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Solving multi-objective problems for multifunctional and sustainable management in maritime pine forest landscapes

2018Journal article Open access
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dc.contributor.authorPérez-Rodríguez, Fernando
dc.contributor.authorNunes, Luís
dc.contributor.authorAzevedo, João
dc.date.accessioned2019-02-01T12:19:45Z
dc.date.available2019-02-01T12:19:45Z
dc.date.issued2018
dc.description.abstractForest management based on sustainability and multifunctionality requires reliable and user-friendly tools to address several objectives simultaneously. In this work we present FlorNExT Pro®, a multiple-criteria landscape-scale forest planning and management computer tool, and apply it in a region in the north of Portugal to find optimized management solutions according to objectives such as maximization of net present value (NPV), volume growth, and carbon storage, and minimization of losses due to fire. Comparisons made among single- and multi-objective solutions were made to explore the range of possible indicators provided by the tool such as carbon sequestered, volume growth, probability of fire occurrence, volume of wood extracted, and evenness of harvesting in the management period. Results show that FlorNExT Pro® is a reliable, flexible, and useful tool to incorporate multiple criteria and objectives into spatially explicit complex management problems and to prepare sustainable and multifunctional forest management plans at the landscape level. FlorNExT Pro® is also suited to guiding and adapting forest management for uncertainty scenarios for the assessment of ecosystem services and fire risk, therefore playing an important role in the maintenance of sustainable landscapes in the south of Europe.pt_PT
dc.description.sponsorshipThis research was funded through the EU 7th Framework Programme for Research, Technological Development, and Demonstration (agreement no 613762: SIMWOOD—Sustainable Innovative Mobilisation of Wood). The authors wish to thank to Arborea—Associação Agro-Florestal e Ambiental da Terra Fria Transmontana for their collaboration in the development of this and other tools to promote sustainable forestry in the Nordeste region in Portugal. The authors acknowledge also the valuable contributions made by two reviewers and the editor of the special issue.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationPérez-Rodríguez, Fernando; Nunes, Luís; Azevedo, João (2018). Solving multi-objective problems for multifunctional and sustainable management in maritime pine forest landscapes. Climate. ISSN 2225-1154. 6:4. p. 1-20pt_PT
dc.identifier.doi10.3390/cli6040081pt_PT
dc.identifier.issn2225-1154
dc.identifier.urihttp://hdl.handle.net/10198/18621
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationSustainable Innovative Mobilisation of Wood
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectOperational researchpt_PT
dc.subjectOptimizationpt_PT
dc.subjectCarbon sequestrationpt_PT
dc.subjectSpatially explicit forest management planningpt_PT
dc.subjectDecision support systemspt_PT
dc.subjectPortugalpt_PT
dc.titleSolving multi-objective problems for multifunctional and sustainable management in maritime pine forest landscapespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleSustainable Innovative Mobilisation of Wood
oaire.awardURIinfo:eu-repo/grantAgreement/EC/FP7/613762/EU
oaire.citation.issue4pt_PT
oaire.citation.startPage81pt_PT
oaire.citation.titleClimatept_PT
oaire.citation.volume6pt_PT
oaire.fundingStreamFP7
person.familyNameNunes
person.familyNameAzevedo
person.givenNameLuís
person.givenNameJoão C.
person.identifier.ciencia-id3F1F-0829-5878
person.identifier.orcid0000-0002-8913-785X
person.identifier.orcid0000-0002-3061-8261
person.identifier.scopus-author-id35222136600
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.nameEuropean Commission
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublicatione15b0e75-689e-4be0-942c-1958cfefdb0f
relation.isAuthorOfPublication.latestForDiscoverye15b0e75-689e-4be0-942c-1958cfefdb0f
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