Satellite imaging coral reef resilience at regional scale. A case-study from Saudi Arabia

https://doi.org/10.1016/j.marpolbul.2012.03.003Get rights and content

Abstract

We propose a framework for spatially estimating a proxy for coral reef resilience using remote sensing. Data spanning large areas of coral reef habitat were obtained using the commercial QuickBird satellite, and freely available imagery (NASA, Google Earth). Principles of coral reef ecology, field observation, and remote observations, were combined to devise mapped indices. These capture important and accessible components of coral reef resilience. Indices are divided between factors known to stress corals, and factors incorporating properties of the reef landscape that resist stress or promote coral growth. The first-basis for a remote sensed resilience index (RSRI), an estimate of expected reef resilience, is proposed. Developed for the Red Sea, the framework of our analysis is flexible and with minimal adaptation, could be extended to other reef regions. We aim to stimulate discussion as to use of remote sensing to do more than simply deliver habitat maps of coral reefs.

Highlights

► Spatially estimating a proxy for coral reef resilience from remote sensing data. ► Develop indices of coral stress from satellite data and apply using GIS. ► Propose the first-basis for a remote sensed resilience index (RSRI). ► RSRI provides an estimate of expected reef resilience. ► The framework presented is flexible and may be adapted to other reef regions.

Introduction

The long term viability of even the most remote and isolated coral reefs can no longer be assured. Corals lack the capacity to escape inclement conditions and must adapt to, or resist, change. Rapid, dramatic and seemingly intractable changes to reef communities have been attributed to a host of stressors; extreme thermal events, fishing pressure, sediment load, and physical destruction (Hughes and Connell, 1999, Wilkinson, 1999). Some reefs however appear to be more resilient than others (Nyström and Folke, 2001). Understanding coral resilience has been a rising theme of reef science. Resilience has three critical components; (1) biodiversity, (2) connectivity and (3) spatial heterogeneity (Nyström et al., 2008). Biodiversity is believed to confer resilience through redundancy within important ecosystem functions and feedbacks. Connectivity between reef systems facilitates the ‘rescue’ of one reef by another following disturbance. Spatial heterogeneity refers to the uneven distribution of resilience components over a reef area.

For use in management, Nyström et al. (2008) recognize the need to develop methods to observe resilience. With this goal in mind, Obura et al. (2009) strive to measure aspects of ecosystems that are important for coral reef resilience. Building forward from previous work, we propose a means of quantifying, what we consider to be, the most accessible and important components of coral reef resilience using remote sensing data. By contrast, conventional SCUBA-based surveys are ill suited to regional-scale assessment. We believe that satellite remote sensing can deliver measures relevant to coral reef resilience across vast geographic areas.

As Obura et al. (2009) note, both positive and negative factors are important to coral reef resilience. A path towards spatial assessment of positive factors has been established, for example by work of Harbourne et al. (2006) who used remote sensing maps to access pertinent information of coral reef diversity. Dalleau et al. (2010) built on this concept to test the efficiency of reef habitats as surrogates of species-level diversity. Wedding et al. (2011) describe the use of map-derived spatial metrics to analyze patterns and processes in marine systems. Negative factors, referred to variously as ‘stress’ or ‘threat’, have also been assessed using both remote sensing and map-based techniques (Halpern et al., 2008, Maina et al., 2008, McPherson et al., 2008, Mumby et al., 2011, Burke et al., 2011). However as Halpern et al. (2008) note, such studies of marine threats suffer from a lack of context and a need for ‘research on the most basic information, such as distribution of habitat types, and whether and how different anthropogenic drivers interact’. In short, while map-based methods have been advanced for considering both positive and negative resilience factors, they have not been addressed in concert.

Herein, we use remote sensing to consider coral stress factors and seascape properties that may confer resilience. Using a geographic information system (GIS) approach, our study focuses on reef environments of the Saudi Arabian Red Sea. Freely available satellite data (NASA, Google Earth) were assembled, along with archived and tasked imagery from the QuickBird commercial satellite (DigitalGlobe Inc.). The biological and physical characteristics of reef landscapes that we consider to promote resilience were mapped. Indicators for coral reef stress were derived from satellite across a large part of the Saudi Red Sea, and used in a more focused assessment of reef resilience in five study sites. These sites span 20,000 sq km and include approximately half the shallow (<20 m) water habitat of the Saudi Red Sea. Sites encompass the spectrum of reef types encountered in the region and are distributed across the latitudinal range of the Red Sea. Coral reef habitats in the five sites were mapped. These maps break new ground as they comprise a geographic area comparable to some of the largest reef mapping efforts (Rohmann et al., 2005), but at meter-scale resolution consummate with the finest achieved from comparable sensors (Purkis et al., 2006, Roelfsema and Phinn, 2010, Scopélitis et al., 2010).

The goals of this paper are twofold. First, to develop a methodology for assimilating regional-scale data into a potential measure of remote sensed reef resilience. Second, to use this measure to assess the differences within sites spread along the 1800 km coastline of the Red Sea. Through this approach we hope to stimulate debate and new thinking about an enhanced role for remote sensing in reef monitoring.

Section snippets

Red Sea study sites

The Red Sea is oriented along an approximate north-west to south-east axis; it is ∼2000 km long, up to 350 km wide and 2000 m deep. We surveyed five regions of the Saudi Red Sea; from north to south, Ras Al-Qasabah, Al Wajh, Yanbu, Farasan Banks, and Western Farasan Islands (Fig. 1).

Measures of stress and the coral reef environment

Obura et al. (2009) state, ‘ecological resilience relates to the entire scope of positive and negative factors affecting a community’. Such a definition is clearly intractable. Any method of resilience assessment must

Remote sensed coral stress in Saudi Arabia

According to our analysis, most Saudi reefs experience some fishing pressure (RFI, Fig. 9a). It is greatest in the waters offshore Jizan and the Farasan Islands. Here, large industrial and traditional fishing fleets are moored. Moderate pressure also occurs on reefs of the central Red Sea (Um Lujh-Al Lith). As would be expected, the highest development stress is seen for reef sites offshore of the large cities Jeddah, Jizan and Yanbu (DI, Fig. 9b). Overall though, most reefs experience very

Discussion

The data presented represent the most expansive and spatially coherent assessment of reefs in the Red Sea to date. This work is underpinned by the theory that resilience of corals can be considered as a product of, what we term, ‘landscape’ and ‘stress’ factors, and that some of the most important of these can be assessed using remote sensing. With reference to principles rooted in the literature, we formulate a series of indices to capture landscape and stress factors. Terms and values used in

Conclusion

Though we have discussed avenues for further development and refinement, the primary goals of this work have been attended to. Remote sensing provides spatially continuous assessment at a regional-scale. In our study, high spatial resolution coral reef habitat mapping underpins a better understanding of the landscape. Based on factors relevant to coral resilience in the Saudi Red Sea, we have provided a flexible framework that uses GIS to rationalize stress and landscape factors within a single

Acknowledgements

Financial support was provided by the National Coral Reef Institute (NCRI) and the Khaled bin Sultan Living Oceans Foundation (KBSLOF). Invaluable logistical field support was provided by the crew of the M/Y Golden Shadow, through the generosity of HRH Prince Khaled bin Sultan. Additional in country support was provided by the Saudi Wildlife Commission (SWC) and PERSGA. Dr. Liisa Metsamaa’s work in the NCRI is supported by the Estonian Science Foundation Mobilitas postdoctoral grant. Thanks are

References (90)

  • Andréfouët, S., Muller-Karger, F.E., Robinson, J.A., Kranenburg, C.J., Torres-Pulliza, D., Spraggins, S.A., Murch, B.,...
  • R.B. Aronson et al.

    Coral bleach-out in Belize

    Nature

    (2000)
  • C. Aubrecht et al.

    A global inventory of coral reef stressors based on satellite observed nighttime lights

    Geocarto International

    (2008)
  • D.J. Ayre et al.

    Genotypic diversity and gene flow in brooding and spawning corals along the Great Barrier Reef. Australia

    Evolution

    (2000)
  • Berkelmans, R., 2009. Bleaching and mortality thresholds. How much is too much? In: van Oppen, M.J.H., Lough, J.M....
  • R. Berkelmans et al.

    A comparison of the 1998 and 2002 coral bleaching events on the Great Barrier Reef: spatial correlation, patterns, and predictions

    Coral Reefs

    (2004)
  • Bruckner, A., Rowlands, G.P., Riegl, B., Purkis, S., Williams, A., Renaud, P., 2011a. Khaled bin Sultan Living Oceans...
  • Bruckner, A.W., Alnazry, H.H., Faisal, M., 2011b. A paradigm shift for fisheries management to enhance recovery,...
  • L. Burke et al.

    Reefs at Risk Revisited

    (2011)
  • N.E. Cantin et al.

    Ocean warming slows coral growth in the Central Red Sea

    Science

    (2010)
  • D.M. Ceccarelli et al.

    Impacts of simulated overfishing on the territoriality of coral reef damselfish

    Marine Ecology Progress Series

    (2006)
  • J.H. Connell et al.

    A 30-year study of coral abundance, recruitment, and disturbance at several scales in space and time

    Ecological Monographs

    (1997)
  • R.K. Cowen

    Scaling of connectivity in marine populations

    Science

    (2006)
  • M. Dalleau et al.

    Use of habitats as surrogates of biodiversity for efficient coral reef conservation planning in Pacific Ocean Islands

    Conservation Biology

    (2010)
  • K.A. Davis et al.

    Observations of the thermal environment on Red Sea platform reefs: a heat budget analysis

    Coral Reefs

    (2011)
  • DeVantier, L., Pilcher, N.J., 2000. Status of coral reefs in Saudi Arabia: 2000. PERSGA Technical Series Report,...
  • Z. Dubinsky et al.

    Marine pollution and coral reefs

    Global Change Biology

    (1996)
  • G. Eshel et al.

    Climatological coastal jet collison, intermediate water formation, and the general circulation of the Red Sea

    Journal of Physical Oceanography

    (1997)
  • R. Einav et al.

    The footprint of the desalination processes on the environment

    Desalination

    (2002)
  • E.T. Game et al.

    Planning for persistence in marine reserves: a question of catastrophic importance

    Ecological Applications

    (2008)
  • W. Gladstone

    Fisheries of the Farasan Islands (Red Sea)

    Naga, World Fish Center Quarterly

    (2002)
  • Griffin, D.A., Rathbone, C.E., Smith, G.P., Suber, K.D., Turner, P.J., 2004. A decade of SST satellite data, final...
  • P. Hallcock et al.

    Nutrient excess and the demise of coral reefs and carbonate platforms

    PALAIOS

    (1986)
  • B.S. Halpern et al.

    A global map of human impact on marine ecosystems

    Science

    (2008)
  • A.R. Harbourne et al.

    Modeling the beta diversity of coral reefs

    Ecology

    (2006)
  • T.P. Hughes

    Catastrophes, phase shifts, and large-scale degradation of a Caribbean coral reef

    Science

    (1994)
  • T.P. Hughes et al.

    Multiple stressors on coral reefs: a long-term perspective

    Limnology and Oceanography

    (1999)
  • J.B.C. Jackson et al.

    Historical overfishing and the recent collapse of coastal ecosystems

    Science

    (2001)
  • S.C. Jameson et al.

    A coral damage index and its application to diving sites in the Egyptian Red Sea

    Coral Reefs

    (1999)
  • S. Jennings et al.

    Comparative size and composition of yield from six Fijian reef fisheries

    Journal of Fish Biology

    (1995)
  • S. Jennings et al.

    The effects of fishing on the diversity, biomass and trophic structure of Seychelles’ reef fish communities

    Coral Reefs

    (1995)
  • Kedidi, S.M., 1984. Description of the artisanal fishery at Tuwwal, Saudi Arabia. Catches, efforts and catches per unit...
  • I.S. Kuffner et al.

    Inhibition of coral recruitment by macroalgae and cyanobacteria

    Marine Ecology Progress Series

    (2006)
  • J.L. Largier

    Considerations in estimating larval dispersal distances from oceanographic data

    Ecological Applications

    (2003)
  • P. Legendre

    Spatial autocorrelation: trouble or new paradigm?

    Ecology

    (1993)
  • Cited by (63)

    • A benthic habitat sensitivity analysis of Qatar's coastal zone

      2021, Marine Pollution Bulletin
      Citation Excerpt :

      The results of this analysis could be used to identify candidate Marine Protected Areas. Similar geospatial efforts raising awareness of important and potentially vulnerable benthic habitats have been reported within the region (Purkis, 2005; Purkis and Riegl, 2005; Purkis et al., 2005; Rowlands et al., 2012; Feary et al., 2013; Aljenaid et al., 2017; Ben-Romdhane et al., 2016; Rowlands et al., 2016). By mapping the ecological sensitivity of the coastal zone, this study can serve as a blueprint for enhanced management of Qatar's coastal waters.

    • Multi-hazards vulnerability assessment of southern coasts of Iran

      2019, Journal of Environmental Management
      Citation Excerpt :

      In this study, the geographical range for determining the intensity of the fishing activities consisted of coastal waters whose seaward boundary is the lower limit of the tidal range and its landward boundary is the upper limit of the hazard zone. Adopting the methodology from Rowlands et al. (2012) and Mafi-Gholami and Ward (2018), the area of coastal waters was divided into 4 × 4 km GIS grid cells (1123 cells) for which the spatially explicit intensity of fishing activities was computed for: (1) boats, which have a length of 5–12 m, a crew of 2–4 people and a fishing capacity of 1–2.5 tons and (2) launches, which have a length of 15–20 m, a crew of more than 4 people, and a fishing capacity of 70–100 tons (ICZM, 2017; Mafi-Gholami and Ward, 2018). Before weighting the nine vulnerability variables and combining them into a the CVI, values of each variable were classified into five vulnerability classes (i.e., very low, low, intermediate, high, and very high).

    View all citing articles on Scopus
    View full text