Emily Charlotte Watt

Metamorphosis, a common and spectacular developmental process, involves major phenotypic changes often linked to environmental transitions. Understanding how these changes affect morphological evolution is crucial for examining metamorphosis's evolutionary impacts. In this study, we analysed the role of metamorphosis and life cycle variation on the morphological evolution of the mandible in Caudata (salamanders and newts), a clade that exhibits a great diversity of life cycles and ecologies. We focused on the mandible, a key component of the masticatory apparatus, to investigate how life cycle variation may influence the diversification of feeding modes. Using 3D geometric morphometrics on 317 extant species of Caudata, we found that both life cycle and size influence mandible shape, with complex interactions between these factors. The morphology of the mandibular bones evolved more independently in species undergoing complete metamorphosis compared to those with partial metamorphosis, likely facilitating feeding diversification in terrestrial adults. On the other hand, high morphological integration in species undergoing partial metamorphosis could promote the rapid evolution of traits, resulting in the differentiation of more disparate morphologies, potentially aiding paedomorphic species in adapting to challenging environments. This study highlights the interplay between metamorphosis and the environment in shaping morphological evolution among species and provides new insights into the role of heterochrony in the morphological diversification of organisms. Read the free Plain Language Summary for this article on the Journal blog.

Evolution of the mandibular structure has played a key role in the taxonomic diversification and niche exploration of tetrapods, from the initial water-to-land transition to the origin and radiation of mammals. While jaw evolution through these key transition points have long attracted attention, no studies of jaw evolution to date capture the breadth of tetrapod diversity and evolutionary history. Here, we reconstruct the compositional evolution of the tetrapod mandible with a comprehensive dataset of 36 traits scored in 3047 species. This sampling spans the earliest eotetrapodiforms to extant amphibians, mammals, and reptiles and birds, capturing immense ecological, developmental, and taxonomic diversity among a near-even split of extant and fossil tetrapods. We find that lower jaw morphology rapidly canalises at the base of each major clade, including, Eotetrapodiformes, Amniota, Synapsida, Sauropsida, and Amphibia, as well as subclades within those groups, and that, as a result, jaw compositional variation is highly phylogenetically structured. We estimate an average of over 100 shifts in three key traits: number of elements (dermal and endochondral bones), number of tooth-bearing elements, and total teeth per hemimandible, with symmetrical rates of gains and losses estimated for the number of elements, and correlated evolution between these three characters. Although novel elements arise occasionally, disparity in jaw composition overwhelmingly decreases as clades canalise rapidly, successively, and pervasively through tetrapod evolutionary history.

Synopsis: Artificial intelligence (AI) is poised to revolutionize many aspects of science, including the study of evolutionary morphology. While classical AI methods such as principal component analysis and cluster analysis have been commonplace in the study of evolutionary morphology for decades, recent years have seen increasing application of deep learning to ecology and evolutionary biology. As digitized specimen databases become increasingly prevalent and openly available, AI is offering vast new potential to circumvent long-standing barriers to rapid, big data analysis of phenotypes. Here, we review the current state of AI methods available for the study of evolutionary morphology, which are most developed in the area of data acquisition and processing. We introduce the main available AI techniques, categorizing them into 3 stages based on their order of appearance: (1) machine learning, (2) deep learning, and (3) the most recent advancements in large-scale models and multimodal learning. Next, we present case studies of existing approaches using AI for evolutionary morphology, including image capture and segmentation, feature recognition, morphometrics, and phylogenetics. We then discuss the prospectus for near-term advances in specific areas of inquiry within this field, including the potential of new AI methods that have not yet been applied to the study of morphological evolution. In particular, we note key areas where AI remains underutilized and could be used to enhance studies of evolutionary morphology. This combination of current methods and potential developments has the capacity to transform the evolutionary analysis of the organismal phenotype into evolutionary phenomics, leading to an era of “big data” that aligns the study of phenotypes with genomics and other areas of bioinformatics.

Directional trends in evolution have long captured the attention of biologists, and are particularly interesting when they reflect fundamental developmental processes that underlie morphological change. Here, we apply deep time data and a phylogenetic comparative framework to assess two fundamental “laws” – Williston’s law of phenotypic simplification and Dollo’s law of irreversibility – in the tetrapod mandible, a structure that has sustained the same primary function of feeding for nearly 400 million years. In spite of this conserved function, the tetrapod mandible has undergone numerous morphological and compositional changes during and since the initial water-to-land transition around 390Ma. To quantify these shifts, we reconstructed the compositional ev olution of the mandible with 31 traits scored in 568 species from early tetrapods through to modern amphibians, thereby capturing immense developmental and ecological diversity as well as an excellent fossil record. Mandibular complexity and jaw disparity are highest at the base of the tetrapod tree and generally decrease through time, with stasis dominating over the last ~160M years. Nonetheless, we find a lack of support for Williston’s and Dollo’s laws, with loss and gain of jaw components equally likely throughout the course of early tetrapod and amphibian evolution. Combined, our results demonstrate that evolutionary patterns of mandibular complexity are more nuanced than either Williston’s or Dollo’s laws allow. Thus, laws of simplification are too crude to capture the evolutionary processes underlying the evolution of even a functionally conserved structure through deep time. Summary: The lower jaw is a key innovation in vertebrate evolution with a unifying primary function: feeding. In spite of this conserved function, the jaw is extremely diverse in shape and composition. In limbed vertebrates (tetrapods), the jaw evolves from a complex structure comprising multiple elements and high numbers of teeth towards a simpler structure comprising few elements and generally fewer teeth. Superficially, this pattern suggests support for both Williston’s and Dollo’s laws of phenotypic simplification and irreversibility, respectively. However, we find a lack of support for either law in the jaw of the earliest tetrapods and amphibians, adding to growing literature refuting overly simplified “laws” governing organismal evolution.