This paper presents the development and evaluation of a Subtidal Seagrass Detector (the Detector). Deep learning models were used to detect most forms of seagrass occurring in a diversity of habitats across the northeast Australian seascape from underwater images and classify them based on how much the cover of seagrass was present. Images were collected by scientists and trained contributors undertaking routine monitoring usi...

Purpose This 3D in vitro cancer model for propagation of patient-derived cells, using a synthetic self-assembling peptide gel, allows the formation of a fully characterised, tailorable tumour microenvironment. Unlike many existing 3D cancer models, the peptide gel is inert, apart from molecules and motifs deliberately added or produced by cells within the model. Methods Breast cancer patient-derived xenografts (PDXs) were disa...

Motivation The Tundra Trait Team (TTT) database includes field‐based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade‐offs, trait–environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system mo...

This study assessed metabolism, growth, and survival of two seagrass species at three different seawater temperatures (27°C, 30°C, and 33°C) under saturating (400 µmol photons m ‐2 s ‐1 ) and limiting (40 µmol photons m ‐2 s ‐1 ) light over 1 month. Halodule uninervis grown at 33°C was within its physiological optimum temperature range, exhibiting 2.3× higher photosynthetic rates than at 27°C, and increased net shoot carbon (C...