Abstract
Human activities are altering the structure of ecological communities, often favouring generalists over specialists. For reef fishes, increasingly degraded habitats and climate-driven range shifts may independently augment generalization, particularly if fishes with least-specific habitat requirements are more likely to shift geographic ranges to track their thermal niche. Using a unique global dataset on temperate and tropical reef fishes and habitat composition, we calculated a species generalization index that empirically estimates the habitat niche breadth of each fish species. We then applied the species generalization index to evaluate potential impacts of habitat loss and range shifts across large scales, on coral and rocky reefs. Our analyses revealed consistent habitat-induced shifts in community structure that favoured generalist fishes following regional coral mortality events and between adjacent sea urchin barrens and kelp habitats. Analysis of the distribution of tropical fishes also identified the species generalization index as the most important trait in predicting their poleward range extent, more so than body or range size. Generalist tropical reef fishes penetrate further into subtropical and temperate zones than specialists. Dynamic responses of reef fishes to habitat degradation imply loss of specialists at local scales, while generalists will be broadly favoured under intensifying anthropogenic pressures. An increased focus on individual requirements of specialists could provide useful guidance for species threat assessments and conservation actions, while ecosystem and multi-species fisheries models should recognize increasing prevalence of generalists.
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Data availability
Raw data from the RLS programme are accessible through a live data portal via the RLS website www.reeflifesurvey.com. SGI values will be accessible through the RLS Reef Species of the World online species database by 1 November 2020 (https://reeflifesurvey.com/species/search.php).
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Acknowledgements
We thank the many RLS divers and scientific collaborators who assisted with field surveys, A. Cooper, J. Berkhout and E. Clausius at the University of Tasmania for logistics and data management, and D. Ceccarelli, E. Oh, A. Cresswell and J. Duggan for analysis of photoquadrats. We also thank N. Barrett, J. Stuart-Smith, S. Baker and T. Bird for further support in the development of RLS, fieldwork and concepts explored in the paper. Development of RLS was supported by the former Commonwealth Environment Research Facilities Program, while analyses were supported by the Marine Biodiversity Hub, a collaborative partnership supported through funding from the Australian Government’s National Environmental Science Program, and by the Australian Research Council. Funding and support for GBR field surveys was provided by The Ian Potter Foundation and Ningaloo surveys by the Western Australian State NRM. RLS data management is supported by Australia’s Integrated Marine Observing System. The Integrated Marine Observing System is enabled by the National Collaborative Research Infrastructure Strategy. It is operated by a consortium of institutions as an unincorporated joint venture, with the University of Tasmania as lead agent.
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R.D.S.-S. conceived the study and drafted the manuscript, G.J.E. and R.D.S.-S. led data collection, C.M. and R.D.S.-S. developed the SGI with input from colleagues, C.M. and A.E.B. analysed the data, and all authors contributed to the writing.
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Extended data
Extended Data Fig. 1 Habitat categories and representation across realms.
Numbers are average % cover of habitat categories.
Extended Data Fig. 2 Distribution of sites with photoquadrat data (n = 4,070 transects) used for quantifying habitat volume.
Site symbols are coloured by realm.
Extended Data Fig. 3 The global habitat volume captured by surveyed reefs.
Principal Coordinates Analysis of habitat structure scored from photoquadrats on 4,070 reef surveys (a). The primary axis of variation from macroalgae (kelps and fucoid algae) to corals explains 22% (PCO1), with the subsequent axes explaining 19% (PCO2) and 17% (PCO3) of total variation. Two dimensional representations of PCO1 versus PCO2 (b), and PCO1 versus PCO3 (c) distinguish temperate (black symbols), tropical (red symbols) sites.
Extended Data Fig. 4 CGI change at sites affected by disturbance (from Fig. 2a) relates to gains in generalist species and losses of specialist species (that is, species turnover).
The Y-axis is the mean SGI of species which were only recorded at a site prior to disturbance minus the mean SGI of those only recorded at that site following the disturbance. Coloured quadrants therefore indicate sites with a net signal of generalisation (blue quadrant, bottom right) and sites with a net signal of specialisation (red, top left) arising from species replacement.
Extended Data Fig. 5 Model summary results plotted in Figs. 2 and 3.
Bold terms are significant.
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Stuart-Smith, R.D., Mellin, C., Bates, A.E. et al. Habitat loss and range shifts contribute to ecological generalization among reef fishes. Nat Ecol Evol 5, 656–662 (2021). https://doi.org/10.1038/s41559-020-01342-7
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DOI: https://doi.org/10.1038/s41559-020-01342-7
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