Dietary and niche analyses of four endemic and sympatric batoid species of the subtropical South Atlantic Ocean

We aimed to characterize the trophic ecology and test the hypothesis of niche overlap between four endemic and sympatric batoid species of the subtropical South Atlantic. Data were collected between 2017 and 2022 from two artisanal fishery communities in southern Brazil. Batoid stomach contents were...

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Bibliographic Details
Main Authors: Lemos, Liliam, Freitas, Renato, Bornatowski, Hugo
Format: Other/Unknown Material
Language:unknown
Published: Zenodo 2023
Subjects:
ray
Online Access:https://doi.org/10.5281/zenodo.7927311
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Summary:We aimed to characterize the trophic ecology and test the hypothesis of niche overlap between four endemic and sympatric batoid species of the subtropical South Atlantic. Data were collected between 2017 and 2022 from two artisanal fishery communities in southern Brazil. Batoid stomach contents were identified, separated into categories, and weighed. We calculated the Levins, Pianka's, and relative dietary importance index (IRI), and performed a similarity test using PERMANOVA and the similarity percentage (SIMPER) for niche analysis. We analyzed 229 stomachs of four batoid species, 187 containing food. All species showed a narrow food niche. The most important diet items for each species were: Leptochaela serratorbita and Onuphidae for Dasyatis hypostigma Nematoda for Pseudobatos horkelii L . serratorbita and Sicyonia dorsalis for Rioraja agassizii and Achelous spinicarpus for Sympterygia bonapartii . The analyses showed (statistically significant) dissimilarity among the species' diets without significant niche overlap. This study provides ecology-feeding information for four batoid species with specialized diets composed of benthic prey species. Our results detected the absence of significant niche overlap among batoid species, suggesting other types of niche partitioning and spatiotemporal habitat variation. This information could be considered for local management plans. Excel and R Language for Statistical Computing 2022. Funding provided by: Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100005667 Award Number: