Elevational patterns of phylogenetic and morphological
structure at local and regional spatial scales
Resulting from interactions between stochastic and deterministic
processes in heterogeneous habitat, phylogenetic and trait-based
structure of most assemblages exhibited random dispersion in two
datasets. However, significant linear patterns of SES.MPD,
SES.PWsize, SES.PWshape in LSD and
SES.PWshape in RED have implied that the relative
importance of deterministic processes (i.e., environmental filtering and
competitive exclusion) varied along the elevational gradient. We
estimate that apparent elevational patterns of community structure in
LSD are resulting from significant niche separation among lineages.
Early study has mentioned that three families (Muridae, Cricetidae and
Sciuridae) in Rodentia have acted key roles in assembling rodent
communities in the HMs (Du et al. 2017). Therein, long-tailed
murine species have occupied the complete gradient, whereas short-tailed
species of Cricetidae mainly distribute at medium and higher elevations.
In addition, hylacolous sciurine species mainly survive in broad-leave
and coniferous forests ranging from mid-low to mid-high elevations,
except for Marmota himalayana surviving in alpine desert steppe.
In contrast, non-significant linear elevational patterns of SES.MPD and
SES.PWsize in RED are possible resulting from higher
environmental heterogeneity and enlarged species component. In RED, the
horizontal extent of each elevational band approach 9 degrees and 14
degrees at longitudinal and latitudinal directions. Resulting from
extraordinarily neighboring topological and climatic heterogeneity in
HMs, regional slice with a 100m-elevation range contains enormous
subareas and microhabitats, which has harbored mass of rodent species
without substantial overlap in distribution. This artificial treatment
might slightly influence the pattern of species diversity, but greatly
affect phylogenetic and functional diversity pattern, especially the
loss or gain of rare species (Mi et al. 2012). To some extent,
this offers an interpretation for the consistent patterns of species
richness but distinct phylogenetic and morphological community structure
patterns in two datasets.
According to best predictive model selection, we have detected that
different facets of community structure performed distinct dependence to
environmental variables, and the degree of environmental dependence was
much lower at regional scale. Obviously, due to higher level of
environmental heterogeneity, enlarged species component and less
accurate treatment in extracting environmental variables, the
interpreting power of climate predictive models deserve to sharply
decline.