Please use this identifier to cite or link to this item: https://knowledgecommons.lakeheadu.ca/handle/2453/4795
Title: Potential of modeling to predict the re-establishment of bat populations affected by white-nose syndrome in northwestern Ontario
Authors: Nesbitt, Dylan
Keywords: Little brown bat;Pseudogymnoascus destructans;White-nose syndrome;Ontario bats;Bat populations (recovery and re-establishment)
Issue Date: 2021
Abstract: Since the first confirmed case in North America in 2007, white nose syndrome caused by Pseudogymnoascus destructans has decimated bat populations in the northeastern US and eastern Canada. Ontario is home to eight species of bat, with four of these being labeled as Endangered, either provincially or federally. Afflicted individuals transmit the fungus through physical contact in roosts or during swarming events. Presence of the host is not required for the fungus to persist in suitable environments such the cool, moist locations chosen as hibernacula. Recently, modeling has been used to better understand this disease and the effects it has on bat populations. Two research questions formed the focus of this thesis: What is the potential of modeling to predict the re-establishment of bat populations in northwestern Ontario? and What information is needed to support a modeling effort? Current literature was reviewed and five papers that employed the use of models were selected. Papers were compared on the basis of goals, scenarios, outcomes and data used. It was determined that modeling could be useful in the context of northwestern Ontario and that data on bat physiology and hibernacula conditions were the most essential.
URI: http://knowledgecommons.lakeheadu.ca/handle/2453/4795
metadata.etd.degree.discipline: Natural Resources Management
metadata.etd.degree.name: Honours Bachelor of Environmental Management
metadata.etd.degree.level: Bachelor
metadata.dc.contributor.advisor: Luckai, Nancy
metadata.dc.contributor.committeemember: Rosenthal, Julie
Appears in Collections:Undergraduate theses

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