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

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dc.creatorSoto, José R.spa
dc.creatorEscobedo, Francisco J.spa
dc.creatorAdams, Damian C.spa
dc.creatorBlanco, Germanspa
dc.date.accessioned2020-05-26T00:07:01Z
dc.date.available2020-05-26T00:07:01Z
dc.date.created2016spa
dc.description.abstractForest 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.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1016/j.envsci.2016.02.015
dc.identifier.issn14629011
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/23953
dc.language.isoengspa
dc.publisherElsevier Ltdspa
dc.relation.citationEndPage37
dc.relation.citationStartPage28
dc.relation.citationTitleEnvironmental Science and Policy
dc.relation.citationVolumeVol. 60
dc.relation.ispartofEnvironmental Science and Policy, ISSN:14629011, Vol.60,(2016); pp. 28-37spa
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84960887698&doi=10.1016%2fj.envsci.2016.02.015&partnerID=40&md5=ab61869d750d536ebe73d51f4fee7725spa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)spa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocURspa
dc.subject.keywordCarbonspa
dc.subject.keywordArticlespa
dc.subject.keywordCarbon sequestrationspa
dc.subject.keywordEcosystemspa
dc.subject.keywordElectric power plantspa
dc.subject.keywordEnvironmental protectionspa
dc.subject.keywordForestspa
dc.subject.keywordForest managementspa
dc.subject.keywordLandscapespa
dc.subject.keywordLinear regression analysisspa
dc.subject.keywordMultiple linear regression analysisspa
dc.subject.keywordPriority journalspa
dc.subject.keywordStatisticsspa
dc.subject.keywordUnited statesspa
dc.subject.keywordCarbon sequestrationspa
dc.subject.keywordDistributional impactsspa
dc.subject.keywordEcosystem servicesspa
dc.subject.keywordForest inventory and analysisspa
dc.subject.keywordQuantile regressionspa
dc.titleA distributional analysis of the socio-ecological and economic determinants of forest carbon stocksspa
dc.typearticleeng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaArtículospa
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