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Gerhard Bönisch

Bio: Gerhard Bönisch is an academic researcher from Max Planck Society. The author has contributed to research in topics: Trait & Nansen Basin. The author has an hindex of 28, co-authored 35 publications receiving 6006 citations. Previous affiliations of Gerhard Bönisch include Columbia University & Lamont–Doherty Earth Observatory.

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-Bares7, 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 Western Sydney6, University of Minnesota7, 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
14 Jan 2016-Nature
TL;DR: Analysis of worldwide variation in six major traits critical to growth, survival and reproduction within the largest sample of vascular plant species ever compiled found that occupancy of six-dimensional trait space is strongly concentrated, indicating coordination and trade-offs.
Abstract: The authors found that the key elements of plant form and function, analysed at global scale, are largely concentrated into a two-dimensional plane indexed by the size of whole plants and organs on the one hand, and the construction costs for photosynthetic leaf area, on the other.

1,814 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
TL;DR: A global meta-analysis of 58 studies of drought-induced forest mortality identified a consistent global-scale response, where mortality increased with drought severity, and suggested that mortality could become increasingly widespread in the future.
Abstract: Drought events are increasing globally, and reports of consequent forest mortality are widespread. However, due to a lack of a quantitative global synthesis, it is still not clear whether drought-induced mortality rates differ among global biomes and whether functional traits influence the risk of drought-induced mortality. To address these uncertainties, we performed a global meta-analysis of 58 studies of drought-induced forest mortality. Mortality rates were modelled as a function of drought, temperature, biomes, phylogenetic and functional groups and functional traits. We identified a consistent global-scale response, where mortality increased with drought severity [log mortality (trees trees-1 year-1 ) increased 0.46 (95% CI = 0.2-0.7) with one SPEI unit drought intensity]. We found no significant differences in the magnitude of the response depending on forest biomes or between angiosperms and gymnosperms or evergreen and deciduous tree species. Functional traits explained some of the variation in drought responses between species (i.e. increased from 30 to 37% when wood density and specific leaf area were included). Tree species with denser wood and lower specific leaf area showed lower mortality responses. Our results illustrate the value of functional traits for understanding patterns of drought-induced tree mortality and suggest that mortality could become increasingly widespread in the future.

332 citations

Journal ArticleDOI
Owen K. Atkin1, Keith J. Bloomfield1, Peter B. Reich2, Peter B. Reich3, Mark G. Tjoelker2, Gregory P. Asner4, Damien Bonal5, Gerhard Bönisch6, Matt Bradford7, Lucas A. Cernusak8, Eric G. Cosio9, Danielle Creek1, Danielle Creek2, Kristine Y. Crous2, Kristine Y. Crous1, Tomas F. Domingues10, Jeffrey S. Dukes11, John J. G. Egerton1, John R. Evans1, Graham D. Farquhar1, Nikolaos M. Fyllas12, Paul P. G. Gauthier13, Paul P. G. Gauthier1, Emanuel Gloor14, Teresa E. Gimeno2, Kevin L. Griffin15, Rossella Guerrieri16, Rossella Guerrieri17, Mary A. Heskel1, Chris Huntingford, Françoise Yoko Ishida8, Jens Kattge6, Hans Lambers18, Michael J. Liddell8, Jon Lloyd8, Jon Lloyd19, Christopher H. Lusk20, Roberta E. Martin4, Ayal P. Maksimov, Trofim C. Maximov, Yadvinder Malhi21, Belinda E. Medlyn22, Belinda E. Medlyn2, Patrick Meir1, Patrick Meir17, Lina M. Mercado23, Nicholas Mirotchnick24, Desmond Ng25, Desmond Ng1, Ülo Niinemets26, Odhran S. O'Sullivan1, Oliver L. Phillips14, Lourens Poorter27, Pieter Poot18, I. Colin Prentice19, I. Colin Prentice22, Norma Salinas9, Norma Salinas21, Lucy Rowland17, Michael G. Ryan28, Stephen Sitch23, Martijn Slot29, Martijn Slot30, Nicholas G. Smith11, Matthew H. Turnbull31, Mark C. Vanderwel29, Mark C. Vanderwel32, Fernando Valladares33, Erik J. Veneklaas18, Lasantha K. Weerasinghe1, Lasantha K. Weerasinghe34, Christian Wirth35, Ian J. Wright22, Kirk R. Wythers3, Jen Xiang1, Shuang Xiang36, Shuang Xiang1, Joana Zaragoza-Castells17, Joana Zaragoza-Castells23 
TL;DR: A new global database of Rdark and associated leaf traits is analyzed and values at any given Vcmax or leaf nitrogen concentration were higher in herbs than in woody plants, and variation in Rdark among species and across global gradients in T and aridity is highlighted.
Abstract: Leaf dark respiration (R-dark) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of R-dark and associated leaf traits. Data for 899 species were compiled from 100 sites (from the Arctic to the tropics). Several woody and nonwoody plant functional types (PFTs) were represented. Mixed-effects models were used to disentangle sources of variation in R-dark. Area-based R-dark at the prevailing average daily growth temperature (T) of each siteincreased only twofold from the Arctic to the tropics, despite a 20 degrees C increase in growing T (8-28 degrees C). By contrast, R-dark at a standard T (25 degrees C, R-dark(25)) was threefold higher in the Arctic than in the tropics, and twofold higher at arid than at mesic sites. Species and PFTs at cold sites exhibited higher R-dark(25) at a given photosynthetic capacity (V-cmax(25)) or leaf nitrogen concentration ([N]) than species at warmer sites. R-dark(25) values at any given V-cmax(25) or [N] were higher in herbs than in woody plants. The results highlight variation in R-dark among species and across global gradients in T and aridity. In addition to their ecological significance, the results provide a framework for improving representation of R-dark in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs).

310 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 ArticleDOI
TL;DR: It is concluded that multiple Imputation for Nonresponse in Surveys should be considered as a legitimate method for answering the question of why people do not respond to survey questions.
Abstract: 25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.

3,216 citations

Journal ArticleDOI
TL;DR: In this paper, a taxonomy of recent contributions related to explainability of different machine learning models, including those aimed at explaining Deep Learning methods, is presented, and a second dedicated taxonomy is built and examined in detail.

2,827 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