RT Journal Article
T1 Predicting Sex in White Rhinoceroses: A Statistical Model for Conservation Management
A1 Martínez, Leticia
A1 Andrés Gamazo, Paloma Jimena de
A1 Caperos, José Manuel
A1 Silván Granado, Gema
A1 Fernández-Morán, Jesús
A1 Casares, Miguel
A1 Crespo, Belén
A1 Vélez Serrano, Daniel
A1 Sanz San Miguel, Luis
A1 Cáceres Ramos, Sara Cristina
A1 Illera Del Portal, Juan Carlos
AB Ensuring the effective management of every rhinoceros population is crucial for securing a future for the species, especially considering the escalating global threat of poaching and the challenges faced in captive breeding programs for this endangered species. Steroid hormones play pivotal roles in regulating diverse biological processes, making fecal hormonal determinations a valuable non-invasive tool for monitoring adrenal and gonadal endocrinologies and assessing reproductive status, particularly in endangered species. The purpose of this study was to develop a statistical model for predicting the sex of white rhinoceroses using hormonal determinations obtained from a single fecal sample. To achieve this, 562 fecal samples from 15 individuals of the Ceratotherium simum species were collected, and enzyme immunoassays were conducted to determine the concentrations of fecal cortisol, progesterone, estrone, and testosterone metabolites. The biological validation of the method provided an impressive accuracy rate of nearly 80% in predicting the sex of hypothetically unknown white rhinoceroses. Implementing this statistical model for sex identification in white rhinoceroses would yield significant benefits, including a better understanding of the structure and dynamics of wild populations. Additionally, it would enhance conservation management efforts aimed at protecting this endangered species. By utilizing this innovative approach, we can contribute to the preservation and long-term survival of white rhinoceros populations.
PB MDPI
SN 2076-2615
YR 2023
FD 2023-08-10
LK https://hdl.handle.net/20.500.14352/103596
UL https://hdl.handle.net/20.500.14352/103596
LA eng
NO Martínez, L., de Andrés, P. J., Caperos, J. M., Silván, G., Fernández-Morán, J., Casares, M., Crespo, B., Vélez, D., Sanz, L., Cáceres, S., & Illera, J. C. (2023). Predicting Sex in White Rhinoceroses: A Statistical Model for Conservation Management. Animals : an open access journal from MDPI, 13(16), 2583. https://doi.org/10.3390/ani13162583
NO 2022 Descuento MDPI
DS Docta Complutense
RD 12 abr 2025