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Virginia Tech

Identifying patterns and processes of sex-biases for an emerging fungal disease of wildlife

Abstract

dc:description.abstract

Anthropogenic changes have facilitated an increase in emerging infectious diseases, threatening biodiversity globally. Identifying the individuals, species, or communities most vulnerable to disease can guide the development of conservation priorities. Processes that structure individual variation, such as demography, can strongly affect the response of populations or species to pathogen introduction. Specifically, sex-biased disease can mediate the size of epidemics as well as the magnitude of populations declines following pathogen introduction. However, the context in which we expect sex-biased disease to occur, and subsequently affect population dynamics, varies among host-pathogen systems. Here, I identified patterns of sex-biased disease across several species of bat hosts impacted by white-nose syndrome and explored novel seasonal processes that gave rise to sex-biased disease, which ultimately scaled up to restructure populations. In scaling ecological dynamics from individuals to populations, I developed an R-based computational package to increase the ease of analyzing advancing PIT tagging technology thus providing tools to study individually based phenology, migratory patterns, network connectedness, and survival of species to a broader audience. Collectively, my work supports conservation of wildlife imperiled by disease, advances the theoretical framework for which we can anticipate sex-biased disease, and expands methods for investigating ecological and evolutionary dynamics, thereby broadening the scope of biological inference.

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Biological Sciences
Department dc:contributor.department
Biological Sciences
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2025

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kailing, Macy Jay
Chair dc:contributor.committeechair
  • Langwig, Kate Elizabeth
Committee members dc:contributor.committeemember
  • Moore, Ignacio T.
  • Hoyt, Joseph R.
  • Hopkins, William A.

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • Creative Commons Attribution 4.0 International
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:43165
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/130397

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Kailing, Macy Jay. Identifying patterns and processes of sex-biases for an emerging fungal disease of wildlife. doctoral thesis, Virginia Tech, 2025. https://hdl.handle.net/10919/130397