Soil nematode abundance and functional group composition at a global scale
Soil organisms are a crucial part of the terrestrial biosphere. Despite their importance for ecosystem functioning, few quantitative, spatially explicit models of the active belowground community currently exist. In particular, nematodes are the most abundant animals on Earth, filling all trophic levels in the soil food web. Here we use 6,759 georeferenced samples to generate a mechanistic understanding of the patterns of the global abundance of nematodes in the soil and the composition of their functional groups. The resulting maps show that 4.4 ± 0.64 × 1020 nematodes (with a total biomass of approximately 0.3 gigatonnes) inhabit surface soils across the world, with higher abundances in sub-Arctic regions (38% of total) than in temperate (24%) or tropical (21%) regions. Regional variations in these global trends also provide insights into local patterns of soil fertility and functioning. These high-resolution models provide the first steps towards representing soil ecological processes in global biogeochemical models and will enable the prediction of elemental cycling under current and future climate scenarios.
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dig-icvv-es-10261-193342 |
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koha |
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España |
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ES |
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Bibliográfico |
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biblioteca |
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Biblioteca del ICVV España |
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English |
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Biogeography Ecological modelling Machine learning Biogeography Ecological modelling Machine learning |
| spellingShingle |
Biogeography Ecological modelling Machine learning Biogeography Ecological modelling Machine learning Hoogen, Johan van den Geisen, Stefan Routh, Devin Ferris, Howard Traunspurger, Walter Wardle, David A. Goede, Ron G. M. de Adams, Byron J. Ahmad, Wasim Andriuzzi, Walter S. Bardgett, Richard D. Bonkowski, Michael Campos-Herrera, R. Cares, Juvenil E. Caruso, Tancredi Brito Caixeta, Larissa de Chen, Xiaoyun Costa, Sofia R. Creamer, Rachel Cunha Castro, José Mauro da Dam, Marie Djigal, Djibril Escuer, M. Griffiths, Bryan S. Gutiérrez, Carmen Hohberg, Karin Kalinkina, Daria Kardol, Paul Kergunteuil, Alan Korthals, Gerard Krashevska, Valentyna Kudrin, Alexey A. Li, Qi Liang, Wenju Magilton, Matthew Marais, Mariette Rodríguez Martín, José Antonio Matveeva, Elizaveta Mayad, El Hassan Mulder, Christian Mullin, Peter Neilson, Roy Nguyen, T. A. Duong Nielsen, Uffe N. Okada, Hiroaki Palomares Rius, Juan E. Pan, Kaiwen Peneva, Vlada Pellissier, Loïc Pereira da Silva, Julio Carlos Pitteloud, Camille Powers, Thomas O. Powers, Kirsten Quist, Casper W. Rasmann, Sergio Sánchez Moreno, Sara Scheu, Stefan Setälä, Heikki Sushchuk, Anna Tiunov, Alexei V. Trap, Jean Putten, Wim van der Vestergård, Mette Villenave, Cecile Waeyenberge, Lieven Wall, Diana H. Wilschut, Rutger Wright, Daniel G. Yang, Jiue-in Crowther, Thomas Ward Soil nematode abundance and functional group composition at a global scale |
| description |
Soil organisms are a crucial part of the terrestrial biosphere. Despite their importance for ecosystem functioning, few
quantitative, spatially explicit models of the active belowground community currently exist. In particular, nematodes
are the most abundant animals on Earth, filling all trophic levels in the soil food web. Here we use 6,759 georeferenced
samples to generate a mechanistic understanding of the patterns of the global abundance of nematodes in the soil and the
composition of their functional groups. The resulting maps show that 4.4 ± 0.64 × 1020 nematodes (with a total biomass
of approximately 0.3 gigatonnes) inhabit surface soils across the world, with higher abundances in sub-Arctic regions
(38% of total) than in temperate (24%) or tropical (21%) regions. Regional variations in these global trends also provide
insights into local patterns of soil fertility and functioning. These high-resolution models provide the first steps towards
representing soil ecological processes in global biogeochemical models and will enable the prediction of elemental cycling
under current and future climate scenarios. |
| author2 |
Netherlands Organization for Scientific Research |
| author_facet |
Netherlands Organization for Scientific Research Hoogen, Johan van den Geisen, Stefan Routh, Devin Ferris, Howard Traunspurger, Walter Wardle, David A. Goede, Ron G. M. de Adams, Byron J. Ahmad, Wasim Andriuzzi, Walter S. Bardgett, Richard D. Bonkowski, Michael Campos-Herrera, R. Cares, Juvenil E. Caruso, Tancredi Brito Caixeta, Larissa de Chen, Xiaoyun Costa, Sofia R. Creamer, Rachel Cunha Castro, José Mauro da Dam, Marie Djigal, Djibril Escuer, M. Griffiths, Bryan S. Gutiérrez, Carmen Hohberg, Karin Kalinkina, Daria Kardol, Paul Kergunteuil, Alan Korthals, Gerard Krashevska, Valentyna Kudrin, Alexey A. Li, Qi Liang, Wenju Magilton, Matthew Marais, Mariette Rodríguez Martín, José Antonio Matveeva, Elizaveta Mayad, El Hassan Mulder, Christian Mullin, Peter Neilson, Roy Nguyen, T. A. Duong Nielsen, Uffe N. Okada, Hiroaki Palomares Rius, Juan E. Pan, Kaiwen Peneva, Vlada Pellissier, Loïc Pereira da Silva, Julio Carlos Pitteloud, Camille Powers, Thomas O. Powers, Kirsten Quist, Casper W. Rasmann, Sergio Sánchez Moreno, Sara Scheu, Stefan Setälä, Heikki Sushchuk, Anna Tiunov, Alexei V. Trap, Jean Putten, Wim van der Vestergård, Mette Villenave, Cecile Waeyenberge, Lieven Wall, Diana H. Wilschut, Rutger Wright, Daniel G. Yang, Jiue-in Crowther, Thomas Ward |
| format |
artículo |
| topic_facet |
Biogeography Ecological modelling Machine learning |
| author |
Hoogen, Johan van den Geisen, Stefan Routh, Devin Ferris, Howard Traunspurger, Walter Wardle, David A. Goede, Ron G. M. de Adams, Byron J. Ahmad, Wasim Andriuzzi, Walter S. Bardgett, Richard D. Bonkowski, Michael Campos-Herrera, R. Cares, Juvenil E. Caruso, Tancredi Brito Caixeta, Larissa de Chen, Xiaoyun Costa, Sofia R. Creamer, Rachel Cunha Castro, José Mauro da Dam, Marie Djigal, Djibril Escuer, M. Griffiths, Bryan S. Gutiérrez, Carmen Hohberg, Karin Kalinkina, Daria Kardol, Paul Kergunteuil, Alan Korthals, Gerard Krashevska, Valentyna Kudrin, Alexey A. Li, Qi Liang, Wenju Magilton, Matthew Marais, Mariette Rodríguez Martín, José Antonio Matveeva, Elizaveta Mayad, El Hassan Mulder, Christian Mullin, Peter Neilson, Roy Nguyen, T. A. Duong Nielsen, Uffe N. Okada, Hiroaki Palomares Rius, Juan E. Pan, Kaiwen Peneva, Vlada Pellissier, Loïc Pereira da Silva, Julio Carlos Pitteloud, Camille Powers, Thomas O. Powers, Kirsten Quist, Casper W. Rasmann, Sergio Sánchez Moreno, Sara Scheu, Stefan Setälä, Heikki Sushchuk, Anna Tiunov, Alexei V. Trap, Jean Putten, Wim van der Vestergård, Mette Villenave, Cecile Waeyenberge, Lieven Wall, Diana H. Wilschut, Rutger Wright, Daniel G. Yang, Jiue-in Crowther, Thomas Ward |
| author_sort |
Hoogen, Johan van den |
| title |
Soil nematode abundance and functional group composition at a global scale |
| title_short |
Soil nematode abundance and functional group composition at a global scale |
| title_full |
Soil nematode abundance and functional group composition at a global scale |
| title_fullStr |
Soil nematode abundance and functional group composition at a global scale |
| title_full_unstemmed |
Soil nematode abundance and functional group composition at a global scale |
| title_sort |
soil nematode abundance and functional group composition at a global scale |
| publishDate |
2019-08-08 |
| url |
http://hdl.handle.net/10261/193342 http://dx.doi.org/10.13039/501100000270 http://dx.doi.org/10.13039/501100002261 http://dx.doi.org/10.13039/501100001807 http://dx.doi.org/10.13039/501100000923 http://dx.doi.org/10.13039/501100002367 http://dx.doi.org/10.13039/501100003593 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/501100004901 http://dx.doi.org/10.13039/501100001871 http://dx.doi.org/10.13039/501100001655 http://dx.doi.org/10.13039/501100001659 http://dx.doi.org/10.13039/100011150 http://dx.doi.org/10.13039/501100003329 http://dx.doi.org/10.13039/501100001809 http://dx.doi.org/10.13039/100000001 |
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1777670952642936832 |
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dig-icvv-es-10261-1933422022-12-01T08:34:15Z Soil nematode abundance and functional group composition at a global scale Hoogen, Johan van den Geisen, Stefan Routh, Devin Ferris, Howard Traunspurger, Walter Wardle, David A. Goede, Ron G. M. de Adams, Byron J. Ahmad, Wasim Andriuzzi, Walter S. Bardgett, Richard D. Bonkowski, Michael Campos-Herrera, R. Cares, Juvenil E. Caruso, Tancredi Brito Caixeta, Larissa de Chen, Xiaoyun Costa, Sofia R. Creamer, Rachel Cunha Castro, José Mauro da Dam, Marie Djigal, Djibril Escuer, M. Griffiths, Bryan S. Gutiérrez, Carmen Hohberg, Karin Kalinkina, Daria Kardol, Paul Kergunteuil, Alan Korthals, Gerard Krashevska, Valentyna Kudrin, Alexey A. Li, Qi Liang, Wenju Magilton, Matthew Marais, Mariette Rodríguez Martín, José Antonio Matveeva, Elizaveta Mayad, El Hassan Mulder, Christian Mullin, Peter Neilson, Roy Nguyen, T. A. Duong Nielsen, Uffe N. Okada, Hiroaki Palomares Rius, Juan E. Pan, Kaiwen Peneva, Vlada Pellissier, Loïc Pereira da Silva, Julio Carlos Pitteloud, Camille Powers, Thomas O. Powers, Kirsten Quist, Casper W. Rasmann, Sergio Sánchez Moreno, Sara Scheu, Stefan Setälä, Heikki Sushchuk, Anna Tiunov, Alexei V. Trap, Jean Putten, Wim van der Vestergård, Mette Villenave, Cecile Waeyenberge, Lieven Wall, Diana H. Wilschut, Rutger Wright, Daniel G. Yang, Jiue-in Crowther, Thomas Ward Netherlands Organization for Scientific Research National Science Foundation (US) Global Environment Facility Natural Environment Research Council (UK) Fundação de Amparo à Pesquisa do Estado de São Paulo Minas Gerais Fundação de Amparo à Pesquisa do Estado de São Paulo Fundação para a Ciência e a Tecnologia (Portugal) European Commission Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brasil) German Research Foundation Chinese Academy of Sciences National Natural Science Foundation of China Ministerio de Economía y Competitividad (España) German Academic Exchange Service National Foundation for Science and Technology Development (Vietnam) Australian Research Council Scottish Government's Rural and Environment Science and Analytical Services Russian Foundation for Basic Research Campos-Herrera, R. [0000-0003-0852-5269] Biogeography Ecological modelling Machine learning Soil organisms are a crucial part of the terrestrial biosphere. Despite their importance for ecosystem functioning, few quantitative, spatially explicit models of the active belowground community currently exist. In particular, nematodes are the most abundant animals on Earth, filling all trophic levels in the soil food web. Here we use 6,759 georeferenced samples to generate a mechanistic understanding of the patterns of the global abundance of nematodes in the soil and the composition of their functional groups. The resulting maps show that 4.4 ± 0.64 × 1020 nematodes (with a total biomass of approximately 0.3 gigatonnes) inhabit surface soils across the world, with higher abundances in sub-Arctic regions (38% of total) than in temperate (24%) or tropical (21%) regions. Regional variations in these global trends also provide insights into local patterns of soil fertility and functioning. These high-resolution models provide the first steps towards representing soil ecological processes in global biogeochemical models and will enable the prediction of elemental cycling under current and future climate scenarios. This research was supported by a grant from DOB Ecology to T.W.C., a grant from the Netherlands Organization for Scientific Research (grant 016.Veni.181.078) to S.G., grants from NSF (OPP 1115245, 1341736, 0840979) to B.J.A., by a Ramon y Cajal fellow award (RYC-2016-19939) to R.C.H., a grant from UNEP & Global Environment Facility to J.E.C., a grant from NERC (NE/M017036/1) to T.C., a grant from FAPEMIG/FAPESP/VALE S.A.(CRA-RDP-00136-10) to L.B.C., through the strategic programme UID/BIA/04050/2013 (POCI-01-0145-FEDER-007569) awarded to S.R.C., a grant from CNPq PROTAX (562346/2010-4) to J.M.d.C.C., a grant from DFG (CRC990) to V.K. and S.S., a grant from the MSHE of Russia (AAAA-A17-117112850234-5) to A.A.K., grants from the Chinese Academy of Sciences (XDB15010402) and the National Natural Science Foundation of China (41877047) to Q.L., grants from the National Natural Science Foundation of China (31330011, 31170484) to W.L., grants from NERC (NE/M017036/1) to M.M., grants from the Spanish Ministry of Innovation (CGL2009-14686-C02-01/ 02, CGL2013-43675-P) to J.A.R.M., grants from NSF (DEB-0450537, DEB-1145440) to P.M., T.O.P. and K. Powers, grants from the German Academic Exchange Service (PKZ 91540366) and NAFOSTED (106.05 – 2017.330) to T.A.D.N., by an ARC Discovery project (DP150104199) to U.N.N., by the National Key Research and Development Program of China (2016YFC0502101) and the National Natural Science Foundation of China (31370632) to K. Pan, a grant from the Natural Environment Research Council (NERC) to D.G.W., a grant from BAPHIQ (106AS-9.5.1-BQ-B3) J.-i.Y. The James Hutton Institute receives financial support from the Scottish Government Rural and Environment Science and Analytical Services (RESAS) division. Investigations in northwest Russia were carried out under state order for IB KarRC RAS and are partially supported by the Russian Foundation for Basic Research (18-34-00849). We thank E. Clark and A. Orgiazzi for review of the manuscript; and R. Bouharroud, Z. Ferji, L. Jackson and E. Mzough for providing data. Peer reviewed 2019-10-24T11:00:21Z 2019-10-24T11:00:21Z 2019-08-08 artículo http://purl.org/coar/resource_type/c_6501 Nature 572: 194-198 (2019) 0028-0836 http://hdl.handle.net/10261/193342 10.1038/s41586-019-1418-6 1476-4687 http://dx.doi.org/10.13039/501100000270 http://dx.doi.org/10.13039/501100002261 http://dx.doi.org/10.13039/501100001807 http://dx.doi.org/10.13039/501100000923 http://dx.doi.org/10.13039/501100002367 http://dx.doi.org/10.13039/501100003593 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/501100004901 http://dx.doi.org/10.13039/501100001871 http://dx.doi.org/10.13039/501100001655 http://dx.doi.org/10.13039/501100001659 http://dx.doi.org/10.13039/100011150 http://dx.doi.org/10.13039/501100003329 http://dx.doi.org/10.13039/501100001809 http://dx.doi.org/10.13039/100000001 en #PLACEHOLDER_PARENT_METADATA_VALUE# info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/RYC-2016-19939 Postprint http://dx.doi.org/10.1038/s41586-019-1418-6 Sí open |