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.

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.

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. Joseph L Graves, Jr.

Bio:

Dr. Joseph Graves, Jr. received his Ph.D. in Environmental, Evolutionary and Systematic Biology from Wayne State University in 1988. In 1994 he was elected a Fellow of the Council of the American Association for the Advancement of Science (AAAS.) In 2012, he was chosen as one of the “Sensational Sixty” commemorating 60 years of the NSF Graduate Research Fellowship Award.  In 2017, he was listed as an “Outstanding Graduates” in Biology at Oberlin College; and was an “Innovator of the Year” in US Black Engineer Magazine.

His research in the evolutionary genomics of adaptation shapes our understanding of biological aging and bacterial responses to nanomaterials. He is presently Associate Director/co-PI of the Precision Microbiome Engineering (PreMiEr) Engineering Research Center of Excellence (Gen-4 ERC) funded by the National Science Foundation (2022—2027). He has published five books: A Voice in the Wilderness: A Pioneering Biologist Explains How Evolution Can Help Us Solve Our Biggest Problems, (New York: Basic Books), 2022; with Alan Goodman, Racism, Not Race: Answers to Frequently Asked Questions, Columbia University Press, 2022. Racism, Not Race was named by Kirkus Reviews as “One of the Best Non-Fiction 2021” and to its “Best Books About Being Black in America 2021”; Principles and Applications of Antimicrobial Nanomaterials, (Amsterdam NE: Elsevier),  2021; The Emperor's New Clothes: Biological Theories of Race at the Millennium, Rutgers University Press, 2005 and The Race Myth: Why We Pretend Race Exists in America, Dutton Press, 2005.

He leads programs addressing underrepresentation of minorities in science. He has aided underserved youth in Greensboro via the YMCA chess program.  He has also served on the Racial Reconciliation and Justice Commission, and COVID Vaccination Task Fore of the Episcopal Diocese of North Carolina. He also served as the science advisor to the Chicago, New Brunswick, and Methodist of Ohio Theological Seminaries through the AAAS Dialogues of Science, Ethics, and Religion (DoSER) program.

Abstract: 

In A Voice in the Wilderness, I discuss the story of how I became the first African American evolutionary biologist.  It was a life of strife that followed me everywhere I went. I was beset by imposter syndrome, by depression, by racism, by negligence, and contempt.  And yet I persevered and became a prominent scholar in evolutionary biology.  I have helped to lead the fight against scientific racism, utilizing my science a tool to resist exploitation and change the demography of the scientific enterprise.



Check out his most recent article here!