Traditional plant functional groups explain variation in economic but not size-related traits across the tundra biome

Aim Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits. Location Tundra biome. Time period Data collected between 1964 and 2016. Major taxa studied 295 tundra vascular plant species. Methods We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species-level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species-level traits. Results Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species-level trait expression. Main conclusions Traditional functional groups only coarsely represent variation in well-measured traits within tundra plant communities, and better explain resource economic traits than size-related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insights for ecological prediction and modelling.Peer reviewe

Global plant trait relationships extend to the climatic extremes of the tundra biome

The majority of variation in six traits critical to the growth, survival and reproduction of plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world.Peer reviewe

The handbook for standardised field and laboratory measurements in terrestrial climate-change experiments and observational studies

Climate change is a worldwide threat to biodiversity and ecosystem structure, functioning, and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate‐change impacts across the soil–plant–atmosphere continuum. An increasing number of climate‐change studies is creating new opportunities for meaningful and high‐quality generalisations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re‐use, synthesis, and upscaling. Many of these challenges relate to a lack of an established “best practice” for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change

Tundra Trait Team: A database of plant traits spanning the tundra biome

Abstract 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

Tundra Trait Team : A database of plant traits spanning the tundra biome

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 Spatial location and grain 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. 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 Major taxa and level of measurement All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods. 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.Peer reviewe

Traditional plant functional groups explain variation in economic but not size‐related traits across the tundra biome

Abstract Aim: Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits. Location: Tundra biome. Time period: Data collected between 1964 and 2016. Major taxa studied: 295 tundra vascular plant species. Methods: We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species‐level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species‐level traits. Results: Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species‐level trait expression. Main conclusions: Traditional functional groups only coarsely represent variation in well‐measured traits within tundra plant communities, and better explain resource economic traits than size‐related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insights for ecological prediction and modelling

Traditional plant functional groups explain variation in economic but not size-related traits across the tundra biome

Aim: Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits. Location: Tundra biome. Time period: Data collected between 1964 and 2016. Major taxa studied: 295 tundra vascular plant species. Methods: We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species-level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species-level traits. Results: Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species-level trait expression. Main conclusions: Traditional functional groups only coarsely represent variation in well-measured traits within tundra plant communities, and better explain resource economic traits than size-related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insights for ecological prediction and modelling.The project was funded by the UK Natural Environment Research Council [ShrubTundra Project NE/M016323/1 (IMS, AB, HT, SAB, DG) & PhD Studentship NE/L002558/1 (HT)], the Synthesis Centre of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig (DFG FZT 118; sTundra working group [postdoctoral fellowship to AB]). The study has been supported by the TRY initiative on plant traits (https://www.try-db.org). The TRY initiative and database is hosted at the Max Planck Institute for Biogeochemistry, Jena, Germany. TRY is currently supported by DIVERSITAS/Future Earth and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. Authors were supported by the Swedish Research Council (2015-00465) (DB) and (2015-00498) (EK), Marie Skłodowska Curie Actions (INCA 600398) (DB), the National Science Foundation (USA; RH), the Carlsberg Foundation (2013-01-0825) (SN), the Danish Council for Independent Research - Natural Sciences (DFF 4181-00565) (SN), European Research Council Synergy grant ERC-SyG-2013-610028 IMBALANCE-P (JP), University of Zurich Research Priority Program on Global Change and Biodiversity (GSS, MIG), the Office of Biological and Environmental Research in the U.S. Department of Energy's Office of Science (Next-Generation Ecosystem Experiments in the Arctic - NGEE Arctic) (CMI), NASA Arctic Boreal Vulnerability Experiment - ABoVE (LB, SG), The Swiss National Science Foundation (EF, AK, SV), NSERC Canada (EL, JJ, AP, BSPG, TZ), ArcticNet (EL, AP, GH), The US National Science Foundation Niwot Ridge LTER (DEB-1637686) (MJ), Long-Term Ecological Research (DEB-1234162) (PR) and Long-Term Research in Environmental Biology (DEB-1242531) (PR), Organismo Autónomo Parques Nacionales (JMN), the Arctic Research Centre, Denmark (JNN), RSF (#14-50-000290) (VO), the Polar Continental Shelf Program (AP, EL, GH), the Royal Canadian Mounted Police (GH), the Montagna di Torricchio Nature Reserve (Italy) (GC) the Academy of Finland Decisions no. 256991 (BF), JPI Climate no. 291581 (BF), and the BBSRC David Phillips Fellowship (BB/L02456X/1) (FTdV). Additional data and contributions were provided by L. Andreu-Hayles, P. Beck, A. Blach Overgaard, B. Bond-Lamberty, J. Craine, J. Dickie, S. Dullinger, B. Eberling, B. Enquist, J. Fang, K. Fleischer, H. Ford, G. Freschet, E. Garnier, D. Georges, R. Halfdan Jørgensen, K. Harper, S. Harrison, M. Harze, G. Henry, S. Jansen, J. Hille Ris Lambers, R. Klady, M. Kleyer, S. Kuleza, T. Lantz, A. Lavalle, F. Louault, B. Medlyn, R. Milla, J. Ordonez, C. Pladevall, H. Poorter, P. Poschlod, C. Price, N. Rueger, B. Sandel, F. Schweingruber, B. Shipley, A. Siefert, L. Street, K. Suding, J. Tremblay, M. Tremblay, M. Vellend, E. Weiher, C. Wirth, P. Wookey and I. Wright and the Royal Botanic Gardens Kew Seed Information Database (SID). We thank innumerable field technicians, logistics teams, graduate and undergraduate assistants for help with data collection, and parks, wildlife refuges, field stations, and the local and indigenous people for the opportunity to conduct research on their land. Finally, we thank the referees and editors for their constructive comments on the manuscript

Traditional plant functional groups explain variation in economic but not size-related traits across the tundra biome

Aim Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits. Location Tundra biome. Time period Data collected between 1964 and 2016. Major taxa studied 295 tundra vascular plant species. Methods We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species-level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species-level traits. Results Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species-level trait expression. Main conclusions Traditional functional groups only coarsely represent variation in well-measured traits within tundra plant communities, and better explain resource economic traits than size-related traits. We recommend caution when using functional group approaches to predict tundra ecosystem change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insight into ecological prediction and modelling