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      The diet of early birds based on modern and fossil evidence and a new framework for its reconstruction

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          ABSTRACT

          Birds are some of the most diverse organisms on Earth, with species inhabiting a wide variety of niches across every major biome. As such, birds are vital to our understanding of modern ecosystems. Unfortunately, our understanding of the evolutionary history of modern ecosystems is hampered by knowledge gaps in the origin of modern bird diversity and ecosystem ecology. A crucial part of addressing these shortcomings is improving our understanding of the earliest birds, the non‐avian avialans (i.e. non‐crown birds), particularly of their diet. The diet of non‐avian avialans has been a matter of debate, in large part because of the ambiguous qualitative approaches that have been used to reconstruct it. Here we review methods for determining diet in modern and fossil avians (i.e. crown birds) as well as non‐avian theropods, and comment on their usefulness when applied to non‐avian avialans. We use this to propose a set of comparable, quantitative approaches to ascertain fossil bird diet and on this basis provide a consensus of what we currently know about fossil bird diet. While no single approach can precisely predict diet in birds, each can exclude some diets and narrow the dietary possibilities. We recommend combining ( i) dental microwear, ( ii) landmark‐based muscular reconstruction, ( iii) stable isotope geochemistry, ( iv) body mass estimations, ( v) traditional and/or geometric morphometric analysis, ( vi) lever modelling, and ( vii) finite element analysis to reconstruct fossil bird diet accurately. Our review provides specific methodologies to implement each approach and discusses complications future researchers should keep in mind. We note that current forms of assessment of dental mesowear, skull traditional morphometrics, geometric morphometrics, and certain stable isotope systems have yet to be proven effective at discerning fossil bird diet. On this basis we report the current state of knowledge of non‐avian avialan diet which remains very incomplete. The ancestral dietary condition in non‐avian avialans remains unclear due to scarce data and contradictory evidence in Archaeopteryx. Among early non‐avian pygostylians, Confuciusornis has finite element analysis and mechanical advantage evidence pointing to herbivory, whilst Sapeornis only has mechanical advantage evidence indicating granivory, agreeing with fossilised ingested material known for this taxon. The enantiornithine ornithothoracine Shenqiornis has mechanical advantage and pedal morphometric evidence pointing to carnivory. In the hongshanornithid ornithuromorph Hongshanornis only mechanical advantage evidence indicates granivory, but this agrees with evidence of gastrolith ingestion in this taxon. Mechanical advantage and ingested fish support carnivory in the songlingornithid ornithuromorph Yanornis. Due to the sparsity of robust dietary assignments, no clear trends in non‐avian avialan dietary evolution have yet emerged. Dietary diversity seems to increase through time, but this is a preservational bias associated with a predominance of data from the Early Cretaceous Jehol Lagerstätte. With this new framework and our synthesis of the current knowledge of non‐avian avialan diet, we expect dietary knowledge and evolutionary trends to become much clearer in the coming years, especially as fossils from other locations and climates are found. This will allow for a deeper and more robust understanding of the role birds played in Mesozoic ecosystems and how this developed into their pivotal role in modern ecosystems.

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          Principal component analysis: a review and recent developments.

          Large datasets are increasingly common and are often difficult to interpret. Principal component analysis (PCA) is a technique for reducing the dimensionality of such datasets, increasing interpretability but at the same time minimizing information loss. It does so by creating new uncorrelated variables that successively maximize variance. Finding such new variables, the principal components, reduces to solving an eigenvalue/eigenvector problem, and the new variables are defined by the dataset at hand, not a priori, hence making PCA an adaptive data analysis technique. It is adaptive in another sense too, since variants of the technique have been developed that are tailored to various different data types and structures. This article will begin by introducing the basic ideas of PCA, discussing what it can and cannot do. It will then describe some variants of PCA and their application.
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            Testing for phylogenetic signal in comparative data: behavioral traits are more labile.

            The primary rationale for the use of phylogenetically based statistical methods is that phylogenetic signal, the tendency for related species to resemble each other, is ubiquitous. Whether this assertion is true for a given trait in a given lineage is an empirical question, but general tools for detecting and quantifying phylogenetic signal are inadequately developed. We present new methods for continuous-valued characters that can be implemented with either phylogenetically independent contrasts or generalized least-squares models. First, a simple randomization procedure allows one to test the null hypothesis of no pattern of similarity among relatives. The test demonstrates correct Type I error rate at a nominal alpha = 0.05 and good power (0.8) for simulated datasets with 20 or more species. Second, we derive a descriptive statistic, K, which allows valid comparisons of the amount of phylogenetic signal across traits and trees. Third, we provide two biologically motivated branch-length transformations, one based on the Ornstein-Uhlenbeck (OU) model of stabilizing selection, the other based on a new model in which character evolution can accelerate or decelerate (ACDC) in rate (e.g., as may occur during or after an adaptive radiation). Maximum likelihood estimation of the OU (d) and ACDC (g) parameters can serve as tests for phylogenetic signal because an estimate of d or g near zero implies that a phylogeny with little hierarchical structure (a star) offers a good fit to the data. Transformations that improve the fit of a tree to comparative data will increase power to detect phylogenetic signal and may also be preferable for further comparative analyses, such as of correlated character evolution. Application of the methods to data from the literature revealed that, for trees with 20 or more species, 92% of traits exhibited significant phylogenetic signal (randomization test), including behavioral and ecological ones that are thought to be relatively evolutionarily malleable (e.g., highly adaptive) and/or subject to relatively strong environmental (nongenetic) effects or high levels of measurement error. Irrespective of sample size, most traits (but not body size, on average) showed less signal than expected given the topology, branch lengths, and a Brownian motion model of evolution (i.e., K was less than one), which may be attributed to adaptation and/or measurement error in the broad sense (including errors in estimates of phenotypes, branch lengths, and topology). Analysis of variance of log K for all 121 traits (from 35 trees) indicated that behavioral traits exhibit lower signal than body size, morphological, life-history, or physiological traits. In addition, physiological traits (corrected for body size) showed less signal than did body size itself. For trees with 20 or more species, the estimated OU (25% of traits) and/or ACDC (40%) transformation parameter differed significantly from both zero and unity, indicating that a hierarchical tree with less (or occasionally more) structure than the original better fit the data and so could be preferred for comparative analyses.
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              PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals

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                Author and article information

                Contributors
                case.miller@connect.hku.hk
                mpittman@hku.hk
                Journal
                Biol Rev Camb Philos Soc
                Biol Rev Camb Philos Soc
                10.1111/(ISSN)1469-185X
                BRV
                Biological Reviews of the Cambridge Philosophical Society
                Blackwell Publishing Ltd (Oxford, UK )
                1464-7931
                1469-185X
                08 July 2021
                October 2021
                : 96
                : 5 ( doiID: 10.1111/brv.v96.5 )
                : 2058-2112
                Affiliations
                [ 1 ] Vertebrate Palaeontology Laboratory, Research Division for Earth and Planetary Science The University of Hong Kong Pokfulam Hong Kong SAR China
                Author notes
                [*] [* ] Authors for correspondence (Tel.: +852 9854 2273; E‐mail: case.miller@ 123456connect.hku.hk ); (Tel.: +852 5625 5019; E‐mail: mpittman@ 123456hku.hk )

                Author information
                https://orcid.org/0000-0002-6467-0199
                https://orcid.org/0000-0002-6149-3078
                Article
                BRV12743
                10.1111/brv.12743
                8519158
                34240530
                e28eeecb-a345-491b-834b-4895933d26a5
                © 2021 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 07 May 2021
                : 07 August 2020
                : 10 May 2021
                Page count
                Figures: 11, Tables: 3, Pages: 55, Words: 61979
                Funding
                Funded by: RAE Improvement Fund of the Faculty of Science, The University of Hong Kong
                Funded by: Research Grant Council of Hong Kong's General Research Fund
                Award ID: 17120920
                Award ID: 17103315
                Funded by: The University of Hong Kong Postgraduate Scholarship
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                October 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.8 mode:remove_FC converted:15.10.2021

                Ecology
                avialae,birds,dental microwear,diet,theropods,dinosaurs,finite element analysis,fossil,mechanical advantage,morphometrics,stable isotopes

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