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MARINE ECOLOGY PROGRESS SERIES
Mar Ecol Prog Ser
Vol. 220: 201–211, 2001 Published September 27
INTRODUCTION
Variation in distribution and abundance is a central
theme of ecology and basic to both descriptive and
experimental approaches to environmental science.
There are, however, no simple patterns of variation,
which has many implications for the development of
ecological generalizations and predictive models of
patterns of abundance and the processes influencing
such patterns. Variation occurs at a hierarchy of differ-
ent scales, from dispersion within and across patches
of habitat (e.g. Morrisey et al. 1992a, Thompson et al.
1996, Underwood 1996a, Underwood & Chapman
1996), to variation across habitats (e.g. Archambault &
Bourget 1996, Miller & Ambrose 2000) up to distribu-
tions at a biogeographical scale (e.g. Kaustuv et al.
1998). Similarly, on a temporal scale, changes in abun-
dances and distributions can change quite markedly
over periods of days, months, decades, etc. (Menge et
al. 1985, Barry & Dayton 1991, Morrisey et al. 1992b).
The relations between temporal and spatial variation
in abiotic variables and biological patterns and pro-
cesses in aquatic assemblages are poorly understood,
particularly the importance of small-scale variations in
such measures. Patterns of reproduction, recruitment,
dispersal, predation etc., often independent by time
and space (Dayton & Tegner 1984, Chapman & Under-
wood 1998, Underwood 1999), and unpredictable indi-
rect effects of interactions, can strongly influence any
patterns observed (Menge et al. 1994, Menge 1995).
Many marine environments are considered physically
© Inter-Research 2001
*E-mail: colabarr@bio.usyd.edu.au
Comparison of patterns of spatial variation of
microgastropods between two contrasting
intertidal habitats
C. Olabarria*, M. G. Chapman
Centre for Research on Ecological Impacts of Coastal Cities, Marine Ecology Laboratories A11, University of Sydney,
New South Wales 2006, Australia
ABSTRACT: Small-scale spatial variation in the distribution of the macrofauna of marine intertidal
shores has long been recognized, but there have been few quantitative studies about the scales of
patchy distribution of the microbenthos on rocky shores. Patchiness has important implications for
comparative and descriptive studies of distribution and abundance because it confounds comparisons
of abundance at the largest spatial scales unless the smaller scales are appropriately incorporated
into the sampling designs. Spatial variation in the distribution of a number of species of intertidal
microgastropods across 2 different habitats (sediment and coralline turf) in Botany Bay, Australia, is
described using a nested, hierarchical sampling design. Significant variation was detected mainly at
small scales, ranging from less than 1 to 10 m. Moreover, the species showed different patterns of
variation depending on the type of habitat and the time of sampling. There was no relation between
these patterns and the taxonomic relations of the species. These data illustrate the scales of variabil-
ity that must be considered when planning long-term or baseline investigations of microbenthos to
assure that the study adequately represents different habitats and that subsequent ecological infer-
ences are valid.
KEY WORDS: Australia · Intertidal habitats · Microgastropods · Spatial scale · Patchiness
Resale or republication not permitted without written consent of the publisher
Mar Ecol Prog Ser 220: 201–211, 2001
unstable, although the persistence (Dayton & Tegner
1984) of the biological components of these systems is
unclear. Underwood & Denley (1984) emphasized that
predictability of community structure cannot depend
exclusively on ‘typical’ areas but must include consid-
eration of natural variability of the biota and their
environment.
Numerous intrinsic ecological issues require de-
tailed quantitative understanding of the scales at
which there are predictable patterns in the abun-
dances of animals and plants and the natural scales of
variability in these patterns. Understanding the pro-
cesses that regulate structure and dynamics of interac-
tions among species requires recognition of the scales
at which they operate and, therefore, quantitative
description of spatial and temporal variation in abun-
dances and diversity (Livingston 1987, Bourget et al.
1994, Metaxas & Scheibling 1994, Underwood 1996a,
Underwood & Chapman 1998a). In addition, identifica-
tion of scale- and habitat-dependent ecological pat-
terns is central to management of fragmented habitats
(Eggleston et al. 1999), and the statistical interaction
between temporal and spatial variability is the focus of
attention for detecting the magnitude of environmental
perturbations (Underwood 1996b). Therefore, accurate
description of patterns is a prerequisite to the under-
standing of ecological processes, development of gen-
eral predictive models, assessment of environmental
impacts, restoration of habitat and many practical
managerial issues.
Although there is a long history of study of patterns
of distribution and abundance, it has, until recently,
been primarily focussed on responses of organisms to
large-scale physical variables (e.g. patterns of zona-
tion in response to emersion or alongshore changes in
response to wave exposure; Lewis 1964). Recent em-
phasis on the importance of patchiness in ecological
interactions (Pickett & White 1985) has focussed on
the large amounts of variability within and among
patches of habitat, often at small spatial scales (e.g.
Downing 1991, Lohse 1993, Chapman 1994, Chapman
et al. 1995, Farnsworth & Ellison 1996, Thompson et
al. 1996, Underwood 1996a, Underwood & Chapman
1996, 1998a). Such patterns have mostly been de-
scribed for the larger components of fauna on inter-
tidal rocky shores or of benthos in soft-sediments (e.g.
Harris 1972, Coull et al. 1979, Phillips & Fleeger 1985,
Thrush 1986, 1991, Morrisey et al. 1992a,b, Hewitt et
al. 1997, Schneider et al. 1997). These studies indicate
that such patterns are variable and complex. Despite
some studies carried out by Underwood (1996a) and
Underwood & Chapman (1996), there are few com-
parisons of the same suite of species across different
habitats to test models of the importance of species-
specific or habitat-specific characteristics in determin-
ing patterns of and variability in abundance or distrib-
ution.
Diverse assemblages of small marine organisms
occur in many natural habitats, e.g. mussel beds
(Lohse 1993), algal beds (Akioka et al. 1999), kelp
holdfasts (Moore 1973) or sediment (Morrisey et al.
1992a,b). These assemblages often contain many spe-
cies that use similar resources (e.g. grazers on diatoms)
but also different trophic levels (e.g. grazers, preda-
tors, detritivores). Such assemblages have great poten-
tial for measuring changes to biodiversity (Gee &
Warwick 1996) and assessing environmental impacts
(Smith & Simpson 1993). A diverse component of the
assemblage can be found in small patches of habitat
under a variety of different environmental conditions,
they can develop in natural and artificial habitats
placed in different areas (Costello & Thrush 1991), and
they can potentially be transplanted from site to site.
One component of intertidal fauna that forms an
ideal test assemblage for many models of ecological
processes and responses to environmental change are
microgastropods (i.e. gastropods with adult size of
<2 mm) because: (1) they are relatively quick and easy
to identify without killing them; (2) they can be han-
dled, marked (for measures of growth, etc.) and moved
among patches of habitat with little mortality; (3) they
are very diverse and abundant in small patches of
habitat; and (4) they have a wide range of phylogenetic
and trophic levels. Despite their diverse nature, little is
known about the basic ecology of most Australian
microgastropods (Beesley et al. 1998) and there have
been no quantitative descriptions of their spatial or
temporal patterns of variability. However, studies on
the basic ecology and life histories of European micro-
gastropod species are most abundant, and some have
shown the importance of substratum, mortality, re-
cruitment and migration of adults in determining the
pattern of spatio-temporal variation (Smith 1973,
Wigham 1975, Southgate 1982, Fernández et al. 1988).
This paper describes patterns of variability of a sub-
set of microgastropods at a hierarchy of spatial scales
in 2 different habitats (sediment and coralline turf)
on 1 shore. The study was done on a single shore
because many larger intertidal gastropods on these
shores show greatest variability in abundances at
small spatial scales along single shores (Underwood &
Chapman 1996). It is also necessary to determine the
scales of spatial replication needed to sample species
representatively within a shore before valid compar-
isons can be made across shores. The spatial scales in
this study varied from <1 to 300 m. The species were
chosen to represent different species in the same
genus or family and a number of different families
of primarily grazing snails. Coralline turf (i.e. algal
beds composed primarily of erect coralline algae) are
202
Olabarria & Chapman: Spatial variation of microgastropods
potentially very important habitats on intertidal rocky
shores in temperate areas (Akioka et al. 1999). These
habitats may modify the spatial distribution and abun-
dance of associated fauna due to reduction of pre-
dation and protection from wave-exposure, and by
offering different availability of trophic resources
(Grahame & Hanna 1989, Akioka et al. 1999). Inter-
tidal and shallow subtidal sandy habitats are charac-
terized by a high abundance and diversity of infaunal
assemblages.
These data were used to test the hypotheses that:
(1) as has been described for larger intertidal gas-
tropods, most of the spatial variation in abundance of
these microgastropods within each habitat is at small
spatial scales, i.e. processes influencing small gas-
tropods operate with a similar overall influence of
small-scale processes; (2) closely related species show
similar patterns of variation because of their similar
responses to ecological processes; and (3) patterns of
variation are similar across different habitats because
similar processes occur in different habitats. This in-
formation is essential in characterizing variation in
this assemblage and necessary for its use as ‘indicators’
of environmental change. In addition, this study is part
of a larger study of natural temporal change in popula-
tions of individual species and the assemblage and
relations of these patterns to aspects of life histories.
MATERIALS AND METHODS
Sampling design. The samples were collected on an
intertidal shore in the Cape Banks Scientific Marine
Research Area on the northern headland of Botany
Bay, New South Wales, Australia (Fig. 1). Two different
sheltered mid-shore habitats were chosen: coralline turf
on intertidal rock platforms and patches of sandy sedi-
ment among intertidal boulders adjacent to the plat-
forms. The turf was composed of tightly packed
upright branches of coralline algae, primarily Corallina
officinalis Linnaeus, forming a stiff matrix that held
significant quantities of sand. Some patches of turf also
included other taxa of articulated coralline algae (e.g.
Jania spp., Amphiroa spp.).
The design incorporated 4 spatial scales in each of
the 2 habitats. Two different locations were chosen to
represent shores with orientations, slopes and wave
exposures that are typical for the area (Fairweather &
Underwood 1991). Location 1 was oriented to the
south-west with a slope of 10° whereas location 2 was
oriented to the west and a slope of 30°. Both locations
were sandstone platforms and were separated by
about 300 m. In each location, 2 sites (patches within
each of these locations) were randomly selected, 50 m
apart. In each site, there were 2 randomly chosen repli-
cate plots (smaller-scale patches that, in the case of the
algal turf, were physically isolated from each other),
10 m apart. Finally, in each plot (approximately 2 m
2
),
3 replicate cores (potentially patches of habitat of dif-
ferent quality within each plot) were sampled. Each
plot was sampled twice, 2 wk apart, in February 2000.
Previous studies in soft-sediments (Nichols & Thomp-
son 1985, Livingston 1987, Morrisey et al. 1992b) and
in mangroves (Underwood & Chapman 1999) have
shown large variability in the abundance and composi-
tion of fauna over periods of days, weeks or months.
Therefore, the replicate cores were sampled to test the
hypothesis that the patterns of abundance were consis-
tent over short periods of time and to identify the scale
of any spatio-temporal interactions.
Sampling methods. Samples were collected using a
10 cm diameter plastic corer. The corer was pushed
203
Fig. 1. Map of Australia showing the sampling locations within
the study area
Mar Ecol Prog Ser 220: 201–211, 2001
into the sediment to a depth of 5 cm. In coralline turf,
the corer was pushed into the turf and the algae and
sediment inside the corer scraped off at the level of the
rock. Because no direct statistical comparisons were
made between habitats, it was not necessary to sample
exactly the same volume of each habitat. Nevertheless,
the turf was approximately 5 cm thick. A 10 cm corer
was used because previous studies of the fauna in
coralline turf in this area showed that the precision
of the estimates of abundance obtained with this size
of core was acceptable (SE/x <0.06; B. Kelaher pers.
comm.).
A pilot experiment was done on the fauna in
coralline turf in order to evaluate the optimal number
of replicates needed to provide a good estimate of
spatial and temporal variability, while minimizing the
amount of time taken to sort the samples. Twelve
cores were taken from each of 2 plots (10 m apart) in
each of 2 sites (50 m apart) in 1 location. The 5 most
abundant species were sorted and the abundances
analyzed by ANOVA. The purpose was to determine
the minimal size of sample that could reliably mea-
sure abundance at a specific time. If estimates at a
single time were imprecise, differences from time to
time in any analysis of temporal change would be
confounded with equally large spatial variation. For
each analysis, the factors were ‘sites’, ‘plots’ nested
within sites and ‘times’, i.e. different subsets of repli-
cates chosen randomly from the sample of 12 to repre-
sent different times of sampling (although all repli-
cates were, in fact, collected at the same time). For
each set of analyses, different numbers of replicates
were used, i.e. n = 2, n = 3, n = 4 and n = 6, picked at
random from the 12 available (each with 1000 ran-
domizations for each species and each experimental
design). The frequency of significant temporal varia-
tion in these analyses provided information about the
probability of detecting real temporal variation with-
out confusion from spatial variability of very patchily
distributed animals using small sample sizes. These
data also allowed comparison of the spatial patterns
using different numbers of replicates.
Samples were fixed in 7% formalin in seawater and
sieved through a 63 µm mesh. Eleven species of micro-
gastropods from a variety of families were selected for
analysis because they occurred in the 2 habitats, were
relatively abundant in at least 1 of these habitats dur-
ing this study and represent different species within a
range of families (Table 1). Despite their large abun-
dances in some habitats, there is little information
about their basic ecology (Beesley et al. 1998). Most
are thought to feed on micro-algae, diatoms and detri-
tus, as inferred from the structure of their radulae,
although Omalogyra liliputia probably feeds on the
cell contents of larger algae, such as Ulva spp. (Ponder
& Keyzer 1998).
Analyses of data. Abundances of each species in
each habitat and for each time were separately ana-
lyzed using nested ANOVA (locations, sites[locations]
and plots[sites]) to get 2 independent measures of:
(1) the scales at which there was significant spatial
variability, and (2) the components of variation at each
spatial scale. In addition, the data were re-analyzed
with time of sampling as a 4th factor to measure the
spatial scale(s) at which there was short-term (2 wk)
temporal interaction in these populations. All factors,
spatial and temporal, were random. Homogeneity of
variances was examined using Cochran’s test, and in
no case was it necessary to transform the data.
RESULTS
Pilot experiment
For all the species analyzed, the frequencies of sig-
nificant temporal variation were low (<6.5%) and were
very similar when using different numbers of repli-
cates (i.e. n = 2, n = 3, n = 4 and n = 6). These results
indicated that whatever samples we used we obtained a
204
Superfamily Family Species
Cingulopsoidea Eatoniellidae Eatoniella atropurpurea (Frauenfeld 1867)
Crassitoniella flammea (Frauenfeld 1867)
Cingulopsidae Eatonina rubrilabiata Ponder & Yoo 1980
Pseudopisinna gregaria gregaria Laseron 1950
Rissooidea Anabathridae Amphithalamus incidata (Frauenfeld 1867)
Scrobs luteofuscus (May 1919)
Scrobs elongatus Powell 1927
Pisinna olivacea (Frauenfeld, 1867)
Anabathron contabulatum (Frauenfeld 1867)
Rissoelloidea Rissoellidae Rissoella confusa roberstoni Ponder & Yoo 1977
Omalogyroidea Omalogyridae Omalogyra liliputia (Laseron 1954)
Table 1. Taxonomic relations of the species of microgastropods selected for this study
Olabarria & Chapman: Spatial variation of microgastropods
good estimate of spatial variability of
these patchy snails, without the risk
of confounding with temporal varia-
tion. Moreover, the mean squares
obtained in these analyses showed
a consistent spatial pattern of the
species, independent of the number
of replicates used. Taking this into
account and trying to minimize the
costs and sorting times, we consid-
ered a sample size of n = 3 to be suit-
able for obtaining a good estimate of
variability.
Scales of spatial variation
All except 1 species, Scrobs luteo-
fuscus, showed significant variation
in abundances at some spatial scale
in at least 1 of the 4 experiments
(2 experiments in each of 2 habi-
tats). Nevertheless, scales of varia-
tion differed among species and
habitats, and between the 2 times
of sampling.
For example, abundances of 8 of the 11 species
showed significant variation among plots in the coralline
turf, but only for Crassitoniella flammea and Pseudo-
pisinna gregaria gregaria was this scale significant on
each of the 2 sampling periods, even though these were
only 2 wk apart (Table 2). In addition, for each of these
species, the relative differences in abundances among
the plots varied from one time to the next, i.e. different
plots did not consistently have larger or smaller densi-
ties than other plots (Fig. 2a,b). Similar variability in
plot-to-plot differences were shown for the other spe-
cies, irrespective of whether differences among plots
were significant (e.g. Scrobs luteofuscus Fig. 2c, Eaton-
ina rubrilabiata Fig. 2d). Therefore, as predicted, in
coralline most species showed small-scale variability in
abundances, but these patterns varied across plots and
sites and times of sampling.
Only 3 species, Scrobs elongatus, Rissoella confusa
robertsoni and Omalogyra liliputia, showed significant
variation in abundance in coralline turf at the scale of
205
Family Species Coralline turf Sediment
Location Site Plot Location Site Plot
T1 T2 T1 T2 T1 T2 T1 T2 T1 T2 T1 T2
Eatoniellidae E. atropurpurea ns ns ns ns ns * ns ns ns ns ns ns
C. flammea ns ns ns ns * * X ns X ns X ns
Cingulopsidae E. rubrilabiata ns ns ns ns ns * ns ns ns ns ns ns
P. gregaria gregaria ns ns ns ns * * ns ns ns ns ns ns
Anabathridae A. incidata ns ns ns ns ns * ns ns * ns ns ns
S. luteofuscus ns ns ns ns ns ns ns ns ns ns ns ns
S. elongatus ns ns ns * * ns ns * ns ns ns ns
P. olivacea ns ns ns ns * ns ns X * X ns X
A. contabulatum ns ns ns ns ns * * * ns ns ns ns
Rissoellidae R. confusa robertsoni *ns ns* nsns ns ns ns ns ns ns
Omalogyridae O. liliputia ns * ns ns ns ns ns ns ns ns ns ns
Table 2. Results of ANOVA for abundances of 11 species of microgastropods in each of 2 habitats measured on 2 occasions (T1
and T2), 2 wk apart. *p < 0.05; ns: p > 0.05; X: insufficient data for analyses. See Table 1 for species abbreviations
Fig. 2. Mean ± SE numbers of individuals per core (n = 3) at each of the 2 times of
sampling (empty and filled bars) for each plot in each location in the coralline algal
turf. (a) Crassitoniella flammea, (b) Pseudopisinna gregaria gregaria, (c) Scrobs
luteofuscus, (d) Eatonina rubrilabiata, (e) Scrobs elongatus. L1: Location 1; L2:
Location 2; p1 to p8: Plots 1 to 8; S1 to S4: Sites 1 to 4
Mar Ecol Prog Ser 220: 201–211, 2001
sites and locations and, again, these patterns differed
between the 2 sampling periods. These differences
were generally due to large abundances at only 1 site
in one of the locations (illustrated for S. elongatus in
Fig. 2e). In no single experiment was there significant
variation at more than 1 scale for any species.
There was very little variation in abundance of snails
at any scale in the sediment. Four species showed sig-
nificant differences in abundances at the scale of sites
or locations, but only Anabathron contabulatum
showed similar patterns of significance over the 2
experiments. Nevertheless, for this species, the differ-
ences in abundances differed between locations from
one time of sampling to the next
(Fig. 3a). No species showed signifi-
cant differences between plots in the
sandy substratum, although many of
the species were found in only 1 or
a few plots (illustrated for Pseudo-
pisinna gregaria gregaria and Eaton-
ina rubrilabiata in Fig. 3b and Fig. 3c,
respectively). The only species that
was consistently found across plots in
the sandy substratum was Amphi-
thalamus incidata (Fig. 3d).
The components of variation for
each of the 4 spatial scales investi-
gated (i.e. <1 m between cores [=
residual], 10 m [between plots], 50 m
[between sites] and 300 m [between
locations]) were independently cal-
culated from the mean square esti-
mates for each habitat, each species
and each time of sampling. There
was very large variability in these estimates between
the 2 times of sampling, and many of the estimates at
the scales of sites or locations were negative, indicat-
ing that the spatial variability at these scales was
underestimated relative to that at the scale of plots
(Underwood 1997). These components of variation
were therefore not formally compared among species
or habitats.
Nevertheless, for all species, very large proportions
of the total variance were found at the scale of cores
within plots (the Residual Mean Squares). These aver-
aged (±SE) 52 ± 5 and 82 ± 4% for the algal habitat
and sediment, respectively (averaged across all species
and the 2 times of sampling). Therefore,
most of the variation in abundances was
at the smallest spatial scale measured
(Table 3). In the coralline algal turf, an-
other 29 ± 4% of the total variation was
found at the scale of plots (ignoring 2
estimates out of 22 that were negative
and, therefore, slightly overestimating
this estimate). Similar calculations were
not done for the sediment because of
the larger number of negative esti-
mates. For all species in each habitat,
therefore, most variation was at the
smallest spatial scales, particularly for
the sediment (Table 3).
Because most of the variation in
abundances was at the smallest spatial
scale measured, the tests of the hy-
potheses that densities of the different
species are spatially correlated used
the number of individuals per core
206
Fig. 3. Mean ± SE numbers of individuals per core (n = 3) at each of the 2 times
of sampling (empty and filled bars) for each plot in each location in the sandy sed-
iment. (a) Anabathron contabulatum, (b) P. gregaria gregaria, (c) E. rubrilabiata,
(d) Amphithalamus incidata. See Fig. 2 for species and other abbreviations
Coralline turf Sediment
Time 1 Time 2 Time 1 Time 2
Plot Residual Plot Residual Residual Residual
(L × S) (L × S)
E. atropurpurea 24.91 51.69 40.69 20.76 66.66 97.64
A. incidata 29.21 54.29 32.25 51.24 83.33 73.49
E. rubrilabiata 37.88 45.84 18.91 27.92 64.28 94.44
S. luteofuscus 8.04 91.96 0 94.44 79.38 82.21
S. elongatus 26.06 27.67 – 59.09 88.13 76.74
P. gregaria gregaria 35.89 57.02 65.26 19.14 70.73 100
P. olivacea 40 60 33.33 66.66 42.10 No test
R. confusa roberstoni 15.38 61.53 – 36.73 100 100
O. liliputia 4.61 84.61 22.35 63.41 76.54 63.62
C. flammea 60 20 37.03 59.25 No test 90.1
A. contabulatum 33.30 58.33 53.60 22.68 99.92 90.1
Table 3. Variance estimates (%) derived from ANOVA for selected taxa from the
2 types of habitats (calculated according to Underwood 1997; –: negative esti-
mates). Only variance estimates at small scale of cores (the residual) and plots
from algal turf, and cores from sediment are shown. L: Location; S: Site.
See Table 1 for species abbreviations
Olabarria & Chapman: Spatial variation of microgastropods
(tested for correlation using Pearson’s r). Because
many species were very patchy and present in only a
few cores at any one time, these tests were restricted
to those species that were relatively widespread, i.e.
found in 75% or more of the cores in any habitat at
either time of sampling. These species were Amphi-
thalamus incidata, Eatoniella atropurpurea, Pseudo-
pisinna gregaria gregaria, Omalogyra liliputia and
Eatonina rubrilabiata.
Only 3 of the correlations were significant; numbers
of Amphithalamus incidata and Eatoniella atropur-
purea were positively correlated at each time of sam-
pling (r = 0.49, p < 0.05 and r = 0.70, p < 0.01, respec-
tively; Fig. 4a) and A. incidata and Pseudopisinna
gregaria gregaria were positively correlated during the
second sampling period (r = 0.80, p < 0.001; Fig. 4b).
For most species, despite very patchy distributions at
very small spatial scales, densities were not correlated
among species or abundances were too patchy for
analysis, especially in the sediment.
Despite this small-scale patchiness (Figs 2 & 3), there
were substantial differences among species in their
distributions and abundances in the 2 different habi-
tats (Table 4). All species except Scrobs luteofuscus
were more abundant in coralline turf than in sediment,
although the magnitude of these differences varied
markedly. These patterns showed no relation to the
taxonomic relations of the different species. For exam-
ple, the increase in abundance between the algal and
sediment habitat for the 2 species in the Eatoniellidae
varied between 700× for Eatoniella atropurpurea and
15× for Crassitoniella flammea (Table 4). Similarly, the
2 species of Scrobs showed different patterns, with S.
luteofuscus more abundant in sediment and S. elonga-
tus more abundant in coralline turf. In general, E.
atropurpurea, Amphithalamus incidata and Pseudo-
pisinna gregaria gregaria were the dominant species
in coralline turf, while A. incidata and S. luteofuscus
were the only 2 relatively abundant and widespread
species in sediment.
Although temporal variability at different temporal
scales is the focus of a related study, the consistency
of these spatial scales of variation over a 2 wk period
was examined using ANOVA for each species and
each habitat separately. There were significant inter-
actions among patterns in time and space in 6 spe-
cies (Eatoniella atropurpurea, Crassitoniella flammea,
Pseudopisinna gregaria gregaria, Pisinna olivacea,
Anabathron contabulatum and Rissoella confusa ro-
bertsoni). All showed significant interactions in abun-
dances in the coralline turf, except for P. olivacea,
which showed similar interactions in sediment, so
patterns of spatial variability in this latter habitat
were more consistent through time. Moreover, most
interactions were at the ‘plot’ scale (E. atropurpurea,
F
4, 32
= 3.71, p < 0.05; C. flammea, F
4, 32
= 5.37, p <
0.01; P. g. gregaria, F
4, 32
= 9.77, p < 0.001; A. contab-
ulatum, F
4, 32
= 2.70, p < 0.05), except for P. olivacea
(F
2, 36
= 9.01, p < 0.001) and R. confusa robertsoni
(F
2, 36
= 6.93, p < 0.01), which varied temporally at
the ‘site‘ scale.
207
Fig. 4. Significant correlations between (a) the numbers of A.
incidata and E. atropurpurea and (b) A. incidata and P. gre-
garia gregaria per core in coralline turf at the 2 times of sam-
pling (time 1: empty symbols, time 2 filled symbols. See Fig. 2
for species abbreviations
Species Coralline turf Sediment
E. atropurpurea 349.7 ± 40.9 0.5 ± 0.2
C. flammea 1.5 ± 0.6 0.1 ± 0.1
E. rubrilabiata 16.4 ± 2.5 1.1 ± 0.6
P. gregaria gregaria 35.6 ± 7.2 0.2 ± 0.1
A. incidata 51.2 ± 8.0 4.1 ± 0.4
S. luteofuscus 1.3 ± 0.4 6.8 ± 4.2
S. elongatus 1.3 ± 0.5 0.0 ± 0.0
P. olivacea 2.0 ± 0.4 0.0 ± 0.0
A. contabulatum 2.7 ± 1.0 0.1 ± 0.1
R. confusa roberstoni 2.8 ± 0.7 0.1 ± 0.0
O. liliputia 12.4 ± 1.7 0.6 ± 0.2
Table 4. Mean ± SE number of individuals per core for each
species, averaged over the 2 times of sampling and all spatial
scales (n = 48). See Table 1 for species abbreviations
Mar Ecol Prog Ser 220: 201–211, 2001
DISCUSSION
This mensurative study showed that abundances of
microgastropods in coralline turf and sandy habitats
are patchy at a number of different spatial scales, and
this varied according to habitat. In each habitat, most
variation was, as predicted, at the smallest spatial
scale, i.e. among small cores of each habitat, spaced
approximately 1 m apart. This was particularly the
case in the sediment where more than 80% of the vari-
ation was found among replicate cores within 2 m
2
sites. This small-scale variability is similar to patterns
shown for other intertidal gastropods (e.g. Underwood
& Chapman 1996) and benthic macrofauna (e.g. Mor-
risey et al. 1992a) and re-emphasizes the need to accu-
rately quantify patterns of abundance at a hierarchy of
scales for understanding ecological processes (Bourget
et al. 1994), measuring patterns of biodiversity (Under-
wood & Chapman 1998a) and assessing environmental
impacts (Underwood 1996a,b).
With respect to the consistency of patterns of varia-
tion across species and habitats, there were relatively
consistent patterns between the 2 types of habitat. Ten
of 11 species were more abundant in coralline turf
than in sediment. For most species, despite the large
amounts of small-scale variability among cores in each
plot, there were also significant differences in abun-
dances between plots (10 m apart) in turf in at least one
of the sites during one or both experiments. In sedi-
ment, significant spatial variation was less common, but
when found, was generally at the larger spatial scales
of sites and locations. Nevertheless, examination of the
mean abundances indicated that most species in sedi-
ment were common in only one or a few sites; no spe-
cies was consistently found in greater numbers in all
sites in one location compared to another location.
In addition, patterns of variability varied from
one period of sampling to another, 2 wk later, in the
coralline algal habitat where the animals were abun-
dant, but not in the sediment. Again, this was generally
manifested at the smallest spatial scale, i.e. densities
varied from time to time at the scale of plots. With more
detailed sampling designs, such small scales of spatio-
temporal interaction are becoming more apparent as
an essential feature of natural ecological variation (e.g.
Morrisey et al. 1992b, Thrush et al. 1994, Underwood &
Chapman 1998b).
The spatial patterns of abundance therefore varied
among species, habitats and times of sampling, and
there was no close correlation between spatial patterns
of abundance and taxonomic relations of the different
species. The species responded to the spatial arrange-
ment of habitats in a landscape according to the patch-
iness of habitat at a number of spatial scales, the type
of habitat, environmental conditions (times of sam-
pling) and characteristics of the species (e.g. McNeill &
Fairweather 1993, Egglestone et al. 1999).
At the scale of habitat, although all species were
found in each habitat, only 1 of the 11 was more com-
mon in the sediment than in the coralline turf.
Coralline turfs are structurally complex matrices,
offering invertebrate animals refuges from predation
(Akioka et al. 1999) and potentially a greater diversity
and quantity of food (Edgar 1990, Bell et al. 1993).
Coralline turf can result in greater rates of survival
than in unvegetated habitats for many small organisms
(Heck & Crowder 1991). Whether the differences in
abundance between the 2 types of habitat identified in
this study are due to differences in mortality, recruit-
ment or emigration and immigration is not, at this
stage, known.
Numerous factors influence spatial heterogeneity in
the distribution of organisms within habitats. Com-
monly, large-scale abiotic factors are considered im-
portant in defining broad patterns of distribution
(Lewis 1964, Barry & Dayton 1991). The large differ-
ences in and changes to abundances of microgastro-
pods among patches of the same type of habitat a few
meters apart may also be influenced by recruitment or
mortality. Therefore, variation in the quality of habitat
and limited dispersal may also partly explain their
patchy patterns of abundance, although the patterns
are likely to be modified by the adult animals redistrib-
uting themselves among patches of habitat (Under-
wood & Chapman 1996). Although there are few data
on rates of movement of adult microgastropods among
patches of habitat, the adults appear to be active dis-
persers. New intertidal boulders are colonized by adult
microgastropods within a few days of deployment (M.
G. Chapman unpubl. data) and hundreds of small gas-
tropods appear in new patches of algal turf within a
couple of weeks (B. Kelaher pers. comm.). Many gas-
tropods respond to small-scale features of their habi-
tats and aggregate in response to cues from the habitat
and each other. As a result, a change or difference in
density in any area can potentially result in quite dif-
ferent responses and patterns of variance (Underwood
& Chapman 1992, Underwood 1996a). Short-term, dy-
namic patterns of immigration and emigration among
patches of habitat are an important aspect of the eco-
logy of small benthic animals, with strong local influ-
ences on patterns of abundance and distribution (e.g.
Barnes 1998). Moreover, variations in recruitment
rates can be a major cause of spatio-temporal variabil-
ity among different habitats (e.g. Littorina acutispira;
Underwood & McFadyen 1983).
The heterogeneity of coralline turf is likely to affect
the patchy distribution and abundance of microgas-
tropods that associate with fronds or live among the
trapped sediment. Most of the microgastropods in this
208
Olabarria & Chapman: Spatial variation of microgastropods
study appeared to be associated with the sediment
among Corallina, except for Eatoniella atropurpurea
and Omalogyra liliputia. In the study area, the co-
ralline turfs showed a great variability in compactness,
which may influence detrital accumulation, thereby
affecting sediment-dwelling populations. Small-scale
changes in physical characteristics associated with
such algae, such as accumulation of detritus and
changes in water flow, have also been reported to
directly or indirectly alter faunal abundance (Eckman
1987, Edgar et al. 1994).
Patchiness in the distribution of invertebrates in
sediments has also been reported at small scales (e.g.
Volckaert 1987, Morrisey et al. 1992a,b). Processes
influencing distributions of organisms may change
with scale (Thrush et al. 1994, 1997). For example,
Hewitt et al. (1997) identified variable relations
between adult and juvenile bivalves with changes in
spatial scales in sediment. Although this variability is
sometimes attributable to small-scale environmental
or biological variables (e.g. Bell et al. 1978, Bell &
Coen 1982, Thrush 1986), much is still inexplicable
with no clear environmental correlate(s). Similarly,
patchiness and short-term variation in abundance and
distribution of organisms have been shown in man-
groves (Underwood & Chapman 1999) and intertidal
rocky shores (Underwood & Chapman 1996, 1998b),
although the latter have been focussed on large com-
ponents of macrofauna. Nevertheless, studies on the
spatio-temporal variability of faunal assemblages in
algal turf have rarely been investigated or have been
poorly done. As 2 examples of many, Hull (1997)
examined seasonal changes of ostracods in only 1
patch of habitat, ignoring any potential variability at
other spatial scales. In addition, Davenport et al.
(1999) compared epifauna associated with 4 species of
algae with each collected in a different patch (<5 m
apart), thus confounding species-specific and small-
scale spatial variability.
This well-replicated mensurative experiment com-
paring a number of different species showed 2 strik-
ing features: first, the difference in the scales of spa-
tial variance for 1 species from habitat to habitat; and
second, the different spatial patterns of variation
among closely related species, which (according to
the limited literature available) were expected to have
similar requirements for resources. Although all spe-
cies examined occur in sediment and algal turfs, these
obviously provide a different quality of habitat for the
different species, but this is reflected in different pat-
terns of variability. Spatial variation of invertebrates
at different scales among habitats may be due to a
real difference in the ecological processes operating
from habitat to habitat, or simply spatial variation
due to stochastic variability from one site to another
(Underwood 1996a). Furthermore, the lack of correla-
tion between patterns of variability and taxonomic
relations of the different species indicate that each
species responded differently to ecological processes.
These results underline the need to incorporate com-
parisons across habitats and species-level discrimina-
tion in any study about spatio-temporal variability at
small scale.
Therefore, the present study has important conse-
quences for studies of the distribution of microgas-
tropods in different intertidal habitats, including those
concerned with environmental monitoring. Coherent
predictions about potential changes to populations in
response to disturbances require understanding of
interactive variances. An impact is definable in terms
of change in the variance component that is associated
with differences between abundances of populations
in disturbed and control sites before and after the dis-
turbance (Underwood 1996b). As a first step to mea-
suring impact it is necessary to have quantitative data
on natural patterns of spatial and temporal variation.
Furthermore, to understand how and to predict under
what circumstances impacts occur, it is necessary to
know how and why the populations vary from place to
place or time to time.
As mentioned above, many ecological and environ-
mental studies are unreplicated or confounded be-
cause of inadequate attention to spatial and temporal
scales of variance. When the scales at which variation
occurs are not known in advance, sampling using
nested designs can identify the relevant scales of vari-
ability to be incorporated into further research (Caffey
1985, Phillips & Fleeger 1985, Jones et al. 1990, Mor-
risey et al. 1992a,b, Underwood 1997, Underwood &
Chapman 1998b). The scales can be chosen arbitrarily
and adapted to the objectives of the particular study,
although it is often useful to do a pilot study to identify
scales at which variation is significant (Underwood
1997). The importance of the small spatial scales in
patterns of abundance re-emphasizes the need to
incorporate hierarchical scales of variability within
locations for any comparisons among locations, be they
to increase understanding of ecological patterns and
processes, or to identify changes in assemblages in
response to human disturbances.
Acknowledgements. This work was supported by funds from
the Australian Research Council, the Institute of Marine Ecol-
ogy and the Centre for Research on Ecological Impacts of
Coastal Cities. We are grateful to many people for help with
sampling, but particularly Stefanie Arndt, who worked hard
in the field and laboratory. We thank Vanessa Mathews and
Michelle Button for help with the graphics, and L. Benedetti-
Cecchi and A. J. Underwood for commenting on an earlier
draft of this paper. We also thank 3 anonymous referees for
comments that improved the manuscript.
209
Mar Ecol Prog Ser 220: 201–211, 2001
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211
Editorial responsibility: Otto Kinne (Editor),
Oldendorf/Luhe, Germany
Submitted: September 15, 2000; Accepted: February 27, 2001
Proofs received from author(s): September 4, 2001