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Socio-ecological factors determine crop performance in agricultural systems
Agricultural production systems are affected by complex interactions between social and ecological factors, which are often hard to integrate in a common analytical framework. We evaluated differences in crop production among farms by integrating components of several related research disciplines in...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7060324/ https://www.ncbi.nlm.nih.gov/pubmed/32144284 http://dx.doi.org/10.1038/s41598-020-60927-1 |
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author | Nkurunziza, Libère Watson, Christine A. Öborn, Ingrid Smith, Henrik G. Bergkvist, Göran Bengtsson, Jan |
author_facet | Nkurunziza, Libère Watson, Christine A. Öborn, Ingrid Smith, Henrik G. Bergkvist, Göran Bengtsson, Jan |
author_sort | Nkurunziza, Libère |
collection | PubMed |
description | Agricultural production systems are affected by complex interactions between social and ecological factors, which are often hard to integrate in a common analytical framework. We evaluated differences in crop production among farms by integrating components of several related research disciplines in a single socio-ecological analysis. Specifically, we evaluated spring barley (Hordeum vulgare, L.) performance on 34 farms (organic and conventional) in two agro-ecological zones to unravel the importance of ecological, crop and management factors in the performance of a standard crop. We used Projections to Latent Structures (PLS), a simple but robust analytical tool widely utilized in research disciplines dealing with complex systems (e.g. social sciences and chemometrics), but infrequently in agricultural sciences. We show that barley performance on organic farms was affected by previous management, landscape structure, and soil quality, in contrast to conventional farms where external inputs were the main factors affecting biomass and grain yield. This indicates that more complex management strategies are required in organic than in conventional farming systems. We conclude that the PLS method combining socio-ecological and biophysical factors provides improved understanding of the various interacting factors determining crop performance and can help identify where improvements in the agricultural system are most likely to be effective. |
format | Online Article Text |
id | pubmed-7060324 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70603242020-03-18 Socio-ecological factors determine crop performance in agricultural systems Nkurunziza, Libère Watson, Christine A. Öborn, Ingrid Smith, Henrik G. Bergkvist, Göran Bengtsson, Jan Sci Rep Article Agricultural production systems are affected by complex interactions between social and ecological factors, which are often hard to integrate in a common analytical framework. We evaluated differences in crop production among farms by integrating components of several related research disciplines in a single socio-ecological analysis. Specifically, we evaluated spring barley (Hordeum vulgare, L.) performance on 34 farms (organic and conventional) in two agro-ecological zones to unravel the importance of ecological, crop and management factors in the performance of a standard crop. We used Projections to Latent Structures (PLS), a simple but robust analytical tool widely utilized in research disciplines dealing with complex systems (e.g. social sciences and chemometrics), but infrequently in agricultural sciences. We show that barley performance on organic farms was affected by previous management, landscape structure, and soil quality, in contrast to conventional farms where external inputs were the main factors affecting biomass and grain yield. This indicates that more complex management strategies are required in organic than in conventional farming systems. We conclude that the PLS method combining socio-ecological and biophysical factors provides improved understanding of the various interacting factors determining crop performance and can help identify where improvements in the agricultural system are most likely to be effective. Nature Publishing Group UK 2020-03-06 /pmc/articles/PMC7060324/ /pubmed/32144284 http://dx.doi.org/10.1038/s41598-020-60927-1 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Nkurunziza, Libère Watson, Christine A. Öborn, Ingrid Smith, Henrik G. Bergkvist, Göran Bengtsson, Jan Socio-ecological factors determine crop performance in agricultural systems |
title | Socio-ecological factors determine crop performance in agricultural systems |
title_full | Socio-ecological factors determine crop performance in agricultural systems |
title_fullStr | Socio-ecological factors determine crop performance in agricultural systems |
title_full_unstemmed | Socio-ecological factors determine crop performance in agricultural systems |
title_short | Socio-ecological factors determine crop performance in agricultural systems |
title_sort | socio-ecological factors determine crop performance in agricultural systems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7060324/ https://www.ncbi.nlm.nih.gov/pubmed/32144284 http://dx.doi.org/10.1038/s41598-020-60927-1 |
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