Questions What is the functional trait variation of European temperate grasslands and how does this reflect global patterns of plant form and function? Do habitat specialists show trait... Show moreQuestions What is the functional trait variation of European temperate grasslands and how does this reflect global patterns of plant form and function? Do habitat specialists show trait differentiation across habitat types? Location Europe. Methods We compiled 18 regeneration and non-regeneration traits for a continental species pool consisting of 645 species frequent in five grassland types. These grassland types are widely distributed in Europe but differentiated by altitude, soil bedrock and traditional long-term management and disturbance regimes. We evaluated the multivariate trait space of this entire species pool and compared multi-trait variation and mean trait values of habitat specialists grouped by grassland type. Results The first dimension of the trait space accounted for 23% of variation and reflected a gradient between fast-growing and slow-growing plants. Plant height and SLA contributed to both the first and second ordination axes. Regeneration traits mainly contributed to the second and following dimensions to explain 56% of variation across the first five axes. Habitat specialists showed functional differences between grassland types mainly through non-regeneration traits. Conclusions The trait spectrum of plants dominating European temperate grasslands is primarily explained by growth strategies which are analogous to the trait variation observed at the global scale, and secondly by regeneration strategies. Functional differentiation of habitat specialists across grassland types is mainly related to environmental filtering linked with altitude and disturbance. This filtering pattern is mainly observed in non-regeneration traits, while most regeneration traits demonstrate multiple strategies within the same habitat type. Show less
The tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better... Show moreThe tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperature-trait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming. Show less
Shipley, B; Belluau, M.; Kuehn, I.; Soudzilovskaia, N.A.; Bahn, M.; Penuelas, J.; ... ; Poschlod, P. 2017
Questions Heinz Ellenberg classically defined "indicator" scores for species representing their typical positions along gradients of key environmental variables, and these have proven very useful... Show moreQuestions Heinz Ellenberg classically defined "indicator" scores for species representing their typical positions along gradients of key environmental variables, and these have proven very useful for designating ecological distributions. We tested a key tenent of trait‐based ecology, i.e. the ability to predict ecological preferences from species’ traits. More specifically, can we predict Ellenberg indicator scores for soil nutrients, soil moisture and irradiance from four well‐studied traits: leaf area, leaf dry matter content, specific leaf area (SLA) and seed mass? Can we use such relationships to estimate Ellenberg scores for species never classified by Ellenberg?Location Global. MethodsCumulative link models were developed to predict Ellenberg nutrients, irradiance and moisture values from Ln‐transformed trait values using 922, 981 and 988 species, respectively. We then independently tested these prediction equations using the trait values of 423 and 421 new species that occurred elsewere in Europe, North America and Morocco, and whose habitat affinities we could classify from independent sources as three‐level ordinal ranks related to soil moisture and irradiance. The traits were SLA, leaf dry matter content, leaf area and seed mass. ResultsThe four functional traits predicted the Ellenberg indicator scores of site fertility, light and moisture with average error rates of <2 Ellenberg ranks out of nine. We then used the trait values of 423 and 421 species, respectively, that occurred (mostly) outside of Germany but whose habitat affinities we could classify as three‐level ordinal ranks related to soil moisture and irradiance. The predicted positions of the new species, given the equations derived from the Ellenberg indices, agreed well with their independent habitat classifications, although our equation for Ellenberg irrandiance levels performed poorly on the lower ranks.ConclusionsThese prediction equations, and their eventual extensions, could be used to provide approximate descriptions of habitat affinities of large numbers of species worldwide. Show less
Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental... Show morePlant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world’s 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models. Show less
