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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Journal of Environme...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Environmental Management
Article . 2020 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Predicting the impact of sea-level rise on intertidal rocky shores with remote sensing

Authors: Emma L. Johnston; Nina Schaefer; Kingsley J. Griffin; Katherine A. Dafforn; Katherine A. Dafforn; William Glamore; Mariana Mayer-Pinto;

Predicting the impact of sea-level rise on intertidal rocky shores with remote sensing

Abstract

Sea-level rise is an inevitable consequence of climate change and threatens coastal ecosystems, particularly intertidal habitats that are constrained by landward development. Intertidal habitats support significant biodiversity, but also provide natural buffers from climate-threats such as increased storm events. Predicting the effects of climate scenarios on coastal ecosystems is important for understanding both the degree of habitat loss for associated ecological communities and the risk of the loss of coastal buffer zones. We take a novel approach by combining remote sensing with the IUCN Red List of Ecosystem criteria to assess this impact. We quantified the extent of horizontal intertidal rocky shores along ~200 km of coastline in Eastern Australia using GIS and remote-sensing (LiDAR) and used this information to predict changes in extent under four different climate change driven sea-level rise scenarios. We then applied the IUCN Red List of Ecosystems Criterion C2 (habitat degradation over the next 50 years based on change in an abiotic variable) to estimate the status of this ecosystem using the Hawkesbury Shelf Marine Bioregion as a test coastline. We also used four individual rocky shores as case studies to investigate the role of local topography in determining the severity of sea-level rise impacts. We found that, if the habitat loss within the study area is representative of the entire bioregion, the IUCN status of this ecosystem is 'near threatened', assuming that an assessment of the other criteria would return lower categories of risk. There was, however, high spatial variability in this effect. Rocky shores with gentle slopes had the highest projected losses of area whereas rocky shores expanding above the current intertidal range were less affected. Among the sites surveyed in detail, the ecosystem status ranged from 'least concern' to 'vulnerable', but reached 'endangered' under upper estimates of the most severe scenario. Our results have important implications for conservation management, highlighting a new link between remote sensing and the IUCN Red List of Ecosystem criteria that can be applied worldwide to assess ecosystem risk to sea-level rise.

Keywords

Conservation of Natural Resources, Climate Change, Australia, Sea Level Rise, Remote Sensing Technology, Ecosystem

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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!
16
Top 10%
Average
Top 10%