Stephanie N. Schmidt's research while affiliated with St. Olaf College and other places

... Digital full-body images of each specimen were photographed in the field (described by Muir et al., 2012), for use in assigning each specimen to one of four known morphs (Fig. 2) using both statistical and visual assignment methods (described by Muir et al., 2014). Statistical shape groups were identified using geometric morphometric analysis of head and body shape (Zelditch et al., 2012), as follows: (1) head and body shape were mapped separately using 2-dimensional coordinates (see Fig. 2 in Muir et al., 2014) by a single individual (MJH) to control for possible investigator bias (Arnqvist and Mårtensson, 1998;Fruciano, 2016;Robinson and Terhune, 2017;Fox et al., 2020); (2) head and body shape maps were converted into partial warp scores free of distortions from horizontal orientation, location, and size (Zelditch et al., 2012); (3) head and body warp scores were converted into principal components to reduce the number of dimensions (Zimmerman et al., 2009;Muir et al., 2014); and (4) individuals were assigned to head and body shape groups using a mixture model-based cluster analysis, with uncertainty of each individual belonging to a group (MCLUST v.4, implemented in R, Fraley and Raftery, 2009). Independent head and body shape groups were then used to assign individuals to morphs based on correspondence between head and body shape groups (Zimmerman et al., 2009): lean morph = long head + slender body; humper morph = short head + fat body; redfin morph = long head + fat body; and siscowet morph = short head + fat body. ...

... Additionally, meristic data such as counts of scales, gill rakers, or fin rays also are used in TM to increase discrimination power. Koelz (1929) was successful in discriminating among ecotypes, as evidenced in recent isotopic assignments of his museum collections, which were consistent with his "species" classifications made almost a hundred years earlier (Schmidt et al. 2009;Schmidt et al. 2011;Blanke et al. 2018). Nonetheless, the utility of TM ratios for describing taxonomic traits has been questioned (Reist 1986;Tatsuta et al. 2018), owing mainly to the problem of allometry (i.e., the effect of size on shape; Zelditch et al. 2012). ...

... In the Lake Ontario basin, cisco are a pelagic cold-water species that was historically a major component of the native forage fish assemblage and had high commercial, cultural, and recreational significance to coastal communities 29 . Cisco populations have sharply declined throughout the basin due to a combination of fishing pressure, habitat and water quality degradation, and competition from non-native aquatic species [30][31][32] . Some ongoing cisco restoration efforts involve reintroductions or augmentations from hatchery stocking programs; however, post-release survival rates are not well-described for this species in the Great Lakes region 32,33 . ...

... SIA has proven effective at delineating food web structure across a suite of diverse environments, including tropical pelagic ecosystems (MacKenzie et al. 2019), high Arctic food webs (Linnebjerg et al. 2016), the Southern Ocean (Stowasser et al. 2012), and eastern boundary systems (Miller et al. 2010;Madigan et al. 2012). SIA of an entire food web can be used to quantify important components of food web structure (Schmidt et al. 2007). These components include species' trophic position, an organism's place in a food web; isotopic niche, an organism's place in isotopic space that is distinct from but closely aligned with trophic niche; resource breadth, the diversity of the base of the food web; and spacing, the level of overall species packing or trophic redundancy (Layman et al. 2007). ...