Dr. Tara Smiley | Smiley Lab

Bio:

I am an evolutionary ecologist interested in how climate and landscape history shape the diversity, biogeography, and ecological structure of mammalian faunas across spatio-temporal scales. I test hypotheses about how changes in climate, tectonic activity, topographic complexity, and habitat heterogeneity impact communities and ecological processes at local scales and govern diversity at regional scales. To do so, I use the fossil record to investigate diversity patterns, macroevolutionary processes, and paleoecology, focusing on the history of small mammals during the Cenozoic. My work on the past is conducted in parallel with investigations of modern and historical small-mammal populations across broad climatic and environmental gradients today.

My research group integrates fieldwork, specimen-based research, and quantitative paleobiology. Primary tools of our research include stable isotope ecology and paleoenvironmental reconstruction, analysis of trait variation, diversification analysis, and coupling of geological and biological modeling approaches. We work in western North America and in the East African Rift, both tectonically active and dynamic landscapes with high species richness today and in the past. 



Abstract: 

Mountains across the globe are biodiversity hotspots for many different groups of plants and animals; however, the deep-time relationship between mountain building and biodiversity remains elusive and requires integration across disciplines in geosciences, paleontology, and biology. When and how did these hotspots form? What role do landscape and climate dynamics play in eco-evolutionary processes? Using modern and fossil records, as well as empirical and quantitative approaches, my research program investigates how the biodiversity of mammals has been influenced by tectonic and climate interactions that shape mountain landscapes and generate topographic and climatic gradients. In this presentation, I will focus on the diversification history and faunal structure of mammals in the Basin and Range Province of western North America across the Neogene, highlighting the role of tectonic extension and global warming during the Miocene Climate Optimum (17-14 million years ago) at multiple spatial scales. I will also share new research from coupled landscape-biotic evolution models to understand how tectonic uplift may both generate and preserve evidence of montane biodiversity hotspots in the fossil record.

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.

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.