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This post followed sea urchins from induced spawning through fertilization, larval development, metamorphosis, and juvenile formation under controlled temperature and salinity treatments. The post documents each stage of the cultivation process, highlighting both experimental techniques and organismal responses.
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This post documents an end-to-end R workflow that combines long-term benthic surveys (Eastern Scheldt) with mesocosm survival experiments to compare a native cockle and an introduced Manila clam under compound thermal and salinity stress.
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This post documents an R simulation for sea urchin foraging: a Lévy-walk–style search that switches to directed movement when the animal enters a chemical-cue detection radius around food sources. The output is an animated GIF that tracks the path and the cue “rings”.
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Short note on handling time-series data in R using POSIXct and ggplot2.
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Ridgeline plots are a clean way to compare distributions of a continuous variable across multiple groups. This note introduces the ggridges package and shows practical options for shaping, spacing, and coloring ridgelines in ggplot2.
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Rolling window analysis is a flexible approach for summarizing relationships in time-ordered or gradient-based data by computing statistics within sliding windows. This note demonstrates a custom implementation in R using the smoking dataset to explore how average weekday smoking amounts vary with age.