Abstract

Information about the distribution and abundance of the habitat-forming sessile organisms in marine ecosystems is of great importance for conservation and natural resource managers. Spatial interpolation methodologies can be useful to generate this information from in situ sampling points, especially in circumstances where remote sensing methodologies cannot be applied due to small-scale spatial variability of the natural communities and low light penetration in the water column. Interpolation methods are widely used in environmental sciences; however, published studies using these methodologies in coral reef science are scarce. We compared the accuracy of the two most commonly used interpolation methods in all disciplines, inverse distance weighting (IDW) and ordinary kriging (OK), to predict the distribution and abundance of hard corals, octocorals, macroalgae, sponges and zoantharians and identify hotspots of these habitat-forming organisms using data sampled at three different spatial scales (5, 10 and 20 m) in Madagascar reef, Gulf of Mexico. The deeper sandy environments of the leeward and windward regions of Madagascar reef were dominated by macroalgae and seconded by octocorals. However, the shallow rocky environments of the reef crest had the highest richness of habitat-forming groups of organisms; here, we registered high abundances of octocorals and macroalgae, with sponges, Millepora alcicornis and zoantharians dominating in some patches, creating high levels of habitat heterogeneity. IDW and OK generated similar maps of distribution for all the taxa; however, cross-validation tests showed that IDW outperformed OK in the prediction of their abundances. When the sampling distance was at 20 m, both interpolation techniques performed poorly, but as the sampling was done at shorter distances prediction accuracies increased, especially for IDW. OK had higher mean prediction errors and failed to correctly interpolate the highest abundance values measured in situ, except for macroalgae, whereas IDW had lower mean prediction errors and high correlations between predicted and measured values in all cases when sampling was every 5 m. The accurate spatial interpolations created using IDW allowed us to see the spatial variability of each taxa at a biological and spatial resolution that remote sensing would not have been able to produce. Our study sets the basis for further research projects and conservation management in Madagascar reef and encourages similar studies in the region and other parts of the world where remote sensing technologies are not suitable for use.

Highlights

  • Coral reefs are important centres of biodiversity (Plaisance et al, 2011) that provide multiple natural resources and ecosystem services to human societies (Mumby et al, 2011)

  • Sponges and zoantharians were scarce in these environments but had slightly higher abundances at the windward (2.6%, 1.0% and 0.7%, respectively) than at the leeward region (1.4%, 0.8% and 0%, respectively) (Fig. 4)

  • The only published past studies using inverse distance weighting (IDW) in coral reef sessile organisms found this method to be a good interpolator for coral cover (Walker et al, 2012; D’Antonio, Gilliam & Walker, 2016); our results corroborate these findings and we extend the applicability of this method to other important sessile organisms that are becoming more abundant, likely because of climate change (Norström et al, 2009)

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Summary

Introduction

Coral reefs are important centres of biodiversity (Plaisance et al, 2011) that provide multiple natural resources and ecosystem services to human societies (Mumby et al, 2011). Hard corals used to dominate the seascape of tropical reefs; their populations have declined in recent decades due to multiple disturbances such as overfishing, eutrophication and high temperatures (Nyström & Folke, 2001), allowing other HFO to increase their abundance (Nyström, Folke & Moberg, 2000; Wilkinson, 2004; Ruzicka et al, 2013; McMurray, Finelli & Pawlik, 2015). As the community structure of coral reefs transitions, the need to monitor the distribution and abundance of all HFO has increased (Norström et al, 2009; Bell et al, 2013; Ruzicka et al, 2013; McMurray, Finelli & Pawlik, 2015)

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