Abstract-We seek to understand the current state of equity, scalability, and sustainability of data science education infrastructure in both the U.S. and Canada. Our analysis of the technological, funding, and organizational structure of four types of institutions shows an increasing divergence in the ability of universities across the United States to provide students with accessible data science education infrastructure, primarily JupyterHub. We observe that generally liberal arts colleges, community colleges, and other institutions with limited IT staff and experience have greater difficulty setting up and maintaining JupyterHub, compared to well-funded private institutions or large public research universities with a deep technical bench of IT staff. However, by leveraging existing public-private partnerships and the experience of Canada's national JupyterHub (Syzygy), the U.S. has an opportunity to provide a wider range of institutions and students access to JupyterHub.

We outline a synthesis of strategies created in collaboration with 35+ colleges and universities on how to advance undergraduate data science education on a national scale. The four core pillars of this strategy include the integration of data science education across all domains, establishing adoptable and scalable cyberinfrastructure, applying data science to non-traditional domains, and incorporating ethical content into data science curricula. The paper analyzes UC Berkeley's method of accelerating the national advancement of data science education in undergraduate institutions and examines the recent innovations in autograders for assignments which helps scale such programs. The conversation of ethical practices with data science are key to mitigate social issues arising from computing, such as incorporating anti-bias algorithms. Following these steps will form the basis of a scalable data science education system that prepares undergraduate students with analytical skills for a datacentric world.

Many territorial species have a mating system characterized by males establishing home ranges in the breeding grounds prior to females, resulting in males competing for territories and females choosing a mate upon their arrival. It remains unknown, however, how the outcomes of decisions surrounding territory establishment and mate choice are influenced by the spatial configuration of the breeding grounds. We use a spatially explicit, individual‐based model to investigate the sex‐specific effects of these decisions on reproductive success. In our model, males that arrive earlier obtain higher quality territories and improve their chances for extra‐pair copulations. Females can choose their mate to maximize the quality of the male or to attempt to minimize the density of other females near their nesting site to avoid competition. Females therefore face a tradeoff between high‐density regions around high‐quality males and low‐quality males in areas of low competition. Our model predicts a negative correlation between male and female reproductive success under a wide range of conditions when the majority of the territories are on the margins of the breeding area. Most notably, this sexual conflict arises as an edge effect suggesting that fragmentation of breeding habitats could impact the consequences of mate choice in many species with territorial breeding habits.