APA
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Higham, T., Ferry, L. A., Schmitz, L., Irschick, D., Starko, S., Anderson, P. S., … Niklas, K. (2021). Linking ecomechanical models and functional traits to understand phenotypic diversity. Trends in Ecology &Amp; Evolution.
Chicago/Turabian
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Higham, T., L. A. Ferry, L. Schmitz, D. Irschick, S. Starko, P. S. Anderson, P. J. Bergmann, et al. “Linking Ecomechanical Models and Functional Traits to Understand Phenotypic Diversity.” Trends in Ecology & Evolution (2021).
MLA
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Higham, T., et al. “Linking Ecomechanical Models and Functional Traits to Understand Phenotypic Diversity.” Trends in Ecology &Amp; Evolution, 2021.
BibTeX Click to copy
@article{t2021a,
title = {Linking ecomechanical models and functional traits to understand phenotypic diversity.},
year = {2021},
journal = {Trends in Ecology & Evolution},
author = {Higham, T. and Ferry, L. A. and Schmitz, L. and Irschick, D. and Starko, S. and Anderson, P. S. and Bergmann, P. J. and Jamniczky, H. and Monteiro, L. R. and Navon, D. and Messier, J. and Carrington, E. and Farina, S. and Feilich, K. L. and Hernandez, L. and Johnson, Michele A. and Kawano, S. M. and Law, C. J. and Longo, S. J. and Martin, Christopher H. and Martone, P. and Rico‐Guevara, A. and Santana, S. E. and Niklas, K.}
}
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, we identify key factors needed for mass data collection, analysis, and the dissemination of models relevant to this framework.