Fossil Leaf Economics Quantified: Calibration

Paleobiology, 33(4), 2007, pp. 574-589

Fossil leaf economics quantified: calibration. Eocene case study, and implications

Dana L. Royer, Lawren Sack, Peter Wilf, Christopher H. Lusk, Gregory J. Jordan, Ulo Niinemets, Ian J. Wright, Mark Westoby, Bárbara Carighno, PhylUs D. Coley, Asher D. Cutter, Kirk R. Johnson, Conrad C. Labandeira, Angela T. Moles, Matthew B. Palmer, and Fernando Valladares

Abstract,•Leaf mass per area (M^) is a central ecological trait that is intercorrelated with leaf life span, photosjnthetic rate, nutrient concentration, and palatability to herbivores. These coordinated variables form a globally convergent leaf economics spectrum, which represents a general continuum running from rapid resource acquisition to maximized resource retention. Leaf economics are little studied in ancient ecosystems because they cannot be directly measured from leaf fossils. Here we use a large extant data set (65 sites; 667 species-site pairs) to develop a new, easily measured scaling relationship between petiole width and leaf mass, normalized for leaf area; this enables M^ estimation for fossil leaves from petiole width and leaf area, two variables that are commonly measurable in leaf compression floras. The calibration data are restricted to woody angiosperms exclusive of monocots, but a preliminary data set (25 species) suggests that broad-leaved gymnosperms exhibit a similar scaling. Application to two well-studied, classic Eocene floras demonstrates that M^ can be quantified in fossil assemblages. First, our results are consistent with predictions from paleobotanical and paleoclimatic studies of these floras. We found exclusively low-M^ species from Republic (Washington, U.S.A., 49 Ma), a humid, warm-temperate flora with a strong deciduous component among the angiosperms, and a wide M^ range in a seasonally dry, warm-temperate flora from the Green River Formation at Bonanza (Utah, U.S.A, 47 Ma), presumed to comprise a mix of short and long leaf life spans. Second, reconstructed M^ in the fossil species is negatively correlated with levels of insect herbivory, whether measured as the proportion of leaves with insect damage, the proportion of leaf area removed by herbivores, or the diversity of insect-damage morphotypes. These correlations are consistent with herbivory observations in extant floras and they reflect fundamental trade-offs in plant-herbivore associations. Our results indicate that several key aspects of plant and plant-animal ecology can now be quantified in the fossil record and demonstrate that herbivory has helped shape the evolution of leaf structure for millions of years.

Dana L. Royer. Department of Earth and Environmental Sciences, Wesleyan University, Middlctown, Con- necticut 06459, E-mail: droyer@wesleyan,edu Lawren Sack,* Department of Botany, University of Hawai'i at Mänoa, Honolulu, Hawai'i 96822 Peter Wilf and Bárbara Cariglino, Department of Geosciences, Pennsylvania State University, University Park, Pennsylvania 16802 Christopher H, Lusk, Ian ], Wright, and Mark Westoby, Department of Biological Sciences, Macquarie Uni- versity, Sydney, New South Wales 2109, Australia Gregory ], Jordan, School of Plant Science, University of Tasmania, Private Bag 55, Hobart 7001, Australia Ulo Niinemets, Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Tartu 51014, Estonia Phyllis D, Coley, Department of Biology, University of Utah, Salt Lake City, Utah 84112 Asher D, Cutter,f Conrad C, Labandeira, and Matthew B, Palmer, Department of Paleobiology, Smithsonian Institution, Washington, D,C, 20013 Kirk R, Johnson, Department of Earth Sciences, Denver Museum of Nature and Science, Denver, Colorado 80205 Angela T Moles,f Department of Biological Sciences, Macquarie University, Sydney, New South Wales 2109, Australia Fernando Valladares, Centro de Ciencias Medioambientales, CSIC, E-28006 Madrid, Spain * Present address: Department of Ecology and Evolutionary Biology, University of California, Los Angeles tPresent address: Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, On- tario M5S 3G5, Canada ifPresent address: School of Biological, Earth, and Environmental Sciences, University of New South Wales, New South Wales 2052, Australia

Accepted: 25 April 2007

Introduction 2006; Parton et al. 2007), but few have been Many leaf traits strongly influence ecosys- quantifiable from the fossil record. Among tem function (Diaz et al. 2004; Wright et al. these traits, leaf dry mass per area (M^; also 2004; Poorter and Bongers 2006; Shipley et al. commonly abbreviated as LMA; M^ is the in-

© 2007 The Paleontological Society. AU rights reserved. 0094-8373/07/3304-0005/$1.00 FOSSIL LEAF ECONOMICS 575 verse of specific leaf area) is a key variable representing the dry mass cost of deploying photosynthetic surface (Reich et al. 1997; Westoby et al. 2002). Species investing in a high M^ tend to have lower mass-based photosynthetic rates but longer leaf lifetimes (LL), such that their lower revenue (fixed carbon) per time may be compensated by a longer-lasting revenue stream (Reich et al. 1997; Westoby et al. 2002; Wright et al. 2004). Leaves with higher M^ are more expensive to construct per unit area, generally operate at lower nitrogen and phosphorus concentrations per unit mass, have slower rates of dark respiration, and are better defended against herbivory owing to their greater thickness and/or toughness (Small 1972; Reich et al. 1997; Westoby et al. 2002; Díaz et al. 2004; Wright et al. 2004). These coordinated trade-offs form a "leaf economics spectrum" (Wright et al. 2004), which represents one component of a general continuum running from specialization for rapid resource acquisition ("fast-return" species) to a strategy that maximizes resource retention ("slow-return" species) (Grime 1974; Grubb Mean annual temperature (°C) 1998). Leaf mass per area is also correlated FIGURE 1. Geographic and climatic distribution of cal- with growth rates and the turnover of plant ibration sites. A, Geographic distribution of the 65 sites used in the calibration data. Black symbols represent parts, and the influence of M^ persists sites where five or more species were sampled; gray through leaf "afterlife effects" into ecosystem symbols represent sites where four or fewer species processes including decomposition of litter were sampled (see "Materials and Methods"). B, Cli- mate information and major biome type (Whittaker (Kazakou et al. 2006) and mineralization of ni- 1975) for the calibration sites. SE = seasonal forest; WL trogen and phosphorus (Kobe et al. 2005). = woodland; SL = shrubland. Biome boundaries are Insect herbivory can be measured directly only approximate and do not encompass all samples. Symbols follow panel A. See Appendices 1 and 2 for fur- from leaf fossils (Beck and Labandeira 1998; ther details about sites. Labandeira 1998; Wilf and Labandeira 1999; Wilf et al. 2001, 2005), but the fundamental leaf economic traits that influence herbivory have been difficult to quantify from fossils. from geographically widespread and climati- Several methods for estimating LL for fossil cally diverse sites (Fig. 1) to develop a new species exist, but three of these, comparison method for quantifying M^ rapidly and ac- with nearest living relatives (Chaloner and curately from the sizes and shapes of leaves. Creber 1990), leaf thickness (Chaloner and We assess several models for estimating M^ Creber 1990), and presence of leaf mats (Spicer from petiole width (PW), leaf area (A), and and Parrish 1986), are qualitative; at best they leaf length, variables chosen because they can can distinguish deciduous from evergreen leaf be easily measured on most well-preserved habits (e.g., Wolfe 1987; Wolfe and Upchurch leaf fossils. For example, although petiole 1987). A fourth method quantifies LL from the length has important biomechanical proper- wood anatomy of conifers (Falcon-Lang ties (Niklas 1994), it is much less frequently 2000a,b; Brentnall et al. 2005), but this method available from fossils, because of incomplete- is not yet applicable to angiosperms. ness, than petiole width. We report results Here we analyze an extant data set drawn (Fig. 2) using the model 576 DANA L. ROYER ET AL.

1000

100

CM I E 3 (0 £ CO l_ (U Q. 1000 mifi B CO E \' M• CO CD

100

• Araucariaceae A Gnetaceae • Podocarpaceae • Taxaceae

10 "T" 0.0001 0.001 0.01 0.1 (Petiole width)2 / (leaf area) EiGURE 3. Representative examples of fossil specimens EiGURE 2. Scaling relationship between petiole width used in study. The specimen in panel A (Alnus parvifolia, (PW) and leaf dry mass per area (M^) for extant data. A, Republic) has a narrower petiole (5.3 mm; see white Calibration data for woody angiosperms. Solid and line) and larger leaf area (442.8 mm^) than the petiolule open symbols represent species-site pairs that came of the specimen in panel B (Caesalpinia pecorae, Bonanza; from sites where five or more species and four or fewer petiole width = 9.7 mm; leaf area = 191.2 mm^); this re- species were sampled, respectively (see "Materials and sults in a lower estimate of leaf dry mass per area for the Methods"); triangles represent means for sites where A, parvifolia specimen (70.8 g m"^) than the C. pecorae ten or more species were sampled. Linear regression for specimen (154.3 g m"^). Scale bars, 1 cm. The black line species (solid black line) is logiMJ = 3.070 + 0.382 X in the A. parvifolia specimen represents a conservative log[PV\P/A]; thin lines represent ±95% prediction in- reconstruction of the leaf-margin segment that was not tervals (Sokal and Rohlf 1995). Linear regression for preserved. See "Materials and Methods" for procedural sites (gray line) is logiM^] = 3.214 + 0.429 X loglPW^/ details on how petioles were measured. A]. B, Preliminary scaling relationship for broad-leaved species with distinct petioles from several gymnosperm families. Species-site pairs are plotted. The following important in the mechanical support of the genera are represented: Agathis, Gnctum, Podocarpus, Phyllocladus (cladodes), Saxegothaea, Torreya, and Taxus. leaf (Salisbury 1913; Niklas 1994; see "Model The gray symbols correspond to the angiosperm data in Fitting and Justification"). panel A. All relationships are significant at the family We apply our method to 187 fossil leaves level using log-log linear regression except Taxaceae (Araucariaceae: r'^ = 0.49, F-^j = 5.85, p = 0.05; Gneta- from two Eocene fossil floras (Republic, Wash- ceae: r^ = 0.92, Fj3 = 22.2, p = 0.04; Podocarpaceae: r^ = ington, Klondike Mountain Formation; and 0.44, Fis = 5.45, p = 0.05; Taxaceae: r^ = 0.09, F^, = 0.20, Bonanza, Utah, Green River Formation) (Figs. p = 0.70). 3, 4) where well-understood systematics (MacGinitie 1969; Wolfe and Wehr 1987), pa- PW^ leoclimate (MacGinitie 1969; Wolfe and Wehr log(M^) = fl + b log (1) 1987; Wing and Greenwood 1993; Wilf et al. 1998; Greenwood et al. 2005), and herbivory This model corresponds to the proposition, (Wilf et al. 2001, 2005; Labandeira 2002) allow based on biomechanical and developmental testable hypotheses. Republic is considered to principles, that the cross-sectional area of the be dominated by deciduous species (Wolfe petiole scales with the mass of the leaf. This and Wehr 1987); thus, our hypothesis is that relationship is expected because the petiole is these species have low reconstructed M^. Bo- FOSSIL LEAF ECONOMICS 577

CO 1fi cu but correctly predicted the bimodal distribu- >>n tion of herbivory observed at the site (Wilf et cu 12 al. 2001). Thus, we hypothesized a broad O) CD range of estimated Mp^ values at Bonanza. We E R compare our reconstructions of M^ with qual- CÖ •a itative observations of the floras and with di- 1 • o rect measurements of insect herbivory, and 0 4 en c use them to refine understanding of plant and 0 site ecology as well as forest nutrient cycling rates for these classic fossil floras. 80 •ö Materials and Methods (/)0 ^•^ .ç ^ 60 Calibration Sites.•To reconstruct M,^ from .I- 0 leaf fossils, we first collected leaves to create CD 5 ro 40 an extant calibration from 667 species-site V) E 0 pairs representing 468 species of woody an- *** CO cá-° 20- giosperms from 65 geographically and cli- 0 matically diverse sites (Fig. 1). We sampled 1-20 mature, representative leaves or equiva- lent photosynthetic organs (phyllodes) (me- J.U- dian = 3; 88% of species-site pairs are based ^ ^-v c •o 5^ 2.5- on two or more leaves) from each of 5-86 spe- ?; 05 cies (median = 21) at 26 sites (Fig. lA). To o O) 2.0- E ro 1 broaden our geographical coverage, we also 1.5- t sampled 4-12 leaves (median = 10) from each ro -D 0 ^ 1.U- of one to four species at 39 additional sites ro g (Fig. lA; Appendices 1-2; Appendix A online 0.5- ,1 ^ ^ 1• at http://dx.doi.org.10.1666/pbio07001.sl). ro Ë -ik-¿- _ 0.0- Ja In aggregate, the sites represent most of the O 50 100 150 200 250 major biomes where the foliage of woody an- Leaf mass per area (g m-2) giosperms is likely to be fossilized (Fig. IB). We collected native, woody angiosperm spe- FIGURE 4. Correlation between insect iierbivory and estimated leaf dry mass per area (M^) for two Eocene fos- cies exclusive of monocots. We generally re- sil floras. Each data point represents a species mean, and stricted our sampling to outer, exposed can- errors in M^ represent ±95% prediction intervals (Sokal opy leaves (Appendices 1, 2) because they con- and Rohlf 1995). Only species where a23 specimens could be scored for insect herbivory are plotted. A, In- stitute the majority of leaf fossils (Spicer 1981). sect damage morphotypes (Wilf et al. 2001, 2005) versus Leaves without obvious, distinct petioles were M^; errors in herbivory represent ±l(r. Statistics of log- excluded. Herbaceous species were also ex- log linear regression for combined data: n = 18; r^ = 0.64; Fi ij = 28.0; p < 0.0001. B, Percentage of leaves with cluded because they rarely fossilize (Spicer insect damage (Wilf et al. 2001, 2005); errors in herbiv- 1981). ory represent ±l(r of the binomial sampling error. Sta- Fossil Sites.•We reconstructed M^ and mea- tistics of log-log linear regression for combined data: n = 18; r^ = 0.67; Fj i^ = 32.6; p < 0.0001. C, Percentage of sured insect herbivory for woody dicot spe- leaf area removed by insect damage; errors in herbivory cies from two fossil lake floras. The first flora. represent standard errors. Statistics of log-log linear re- Republic (Wolfe and Wehr 1987; Radtke et al. gression for combined data: n = 15; r^ = 0.68; Fj ¡3 = 27.4; p < 0.0001. 2005), is from the Klondike Mountain Forma- tion in northeastern Washington, U.S.A., and is late early Eocene in age (ca. 49 Ma [reported nanza putatively contains a mix of species in Radtke et al. 2005]). The climate at Republic with both short and long LL (MacGinitie 1969; is interpreted as humid and warm temperate Wilf et al. 2001); these interpretations were (mean annual temperature [MAT] = 13°C; based on qualitative methods discussed above mean annual precipitation [MAP] > 1000 578 DANA L. ROYER ET AL. mm) (Wolfe and Wehr 1987; Greenwood et al. tion digital images (600 dpi minimum); leaf 2005). The second flora. Bonanza (MacGinitie area was determined from digital images. For 1969), is from the uppermost Green River For- the extant calibration data, we calculated M^ mation in northeastern Utah, U.S.A., and is from the dry mass and area of the leaf blade early middle Eocene in age (47.3 Ma [Smith et and petiole (Cornelissen et al. 2003). Leaf mass al. 2007]). In contrast to Republic, the climate per area varies 30-fold and leaf area 3.5 orders at Bonanza has been interpreted as warmer of magnitude in the calibration data; world- and more seasonally dry (MAT = 15°C; MAP wide, M^ varies about 50-fold and leaf area = 840 mm) (MacGinitie 1969; Wing and five orders of magnitude (Wright et al. 2004). Greenwood 1993; Wilf et al. 1998). The 187 Our calibration data thus capture the majority specimens with measurable leaf area and pet- of the known variation in these variables. Giv- iole width were selected from recent unbiased en the biomechanical basis for the scaling re- census collections made by K.R.J. of 1019 dicot lationship (see "Model Fitting and Justifica- leaves at Republic and 894 at Bonanza, re- tion"), PW could be better optimized for fresh ported by Wilf et al. (2001, 2005). Both floras than dry leaf mass. However, in a subset of 98 were collected from single stratigraphie hori- species-site combinations, there was a strong zons (thickness of sampled horizons = 1.6 m correlation across species between dry mass and 0.1 m for Republic and Bonanza, respec- and fresh mass (r^ = 0.96; F^ ç,^ = 2068; p < tively [Wilf et al. 2001, 2005]). 0.0001). Thus, for this subset, there was little Leaf Measurements for Quantifying M^.•We difference in the strength of correlation be- measured petiole width (PW) perpendicular tween PW^ IA and M^ calculated on a fresh or to the midvein in the plane of the leaf blade, dry mass basis (r^ = 0.81 and 0.77 for fresh at the basal-most insertion of the lamina into and dry mass, respectively); moreover, the the petiole. If the position of this measurement slopes of the correlations were not significant- corresponded to a locally thickened or winged ly different (p = 0.72; likelihood ratio method region of the petiole, PW was measured just of Falster et al. 2003). basal to the feature. Leaflets and petiolules For PW measurements of fossils, only spec- were the units measured for compound imens where the petiole was clearly and com- leaves, and phyllodes and basal attachments pletely preserved at the point of measurement for phyllodes; for our data set, simple leaves for PW, described above, were used (Fig. 3; and leaflets did not differ in their scaling re- Appendix B online at http://dx.doe.org.10. lationship between M^ and PYP-1A (slope: p = 1666/pbio07001/s2). One hazard with fossil 0.44; y-intercept: p = 0.45; likelihood ratio petioles is longitudinal splitting, creating the method of Falster et al. 2003). For a subset of false appearance of a thin petiole; thus, fossil leaves from our calibration data set, we also petioles were inspected under binocular mi- measured PW at the thinnest point and the croscopes to ensure that both petiole margins midpoint of the petiole, but these alternative were preserved before measurement at mag- measurements did not yield improved corre- nification. For specimens with partially pre- lations and tended to be highly correlated served leaf blades, only those specimens across species. Because complete petioles with whose full leaf areas could be reconstructed bases are only rarely preserved, our protocol with reasonable confidence were considered. allows measurement of a greater number of Species represented by only one specimen fossils than these alternatives. It is possible were excluded. that a combination of petiole width and depth A potential error with fossils is that their correlates more strongly with IsA/^ than does morphology can change postmortem. How- PW alone, but original petiole depth is rarely ever, previous experiments that mimicked the preserved in compressed fossils (Niklas 1978; fossilization process indicated little to no Rex 1986). change in the two-dimensional shape of leaf We measured PW and leaf length with cal- blades and at most a 10% inflation in the ipers, often using clear acetate sheets for fos- width of xylem-rich tissues, such as petioles, sils to protect surfaces, or from high-resolu- that are buried in fine-grained sediment (Wal- FOSSIL LEAF ECONOMICS 579

ton 1936; Niklas 1978; Rex and Chaloner 1983; Rex 1986) such as the two fossil locahties studied here (MacGinitie 1969; Wolfe and Wehr 1987); a 10% inflation of PW would lead to a 7.6% overestimation of M^. Leaf Measurements for Quantifying Insect Her- hivory.•High rates of insect herbivory generally correlate with trait values towards the "fast-return" end of the leaf economics spectrum, including high foliar nitrogen concentration and short LL (Coley 1983; Westoby et 100 150 200 250 al. 2002); herbivory is predicted to inversely Leaf mass per area (g nr^) correlate with M^, but this has rarely been di- FIGURE 5. Rate of leaf area removed by insect damage rectly tested in extant vegetation (Moles and (Coley 1983) versus leaf dry mass per area (M^) for pre- Westoby 2000; Poorter et al. 2004) and never sent-day vegetation (saplings) at Barro Colorado Island, before tested in fossil vegetation. To test for Panama. Errors represent standard errors. Statistics of log-log linear regression: n = 44; r^ = 0.36; Fjjj = 24.1; the hypothesized negative correlation be- p < 0.0001. The offset to lower M^ in these data relative tween herbivory and M^, we compared pub- to the fossil reconstructions (Fig. 4) is a consequence of lished data on insect herbivory (Coley 1983) to saplings having leaves with a lower M^ than mature plants (Thomas and Winner 2002), and mature plants M^ determined from saplings of the same spe- constitute the bulk of fossil plant deposits (Spicer 1981). cies in a present-day tropical forest on Barro The offset in herbivory relative to the fossil measure- Colorado Island, Panama (Fig. 5). ments (Fig. 4) is a consequence of the fragmentary nature of fossil leaves (see "Materials and Methods" for Insect damage morphotypes and percent- further details). Importantly, the dividing line in the age of specimens with insect damage were Panama data between leaves that are highly damaged by previously tabulated for the Republic (Wilf et insects and those that are not corresponds to an M^ of -50 g m-2, or a leaf life span (LL) oí -12 months (95% al. 2005) and Bonanza (Wilf et al. 2001) fossil of species with an M^ <51.5 g m"^ have a LL oí <12 floras. Only species for which >23 specimens months, whereas 87% of species with an M^ >51.5 g m"^ could be scored for insect herbivory were in- have a LL oí >12 months). This relationship between herbivory and LL is consistent with the fossil data (see cluded here; this sample size represents a "Results and Discussion") and further emphasizes that compromise between an adequate sampling the fossil and Panama data sets are compatible. level for precise results and the inclusion of enough species to establish reliable site-level trends. To account for uneven sampling across Model Fitting and Justification species, insect damage morphotype data were We fit several models (Table 1) to the ob- randomly subsampled to 23 specimens 5000 served relationships (Appendix A online) be- times without replacement (Wilf et al. 2001), tween M^, PW, and other leaf dimensions. and the means of these subsamples are re- Previous work in two species has shown that ported here (Fig. 4A). Both floras were scored petiole cross-sectional area correlates with for percentage of leaf area lost to insect dam- supported mass and area within species (Nik- age following the method of Beck and Laban- las 1991a; Yamada et al. 1999). Additionally, deira (1998) (n = 1019 and 894 leaves for Re- several studies have examined relationships public and Bonanza, respectively; only those among petiole biomechanical properties with- species where >23 specimens could be scored in and across species (Niklas 1991a,b, 1994, for insect herbivory were included in the tal- 1999). Our study is the first to our knowledge ly); species means were based on the arcsine to demonstrate general scaling between peti- transformation of individual leaves (Sokal and ole and lamina dimensions across diverse spe- Rohlf 1995). We consider these measurements cies, and to develop from these interrelation- (Fig. 4C) minima because areas of the leaf that ships a prediction of M^. Scaling might be in- were not preserved, and that therefore may fluenced by hydraulic supply as well as by me- have been damaged or entirely removed by in- chanical support because the petiole delivers sects, cannot be analyzed. the transpiration stream to the leaf, and peti- 580 DANA L. ROYER ET AL.

TABLE 1. Models fitted. AU models are based on individual species-site samples (n = 667). Both leaf dry mass per area (M^; units in g m"^) and the predictor variables are handled on log scales to allow the use of power law allometries, and because variance increases with the mean whereas after log transformation scatter is more normally distributed (Fig. 2A). All models are fitted using linear regression in order to minimize the sum-of-squares in the y-dimension (i.e., M^), to facilitate retrodiction with fossils. This contrasts with the standardized major axis (SMA) estimation (also known as Model II regression, geometric mean regression, or reduced major axis), where errors in both the X- and y-dimensions are minimized simultaneously (Falster et al. 2003; Warton et al. 2006); we use SMA to investigate the slopes of allometric relationships (see Model Fitting and Justification). The logic of each model is explained in Model Fitting and Justification; Model E corresponds to equation (1) in the text. PW = petiole width (mm); A = one-sided projected area of leaf (mm^); L = leaf length (mm); N/A = not applicable because SMA cannot be calculated for multivariate models.

Model Slope* SMA A log(MA) = a + log(PWVA) 4.930 0.89 0.13 1.00 B log(MA) = a + \og{PWO'yA) 4.870 0.92 0.001 1.00 C logiMj = a + Wog(PWVA) 2.740 0.289 0.47 1.13 0.42 D log(MA) = a + Mog(PW/A) 2.870 0.307 0.42 1.09 0.47 E logiMj = a + Wog(PV\P/A) 3.070 0.382 0.55 1.04 0.51 F log(MA) = a + Wog(PW) + dog(A) 3.064 0.983 -0.386 0.58 1.05 N/A G logíMJ = a + Mogl{PW)/(L X A)] 2.876 0.194 0.39 1.10 0.32 * slope of measured vs. estimated M^ linear regression fixed through the origin. ole cross-sectional area correlates with xylem tionship between the ratio of the square of pet- vessel area and with petiole hydraulic con- iole cross-sectional area to leaf area versus ductance per leaf area for leaves of a given M^. This relationship, M^ =^ PW^/A, where species (Salisbury 1913; Sack et al. 2002, 2003). PW = petiole width and A = leaf area, would However, across distantly related species, pet- be expected if the leaf behaved as a mass ap- iole cross-sectional area per leaf area does not plied to a vertical petiole that was just suffi- necessarily correlate with petiole or leaf hy- cient to support it. Preservation of compres- draulic conductance per leaf area because sive strength to maintain resistance to buck- both the numbers and sizes of xylem conduits ling then leads to the expectation of PV\P «: M, within petioles vary strongly (Nardini et al. where M = leaf mass, and thus M^ '^ PVP/A. 2005; Sack and Frole 2006). This scaling treats petiole length as varying Here we discuss the possible underlying bi- little, or at least independently of leaf size. Al- ology of the models, the statistical strengths of ternatively, if petiole length and width are co- their fitting to the data, and possible interpre- optimized, a slightly different scaling follow- tations of the observed scaling coefficients. We ing "elastic similarity" as for animal legs note that although our models consider peti- might be expected (McMahon and Bonner ole length implicitly as described below, we do 1983; Peters 1983; Schmidt-Nielsen 1984), with not explicitly include petiole length as a pre- PW"*^^ a M (and M^ ^ PW^^A; Model B). dictive variable because complete fossil peti- Leaf mass is only rarely incident on a ver- oles are rare. Also, we recognize that wind tical petiole; instead, leaves are usually better load may affect scaling relationships between modeled as end-loaded cantilevered beams M^ and petiole dimensions because plants in (Niklas 1991b, 1999). Under this scenario, if windy habitats can have higher M^ and small- the petiole supports the leaf mass with a fixed er petiole cross-sectional area to allow easier deflection distance, at a given wind-load, and bending and twisting for reducing drag (Nik- without leaf shape and petiole composition las 1996, 1998). However, because this adap- and mechanical properties being influential tation would lead to the opposite trend doc- variables, the expected relation is M oc 3 El/ umented here (Fig. 2), wind load is likely of PU, where E is the petiole elastic modulus, I only minor importance. Lastly, the relation- the second moment of area of the petiole, the ships in this study were determined across di- product El the petiole flexural rigidity, and PL verse species, but they have yet to be tested the petiole length (Niklas 1991b, 1994, 1999). within species. Indeed, previous work has shown that PL^ Model A is based on a simple scaling rela- scales with El as expected from the cantilever FOSSIL LEAF ECONOMICS 581

model across a diverse range of leaves (Niklas ally longer life spans (Villar and Merino 2001; 1991b, 1994, 1999). Model C applies this sce- Wright et al. 2004). nario, assuming PW to be independent of PL, Model E, corresponding to equation (1), was and petiole shape to be relatively invariant; in used for estimation because of its relatively this case, M would be proportional to El and high goodness of fit (r^ = 0.55 for species / would be related to PW\ and M^ ^ PW^/A. means) and its low bias (the slope of the plot Model D applies the same scenario, addition- for measured versus estimated M^ is 1.04; Ta- ally assuming that PW «: PL; in this case, the ble 1). This model also has the advantage of cantilevered beam model simplifies to M ^ being a simple expression of the allometric 3{E1/PU) <^ 3(E X PWyPU) oc PW, and M^ « scaling of petiole and lamina dimensions as PW/A. discussed above. The parameters of Model E Models E-G represent additional scenarios, indicate that an approximation of petiole with greater flexibility. Model E preserves the cross-sectional area relative to leaf area scales expectation of the scaling of PWP with M, as strongly with M^, with SMA slope of 0.51 in Model A (and as observed to hold within (±0.026 95% confidence intervals); this model given species, as discussed above), but allows is most compatible with petioles with circular an allometric scaling, M^ oc {PWß/Af. Model and square cross-sections (fcX^, where fc is a F modifies Models C-E by allowing the ex- constant and X is the length of the side of a ponents to vary independently. Model G mod- square or the radius of a circle), however a ifies Model D by including leaf length as an mixture of cross-sectional shapes will de- additional factor, reflecting the extra leverage crease somewhat the predictive power of the of a given mass that is farther from the attach- model. Model F has a slightly higher r^-value ment point of the leaf. than Model E (0.58; Table 1), but this extra ex- The fits of Models C-G indicate a strong planatory power is largely due to Model F's scaling of M^ with petiole and lamina dimen- having an additional parameter. sions (Table 1); however, the fitted parameters Calculating Errors for M^ Estimates.•The cal- do not fit simply with many of the expecta- culation of 95% prediction intervals (PI) fol- tions discussed above. For example. Models lows Sokal and Rohlf (1995): C-E and G show slopes b substantially lower log PI than the expectations for a slope of 1, as determined by a standardized major axis (SMA) 1 1 (X, - xy estimation (Falster et al. 2003). Further, all I log M, - + - + ^ models indicate that PW relative to leaf area is 1 inordinately high for leaves of high M^ rela- X in^0.05[i!-2]' K-^) tive to what simple support requirements where Sy.x^ = unexplained mean square, k = would require, under any of the above scenar- size of unknown sample, n = sample size of ios. This could be one explanation for the pre- calibration data, X, = mean log(PW^/A) of un- viously demonstrated result that petiole flex- known sample, X = mean log(PVV^/A) of cal- ural rigidity (E7) increases more strongly with ibration data, X x^ = sum of squares of cali- leaf mass (M) than is predicted from the can- bration data, and f, critical value of tilever model {El «: M with an exponent of 1.6- 0.05[«-2] Student's distribution for (n • 2) degrees of 2.3 for diverse species sets [Niklas 1991a]). freedom. Table 2 provides the necessary in- The disproportionate PW relative to leaf area formation for calculating 95% Pis (for species for leaves of larger M^ and the consequently and sites) from the regressions presented in higher petiole flexural rigidity would contrib- Figure 2A; errors are asymmetric with respect ute greater support stability given that the to means because the regressions are based on laminar center of mass could be displaced logarithmic relationships. over larger petiolar second moment of area. Such investment in greater safety is consistent Results and Discussion with the investment in greater construction Testing Extant Vegetation.•Fitting Model E cost for leaves of higher M^, and their gener- to our calibration data shows that the M. of 582 DANA L. ROYER ET AL.

TABLE 2. Parameters used to calculate 95% predictions intervals for estimates of leaf dry mass per area (M^). S^.x = unexplained mean square, n = sample size of calibration data, X = mean log(PW^/A) of calibration data, Sx^ = sum of squares of calibration data, and ioo5[• - 2] ~ critical value of Student's distribution for (n • 2) degrees of freedom. See "Materials and Methods" for details.

X in Species means 0.032237 667 -3.011 182.1 1.964 Site means 0.005285 25 -2.857 5.331 2.069

individual species is estimated to a significant tercorrelated (Reich et al. 1997; Westoby et al. degree (Fig. 2A; n = 667, r^ = 0.55, F^ ^66 = 825, 2002; Wright et al. 2004, 2005), our method has p < 0.0001): 95% prediction intervals (Sokal the potential to predict other traits. For ex- and Rohlf 1995) are ¡^ô/° of observed values. ample, in a worldwide compilation of leaf eco- assuming a sample size of three leaves. This nomic information (Wright et al. 2004), a M^ error is small compared to the ~30-fold range of 129 g m^^ for woody angiosperms corre- observed across species. sponded to a mean LL of 12 months. We de- Estimates of M^ are unbiased: the regres- termined this LL category (<12 or >12 sion slope of the measured versus estimated months) for a subset of our data (n = 496 spe- MA is close to unity (1.04 ± 0.04 95% confi- cies-site pairs). A PViF/A of 0.0011, corre- dence intervals). Mean values for sets of spe- sponding to an estimated M^ of 87 g m^^, cor- cies at sites can be estimated very precisely be- rectly predicts the LL category 85% of the time cause of the lack of bias and increased sample in our calibration data. We adopt these M^ val- size (Fig. 2A; n = 25, r^ = 0.89, F^ 24 = 186, p ues to broadly distinguish between the short- < 0.0001; 95% prediction intervals for individ- lived "fast-return" (<~87 g m^^) and long- ual sites are ~±}|o/° of their observed values, lived "slow-return" (>~129 g m^^) ends of assuming a sample size of ten species). Pre- the leaf economic spectrum. liminary data from broad-leaved gymno- Application to Fossil Record.•We hypothe- sperms (n = 25 species) match the correlation sized low M^ at Republic and a broader range as well (Fig. 2B), suggesting applications that of M^ at Bonanza on the basis of previously include the pre-angiosperm record. published, qualitative interpretations (see "In- We tested whether MAT or MAP modulated troduction"). Consistent with hypotheses, re- the relationship between M^ and PV\P/A in sults from Republic show domination by low- our calibration data, using partial correlation. M^ species (57-87 g m^^; Table 3). Conse- The relationship between PW^/A and M^ re- quently, it is likely that most of these species mains significant and largely unchanged (full had leaf life spans of <12 months, suggesting correlation: r = 0.74; correlation after account- the presence of a deciduous forest among the ing for MAT and MAP: r = 0.75 and 0.74, re- angiosperms. Also consistent with hypothe- spectively; n = 667 and p < 0.0001 for both ses, the Bonanza flora shows a broader mix of tests). This insensitivity to environmental con- MA values (70-157 g m-^; Table 3). The most ditions contrasts with many other paleoeco- abundant species at Bonanza have high M^ logical and paleoclimatological proxies (Royer values (Table 3), suggesting that the vegeta- et al. 2002) and reinforces the notion that tion was dominated by species with long-lived PW^/A is a faithful recorder of M^. Moreover, leaves. The site mean of M^ among angio- interrelationships among leaf economic vari- sperms is significantly higher at Bonanza than ables such as M^ and LL are not strongly mod- Republic (113.2 ±î|| versus 76.8 ±1^ g m-^; er- ulated by phylogeny (Ackerly and Reich 1999); rors represent 95% prediction intervals; f^ 14 = this is important for paleobiological studies, 3.54, p = 0.003), and Bonanza is associated where fossil taxa may be extinct, be only dis- with a higher coefficient of variation (23.8% tantly related to taxa in the calibration data, or versus 12.8%; f^ 17 = 2.85, p = 0.01 after arcsine have unknown affinities. transformation; Sokal and Rohlf 1995). Because leaf economic traits are strongly in- Thus, these floras had very different ecolog- FOSSIL LEAF ECONOMICS 583

TABLE 3. Reconstructions of leaf dry mass per area (M^) for measurable species in the Republic and Bonanza fossil floras. MA estimates for the Fabaceae (legumes) may be somewhat too high because of their short, pulvinulate petiolules.

Abundance* (%) M^** (g m-^) REPUBLIC Alnus parvifolia (Betulaceae) 37 44.2 82.5 Betula leopoldae (Betulaceae) 5 3.1 72.0 Cercidiphylluni obtritum (Cercidiphyllaceae) 17 12.6 81.7 Cornus sp. (Cornaceae) 2 0.8 57.3 aff. Crataegus sp. (Rosaceae) 3 0.5 79.8 Crataegus sp. (Rosaceae) 2 3.2 84.8 Ericaceae sp. 2 0.4 84.0 Itea sp. (Saxifragaceae) 3 2.0 77.9 Macginitiea gracilis (Platanaceae) 2 1.8 69.2 Photinia pageae (Rosaceae) 2 2.0 63.2 Prunus sp. (Rosaceae) 2 0.6 68.4 Rhus malloryi (Anacardiaceae) 7 2.9 85.6 Sassafras hesperia (Lauraceae) 4 4.8 80.6 Spiraea sp. (Rosaceae) 8 2.5 86.7 Ternstroemia sp. (Theaceae) 2 0.2 87.0 Ulnius sp. (Ulmaceae) 8 8.1 67.0 Zelkaoa sp. (Ulmaceae) 2 0.5 85.9 Zizyphoides flabella (Trochodendraceae) 2 1.7 63.0 BONANZA Allophylus flexifolia (Sapindaceae) 4 4.9 73.6 Caesalpinia pecorae^ (Fabaceae) 5 4.4 133.2 Cardiospermum coloradensis* (Sapindaceae) 2 3.8 96.7 Cedrelospermum nervosumt (Ulmaceae) 18 26.7 118.3 Leguminosites lesquereuxiana (Fabaceae) 6 2.0 103.3 Macginitiea myomingensist (Platanaceae) 7 5.3 70.0 Parvileguminophyllum coloradensis* (Fabaceae) 5 33.1 156.6 Populus tidmelliit (Salicaceae) 2 2.6 98.9 Populus wilmattaet (Salicaceae) 3 2.9 82.7 Rhus nigricans (Anacardiaceae) 13 7.2 115.2 Salix cockerellit (Salicaceae) 6 2.7 96.1 Styrax transversa (Styracaceae) 4 0.8 72.2 Syzygioides americana (Myrtaceae) 2 1.0 137.2 * Based on unbiased field census collections (Wilf et al. 2001, 2005). Values within floras do not sum to 100% because not all species are represented here (see "Materials and Methods"). ** We interpret leaves with Mj^ values of <87 g m"^ to have leaf life spans of <1 year, and leaves ^vith M^ values >129 g m"^ to have leaf life spans of >1 year (see "Results" and "Discussion"). t Inferred by Wilf et al. (2001) to have long leaf life spans. ^ Inferred by Wilf et al. (2001) to have short leaf life spans. ical structuring among woody angiosperms. we infer that forest-wide nutrient cycling Republic was dominated by species associated among woody angiosperms was probably with relatively rapid mass-based rates of gas more rapid at Republic than Bonanza. exchange and more rapid litter decomposi- By quantifying the frequency, amount, and tion, whereas Bonanza was dominated by diversity of insect damage on leaves from Re- "slow-return" species, but with an important public and Bonanza, we directly correlated secondary component of "fast-return" spe- M^ (and LL by extension) to insect herbivory cies. This difference may have been driven by (Fig. 4). We hypothesized a negative relation- the seasonally drier climate at Bonanza, a pat- ship because leaves with high NLf^ are typically tern consistent with observations in present- associated with greater thickness and/or day vegetation of greater variance in M^ in toughness, higher amounts of chemical toxins seasonally dry forests relative to moister for- and/or other chemical deterrents, and lower ests (Niinemets 2001; Wright et al. 2005). Be- foliar nitrogen concentrations (Coley 1983; cause litter decomposition rates influence nu- Westoby et al. 2002); all of these characteristics trient turnover rates (Kobe et al. 2005) and re- help to minimize insect damage. At Republic, gional biogeochemical cycling (Chapin 2003), where all species have an estimated M^ of <87 584 DANA L. ROYER ET AL. g m"^, insect damage ranges from moderately nomic information, including important as- high to very high (Fig. 4). In contrast, at Bo- pects of plant-animal interactions and con- nanza there is a greater range in M^ and her- straints on nutrient cycling rates, from bivory levels, and these properties negatively lesser-known floras. correlate with one another. For both floras, the dividing line between species that are highly Acknowledgments damaged and those that are not corresponds This work arose from a working group of the to an MA of 90-100 g m^^ (Fig. 4), or an in- ARC-NZ Research Network for Vegetation ferred LL of ~12 months. These Eocene results Function, supported by the Australian Research are consistent with our predictions and with Council. This work was also supported by the patterns observed in an extant forest (Fig. 5), Petroleum Research Fund of the American suggesting that strong insect selection of leaf Chemical Society grant 40546-AC8, the Perm functional traits is of great antiquity. State Institutes of Energy and the Environment, a Macquarie University New Staff Grant Conclusions A007220, the Estonian Academy of Sciences, An extant calibration indicates that leaf and National Science Foundation grants DEB- mass per area can be easily reconstructed for 0345750, EAR-0236489, and IOB-0546787. We fossils from the measurement of petiole width thank R. Bumham, N Cellinese, D. Danehy, D. and leaf area. This represents, to our knowl- Dilcher, B. Ellis, P Huff, C. Jander, E. Kowalski, edge, the first proxy for fossil M^. Some key T. Lott, E. Manzane, F Marsh, D. Meade-Hunter, advantages of the method include the follow- S. Passmore, M. Reynolds, C. Streeter, S. Trom- ing: the required measurements can be made bulak, M. Wiemann, K. Wilson, S. Wing, G. quickly and accurately on most well-pre- Zotz, and the 45 members of the World Herbiv- served leaf fossils; the statistical errors for pre- ory Project for help in collecting and processing dicting M^ are at most ±3^^ if three or more specimens. We thank R. Burnham, K. Niklas, leaves are measured per species; and the bio- and J. Parrish for constructive reviews. This is mechanical scaling relationship is not strongly contribution 171 of the Evolutionary and Ter- modulated by factors that can be difficult to restrial Ecosystems consortium at the National evaluate in the fossil record (e.g., temperature, Museum of Natural History. rainfall). Importantly, a preliminary analysis suggests that the method may also be appli- Literature Cited cable for some gymnosperm groups. Ackerly, D. D., and P. B. Reich. 1999. Convergence and correla- We quantified M^ for 31 species in two well- tions among leaf size and function in seed plants: a compar- understood Eocene floras, and we compared ative test using independent contrasts. American Journal of Botany 86:1272-1281. these estimates with measurements of insect Beck, A. L., and C. C. Labandeira. 1998. Early Permian insect herbivory and qualitative inferences of other folivory on a gigantopterid-dominated riparian flora from leaf economic variables for the same species. north-central Texas. Palaeogeography, Palaeoclimatology, Pa- laeoecology 142:139-173. At Republic, where most species have an in- Brentnall, S. J., D. J. Beerling, C. P. Osborne, M. Harland, J. E. ferred short LL, we reconstructed low M^; at Francis, P. J. Valdes, and V. E. Wittig. 2005. Climatic and eco- Bonanza, where there is a broader range in in- logical determinants of leaf lifespan in polar forests of the high C02 Cretaceous 'greenhouse' world. 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