{"doi":"10.1101/2023.12.22.573139","title":"Multiple performance peaks for scale-biting in an adaptive radiation of pupfishes","abstract":"pupfishes to measure the relationship between feeding kinematics and performance during adaptation to a novel trophic niche, lepidophagy, in which a predator removes only the scales, mucus, and sometimes tissue from their prey using scraping and biting attacks. We used high-speed video to film scale-biting strikes on gelatin cubes by scale-eater, molluscivore, generalist, and hybrid pupfishes and subsequently measured the dimensions of each bite. We then trained the SLEAP machine-learning animal tracking model to measure kinematic landmarks and automatically scored over 100,000 frames from 227 recorded strikes. Scale-eaters exhibited increased peak gape and greater bite length; however, substantial within-individual kinematic variation resulted in poor discrimination of strikes by species or strike type. Nonetheless, a complex performance landscape with two distinct peaks best predicted gel-biting performance, corresponding to a significant nonlinear interaction between peak gape and peak jaw protrusion in which scale-eaters and their hybrids occupied a second performance peak requiring larger peak gape and greater jaw protrusion. A bite performance valley separating scale-eaters from other species may have contributed to their rapid evolution and is consistent with multiple estimates of a multi-peak fitness landscape in the wild. We thus present an efficient deep-learning automated pipeline for kinematic analyses of feeding strikes and a new biomechanical model for understanding the performance and rapid evolution of a rare trophic niche.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2023,"id":397993,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9588,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":427743,"name":"Michelle E. St. John","orcid":"0000-0001-7588-5593","position":1,"is_corresponding":false},{"id":1174461,"name":"Dylan Chau","orcid":null,"position":2,"is_corresponding":false},{"id":1174462,"name":"Chloe Clair","orcid":null,"position":3,"is_corresponding":false},{"id":1174177,"name":"HoWan Chan","orcid":"0009-0003-4519-6035","position":4,"is_corresponding":false},{"id":439777,"name":"Roi Holzman","orcid":"0000-0002-2334-2551","position":5,"is_corresponding":false},{"id":392561,"name":"Christopher H. Martin","orcid":"0000-0001-7989-9124","position":6,"is_corresponding":false},{"id":1174460,"name":"Anson Tan","orcid":null,"position":0,"is_corresponding":true}],"reference_count":77,"raw_metadata":null,"created_at":"2026-07-19T01:19:43.776284Z","pmid":"38187684","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}