{"id":{"repo_id":"toronto-retro","oai_identifier":"oai:utoronto.scholaris.ca:1807/111420"},"canonical_url":"https://search.dev.ndltd.org/etd/toronto-retro/oai:utoronto.scholaris.ca:1807/111420","repository":{"repo_id":"toronto-retro","name":"University of Toronto","base_url":"https://utoronto.scholaris.ca/server/oai/request"},"display":{"title":"Parasitism, Predation Prediction: Modelling Variations in Ecological Interactions from Mechanisms to Networks","abstract":"Ecological interactions are fundamental to ecology and evolution, regulating population dynamics as well as influencing the biodiversity and stability of communities. Intraspecific and environmental variations are often present in ecological interactions and are typically observable within the processes that regulate the existence and strength of these interactions as well as in the topology of ecological interaction networks. The main objectives of my PhD thesis were to improve the frameworks and methodologies used for predicting and quantifying variations in interactions and their processes and to understand how intraspecific variation can influence the topology of ecological networks. In Chapter 2, I introduced a framework for creating efficient predictive models, which summarizes the three main stages of the modelling process – (1) Framing the Question; (2) Model-Building and Testing; and (3) Uncertainty Evaluation – and outlines stage-specific interdisciplinary strategies designed to improve the accuracy, reliability, and transparency of predictive modelling. As understanding ecological interactions requires insight into the mechanisms underpinning these interactions, in Chapter 3, I evaluated common approaches for measuring resistance and tolerance processes, two key defense strategies regulating host-parasite interactions. Using individual-based models to simulate host-macroparasite experiments, I demonstrated how the design of experiments and methodologies could interact with resistance and tolerance processes to produce unreliable and biased measures and outlined how modifications to the experimental set-up, sampling design, and statistical analyses could help improve the accuracy and precision of these measurements. As intraspecific variation is expected to influence ecological interaction networks, in Chapter 4, I demonstrated how to detect a major source of this variation, ontogenetic variation, in inferred interaction networks using a framework of count-based inferential methods and graphlet-based techniques. I showed that for freshwater stream fish communities, the inclusion of juveniles – specifically larger species’ juveniles – fundamentally altered the structure of their interaction networks. Altogether, the findings in my thesis emphasize both the importance of considering variations in ecological interactions and their processes and the need for appropriate research designs and methodologies to inform our inferences and predictions.","abstract_html":"Ecological interactions are fundamental to ecology and evolution, regulating population dynamics as well as influencing the biodiversity and stability of communities. Intraspecific and environmental variations are often present in ecological interactions and are typically observable within the processes that regulate the existence and strength of these interactions as well as in the topology of ecological interaction networks. The main objectives of my PhD thesis were to improve the frameworks and methodologies used for predicting and quantifying variations in interactions and their processes and to understand how intraspecific variation can influence the topology of ecological networks. In Chapter 2, I introduced a framework for creating efficient predictive models, which summarizes the three main stages of the modelling process – (1) Framing the Question; (2) Model-Building and Testing; and (3) Uncertainty Evaluation – and outlines stage-specific interdisciplinary strategies designed to improve the accuracy, reliability, and transparency of predictive modelling. As understanding ecological interactions requires insight into the mechanisms underpinning these interactions, in Chapter 3, I evaluated common approaches for measuring resistance and tolerance processes, two key defense strategies regulating host-parasite interactions. Using individual-based models to simulate host-macroparasite experiments, I demonstrated how the design of experiments and methodologies could interact with resistance and tolerance processes to produce unreliable and biased measures and outlined how modifications to the experimental set-up, sampling design, and statistical analyses could help improve the accuracy and precision of these measurements. As intraspecific variation is expected to influence ecological interaction networks, in Chapter 4, I demonstrated how to detect a major source of this variation, ontogenetic variation, in inferred interaction networks using a framework of count-based inferential methods and graphlet-based techniques. I showed that for freshwater stream fish communities, the inclusion of juveniles – specifically larger species’ juveniles – fundamentally altered the structure of their interaction networks. Altogether, the findings in my thesis emphasize both the importance of considering variations in ecological interactions and their processes and the need for appropriate research designs and methodologies to inform our inferences and predictions.","abstract_has_math":false,"creators":["Bodner, Korryn"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Ecology and Evolutionary Biology","school":null,"contributors":[],"advisors":["Fortin, Marie-Josée","Molnár, Péter"],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-11","date_published":"2021-11","updated_at":"2026-07-27T21:28:16Z","subjects":["freshwater fish","inferred networks","macroparasites","prediction","resistance","tolerance"],"languages":[],"rights":["Attribution-NoDerivatives 4.0 International"],"rights_urls":["http://creativecommons.org/licenses/by-nd/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1807/111420","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Fortin, Marie-Josée","Molnár, Péter"]},{"key":"dc:contributor.department","label":"Department","values":["Ecology and Evolutionary Biology"]},{"key":"dc:creator","label":"Author","values":["Bodner, Korryn"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2021-11"]},{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-05-29T04:01:26Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-05-29T04:01:26Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-11"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["freshwater fish","inferred networks","macroparasites","prediction","resistance","tolerance"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Attribution-NoDerivatives 4.0 International"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://creativecommons.org/licenses/by-nd/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1807/111420"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Ecological interactions are fundamental to ecology and evolution, regulating population dynamics as well as influencing the biodiversity and stability of communities. Intraspecific and environmental variations are often present in ecological interactions and are typically observable within the processes that regulate the existence and strength of these interactions as well as in the topology of ecological interaction networks. The main objectives of my PhD thesis were to improve the frameworks and methodologies used for predicting and quantifying variations in interactions and their processes and to understand how intraspecific variation can influence the topology of ecological networks. In Chapter 2, I introduced a framework for creating efficient predictive models, which summarizes the three main stages of the modelling process – (1) Framing the Question; (2) Model-Building and Testing; and (3) Uncertainty Evaluation – and outlines stage-specific interdisciplinary strategies designed to improve the accuracy, reliability, and transparency of predictive modelling. As understanding ecological interactions requires insight into the mechanisms underpinning these interactions, in Chapter 3, I evaluated common approaches for measuring resistance and tolerance processes, two key defense strategies regulating host-parasite interactions. Using individual-based models to simulate host-macroparasite experiments, I demonstrated how the design of experiments and methodologies could interact with resistance and tolerance processes to produce unreliable and biased measures and outlined how modifications to the experimental set-up, sampling design, and statistical analyses could help improve the accuracy and precision of these measurements. As intraspecific variation is expected to influence ecological interaction networks, in Chapter 4, I demonstrated how to detect a major source of this variation, ontogenetic variation, in inferred interaction networks using a framework of count-based inferential methods and graphlet-based techniques. I showed that for freshwater stream fish communities, the inclusion of juveniles – specifically larger species’ juveniles – fundamentally altered the structure of their interaction networks. Altogether, the findings in my thesis emphasize both the importance of considering variations in ecological interactions and their processes and the need for appropriate research designs and methodologies to inform our inferences and predictions."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Parasitism, Predation Prediction: Modelling Variations in Ecological Interactions from Mechanisms to Networks"]}]}],"canonical_facts":{"dc:contributor.advisor":["Fortin, Marie-Josée","Molnár, Péter"],"dc:contributor.department":["Ecology and Evolutionary Biology"],"dc:creator":["Bodner, Korryn"],"dc:date":["2021-11"],"dc:date.accessioned":["2022-05-29T04:01:26Z"],"dc:date.available":["2022-05-29T04:01:26Z"],"dc:date.issued":["2021-11"],"dc:description.abstract":["Ecological interactions are fundamental to ecology and evolution, regulating population dynamics as well as influencing the biodiversity and stability of communities. Intraspecific and environmental variations are often present in ecological interactions and are typically observable within the processes that regulate the existence and strength of these interactions as well as in the topology of ecological interaction networks. The main objectives of my PhD thesis were to improve the frameworks and methodologies used for predicting and quantifying variations in interactions and their processes and to understand how intraspecific variation can influence the topology of ecological networks. In Chapter 2, I introduced a framework for creating efficient predictive models, which summarizes the three main stages of the modelling process – (1) Framing the Question; (2) Model-Building and Testing; and (3) Uncertainty Evaluation – and outlines stage-specific interdisciplinary strategies designed to improve the accuracy, reliability, and transparency of predictive modelling. As understanding ecological interactions requires insight into the mechanisms underpinning these interactions, in Chapter 3, I evaluated common approaches for measuring resistance and tolerance processes, two key defense strategies regulating host-parasite interactions. Using individual-based models to simulate host-macroparasite experiments, I demonstrated how the design of experiments and methodologies could interact with resistance and tolerance processes to produce unreliable and biased measures and outlined how modifications to the experimental set-up, sampling design, and statistical analyses could help improve the accuracy and precision of these measurements. As intraspecific variation is expected to influence ecological interaction networks, in Chapter 4, I demonstrated how to detect a major source of this variation, ontogenetic variation, in inferred interaction networks using a framework of count-based inferential methods and graphlet-based techniques. I showed that for freshwater stream fish communities, the inclusion of juveniles – specifically larger species’ juveniles – fundamentally altered the structure of their interaction networks. Altogether, the findings in my thesis emphasize both the importance of considering variations in ecological interactions and their processes and the need for appropriate research designs and methodologies to inform our inferences and predictions."],"dc:description.degree":["Ph.D."],"dc:identifier.uri":["http://hdl.handle.net/1807/111420"],"dc:rights":["Attribution-NoDerivatives 4.0 International"],"dc:rights.uri":["http://creativecommons.org/licenses/by-nd/4.0/"],"dc:subject":["freshwater fish","inferred networks","macroparasites","prediction","resistance","tolerance"],"dc:title":["Parasitism, Predation Prediction: Modelling Variations in Ecological Interactions from Mechanisms to Networks"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T21:28:16Z"}