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th
of recruits on sea-surface temperature to the 11 power; Shkedy and Roughgarden,
1997. The regression was associated with 59 of the variation in numbers of recruits, which is a remarkably good fit for field-derived empirical data.
So, in those systems that conform persistently to one or other end of the gradient of magnitude of recruitment, supply-side models and coupling with upwelling and other
coastal oceanographic processes can provide considerable understanding of and capacity to predict numbers of adults in intertidal populations.
3. Some methodological issues in experimental design
As with many areas of modern ecology, intertidal ecology has been concerned with improvements to its methods, particularly those concerned with the design, analysis and
interpretation of quantitative and experimental data. Some of these contributions are briefly described here.
3.1. Experimental designs: competition The formal analysis of competitive interactions has been fraught with difficulties of
understanding the relevant processes and scales Connell, 1983; Schoener, 1983 and of logical structures in the design of the experiments reviewed by Underwood, 1986a,
1992a. There is no need to repeat the issues for design, but the main points are worth iterating once more because they seem to have eluded some authors. If it is proposed
that two species A and B have negative effects on each other because of their joint needs for some resources Birch, 1957, there are two major procedures. First, the
amount of resource may be manipulated. For example, the amount of food in areas can be experimentally increased or decreased to test the hypothesis that outcomes of
competition will be less or more stark. Second, the numbers of consumers of resources can be manipulated, again to test hypotheses about directions and magnitudes of
interactions among the consumers.
In the simplest experiments, to examine the influence of species B on species A, some relevant density of A must be created in the absence of B. As the second experimental
treatment, the same density of A must be established with a relevant density of B. Thus, the minimal experiment has independently replicated arenas with density N of A and
A
independently replicated areas with N plus density M
of B. To determine the
A B
reciprocal influence of species A on species B, there must also be independently replicated arenas with M of species B alone and M of species B with N of species A.
B B
A
In some studies, the treatments with the two species together can be the same arenas using results for species A and results of species B in analyses; Underwood, 1978a,
1984, 1986a, 1992a; Creese and Underwood, 1982. Sometimes, because of issues of non-independence of data, it will be more appropriate to establish two sets of replicate
arenas for the combined treatment and use one set to provide data for species A and the other set to provide data for species B. Attempts to do such experiments by holding the
total density of organisms constant are confounded. So, some authors investigate the effect of B on A with N individuals of species A in one treatment and a total of N
A .J. Underwood J. Exp. Mar. Biol. Ecol. 250 2000 51 –76
61
summed from species A and B in the other treatment see Underwood, 1986a. The latter alters the mix of species as required by the hypothesis and simultaneously alters the
density of species A. Any comparison between the treatments cannot test the hypothesis as stated see detailed discussion in Underwood, 1986a, 1992a.
It is often the case by hypothesis and wherever per capita influences of com- petitive interactions must be determined, that the influences of each species must
be investigated at several densities. Thus, there must now be different densities of species A N , N , etc., as required. Each of these must also be established at
A A
1 2
the appropriate densities of species B. This creates a two-factorial matrix with N ,
N 1 M , N 1 M , . . . . . . . . . , N , N 1 M , N 1 M , . . . . . . . . . ,
A A
B A
B A
A B
A B
1 1
1 1
2 2
2 1
2 2
etc. as treatments. The analysis of this sort of experiment remains straightforward and can be extended to
make simultaneous comparisons of the influence of several potential pairwise interac- tions. The experiment becomes a little more complex where possible asymmetries
Lawton and Hassell, 1981; Connell, 1983; Schoener, 1983 in the intensity of competition between two or more species must also be investigated. For this to be
possible, an experiment must simultaneously include treatments with the same additions as before, but this time of the same species A added to A; B added to B. For the
simplest case, of one density of species A N and one density of species B M , there
A B
must be treatments N , N 1 M as before, plus N 1 M to determine the magnitude
A A
B A
A
of intraspecific competition, i.e., species A on species A, relative to that of interspecific competition, i.e., species B on species A. Then, there must also be M , M 1 N ,
B B
A
M 1 N to determine the influences on species B. If the asymmetry is to be compared
B B
between the two species, in addition to measuring it for each species separately, there should really also be treatments M ; M 1 N , M 1 N ; N ; N 1 M , N 1 M to
A A
A A
B B
B A
B B
ensure that a comparison of per capita influences does not confound inter- and intra- specific differences with differences in the density of the two species.
These designs and their interpretation have become quite standard in studies of competition on rocky shores. They are well-suited to the manipulation of densities and
composition of grazing species, particularly where the species are abundant, so that experimental plots are small and there are many individuals to make up the experimental
densities.
3.2. Experimental designs: transplantation Another quite common requirement of studies of distributions of organisms across
gradients is to be able to transplant individuals from one part of the gradient to another to test specific types of hypotheses reviewed by Chapman, 1986, 1999; Underwood,
1988; Chapman and Underwood, 1992. For example, suppose there is a gradient in size of mobile animals with smaller ones at higher levels on the shore. In some areas, an
appropriate model to explain the observed pattern is that small animals are more likely for whatever reason to move upshore than are large individuals. Any large individual
wandering at random downshore will tend to stay there, whereas a small animal will move upwards. Reasons for such behaviour include perception of an increased risk of
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predation, even though more food is available at lower levels e.g. Paine, 1969. Larger animals can move to and survive at lower levels because they are less likely to be eaten
by a predator than are the small individuals. Alternatively, in some cases, more food may be available to competitively inferior small individuals at higher levels on the shore
e.g. Wolcott, 1973. So, small individuals keep moving until they find food at the higher levels. There are, of course, other models, but these examples will illustrate the point.
From this model to explain the gradient in size, an appropriate hypothesis is that if some large and some small individuals are transplanted downshore, small individuals
will change their behaviour and will show greater tendencies to move upshore than do large animals, and shown by small ones in the original habitat.
To test the above hypothesis requires appropriate controls for disturbing the animals whilst moving them and for moving them to a new habitat, regardless of it being at a
lower level. Suppose, for example, that individuals put in a new location, wherever it is, are seriously dismayed by unfamiliar surroundings and or by unfamiliar individuals in
those surroundings. As a result, they become disorientated and tend to move more often and to move greater distances upshore, as a response to such disorientation.
Under these circumstances, discovering a greater tendency to move upshore does not unambiguously support the hypothesis. Such a conclusion is potentially confounded with
any effects of disorientation. Appropriate controls must include translocations, i.e., the disturbance of animals that are moved to a new location in the same upper part of the
gradient where they were originally found Chapman, 1986; Chapman and Underwood, 1992. Where such controls have been properly incorporated in experimental designs,
they have often revealed the existence of the potential artefacts Underwood, 1988; Chapman, 1999. The roles, needs and natures of the appropriate controls in such
ecological experiments wherever they are to be done have been greatly elucidated by experimentation on rocky shores.
3.3. Variation in processes and hierarchies in patterns Ecologists studying rocky intertidal habitats have been very concerned with spatial
and temporal variability in the patterns and processes that influence distributions and abundances of animals and plants. Early attempts to fit simple models of zonation e.g.
Colman, 1933; Lewis, 1964, i.e., the replacement of one sub-assemblage by another in discrete and abrupt boundaries between low and high tide, persist in the literature. They
have, however, never been supported by quantitative data and have been refuted by quantitative tests of their predictions Underwood, 1978b; Chaloupka and Hall, 1985.
They are as inaccurate a description of the distributions of species across intertidal gradients as were descriptions of series of communities of plants at different heights on
the Smoky Mountains. The latter were demolished by quantitative sampling by Whittaker 1956.
Instead, there has more recently been a focus on patch dynamics and attempts to understand and model responses to mixtures of disturbances, physical factors and
variable rates and intensities of competition and predation see particularly the mix of theory and experimentation by Levin and Paine 1974 and Paine and Levin 1981. All
of these interacting ecological processes are affected by issues of recruitment see
A .J. Underwood J. Exp. Mar. Biol. Ecol. 250 2000 51 –76
63
particularly the experimental work of Dayton, 1971; Menge, 1976; Sousa, 1979a,b, 1980b; Underwood et al., 1983.
In some parts of the world, however, this is being replaced by an increasing interest in processes operating at different spatial and temporal scales as hierarchies, rather than as
interactions at one place or time of investigation. Some of the background to considering ecological scales in hierarchies was summarized by Allen and Starr 1982. Examples of
the sort of ecological models that involve hierarchies of processes operating at different scales were provided for subtidal kelp-beds in studies by Dayton and Tegner 1984.
In analyses of intertidal habitats, there have been several approaches to considering hierarchies of spatial scales. One was the survey done by Foster 1990. Along the coast
of California, Foster examined a series of typical rocky headlands chosen because they had similar physical characteristics. On each shore, he examined a series of patterns to
determine how widespread or how frequent they were. The object of the exercise was to test predictions derived from models about processes influencing the local structure of
assemblages. So, predation on superior competitive mussels had been proposed as a widespread and important influence on distributions Paine, 1974; see earlier discussion
of keystone predation. Similarly, Foster’s 1982 own work on competition for space between algae was thought to be an important process.
If any of the processes considered was, in fact, important, Foster 1990 hypothesized that the patterns resulting from the processes should be found frequently over a set of
shores for which the processes were claimed to be operating. This hypothesis was not generally supported by the data. Despite objections to this approach Paine, 1991, it has
great merit. If the patterns that are supposed to be the result of some process are not widespread, it is difficult to maintain an argument that the process occurs widely. It is
not ‘nihilist’ Paine, 1991 to question dogma by testing hypotheses about outcomes of supposedly general processes. When predictions fail, new models and understanding are
needed Popper, 1968; Simberloff, 1983; Underwood, 1990. There must usually be a delay between discovering that some previous paradigm must be overthrown because it
has failed and proposing new models that incorporate the older ideas and the new observations that failed to confirm them Kuhn, 1970.
So, this approach examines the frequency of patterns that should result from various processes. An alternative, sometimes called a comparative experimental approach
Menge et al., 1994, uses experimental procedures, done at small scales, but arranged across larger spatial scales. This was used successfully to identify the variable responses
to removals of predatory starfish along a coast-line discussed earlier and to compare this interaction across coastlines Paine et al., 1985. It has also served well to
demonstrate the inconsistencies in colonization and development of algal assemblages on low-shore rocky habitats on the exposed coast-line of New South Wales Chapman
and Underwood, 1998. It was essential for Wethey’s 1984b analysis of short-term variation in settlement of barnacles on British shores and Caffey’s 1982 experimental
tests of hypotheses about the influences of different types of rock on the settlement of barnacles. This approach has, however, not yet managed to synthesize results of some
complex intertidal issues, for example, the timing, frequency and duration of foraging by intertidal homing limpets on British shores Hartnoll and Wright, 1977; Little et al.,
1990; Gray and Naylor, 1996.
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One of the problems with this comparative approach is that it is better to plan the experiments to make specific contrasts interpretable, i.e., to propose and test specific
hypotheses about different types of habitats or weathers, or seasons, etc.. This has numerous advantages over the attempt to gather together the outcomes of various
experiments on similar topics, but done for different purposes without directly comparable designs and without the appropriate spatial and temporal replication see the
discussion in Underwood and Petraitis, 1993.
So, planned comparative experimentation can reveal not only the relevant variation in processes at large spatial scales for example, variations in diets and growth of predators
on shores dominated by different types of prey; Moran et al., 1984, but also the similarities in shores of similar type compared to the differences from one habitat to
another for example, the influences of experimental removals of predatory whelks from two different intertidal habitats; Fairweather and Underwood, 1991. Doing experiments
over short periods, but repeating them in a planned manner over several time-periods had similar advantages for understanding temporal variation Underwood and Chapman,
1992.
The third and final approach to investigating hierarchies in ecological processes and their resulting patterns has been the analysis of the spatial or temporal hierarchy itself.
Some examples showing methods of analysis and results for spatial variation in abundances of intertidal snails and barnacles have been described in Underwood
1996b, and Underwood and Chapman 1996, 1998.
In a comparison of relevant procedures spatial autocorrelation, fractal analysis, block mean square analysis and hierarchical analysis of variance, Underwood and Chapman
1996 found that the traditional hierarchical analyses had considerable advantages. So, for sessile species and species with limited mobility that are typical of denizens on rocky
shores, investigations to test hypotheses at scales from tens of kilometres down to centimetres can be done by sets of experimental or sampling units at small spatial
intervals repeated at sites, locations, etc., that are different distances apart. The other procedures investigated all required much more effort, were very time-consuming to
replicate and impossible to do over very large spatial scales.
The second important result from these types of analyses is that specific hypotheses about a hierarchical series of processes operating simultaneously can be tested in
comparison with each other. So, very small-scale centimetres to metres variation in densities of an intertidal snail can be shown to be the result of small-scale behavioural
responses by individuals to local topography, food, micro-climate. Larger-scale metres to tens of metres variability can be attributed to variation in biological processes of
pre-emption, interference, predation. At yet larger scales tens to hundreds of metres, variation may largely be affected by variations in recruitment or physical disturbances
due to weather. At even larger scales of hundreds of metres to kilometres, there may be consistent variation due to wave-action and storms. Finally, at very large spatial scales
tens to hundreds of kilometres, there may be biogeographic variation caused by consistent latitudinal differences in climate.
Hierarchical analysis of variance is a robust tool for extracting estimates of variance from data collected at these scales, so that comparisons can be made about the relative
magnitudes of such variance e.g. Burdick and Graybill, 1992; Searle et al., 1992;
A .J. Underwood J. Exp. Mar. Biol. Ecol. 250 2000 51 –76
65
Underwood, 1997. Where this has been used for intertidal species Underwood, 1996b; Underwood and Chapman, 1996, the outcome has almost universally been that variation
is very great at the smallest spatial scales. This not only implies a very great importance for small-scale interactions of behaviour and ecology in response to food, micro-climate
and topography. It also, fortunately, justifies assumptions of independence, thus validating experimental manipulations where replicate experimental units have been
separated by a few metres see also Underwood, 1998a.
3.4. Contributions to social uses of ecology Ecological methods used routinely on rocky coasts have also been adapted to help
solve various problems of a practical, environmental nature. Three examples will illustrate the point. First, there have been developments of the asymmetrical sampling
designs needed for detecting and estimating the sizes of environmental impacts reviewed by Underwood, 1994. It has long been realized that impacts can only be
defined and detected as a statistical interaction in time and space Green, 1979. There must be a different pattern of change in some relevant variables from before to after a
human disturbance in the disturbed site compared to undisturbed, reference areas. Routinely, such interactions have been detected using a comparison of the disturbed to a
single undisturbed site BACI procedures; Bernstein and Zalinski, 1983; Stewart-Oaten et al., 1986. These procedures are unreplicated, so the comparison is always potentially
confounded. ‘Beyond BACI’ procedures compare the site disturbed with a sample of undisturbed sites Underwood, 1992b, 1993, 1994 and arose from the asymmetrical
analytical procedures used to analyse competitive interactions Underwood, 1978a, 1984. These procedures have been extended to situations where there are no data before
the disturbance Glasby, 1997.
A more recent approach to this latter problem involves a meta-analysis of a series of paired comparisons, each of one disturbed and a paired undisturbed site McDonald et
al., 1993. Any interpretation of the result of each comparison would be confounded as above, but the whole set of comparisons provides independent replication of the tests,
providing an unconfounded interpretation. In the case of oil-spills, for which these methods were originally used, there may be problems with finding independent sets of
oiled and unoiled sites that did not originally differ and therefore subsequently interact in some important way that has nothing to do with oil-spills Underwood, 1999c.
Nevertheless, these are promising methods in the detection of impacts.
The third example is the recent development Underwood and Chapman, 1998 of univariate analyses of measures of composition and relative abundance of species in
intertidal assemblages to be able to use the previously mentioned hierarchical analyses of spatial variation. The methods generate independent measures of multivariate
differences among replicates in samples at different scales. These can then be analysed by the versatile procedures available for univariate measures Winer et al., 1991;
Underwood, 1997. Such techniques may be helpful in assessments of scales of variation of ecological diversity and for such problems as divisions of coast-lines, habitats,
regions, etc., for conservation, management, establishing marine reserves, etc.
The development of analytical and experimental methodologies capable of dealing
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with the very variable abundances of populations, patchiness of occupation of habitat, rates and intensities of processes influencing densities and sizes and the composition of
assemblages in intertidal habitats is an on-going research programme in intertidal ecology. It is not surprising that some of the outcomes spill into areas of applied
problem-solving.
4. Conclusions
