{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/115645"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/115645","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Information use, risk perception, and stress in wildlife populations","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-05-01","abstract_has_math":false,"creators":["Sutton, Nicholas M."],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Ecol, Evol, Conservation Biol","degree_department":null,"school":null,"contributors":["O'Dwyer, James","Bell, Alison","Paige, Ken","Schooley, Robert"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-05","date_published":"2022-05","updated_at":"2026-07-22T22:24:54Z","subjects":["Animal behavior","animal cognition","Bayesian","optimality theory","wildlife","stress hormones"],"languages":["en","eng"],"rights":["Copyright 2022 Nicholas Sutton"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/115645","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["O'Dwyer, James","Bell, Alison","Paige, Ken","Schooley, Robert"]},{"key":"dc:creator","label":"Author","values":["Sutton, Nicholas M."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-05","2022-04-20"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Ecol, Evol, Conservation Biol"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Animal behavior","animal cognition","Bayesian","optimality theory","wildlife","stress hormones"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2022 Nicholas Sutton"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/115645"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-05-01","The student, Nicholas Sutton, accepted the attached license on 2022-04-20 at 13:53.","The student, Nicholas Sutton, submitted this Dissertation for approval on 2022-04-20 at 14:04.","This Dissertation was approved for publication on 2022-04-20 at 16:45.","DSpace SAF Submission Ingestion Package generated from Vireo submission #17850 on 2022-11-14 at 00:24:52","Animal behavior can vary widely between individuals even when faced with the same context, with high intraspecific behavioral variation arising from differences in past experience, genetic pre-disposition, information use, and more. These sources of variation complicate attempts to characterize information use and decision-making in animals, and the behaviors underlying decisions such as when to search for new foraging opportunities or when to flee from predators are notoriously challenging to predict quantitatively. In wildlife, this becomes all the more challenging as observed behavior cannot always be linked to additional data on individual animals without extensive monitoring programs. This dissertation explores methods for modeling and characterizing decision-making behaviors in wildlife populations. I first developed a modelling framework to describe white-tailed deer (Odocoileus virginianus) escape behavior and decision-making in response to humans in Illinois state parks. Using this framework, I 1) accurately described observed escape decisions, 2) tested hypotheses regarding what information deer were using to make their decisions, and 3) inferred how prior perceptions of risk are distributed within populations, effectively accounting for variation in individual histories. I then applied this framework to seven Australian waterbird species to quantify differences in species risk perception in response to human activity and found species-specific trends in how readily birds adjust perceived risk when faced with different levels of human activity. Finally, I returned to the white-tailed deer system to dig deeper into one potential source of variation in risk perception: internal state as measured via stress hormone level. I explored how stress levels are distributed in different deer populations and found that stress hormone metabolite levels follow a power-law in all populations, but with differences that align with differences in population exposure to human activity. I also note an interesting seasonal trend and explore stress-response models to better understand the observed power-laws. Taken together, the research in this dissertations represents advances in inference methods for modeling wildlife decision-making and information use via novel interpretations and analyses of distributions of prior perceptions of risk and stress hormone levels in wildlife populations."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Information use, risk perception, and stress in wildlife populations"]}]}],"canonical_facts":{"dc:contributor":["O'Dwyer, James","Bell, Alison","Paige, Ken","Schooley, Robert"],"dc:creator":["Sutton, Nicholas M."],"dc:date":["2022-05","2022-04-20"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-05-01","The student, Nicholas Sutton, accepted the attached license on 2022-04-20 at 13:53.","The student, Nicholas Sutton, submitted this Dissertation for approval on 2022-04-20 at 14:04.","This Dissertation was approved for publication on 2022-04-20 at 16:45.","DSpace SAF Submission Ingestion Package generated from Vireo submission #17850 on 2022-11-14 at 00:24:52","Animal behavior can vary widely between individuals even when faced with the same context, with high intraspecific behavioral variation arising from differences in past experience, genetic pre-disposition, information use, and more. These sources of variation complicate attempts to characterize information use and decision-making in animals, and the behaviors underlying decisions such as when to search for new foraging opportunities or when to flee from predators are notoriously challenging to predict quantitatively. In wildlife, this becomes all the more challenging as observed behavior cannot always be linked to additional data on individual animals without extensive monitoring programs. This dissertation explores methods for modeling and characterizing decision-making behaviors in wildlife populations. I first developed a modelling framework to describe white-tailed deer (Odocoileus virginianus) escape behavior and decision-making in response to humans in Illinois state parks. Using this framework, I 1) accurately described observed escape decisions, 2) tested hypotheses regarding what information deer were using to make their decisions, and 3) inferred how prior perceptions of risk are distributed within populations, effectively accounting for variation in individual histories. I then applied this framework to seven Australian waterbird species to quantify differences in species risk perception in response to human activity and found species-specific trends in how readily birds adjust perceived risk when faced with different levels of human activity. Finally, I returned to the white-tailed deer system to dig deeper into one potential source of variation in risk perception: internal state as measured via stress hormone level. I explored how stress levels are distributed in different deer populations and found that stress hormone metabolite levels follow a power-law in all populations, but with differences that align with differences in population exposure to human activity. I also note an interesting seasonal trend and explore stress-response models to better understand the observed power-laws. Taken together, the research in this dissertations represents advances in inference methods for modeling wildlife decision-making and information use via novel interpretations and analyses of distributions of prior perceptions of risk and stress hormone levels in wildlife populations."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/115645"],"dc:language":["en","eng"],"dc:rights":["Copyright 2022 Nicholas Sutton"],"dc:subject":["Animal behavior","animal cognition","Bayesian","optimality theory","wildlife","stress hormones"],"dc:title":["Information use, risk perception, and stress in wildlife populations"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Ecol, Evol, Conservation Biol"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:54Z"}