BECAS
VAZQUEZ Diego Martin
artículos
Título:
Estimating intrinsic susceptibility to extinction when little ecological information is available: the case of Neotropical freshwater stingrays (Chondrichthyes: Potamotrygoninae)
Autor/es:
VAZQUEZ, DIEGO M.; LUCIFORA, LUIS O.
Revista:
FISH AND FISHERIES
Editorial:
WILEY-BLACKWELL PUBLISHING, INC
Referencias:
Lugar: Londres; Año: 2023
ISSN:
1467-2960
Resumen:
Determining the extinction risk of poorly known species is difficult, as data on both their biological traits and the threats to which they are exposed are often not available. Neotropical freshwater stingrays (potamotrygonins) represent such a challenge, as limited ecological data prevent formal assessments. Geographic range size (GRS) was computed for the first time for potamotrygonins (as a longitudinal extent of occurrence measured in km of river length) and, together with two other traits correlated with intrinsic susceptibility to extinction—body size, biological productivity(rmax)—was used to rank potamotrygonins according to their intrinsic susceptibility to extinction. Potamotrygonin GRS was only 6%–7% of that of marine elasmobranchs and is likely to be a significant driver of potamotrygonin extinction risk. The relationship between potamotrygonin GRS and body size differed from the expected triangular theoretical pattern; probably a result of the fragmented nature of freshwater habitats. Using K-medoids clustering, we identified seven groups of species; the most susceptible groups comprised the biggest species such as Potamotrygon brachyura and Paratrygon spp. Intrinsic susceptibility was also highest in the largest hydrographicbasins, likely as a result of species with low rmax being more common there. Exposure to anthropogenic threats is highest for the species most intrinsically susceptible to extinction, which consequently have a high-extinction risk. We recommend the use of longitudinal extents of occurrence as standardized measurements of freshwater taxa GRS. Our ranking method, combining observed and predicted traits, may be a useful tool to assess poorly known taxa to assist conservation prioritization.