \Tilcoxon matched pairs non-parametric test to

determine if there was a significant difference between years in the total catch

abundance, mass) or number of species caught (Table l4). No significant difference was

present for N and IZ although both means were higher during the second year. The

TABLE 14. Comparisons between years of catch summary statistics from Labu estuaryusing a paired r-test

Year one Year two

StandardMean error

StandardMean error

Degreesof

freedom P

Mean total number of individualsper site per time

Mean total weight (g) per siteper time

Nur,'rber of fish species per time

77.5

442.1t2.4

7.4

58.60.5

92.0

479.9r4.3

t0.2

60.9o.7

15 N.S. t-23

15 N.S. 0.s415 <O.O5 2 27

TABLE 15. Comparisons between years of number of individuals of abundant species

from the Labu estuary using a paired r-test

Year one Year two

StandardMean error

StandardMean ertor

Degreesof

freedom P

Equula equulasecutor ruconiusMetapenaeus demaniGazza achlamysAmbassis interruPtusP oly dactg lus mi cr o st omusApogon amboinensisGerres f.lamentosusLactarius IactariusCaranx sexfasciatusPseudosciaena weberiPomadasys argyreusLutjanus johni

93618.716.85.73.80.8150.60.7070.00'40.5

9.89.63.9241.00.20.40.20.20.20.00.10.1

t36.272.2t2'8482.8l.l0.5050.60.31.90.302

19.14.42.71.00.6o.30.20.2020.10.50.10.1

15

15t58

l515

15

15

15

15

15

t5l5

<0.01 2 93N.S. 0.58N.S. 0.01N.S. 0.32N.S. 0.31N.S. 0.32

< 0.05 2.27N.S. 0.40N.S. 1.0rN.S. 1.38

< 0.001 4.38N.S. 0 77

<0.01 1.83

530 N. J. Quinn €s B. L. Kojis

Tesrn 16. Comparisons between years of catch weight of selected species from theLabu estuary using a paired l-test

Year one Year two

StandardMean error

Standardetror

Degreesof

freedom

Equula equulaArothron recticularisMetapenaeus demaniSecutor ruconiusGazza achlamysP o ly d a c ty lu s mi cr o s t omu s

Lurianus.iohniPomadasgs argyreusAmbassis interruptusLactarius lactariusApogon amboinensisGerres filamentosus

404.3t68.429.432.427823'628.915'922679

29.77.1

79'073.86'7

18.08.97.78.4

10.0b.92.42.12.4

624.152.544.327.346'820.03.53.9

20.511.1

5.3

95.628.68.78.4

13.94.61.82.15.2331.6t.7

t5l515

l58

15

t5l515

l5l5t5

<0.05 2.2tN.S. t-45N.S. r.53N.S. 0'25N.S. 0.95N.S. 0.43<0'01 2.82N.S. 1.15N.S. 0'32N.S. 0.86<0.01 3.06N.S. 0's3

number of species per time) S, was significantly different with 12.4 species during thefirst year and 14.3 during the second.

A comparison of the abundances of the 13 most abundant species between the twoyears found three significant differences. The dominant, Equula equula, was significantlymore abundant during the second year than during the first (Table l5). Pseudosciaenaweberi was caught only during the second year and Apogon amboinensis was less abundantduring the second year.

Catch weight for most species was similar between years; only three species had sig-nificant differences (Table 16). Catch weight for Equula equula was greater during thesecond year, while the catch weight for Apogon amboinensis was greater during the firstyear. These results were consistent with those for abundances. The weight of Lutjanusjohni was greater in the first year, suggesting that larger individuals were caught that yearas there was no significant difference in numbers of individuals between years.

Discussion

The hydrological study of the Labu estuary shows the existence of minor physico-chemical gradients associated with the penetration of tides and runoff. As the estuary isrelatively short and shallow, a saline environment exists in all sections throughout theyear. The tidal currents are only strong in the lower reaches resulting in little turbulenceand vertical mixing in other regions. The upper reach is a zone of reduced dissolvedoxygen and salinity and increased temperature. Spatial variation in hydrological param-eters is less than temporal variation. It is likely that the estuary's homogeneity andlimited extent reduce the number of niches available for utilization by fish.

Variations in temperature and salinity in the Labu estuary follow annual cycles.Although there was no distinct dry season at the rain gauge in Lae, it is hypothesized thatthe rainfall in the higher altitudes of the Labu watershed was more seasonal which

N o cturnal nekton as s emb lag e a ari ati on

resulted in the annual variation of hydrological parameters in the Labu estuary. $7hile

cycles in salinity have been recognized in tropical estuaries, it has been commonlythought that the temperature remains nearly constant all year (Rodriguez, 1975).

Although tropical estuarine temperature variation is less than that observed in subtropi-cal waters (Quinn, 1980), there is still a regular annual cycle to which fish could respond.

There is no apparent cycle in dissolved oxygen or turbidity.Temperature/salinity cycles are probably related as lower temperatures occur during

periods of lowest salinity in the estuary. The months of July/August in Lae are charac-

terized by cloudy days with prolonged periods of rain. This agrees with the observation

by Egborge (1972) in a study of the hydrology of the Oshun River, Nigeria, that lowertemperatures in flood periods occur because of increased cloud cover.

The Labu estuary is stratified with significant differences between surface and sub-

surface hydrological values. The differences between near substrate and mid-river sur-face temperatures are similar to results from other studies; for example, 3'0'C in a

Ghanaian river (Thomas, 1966) and 1.0'C in a Malayan stream (Bishop, 1973). This isexpected in sheltered coastal waters where there is little wind-generated water move-

ment to mix the less dense freshwater on the surface with higher salinity water below.Additionally, the small tidal range (maximum range l'1 m) does not encourage mixing.

Despite its limited extent, the estuary was occupied by at least 38 species of bottomfish from 26 different families. Thirty one of these species were eaten by local villagers.

Some small demersal fish species were probably missed owing to the mesh size and othersampling considerations. Schooling fish (e.g. mullet) and surface feeders (e.g. gar) werepresent in the estuary, but not caught.

The fish recorded are generally typical of those recorded from similar locations in the

Indo-west Pacific tropics, except for the absence of members of several families such as

Platycephalidae, Cynoglossidae, Sillaginidae and Soleidae. The assemblage is appar-ently much less diverse that that of Trinity Inlet, Queensland (16'55'S), with 54 species

(Blaber, 1980), and Ponggal estuary, Singapore (1'N), with 80 species (Thia-Eng, 1973).

The use of fine mesh seines in these studies undoubtedly increased the number of species

caught. Only six species (11%) were common with the Trinity Inlet and five species

(6?i,) with Ponggol estuary.The assemblage was dominated by Equula equula, representing 70'3oio of all individ-

uals caught and 59.19i, of the mass. It was the most ubiquitous teleost occurring in all 41

trawl dates. No published studies of E. equula are available, but in a detailed study a

related species, Leigonathus breairostris, was found to spawn throughout the year in the

Gulf of Mannar (8"N, 79'E) with individual fish possibly spawning more than once a

year (James & Badrudeen, 1975). The presence of juvenile E. equula (S.L.<55mm)throughout the year in Labu estuary suggests that it could have a similar reproductivebiology.

The biology of Pomadasys argyreus is reasonably well known. In eastern India' itgrows to a maximum of 45 cm (S.L.) weighing 1'5 kg, becomes sexually mature at l3 cm

and spawns in February (Konchina, 1977). This suggests that spawning would occuraround August in the southern hemisphere. Estuary catches of P. argyrezs declined

throughout the study and had no annual cycle. Individuals caught were mostly juveniles,

3-l I cm, whose presence was inversely related to water temperature of the previous twomonrhs suggesting that in a more favourable habitat the greatest abundance would occurin the cooler season of June to August. The estuary is probably used only as a nurserywith breeding probably occurring elsewhere.

53r

532 N . J . Quinn {s B. L. Kojis

The main feature of the life cycles of some coastal fish is the division into a juvenile

phase which is largely estuarine and an adult phase which is primarily marine. It is com-monly thought that most species breed on the continental shelf, because only a few small

specialized forms have adapted their entire life cycles to the variable conditions oftemperature, salinity and turbidity characteristic of estuaries (Vallace & van der Elst,1975). Generally, there is a seasonal movement of adult populations into the inshorespawning grounds. Fish in pre-spawning and partially spawned condition tend to move

in and out of the lower reaches of estuaries with the tides, while post-spawners generally

leave the system.Lowe-McConnell (1977) outlined four zones from inshore muddy water to clear, deep

water with characteristic fish populations and suggested that broad shelf communitiesare highly diverse, while shelf communities near large rivers with seasonal outflowsgenerally were less diverse and contained dominants. As the continental shelf of the

Huon Gulf was extremely narrow (<2km) and limited in extent (<20km long), it istikely that this assemblage has small populations of many species if not lower diversity.To test whether the fish assemblage of the continental shelf of the Huon Gulf is less

diverse than the 350 + species recorded from the much larger shelf of the Gulf of Papua

(9'00'S, 143"27'E to 9'02'S, 146"38'E) (Kailola & Wilson, 1978) an extensive trawlingstudy of the Huon Gulf is suggested.

If the biology of tropical estuarine fish is governed by the seasonality of flooding(Lowe-McConnell, 1977), then the irregularity of the local rainfall patterns is likely to

result in local anomalies in the reproductive biology. In India with its regular monsoons,

Sreekumari (1977) noted that the beginning of rains brings changes in the environmentthat act as a definite stimulus to spawning even in species llke Stolephorus zollingeri,which are continuous breeders. In New Ireland, Papua New Guinea, Dalzell (1980) also

observed that spawning in S. deztisi and S. heterolobu.s occurs at a low level all year round,but is greatest at the time of change in monsoon season. Catches of S. bataaiensfu in the

Labu estuary were too small for any generalized observations. Flowever, it is likely thatusing a small mesh net would result in a greater catch. Spawning would most likely occuraround April to May and October/November to December, at the time of the slightchange in seassns.

Although generalized temperature and salinity preferences have been shown forvarious estuarine species (Copeland & Bechtel, I974), as a whole these organisms show a

wide tolerance for short-term changes in these parameters. This could help to explainthe general lack of importance of temperature and salinity as critical variables in the

multiple regression analysis. The annual salinity and temperature range was small owingto, respectively, heavy rainfall throughout the year and the equatorial position of the

estuary. The multiple regression technique was limited in its application as the abioticparameter variation was perhaps too subtle to accommodate sampling and annual vari-arions. Other factors such as biological interactions could complicate such an approach

to determination of predictive factors (Oviatt & Nixon, L973).lt is possible that trophicrelationships and reproductive cycles are of critical importance in the spatial and

temporal distribution of estuarine populations. As in other low latitude estuaries, the

Labu estuary is dominated by juvenile stages of a small number of species.

Fluctuations in the abundance of higher latitude marine species throughout a year is

well known. Considerable within-estuarine species variability in annual abundances has

been noted (Livingston et al., 1976) and occasionally related to climatic cycles over

several decades (Dow, 1977). ln the tropics, less is known about within- and

Nocturnal nekton assemblage zsariation

between-year variarion in estuarine biota. In this study hydrological variation was

greater between years than within years and a few species experienced significant

changes between years.

The hydrological and biological consequences of exceptionally wet or dry years are

largely unknown. It is obvious that periods of high rainfall will have a tremendous effect

on the hydrodynamics and sedimentation of the estuary. The biological effects of low

salinity will also be considerable. On the other hand, drought conditions are also likely to

have an ellect as evaporation would increase the salinity. A severely reduced runoffmight also allow sediment to block the mouth as occurs in South Africa (Blaber, 1973)

and effect the assemblage composition.During the second year of this study, drought conditions were experienced in the

Markham River valley and higher salinities were experienced in the estuary. The signifi-cant population variation between years could be related to the hydrological variation.

llowever, it is possible that some species have a 'supra'-annual cycle and these cycles

could have accounted for the community changes. Stephenson (1980c) noted manymacrobenthic species had cycles of three to six years. The testing of this hypothesis usingtwo-year data should only be considered as preliminary.

Pseudosciaena weberi (S.L. 3-10 cm) was caught only during the second year ofsampling. This catch variation differs with pseudosciaenid populations in India whichare prolonged breeders and resident in the estuary throughout the year (Nair, 1977).

llowever, it has been suggested that within the tropics fish populations vary greatly fromyear to year owing to changes in abiotic and biotic factors (Lowe-McConnell, 1979). Thesalinity in the estuary was higher during the second year and the population

demonstrated a correlation with salinity values of the previous several fortnights. Thedifference between years may be related to other unmeasured abiotic factors such as the

injection of nutrients into the system) or by biotic pressures such as the alteration of apreferred habitat for predators and subsequent decrease in their populations. Such

influences may impose a between-year variation in the relatively aseasonal estuarine

environment that restricts efforts to determine stable annual patterns in suchenvironments.

It is evident from the foregoing that the distribution of juvenile fish in Labu estuary

cannot be satisfactorily explained solely with regard to physical factors. It is likely thatthe community structure depends on small environmental changes interacting with pre-dation and other biotic pressures. In this study, large piscivorous fish such as sharks,

carangids and sciaenids were not caught in any of the sites. The absence of such pred-ators from the shallow sampling sites may increase the attraction of these areas as sanctu-aries for juvenile fish, as was suggested for a north Queensland estuary (Blaber' 1980).

Predation by birds on juvenile fish in African estuaries has been shown to be high(Blaber, 1973). However, few birds were observed in the Labu estuary, possibly because

their plumage is commonly sought by local villagers for decoration. Intense humanpredation probably results in small bird populations and consequently bird predation offish was probably not important.

This work uses the same sampling device, a 3 m beam trawl, as previous work (Quinn,1980; Quinn & Kojis, 1981) carried out in a similar estuary at approximately the same

longitude (150'E), but with a 20' latitudinal difference. It is commonly thought thatspecies diversity increases as latitude decreases (Pianka, 1966). However, along the EastAustralian/Papua New Guinea coast, this does not appear to be true. Vhile 45 speciesof fish were caught in the subtropical Serpentine Creek, only 39 were caught in this

533

534 N. J. Quinn Cx B. L. Kojis

study. This was in spite of a longer sampling programme for the latter study. Thesubtropical estuary was characterized by three species, Spheroides pleurostictus, Gerresor.)atus, and Sillago maculata, each representing about 20, 17 and l7o/o of the totalabundances respectively (Quinn, 1980). The tropical estuary was dominated by a singlespecies, Equula equula, representing 70'3% of the catch. The sub-dominant fish Secutorruconius occurred in 9'loft of the catch with Metapenaeus demani representing l03%.Thus, the low latitude, tropical Labu estuary is less diverse than the subtropicalSerpentine Creek.

MacArthur (1965) suggested that the number of species within a habitat can be expec-ted to increase with productivity, with structural complexity and lack of seasonality ofresources. As there are no studies of the productivity of the Labu estuary, no com-parisons can be made. Less seasonal variation of resources in the Labu estuary has notresulted in increased diversity. It is possible that the Serpentine Creek estuary is a morecomplex habitat than the Labu estuary and thus alters the latitudinal effects.

It is further postulated that the diversity of the estuarine assemblage is also related todiversity of the shallow-water fauna of the Huon Gulf. Moreton Bay is a large shallowbay with a variety of habitats and physico-chemical environments which support a largenekton community which has been described by Bradbury (1980) and Stephenson andBurgess (1980). As there is no study of the demersal fish of the Huon Gulf, it is imposs-ible to compare the open water stocks available to both studies and relate it to estuarinenekton diversity. Ifowever, the area of shallow water is known to be small in the HuonGulf and a narrower range of habitats and physicochemical environments is likely. It issuggested that future studies investigate the community structure of the demersalnekton in the waters < 180 m of the Huon Gulf. Populations studies should focus on thesuspected dominant family, Leiognathidae.

Alternatively, according to present theory, high diversity can be maintained only in anon-equilibrium or sub-climax state (Patrick,1967; Odum, 1969; Slobodkin & Sanders,1969; Louchs, 1970). According to this 'intermediate disturbance hypothesis' (Connell,1978), diversity declines during long stable interludes due to competitive elimination,resulting in resource monopolized climax assemblages composed of few species. Distur-bances such as cyclones and wide ranges of temperature and salinity interrupt and setback this process of competitive exclusion. Organisms are killed, populations decimatedat various scales of frequency and intensity. If the intensity and frequency of disturbanceis sufficient to affect all, or most species, then the assemblage will return to pioneeringstages and diversity will be low. If, however, intensity and frequency of disturbance areof a magnitude which affects only certain species, thus acting in a selective manner as a'pruning device' to prevent resource monopolization, diversity will attain a maximumrelative to the extremes of no disturbance or severe disturbance.

The Labu estuary is a relatively disturbance-free habitat for euryhaline species anddiversity is low. As the estuary is not directly connected to the Markham River, annualvariation in salinity is not affected by heavy rains far up the valley and hence the annualvariation in salinity is small. Only locally intense rains are likely to greatly reduce thesalinity and serve as a disruptive influence. As less than average rain fell during most ofthe sampling period, it is impossible to assess how much the bottom salinity would dropand to what extent the freshwater intrusion would affect euryhaline populations. Furthersampling during and after a year of heavy rain is necessary to determine the extent thecommunity is altered after an unusually large lowering of salinities.

Nocturnal nekton assemblage uariation 535

Acknowledgernents\We are indebted to the people of Labu Butu village for their assistance and cooperation.$7e would like to gratefully acknowledge the Papua New Guinea University of Tech-nology for financial assistance for this study. Additional financial support was providedby the Papua New Guinea Harbours Board and the South Pacific Commission.

Messers R. Adams, K. Bakoma, M. Blowers, R. Hancock, K. Kapi, M. Matmillo, M.Sappu, H. Silver, D. Stewart, C. $flright and T. Yamelo assisted with the fieldwork. MrJ. Johnson of the Queensland Museum kindly assisted with fish identification. Mr S.

Frusher, Department of Primary Industry, Dr A.J. Bruce, Northern Territory Museumof Arts and Sciences, Mr P. Davie, Queensland Museum and Dr P. Rothlisberg, CSIROhelped identify the Crustacea. Prof. W. Stephenson kindly assisted with computeranalysis performed at the lJniversity of Queensland. Both he and Prof. J.M. Thomsonconstructively criticized portions of the manuscript. Dr G.R. Huntsman and an

anonymous reviewer offered useful suggestions.

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Appendix: List of organisms caught in the beam trawl

Species FamilyLocallyeaten

Ambassis interraprzs Bleeker 1956Anodonto stoma chacunda (H.-B.) 1822Antennarius hispfdzrs (Bloch & Schneider) l80lApogon amboinens,s Bleeker 1858A. hyalosoma Bleeker 1952Ar chamia buroensi s (Bleeker) I 956Arothron reticularis (Bloch & Schneider) 180 IAutaous grammepomus (Blecker, I 849)Callianassa c.f . karumbaCharybdis helleriCaranx sexfascicrzs Quoy & Gaimard 1824Eleotrisfuscus (Bloch & Schneider) 1801E. c.f. macroleprs (Bleeker) 1875Epinephelus tauztina (Forskhl) L7 7 5Equula equula (Forskil) I 775Gazza achlamgs Jordan & Starks 1917Gerres filamentoszs Cuvier 1829Glossogobius circumspectus (Macleay, 1884)Harpodon translucens Saville-Kent 1889Himantura granulata (Macleay) 1883Lactarius lactarius (Bloch & Schneider) l80lLutjanus argentimaculatus (Forsk6l) 1775L. ehrenbergi (Peters) 1869L. johni (Bloch) 7792L. maxweberi? Popta, 1921Metapeneaus demaniMonodactylus argenteus (L.) 1758Mur aene so x ciner eus (ForskAl) I 775Oratosquilla nepaOxyurichthys tentacularis? (C. & V., 1837)Palaemonid prawnsPenaeus semisulcatusPlatax orbicularui (Forskil) 1775P oly dacty lus micro stomus (Bleeker) I 85 IPomadasys argyrens (Valenciennes) 1833Portunus pelagicusP seudo sciaena we beri (Bleeker) 187 7Scatophagus argus (L.) 7766Secutor runconius (H.-8.) 1822Setipinna papuezsrs Munro 1964S tol ephorus bataoi ensis Hardenberg I 933Tetraroge barbara (Cuvier) 1829Thalamita sp.Toxotes jaculator (Pallas) 1766Triancanthus indicus Regan 1903U peneus ait t atus (Forskil) 1 775Upeneus sp.V aruna litt er at a (Fabricius) I 798

ChandidaeDorosomidaeAntennariidaeApogonidaeApogonidaeApogonidaeTetrodontidaeGobiidaeCallianassaPortunidaeCarangidaeEleotridaeEleotridaeEpinephelidaeLeiognathidaeLeiognathidaeGerridaeGobiidaeHarpodontidaeDasyatidaeLactariidaeLutjanidaeLutianidaeLutjanidaeLutjanidaePenaeidaeMonodactylidaeMuraenesocidaeSquillidaeGobiidaePalaemonidaePenaeidaePlatacidaePolynemidaePomadasyidaePortunidaeSciaenidaeScatophagidaeLeiognathidaeEngraulidaeEngraulidaeTetrarogidaePortunidaeToxotidaeTriacanthidaeMullidaeMullidaeGrapsidae

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