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Climate change poses a threat to biodiversity, and it is unclear whether species can adapt to or tolerate new conditions, or migrate to areas with suitable habitats. Reconstructions of range shifts that occurred in response to environmental changes since the last glacial maximum (LGM) from species distribution models (SDMs) can provide useful data to inform conservation efforts. However, different SDM algorithms and climate reconstructions often produce contrasting patterns, and validation methods typically focus on accuracy in recreating current distributions, limiting their relevance for assessing predictions to the past or future. We modeled historically suitable habitat for the threatened North American tree green ashFraxinus pennsylvanicausing 24 SDMs built using two climate models, three calibration regions, and four modeling algorithms. We evaluated the SDMs using contemporary data with spatial block cross‐validation and compared the relative support for alternative models using a novel integrative method based on coupled demographic‐genetic simulations. We simulated genomic datasets using habitat suitability of each of the 24 SDMs in a spatially‐explicit model. Approximate Bayesian computation (ABC) was then used to evaluate the support for alternative SDMs through comparisons to an empirical population genomic dataset. Models had very similar performance when assessed with contemporary occurrences using spatial cross‐validation, but ABC model selection analyses consistently supported SDMs based on the CCSM climate model, an intermediate calibration extent, and the generalized linear modeling algorithm. Finally, we projected the future range of green ash under four climate change scenarios. Future projections using the SDMs selected via ABC suggest only minor shifts in suitable habitat for this species, while some of those that were rejected predicted dramatic changes. Our results highlight the different inferences that may result from the application of alternative distribution modeling algorithms and provide a novel approach for selecting among a set of competing SDMs with independent data. 

Abstract. Land cover governs the biogeophysical and biogeochemical feedbacks between the land surface and atmosphere. Holocene vegetation-atmosphere interactions are of particular interest, both to understand the climate effects of intensifying human land use and as a possible explanation for the Holocene Conundrum, a widely studied mismatch between simulated and reconstructed temperatures. Progress has been limited by a lack of data-constrained, quantified, and consistently produced reconstructions of Holocene land cover change. As a contribution to the Past Global Changes (PAGES) LandCover6k Working Group, we present a new suite of land cover reconstructions with uncertainty for North America, based on a network of 1445 sedimentary pollen records and the REVEALS pollen-vegetation model coupled with a Bayesian spatial model. These spatially comprehensive land cover maps are then used to determine the pattern and magnitude of North American land cover changes at continental to regional scales. Early Holocene afforestation in North America was driven by rising temperatures and deglaciation, and this afforestation likely amplified early Holocene warming via the albedo effect. A continental-scale mid-Holocene peak in summergreen trees and shrubs (8.5 to 4 ka) is hypothesized to represent a positive and understudied feedback loop among insolation, temperature, and phenology seasonality. A last-millennium decrease in summergreen trees and shrubs with corresponding increases in open land likely was driven by a spatially varying combination of intensifying land use and neoglacial cooling. Land cover trends vary within and across regions, due to individualistic taxon-level responses to environmental change. Major species-level events, such as the mid-Holocene decline of eastern hemlock, may have altered regional climates. The substantial land-cover changes reconstructed here support the importance of biogeophysical vegetation feedbacks to Holocene climate dynamics. However, recent model experiments that invoke vegetation feedbacks to explain the Holocene Conundrum may have overestimated the land cover forcing by replacing Northern Hemisphere grasslands >30° N with forests; an ecosystem state that is not supported by these land cover reconstructions. These Holocene reconstructions for North America, along with similar LandCover6k products now available for other continents, serve the Earth system modeling community by providing better-constrained land cover scenarios and benchmarks for model evaluation, ultimately making it possible to better understand the regional- to global-scale processes driving Holocene land cover dynamics. 

Abstract AimBiogeographers have used three primary data types to examine shifts in tree ranges in response to past climate change: fossil pollen, genetic data and contemporary occurrences. Although recent efforts have explored formal integration of these types of data, we have limited understanding of how integration affects estimates of range shift rates and their uncertainty. We compared estimates of biotic velocity (i.e. rate of species' range shifts) using each data type independently to estimates obtained using integrated models. LocationEastern North America. TaxonFraxinus pennsylvanicaMarshall (green ash). MethodsUsing fossil pollen, genomic data and modern occurrence data, we estimated biotic velocities directly from 24 species distribution models (SDMs) and 200 pollen surfaces created with a novel Bayesian spatio‐temporal model. We compared biotic velocity from these analyses to estimates based on coupled demographic‐coalescent simulations and Approximate Bayesian Computation that combined fossil pollen and SDMs with population genomic data collected across theF. pennsylvanicarange. ResultsPatterns and magnitude of biotic velocity over time varied by the method used to estimate past range dynamics. Estimates based on fossil pollen yielded the highest rates of range movement. Overall, integrating genetic data with other data types in our simulation‐based framework reduced apparent uncertainty in biotic velocity estimates and resulted in greater similarity in estimates between SDM‐ and pollen‐integrated analyses. Main ConclusionsBy reducing uncertainty in our assessments of range shifts, integration of data types improves our understanding of the past distribution of species. Based on these results, we propose further steps to reach the integration of these three lines of biogeographical evidence into a unified analytical framework. 

Abstract. Holocene climate reconstructions are useful for understanding the diversefeatures and spatial heterogeneity of past and future climate change. Herewe present a database of western North American Holocene paleoclimaterecords. The database gathers paleoclimate time series from 184 terrestrialand marine sites, including 381 individual proxy records. The records spanat least 4000 of the last 12 000 years (median duration of 10 725 years)and have been screened for resolution, chronologic control, and climatesensitivity. Records were included that reflect temperature, hydroclimate,or circulation features. The database is shared in the machine readableLinked Paleo Data (LiPD) format and includes geochronologic data forgenerating site-level time-uncertain ensembles. This publicly accessible andcurated collection of proxy paleoclimate records will have wide researchapplications, including, for example, investigations of the primary featuresof ocean–atmospheric circulation along the eastern margin of the NorthPacific and the latitudinal response of climate to orbital changes. Thedatabase is available for download at https://doi.org/10.6084/m9.figshare.12863843.v1 (Routson and McKay, 2020).