QCBS Working Groups

Working Group 23

One Model: Co-developing an integrated global platform to forecast and manage biodiversity and ecosystem services under climate change

As global climate change accelerates, we urgently need to develop accurate predictions about biological responses to guide effective mitigation strategies for protecting biodiversity and ecosystem services. Most predictive models, however, are correlative and exclude important biological mechanisms such as demography, dispersal, evolution, and species interactions that have proven important in mediating past and present responses to climate change. The lack of biological realism in current predictive models calls into question our ability to implement effective solutions to mitigate biodiversity loss and its associated impacts. To address this 21st century challenge, biologists are developing tools that incorporate the key biological processes needed to improve predictive accuracy. Although several such models exist, they have largely developed in isolation and focus on a subset of key processes. We need one model that synthesizes important mechanistic submodels, is flexible enough to be applied to a range of systems and questions, and can integrate feedbacks with climate and land use models. We seek to co-develop One Model, a hub to integrate biological, climate, land use, and ecosystem service models in one comprehensive, adaptable, and readily useable platform. Consequently, One Model would allow governments and non-profits to assess effective conservation strategies to maintain biodiversity and ecosystem services. Although we focus on climate change, the platform would be adaptable to any environmental change. We would develop the platform with applied end users in mind. First, we would assemble implementation partners to co-design and develop common objectives and principles. Second, we would integrate mechanistic submodels into one flexible and modular biodiversity model. Third, we would bring key developers of ecosystem, land use, and climate models together with biological modelers to co-formulate an integrated socio-ecological platform. Fourth, we would apply One Model to generate two proofs of principle by projecting malaria and biodiversity loss in Africa. As climate change accelerates, we still lack the means to predict biodiversity and ecosystem changes with acceptable levels of accuracy. By integrating important mechanisms and their linkages into a single publicly available platform, we can substantially enhance our ability to mitigate future changes to global biodiversity and its services.


Andrew Gonzalez (McGill University), Timothée Poisot (Université de Montréal), Pedro Peres-Neto (Concordia University), Patrick M.A. James (Université de Montréal), Andrew Hendry (McGill University), Dominique Gravel (Université de Sherbrooke), Luc De Meester (KU Leuven, Belgium), Cécile Albert (McGill University),


Title Event Number of Participants Date