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Carbon storage patterns and landscape sustainability in northeast portugal: a digital mapping approach

2023Artigo científico Acesso aberto
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dc.contributor.authorPatrício, Matheus Bueno
dc.contributor.authorLado, Marcos
dc.contributor.authorFigueiredo, Tomás de
dc.contributor.authorAzevedo, João
dc.contributor.authorBueno, Paulo
dc.contributor.authorFonseca, Felícia
dc.date.accessioned2024-01-24T13:53:57Z
dc.date.available2024-01-24T13:53:57Z
dc.date.issued2023
dc.description.abstractThis study investigated the impact of regional land abandonment in northeast Portugal. It specifically focused on carbon sequestration opportunities in the Upper Sabor RiverWatershed, situated in the northeast of Portugal, amidst agricultural land abandonment. The study involved mapping the distribution of soil organic carbon (SOC) across four soil layers (0–5 cm, 5–10 cm, 10–20 cm, and 20–30 cm) at 120 sampling points. The quantification of SOC storage (measured in Mg C ha−1) allowed for an analysis of its relationship with various landscape characteristics, including elevation, land use and land cover (LULC), normalized difference vegetation index (NDVI), modified soil-adjusted vegetation index (MSAVI), topographic wetness index (TWI), and erosion risk (ER). Six statistical tests were employed, including multivariate approaches like Cubist and Random Forest, within different scenarios to assess carbon distribution within the watershed’s soils. These modeling results were then utilized to propose strategies aimed at enhancing soil carbon storage. Notably, a significant discrepancy was observed in the carbon content between areas at higher elevations (>1000 m) and those at lower elevations (<800 m). Additionally, the study found that the amount of carbon stored in agricultural soils was often significantly lower than in other land use categories, including forests, mountain herbaceous vegetation, pasture, and shrub communities. Analyzing bi- and multivariate scenarios, it was determined that the scenario with the greatest number of independent variables (set 6) yielded the lowest RMSE (root mean squared error), serving as a key indicator for evaluating predicted values against observed values. However, it is important to note that the independent variables used in set 4 (elevation, LULC, and NDVI) had reasonably similar values. Ultimately, the spatialization of the model from scenario 6 provided actionable insights for soil carbon conservation and enhancement across three distinct elevation levels.pt_PT
dc.description.sponsorshipThis research received financial support from the European Regional Development Fund (ERDF) through the Operational Programme for Competitiveness Factors (COMPETE) and fromnational funds through FCT (Foundation for Science and Technology) (PTDC/AAG-MAA/4539/2012/FCOMP01-0124-FEDER-02786), and from national funds FCT/MCTES (PIDDAC) through CIMO (UIDB/00690/ 2020 and UIDP/00690/2020) and SusTEC (LA/P/0007/2020).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationPatrício, Matheus Bueno; Lado, Marcos; Figueiredo, Tomás de; Azevedo, João; Bueno, Paulo; Fonseca, Felícia (2023). Carbon storage patterns and landscape sustainability in northeast portugal: a digital mapping approach. Sustainability. eISSN 2071-1050. 15:24, p. 1-25pt_PT
dc.identifier.doi10.3390/su152416853pt_PT
dc.identifier.eissn2071-1050
dc.identifier.urihttp://hdl.handle.net/10198/29355
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationMountain Research Center
dc.relationMountain Research Center
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectTerrain featurespt_PT
dc.subjectRegression analysispt_PT
dc.subjectLand use planningpt_PT
dc.subjectLand use and land coverpt_PT
dc.subjectElevationpt_PT
dc.titleCarbon storage patterns and landscape sustainability in northeast portugal: a digital mapping approachpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleMountain Research Center
oaire.awardTitleMountain Research Center
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00690%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00690%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.citation.endPage25pt_PT
oaire.citation.issue24pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleSustainabilitypt_PT
oaire.citation.volume15pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameFigueiredo
person.familyNameAzevedo
person.familyNameFonseca
person.givenNameTomás d'Aquino
person.givenNameJoão C.
person.givenNameFelícia
person.identifier1297327
person.identifier.ciencia-id961D-607D-51CC
person.identifier.ciencia-id3F1F-0829-5878
person.identifier.orcid0000-0001-7690-8996
person.identifier.orcid0000-0002-3061-8261
person.identifier.orcid0000-0001-7727-071X
person.identifier.scopus-author-id54790554500
person.identifier.scopus-author-id36970960500
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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