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Journal ArticleDOI

A novel framework for linking functional diversity of plants with other trophic levels for the quantification of ecosystem services.

TL;DR: A novel conceptual framework is presented that proposes to apply trait-based approaches to predicting the impact of environmental change on ecosystem service delivery by multi-trophic systems by leveraging the response-effect trait approach to capture functional relationships that drive trophic interactions.
Abstract: A novel conceptual framework is presented that proposes to apply trait-based approaches to predicting the impact of environmental change on ecosystem service delivery by multi-trophic systems. Development of the framework was based on an extension of the response-effect trait approach to capture functional relationships that drive trophic interactions. The framework was populated with worked examples to demonstrate its flexibility and value for linking disparate data sources, identifying knowledge gaps and generating hypotheses for quantitative models. A novel conceptual framework, based on an extension of the plant response - effect trait approach, proposes to apply trait-based approaches to predicting the impact of environmental change on ecosystem services delivered by multiple trophic levels. We demonstrate the flexibility and value of the framework for linking disparate data sources, identifying knowledge gaps and generating hypotheses for quantitative models. © 2013 International Association for Vegetation Science.
Citations
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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
TL;DR: Emerging evidence that illustrates how root traits impact ecosystem processes is synthesised, and a pathway to unravel the complex roles of root traits in driving ecosystem processes and their response to global change is proposed.
Abstract: Ecologists are increasingly adopting trait-based approaches to understand how community change influences ecosystem processes. However, most of this research has focussed on aboveground plant traits, whereas it is becoming clear that root traits are important drivers of many ecosystem processes, such as carbon (C) and nutrient cycling, and the formation and structural stability of soil. Here, we synthesise emerging evidence that illustrates how root traits impact ecosystem processes, and propose a pathway to unravel the complex roles of root traits in driving ecosystem processes and their response to global change. Finally, we identify research challenges and novel technologies to address them.

824 citations

Journal ArticleDOI
TL;DR: It is shown how functional biogeography bridges species-basedBiogeography and earth science to provide ideas and tools to help explain gradients in multifaceted diversity (including species, functional, and phylogenetic diversities), predict ecosystem functioning and services worldwide, and infuse regional and global conservation programs with a functional basis.
Abstract: Understanding, modeling, and predicting the impact of global change on ecosystem functioning across biogeographical gradients can benefit from enhanced capacity to represent biota as a continuous distribution of traits. However, this is a challenge for the field of biogeography historically grounded on the species concept. Here we focus on the newly emergent field of functional biogeography: the study of the geographic distribution of trait diversity across organizational levels. We show how functional biogeography bridges species-based biogeography and earth science to provide ideas and tools to help explain gradients in multifaceted diversity (including species, functional, and phylogenetic diversities), predict ecosystem functioning and services worldwide, and infuse regional and global conservation programs with a functional basis. Although much recent progress has been made possible because of the rising of multiple data streams, new developments in ecoinformatics, and new methodological advances, future directions should provide a theoretical and comprehensive framework for the scaling of biotic interactions across trophic levels and its ecological implications.

517 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
TL;DR: In this article, a comprehensive overview of ecosystem services provided by natural and semi-natural grasslands, using southern Africa (SA) and northwest Europe as case studies, respectively, is presented.
Abstract: Extensively managed grasslands are recognized globally for their high biodiversity and their social and cultural values. However, their capacity to deliver multiple ecosystem services (ES) as parts of agricultural systems is surprisingly understudied compared to other production systems. We undertook a comprehensive overview of ES provided by natural and semi-natural grasslands, using southern Africa (SA) and northwest Europe as case studies, respectively. We show that these grasslands can supply additional non-agricultural services, such as water supply and flow regulation, carbon storage, erosion control, climate mitigation, pollination, and cultural ES. While demand for ecosystems services seems to balance supply in natural grasslands of SA, the smaller areas of semi-natural grasslands in Europe appear to not meet the demand for many services. We identified three bundles of related ES from grasslands: water ES including fodder production, cultural ES connected to livestock production, and population-based regulating services (e.g., pollination and biological control), which also linked to biodiversity. Greenhouse gas emission mitigation seemed unrelated to the three bundles. The similarities among the bundles in SA and northwestern Europe suggest that there are generalities in ES relations among natural and semi-natural grassland areas. We assessed trade-offs and synergies among services in relation to management practices and found that although some trade-offs are inevitable, appropriate management may create synergies and avoid trade-offs among many services. We argue that ecosystem service and food security research and policy should give higher priority to how grasslands can be managed for fodder and meat production alongside other ES. By integrating grasslands into agricultural production systems and land-use decisions locally and regionally, their potential to contribute to functional landscapes and to food security and sustainable livelihoods can be greatly enhanced. (Less)

402 citations

References
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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 ArticleDOI
TL;DR: This paper provides an international methodological protocol aimed at standardising this research effort, based on consensus among a broad group of scientists in this field, and features a practical handbook with step-by-step recipes, for 28 functional traits recognised as critical for tackling large-scale ecological questions.
Abstract: There is growing recognition that classifying terrestrial plant species on the basis of their function (into 'functional types') rather than their higher taxonomic identity, is a promising way forward for tackling important ecological questions at the scale of ecosystems, landscapes or biomes. These questions include those on vegetation responses to and vegetation effects on, environmental changes (e.g. changes in climate, atmospheric chemistry, land use or other disturbances). There is also growing consensus about a shortlist of plant traits that should underlie such functional plant classifications, because they have strong predictive power of important ecosystem responses to environmental change and/or they themselves have strong impacts on ecosystem processes. The most favoured traits are those that are also relatively easy and inexpensive to measure for large numbers of plant species. Large international research efforts, promoted by the IGBP–GCTE Programme, are underway to screen predominant plant species in various ecosystems and biomes worldwide for such traits. This paper provides an international methodological protocol aimed at standardising this research effort, based on consensus among a broad group of scientists in this field. It features a practical handbook with step-by-step recipes, with relatively brief information about the ecological context, for 28 functional traits recognised as critical for tackling large-scale ecological questions.

3,288 citations

Journal ArticleDOI
TL;DR: A framework using concepts and results from community ecology, ecosystem ecology and evolutionary biology to provide a linkage between traits associated with the response of plants to environmental factors and traits that determine effects of plants on ecosystem functions is presented.
Abstract: Summary 1. The concept of plant functional type proposes that species can be grouped according to common responses to the environment and/or common effects on ecosystem processes. However, the knowledge of relationships between traits associated with the response of plants to environmental factors such as resources and disturbances (response traits), and traits that determine effects of plants on ecosystem functions (effect traits), such as biogeochemical cycling or propensity to disturbance, remains rudimentary. 2. We present a framework using concepts and results from community ecology, ecosystem ecology and evolutionary biology to provide this linkage. Ecosystem functioning is the end result of the operation of multiple environmental filters in a hierarchy of scales which, by selecting individuals with appropriate responses, result in assemblages with varying trait composition. Functional linkages and trade-offs among traits, each of which relates to one or several processes, determine whether or not filtering by different factors gives a match, and whether ecosystem effects can be easily deduced

2,786 citations

Journal ArticleDOI
TL;DR: It is concluded that in order to reliably predict the effects of GEC on community and ecosystem processes, the greatest single challenge will be to determine how biotic and abiotic context alters the direction and magnitude of G EC effects on biotic interactions.
Abstract: The main drivers of global environmental change (CO2 enrichment, nitrogen deposition, climate, biotic invasions and land use) cause extinctions and alter species distributions, and recent evidence shows that they exert pervasive impacts on various antagonistic and mutualistic interactions among species. In this review, we synthesize data from 688 published studies to show that these drivers often alter competitive interactions among plants and animals, exert multitrophic effects on the decomposer food web, increase intensity of pathogen infection, weaken mutualisms involving plants, and enhance herbivory while having variable effects on predation. A recurrent finding is that there is substantial variability among studies in both the magnitude and direction of effects of any given GEC driver on any given type of biotic interaction. Further, we show that higher order effects among multiple drivers acting simultaneously create challenges in predicting future responses to global environmental change, and that extrapolating these complex impacts across entire networks of species interactions yields unanticipated effects on ecosystems. Finally, we conclude that in order to reliably predict the effects of GEC on community and ecosystem processes, the greatest single challenge will be to determine how biotic and abiotic context alters the direction and magnitude of GEC effects on biotic interactions.

2,070 citations

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 Lloyd49, Jon Lloyd14, 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