Edgar, G. J. | bioRxiv Science

bioRxiv2024

From local seafloor imagery to global patterns in benthic habitat states: contribution of citizen science to habitat classification across latitudes

AimThe aim of this study was to define reef benthic habitat states and explore their spatial and temporal variability at a global scale using an innovative clustering pipeline. LocationThe study uses data on the transects surveyed on shallow (< 20m) reef ecosystems across the globe. Time period: Transects sampled between 2008 and 2021. Major taxa studied: Macroalgae, sessile invertebrates, hydrozoans, seagrass, corals. MethodsPercentage cover was estimated for 24 functional groups of sessile biota and substratum from annotated underwater photoquadrats taken along 6,554 transects by scuba divers contributing to the Reef Life Survey dataset. A clustering pipeline combining a non-linear dimension-reduction technique (UMAP), with a density-based clustering approach (HDBSCAN), was used to identify benthic habitat states. Spatial and temporal variation in habitat distribution was then explored across ecoregions. ResultsThe UMAP-HDBSCAN pipeline identified 17 distinct clusters representing different benthic habitats and gradients of ecological state. Certain habitat states displayed clear biogeographic patterns, predominantly occurring in temperate regions or tropical waters. Notably, some reefs dominated by turf algae were ubiquitous across latitudinal zones. Transition zones between temperate and tropical waters emerged as spatial hotspots of habitat state diversity. Temporal analyses revealed changes in the proportion of certain states over time, notably an increase in turf algae occurrence. Main ConclusionsThe UMAP-HDBSCAN clustering pipeline effectively characterised fine-scale benthic habitat states at a global scale, confirming known broader biogeographic patterns, including the importance of temperate-tropical transition zones as hotspots of habitat state diversity. This fine-scale, yet broadly-scalable habitat classification could be applied as a standardised template for tracking benthic habitat change across space and time at a global scale. The UMAP-HDBSCAN pipeline has proven to be a powerful and versatile approach for analysing complex biological datasets and can be applied in various ecological domains.

ecology↗

bioRxiv2021

A quantitative review of abundance-based species distribution models

The contributions of species to ecosystem functions or services depend not only on their presence in a given community, but also on their local abundance. Progress in predictive spatial modelling has largely focused on species occurrence, rather than abundance. As such, limited guidance exists on the most reliable methods to explain and predict spatial variation in abundance. We analysed the performance of 68 abundance-based species distribution models fitted to 800,000 standardised abundance records for more than 800 terrestrial bird and reef fish species. We found high heterogeneity in performance of abundance-based models. While many models performed poorly, a subset of models consistently reconstructed range-wide abundance patterns. The best predictions were obtained using random forests for frequently encountered and abundant species, and for predictions within the same environmental domain as model calibration. Extending predictions of species abundance outside of the environmental conditions used in model training generated poor predictions. Thus, interpolation of abundances between observations can help improve understanding of spatial abundance patterns, but extrapolated predictions of abundance, e.g. under climate change, have a much greater uncertainty. Our synthesis provides a roadmap for modelling abundance patterns, a key property of species distributions that underpins theoretical and applied questions in ecology and conservation.

ecology↗