Applying systematic conservation planning to improve the allocation of restoration actions at multiple spatial scales. Issue 5 (15th June 2021)

• Record Type: Journal Article
• Authors: Gilby, Ben L.; Olds, Andrew D.; Brown, Christopher J.; Connolly, Rod M.; Henderson, Christopher J.; Maxwell, Paul S.; Schlacher, Thomas A.
• Is Part Of: Restoration ecology. Volume 29:Issue 5(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-06-15
• Subjects: coastal ecosystems -- feasibility -- mangroves -- oyster reefs -- seagrass -- spatial planning; Restoration ecology -- Periodicals; Reclamation of land -- Environmental aspects -- Periodicals; 333.7153
• DOI: 10.1111/rec.13403
• Languages: English
• ISSNs: 1061-2971

Abstract

Abstract : Ecological restoration is increasingly being upscaled to larger spatial scales of tens to hundreds of kilometers. Yet the complex logistics and high costs of ecological restoration mean that actions must be placed strategically at local scales of tens of meters to maximize ecological benefits and reduce socioeconomic costs. Despite the purported use of systematic planning tools for allocating restoration effort, the uptake and implementation of data‐driven restoration planning and ecological goal setting remains poor in many restoration programs. Here we demonstrate how the sequential workflows of systematic conservation planning can be translated to restoration at two spatial scales to enhance estuarine fisheries in eastern Australia. We select estuaries where restoration is feasible and recommended based on quantitative regional ecological goals (i.e. regional‐scale prioritization), and then identify potential restoration sites at smaller spatial scales within estuaries based on the principles of spatial ecology to ensure that the success and benefits of restoration are maximized (i.e. local‐scale prioritization). At the regional scale, we identified four levels of restoration priorities (very high, high, intermediate, and low) using quantitative ecological goals and the current ecological understanding of each system. At the local scale, we used spatially explicit Bayesian belief networks to identify sites that maximize restoration outcomes based on the environmental niche of habitat‐forming species and the spatial configuration of habitats that maximizes their use by fish. We show that using systematic frameworks can become an essential tool to optimize restoration investments at multiple scales as efforts upscale globally.