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Daniel C. Laughlin

Bio: Daniel C. Laughlin is an academic researcher from University of Wyoming. The author has contributed to research in topics: Trait & Specific leaf area. The author has an hindex of 42, co-authored 118 publications receiving 8390 citations. Previous affiliations of Daniel C. Laughlin include Northern Arizona University & University of Waikato.


Papers
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Journal ArticleDOI
Jens Kattge1, Sandra Díaz2, Sandra Lavorel3, Iain Colin Prentice4, Paul Leadley5, Gerhard Bönisch1, Eric Garnier3, Mark Westoby4, Peter B. Reich6, Peter B. Reich7, Ian J. Wright4, Johannes H. C. Cornelissen8, Cyrille Violle3, Sandy P. Harrison4, P.M. van Bodegom8, Markus Reichstein1, Brian J. Enquist9, Nadejda A. Soudzilovskaia8, David D. Ackerly10, Madhur Anand11, Owen K. Atkin12, Michael Bahn13, Timothy R. Baker14, Dennis D. Baldocchi10, Renée M. Bekker15, Carolina C. Blanco16, Benjamin Blonder9, William J. Bond17, Ross A. Bradstock18, Daniel E. Bunker19, Fernando Casanoves20, Jeannine Cavender-Bares6, Jeffrey Q. Chambers21, F. S. Chapin22, Jérôme Chave3, David A. Coomes23, William K. Cornwell8, Joseph M. Craine24, B. H. Dobrin9, Leandro da Silva Duarte16, Walter Durka25, James J. Elser26, Gerd Esser27, Marc Estiarte28, William F. Fagan29, Jingyun Fang, Fernando Fernández-Méndez30, Alessandra Fidelis31, Bryan Finegan20, Olivier Flores32, H. Ford33, Dorothea Frank1, Grégoire T. Freschet34, Nikolaos M. Fyllas14, Rachael V. Gallagher4, Walton A. Green35, Alvaro G. Gutiérrez25, Thomas Hickler, Steven I. Higgins36, John G. Hodgson37, Adel Jalili, Steven Jansen38, Carlos Alfredo Joly39, Andrew J. Kerkhoff40, Don Kirkup41, Kaoru Kitajima42, Michael Kleyer43, Stefan Klotz25, Johannes M. H. Knops44, Koen Kramer, Ingolf Kühn16, Hiroko Kurokawa45, Daniel C. Laughlin46, Tali D. Lee47, Michelle R. Leishman4, Frederic Lens48, Tanja Lenz4, Simon L. Lewis14, Jon Lloyd14, Jon Lloyd49, Joan Llusià28, Frédérique Louault50, Siyan Ma10, Miguel D. Mahecha1, Peter Manning51, Tara Joy Massad1, Belinda E. Medlyn4, Julie Messier9, Angela T. Moles52, Sandra Cristina Müller16, Karin Nadrowski53, Shahid Naeem54, Ülo Niinemets55, S. Nöllert1, A. Nüske1, Romà Ogaya28, Jacek Oleksyn56, Vladimir G. Onipchenko57, Yusuke Onoda58, Jenny C. Ordoñez59, Gerhard E. Overbeck16, Wim A. Ozinga59, Sandra Patiño14, Susana Paula60, Juli G. Pausas60, Josep Peñuelas28, Oliver L. Phillips14, Valério D. Pillar16, Hendrik Poorter, Lourens Poorter59, Peter Poschlod61, Andreas Prinzing62, Raphaël Proulx63, Anja Rammig64, Sabine Reinsch65, Björn Reu1, Lawren Sack66, Beatriz Salgado-Negret20, Jordi Sardans28, Satomi Shiodera67, Bill Shipley68, Andrew Siefert69, Enio E. Sosinski70, Jean-François Soussana50, Emily Swaine71, Nathan G. Swenson72, Ken Thompson37, Peter E. Thornton73, Matthew S. Waldram74, Evan Weiher47, Michael T. White75, S. White11, S. J. Wright76, Benjamin Yguel3, Sönke Zaehle1, Amy E. Zanne77, Christian Wirth58 
Max Planck Society1, National University of Cordoba2, Centre national de la recherche scientifique3, Macquarie University4, University of Paris-Sud5, University of Minnesota6, University of Western Sydney7, VU University Amsterdam8, University of Arizona9, University of California, Berkeley10, University of Guelph11, Australian National University12, University of Innsbruck13, University of Leeds14, University of Groningen15, Universidade Federal do Rio Grande do Sul16, University of Cape Town17, University of Wollongong18, New Jersey Institute of Technology19, Centro Agronómico Tropical de Investigación y Enseñanza20, Lawrence Berkeley National Laboratory21, University of Alaska Fairbanks22, University of Cambridge23, Kansas State University24, Helmholtz Centre for Environmental Research - UFZ25, Arizona State University26, University of Giessen27, Autonomous University of Barcelona28, University of Maryland, College Park29, Universidad del Tolima30, University of São Paulo31, University of La Réunion32, University of York33, University of Sydney34, Harvard University35, Goethe University Frankfurt36, University of Sheffield37, University of Ulm38, State University of Campinas39, Kenyon College40, Royal Botanic Gardens41, University of Florida42, University of Oldenburg43, University of Nebraska–Lincoln44, Tohoku University45, Northern Arizona University46, University of Wisconsin–Eau Claire47, Naturalis48, James Cook University49, Institut national de la recherche agronomique50, Newcastle University51, University of New South Wales52, Leipzig University53, Columbia University54, Estonian University of Life Sciences55, Polish Academy of Sciences56, Moscow State University57, Kyushu University58, Wageningen University and Research Centre59, Spanish National Research Council60, University of Regensburg61, University of Rennes62, Université du Québec à Trois-Rivières63, Potsdam Institute for Climate Impact Research64, Technical University of Denmark65, University of California, Los Angeles66, Hokkaido University67, Université de Sherbrooke68, Syracuse University69, Empresa Brasileira de Pesquisa Agropecuária70, University of Aberdeen71, Michigan State University72, Oak Ridge National Laboratory73, University of Leicester74, Utah State University75, Smithsonian Institution76, University of Missouri77
01 Sep 2011
TL;DR: TRY as discussed by the authors is a global database of plant traits, including morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs, which can be used for a wide range of research from evolutionary biology, community and functional ecology to biogeography.
Abstract: Plant 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.

2,017 citations

Journal ArticleDOI
Jens Kattge1, Gerhard Bönisch2, Sandra Díaz3, Sandra Lavorel  +751 moreInstitutions (314)
TL;DR: The extent of the trait data compiled in TRY is evaluated and emerging patterns of data coverage and representativeness are analyzed to 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.
Abstract: 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.

882 citations

Journal ArticleDOI
14 Jan 2016-Nature
TL;DR: Traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies.
Abstract: Phenotypic traits and their associated trade-offs have been shown to have globally consistent effects on individual plant physiological functions, but how these effects scale up to influence competition, a key driver of community assembly in terrestrial vegetation, has remained unclear. Here we use growth data from more than 3 million trees in over 140,000 plots across the world to show how three key functional traits--wood density, specific leaf area and maximum height--consistently influence competitive interactions. Fast maximum growth of a species was correlated negatively with its wood density in all biomes, and positively with its specific leaf area in most biomes. Low wood density was also correlated with a low ability to tolerate competition and a low competitive effect on neighbours, while high specific leaf area was correlated with a low competitive effect. Thus, traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies. Competition within species was stronger than between species, but an increase in trait dissimilarity between species had little influence in weakening competition. No benefit of dissimilarity was detected for specific leaf area or wood density, and only a weak benefit for maximum height. Our trait-based approach to modelling competition makes generalization possible across the forest ecosystems of the world and their highly diverse species composition.

618 citations

Journal ArticleDOI
TL;DR: In this article, the authors highlight recent work and outstanding questions in three areas: (i) selecting relevant traits; (ii) describing intraspecific trait variation and incorporating this variation into models; and (iii) scaling trait data to community and ecosystem-level processes.
Abstract: One of ecology's grand challenges is developing general rules to explain and predict highly complex systems. Understanding and predicting ecological processes from species' traits has been considered a 'Holy Grail' in ecology. Plant functional traits are increasingly being used to develop mechanistic models that can predict how ecological communities will respond to abiotic and biotic perturbations and how species will affect ecosystem function and services in a rapidly changing world; however, significant challenges remain. In this review, we highlight recent work and outstanding questions in three areas: (i) selecting relevant traits; (ii) describing intraspecific trait variation and incorporating this variation into models; and (iii) scaling trait data to community- and ecosystem-level processes. Over the past decade, there have been significant advances in the characterization of plant strategies based on traits and trait relationships, and the integration of traits into multivariate indices and models of community and ecosystem function. However, the utility of trait-based approaches in ecology will benefit from efforts that demonstrate how these traits and indices influence organismal, community, and ecosystem processes across vegetation types, which may be achieved through meta-analysis and enhancement of trait databases. Additionally, intraspecific trait variation and species interactions need to be incorporated into predictive models using tools such as Bayesian hierarchical modelling. Finally, existing models linking traits to community and ecosystem processes need to be empirically tested for their applicability to be realized.

475 citations

Journal ArticleDOI
Helge Bruelheide1, Jürgen Dengler2, Jürgen Dengler3, Oliver Purschke1, Jonathan Lenoir4, Borja Jiménez-Alfaro1, Borja Jiménez-Alfaro5, Stephan M. Hennekens6, Zoltán Botta-Dukát, Milan Chytrý7, Richard Field8, Florian Jansen9, Jens Kattge10, Valério D. Pillar11, Franziska Schrodt8, Franziska Schrodt10, Miguel D. Mahecha10, Robert K. Peet12, Brody Sandel13, Peter M. van Bodegom14, Jan Altman15, Esteban Álvarez-Dávila, Mohammed Abu Sayed Arfin Khan2, Mohammed Abu Sayed Arfin Khan16, Fabio Attorre17, Isabelle Aubin18, Christopher Baraloto19, Jorcely Barroso20, Marijn Bauters21, Erwin Bergmeier22, Idoia Biurrun23, Anne D. Bjorkman24, Benjamin Blonder25, Benjamin Blonder26, Andraž Čarni27, Andraž Čarni28, Luis Cayuela29, Tomáš Černý30, J. Hans C. Cornelissen31, Dylan Craven, Matteo Dainese32, Géraldine Derroire, Michele De Sanctis17, Sandra Díaz33, Jiří Doležal15, William Farfan-Rios34, William Farfan-Rios35, Ted R. Feldpausch36, Nicole J. Fenton37, Eric Garnier38, Greg R. Guerin39, Alvaro G. Gutiérrez40, Sylvia Haider1, Tarek Hattab41, Greg H. R. Henry42, Bruno Hérault38, Pedro Higuchi43, Norbert Hölzel44, Jürgen Homeier22, Anke Jentsch2, Norbert Jürgens45, Zygmunt Kącki46, Dirk Nikolaus Karger47, Dirk Nikolaus Karger48, Michael Kessler47, Michael Kleyer49, Ilona Knollová7, Andrey Yu. Korolyuk, Ingolf Kühn1, Daniel C. Laughlin50, Daniel C. Laughlin51, Frederic Lens14, Jacqueline Loos22, Frédérique Louault52, Mariyana Lyubenova53, Yadvinder Malhi26, Corrado Marcenò23, Maurizio Mencuccini, Jonas V. Müller54, Jérôme Munzinger38, Isla H. Myers-Smith55, David A. Neill, Ülo Niinemets, Kate H. Orwin56, Wim A. Ozinga57, Wim A. Ozinga6, Josep Peñuelas58, Aaron Pérez-Haase59, Aaron Pérez-Haase58, Petr Petřík15, Oliver L. Phillips60, Meelis Pärtel61, Peter B. Reich62, Peter B. Reich63, Christine Römermann64, Arthur Vinicius Rodrigues, Francesco Maria Sabatini1, Jordi Sardans58, Marco Schmidt, Gunnar Seidler1, Javier Silva Espejo65, Marcos Silveira20, Anita K. Smyth39, Maria Sporbert1, Jens-Christian Svenning24, Zhiyao Tang66, Raquel Thomas67, Ioannis Tsiripidis68, Kiril Vassilev69, Cyrille Violle38, Risto Virtanen70, Evan Weiher71, Erik Welk1, Karsten Wesche72, Karsten Wesche73, Marten Winter, Christian Wirth74, Christian Wirth10, Ute Jandt1 
Martin Luther University of Halle-Wittenberg1, University of Bayreuth2, Zürcher Fachhochschule3, University of Picardie Jules Verne4, University of Oviedo5, Wageningen University and Research Centre6, Masaryk University7, University of Nottingham8, University of Rostock9, Max Planck Society10, Universidade Federal do Rio Grande do Sul11, University of North Carolina at Chapel Hill12, Santa Clara University13, Leiden University14, Academy of Sciences of the Czech Republic15, Shahjalal University of Science and Technology16, Sapienza University of Rome17, Natural Resources Canada18, Florida International University19, Universidade Federal do Acre20, Ghent University21, University of Göttingen22, University of the Basque Country23, Aarhus University24, Rocky Mountain Biological Laboratory25, Environmental Change Institute26, Slovenian Academy of Sciences and Arts27, University of Nova Gorica28, King Juan Carlos University29, Czech University of Life Sciences Prague30, VU University Amsterdam31, University of Würzburg32, National University of Cordoba33, National University of Saint Anthony the Abbot in Cuzco34, Wake Forest University35, University of Exeter36, Université du Québec en Abitibi-Témiscamingue37, University of Montpellier38, University of Adelaide39, University of Chile40, IFREMER41, University of British Columbia42, Universidade do Estado de Santa Catarina43, University of Münster44, University of Hamburg45, University of Wrocław46, University of Zurich47, Swiss Federal Institute for Forest, Snow and Landscape Research48, University of Oldenburg49, University of Waikato50, University of Wyoming51, Institut national de la recherche agronomique52, Sofia University53, Royal Botanic Gardens54, University of Edinburgh55, Landcare Research56, Radboud University Nijmegen57, Spanish National Research Council58, University of Barcelona59, University of Leeds60, University of Tartu61, University of Sydney62, University of Minnesota63, University of Jena64, University of La Serena65, Peking University66, Iwokrama International Centre for Rain Forest Conservation and Development67, Aristotle University of Thessaloniki68, Bulgarian Academy of Sciences69, University of Oulu70, University of Wisconsin–Eau Claire71, American Museum of Natural History72, International Institute of Minnesota73, Leipzig University74
TL;DR: It is shown that global trait composition is captured by two main dimensions that are only weakly related to macro-environmental drivers, which reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale.
Abstract: Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait-environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.

349 citations


Cited by
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Journal ArticleDOI
07 Jun 2012-Nature
TL;DR: It is argued that human actions are dismantling the Earth’s ecosystems, eliminating genes, species and biological traits at an alarming rate, and the question of how such loss of biological diversity will alter the functioning of ecosystems and their ability to provide society with the goods and services needed to prosper is asked.
Abstract: The most unique feature of Earth is the existence of life, and the most extraordinary feature of life is its diversity. Approximately 9 million types of plants, animals, protists and fungi inhabit the Earth. So, too, do 7 billion people. Two decades ago, at the first Earth Summit, the vast majority of the world's nations declared that human actions were dismantling the Earth's ecosystems, eliminating genes, species and biological traits at an alarming rate. This observation led to the question of how such loss of biological diversity will alter the functioning of ecosystems and their ability to provide society with the goods and services needed to prosper.

5,244 citations

Journal Article
TL;DR: In this article, the authors present a document, redatto, voted and pubblicato by the Ipcc -Comitato intergovernativo sui cambiamenti climatici - illustra la sintesi delle ricerche svolte su questo tema rilevante.
Abstract: Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

4,187 citations

Journal ArticleDOI
TL;DR: This new handbook has a better balance between whole-plant traits, leaf traits, root and stem traits and regenerative traits, and puts particular emphasis on traits important for predicting species’ effects on key ecosystem properties.
Abstract: Plant functional traits are the features (morphological, physiological, phenological) that represent ecological strategies and determine how plants respond to environmental factors, affect other trophic levels and influence ecosystem properties. Variation in plant functional traits, and trait syndromes, has proven useful for tackling many important ecological questions at a range of scales, giving rise to a demand for standardised ways to measure ecologically meaningful plant traits. This line of research has been among the most fruitful avenues for understanding ecological and evolutionary patterns and processes. It also has the potential both to build a predictive set of local, regional and global relationships between plants and environment and to quantify a wide range of natural and human-driven processes, including changes in biodiversity, the impacts of species invasions, alterations in biogeochemical processes and vegetation–atmosphere interactions. The importance of these topics dictates the urgent need for more and better data, and increases the value of standardised protocols for quantifying trait variation of different species, in particular for traits with power to predict plant- and ecosystem-level processes, and for traits that can be measured relatively easily. Updated and expanded from the widely used previous version, this handbook retains the focus on clearly presented, widely applicable, step-by-step recipes, with a minimum of text on theory, and not only includes updated methods for the traits previously covered, but also introduces many new protocols for further traits. This new handbook has a better balance between whole-plant traits, leaf traits, root and stem traits and regenerative traits, and puts particular emphasis on traits important for predicting species’ effects on key ecosystem properties. We hope this new handbook becomes a standard companion in local and global efforts to learn about the responses and impacts of different plant species with respect to environmental changes in the present, past and future.

2,744 citations

Journal ArticleDOI
02 Apr 2015-Nature
TL;DR: A terrestrial assemblage database of unprecedented geographic and taxonomic coverage is analysed to quantify local biodiversity responses to land use and related changes and shows that in the worst-affected habitats, pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%.
Abstract: Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.

2,532 citations

Journal ArticleDOI
TL;DR: A single ‘fast–slow’ plant economics spectrum that integrates across leaves, stems and roots is a key feature of the plant universe and helps to explain individual ecological strategies, community assembly processes and the functioning of ecosystems.
Abstract: Summary 1. The leaf economics spectrum (LES) provides a useful framework for examining species strategies as shaped by their evolutionary history. However, that spectrum, as originally described, involved only two key resources (carbon and nutrients) and one of three economically important plant organs. Herein, I evaluate whether the economics spectrum idea can be broadly extended to water – the third key resource –stems, roots and entire plants and to individual, community and ecosystem scales. My overarching hypothesis is that strong selection along trait trade-off axes, in tandem with biophysical constraints, results in convergence for any taxon on a uniformly fast, medium or slow strategy (i.e. rates of resource acquisition and processing) for all organs and all resources. 2. Evidence for economic trait spectra exists for stems and roots as well as leaves, and for traits related to water as well as carbon and nutrients. These apply generally within and across scales (within and across communities, climate zones, biomes and lineages). 3. There are linkages across organs and coupling among resources, resulting in an integrated whole-plant economics spectrum. Species capable of moving water rapidly have low tissue density, short tissue life span and high rates of resource acquisition and flux at organ and individual scales. The reverse is true for species with the slow strategy. Different traits may be important in different conditions, but as being fast in one respect generally requires being fast in others, being fast or slow is a general feature of species. 4. Economic traits influence performance and fitness consistent with trait-based theory about underlying adaptive mechanisms. Traits help explain differences in growth and survival across resource gradients and thus help explain the distribution of species and the assembly of communities across light, water and nutrient gradients. Traits scale up – fast traits are associated with faster rates of ecosystem processes such as decomposition or primary productivity, and slow traits with slow process rates. 5. Synthesis. Traits matter. A single ‘fast–slow’ plant economics spectrum that integrates across leaves, stems and roots is a key feature of the plant universe and helps to explain individual ecological strategies, community assembly processes and the functioning of ecosystems.

2,246 citations