Biology subjects

Gerard, J.

Publications and source records attributed to Gerard, J..

4 recordsLinked to original sources

bioRxiv2026

WIO-ReefFish: A High-Resolution Dataset for Taxon-Aware Coral Reef Fish Detection in the Western Indian Ocean

Coral reef fish assemblages are widely used as indicators of ecosystem condition, yet manual annotation of underwater video remains a major bottleneck for scalable biodiversity monitoring. Despite rapid progress in automated detection, ecologically realistic and publicly available datasets remain scarce, particularly for the Western Indian Ocean. Here, we present WIO-ReefFish, a reef fish detection dataset derived from diver-operated line-intercept transects and designed for ecological monitoring under natural survey conditions. WIO-ReefFish comprises 1,000 ultra-high-definition images (3840 $\times$ 2160 pixels) and 6,768 exhaustive bounding-box annotations spanning 24 taxonomic categories, thereby preserving full-frame assemblage structure in complex reef scenes. We also establish a standardized benchmark across nine object detection models under two complementary protocols: class-aware detection and class-agnostic fish localization. Detection performance was consistently higher under the class-agnostic protocol. The best-performing model (RT-DETR) improved from 0.48 mAP50 in the class-aware setting to 0.70 mAP50 when taxonomic constraints were removed, indicating that taxonomic discrimination remains substantially more challenging than fish localisation in reef imagery. Spatially independent evaluation revealed a pronounced generalisation gap, particularly for taxonomic detection, whereas class-agnostic fish localisation remained substantially more robust across transects and countries. Together, these results establish WIO-ReefFish as a realistic benchmark for automated reef fish detection and provide a foundation for more robust computer-vision tools in coral reef biodiversity monitoring. The WIO-ReefFish dataset and associated benchmarking resources are publicly available.

ecology↗

bioRxiv2025

Beyond species means - the intraspecific contribution to global wood density variation

Wood density is central for estimating vegetation carbon storage and a plant functional trait of great ecological and evolutionary importance. However, the global extent of wood density variation is unclear, especially at the intraspecific level. We assembled the most comprehensive wood density collection to date (GWDD v.2), including 109,626 records from 16,829 plant species across woody life forms and biomes. Using the GWDD v.2, we explored the sources of variation in wood density within individuals, within species, and across environmental gradients. Intraspecific variation accounted for up to 15% of overall wood density variation (sd = 0.068 g cm-3). Sapwood densities varied 50% less than heartwood densities, and branchwood densities varied 30% less than trunkwood densities. Individuals in extreme environments (dry, hot, acidic soils) had higher wood density than conspecifics elsewhere (+0.02 g cm-3, [~]4% of the mean). Intraspecific environmental effects strongly tracked interspecific patterns (r = 0.83) but were only 20-30% as large and varied considerably among taxa. Individual plant wood density was difficult to predict (RMSE > 0.08 g cm-3; single-measurement R2 = 0.59). We recommend (i) systematic within-species sampling for local applications, and (ii) expanded taxonomic coverage combined with integrative models for robust estimates across ecological scales.

plant biology↗

bioRxiv2018

Cohesin interacts with a panoply of splicing factors required for cell cycle progression and genomic organization

The cohesin complex regulates sister chromatid cohesion, chromosome organization, gene expression, and DNA repair. Here we report that endogenous human cohesin interacts with a panoply of splicing factors and RNA binding proteins, including diverse components of the U4/U6.U5 tri-snRNP complex and several splicing factors that are commonly mutated in cancer. The interactions are enhanced during mitosis, and the interacting splicing factors and RNA binding proteins follow the cohesin cycle and prophase pathway of regulated interactions with chromatin. Depletion of cohesin-interacting splicing factors results in stereotyped cell cycle arrests and alterations in genomic organization. These data support the hypothesis that splicing factors and RNA binding proteins control cell cycle progression and genomic organization via regulated interactions with cohesin and chromatin.\n\nOne Sentence SummaryEndogenous tagging reveals that cohesin interacts with diverse chromatin-bound splicing factors that regulate cell cycle progression and genomic organization in human cells.

cell biology↗

bioRxiv2018

New formula and conversion factor to compute tree species basic wood density from a global wood technology database.

Premise of the studyBasic wood density is an important ecological trait for woody plants. It is used to characterize species performance and fitness in community ecology, and to compute tree and forest biomass in carbon cycle studies. While wood density has been historically measured at 12% moisture, it is convenient for ecological purposes to convert this measure to basic wood density, i.e. the ratio of dry mass over green volume. Basic wood density can then be used to compute tree dry biomass from living tree volume.\n\nMethodsHere, we derive a new, exact formula to compute the basic wood density Db from the density at moisture content w denoted Dw, the fibre saturation point S, and the volumetric shrinkage coefficient R. We estimated a new conversion factor using a global wood technology database where values to use this formula are available for 4022 trees collected in 64 countries (mostly tropical) and representing 872 species.\n\nKey resultsWe show that previous conversion factors used to convert densities at 12% moisture into basic wood densities are inconsistent. Based on theory and data, we found that basic wood density could be inferred from the density at 12% moisture using the following formula: Db = 0.828D122. This value of 0.828 provides basic wood density estimates 4-5% smaller than values inferred from previous conversion factors.\n\nConclusionsThis new conversion factor should be used to derive basic wood densities in global wood density databases. This would prevent overestimating global forest carbon stocks and allow predicting better tree species community dynamics from wood density.

plant biology↗