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Computer vision for assessing species color pattern variation from web-based community science images.

ABSTRACT: Openly available community science digital vouchers provide a wealth of data to study phenotypic change across space and time. However, extracting phenotypic data from these resources requires significant human effort. Here, we demonstrate a workflow and computer vision model for automatically categorizing species color pattern from community science images. Our work is focused on documenting the striped/unstriped color polymorphism in the Eastern Red-backed Salamander (Plethodon cinereus). We used an ensemble convolutional neural network model to analyze this polymorphism in 20,318 iNaturalist images. Our model was highly accurate (∼98%) despite image heterogeneity. We used the resulting annotations to document extensive niche overlap between morphs, but wider niche breadth for striped morphs at the range-wide scale. Our work showcases key design principles for using machine learning with heterogeneous community science image data to address questions at an unprecedented scale.

SUBMITTER: Hantak MM

PROVIDER: S-EPMC9379571 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Computer vision for assessing species color pattern variation from web-based community science images.

Hantak Maggie M MM Guralnick Robert P RP Zare Alina A Stucky Brian J BJ

iScience 20220719 8

Openly available community science digital vouchers provide a wealth of data to study phenotypic change across space and time. However, extracting phenotypic data from these resources requires significant human effort. Here, we demonstrate a workflow and computer vision model for automatically categorizing species color pattern from community science images. Our work is focused on documenting the striped/unstriped color polymorphism in the Eastern Red-backed Salamander (<i>Plethodon cinereus</i> ...[more]

PMID: 35982791

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Dataset Information

Computer vision for assessing species color pattern variation from web-based community science images.

Publications

Computer vision for assessing species color pattern variation from web-based community science images.

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