Identifying and explaining the farming system composition of agricultural landscapes: The role of socioeconomic drivers under strong biophysical gradients

Detalhes bibliográficos
Autor(a) principal: Silva, J.F.
Data de Publicação: 2020
Outros Autores: Santos, J.L., Ribeiro, P.F., Canadas, M.J., Novais, A., Lomba, A., Magalhães, M.R., Moreira, F.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.5/22059
Resumo: In mountain landscapes, agricultural abandonment is taking place in the most vulnerable areas, while intensification increases in the most productive lands. These contrasting processes, which have different impacts on biodiversity and ecosystem services (BES), are related to changes in the farming system component of these landscapes. Farming systems are identified based on farmer’s decisions on, for example, type of crop and level of fertilizers, which represent the descriptors of farming systems and can be grouped into several dimensions (e.g. land use and intensity). Since obtaining this data at farm-level is often difficult, an alternative is to study the spatial combinations of farming systems at parish-level, i.e., Farming System Mixes (FSM), relying on agricultural census data. Other biophysical (e.g. climate, soil) and socioeconomic (e.g. labour, farmer’s age) variables, independent of farmers' decisions, represent the exogenous drivers of these decisions. The separation between descriptors and drivers is important to improve knowledge about what drives farmers' decisions regarding farming system choice, as these choices are often the focus of policies aiming the support of BES. In this study, we explored the underlying drivers of FSM and assessed the role of socioeconomic drivers, main target for policy makers, in a context of strong biophysical gradients. Biophysical drivers emerge as those that primarily discriminate between the FSM located in different topographic positions (valleys, mountains and plateau). In the situations where there is a greater range of productive choices available for farmers, such as in valleys, socioeconomic drivers assume a preponderant role on farming system choice
id RCAP_8ff2fb6b51e242b7d31c2464bd80fced
oai_identifier_str oai:www.repository.utl.pt:10400.5/22059
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Identifying and explaining the farming system composition of agricultural landscapes: The role of socioeconomic drivers under strong biophysical gradientsagricultural landscapessocioeconomic driversfarming systemsIn mountain landscapes, agricultural abandonment is taking place in the most vulnerable areas, while intensification increases in the most productive lands. These contrasting processes, which have different impacts on biodiversity and ecosystem services (BES), are related to changes in the farming system component of these landscapes. Farming systems are identified based on farmer’s decisions on, for example, type of crop and level of fertilizers, which represent the descriptors of farming systems and can be grouped into several dimensions (e.g. land use and intensity). Since obtaining this data at farm-level is often difficult, an alternative is to study the spatial combinations of farming systems at parish-level, i.e., Farming System Mixes (FSM), relying on agricultural census data. Other biophysical (e.g. climate, soil) and socioeconomic (e.g. labour, farmer’s age) variables, independent of farmers' decisions, represent the exogenous drivers of these decisions. The separation between descriptors and drivers is important to improve knowledge about what drives farmers' decisions regarding farming system choice, as these choices are often the focus of policies aiming the support of BES. In this study, we explored the underlying drivers of FSM and assessed the role of socioeconomic drivers, main target for policy makers, in a context of strong biophysical gradients. Biophysical drivers emerge as those that primarily discriminate between the FSM located in different topographic positions (valleys, mountains and plateau). In the situations where there is a greater range of productive choices available for farmers, such as in valleys, socioeconomic drivers assume a preponderant role on farming system choiceElsevierRepositório da Universidade de LisboaSilva, J.F.Santos, J.L.Ribeiro, P.F.Canadas, M.J.Novais, A.Lomba, A.Magalhães, M.R.Moreira, F.2021-09-28T09:42:25Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/22059engLandscape and Urban Planning 202 (2020) 103879https://doi.org/10.1016/j.landurbplan.2020.103879info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-10-01T01:30:44Zoai:www.repository.utl.pt:10400.5/22059Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:06:34.107309Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Identifying and explaining the farming system composition of agricultural landscapes: The role of socioeconomic drivers under strong biophysical gradients
title Identifying and explaining the farming system composition of agricultural landscapes: The role of socioeconomic drivers under strong biophysical gradients
spellingShingle Identifying and explaining the farming system composition of agricultural landscapes: The role of socioeconomic drivers under strong biophysical gradients
Silva, J.F.
agricultural landscapes
socioeconomic drivers
farming systems
title_short Identifying and explaining the farming system composition of agricultural landscapes: The role of socioeconomic drivers under strong biophysical gradients
title_full Identifying and explaining the farming system composition of agricultural landscapes: The role of socioeconomic drivers under strong biophysical gradients
title_fullStr Identifying and explaining the farming system composition of agricultural landscapes: The role of socioeconomic drivers under strong biophysical gradients
title_full_unstemmed Identifying and explaining the farming system composition of agricultural landscapes: The role of socioeconomic drivers under strong biophysical gradients
title_sort Identifying and explaining the farming system composition of agricultural landscapes: The role of socioeconomic drivers under strong biophysical gradients
author Silva, J.F.
author_facet Silva, J.F.
Santos, J.L.
Ribeiro, P.F.
Canadas, M.J.
Novais, A.
Lomba, A.
Magalhães, M.R.
Moreira, F.
author_role author
author2 Santos, J.L.
Ribeiro, P.F.
Canadas, M.J.
Novais, A.
Lomba, A.
Magalhães, M.R.
Moreira, F.
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Silva, J.F.
Santos, J.L.
Ribeiro, P.F.
Canadas, M.J.
Novais, A.
Lomba, A.
Magalhães, M.R.
Moreira, F.
dc.subject.por.fl_str_mv agricultural landscapes
socioeconomic drivers
farming systems
topic agricultural landscapes
socioeconomic drivers
farming systems
description In mountain landscapes, agricultural abandonment is taking place in the most vulnerable areas, while intensification increases in the most productive lands. These contrasting processes, which have different impacts on biodiversity and ecosystem services (BES), are related to changes in the farming system component of these landscapes. Farming systems are identified based on farmer’s decisions on, for example, type of crop and level of fertilizers, which represent the descriptors of farming systems and can be grouped into several dimensions (e.g. land use and intensity). Since obtaining this data at farm-level is often difficult, an alternative is to study the spatial combinations of farming systems at parish-level, i.e., Farming System Mixes (FSM), relying on agricultural census data. Other biophysical (e.g. climate, soil) and socioeconomic (e.g. labour, farmer’s age) variables, independent of farmers' decisions, represent the exogenous drivers of these decisions. The separation between descriptors and drivers is important to improve knowledge about what drives farmers' decisions regarding farming system choice, as these choices are often the focus of policies aiming the support of BES. In this study, we explored the underlying drivers of FSM and assessed the role of socioeconomic drivers, main target for policy makers, in a context of strong biophysical gradients. Biophysical drivers emerge as those that primarily discriminate between the FSM located in different topographic positions (valleys, mountains and plateau). In the situations where there is a greater range of productive choices available for farmers, such as in valleys, socioeconomic drivers assume a preponderant role on farming system choice
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-01-01T00:00:00Z
2021-09-28T09:42:25Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/22059
url http://hdl.handle.net/10400.5/22059
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Landscape and Urban Planning 202 (2020) 103879
https://doi.org/10.1016/j.landurbplan.2020.103879
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799131158587375616