Predictive Biogeography Special Issue

In this special issue, we aim to broaden the scope and application of predictive biogeography, moving beyond the confines of SDMs to spotlight cutting edge research across different dimensions of the field. The deliberate use of the term biogeography, as opposed to ecology or macroecology, reflects our intent to include a more diverse array of approaches – statistical, evolutionary, historical, geological, and more – that contribute to understanding and forecasting distribution, abundance, and diversity across broad spatial and/or temporal scales. This scope includes not only natural systems but also productive systems (e.g. agroecosystems).

We propose a definition of predictive biogeography as a subdiscipline of biogeography that uses known ecological or evolutionary patterns and processes to predict the abundance, distribution, and diversity, whether it be at the species, intra-, or inter-specific levels, including biotic interactions and their relationship with the environment, over broad spatial and temporal scales. Over the past two decades, this research field has experienced exponential growth, driven by the increasing availability of digital data on the distribution of species and the genetic variability within them, as well as the proliferation of spatially explicit environmental data layers and increasingly fine spatial and temporal resolutions. This rapid evolution has catalysed the development of new syntheses and theories, alongside advancements in methodologies and computational capabilities. As a result, biogeography is undergoing a transformation from the primarily descriptive discipline championed by the likes of Alexander von Humboldt (1769–1859), Augustin Pyramus de Candolle (1778–1841), Alfred Russel Wallace (1823–1913), and Philip Lutley Sclater (1829–1913), amongst others, to a predictive science, capable of informing both fundamental research and practical applications in conservation, resource management, and beyond. The emergence of predictive biogeography as a discipline has been driven primarily by a pressing societal demand (Dietze et al. 2018, Enquist et al. 2024). The growing array of global challenges – including the widespread decline in biodiversity, rising food demands, and the far-reaching impacts of recent global pandemics – paired with ongoing global changes that threaten biodiversity, ecosystem services, food security, and public health, have made the ability to anticipate these changes across broad spatial and temporal scales an existential priority for humanity.

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