Austral Ecology (2007) 32, 93–104
10.1111/j.1442-9993.2007.01744.x
Ant mosaics in a tropical rainforest in Australia and
elsewhere: A critical review
NICO BLÜTHGEN1* AND NIGEL E. STORK2†
Department of Animal Ecology and Tropical Biology, University of Würzburg, Biozentrum, D-97074,
Germany (Email: [email protected]);and 2Rainforest Cooperative Research
Centre at James Cook University, Cairns, Queensland, Australia
1
Abstract The concept of ‘ant mosaics’ has been established to describe the structure of arboreal ant communities
in plantations and other relatively simple forest systems. It is essentially built upon the existence of negative and
positive associations between ant species plus the concept of dominance hierarchies. Whether this concept can be
applied to ant communities in more complex mature tropical rain forests has been questioned by some authors.
Here we demonstrate that some previous attempts to prove or disprove the existence of such ant mosaics sampled
by knockdown insecticide canopy fogging in near pristine tropical forests may have been thwarted by poor statistical
power and too coarse spatial resolution, and the conclusions may be highly dependent on ant species and forest
stratum selected for the study. Moreover, the presence or absence of ant mosaics may be driven by the density of
suitable resources. We use an intensively studied ant community in the lowland rainforests of North-East
Queensland, Australia to outline processes that may lead to ant mosaic patterns, reasoning that competition for
highly predictable resources in space and time such as honeydew and nectar is a fundamental process to maintain
the mosaic structure. Honeydew and nectar sources, particularly their amino acids, are of crucial importance for
nourishment of arboreal ant species. We use canopy fogging data from the same site in Australia and from two
mature rainforests in South-East Asia to compare spatial avoidance and co-occurrence patterns implied by ant
mosaics. Significant negative and positive associations were found among the three most abundant ant species in
each dataset. Several problems with such spatial analyses are discussed, and we suggest that studies of ant mosaics
in complex rainforest communities would benefit from a more focused approach on patterns of resource distribution and their differential utilisation by ants.
Key words: ant mosaic, Australia, competition, dominant ant, South-East Asia, tropical rainforest.
THE ANT MOSAIC CONCEPT
In the early 1970s, entomologists studying ants associated with cocoa and other plantation crops, initially
in West Africa and later elsewhere in the world, demonstrated a hierarchical structure to ant communities
in such plantations (Room 1971; Majer 1972,
1976a,b,c, 1993; Leston 1973; Room & Smith 1975;
Room 1975; Taylor 1977; Jackson 1984b; Majer et al.
1994). They observed that two or more species of ants
were typically much more abundant than any other
species and that the areas of activity of these ‘dominant’ ant species in the trees did not overlap. The
patchwork distribution these ants formed was termed
‘ant mosaic’ (Leston 1973). Such dominant ant
species maintain large colonies and are characterised
by their high abundance and activity density, but
*Corresponding author.
†
Present address: Department of Natural Resource Management, University of Melbourne, Melbourne,Vic. 3010, Australia.
Accepted for publication December 2006.
© 2007 Ecological Society of Australia
numerical dominance in ants is often (but not always)
associated with behavioural dominance in terms of a
high inter- and intraspecific aggression and potential
to defend resources and territories against other ants
(Hölldobler 1983; Hölldobler & Wilson 1990; Majer
1993; Andersen 1995; Davidson 1997). Interference
competition between ants can be intense (Jackson
1984a; Fellers 1987; Savolainen & Vepsäläinen 1988;
Andersen 1992; Andersen & Patel 1994). Ant mosaics
may thus largely reflect ongoing or past competition
between the dominant ants involved, leading to mutual
exclusion of the dominant ants’ territories, thereby
avoiding frequent direct confrontations which may be
costly. Majer (1976c) showed how the experimental
removal of a colony of a particular dominant ant
species leads to replacement by a neighbouring colony
from a different species, this providing strong evidence
for competitive release. Species-specific microhabitat
requirements may play an additional role in shaping
the ants’ distribution (Leston 1973; Majer 1976c;
Andersen 1995; Way & Bolton 1997).
Besides mutual exclusion between dominants,
nearly all ant mosaics described to date also
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N. B L Ü T H G E N A N D N. E . S TO R K
included patterns of coexistence, particularly among
non-dominant or submissive ant species within each
dominant’s territory. Both patterns may lead to a
complex situation of significantly negative and positive
associations between species pairs (Room 1971;
Leston 1975; Taylor 1977; Majer 1993; Majer et al.
1994). A number of studies from all tropical continents have contributed to our understanding of ant
mosaics, which appear to be a nearly universal feature
of tropical plantations. Ant mosaics have also been
noted in unmanaged ecosystems, such as mangrove
forests (Adams 1994) and secondary tropical forests
(Leston 1978; Dejean et al. 1994). Ant mosaics have
been the subject of several reviews (Jackson 1984a;
Majer 1993; Dejean & Corbara 2003) and yet only a
few studies have examined ant mosaics in the canopy
of primary rainforest. These include the work of
Dejean and colleagues using the canopy raft and sled
in Cameroon (Dejean et al. 1999; Dejean & Gibernau
2000; Dejean et al. 2000), among other studies
(Blüthgen et al. 2000).
Recently, the existence of ant mosaics in plantations
and, particularly, in mature rainforests has been questioned (Floren & Linsenmair 2000; Ribas & Schoereder 2002).The former authors investigated a highly
diverse canopy fauna in a mature rainforest in Sabah,
Borneo. They made extensive collections of arboreal
ants from 19 individual Aporusa or Xantophyllum trees
in the lower canopy using knockdown insecticide
fogging (Floren & Linsenmair 1997).The collection of
unwanted insects from taller neighbouring trees was
carefully prevented by covering the sampled trees with
sheets (see also Adis et al. 1999). Their statistical
analysis of the resulting data failed to significantly
demonstrate effects of mutual exclusion between ant
species (Floren & Linsenmair 1997, 1998, 2000;
Floren et al. 2001). Aside from these analytical results,
extensive observations in these relatively small crowns
indicated that resource monopolisation by dominant
ants was uncommon on these trees (Floren & Linsenmair 2000; A. Floren, pers. comm. 2006). Floren and
Linsenmair (2000) thus concluded that the diverse
and complex ant communities in rainforest canopies
are more likely structured by stochastic processes
rather than by competitive effects that are the heart of
ant mosaic theory. Moreover, Ribas and Schoereder
(2002) used a different statistical approach based on a
‘checkerboardedness’ index (Stone & Roberts 1990)
to reanalyse several previous studies on ant mosaics
from plantations and secondary forests and failed to
significantly confirm a structured distribution in most
of these studies. They suggested that spatial distribution patterns may not be different from expectations
based on null models and may not necessarily imply
competition between these species. Subsequently,
Floren and Linsenmair (2005) also applied the ‘checkerboardedness’ index to reanalyse their data from the
mature rainforest ant community and found that it did
not deviate significantly from random associations.
The presence or absence of ant mosaics in plantations and forests may be important to understand the
general role of interspecific competition in communities of variable degrees of disturbance and complexity.
Moreover, ant mosaics may also play a fundamental
role for the structure of the arthropod community as a
whole and resulting ecosystem functions. In plantations, certain dominant ants have been shown to play
a crucial role in pest control, while others may be less
effective or even have detrimental net effects (Way
1953, 1963; Way & Khoo 1991; Dejean et al. 1997b).
Moreover, it has been suggested that each dominant
ant species may be associated with a different arthropod fauna, including competitors, prey or trophobiotic
partners tended for honeydew (Bigger 1993). Such
assemblages may vary among dominant ant species
and be relatively distinct (Room & Smith 1975; Majer
1976a). Arthropod assemblages may even change
towards the typical associates of a new dominant ant
species following an experimental removal of the nests
of a previous dominant ant (Majer 1976b). The presence and identity of dominant ants may thus affect the
distribution of other arthropods, either directly or
indirectly, for example, via predation, competition or
via mutualistic interaction. Such effects have been
rarely examined in natural forest ecosystems. For
example, dominant ants have been shown to prevent
colonisation of several common lycaenid caterpillars
on a tree species in Malaysia and tolerate only the
presence of specialised obligate myrmecophile species
(Seufert & Fiedler 1996). For African savanna trees,
Mody and Linsenmair (2004) have shown that the
complex arthropod assemblage changed in a predictable way when ants were excluded, and the effect on
damage by herbivores differed significantly among different dominant species. Hence, the ants’ specific
impact on arthropods potentially translates into plant
performance and may thus provide a keystone function for a variety of ecosystem processes.
The question addressed in our paper is whether the
current sampling methods, sampling scales and classical analytical methods used by most researchers are
adequate to detect the existence of ant mosaics with
sufficient power and reliability. We first illustrate an
example of an intensively studied ant community
which we suggest exhibits a clear ant mosaic pattern in
a relatively simple tropical forest system in North-East
Queensland, describing mechanisms that were found
to be important for competition in this community.We
then compare spatial patterns implied from canopy
fogging at the same site with those from more complex
rainforest communities elsewhere and critically discuss
the methodology, selection of sampling units, characteristics and putative pitfalls associated with analyses
of ant mosaics used to date.
© 2007 Ecological Society of Australia
ANT MOSAICS IN TROPICAL RAINFORESTS
CASE STUDY IN NORTH-EAST
QUEENSLAND
In the coastal lowland rainforest in Cape Tribulation
(Daintree, North-East Queensland, Australia) we used
the canopy crane (Stork 2007) to study processes that
shape the distribution of ants on plants. The rainforest
in this region is regularly disturbed by cyclones, resulting in a relatively open forest canopy not taller than
25–40 m. The 1-ha crane site has 92 species of tree
above 10 cm d.b.h. and about 30 species of vines (see
Laidlaw et al. 2007). Fourteen of the tree species, 10
species of climbing plants, and six understorey shrubs
possess extrafloral nectaries, all of which were most
commonly attended by ants (Blüthgen & Reifenrath
2003). Australian rainforests maintain a large proportion of the continent’s fauna and flora, but are comparatively species-poor in relation to South-East Asian
forests (for ants, see Brühl et al. 1998; Shattuck 1999;
Majer et al. 2001).
A total of 66 species of ants have been collected in
the canopy and understorey at the canopy crane site
and nearby (Blüthgen & Fiedler 2004b; Blüthgen et al.
2004b; see Appendix i for an updated list). Additional
ant species have been found at ground level, although
no extensive search for ants associated with the ground
layer, leaf litter and dead wood has been made. Two
species of ants, Oecophylla smaragdina (Formicinae)
and Anonychomyrma gilberti (Dolichoderinae), are
numerically dominant in the canopy and understorey.
Both species have large colonies that forage on several
neighbouring trees and are clearly mutually exclusive.
At territorial borders, extended combats between
these two species were observed on three occasions,
when a number of workers were killed and, on some
trees, O. smaragdina replaced A. gilberti (N. Blüthgen,
unpubl. obs. 2000). Colonies of A. gilberti nested
exclusively in Syzygium ‘erythrocalyx’ (Myrtaceae) tree
trunks and attended cicadellids and extrafloral nectaries on the same and on several neighbouring trees
(Blüthgen et al. 2004b). Oecophylla smaragdina built
leaf nests in tree crowns and attended large aggregations of hemipterans in the upper canopy, particularly
on vines (Blüthgen & Fiedler 2002), as well as several
extrafloral nectar sources in all strata (Blüthgen et al.
2004b). Both ant species are also highly predatory,
although honeydew and nectar provide a large part of
their nitrogen and carbon budgets (Blüthgen et al.
2003). Oecophylla smaragdina was particularly
common on honeydew and nectar sources with the
highest nutrient quality in terms of amino acids and
carbohydrates, where it often monopolizes these
resources and effectively excludes its competitors
(Blüthgen & Fiedler 2004a). On trails and poorer
nectar sources, it often co-occurred with certain other
ant species, including several species of the genera
Crematogaster, Echinopla and Polyrhachis, but never
© 2007 Ecological Society of Australia
95
with A. gilberti (Blüthgen et al. 2004b). Anonychomyrma gilberti itself was only associated with a small
number of ant species, particularly Polyrhachis spp.
(Blüthgen et al. 2004b). Thus, a specific spectrum of
submissive ants was tolerated by each dominant ant, a
pattern that has also been reported as integral part of
ant mosaics elsewhere (Dejean & Corbara 2003).
STATISTICAL PITFALLS
Historically, in most ant mosaic studies, the association between a pair of species is commonly tested by
c2-statistics or Fisher’s exact tests (Leston 1973, 1975;
Room & Smith 1975; Jackson 1984b; Dejean et al.
1994; Majer et al. 1994). The association is represented in a 2 ¥ 2 contingency table, with two rows for
one species being present or absent, and two columns
for the other species present or absent, respectively.
The total of all cell entries then equals the total
number of sampling units (trees or plots), hence
including units where none of the two species was
present. A critical issue of contingency table analysis
is the statistical independence of count data – an
assumption frequently violated by spatial autocorrelations or genetic relatedness of ant colonies though
processes like colony budding. These pairwise tests
were often applied to many combinations of ant
species, without any corrections for multiple comparisons in order to deal with an increasing global risk of
type I error (i.e. falsely rejecting the null hypothesis).
In contrast, Floren and Linsenmair (2000) examined
63 ant species that occurred on three or more trees,
and tested the co-occurrence of all 1953 combinations
between these species, using c2-tests with a Bonferroni
correction for the number of tests applied. However,
the methodological drawback of this method lies in a
high risk of a type II error (Cabin & Mitchell 2000;
Moran 2003), particularly since the individual tests are
clearly non-independent (Gotelli & Ellison 2004).
Note that there are more sensitive techniques than
(non-sequential) Bonferroni correction, most notably
‘false discovery rate’ (Bejamini & Hochberg 1995), but
they do not entirely reduce the problem. This risk of
incorrectly accepting the null hypothesis becomes
excessively large in combination with a small sample
size. Even for a hypothetical case of a complete mutual
exclusion between two highly common ant species on
the 19 trees sampled by Floren and Linsenmair (e.g.
each of the ant species occurred on eight trees without
any overlap), this statistic would not yield a significant
effect. Species were included in the analysis if they
were found on at least three trees, although a complete
exclusion between species that occurred on five trees
each would not cause a significant result in a c2-test,
even before correcting for multiple comparisons.
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N. B L Ü T H G E N A N D N. E . S TO R K
Given the low statistical power, the lack of any significant positive or negative associations in their analysis is
not surprising.
One way to at least partly overcome this problem is
to limit the number of comparisons based on a priori
selection criteria. In true ant mosaics, territorial exclusiveness is limited to dominant ant species with large
colonies, while many other (subdominant and nondominant) ants typically coexist with these dominants
(Majer 1993; Dejean & Corbara 2003). Analyses may
therefore be restricted to dominant species in each
dataset, and hence to the most meaningful comparisons (Leston 1975; Jackson 1984b; Davidson et al.
1989; Bigger 1993). We are aware that any selection is
problematic, as behavioural dominance is a subjective
criterion as long as detailed insights and behavioural
bioassays are unavailable for all species, and behavioural dominance is not necessarily correlated with
colony size and colony abundance. For our analysis
below, we selected the three most abundant species (in
terms of the total number of individuals) that occurred
in three or more sampling units (i.e. funnels, trees, or
plots, respectively).
Two studies (Ribas & Schoereder 2002; Floren &
Linsenmair 2005) have used a statistic derived from
studies of island geographical distribution to test ant
mosaic patterns, namely a randomisation of the
‘checkerboardedness’ or C-score index (Stone &
Roberts 1990). Like several other techniques that
allow a comparison of co-occurrence patterns with
null models (see Gotelli & Graves 1996; Gotelli 2000),
this technique reduces the complex data of positive,
neutral and negative associations between many pairs
of species into a single value rather than showing
the variation of associations. A higher C-score than
expected by a null model suggests that negative associations predominate in the assemblage. Both studies
(Ribas & Schoereder 2002; Floren & Linsenmair
2005) applied this method to entire ant communities,
as well as to reduced datasets from which rare species
or otherwise classified ‘non-dominants’ have been
removed. They tested whether C-scores were higher
than random, implying that negative associations outweigh positive associations in a community structured
by ant mosaics. However, this assumption may not
hold for numerous ant mosaics described, where the
number of significant positive associations reached or
even exceeded the number of negative associations
between abundant species (Room 1971; Leston 1975;
Taylor 1977; Majer 1993; Majer et al. 1994). Therefore, C-scores for ant communities may be expected to
be similar to, or even lower than, those of null models
if positive interactions are common. Results may thus
strongly depend on the restriction of the dataset to
true ‘dominants’ (but see Ribas & Schoereder 2002),
and on the abundance level and criteria used for this
selection. Both types of analyses, the 2 ¥ 2 association
tables and C-score randomisation as used above,
reduce the information of species abundance to binary
data of presence or absence. This approach will be
mostly conservative for detecting negative associations, since it does not account for the numerical effect
observed within areas where different dominant ants
overlap, that is, at least one species is usually not
abundant (Majer 1972; Jackson 1984b; our Fig. 1).
Furthermore, the inclusion of all sampling units
lacking any of the two species into the 2 ¥ 2 association
analysis (but not into C-score) may be conservative for
testing exclusiveness. There has been a controversial
debate about the validity and properties of different
approaches to detect species exclusion in the context
of island biogeography (Grant & Abbott 1980; Gilpin
& Diamond 1982; Manly 1995; Gotelli & Graves
1996; Gotelli 2000). These approaches, and several
other techniques of parametric-free statistics and
simulations, may also include fruitful techniques to
analyse ant mosaics (Floren & Linsenmair 2000,
2005), if the mixture of negative and positive associations is appropriately controlled for and if these
techniques are unaffected by unequal sampling effort
between species-poor and species-rich systems. Moreover, an inclusion of abundance data into such analyses may provide a better statistical power.
DETECTING ANT MOSAICS USING
CANOPY FOGGING
While observational evidence and the distribution
pattern of ants on plants indicate a pronounced ant
mosaic at the study site in Queensland, and the underlying mechanisms at least partly understood (resource
quality), the question remains whether spatial effects of
this mosaic are visible in canopy fogging data. For this
purpose, we used unpublished data from canopy
knockdowns in the same forest performed in 2000
(R.L. Kitching and coworkers, unpublished 2000).
Three 10 ¥ 10 m plots were installed underneath
several tree crowns in the forest, each with 20 halfmetre square collecting trays (Majer et al. 2001). In
total, 29 ant species were collected in these samples,
sorted by one of us (N. Blüthgen) and compared with
specimens from the same site that were identified with
the help of several taxonomists (see Acknowledgements).
We use 2 ¥ 2 contingency tables and correlations
between number of workers to illustrate patterns implying mutual exclusion or positive associations, two
methods which we will critically discuss below, and
restrict our analysis to the three most abundant species.
Oecophylla smaragdina and A. gilberti were the most
abundant ants in the fogging samples, corresponding to
the canopy fogging data from two other sites nearby
(Majer et al. 2001).These species represented 34% and
27%, respectively, of the total 342 individuals and
© 2007 Ecological Society of Australia
ANT MOSAICS IN TROPICAL RAINFORESTS
97
Fig. 1. Abundance of the three most abundant ant species in three canopy fogging samples from mature rainforests from (a)
North-East Queensland, Australia, (b) Sulawesi, and (c) Brunei. Number of ant workers shown for each trap (a, b) or tree (c).
Note that most points are distributed along the axes or close to the axes, while areas between axes are largely empty, thus only
one species was abundant in a tray.The commonly co-occurring Oecophylla smaragdina and Crematogaster cf. fusca (a) provide the
most prominent exception.
occurred in 30 and 18, respectively, of the 60 trays.They
only occurred together in two trays. The exclusive
occurrence of these species is highly significant in a
Fisher’s exact test (Table 1a). In each of the two trays
where O. smaragdina and A. gilberti were collected
together, only a single O. smaragdina worker was caught
© 2007 Ecological Society of Australia
(Fig. 1a). Hence, there was no case where both were
common in the same tray. Consequently, there was a
highly significant negative correlation between the
number of O. smaragdina and the number of A. gilberti
per tray (Spearman rank rS = -0.78, P < 10-6, n = 46
trays with at least one of both species).
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N. B L Ü T H G E N A N D N. E . S TO R K
Table 1. Co-occurrence of the three most abundant ant species in each of the fogging samples from (a) North-East Queensland, Australia, (b) Sulawesi and (c) Brunei, and sampling units analysed were trays (a, b) or trees (c)
(a) Australia, 60 trays
Oecophylla smaragdina
Anonychomyrma gilberti
Crematogaster cf. fusca
(b) Sulawesi, 350 trays
Crematogaster sp.3
Dolichoderus sp.1
Iridomyrmex sp.1
(c) Brunei, 10 trees
Myrmicaria sp.B
Crematogaster sp.B
Myrmicaria sp.A
Ants
117
93
38
n
30
18
24
Ants
581
501
304
n
46
41
64
Ants
1310
789
488
n
7
4
3
O. smaragdina
30
–
2 (–) (P = 0.0001)
18 (+) (P = 0.003)
Crematogaster sp.3
36
–
15 (+) (P < 0.0001)†
15 (+) (P = 0.20)‡
Myrmicaria sp.B
7
–
1 (–) (P = 0.033)
0 (–) (P = 0.008)
A. gilberti
18
–
2 (–) (P = 0.004)
Dolichoderus sp.1
41
–
14 (+) (P = 0.12)§
Crematogaster sp.B
4
–
3 (+)¶
Maximum overlap that would yield a significant negative association: †1 tray, ‡3 trays, §2 trays.
¶
Numbers of occurrences too low to test for significant positive or negative association.
‘Ants’ denotes the total number of ant workers collected, n the total number of sampling units in which each species was
recorded, and each interaction cell provides the number of sampling units where both species overlap. (+) or (–) denote whether
this number was higher or lower than expected by chance, respectively. Significance level shown for Fisher’s exact test, two-tailed.
The third most common ant in this sampling, Crematogaster cf. fusca (11% of the individuals), rarely
overlapped with A. gilberti, but was frequently sampled
together with O. smaragdina in the same tray. Fishers
exact test confirmed a significantly negative association between C. fusca and A gilberti and a significant positive association between C. fusca and
O. smaragdina (Table 1a). A negative correlation was
found between the number of C. fusca versus A. gilberti
workers in a tray (rS = -0.81, P < 10-6, n = 40), while
abundances of C. fusca and O. smaragdina were not
significantly correlated (rS = -0.18, p = 0.28, n = 36)
(Fig. 1a). These fogging data were consistent with
direct observations at nectar sources and trails, where
O. smaragdina and C. fusca were commonly found
together, but neither A. gilberti with O. smaragdina nor
A. gilberti with C. fusca (Blüthgen et al. 2004b). These
three ant species were also the most abundant ones in
the surveys of nectar plants (Blüthgen et al. 2004b),
and among the seven most abundant ones on sugar
baits in the same area (Blüthgen & Fiedler 2004b).
Therefore, behavioural dominance and mutual aggression may be associated with abundance in some cases
(O. smaragdina and A. gilberti), but not in others
(C. fusca).
Can such distribution patterns also be detected in
canopy fogging samples from more species-rich communities that are much less understood? We used the
same approach to analyse two datasets from canopy
fogging in Brunei (northern Borneo) and the Indonesian island of Sulawesi. In the former study, 10 semiisolated trees ranging in height from 30 to 75 m in a
mature lowland dipterocarp forest in Brunei were
fogged and the falling insects were collected on a single
large sheet under each tree (total sheet area under
10 trees = 200 m2). The faunal composition, guild
structure, body size species/abundance relationships,
and factors affecting the similarity of the faunas in the
different trees sampled have been published elsewhere
(Stork 1987, 1991; Morse et al. 1988). In the second
canopy fogging study in Sulawesi, 350 catching trays
(each 1 m2) were placed haphazardly in three
12 ¥ 12 m plots (lowland forest data only), where the
crowns of the trees often overlapped (Stork & Brendell
1990). Totals of 98 and 77 morphospecies, respectively, were identified by Barry Bolton (Natural
History Museum, London) from the Brunei and
Sulawesi samples. The former study is analysed at the
level of individual trees and the latter at the level of
individual trays (data from plots pooled).
The results are shown in Table 1. In Brunei
(Table 1c), two species combinations revealed a significant negative association.The remaining third association seemed to be positive, but could not be tested
given the low sample size of trees (Table 1c). The
analysis of the fogging trays in Sulawesi (Table 1b)
showed a relatively large overlap between the three
most abundant species (one combination was significantly positive). However, this example also illustrates
the low statistical power for detecting negative associations in such a community, since each of the three
species was only found on a relatively small proportion
(12–18%) of the 350 fogging trays analysed. The
threshold for a significantly negative effect in Fisher’s
exact test is very low: for instance, only an overlap in
one or none of the trays would yield a significant
exclusion between the two most abundant species
(Table 1b). The entire analysis is therefore highly
© 2007 Ecological Society of Australia
ANT MOSAICS IN TROPICAL RAINFORESTS
constrained by the abundance of the species in relation
to the number of sampling units (if trays lacking any of
the two species were excluded from the analysis, all
three associations would have been significantly
negative). For the Brunei data, there is a negative
correlation between the abundances of both Myrmicaria species (rS = -0.79, P < 0.01, n = 10), while correlations between each of these with Crematogaster
were not significant (P ⱖ 0.22) (Fig. 1c). For the data
from Sulawesi, abundances of all three species were
strongly negatively correlated (all rS ⱕ -0.51,
P ⱕ 10-6, n ⱖ 72 trays in which at least one species of
each pair occurred). Therefore, while abundance data
clearly suggest negative associations between the three
dominant ant species in Sulawesi (Fig. 1c), this is not
evident in the more conservative approach based on
presence–absence data (Table 1b).
Any analysis based on presence–absence may clearly
underestimate the degree these species avoid each
other, since occasions where a single worker co-occurs
with its putative competitors are evaluated as
co-occurrence in the same way if both species were
common (Jackson 1984b). Correlations between the
number of ants per tray represent a finer scale, but may
be more difficult to interpret as putative effect of competition in relation to null models: a simple patchy
distribution of workers in social insect (irrespective of
competitive interactions) may also lead to negative
correlations of worker abundances if the colony density
is comparatively low. This problem is less evident, but
not absent in the cruder contingency table analyses.
SPATIAL SCALE OF MOSAICS
Social insects such as ants usually show a highly patchy
distribution when they are mapped at a small spatial
scale, especially when nests or resources with mass
recruitment are involved.The above analyses of the ant
distribution patterns in Australia and Sulawesi were
based on single 1-m2 trays. This unit certainly represents only a small fraction of typical ant territories, and
especially so for the dominant territorial species that
create the ant mosaic (if it does exist). On the other
hand, insects captured by each tray may involve a
vertical column of several plant layers which, in
complex forest canopies, could include different compartments of ant mosaics (Majer 1993). Such columns
in pristine forest can be up to 70 m high, as in the case
of some of the Bornean trees, whereas in cocoa plantations, mangroves or secondary forests they may be only
5–20 m high. Hence, the chance of several dominant
species being found in different strata may be increased
in mature forest. Floren and Linsenmair (2000) solved
this problem by restricting their analyses to trees with
relatively small crowns in the subcanopy layer and by
using protective sheets against upper forest layers.
© 2007 Ecological Society of Australia
99
The main statistical problem of an analysis of single
trays (as in Fig. 1a,b and Table 1a,b) is that neighbouring ones may frequently not represent independent units (ant colonies). Data from each tray are thus
prone to spatial autocorrelation, limiting the expressiveness of tests based on trays if not adequately controlled by null models. Correlations between the
abundance of one species in each spatial unit versus
that of another species as used above (see also Majer
1972) may thus have to be interpreted with caution
and can not be seen as direct evidence for competition.
In contrast to single trays, the spatial resolution at the
level of individual tree canopies (all trays pooled) may
be too crude to detect exclusive territories, at least in
complex forest canopies. Despite this crude resolution,
two species pairs in Brunei (Table 1c, Fig. 1c) show a
strong pattern of mutual avoidance on the level of
trees, but other cases involving patterns on smaller
scales may be more difficult to detect. Small isolated
tree crowns in plantations, as in the classic ant mosaic
studies, usually represent small spatial units which ant
colonies may be able to monopolize, sometimes by
defending the trunk or major branches (Hölldobler &
Lumsden 1980). However, in several cases, even such
small tree crowns may harbour nests or areas of activity of two dominant ant species. Such ‘codominants’
on trees in plantations were usually separated vertically
or had different activity schedules or food niches
(Room 1971; Majer 1972, 1976a; Leston 1973; Way &
Bolton 1997). Simultaneous existence of different
dominants may be even more pronounced in large
crowns of rainforest trees where lianas may connect
neighbouring crowns and lead to structurally complex,
intermingled canopy layers. For instance, in an Amazonian rainforest, different dominant ant species and
their trophobionts were found on different branches of
the same large tree crown (Blüthgen et al. 2000). This
spatial complexity is much reduced in small-crowned
isolated forest trees which may be more comparable to
crowns in some tree plantations (Floren & Linsenmair
2000). On the other hand, colony territories of some
dominant ant species may even comprise a number of
adjacent trees (e.g. Hölldobler 1983; Bigger 1993;
Majer 1993). This suggests that detailed mapping of
the distribution of dominant ant colonies within an
area, in conjunction with adequate spatial statistics,
may be a more appropriate approach to analyse ant
mosaics than selecting some non-neighbouring trees as
in the study by Floren and Linsenmair (2000).
WHICH ANT SPECIES ARE CONSIDERED
DOMINANT, AND FOR WHICH RESOURCES
DO THEY COMPETE?
Of course, the restriction of the analysis above to the
three most abundant ant species is rather arbitrary.
100
N. B L Ü T H G E N A N D N. E . S TO R K
There is no clear a priori definition of dominance that
can be applied to an unknown ant community so far.
While experienced myrmecologists have little difficulty
in assigning a species to be dominant, subdominant or
submissive in intensively studied ant communities
(e.g. Hölldobler 1983; Andersen 1995; Dejean et al.
2000), more objective criteria would be needed to
disentangle the relationship between dominance and
other attributes. For example, numerically abundant
species may not necessarily show a high level of interspecific aggression (Davidson 1998). Davidson (1997)
suggests that the most dominant arboreal ants are
characterised by a modified proventriculus that
enables them to effectively harvest honeydew and other
fluids, associated with a high level of carbohydrate
feeding, carbohydrate-based defence and high ‘tempo’ activity (see also Davidson et al. 2004; Davidson
2005). Such species usually come from a restricted
number of predictable phylogenetic groups, involving
genera or species that are dominant both in plantations
as well as in mature rainforests; examples include
Crematogaster, Dolichoderus and some Camponotus
(worldwide), Oecophylla (palaeotropics) and Azteca
(neotropics) (Majer 1993; Davidson 1997). The high
taxonomic similarity between dominants in tropical
plantations versus forest canopies suggests that similar
ecological interactions may be found in these
ecosystems.
Most dominant arboreal ants are omnivorous, but
feed extensively on honeydew in trophobiotic associations with hemipterans or lycaenids in plantations
(Room & Smith 1975; Jackson 1984b; Bigger 1993)
or natural ecosystems (Davidson 1997; Dejean et al.
2000; Fiedler 2001). Ants usually monopolize such
trophobionts by effectively excluding their competitors
(Dejean et al. 1997a; Blüthgen et al. 2000, 2004b,
2006). Honeydew and nectar may provide spatiotemporally relatively constant, renewable rewards for
which ants may compete (Jackson 1984b; Blüthgen
et al. 2000; Hossaert-McKey et al. 2001). In contrast,
prey and food items collected by opportunistic scavengers may be typically more scattered, less predictable, and usually replenish following a brief period of
consumption. Therefore, if territorial defences aim to
directly defend resources (rather than spaces that may
potentially include resources), ant territoriality may be
expected to be particularly pronounced for qualitatively and quantitatively rewarding honeydew and
nectar sources. Among such liquid food sources, many
honeydew sources tend to be more productive, contain
more amino acids, and are spatially more concentrated
compared with most extrafloral and floral nectar
sources (Blüthgen et al. 2004a; N. Blüthgen pers. obs.
2000). Many dominant canopy ants obtain a large
proportion of their nitrogen requirements for larval
growth from amino acids in honeydew and/or nectar
(Blüthgen et al. 2003; Davidson et al. 2003). These
features also apply to mound-building wood ants
(Formica) (e.g. Savolainen & Vepsäläinen 1988), suggesting that high levels of trophobioses are indeed
characteristic for many territorial dominant ants
worldwide.
Studies in mature rainforests have shown that anthemipteran aggregations can be abundant (Blüthgen
et al. 2000; Dejean et al. 2000). On all 10 upper
canopy trees sampled in Brunei, hemipterans were
abundant, contributing to 7.0–26.0% of the arthropod
individuals per tree (Stork 1991). These hemipterans
were dominated by cicadellids and membracids with
an average of 47 species per tree (N. Stork, unpubl.
data 1982). Many species from both taxa are strongly
tended by ants for honeydew (Delabie 2001; Blüthgen
et al. 2006). Hemipterans in the canopy investigated in
Sulawesi contributed between 2.8% and 12.3% of the
individuals in different plots (Stork & Brendell 1990).
These figures certainly underestimate the abundance
of hemipterans, since several sessile hemipterans such
as scale insects whose stylets are firmly inserted into
the plant tissues are poorly captured in canopy foggings or not at all (Dejean et al. 2000). However, these
taxa can play a major role as honeydew producers and
are commonly attended by ants in rainforests (Dejean
et al. 2000; Blüthgen et al. 2006). Aggregations of anttended hemipterans often occur in the upper canopy
or in forest gaps (Blüthgen et al. 2000, 2006), so light
availability might play an important role. Plant productivity affects the quality and quantity of honeydew,
and both homopterans and ants might actively seek the
most productive parts of the plant, with ants being able
to actively transport some homopterans to their
feeding sites (Way 1963). Consequently, hemipterans
in forest canopies are typically confined to the outermost twigs on trees and climbing plants where the
stem and leaf tissue is relatively young (Blüthgen et al.
2000; Blüthgen & Fiedler 2002). Floren and Linsenmair (1997, 2000), studying trees of the lower canopy
that were always exceeded in height by trees of the
upper canopy, found no spatio-temporally constant
trophobiosis between ants and hemipterans. Only 1.7–
11.6% of the individuals in their samples were hemipterans (Floren & Linsenmair 1997), less than in the
Brunei data from Stork (1991). The absence of pronounced trophobiotic associations as defendable
resources may indeed be a major reason why ant
mosaics could be non-existent. In summary, lower
canopy trees may have much fewer rewarding and
stable resources for ants to compete for than the upper
canopy, and hence ant mosaics may be less evident or
absent in the lower canopy than the upper canopy.
While few studies have indicated the importance of
honeydew and nectar use by ants in rainforest canopies by canopy observations (Blüthgen et al. 2000,
2004b; Dejean et al. 2000) or indirectly by stable
isotope analysis (Blüthgen et al. 2003; Davidson et al.
© 2007 Ecological Society of Australia
ANT MOSAICS IN TROPICAL RAINFORESTS
2003), honeydew productivity and availability has not
been quantified in upper and lower rainforest
canopies.
OUTLOOK
Overall, we suggest that effects of competition
between ants in species rich communities may need
to be investigated with higher spatial resolution and
statistical power. Until tests with an appropriate
spatial scale and statistical power are applied, it will
be impossible to decide whether patterns such as ant
mosaics do not exist or are just more difficult to detect
in complex communities compared with plantations.
Our data from Brunei strongly suggest the presence
of ant mosaics in the upper forest canopy. Moreover,
while the term ‘ant mosaic’ as defined by Leston
(1973) implies a merely static spatial pattern, such
spatial patterns are based on behavioural or ecological
processes and may be relatively dynamic. Spatial distribution is only a rather indirect measure or consequence of complex competitive interactions and may
not necessarily reveal underlying structural mechanisms of competitive hierarchies in ant communities
(see Jackson 1984a). Therefore, an increased focus on
the ants’ behavioural interactions (Hölldobler 1979,
1983; Adams 1994; Mercier et al. 1998), colonisation
abilities (Greenslade 1971; Yu et al. 2001) or interaction with natural resources (Davidson 1997;
Hossaert-McKey et al. 2001) may be more fruitful
than a sole focus on static spatial distribution patterns
of workers or colonies. A survey of honeydewproducing hemipterans and associated ants in different strata of mature forests would be required to
evaluate the potential of stable resources as a basis for
ant mosaics. Bait experiments may provide a good
picture of ant activity and competitive interactions,
combined with a much higher statistical power than
usually provided by spatial mapping (Andersen 1992;
Andersen & Patel 1994; Yanoviak & Kaspari 2000;
Floren et al. 2002; Blüthgen & Fiedler 2004b; Gibb &
Hochuli 2004), although the criticism that the quality
and spatial concentration of many typical baits may
not always reflect natural resources may be valid (Kay
2002; Ribas & Schoereder 2002). Moreover, experimental manipulations may be a very fruitful approach
to study competition in general (Schoener 1983), specifically in ant communities where a dominant ant
can be removed to study the effects on competitive
release (Majer 1976c; Perfecto 1994; Gibb & Hochuli
2004). Finally, a clearer definition and better understanding of ‘dominance’ in ants and its relationship to
colony size and local abundance is needed to allow
more precise predictions about structural patterns in
ant communities.
© 2007 Ecological Society of Australia
101
ACKNOWLEDGEMENTS
We thank Alan Andersen, Brian Heterick, Rudy
Kohout, Hanna Reichel and Steve Shattuck for their
help with identification of Australian ants, Barry
Bolton for identification of the South-East Asian ants,
and Roger Kitching and his team for providing the
ants from their fogging samples in Australia. We thank
Konrad Fiedler for his continuous advice during the
field work in Australia and helpful comments on
the manuscript, Rob Dunn and Jonathon Majer
for providing insightful comments, and K. Eduard
Linsenmair and Andreas Floren for stimulating this
discussion as well as providing helpful comments on
earlier versions of the manuscript. Field work in
Australia was kindly supported by the Deutsche
Forschungsgemeinschaft (Fi 547/9-1), by Fuchs Oils
(Mannheim/Sydney) through the Australian Canopy
Crane company, and by a doctoral fellowship of the
Studienstiftung des deutschen Volkes to N.B.
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APPENDIX I
Ant species collected from the canopy
and under-storey vegetation at the
Australian canopy crane site (Cape
Tribulation, North-East Queensland)
and surrounding forests
Subfamilies: DOL, Dolichoderinae; FOR, Formicinae; MYR, Myrmicinae; PON, Ponerinae; PSE,
Pseudomyrmecinae.
Anonychomyrma gilberti (DOL), Camponotus
(Colobobsis) macrocephalus (FOR), Ca. sp.1 (macrocephalus gp.), Ca. sp.3, Ca. sp.5 (both novaehollandiae gp.), Ca. sp.4 (macrocephalus gp.), Ca. sp.6
104
N. B L Ü T H G E N A N D N. E . S TO R K
(gasseri gp.), Ca. sp.7 (extensus gp.), Ca. vitreus, Cardiocondyla wroughtonii (MYR), Crematogaster aff.
fusca (MYR), Cr. aff. pythia, Cr. sp.3, Echinopla australis (FOR), Heteroponera sp.1 (PON), Leptomyrmex unicolor (DOL), Monomorium cf. intrudens
(MYR), Mo. fieldi var. laeve nigrius, Mo. floricola,
Odontomachus cephalotes (PON), Oecophylla smaragdina (FOR), Pachycondyla sp.1 (PON),
Paratrechina minutula gp. (FOR), Pa. vaga gp.,
Pheidole nr. impressiceps (MYR), Ph. aff. platypus,
Ph. sp.1, Ph. sp.4, Ph. sp.5, Ph. sp.11, Ph. sp.13, Ph. cf.
athertonensis,
Pheidologeton
affinis
(MYR),
Podomyrma sp1 (MYR), Polyrhachis ‘Cyrto 03’, Po.
‘Cyrto 06’, Po. ‘Cyrto 08’, Po. ‘Cyrto NB5041’, Po.
yorkana (all Cyrtomyrma), Po. (Hagiomyrma) thusnelda, Po. barretti, Po. cupreata (both Hedomyrma),
Po. (Myrma) foreli, Po. (Myrmatopa) lobokensis, Po.
(Myrmhopla) mucronata, Po. (Myrmothrinax) delicata, Rhopalomastrix rothneyi (MYR), Rhoptromyrmex wroughtonii (MYR), Rhytidoponera
kurandensis (PON), Rh. purpurea, Rh. spoliata, Rh.
sp.1, Solenopsis sp.1 (MYR), Strumigenys guttulata
(MYR), Tapinoma melanocephalum (DOL), Ta.
minutum gp., Technomyrmex aff. albipes (DOL), Te.
quadricolor, Te. sp.3, Tetramorium bicarinatum
(MYR), Tet. insolens, Tet. validiusculum, Tetraponera
nitida (PSE), Turneria bidentata (DOL), Vollenhovia
sp1 (MYR), Vombisidris australis (MYR).
Underlined species names or name additions are
corrections from previous publications (Blüthgen et al.
2003; Blüthgen & Fiedler 2004a,b; Blüthgen et al.
2004b) by Alan Andersen (pers. comm. 2004).
© 2007 Ecological Society of Australia