Literature DB >> 28754519

Long-term analysis of Zostera noltei: A retrospective approach for understanding seagrasses' dynamics.

Felipe Calleja1, Cristina Galván2, Ana Silió-Calzada3, José A Juanes4, Bárbara Ondiviela5.   

Abstract

Long-term studies are necessary to establish trends and to understand seagrasses' spatial and temporal dynamic. Nevertheless, this type of research is scarce, as the required databases are often unavailable. The objectives of this study are to create a method for mapping the seagrass Zostera noltei using remote sensing techniques, and to apply it to the characterization of the meadows' extension trend and the potential drivers of change. A time series was created using a novel method based on remote sensing techniques that proved to be adequate for mapping the seagrass in the emerged intertidal. The meadows seem to have a decreasing trend between 1984 and the early 2000s, followed by an increasing tendency that represents a recovery in the extension area of the species. This 30-year analysis demonstrated the Z. noltei's recovery in the study site, similar to that in other estuaries nearby and contrary to the worldwide decreasing behavior of seagrasses.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bay of Biscay; Estuaries; Remote sensing; Seagrass; Spectral signatures; Trends

Mesh:

Year:  2017        PMID: 28754519     DOI: 10.1016/j.marenvres.2017.07.017

Source DB:  PubMed          Journal:  Mar Environ Res        ISSN: 0141-1136            Impact factor:   3.130


  2 in total

1.  Evaluating Seagrass Meadow Dynamics by Integrating Field-Based and Remote Sensing Techniques.

Authors:  Danijel Ivajnšič; Martina Orlando-Bonaca; Daša Donša; Veno Jaša Grujić; Domen Trkov; Borut Mavrič; Lovrenc Lipej
Journal:  Plants (Basel)       Date:  2022-04-28

2.  Blue Carbon stock in Zostera noltei meadows at Ria de Aveiro coastal lagoon (Portugal) over a decade.

Authors:  Ana I Sousa; José Figueiredo da Silva; Ana Azevedo; Ana I Lillebø
Journal:  Sci Rep       Date:  2019-10-07       Impact factor: 4.379

  2 in total

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