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Top 10+1 indicators for assessing forest ecosystem conditions: A five-decade fragmentation analysis

2024Artigo científico Acesso aberto
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dc.contributor.authorAlmeida, Bruna
dc.contributor.authorCabral, Pedro
dc.contributor.authorFonseca, Catarina
dc.contributor.authorGil, Artur
dc.contributor.authorScemama, Pierre
dc.date.accessioned2024-11-27T14:34:11Z
dc.date.available2024-11-27T14:34:11Z
dc.date.issued2024
dc.description.abstractGlobally, land use change has consistently resulted in greater losses than gains in aboveground biomass (AGB). Forest fragmentation is a primary driver of biodiversity loss and the depletion of natural capital. Measuring landscape characteristics and analyzing changes in forest landscape patterns are essential for accounting for the contributions of forest ecosystems to the economy and human well-being. This study predicts national forest distribution for 2036 and 2054 using a Cellular Automata (CA) system and assesses ecosystem conditions through landscape metrics at the patch, class, and landscape levels. We calculated 130 metrics and applied a Variance Threshold method to remove features with low variance, testing different thresholds. The first filtered-out metrics were further analysed through Principal Component Analysis combined with a Feature Importance technique to select and rank the top 10 indicators: effective mesh size, splitting index, mean radius of gyration, largest patch index, mean core area, core area percentage, Simpson's evenness index, mutual information, Simpson's diversity index, and mean contiguity index. The eleventh selected indicator is the AGB density, a structural measurement for ecosystem condition and a proxy for forest carbon storage and sequestration assessments. From 2000 to 2018, the national AGB forest carbon stock decreased from 131.5 to 91.3 Megatons (Mt) with expected values for 2036 and 2054 being 71.8 and 55.3 Mt., respectively. Landscape measurements quantitatively describe forest dynamics, providing insights into the structure, configuration, and changes characterizing landscape evolution. This research underscores the capability of CA models to map large-scale forest resources and predict future development scenarios, offering useful information for conservation and environmental management decisions. Additionally, it provides measurements to support Ecosystem Accounting by assessing forest extent and indicators of its conditions.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAlmeida, B., Cabral, P., Fonseca, C., Gil, A., & Scemama, P. (2024). Top 10+1 indicators for assessing forest ecosystem conditions: A five-decade fragmentation analysis. "Science of the Total Environment", 957, 177527. DOI:10.1016/j.scitotenv.2024.177527pt_PT
dc.identifier.doi10.1016/j.scitotenv.2024.177527pt_PT
dc.identifier.eissn1879-1026
dc.identifier.issn0048-9697
dc.identifier.urihttp://hdl.handle.net/10400.3/7193
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0048969724076848?via%3Dihubpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/pt_PT
dc.subjectForestrypt_PT
dc.subjectEcological Applicationspt_PT
dc.subjectEnvironmental Conservationpt_PT
dc.subjectCorine Land use Land Coverpt_PT
dc.subjectCarbon Storage and Sequestrationpt_PT
dc.subjectGIS Modellingpt_PT
dc.titleTop 10+1 indicators for assessing forest ecosystem conditions: A five-decade fragmentation analysispt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceNetherlandspt_PT
oaire.citation.endPage14pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleScience of The Total Environmentpt_PT
oaire.citation.volume957pt_PT
person.familyNamealmeida
person.familyNameCabral
person.familyNameFonseca
person.familyNameScemama
person.givenNamebruna
person.givenNamePedro
person.givenNameCatarina
person.givenNamePierre
person.identifierB-2616-2010
person.identifier.ciencia-idC314-19F4-4DCC
person.identifier.ciencia-idBB12-BCEF-6CA6
person.identifier.orcid0000-0001-7431-5468
person.identifier.orcid0000-0001-8622-6008
person.identifier.orcid0000-0002-5864-4592
person.identifier.orcid0000-0003-3798-4130
person.identifier.scopus-author-id56221630400
person.identifier.scopus-author-id57197686932
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication2085a536-19bf-4bb9-8bb2-58e6b55de34b
relation.isAuthorOfPublication5f5b6ee6-a5c9-4e56-9583-5f1f64041b96
relation.isAuthorOfPublication18322175-532f-4079-aa09-c66c6a9ab23f
relation.isAuthorOfPublication57b6e6f8-dac6-4ca4-8930-e925c5ea2c26
relation.isAuthorOfPublication.latestForDiscovery57b6e6f8-dac6-4ca4-8930-e925c5ea2c26

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