Grant: Alliance Grants
University of Waterloo
$68,382.00
Identifying climate change resilient habitat using an integrative machine learning and coupled microclimate-biophysical modelling framework
EF 2024-25
Résumé
Loss of biodiversity is occurring at unprecedented rates with an estimated 1 million species facing extinction. Canada has the second largest area of intact natural landscapes and, therefore, a responsibility and opportunity to be a global leader in biodiversity conservation. Yet, Canada is facing a biodiversity crisis that particularly targets reptiles, one of the most endangered groups of vertebrates in the world and the most endangered in Canada. Continued reptile declines are the result of multiple stressors, including land use and climate change, which continue to accelerate. Ultimately, failure to address the biodiversity crisis will be costly as declines in ecosystem biodiversity negatively impact food production, human health, and water quality, posing direct and indirect socio-economic consequences. Biodiversity loss remains a key challenge in wildlife conservation and requires transformative conservation and management strategies that cut across traditional disciplinary boundaries. Our project will leverage an open-sourced habitat mapping database currently under development in collaboration with project partners to identify (1) reproductive and (2) overwintering habitats that will be resilient to climate change, thus providing critical refugia to species at risk. Specifically, our project will (O1) develop a regional-scale microclimate model based on land cover by leveraging a habitat mapping database and by up-scaling a site-specific soil depth model; (O2) develop a regional-scale biophysical model to identify climate-resilient upland habitat that provides critical habitat for reptile reproduction (i.e., nesting); and (O3) develop a regional-scale wetlands model to prioritize protection of critical reptile overwintering habitat. Biophysical models represent the cutting edge in modelling connections between physical and biological/ecological dynamics, and their use is integral to understanding habitat conditions under present and future climate conditions. The outcomes and tools generated from this research will facilitate effective habitat management and land use planning, collaborative stewardship among partners, and enable evidence-based decision making.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
597757-2024
Name nom
Markle, Chantel CEK
Department département
Environment, Resources and Sustainability, School of
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2024
Award amount
68382
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
400
Area of application group en
Environment
Area of application group fr
Environnement
Area of application en
Environment
Area of application fr
Environnement
Research subject code
4013
Research subject group en
Earth science
Research subject group fr
Sciences de la terre
Research subject en
Earth-systems science
Research subject fr
Sciences des systèmes terrestres
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Identifying climate change resilient habitat using an integrative machine learning and coupled microclimate-biophysical modelling framework
Keywords
biophysical models; change change; habitat mapping; microclimate models; regional models; remote sensing; reptiles; species at risk; wetlands
Application summary
Loss of biodiversity is occurring at unprecedented rates with an estimated 1 million species facing extinction. Canada has the second largest area of intact natural landscapes and, therefore, a responsibility and opportunity to be a global leader in biodiversity conservation. Yet, Canada is facing a biodiversity crisis that particularly targets reptiles, one of the most endangered groups of vertebrates in the world and the most endangered in Canada. Continued reptile declines are the result of multiple stressors, including land use and climate change, which continue to accelerate. Ultimately, failure to address the biodiversity crisis will be costly as declines in ecosystem biodiversity negatively impact food production, human health, and water quality, posing direct and indirect socio-economic consequences. Biodiversity loss remains a key challenge in wildlife conservation and requires transformative conservation and management strategies that cut across traditional disciplinary boundaries. Our project will leverage an open-sourced habitat mapping database currently under development in collaboration with project partners to identify (1) reproductive and (2) overwintering habitats that will be resilient to climate change, thus providing critical refugia to species at risk. Specifically, our project will (O1) develop a regional-scale microclimate model based on land cover by leveraging a habitat mapping database and by up-scaling a site-specific soil depth model; (O2) develop a regional-scale biophysical model to identify climate-resilient upland habitat that provides critical habitat for reptile reproduction (i.e., nesting); and (O3) develop a regional-scale wetlands model to prioritize protection of critical reptile overwintering habitat. Biophysical models represent the cutting edge in modelling connections between physical and biological/ecological dynamics, and their use is integral to understanding habitat conditions under present and future climate conditions. The outcomes and tools generated from this research will facilitate effective habitat management and land use planning, collaborative stewardship among partners, and enable evidence-based decision making.