Social-ecological system approach relevant for modelling the ecological niche of a mangrove gastropod at small regional scale

The gastropod Terebralia palustris is found in mangroves from the Indo-Pacific, where it plays important ecological roles and is fished by humans. As such, it reflects interactions occurring within the socio-ecosystem, although information regarding its regional distribution and ecological niche is uneven. The present study aimed at defining the relative importance of factors of the mangrove socio-ecological system (MSES) on the realized niche of T. palustris at the regional scale. We studied its distribution at the scale of Mayotte Island (France, Indian Ocean), including local ecological knowledge and environmental memory held by population. To this end, a survey campaign of the 29 mangroves of Mayotte allowed mapping its occurrence and correlating the spatial pattern to factors of the MSES related to three dimensions of the niche (accessibility, abiotic, and biotic) pertaining to both societal and ecological components. Questionnaire interviews revealed both past presence and current presence undetected by the survey campaign. At the scale of Mayotte, the gastropod is found on large and deep mangroves, distant from the sea by a deep central and external mangrove, where Avicennia marina is not the only mangrove tree species and the canopy is relatively opened, at the bottom of watersheds holding large urban areas. Our study showed that dealing with both ecosystemic and societal subsystems and their involvement in each dimension of the niche concept is a promising way of understanding the drivers of species distribution in anthropized systems. • Terebralia palustris is found within 13 of the 29 landward mangroves of Mayotte • Realized niche of T. palustris is mostly explained by ecosystemic variables • Little societal influence on the presence of T. palustris at the island scale • Local ecological knowledge improves species distribution data in data poor regions • Social-ecological system approach helps highlight issues of scale and threshold