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Kierann Santala, Françoise Cardou, Denys Yemshanov, Isabelle Aubin & coll.
Successful restoration must address multiple goals for ecosystem service delivery and ecosystem functionality. This is particularly true in highly impacted socio-ecological systems, such as industrial landscapes, where practitioners aim to kickstart ecosystem recovery towards desired ecosystem states by balancing local ecological imperatives, uncertainty associated with climate change and the socio-economic and environmental values of stakeholders. We present a tool to assist managers in developing restoration strategies that can accommodate these multiple goals. We use the case of Cu-Ni smelter damaged forests of Sudbury (Canada) to demonstrate how this tool allows managers to identify species mixtures that optimize the delivery of targeted ecological functions and services, as captured by functional traits, under a set of economic and logistical constraints. Following a plant community engineering approach, we use an economic optimization model to generate different costeffective combinations of species that optimise desired restoration goals. These virtual plant assemblages can serve as a “thinking tool” to inform planting strategies. What should we plant now so future forests will provide the desired ecosystem services? In the Sudbury system, stakeholders prioritized a range of ecosystem services that included rapid vegetation cover growth and soil building. Importantly, the weight attributed to each ecological goal or economic constraint led to contrasted optimal plant assemblages. This finding demonstrates the need to balance competing objectives in developing species mixtures for restoration, and functional traits can help us capture these tradeoffs. We discuss potential application of this approach to other socio-economic systems.
Conference Presentation, SER2021
Pre-approved for CECs under SER's CERP program