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Can morphological plant functional traits predict demographic rates (e.g., growth) within plant communities as diverse as tropical forests? This is one of the most important next-step questions in trait-based ecology and particularly for global reforestation efforts. Due to the diversity of tropical tree species and their longevity, it is difficult to predict their performance prior to reforestation efforts. In this study, we investigate if simple leaf traits are predictors of the more complex ecological process of plant growth in regenerating selectively logged natural forest within the Wet Tropics (WTs) bioregion of Australia. This study used a rich historical data set to quantify tree growth within plots located at Danbulla National Park and State Forest on the Atherton Tableland. Leaf traits were collected from trees that have exhibited fast or slow growth over the last ~50 yr of measurement. Leaf traits were found to be poor predictors of tree growth for trees that have entered the canopy; however, for sub-canopy trees, leaf traits had a stronger association with growth rates. Leaf phosphorus concentrations were the strongest predictor of Periodic Annual Increment (PAI) for trees growing within the sub-canopy, with trees with higher leaf phosphorus levels showing a higher PAI. Sub-canopy tree leaves also exhibited stronger trade-offs between leaf traits and adhere to theoretical predictions more so than for canopy trees. We suggest that, in order for leaf traits to be more applicable to reforestation, size dependence of traits and growth relationships need to be more carefully considered, particularly when reforestation practitioners assign mean trait values to tropical tree species from multiple canopy strata.

Conservative survival strategy of plants growing in harsh karst habitats is observed from the view of plant functional traits, such as morphological traits and ecological stoichiometry. However, whether the plant communities in karst forests with high species turnover adopt a conservative strategy remains undetermined. This study comprehensively investigated the characteristics of functional traits of dominant plant species in four forests (i.e. Platycarya strobilacea , Quercus fabri , Quercus variabilis , and Pinus massoniana forests) in a trough‐valley karst watershed in Northern Guizhou Province, Southwestern China to explore the adaptation strategy of karst forests at the community level. At the organ and the species levels, traits differed among species, and the leaf and the bark morphological traits and root C:N:P ecological stoichiometry presented large interspecific variations. At the community level, the P . massoniana forest presented the lowest specific root length and dry matter content and tissue density of roots, branch, twig, and bark; the Q . fabri and the Q . variabilis forests displayed low specific leaf area and high dry matter content and tissue density of roots, branch, and twig; and the Platycarya strobilacea forest exhibited high specific leaf area. The P . massoniana forest was subjected to N and P colimitation, and the three other broad‐leaved forests were limited by P supply. The community‐weighted means rather than the arithmetic means of traits were preferential to represent the trait characteristics at the community level. From the view of plant functional traits at the community level, karst forests develop multiple functional traits like low specific leaf area, high dry matter content and tissue density of leaf, roots, branch, and twig, and decrease N and P investments in leaf for a conservative survival strategy to adapt to harsh habitats.

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Abstract. Functional trait databases are emerging as a crucial tool for a wide range of ecological studies including the next-generation vegetation modeling across the world. However, few large-scale studies have been reported on plant traits in the Tibetan Plateau (TP), the cradle of East Asian flora and fauna with specific alpine ecosystems, no report on plant trait databases could be found. Here an extensive dataset of 11 leaf functional traits (TiP-Leaf) for mainly herbs and shrubs and a few trees on the TP was compiled through field surveys. The TiP-Leaf dataset, compiled from 336 sites distributed mainly in the plateau surface and the northern margin of the TP across alpine and temperate vegetation regions and sampled from 2018 to 2021, contains 1692 morphological trait measurements of leaf thickness, leaf fresh weight, leaf dry weight, leaf dry-matter content, leaf water content, leaf area, specific leaf area and leaf mass per area and 1645 chemical element trait measurements of leaf carbon, nitrogen and phosphorus contents. Thus, 468 species belonging to 184 genera and 51 families were obtained and measured. In addition to leaf trait measurements, geographic coordinates, bioclimate variables, disturbance intensity and vegetation types of each site were also recorded. The dataset could provide solid data support for effectively quantifying the modern ecological features of alpine ecosystems, further evaluating the response of alpine ecosystem to climate change and human disturbances and improving the next-generation vegetation model. It could be a great contribution to the regional and global plant trait databases. The dataset is available from the National Tibetan Plateau Data Center (TPDC; Jin et al., 2022; https://doi.org/10.11888/Terre.tpdc.272516).

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