Hydrologic and geomorphic classifications have gained traction in response to the increasing need for basin-wide water resources management. Regardless of the selected classification scheme, an open scientific challenge is how to extend information from limited field sites to classify tens of thousands to millions of channel reaches across a basin. To address this spatial scaling challenge, we leveraged machine learning to predict reach-scale geomorphic channel types using publicly available geospatial data.
Compositional variation in early life parenting structures alters oxytocin and vasopressin 1a receptor development in prairie voles (Microtus ochrogaster)Forrest Rogers, Sara Freeman, Marina Anderson, Michelle Palumbo & Karen Bales
Paternal absence can significantly alter bio-behavioral development in many biparental species. This effect has generally been demonstrated by comparing the development of offspring reared under biparental care with those reared after removal of the father. However, studies employing this design conflate two significant modifications to early life experience: removal of father-specific qualities and the general reduction of offspring-directed care. In the socially monogamous prairie vole (Microtus ochrogaster), the experience of paternal absence without substitution during...