Dana Royer
Department of Earth and Environmental Sciences
Wesleyan University
Exley Science Center 445 (265 Church St.)
Middletown, CT 06459-0139
office: 860.685.2836; lab: 860.685.2873; fax: 860.685.3651

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Using the sizes and shapes of leaves to reconstruct paleoclimatic and paleoecological variables

After nearly 100 years of use, the analysis of leaf size and shape (physiognomy) remains one of the more reliable means to reconstruct terrestrial climates from before the Pleistocene (for review, see Royer 2012). In particular, the strong correlation observed in living forests between the proportion of plant species that have untoothed leaf margins and mean annual temperature is widely applied to fossil floras (“leaf-margin analysis”; see Figure 1). Given the importance of leaf-margin analysis, it is striking that both the mechanistic underpinnings behind the correlation are poorly known and that potentially more accurate methods based on leaf physiognomy are not considered reproducible (e.g., Peppe et al., 2010).

Why do leaves have teeth?
We tested the hypothesis that teeth enhance plant growth at the beginning of the growing season when temperatures are limiting (Royer & Wilf, 2006). Testing involved tracking seasonal patterns of leaf-margin gas exchange of a warm and cold temperate flora, enabling quantitative comparisons among species as well as groups of species. Significant results are: physiological activity at leaf margins is greatest early in the growing season; toothed margins are more active than untoothed margins; and leaf margins are more active in species native to colder region. Thus, teeth boost transpiration and photosynthate production early in the growing season, maximizing carbon gain when temperature is limiting. This helps explain the core observation underlying most paleoclimate estimates based on fossil leaf teeth.

Digital leaf physiognomy: a better method for estimating paleoclimate from fossil leaves?
My colleagues and I developed a method for estimating climate from computerized images of leaves. Relative to leaf-margin analysis, this method, called digital leaf physiognomy, describes more fully the sizes and shapes of leaves. Analysis of 92 worldwide sites demonstrates that many size and shape variables correlate significantly with mean annual temperature, indicating a coordinated, convergent evolutionary response of fewer teeth, smaller tooth area, and lower degree of blade dissection in warmer environments (Royer et al., 2005; Peppe et al., 2011). These same patterns are sometimes observed within species, both in the field (Royer et al., 2005, 2008) and with experimental manipulation (Royer et al., 2009; Royer, 2012). Provisional temperature estimates from several North American fossil floras are considerably warmer and in better agreement with independent paleoclimate evidence (Peppe et al., 2011). This opens the exciting possibility for reconstructing ancient terrestrial climates from fossil leaves more accurately. We are currently exploring the influence of leaf habit (deciduous vs.evergreen) (Royer et al., 2012) and phylogenetic history on these leaf-climate relationships.

Can leaf physiognomy tell us anything about ecology?
We also explore correlations between the shapes of leaves and leaf economic variables. Leaf economic variables describe how fast or slow a plant “spends” its nutrient resources, and include leaf photosynthetic rate, leaf nitrogen content, leaf mass per area, and leaf lifespan. These variables tell us something important about the functioning of a given ecosystem (i.e., how fast or slow it is turning over its nutrient resources), but unfortunately they cannot be directly quantified on fossil plants. We developed a method for quantifying leaf mass per area from petiole width and leaf area, two variables that are easily measurable on most well-preserved leaf fossils (Royer et al., 2007, 2010; Royer, 2008; Peppe et al., 2014). This proxy has allowed us to quantify leaf economic strategies within early angiosperms (Royer et al., 2010) and angiosperms across the Cretaceous-Paleogene boundary (Blonder et al., 2014).

Our ultimate goal is to reconstruct, from single outcrops, climate and leaf economics from the physiognomy of fossil leaves. These data can be coupled with other outcrop data such as insect herbivory, leaf stomatal density, and the stable carbon isotopic composition of fossil leaf organic material, providing powerful snapshots of ancient ecosystems.

<Figure 1>

Figure 1. Fit of mean annual temperature to the proportion of untoothed species in floras from the East Asian data set of Wolfe (1979): MAT = 30.6P + 1.14 (n = 34; r2 = 0.98). Each data point is one living flora with many species.

Related publications

[pdf] McKee ML, Royer DL, Poulos H. 2019. Experimental evidence for species-dependent responses in leaf shape to temperature: implications for paleoclimate inference. PLoS ONE, 14: e021884. doi:10.1371/journal.pone.021884.[supplemental information]

[pdf] Blonder B, Royer DL, Johnson KR, Miller I, Enquist BJ. 2014. Plant ecological strategies shift across the Cretaceous-Paleogene boundary. PLoS Biology, 12(9): e1001949. doi: 10.1371/journal.pbio.1001949. [supplemental information]

[pdf] Peppe DJ, Lemons CR, Royer DL, Wing SL, Wright IJ, Lusk CH, Rhoden CH. 2014. Biomechanical and leaf-climate relationships: a comparison of ferns and seed plants. American Journal of Botany, 101: 338-347.

[pdf] Royer DL. 2012. Leaf shape responds to temperature but not CO2 in Acer rubrum. PLoS ONE, 7(11): e49559. doi:10.1371/journal.pone.0049559.

[pdf] Royer DL. 2012. Climate reconstruction from leaf size and shape: new developments and challenges. In: Ivany LC, Huber BT (eds). Reconstructing Earth's Deep-Time Climate—The State of the Art in 2012. Paleontological Society Papers, 18: 195-212 (invited contribution).

[pdf] Royer DL, Peppe DJ, Wheeler EA, Niinemets Ü. 2012. Roles of climate and functional traits in controlling toothed vs. untoothed leaf margins. American Journal of Botany, 99: 915-922. [supplemental information]

[pdf] Peppe DJ, Royer DL, Cariglino B, Oliver SY, Newman S, Leight E, Enikolopov G, Fernandez-Burgos M, Herrera F, Adams JM, Correa E, Currano ED, Erickson JM, Hinojosa LF, Iglesias A, Jaramillo CA, Johnson KR, Jordan GJ, Kraft N, Lovelock EC, Lusk CH, Niinemets Ü, Peñuelas J, Rapson G, Wing SL, Wright IJ. 2011. Sensitivity of leaf size and shape to climate: global patterns and paleoclimatic applications. New Phytologist, 190: 724-739. [supplemental information] [original leaf images]

[pdf] Peppe DJ, Royer DL, Wilf P, Kowalski EA. 2010. Quantification of large uncertainties in fossil leaf paleoaltimetry. Tectonics, 29, TC3015, doi:10.1029/2009TC002549. [supplemental information]

[pdf] Royer DL, Miller IM, Peppe DJ, Hickey LJ. 2010. Leaf economic traits from fossils support a weedy habit for early angiosperms. American Journal of Botany, 97: 438-445. [supplemental information]

[pdf] Royer DL, Meyerson LA, Robertson KM, Adams JM. 2009. Phenotypic plasticity of leaf shape along a temperature gradient in Acer rubrum. PLoS ONE, 4(10): e7653. doi:10.1371/journal/pone.0007653. [supplemental information]

[pdf] Royer DL, Kooyman RM, Little SA, Wilf P. 2009. Ecology of leaf teeth: A multi-site analysis from an Australian subtropical rainforest. American Journal of Botany, 96: 738-750. [supplemental Appendix S1] [supplemental Appendix S2]

[pdf] Royer DL. 2008. Nutrient turnover rates in ancient terrestrial ecosystems. Palaios, 23: 421-423.

[pdf] Royer DL, McElwain JC, Adams JM, Wilf P. 2008. Sensitivity of leaf size and shape to climate within Acer rubrum and Quercus kelloggii. New Phytologist, 179: 808-817. [supplemental information] [original leaf images]

[pdf] Royer DL, Sack L, Wilf P, Lusk CH, Jordan GJ, Niinemets Ü, Wright IJ, Westoby M, Cariglino B, Coley PD, Cutter AD, Johnson KR, Labandeira CC, Moles AT, Palmer MB, Valladares F. 2007. Fossil leaf economics quantified: calibration, Eocene case study, and implications. Paleobiology, 33: 574-589. [online appendix A] [online appendix B]

[pdf] Royer DL, Wilf P. 2006. Why do toothed leaves correlate with cold climates? Gas-exchange at leaf margins provides new insights into a classic paleotemperature proxy. International Journal of Plant Sciences, 167: 11-18.

[pdf] Royer DL, Wilf P, Janesko DA, Kowalski EA, Dilcher DL. 2005. Correlating climate and plant ecology to leaf size and shape: potential proxies for the fossil record. American Journal of Botany, 92: 1141-1151. [supplemental information] [original leaf images]

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Using stomatal distributions to reconstruct ancient levels of atmospheric CO2

The leaves of most modern vascular plants show an inverse correlation between stomatal index (the percentage of leaf epidermal cells that are stomata) and the partial pressure of atmospheric CO2. By using phylogenetically conservative taxa such as Ginkgo (maidenhair tree) or Metasequoia (dawn redwood), these modern relationships can be applied to the fossil record to reconstruct paleo-CO2. A limitation with traditional stomatal-CO2 approaches like stomatal index is that they typically saturate above 700 ppm or so and require that the fossil species be calibrated with the same species in the present-day. This severely restricts the method's applicability in time and CO2 space. To address these shortcomings, we developed a new stomatal-based approach that follows well-defined physiological principles (Franks et al., 2014). The new method requires measurement of stomatal density, stomatal size, and leaf carbon isotopic composition. We hope that this more robust and more broadly applicable proxy becomes the new standard.

My group has produced CO2 records for the the early Paleogene (65 to 45 Myrs ago: Royer et al., 2001; Kowalczyk et al., 2018), middle Eocene (~40 Myrs ago: Doria et al., 2011; Maxbauer et al., 2014), and middle Miocene (17.5 to 15.5 Myrs ago: Royer et al., 2001). These records, especially in context of all CO2 proxy records for the Cenozoic, show a strong first-order link to reconstructed global temperatures (see also next section below).

Related publications

[pdf] Royer DL, Moynihan KM*, McKee ML*, Londoño L, Franks PJ. 2019. Sensitivity of a leaf gas-exchange model for estimating paleoatmospheric CO2 concentration. Climate of the Past, 15: 795-809.[supplemental information]

[pdf] Milligan JN*, Royer DL, Franks PJ, Upchurch GR, McKee ML*. 2019. No evidence for a large atmospheric CO2 spike across the Cretaceous-Paleogene boundary. Geophysical Research Letters, 46: 3462-3472. [supplemental information]

[pdf] Kowalczyk JB, Royer DL, Miller IM, Anderson CW, Beerling DJ, Franks PJ, Grein M, Konrad W, Roth-Nebelsick A, Bowring SA, Johnson KR, Ramezani J. 2018. Multiple proxy estimates of atmospheric CO2 from an early Paleocene rainforest. Paleoceanography and Paleoclimatology, 33: 1427-1438. [supplemental information]

[pdf] Londoño L, Royer DL, Jaramillo C, Escobar J, Foster DA, Cárdenas-Rozo AL, Wood A. 2018. Early Miocene CO2 estimates from a Neotropical fossil assemblage exceed 400 ppm. American Journal of Botany, 105: 1929-1937. [supplemental information]

[pdf] Franks PJ, Royer DL. 2017. Comment on "Was atmospheric CO2 capped at 1000 ppm over the past 300 million years?" by McElwain J. C. et al. [Palaeogeogr. Palaeoclimatol. Palaeoecol. 441 (2016) 653-658]. Palaeogeography, Palaeoclimatology, Palaeoecology, 472: 256-259.

[pdf] Maxbauer DP, Royer DL, LePage BA. 2014. High Arctic forests during the middle Eocene supported by moderate levels of atmospheric CO2. Geology, 42: 1027-1030. [supplemental information]

[pdf] Franks PJ, Royer DL, Beerling DJ, Van de Water PK, Cantrill DJ, Barbour MM, Berry JA. 2014. New constraints on atmospheric CO2 concentration for the Phanerozoic. Geophysical Research Letters, 41: 4685-4694. [supplemental information]

[pdf] Doria G, Royer DL, Wolfe AP, Fox A, Westgate JA, Beerling DJ. 2011. Declining atmospheric CO2 during the late Middle Eocene climate transition. American Journal of Science, 311: 63-75.

[pdf] Royer DL. 2003. Estimating latest Cretaceous and Tertiary atmospheric CO2 from stomatal indices. In: Wing SL, Gingerich PD, Schmitz B, Thomas E (eds). Causes and Consequences of Globally Warm Climates in the Early Paleogene. Geological Society of America Special Paper, 369: 79-93.

[pdf] Beerling DJ, Lomax BH, Royer DL, Upchurch GR, Kump LR. 2002. An atmospheric pCO2 reconstruction across the Cretaceous-Tertiary boundary from leaf megafossils. Proceedings of the National Academy of Sciences USA, 99: 7836-7840.

[pdf] Beerling DJ, Royer DL. 2002. Fossil plants as indicators of the Phanerozoic global carbon cycle. Annual Review of Earth and Planetary Sciences, 30: 527-556.

[pdf] Beerling DJ, Royer DL. 2002. Reading a CO2 signal from fossil stomata. New Phytologist, 153: 387-397.

[pdf] Royer DL. 2002. Estimating latest Cretaceous and Tertiary PCO2 from stomatal indices [Ph.D. thesis]. Yale University, New Haven, 163 p.

[pdf] Royer DL, Wing SL, Beerling DJ, Jolley DW, Koch PL, Hickey LH, Berner RA. 2001. Paleobotanical evidence for near present day levels of atmospheric CO2 during part of the Tertiary. Science, 292: 2310-2313.

[pdf] Royer DL, Berner RA, Beerling DJ. 2001. Phanerozoic atmospheric CO2 change: Evaluating geochemical and paleobiological approaches. Earth-Science Reviews, 54: 349-392.

[pdf] Royer DL. 2001. Stomatal density and stomatal index as indicators of paleoatmospheric CO2 concentration. Review of Palaeobotany and Palynology, 114: 1-28.

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Relationship between CO2 and temperature in the ancient past

A firm understanding of the relationship between atmospheric CO2 concentration and temperature is critical for interpreting past climate change and for anticipating future changes. A recent synthesis suggests that the increase in global-mean surface temperature in response to a doubling of CO2, termed ‘climate sensitivity’, is between 1.5 and 4.5 °C (with 66% confidence) (see also Rohling et al., 2012). However, these calculations exclude factors that respond very slowly (like continental ice sheets) and factors that may have been important in the past but are not important today (like polar forests). A calculation of climate sensitivity that includes all feedbacks is called Earth system sensitivity (ESS). The geologic record is ideally posed to evaluate ESS, and we have calculated ESS two independent ways. First, we used CO2 (Royer et al., 2004; Royer, 2006; Beerling and Royer, 2011) and temperature records directly to calculate ESS. For the last 35 Myrs, when ice sheets were present on Antarctica, ESS was ~6 °C per CO2 doubling (Hansen et al., 2008). For part of the Cretaceous-early Paleogene interval (125-45 Myrs ago), when little-to-no ice was present on Earth, ESS sometimes exceeded 3 °C (Royer et al., 2012). Second, we have estimated ESS by modelling CO2 concentrations over the past 420 Myrs and comparing our calculations with the proxy CO2 record (Royer et al., 2007; Park and Royer, 2011). This approach yields a best-fit estimate of 3.2 °C per CO2 doubling and can exclude an ESS below 1.5 °C with 95% confidence. Moreover, during times in Earth's history with large ice sheets (340-260 and 35-0 Myrs ago) ESS was roughly double the ice-free value (6-8 °C).

The consensus with these and other studies is an ESS of 6+ °C during glacial periods and 3 °C or higher during ice-free periods. More broadly, ESS is typically at least as high as the ‘fast-feedback’ climate sensitivity (3 °C per CO2 doubling). The dynamics of continental ice sheets likely explain the amplification during glacial periods, but during ice-free times the source of the amplification is less clear. Understanding these ice-free climate feedbacks will become increasingly important as we move to a less icy future.

Related publications

[pdf] Wolfe AP, Reyes AV, Royer DL, Greenwood DR, Doria G, Gagen MH, Siver PA, Westgate JA. 2017. Middle Eocene CO2 and climate reconstructed from the sediment fill of a subarctic kimberlite maar. Geology, 45: 619-622. [supplemental information]

[pdf] Foster GL, Royer DL, Lunt DJ. 2017. Future climate forcing potentially without precedent in the geological record. Nature Communications, 8: 14845. doi: 10.1038/ncomms14845. [supplemental information]

[pdf] Royer DL. 2016. Climate sensitivity in the geologic past. Annual Review of Earth and Planetary Sciences, 44: 277-293.

[pdf] Peppe DJ, Royer DL. 2015. Can climate feel the pressure? Science, 348: 1210-1211.

[pdf] Rohling EJ, Sluijs A, Dijkstra HA, Köhler P, van de Wal RSW, von der Heydt AS, Beerling D, Berger A, Bijl PK, Crucifix M, DeConto R, Drijfhout SS, Fedorov A, Foster G, Ganopolski A, Hansen J, Hönisch B, Hooghiemstra H, Huber M, Huybers P, Knutti R, Lea DW, Lourens LJ, Lunt D, Masson-Demotte V, Medina-Elizalde M, Otto-Bliesner B, Pagani M, Pälike H, Renssen H, Royer DL, Siddall M, Valdes P, Zachos JC, Zeebe RE. 2012. Making sense of palaeoclimate sensitivity. Nature, 491: 683-691. [supplemental information]

[pdf] Royer DL, Pagani M, Beerling DJ. 2012. Geobiological constraints on Earth system sensitivity to CO2 during the Cretaceous and Cenozoic. Geobiology, 10: 298-310.

[pdf] Beerling DJ, Royer DL. 2011. Convergent Cenozoic CO2 history. Nature Geoscience, 4: 418-420. [supplemental information]

[pdf] Park J, Royer DL. 2011. Geologic constraints on the glacial amplification of Phanerozoic climate sensitivity. American Journal of Science, 311: 1-26.

[pdf] Royer DL. 2010. Fossil soils constrain ancient climate sensitivity. Proceedings of the National Academy of Sciences USA, 107: 517-518.

[pdf] Hansen J, Sato M, Kharecha P, Beerling D, Berner R, Masson-Delmotte V, Pagani M, Raymo M, Royer DL, Zachos JC. 2008. Target atmospheric CO2: where should humanity aim? Open Atmospheric Science Journal, 2: 217-231. [supplemental information]

[pdf] Royer DL. 2008. Linkages between CO2, climate, and evolution in deep time. Proceedings of the National Academy of Sciences USA, 105: 407-408.

[pdf] Royer DL, Berner RA, Park J. 2007. Climate sensitivity constrained by CO2 concentrations over the past 420 million years. Nature, 446: 530-532. [supplemental information]

[pdf] Royer DL. 2006. CO2-forced climate thresholds during the Phanerozoic. Geochimica et Cosmochimica Acta, 70: 5665-5675. [supplemental information]

[pdf] Royer DL, Berner RA, Montañez IP, Tabor NJ, Beerling DJ. 2004. CO2 as a primary driver of Phanerozoic climate change: Reply. GSA Today, 14(7): 18.

[pdf] Royer DL, Berner RA, Montañez IP, Tabor NJ, Beerling DJ. 2004. CO2 as a primary driver of Phanerozoic climate change. GSA Today, 14(3): 4-10. [supplemental information]

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