Owen Forbes
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owenforbes.bsky.social
Owen Forbes
@owenforbes.bsky.social
410 followers 690 following 11 posts
Translational data science | Bayesian stats | Bridging data & impact | he/him
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owenforbes.bsky.social
Patterns of decline vary across taxa and regions - biggest declines seen for plants and vertebrates, with insects showing more recent peak and decline
Plots indicating trends in sampling over time by number of specimens, number of unique species, and number of spatial grids (1 degree lat/long) represented globally Left column = Chordata; middle column = Plantae; right column = Arthropoda. Top row = number of specimens per year; middle row = number of unique species per year; bottom row = spatial extent based on the number of 1-degree grid cells with specimens observed per year. Blue, green and red lines indicate LOESS (locally estimated scatterplot smoothing) curves for specimen counts by collection year for Chordata, Plantae and Arthropoda, respectively.
October 21, 2025 at 5:34 AM
owenforbes.bsky.social
We're collecting less than half as many biodiversity specimens as in the 1960s-1980s, at a time when they're more important than ever for climate & ecology science. Natural history collections provide crucial data that no other source can match. Our new paper in Nature Comms: doi.org/10.1038/s414...
This heatmap displays the change in the mean annual count of specimens collected between 2010 and 2019 compared to the reference period of 1970–2009, in 1-degree latitude-longitude grids, across all three taxonomic groups combined (Chordata, Plantae and Arthropoda). Substantial patterns of decline are seen, particularly apparent across areas with historically high levels of collecting across Australia, North America, Western Europe
October 21, 2025 at 5:23 AM
owenforbes.bsky.social
Our new Ecology Letters paper shows how natural history collections can use Bayesian decision theory & VOI to transform sampling and resourcing. Moving beyond taxonomy-focused collecting to strategic approaches, maximising impact for climate science, genomics & conservation
doi.org/10.1111/ele.70188
Data-driven research prioritisation example—sampling design for the bare-nosed wombat (Vombatus ursinus) in New South Wales, Australia, based on observation and specimen data from GBIF. (A) Value of Information (VOI) map showing expected information gain from additional sampling (darker blue = higher gain), calculated using a binomial model of annual observations in each 50 km grid, with expected information gain calculated using Kullback–Leibler divergence between current and updated probability distributions after simulated sampling. (B) Need for Information (NFI) map based on habitat loss percentiles (darker green = greater habitat loss), derived from the Habitat Condition Assessment System. (C) Cost of Information (COI) map using the Australian Bureau of Statistics' remoteness classification system (darker purple = metropolitan areas with higher accessibility and lower expected sampling costs). (D) Consensus diagram—VOI-NFI quadrant analysis revealing priority sampling locations (upper right quadrant) where both information value and ecological need are high. In Panel A, grid cells (50 km) with insufficient data appear in grey (fewer than 2 total observations per grid). See Data S1 for details on methodology, data sources, and implementation.
August 4, 2025 at 1:53 AM
owenforbes.bsky.social
Awesome to learn about the Murujuga Rock Art monitoring program from Rebecca O’Leary and the team at Curtin Uni, and their work to understand the effects of air quality on petroglyphs. #TIES2024

murujuga.org.au/worlds-large...
December 2, 2024 at 11:36 PM
owenforbes.bsky.social
Excellent plenary by @sarahinscience.bsky.social to kick off The International Environmetrics Society Conference 2024 here in Tarntanya/Adelaide. Excited to learn about environment & ecology stats, spend time with old friends and make new ones! #TIES2024
Sarah Perkins-Kirkpatrick giving plenary talk at TIES2024
December 2, 2024 at 1:06 AM