Distribución potencial de Kinosternon cora (Testudines: Kinosternidae) e implicaciones para su conservación

Jesús Alberto Loc-Barragán; Héctor Alexis Castro-Bastidas

doi:10.30550/j.azl/2254

Authors

Jesús Alberto Loc-Barragán Ciencia Conservación y Desarrollo de las Comunidades (CICODEC) A.C., Tepic 63066, Nayarit, México. https://orcid.org/0000-0001-6851-054X
Héctor Alexis Castro-Bastidas Centro de Estudios "Justo Sierra" (CEJUS), Badiraguato 80600, Sinaloa, México https://orcid.org/0000-0002-6448-5639

DOI:

https://doi.org/10.30550/j.azl/2254

Keywords:

Endemic species, Freshwater turtles, MaxEnt, Nayarit, Sinaloa

Abstract

Kinosternon cora, an endemic turtle of the Pacific Coastal Plain in
Sinaloa and Nayarit, Mexico, is classified as “Endangered” due to its
restricted distribution, habitat loss, and illegal collection. This study
modeled its potential distribution using MaxEnt and 48 verified pres-
ence records, analyzing bioclimatic variables (mean annual tempera-
ture, diurnal temperature range, temperature of the warmest quarter,
precipitation of the driest and coldest quarters). The LQPTH/?3 model
showed high performance (AUC = 0.970, pROC = 1.51, p = 0.001),
predicting 3,548.27 km² of suitable habitat with 85.9% overlap with the
known distribution. Mean annual temperature (29.5–30.0°C) and low
dry-season precipitation (<100 mm) were the most influential predic-
tors, contributing 41.64% and 22.2% to the model, respectively, with
optimal diurnal temperature ranges (10.0–16.0°C) and warmest quar-
ter temperatures (28.5–30.0°C), reflecting reliance on thermally stable
wetlands. Precipitation in the coldest quarter had no significant effect.
These results identify climatically suitable areas for K. cora, highlighting
the need to protect aquatic and semi-aquatic habitats threatened by
wetland degradation and illegal trade. Unconfirmed predicted areas
suggest zones for targeted surveys to refine distribution knowledge.
This study supports conservation efforts by identifying priority areas for habitat protection and recommending the integration of non-bioclimatic
variables, such as vegetation cover, to refine future distribution models.

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