Cross-disciplinary information for understanding macroevolution

Many different macroevolutionary models can produce the same observations. Despite efforts in building more complex and realistic models, it may still be difficult to distinguish the processes that have generated the biodiversity we ob-serve. In this opinion we argue that we can make new progress by reaching out across disciplines, relying on independent data and theory to constrain macro -evolutionary inference. Using mainly paleontological insights and data, we illus-trate how we can eliminate less plausible or implausible models, and/or parts of parameter space, while applying comparative phylogenetic approaches. We em-phasize that such cross-disciplinary insights and data can be drawn between many other disciplines relevant to macroevolution. We urge cross-disciplinary training, and collaboration using common-use databases as a platform for increasing our understanding.

Automated summary

Despite efforts in building more complex models, it is still difficult to distinguish the processes that have generated biodiversity. By reaching out across disciplines and using independent data and theory, we can make new progress in macroevolutionary inference. Using paleontological insights and comparative phylogenetic approaches, less plausible models can be eliminated and our understanding can be increased through cross-disciplinary collaboration and training using common-use databases.