Growth, Seasonality, and Lizard Life Histories: Age and Size at Maturity

Nordic Society Oikos

Growth, Seasonality, and Lizard Life Histories: Age and Size at MaturityAuthor(s): Stephen C. Adolph and Warren P. PorterSource: Oikos, Vol. 77, No. 2 (Nov., 1996), pp. 267-278Published by: Blackwell Publishing on behalf of Nordic Society OikosStable URL: http://www.jstor.org/stable/3546065Accessed: 08/07/2009 12:52

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OIKOS 77: 267-278. Copenhagen 1996

Growth, seasonality, and lizard life histories: age and size at maturity

Stephen C. Adolph and Warren P. Porter

Adolph, S. C. and Porter, W. P. 1966. Growth, seasonality, and lizard life histories: age and size at maturity. - Oikos 77: 267-278.

Temperature influences the activity seasons, reproductive phenology, survival rates, and growth rates of lizards. We present a model of lizard growth that predicts phenotypic patterns of age and size at reproductive maturity in different thermal environments (i.e. different activity seasons). The model predicts a threshold in length of activity season: above this threshold (long season), lizards can mature one year earlier, but at a smaller size, compared to populations with activity seasons below the threshold. This environmentally imposed pattern reflects the proximate consequences of temperature, together with simple rules about the timing of maturation. A key prediction of the model is that age and size at maturity can vary non-linearly with the length of the activity season, and with the timing and duration of egg laying and hatching. We tested these predictions with published data from field studies of the phrynosomatid lizard Sceloporus undulatus, which is geographically widespread and occupies a range of thermal environments. We estimated activity seasons for each population by modeling the links between climates, microclimates and lizard body temperatures using heat-transfer principles. Female age at maturity showed the predicted threshold in length of activity season, whereas female size at maturity did not show the predicted threshold, but instead was negatively correlated with length of activity season. Two prairie populations were exceptions to this pattern: females matured in one year despite their short activity seasons, and consequently matured at an unusually small size. Prairie populations may have evolved differences in growth response and reproductive timing. The thermal environment appears to be an important correlate of life history variation among populations of Sceloporus undulatus.

S. C. Adolph and W. P. Porter, Dept of Zoology, Univ. of Wisconsin-Madison, 1117 West Johnson St., Madison, WI 53706, USA (present address of SCA: Dept of Biology, Harvey Mudd College, 301 E. Twelfth St., Claremont, CA 91711, USA (stephen_ adolph@hmc .edu)).

A central question in life history research is whether variation among populations or species represents environmental or genetic variation (Ballinger 1983, Stearns 1989). Historically, this question has received less attention than the separate issue of whether life history variation is adaptive. However, an increasing number of studies have examined proximate environmental influences on the expression of ectotherm life history traits (Ballinger 1977, 1979, Dunham 1978, Berven et al. 1979, Ferguson and Brockman 1980, Berven and Gill

1983, Porter and Tracy 1983, Jones and Ballinger 1987, Jones et al. 1987, Sinervo and Adolph 1989, 1994, Grant and Dunham 1990, Sinervo 1990, Grant and Porter 1992, Ferguson and Talent 1993, Niewiarowski and Roosenburg 1993, James and Whitford 1994, Curtin 1995). Many of these studies address the role of temperature, which frequently exerts strong proximate effects on ectotherm life histories (Levinton and Mona- han 1983, Conover and Present 1990, Sinervo and Doyle 1990, Adolph and Porter 1993, Bernardo 1994).

Accepted 10 January 1996

Copyright ? OIKOS 1996 ISSN 0030-1299 Printed in Ireland - all rights reserved

OIKOS 77:2 (1996) 267

The thermal environment restricts the growing season for many organisms. Organisms at low elevations or low latitudes can grow and be active much of the year, whereas the growing season is curtailed at high elevations or high latitudes. Thermal effects on growth can greatly alter life histories. A common consequence is that organisms in cold environments exhibit delayed maturity, postponing reproduction until they are chronologically older (Tinkle et al. 1970). Although age at maturity is an important life history parameter (Cole 1954, Roff 1992, Stearns 1992), relatively little attention has been paid to the evolution of age and size at maturity among populations experiencing different thermal environments (Stearns and Koella 1986, Berri- gan and Charnov 1994). A first step is to quantify how these life history traits would be expressed in different environments in the absence of other differences (e.g., genetic composition, food resources) among populations (Stearns 1989). This can serve as a physiologically based null hypothesis for life history variation, useful both for evaluating field data and for constructing models of life history evolution that incorporate proximate effects (e.g., Beuchat and Ellner 1987).

A related complication results from seasonal constraints on reproduction. In the vast majority of lizard species, reproduction occurs at particular times of year (Fitch 1970, Duvall et al. 1982, James and Shine 1985). For example, most temperate zone oviparous lizards reproduce during the first half of the activity season. Reproductive phenology leads to a discontinuous distribution of ages at maturity of lizard populations and species (Fig. 1). The modal reported age at maturity is 12 months, and represents both tropical and temperate species. A second mode occurs at 24 months. Gaps in the distribution presumably reflect times of year that would be inappropriate for reproduction, and therefore inappropriate for a growing lizard to become reproduc-

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tively mature, although it may have attained the minimum size for reproduction. The discontinuities imposed by reproductive seasonality complicate both the inter- pretation of comparative data and the formulation of models predicting optimal life histories.

In this paper, we present a simple model for growth and maturation of lizards in a seasonal environment. The model uses daily and annual activity times as measures of physiological time for lizards (Sinervo and Adolph 1989, 1994, Adolph and Porter 1993), analogous to degree-day measures used for insects, marine invertebrates, and plants (Taylor 1981, King- solver 1989, Sinervo and Doyle 1990, Roff 1992, Wood- ward 1992). The model assumes that growth rate is temperature dependent (Buffenstein and Louw 1982, Avery 1984, Sinervo and Adolph 1989, 1994), and predicts how age and size at maturity will differ among short and long growing seasons, as a proximate consequence of temperature. We then evaluate data on size and age at maturity from field studies of the eastern fence lizard Sceloporus undulatus (Sauria: Phrynoso- matidae), which is widespread in North America and occurs in a variety of thermal environments. We used computer models based on biophysical principles to estimate activity seasons for 11 populations, and compared published data on female age and size at maturity to our estimates of activity seasons. This serves as an empirical test of our growth model and identifies populations whose life history features deviate from general patterns of covariation between life histories and thermal environments.

Thermal dependence of lizard growth rate Individual growth curves of small iguanid lizards are reasonably well described by the logistic-by-mass function

dM M ( dt r Ml I- )

I 0 I1Illllli . ... 1. m.. .11

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 > 40

AGE AT MATURITY (MONTHS)

Fig. 1. Frequency distribution of ages at reproductive maturity of female lizards (field data compiled by Dunham et al. 1988). These data represent 139 populations of 102 species from 10 families, collected by a variety of researchers. The distinctness of the modes at 12 and 24 months, and the absence of data for some ages (e.g., 23 months), may reflect rounding by some researchers. Nevertheless, it is clear that most lizards mature within their first two years, and that maturation times are constrained by annual environmental cycles.

(1)

where M is mass, t is time, r is a growth constant, and M,..ax is the maximum (asymptotic) mass (Dunham 1978, Schoener and Schoener 1978, Andrews 1982). Integrating (1) yields

M= M_-X

+ -M .I.e-,)' + \ 0Mo

(2)

which describes lizard mass as a function of time and initial mass Mo. This equation can be modified to include other factors affecting growth by considering r as a variable rather than a constant parameter. For example, the effect of reduced food level could be

268 OIKOS 77:2 (1996)

modeled by choosing a smaller value of r. Similarly, thermal influences on growth rate can be modeled by making r a function of body temperature, Th. Because rt appears as a product in eq. 2, modifying r can be viewed as rescaling chronological time t in terms of physiological time.

Here, we are interested in the effect of the thermal environment on growth rate. For temperate zone lizards, temperature is likely to influence growth in two ways. First, lizards only grow during their activity season, which is jointly determined by the availability of suitable microclimates, temperature-dependent physiology and behavior, and sometimes additional considerations (e.g., food and moisture availability). During winter inactivity, lizards lose some body mass (e.g., Blair 1960). Thus, annual growth potential will be greater in environments with a longer activity season, all else being equal (Pianka 1970, Tinkle 1972a, Ballinger 1979, 1983, James and Shine 1988, Grant and Dunham 1990). Second, growth rates during different parts of the activity season are likely to vary due to seasonal variation in temperature, water, food availability, and energy expenditure (Andrews 1982).

Daily growth rates during the activity season are likely to be a function of the amount of time the thermal environment permits activity at high T,b, i.e., by "thermal opportunity" (Sinervo and Adolph 1994). This assumption is supported by several laboratory studies on lizards and snakes. Growth rates of juvenile Lacerta vivipara, Sceloporus occidentalis, Sceloporus graciosus, and Thamnophis elegans increase with daily activity time (i.e., access to high T,, via heat lamps; Avery 1984, Sinervo and Adolph 1989, 1994, Sinervo 1990, Peterson and Arnold, cited in Peterson et al. 1993). Thermally induced variation in growth rates probably results from several mechanisms acting in concert (Sinervo and Adolph 1989, Adolph and Porter 1993). Lizards with longer activity times spend more time at high Th, at which rates of physiological pro- cesses underlying growth (e.g., metabolism, digestion) are higher (Bennett and Dawson 1976, Skoczylas 1978, Huey 1982). Longer activity times also permit longer feeding periods (Avery 1984, Karasov and Anderson 1984, Waldschmidt et al. 1986). Thus, growth rates should often be positively correlated with thermal opportunity, whether growth is limited by processing rates or by resource harvesting rates (Congdon 1989).

Following the above laboratory studies, we assume that daily growth rates increase linearly with daily activity time h according to

r = rmax ch, (3)

where r,,ax is maximum relative growth rate and c is a constant relating growth rate to activity time. Labora- tory experiments with juvenile Sceloporus occidentalis and S. graciosus indicate that a linear growth model is

MONTH

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Fig. 2. A) Seasonal variation in potential activity time of a diurnal lizard, as determined by the thermal environment and thermal physiology of the lizard. Within the ellipse thermal conditions permit activity; outside the ellipse lizards would be inactive. Here, we present activity season characteristic of many diurnal temperate zone lizards. Seasonal activity patterns in deserts and lowland tropical areas may be better described by other shapes, such as rectangles or ellipses with midday periods of inactivity (Adolph and Porter 1993). B) Activity ellipse for a warm environment. Dates of oviposition (dark area) and egg hatching (hatched area) are indicated. C) Activity ellipse for a cool environment, including dates of oviposition and hatching.

reasonably accurate for day lengths up to 12 h (Sinervo and Adolph 1989, 1994). In Appendix A we show how a curvilinear growth function can be incorporated into the model. A curvilinear growth response does not alter the general results.

Substituting (3) into (1) gives the following expression for the dependence of daily growth rate on temperature, via the effect of temperature on activity time:

dM (M M

dt IIX

Ml(t-A^ ) (4)

Seasonal variation in activity times and growth rate

In the temperate zone, potential daily activity times for diurnal lizards are typically long in the summer and short in the spring and fall (Porter et al. 1973, Porter and Tracy 1983, Sinervo and Adolph 1994). This pattern of seasonal change in daily activity time can be conveniently approximated as an ellipse (Fig. 2), where the length of the activity season = 2y d, and the length

OIKOS 77:2 (1996) 269

of the maximum activity day = 2d h (Adolph and Porter 1993). For an elliptical activity season the potential number of hours of activity per day is then given by

h = 2d1- ) (5)

where j represents the Julian day of the year, rescaled so that j = 0 at the middle of the activity season, where h is maximal. The area of the ellipse rT y d equals the cumulative potential hours of activity per year.

Diurnal lizards are primarily active when the thermal environment permits them to reach a T. within their preferred range (Cowles and Bogert 1944, Bartlett and Gates 1967, Norris 1967, Huey 1982). Values of y and d reflect these thermal constraints, which are determined both by environmental characteristics (mainly air temperature and solar radiation) and by the lizard's thermal physiology and morphology (Porter et al. 1973, Porter and James 1979, Porter and Tracy 1983, Bakken 1989, 1992, Grant 1990, Adolph and Porter 1993). As discussed in Adolph and Porter (1993), shapes other than ellipses might be more appropriate for certain thermal environments, such as deserts or tropical low- lands. Here, we will restrict our analysis to elliptical activity seasons, but our model can be applied readily to any seasonal activity pattern.

Substituting expression (5) into eq. (4) yields an expression for growth rate as a function of time of year:

dt (6)

Eq. (6) is a modified version of eq. (1), with additional factors that rescale daily growth rate according to thermal opportunity. To determine how body mass changes we need to integrate eq. (6) over the appropriate time period. This yields

_f(j) 1- 1 1_

f(io) _M M x _ Mm ' (

where Mo = body mass at the beginning of the time period, J0 = initial date, and

f(j) = exp{rma /y2 x2 + y sin- (} (8)

For example, for the first (partial) growing season, Mo represents hatchling (or neonate) mass and Jo the date of hatching (or birth). Eq. (7), evaluated at j = y, gives the size reached by juveniles when their first growing season ends.

Environmental seasonality and age and size at maturity

Eq. (7) can be used to examine how age and size at maturity will vary as a proximate consequence of different thermal environments. This requires additional information on hatchling or neonate size, minimum reproductive size, and reproductive phenology. Sizes at hatching and sexual maturity can be estimated from interspecific allometric relationships, if data are un- available (Appendix B).

We assume that a growing lizard will become reproductively mature if it has reached the minimum reproductive size and it is the appropriate time of year. This rule seems reasonable for lizards, although different rules may apply for other ectotherms (Bernardo 1993). Temperature probably plays the most important role in determining the time window for physiological decisions regarding maturation in temperate zone lizards, both as a proximate factor and a selective agent (Licht 1984, Lofts 1978, Marion 1970, 1982, Duvall et al. 1982). The latest possible date at which a maturation decision is feasible for females is likely to be determined by the total length of time required to mobilize resources for ovarian development, to produce eggs, for the eggs to incubate (or gestate), and for hatchlings (or neonates) to prepare for the onset of the inactive season. A longer activity season should permit an earlier date for the beginning of the maturation window, as reflected by the earlier reproduction frequently observed at lower alti- tudes and latitudes (Fitch 1970, Goldberg 1974). In addition, longer activity seasons often allow multiple clutches by a single female (e.g., McCoy and Hodden- bach 1966, Fitch 1970, Pianka 1970, Pianka and Parker 1972, Goldberg 1974, Parker and Pianka 1975, Ballinger 1983, Jones et al. 1987, James and Shine 1988), suggesting that window duration should increase with the length of the activity season.

A variety of mechanisms could be responsible for the timing and duration of the maturation window in natural populations. For the purposes of this model, it is not necessary to identify the mechanism(s) operating in nature, but it is useful to specify a quantitative relationship between the maturation window and the length of the activity season that is consistent with observed patterns. Here, we assume that the maturation window spans a constant proportion of the activity season length (in d), with the initial date given by j = -0.75y and the final date by j= -0.4y. Thus, the maturation window will begin at an earlier calendar date given a longer activity season, and its length will increase linearly (with a slope of 0.35) with the length of the activity season.

Fig. 3 shows an example of a female lizard's growth to reproductive maturity in a cool environment with a short activity season (180 d; y = 90; 1,696 h/yr) and a warm environment with a long activity season (280 d; y = 140; 2,639 h/yr). Both seasons have maximum daily

OIKOS 77:2 (1996) 270

SHORT ACTIVITY SEASON

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window

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RELATIVE DATE (DAYS)

Fig. 3. Examples of growth curves for a lizard with a short activity season (upper panels) and a lizard with a long activity season (lower panels), calculated using eq. 7. We used the same growth parameters for both examples: r,,,.. = 0.02, c = 0.0833, Mhatchling = 0.75 g, M,,,a- = 20 g. Shaded regions indicate maturation windows, during which a lizard must reach the minimum reproductive size (8.0 g, based on allometric relationships in Appendix B) in order to become reproductively mature that season. In this example, we assumed the maturation window included days affording 8-11 h activity. In the cool environment (short season), the lizard does not reach the minimum size until after the maturation window, so it continues to grow until the end of the activity season. It matures in its second full growing season, at nearly two years of (chronological) age, and at a relatively large size. In contrast, the lizard with the long. growing season is able to reach minimum reproductive size at the end of its first maturation window, and therefore matures at nearly one year of age and a small size.

activity periods of 12 h/d (d= 6). Growth follows eq. (7), with parameter values given in the figure legend. We assumed the same growth parameters, hatchling size, and minimum size at maturity for both cases, so that growth differences were due solely to environmental differences. In the short activity season, the lizard hatchling has 50 d to grow before the end of the activity season. During its second growing season, it does not reach minimum reproductive size during the maturation window, and continues to grow until the end of the season. By the time it reaches the maturity window in its third growing season, it is well above the minimum size for maturation. Its size at maturity is 12 g, and its chronological age at maturity is 20.5 months. In the long growing season, the hatchling has 120 d to grow during the remainder of the growing season. In its second year, the lizard reaches minimum reproductive size towards the end of the maturation window, and therefore matures at a small size (8 g) and a young age (9.4 months). After they mature, female lizards would probably not follow the illustrated growth trajectories because energy is diverted towards reproduction.

The long and short activity seasons in the above example (Fig. 3) represent points along a continuum of possible activity seasons. In Fig. 4 we show the average ages and sizes at maturity obtained for a range of activity seasons, using a particular set of growth parameters (see the figure caption for parameter values). For this example, we assumed a uniform distribution of hatching dates, beginning 100 d after the first date of the maturation window and ending 100 d after the last date of the maturation window. Thus, the duration of the hatching period was equal to the duration of the maturation window, which increased with the length of the activity season. For each hatching date, we determined the age and size at which a lizard would reach reproductive maturity, based on the growth and maturation rules outlined above. We then computed the mean size and age at maturity (averaged over all hatching dates) for each activity season.

For short activity seasons, the model predicts an average age at maturity around 20 months, whereas for long activity seasons lizards mature around 8 months of age. For intermediate activity seasons, average age at maturity reflects a combination of some lizards who mature in their first full summer and some who mature in their second full summer, depending on hatching date. As season length increases, a larger proportion of hatching dates would allow maturation in under one year, so the average age at maturity declines. Size at maturity varies with length of activity season in a more complicated way. Initially, as season length increases, average size at maturity increases, because of the greater amount of time available for growth between hatching and the maturation window. Once the season is long enough for the earliest hatchlings to mature in their first year, however, average size at maturity de-

OIKOS 77:2 (1996)

U- LL LEL 0 w 2

24 , Ii . .... l

271

of a single species. The eastern fence lizard, Sceloporus undulatus (Sauria: Phrynosomatidae), is an excellent

20- . ....... candidate (Jones and Ballinger 1987). Sceloporus undulatus is widespread in the United States, occurring

15- in montane, woodland, prairie and desert habitats (Smith 1946). Field studies by a number of researchers

10- have demonstrated extensive geographic variation in a number of life history traits. We used data from

1000 1500 2000 2500 3000 11 populations (Fig. 5) collected by several different researchers; these data are summarized and analyzed

20 in Tinkle and Dunham (1986) and Dunham et al. (1988).

15- / X Data on duration of activity season were not reported for most of these populations. Therefore, we

,10 estimated potential activity seasons for each population using computer models that calculate microclimates and animal Tb based on heat transfer principles (Porter

0 , , , et al. 1973, Porter and Tracy 1983, Porter 1989, see 1000 1500 2000 2500 3000 Adolph and Porter 1993 for further details). In brief,

ACTIVITY SEASON (HOURS) we used climate data for each site for each year of the

ample of model predictions of age (A) and size (B) field study (United States Weather Bureau) together y versus length of activity season (total potential with geographic data (latitude and altitude; obtained activity per year). For this example, we used the from United States Geological Survey maps in conjunc- parameter values: r = 0.025, M,, .....= 20 g, Mwith,, author=

-,,,,,, ,= 8.0 g, c = 0.0833, and d- 6 h. We assumed tion wth authors descriptions of the study sites) as distribution of hatching dates, beginning and ending input to the model. The model calculated solar radia- * the beginning and end of the maturation window. tion using program SOLRAD (McCullough and Porter represents the average value obtained for all hatch-

or a given activity season. 1971, see Adolph and Porter 1993) assuming clear sky 'or a given activity season. conditions. The microclimate simulations were coupled to a second computer model that calculated the equi-

ecause these lizards are maturing at a smaller librium Tb, attainable by S. undulatus, and determined Is, average size at maturity decreases with the times of day that a 10-g individual could reach its length of activity season over this intermedi- preferred body temperature range of 32?-37?C (Bogert of season lengths. Finally, for seasons suffi- 1949, Avery 1982, Crowley 1985, Grant and Porter

ciently long that all lizards can mature in under one year, average size at maturity should again increase as season length increases.

Thus, a key prediction of the model is that age and size at maturity can vary nonlinearly, and sometimes non-monotonically, with the length of the activity season. The exact forms of these relationships depend on the values of growth parameters, duration of maturation window, and distribution of hatching dates. How- ever, the general form of these relationships is fairly robust for a variety of parameter values that are realis- tic for small-to-medium-sized lizards. Average age at maturity is predicted to show a series of plateaus (Fig. 4A), whereas average size at maturity is predicted to show a series of peaks (Fig. 4B), as a function of length of activity season.

Testing the model: analyzing field data from Sceloporus undulatus

Stearns (1980) suggested that hypotheses about life history variation are ideally tested among populations

1 1000 KM \I f

Fig. 5. Locations of life history field studies of the eastern fence lizard Sceloporus undulatus in the United States. Abbre- viations of states (and authors of studies) are: AZ (Arizona; Tinkle and Dunham 1986); CO (Colorado; Tinkle and Ballinger 1972); GA (Georgia; Crenshaw 1955); KS (Kansas; Ferguson et al. 1980); NM1 and NM2 (New Mexico; Vinegar 1975); NE (Nebraska; Ballinger et al. 1981); OH (Ohio; Tinkle and Ballinger 1972); SC (South Carolina; Tinkle and Ballinger 1972); TX (Texas; Tinkle and Ballinger 1972); UT (Utah; Tinkle 1972b).

OIKOS 77:2 (1996)

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creases, b size. Thu increasing ate range

272

1992) in acceptable microhabitats. These daily potential activity periods were summed over the year to give an estimate of the total number of hours of potential activity. Estimated annual activity seasons ranged from 1707 h/yr for an Ohio population to 3012 h/yr for a population in Texas, nearly a two-fold range. In general, populations at low latitudes had longer estimated activity seasons (compare Figs 5 and 6).

Life history traits of most S. undulatus populations varied consistently with estimated length of activity season. Female age at maturity varied approximately as a step function of season length (Fig. 6A): lizards in environments with estimated activity seasons <2300 h/yr matured in their second full activity season, at ~20 months of age; lizards with activity seasons >2400 h/yr matured at 12 months. A New Mexico montane population, with an estimated season length of 2330 h/yr, had a mean age of maturity of 18 months, because some individuals matured in their first reproductive season and others in their second (Vinegar 1975). However, two populations from prairie habitats in Kansas and Nebraska were exceptions to this pattern: females matured during their first reproductive season, despite having short estimated activity seasons (% 2000 h/year; Fig. 6A). Female size at maturity de- creased with increasing season length (Fig. 6B), except for the two prairie populations, in which females matured at a smaller than expected size because they matured a year early (Fig. 6B). The number of clutches laid per year increased with activity season length (Fig. 6C; r = 0.678); this supports the idea that the length of the maturation window should covary with the length of the activity season.

Discussion

The effect of season length on lizard life histories is well known to field researchers, but is rarely included in analyses of life history variation. Our model can be used to make quantitative predictions about how life- history phenotypes should vary as a proximate consequence of different thermal environments, given simple rules about reproductive phenology and the thermal dependence of growth. It shows that seasonal reproduction can lead to discontinuous variation in age and size at maturity along latitudinal and altitudinal temperature gradients in nature. In an earlier paper, we modeled the influence of activity season length on annual survival rate and reproductive output (Adolph and Porter 1993). Predictions of these models are summarized in Table 1. The combinations of life history traits predicted by "null" physiological models are the same as those predicted by evolutionary models: populations experiencing high adult mortality should have early maturity and/or high fecundity, relative to populations

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ANNUAL ACTIVITY SEASON (HOURS)

Fig. 6. Female size at maturity (snout-vent length; A), age at maturity (B), and average number of clutches laid per year (C) versus length of activity season for populations of the iguanid lizard Sceloporus undulatus in the United States. Activity seasons were calculated using microclimate simulations. Field data are from published studies summarized in Dunham et al. (1988); letters indicate location of study site (see Fig. 5). Prairie populations from Kansas (KS) and Nebraska (NE ) deviate from the general patterns. Omitting the KS and NE populations, size at maturity is negatively correlated with annual activity hours (r= -0.83; P < 0.01).

experiencing low mortality (reviews in Roff 1992 and Stearns 1992). This finding is consistent with Shine and Charnov's (1992) analysis of published data on survival, growth and maturation in lizards and snakes, which showed that adult survival rate was positively correlated with age at maturity. Similarly, Ballinger and Congdon (1981) commented that "Lizards occurring in

OIKOS 77:2 (1996)

1 , ,.

*----__-_ --_

3

273

environments with long growing seasons typically produce multiple clutches, have high reproductive efforts, and have short life expectancies. Conversely, lizards occurring in environments with short growing seasons are longer-lived with low reproductive efforts". Ob- served patterns of variation in life history traits among wild lizard populations could reflect proximate environmental influences, adaptive genetic differentiation, or a combination of both.

Our model also highlights the functional relationships among sizes, growth rates, seasonality, and the duration of different components of reproduction (e.g., egg laying, hatching). Changing any one of these factors will usually affect the population mean size and/or age at maturity. This effect will be particularly strong when activity seasons are near the threshold length: a small change in growth rate, hatchling mass, or incubation time could have a large effect on age and size at maturity. This suggests that selection on age or size at maturity could act indirectly on these functionally con- nected traits. For example, selection for early maturity could result in the evolution of shorter incubation time, or higher growth rate. Thus, seasonality can result in "leveraged" effects of growth-related traits on major fitness components. Similarly, a population experiencing directional climate change could experience a dis- proportionate change in one or more life history traits, which could have both demographic and evolutionary consequences.

Life history variation in Sceloporus undulatus

A number of researchers have examined intraspecific variation in life history traits of S. undulatus (Tinkle and Ballinger 1972, Ferguson et al. 1980, Ballinger et al. 1981, Tinkle and Dunham 1986, Dunham et al. 1988, Gillis and Ballinger 1992, Niewiarowski 1994). Neither habitat type nor phylogenetic relatedness provides a satisfactory explanation for the observed pattern of geographic variation (Tinkle and Dunham 1986, Gillis and Ballinger 1992). Gillis and Ballinger (1992) suggested that climatic and biophysical considerations might improve our understanding of life history patterns in this species.

Table 1. Lizard life history patterns predicted as a proximate consequence of different thermal environments (this study and Adolph and Porter 1993).

Life history Long activity Short activity characteristic season season

Annual survival low high rate

Annual reproductive high low output

Age at maturity early delayed Size at maturity small large

Our analysis indicates that the thermal environment, through its effects on activity time, growth energetics, and reproductive seasonality, may explain some of the variation in age at maturity in S. undulatus. In addition, variation in size at maturity may be strongly related to length of activity season; however, our model predicted a different form for this relationship. Previously, we found that annual adult survival rate was negatively correlated with length of activity season (Adolph and Porter 1993). We also showed that size-corrected annual egg mass production (a measure of reproductive investment) was positively correlated with length of activity season, and that body size and length of activity season together explained 87% of the variation among populations in annual egg mass.

Together, these results are consistent with the hypothesis that the proximate effects of climate govern much of the life history variation among populations of S. undulatus. Populations with longer estimated activity seasons matured earlier and at a smaller size, produced more clutches and more eggs per year, and had lower annual survival rates, compared to populations living in cool environments. Most of these trends can be inter- preted as simple proximate consequences of temperature, via its influence on daily and seasonal activity time, growth energetics and reproductive phenology. However, female size at maturity varied with annual activity time in a manner different from that predicted by our physiological model, suggesting that the as- sumptions of our model are not met by these populations. For example, populations could differ in resource availability, which can also affect growth rates in nature (Grant and Dunham 1990).

Alternatively, these populations could differ genetically in their growth or size parameters, such as r,n,

initial (hatchling) size or maximum size. Indeed, both egg size and adult size vary substantially among these populations (Dunham et al. 1988). Aspects of size are also strongly correlated with one another; for example, female SVL at maturity is positively correlated with both mean egg mass (r = 0.72) and mean female SVL (r = 0.94) (omitting the two outlier populations in Kan- sas and Nebraska). Hence, like female SVL at maturity, mean egg mass and mean female SVL are also negatively correlated with length of activity season. Hatch- ling size is also likely to covary with egg and adult size; hatchling mass is positively correlated with egg mass among individuals of S. undulatus (Ferguson and Brockman 1980) and of the related species Sceloporus occidentalis and S. graciosus (Sinervo and Adolph 1989, Sinervo and Huey 1990, S. C. Adolph and B. Sinervo unpubl.).

Several common-garden studies have revealed differences in growth rates among populations of S. undulatus that may represent genetic differences. Ferguson and Talent (1993) raised lizards from eggs to maturity in the laboratory, and found that Utah and Oklahoma

OIKOS 77:2 (1996) 274

populations differed in growth rate, age and size at maturity, clutch size, and egg size. Lizards from both populations matured in just 4-5 months in the laboratory, compared to 1-2 yr in the field. This clearly demonstrates that age at maturity is phenotypically plastic in this species (see also Porter and Tracy 1983). Ferguson and Talent (1993) also found that size at maturity differed between the laboratory and the field: in the lab, Utah lizards were smaller at maturity, but Oklahoma lizards were larger at maturity, compared to lizards in their respective field populations. Ferguson and Brockman (1980) found interpopulational differences in growth rates of laboratory-reared juveniles of three populations of S. undulatus. Niewiarowski and Roosenburg (1993) performed reciprocal field trans- plants of juvenile S. undulatus and found differences in growth response between lizards from Nebraska and New Jersey populations: lizards from both populations grew at similar rates when grown in New Jersey, but lizards from Nebraska grew faster in Nebraska. These results may reflect genetic differences in plasticity of growth rate in response to environments differing in thermal opportunity (see also Sinervo and Adolph 1994). Growth rates of juvenile S. occidentalis in the laboratory also indicate possible genetic variation within and between populations (Sinervo and Adolph 1989, 1994, Sinervo 1990). Thus, a number of studies on S. undulatus and other Sceloporus species indicate that genetically based differences in egg size, adult size, and growth rate may be common.

Together, size and temperature appear to explain much of the phenotypic life history variation among populations of S. undulatus. Our analysis suggests that proximate effects of the thermal environment could be responsible for some of the variation in size at maturity among populations. However, variation in egg size, hatchling size, and maximum body size are not readily explained by proximate effects of temperature. Because these measures of size are highly correlated among populations of S. undulatus, (see above) they are probably not free to evolve independently, but instead would evolve in a correlated manner. The tendency for eggs, hatchlings and adults to be smaller where activity seasons are longer could reflect adaptation to different climates. For example, body size influences the ability of ectotherms to thermoregulate: all else being equal, large lizards can maintain a higher equilibrium Th than small lizards, because of their larger boundary layers (Porter and Gates 1969). However, this difference would be small (<2?C) over the size range encom- passed by populations of S. undulatus (Stevenson 1985), and therefore would probably have little effect on activity times. Another possibility is that longer seasons somehow favor smaller lizards via the life history corre- lates of body size. These possibilities could be addressed through field measurements of natural selection (e.g., Ferguson and Fox 1984, Sinervo et al. 1993), or by

developing an optimization model that includes the proximate effects of temperature (e.g., Beuchat and Ellner 1987) along with size- and season-specific mortality schedules. Still another possibility is the interac- tion between thermal opportunity and food availability (Grant and Dunham 1990, Dunham 1993). For example, intermittent or chronic food shortages, which might be more common for populations with long activity seasons, would reduce growth potential, and possibly cause selection for slower growth rates and/or smaller body size.

Why are the prairie populations exceptions to the general patterns? Life history theory predicts that early maturation is likely to evolve when adult mortality is high (Roff 1992, Stearns 1992). However, the Kansas and Nebraska populations have among the highest adult annual survival rates of all S. undulatus populations (Jones and Ballinger 1987, Dunham et al. 1988). Thus, neither an evolved response to age-specific mortality patterns nor the proximate effects of temperature offer a simple explanation for early maturation of females in prairie populations. This suggests that selection on size per se, rather than reproductive timing, could be involved.

Ecological and evolutionary implications

Simple physiologically based models predict that the proximate effects of temperature on lizard life history traits can be automatically compensatory: thermal environments resulting in reduced survival rates also permit higher annual reproductive output and earlier maturity (Table 1; Adolph and Porter 1993). This phenomenon has implications for both population ecology and the evolution of life history traits. On an ecological time scale, lizard population dynamics could be partially buffered against temporal (or geographic) variation in climate, as population mean life history phenotypes respond to the proximate effects of temperature (but see Dunham 1993). The fact that many species such as Sceloporus undulatus can exist in a variety of thermal environments indicates one possible advantage of having a phenotypically plastic life history. Indeed, widespread species that are not genetically adapted to local thermal conditions may be better able to cope with temporal climatic changes; lack of local adaptation may indicate that phenotypic flexibility is sufficient.

Similarly, from an evolutionary perspective, one might expect natural selection to have favored patterns of phenotypic response of the appropriate shape to maximize fitness across a range of environmental conditions (Stearns and Koella 1986, Sinervo and Adolph 1994). The physiological mechanism outlined in our models would facilitate the evolutionary adjustment of norms of reaction of life history traits, because the proximate effects of temperature, acting via activity

OIKOS 77:2 (1996) 275

time, are already in the appropriate direction. Thus, adaptive evolution of the norms of reaction of lizard life history traits could involve fine-tuning of an already existing response, rather than wholesale adjustments.

Acknowledgements - We thank S. Beaupre, J. Jaeger, G. C. Mayer, R. T. M'Closkey, D. K. Padilla, P. S. Reynolds, R. Shine, B. Sinervo, and B. Wilson for helpful discussion or comments on the manuscript, and B. Feeny for help with the United States map. This research was supported by the Office of Health and Environmental Research, US Dept of Energy, through contract DE-FG02-88ER60633 to WPP, and a Guyer Fellowship from the Dept of Zoology, UW, to SCA. Manuscript preparation was supported by a faculty research grant from Harvey Mudd College to SCA.

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Appendix A. Derivation of growth expression when daily growth rate varies non-linearly with potential activity time.

Substituting expression (10) into eq. (4) yields an expression for growth rate as a function of time of year:

dM = M )M -s-- =r,,U.AMl - 1 M1

x L2cd l- 2)-4kd(2l-(j )) 2)) (11)

Integrating eq. (11) over the growth period yields the following expression for body size as a function of time of year:

f(j) 1 1 -- M(j) = () - + M

fYo)_Mo M,nc.x- Mnax -. (12)

where Mo is body mass at the beginning of the time period and

f(/) = exp r,,, -- j/y2 _j2 +y2 sin-l Y -

- j3 -

+4kd2 J3- 'K - 3y _

This model is a more general case of the model described in the text, which is equivalent to the case k = 0.

Appendix B. Allometry of hatchling size, minimum reproductive size, and time to maturity in lizards.

(13)

Several empirical studies (Sinervo and Adolph 1989, 1994) have shown that daily growth rates may show diminishing returns as a function of daily activity time. We can model this effect as follows:

r= r, (ch - kh2), (9)

choosing a value of k such that r increases monotonically with h over the range of activity times experienced in nature. Values for k between 0 and 0.04c yield a range of responses similar to those observed in the laboratory. The advantage of using a quadratic form to describe diminishing returns, versus an exponential or some other expression, is that (9) leads to analytically tractable solutions.

Substituting (9) into (1) gives the following expression for the dependence of daily growth rate on activity time:

d-=r,, ,x(ch-kh2)M(l-M ) (10) dt M^J

Andrews (1982) provides tables of size data for a number of lizard species, including hatchling size, size at reproductive maturity (females), and maximum body size. We converted these data (snout-vent lengths in mm) to mass (g) using the interspecific allometric relationship SVL = 29.98M0333 (Porter and Tracy 1983), and used least-squares linear regression of log-trans- formed data to derive the following allometric relationships for female lizards:

Mlltlchil= 0.0866M?, l.' (14)

and

M, .t,,,ty =0.623M? ,843 ......l'tt Illa . I (15)

These equations can be used to estimate hatchling and minimum reproductive sizes when only maximum size is available. Shine and Charnov (1992) present additional allometric analysis of size at maturity and maximum size in lizards and snakes.

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Growth, Seasonality, and Lizard Life Histories: Age and Size at Maturity

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