Applications of species distribution modeling to paleobiology

Species distribution modeling (SDM: statistical and/or mechanistic approaches to the assessment of range determinants and prediction of species occurrence) offers new possibilities for estimating and studying past organism distributions. SDM complements fossil and genetic evidence by providing (i) quantitative and potentially high-resolution predictions of the past organism distributions, (ii) statistically formulated, testable ecological hypotheses regarding past distributions and communities, and (iii) statistical assessment of range determinants. In this article, we provide an overview of applications of SDM to paleobiology, outlining the methodology, reviewing SDM-based studies to paleobiology or at the interface of paleo- and neobiology, discussing assumptions and uncertainties as well as how to handle them, and providing a synthesis and outlook. Key methodological issues for SDM applications to paleobiology include predictor variables (types and properties; special emphasis is given to paleoclimate), model validation (particularly important given the emphasis on cross-temporal predictions in paleobiological applications), and the integration of SDM and genetics approaches. Over the last few years the number of studies using SDM to address paleobiology-related questions has increased considerably. While some of these studies only use SDM (23%), most combine them with genetically inferred patterns (49%), paleoecological records (22%), or both (6%). A large number of SDM-based studies have addressed the role of Pleistocene glacial refugia in biogeography and evolution, especially in Europe, but also in many other regions. SDM-based approaches are also beginning to contribute to a suite of other research questions, such as historical constraints on current distributions and diversity patterns, the end-Pleistocene megafaunal extinctions, past community assembly, human paleobiogeography, Holocene paleoecology, and even deep-time biogeography (notably, providing insights into biogeographic dynamics >400 million years ago). We discuss important assumptions and uncertainties that affect the SDM approach to paleobiology e the equilibrium postulate, niche stability, changing atmospheric CO2 concentrations e as well as ways to address these (ensemble, functional SDM, and non-SDM ecoinformatics approaches). We conclude that the SDM approach offers important opportunities for advances in paleobiology by providing a quantitative ecological perspective, and hereby also offers the potential for an enhanced contribution of paleobiology to ecology and conservation biology, e.g., for estimating climate change impacts and for informing ecological restoration.