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Hadrosaurid (duck-billed) dinosaur bonebeds are exceedingly prevalent in upper Cretaceous (Campanian-Maastrichtian) strata from the Midwest of North America (especially Alberta, Canada, and Montana, U.S.A) but are less frequently documented from more northern regions. The Wapiti Formation (Campanian-Maastrichtian) of northwestern Alberta is a largely untapped resource of terrestrial palaeontological information missing from southern Alberta due to the deposition of the marine Bearpaw Formation. In 2018, the Boreal Alberta Dinosaur Project rediscovered the Spring Creek Bonebed, which had been lost since 2002, along the northern bank of the Wapiti River, southwest of Grande Prairie. Earlier excavations and observations of the Spring Creek Bonebed suggested that the site yielded young hadrosaurines. Continued work in 2018 and 2019 recovered ~300 specimens that included a minimum of eight individuals, based on the number of right humeri. The morphology of several recovered cranial elements unequivocally supports lambeosaurine affinities, making the Spring Creek sample the first documented occurrence of lambeosaurines in the Wapiti Formation. The overall size range and histology of the bones found at the site indicate that these animals were uniformly late juveniles, suggesting that age segregation was a life history strategy among hadrosaurids. Given the considerable size attained by the Spring Creek lambeosaurines, they were probably segregated from the breeding population during nesting or caring for young, rather than due to different diet and locomotory requirements. Dynamic aspects of life history, such as age segregation, may well have contributed to the highly diverse and cosmopolitan nature of Late Cretaceous hadrosaurids., Competing Interests: The authors declare that they have no competing interests., (© 2021 Holland et al.)

Cluster analysis is one of the most commonly used methods in palaeoecological studies, particularly in studies investigating biogeographic patterns. Although a number of different clustering methods are widely used, the approach and underlying assumptions of many of these methods are quite different. For example, methods may be hierarchical or non-hierarchical in their approaches, and may use Euclidean distance or non-Euclidean indices to cluster the data. In order to assess the effectiveness of the different clustering methods as compared to one another, a simulation was designed that could assess each method over a range of both cluster distinctiveness and sampling intensity. Additionally, a non-hierarchical, non-Euclidean, iterative clustering method implemented in the R Statistical Language is described. This method, Non-Euclidean Relational Clustering (NERC), creates distinct clusters by dividing the data set in order to maximize the average similarity within each cluster, identifying clusters in which each data point is on average more similar to those within its own group than to those in any other group. While all the methods performed well with clearly differentiated and well-sampled datasets, when data are less than ideal the linkage methods perform poorly compared to non-Euclidean based k-means and the NERC method. Based on this analysis, Unweighted Pair Group Method with Arithmetic Mean and neighbor joining methods are less reliable with incomplete datasets like those found in palaeobiological analyses, and the k-means and NERC methods should be used in their place.

Quantitative morphometric analyses, particularly ontogenetic allometry, are common methods used in quantifying shape, and changes therein, in both extinct and extant organisms. Due to incompleteness and the potential for restricted sample sizes in the fossil record, palaeobiological analyses of allometry may encounter higher rates of error. Differences in sample size between fossil and extant studies and any resulting effects on allometric analyses have not been thoroughly investigated, and a logical lower threshold to sample size is not clear. Here we show that studies based on fossil datasets have smaller sample sizes than those based on extant taxa. A similar pattern between vertebrates and invertebrates indicates this is not a problem unique to either group, but common to both. We investigate the relationship between sample size, ontogenetic allometric relationship and statistical power using an empirical dataset of skull measurements of modern Alligator mississippiensis. Across a variety of subsampling techniques, used to simulate different taphonomic and/or sampling effects, smaller sample sizes gave less reliable and more variable results, often with the result that allometric relationships will go undetected due to Type II error (failure to reject the null hypothesis). This may result in a false impression of fewer instances of positive/negative allometric growth in fossils compared to living organisms. These limitations are not restricted to fossil data and are equally applicable to allometric analyses of rare extant taxa. No mathematically derived minimum sample size for ontogenetic allometric studies is found; rather results of isometry (but not necessarily allometry) should not be viewed with confidence at small sample sizes.