Transient analyses of population dynamics using matrix projection models

The bulk of theoretical population biology has focused on long-term, asymptotic population dynamics for which tractable analytical solutions can be derived for particular questions. Following suit, the vast majority of empirical studies have focused on the established parameters provided by theory, such as the asymptotic population growth rate associated with a stable stage structure. But ‘there is nothing permanent [in natural environments] except change’ (Heraclitus), and thus there are good reasons to expect nonstable stage structures in real populations. The urgency of global change is indeed prompting increasing popularity of studying the transient dynamics caused by nonstable stage structures that occur before asymptotic dynamics are reached. This chapter provides an introduction to the concepts and analysis of transient dynamics using matrix projection models and ample examples.

Illuminating women’s hidden contribution to the foundation of theoretical population genetics

Plentiful evidence shows an historic and continuing gender gap in participation and success in scientific research. However, less attention has been directed at clarifying obscured contributions of women to science. The lack of visible women role models (particularly in computational fields) contributes to a reduced sense of belonging and retention among women. We seek to counteract this cycle by illuminating the contribution of women programmers to the foundation of our own fields—population and evolutionary genetics. We consider past ‘acknowledged programmers’ (APs), who developed, ran, and sometimes analyzed the results of early computer programs. Due to authorship norms at the time, these programmers were credited in the acknowledgments sections of manuscripts, rather than being recognized as authors. For example, one acknowledgement reads “I thanks Mrs. M. Wu for help with the numerical work, and in particular for computing table I.”. We identified APs in Theoretical Population Biology articles published between 1970 and 1990. While only 7% of authors were women, 43% of APs were women. This significant difference (p = 4.0×10−10) demonstrates a substantial proportion of women’s contribution to foundational computational population genetics has been unrecognized. The proportion of women APs, as well as number of APs decreased over time. These observations correspond to the masculinization of computer programming, and the shifting of programming responsibilities to individuals credited as authors (likely graduate students). Finally, we note recurrent APs who contributed to several highly-cited manuscripts. We conclude that, while previously overlooked, historically, women have made substantial contributions to computational biology.