A distributional analysis of the socio-ecological and economic determinants of forest carbon stocks

Forest carbon (C) sequestration is being actively considered by several states as a way to cost-effectively comply with the forthcoming United States (US) Environmental Protection Agency's rule that will reduce power plant C emissions by 32% of 2005 levels by 2030. However, little is known abou...

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Autores:
Tipo de recurso:
Fecha de publicación:
2016
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/23953
Acceso en línea:
https://doi.org/10.1016/j.envsci.2016.02.015
https://repository.urosario.edu.co/handle/10336/23953
Palabra clave:
Carbon
Article
Carbon sequestration
Ecosystem
Electric power plant
Environmental protection
Forest
Forest management
Landscape
Linear regression analysis
Multiple linear regression analysis
Priority journal
Statistics
United states
Carbon sequestration
Distributional impacts
Ecosystem services
Forest inventory and analysis
Quantile regression
Rights
License
Abierto (Texto Completo)
id EDOCUR2_5921812b792aa3d73911ceda1657ca35
oai_identifier_str oai:repository.urosario.edu.co:10336/23953
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repository_id_str
spelling 26df483b-680b-416a-a43c-90faacb1ead9-12d7c8bf2-67a1-46d2-a8e0-b82768ad86d9-165878e80-826f-4f78-9afd-6a08a68c8b69-19365b3f2-28ac-4ae4-b0b7-2571e0fc581f-12020-05-26T00:07:01Z2020-05-26T00:07:01Z2016Forest carbon (C) sequestration is being actively considered by several states as a way to cost-effectively comply with the forthcoming United States (US) Environmental Protection Agency's rule that will reduce power plant C emissions by 32% of 2005 levels by 2030. However, little is known about the socio-ecological and distributional effects of such a policy. Given that C is heterogeneous across the landscape, understanding how social, economic, and ecological changes affect forest C stocks and sequestration is key for developing forest management policies that offset C emissions. Using Florida US as a case study, we use US National Forest Inventory Analysis and Census Bureau data in both linear regression and quantile regression analyses to examine the socio-ecological and economic determinants of forest C stocks and its relationship with differing communities. Quantile regression findings demonstrate nonlinearity in the effects of key determinants, which highlight the limitations of regularly used mean-based regression analyses. We also found that forest basal area, site quality, stand size, and stand age are significant ecological predictors of carbon stocks, with a positive and increasing effect on upper quantiles where C stocks are greater. The effect of education was generally positive and mostly significant at upper quantiles, while the effects of income and locations with predominantly minority residents (as compared to whites) were negative. Upper quantiles were also affected by population age. Our findings underscore the importance of considering the broader socio-ecological and economic implications of compliance strategies that target the management of forests for carbon sequestration and other ecosystem services. © 2016 Elsevier Ltd.application/pdfhttps://doi.org/10.1016/j.envsci.2016.02.01514629011https://repository.urosario.edu.co/handle/10336/23953engElsevier Ltd3728Environmental Science and PolicyVol. 60Environmental Science and Policy, ISSN:14629011, Vol.60,(2016); pp. 28-37https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960887698&doi=10.1016%2fj.envsci.2016.02.015&partnerID=40&md5=ab61869d750d536ebe73d51f4fee7725Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURCarbonArticleCarbon sequestrationEcosystemElectric power plantEnvironmental protectionForestForest managementLandscapeLinear regression analysisMultiple linear regression analysisPriority journalStatisticsUnited statesCarbon sequestrationDistributional impactsEcosystem servicesForest inventory and analysisQuantile regressionA distributional analysis of the socio-ecological and economic determinants of forest carbon stocksarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Soto, José R.Escobedo, Francisco J.Adams, Damian C.Blanco, German10336/23953oai:repository.urosario.edu.co:10336/239532022-05-02 07:37:21.309493https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv A distributional analysis of the socio-ecological and economic determinants of forest carbon stocks
title A distributional analysis of the socio-ecological and economic determinants of forest carbon stocks
spellingShingle A distributional analysis of the socio-ecological and economic determinants of forest carbon stocks
Carbon
Article
Carbon sequestration
Ecosystem
Electric power plant
Environmental protection
Forest
Forest management
Landscape
Linear regression analysis
Multiple linear regression analysis
Priority journal
Statistics
United states
Carbon sequestration
Distributional impacts
Ecosystem services
Forest inventory and analysis
Quantile regression
title_short A distributional analysis of the socio-ecological and economic determinants of forest carbon stocks
title_full A distributional analysis of the socio-ecological and economic determinants of forest carbon stocks
title_fullStr A distributional analysis of the socio-ecological and economic determinants of forest carbon stocks
title_full_unstemmed A distributional analysis of the socio-ecological and economic determinants of forest carbon stocks
title_sort A distributional analysis of the socio-ecological and economic determinants of forest carbon stocks
dc.subject.keyword.spa.fl_str_mv Carbon
Article
Carbon sequestration
Ecosystem
Electric power plant
Environmental protection
Forest
Forest management
Landscape
Linear regression analysis
Multiple linear regression analysis
Priority journal
Statistics
United states
Carbon sequestration
Distributional impacts
Ecosystem services
Forest inventory and analysis
Quantile regression
topic Carbon
Article
Carbon sequestration
Ecosystem
Electric power plant
Environmental protection
Forest
Forest management
Landscape
Linear regression analysis
Multiple linear regression analysis
Priority journal
Statistics
United states
Carbon sequestration
Distributional impacts
Ecosystem services
Forest inventory and analysis
Quantile regression
description Forest carbon (C) sequestration is being actively considered by several states as a way to cost-effectively comply with the forthcoming United States (US) Environmental Protection Agency's rule that will reduce power plant C emissions by 32% of 2005 levels by 2030. However, little is known about the socio-ecological and distributional effects of such a policy. Given that C is heterogeneous across the landscape, understanding how social, economic, and ecological changes affect forest C stocks and sequestration is key for developing forest management policies that offset C emissions. Using Florida US as a case study, we use US National Forest Inventory Analysis and Census Bureau data in both linear regression and quantile regression analyses to examine the socio-ecological and economic determinants of forest C stocks and its relationship with differing communities. Quantile regression findings demonstrate nonlinearity in the effects of key determinants, which highlight the limitations of regularly used mean-based regression analyses. We also found that forest basal area, site quality, stand size, and stand age are significant ecological predictors of carbon stocks, with a positive and increasing effect on upper quantiles where C stocks are greater. The effect of education was generally positive and mostly significant at upper quantiles, while the effects of income and locations with predominantly minority residents (as compared to whites) were negative. Upper quantiles were also affected by population age. Our findings underscore the importance of considering the broader socio-ecological and economic implications of compliance strategies that target the management of forests for carbon sequestration and other ecosystem services. © 2016 Elsevier Ltd.
publishDate 2016
dc.date.created.spa.fl_str_mv 2016
dc.date.accessioned.none.fl_str_mv 2020-05-26T00:07:01Z
dc.date.available.none.fl_str_mv 2020-05-26T00:07:01Z
dc.type.eng.fl_str_mv article
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.spa.spa.fl_str_mv Artículo
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1016/j.envsci.2016.02.015
dc.identifier.issn.none.fl_str_mv 14629011
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/23953
url https://doi.org/10.1016/j.envsci.2016.02.015
https://repository.urosario.edu.co/handle/10336/23953
identifier_str_mv 14629011
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 37
dc.relation.citationStartPage.none.fl_str_mv 28
dc.relation.citationTitle.none.fl_str_mv Environmental Science and Policy
dc.relation.citationVolume.none.fl_str_mv Vol. 60
dc.relation.ispartof.spa.fl_str_mv Environmental Science and Policy, ISSN:14629011, Vol.60,(2016); pp. 28-37
dc.relation.uri.spa.fl_str_mv https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960887698&doi=10.1016%2fj.envsci.2016.02.015&partnerID=40&md5=ab61869d750d536ebe73d51f4fee7725
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
rights_invalid_str_mv Abierto (Texto Completo)
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Elsevier Ltd
institution Universidad del Rosario
dc.source.instname.spa.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.spa.fl_str_mv reponame:Repositorio Institucional EdocUR
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
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