Burrowing into the past: Extending modelled breeding niche spaces of burrowing procellariiforms by merging fossil and historic data

Predicting species’ potential distributions and niches requires multi-scale data encompassing the past and present. Increasingly, researchers have advocated using historical contexts to inform ecological niche models (ENMs). Two key sources of past distributions are fossils and historical records. Fossils are subject to sampling and taphonomy biases but can offer insights into the temporal dynamics over millennia. Historical records are filtered by human perceptions and biases and have a shorter temporal range but compared to fossils provide different contextual information from a broader range of habitats. New Zealand has a relatively short history of human occupation and rich fossil archives and historical literature. Approximately 25% of the world’s seabirds, nearly half of which are endemic, breed in New Zealand. Since human arrival in New Zealand, many seabird populations have declined in numbers and breeding ranges, primarily due to introduced mammalian predators. Here, we explored the ecological niche space for breeding colonies of three size groups of burrowing procellariiforms using four admixtures of locational records (fossil bones, fossil bones + historical observations, historical observations, and post-1990 observational records). We fitted ENMs using the maximum entropy algorithm and calculated niche metrics. For all groups, the breeding niche space captured separately by the fossils and historical data had low overlap with each other and reflected different environmental aspects. The combined fossil + historic datasets predicted a niche that overlapped the post-1990 observed niche. Moreover, the combination of the fossil and historic datasets demonstrated that breeding grounds, now restricted mainly to predator-free settings, were once more widespread across New Zealand. We show that historical and fossil datasets complement each other mitigating biases unique to either dataset. Together, such records can provide critical insights into the historical drivers of species range contractions, contextualising current ecosystems.