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| 91. |  | Arboleya, J.Gilsanz, J.C.García, C.Quintana, R. Fertirriego ln: Seminario Cultivos Protegidos y Hortalizas de Hoja, 1995, Rivera, Uruguay Trabajos presentados. Las Brujas, Canelones (Uruguay): INIA, 1995. p. 21-25 (INIA Serie Actividades de Difusión ; 69) "JUNAGRA; PNUD; INIA"| Biblioteca(s): INIA La Estanzuela; INIA Las Brujas; INIA Tacuarembó. |
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| 100. | | Arboleya, J.Gilsanz, J.C.García, C.Quintana, R. Sistema de riego ln: Seminario Cultivos Protegidos y Hortalizas de Hoja, 1995, Rivera, Uruguay Trabajos presentados. Las Brujas, Canelones (Uruguay): INIA, 1995. p. 18-20 (INIA Serie Actividades de Difusión ; 69) "JUNAGRA; PNUD; INIA"| Biblioteca(s): INIA La Estanzuela; INIA Las Brujas; INIA Tacuarembó. |
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
17/05/2022 |
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Actualizado : |
17/05/2022 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
PACHECO-ROMERO, M.; VALLEJOS, M.; PARUELO, J.; ALCARAZ-SEGURA, D.; TORRES-GARCÍA, M. T.; SALINAS-BONILLO, M. J.; CABELLO, JAVIER |
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Afiliación : |
MANUEL PACHECO-ROMERO, Andalusian Center for the Assessment and Monitoring of Global Change (CAESCG), Univ. of Almería, Spain; Dept. of Biology and Geology, Univ. of Almería, Spain; Faculty of Sustainability, Leuphana, Univ. Lüneburg, Germany.; MARÍA VALLEJOS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Cátedra de Métodos Cuantitativos y Sistemas de Información, Facultad de Agronomía, Universidad de Buenos Aires, Buenos Aires, Argentina; JOSÉ PARUELO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Cátedra Métodos Cuantitativos y Sistemas de Información, Fac. Agronomía, Univ. de Buenos Aires, Bs.As., Argentina; Fac. de Ciencias, IECA, Universidad de la República, Mdeo, Uruguay.; DOMINGO ALCARAZ-SEGURA, Andalusian Center for the Assessment and Monitoring of Global Change (CAESCG), Univ. of Almería, Spain;Dept. of Botany, Univ. of Granada, Spain; Iecolab, Interuniversity Institute for Earth System Research (IISTA), Univ. of Granada, Spain; M. TRINIDAD TORRES-GARCÍA, Andalusian Center for the Assessment and Monitoring of Global Change (CAESCG), University of Almería, Almería, Spain Department of Biology and Geology, University of Almería, Almería, Spain; MARÍA J. SALINAS-BONILLO, Andalusian Center for the Assessment and Monitoring of Global Change (CAESCG), University of Almería, Almería, Spain Department of Biology and Geology, University of Almería, Almería, Spain; JAVIER CABELLO, Andalusian Center for the Assessment and Monitoring of Global Change (CAESCG), University of Almería, Almería, Spain Department of Biology and Geology, University of Almería, Almería, Spain. |
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Título : |
A data-driven methodological routine to identify key indicators for social-ecological system archetype mapping. |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
Environmental Research Letters, 2022, Volume 17, Issue 4, Article number 045019. OPEN ACCESS. doi: https://doi.org/10.1088/1748-9326/ac5ded |
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ISSN : |
1748-9318 |
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DOI : |
10.1088/1748-9326/ac5ded |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 2 July 2021; Revised 28 January 2022; Accepted for publication 15 March 2022; Published 30 March 2022.
License: Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must
maintain attribution to the author(s) and the title of the work, journal citation and DOI. -- Article: Gold Open Access, Green Open Access.
Corresponding author: Pacheco-Romero, M.; Andalusian Center for the Assessment and Monitoring of Global Change (CAESCG), University of Almería, Almería, Spain; email:manuel.pacheco@ual.es --
Funding text - We thank R Romero-Calcerrada and J M Requena-Mullor for helpful discussions, and three anonymous reviewers for their constructive suggestions to improve this paper. We also thank the Spanish Ministry of Economy and Business (Project CGL2014-61610-EXP) for the financial support, as well as the Spanish Ministry of Education for the FPU Predoctoral Fellowship of MPR (FPU14/06782) and MTTG (16/02214). MPR gratefully acknowledges funding from Universidad de Almería for a research stay at the Laboratory of Regional Analysis and Remote Sensing (LART) of University of Buenos Aires to develop this study. This research was done within the LTSER Platforms of the Arid Iberian South East—Spain (LTER_EU_ES_027) and Sierra Nevada/Granada (ES- SNE)—Spain (LTER_EU_ES_010), and contributes to the Global Land Programme. |
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Contenido : |
ABSTRACT.- The spatial mapping of social-ecological system (SES) archetypes constitutes a fundamental tool to operationalize the SES concept in empirical research. Approaches to detect, map, and characterize SES archetypes have evolved over the last decade towards more integrative and comparable perspectives guided by SES conceptual frameworks and reference lists of variables. However, hardly any studies have investigated how to empirically identify the most relevant set of indicators to map the diversity of SESs. In this study, we propose a data-driven methodological routine based on multivariate statistical analysis to identify the most relevant indicators for mapping and characterizing SES archetypes in a particular region. Taking Andalusia (Spain) as a case study, we applied this methodological routine to 86 indicators representing multiple variables and dimensions of the SES. Additionally, we assessed how the empirical relevance of these indicators contributes to previous expert and empirical knowledge on key variables for characterizing SESs. We identified 29 key indicators that allowed us to map 15 SES archetypes encompassing natural, mosaic, agricultural, and urban systems, which uncovered contrasting land sharing and land sparing patterns throughout the territory. We found synergies but also disagreements between empirical and expert knowledge on the relevance of variables: agreement on their widespread relevance (32.7% of the variables, e.g. crop and livestock production, net primary productivity, population density); relevance conditioned by the context or the scale (16.3%, e.g. land protection, educational level); lack of agreement (20.4%, e.g. economic level, land tenure); need of further assessments due to the lack of expert or empirical knowledge (30.6%). Overall, our data-driven approach can contribute to more objective selection of relevant indicators for SES mapping, which may help to produce comparable and generalizable empirical knowledge on key variables for characterizing SESs, as well as to derive more representative descriptions and causal factor configurations in SES archetype analysis.
© 2022 The Author(s). Published by IOP Publishing Ltd. MenosABSTRACT.- The spatial mapping of social-ecological system (SES) archetypes constitutes a fundamental tool to operationalize the SES concept in empirical research. Approaches to detect, map, and characterize SES archetypes have evolved over the last decade towards more integrative and comparable perspectives guided by SES conceptual frameworks and reference lists of variables. However, hardly any studies have investigated how to empirically identify the most relevant set of indicators to map the diversity of SESs. In this study, we propose a data-driven methodological routine based on multivariate statistical analysis to identify the most relevant indicators for mapping and characterizing SES archetypes in a particular region. Taking Andalusia (Spain) as a case study, we applied this methodological routine to 86 indicators representing multiple variables and dimensions of the SES. Additionally, we assessed how the empirical relevance of these indicators contributes to previous expert and empirical knowledge on key variables for characterizing SESs. We identified 29 key indicators that allowed us to map 15 SES archetypes encompassing natural, mosaic, agricultural, and urban systems, which uncovered contrasting land sharing and land sparing patterns throughout the territory. We found synergies but also disagreements between empirical and expert knowledge on the relevance of variables: agreement on their widespread relevance (32.7% of the variables, e.g. crop and livestock prod... Presentar Todo |
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Palabras claves : |
Coupled human and natural systems; Essential social-ecological system variables; Human-environment interactions; LONG-TERM SOCIAL-ECOLOGICAL RESEARCH; LTSER; Random forest; SOCIAL-ECOLOGICAL SYSTEM FRAMEWORK. |
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Asunto categoría : |
A50 Investigación agraria |
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URL : |
https://iopscience.iop.org/article/10.1088/1748-9326/ac5ded/pdf
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Marc : |
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024 7 $a10.1088/1748-9326/ac5ded$2DOI
100 1 $aPACHECO-ROMERO, M.
245 $aA data-driven methodological routine to identify key indicators for social-ecological system archetype mapping.$h[electronic resource]
260 $c2022
500 $aArticle history: Received 2 July 2021; Revised 28 January 2022; Accepted for publication 15 March 2022; Published 30 March 2022. License: Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. -- Article: Gold Open Access, Green Open Access. Corresponding author: Pacheco-Romero, M.; Andalusian Center for the Assessment and Monitoring of Global Change (CAESCG), University of Almería, Almería, Spain; email:manuel.pacheco@ual.es -- Funding text - We thank R Romero-Calcerrada and J M Requena-Mullor for helpful discussions, and three anonymous reviewers for their constructive suggestions to improve this paper. We also thank the Spanish Ministry of Economy and Business (Project CGL2014-61610-EXP) for the financial support, as well as the Spanish Ministry of Education for the FPU Predoctoral Fellowship of MPR (FPU14/06782) and MTTG (16/02214). MPR gratefully acknowledges funding from Universidad de Almería for a research stay at the Laboratory of Regional Analysis and Remote Sensing (LART) of University of Buenos Aires to develop this study. This research was done within the LTSER Platforms of the Arid Iberian South East—Spain (LTER_EU_ES_027) and Sierra Nevada/Granada (ES- SNE)—Spain (LTER_EU_ES_010), and contributes to the Global Land Programme.
520 $aABSTRACT.- The spatial mapping of social-ecological system (SES) archetypes constitutes a fundamental tool to operationalize the SES concept in empirical research. Approaches to detect, map, and characterize SES archetypes have evolved over the last decade towards more integrative and comparable perspectives guided by SES conceptual frameworks and reference lists of variables. However, hardly any studies have investigated how to empirically identify the most relevant set of indicators to map the diversity of SESs. In this study, we propose a data-driven methodological routine based on multivariate statistical analysis to identify the most relevant indicators for mapping and characterizing SES archetypes in a particular region. Taking Andalusia (Spain) as a case study, we applied this methodological routine to 86 indicators representing multiple variables and dimensions of the SES. Additionally, we assessed how the empirical relevance of these indicators contributes to previous expert and empirical knowledge on key variables for characterizing SESs. We identified 29 key indicators that allowed us to map 15 SES archetypes encompassing natural, mosaic, agricultural, and urban systems, which uncovered contrasting land sharing and land sparing patterns throughout the territory. We found synergies but also disagreements between empirical and expert knowledge on the relevance of variables: agreement on their widespread relevance (32.7% of the variables, e.g. crop and livestock production, net primary productivity, population density); relevance conditioned by the context or the scale (16.3%, e.g. land protection, educational level); lack of agreement (20.4%, e.g. economic level, land tenure); need of further assessments due to the lack of expert or empirical knowledge (30.6%). Overall, our data-driven approach can contribute to more objective selection of relevant indicators for SES mapping, which may help to produce comparable and generalizable empirical knowledge on key variables for characterizing SESs, as well as to derive more representative descriptions and causal factor configurations in SES archetype analysis. © 2022 The Author(s). Published by IOP Publishing Ltd.
653 $aCoupled human and natural systems
653 $aEssential social-ecological system variables
653 $aHuman-environment interactions
653 $aLONG-TERM SOCIAL-ECOLOGICAL RESEARCH
653 $aLTSER
653 $aRandom forest
653 $aSOCIAL-ECOLOGICAL SYSTEM FRAMEWORK
700 1 $aVALLEJOS, M.
700 1 $aPARUELO, J.
700 1 $aALCARAZ-SEGURA, D.
700 1 $aTORRES-GARCÍA, M. T.
700 1 $aSALINAS-BONILLO, M. J.
700 1 $aCABELLO, JAVIER
773 $tEnvironmental Research Letters, 2022, Volume 17, Issue 4, Article number 045019. OPEN ACCESS. doi: https://doi.org/10.1088/1748-9326/ac5ded
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