Results 121 to 130 of about 188,650 (215)

Undergraduate entomology field excursions are a valuable source of biodiversity data: a case for spider (Araneae) bycatches in ecological studies. [PDF]

Biodivers Conserv, 2021
Haddad CR.
europepmc   +1 more source

An unusual titanosaur axis from the Upper Cretaceous of Brazil and its significance for sauropod anatomy and systematics

The Anatomical Record, EarlyView.
Abstract The Upper Cretaceous São José do Rio Preto Formation (Bauru Group, southeastern Brazil) has yielded a fragmentary but taxonomically diverse record of titanosaur sauropods, although elements from cervical series remain scarce. Here, we describe a nearly complete sauropod axis from the Vila Ventura Paleontological Area, representing an uncommon ...
Bruno A. Navarro, Jeffrey A. Wilson Mantilla, Jhonata H. A. Martins, Fabiano V. Iori, Leonardo S. Paschoa, Alberto B. Carvalho, Joseli M. Piranha, Hussam Zaher   +7 more
wiley   +1 more source

Globally aggregated biodiversity data impact predictive and descriptive research. [PDF]

Proc Natl Acad Sci U S A
Steinke D, Gemeinholzer B, Martínez-Meyer E, Noesgaard D, Young A, Schigel D.   +5 more
europepmc   +1 more source

People are essential to linking biodiversity data. [PDF]

Database (Oxford), 2020
Groom Q, Güntsch A, Huybrechts P, Kearney N, Leachman S, Nicolson N, Page RDM, Shorthouse DP, Thessen AE, Haston E.   +9 more
europepmc   +1 more source

Osteohistology of two phorusrhacids reveals uninterrupted growth strategy

The Anatomical Record, EarlyView.
Abstract Phorusrhacidae were apex predators that primarily dominated South America ecosystems for at least 40 million years with their imposing size and predatory lifestyle—yet some aspects of their biology remain poorly understood. Osteohistology is a tool for understanding growth dynamics and biomechanical adaptations.
Lotta Dreyer, Christian Cooper, Jingmai O'Connor   +2 more
wiley   +1 more source

Omics exploration of deep-sea biodiversity: data from the "Pourquoi Pas les Abysses?" and eDNAbyss projects. [PDF]

Sci Data
Arnaud-Haond S, Trouche B, Liautard-Haag C, Alain K, Aubé J, Bonhomme F, Brandt MI, Caillarec-Joly A, Cambon MA, Cornette F, Cueff-Gauchard V, Durand P, de Vargas C, Felix C, Fuchs S, Genoscope Technical Team, Günther B, Henry N, Hourdez S, Jollivet D, Le Port AS, Lesongeur F, Maignien L, Comtet-Marre S, Matabos M, Omnes E, Peyret P, Pradillon F, Sarrazin J, Schauberger C, Tran Lu Y A, Ulloa O, Vaz S, Zeppili D, Viard F, Gavory F, Gaz S, Guy J, Jacoby E, Oliveira PH, Samson G, Aury JM, Wincker P, Pesant S, Poulain J, Belser C.   +45 more
europepmc   +1 more source

Over the edge: Empirical evidence for the cliff‐edge model of obstetric selection

The Anatomical Record, EarlyView.
Abstract The cliff‐edge model of obstetric selection maintains that larger neonates and smaller birth canals confer a positive selective advantage until labor becomes obstructed and vaginal delivery is no longer possible, eliciting an abrupt reduction in fitness.
Laura M. Watson, Pierre Frémondière, Kaspar Staub, Philipp Mitteroecker, Barbara Fischer, Martin Haeusler, Nicole M. Webb   +6 more
wiley   +1 more source

Prioritisation of ocean biodiversity data collection to deliver a sustainable ocean. [PDF]

Commun Earth Environ
Bridges AEH, Howell KL.
europepmc   +1 more source

A second species of non‐crocodyliform crocodylomorph from the Late Triassic fissure deposits of southwestern UK: Implications for locomotory ecological diversity in Saltoposuchidae

The Anatomical Record, EarlyView.
Abstract The Late Triassic–Early Jurassic fissures of the Bristol Channel area (southwest England and south Wales) are renowned for their diverse vertebrate faunas. These assemblages have yielded an array of predominantly small‐bodied forms that are crucial to our understanding of the early evolution of several major tetrapod clades.
Ewan H. Bodenham, Stephan N. F. Spiekman, Susannah C. R. Maidment, Paul Upchurch, Philip D. Mannion   +4 more
wiley   +1 more source

From literature to biodiversity data: mining arthropod organismal traits with machine learning. [PDF]

Biodivers Data J
Cornelius J, Detering H, Lithgow-Serrano O, Agosti D, Rinaldi F, Waterhouse RM.   +5 more
europepmc   +1 more source