Introduction
The “entangled bank” metaphor of Darwin has inspired generations of
community ecologists to explore the rules governing species coexistence
and co-occurrence (Chesson, 2000; Gause, 1934; MacArthur, 1958; Ricklefs
& Schluter, 1993; Tilman, 1982). Studies on species co-occurrence in
species-rich communities over the past decades have reinforced the
importance of the relationship between trait-mediated species
differences
and
spatial distribution patterns among species in understanding the
processes underlying coexistence and patterns of biodiversity (Chesson,
2000, 2013; He & Biswas, 2019; HilleRisLambers, Adler, Harpole, Levine,
& Mayfield, 2012; Kraft, Godoy, & Levine, 2015; Laughlin, 2014; Li et
al., 2018).
Species
differences quantified by trait dissimilarity are frequently used as a
proxy for the niche differences among species that are believed to drive
species co-occurrence by influencing species’ response to environmental
conditions and neighborhood interaction (Burns & Strauss, 2011;
Cadotte, Carboni, Si, & Tatsumi, 2019; Cavender-Bares, Kozak, Fine, &
Kembel, 2009; Kraft & Ackerly, 2010). With such approaches, the
environment is often assumed to act as a filter that selects for species
possessing similar traits, leading to aggregated interspecific spatial
associations between species with similar traits, while the pairwise
spatial repulsion between species with similar traits are thought to
result from limiting similarity via competition (Cavender-Bares &
Wilczek, 2003; He & Biswas, 2019). However, the assumed link between
species differences and co-occurrence only holds when the measured
traits dissimilarity actually reflect niche differences and influence
neighborhood competition (Cadotte, Davies, & Peres-Neto, 2017). When
these assumptions do not hold, for example, neighborhood competition is
not driven by trait dissimilarity but by competitive advantage
associated with particular trait values (i.e. trait hierarchy) (Kunstler
et al., 2016, 2012), the pattern that species with similar functional
traits co-occur together could also be the result of competitive
exclusion of inferior competitors (hereafter hierarchical competition)
in the absence of niche segregation when trait similar species have
similarly high fitness -e.g. trees with resource conservative traits
(Chesson, 2000; Lasky, Uriarte, Boukili, & Chazdon, 2014; Mayfield &
Levine, 2010). Therefore, the relationship between interspecific spatial
associations and species differences characterized by trait
dissimilarity and trait hierarchy is key for disentangling the relative
importance of multiple assembly mechanisms, especially those leading to
identical co-occurrence patterns, e.g. environmental filtering and
hierarchical competition .
Trait dissimilarity and trait hierarchy can be characterized
respectively as absolute and hierarchical (i.e. directional)
interspecific trait differences to represent species niche and fitness
differences (Kunstler et al., 2012).
Bivariate
spatial point pattern analysis is a primary tool for estimating the
degree of pairwise species co-occurrence patterns departing from
independence (Fig. 1a and Fig. 1b), and understanding the underlying
processes that cause the departure from independence (He & Duncan,
2000; Wiegand et al., 2007; Wiegand & Moloney,
2014).
Associations with trait dissimilarity and trait hierarchy provide the
bivariate analysis with a basis for detecting the relative importance of
multiple assembly processes (Carmona, de Bello, Azcárate, Mason, &
Peco, 2019; Kunstler et al., 2016, 2012; Lasky et al., 2014; Shen,
Wiegand, Mi, & He, 2013; Wiegand et al., 2007, 2017). It is notable
that the relative importance of different assembly mechanisms and their
signatures on spatial associations is highly scale-dependent (Gianuca et
al., 2016; Smith, Sandel, Kraft, & Carey, 2013).
In
this study, we predict that limiting similarity should result in
functionally similar species occupying segregated areas (i.e.
functionally similar-spatial repulsive pattern), leading to a positive
relationship between the absolute functional trait distance (trait
dissimilarity) and pairwise spatial associations (Fig. 1c). While, at
the same time, functionally similar species would co-occur together more
likely (i.e.
forming
functionally similar-spatial aggregated pattern) resulting from either
environmental filtering or hierarchical competition (HilleRisLambers et
al., 2012; Mayfield & Levine, 2010), leading to a negative relationship
between the absolute functional trait distance and spatial associations
Fig. 1d). To disentangle which of these two processes in the case of
Fig. 1d , environmental filtering and hierarchical competition, is
responsible for the functionally similar-spatial aggregated pattern, it
is necessary to simultaneously test and compare the relative strengths
of trait dissimilarity and trait hierarchy on pairwise spatial
associations. If environmental filtering prevails, we would expect that
the strength of trait dissimilarity should be greater than that of trait
hierarchy (Fig. 1e), and if hierarchical competition drives the
community assemblage, the effects of trait hierarchy are expected to be
stronger than that of trait dissimilarity (Fig. 1f).
To link forest assembly mechanisms to trait difference- spatial
association relationships and test the three hypotheses above (Fig. 1c,
d, e and f), we addressed the following questions about spatial
associations: (1) How are pairwise spatial associations correlated with
trait dissimilarity and trait hierarchy? (2) Do the spatial
pattern-trait difference relationships remain consistent across
different spatial scales? Moreover, little attention has been paid to
variation in abundances among the focal tree species and relative
importance of different assembly mechanisms. In this study, we explored
how the magnitude that the hierarchical competition effects outcompete
the environmental filtering effects was related to the abundance of each
focal species when trait hierarchy effects were detected.
To address these questions, we analyzed the bivariate spatial
associations of 80 common species in a fully mapped 50 ha (1000× 500 m)
plot in Heishiding nature reserve in southern China using spatial point
pattern analysis. To reveal how trait dissimilarity and hierarchy
determine species co-occurrence patterns in the study forest, we
evaluated the support for the three hypotheses by assessing the spatial
pattern-trait difference relationships across different spatial scales.
We then related the relative strengths of trait hierarchy and trait
dissimilarity on spatial associations to the abundance of each focal
species to better understand the underlying mechanisms.