Discussion
Trait dissimilarity effects were widely considered to explain species
co-occurrence and coexistence over the past decade (Burns & Strauss,
2011; He & Biswas, 2019; Kraft & Ackerly, 2010). Consistent to the
findings in He & Biswas (2019), we observed negative relationships
between trait dissimilarity and pairwise spatial associations in this
study across different summary statistics and spatial scales for
individual and multiple functional traits (Fig. 2), except LDMC that
showed non-significant effects on pairwise spatial associations.
However, while necessary, this evidence is not sufficient to support
that environmental filtering is the dominant mechanism. Instead of
simply interpreting this negative relationship as a result of
environmental filtering and absence of competition (He and Biswas 2019),
we pointed out
that
hierarchical competition that selects species with traits conferring
competitive advantages (i.e. hierarchical competition) could also be
able to produce a negative relationship between trait dissimilarity and
pairwise spatial associations, which is identical to the result of
environmental filtering (Fig. 1d).
By comparing the relative strengths of trait dissimilarity and hierarchy
on pairwise spatial associations, we demonstrated that competitive
hierarchies captured by the traits of LA, WD and Hmaxbetter explained species co-occurrence than trait dissimilarity (Fig. 3
and Fig. S2-6), which supports the hypothesis that hierarchical
competition contributes to the co-occurrence patterns. As for the trait
of SLA and WDMC, we observed that the effects of trait dissimilarity and
hierarchy were comparable on the pairwise spatial associations.
Taking together the effects of both trait dissimilarity and trait
hierarchy on pairwise spatial associations, we infer that except LDMC,
other traits showed either stronger (e.g. LA, WD and
Hmax) or comparable (SLA and WDMC) trait hierarchy
effects relative to trait dissimilarity effects on interspecific spatial
associations, indicating that the effects of hierarchical competition on
the co-occurrence patterns in our forest plot were greater than or
comparable to the effects of environmental filtering. Other traits may
show stronger effects of environmental filtering or limiting similarity
in structuring the forest community, but we currently lack the trait
data to capture such effects.
This study provides a novel method to disentangle the relative
importance of multiple assembly mechanisms in structuring co-occurrence
patterns by assessing the effects of trait hierarchy and trait
dissimilarity on pairwise spatial associations. By linking the pairwise
spatial associations, which reflect signatures left by different
assembly mechanisms to the effects of trait dissimilarity and trait
hierarchy, our study provides alternative perspectives and better
understanding in the underlying mechanisms that govern the co-occurrence
pattern (He & Duncan, 2000; Wiegand et al., 2007; Wiegand & Moloney,
2014).
The negative relationship between trait dissimilarity and pairwise
spatial associations was typically interpreted as evidence for no signal
of competition and inferred as a result of environmental filtering (He
& Biswas 2019). However, this interpretation could be misleading
because the negative relationship between trait dissimilarity and
pairwise spatial associations could also be caused by neighborhood
competition that selects species with particular trait values
independent of environmental filtering (Carmona et al., 2019;
HilleRisLambers et al., 2012; Mayfield & Levine, 2010). In this study,
we found support for the hypothesis that hierarchical competition leads
to the negative relationship between trait dissimilarity and pairwise
spatial associations as well.
This study also strongly suggests that trait dissimilarity has little
effects on neighborhood competition and that neighborhood competition is
more likely to be driven by trait hierarchy, which is consistent to the
findings in Kunstler et al. (2012; 2016) and Carmona et al. (2019). If
trait dissimilarity was positively correlated to pairwise spatial
associations, we would infer that trait dissimilarity affects the
neighborhood competition and leads species with similar trait occupying
segregated areas. However, which is not the case in this study. Now that
the positive relationship between trait dissimilarity and spatial
associations was absent and effects of hierarchical competition that
exclude inferior competitors were found, we therefore speculate that
neighborhood competition in our forest plot was more likely to be driven
by trait hierarchy but not by trait dissimilarity as presumed (Carmona
et al., 2019; Kunstler et al., 2012).
The two metrics summarizing spatial point patterns
(gij (r ) andDij (r )) that we used in this study showed
no significant differences in the effects of trait dissimilarity and
trait hierarchy on spatial associations for each trait (Fig. 2 and Fig.
3). We therefore speculate that extreme heterogeneity of species
distributions were not prevalent in our forest plot (Wiegand et al.,
2007). Since these two summary statistics respectively characterize the
mean number of individuals and the nearest neighbors of the second
species around the focal species, the findings that these two summary
statistics of spatial point patterns reveal similar trait effects
suggest that the neighborhood interspecific competitive effects on the
focal trees come from both the average neighbor density and the nearest
neighbors of the other species at least within the scale of 50 m.
By linking the magnitude that trait hierarchy effects outcompete trait
dissimilarity effects (MHD) on pairwise spatial associations to the
abundance of focal species, we found inconsistency among the three
traits LA, WD and Hmax that all showed trait hierarchy
effects on population fitness (Fig. 4). This inconsistency suggests that
different fitness components, e.g., growth, survival and reproduction of
each species, might be unequally influenced by traits and a trait might
positively affect one component but negatively affects another, e.g.,
growth-survival trade-off and reproduction-survival trade-off (Laughlin,
Gremer, Adler, Mitchell, & Moore, 2020). These unequal effects on
different components of fitness and trade-offs might therefore influence
the abundance of the focal species and lead to variations in the
relationships between MHD and focal species abundance for different
traits.
In conclusion, we disentangled the assembly mechanisms of limiting
similarity, environmental filtering and hierarchical completion in
structuring our forest community by assessing and comparing the effects
of trait dissimilarity and trait hierarchy on pairwise spatial
associations in this study. More specifically, we found that limiting
similarity was weak or absent and hierarchical competition played a more
(or at least equally) important role than environmental filtering in
structuring the co-occurrence patterns in our forest community. This
study also reinforced the importance of trait hierarchy, rather than
trait dissimilarity, in driving interspecific competition.