The role of niche specialization and narrowing in the evolution and extinction of the ichthyosaurs has been widely discussed in the literature. However, previous studies have concentrated on a qualitative discussion of these variables only. Here, we use the recently developed approach of quantitative ecospace modelling to provide a high-resolution quantitative examination of the changes in dietary and ecological niche experienced by the ichthyosaurs throughout their evolution in the Mesozoic. In particular, we demonstrate that despite recent discoveries increasing our understanding of taxonomic diversity among the ichthyosaurs in the Cretaceous, when viewed from the perspective of ecospace modelling, a clear trend of ecological contraction is visible as early as the Middle Jurassic. We suggest that this ecospace redundancy, if carried through to the Late Cretaceous, could have contributed to the extinction of the ichthyosaurs. Additionally, our results suggest a novel model to explain ecospace change, termed the 'migration model'.

Reconstructing ecological niche shifts during ontogeny in extinct animals with no living analogues is difficult without exceptional fossil collections. Here we demonstrate how a previously identified ontogenetic shift in the size and shape of the dentition in the early Toarcian ichthyosaur Stenopterygius quadriscissus accurately predicts a particular dietary shift. The smallest S. quadriscissus fed on small, burst‐swimming fishes, with a steady shift towards faster moving fish and cephalopods with increasing body size. Larger adult specimens appear to have been completely reliant on cephalopods, with fish completely absent from gut contents shortly after onset of sexual maturity. This is consistent with a previously proposed ontogenetic niche shift based on tooth shape and body size, corroborating the idea that dental ontogeny may be a useful predictor of dietary shifts in marine reptiles. Applying the theoretical framework used here to other extinct species will improve the resolution of palaeoecological reconstructions, where appropriate sample sizes exist.

We explore the functional, developmental, and evolutionary processes which are argued to produce tooth reduction in the extinct marine reptile Stenopterygius quadriscissus (Reptilia: Ichthyosauria). We analyze the relationship between mandible growth and tooth size, shape, and count, to establish an ontogenetic trend. The pattern in S. quadriscissus is consistent with hypotheses of tooth size reduction by neutral selection, and this unusual morphology (a functionally edentulous rostrum) was produced by a series of different evolutionary developmental changes that are known for other taxa showing tooth reduction and loss. Specifically, this species evolved functional edentulism by evolutionary changes in the growth allometry of the dentition and by altering growth rates through ontogeny. This observation supports previous hypotheses that S. quadriscissus underwent ontogenetic tooth reduction. Tooth reduction in S. quadriscissus may be caused by unique selective pressures resulting from prey choice and feeding behavior, expanding our current understanding of the mechanisms producing tooth reduction.

Cretaceous ichthyosaurs were relatively diverse in temperate latitudes, but few species have been described from the palaeotropics. Here, we describe a new ophthalmosaurid ichthyosaur, Muiscasaurus catheti gen. et sp. nov., from the Barremian–Aptian aged Paja Formation of Colombia. This species is known only from a partial skull and differs from all other ichthyosaurs in the unusual configuration of the external narial opening, slender rostrum, narrow postorbital region, and gracile dentition. It is the second ichthyosaur described from the Paja Formation, suggesting moderate taxonomic and ecological ichthyosaur diversity in the region during the Early Cretaceous.

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Quantitative ecospace models are a numerical approach to comparing the functional structure of different ecosystems on macroevolutionary time‐scales, by quantifying the distribution of functional ecological traits. Ecospace modelling has historically been restricted to a combination of visual interpretation and quantification via metrics such as mean sum of ranges. We argue that comparing ecosystem function in this way overlooks critical information about degrees of overlap and redundancy, and potentially misrepresents the role of “empty ecospace” in driving macroevolution. Fuzzy ecospace modelling (FEM) places conventional ecospace modelling within a fuzzy set‐theoretic framework, wherein functional groups are learned from the dataset, creating models which are sensitive to overlap and the role of empty ecospace. Fuzzy ecospace modelling is a machine learning program which quantifies functional ecological similarity, and uses this information to classify new taxa. It creates functional groups using a Gower dissimilarity coefficient‐based approach to the k‐medoids algorithm, and uses fuzzy discriminant analysis to classify the taxa present in another ecosystem into these clusters, based on minimal Gower dissimilarity with a fuzzy threshold. This has the effect of quantifying the similarity between these ecosystems in terms of their functional groups, accounting for total redundancy, partial redundancy/novelty and total novelty. By using fuzzy membership functions, FEM can classify taxa which are highly ecologically dissimilar (outliers with respect to all functional groups), taxa which are fully redundant (100% similarity to those in a given functional group) and taxa in‐between, which represent degrees of niche overlap. This can be used to compare the functional groups present in different ecosystems (as well as their degrees of overlap), and as a metric approach to comparing total ecological disparity. These results can be used to test models of the role of empty ecospace in macroevolutionary trends, or to investigate how ecosystems respond to global perturbations. Furthermore, it allows us to define numerically the concept of empty ecospace for n‐dimensional datasets. A cluster‐based approach to the quantification of ecospace allows for a numerical estimate of niche overlap, a value particularly difficult to quantify in fossil contexts.

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A number of metrics for quantifying the amount of functional redundancy in a community have been proposed over the years. Two of the most popular metrics are based on comparing a taxonomic diversity measure with a generalized form of the same measure that accounts for functional dissimilarities between taxa. These two metrics express redundancy as either an absolute or relative difference between the taxonomic diversity measure and its generalized form. Because they express the amount of redundancy in a community in terms of raw diversity values, both redundancy metrics are susceptible to the same issues that complicate the interpretation of most commonly used diversity indices. It is possible to overcome these issues by restating these two indices using a Hill numbers framework. As a growing number of authors have noted, these modified metrics provide a more intuitive quantitative definition of functional redundancy when used to rank communities. Beyond this intuitive definition, measuring redundancy in terms of Hill numbers allows researchers to control the influence of rare taxa on the output value, enabling ecologists to better predict how a community is expected to respond when exposed to an external perturbation that selectively eliminates rare or common taxa. Here I show that, of the two possible Hill number‐based redundancy metrics, the form based on a popular absolute redundancy metric is extremely sensitive to differences in taxonomic diversity and can provide a misleading picture of how much redundancy is present in a community. For this reason, I argue that Hill number‐based functional redundancy should be quantified using a relative metric that explicitly accounts for differences in effective taxonomic diversity. The proposed Hill number‐based relative redundancy measure is shown to provide a much more complete picture of the distribution of redundant taxa within a community, highlighting subtle patterns that are completely missed by the Hill number‐based absolute redundancy metric. I include open‐source R code for calculating the indices discussed here. Read the free Plain Language Summary for this article on the Journal blog.