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Abstract Technological advances in three imaging techniques have opened the door to advanced morphological analyses and habitat mapping for biologists and ecologists.At the same time, the challenge of translating complex 3D data into meaningful metrics that can be used in conjunction with biological data currently hinders progress and accessibility.We introducehabtools, an R package that provides R functions to efficiently calculate complexity and shape metrics from DEMs, 3D meshes and 2D shapes as well as some helper functions to facilitate workflow.We expect the functionality ofhabtoolsto continue to expand as new metrics and faster methods become available, and we welcome new contributions and ideas. 

Abstract The relative importance of evolutionary history and ecology for traits that drive ecosystem processes is poorly understood. Consumers are essential drivers of nutrient cycling on coral reefs, and thus ecosystem productivity. We use nine consumer “chemical traits” associated with nutrient cycling, collected from 1,572 individual coral reef fishes (178 species spanning 41 families) in two biogeographic regions, the Caribbean and Polynesia, to quantify the relative importance of phylogenetic history and ecological context as drivers of chemical trait variation on coral reefs. We find: (1) phylogenetic relatedness is the best predictor of all chemical traits, substantially outweighing the importance of ecological factors thought to be key drivers of these traits, (2) phylogenetic conservatism in chemical traits is greater in the Caribbean than Polynesia, where our data suggests that ecological forces have a greater influence on chemical trait variation, and (3) differences in chemical traits between regions can be explained by differences in nutrient limitation associated with the geologic context of our study locations. Our study provides multiple lines of evidence that phylogeny is a critical determinant of contemporary nutrient dynamics on coral reefs. More broadly our findings highlight the utility of evolutionary history to improve prediction in ecosystem ecology. 

Abstract AimHabitat complexity plays an important role in the structure and function of ecosystems worldwide. On coral reefs, habitat complexity influences ecosystem services such as harvestable fish biomass and attenuation of wave energy. Here, we test how three descriptors of surface complexity—rugosity, fractal dimension, and height range—trend with the geological age of reefs (0.2–5.1 million years old), depth (1–25 m), wave exposure (1–306 kW/m), coral cover (0–80%), and three habitat types (aggregated reef, rock and boulder, and pavement). LocationWe surveyed across 234 sites and 4 degrees of latitude in the eight main Hawaiian Islands. Time PeriodApril 2019 – July 2019. Major Taxa StudiedReef building corals. MethodsWe estimate three surface descriptors (rugosity, fractal dimension and height range) using structure‐from‐motion photogrammetry. We evaluate hypothesized relationships between these descriptors and geological reef age, depth, wave exposure, coral cover and reef habitat type using generalized linear models that account for survey design. ResultsThe rugosity of reef habitats decreased with geological reef age; fractal dimension (and coral cover) decreased with wave exposure; and height range decreased with depth. Variations in these patterns were explained by the different habitat types and the way they are formed over time. Nonetheless, the three surface descriptors were geometrically constrained across all habitat types, and so habitats occupied distinctly different regions of habitat complexity space. Main ConclusionsThis study showed how broad environmental characteristics influence the structural complexity of habitats, and therefore geodiversity, which is an important first step toward understanding the communities supported by these habitats and their ecosystem services. 

Abstract In their recent synopsis, Loke and Chisholm (Ecology Letters, 25, 2269–2288, 2022) present an overview of habitat complexity metrics for ecologists. They provide a review and some sound advice. However, we found several of their analyses and opinions misleading. This technical note provides a different perspective on the complexity metrics assessed. 

Abstract Humans have long sought to restore species but little attention has been directed at how to best select a subset of foundation species for maintaining rich assemblages that support ecosystems, like coral reefs and rainforests, which are increasingly threatened by environmental change.We propose a two‐part hedging approach that selects optimized sets of species for restoration. The first part acknowledges that biodiversity supports ecosystem functions and services, and so it ensures precaution against loss by allocating an even spread of phenotypic traits. The second part maximizes species and ecosystem persistence by weighting species based on characteristics that are known to improve ecological persistence—for example abundance, species range and tolerance to environmental change.Using existing phenotypic‐trait and ecological data for reef building corals, we identified sets of ecologically persistent species by examining marginal returns in occupancy of phenotypic trait space. We compared optimal sets of species with those from the world's southern‐most coral reef, which naturally harbours low coral diversity, to show these occupy much of the trait space. Comparison with an existing coral restoration program indicated that current corals used for restoration only cover part of the desired trait space and programs may be improved by including species with different traits.Synthesis and applications. While there are many possible criteria for selecting species for restoration, the approach proposed here addresses the need to insure against unpredictable losses of ecosystem services by focusing on a wide range of phenotypic traits and ecological characteristics. Furthermore, the flexibility of the approach enables the functional goals of restoration to vary depending on environmental context, stakeholder values, and the spatial and temporal scales at which meaningful impacts can be achieved.