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Grant: Canada Research Chairs

University of New Brunswick

$45,000.00

Ecological Modelling

FY 2024-25

Summary
Marine ecosystems are undergoing novel and unprecedented changes due to climate change and other human-induced stressors. To generate effective conservation plans for safeguarding our marine future, scientists must first understand how a multitude of factors are coming together to impact marine ecosystems. This research program will apply contemporary inference frameworks to quantify how social and environmental factors are impacting imperilled marine systems, under three objectives: (1) community-engaged causal analysis of marine and coastal ecosystems, (2) assessing fisheries recovery through causal discovery and causal effect estimation, and (3) quantifying impacts of global marine change. Projects under objective 1 will represent the first set of research projects that will integrate community-engaged research with contemporary causal modelling to gain insight into local marine and coastal ecosystems. Here, interdisciplinary researchers and local community members (including youth, fishers, Indigenous knowledge holders, and conservation practitioners) will co-generate causal diagrams that integrate a plurality of ecological knowledge systems, which in turn will guide the development of causal models that uncover the mechanisms impacting local ecosystems. Projects under objective 2 will apply contemporary approaches in causal discovery (e.g., constraint-based, asymmetry-based, and score-based approaches) and causal effect estimation (e.g., structural causal model adapted to time-series data) on fisheries time-series data to help set conservation priorities that can rebuild recovering fisheries across Atlantic Canada. Projects under objective 3 will integrate causal inference frameworks with artificial intelligence and non-parametric statistical techniques to harness the full potential of big data in marine ecology, uncovering causal mechanisms that are driving marine changes at global scales. By centering causal inference in marine research, this program will cut across multiple processes, scales, and disciplines, providing a coherent framework for thinking about ecological complexity and generating informed marine conservation solutions. Ultimately, research arising from this program will accelerate the depth and pace at which we understand the underlying mechanisms driving marine ecosystem change, while simultaneously providing methodological advancements that every ecologist can apply to answer fundamental causal questions in nature.
Program
Canada Research Chairs
Location
New Brunswick, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
CRC-2023-00248
Name nom
Arif, Suchinta
Department département
Biology - Dalhousie University
Organization id
75
Institution établissement
University of New Brunswick
Province en
New Brunswick
Province fr
Nouveau-Brunswick
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2023
Award amount
45000
Program id
CRC
Program name en
Canada Research Chairs
Program name fr
Chaires de recherche du Canada
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
9998
Committee name en
Canada Research Chair Selection Committee
Committee name fr
Comité de sélection des Chaires de recherche du Canada
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
9999
Research subject group en
Not available
Research subject group fr
Non disponible
Research subject en
Not available
Research subject fr
Non disponible
Field of research list codes
RDF1060305
Field of research list names en
Marine ecology (including marine ichthyology)
Field of research list names fr
Écologie marine (y compris l'ichtyologie marine)
Socioeconomic objective list codes
RDS10805
Socioeconomic objective list names en
Fisheries (including aquaculture and wild caught)
Socioeconomic objective list names fr
Pêches (y compris l'aquaculture et les poissons capturés à l'état sauvage)
Application title
Ecological Modelling
Keywords
causal inference; causal discovery; big data; marine conservation; fisheries; sustainability
Application summary
Marine ecosystems are undergoing novel and unprecedented changes due to climate change and other human-induced stressors. To generate effective conservation plans for safeguarding our marine future, scientists must first understand how a multitude of factors are coming together to impact marine ecosystems. This research program will apply contemporary inference frameworks to quantify how social and environmental factors are impacting imperilled marine systems, under three objectives: (1) community-engaged causal analysis of marine and coastal ecosystems, (2) assessing fisheries recovery through causal discovery and causal effect estimation, and (3) quantifying impacts of global marine change. Projects under objective 1 will represent the first set of research projects that will integrate community-engaged research with contemporary causal modelling to gain insight into local marine and coastal ecosystems. Here, interdisciplinary researchers and local community members (including youth, fishers, Indigenous knowledge holders, and conservation practitioners) will co-generate causal diagrams that integrate a plurality of ecological knowledge systems, which in turn will guide the development of causal models that uncover the mechanisms impacting local ecosystems. Projects under objective 2 will apply contemporary approaches in causal discovery (e.g., constraint-based, asymmetry-based, and score-based approaches) and causal effect estimation (e.g., structural causal model adapted to time-series data) on fisheries time-series data to help set conservation priorities that can rebuild recovering fisheries across Atlantic Canada. Projects under objective 3 will integrate causal inference frameworks with artificial intelligence and non-parametric statistical techniques to harness the full potential of big data in marine ecology, uncovering causal mechanisms that are driving marine changes at global scales. By centering causal inference in marine research, this program will cut across multiple processes, scales, and disciplines, providing a coherent framework for thinking about ecological complexity and generating informed marine conservation solutions. Ultimately, research arising from this program will accelerate the depth and pace at which we understand the underlying mechanisms driving marine ecosystem change, while simultaneously providing methodological advancements that every ecologist can apply to answer fundamental causal questions in nature.