Motivation The Tundra Trait Team (TTT) database includes field‐based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade‐offs, trait–environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters. Main types of variable contained The database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (> 1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density. Spatial location and grain Measurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and sub‐Antarctic Marion Island. More than 99% of observations are georeferenced. Time period and grain All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement Trait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species. Software format csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release.

Questions How does the spatial structure of plant communities vary with the spatial grain and with the measure of species presence used? How can communities most efficiently be sampled for spatial autocorrelation? Location Four communities – riverbed, bog, ultramafic shrubland/herbfield and forest – in southwest New Zealand. Methods Each site was sampled over an extent of ca. 120 m at seven spatial grains, from 0.0025 to 25 m2, using an innovative triangular sampling scheme. At the 1‐m2 grain, species abundances (local frequencies) were recorded, as well as presence/absence. Results The percentage variation in species composition explained by distance, i.e. by spatial autocorrelation, was higher at larger grain. However, it reached a maximum of only 15%. The nugget – the Y‐intercept of the dissimilarity/distance relation – has been seen as a measure of randomness in community composition. It was generally about 0.5 dissimilarity on a 0–1 scale, although values in the range 0.7–0.8 were found at smaller grain sizes in the forest. The 90% distance, i.e. the distance at which dissimilarity reaches 90% of its final value, was interpretable only for the two sites where spatial autocorrelation was strong, but gave realistic estimates. Unsurprisingly, some parameter estimates were unrealistic when the fits were poor. Abundance information added nothing to the ability of distance to predict dissimilarity. Conclusion The strength of spatial autocorrelation rose with increasing grain, to a low value but one congruent with the few comparable studies in the literature. That is, control of species composition seemed to be at the larger grain sizes sampled, rather than at a very fine scale. Strong spatial autocorrelation has been reported only over large extents, over environmental heterogeneity and/or when examining one guild within a community. The nugget was generally somewhat lower than other values in the literature, indicating less randomness. The lack of increased spatial community predictability when including species abundances conforms to the majority of previous studies, suggesting that the primary community control is on the presence of species, not their abundance. However, the differences in spatial autocorrelation between the four sites sampled emphasize that comparative studies using consistent methods are needed. The triangular sampling scheme used here was rapid, accurate, and efficient in its distribution of distances.

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