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Full-Text Articles in Physical Sciences and Mathematics
High Frequency Temperature Variability Reduces The Risk Of Coral Bleaching, Aryan Safaie, Nyssa J. Silbiger, Timothy R. Mcclanahan, Geno Pawlak, Daniel J. Barshis, James L. Hench, Gareth J. Williams, Kristen A. Davis
High Frequency Temperature Variability Reduces The Risk Of Coral Bleaching, Aryan Safaie, Nyssa J. Silbiger, Timothy R. Mcclanahan, Geno Pawlak, Daniel J. Barshis, James L. Hench, Gareth J. Williams, Kristen A. Davis
Biological Sciences Faculty Publications
Coral bleaching is the detrimental expulsion of algal symbionts from their cnidarian hosts, and predominantly occurs when corals are exposed to thermal stress. The incidence and severity of bleaching is often spatially heterogeneous within reef-scales (km), and is therefore not predictable using conventional remote sensing products. Here, we systematically assess the relationship between in situ measurements of 20 environmental variables, along with seven remotely sensed SST thermal stress metrics, and 81 observed bleaching events at coral reef locations spanning five major reef regions globally. We find that high-frequency temperature variability (i.e., daily temperature range) was the most influential factor in …
Integrating Dynamic Subsurface Habitat Metrics Into Species Distribution Models, Stephanie Brodie, Michael G. Jacox, Steven J. Bograd, Heather Welch, Heidi Dewar, Kylie L. Scales, Sara M. Maxwell, Dana M. Briscoe, Christopher A. Edwards, Larry B. Crowder, Rebecca L. Lewison, Elliott L. Hazen
Integrating Dynamic Subsurface Habitat Metrics Into Species Distribution Models, Stephanie Brodie, Michael G. Jacox, Steven J. Bograd, Heather Welch, Heidi Dewar, Kylie L. Scales, Sara M. Maxwell, Dana M. Briscoe, Christopher A. Edwards, Larry B. Crowder, Rebecca L. Lewison, Elliott L. Hazen
Biological Sciences Faculty Publications
Species distribution models (SDMs) have become key tools for describing and predicting species habitats. In the marine domain, environmental data used in modeling species distributions are often remotely sensed, and as such have limited capacity for interpreting the vertical structure of the water column, or are sampled in situ, offering minimal spatial and temporal coverage. Advances in ocean models have improved our capacity to explore subsurface ocean features, yet there has been limited integration of such features in SDMs. Using output from a data-assimilative configuration of the Regional Ocean Modeling System, we examine the effect of including dynamic subsurface …