Vertical structural complexity of plant communities represents the combined effects of resource acquisition and environmental stress on the Tibetan Plateau

Knowledge of vertical structural complexity (VSC) is important, because
the resulting spatial partitioning is closely linked to resource
utilization and environmental adaptation. However, the spatial pattern of
VSC on large scales and its underlying mechanisms are poorly understood.
Here, we systematically investigated 2,013 plant communities through grid
sampling on the Tibetan Plateau (TP). VSC was quantified as the maximum
plant height within a plot (Height-max), coefficient of variation of plant
height (Height-var), and Shannon evenness of plant height (Height-even).
Precipitation dominated the spatial variation in VSC in forests and
shrublands, supporting the classic physiological tolerance hypothesis
(PTH). In contrast, for alpine meadows, steppes, and desert grasslands in
extreme environments, non-resource limiting factors (e.g., wide diurnal
temperature ranges and strong winds) dominate VSC variation. Generally,
with the shifting of climate from favorable to extreme, the effect of
resource availability gradually decreases, but the effect of non-resource
limiting factors gradually increases, and that the PTH only applicable in
“favorable conditions”. With the help of machine learning models, maps
of VSC at 1-km resolution were produced for the TP for the first
time. Our new findings and maps of VSC provide new insights into
macroecological studies, especially for adaptation mechanisms and model
optimization.