Preferential habitats prediction in syngnathids using species distribution models

Abstract

Syngnathids are considered as flagship species for marine conservation. Seahorses and pipefish are highly vulnerable to anthropogenic and environmental disturbances, but most species are currently considered Data Deficient by IUCN, requiring more biological and ecological research. Although syngnathids are well known for their unusual breeding biology, some aspects on the ecology of this family have rarely received attention. The knowledge on the factors governing syngnathids distribution is limited to some species and geographical regions. The present study is the first approach to predict syngnathid habitat preference in Spanish coasts, particularly in a marine National Park. In this study, Species Distribution Models (SDMs) were implemented to investigate the preferential habitat and distribution of the pipefish Syngnathus acus in Cíes Archipelago (Atlantic Islands of Galicia National Park, PNIA). Occurrence data of the species obtained from 2016 to 2018 surveys in PNIA were modeled as a function of bathymetric (depth, slope), substrate (sediment texture) and oceanographic (waves exposure) variables, using GAM, Random Forest and Maxent algorithms. From those SDMs, prediction models were built and the ensemble map of predictions was performed. The variables that most determined the distribution of the species were depth and wave exposure. The results of this study provide information on (1) habitat preference in the most dominant species in PNIA, the pipefish S. acus, towards sustainable management of this species in the National Park, and (2) predictive statistical tools for proper spatial conservation plans of this syngnathid species.

Keywords: Ensemble modeling; Habitat suitability; Pipefish; Species distribution models; Sustainable management; Syngnathids.