For most marine organisms, species richness peaks in the Central Indo-Pacific region and declines longitudinally, a striking pattern that remains poorly understood. Here, we used phylogenetic approaches to address the causes of richness patterns among global marine regions, comparing the relative importance of colonization time, number of colonization events, and diversification rates (speciation minus extinction). We estimated regional richness using distributional data for almost all percomorph fishes (17 435 species total, including approximately 72% of all marine fishes and approximately 33% of all freshwater fishes). The high diversity of the Central Indo-Pacific was explained by its colonization by many lineages 5.3 -34 million years ago. These relatively old colonizations allowed more time for richness to build up through in situ diversification compared to other warm-marine regions. Surprisingly, diversification rates were decoupled from marine richness patterns, with clades in low-richness cold-marine habitats having the highest rates. Unlike marine richness, freshwater diversity was largely derived from a few ancient colonizations, coupled with high diversification rates. Our results are congruent with the geological history of the marine tropics, and thus may apply to many other organisms. Beyond marine biogeography, we add to the growing number of cases where colonization and time-for-speciation explain large-scale richness patterns instead of diversification rates.

The integration of theory and data drives progress in science, but a persistent barrier to such integration in ecology and evolutionary biology 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. A 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. To promote such interactive learning of quantitative models, we developed EcoEvoApps, a collection of free, open‐source, and multilingual 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 interactions, and landscape ecology. These 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 working with 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.