Generating ecological insights from historical data

Abstract

E cologists worldwide are searching for historical datasets that can provide insight into how ecosystems and species are responding to climate change, often with a focus on changes in species' phenology, distribution, and abundance (Primack and Miller-Rushing 2012;Vellend et al. 2013;Primack et al. 2022). Once confined to libraries, museums, attics, and overlooked file cabinets, physical or offline records are increasingly being digitized, made available online, and used by ecologists in innovative ways.In many cases, these records provide detailed descriptions of changes that occurred in particular places. Resurveying the records of ecologist Joseph Grinnell from the Sierra Nevada Mountains is yielding information about bird species' range shifts and helping to identify climate-change refugia (Tingley et al. 2009). Revisiting amateur naturalist David Bertelsen's observations of the Santa Catalina Mountains has generated insights into community-level changes in phenology in an arid ecosystem (Crimmins et al. 2009). Likewise, our own work with the records of the environmental philosopher Henry David Thoreau (Figure 1a), and less well-known naturalists like Alfred Hosmer, from Concord, Massachusetts, has provided evidence of changes in phenology and abundance in plant communities and across trophic levels (Primack et al. 2022;Miller et al. 2023).Are the changes observed in these welldocumented places -range shifts in the Sierra Nevada, phenology shifts in the Santa Catalinas, or changes in community ecology in Massachusetts -representative of what is happening elsewhere or across larger spatial scales? While researchers are already assessing the generality and transferability of phenological results, we feel that there is much untapped potential in exploring these cross-scale connections further (Gallinat et al. 2021).Traditionally, investigations into variation across systems rely on replicating studies in different locations, analyzing comparable data across locations, or testing hypotheses experimentally. For example, an experiment might be designed to disentangle the effects of snowmelt