摘要：The Decade on Ecosystem Restoration aims to provide the means and incentives for upscaling restoration efforts worldwide. Although ecosystem restoration is a broad, interdisciplinary concept, effective ecological restoration requires sound ecological knowledge to successfully restore biodiversity and ecosystem services in degraded landscapes. We emphasize the critical role of knowledge and data sharing to inform synthesis for the most robust restoration science possible. Such synthesis is critical for helping restoration ecologists better understand how context affects restoration outcomes, and to increase predictive capacity of restoration actions. This predictive capacity can help to provide better information for evidence-based decision-making, and scale-up approaches to meet ambitious targets for restoration. We advocate for a concerted effort to collate species-level, fine-scale, ecological community data from restoration studies across a wide range of environmental and ecological gradients. Well-articulated associated metadata relevant to experience and social or landscape contexts can further be used to explain outcomes. These data could be carefully curated and made openly available to the restoration community to help to maximize evidence-based knowledge sharing, enable flexible re-use of existing data and support predictive capacity in ecological community responses to restoration actions. We detail how integrated data, analysis and knowledge sharing via synthesis can support shared success in restoration ecology by identifying successful and unsuccessful outcomes across diverse systems and scales. We also discuss potential interdisciplinary solutions and approaches to overcome challenges associated with bringing together subfields of restoration practice. Sharing this knowledge and data openly can directly inform actions and help to improve outcomes for the Decade on Ecosystem Restoration.
