Conceived and designed the experiments: SAL SWK PW. Analyzed the data: SWK. Contributed reagents/materials/analysis tools: SAL. Wrote the paper: SAL SWK PW. Compiled
The authors have declared that no competing interests exist.
Present-day correlations between leaf physiognomic traits (shape and size) and climate are widely used to estimate paleoclimate using fossil floras. For example, leaf-margin analysis estimates paleotemperature using the modern relation of mean annual temperature (MAT) and the site-proportion of untoothed-leaf species (NT). This uniformitarian approach should provide accurate paleoclimate reconstructions under the core assumption that leaf-trait variation principally results from adaptive environmental convergence, and because variation is thus largely independent of phylogeny it should be constant through geologic time. Although much research acknowledges and investigates possible pitfalls in paleoclimate estimation based on leaf physiognomy, the core assumption has never been explicitly tested in a phylogenetic comparative framework. Combining an extant dataset of 21 leaf traits and temperature with a phylogenetic hypothesis for 569 species-site pairs at 17 sites, we found varying amounts of non-random phylogenetic signal in all traits. Phylogenetic vs. standard regressions generally support prevailing ideas that leaf-traits are adaptively responding to temperature, but wider confidence intervals, and shifts in slope and intercept, indicate an overall reduced ability to predict climate precisely due to the non-random phylogenetic signal. Notably, the modern-day relation of proportion of untoothed taxa with mean annual temperature (NT-MAT), central in paleotemperature inference, was greatly modified and reduced, indicating that the modern correlation primarily results from biogeographic history. Importantly, some tooth traits, such as number of teeth, had similar or steeper slopes after taking phylogeny into account, suggesting that leaf teeth display a pattern of exaptive evolution in higher latitudes. This study shows that the assumption of convergence required for precise, quantitative temperature estimates using present-day leaf traits is not supported by empirical evidence, and thus we have very low confidence in previously published, numerical paleotemperature estimates. However, interpreting qualitative changes in paleotemperature remains warranted, given certain conditions such as stratigraphically closely-spaced samples with floristic continuity.
In a seminal 1915 paper, Bailey and Sinnott proposed “a botanical index of Cretaceous and Tertiary climates”
Paleobotanists have since continued to make extensive use of Bailey and Sinnott's “index,” eventually developing a quantitative method known as leaf-margin analysis, based on linear regressions of extant proportions of untoothed species (NT) and mean annual temperature (MAT)
In particular, precise, quantitative paleotemperature estimates from taxon-free approaches operate under a still-untested core assumption that leaf-trait variation principally results from adaptive environmental convergence, and because it is thus largely independent of phylogeny it should be constant through geologic time. If the assumption is valid, then the current uniformitarian applications are warranted, and modern trait-climate relations should estimate past climate in a quantitatively precise manner. However, certain observations cast doubt on the core assumption
An additional, more theoretical consideration is that even under an ideal model of adaptive convergence without phylogenetic signal, directional selection is expected to affect the assumption of constancy through time. Given a hypothetically unchanging climate, with constant species composition, directional selection should shift trait values over time; producing an increase in number of teeth over geological time under a constant low MAT for example. Thus, lineage persistence may contribute to some observed changes in leaf-traits through geologic time, unrelated to climate change. Further, given that lineages are expected to have differing rates of evolution, extinction and species radiation, trait-climate relations should vary through deep time, even if adaptive leaf-trait responses were ideal
The issues above are important because if present-day trait-climate relations do not have the expected adaptive explanation, or were not constant over evolutionary time, then the core assumption of the current uniformitarian approach would not be valid (i.e., leaf physiognomy-climate relations may have differed in the past). In this case, one would require additional information in order to precisely quantify a past trait-climate relation with confidence, such as data regarding phylogenetic placement of difficult-to-identify fossil leaves, or independent, highly accurate and well-correlated climate proxies. We note that several examples of temperature estimates from isotopic data are considered broadly concordant with associated leaf-physiognomy estimates
We test the assumption of adaptive convergence of leaf traits with temperature by quantifying phylogenetic signal in a dataset comprising 21 leaf-physiognomic traits and MAT among 569 species-site pairs at 17 sites in the eastern USA and Barro Colorado Island, Republic of Panamá, published by Huff
We note that the issues addressed by our analysis are separate from the numerous additional sources of uncertainty in leaf paleothermometry that have been noted, including environmental, taphonomic/preservational, sampling, and scoring biases
The Huff
We created a phylogenetic hypothesis for the species included in this study by grafting them onto a family-level phylogenetic supertree of the angiosperms
Phylogenetic signal is a tendency for closely related taxa to possess similar trait values due to descent from a common ancestor. Phylogenetic signal in all traits, including MAT, was measured using the
All data | BCI removed | Nonphylogenetic model | Phylogenetic model (branch lengths scaled) | ||||||||||||
Trait |
|
N |
|
N | Y-int | SE | Slope | SE | AIC | Y-int | SE | Slope | SE | λ | AIC |
MAT | 0.62 | 569 | 0.18 | 413 | — | — | — | — | — | — | — | — | — | — | — |
Margin untoothed (ternary) | 0.51 | 569 | 0.44 | 413 | −0.87 | 0.10 | 1.13 | 0.09 | 632.6 | 0.35 | 0.18 | 0.31 | 0.07 | 1.00 | 181.0 |
Margin untoothed (binomial) | — | — | — | — | −2.98 | 0.27 | 0.16 | 0.01 | — | −0.02 | 0.75 | 0.04 | 0.02 | — | — |
Blade area | 0.28 | 569 | 0.31 | 413 | 1.42 | 0.10 | 0.02 | 0.09 | 661.8 | 2.11 | 0.21 | −0.38 | 0.09 | 0.94 | 431.4 |
Perimeter | 0.25 | 569 | 0.28 | 413 | 1.55 | 0.06 | −0.09 | 0.05 | 0.4 | 1.84 | 0.11 | −0.27 | 0.05 | 0.91 | −236.0 |
Internal Perimeter | 0.35 | 325 | 0.34 | 294 | 1.52 | 0.07 | −0.15 | 0.06 | −63.5 | 1.78 | 0.10 | −0.25 | 0.05 | 0.85 | −270.5 |
Perimeter ratio | 0.31 | 323 | 0.35 | 293 | 0.15 | 0.02 | −0.08 | 0.02 | −964.0 | 0.12 | 0.03 | −0.06 | 0.01 | 0.89 | −1154.5 |
Compactness | 0.23 | 569 | 0.26 | 413 | 1.69 | 0.04 | −0.22 | 0.03 | −460.7 | 1.61 | 0.07 | −0.19 | 0.04 | 0.77 | −623.1 |
Shape factor | 0.27 | 569 | 0.28 | 413 | −0.59 | 0.04 | 0.21 | 0.03 | −466.9 | −0.51 | 0.07 | 0.18 | 0.04 | 0.77 | −626.9 |
Major axis length | 0.20 | 569 | 0.25 | 413 | 0.87 | 0.05 | 0.10 | 0.04 | −132.5 | 1.27 | 0.10 | −0.17 | 0.05 | 0.93 | −338.4 |
Minor axis length | 0.38 | 569 | 0.36 | 413 | 0.81 | 0.06 | −0.14 | 0.05 | 122.3 | 1.10 | 0.13 | −0.26 | 0.05 | 0.97 | −173.3 |
Feret diameter | 0.28 | 569 | 0.31 | 413 | 0.75 | 0.05 | 0.01 | 0.04 | −94.8 | 1.10 | 0.11 | −0.19 | 0.05 | 0.94 | −326.0 |
Feret diameter ratio | 0.70 | 569 | 0.39 | 413 | −0.01 | 0.02 | −0.08 | 0.01 | −1287.3 | −0.18 | 0.04 | −0.01 | 0.01 | 0.99 | −1573.4 |
Tooth area | 0.75 | 325 | 0.59 | 294 | 0.66 | 0.18 | −0.79 | 0.16 | 528.1 | 0.66 | 0.35 | −0.54 | 0.14 | 0.97 | 368.3 |
Tooth area : blade area | 0.45 | 324 | 0.34 | 293 | −1.12 | 0.14 | −0.49 | 0.13 | 373.3 | −1.59 | 0.31 | −0.02 | 0.11 | 1.00 | 250.7 |
Tooth area : perimeter | 1.01 | 325 | 0.81 | 294 | −1.07 | 0.14 | −0.56 | 0.13 | 390.3 | −1.31 | 0.31 | −0.18 | 0.11 | 1.00 | 240.3 |
Tooth area : internal perimeter | 0.92 | 325 | 0.73 | 294 | −0.92 | 0.15 | −0.64 | 0.14 | 429.3 | −1.19 | 0.32 | −0.24 | 0.11 | 1.00 | 272.8 |
Number of primary teeth | 0.36 | 325 | 0.40 | 294 | 2.06 | 0.14 | −0.54 | 0.13 | 398.8 | 1.59 | 0.26 | −0.39 | 0.09 | 1.00 | 135.2 |
Number of secondary teeth | 0.49 | 150 | 0.51 | 143 | 1.36 | 0.26 | −0.47 | 0.25 | 227.8 | 1.14 | 0.29 | −0.56 | 0.16 | 0.94 | 130.9 |
Number of teeth | 0.37 | 325 | 0.43 | 294 | 2.16 | 0.15 | −0.60 | 0.14 | 430.3 | 1.65 | 0.27 | −0.43 | 0.10 | 1.00 | 156.6 |
Average tooth area | 1.88 | 325 | 1.73 | 294 | −1.49 | 0.20 | −0.20 | 0.18 | 601.5 | −1.00 | 0.31 | −0.09 | 0.11 | 1.00 | 253.3 |
Number of teeth : perimeter | 0.49 | 324 | 0.63 | 293 | 0.46 | 0.17 | −0.38 | 0.15 | 483.6 | −0.22 | 0.25 | −0.15 | 0.09 | 1.00 | 120.8 |
Number of teeth : internal perimeter | 0.52 | 324 | 0.70 | 293 | 0.60 | 0.17 | −0.47 | 0.16 | 505.2 | −0.11 | 0.26 | −0.21 | 0.09 | 1.00 | 143.7 |
Non-phylogenetic generalized least squares (GLS) and phylogenetic GLS (
We performed analyses treating the ‘Margin untoothed’ trait as a binary and as a ternary variable to perform comparisons among the phylogenetic vs. non phylogenetic trait-temperature GLS models. Current physiognomic methods use the proportion of untoothed taxa at a site as a continuous variable in a least squares regression with site-climate variables. Because our analyses were based on species-level data and not site means, ‘Margin untoothed’ was defined as a ternary variable for each species at a site as follows: 1 = all leaves untoothed, 0.5 = both toothed and untoothed, 0 = toothed. Leaf margin analysis and multivariate physiognomic methods treat the presence-absence of leaf teeth in this way to calculate the site means that are used as continuous values
There was non-random phylogenetic signal in MAT and all measured leaf traits (
Mean tooth-area character mapped at tips of the phylogeny of all species in the community samples
All trait-climate regression models were improved by incorporation of phylogenetic relationships (
Mean annual temperature (MAT) versus the six leaf traits featured in Figure 2 of Royer
Traits with the strongest phylogenetic signal (highest
The presence of non-random phylogenetic signal in all traits (
The greatly improved model fits (reduced AIC values) for all
The nonzero slopes of phylogenetic regressions (
Overall, our results support the prevailing idea that leaves are adaptively responding to climate, but that phylogenetic signal in leaf traits is responsible for a portion of variation in leaf-climate relationships, and phylogenetic information modifies our understanding of adaptive relationships between leaf physiognomic variables and climate. Several insights for improved understanding of adaptive relationships between leaf traits and temperature were revealed by our analyses; for example, Feret diameter did not appear to be strongly responsive to temperature in the dataset previously (GLS slope)
Although we expected to find some influence of phylogenetic signal in the leaf traits and their relation to temperature, the most surprising results involved the high signal in presence of leaf teeth (Margin Untoothed). This trait is the basis of leaf-margin analysis (NT-MAT relation) and a key component of all multivariate approaches that estimate paleotemperature
The relations between MAT and the traits Feret diameter ratio, Tooth area : blade area, and Average tooth area also had phylogenetic regressions with highly flattened slopes, similar to that of the NT-MAT relation (
The weak relationship between presence of leaf teeth and temperature after accounting for phylogeny indicates that the prevailing adaptive scenario since 1915
Because our results indicate that historical events unrelated to temperature contributed to the majority of the present-day distribution of toothed lineages, the modern NT-MAT relationship, which is variable at a global scale, now deserves renewed investigation
The cool-temperature selection scenario, suggested here, is also provisionally consistent with the fossil record, in which many characteristically, or commonly, toothed clades (e.g. Betulaceae, temperate
Observations of changing relative presence of leaf teeth through deep time that are qualitatively validated by correlation to independent temperature proxies, are often considered to be related to the migrations of clades along temperature gradients (e.g., latitude, altitude)
Qualitative analyses, i.e., detection of relative warming and cooling, remain justified using physiognomic data from well-understood regional floras that have supporting data on taxonomy, paleogeography, and distribution of traits along independently inferred paleotemperature gradients (i.e. using floras from several latitudinally adjacent basins). In practical terms, these conditions are met for several heavily studied assemblages (i.e., latest Cretaceous and Paleogene floras of the Western USA and Germany). However, we reiterate that although physiognomic
Despite our results, it may be tempting to continue relying on current, taxon-free leaf physiognomy to generate quantitatively inferred paleotemperature estimates, by using traits that show clear adaptive responses to temperature (i.e. Number of teeth), using traits that display only slightly altered phylogenetic regressions with temperature (i.e., Shape factor), using standard leaf-margin analysis as a convenient proxy for the presence of adaptive tooth-trait response, or relying on multivariate approaches
Regional differences in the relationship between proportions of toothed species and temperature (NT-MAT), wherein temperature estimates for a given value of NT differ by >5°C, may well be due to differences in phylogenetic history among biogeographic regions
In summary, we have demonstrated that there is evidence for an adaptive response to temperature in many leaf traits. However, the presence of non-random phylogenetic signal throughout leaf physiognomic data leads to leaf trait-climate relationships that are driven both by adaptive evolution and phylogenetic history, and the adaptive signal is especially weak for the most widely used variable, presence of teeth. Non-independence of species data due to phylogenetic relatedness results in conventional, non-phylogenetic models of leaf trait-climate relationships underestimating the true uncertainty in estimates of paleotemperature from leaf traits. An approach that should permit reliable qualitative estimation of change in paleoclimate from leaf traits would be to use leaf physiognomic variables that show the strongest evolutionary correlations with climate based on
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We thank D. Royer for significant assistance as well as M. Carvalho, G. Jordan, and D. Royer for helpful critiques of earlier drafts.