While community‐weighted means of plant traits have been linked to mean environmental conditions at large scales, the drivers of trait variation within communities are not well understood. Local environmental heterogeneity (such as microclimate variability), in addition to mean environmental conditions, may decrease the strength of environmental filtering and explain why communities support different amounts of trait variation. Here, we assess two hypotheses: first, that more heterogeneous local environments and second, that less extreme environments, should support a broader range of plant strategies and thus higher trait variation. We quantified drivers of trait variation across a range of environmental conditions and spatial scales ranging from sub‐meter to tens of kilometers in montane and alpine plant communities. We found that, within communities, both environmental heterogeneity and environmental means are drivers of trait variation. However, the importance of each environmental factor varied depending on the trait. Our results indicate that larger‐scale trait–climate linkages that hold across communities also apply at small spatial scales, suggesting that microclimate variation within communities is a key driver of community functional diversity. Microclimatic variation provides a potential mechanism for helping to maintain diversity in local communities and also suggests that small‐scale environmental heterogeneity should be measured as a better predictor of functional diversity.

Functional trait data enhance climate change research by linking climate change, biodiversity response, and ecosystem functioning, and by enabling comparison between systems sharing few taxa. Across four sites along a 3000–4130 m a.s.l. gradient spanning 5.3 °C in growing season temperature in Mt. Gongga, Sichuan, China, we collected plant functional trait and vegetation data from control plots, open top chambers (OTCs), and reciprocally transplanted vegetation turfs. Over five years, we recorded vascular plant composition in 140 experimental treatment and control plots. We collected trait data associated with plant resource use, growth, and life history strategies (leaf area, leaf thickness, specific leaf area, leaf dry matter content, leaf C, N and P content and C and N isotopes) from local populations and from experimental treatments. The database consists of 6,671 plant records and 36,743 trait measurements (increasing the trait data coverage of the regional flora by 500%) covering 11 traits and 193 plant taxa (ca. 50% of which have no previous published trait data) across 37 families.

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