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Large-ccale prediction of seagrass distribution integrating landscape metrics and environmental factors: The case of cymodocea nodosa (Mediterranean-Atlantic)

2016-07Journal article Restricted
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dc.contributor.authorChefaoui, Rosa M.
dc.contributor.authorAssis, J.
dc.contributor.authorDuarte, Carlos M.
dc.contributor.authorSerrão, Ester
dc.date.accessioned2017-04-07T15:57:40Z
dc.date.available2017-04-07T15:57:40Z
dc.date.issued2016-07
dc.description.abstractUnderstanding the factors that affect seagrass meadows encompassing their entire range of distribution is challenging yet important for their conservation. Here, we predict the realized and potential distribution for the species Cymodocea nodosa modelling its environmental niche in the Mediterranean and adjacent Atlantic coastlines. We use a combination of environmental variables and landscape metrics to perform a suite of predictive algorithms which enables examination of the niche and find suitable habitats for the species. The most relevant environmental variables defining the distribution of C. nodosa were sea surface temperature (SST) and salinity. We found suitable habitats at SST from 5.8 A degrees C to 26.4 A degrees C and salinity ranging from 17.5 to 39.3. Optimal values of mean winter wave height ranged between 1.2 and 1.5 m, while waves higher than 2.5 m seemed to limit the presence of the species. The influence of nutrients and pH, despite having weight on the models, was not so clear in terms of ranges that confine the distribution of the species. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. We found potential suitable areas not occupied by the seagrass mainly in coastal regions of North Africa and the Adriatic coast of Italy. The present study describes the realized and potential distribution of a seagrass species, providing the first global model of the factors that can be shaping the environmental niche of C. nodosa throughout its range. We identified the variables constraining its distribution as well as thresholds delineating its environmental niche. Landscape metrics showed promising prospects for the prediction of coastal species dependent on the shape of the coast. By contrasting predictive approaches, we defined the variables affecting the distributional areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. These findings are encouraging for its use in future studies on climate-related marine range shifts and meadow restoration projects of these fragile ecosystems.
dc.description.sponsorshipCCMAR/BPD/0045/2013
dc.identifier.doi10.1007/s12237-015-9966-y
dc.identifier.issn1559-2723
dc.identifier.otherAUT: ESE00527;
dc.identifier.urihttp://hdl.handle.net/10400.1/9785
dc.language.isoeng
dc.peerreviewedyes
dc.relationExtant or extinct tipping points - climate changes drive genetic diversity and dynamics of range edge populations as evolutionary hotspots
dc.relation.isbasedonWOS:000367525900010
dc.titleLarge-ccale prediction of seagrass distribution integrating landscape metrics and environmental factors: The case of cymodocea nodosa (Mediterranean-Atlantic)
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleExtant or extinct tipping points - climate changes drive genetic diversity and dynamics of range edge populations as evolutionary hotspots
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBPD%2F85040%2F2012/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/EXCL%2FAAG-GLO%2F0661%2F2012/PT
oaire.citation.endPage137
oaire.citation.issue1
oaire.citation.startPage123
oaire.citation.titleEstuaries and Coasts
oaire.citation.volume39
oaire.fundingStreamSFRH
oaire.fundingStream3599-PPCDT
person.familyNameAssis
person.familyNameSerrao
person.givenNameJorge
person.givenNameEster A.
person.identifierC-6686-2012
person.identifier.ciencia-id5C1D-05B6-29F7
person.identifier.ciencia-id5B13-B26E-B1EC
person.identifier.orcid0000-0002-6624-4820
person.identifier.orcid0000-0003-1316-658X
person.identifier.ridG-9688-2012
person.identifier.scopus-author-id53463298700
person.identifier.scopus-author-id7004093604
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
rcaap.rightsrestrictedAccess
rcaap.typearticle
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relation.isAuthorOfPublication45ccfe90-155c-4d6f-9e86-8f0fd064005f
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