JISAR

Journal of Information Systems Applied Research

Volume 16

V16 N1 Pages 52-62

Mar 2023


Identification of Stressed Wolf Populations Based on Hormone Levels Using Support Vector Machines (SVM)


John Stewart
Robert Morris University
Pittsburgh, PA USA

Gary Alan Davis
Robert Morris University
Pittsburgh, PA USA

Abstract: In North America, wolf populations have been relentlessly hunted and persecuted since Europeans landed in the new world. In recent years, in an effort to restore the balance of flora and fauna in ecosystems, wolves have been reintroduced in some areas. In other areas, wolf populations are still hunted based upon the premise of “managing them.” Prior studies have suggested that physiological indicators, specifically elevated hormone levels, are symptomatic of higher stress levels in individual wolf subjects in heavily hunted populations. This stress has far-reaching implications for reproduction, social structure and pack dynamics. The current study supports prior studies that used statistics to show elevated stress levels in hunted wolf populations and classification of individual wolf subjects as belonging to hunting-based stressed populations based on physiological data, using machine learning.

Download this article: JISAR - V16 N1 Page 52.pdf


Recommended Citation: Stewart, J., Davis, G., (2023). Identification of Stressed Wolf Populations Based on Hormone Levels Using Support Vector Machines (SVM). Journal of Information Systems Applied Research16(1) pp 52-62. http://JISAR.org/2023-1/ ISSN : 1946 - 1836. A preliminary version appears in The Proceedings of CONISAR 2022