To assess evolutionary processes in deep-time, it is essential to understand the roles of development and environment, both recorded through the morphological variability of fossil assemblages. Thanks to their great abundance and the high temporal resolution of their fossil record, conodont elements are ideal to address this issue. In this paper, we present the first quantitative study of a Carnian-Norian (late Triassic) assemblage of closely related P1 conodont elements. Using geometric morphometrics (landmarks, sliding-landmarks and elliptic Fourier analysis), we explore the main axes of phenotypic variation and relate them to classically used taxonomical characters. We show that some important taxonomic features follow laws of covariation, hence highlighting developmental constraints. Furthermore, the intraspecific variation within all considered species, either Carnian or Norian forms, is similarly restricted, emphasizing, for the first time in conodont P1 elements, a common line of least resistance to evolution, which means that similar intrinsic (developmental) factors were acting on these taxa and likely biased the evolutionary trajectories of all these taxa in a similar way. Since the evolution between Carnian and Norian forms is known to have followed a trajectory that is significantly different from the line of least resistance, strong extrinsic pressures, such as environmental disturbances, were probably at play around the Carnian-Norian boundary to counteract the effects of these intrinsic, developmental constraints.

Guenser et al 2018_Supplementary material_R codeThese are the code lines used in R software to perform the statistical analyses (STATIS and correlation tests).Supplementary_Tables_Variables_for_statistical_analysesThere are six tables containing variables (aligned coordinated after generalised Procruste superposition, or harmonics obtained from elliptical fourier analysis) we used for statistical analyses. Table 1 to 3 contain the variables from conodont elements we scanned. Table 4 to 6 contain the latter variables, as well as variables from the elements illustrated in the literature.Variables_used_for_statistical_analyses.zip