OVERVIEW
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The main objective of ResNet’s Theme 3 is to provide guidelines on how to monitor and understand trends in ecosystem services (ES) to guide management for their long-term sustainability.
However, to do this we must first understand how natural and anthropogenic drivers affect the supply of ES. Our team developed a social-ecological network approach to the detection-attribution of ES trends, using the essential ecosystem service variables (EESVs) framework, proposed by GEO BON. EESVs combine social, ecological, and economic dimensions of ES and evaluate trends in ES based on change in these different dimensions. This framework assesses spatio-temporal change and explicitly estimates the magnitude and direction of ecosystem service trends across scales and governance. Our approach couples flexible analytical tools (e.g. Bayesian network models, intervention analysis), with a range of datasets capturing the ecological and |
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social dynamics of ecosystem services. Our team has assessed trends in multiple ecosystem services in Canada (e.g. air quality, fisheries, carbon storage, wildlife viewing, recreation, maple syrup production) to understand how monitoring can detect change and to attribute causes for the detected trends to guide their management.
The guidelines that Theme 3 is preparing will include lessons learned and highlight some of the pitfalls, challenges, and solutions required to monitor changes in ecosystem services. Theme 3 will provide a series of actions intended to foster the sustainability of ecosystem services in Canada and abroad.
The guidelines that Theme 3 is preparing will include lessons learned and highlight some of the pitfalls, challenges, and solutions required to monitor changes in ecosystem services. Theme 3 will provide a series of actions intended to foster the sustainability of ecosystem services in Canada and abroad.
THEME 3 TEAM
Andrew Gonzalez co-lead McGill University |
Marie-Josée Fortin she/her CO-LEAD University of Toronto |
Apex Resource Management Solutions PARTNER ORGANIZATION |
Peter Rodriguez he/him phD student University of Toronto |
Colin Daniel he/him COLLABORATOR Apex Resource Management Solutions 
Étienne Laliberté he/him COLLABORATOR University of Montréal 
Carina Firkowski she/her ALUM |
Flavio Affinito phd student McGill University 
Dominique Gravel COLLABORATOR University of Sherbrooke |
Amanda Schwantes Postdoctoral Researcher University of Toronto 
Graham MacDonald COLLABORATOR McGill University |
Sebastien Theis he/him POST DOCTORAL RESEARCHER University of Toronto 
Joseph Bennett he/him COLLABORATOR Carleton University |
FEATURED PUBLICATIONS
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Monitoring social–ecological networks for biodiversity and ecosystem services in human-dominated landscapes
Firkowski C.R., Schwantes A.M., Fortin M.-J. and Gonzalez A.
The demand the human population is placing on the environment has triggered accelerated rates of biodiversity change and created trade-offs among the ecosystem services we depend upon. Decisions designed to reverse these trends require the best possible information obtained by monitoring ecological and social dimensions of change. Here, we conceptualize a network framework to monitor change in social–ecological systems. We contextualize our framework within Ostrom’s social–ecological system framework and use it to discuss the challenges of monitoring biodiversity and ecosystem services across spatial and temporal scales. We propose that spatially explicit multilayer and multiscale monitoring can help estimate the range of...
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A comparison of approaches to quantify carbon for ecosystem service assessments through time
Schwantes A.M., Firkowski C.R., Fortin M.-J., Gonzalez A., and Rodriguez P. S.,
Monitoring of global climate regulation ecosystem services is needed to inform national accounts, meet emission targets, and evaluate nature-based climate solutions. As carbon monitoring is context-dependent, the most useful methodological approach will depend on the spatial extent and resolution, temporal frequency, baseline, available data, funding, and dominant drivers of change, all of which will impact results and interpretation. Here, focusing on above and belowground carbon storage and sequestration, we review four groups of methods for estimating trends in carbon over time: (1) field-based measurements, (2) land cover maps with reference carbon values by land cover type, (3) statistical and machine learning models linking field measurements to remotely sensed data, and (4) mass balance models representing key carbon pools and flows between them
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