Summary• Paleobotanists have long used models based on leaf size and shape to reconstruct paleoclimate. However, most models incorporate a single variable or use traits that are not physiologically or functionally linked to climate, limiting their predictive power. Further, they often underestimate paleotemperature relative to other proxies.• Here we quantify leaf-climate correlations from 92 globally distributed, climatically diverse sites, and explore potential confounding factors. Multiple linear regression models for mean annual temperature (MAT) and mean annual precipitation (MAP) are developed and applied to nine well-studied fossil floras.• We find that leaves in cold climates typically have larger, more numerous teeth, and are more highly dissected. Leaf habit (deciduous vs evergreen), local water availability, and phylogenetic history all affect these relationships. Leaves in wet climates are larger and have fewer, smaller teeth. Our multivariate MAT and MAP models offer moderate improvements in precision over univariate approaches (± 4.0 vs 4.8°C for MAT) and strong improvements in accuracy. For example, our provisional MAT estimates for most North American fossil floras are considerably warmer and in better agreement with independent paleoclimate evidence.• Our study demonstrates that the inclusion of additional leaf traits that are functionally linked to climate improves paleoclimate reconstructions. This work also illustrates the need for better understanding of the impact of phylogeny and leaf habit on leaf-climate relationships.
The utility of regression and correspondence models for deducing climate from leaf physiognomy was evaluated by the comparative application of different predictive models to the same three leaf assemblages. Mean annual temperature (MAT), mean annual precipitation (MAP), and growing season precipitation (GSP) were estimated from the morphological characteristics of samples of living leaves from two extant forests and an assemblage of fossil leaves. The extant forests are located near Gainesville, Florida, and in the Florida Keys; the fossils were collected from the Eocene Clarno Nut Beds, Oregon. Simple linear regression (SLR), multiple linear regression (MLR), and canonical correspondence analysis (CCA) were used to estimate temperature and precipitation. The SLR models used only the percentage of species having entire leaf margins as a predictor for MAT and leaf size as a predictor for MAP. The MLR models used from two to six leaf characters as predictors, and the CCA used 31 characters. In comparisons between actual and predicted values for the extant forests, errors in prediction of MAT were 0.6°-5.7°C, and errors in prediction of precipitation were 6-89 cm (=6-66%). At the Gainesville site, seven models underestimated MAT and only one overestimated it, whereas at the Keys site, all eight models overestimated MAT. Precipitation was overestimated by all four models at Gainesville, and by three of them at the Keys. The MAT estimates from the Clarno leaf assemblage ranged from 14.3° to 18.8°C, and the precipitation estimates from 227 to 363 cm for MAP and from 195 to 295 cm for GSP.
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