Dr. Bryan Dewsbury | Dewsbury Lab

Bio:

Bryan Dewsbury is an Associate Professor of Biology at Florida International University where he also is an Associate Director of the STEM Transformation Institute. He received is Bachelors degree in Biology from Morehouse College in Atlanta, GA, and his Masters and PhD in Biology from Florida International University in Miami, FL. He is the Principal Investigator of the Science Education And Society (SEAS) program, where his team conducts research on the social context of education. He is a Fellow of the John N. Gardner Institute and a Director at RIOS (Racially-Just Inclusive Open Science) institute. He conducts faculty development and support for institutions interested in transforming their educational practices pertaining to creating inclusive environments and, in this regard, has worked with over 100 institutions across North America, United Kingdom and West Africa. He is a co-author of the book 'Norton's Guide to Equity-Minded Teaching', available for free as an E-book. He is the founder of the National Science Foundation (NSF) funded Deep Teaching Residency, a national workshop aimed at supporting faculty in transforming their classroom to more meaningfully incorporate inclusive practices. He is the creator of the MOOC called 'Inclusive Teaching' sponsored by HHMI Biointeractive which will be released on August 15th. Bryan is originally from the Republic of Trinidad and Tobago and proudly still calls the twin island republic home.

Abstract:

Education holds the promise of preparing students to be engaged, thriving participants in a socially just democracy. For that ideal to occur, the structure and experience of the classroom must reflect both its constituents and consider the socially just imaginaries in which we would all like to inhabit. Using examples from the civil rights era's interrogation of our society, we will explore how an introductory biology course can help fulfill higher

education's civic mission.



Check out his book here!

Check out his HHMI/Inclusive Teaching trailer here!



Watch the seminar here!

Dr. Bryan Dewsbury | Dewsbury Lab

Bio:

Bryan Dewsbury is an Associate Professor of Biology at Florida International University where he also is an Associate Director of the STEM Transformation Institute. He received is Bachelors degree in Biology from Morehouse College in Atlanta, GA, and his Masters and PhD in Biology from Florida International University in Miami, FL. He is the Principal Investigator of the Science Education And Society (SEAS) program, where his team conducts research on the social context of education. He is a Fellow of the John N. Gardner Institute and a Director at RIOS (Racially-Just Inclusive Open Science) institute. He conducts faculty development and support for institutions interested in transforming their educational practices pertaining to creating inclusive environments and, in this regard, has worked with over 100 institutions across North America, United Kingdom and West Africa. He is a co-author of the book 'Norton's Guide to Equity-Minded Teaching', available for free as an E-book. He is the founder of the National Science Foundation (NSF) funded Deep Teaching Residency, a national workshop aimed at supporting faculty in transforming their classroom to more meaningfully incorporate inclusive practices. He is the creator of the MOOC called 'Inclusive Teaching' sponsored by HHMI Biointeractive which will be released on August 15th. Bryan is originally from the Republic of Trinidad and Tobago and proudly still calls the twin island republic home.

Abstract:

Education holds the promise of preparing students to be engaged, thriving participants in a socially just democracy. For that ideal to occur, the structure and experience of the classroom must reflect both its constituents and consider the socially just imaginaries in which we would all like to inhabit. Using examples from the civil rights era's interrogation of our society, we will explore how an introductory biology course can help fulfill higher

education's civic mission.



Check out his book here!

Check out his HHMI/Inclusive Teaching trailer here!



Watch the seminar here!

Dr. Bryan Dewsbury | Dewsbury Lab

Bio:

Bryan Dewsbury is an Associate Professor of Biology at Florida International University where he also is an Associate Director of the STEM Transformation Institute. He received is Bachelors degree in Biology from Morehouse College in Atlanta, GA, and his Masters and PhD in Biology from Florida International University in Miami, FL. He is the Principal Investigator of the Science Education And Society (SEAS) program, where his team conducts research on the social context of education. He is a Fellow of the John N. Gardner Institute and a Director at RIOS (Racially-Just Inclusive Open Science) institute. He conducts faculty development and support for institutions interested in transforming their educational practices pertaining to creating inclusive environments and, in this regard, has worked with over 100 institutions across North America, United Kingdom and West Africa. He is a co-author of the book 'Norton's Guide to Equity-Minded Teaching', available for free as an E-book. He is the founder of the National Science Foundation (NSF) funded Deep Teaching Residency, a national workshop aimed at supporting faculty in transforming their classroom to more meaningfully incorporate inclusive practices. He is the creator of the MOOC called 'Inclusive Teaching' sponsored by HHMI Biointeractive which will be released on August 15th. Bryan is originally from the Republic of Trinidad and Tobago and proudly still calls the twin island republic home.

Abstract:

Education holds the promise of preparing students to be engaged, thriving participants in a socially just democracy. For that ideal to occur, the structure and experience of the classroom must reflect both its constituents and consider the socially just imaginaries in which we would all like to inhabit. Using examples from the civil rights era's interrogation of our society, we will explore how an introductory biology course can help fulfill higher

education's civic mission.



Check out his book here!

Check out his HHMI/Inclusive Teaching trailer here!



Watch the seminar here!

Ned Dochtermann | Dochtermann Lab

Abstract:

While behavioral syndromes are frequently argued to represent an optimal outcome of correlated selection, they also have the potential to constrain evolutionary responses. Via intraspecific and interspecific comparisons we attempted to determine whether behavioral variation was distributed in a manner consistent with either (or both) of these explanations. We compared the distribution of genetic variation across four populations of field crickets (Gryllus integer) and for seven behavioral measures. The distribution and orientation of genetic variation was conserved across populations and divergence among populations was constrained to a shared direction in multivariate space. We then compared the distribution of behavioral variation across five species of crickets and identified a strong phylogenetic signal. Combined, these intra- and interspecific comparisons are consistent with behavioral syndromes acting as constraints on evolutionary outcomes. Finally, in a natural population of deer mice (Peromyscus maniculatus) we compared the orientation of behavioral variation with the direction of selection acting on the population. We found that the distribution of behavioral variation was inconsistent with our a priori predictions. These three independent results suggest that intuitive adaptive explanations may be insufficient to explain the ubiquity of behavioral syndromes.

Check out the seminar here!

Ned Dochtermann | Dochtermann Lab

Abstract:

While behavioral syndromes are frequently argued to represent an optimal outcome of correlated selection, they also have the potential to constrain evolutionary responses. Via intraspecific and interspecific comparisons we attempted to determine whether behavioral variation was distributed in a manner consistent with either (or both) of these explanations. We compared the distribution of genetic variation across four populations of field crickets (Gryllus integer) and for seven behavioral measures. The distribution and orientation of genetic variation was conserved across populations and divergence among populations was constrained to a shared direction in multivariate space. We then compared the distribution of behavioral variation across five species of crickets and identified a strong phylogenetic signal. Combined, these intra- and interspecific comparisons are consistent with behavioral syndromes acting as constraints on evolutionary outcomes. Finally, in a natural population of deer mice (Peromyscus maniculatus) we compared the orientation of behavioral variation with the direction of selection acting on the population. We found that the distribution of behavioral variation was inconsistent with our a priori predictions. These three independent results suggest that intuitive adaptive explanations may be insufficient to explain the ubiquity of behavioral syndromes.

Check out the seminar here!

Ned Dochtermann | Dochtermann Lab

Abstract:

While behavioral syndromes are frequently argued to represent an optimal outcome of correlated selection, they also have the potential to constrain evolutionary responses. Via intraspecific and interspecific comparisons we attempted to determine whether behavioral variation was distributed in a manner consistent with either (or both) of these explanations. We compared the distribution of genetic variation across four populations of field crickets (Gryllus integer) and for seven behavioral measures. The distribution and orientation of genetic variation was conserved across populations and divergence among populations was constrained to a shared direction in multivariate space. We then compared the distribution of behavioral variation across five species of crickets and identified a strong phylogenetic signal. Combined, these intra- and interspecific comparisons are consistent with behavioral syndromes acting as constraints on evolutionary outcomes. Finally, in a natural population of deer mice (Peromyscus maniculatus) we compared the orientation of behavioral variation with the direction of selection acting on the population. We found that the distribution of behavioral variation was inconsistent with our a priori predictions. These three independent results suggest that intuitive adaptive explanations may be insufficient to explain the ubiquity of behavioral syndromes.

Check out the seminar here!

Ned Dochtermann | Dochtermann Lab

Abstract:

While behavioral syndromes are frequently argued to represent an optimal outcome of correlated selection, they also have the potential to constrain evolutionary responses. Via intraspecific and interspecific comparisons we attempted to determine whether behavioral variation was distributed in a manner consistent with either (or both) of these explanations. We compared the distribution of genetic variation across four populations of field crickets (Gryllus integer) and for seven behavioral measures. The distribution and orientation of genetic variation was conserved across populations and divergence among populations was constrained to a shared direction in multivariate space. We then compared the distribution of behavioral variation across five species of crickets and identified a strong phylogenetic signal. Combined, these intra- and interspecific comparisons are consistent with behavioral syndromes acting as constraints on evolutionary outcomes. Finally, in a natural population of deer mice (Peromyscus maniculatus) we compared the orientation of behavioral variation with the direction of selection acting on the population. We found that the distribution of behavioral variation was inconsistent with our a priori predictions. These three independent results suggest that intuitive adaptive explanations may be insufficient to explain the ubiquity of behavioral syndromes.

Check out the seminar here!

Ned Dochtermann | Dochtermann Lab

Abstract:

While behavioral syndromes are frequently argued to represent an optimal outcome of correlated selection, they also have the potential to constrain evolutionary responses. Via intraspecific and interspecific comparisons we attempted to determine whether behavioral variation was distributed in a manner consistent with either (or both) of these explanations. We compared the distribution of genetic variation across four populations of field crickets (Gryllus integer) and for seven behavioral measures. The distribution and orientation of genetic variation was conserved across populations and divergence among populations was constrained to a shared direction in multivariate space. We then compared the distribution of behavioral variation across five species of crickets and identified a strong phylogenetic signal. Combined, these intra- and interspecific comparisons are consistent with behavioral syndromes acting as constraints on evolutionary outcomes. Finally, in a natural population of deer mice (Peromyscus maniculatus) we compared the orientation of behavioral variation with the direction of selection acting on the population. We found that the distribution of behavioral variation was inconsistent with our a priori predictions. These three independent results suggest that intuitive adaptive explanations may be insufficient to explain the ubiquity of behavioral syndromes.

Check out the seminar here!

Dr. Van Savage

Bio:

I am a Professor in the Ecology and Evolutionary Biology and Biomathematics departments. A major goal of my research is to quantify and understand the possible functions, forms, and interactions of biological systems that result in the extraordinary diversity in nature. I have studied a wide range of areas such as metabolic scaling, consumer-resource interactions, rates of evolution, effects of global warming on ecosystems, tumor growth, and sleep. Complementary to this, I aim to understand how much variation around optima or averages is considered healthy or adaptive versus diseased or disturbed states, which are essentially deviations from normal or sustainable functioning. As I attempt to make progress on these questions, I join together ecology, evolutionary theory, physiology, mathematical modeling, image-analysis software, informatics, and biomedical sciences. Many theories, including some of my work, focus on optimal or average properties, but more recently, I have been working to obtain the large amounts of data necessary to characterize variation in key properties. My new findings about the diversity and variation in form and function are revealing flaws in current models, and I am working to develop new theories that incorporate realistic amounts of natural variation.

Abstract:

The question of which factors contribute to ecosystem and food webs stability is one of the most fundamental and foundational in all of ecology. Here I present findings from a new numerical model that allows us to include or exclude different potential factors, and I interpret these results using a novel method that examines how stability and connectance change with consumer-resource size ratios. In this way we are able to compare our predictions and model with empirically grounded data and known trends. Consequently, we are also able to study how variation in size distributions within food webs overall impact the stability of food webs. These results are followed by a more analytical mathematical treatment of how eigenvalue distributions—directly related to system stability—change depending on the structure of the interaction matrix. As part of this, I review and revisit seminal work by Robert May and Stefano Allesina, and connect with and synthesize some lesser known theorems from linear algebra to illuminate and understand some of the results from our numerical model. Finally, I talk about how this work might be extended to consider the impacts of increasing or fluctuating temperatures due to climate change, and possible directions for enlarging and extending the

mathematical concept of stability to something closer to its ecological meaning.

Dr. Van Savage

Bio:

I am a Professor in the Ecology and Evolutionary Biology and Biomathematics departments. A major goal of my research is to quantify and understand the possible functions, forms, and interactions of biological systems that result in the extraordinary diversity in nature. I have studied a wide range of areas such as metabolic scaling, consumer-resource interactions, rates of evolution, effects of global warming on ecosystems, tumor growth, and sleep. Complementary to this, I aim to understand how much variation around optima or averages is considered healthy or adaptive versus diseased or disturbed states, which are essentially deviations from normal or sustainable functioning. As I attempt to make progress on these questions, I join together ecology, evolutionary theory, physiology, mathematical modeling, image-analysis software, informatics, and biomedical sciences. Many theories, including some of my work, focus on optimal or average properties, but more recently, I have been working to obtain the large amounts of data necessary to characterize variation in key properties. My new findings about the diversity and variation in form and function are revealing flaws in current models, and I am working to develop new theories that incorporate realistic amounts of natural variation.

Abstract:

The question of which factors contribute to ecosystem and food webs stability is one of the most fundamental and foundational in all of ecology. Here I present findings from a new numerical model that allows us to include or exclude different potential factors, and I interpret these results using a novel method that examines how stability and connectance change with consumer-resource size ratios. In this way we are able to compare our predictions and model with empirically grounded data and known trends. Consequently, we are also able to study how variation in size distributions within food webs overall impact the stability of food webs. These results are followed by a more analytical mathematical treatment of how eigenvalue distributions—directly related to system stability—change depending on the structure of the interaction matrix. As part of this, I review and revisit seminal work by Robert May and Stefano Allesina, and connect with and synthesize some lesser known theorems from linear algebra to illuminate and understand some of the results from our numerical model. Finally, I talk about how this work might be extended to consider the impacts of increasing or fluctuating temperatures due to climate change, and possible directions for enlarging and extending the

mathematical concept of stability to something closer to its ecological meaning.