Tipo
Artigos em Revista
Tipo de Documento
Artigo Completo
Título
Catching the Drift of Marine Invertebrate Diversity through Digital Repositories—A Case Study of the Mangroves and Seagrasses of Maputo Bay, Mozambique
Participantes na publicação
Marta Bento (Author)
Dep. Biologia Animal
MARE
José Paula (Author)
MARE - Centro de Ciências do Mar e Ambiente, -Universidade de Lisboa
Dep. Biologia Animal
Salomão Bandeira (Author)
Alexandra Marçal Correia (Author)
Dep. Biologia Animal
MARE
Resumo
Mangroves and seagrasses present with high marine macroinvertebrate biodiversity that contributes to their structure and functioning. Macroinvertebrates possess a broad range of functional traits, making them excellent models for biodiversity and available-trait-based studies. This study aimed to characterize the biodiversity of marine macroinvertebrates as two different ecosystems situated along the coastline of Maputo Bay by compiling dispersed data from online databases. Specifically, this study addressed species richness, taxonomic and functional diversity based on two traits (habitat occupation and trophic guild), and the community structure of these traits. Mangroves presented with a higher species richness and taxonomic diversity than seagrasses. The functional diversity of mangroves was mostly explained by the trophic guild trait. In the case of seagrasses, functional diversity was mostly due to differences in habitat occupation in the 20th century, but the trophic guild accounted for this functional diversity from 2000 onwards. The comparison of community compositions between the two ecosystems showed low or no similarity. The use of digital databases revealed some limitations, mostly regarding the sampling methods and individual counts. The trends and data gaps presented in this study can be further used to inform subsequent systematic data acquisition and support the development of future research. A further step that may be taken to improve the use of digital data in future biodiversity studies is to fully incorporate functional traits, abundance and sampling methods into online databases.
Data de Submissão/Pedido
2022-12-28
Data de Aceitação
2023-02-07
Data de Publicação
2023-02-09
Instituição
MARE – Marine and Environmental Sciences Centre, Universidade de Lisboa
Suporte
Diversity
Identificadores da Publicação
ISSN - 1424-2818
Editora
MDPI AG
Identificadores do Documento
DOI -
https://doi.org/10.3390/d15020242
URL -
https://www.mdpi.com/1424-2818/15/2/242
Identificadores de Qualidade
SCIMAGO Q1 (2021) - 668 - Agricultural and Biological Sciences (miscellaneous)
Keywords
species richness
taxonomic diversity
functional diversity
community composition
East Africa
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