Plant traits poorly predict winner and loser shrub species in a warming tundra biome

Climate change is leading to species redistributions. In the tundra biome, shrubs are generally expanding, but not all tundra shrub species will benefit from warming. Winner and loser species, and the characteristics that may determine success or failure, have not yet been fully identified. Here, we investigate whether past abundance changes, current range sizes and projected range shifts derived from species distribution models are related to plant trait values and intraspecific trait variation. We combined 17,921 trait records with observed past and modelled future distributions from 62 tundra shrub species across three continents. We found that species with greater variation in seed mass and specific leaf area had larger projected range shifts, and projected winner species had greater seed mass values. However, trait values and variation were not consistently related to current and projected ranges, nor to past abundance change. Overall, our findings indicate that abundance change and range shifts will not lead to directional modifications in shrub trait composition, since winner and loser species share relatively similar trait spaces

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Small and slow is safe : on the drought tolerance of tropical tree species

Understanding how evolutionary history and the coordination between trait trade-off axes shape the drought tolerance of trees is crucial to predict forest dynamics under climate change. Here, we compiled traits related to drought tolerance and the fast-slow and stature-recruitment trade-off axes in 601 tropical woody species to explore their covariations and phylogenetic signals. We found that xylem resistance to embolism (P50) determines the risk of hydraulic failure, while the functional significance of leaf turgor loss point (TLP) relies on its coordination with water use strategies. P50 and TLP exhibit weak phylogenetic signals and substantial variation within genera. TLP is closely associated with the fast-slow trait axis: slow species maintain leaf functioning under higher water stress. P50 is associated with both the fast-slow and stature-recruitment trait axes: slow and small species exhibit more resistant xylem. Lower leaf phosphorus concentration is associated with more resistant xylem, which suggests a (nutrient and drought) stress-tolerance syndrome in the tropics. Overall, our results imply that: 1) drought tolerance is under strong selective pressure in tropical forests, and TLP and P50 result from the repeated evolutionary adaptation of closely related taxa; and 2) drought tolerance is coordinated with the ecological strategies governing tropical forest demography. These findings provide a physiological basis to interpret the drought-induced shift toward slow-growing, smaller, denser-wooded trees observed in the tropics, with implications for forest restoration programmes

Small and slow is safe: on the drought tolerance of tropical tree species

Understanding how evolutionary history and the coordination between trait trade-off axes shape the drought tolerance of trees is crucial to predict forest dynamics under climate change. Here, we compiled traits related to drought tolerance and the fast-slow and stature-recruitment trade-off axes in 601 tropical woody species to explore their covariations and phylogenetic signals. We found that xylem resistance to embolism (P50) determines the risk of hydraulic failure, while the functional significance of leaf turgor loss point (TLP) relies on its coordination with water use strategies. P50 and TLP exhibit weak phylogenetic signals and substantial variation within genera. TLP is closely associated with the fast-slow trait axis: slow species maintain leaf functioning under higher water stress. P50 is associated with both the fast-slow and stature-recruitment trait axes: slow and small species exhibit more resistant xylem. Lower leaf phosphorus concentration is associated with more resistant xylem, which suggests a (nutrient and drought) stress-tolerance syndrome in the tropics. Overall, our results imply that (1) drought tolerance is under strong selective pressure in tropical forests, and TLP and P50 result from the repeated evolutionary adaptation of closely related taxa, and (2) drought tolerance is coordinated with the ecological strategies governing tropical forest demography. These findings provide a physiological basis to interpret the drought-induced shift toward slow-growing, smaller, denser-wooded trees observed in the tropics, with implications for forest restoration programmes

The global spectrum of plant form and function: Enhanced species-level trait dataset

Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.Fil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Kattge, Jens. Max Planck Institute For Biogeochemistry; Alemania. German Centre for Integrative Biodiversity Research; AlemaniaFil: Cornelissen, Johannes H. C.. Vrije Universiteit Amsterdam; Países BajosFil: Wright, Ian J.. Macquarie University; Australia. University of Western Sydney; AustraliaFil: Lavorel, Sandra. Universite Grenoble Alpes; FranciaFil: Dray, Stéphane. Université Claude Bernard Lyon 1; FranciaFil: Reu, Björn. Universidad Industrial Santander; ColombiaFil: Kleyer, Michael. Universität Oldenburg; AlemaniaFil: Wirth, Christian. Max Planck Institute For Biogeochemistry; Alemania. Universitat Leipzig; Alemania. German Centre for Integrative Biodiversity Research; AlemaniaFil: Prentice, I. Colin. Tsinghua University; China. Imperial College London; Reino Unido. Macquarie University; AustraliaFil: Garnier, Eric. Université Montpellier II; FranciaFil: Bönisch, Gerhard. Max Planck Institute for Biogeochemistry; AlemaniaFil: Westoby, Mark. Macquarie University; AustraliaFil: Poorter, Hendrik. Macquarie University; Australia. Helmholtz Gemeinschaft. Forschungszentrum Jülich; AlemaniaFil: Reich, Peter B.. University of Minnesota; Estados Unidos. University of Michigan; Estados Unidos. University of Western Sydney; AustraliaFil: Moles, Angela T.. University of Western Sydney; AustraliaFil: Dickie, John. Royal Botanic Gardens; Reino UnidoFil: Zanne, Amy E.. University of Miami; Estados Unidos. The George Washington University; Estados UnidosFil: Chave, Jérôme. Université Paul Sabatier; FranciaFil: Wright, S. Joseph. Smithsonian Tropical Research Institute; PanamáFil: Sheremetiev, Serge N.. Russian Academy Of Sciences; RusiaFil: Jactel, Hervé. Universite de Bordeaux; FranciaFil: Baraloto, Christopher. Florida International University; Estados UnidosFil: Cerabolini, Bruno E. L.. Università Degli Studi Dell'insubria; ItaliaFil: Pierce, Simon. Università degli Studi di Milano; ItaliaFil: Shipley, Bill. University of Sherbrooke; CanadáFil: Casanoves, Fernando. Centro Agronómico Tropical de Investigación y Enseñanza; Costa RicaFil: Joswig, Julia S.. Max Planck Institute For Biogeochemistry; Alemania. Universitat Zurich; SuizaFil: Falczuk, Valeria. Universidad Nacional de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Gorne, Lucas Damián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentin

Plant traits poorly predict winner and loser shrub species in a warming tundra biome

Peer reviewe

The global spectrum of plant form and function: enhanced species-level trait dataset.

Here we provide the 'Global Spectrum of Plant Form and Function Dataset', containing species mean values for six vascular plant traits. Together, these traits -plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass - define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date