PLoS BIOLOGY

Seed Dispersal and Spatial Pattern
in Tropical Trees
Tristram G. Seidler1, Joshua B. Plotkin2*
1 Natural Environment Research Council Centre for Population Biology, Imperial College, Ascot, Berkshire, United Kingdom, 2 Department of Biology, University ofPennsylvania, Philadelphia, Pennsylvania, United States of America

Theories of tropical tree diversity emphasize dispersal limitation as a potential mechanism for separating species inspace and reducing competitive exclusion. We compared the dispersal morphologies, fruit sizes, and spatial
distributions of 561 tree species within a fully mapped, 50-hectare plot of primary tropical forest in peninsular
Malaysia. We demonstrate here that the extent and scale of conspecific spatial aggregation is correlated with the modeof seed dispersal. This relationship holds for saplings as well as for mature trees. Phylogenetically independent
contrasts confirm that the relationship between dispersal and spatial pattern is significant even after controlling forcommon ancestry among species. We found the same qualitative results for a 50-hectare tropical forest plot in
Panama. Our results provide broad empirical evidence for the importance of dispersal mode in establishing the longterm community structure of tropical forests.
Citation: Seidler TG, Plotkin JB (2006) Seed dispersal and spatial pattern in tropical trees. PLoS Biol 4(11): e344. DOI: 10.1371/journal.pbio.0040344

trees greater than 1 cm in diameter at breast height, mapped
within 1-m accuracy [17]. We partitioned these species into
primary dispersal syndromes, based on their fruit anatomy
and morphology, and we asked whether dispersal syndromescorrelate with spatial distributions.

Introduction
Tropical forest tree communities are among the most
species-rich on Earth. Although the maintenance of diversity
remains a central problem in ecology [1], theoretical work has
highlighted conspeciﬁc aggregation as a mechanism of
reducing competitive exclusion and promoting diversity[2,3]. Indeed, tropical forests exhibit extensive aggregationof conspeciﬁc trees at scales ranging from a few meters to afew hundred meters [4–6]. The cause of conspeciﬁc clustering
remains unclear [7], and it has been variously attributed topatchy habitat variation [5,8], to the limited dispersal of seeds[9], or to neutral processes that disregard species-speciﬁc
traits [10]. Here we demonstrate that dispersal morphologies
are strongly correlated with spatial distributions for hundreds of tree species, and therefore with the community
structure of tropical forests.
Tropical tree species vary in their ability to disperse seeds.
Limited dispersal is known to cause spatial aggregation
among seeds and seedlings of pioneer trees [11]. Whether
or not the spatial patterns produced by limited dispersal
persist beyond the seedling stage is less well understood, aside
from anecdotal evidence or studies limited to a few species[4,6,7]. Establishing a link between dispersal mechanisms andspatial patterns at the community level would help close thegap in the ‘‘demographic loop’’ that separates observations oflimited seed dispersal from the long-term consequences ofdispersal for tree populations [7,12,13]. Spatial aggregationinduced by local dispersal could be reinforced by associations
with patchy habitats [14] or it could be disrupted by densitydependent mortality from predation [15,16]. Nevertheless, wehypothesize that trees of a species with limited seed dispersal
will be tightly clustered in space, whereas a species with amechanism for long-distance seed dispersal will exhibit lessclustering or even spatial randomness.
To examine this hypothesis, we analyzed dispersal mechanisms and spatial distributions of trees within a fully
mapped, 50-ha plot of lowland tropical forest in peninsular
Malaysia (see Materials and Methods). The census includes all
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Results
Variation in seed and fruit morphology is caused in part by
selection for dispersal capabilities [18]. Wings and plumes, aswell as ﬂeshy, juicy, and nutritious tissues, have each arisen
many times across a broad taxonomic range [19], and they
originate in a variety of histological layers of the testa, pericarp,
and adjacent tissues. We assigned each of 561 study species to
one of seven dispersal syndromes, on the basis of data from ﬁeld
collections, herbarium specimens, and descriptions frompublished ﬂora [20–24]. The seven dispersal syndromes are:ballistic, gravity, gyration, wind, animal (small fruit size),
animal (medium fruit), and animal (large fruit) (Table 1).
In order to quantify the overall degree of spatial
aggregation for each species, we ﬁt a Poisson cluster point
process to the observed distribution of conspeciﬁc individuals in the plot (see Materials and Methods). The Poissoncluster process, and this method of ﬁtting parameters inparticular, faithfully reproduces the qualitative spatial patterns of most species [5]. As a result of ﬁtting a Poisson cluster
process, for each species we obtained an average ‘‘cluster
size,’’ r, that quantiﬁes the typical diameter of a conspeciﬁc
Academic Editor: Ran Nathan, The Hebrew University of Jerusalem, Israel
Received April 10, 2006; Accepted August 14, 2006; Published October 17, 2006
DOI: 10.1371/journal.pbio.0040344
Copyright: Ó 2006 Seidler and Plotkin. This is an open-access article distributed
under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided theoriginal author and source are credited.
Abbreviations: BCI, Barro Colorado Island; df, degrees of freedom* To whom correspondence should be addressed. E-mail: jplotkin@sas.upenn.edu

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tree cluster. Small values of r indicate tight spatial clusters;
large values indicate more diffuse clusters (Figure 1).
Figure 2 shows the relationship between dispersal syndrome and cluster size r for our 561 study species.
Ballistically dispersed species exhibit the smallest r values—i.e., the most aggregated spatial distributions—followed bygravity-dispersed, gyration-dispersed, wind-dispersed, andﬁnally animal-dispersed species. Among the species dispersedby animals, the degree of spatial clustering depends on fruit
diameter. Species with fruits less than 2 cm in diameter are
more aggregated than those with fruits 2–5 cm in diameter;and species with fruits greater than 5 cm in diameter show
the least spatial clustering (Figure 2).
Overall, there is a highly signiﬁcant relationship between
spatial cluster size and dispersal syndrome across our 561
study species (Kruskal-Wallis, degrees of freedom [df] ¼ 6, v2¼
64.3, p , 106). In addition to this overall analysis of variance,
we compared spatial cluster sizes between pairs of syndromes
or between groups of syndromes. Each of these comparisons
was performed under two different assumptions about
species relationships: ﬁrst, we treated the study species as
independent, and second, we controlled for the phylogenetic
relationships among the species [25] (see Materials andMethods). By controlling for phylogeny, we can interrogate
the relationship between aggregation pattern and dispersal
mechanism, while avoiding the potential problem of pseudoreplication among species that share a common ancestor.
Although phylogenetic contrasts cannot rule out the possibility that a third trait (such as stature) explains the variationin both dispersal syndrome and spatial cluster size, such ananalysis controls for neutrally evolving traits determined by
the pattern of ancestry among species.
Animal-dispersed species exhibit signiﬁcantly larger cluster
sizes than species not dispersed by animals (Wilcoxon signrank test, p , 106). This relationship is signiﬁcant even after
controlling for phylogenetic relationships among the study
species (p ¼ 0.002). Animal-dispersed species with fruits .5
cm in diameter have larger cluster sizes than animaldispersed species with fruits ,2 cm in diameter (p ¼0.0007), a relationship that is also conserved under phylogenetically independent contrasts (p ¼ 0.001). Gravity-dispersed
species exhibit signiﬁcantly larger cluster sizes than species
dispersed ballistically do (p ¼ 0.03), but this trend could not be
tested when controlling for phylogeny because of the paucity
of independent contrasts.
Fruit size is also related to the spatial distribution of trees.
Among the animal-dispersed species, there is a weak but
signiﬁcant positive correlation between fruit diameter andcluster size r (n¼425 species, Spearman r¼0.13, p¼0.022). This
correlation remains signiﬁcant even after controlling for
phylogenetic relationships (n ¼ 143 contrasts, r ¼ 0.18, p ¼
0.032). Among species not dispersed by animals, fruit diameteris also correlated with cluster size (n ¼ 78 species, r ¼ 0.33, p ¼
0.0039), and this correlation remains signiﬁcant after controlling for phylogeny (n ¼ 39 contrasts, r ¼ 0.39, p ¼ 0.014).
In addition to mean cluster size r, we can quantify
aggregation over a range of spatial scales using the secondmoment measure called Ripley’s k [26]. For each species, thestatistic k(d) quantiﬁes the average number of conspeciﬁcs
within a distance d of a focal tree, divided by the density ofconspeciﬁcs in the plot. If individuals are distributed at
random, then the expected value of k(d) is pd2. We report the
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dimensionless statistic K(d)¼k(d)/(pd2). K(d) exceeds unity whena species is more aggregated than random at distance scale d;K(d) is less than unity when a species is more regular thanrandom.
Compared to the mean cluster size r, the statistic K(d) can
provide a more detailed description of the relationshipbetween dispersal mechanism and spatial pattern. The K(d)curves within each dispersal syndrome (Figure 3) areconsistent with the results obtained using the mean cluster
size r (Figure 2). Figure 3 additionally reveals that smallscale aggregation (d  75 m) is more strongly correlatedwith dispersal syndrome than large-scale aggregation. Atvery large spatial scales (d  200 m), spatial patterns are nolonger correlated with dispersal syndromes. This result
suggests that whatever large-scale aggregation is present, it
is likely caused by factors other than dispersal, such as
associations with patchy habitats. This result is consistent
with the scale of topographic variation in our study plot [5].
To examine the generality of our results across the new- andold-world tropics, we have also analyzed spatial patterns anddispersal modes at the 50-ha plot on Barro Colorado Island(BCI), Panama [27–29]. There are substantial differences in the
ﬂoral and faunal assemblages of BCI and Pasoh, which could
induce differences in the relationship between dispersal andspatial patterns. Nevertheless, we found qualitatively similar
results at BCI: ballistically dispersed species are the mostaggregated (mean r ¼ 49.0 m), followed by wind-dispersed
species (mean r ¼ 65.2 m), mammal-dispersed species (mean r¼ 112.6 m), and bird/bat-dispersed species (mean r ¼ 146.8 m).
The relationship between dispersal mode and spatial pattern
at BCI is signiﬁcant (Kruskal-Wallis, df ¼ 3, v2¼ 9.32, p ¼ 0.025)
but weaker than at Pasoh, which is due in part to the reduced
number of species. As at Pasoh, animal-dispersed species at
BCI are more diffuse than species that lack primary animal
dispersal (p ¼ 0.003).

Discussion
Although previous studies have used seed-fall data andrepeated censuses to examine the consequences of dispersal
for seedling distributions [11,30], such an approach is not
feasible over the time scales necessary to study more maturetree populations. In contrast, here we have taken advantage
of variation in dispersal mechanisms over a broad phylogenetic range of species to interrogate the relationshipbetween dispersal ability and spatial clustering. Estimatedcluster sizes, supported by Ripley’s k curves, indicate that
dispersal syndromes with a greater potential for longdistance seed transport result in signiﬁcantly larger cluster
sizes. Most of these correlations remain signiﬁcant evenwhen controlling for phylogeny, indicating that the relationship between dispersal and spatial pattern is not likely a side
effect of variation in other, neutrally evolving species traits.
Additionally, this relationship is unlikely to be caused bycovariation in tree stature, because stature shows nocorrelation with spatial pattern (Figures S2 and S3).
The sequence of spatial patterns along the axis ofincreasing dispersion (Figure 1) illustrates several important
points concerning the natural history of seed dispersal intropical trees. Animal-dispersed species that produce small
fruits exhibit tighter clusters than those that produce larger
fruits—a result that supports the hypothesis that larger0002

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Dispersal and Spatial Pattern

Table 1. The Definition of Dispersal Syndromes Used in this Study, and Characteristics of Species within Each Dispersal Syndrome
Dispersal
Syndrome

Fruit Morphology

Fruit or Seed
Trait Relevant
to Dispersal

Numberof Species

Numberof Genera

Numberof Families

Fruit Diameter,
Long Axis (mm)Ballistic

Explosive capsule

16

9

1

19.5 6 3.5

636 6 155

31.1 6 4.7

GravityNut, wings absent

24

14

7

82.0 6 23.4

1,144 6 424

47.4 6 4.9Gyration

Winged nut

29

10

5

107.6 6 15.2

872 6 228

54.5 6 6.2

Wind

Capsule, pod,
winged nut
Berry, drupe,
or capsule
Berry, drupe,
or capsule
Berry, drupe,
or capsule

Aril reducedor absent
28 dispersal byseed disperser
28 dispersal byseed disperser
Tiny seed or fruit;
plumed or winged
Edible aril or pulp

19

17

11

80.4 6 16.3

300 6 9964.5 6 13.4

209

97

43

13.3 6 0.35

506 6 56

99.3 6 7.7

Edible aril or pulp

177

84

35

32.7 6 0.72

527 6 74

120.6 6 10.6

Edible aril or pulp

87

41

20

96.9 6 6.0

312 6 53

157.8 6 17.0

Animal ,2 cm
Animal 2–5 cm
Animal .5 cm

Number of Trees
per Species

Cluster Sizesigma; (m)Species dispersed by animals are subdivided into three groups based on fruit diameter. The ballistic, gravity, gyration, and wind syndromes rely on mechanical means for primary dispersal.
Many gravity- and gyration-dispersed species are further dispersed by animal seed dispersers, either incidentally or through caching. The table indicates the number of species, genera, andfamilies within each primary dispersal category; the mean 6 1 standard error of fruit diameters; the mean 6 1 standard error of species abundances; and the mean 6 1 standard error
cluster size.
DOI: 10.1371/journal.pbio.0040344.t001

bodied birds and mammals eat larger fruits [18,31], havelarger home ranges [32], and may carry seeds over longer
distances than small birds and mammals do. We have seenthat wind-dispersed species typically exhibit tighter clusters
than animal-dispersed species do (Figure 1). This trend may
be explained in part by the inﬂuence of the forest canopy

on wind speeds. Although high winds can occur at Pasoh,most seeds fall through the forest canopy, where air
movement is restricted [33]. Gyration-dispersed species areoccasionally dispersed over long distances by high winds.
But such fruits typically have limited lift, due to high mass–
to–wing area ratio [34] (Figure S1). The species in our

Figure 1. Examples of Mapped Tree Populations for Four Species in the 50-ha Pasoh Forest Plot
Upper left, Baccaurea racemosa (animal dispersed; n ¼ 1,228, r ¼ 146.5 m); lower left, Neobalanocarpus heimii (gravity dispersed; n ¼ 3,334, r ¼ 86.7 m);
upper right, Shorea leprosula (gyration dispersed; n ¼ 2,154, r ¼ 33.1 m); lower right Croton argyratus (ballistically dispersed; n ¼ 1,248, r ¼ 27.9 m).
DOI: 10.1371/journal.pbio.0040344.g001
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Dispersal and Spatial Patterndrawbacks. Foremost among these is our coarse characterization of ‘‘dispersal mechanism’’ into a few simple categories.
Dispersal mechanisms, let alone kernels, are certainly morevaried than our several categories can quantify. Moreover, theimportant concept of recruitment limitation [9] is more
complex than dispersal mechanism alone, and it includes
species-speciﬁc limitations in fecundity and establishmentthat our analysis has ignored. Our results are therefore
limited to the relationship between morphologically deﬁned
modes of propagule distribution and the resulting spatial
patterns of trees. The possibility remains, of course, that
other traits covary with dispersal mode and may be
responsible for the correlations we have observed.
Although we cannot disentangle the effects of differential
propagule distribution from those of differential establishment, we can at least analyze the spatial distributions of wellestablished, mature trees. The entire Pasoh dataset, analyzed
above, includes saplings of many species. However, when we
repeat our analysis of spatial patterns restricted to mature
trees only—i.e., stems wider than 5 cm in diameter [42]—weﬁnd the same qualitative relationship between dispersal
syndromes and spatial distributions (Figure 4), which is still
highly signiﬁcant (Kruskal-Wallis, df ¼ 6, v2¼ 46.7, p , 106).
The concordance of our results across different life stages
suggests that dispersal mode itself plays some role in causing
the observed correlations.
Despite their limitations, our results help provide anempirical basis for theories of community assembly anddiversity mediated by variation in dispersal mode. According
to theoretical models, conspeciﬁc spatial clustering is
recognized as a critical mechanism for reducing competitive
exclusion and promoting diversity. The effect of clustering on
diversity depends on scale. At small spatial scales, clustering
tends to reduce the local (alpha) diversity, whereas at larger
scales, limited dispersal leads to higher species turnover

Figure 2. The Relationship between Dispersal Syndrome and Spatial
Aggregation for 561 Tree Species at Pasoh, Malaysia
The figure shows the mean 6 1 standard error of the spatial cluster size(r) for tree species in each of seven dispersal syndromes.
DOI: 10.1371/journal.pbio.0040344.g002

gravity-dispersed category often experience secondary dispersal from the ground after fruit fall. Why, then, are these
species more tightly aggregated than the primary animaldispersed species? The answer is likely related to the factthat secondary dispersal of seeds lacking secondary rewards
is typically performed by mammals, such as seed-cachingrodents [35–37], that carry seeds over relatively shortdistances [38]. The gravity- and gyration-dispersed species
are the dominant mast fruiters in Asian tropical forests [39].
During mast-fruiting events, seeds overwhelmingly escapepredation either by satiation of predators [40] or by rapid
germination before the arrival of migratory predators [41].
Thus, the impact on aggregation of secondary dispersal byseed predators may be limited, a hypothesis that is
supported by our analysis of spatial patterns in such species.
In part, our ﬁndings contradict early studies of dispersal
mode and spatial pattern performed by Hubbell [4]. When
comparing 30 tree species at BCI, Hubbell found that the
mammal-dispersed species were the most aggregated, followed by wind-dispersed species. By contrast, at both BCI andPasoh, we found that species dispersed by wind are moreaggregated than those dispersed by mammals. There areseveral methodological explanations for the discrepancy
between our results and those of Hubbell. Aside from thefact that we have used potentially different dispersal
categories and analyzed far more species than Hubbell, we
have also used a different metric of spatial aggregation, r,
which quantiﬁes the overall degree of clustering [5] as
opposed to only the local pattern [4]. Nevertheless, ouranalysis conﬁrms Hubbell’s observation that the species at
BCI dispersed by bird or bat exhibit the most diffuse spatial
patterns.
Compared to studies of seed-fall data for a limited numberof tractable species, our study is strengthened by the large
number and phylogenetic breadth of species analyzed.
However, the scale of our analysis entails several major
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Figure 3. The Spatial Aggregation Statistic, K(d), Evaluated at a Range ofDistances for Tree Species in Four Dispersal SyndromesWithin each dispersal syndrome, the graph shows the mean K(d) value 6
1 standard error. A species is aggregated at distance d if K(d) exceeds
unity. Dotted lines indicate K(d) for a Poisson random spatial distribution.
All species are strongly aggregated at small spatial scales and weakly
aggregated at large scales. At spatial scales d  75 m, each of thedispersal types has a significantly different mean K(d) value (Wilcoxon p, 0.008). At larger spatial scales (d . 200m), spatial aggregation is not
significantly correlated with dispersal syndrome. (The other threedispersal syndromes are omitted for clarity.)
DOI: 10.1371/journal.pbio.0040344.g003
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Dispersal and Spatial PatternAmong species not dispersed by animals, we deﬁne four dispersal
syndromes: wind dispersal, gyration dispersal, gravity dispersal, andballistic dispersal (Table 1). Species having ﬂeshy or membranous
wings are divided into wind and gyration dispersal, based on the ratio
of propagule volume (cm3) to wing area (cm2), which is a standard
estimate of wing loading [34,46]. Species whose inverse wing loading
exceeds 100 times propagule volume are classiﬁed as wind-dispersed;
the remaining winged species are classiﬁed as gyration-dispersed(Figure S1). This distinction approximates dispersal distance based onwing loading and propagule volume [46,47]. All plumed species in thisstudy have small propagules and are classiﬁed as wind-dispersed.
Ballistically dispersed species possess explosively dehiscing capsules that throw the seeds some distance from the parent plant. Gravitydispersed species are deﬁned as those lacking any obvious dispersal
mechanism or disperser reward. Though many species are subject tosecondary dispersal by animals or water, for the purpose of theseanalyses we examined only the primary phase of dispersal.
Estimating spatial cluster size. A Poisson cluster process consists ofrandomly located cluster centers; around each cluster center, trees
are positioned according to a radially symmetric Gaussian distribution. For each species, the cluster model is deﬁned by two parameters:
q, the density of cluster centers, and r, where 2r2 denotes the meansquared distance of a tree from the center of its cluster. For an
observed spatial distribution of a species, q and r were chosen to best
ﬁt the Ripley’s k curve, as previously described [5]. Forty-six species
exhibit nearly random spatial distributions, resulting in ﬁtted r
values larger than the width of the 50-ha plot, or ﬁtted q values
greater than the density of trees. Such species were assigned r ¼ 500
m, although the choice of the upper bound on r does not affect theresults of our (nonparametric) analyses. The ﬁtted cluster sizes r are
not normal or homoscedastic, and so we use nonparametric methods
in all our statistical analyses.
Phylogenetic regressions. The phylogenetic relationships amongour 561 study species were estimated using the Phylomatic databaseand assembly tools [48]. We used the recent angiosperm tree of Soltis etal. [49], to which strict consensus trees are attached. The Phylomatic
program uses this skeleton tree to construct a complete tree of input
taxa, attaching unrecognized species to a polytomous genus node andunrecognized genera to a polytomous family node. The phylogeny usedhere thus represents a best estimate for the relationship of taxa basedon a large number of studies of molecular data and morphology, with its
terminal clades being strict consensuses. A NEXUS version of our 561taxon tree is available on request.
We performed phylogenetically independent contrasts according
to Pagel’s method [25] as implemented in the comparative analysis byindependent contrasts program [50]. Degrees of freedom forunresolved polytomies were calculated according to Purvis’ method[51], resulting in conservative tests of the evolutionary hypothesis. In
all cases, the dependent variable was the cluster size r. Continuous
contrasts were computed using fruit length as the independent
variable. Binary contrasts were computed using pairs of dispersal
categories. Rather than computing contrasts for all pairs of dispersal
syndromes, we compared groups of syndromes; for example, ‘‘animaldispersed’’ versus ‘‘not animal-dispersed.’’BCI data. We also studied tree species within the 50-ha permanent
forest dynamics plot on BCI [27–29], censused in 1995. Our analysis
includes 209 species represented by at least 20 individuals in the plot,
whose dispersal syndromes have recently been characterized [52,53].
The dispersal syndromes of BCI species are classiﬁed into ballistic,
wind, bird/bat, or mammal categories. (Mammal takes precedence incases of multiple mechanisms, although this choice does not
signiﬁcantly affect our results.) These classiﬁcations do not include
information on fruit diameter or wing loading.

Figure 4. The Relationship Between Dispersal Syndrome and Spatial
Aggregation among 425 Tropical Tree Species, Restricted to Mature
Trees Only (Stem Diameter . 5 cm)
The figure shows the mean spatial cluster size r for tree species in eachof seven dispersal syndromes. Dispersal syndromes are significantly
associated with spatial aggregation among mature trees (Kruskal-Wallis,
df ¼ 6, v2 ¼ 46.7, p , 106).
DOI: 10.1371/journal.pbio.0040344.g004

increasing total (beta and gamma) diversity [3]. The typicalscale of clustering among our study species (r ; 100 m) is
signiﬁcantly smaller than the scale of the entire Pasoh plot,
and thus we expect that clustering generally acts to increase
species diversity within the plot. Aside from separating
species in space, interspeciﬁc variation in dispersal syndrome
may also maintain diversity by imposing a competition/colonization tradeoff, as suggested by a large body oftheoretical literature [3,43,44].

Materials and Methods
Data. We studied tree species within the 50-ha permanent forest
dynamics plot at Pasoh Forest Reserve, located in peninsular Malaysia(28589N, 1028179E). The reserve contains 2,450 ha of protected
lowland dipterocarp-dominated forest with about 1,700 mm ofrainfall per year. All free-standing trees and shrubs that exceeded 1
cm diameter at breast height were mapped, measured, and identiﬁed
to species [17]. 814 species in 290 genera and 78 families wereidentiﬁed, comprising a total of nearly 340,000 stems. The mostabundant families were Euphorbiaceae, Dipterocarpaceae, andAnnonaceae. Censuses took place in 1986–1987, 1990, 1995, and2000. In the 1995 census, which was used in this study, 637 species
were represented by at least 20 individuals in the plot. Species withfewer individuals were not considered. We were able to assign
dispersal syndromes to 561 of these 637 species.
Assignment of dispersal syndromes. Animal-dispersed species aredeﬁned as having edible parts that encourage the swallowing ortransport of seeds during or subsequent to feeding by vertebrates.
Animal dispersers vary in gape width and other characteristics,
affecting their choice of fruits [31] and the distances over which they
carry seeds [45].
Depending on the analysis, we used fruit diameter at the longest axis
as a continuous variable, or we divided the animal-dispersed species
into three groups based on fruit diameter (Table 1). Passerines are themost likely dispersers of fruits in the smallest class (,2 cm diameter,along the longest axis); birds and small to medium mammals are themost likely dispersers of medium-sized fruits (2–5 cm diameter); andlarge birds and large mammals are the likely dispersers of large-fruitedspecies (.5 cm diameter). Because we did not use seed size as acriterion, large fruits with large seeds are not distinguished from large
fruits with small seeds, even though the latter may sometimes be
dispersed by small birds or mammals incapable of swallowing fruits
whole.
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Supporting Information
Figure S1. Wing Area and Propagule Volume for Winged Tropical
Tree Species
Volume is used here as a proxy for mass. Species with winged
propagules are classiﬁed as wind- or gyration-dispersed according to
the ratio of the lift produced by the relative size of the wings and theabsolute size of the propagule. The y-axis estimates the reciprocal ofwing loading. We deﬁne gyration dispersal (solid inverted triangles) as
y , 100x (weak lift and a large propagule), and wind dispersal (opentriangles) when y . 100x (strong lift and a small propagule; line
deﬁnes y ¼ 100x). Several species with tufts or plumes rather thanwings were not included in this analysis and were categorized as winddispersed.
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Dispersal and Spatial Pattern

We thank Abdul-Razak Mohammed Ali of the Forest ResearchInstitute of Malaysia for permission to collect specimens at Pasoh

Forest and the Smithsonian Institution’s Center for Tropical Forest
Science for access to the Pasoh and BCI datasets. We thank Joe Wrightfor sharing data on dispersal modes at BCI. We are greatly indebted toPeter Ashton and William Bossert for conceptual input. We also thankAndy Purvis, Ran Nathan, Charles Godfray, Mark Rees, Jack Putz,
Kristina Stinson, and two anonymous reviewers for their input on the
manuscript.
Author contributions. TGS and JBP conceived and designed theexperiments. TGS and JBP performed the experiments. TGS and JBP
analyzed the data. TGS and JBP wrote the paper.
Funding. TGS was supported in part by the Conservation, Foodand Health Foundation; JBP was supported in part by the Burroughs
Wellcome Fund and the William F. Milton Fund.
Competing interests. The authors have declared that no competinginterests exist.

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DOI: 10.1371/journal.pbio.0040344.sg001 (456 KB EPS).
Figure S2. Spatial Cluster Size r Is Not Correlated with Tree Statureacross All Study Species (p ¼ 0.9146)
DOI: 10.1371/journal.pbio.0040344.sg002 (585 KB EPS).
Figure S3. Spatial Cluster Size r Is Not Correlated with Tree Stature
among Species Dispersed by Biotic or Abiotic Mechanisms (Biotic
Dispersal, p ¼ 0.5098; Abiotic Dispersal, p ¼ 0.2324)
DOI: 10.1371/journal.pbio.0040344.sg003 (541 KB EPS).

Acknowledgments

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November 2006 | Volume 4 | Issue 11 | e344