Host identity shapes Endozoicomonas composition in coral microbiomes across depths and marine protected areas at Little Cayman Island - Madelaine L. Brown; Andrew J. Maritan; Gretchen Goodbody-Gringley; Matthew L. Doherty; Alex D. Chequer; Frank J. Stewart; Zoe A. Pratte (Coral Reefs, 2026)
The bacterial genus Endozoicomonas is prevalent and abundant in the microbiome of many corals, but the combination of environmental and host factors shaping its distribution remains uncertain. In this study, we used 16S rRNA gene sequencing to examine the distribution of Endozoicomonas across hard ( Porites astreoides , Montastraea cavernosa , Agaricia spp.) and soft coral ( Muricea spp., Gorgoniidae, Cladiellidae, Malacalcyonacea) microbiomes across a depth gradient from shallow (4.5 m) to upper mesophotic zones (36.6 m) at four sites around the Little Cayman Island, including two marine protected areas. Endozoicomonas was abundant across all coral microbiomes, with soft corals exhibiting near-total dominance (relative abundance range 0.1–99%, median 55.3%) by this genus and notable abundances (range 0–96%, median 22.2%) in hard corals. Endozoicomonas composition was strongly structured by coral host identity across sites and depths, with each coral type harboring two to four unique Endozoicomonas amplicon sequence variants. Site and depth also contributed to Endozoicomonas abundance in soft and hard corals, respectively, where relative abundances were highest at unprotected sites in soft corals and in shallow to mid photic zones in hard corals. These findings suggest that Endozoicomonas abundance is shaped by both coral host identity and local environmental conditions.

Fate tracking of Acropora cervicornis colonies post-outplanting reveals genotype-specific responses to marine heatwaves - Gretchen Goodbody-Gringley; Brett D. Jameson; Haley A. Davis; Janna L. Randle; Matthew L. Doherty; Jack V. Johnson; Alex D. Chequer; John F. Bruno (Coral Reefs, 2026)

Remotely Sensed Fire Heterogeneity and Biomass Recovery Predicts Empirical Biodiversity Responses - Rebecca K. Gibson; Don A. Driscoll; Kristina J. Macdonald; Grant J. Williamson; Rachael H. Nolan; Tim S. Doherty; Dale G. Nimmo; Euan G. Ritchie; Mark Tozer; Liz Tasker; Aaron Greenville; Adam Roff; et al. (Global Ecology and Biogeography, 2025)
Aim To compare field‐based evidence of plant and animal responses to fire with remotely sensed signals of fire heterogeneity and post‐fire biomass recovery. Location South‐eastern Australia; New South Wales. Time Period 2019–2022. Major Taxa Studied A total of 982 species of plants and animals, in eight taxonomic groups: amphibians, birds, fish, insects, mammals, molluscs, plants and reptiles. Methods We collated 545,223 plant and animal response records from 47 field surveys of 4613 sites that focussed on areas burnt in 2019–2020. For each site, we calculated remotely sensed signals of fire heterogeneity and post‐fire biomass recovery, including the delayed recovery index. Meta‐regression analyses were conducted separately for species that declined after fire (negative effect sizes) and species that increased after fire (positive effect sizes) for each buffer size (250 m, 500 m, 1 km, 1.5 km, 2 km and 2.5 km radius). Results We found that species exposed to homogenous high‐severity fire (i.e., low fire heterogeneity) were more likely to exhibit decreased abundance/occurrence or inhibited recovery. Areas with delayed recovery of biomass also had significant negative on‐ground responses, with lower abundance or occurrence in areas where biomass recovery was slower. Main Conclusions The fire heterogeneity index and the delayed recovery index are suitable for inclusion in monitoring and reporting systems for tracking relative measures over time, particularly when field survey data is not available at the landscape scales required to support reporting and management decisions. Locations with remotely sensed signals of delayed recovery should be prioritised for protection against further disturbances that may interfere with the recovery process. Research attention must next focus on how cumulative fire heterogeneity patterns of successive fires affect the post‐fire recovery dynamics to further inform the application of remote sensing indicators as management tools for biodiversity conservation.

Phenotypic variability of Montastraea cavernosa and Porites astreoides along a depth gradient from shallow to mesophotic reefs in the Cayman Islands - Matthew L. Doherty; Alex D. Chequer; Tali Mass; Gretchen Goodbody-Gringley (Coral Reefs, 2024)
Phenotypic variability is the ability of the same species to express different phenotypes under different environmental conditions. Several coral species that exist along a broad depth distribution have been shown to differ in skeletal morphology and nutrient acquisition at different depths, which has been attributed to variability in response to differing levels of light availability. This study examined the phenotypic variability of two common depth generalist corals, Montastraea cavernosa and Porites astreoides, along a gradient from 10 to 50 m in the Cayman Islands, by examining changes in skeletal morphology, photophysiology, symbiont cell density, and chlorophyll concentration. Skeletal features of M. cavernosa were found to increase in size from 10 to 30 m, but returned to smaller sizes from 30 to 50 m, while P. astreoides skeletal features continued to increase in size from 10 to 40 m. No differences were observed in either symbiont density or chlorophyll concentration across depths for either species. However, all photophysiological parameters exhibited significant depth-dependent variations in both species, revealing adaptive strategies to different light environments. These results suggest that both species have high variability in response to depth. Patterns of skeletal morphology and photophysiology, however, suggest that M. cavernosa may be more variable in regulating photosynthetic efficiency compared to P. astreoides , which likely facilitates the broader depth distribution of this species.

BioTIME: A database of biodiversity time series for the Anthropocene - Maria Dornelas; Laura H. Antão; Faye Moyes; Amanda E. Bates; Anne E. Magurran; Dušan Adam; Asem A. Akhmetzhanova; Ward Appeltans; José Manuel Arcos; Haley Arnold; Narayanan Ayyappan; Gal Badihi; et al. (Global Ecology and Biogeography, 2018)
Motivation The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km 2 (158 cm 2 ) to 100 km 2 (1,000,000,000,000 cm 2 ). Time period and grain BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format .csv and .SQL.

Physical map of two tammar wallaby chromosomes: A strategy for mapping in non-model mammals - Janine E. Deakin; Edda Koina; Paul D. Waters; Ruth Doherty; Vidushi S. Patel; Margaret L. Delbridge; Bianca Dobson; James Fong; Yanqiu Hu; Cecilia van den Hurk; Andrew J. Pask; Geoff Shaw; et al. (Chromosome Research, 2008)

Contributory presentations/posters - N. Manoj; V. R. Srinivas; A. Surolia; M. Vijayan; K. Suguna; R. Ravishankar; K. Suguna; A. Surolia; M. Vijayan; R. Schwarzenbacher; K. Zeth; Diederichs; et al. (Journal of Biosciences, 1999)