Advancing Our Understanding of Tropical Forests and Improving the Predictive Capability of Vegetation Models with Data–Model Integration at Barro Colorado Island

Tropical forests cycle large amounts of water, carbon, and energy between the land and atmosphere and are therefore essential components of the Earth system that must be adequately represented in models that predict the Earth’s future climate. Representing the structural and functional complexity of tropical forests requires the ability to make detailed observations to inform model algorithms and parameters. In this chapter, we show how decades of data collection at Barro Colorado Island (BCI) have contributed to the development and testing of large-scale vegetation models and highlight the ways that these models in turn have improved our understanding of dynamics at BCI and across tropical forests. By sharing, assembling, adapting, and filling gaps in these data, integrated teams of modelers and empiricists have developed BCI into a high value vegetation model testbed. We conclude with a discussion of future opportunities for data–model integration and call for a continued and strengthened collaboration between empiricists and modelers.