bioRxivEcology
EcoEvoApps: Interactive Apps for Theoretical Models in Ecology and Evolutionary Biology
R. M. McGuire, K. T. Hayashi, X. Yan, M. Carita Vaz, D. Cinoglu, M. C. Cowen, A. Martinez-Blancas, L. L. Sullivan, S. Vazquez-Morales, G. S. Kandlikar
Abstract
O_LIThe integration of theory and data drives progress in science, but a persistent barrier to such integration in ecology and evolutionary biology (EEB) is that theory is often developed and expressed in the form of mathematical models that can feel daunting and inaccessible for students and empiricists with variable quantitative training and attitudes towards math. C_LIO_LIA promising way to make mathematical models more approachable is to embed them into interactive tools with which one can visually evaluate model structures and directly explore model outcomes through simulation. C_LIO_LITo promote such interactive learning of quantitative models, we developed EcoEvoApps, a collection of free, open-source (R/Shiny) apps that include model overviews, interactive model simulations, and code to implement these models directly in R. The package currently focuses on canonical models of population dynamics, species interaction, and landscape ecology. We also outline a vision and approach for growing the collection to include more models from across EEB. C_LIO_LIThese apps help illustrate fundamental results from theoretical ecology and can serve as valuable teaching tools in classroom settings. We present data from student surveys which show that students rate these apps as useful learning tools, and that using interactive apps leads to substantial gains in students interest and confidence in mathematical models. This points to the potential for interactive activities to make theoretical models more accessible to a wider audience, and thus facilitate the feedback between theory and data across ecology and evolutionary biology. C_LI
- research focus: software / tool
- research focus: benchmarking
- research focus: database / resource
- approach: experimental assay
- approach: wet-lab / biochemical assay
- approach: microscopy & imaging analysis
- approach: genetic perturbation / CRISPR
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