SYMPOSIA
Most submitted talks will be scheduled into concurrent sessions (rather than symposia), and will be organized by topic and arranged according to what is submitted. These concurrent sessions will be outlined closer to the conference. A select number of society sponsored symposia will be held at either the in-person or virtual conference, and are outlined below.
Virtual meeting symposia (May 29-30)
SSE Presidential Symposium: Determinants of Life History Evolution
Life histories are foundational to fitness and evolution. Evolutionary trajectories depend on the linkages among life history traits, due to genetic architecture, a mix of genetics and plasticity, or physiological and morphological constraints. This symposium explores these linkages and their implications for realized life histories and evolution. Speakers: Dr. Thomas Flatt, Dr. Kate Laskowski, and Dr. Anja Felmy.
SSE - W.D. HAMILTON AWARD SYMPOSIUM
The W. D. Hamilton Award for Outstanding Graduate Student Presentation will be given to a current or very recent graduate student who presents an outstanding talk based on their graduate work at the annual meeting. Finalists will present their talks during the Hamilton Award symposium during the virtual meeting. The application to become a Hamilton award finalist is part of registration for the annual meeting. Applicants must check a box during registration indicating their interest for the Hamilton Award and submit an abstract. For more information, see here.
SSB - ERNST MAYR AWARD SYMPOSIUM
The Ernst Mayr Award is given to the presenter of the outstanding student talk in the field of systematics at the annual meetings of the Society of Systematic Biologists (SSB). This is SSB's premier award, and is judged by the quality and creativity of the research completed over the course of the student's Ph.D. program. For more information, see here.
Organizer: SSB Awards Director
Organizer: SSB Awards Director
In-person award plenaries/symposia (June 20-24)
IDEA Award (June 20 - 7 pm)
asn - eARLY CAREER INVESTIGATOR (Jun 21 - PM)
sse - DOBZHANSKY (Jun 21 - PM)
Society-led in-person symposia (June 20-24)
ASN Vice Presidential Symposium - When, where and how can evolution rescue wild populations? (Jun 21 - AM)
When, where and how can evolution rescue wild populations?
Organizer: Amy Angert, Vice-President, American Society of Naturalists
It has been many years since several prominent reviews highlighted the challenges and opportunities for merging theory and empirical work on evolutionary rescue. In this symposium, we will assess the state of the art for detecting and predicting evolutionary rescue in wild populations.
TJ Clark-Wolf - The potential for evolutionary rescue under environmental change for vertebrates
Sarah Diamond - City upon a fitness hill
Claire Godineau - The two-edged sword of temporal variability in evolutionary rescue: sometimes it hurts, sometimes it helps
Emily Harmon - Buying time: plasticity, population persistence, and evolution
Mark Urban - Assisting gene flow in a complex and changing world
Organizer: Amy Angert, Vice-President, American Society of Naturalists
It has been many years since several prominent reviews highlighted the challenges and opportunities for merging theory and empirical work on evolutionary rescue. In this symposium, we will assess the state of the art for detecting and predicting evolutionary rescue in wild populations.
TJ Clark-Wolf - The potential for evolutionary rescue under environmental change for vertebrates
Sarah Diamond - City upon a fitness hill
Claire Godineau - The two-edged sword of temporal variability in evolutionary rescue: sometimes it hurts, sometimes it helps
Emily Harmon - Buying time: plasticity, population persistence, and evolution
Mark Urban - Assisting gene flow in a complex and changing world
Scopes & Kitzmiller Anniversary Symposium (Jun 21 - PM)
Join us for a two-part panel discussion on how lessons from the past can inform our strategies for the future and how we can continue the fight to ensure that accurate, evidence-based science remains a cornerstone of education for future generations. In 2025, we mark two significant milestones in the ongoing battle for science education: the 100th anniversary of the Scopes "Monkey" Trial and the 20th anniversary of the landmark Kitzmiller v. Dover trial. The Scopes trial brought public perceptions surrounding the teaching of evolution and religious values to the national stage and ultimately signaled a shift away from prohibition of teaching evolution in classrooms. The Kitzmiller decision, which ruled against the teaching of "intelligent design" in public schools, is a reminder of the critical role the courts play in safeguarding evidence-based science education. However, despite these important victories, science denial remains a pervasive issue. This session will explore the legacy of these two historic trials and examine the current challenges facing science education in the U.S. It will also address the increasing influence of misinformation, the role of scientific organizations in advocacy, and the importance of public policy in defending scientific literacy.
Speakers will include:
Kenneth R. Miller, Brown University biologist, textbook author, and lead witness at the Kitzmiller trial.
Richard Katzkee, Duke Law Appellate Division Director and Assistant Clinical Professor, former Vice President and Lead Attorney for Americans United for Separation of Church and State, and attorney for the plaintiffs in the Kitzmiller trial.
Joseph Graves, Professor of Biology at North Carolina A & T University, award winning-scholar
Amanda L. Townley, Executive Director of the National Center for Science Education and former Associate Professor of Science Education at Georgia Southern University.
Speakers will include:
Kenneth R. Miller, Brown University biologist, textbook author, and lead witness at the Kitzmiller trial.
Richard Katzkee, Duke Law Appellate Division Director and Assistant Clinical Professor, former Vice President and Lead Attorney for Americans United for Separation of Church and State, and attorney for the plaintiffs in the Kitzmiller trial.
Joseph Graves, Professor of Biology at North Carolina A & T University, award winning-scholar
Amanda L. Townley, Executive Director of the National Center for Science Education and former Associate Professor of Science Education at Georgia Southern University.
Machine learning and new inference algorithms: expanding what is possible in evolutionary biology and phylogenetic analysis (Jun 22 - PM)
Organizers:
Isabel Sanmartín, Real Jardín Botánico
Robert Thomson, University of Hawaiʻi
Description:
Investigators across different fields of evolutionary biology are increasingly turning their attention to more integrative and complex inference models. This is driven partly by the advent of next generation sequencing technologies, scaling up the numbers of genes, individuals and species sampled, and partly by the exponential growth of biodiversity and biogeographic databases at the local, regional and community scales. This massive increase in the quantity of data available has opened up a range of new questions but also unexpected challenges that require the development of more sophisticated approaches to data modeling. For example, a standing challenge is how to hybridize lineage-based, individual-based, and gene-based models to account for all axes of biodiversity loss (richness, abundance, diversity) in explaining the biotic impacts of climate change. The COVID pandemics introduced the need for models that are computationally efficient and can analyze in a short time thousands of sequences differing only in a few nucleotides. Statistical models in evolutionary biology are typically built around stochastic parameters linked by “hard-coded” dependencies, but there is an increasing demand for models that allow “hidden”, unobserved, components or that include a directional component (non-stationary, non equilibrium models). Finally, some commonly used models of evolutionary inference have issues with non identifiability: different model parameters induce the same probability distributions and are structurally or practically undistinguishable. Here, we review potential solutions and paths forward to address these challenges. These include the introduction of 'online' phylogenetics, the development of probabilistic programming languages, and the growing use of machine learning (AI) approaches in fields as diverse as phylogenetics, epidemiology, community ecology, and phylogeography. Although likelihood-based probabilistic modeling remains fundamental to evolutionary biology, these emerging approaches hold the promise of reducing computational time (accelerating analyses) and addressing more complex biological scenarios for which analytical solutions do not yet exist. They can also support traditional statistical inference, for example, by providing simulation-based 'shortcuts' for inferring difficult-to-model parameters ('hybrid' models).
Speakers:
**First session (1 hour): 2:30-3:30**
30 minutes - Daniele Silvestro: Emerging uses of AI in macroevolution,
15 minutes - Pablo Gutierrez de la Peña: Deep learning for birth-death modeling of extant phylogenetic trees
15 minutes - Albert Soewongsono: Inferring rates under density-dependent GeoSSE with geographic overlap using deep learning approach
**Second session (1.5 hour) 4:00 - 5:30**
30 minutes - Nicola De Maio: New methods for Pandemic-scale Phylogenetics
15 minutes - Isabel Sanmartin: TreePPL: A Probabilistic Programming Language for Statistical Phylogenetics
15 minutes - Analisa Milkey: How much information is there about the species tree even if gene trees are known without error?
30 minutes - Stephane Guindon: Recent advances in statistical phylogeography
Isabel Sanmartín, Real Jardín Botánico
Robert Thomson, University of Hawaiʻi
Description:
Investigators across different fields of evolutionary biology are increasingly turning their attention to more integrative and complex inference models. This is driven partly by the advent of next generation sequencing technologies, scaling up the numbers of genes, individuals and species sampled, and partly by the exponential growth of biodiversity and biogeographic databases at the local, regional and community scales. This massive increase in the quantity of data available has opened up a range of new questions but also unexpected challenges that require the development of more sophisticated approaches to data modeling. For example, a standing challenge is how to hybridize lineage-based, individual-based, and gene-based models to account for all axes of biodiversity loss (richness, abundance, diversity) in explaining the biotic impacts of climate change. The COVID pandemics introduced the need for models that are computationally efficient and can analyze in a short time thousands of sequences differing only in a few nucleotides. Statistical models in evolutionary biology are typically built around stochastic parameters linked by “hard-coded” dependencies, but there is an increasing demand for models that allow “hidden”, unobserved, components or that include a directional component (non-stationary, non equilibrium models). Finally, some commonly used models of evolutionary inference have issues with non identifiability: different model parameters induce the same probability distributions and are structurally or practically undistinguishable. Here, we review potential solutions and paths forward to address these challenges. These include the introduction of 'online' phylogenetics, the development of probabilistic programming languages, and the growing use of machine learning (AI) approaches in fields as diverse as phylogenetics, epidemiology, community ecology, and phylogeography. Although likelihood-based probabilistic modeling remains fundamental to evolutionary biology, these emerging approaches hold the promise of reducing computational time (accelerating analyses) and addressing more complex biological scenarios for which analytical solutions do not yet exist. They can also support traditional statistical inference, for example, by providing simulation-based 'shortcuts' for inferring difficult-to-model parameters ('hybrid' models).
Speakers:
**First session (1 hour): 2:30-3:30**
30 minutes - Daniele Silvestro: Emerging uses of AI in macroevolution,
15 minutes - Pablo Gutierrez de la Peña: Deep learning for birth-death modeling of extant phylogenetic trees
15 minutes - Albert Soewongsono: Inferring rates under density-dependent GeoSSE with geographic overlap using deep learning approach
**Second session (1.5 hour) 4:00 - 5:30**
30 minutes - Nicola De Maio: New methods for Pandemic-scale Phylogenetics
15 minutes - Isabel Sanmartin: TreePPL: A Probabilistic Programming Language for Statistical Phylogenetics
15 minutes - Analisa Milkey: How much information is there about the species tree even if gene trees are known without error?
30 minutes - Stephane Guindon: Recent advances in statistical phylogeography
AI in Evolutionary Biology (Jun 23 - PM)
Organizers:
James Boyko, University of Michigan
Jake Berv, University of Michigan
Michael Landis, Washington University
Symposium theme
In many scientific domains, an AI revolution is underway (LeCun et al., 2015). This revolution was sparked by the growing abundance of large scale data sets and the unparalleled ability of deep neural networks to learn from a variety of data types. And in evolutionary biology, we are just now beginning to explore how these powerful tools can be applied to outstanding questions within our field (Borowiec et al. 2022).
In our symposium we wish to explore how AI, and specifically deep learning, is being applied to basic questions of evolutionary biology by bringing together researchers from a variety of distinct evolutionary domains. Including a diverse set of evolutionary disciplines in our symposium serves a dual purpose. First, it allows us to engage with a broader audience of Evolution attendees; our symposium will have practical applications in several evolutionary disciplines. Second, it gives a variety of methodological perspectives on how deep learning techniques have been applied to otherwise separate domains. For example, the convolutional neural network, a fundamental building block of much AI research, has been applied to identify species based on images (Wäldchen et al. 2018), study complex morphology (Goswami and Kumar 2022), and build phylogenetic trees from sequence data (Smith and Hahn 2023). Under a traditional view, these tasks work with fundamentally different types of data and would likely have little to say to each other. However, applying AI to the question forces us to move away from traditional views - by taking a different perspective on long-standing evolutionary questions, we begin to see the essential similarities in structure of our data and identify common methodological threads.
Beyond methodological advances, integrating AI and evolutionary research offers an opportunity to take a step back from all-too-common pipelines, and ask ourselves: what do we want to know about biodiversity? Progress in other biological fields shows that AI is not just a tool for improving existing workflows but a means of reframing questions. For instance, in molecular biology, AI-driven protein prediction by tools like AlphaFold reframed the long-standing problem of determining 3D structures from sequences as a pattern-recognition challenge (Jumper et al. 2021). This enabled major breakthroughs that were not possible using traditional methods. For evolutionary biology, this reframing could target critical issues such as analyzing high-dimensional morphology, predicting adaptive responses to environmental change, or refining models of population genetics. However, evolutionary data bring several unique challenges. By bringing together the Evolution community in our AI-focused symposium, we hope to highlight specific problems, while seeking actionable solutions with the community. Furthermore, with many of the AI tools still being in their nascent stages, this is an ideal opportunity to come together as a field and discuss the outlook of AI in evolutionary research
James Boyko, University of Michigan
Jake Berv, University of Michigan
Michael Landis, Washington University
Symposium theme
In many scientific domains, an AI revolution is underway (LeCun et al., 2015). This revolution was sparked by the growing abundance of large scale data sets and the unparalleled ability of deep neural networks to learn from a variety of data types. And in evolutionary biology, we are just now beginning to explore how these powerful tools can be applied to outstanding questions within our field (Borowiec et al. 2022).
In our symposium we wish to explore how AI, and specifically deep learning, is being applied to basic questions of evolutionary biology by bringing together researchers from a variety of distinct evolutionary domains. Including a diverse set of evolutionary disciplines in our symposium serves a dual purpose. First, it allows us to engage with a broader audience of Evolution attendees; our symposium will have practical applications in several evolutionary disciplines. Second, it gives a variety of methodological perspectives on how deep learning techniques have been applied to otherwise separate domains. For example, the convolutional neural network, a fundamental building block of much AI research, has been applied to identify species based on images (Wäldchen et al. 2018), study complex morphology (Goswami and Kumar 2022), and build phylogenetic trees from sequence data (Smith and Hahn 2023). Under a traditional view, these tasks work with fundamentally different types of data and would likely have little to say to each other. However, applying AI to the question forces us to move away from traditional views - by taking a different perspective on long-standing evolutionary questions, we begin to see the essential similarities in structure of our data and identify common methodological threads.
Beyond methodological advances, integrating AI and evolutionary research offers an opportunity to take a step back from all-too-common pipelines, and ask ourselves: what do we want to know about biodiversity? Progress in other biological fields shows that AI is not just a tool for improving existing workflows but a means of reframing questions. For instance, in molecular biology, AI-driven protein prediction by tools like AlphaFold reframed the long-standing problem of determining 3D structures from sequences as a pattern-recognition challenge (Jumper et al. 2021). This enabled major breakthroughs that were not possible using traditional methods. For evolutionary biology, this reframing could target critical issues such as analyzing high-dimensional morphology, predicting adaptive responses to environmental change, or refining models of population genetics. However, evolutionary data bring several unique challenges. By bringing together the Evolution community in our AI-focused symposium, we hope to highlight specific problems, while seeking actionable solutions with the community. Furthermore, with many of the AI tools still being in their nascent stages, this is an ideal opportunity to come together as a field and discuss the outlook of AI in evolutionary research
Teaching Sex and Gender in Science Education (Jun 24 - AM)
9:30am - 12:30 pm - 24 June 2025, Athens GA
This symposium will explore the current science behind sex and gender, explore how educators can move their instruction beyond simple binary XX/XY paradigms, and provide educational materials for teaching this nuanced and difficult subject.
Dr Sara E Lipshutz - Duke University
Sara Lipshutz is an Assistant Professor in the Biology Department at Duke University. Her lab's research focuses on the evolution of behavior across weird and wonderfully diverse species of birds. This work bridges “muddy boots” experimental fieldwork with a variety of molecular and computational approaches in population genomics, transcriptomics, and neuroendocrinology. “Biological sex” can describe a complex suite of traits across multiple organizational levels, including gamete type, chromosomal inheritance, physiology, morphology, and behavior. Her
studies of sex associated traits aim to capture the full range of sex variability and diversity and offer practical guidance for conceptual frameworks, experimental designs, and analytical methods for studying sex.
Title: Multivariate models of animal sex: breaking binaries leads to a better understanding of evolution
Abstract: Scientists often rely on a binarized operationalization of animal sex, in which two discrete sexes are defined by gamete type. However, “biological sex” can describe a complex suite of traits across multiple organizational levels, including chromosomal inheritance, physiology, morphology, behavior, etc. To capture the full range of sex variability and diversity, we must critically assess our research approaches for studying sex associated traits. In this talk, I will provide practical guidance for conceptual frameworks, experimental designs, and analytical methods for studying and teaching the biology of sex. I invite fellow scientists and educators to conscientiously apply these inclusive approaches, to advance our biological understanding of sex and to encourage academically and socially responsible outcomes of our research.
Dr Thomas Sanger - Loyola University
Thomas J. Sanger is an associate professor in the Department of Biology at Loyola University Chicago. His lab performs research at the interface of evolutionary and developmental biology. He has studied the embryology and molecular regulation of vertebrate genitalia, including the process by which male and female genitalia differentiate. He has also taught the course, The Evolution of Animal Sex, for the past eight years. This course challenges student perceptions of biological sex from developmental, physiological, and evolutionary viewpoints. In this course, students also learn how to discuss stigmatized scientific topics with broad, non-scientific audiences.
Title: Shining light into the black box: The developmental bases of sexual diversity
Abstract: Sexual diversity among human and non-human animals is the subject of intense study across medical and biological disciplines. Yet, countless misconceptions about sex and sexual diversity exist in our society. Although science is thought to be objective and free of emotion, many people are uncomfortable talking about the biology of sex. That discomfort and fear leaves room for hostile attacks on the science of sex to easily propagate through political and social channels. This creates unique challenges for educators in this area. In this presentation, I will discuss the biological basis of sex and sexual diversity from the perspective of a developmental biologist. The hierarchical nature of development connects genetics to phenotypes. Development dictates how sexual diversity emerges within species. The evolution of development dictates how sexual diversity arises among species. I will use development to demonstrate how biologists can distill complexity down into understandable chunks to address the most pervasive misconceptions about sex, especially those actively being used to take away
people’s rights.
Dr Sarah Eddy - University of Minnesota – Twin Cities
Sarah L. Eddy (they|them) is an associate professor in the Department of Biology Teaching and Learning at the University of Minnesota- Twin Cities. They received a BS in Biological Sciences from Purdue University and a PhD in Zoology at Oregon State University. Sarah studied sexual selection in salamanders before shifting their research focus to the study of college classrooms through a Postdoctoral experience at the University of Washington. Their research generates data and resources that support college instructors to create instructional approaches, course climates, and content that promote student belonging, motivation, and learning. In addition to
scholarly publications, Sarah's work has been featured in the New York Times, The Atlantic, Science, and Insight into Diversity. Lab website: https://www.eddy-lab.org/
Title: From “completely erasure” to “there is a place for us here”: How narratives in biology courses influence the experiences of trans-spectrum undergraduates
Abstract: Biology is the study of the diversity of life, which includes diversity in sex, gender, sexual behavior, and sexual and romantic orientations. However, the few existing studies of biology textbooks and classrooms suggest that many textbook authors and classroom instructors represent only a narrow swath of this diversity which can lead to an over emphasis on binary sex, conflation of sex and gender, and reinforcement of essentialisms. To more fully characterize the current range of narratives about sex, gender, sexual behavior, and orientation (SGBO narratives) present in undergraduate biology courses, we interviewed a national sample of 53 biology majors whose genders do not align with the sex they were assigned at birth (i.e., trans-spectrum students) about the SGBO narratives they encountered in biology courses. We interviewed trans-spectrum students both because (a) they are a minoritized population in STEM and one aim of the project was to identify strategies to support them in biology and (b) research out of psychology suggests that the people who are best positioned to notice common narratives in a context are those that do not fit those narratives. We analyzed interviews using reflexive thematic analysis with the goal of identifying SGBO narrative in biology content and how these narratives supported or harmed these students’ sense of belonging in biology classrooms. We found five SGBO narratives that harmed trans-spectrum students’ sense of belonging. We also found three narratives that supported trans-spectrum students' belonging.
These narratives could manifest in the classroom in multiple ways ranging from short disclaimers to elaborate case studies. The ways the narratives manifested influenced their impact on at least some students. These narratives and how they manifest provide potential teaching suggestions to both support trans-spectrum in STEM classrooms and more accurately teach the diversity of biology of sex, gender, sexual behavior, and orientation.
Dr Cissy Ballen - Auburn University
Cissy Ballen is an associate professor at Auburn University in the Department of Biological Sciences. Prior to starting at Auburn, she completed postdoctoral research positions at Cornell University and the University of Minnesota, studying the effects of teaching practices and classroom culture on student outcomes in undergraduate biology. She completed a doctoral degree in evolutionary biology at the University of Sydney, Australia. As a discipline-based education researcher, Cissy directs multiple biology education reform efforts and is deeply engaged in the study of evidence-based and equitable teaching practices in higher education.
Title: Discussions of sexual diversity in nature increase student sense of belonging in biology
Abstract: Biological sex is a complex and highly variable trait; however, overly simplistic explanations are common in undergraduate biology classrooms. Here we test the impact of an accurate approach to teaching about the diversity of biological sex in organismal biology (‘treatment’ lecture) and compare this approach to a ‘traditional’ lecture section of the same introductory biology course. We show that (1) the treatment lecture has a positive impact on feelings of inclusion for LGBTQIA+ students, (2) the treatment lecture had a positive impact on LGBTQIA+ and TGNC (transgender and gender nonconforming) student experiences in the course compared to other students, (3) after the treatment lecture students were able to more accurately define sex and gender compared to the control section, and (4) regardless of treatment students reject the naturalistic fallacy. Results highlight the importance of teaching the diversity of biological sex in an accurate way and distinguishing sex from gender.
This symposium will explore the current science behind sex and gender, explore how educators can move their instruction beyond simple binary XX/XY paradigms, and provide educational materials for teaching this nuanced and difficult subject.
Dr Sara E Lipshutz - Duke University
Sara Lipshutz is an Assistant Professor in the Biology Department at Duke University. Her lab's research focuses on the evolution of behavior across weird and wonderfully diverse species of birds. This work bridges “muddy boots” experimental fieldwork with a variety of molecular and computational approaches in population genomics, transcriptomics, and neuroendocrinology. “Biological sex” can describe a complex suite of traits across multiple organizational levels, including gamete type, chromosomal inheritance, physiology, morphology, and behavior. Her
studies of sex associated traits aim to capture the full range of sex variability and diversity and offer practical guidance for conceptual frameworks, experimental designs, and analytical methods for studying sex.
Title: Multivariate models of animal sex: breaking binaries leads to a better understanding of evolution
Abstract: Scientists often rely on a binarized operationalization of animal sex, in which two discrete sexes are defined by gamete type. However, “biological sex” can describe a complex suite of traits across multiple organizational levels, including chromosomal inheritance, physiology, morphology, behavior, etc. To capture the full range of sex variability and diversity, we must critically assess our research approaches for studying sex associated traits. In this talk, I will provide practical guidance for conceptual frameworks, experimental designs, and analytical methods for studying and teaching the biology of sex. I invite fellow scientists and educators to conscientiously apply these inclusive approaches, to advance our biological understanding of sex and to encourage academically and socially responsible outcomes of our research.
Dr Thomas Sanger - Loyola University
Thomas J. Sanger is an associate professor in the Department of Biology at Loyola University Chicago. His lab performs research at the interface of evolutionary and developmental biology. He has studied the embryology and molecular regulation of vertebrate genitalia, including the process by which male and female genitalia differentiate. He has also taught the course, The Evolution of Animal Sex, for the past eight years. This course challenges student perceptions of biological sex from developmental, physiological, and evolutionary viewpoints. In this course, students also learn how to discuss stigmatized scientific topics with broad, non-scientific audiences.
Title: Shining light into the black box: The developmental bases of sexual diversity
Abstract: Sexual diversity among human and non-human animals is the subject of intense study across medical and biological disciplines. Yet, countless misconceptions about sex and sexual diversity exist in our society. Although science is thought to be objective and free of emotion, many people are uncomfortable talking about the biology of sex. That discomfort and fear leaves room for hostile attacks on the science of sex to easily propagate through political and social channels. This creates unique challenges for educators in this area. In this presentation, I will discuss the biological basis of sex and sexual diversity from the perspective of a developmental biologist. The hierarchical nature of development connects genetics to phenotypes. Development dictates how sexual diversity emerges within species. The evolution of development dictates how sexual diversity arises among species. I will use development to demonstrate how biologists can distill complexity down into understandable chunks to address the most pervasive misconceptions about sex, especially those actively being used to take away
people’s rights.
Dr Sarah Eddy - University of Minnesota – Twin Cities
Sarah L. Eddy (they|them) is an associate professor in the Department of Biology Teaching and Learning at the University of Minnesota- Twin Cities. They received a BS in Biological Sciences from Purdue University and a PhD in Zoology at Oregon State University. Sarah studied sexual selection in salamanders before shifting their research focus to the study of college classrooms through a Postdoctoral experience at the University of Washington. Their research generates data and resources that support college instructors to create instructional approaches, course climates, and content that promote student belonging, motivation, and learning. In addition to
scholarly publications, Sarah's work has been featured in the New York Times, The Atlantic, Science, and Insight into Diversity. Lab website: https://www.eddy-lab.org/
Title: From “completely erasure” to “there is a place for us here”: How narratives in biology courses influence the experiences of trans-spectrum undergraduates
Abstract: Biology is the study of the diversity of life, which includes diversity in sex, gender, sexual behavior, and sexual and romantic orientations. However, the few existing studies of biology textbooks and classrooms suggest that many textbook authors and classroom instructors represent only a narrow swath of this diversity which can lead to an over emphasis on binary sex, conflation of sex and gender, and reinforcement of essentialisms. To more fully characterize the current range of narratives about sex, gender, sexual behavior, and orientation (SGBO narratives) present in undergraduate biology courses, we interviewed a national sample of 53 biology majors whose genders do not align with the sex they were assigned at birth (i.e., trans-spectrum students) about the SGBO narratives they encountered in biology courses. We interviewed trans-spectrum students both because (a) they are a minoritized population in STEM and one aim of the project was to identify strategies to support them in biology and (b) research out of psychology suggests that the people who are best positioned to notice common narratives in a context are those that do not fit those narratives. We analyzed interviews using reflexive thematic analysis with the goal of identifying SGBO narrative in biology content and how these narratives supported or harmed these students’ sense of belonging in biology classrooms. We found five SGBO narratives that harmed trans-spectrum students’ sense of belonging. We also found three narratives that supported trans-spectrum students' belonging.
These narratives could manifest in the classroom in multiple ways ranging from short disclaimers to elaborate case studies. The ways the narratives manifested influenced their impact on at least some students. These narratives and how they manifest provide potential teaching suggestions to both support trans-spectrum in STEM classrooms and more accurately teach the diversity of biology of sex, gender, sexual behavior, and orientation.
Dr Cissy Ballen - Auburn University
Cissy Ballen is an associate professor at Auburn University in the Department of Biological Sciences. Prior to starting at Auburn, she completed postdoctoral research positions at Cornell University and the University of Minnesota, studying the effects of teaching practices and classroom culture on student outcomes in undergraduate biology. She completed a doctoral degree in evolutionary biology at the University of Sydney, Australia. As a discipline-based education researcher, Cissy directs multiple biology education reform efforts and is deeply engaged in the study of evidence-based and equitable teaching practices in higher education.
Title: Discussions of sexual diversity in nature increase student sense of belonging in biology
Abstract: Biological sex is a complex and highly variable trait; however, overly simplistic explanations are common in undergraduate biology classrooms. Here we test the impact of an accurate approach to teaching about the diversity of biological sex in organismal biology (‘treatment’ lecture) and compare this approach to a ‘traditional’ lecture section of the same introductory biology course. We show that (1) the treatment lecture has a positive impact on feelings of inclusion for LGBTQIA+ students, (2) the treatment lecture had a positive impact on LGBTQIA+ and TGNC (transgender and gender nonconforming) student experiences in the course compared to other students, (3) after the treatment lecture students were able to more accurately define sex and gender compared to the control section, and (4) regardless of treatment students reject the naturalistic fallacy. Results highlight the importance of teaching the diversity of biological sex in an accurate way and distinguishing sex from gender.
