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Linking Ecomechanical Models And Functional Traits To Understand Phenotypic Diversity, T. E. Higham, L. A. Ferry, L. Schmitz, D. J. Irschick, S. Starko, P. S L Anderson, P. J. Bergmann, H. A. Jamniczky, L. R. Monteiro, D. Navon, J. Messier, E. Carrington, S. C. Farina, K. L. Feilich, L. P. Hernandez, Michele A. Johnson, S. M. Kawano, C. J. Law, S. J. Longo, C. H. Martin, P. T. Martone, A. Rico-Guevara, S. E. Santana, K. J. Niklas
Linking Ecomechanical Models And Functional Traits To Understand Phenotypic Diversity, T. E. Higham, L. A. Ferry, L. Schmitz, D. J. Irschick, S. Starko, P. S L Anderson, P. J. Bergmann, H. A. Jamniczky, L. R. Monteiro, D. Navon, J. Messier, E. Carrington, S. C. Farina, K. L. Feilich, L. P. Hernandez, Michele A. Johnson, S. M. Kawano, C. J. Law, S. J. Longo, C. H. Martin, P. T. Martone, A. Rico-Guevara, S. E. Santana, K. J. Niklas
Biology Faculty Research
Physical principles and laws determine the set of possible organismal phenotypes. Constraints arising from development, the environment, and evolutionary history then yield workable, integrated phenotypes. We propose a theoretical and practical framework that considers the role of changing environments. This 'ecomechanical approach' integrates functional organismal traits with the ecological variables. This approach informs our ability to predict species shifts in survival and distribution and provides critical insights into phenotypic diversity. We outline how to use the ecomechanical paradigm using drag-induced bending in trees as an example. Our approach can be incorporated into existing research and help build interdisciplinary bridges. Finally, …
Detecting Bias In Large-Scale Comparative Analyses: Methods For Expanding The Scope Of Hypothesis-Testing With Hormonebase, Michele A. Johnson, C. D. Francis, E. T. Miller, C. J. Downs, Maren N. Vitousek
Detecting Bias In Large-Scale Comparative Analyses: Methods For Expanding The Scope Of Hypothesis-Testing With Hormonebase, Michele A. Johnson, C. D. Francis, E. T. Miller, C. J. Downs, Maren N. Vitousek
Biology Faculty Research
To address large-scale questions in evolutionary biology, the compilation of data from a variety of sources is often required. This is a major challenge in the development of databases in organismal biology. Here, we describe the procedure we used to reconstruct the phylogeny of the 474 species represented in HormoneBase, including fish, amphibians, mammals, birds, and reptiles. We also provide the methodology used to compile vertebrate environmental, life history, and metabolic rate data for use in conjunction with the HormoneBase database to test hypotheses of the evolution of steroid hormone traits. We then report a series of analyses using these …