Research articlePredicting the impact of sea-level rise on intertidal rocky shores with remote sensing
Introduction
Climate change threatens marine ecosystems at a global scale through changes in temperature, ocean acidification and sea-level rise (Brierley and Kingsford, 2009; Doney et al., 2012; Hoegh-Guldberg and Bruno, 2010). Sea-level rise is a consequence of thermal expansion of the ocean and the melting of water stored in glaciers and ice-caps (Church et al., 2011; IPCC, 2013). Under climate change, sea-level rise has been projected to exceed previously observed rates (IPCC, 2013), but predictions for the level of this rise vary depending on the amount of anthropogenic contributions (in the form of emissions and land-use change) to radiative forcing. Radiative forcing is a measure of change in the balance between incoming solar radiation and outgoing infrared radiation due to a forcing agent (IPCC, 2013). Four global scenarios developed by the International Panel for Climate Change (IPCC) are used to represent the effect of radiative forcing in 2100, relative to preindustrial levels: RCP2.6, RCP4.5, RCP6.0, RCP8.5 (IPCC, 2013). Under these scenarios, global sea-level rise is expected to increase at a rate of 4.4, 6.1, 7.4 and 11.2 mm/year (values represent median values), respectively (IPCC, 2013).
Sea-level rise will have the greatest ecological impact along low lying coastlines through increasing inundation of the intertidal zone, which supports important ecological assemblages such as mangroves, seagrasses, saltmarshes and rocky shores (FitzGerald et al., 2008; Nicholls and Cazenave, 2010; Nicholls et al., 1999). Apart from providing habitat for intertidal biodiversity, these habitats provide a buffer from destructive ocean forces, reducing the impact of storm events and mitigating erosion (Gedan et al., 2011; Shepard et al., 2011; Spalding et al., 2014). It is therefore important to quantify the risks to important coastal habitats from sea-level rise. In this study we used the Hawkesbury Shelf Marine Bioregion as a test region and applied remote sensing to investigate the threat of sea-level rise to intertidal rocky shores (Fig. 1).
Intertidal rocky shores are the most common coastal habitat worldwide and are ecologically valuable (Thompson et al., 2002). They support a diverse array of species, which is attributed to the high structural complexity of rocky shores (Blanchard and Bourget, 1999; Chapman, 2003; Sebens, 1991). Intertidal rocky shores and the communities living on them provide numerous ecosystem functions and services. Filter-feeders such as oysters improve water quality and further promote biodiversity by creating additional habitat for other intertidal organisms (Coen et al., 2007; Grabowski et al., 2012). Intertidal rocky shore also act as important nursery and feeding ground for fish during high tide and shorebirds during low tide (Burrows et al., 1999; Cantin et al., 1974; Rangeley and Kramer, 1995). Yet rocky shores are also amongst the most vulnerable marine systems, facing a variety of anthropogenically induced threats (Halpern et al., 2007; Thompson et al., 2002).
Since alternating periods of emersion and submersion is the key physical driver on intertidal rocky shores (Menge and Branch, 2001), rapid changes in sea-level can have particularly severe consequences for the availability of habitat. In Scotland, a study used existing maps of rocky shorelines (a triangular irregular network of contour data) found that a rise in sea-level between 0.3 and 1.9 m will, in some areas, result in a loss of 10%–50% of rocky shore extent (Jackson and McIlvenny, 2011). Furthermore, under a 1.9 m sea-level rise scenario, slopes are predicted to steepen in these areas, with at least 50% of rocky shores becoming vertical (≥45°) (Jackson and McIlvenny, 2011). The transition to a steeper relief from a flat rocky shore may force organisms into greater densities and increase pressure from competition, particularly in areas where static vertical barriers such as seawalls prevent a landward migration (Pontee, 2013). Yet little is known about the effect of sea-level rise on intertidal rocky shores in other areas of the world or in the context of multiple climate change scenarios. Sea-level rise is an inevitable consequence of climate change, and understanding the possible negative consequences is essential to inform conservation and mitigate impacts. We take a novel approach to understand this change and its potential impacts by combining remote sensing data (LiDAR) and the IUCN Red List of Ecosystems criteria. Remote sensing provides solutions to rapidly collect geospatial data over large spatial scales, whereas the IUCN Red List of Ecosystem criteria provide a consistent framework for ecosystem risk assessments that can be applied worldwide.
Here, by following the framework of the IUCN Red List of Ecosystems criteria (Keith et al., 2013), we assessed the current status of ~200 km of coastline within the Hawkesbury Shelf Marine Bioregion in order to estimate the status of intertidal rocky shores of the entire bioregion and discuss potential effects of sea-level rise on associated biota. Under the IUCN system, the status of an ecosystem is assessed against five criteria, with the final ecosystem status determined based on the highest risk returned for any one category. We focus on criterion C2, which involves an assessment of the extent and relative severity of habitat degradation in the next 50 years. We used a high-resolution LiDAR (light detection and ranging) survey of coastal elevation to estimate the net loss/gain of intertidal rocky shores under sea-level rise scenarios.
Section snippets
IUCN red list of ecosystems
The IUCN Red List of Ecosystems was established to fill the demand for biodiversity assessments that address levels of biodiversity above those of single species, such as those of ecosystems (Rodríguez et al., 2011). It assesses the risk of an ecosystem collapse, which occurs when an ecosystem loses its defining biotic or abiotic features, and the characteristic native biota and ecosystem processes are lost (Keith et al., 2013). The framework of the IUCN Red List of Ecosystems to assess the
Net loss of intertidal rocky shore extent
The current area of intertidal rocky shores is estimated at 374,689 m2 along approximately 50 km of rocky shore within the assessed 210 km of the NSW coastline. However, the area is likely to be underestimated due to the lack of reliable elevation data available in the low and mid-intertidal zones (see Methods: Spatial analysis).
Model predictions based on median sea-level rise rates suggest that the available habitat for intertidal organisms will be reduced over the next 50 years at an overall
Discussion
Coastal ecosystems are changing worldwide as a result of climate change, including sea-level rise. Here we quantified the sea-level rise threat to rocky intertidal communities along ~200 km of coastline in SE Australia using the criteria applied in the IUCN Red List of Ecosystems. Under the IUCN Criterion C2, which considers the degradation of an abiotic variable over the next 50 years, we found that intertidal rocky shores in this bioregion should be classified as ‘near threatened’ due to the
Conclusion
This study highlighted the high degree of risk to intertidal rocky shore environments from sea-level rise. We found that the IUCN threshold for ‘vulnerable’ classification is not exceeded for median estimates of sea-level rise in the next 50 years, but it is certain that rising sea-levels will increase the inundation of rocky shores into the future. The overall status of ‘near threatened’ highlights the need for ongoing assessment of this habitat such that proactive management and conservation
CRediT authorship contribution statement
Nina Schaefer: Conceptualization, Methodology, Formal analysis, Writing - original draft. Mariana Mayer-Pinto: Conceptualization, Writing - review & editing, Supervision. Kingsley J. Griffin: Methodology, Formal analysis, Visualization, Writing - review & editing. Emma L. Johnston: Conceptualization, Writing - review & editing, Supervision, Funding acquisition. William Glamore: Methodology, Resources, Writing - review & editing. Katherine A. Dafforn: Conceptualization, Writing - review &
Acknowledgements
We thank Valentin Heimhuber for his assistance and advice on GIS processing. The authors further thank three anonymous reviewers and the editor for their comments, which significantly improved the manuscript. The authors declare no conflicts of interest. This research was funded by an Australian Research Council Linkage Grant LP140100753 awarded to Katherine A. Dafforn and Emma L. Johnston.
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