A Dataset of Marine Macroinvertebrate Diversity from Mozambique and São Tomé and Príncipe

Marta Bento (), Henrique Niza, Alexandra Cartaxana, Salomão Bandeira, José Paula and Alexandra Marçal Correia ()
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Marta Bento: Department of Animal Biology, Faculty of Sciences, University of Lisbon, Campo Grande, 1749-016 Lisboa, Portugal
Henrique Niza: MARE—Marine and Environmental Sciences Centre/ARNET—Aquatic Research Network, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal
Alexandra Cartaxana: MARE—Marine and Environmental Sciences Centre/ARNET—Aquatic Research Network, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal
Salomão Bandeira: Department of Biological Sciences, Eduardo Mondlane University, Maputo 1100, Mozambique
José Paula: Department of Animal Biology, Faculty of Sciences, University of Lisbon, Campo Grande, 1749-016 Lisboa, Portugal
Alexandra Marçal Correia: Department of Animal Biology, Faculty of Sciences, University of Lisbon, Campo Grande, 1749-016 Lisboa, Portugal

Data, 2023, vol. 8, issue 5, 1-4

Abstract: Marine macroinvertebrate communities play a key role in ecosystem functioning by regulating flows of energy and materials and providing numerous ecosystem services. In Mozambique and São Tomé and Príncipe marine macroinvertebrates are important for the livelihood and food security of local populations. We compiled a dataset on marine invertebrates from Mozambique and São Tomé and Príncipe through an extensive data search of digital platforms, scientific literature, and natural history collections (NHC). This dataset encompasses data from 1816 to 2023 and comprises 20,122 records, representing 617 families, 1552 genera, 2137 species, providing species occurrence in mangrove forests, seagrass beds, coral reefs, and other coastal and offshore habitats. The dataset has a Darwin Core standard format and has been fully released in the Global Biodiversity Information Facility (GBIF). It is accessible through the GBIF portal under the Creative Commons Attribution 4.0 International license. The data are standardized and validated with tools such as WoRMS, GEOLocate, and Google Maps. Therefore, they can be readily used for further studies on species richness, distribution, and functional traits. Overall, this dataset contributes baseline information on marine biodiversity for future research.

Keywords: biodiversity; mangrove forests; seagrass beds; database; GBIF (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2023
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