ICES mar. Sei. Symp., 199: 19-25. 1995
Covariation in life-history parameters of soft-shell clams (Mya
arenarid) along a latitudinal gradient
Richard S. Appeldoorn
Appeldoorn, R. S. 1995. Covariation in life-history parameters of soft-shell clams
(Mya arenaria) along a latitudinal gradient. - ICES mar. Sei. Symp., 199: 19-25.
Twenty-five populations of Mya arenaria were sampled along the northeast coast of
North America, from Chesapeake Bay to Nova Scotia. Significant correlations were
found among life-history parameters, and these varied systematically with latitude.
Variation in latitude represented a marked environmental gradient in terms of tem­
perature and hydrographic and edaphic conditions. Southern populations generally
grew faster, and this was associated with greater variation in juvenile mortality, large
egg size, lower egg density, and decreased longevity. In addition, literature data show
southern populations to have a larger size at maturation, but rapid growth results in the
age of maturation decreasing toward the south. These relationships are thought to
arise from coupled physiological pathways and trade-offs during ontogeny, and could
be due to either genetic differentiation among populations or phenotypic plasticity in
the expression of life history.
Richard S. Appeldoorn: Department o f Marine Sciences, University o f Puerto Rico,
Mayagüez, Puerto Rico 006815000 [tel: (+809) 899 2048, fax: (+809) 899 5500].
Introduction
The study of life-history strategies is important for
understanding population dynamics, and can provide
insight relevant to the management of exploited species
(e.g., Adams, 1980; Gunderson, 1980; Ware, 1985). A
life-history strategy is a design for survival. It consists of
a set of traits, coadapted through natural selection,
which provide a species with a means of dealing success­
fully with environmental problems (Stearns, 1976).
However, elucidation of life-history strategies has
proven difficult. A wide variety of traits need to be
accounted for, many of which vary ontogenetically.
These include growth rate, reproductive effort, egg size
and number, mortality, metabolic efficiency, and the
age and size at maturation. These traits do not respond
to selective pressure independently of each other, and
some of these responses are subject to taxonomic and
allometric constraints (Brown, 1983; Steams, 1983,
1984). It also must be determined whether responses
observed are truly genetic or only phenotypic (Rolf,
1984; Stearns and Crandall, 1984; Stearns and Koella,
1986; Appeldoorn, 1989). A further step in elucidating
any particular strategy is to relate variability in lifehistory traits to environmental factors affecting selec­
tion. This implies the pertinent factors are known and
can be measured. Spatial and temporal variations in
local conditions may affect sampling or mask true re­
lationships. This may require large sample sizes or a long
time series of observations.
The soft-shell clam, Mya arenaria L., is a commer­
cially important species (MacKenzie, 1979) that oc­
cupies a variety of habitats and is subject to a wide range
of environmental conditions. Being a deep-burrowing
infaunal filter-feeder, Mya is exposed to conditions of
both the substrate and the overlying water column. It is
predominantly intertidal throughout most of its range
and therefore subject to the environmental extremes
associated with this habitat.
Given the wide variety of local (i.e., 1-10 km in scale)
conditions in any region (i.e., 10-100’s km in scale) and
the dispersal potential of pelagic larvae, it has been
difficult to conceive of adaptation in Mya populations on
a local scale. That the development of life-history traits
in Mya is dominated by local conditions has long been
known (Spear and Glude, 1957). Because of this,
attempts to determine patterns in life-history traits have
focused on differences over broad geographical dis­
tances. Along the northeast coast of North America
Mya is found in abundance from Chesapeake Bay to
Newfoundland. Spanning this latitudinal range is a
gradient in environmental conditions, including tem­
perature, sediment characteristics, salinity, current
flow, tidal range, and vertical position on the tide
20
R. S. Appeldoorn
ICES mar. Sei. Symp., 199 (1995)
wherein Mya is found (Appeldoorn, 1983). Neverthe­
less, variations in local conditions have tended to mask
significant latitudinal trends in life-history traits. For
example, Newcombe (1936), Turner (1948), and
Brousseau (1979) could not conclusively show any re­
lationship between growth and latitude. Such a relation­
ship was not shown until recently (Appeldoorn 1983),
and required a large number of samples over the com­
plete geographic range.
Given the difficulties in determining life-history strat­
egies in general, and in Mya in particular, a prudent
approach would be first to determine the existence and
nature of any patterns in life-history traits. The purpose
of this study is to determine such patterns in M. arenaria
sampled across its geographic range from Chesapeake
Bay to Nova Scotia. Because life-history traits are co­
variable, my approach is first to establish relationships
among traits using growth rate as the standard for com­
parison. Growth was chosen because it is a good predic­
tor and integrator of environmental conditions, it is
manifested early in ontogeny, and it directly influences
many subsequent traits subject to the constraints of size
and allometry (Appeldoorn, 1989). The fact that there
exists a latitudinal gradient in environmental conditions
and that growth rate has been related already to this
gradient (Appeldoorn, 1983) allows resulting patterns to
be presented in an environmental context.
Methods
Data collection
Samples of soft-shell clams were collected at 25 sites
along the northeast coast of North America (Table 1,
Fig. 1). Populations were initially sampled for a study on
neoplasia and pollution (Brown et al. , 1979; Appeldoorn
et al. , 1984). As such, samples were collected at different
times of the year and under different environmental
conditions; estimates could not be made on all traits for
all populations, and some traits are estimated only ap­
proximately. The net effect is an increase in data varia­
bility. While this limits individual comparisons, overall
trends can be educed because the large sample size will
offset the higher degree of variance. Because of
enhanced variability in the data, the significance of any
trend observed will be conservative.
All sampled individuals were measured for shell
length, weighed, and sectioned for histological analysis.
Table 1. Life-history parameters estimated for each population. Measurements of egg density and egg diameter are from
individuals in the late-developing stage of gametogenesis. - - Missing value, n = sample size, VJM = variation in iuvenile
mortality.
Sampling site
Site
code
Date of
sampling
n
Log(iü)
VJM
z
Tangier Sound, MD
Big Annemessex River, MD
Navesink River, NJ
Raritan Bay, NJ
Winnapaug Pond, RI
Quonochontaug Pond-1, RI
Quonochontaug Pond-2, RI
Saugatucket River, RI
Wickford, RI
Allen Harbor, RI
East Greenwich Cove, RI
Watchemoket Cove, RI
New Bedford, MA
West Falmouth, MA
Bourne, MA
Coonamessett River, MA
Portland, ME
Long Cove, Searsport, ME
Stockton H arbor, ME
Goose Cove, ME
Deer Isle, ME
Perry, ME
Robinston, ME
Janvrin Lagoon, NS
Potato Island. NS
TS
AR
NR
RB
WP
Q1
Q2
SR
WK
AH
EG
WC
NB
WF
BN
CR
PT
SP
SH
GC
DI
PY
RS
JL
PI
27-03-78
27-03-78
2-06-77
1-06-77
18-07-77
22-06-76
4-04-77
14-12-78
15-03-76
27-09-77a
3-03-76“
12-05-76
18-10-78
3-05-77
22-05-76
12-05-77
21-07-76
22-09-76“
13-09-78
20-07-76
22-09-76“
15-08-78
15-08-78
18-07-78
18-07-78
166
177
103
200
229
198
146
140
203
144
192
90
180
183
187
124
367
152
164
101
318
180
190
201
201
1.4488
1.4677
1.3808
1.1734
1.3418
1.0396
1.0743
1.1855
1.3066
1.0095
1.1025
1.0899
1.1360
1.0982
0.9294
1.2905
0.9986
1.0756
0.8847
0.9294
0.9311
-0.226
0.301
0.212
-0.014
0.050
-0.101
-0.510
1.19
1.12
1.02
1.37
0.56
0.70
0.28
a Supplementary samples were taken on other dates.
_
1.0754
0.7078
0.9053
_
Longevity
(years)
Egg
density
Egg
diameter
(n.m)
4.34
4.84
15.03
5.11
13.13
9.37
12.02
14.07
8.34
12.25
7.10
7.54
8.10
9.64
676
495
44.9
36.6
1515
38.9
1009
1303
890
42.2
38.5
38.4
1285
40.4
1318
1260
25.9
35.1
1414
1541
35.1
35.9
1337
37.6
0.373
-0.352
0.051
0.484
-0.009
0.35
0.23
1.40
0.31
0.45
0.220
-0.113
0.26
0.44
14.15
14.73
-0.228
0.24
13.26
-0.285
0.15
_
0.278
0.45
10.85
ill'!
0.86
9.79
_
_
_
_
_
_
_
_
_
Life-history parameters o f soft-shell clams
IC E S mar. Sei. Symp., 199 (1995)
75°W
70» W
21
65°W
RS
PY
SH
NORTH
AMERICA
45° N
SP
8N.
NB
JL
SC
WC'
EG
PT
AH.
CR
RB
40° N
40° N
WF
WK
SR
Ql + 0 2
WP
TS
NR
ATLANTIC
OCEAN
AR
75°W
Figure 1. Location of sampling sites for Mya arenaria (from Appeldoorn, 1983). Site codes are given in Table 1.
Sections were prepared using standard techniques
(Brown et al., 1977), cut at 6 (xm, and stained with
haematoxylin and eosin. Further details on sampling
and habitat characteristics are given in Appeldoorn
(1983) and Appeldoorn etal. (1984).
A ge structure, growth, and longevity
Population age structures and von Bertalanffy growth
parameters were determined in Appeldoorn (1981,
1983) using length-frequency analysis. These were used
in the present study. Growth in shell length was
expressed as Log10(oj) (Appeldoorn, 1983), where a> is
the product of the von Bertalanffy parameters k and L*
and represents the initial slope of the growth curve at
length = 0 (Gallucci and Quinn, 1979). Longevity was
estimated by calculating the age of the largest individual
collected at each site.
Adult mortality and variation in juvenile
mortality (VJM)
Adult mortality was estimated using catch-curve analy­
sis (Ricker, 1975) on the Appeldoorn (1981,1983) data.
Catch-curve analysis assumes constant mortality and
non-selective sampling. Data from Brousseau (1978a)
indicate that adult mortality is uniformly low. To control
against selection effects, young year classes (generally
<40 mm shell length) were not used in the catch-curve
analysis to ensure complete recruitment and sampling.
Catch-curve analysis gives the coefficient of instan­
taneous mortality (Z) by regression of the natural logar­
ithm of age-class size against estimated age. This
approach assumes that variations in recruitment are
random with a lognormal distribution about the mean
level of recruitment (Hilborn and Walters, 1992). While
long-term cycles (i.e., on a scale much greater than the
lifespan of Mya) in recruitment success have been re­
ported in northern New England populations of Mya
(Glude, 1954; Dow, 1972), there is no specific infor­
mation on the short-term variations that are of interest
here. Information from fishes in the region (Hennemuth
et al., 1980) suggests that lognormal distributions of
recruitment are a general feature of highly fecund
marine species. Accepting this assumption, the variation
around the catch-curve regression line represents varia­
bility in the set and survival of juveniles (Haukioja and
R. S. Appeldoorn
ICES mar. Sei. Symp., 199 (1995)
Table 2. Results of functional regression analyses of life-history variables against relative growth = Log(io).
Variable
VJM
Mortality (Z)
Longevity
Egg size
Egg density
r
Intercept (u)
Slope (v)
Approximate 95% confidence limits
n
0.432
0.436
-0.267
0.431
-0.899
-1.635
-1.981
34.063
12.151
2972
1.424
2.277
-20.651
23.106
-1645
0.744 < v <
2.105
1.192 < v <
3.362
-30.835 < v < -10.467
8.738 < v < 37.475
-2141 < v < -1150
18
18
19
12
12
Hakala, 1978). Thus, the standard deviation of residuals
from the regression is a measure of this variation. Since
standard deviation is dependent upon sample size, a
regression of the standard deviation against number of
age groups was made. The residuals from this were
taken as the corrected estimate of VJM; a negative value
indicates a lower standard deviation than expected and
hence lower VJM.
Reproductive parameters
Egg diameter and density were determined from 20
female histological sections selected randomly from
each sample. Each individual was classified to repro­
ductive stage using the seven categories of Porter (1974)
and terminology of Brousseau (1978b): indifferent,
early developing, mid-developing, late developing, ripe,
partially spawned, and spent.
Egg diameters were measured on five ova per individ­
ual using an ocular micrometer. Data were expressed as
average egg diameter per reproductive stage. For each
individual, triplicate egg density counts were made,
defined as the number of eggs (with nucleus visible)/
microscope field = 0.29 mm2. Data were expressed as
average density per reproductive stage. Brousseau
(1978b) found egg densities to remain constant through­
out the gonad. Therefore, density estimates reflect fec­
undity/unit of gonad, or relative fecundity. Absolute
fecundity could not be determined because possible
variations in gonad volume could not be accounted for.
Regression analyses
In regressions between population parameters, no single
parameter can be considered as an independent vari­
able. The growth parameter Log10(w) was used as the xvariate in all regressions. Adult mortality, longevity,
VJM, egg diameter and egg density were then regressed
against growth. Geometric mean functional regressions
were used in all cases because of the lack of an explicit
independent variable, the variability in estimates of both
the x and y variates, and the small sample size (Ricker,
1973,1984; Laws and Archie, 1981). Significance of the
regression was tested by determining if the 95% confi-
Table 3. Pair-wise comparisons of egg density and egg diam­
eter.
Comparison
G C -P T
JL -P I
P Y -R S
EG - WK
E G -B N
E G -W C
B N -W C
A R -T S
A H -Q 2
D I-S P
D I-S H
S P -S H
Larger egg density
Larger egg diameter
GCa
JLb
RSC
WKa
BNb
WCb
BNb
TSa
Q2a
D Ia
DIC
SP0
GC
JL
PY
WK
EG
EG
BN
TS
Q2
DI
DI
SP
a Comparisons were made using females in the late devel­
oping stage of gametogenesis.
b Comparisons were made using ripe females.
c Comparisons were made using females in the early devel­
oping stage of gametogenesis.
dence interval around the slope bracketed zero (Ricker,
1973).
Results
Estimates of all parameters used in the regressions are
given in Table 1. Table 2 gives the results of regressions
of adult mortality, VJM, and longevity versus growth.
The regressions indicate that longevity is negatively
related to growth, while adult mortality and VJM were
positively associated with growth.
Table 2 also gives the results for regressions of egg
diameter and egg density against growth. These analyses
were based solely on individuals classified as being in the
late developing stage of gametogenesis. This stage was
chosen because more populations had individuals in this
stage than in any other. The regressions show a positive
relationship between egg size and growth, and a strong
negative relationship between egg density and growth.
Table 3 illustrates the relationship between egg diam­
eter and egg density in a series of pairwise comparisons.
Sample pairs consist of two sites sampled proximally in
both time and space. Hence, any apparent trends should
ICES mar. Sei. Symp., 199 (1995)
Life-history parameters o f soft-shell clams
23
larger size-at-age. This combination of traits is inconsist­
ent with predictions based on the expectations of either
the r-K or bet-hedging life-history theories (Steams,
1976), and may reflect a combination of taxonomic,
allometric, and environmental constraints.
As an example of the latter, consider that there are
two trends in mortality. First, length of life decreases
toward the south. This is expected since Mya is a boreal
species (Laursen, 1966) and under temperature stress in
the southern part of its range (Pfitzenmeyer, 1972), and
that warmer temperatures in general increase metab­
Discussion
olism and rate of development, while decreasing
The results show that faster growth is related to a shorter longevity (Pauly, 1979). Secondly, variation in juvenile
lifespan (lower longevity, higher adult mortality), mortality increases toward the south, implying that en­
earlier sexual maturation but at a larger size, and larger vironmental conditions are more variable. This might
but relatively fewer eggs. More variable juvenile mor­ also be expected; in Chesapeake Bay, for example, Mya
tality is also related to rapid growth; however, VJM is can be limited by high temperatures, low salinity, low
more an indicator of environmental variability than a dissolved oxygen (Pfitzenmeyer, 1972), unsuitable sub­
biological trait. By placing these results in a latitudinal strate conditions (Pfitzenmeyer and Drobeck, 1963),
context, with growth being more rapid to the south and more consistent post-settlement predation pressure.
(Appeldoorn, 1983), comparison with other studies is These limitations arise from increased temperature
stress and increased submergence in southern popu­
possible, and a more synoptic picture may be suggested.
Literature review supports the results on mortality lations. The trend in adult mortality would suggest that
and longevity. The lifespan of M. arenaria is reported to early maturation (or larger size at maturation) would be
be 5 years in Chesapeake Bay (Pfitzenmeyer, 1972), 12 advantageous, and that smaller but more numerous eggs
years in Massachusetts (Belding, 1930) and over 20 years be produced. The expectations regarding maturation
are observed, and because of larger body size more eggs
in Canada (MacDonald and Thomas, 1980).
For reproduction, there is insufficient literature data may be produced, but they are not smaller, i.e., more
available for comparison to the observed trend in egg energy is being put into each egg than expected. How­
density. While fecundity estimates range from 120000/ ever, given greater variability in juvenile mortality, par­
year (Brousseau, 1978b) to several million/spawn ticularly that associated with larval settlement (Bayne,
(Belding, 1930; Stickney, 1964), little geographical sep­ 1965), it would be prudent to ensure that each egg/larvae
aration is represented in these data. However, infor­ had sufficient energy, and therefore produce larger eggs
mation is available on latitudinal variations in frequency as observed. However, high VJM would favour a longer
of spawning (Ropes and Stickney, 1965; Brousseau, reproductive life and the production of more broods.
1987) and on the size at maturation. In some northern While southern populations more consistently spawn
regions Mya may only spawn once per year, while in twice/year, their lifespan is shorter. Similar environmen­
southern regions two spawns occur. In central regions tally imposed inconsistencies between observed and
two spawns become more common toward the south, expected life histories have been reported for other
but either one or two spawns are possible depending molluscs (e.g., Hart and Begon, 1982).
At present there is no clear indication that the trends
upon local conditions. Size at maturation increases to­
ward the south; reported values are 15mm in Maine observed represent genetic adaptation or are merely the
(Hanks, 1963), 20 mm in southern New England (Coe results of phenotypic expression. The trends were found
and Turner, 1938), and 25 mm in Chesapeake Bay over an extensive geographic range and environmental
(Pfitzenmeyer, 1972). Age-at-length data (Appeldoorn, gradient, yet local spatial and temporal effects still
1983: Appendix Table 1) indicate that despite these size accounted for much of the variability. Because of this
differences maturation occurs at an earlier age toward great local variability, and the dispersal potential of
pelagic larvae, Appeldoorn (1989) hypothesized that
the south.
The following association of traits is suggested: more Mya may be adapted for variable phenotypic expression
southern populations are characterized by more rapid of life-history traits, rather than genetically adapted to
growth, shorter lifespan, maturation at a larger size and specific conditions; only a limited amount of genetic
earlier age, more consistently spawning twice/year, and adaptation to the environmental gradient found across
the production of larger eggs at lower densities. How­ the geographic range of Mya would be possible. The
ever, with fecundity generally related to body size observed trends may represent this small amount of
(Brousseau, 1978b) lower egg density may be offset by genetic fine-tuning of the life history. In support of this
represent differences due to variations in local con­
ditions. The table shows evidence of a positive re­
lationship between egg diameter and egg density. This
relationship was tested using a binomial test (Hollander
and Wolfe, 1973) and was found to be significant at p =
0.07. Given the high degree of variability in the data and
the low power of the test, rejecting the null hypothesis of
no relationship may be warranted.
24
R. S. Appeldoorn
view, Morgan et al. (1978) reported significant genetic
differences between Mya from Maine and Chesapeake
Bay, with the latter having greater polymorphism and
heterozygosity. That genetic differentiation exists on a
geographic scale makes adaptation possible on the same
scale.
For two traits, egg size and density, a phenotypic
relationship was found that differed from the relation­
ship found over the geographic range. In comparisons of
paired populations sampled proximally in space and
time, egg size and density were positively correlated, in
contrast to the trend observed among all populations.
Similarly, Brousseau (1978b) found a direct relationship
between egg size and fecundity among spawns within a
population. Such a relationship is an obvious conse­
quence of variation in local conditions; when resources
are abundant and conditions benign, more energy is
available for egg production, regardless of any genetic
adaptation towards a particular strategy. This is not to
say that the presence of a local, phenotypic relationship
implies that the latitudinal trend was genetic. If signifi­
cant phenotypic plasticity in the expression of life history
traits exists, the expression of these traits may be set
early in ontogeny (Appeldoorn, 1989), and the effects of
any year-to-year variations later in life could be super­
imposed over this.
The demonstration of patterns in life-history traits
within M. arenaria, and the variability around them, has
certain implications for management. First, the exist­
ence of genetic adaptation is implied, and this would
have consequences on any transplanting of stocks over
long distances. The heritability of life-history traits in
Mya needs further study. Second, the fact that patterns
exist implies that they could be incorporated into management-oriented models. However, an important con­
sideration is the large degree of unexplained variability
resulting from variations in local conditions. This
implies that detailed life-history models would be very
site-specific. As such, they would not be generally appli­
cable, and hence not cost effective for practical manage­
ment. However, such models would still be valuable for
heuristic studies (e.g., Brousseau, 1978a; Brousseau et
al. , 1983). Lastly, the large degree of locally induced
variability suggests that local-scale transplanting of spat
from high density or marginal populations to other areas
is a possible management strategy. Reasonable growth
and survival could be achieved without altering the gen­
etic composition of local populations.
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ICES mar. Sei. Symp., 199 (1995)
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