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How will climate change impact maritime pine forest distribution and productivity in Portugal

2023Conference paper Open access
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dc.contributor.authorAlegria, Cristina Maria
dc.contributor.authorAlmeida, Alice M.
dc.contributor.authorRibeiro, Maria Margarida
dc.contributor.authorMartins Roque, Natália
dc.contributor.authorFernandez, Paulo
dc.contributor.authorGerassis, Saki
dc.contributor.authorAlbuquerque, Maria Teresa
dc.date.accessioned2025-04-07T15:43:27Z
dc.date.available2025-04-07T15:43:27Z
dc.date.issued2023
dc.descriptionDisponível o resumo e os diapositivos que acompanharam a apresentação oral. Estes têm o título What wiil be the impact of climate chan ge on maritime pine forest disptribution and productivity in Portugal?
dc.description.abstractPortuguese maritime pine forests are severely affected by forest fires. The study aimed at modelling: (1) species’ current distribution and productivity; and (2) species’ distribution for projected future climate change scenarios. The land cover, national forest inventory, and environmental data were used. A Bayesian Machine Learning (ML) analysis allowed exploring the most influential environmental variables. Species’ spatial productivity was modelled by stochastic Sequential Gaussian Simulation. Species’ potential distribution modelling was performed using two methodological approaches: (1) ML algorithms (Random Forest and Maximum Entropy); and (2) GIS map algebra (ecological envelopes) maps regarding a set of environmental variables and previously known thresholds. Results showed that species distribution was mainly determined by precipitation-related variables, but elevation and temperature related variables were important to differentiate species productivity. Species’ distribution for the present using ML modelling provided fitting efficiencies around 70% and matched well the species’ current distribution. The species ecological envelope map for the present was closer to the species’ empiric potential distribution. Climate change impacts on species’ future distributions by the ML approach were moderate with areas being relocated (47.3% regular-medium-high suitability area to 48.7%–48.3% in the future). The impacts in species’ ecological envelopes maps were higher and with greater future losses than the latter (76.5% regular-favourable-optimum suitability area to 58.2%–51.6% in the future). The two approaches showed a 44% concordance in the present, decreasing to 30%–35% in the future. These maps are key to support recommendations to set species' best suitability areas in planning future afforestation to attain fire-resilient landscapes, enhanced forest ecosystems biodiversity, functionality, and productivity under climate change scenarios.eng
dc.identifier.citationALEGRIA, Cristina [et al.] (2023) - How will climate change impact maritime pine forest distribution and productivity in Portugal. In IUFRO Forest Environment, DIV 8 Conference, Évora, 2023 - Book of abstracts. P. 83.
dc.identifier.urihttp://hdl.handle.net/10400.11/10111
dc.language.isoeng
dc.peerreviewedyes
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectMaritime pine
dc.subjectPortugal
dc.subjectForest management
dc.titleHow will climate change impact maritime pine forest distribution and productivity in Portugaleng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2023
oaire.citation.conferencePlaceÉvora
oaire.citation.endPage83
oaire.citation.startPage83
oaire.citation.titleIUFRO Forest Environment, DIV 8 Conference
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameAlegria
person.familyNameRibeiro
person.familyNameMartins Roque
person.familyNameFernandez
person.familyNameAlbuquerque
person.givenNameCristina Maria
person.givenNameMaria Margarida
person.givenNameNatália
person.givenNamePaulo
person.givenNameMaria Teresa
person.identifieruser=YnBEv3oAAAAJ&hl=en
person.identifierNatália Martins Roque
person.identifier.ciencia-id9311-1EE5-AB03
person.identifier.ciencia-id451A-332D-0798
person.identifier.ciencia-id9E1E-1C0B-0DCB
person.identifier.ciencia-id5A1C-8956-4C0A
person.identifier.orcid0000-0002-6906-6660
person.identifier.orcid0000-0003-0107-889X
person.identifier.orcid0000-0001-8859-4365
person.identifier.orcid0000-0001-7252-8320
person.identifier.orcid0000-0002-8782-6133
person.identifier.ridB-1536-2013
person.identifier.scopus-author-id36952993700
person.identifier.scopus-author-id57200227653
person.identifier.scopus-author-id56675313500
person.identifier.scopus-author-id55507421600
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