small fish and crustaceans demonstrate a preference for particular small-scale habitats when...

y and Ecology 353 (2007) 164–179www.elsevier.com/locate/jembe

Journal of Experimental Marine Biolog

Small fish and crustaceans demonstrate a preference for particularsmall-scale habitats when mangrove forests are not accessible

Ross Johnston ⁎, Marcus Sheaves 1

School of Marine and Tropical Biology, James Cook University, Townsville, Queensland, 4815, Australia

Received 20 April 2006; received in revised form 23 May 2007; accepted 29 May 2007

Abstract

Availability of large areas of complex habitat (particularly mangrove forest) is an important reason why fish use estuaries as nurseryareas. However for aquatic species, access to much of the complex habitat in tidal systems is restricted to short periods of time.Consequently, aquatic species must spend considerable time in ex-forest habitats; habitats available when mangrove forests are notaccessible. The objective of this study was to determine the extent to which the availability of particular small-scale, ex-forest habitatsinfluenced the distribution of small fish (b100mmFL) and crustaceans. Substantially higher numbers of small fish and crustaceanswererecorded frommuddy substrata than from sandy substrata. Overmuddy substrata, bank architecture such as drains returningwater to sub-tidal areas and water depths b0.375 m strongly influenced the distributions of abundant species, whereas areas of low current velocityand hydrodynamic features had only minor influence on distributions. Similarly, water depths b0.375 m and bank architecture, such asdrains, strongly influenced the distribution of the abundant crustacean taxa. Current velocity and hydrodynamic features had littleinfluence on the distribution of crustaceans. Most of the abundant taxa showed a positive response to small-scale ex-forest habitats thateither provided longer access time to complex intertidal habitat and/or shallow water. However it was unclear whether those habitatpreferences also provided feeding opportunity, refuge from predation or energetic advantage.© 2007 Elsevier B.V. All rights reserved.

Keywords: Crustacean distribution; Depth; Drains; Fish distribution; Habitat; Tropical estuaries

1. Introduction

Availability of large areas of complex habitat, inparticular mangrove forest, has been used to explain whyestuaries function as nursery areas (Robertson and Blaber,1992). However, although it is apparent that fish andcrustaceans use mangrove forests extensively (Thayeret al., 1987; Vance et al., 1996) many questions remainabout the way fish use intertidal and sub-habitats and aboutthe biological connectivity between those habitats.

⁎ Corresponding author. Tel.: +61 7 4781 4626; fax: +61 7 4725 1570.E-mail addresses: [email protected] (R. Johnston),

[email protected] (M. Sheaves).1 Tel.: +61 7 4781 4144; fax: +61 7 4725 1570.

0022-0981/$ - see front matter © 2007 Elsevier B.V. All rights reserved.doi:10.1016/j.jembe.2007.05.039

Biological connectivity between sub-tidal and inter-tidalhabitats clearly exists because fish use mangrove forestswhen they are available (Thayer et al., 1987; Laegdsgaardand Johnson, 1995; Vance et al., 1996) and, with a fewspecialist exceptions, cannot remain in the high intertidalonce the tide has receded. Tidally-driven migrations(Gibson, 2003; Krumme et al., 2004) are one mechanismthat facilitates connectivity between intertidal and sub-tidalhabitats, but previous literature provides little informationabout the habitat- related distribution of small fish whenintertidal habitats such as mangrove forests are notavailable (Laegdsgaard and Johnson, 1995).

Mangrove forests are only accessible to aquaticspecies for short periods; access to forests is restricted

mailto:[email protected]

mailto:[email protected]

http://dx.doi.org/10.1016/j.jembe.2007.05.039

Fig. 1. Location of the estuary systems studied on the tropical north-eastern coast of Australia.

165R. Johnston, M. Sheaves / Journal of Experimental Marine Biology and Ecology 353 (2007) 164–179

by both daily-and lunar-tidal cycles, so aquatic speciesmust spend much of their time in ex-forest habitats,defined here as habitats available to aquatic taxa whenmangrove forests are not accessible. Such habitatsprovide relatively little complex structure compared to

Table 1Descriptions and definitions of sub-tidal habitat types and categories within

Habitat categories Habitat types Habitat type defin

Substrate Sand; mud 1. Sand — sand s2. Mud — fine si

Bankarchitecture

Non-drain; drain 1. Non-drain — sdrainage system e2. Drain — drainintertidal areas to

Depth Continuous Depths measuredBank Slope Low angle;

intermediateangle;steep angle

1. Low angle —2. Intermediate an3. Steep angle —

Hydrodynamicfeatures

Parallel flow;turbulent flow

1. Parallel flow —the general flow p2. Turbulent flowaltered flow patteobstacles and pot

Currentvelocity

Ranked 0–5 Based on the amoand 5 = maximumconsidered to be s

forested areas and therefore may have a markedly lowervalue as a refuge from predators than adjacent intertidalforest habitats. Furthermore, once the tide ebbs from themangrove forest it has the effect of concentrating bothpredators and prey in considerably smaller volumes of

each habitat type

itions

ediments with b10% silt/claylt/clay sediments with b10% sand contentections of bank along main channels with nontering the main channelage systems up to 3.5 m wide that return water fromthe main channel during ebb tidesin metresbank slope b30°gle — bank slope 30°−60°bank slope N60°

Down current flow is parallel to bank and although turbulentattern is not disrupted by bank architecture— Areas where parallel flow is disrupted by structures that create anrn (turbulence), e.g. down current flow is being deflected by solidentially creating low energy zonesunt of net deflection induced by current, where 0 = no net deflectiondeflection at which cast net was (subjectively)till fishing effectively

Table 2Taxa recorded during the study, their total abundance and theirfrequency of occurrence over different substrata

Taxon Abundance/%nets all substrata

Abundance/% nets mud

Abundance/% nets sand

# nets=950 # nets=451 # nets=499

FishLeiognathusequulus

4296/18.4 3049/31.9 1247/4.9

Acentrogobiusviridipunctatus

340/14.8 18/2.9 322/25.7

Ambassis vachelli 3562/14.0 1741/20.8 1821/4.7Clupeids 1091/12.3 577/17.7 514/4.9Pseudomugilsignifer

855/9.4 831/18.8 24/0.8

Pomadasys kakaan 75/5.0 73/10.2 2/0.4Chelonodon patoca 93/4.6 78/49 15/1.8Gerresfilamentosus

447/4.4 23/2.4 424/4.2

Butis butis 51/4.2 41/4.7 10/1.8Leiognathussplendens

342/3.7 56/4.4 286/3

Maralynapleurosticta

59/3.4 52/4.7 7/0.2

Zenarchopterusbuffonis

44/2.6 43/4.4 1/0.2

Glossogobiuscircumspectus

28/2.1 28/4.4 –

Sillago burrus 28/2.1 2/0.4 26/3.6Acanthopagrusberda

34/1.9 32/3.3 2/0.2

Atherinomorusendrachtensis

99/1.9 90/2.9 9/1.0

Liza vaigiensis 30/1.7 7/1.1 23/2.2Leiognathus bindus 51/1.6 41/2.7 10/0.6Platycephalus fuscus 15/1.4 5/1.1 10/1.6Liza subviridis 18/1.3 17/2.4 1/0.2Sillago sihama 23/1.2 12/1.8 11/0.6Gazza minuta 58/0.9 3/0.7 55/1.2Lutjanus russelli 10/0.8 9/1.3 1/0.2Sillago analis 11/0.8 4/0.7 7/1.0Arothron manilensis 7/0.7 6/1.3 1/0.2Secutor ruconius 29/0.7 8/0.7 21/0.8Siganus lineatus 9/0.7 8/1.6 1/0.2Valamugil seheli 16/0.7 12/0.9 4/0.6Acanthopagrusaustralis

15/0.6 6/1.3 9/0.6

Gobid sp. 2 8/0.6 7/1.3 1/0.2Acentrogobiusgracilis

7/0.4 7/0.9 –

Hyporamphus affinis 4/0.4 4/0.9 –Paraplagusiabilineata

4/0.4 1/0.2 3/0.6

Paraplagusia gutata 5/0.4 1/0.2 4/0.8Pseudorhombusarsius

6/0.4 2/0.4 4/0.8

Scatophagus argus 13/0.4 13/0.9 –Yongeichthysnebulosus

5/0.4 3/0.7 2/0.2

Acanthurus sp1 3/0.3 2/0.4 1/0.2

Table 2 (continued )

Taxon Abundance/%nets all substrata

Abundance/% nets mud

Abundance/% nets sand

# nets=950 # nets=451 # nets=499

FishAmbassis nalua 4/0.3 3/0.7 1/0.2Elethronemateradactylus

4/0.3 4/0.7 –

Lutjanusargentimaculatus

3/0.3 3/0.7 –

Pomadasysargenteus

3/0.3 2/0.4 1/0.2

Scomberomoruscommerson

4/0.3 2/0.2 2/0.4

Terapon jarbua 4/0.3 2/0.4 2/0.2Bathygobius sp. 1 2/0.2 1/0.2 1/0.2cf Trachyrhamphussp. 1

2/0.2 2/0.4 –

Pelatessexalineatus

2/0.2 2/0.4 –

Periopthalamus sp. 1 3/0.2 3/0.4 –Sillago cilliata 5/0.2 – 5/0.4Toxotes chatareus 2/0.2 2/0.4 –Apogon hyalosoma 1/0.1 1/0.2 –Arramphussclerolepis

3/0.1 2/0.4 1/0.2

Ctenogobius sp. 1 1/0.1 1/0.2 –Gobid sp. 1 3/0.1 2/0.2 1/0.2Hyporamphus quoyi 1/0.1 1/0.2 –Lates calcarifer 1/0.1 1/0.2 –Paradicula setifer 2/0.1 1/0.2 1/0.2Pegasus volitans 1/0.1 – 1/0.2Sphyraenabarracuda

1/0.1 1/0.2 –

Tetractenushamiltoni

3/0.1 2/0.4 1/0.2

CrustaceansPenaeusmerguiensis

3912/34.2 3721/62.7 191/4.6

Acetes sibogaeaustralis

33818/22.6 32324/42.6 1494/4.6

Palaeomonids 922/13.8 902/25.3 20/3.4Metapenaeus spp. 130/6.5 105/11.1 25/2.4Penaeus esculentus 7/0.6 5/0.9 2/0.4Macrobrachium sp1 9/0.5 9/1.1 –Penaeus indicus 2/0.2 1/0.2 1/0.2

166 R. Johnston, M. Sheaves / Journal of Experimental Marine Biology and Ecology 353 (2007) 164–179

water (Krumme et al., 2004). This suggests that in anursery area context the role of ex-forest habitat may beas important, if not more important, than that of complexintertidal habitats such as mangrove forests.

The primary objective of this study was to determinethe extent to which the availability of particular small-scale, ex-forest habitats influences the distribution ofsmall fish (b100 mm FL) and crustaceans during periodswhen the mangrove forests are unavailable to them.


2. Methods

2.1. Study sites

The study was conducted between April 2000 andMarch 2001 in Deluge Inlet and Victoria Creek on thetropical north-eastern coast of Australia (Fig. 1). Bothsystems are mangrove-lined throughout most of thelower reaches, 0–7 km, where all sampling was con-

Fig. 2. Univariate C&RT analyses for the fish Leiognathus equulus on mud susplit in the tree used to determined which locations/trip combinations had suffside of panel). The table provides details of sample size (n), proportion of ne(Mean), and percentage of variance explained (proportion of the variance expltree in the RH panel and the error associated with that model. The lower panel4 in table) for each leaf of the tree and the number of samples for each branch oTrip DI Deluge Inlet, V Victoria Creek; Ap April, J June, Au August, O ODn drain; De depth (depths are reported in metres); Hy hydrodynamics, P par

ducted, and have a semi-diurnal tidal regime with amaximum range around 3.8 m. In both estuaries, floodtides entered the lowest mangrove fringes at around 1 mbut the vast majority of forest was not accessible to fishuntil tidal height exceeded 2 m. All habitat types underinvestigation (Table 1) were well represented in bothsand and mud substrata in each estuary, however eachestuary had a different pattern of distribution of sub-strata. Banks along the lower reaches of the sampling

bstrata. The small figure in the upper left of each panel shows the firsticient density of data (RH branch) for further analysis (trees on the RHts in which the taxa was present (Ppn) and the mean abundance per netained by the full model that is explained by the model presented) for theprovides a graphical representation of the mean abundance per net (colf the primary split (n =). Abbreviations used in all figures are: Location/ctober, D December, M March; Ba bank architecture, ND non-drain,allel, T turbulent; Cv current velocity (ranked 0–5 where 0 = no flow).


area, 0-3 km, in Victoria Creek were almost exclusivelysand substrata, and the upstream parts of the samplingarea were predominately mud substrata. In contrast,sand and mud substrata were present throughout thestudy area in Deluge Inlet.

2.2. Classification of habitat

Habitat categories, and habitat types within thosecategories, investigated in this study were: substrate(sand, mud), bank architecture (drain or non-drain),depth, bank slope (low, intermediate or steep angle),hydrodynamic features (parallel or turbulent flow) andcurrent velocity (Table 1).

Fig. 3. Univariate C&RT analyses for the fish Ambassis va

2.3. Faunal samples

A minimum of 18 replicate samples from eachcategory of bank architecture and a minimum of 12replicates for each bank slope category were collectedevery second month, for 12 months, from both estuarinesystems. Sampling scheduled for February 2001 wasdelayed until March 2001 because of flooding. Cast nets(3.07 m diameter, 6 mm multi-filament mesh), operatedby the same individual were used for faunal sampling.Cast nets were used because they were suitable forcollecting samples of small mobile fauna in tropicalestuaries (Johnston et al in press), and they matched thescale of the habitats in question.

chelli on mud substrata. Abbreviations as in Fig. 2.


Sampling was conducted during spring tides imme-diately preceding the new moon. Data were collectedrandomly from each micro-habitat type over both mudand sand substrata, and were collected over fourconsecutive days alternating daily between the twoestuaries. All samples were collected from banks at theedges of channels or from edges of mid-stream banks.Sampling was arbitrarily restricted to waters less than2 m deep because it was possible that net avoidance byfish may become a problem in deeper water because ofthe relatively slow sink rates of the 6 mm mesh cast net.A fine mesh net was necessary to represent the smallerindividuals in the systems. Sampling commenced oncethe ebb tide had receded from mangrove forests, at atidal height of 1 to 1.2 m depending on location, and

Fig. 4. Univariate C&RT analyses for the fish Pseudomugil

concluded before the flood tide re-entered the forest.Although ebb and flood tides had a potential toinfluence the distributions of taxa in different ways81% of samples were collected during ebb tides becausethey provided more time for data collection than floodtides. Comparison of the ebb versus flood tide dataindicated that tidal state had little influence on thedistribution of taxa when mangrove forest was notaccessible.

Fauna were euthanased in an ice-water slurry beforetransport to the laboratory where they were identified tothe lowest taxonomic level, usually species, and counted.However, a number of species were difficult to separatemorphologically as small juveniles, so these juvenileswere pooled into broader taxonomic groups to maintain

signifer on mud substrata. Abbreviations as in Fig. 2.


consistency. Clupeid fishes (mainly Herklotsichthys andSardinella spp.), almost all in the 14–50 mm FL sizerange, were pooled into a single “clupeid” group. Meta-penaeus spp. were pooled into a “Metapenaeus” group,and paleomonid shrimps pooled into a “palemonid”group. Individuals included in pooled taxonomic group-ings performed similar trophic functions. Althoughpooling to taxonomic groups may generate “average”outputs across different species, consistently clear, strongresponses would indicate that most individuals in thegroup were responding to the same stimuli.

2.4. Data analysis

There were substantial differences in abundance andtaxonomic composition between sand and mud substrata,

Fig. 5. Univariate C&RT analyses for the clupeid fish

with particular taxa favouring one substrate over the other(Table 2). For most species this meant there was littledensity of data in one habitat type, consequently data frommud and sand substrata were analysed separately.

Univariate classification and regression trees (C&RT)(De'Ath and Fabriscius, 2000) were used to examinespecies-specific responses to different habitat types. Datawere typical of those from tropical estuary fish assem-blages, with a few species dominating numbers (Sheaves,2006). The frequency of occurrence of most taxa was toolow for reliable analysis so only the ten taxa that werepresent in at least 5% of samples were analysed (McCuneand Grace, 2002). The explanatory variables used to growtrees were location, trip and the five habitat categories(Table 1). Abundances of each taxon, fourth root trans-formed to limit the influence of a few nets with very high

es on mud substrata. Abbreviations as in Fig. 2.


abundance, were entered as response variables. With theexception of one taxon, Acetes sibogae australis, theprimary split in all C&RTswas a location/trip split. The lefthand branch of that split represented locations/trips whenthe density of data was low and therefore contained littleuseful information on difference among habitat types.Consequently, detailed analyses were only undertaken fordata contained in the right hand branchof each treewith theexception of A. s. australis where both branches areincluded. Using this technique the splits obtained from theright hand data are identical to those thatwould be obtainedin the right hand branches of a tree generated from thecomplete data set. In effect, the technique is simplyignoring responses generated from low abundance loca-

Fig. 6. Univariate C&RT analyses for the fish Pomadasys k

tions/trips and concentrating on locations/trips when therewere sufficient data for sensible interpretation.

Univariate trees were constructed to a size thatprovided a useful assessment of the relative importanceof each habitat type (StatSoft., 2002). The final treemodels were determined using multiple approaches.Firstly, scree plots of explained sums of squares wereused to determine the model size beyondwhich additionalexplanation was minimal, i.e. a point of inflection in theplot. Habitat splits that occurred in this initial model wereconsidered to have substantial effects because theyexplained much of the variability. The initial model wasexamined, and if there were not at least three splits onhabitat categories successively larger trees were examined

akaan on mud substrata. Abbreviations as in Fig. 2.


until three habitat splits were obtained. At least three splitson habitat were desired because response to differences inhabitat type was the primary focus of the analyseshowever additional habitat splits obtained in this mannerwere considered indicative rather than having substantialinfluence. Building trees in this manner meant that thehabitat categories could be ranked by importance.However, for several trees the third split had very lowexplanatory power and produced overly complex modelsso final models with two habitat splits were used in thosecases. The additional habitat splits in trees such as thoseoccurred very low on the trees explaining little of thevariability and thus provided no sound habitat informa-tion. Depths were recorded from the centre of the areaenclosed by the net, but because there was usually someslope associated with the stream bed, depth would be

Fig. 7. Univariate C&RT analyses for the fish Acentrogobius vir

shallower than the measured depth at one edge of the netand deeper on the other. Consequently, depth measure-ments used in analyses represented average depths.

3. Results

3.1. Fish

There were substantial differences in abundance andtaxonomic composition between sand and mud substratawith particular taxa favouring one substrate over theother. A total of sixty fish taxa were recorded during thestudy with fifty eight recorded from mud substrata andforty five from sand (Table 2). Acentrogobius viridi-punctatus was the only fish to occur consistently inreasonable abundances on sand.

idipunctatus on sand substrata. Abbreviations as in Fig. 2.


3.1.1. Mud

3.1.1.1. Leiognathus equulus. After location by tripcombinations with a low density of data were excluded,location and trip still had a strong influence on thedistribution of L. equulus (Fig. 2). Highest abundancesoccurred during December in Victoria Creek. At thattime highest abundances, and the highest frequency ofoccurrence, and highest mean abundance per net wererecorded from depths between 0.275 and 0.375 m.When depth was less than 0.275 m bank architecturewas important, with higher abundances in drains thanout of drains. Bank architecture was more importantthan depth among the remaining location/trip combina-tions. Higher abundance, frequency of occurrence andmean abundance per net occurred in drain habitats. That

Fig. 8. Univariate C&RT analyses for the crustacean Penaeus m

switch from depth being most important in VictoriaCreek in December to bank architecture having mostinfluence in the remaining location/trip combinations isone of the few instances where there were spatio-temporal interactions in habitat utilisation.

3.1.1.2. Ambassis vachelli. Ambassis vachelli respon-ded most strongly to bank architecture (Fig. 3). Higherabundances were recorded from drain than non-drainhabitats. Within drain habitats hydrodynamic featureswere influential, with higher abundance, higher fre-quency of occurrence and substantially higher meanabundance per net in areas of turbulent water.

3.1.1.3. Pseudomugil signifer. Depth had the strongestinfluence on the distribution of P. signifer (Fig. 4).

erguiensis on mud substrata. Abbreviations as in Fig. 2.


Highest abundance, frequency of occurrence, and high-est mean abundance per net of P. signifer were recordedfrom depths less than 0.375 m. Hydrodynamic featureswere important at shallow depths (b0.375 m) with mostP. signifer in turbulent areas, and location/trip influencedabundances in those turbulent areas. Low current areasheld substantially more individuals than high currentareas within the high abundance right hand branches.

3.1.1.4. Clupeids. The most influential factor on thedistribution of clupeid fishes was bank architecture(Fig. 5). Drains held substantially higher abundance,frequency of occurrence, and higher mean abundanceper net than non-drain habitats.

3.1.1.5. Pomadasys kakaan. Highest abundance andhighest mean abundance per net of P. kakaan wererecorded from areas of low current velocity (Fig. 6).Where current velocities were high, the highest

Fig. 9. Univariate C&RT analyses for the crustacean Acetes sibo

frequency of occurrence was recorded where hydrody-namic flow was parallel but as the sample size was small(n=2), little weight should be placed on this result.

3.1.2. Sand

3.1.2.1. Acentrogobius viridipunctatus. Abundance,frequency of occurrence and mean abundance per net ofA. viridipunctatus were substantially higher in areas oflow current velocity (Fig. 7). In these areas depth wasimportant, with most individuals found at depths lessthan 0.375 m.

3.2. Crustaceans

Seven crustacean taxa were recorded from mud andsix taxa were recorded from sand (Table 2). Nocrustacean taxa occurred frequently enough on sand towarrant analysis.

gae australis on mud substrata. Abbreviations as in Fig. 2.


3.2.1. Mud

3.2.1.1. Penaeus merguiensis. The distribution ofP. merguiensis was strongly influenced by depth(Fig. 8). Abundances were substantially higher at depthsless than 0.375 m than it was in deeper water. When depthwas greater than 0.375 m, higher abundance, higher fre-quency of occurrence and highest mean abundance per netwere recorded from areas of low current velocity. Trip hadthe greatest influence on distribution in depths b0.375 m.

3.2.1.2. Acetes sibogae australis. Bank architecture hadthe greatest influence on the distribution of A. s. australis(Fig. 9). Abundance, frequency of occurrence and meanabundance per net were substantially higher in drainhabitats than in non-drain habitats. The effects of location

Fig. 10. Univariate C&RT analyses for Paleomonid shri

and trip were of secondary importance in both bankarchitecture categories.

3.2.1.3. Paleomonids. Depth, bank architecture andhydrodynamic features influenced the distribution ofpaleomonid shrimps (Fig. 10). Paleomonids were moreabundant in water less than 0.375 m deep. At greaterdepths substantially higher abundance, frequency ofoccurrence and mean abundance per net were recordedfrom drain habitats. When water was less than 0.375 mmuch higher abundance, higher frequency of occurrenceand the highest mean abundance per net were found inturbulent areas.

3.2.1.4. Metapenaeus spp. Bank architecture had thegreatest influence on the distribution of Metapenaeus

mps on mud substrata. Abbreviations as in Fig. 2.


spp. (Fig. 11). Highest abundances were recorded fromdrain habitats. In drain habitats depth was influential,with substantially more individuals at depths less than0.375 m. In non-drain habitats current velocity appearedto influence the distribution of Metapenaeus spp., butthis should be interpreted with caution because of thelow number of samples in leaf two.

3.3. Summary of the relative importance of habitattypes

3.3.1. FishBank architecture and depth, each with two first splits

and two lower level splits, were the most influentialhabitats for fish (Figs. 2–7). Primary splits for bankarchitecture and one secondary split and all splits fordepth explained substantial variability. Three taxa showed

Fig. 11. Univariate C&RT analyses for the crustaceans Metape

responses to bank architecture, and in each case higherabundance was recorded from drain habitats. Depth alsodrew response from three taxa, and the highest abundancefor each of those taxa occurred at depths less than0.375 m. Current velocity (two first splits and one lowerlevel split all explained substantial variability), was alsoimportant for three taxa. Lower current velocities werepreferred by each of those taxa. Hydrodynamic featureshad a minor influence on distributions, being responsiblefor three lower level splits, however all three explainedsubstantial variability. In each case the higher abundanceswere in turbulent areas. Bank profile did not produce anyinfluential splits.

3.3.2. CrustaceansDepth and bank architecture, each with three splits

explaining substantial variability, had the strongest

naeus spp. on mud substrata. Abbreviations as in Fig. 2.


influences on the distribution of crustacean taxa (Figs. 8–11). Shallow water (b0.375 m) and drain habitats wereparticularly important to all four taxa. Splits on currentvelocity (two taxa) and hydrodynamic features (onetaxon) explained substantial variability for those taxa buthad minor influences on distributions of the other taxa.There were no splits on bank profile for any taxon.

It is notable that the highest probability of encounter(presence/absence data) and the highest mean abun-dance per net (abundance data) occurred in the samehabitat combinations for all taxa except the fish Poma-dasys kakaan (Fig. 6) and the crustacean Metapenaeusspp. (Fig. 11). In the latter cases the highest probabilityof encounter occurred for habitat combinations withvery few samples.

4. Discussion

Total number of species recorded in this study (62)was somewhat lower than that reported from othertropical estuarine studies (N100 species e.g. Robertsonand Duke, 1987, 1990a,b; Sheaves, 2006), however thiswas not surprising given that sampling was restricted tosmall-scale habitats, a narrow depth range and a netmesh size that restricted the size of individuals likely tobe captured. Despite this, most numerically dominantspecies from previous studies (Robertson and Duke,1987, 1990a,b; Sheaves, 2006) were abundant in thisstudy, suggesting that the main components of the smallfish and crustacean faunas were effectively representedin the present study. Consequently the choice ofsampling gear did not unduly bias results.

Composition of the small fish and prawn assemblagewas clearly different between sand and mud substrata(Table 2). Mud substrata consistently had many taxapresent in relatively high abundance whereas sandsubstrata could be characterised by the presence of oneconsistently abundant species (Acentrogobius viridi-punctatus). Clearly, the availability of muddy substratais particularly important in structuring the small fish andcrustacean assemblages. Only one other tropical Aus-tralian study (Robertson and Duke, 1987) had explicitlycompared fish abundance between sand and mud banksusing the same sampling gear in both habitats. Thatstudy reported higher abundance of fish over mud banksthan on sand banks over a 13 month period in fourestuarine systems. Although that study targeted largerfishes they also found differences between mud andsand habitats to be robust among locations and overtime.

After substrate type, trip had the greatest influence onthe distribution of fish and crustacean taxa (Figs. 2–11).

A majority of taxa were more abundant during thewarmer months from December to April, with highestabundances for most species recorded during December.Consistency in patterns of habitat use among locationscan be interpreted from interactions between locationsand habitat types, i.e. a lack of interaction would implyconsistency in habitat use between systems and overtime. In the present study, there were few interactionsbetween location and habitat type thus habitat usegenerally remained spatially and temporally consistentfor all abundant taxa.

Among habitat categories bank architecture anddepth had greatest influence on the distribution of thefish and crustacean assemblages (Figs. 2–11). Splits onbank architecture consistently showed higher abun-dances in drain habitats regardless of location or trip. Incontrast, depths at which highest abundances of taxawere recorded frequently differed between locations andamong trips. Despite those differences, higher abun-dances were always present in water b1.0 m deep.Current velocity had low level influences for a few fishtaxa, but had little influence on crustacean distributions.Hydrodynamic features had little influence on fish orcrustaceans, and bank profile did not influence thedistribution of any of the taxa examined. The taxon-specific responses to different habitat categories meantthat no single habitat category could be identified ashaving an overriding importance for all taxa relative toalternative categories (Figs. 2–11). However it was clearthat depth and bank architecture had much greaterinfluences on the patterns of distribution of small fishand crustaceans than current velocity or hydrodynamicfeatures.

The lack of importance of bank slope for any taxawas surprising given that a study in Chesapeake Bay(McIvor and Odum, 1988), in temperate North America,found fish abundance was significantly higher onshallow, low angle accreting banks than on deeper,steeper angled, erosional banks. Separating the influ-ence of depth from bank slope is difficult. The twohabitat categories are intrinsically linked because lowangle banks will have a greater area of shallow wateravailable than steep angle banks. McIvor and Odum(1988) suggested that their result may have beenbecause of reduced predator pressure due to shallowwater, a longer period of access to intertidal areas, or toenergetic advantages through reduced current speeds onlow angle banks. In the present study no taxa showed aresponse to bank profile, whereas depth stronglyinfluenced the distribution of many taxa (Figs. 2–11).The strength of the association with shallow water, andlack of response to bank slope suggest that the


availability of shallow water may alone explain thepattern observed in the Chesapeake Bay study.

Use of shallow low angle banks to gain an energeticadvantage (McIvor and Odum, 1988; Gaudin andSempeski, 2001) suggested that hydrodynamic featuresand current velocities may be important factorsinfluencing the distributions and fishes and crustaceans.However, although many taxa were more abundant inlow velocity areas, and where turbulent flow occurred(Figs. 2–11), current velocity and hydrodynamic featuresplits in the analyses accounted for little of the explainedvariability, indicating relatively minor influences on thedistribution of taxa.

Bank architecture also had a strong influence on thedistribution of fish and crustaceans (Figs. 2–11). In allbank architecture splits higher abundances of taxa wererecorded from drain habitats. Drains and shallow waterhave previously been identified as areas of highabundance of small fish and crustaceans (Rozas et al.,1988), however because different gears were used tosample alternative habitat options in many previousstudies (e.g. Blaber et al., 1989) direct comparisonsbetween alternative habitat options have not usuallybeen possible. It has been suggested that highconcentration of fish in drains is because drains act asconduits through which small fish and crustaceansaccess mangrove forests or other intertidal areas (Rozaset al., 1988). In fact when investigating the use ofintertidal habitat it is common practice to place nets indrainage systems to intercept fish traveling betweenintertidal and sub-tidal habitats. However drains provideareas of shallow water habitat, so a preference forshallow water rather than drains per se could explain thehigher concentrations of fish and crustaceans noted fordrains without the need to invoke a conduit effect. Thusit remains unclear whether drains act as conduits tointertidal areas or play some other role.

In addition to providing access to intertidal areas, oracting as a shallow habitat, drains may be preferredhabitats for small fish and crustaceans because theyprovide greater feeding opportunity. Drains may bemore nutrient rich than non-drain habitats because theypotentially accumulate and concentrate nutrients fromintertidal areas. Such concentrations of nutrients couldpromote increased abundance of small benthic preyspecies. Alternatively drains may simply act to concen-trate pelagic prey such as plankton as tidal water recedesfrom intertidal areas, providing increased feedingopportunities for small fishes. Both benthic-feedingand planktivorous fishes were in highest abundances indrains suggesting increased feeding opportunity couldexist for both feeding groups.

Estuarine ecologists usually present two mainreasons to explain why estuaries function as nurseryareas; reduced predation levels and/or greater availabil-ity of food than alternative nursery areas (Robertson andBlaber, 1992). The first of these, reduced predation, mayresult from three factors, a) availability of large areas ofcomplex habitat such as mangrove forests, b) reducedefficiency of visual predators due to high turbidity,c) availability of large areas of shallowwater that containsfew predators. Many taxa in the present study showed apositive response to small-scale ex-forest habitats thateither provided longer access time to complex intertidalhabitat and/or shallow water. Those habitat preferencespotentially support the idea that predation levels may belower in shallow water. However, Sheaves (2001)suggested that it had not been demonstrated that thereare in fact few piscivores in shallow water and presentedsupport for the alternative idea that predator-mediatedmortality of small fish may be substantial in shallowwater. This argument is supported by data that confirmthere are large numbers of small piscivores in shallowestuarine habitats (Baker and Sheaves, 2005) and thatthose same shallow habitats are used extensively byrelatively large predators (Baker and Sheaves, 2006).

The strong responses of small fish and crustaceans totrip, substrate type, depth and bank architecture haveimportant implications for estuary researchers andmanagers. Examinations of estuarine faunas, for impactassessment, assessments of estuary “health”, or forconservation purposes, will only be representative of thecombination of habitat and substrate types from whichestimates are derived. Estimates of population para-meters, assemblage compositions or overall biodiversitycollected from a single site or at only one time areunlikely to provide a true representation of the fish andcrustacean faunas that utilise a particular estuary, orparts thereof. In addition, although investigations ofspecies utilisation at broad habitat scales (e.g. sandversus mud substrata) may be useful for manyapplications, they only provide an average measure ofassemblage or species response to many smaller-scalehabitats contained within those broad categories. Smallfish and crustaceans utilised all of the ex-forest habitattypes investigated in the present study, however somehabitats were preferred over others and thus may bepotentially more important from a management per-spective. This does not mean however that less preferredhabitats can be ignored. It may be the diversity ofhabitats available that is the major factor contributingto the use of estuaries as nursery areas by small fish andcrustaceans and management decisions should reflectthat diversity and the roles of all (micro) habitat types.


Acknowledgements

We thank the anonymous reviewers for their valuablecontributions to this manuscript. This work was partiallyfunded by the Cooperative Research Centre for CoastalZone, Estuary and Waterway Management. [RH]

References

Baker, R., Sheaves, S., 2005. Redefining the piscivore assemblage ofshallow estuarine nursery habitats. Mar. Ecol. Prog. Ser. 291,197–213.

Baker, R., Sheaves, S., 2006. Visual surveys reveal high densities oflarge piscivores in shallow estuarine nurseries. Mar. Ecol. Prog.Ser. 323, 75–82.

Blaber, S.J.M., Brewer, D.T., Salini, J.P., 1989. Species compositionand biomass of fishes in different habitats of a tropical northernAustralian estuary: their occurrence in the adjoining sea andestuarine dependence. Estuar. Coast. Shelf Sci. 29, 509–531.

De'Ath, G., Fabriscuis, K., 2000. Classification and regression trees: apowerful yet simple technique for ecological data analysis.Ecology 81, 3178–3192.

Gaudin, P., Sempeski, P., 2001. The role of river bank habitat in theearly life of fish: the example of grayling, Thymallus thymallus.Int. J. Ecohydrology Hydrobiol. 1, 203–208.

Gibson, R.N., 2003. Go with the flow: tidal migration in marineanimals. Hydrobiologia 503, 153–161.

Krumme, U., Saint-Paul, U., Rosenthal, H., 2004. Tidal and dielchanges in the structure of a nekton assemblage in small intertidalmangrove creeks in northern Brazil. Aquat. Living Resour. 17,215–229.

Laegdsgaard, P., Johnson, C.R., 1995. Mangrove habitats as nurseries:unique assemblages of juvenile fish in subtropical mangroves ineastern Australia. Mar. Ecol. Prog. Ser. 126, 67–81.

McCune, B., Grace, J.B., 2002. Analysis of Ecological Communities.MjM Software Design, Gleneden Beach, USA. 300p.

McIvor, C.C., Odum, W.E., 1988. Food, predation risk, andmicrohabitat selection in a marsh fish assemblage. Ecology 69,1341–1351.

Robertson, A.I., Duke, N.C., 1987. Mangroves as nursery sites:comparisons of the abundance and species composition of fish andcrustaceans in mangroves and other nearshore habitats in tropicalAustralia. Mar. Biol. 96, 193–205.

Robertson, A.I., Duke, N.C., 1990a. Mangrove fish-communities intropical Queensland, Australia: Spatial and temporal patterns indensities, biomass and community structure. Mar. Biol. 104,369–379.

Robertson, A.I., Duke, N.C., 1990b. Recruitment, growth andresidence time of fishes in a tropical Australian mangrove system.Estuar. Coast. Shelf Sci. 31, 725–745.

Robertson, A.I., Blaber, S.J.M., 1992. Plankton, epibenthos and fishcommunities. In: Robertson, A.I., Alongi, D.M. (Eds.), TropicalMangrove Ecosystems. American Geophysical Union, Washing-ton, USA, pp. 173–224.

Rozas, L.P., McIvor, C.C., Odum, W.E., 1988. Intertidal rivulets andcreekbanks: corridors between tidal creeks and marshes. Mar. Ecol.Prog. Ser. 47, 303–307.

Sheaves, M., 2001. Are there really few piscivorous fishes in shallowwater. Mar. Ecol. Prog. Ser. 222, 279–290.

Sheaves, M., 2006. Scale-dependent variation in composition of fishfauna among sandy tropical estuarine embayments. Mar. Ecol.Prog. Ser. 310, 173–184.

StatSoft, Inc. 2002 STATISTICA (data analysis software system),www.statsoft.com.

Thayer, G.W., Colby, D.R., Hettler Jr., W.F., 1987. Utilisation of redmangrove prop root habitat by fishes in south Florida. Mar. Ecol.Prog. Ser. 35, 25–38.

Vance, D.J., Haywood, M.D.E., Heales, D.S., Kenyon, R.A., Lone-ragan, N.R., Pendry, R.C., 1996. How far do prawns and fish moveinto mangroves? Distribution of juvenile banana prawns Peneausmerguiensis and fish in a tropical mangrove forest in northernAustralia. Mar. Ecol. Prog. Ser. 131, 115–124.

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