Reconstructing large-scale climate patterns from sparse local records is crucial for understanding past climates. Yet, it remains challenging to derive those reconstructions due to the patchiness, uneven spatial distribution, and disparate nature of palaeoclimatic proxy records. In this study, Eichenseer and Jones developed a Bayesian hierarchical model to integrate ecological data with established geochemical proxies into a unified quantitative framework, which bridges the gap in the latitudinal coverage of proxy data. They showed that this framework has the potential to enhance quantitative palaeoclimatic reconstructions especially the latitudinal temperature gradient estimated from datasets with limited spatial sampling.