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Philip Patton

@ptpatton.bsky.social

453 followers 537 following 21 posts

Postdoctoral Fellow at the Smithsonian's National Zoo and Conservation Biology Institute, Migratory Bird Center Webpage: philpatton.github.io Cover image: biodiversitystripes.info/global/bir…

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Philip Patton @ptpatton.bsky.social · 20/06/2026

Bad day to be a p-value @rmcelreath.bsky.social @avehtari.bsky.social @vianeylb.bsky.social

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Philip Patton @ptpatton.bsky.social · 14/01/2025

False negatives, i.e., an individual was resighted but erroneously marked as a first capture, dictated the optimal strategy in many cases. A 2% increase in the false negative rate translated to a 5% increase in the relative bias in abundance estimates. This rate is easy to compute in practice.

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Philip Patton @ptpatton.bsky.social · 14/01/2025

We fed the results into a custom optimization tool to discern the optimal strategy, that is, the optimal method for generating capture histories with an algorithm, for each dataset. We found that true automation was optimal when the algorithm matched images well.

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Philip Patton @ptpatton.bsky.social · 14/01/2025

Automating photo-ID creates tradeoffs between reducing effort and increasing estimation error. We explored these tradeoffs with a simulation study, informed by 39 photo-ID datasets representing 24 cetacean species.

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Philip Patton @ptpatton.bsky.social · 14/01/2025

I’m thrilled to see my dissertation’s second chapter published in Conservation Biology. In the paper, we found that researchers can use high-performance identification algorithms to reduce the cost of population assessments without biasing abundance estimates. tinyurl.com/ne8tbpw3

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Philip Patton @ptpatton.bsky.social · 14/01/2025

Plot showing the correlation between the false negative rate and parameter estimates from a capture-recapture model.

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Philip Patton @ptpatton.bsky.social · 14/01/2025

Results from out optimization for three example datasets.

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Philip Patton @ptpatton.bsky.social · 14/01/2025

A schematic showing our methods for the simulation study.

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