Accurate Early Prediction of Leafy Spurge Invasion Using Species Distribution Models (SDMs) in Alberta
| dc.contributor.advisor | Vamosi, Jana | |
| dc.contributor.author | Zardecki, Natalie Ruth | |
| dc.contributor.committeemember | McLean, Mary Ann | |
| dc.contributor.committeemember | Ruckstuhl, Kathreen | |
| dc.date | 2024-11 | |
| dc.date.accessioned | 2024-08-23T14:14:39Z | |
| dc.date.available | 2024-08-23T14:14:39Z | |
| dc.date.issued | 2024-08-16 | |
| dc.description.abstract | Globalization has resulted in the development of new ecological communities with the introduction of new species to native habitats. While some introduced species benefit their surrounding environments or leave insignificant impacts, others are invasive and decrease an area’s ecological stability. One such invasive plant species, commonly known as Leafy spurge, is increasing in concern to Alberta’s grasslands and agricultural industries. The plant produces a noxious latex that is toxic to livestock and aggressively outcompetes surrounding vegetation. Once established in an environment, Leafy spurge becomes resistant to control mechanisms, requiring multiple treatments to reduce patch sizes. To better predict Leafy spurge’s invasion status in Alberta, I explored the development of Species Distribution Models (SDMs) using BIOMOD2 and MaxENT approaches to compare their predictive abilities using bioclimatic and ecological variables and then tested the accuracy of the models with independent data from field surveys. Results indicated that BIOMOD2 models are more accurate due to the ensemble-modelling approach, which had evaluation scores consistently higher than those of MaxENT, and the inclusion of variables relating to establishment and dispersal contributed more to model accuracy than bioclimatic variables. With the use of this SDM for Leafy spurge invasion in Alberta, mitigating controls can be effectively implemented to limit its spread and predict at-risk areas in need of greater surveillance. | |
| dc.identifier.citation | Zardecki, N. R. (2024). Accurate early prediction of leafy spurge invasion using species distribution models (SDMs) in Alberta (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. | |
| dc.identifier.uri | https://hdl.handle.net/1880/119470 | |
| dc.language.iso | en | |
| dc.publisher.faculty | Graduate Studies | |
| dc.publisher.institution | University of Calgary | |
| dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | |
| dc.subject | SDM | |
| dc.subject | Species Distribution Model | |
| dc.subject | Leafy spurge | |
| dc.subject | Alberta | |
| dc.subject.classification | Ecology | |
| dc.title | Accurate Early Prediction of Leafy Spurge Invasion Using Species Distribution Models (SDMs) in Alberta | |
| dc.type | master thesis | |
| thesis.degree.discipline | Biological Sciences | |
| thesis.degree.grantor | University of Calgary | |
| thesis.degree.name | Master of Science (MSc) | |
| ucalgary.thesis.accesssetbystudent | I require a thesis withhold – I need to delay the release of my thesis due to a patent application, and other reasons outlined in the link above. I have/will need to submit a thesis withhold application. |