Author

Janet C. Buckner

Louisiana State UniversityORCID 0000-0001-7509-8370Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Evolutionary Biology· 3

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:development & morphogenesis· 2 Research Focus:host-pathogen & immune response· 2 Research Focus:ecology & biodiversity· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Organism:multiple species· 1 Organism:non-human primate· 1

Frequent Co-Authors

Ray Mariano ChatterjiiD· 2 shared Amanda Dawn MeliniD· 1 shared Courtney A. HofmaniD· 1 shared Eva C. WikbergiD· 1 shared Helen F. JamesiD· 1 shared Jessica Ward LynchiD· 1 shared Katharine M. JackiD· 1 shared Linda Marie FediganiD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersEvolutionary Biology

Ray Mariano ChatterjiORCID

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3 papers

Recent·Most cited

Evolutionary BiologySystematic BiologyPeer-reviewedFeb 25, 2026

Dietary specialization drives adaptation, convergence, and integration across the cranial and appendicular skeleton in Waterfowl (Anseriformes).

Ray M Chatterji, Tracy A. Heath, Helen F. James…·Janet C. Buckner

The paper shows dietary ecology drives morphological convergence and integration across multiple skeletal structures in waterfowl.

5 citationstop 1%

multiple speciesimaging

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Evolutionary BiologyPrimatesPeer-reviewedNov 27, 2025

MHC heterozygosity may increase subordinate but not alpha male siring success in white-faced capuchin monkeys (Cebus imitator)

Janet C. Buckner, Katharine M. Jack, Margaret S. Buehler…·Jessica Ward Lynch

This study examines MHC heterozygosity's role in siring success among white-faced capuchin monkeys, finding that subordinate males with MHC diversity sire more offspring when related to alpha males.

DOI 10.1007/s10329-025-01228-x

non-human primatestatistical model

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Evolutionary BiologybioRxivPreprintMay 29, 2025

Geometric morphometrics enables accurate predictions of paleoecology and reveals unique adaptations to an expanded niche space in extinct waterfowl

Ray Mariano Chatterji, Shante Williams, Janet C. Buckner

This study uses geometric morphometrics and machine learning to predict the diets of extinct waterfowl and identifies unique ecological adaptations not seen in modern species.

DOI 10.1101/2025.05.29.656821

statistical modelmachine learning (classical)

𝕏 PostBluesky