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Journal of Applied Ecology
Article . 2023 . Peer-reviewed
License: CC BY NC
Data sources: Crossref
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https://www.biorxiv.org/conten...
Article
License: CC BY NC ND
Data sources: UnpayWall
https://doi.org/10.1101/2021.1...
Article . 2021 . Peer-reviewed
Data sources: Crossref
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Selecting coral species for reef restoration

Authors: Joshua S. Madin; Michael McWilliam; Kate Quigley; Line K. Bay; David Bellwood; Christopher Doropoulos; Leanne Fernandes; +9 Authors

Selecting coral species for reef restoration

Abstract

Abstract Humans have long sought to restore species but little attention has been directed at how to best select a subset of foundation species for maintaining rich assemblages that support ecosystems, like coral reefs and rainforests, which are increasingly threatened by environmental change. We propose a two‐part hedging approach that selects optimized sets of species for restoration. The first part acknowledges that biodiversity supports ecosystem functions and services, and so it ensures precaution against loss by allocating an even spread of phenotypic traits. The second part maximizes species and ecosystem persistence by weighting species based on characteristics that are known to improve ecological persistence—for example abundance, species range and tolerance to environmental change. Using existing phenotypic‐trait and ecological data for reef building corals, we identified sets of ecologically persistent species by examining marginal returns in occupancy of phenotypic trait space. We compared optimal sets of species with those from the world's southern‐most coral reef, which naturally harbours low coral diversity, to show these occupy much of the trait space. Comparison with an existing coral restoration program indicated that current corals used for restoration only cover part of the desired trait space and programs may be improved by including species with different traits. Synthesis and applications. While there are many possible criteria for selecting species for restoration, the approach proposed here addresses the need to insure against unpredictable losses of ecosystem services by focusing on a wide range of phenotypic traits and ecological characteristics. Furthermore, the flexibility of the approach enables the functional goals of restoration to vary depending on environmental context, stakeholder values, and the spatial and temporal scales at which meaningful impacts can be achieved.

Country
Australia
Keywords

570, 590

  • BIP!
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    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).
    24
    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.
    Top 10%
    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%
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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Average
Top 10%
Green
hybrid