Prioritizing phylogenetic diversity to protect functional diversity of reef corals

Abstract

AbstractAimThe ecosystem functions and services of coral reefs are critical for coastal communities worldwide. Due to conservation resource limitation, species need to be prioritized to protect desirable properties of biodiversity, such as functional diversity (FD), which has been associated with greater ecosystem functioning but is difficult to quantify directly. Selecting species to maximize phylogenetic diversity (PD) has been shown to indirectly capture FD in certain other taxa but not corals. Here, we test this hypothesis, the “phylogenetic gambit”, on corals within global marine protected areas (MPAs).LocationGlobal coral reefs.MethodsBased on the global distributions of reef corals, a complete species‐level phylogeny and trait data, we compared the FD of coral assemblages within MPAs when selected to maximize PD versus FD for assemblages selected randomly. The relationships between PD and FD were also tested as predictors of surrogacy. We then used coral FD and PD to perform spatial prioritization of reefs for protection and assessed the congruence between the two approaches.ResultsSelecting assemblages to maximize PD captured significantly more FD than a random subset of species for 83.1% of all selection scenarios across MPAs and would protect on average 18.7% more FD than random selection. Spatial prioritization analyses showed some mismatches between PD‐ and FD‐optimized planning units, particularly in the Tropical Western Atlantic, but the high degree of overlap between the optimizations for other reef regions lends further credence to the PD‐maximizing strategy in conserving coral FD.Main ConclusionsA PD‐maximizing strategy generally protects greater FD of coral assemblages relative to random selection of species, suggesting that the “phylogenetic gambit” is valid for reef corals. There are risks, however, and the mismatches between PD‐maximized and FD‐maximized MPA networks highlight specific shortcomings of the PD‐maximization approach. Nevertheless, in data‐deficient circumstances, maximizing PD may provide a viable alternative.