J. Exp. Mar. Biol. Ecoi., 1987, Vol. 108, pp. 199-216

Elsevier

199

JEM 00878

Life history traits and resource allocation in the purple sea urchin Strongylocentrotus purpuratus (Stimpson)

Michael P. Russell Department of Biology, San Diego State University, San Diego, California. U.S.A.

(Received 2 September 1986; revision received 16 December 1986; accepted 16 February 1987)

Abstract: Variation in recruitment and longevity of the purple sea urchin Srrongylocentrotus purpuratus (Stimpson) along its latitudinal distribution suggests clinal differences in the life history traits of this species. Two complimentary approaches were employed to assess degree and nature of the intraspecific variation

in life history traits. Growth, mortality, and recruitment data were gathered in the field and in the laboratory sea urchins were held under the same conditions to determine the extent of plasticity in resource allocation. Both laboratory and field measurements indicate the observed demographic patterns are best attributed

to phenotypic responses to varying environmental conditions rather than genetically determined intraspeci- fic differences in life history traits.

Key words: Strongylocentrotus purpuratus; Life history; Resource allocation; Demography

INTRODUCTION

An organism’s life history is a function of its pattern of resource allocation to growth, maintenance, and reproduction over its entire life (Gadgil & Bossert, 1970). One fruitful approach to life history studies in the comparative examination of resource allocation patterns, in which life history is summarized by age-specific rates of survival and reproduction. These life history parameters can be considered a population average or an expectation for an individual (Kirkwood, 1981). Examination of population level plasticity of resource allocation is an essential step in studying life history evolution at the species level.

Ebert (1983) has gathered evidence suggesting that the life history traits of the purple sea urchin Strongylocentrotus purpurutus vary with latitude. He proposed that this variation may be due to differential selection operating in response to a cline of recruit- ment success over the geographic range. The genetic aspects of clinal variation have been addressed by several workers (Endler, 1977; Berven, 1982); however, few studies have dealt with the evolutionary implications of an intraspecific but genetically based cline of life history parameters.

Correspondence address: M. P. Russell, Department of Paleontology, University of California, Berkeley, CA 94720. U.S.A.

0022-0981/87/$03.50 0 1987 Elsevier Science Publishers B.V. (Biomedical Division)

200 M. P. RUSSELL

During a 20-yr study, Ebert (1983) documented that S. purpuratus recruited more predictably and had a shorter life span at False Point, San Diego, than at Sunset Bay, Oregon. Other studies, reporting S. purpuratus demographics, support the suggestion of clinal variation in recruitment and longevity (Fig. 1; Pearse et al., 1970; North, 1974; Schroeter, 1977; Tegner & Dayton, 1981; Duggins, 1983).

The contrasting demographic traits in S. purpuratus at either end of its range suggest related differences with respect to resource allocation (Ebert, 1983). Since the establish- ment of individuals at high latitudes is unpredictable, the sea urchins occurring in these areas must survive the periods of poor recruitment to maintain the present-day northern range. This may favor increased resource allocation to maintenance, that is morphologi- cal, physiological, or behavioral features that increase the probability of survival. In contrast, predictable recruitment in the lower latitudes could allow for increased repro- ductive allocation at the expense of maintenance. Ebert (1983) has further speculated that selective pressures in the north for increased maintenance allocation, and in the south for increased reproduction, represent the extremes in a selection gradient. If the observed demographic patterns represent adaptive responses, then an intraspecific measure of an evolutionary response to varying recruitment regimes is available. Alter- natively, the adult life history of this species may be unrelated to recruitment patterns and simply result from phenotypic responses to varying environmental conditions.

Here I report on variation in growth, mortality schedules and degree of plasticity in resource allocation of S.purpuratus (Stimpson) from three populations along its latitudinal distribution. Specifically, I want to assess whether the demographic patterns of this species are best explained as genetically determined life history variation or phenotypic responses to environmental conditions.

MATERIALS AND METHODS

Two complimentary approaches were employed in this study. First, estimates of growth, mortality, and recruitment were gathered at three field sites along the latitudinal distribution of S.purpuratus. Secondly, to assess the degree of resource allocation plasticity, sea urchins from the study sites were held under the same conditions in the laboratory and subsamples dissected every 4-5 wk.

The three field sites sampled were: (1) Pachena Point, Vancouver Island, British Columbia, Canada (48”43’N); (2) Children’s Pool, San Diego County, California, U.S.A. (32” 51’N); and (3) Punta Baja, Baja California, Mexico (29”56’N) (Fig. 1). These sites span more than half the latitudinal range of S. pulpuratus and are easily accessible. Study sites were visited twice: between 15 September and 15 October of 1981 and 1 yr later in 1982. The first sampling period entailed tagging (see Growth measurements) and measuring sea urchins (test diameters), and collecting samples for the laboratory study. During the second sampling period tagged sea urchins were collected, measured, and subsamples were dissected.

S. PURPURATUS RESOURCE ALLOCATION AND LIFE HISTORY 201

In the field sea urchins at all three sites were sampled from tidepools on intertidal sandstone benches. Because sea urchins occur in tidepools in high densities and emigration out of the tidepools is unlikely (Paine & Vadas, 1969), tidepools are suitable for mark and recapture studies of sea urchins.

Duggins. 1980 A

Vancouver Island

Ebert,

Schroeter,

Ebert, 1983: Tegner 8 Dayton, 198 1

North, 1974: Pearse et al

San

Punta Baja

0 0

%

I I I

160 w 140 w 120 w

Longitude

Fig. 1. The stippled area depicts the latitudinal distribution of S. purpuratus. Locations where researches reported on the longevity or recruitment of this sea urchin are indicated with the reference. The three sites

examined in this study are also marked.

202 M.P. RUSSELL

During the first sampling period, sea urchins were collected from sites adjacent to the study areas and transported to the San Diego State University marine laboratory on Mission Bay. An effort was made to collect a representative sample of size classes from each site. Sea urchins from each site were held in cylindrical fiberglass tanks (1.25 m diameter and 0.25 m deep) which were maintained on closed-system aquaria sharing a common water source. The animals were fed Mucrocystispyrifera (Linnaeus) ad libitum. The sea urchins were acclimated to the aquaria for 10 wk and then all individuals were tagged with tetracycline. A monthly dissection schedule began in January 1982, i.e. 10 sea urchins were dissected from each sample every 4-5 wk. In January 1983, after 15 months in the laboratory, the remaining animals from each sample were prepared for growth analysis.

GROWTH MEASUREMENTS

Field and laboratory growth measurements were made using a tetracycline tagging method (Kobayashi & Taki, 1969; Ebert, 1975, 1980b, 1982; Pearse & Pearse, 1975; Fansler, 1983). One gram of tetracycline-HCl was dissolved in 100 ml of sea water and w 0.2 ml injected into each sea urchin through the peristomal membrane. In growing sea urchins, tetracycline is deposited in the skeletal structure. Tetracycline fluoresces under ultraviolet light and this label indicated the size of the skeletal element at the time of tagging.

To assess growth after tagging, soft tissue was removed with 5 % sodium hypochlorite. The skeletal elements were then thoroughly rinsed in tap water and air-dried. Test diameters were measured and the half pyramid of Aristotle’s lantern (the jaw) examined under ultraviolet light for growth.

Growth of the sea urchins was estimated by calculating the parameters of the Richards function (Richards, 1959) for both field and laboratory samples. The Richards function, also called the generalized Von Bertalanfy equation (Pauly & David, 1981), is a flexible growth equation:

s, = S,(l - bKkc)-”

where S, is size at time t; S, is asymptotic size; k is a growth constant; n is a shape parameter and b is a scaling parameter equal to:

b = (S&I?-- _ ~,l’“-‘).(~,l’“-‘)-l

where S, is size at time 0, or w 0.5 mm for animals in this study. When S, is much less than S,, then b will be very close to 1.00 (Ebert, 1980a).

Growth curves were generated using the set of Richards function parameters that minimized the sum of squares of error (SSE) for a Walford plot (Walford, 1946) of S, + T (final size of jaw) vs. S, (initial size of jaw). These parameters define the growth curve that best tit a particular mark and recapture data set.

Comparison of the growth curves could be complicated because three parameters describe a particular curve (i.e., S,, K and n). Comparing single parameters among

S. PVRPVRATVS RESOURCE ALLOCATION AND LIFE HISTORY 203

samples yields little information because the other parameters may vary a great deal. The likelihood ratio [R(e)], as developed by Pienaar & Thompson (1973) and Ebert (1980a), based on the work of Sprott & Kalbfleisch (1965), was used in comparing growth. The likelihood function [L(e)] is defined as:

~(0) = ~N.2-l exp-N.2-’ SSE-N.2 -’

where N is the number of data points in a Walford plot and sSE is the sum of squares of error for those points around a Richards function curve.

then L((j).c-’ = ss~-~.~-‘.

The least SSE produces the maximum value for the likelihood function [L(g). c ’ 1,

which by definition represents the growth parameters that best fit a particular set of points in a Walford plot. Sets of Richards function parameters were calculated for each tidepool and laboratory sample by minimizing the SSE [or maximizing the L(0)] for the Walford plots (Ebert, 1980a).

Comparisons of growth were made by fitting all the sets of Richards function parameters to the sets of mark and recapture points on the Walford plots and calculating a new SSE and L(B). A likelihood ratio can thus be formed:

R(8) = L(6).L(8)- l

which compares the newly calculated L(B) to the L(d) and varies between 0 and 1. The closer the R(8) is to unity the “closer the fit” between the mark and recapture growth data and the Richards function growth parameters. For example, it was found that S, = 5.11 cm, K = 3.65 x 10p5, and 12 = - 0.185 are the best estimates for the parameters for VI1 (Table I). A new SSE was calculated using these parameters and the VI2 mark and recapture data to compare how well the VI1 parameters describe growth in the VI2 sample. This new SE calculated from the VI1 parameters with the VI2 data was used to generate a L(6) value which formed the numerator in the R(8). This series of calculations was performed for all pairwise comparisons of growth parameters and mark and recapture data sets.

MORTALITY

The instantaneous mortality coefficient (Z) is defined in the survivorship equation:

N f = No exp( - =,)

where N,, is population size at time 0 and N, is population size t-time units later. Assuming periodic recruitment, Z can be estimated utilizing the growth parameters of the Richards function and size distribution data (Ebert, 198 1). Z was calculated for each

204 M. P. RUSSELL

tidepool; the annual mortality rate (1 - expt - z]) and average life span following recruit- ment (1. Z- ‘) can also be calculated from these estimates (Ebert, 1981).

RESOURCE ALLOCATION

The relative amount of tissue making up a body component can be used as an index of resource allocation to that component (Ebert, 1982). Proximate functions (e.g., maintenance or reproduction) can be assigned to body components, and so shifts in resource allocation should be detectable by comparing component indices through time. This logic was used to estimate the degree of plasticity in resource allocation patterns of S. purpuratus.

An analysis of covariance (ANCOVA) was performed on each monthly laboratory dissection and the 1982 field dissections, to test for differences in gonad and body wall components (Laszlo, 1981). The analyses used the Ln dry weight of the body components as the dependent variables adjusted for the Ln total wet weight.

RESULTS

RECRUITMENT

Recruitment of sea urchins is usually estimated by the number of individuals in the first age class of a size frequency distribution (Ebert, 1968; Tegner & Dayton, 1981). Inspection of the size frequency distributions (Fig. 2) from this study reveal no obvious differences in recruitment among the three sites. In contrast to what was observed, higher recruitment was expected for the San Diego and Punta Baja sites while no or little recruitment was expected at Vancouver Island. Although the smallest urchins were

Vancouver island San Diego Punta Baja

,!FAyFx , /:;%, ,

i;lIfA ,__:, ,, ,%+:;.+,,, (

0 I 2 3 4 5 b 7 8 12345678 12345678

Test diameter (cm)

Fig. 2. Test diameters of the sea urchins found at the three field sites in 1981 and 1982. There does not appear to be any substantial differences in recruitment among the three sites during the course of this

study.

S. PURPURATUS RESOURCE ALLOCATION AND LIFE HISTORY 205

found at the Vancouver Island site during both sampling periods, the only inference drawn is that no major recruitment episodes occurred at any of the sites during this study. It is difficult to draw resolute conclusions about recruitment from the present study because I cannot address the problem of variability between years. Several years of repeated sampling at several sites are necessary to establish recruitment patterns. The 2 yr of data presented here are insufficient to adequately assess the proposed latitudinal recruitment pattern.

Vancouver Island 9

N

m 0-

w 0-

VI3

N=68

v d 1 / a

VI2

Nell

St (cm)

Fig. 3a. Walford plots of jaw growth for the Vancouver Island (VI) field site. Each plot is for one tidepool (i.e., VI1 = Vancouver Island tidepool no. 1). The abscissa is initial size (S,) and the ordinate is the size

1 yr later (S,, =). The straight diagonal line represents no growth, i.e. S,, T = S,.

206 M. P. RUSSELL

GROWTH

Growth data (Figs. 3 and 4) are presented in the form of Walford plots and the growth curves on these plots were generated using Richards function parameters (Table I). For any particular parameter, there appears to be a trend between the field and laboratory in the same direction among all three samples. In the laboratory, the n and S, parameters tended to decrease while K increased.

4J San Dlego

L

- SD1 SD2

_ Nz55 N=118 hl L

PBl

N=88

Punta -I

Baja

P82

Nz178

L ‘I”‘I”‘I”‘I ” vIra ‘1”‘1”‘1

b 0

0 0.4 08 1.2 I.4 04 08 1.2 1.6

St (cm)

Fig. 3b. Walford plots of jaw growth for the San Diego (SD) and Punta Baja (PB) field sites. Each plot is for one tidepool (i.e., SD1 = San Diego tidepool no. 1). The abscissa is initial size (S,) and the ordinate

is the size 1 yr later (S,, =). The straight diagonal line represents no growth, i.e., S,, T = S,.

S. PURPURATUS RESOURCE ALLOCATION AND LIFE HISTORY 207

Growth parameters from all the tidepools and laboratory samples were compared using R(8) (Table II). The columns of Table IT represent the comparisons between the growth data for a particular sample and the sets of growth parameters from all other samples. The values in the diagonal of the table are equal to 1 (i.e., L(8). L(d)- ’ = 1). Since the number of data points in the samples are not equal, the table should be interpreted by columns, with the higher R(0) representing the better fitting growth parameters for a particular data set. Two lines of evidence can be derived from Table II that address the hypothesis that there is a latitudinal trend in the resource allocation patterns of S. purpuratus. First, the in situ growth patterns of sea urchins found in different tidepools within any site vary considerably. For example, the lowest R(0) (i.e., “the worst fit”) for PBl was produced by the growth parameters of PB2. The highest

-0

-7

N.17

,

::__

. .

NZ21 /

1 :

..II” / /

-m- 00 04 0.8 12 I.5 0.4 0.8 12 14 0.4 0.8 12 lb

St (cm)

San Diego Punta Baja

Nd33

!

I I ’ I I

Fig. 4. Walford plots for the jaw growth for the three laboratory samples. The abscissa is initial size (S,) and the ordinate is the size 1 yr later (S f+ =). The straight diagonal line represents no growth, i.e.

s I+ 7. = &

TABLE I

Estimates of Richards function growth parameters of the half pyramid of Aristotle’s lantern for laboratory and field samples. The numbers indicate tidepool samples and the “L” indicates laboratory samples.

Site Sample S, (cm) K ?I SSE

Vancouver Island VI1 5.11 3.65 x 1O-5 - 0.185 3.81 x IO-’

VI2 1.56 5.29 x lo-’ - 0.244 1.75 x 1om3 VI3 1.92 1.16 x lo-* - 0.211 5.47 x lo-* VI4 4.02 1.71 x 1o-4 -0.185 6.77 x 1O-3 VIL 1.34 1.14 x IO-’ - 0.260 1.13 x 10-z

San Diego SD1 4.30 8.86 x 1o-5 - 0.198 4.81 x lo-* SD2 4.39 5.44 x lo-5 - 0.182 4.95 x 10-Z

SDL 1.38 1.31 x 10-l - 0.390 1.37 x lo- Z

Punta Baja PBl 5.81 1.46 x lo-“ - 0.234 1.41 x 10-I PB2 1.51 2.74 x 10m2 - 0.242 2.25 x 10 ’ PBL 1.73 4.57 x 1o-2 - 0.291 2.40 x lo-’

TA

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(R(0))

for

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sam

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VI1

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VI3

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SD

1 S

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PB

l P

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VIL

S

DL

P

BL

z

VI1

1 .

OO

E 00

2.

20E

-02

2.32

E-0

1 5.

15E

-04

1.70

E-1

0 2.

27E

-06

6.57

E-0

2 5.

9lE

-47

9.00

E-0

2 %

1.

98E

-02

7.25

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5 V

I2

2.27

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5 l.

OO

E 0

0 6.

80B

02

3.47

8-03

1.

93E

-18

3.88

E-3

0 6.

57E

-02

2.52

E-6

2 4.

24E

-01

5.92

E-0

1 1.

13E

-01

z V

I3

2.57

E-0

4 4.

45E

-02

1 .O

OE

00

1.50

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4 9.

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-12

2.59

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3 2.

16E

-01

9.26

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6 l.

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-01

1.33

E-0

1 l.

O7E

-03

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VI4

2.

79E

-03

1.37

E-0

1 1.

34E

-02

l.O

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4.25

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8 2.

52E

-22

3.67

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2 1.

93E

-68

3.24

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1 4&

E-0

1 6.

52E

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D1

6.35

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7 1.

69E

-05

4.44

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2 2.

96E

-09

l.O

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00

8.07

E-1

1 1.

66E

-16

5.5

lE-0

4 1.

82E

-06

1.20

E-0

5 1.

42E

-32

r S

D2

5.83

E-1

4 4.

30E

-04

4.25

E-0

6 6.

98E

-07

3.47

E-0

3 l.

OO

E 0

0 l.

O6E

-08

5.97

E-2

4 3.

04E

-04

1.76

E-0

4 1.

99E

-18

PB

l 4.

04E

-09

4.37

E-0

2 2.

32E

-02

6.99

E-0

5 1.

27E

-14

l.l6

E-2

5 L

OO

E 00

1.

15E

-49

9.00

E-0

2 4.

77E

-01

8.67

E-0

2 P

B2

1.4l

E-3

1 4.

5 lE

-06

2.77

E-1

4 3.

53E

-10

8.12

E-0

2 2.

59E

-13

l.O

8E-1

8 1 .

OO

E 00

4.

30E

-07

1.48

E-0

5 4.

93E

-36

VIL

2.

76E

-01

3.87

E-0

2 7.

34E

-01

1.64

E-0

3 1.

92E

-17

7.72

E-2

4 2.

16E

-01

3.17

E-6

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E 0

0 7.

39E

-01

4.39

E-0

1 S

DL

7.

55E

-17

1.48

E-0

3 7.

47E

-04

1.46

E-0

7 l.

l8E

-13

1.96

E-2

6 3.

52E

-05

~

___

9.79

E-3

8 6.

33E

-03

l.O

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00

2.17

E-0

6 P

BL

2.

97E

-14

2.3l

E-0

2 1.

48E

-04

l.O

9E-0

5 7.

28E

-18

1.67

E-3

6 3.

84E

-03

4.59

E-5

4 3.

6lE

-02

l.lO

E-0

1 l.

OO

E 0

0

S. PURPUMTUS RESOURCE ALLOCATION AND LIFE HISTORY 209

R(8) for these data was produced by the VI3 and VIL parameters. This means that the growth parameters for every other sample (field or laboratory) produced a better lit for

the PB 1 data than did the PB2 parameters. Secondly, the VIL parameters provided the best tit [highest R(O)] for both the SDL and PBL growth data (Table II). This demonstrates that when sea urchins are held under the same conditions, resource allocation to growth converges on a similar pattern among all three samples.

The latitudinal hypothesis predicts that growth patterns between tidepools within an area would be more similar than growth patterns between tidepools from different areas. Also, if these differences were genetically determined, then the latitudinal trend should be conserved when animals are brought into the laboratory. Based on the variability of growth patterns in the field and the similarity of growth patterns in the laboratory, the latitudinal hypothesis is not supported with respect to resource allocation to growth.

MORTALITY

Before estimates of Z were calculated using the Richards function parameters it was first necessary to transform S, and n because growth estimates were made using jaw elements and the size distribution data were derived from test diameters. Using the allometric coefficients which were derived from geometric mean (GM) functional regressions (Ricker, 1975) of log, transformed test and jaw lengths (Fig. 4) these conversions are (Ebert, 1982):

T, = aJi

The mortality estimates for the tidepools appear to be consistent between the two sampling dates (Table III). Based on these estimates, mortality for S. purpuratus is higher in the southern end of its range than in the north. Although these observations

TABLE III

Estimates of mortality coeffkients (Z) for field samples.

Z

Sample 1981 1982

VI1 0.116 0.131

VI2 0.093 0.115

VI3 0.087 0.098

VI4 0.150 0.159

SD1 0.243 0.263

SD2 0.146 0.165

PBl 0.323 0.336

PB2 0.280 0.328

210 M.P. RUSSELL

are consistent with the proposed latitudinal trend, the differential mortality may or may not be due to intraspecific life history variation resulting from resource allocation differences.

I cannot rule out the possibilities of either differential predation rates or increased water temperature in the southern range accounting for the mortality differences. Ocean temperatures in the southern latitudes occasionally rise above the 23 “C lethal limit of

Vancouver bland

“7 VI1 1 VI2 s

* _

*I.. . 1 OV .

Jaw length (cm)

Fig. 5. The allometric equations and regression lines relating test (T) to jaw (J) size.

S. PURPURATUS RESOURCE ALLOCATION AND LIFE HISTORY 211

S. purpurutus (Farmanfarmaian & Giese, 1963). Presumably, exposure to elevated water temperatures in the south stress these sea urchins physiologically. The warmer waters in the southern latitudes may result in higher mortality whether or not differences in resource allocation exist.

RESOURCE ALLOCATION

A variety of body component indices have been developed to compare sea urchins (Moore, 1934, 1937; Fuji, 1967; Giese, 1967; Ebert, 1968; Gonor, 1972, 1973a; Magniez, 1983). These indices may be problematical when comparing urchins of different sizes. The gonadal index for S. purpurufus is a second order function (Gonor, 1972) i.e., it increases in urchins up to 4.0-4.5 cm in test diameter and drops off with urchins > 5.0 cm. The relationship between test diameter and height was statistically indistinguishable for urchins from tidepools within a particular site; however, the slopes of these regressions among the three areas were significantly different (Table IV). These

TARLE IV

ANCOVA of test diameter vs. height for field samples. The covariate is diameter, the dependent variable is height, and all measurements are in centimeters.

Covariate Regression coefficient diameter 0.573 O.Z6

Group N Group mean

Vancouver Island 398 2.63 San Diego 350 2.04

Punta Baja 491 2.08

Source of variation d.f. SS

Equality of adjusted means 2 2.67 Zero slope 1 262.44

Error 1241 40.79

Equality of slopes 2 0.99 Error 1239 39.80

Slope within each group Vancouver Island San Diego Punta Baja

0.68 0.58 0.53

1 value 89.359

Adjusted group mean

2.29 2.27 2.19

MS F 1.34 40.68

262.44 7985.04 0.03

0.49 15.40 0.03

SE

0.010

0.010 0.010

P 0.0 0.0

0.0

differences in height-diameter relationships could result in misleading conclusions if test diameters were used to standardize comparisons, i.e., for a given test diameter the volumes of the tests vary among sites and thus the mass of the body components also varies. Therefore, comparison of body components were made by adjusting for differ- ences in total wet weight. The adjusted means for the gonad and body wall components, calculated from the ANCOVA, were plotted against time (Figs. 6 and 7).

Dramatic changes took place when the sea urchins were placed under laboratory conditions (Figs. 6 and 7). Both body wall and gonadal components increased signifi- cantly. These increases were probably brought about by the abundant food supply.

M. P. RUSSELL

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOY DEC 1982

Fig. 6. Means of Ln gonad dry weight adjusted for total wet weight + 1 SD for field and laboratory samples. Laboratory means based on 10 animals. An F indicates field samples and the sample sizes for these means

are: Vancouver Island = 40, San Diego = 20, and Punta Baja = 30.

6 F

A Vancouver Island

D San Diego

x Punta Baja

JAN FE8 MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 1882

Fig. 7. Means of Ln body wall dry weight adjusted for total wet weight + 1 SD for field and laboratory samples. Laboratory means based on 10 animals. AnF indicates field samples and the sample sizes for these

means are: Vancouver Island = 40, San Diego = 20, and Punta Baja = 30.

S. PURpUI&4 TUS RESOURCE ALLOCATION AND LIFE HISTORY 213

A rise in the gonadal index between July and August is followed by a decline in September and October with another rise in December (Fig. 6). Peaks followed by declines have been interpreted as spawning episodes in field populations (Giese et al.,

1958; Fuji, 1967; Pearse, 1981; Magniez, 1983), but their significance under laboratory conditions is less certain.

The reproductive cycle for S. pwpuratus peaks in the field during the winter, drops off in the spring and begins to rise again in the fall (Boolootian & Giese, 1959; Gonor, 1973a, b). This is in contrast to the slight summer peak that took place in the laboratory. The factors responsible for synchronizing the reproductive cycle of S. purpuratus have been the subject of much interest (Leahy et al., 1981; see Pearse, 1981, for review). Conclusions made about the cause(s) for the shift in the laboratory cycle would be speculative at best; however, all laboratory samples followed the same cycle from April through December including the anomalous peak in August. Whatever factor(s) influenced the reproductive cycle had the same effect on all three samples regardless of

origin. It appears that resource allocation to gonads was altered in the laboratory resulting in approximately the same pattern for all samples. These data do not support the hypothesis that there are genetically based resource allocation differences in S. purpuratus along its latitudinal distribution.

A similar case can be made for allocation to maintenance as evidenced by the changes that occurred in the body wall component (Fig. 7). All three laboratory samples reached an increased level over the field samples and followed the same pattern throughout the year, again indicating a high degree of resource allocation plasticity.

DISCUSSION

The dissection data provide the strongest evidence against the hypothesis of genetically based adaptive changes with latitude and suggest an alternative explanation for the field and laboratory observations. In light of the growth and resource allocation data, it is more plausible to consider the internal economy of these organisms as being plastic, with, potentially the same genotype (with respect to resource allocation) across the geographic range. Because of the variability observed within sites in the field and the congruencies in the laboratory, the demographic patterns reported in the literature can be better explained as phenotypic responses of similar genotypes to varying environ- mental conditions.

Although the evolutionary consequences of life history variation are dependent upon the presence of a genetic component (Law, 1979), most life history studies have focused either on intraspecific variation without regard to the effects of phenotypic plasticity, or, interspecific comparisons without regard to phylogeny (e.g., Frank, 1975; Licht, 1975; Dearn, 1977; Haukioja & Hakala, 1978; Leggett & Carscadden, 1978). Only recently have efforts focused on separating heritable from environmentally induced life history variation (Berven, 1982; Gill et al., 1983; Istock, 1983; Stearns, 1982; 1983a;

214 M. P. RUSSELL

Luckinbill, 1984). In addition, the importance of phylogenetic constraints on life history evolution are starting to be made explicit (Stearns, 1983b; Fenwick, 1984; Hutchings 8z Morris, 1985). An element that is lacking in many life history studies is the establish- ment of the relative importance of plasticity in life history trait variation. Although this is not simple, it is essential for a better understanding of life history evolution. In the present study I examined life history variation in S. purpurutus through a comparative examination of resource allocation and found a high degree of plasticity in these patterns.

The results of this study are not surprising considering the natural history of S. pulpu-

rufus. This species is a broadcast spawner and has a free swimming larval period between two and three months (Strathmann, 1978). However, even with such dispersal abilities, genetic differences could develop (Endler, 1977).

S. purpurutus occurs bathymetrically from the rocky intertidal to subtidal regions. The variety of habitat conditions encountered along this tidal gradient may be just as varied as those occurring along the latitudinal range. Assuming that a sea urchin resulting from a spawning episode in the intertidal zone could settle several hundred kilometers down the coast in a subtidal habitat, then the presence of a high degree of plasticity in resource allocation could be an adaptive feature. In fact, plasticity may be an adaptation in itself resulting from natural selection (Wright, 193 1).

ACKNOWLEDGEMENTS

The results of this study fulfilled part of the requirements for the MS degree in Biology at San Diego State University. A Grant-in-Aid of Research from Sigma Xi defrayed part of the financial costs and the Ecology program at San Diego State University provided material assistance. I greatly benefited from the comments of C. Barilotti, W. Cheek, M. Donoghue, T. Ebert, J. Estes, D. Farris, D.R. Lindberg, J. Malusa, G. VanBlaricom, and two anonymous reviewers. In addition I am grateful for the industrious laboratory and field assistance of M. Cohen, P. Jacks, S. Fansler, M. Krattli, M. Landen, L. King, D. Clark, C. Jorolman, and the staff of the Bamtield Marine Station.

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