R. C. Babcock's Lab
Department: Oceans and Atmosphere
Featured research (2)
On coral reefs, changes in the cover and relative abundance of hard coral taxa often follow disturbance. Although the ecological responses of common coral taxa have been well documented, little is known about the ecological responses of uncommon coral taxa or of coral morphological groups across multiple adjacent reef zones. We used Multivariate Auto-Regressive State-Space modelling to assess the rate and direction of change of hard coral cover across a variety of coral genera, growth-forms, and susceptibility to bleaching and physical damage covering multiple reef zones at northern Ningaloo Reef in Western Australia. Trends were assessed between 2007 and 2016, during which multiple episodic disturbances occurred including cyclones and a heatwave. We provide evidence of zone specific trends, not only in total hard coral cover, but also in taxonomic and morphological groups of corals at Ningaloo Reef. Declines in total coral cover on the reef flat corresponded with declines in fast growing corals, particularly Acropora. In contrast, total coral cover on the reef slope and inshore (lagoon) did not undergo significant change, despite divergent trajectories of individual genera. Importantly, we also show that changes in the composition of coral assemblages can be detected using a morphological based approach when changes are not evident using a taxonomic approach. Therefore, we recommend that future assessments of coral reef trends incorporate not just standard metrics such as total coral cover, but also metrics that provide for detailed descriptions of trends in common and uncommon taxa and morphological groups across multiple reef zones.
Aim: To investigate how changing grid size can alter model predictions of the distribution of mesophotic taxa and how it affects different modelling methods. Location: Ningaloo Marine Park, Western Australia. Taxon: Benthic mesophotic taxa: corals, macroalgae and sponges. Methods: We determined the distributions of the major benthic taxonomic groups: corals, macroalgae and sponges, using a number of modelling techniques and an ensemble using the ‘sdm’ R package. A range of grid sizes were used (10, 50, 100 and 250 m) to identify how model predictions were altered. Models were evaluated using the area under the curve of a receiver operator characteristic plot (AUC) and the true skill statistic (TSS) using a spatially independent dataset. Results: Grid size had a large effect on model performance across the taxonomic groups. Model outputs were compared to null surfaces and 88.8% of models performed significantly better than null. Distribution of corals was best predicted using the finest grid size (10 m) regardless of modelling method, although a model ensemble produced the best results (AUC = 0.80, TSS = 0.52). Macroalgae and sponges were better predicted at coaster grids sizes (250 m). Again, ensembles performed well for both macroalgae (AUC = 0.83, TSS = 0.63) and sponges (AUC = 0.88, TSS = 0.66). Model ensembles maintained high accuracy across grid sizes and were consistently the best, or second‐best, performing method. Main conclusions: This study has shown how grid size should be considered when producing distribution models. Identifying the most relevant grid size and being aware of the influence it may have will provide more accurate predictions of the distributions of taxa. Ensemble methods maintained good performance across scenarios and thus provide a useful tool for conservation and management especially where single modelling methods showed high levels of variability.