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A new index to assess the state of dune vegetation derived from true colour images

dc.contributor.authorTalavera, Lara
dc.contributor.authorCostas, Susana
dc.contributor.authorFerreira, Oscar
dc.date.accessioned2022-09-13T15:41:51Z
dc.date.available2022-09-13T15:41:51Z
dc.date.issued2022
dc.description.abstractVegetation on coastal dunes is a key element, as it promotes the growth and stabilization of these landforms while contributing significantly to biodiversity. Physical (e.g. impact of storms), ecological (e.g. animal grazing) and human-related (e.g. farming and recreation) factors may disturb coastal dune vegetation, changing dune dynamics and eventually inducing ecogeomorphic state shifts. Therefore, understanding vegetation dynamics and state turns crucial to predict dune evolution paths. The latter must be supported by observations combined with the development of tools (e.g. indexes) able to detect eventual changes and to automatically categorize the state of the vegetation. Here, a multi-step index to characterise the dune vegetation state (DUVES) was developed and tested in Barreta Island (South Portugal), where grey dune vegetation has declined in recent years. The index was computed using classified true colour orthophotos and orthomosaics derived from UAS (Unmanned Aerial Systems) surveys. Google Earth images were used as complementary data to analyse the evolution trends. The possible sources of disturbance (i.e. human-related activities and gull occupation) were also investigated by comparing their distribution with the vegetation changes. DUVES successfully identified different states of vegetation cover that expressed its stability, perturbation or growth based on temporal changes and allowed the analysis of their evolutionary trends. The distribution of perturbation was mostly associated with gull nesting areas, increasing over time, and to a less extent to human-related activities. The observed grey dune habitat loss was due to replacement of plants typical from this habitat by ruderal species promoted by the positive feedback established between gulls and vegetation. The developed index proved to be of great utility to define dune habitat evolution and understand the associated drivers, being a tool with a wide range of applications, namely for improving future coastal management actions aimed at conserving dune habitats. Moreover, DUVES is potentially transferable due to its easy adaptability depending on the particularities of each study site or goal.pt_PT
dc.description.sponsorshipNAT/PT/000927
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.ecolind.2022.108770pt_PT
dc.identifier.issn1470-160X
dc.identifier.urihttp://hdl.handle.net/10400.1/18248
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationCentre for Marine and Environmental Research (CIMA)
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectUnmanned Aerial Systemspt_PT
dc.subjectDune vegetation state indexpt_PT
dc.subjectGull impactpt_PT
dc.subjectDune conservationpt_PT
dc.subjectDune vegetation mappingpt_PT
dc.subjectImage classificationpt_PT
dc.titleA new index to assess the state of dune vegetation derived from true colour imagespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCentre for Marine and Environmental Research (CIMA)
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00350%2F2020/PT
oaire.citation.startPage108770pt_PT
oaire.citation.titleEcological Indicatorspt_PT
oaire.citation.volume137pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameTalavera
person.familyNameCostas
person.familyNameFerreira
person.givenNameLara
person.givenNameSusana
person.givenNameÓscar
person.identifier1448818
person.identifier.ciencia-idDC15-E5E9-C696
person.identifier.ciencia-idAF19-9EEE-7550
person.identifier.ciencia-id1F1C-DF44-94C9
person.identifier.orcid0000-0001-6708-9933
person.identifier.orcid0000-0002-4005-077X
person.identifier.orcid0000-0001-9975-0036
person.identifier.scopus-author-id9043656500
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationfb40a070-5356-4fe6-ab7e-e1c4830eeebb
relation.isAuthorOfPublication62d73183-10ba-42ca-80a7-458c42d1375b
relation.isAuthorOfPublication14adf536-4f81-42de-b00f-6d1cf3b0d75e
relation.isAuthorOfPublication.latestForDiscovery14adf536-4f81-42de-b00f-6d1cf3b0d75e
relation.isProjectOfPublication607b395b-b4ff-4b27-b6e4-779cdea78d97
relation.isProjectOfPublication.latestForDiscovery607b395b-b4ff-4b27-b6e4-779cdea78d97

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