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Title (Primary) The power of data synthesis to shape the future of the restoration community and capacity
Author Ladouceur, E.; Shackelford, N.;
Journal Restoration Ecology
Year 2021
Department iDiv; PHYDIV;
Volume 29
Issue 1
Language englisch;
POF III (all) T11;
Keywords database, Decade on Ecosystem Restoration, global analyses, meta-analysis, networks, synthesis
Abstract Restoration efforts will be taking place over the next decade(s) in the largest scope and capacity ever seen. Immense commitments, goals, and budgets are set, with impactful wide‐reaching potential benefits for people and the environment. These are ambitious aims for a relatively new branch of science and practice. It is time for restoration action to scale up, the legacy of which could impact over 350 million hectares targeted for the U.N. Decade on Ecosystem Restoration. However, restoration still proceeds on a case‐by‐case, trial by error basis and restoration outcomes can be variable even under similar conditions. The ability to put each case into context—what about it worked, what did not, and why—is something that the synthesis of data across studies can facilitate. The link between data synthesis and predictive capacity is strong. There are examples of extremely ambitious and successful efforts to compile data in structured, standardized databases which have led to valuable insights across regional and global scales in other branches of science. There is opportunity and challenge in compiling, standardizing, and synthesizing restoration monitoring data to inform the future of restoration practice and science. Through global collation of restoration data, knowledge gaps can be addressed and data synthesized to advance toward a more predictive science to inform more consistent success. The interdisciplinary potential of restoration ecology sits just over the horizon of this decade. Through truly collaborative synthesis across foci within the restoration community, we have the opportunity to rapidly reach that potential and achieve extraordinary outcomes together.
ID 23725
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=23725
Ladouceur, E., Shackelford, N. (2021):
The power of data synthesis to shape the future of the restoration community and capacity
Restor. Ecol. 29 (1), e13251