Macroalgae niche modelling : a two-step approach using remote sensing and in situ observations of a native and an invasive Asparagopsis

Detalhes bibliográficos
Autor(a) principal: Casas, Enrique
Data de Publicação: 2021
Outros Autores: Fernandez, Marc, Gil, Artur José Freire, Yesson, Chris, Prestes, Afonso L., Moreu‐Badia, Ignacio, Neto, Ana I., Arbelo, Manuel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.3/6051
Resumo: We are facing a global loss of biodiversity due to climate change. This will lead to unpredictable changes in ecosystems, affecting the goods and services they provide introduction of non-indigenous marine species. This represents one of the major threats to marine biodiversity and therefore, there is a strong need to assess, map and monitor these alien species. The appearance of non-indigenous species is especially dangerous in fragile ecosystems and it is of great importance to better understand the invasion mechanisms of these invasive species. This is the case for invasive alga Asparagopsis armata, present in the Azores Archipelago. In this study we propose a methodology to define the realized ecological niche of this invasive alga, alongside the native Asparagopsis taxiformis, to understand better its distribution and potential impact on native communities and ecosystem services. These objectives comply with the EU Biodiversity strategy for 2020 goals and the need to map and assess ecosystems and their services. The lack of reliable high-resolution data makes this a challenging task. Within this scope, we propose a combination of Remote Sensing, Unmanned Aerial Vehicle based imagery together with in-situ field data to build ecological niche modelling approaches as a cost-effective methodology to identify and characterize vulnerable marine ecosystems. Our results show that this combination can help achieve monitoring, leading to a better understanding of ecological niches and the consequences of non-indigenous species invasion in fragile ecosystems, like small islands, when faced with limited data.
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spelling Macroalgae niche modelling : a two-step approach using remote sensing and in situ observations of a native and an invasive AsparagopsisAsparagopsis armataAsparagopsis taxiformisEcological Niche ModellingRemote SensingUnmanned Aerial VehicleWe are facing a global loss of biodiversity due to climate change. This will lead to unpredictable changes in ecosystems, affecting the goods and services they provide introduction of non-indigenous marine species. This represents one of the major threats to marine biodiversity and therefore, there is a strong need to assess, map and monitor these alien species. The appearance of non-indigenous species is especially dangerous in fragile ecosystems and it is of great importance to better understand the invasion mechanisms of these invasive species. This is the case for invasive alga Asparagopsis armata, present in the Azores Archipelago. In this study we propose a methodology to define the realized ecological niche of this invasive alga, alongside the native Asparagopsis taxiformis, to understand better its distribution and potential impact on native communities and ecosystem services. These objectives comply with the EU Biodiversity strategy for 2020 goals and the need to map and assess ecosystems and their services. The lack of reliable high-resolution data makes this a challenging task. Within this scope, we propose a combination of Remote Sensing, Unmanned Aerial Vehicle based imagery together with in-situ field data to build ecological niche modelling approaches as a cost-effective methodology to identify and characterize vulnerable marine ecosystems. Our results show that this combination can help achieve monitoring, leading to a better understanding of ecological niches and the consequences of non-indigenous species invasion in fragile ecosystems, like small islands, when faced with limited data.This study is a contribution to the research project ‘ASPAZOR— Ecosystem impacts and socio‐economic benefits of Asparagopsis armata in the Azores' (Ref. ACORES‐01‐1045‐FEDER‐00060) funded through FEDER (85%) and regional funds (15%) via ‘Programa Operacional Açores 2020'. CY is supported by Research England.SpringerRepositório da Universidade dos AçoresCasas, EnriqueFernandez, MarcGil, Artur José FreireYesson, ChrisPrestes, Afonso L.Moreu‐Badia, IgnacioNeto, Ana I.Arbelo, Manuel2022-04-29T00:30:32Z2021-042021-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.3/6051engCasas, E., Fernandez, M., Gil, A., Yesson, Chris., Prestes, A., Moreu-Badia. I., Neto, A.I. & Arbelo, M. (2021). Macroalgae niche modelling: a two-step approach using remote sensing and in situ observations of a native and an invasive Asparagopsis. "Biological Invasions", Online early. DOI:10.1007/s10530-021-02554-z1387-354710.1007/s10530-021-02554-z1573-1464info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-12-20T14:34:25Zoai:repositorio.uac.pt:10400.3/6051Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:28:12.003604Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Macroalgae niche modelling : a two-step approach using remote sensing and in situ observations of a native and an invasive Asparagopsis
title Macroalgae niche modelling : a two-step approach using remote sensing and in situ observations of a native and an invasive Asparagopsis
spellingShingle Macroalgae niche modelling : a two-step approach using remote sensing and in situ observations of a native and an invasive Asparagopsis
Casas, Enrique
Asparagopsis armata
Asparagopsis taxiformis
Ecological Niche Modelling
Remote Sensing
Unmanned Aerial Vehicle
title_short Macroalgae niche modelling : a two-step approach using remote sensing and in situ observations of a native and an invasive Asparagopsis
title_full Macroalgae niche modelling : a two-step approach using remote sensing and in situ observations of a native and an invasive Asparagopsis
title_fullStr Macroalgae niche modelling : a two-step approach using remote sensing and in situ observations of a native and an invasive Asparagopsis
title_full_unstemmed Macroalgae niche modelling : a two-step approach using remote sensing and in situ observations of a native and an invasive Asparagopsis
title_sort Macroalgae niche modelling : a two-step approach using remote sensing and in situ observations of a native and an invasive Asparagopsis
author Casas, Enrique
author_facet Casas, Enrique
Fernandez, Marc
Gil, Artur José Freire
Yesson, Chris
Prestes, Afonso L.
Moreu‐Badia, Ignacio
Neto, Ana I.
Arbelo, Manuel
author_role author
author2 Fernandez, Marc
Gil, Artur José Freire
Yesson, Chris
Prestes, Afonso L.
Moreu‐Badia, Ignacio
Neto, Ana I.
Arbelo, Manuel
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade dos Açores
dc.contributor.author.fl_str_mv Casas, Enrique
Fernandez, Marc
Gil, Artur José Freire
Yesson, Chris
Prestes, Afonso L.
Moreu‐Badia, Ignacio
Neto, Ana I.
Arbelo, Manuel
dc.subject.por.fl_str_mv Asparagopsis armata
Asparagopsis taxiformis
Ecological Niche Modelling
Remote Sensing
Unmanned Aerial Vehicle
topic Asparagopsis armata
Asparagopsis taxiformis
Ecological Niche Modelling
Remote Sensing
Unmanned Aerial Vehicle
description We are facing a global loss of biodiversity due to climate change. This will lead to unpredictable changes in ecosystems, affecting the goods and services they provide introduction of non-indigenous marine species. This represents one of the major threats to marine biodiversity and therefore, there is a strong need to assess, map and monitor these alien species. The appearance of non-indigenous species is especially dangerous in fragile ecosystems and it is of great importance to better understand the invasion mechanisms of these invasive species. This is the case for invasive alga Asparagopsis armata, present in the Azores Archipelago. In this study we propose a methodology to define the realized ecological niche of this invasive alga, alongside the native Asparagopsis taxiformis, to understand better its distribution and potential impact on native communities and ecosystem services. These objectives comply with the EU Biodiversity strategy for 2020 goals and the need to map and assess ecosystems and their services. The lack of reliable high-resolution data makes this a challenging task. Within this scope, we propose a combination of Remote Sensing, Unmanned Aerial Vehicle based imagery together with in-situ field data to build ecological niche modelling approaches as a cost-effective methodology to identify and characterize vulnerable marine ecosystems. Our results show that this combination can help achieve monitoring, leading to a better understanding of ecological niches and the consequences of non-indigenous species invasion in fragile ecosystems, like small islands, when faced with limited data.
publishDate 2021
dc.date.none.fl_str_mv 2021-04
2021-04-01T00:00:00Z
2022-04-29T00:30:32Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.3/6051
url http://hdl.handle.net/10400.3/6051
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Casas, E., Fernandez, M., Gil, A., Yesson, Chris., Prestes, A., Moreu-Badia. I., Neto, A.I. & Arbelo, M. (2021). Macroalgae niche modelling: a two-step approach using remote sensing and in situ observations of a native and an invasive Asparagopsis. "Biological Invasions", Online early. DOI:10.1007/s10530-021-02554-z
1387-3547
10.1007/s10530-021-02554-z
1573-1464
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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