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Moving restoration ecology forward with combinatorial approaches

pmid: 38822568
AbstractOur current planetary crisis, including multiple jointly acting factors of global change, moves the need for effective ecosystem restoration center stage and compels us to explore unusual options. We here propose exploring combinatorial approaches to restoration practices: management practices are drawn at random and combined from a locally relevant pool of possible management interventions, thus creating an experimental gradient in the number of interventions. This will move the current degree of interventions to higher dimensionality, opening new opportunities for unlocking unknown synergistic effects. Thus, the high dimensionality of global change (multiple jointly acting factors) would be more effectively countered by similar high‐dimensionality in solutions. In this concept, regional restoration hubs play an important role as guardians of locally relevant information and sites of experimental exploration. Data collected from such studies could feed into a global database, which could be used to learn about general principles of combined restoration practices, helping to refine future experiments. Such combinatorial approaches to exploring restoration intervention options may be our best hope yet to achieve decisive progress in ecological restoration at the timescale needed to mitigate and reverse the most severe losses caused by global environmental change.
- Cranfield University United Kingdom
- Berlin Brandenburg Institute of Advanced Biodiversity Research Germany
- Freie Universität Berlin Germany
- Cranfield University United Kingdom
Conservation of Natural Resources, Ecology, Climate Change, Ecosystem, Environmental Restoration and Remediation
Conservation of Natural Resources, Ecology, Climate Change, Ecosystem, Environmental Restoration and Remediation
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).5 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
