Abstract. Evolutionary developmental biology seeks to elucidate the developmental mechanisms underlying phenotypic evolution. Central to this endeavor is the quantitative analysis of morphological variation, for which morphometric approaches have become indispensable tools. While morphometric methods have been extensively applied in paleontological research across diverse fossil groups, certain taxa remain underexplored. Among these, ostracods (Crustacea) represent a particularly promising yet underutilized group for such analyses. The suitability of ostracods for evolutionary and developmental investigations stems from several key attributes: their near-ubiquitous distribution across aquatic habitats, a remarkable taxonomic and morphological diversity, and an exceptional fossil record spanning geological time scales. Traditional morphometric approaches are constrained by the time-intensive nature of data acquisition, limiting the extent of achievable datasets. To address this bottleneck, we evaluate the efficacy of AutoMorph, a high-throughput imaging pipeline, for automated extraction of size and shape data from ostracod valves. We apply this approach to two ostracod species, Leucocythere dorsotuberosa and Leucocytherella sinensis, sampled from six lakes across the Tibetan Plateau, a region offering aquatic ecosystems with high endemism, providing an ideal setting for investigating ecological and evolutionary responses through morphological approaches. Our findings demonstrate that the AutoMorph pipeline successfully extracts morphometric measurements and coordinate data from ostracod valves, substantially reducing processing time while minimizing subjective bias inherent in manual approaches. This methodological advancement facilitates the generation of extensive datasets, thereby enabling more comprehensive investigations of ecological and evolutionary processes on large spatial and temporal scales.
Hoehle et al. (Mon,) studied this question.