How well do laboratory experiments explain field patterns of zooplankton emergence?

How well do laboratory experiments explain ®eldpatterns of zooplankton emergence?

CARLA E. CAÂ CERES and MICHAEL S. SCHWALBACH1

Center for Aquatic Ecology, Illinois Natural History Survey, Champaign, IL, U.S.A.

SUMMARY

1. We conducted a laboratory experiment to explore potential mechanisms driving

variation in zooplankton emergence from diapausing eggs observed in Oneida Lake, NY,

U.S.A. We hypothesized that variation in timing of ice-out (date of thawing of ice) between

1994 and 1995, which resulted in variation in photoperiod±temperature cues, contributed

to the differences in the observed ®eld patterns. Environmental chambers were used to

establish weekly photoperiod±temperature combinations that reproduced natural condi-

tions in Oneida Lake in 1994 and 1995. In addition, a third treatment (`dark') exposed eggs

only to the changes in temperature. We recorded zooplankton emergence for 2.5 simulated

ice-free seasons.

2. Nine cladoceran taxa were found to hatch, but only Daphnia pulicaria in large numbers.

Hatching of D. pulicaria was recorded throughout the season in the two light treatments

and sporadically in the dark treatment. The early ice-out treatment had the highest

emergence, followed by the late ice-out and dark treatments. Among taxa, there was

temporal segregation with ®ve hatching in the early weeks of sampling and two taxa

hatching during the middle weeks. Alona hatched late in the ®rst year, but earlier in the

second year.

3. We compared our laboratory results of D. pulicaria hatching with the ®eld data obtained

by CaÂceres (1998). Hatching was continuous in the laboratory, whereas a synchronous

spring emergence was found in the ®eld. However, in both the laboratory and the ®eld,

more D. pulicaria hatched under conditions re¯ecting ice-out occurring in March as

opposed to April. Because differences in rates and timing of emergence can affect the

population and community dynamics of pelagic systems, we suggest caution when

applying laboratory results to ®eld populations.

Keywords: Daphnia, diapause, dormancy, egg bank, ephippia

Introduction

Although it is well established that many aquatic

invertebrates have both active and diapausing stages

in their life cycle (Marcus et al., 1994; Hairston, 1996;

CaÂceres, 1997a; Brendonck, De Meester & Hairston,

1998), the ties between these stages are not well

understood. Because many dormant propagules can

remain viable for many years or decades, they may

substantially impact the ecological and evolutionary

dynamics of the populations that produce them (Wolf

& Carvalho, 1989; Marcus et al., 1994; Hairston, 1996;

Weider et al., 1997; CaÂceres, 1997b, 1998; Kerfoot,

Robbins & Weider, 1999; Hairston et al., 1999). For

freshwater zooplankton, one of the major barriers to

exploring the consequences of this complex life cycle

is a general lack of knowledge regarding the cues that

initiate and terminate dormancy. Despite several

laboratory experiments suggesting that photoperiod,

temperature, oxygen concentration, crowding, food

Correspondence: Carla E. CaÂceres, Center for Aquatic Ecology,

Illinois Natural History Survey, 607 E. Peabody Drive, Cham-

paign, IL 61820, U.S.A. E-mail: [email protected] address: University of Southern California, Los

Angeles, CA 90089-0371, U.S.A.

Freshwater Biology (2001) 46, 1179±1189

Ó 2001 Blackwell Science Ltd 1179

limitation and predation may be proximate cues that

induce or terminate diapause (e.g. Brewer, 1964;

Stross, 1966; Carvalho & Hughes, 1983; Kleiven,

Larsson & Hobñk, 1992; Slusarczyk, 1995), the com-

bined results of these experiments have indicated that

genotypes, populations and species exhibit consider-

able variation in response to these cues (Ferrari

& Hebert, 1982; Schwartz & Hebert, 1987; Hairston

& Dillon, 1990; Larsson, 1991; De Meester, Cousyn &

Vanoverbeke, 1998; Pfrender & Deng, 1998). Hence,

the dormant phase of the life cycle, as well as the

potential links to the active fraction, is not well

understood for most systems.

Most studies addressing the cues terminating dor-

mancy in freshwater zooplankton have been conduc-

ted in the laboratory (e.g. Pancella & Stross, 1963;

Stross, 1966; Schwartz & Hebert, 1987). Several

authors have been successful in breaking dormancy

but, for many of these studies, the primary goal was to

®nd any cue that would lead to hatching1 , regardless of

its relevance in nature (e.g. Pancella & Stross, 1963;

Davison, 19692 ; Doma, 1979; Schwartz & Hebert, 1987).

Hence, the procedures used to terminate dormancy

were often quite arti®cial (e.g. removing the eggs from

the casing, 24 h high light conditions, sodium hypo-

chlorite exposure) or investigated for a limited num-

ber of clones or populations. As a result, it is dif®cult

to use these laboratory results to predict how the

termination of dormancy will in¯uence the dynamics

of natural populations.

Only a handful of studies have investigated dia-

pause termination in the ®eld. Emergence traps have

occasionally been used to document the temporal and

spatial hatching dynamics of zooplankton (Herzig,

1985; Dana et al., 1988; De Stasio, 1989, 1990; Wolf

& Carvalho, 1989; CaÂceres, 1998; Hairston et al., 2000).

However, ®eld studies often only document the

timing and rate of emergence without directly testing

the mechanisms that might be driving those patterns.

For example, CaÂceres (1998) used inverted-funnel

emergence traps to investigate diapause termination

in Oneida Lake, NY, U.S.A. Over 4 years of sampling

(two with sampling from ice-out through November,

two with sampling summer and autumn only), it was

found that Daphnia emerged only in the spring, and

that emergence rates differed among years. For the

2 years in which sampling was conducted throughout

the ice-free season, both D. pulicaria (Forbes) and

D. galeata mendotae (Birge) were found to emerge in

1 year (1994), while only D. pulicaria was found in the

other (1995). Moreover, the number of emerging

D. pulicaria was higher in 1995 than in 1994 (CaÂceres,

1998).

Based on the data of CaÂceres (1998), we hypothes-

ized that variation in photoperiod and temperature

between 1994 and 1995 could have in¯uenced the

differences in emergence patterns. Each winter, ice

with snow-cover keeps the dormant eggs under cold

and relatively dark conditions. When the ice melts

each spring, the diapausing eggs at the bottom of the

lake are exposed to light and increasing temperature.

Although the water temperature at ice-out is constant

from year to year (< 4 °C), photoperiod is not.

Between 1986 and 1995 the date of ice-out on Oneida

Lake varied between 2 March and 25 April (E.L. Mills,

personal communication). This variation in timing of

ice-out leads to a wide range of photoperiods ®rst

reaching the sediment each spring, therefore causing

variation in the photoperiod±temperature combina-

tions received by the dormant eggs among seasons.

Although additional years of ®eld data are necessary

to con®rm this pattern, if different species and clones

require precise photoperiod±temperature cues to

hatch, then perhaps the different timing of ice-out

between 1994 and 1995 in¯uenced the hatching

patterns observed in the ®eld.

Our present study is an experimental analysis of the

cues driving the emergence of D. pulicaria in Oneida

Lake, NY. By exposing diapausing eggs to different

combinations of temperature and photoperiod, we

addressed the following questions: (1) does the timing

of ice-out in Oneida Lake affect the emergence

patterns of D. pulicaria? (2) what are the seasonal

patterns of zooplankton emergence seen in the labor-

atory? (3) how well do the laboratory results mirror

those obtained from the ®eld? We focused our study

on D. pulicaria because poor recruitment to the egg

bank by D. galeata mendotae in the years preceding our

experiment led to a low density of viable diapausing

eggs in the surface sediments collected for this project

(CaÂceres, 1997b, 1998).

Methods

To address the hypothesis that variation in timing of

ice-out between 1994 and 1995 led to variation in the

emergence of Oneida Lake zooplankton, we estab-

lished two laboratory treatments representing natural

1180 C.E. CaÂceres and M.S. Schwalbach

Ó 2001 Blackwell Science Ltd, Freshwater Biology, 46, 1179±1189

lake conditions for a year in which ice-out occurs in

March (1995) versus April (1994). Because both

photoperiod and temperature changed each week,

we also established a continuously `dark' treatment in

which only temperature varied.

Sediments were collected in May 1997 from a deep-

water (12 m) site in Oneida Lake, NY using an Ekman

Dredge. To concentrate the ephippia of Daphnia,

portions of the sediment were poured through a

200-lm mesh sieve. Although this procedure

increased the abundance of large diapausing eggs, it

probably reduced the density of many smaller eggs

(e.g. copepods, rotifers, small Cladocera). The sedi-

ment with ephippia was transported on ice to the

Illinois Natural History Survey in 2-L plastic contain-

ers that were wrapped in aluminium foil. In the

laboratory, containers were stored in the dark at 4 °C

to simulate winter conditions.

After 4 months, the sediment was thoroughly mixed

and a measuring cup was used to transfer 125 mL

aliquots of sediment to each of the 30 experimental

enclosures (10 replicates of three treatments). Each

replicate was a rectangular (9 cm ´ 13 cm ´ 6 cm)

polypropylene container in which the bottom had

been painted black. In addition, the enclosure and the

lid of each `dark' replicate were wrapped in alumin-

ium foil to prevent light pollution. After the sediment

(� 1 cm deep) was added to each enclosure, 400 mL of

®ltered (Whatman GF/C3 ; Whatman, Maidstone, U.K.)

Oneida Lake water was poured over the top of the

mud. During set-up, and during all subsequent

sampling, the `dark' treatment was examined in a

dark room under a red light (Sandmar ®reball

safelight4 ). Five aliquots of sediment were frozen for

analysis of the initial egg density.

Two environmental chambers were used to estab-

lish photoperiod±temperature combinations, with the

initial conditions set to replicate natural conditions at

ice-out (Fig. 1). Each week, the photoperiod and tem-

perature settings were changed to re¯ect the changes

occurring in the lake. Oneida Lake does not stratify

thermally, and the weekly temperature settings (which

were the same for both chambers) were based on data

collected weekly from Oneida Lake in 1994 and 1995. To

reduce the possibility of chamber and position effects,

on each sampling date, the treatments were switched

between the two chambers, and the 10 replicates were

haphazardly placed on one shelf within the chamber.

The top of each replicate was covered with plastic

wrap to reduce evaporation. Replicates for the `dark'

treatment were split between the two environmental

chambers and covered with black plastic.

On each sampling date, we gently siphoned all the

water from each replicate into a beaker. To enhance

emergence rates, the mud was stirred to bring any

buried eggs to the sediment surface. The water was

poured back into the enclosure through a 55-lm mesh

sieve, and additional ®ltered water was added to the

enclosure when necessary. The contents of the ®lter

were rinsed into a sample jar and examined immedi-

ately. Juvenile organisms were transferred to separate

containers for rearing until species identi®cation

could be made.

Sampling occurred weekly for the ®rst 34 weeks. At

week 34, all 30 replicates were once again transferred

to the `winter' conditions of darkness and 4 °C. After

4 months, the replicates were again transferred to the

conditions re¯ecting ice-out in March or April. Samp-

ling was carried out weekly for the ®rst 14 weeks, then

every other week thereafter. After the second 34 weeks

of sampling, winter conditions were imposed again.

After 4 months, a third year of sampling began. We

sampled weekly for 9 weeks, at which time all repli-

cates were frozen for later assessment of ®nal egg

density. Five haphazardly chosen replicates from each

treatment were screened for ®nal egg density.

To assess both initial and ®nal egg density, as much

®ne sediment as possible was removed with a 200-lm

mesh sieve. The remaining sediment was placed into a

15-mL centrifuge tube with a 30% sucrose solution

and centrifuged at 1100 r.p.m. for 1.5 min (Hairston

et al., 1995; CaÂceres, 1998). This process suspended

most of the ephippia, which were then poured onto a

150-lm sieve and resuspended in tap water for

examination under a dissecting microscope. The pellet

remaining at the bottom of the centrifuge tube was

also examined for ephippia. All ephippia encountered

were identi®ed to species based on the morphometry

of the dorsal ridge (C.E. CaÂceres, unpublished data),

opened, and assessed for the number of viable

diapausing eggs (0, 1 or 2).

Statistical analyses were performed in SYSTATSYSTAT 8.0

(Wilkinson, 1998) and DATADESKDATADESK 6.0 (Velleman, 1997).

Results

The sediment egg bank of Oneida Lake contains four

species of Daphnia: D. pulicaria, D. galeata mendotae,

Diapause termination 1181


D. retrocurva (Forbes), and D. ambigua (Scour®eld).

Even with sieving of the sediment which probably

concentrated diapausing eggs above densities found

in Oneida Lake, the number of eggs initially added to

each replicate was low for the latter three species

(Table 1). Because only D. pulicaria emerged in large

numbers (total hatching: D. pulicaria � 406,D. galeata �19, D. retrocurva � 27 and D. ambigua � 16), statistical

analyses were performed only for D. pulicaria.

Daphnia pulicaria began hatching in the fourth

week after the experiment began (Fig. 1). In both the

March and April treatments, hatching was recorded

throughout the ®rst year. In the dark treatment,

hatching was recorded in weeks 6, 7, 33 and 34. In

the second year, hatching began immediately in the

March and dark treatments, and in week 2 of the April

treatment. The majority of hatching occurred during

the ®rst 12 weeks of the second year, although there

was some hatching in later weeks. At week 5 in the

second year, there was a peak of emergence in all

three treatments. In the third year, only one D. pulicaria

emerged from all 30 replicates over the 9 weeks of

sampling.

Emergence of D. pulicaria varied signi®cantly

among treatments with the March treatment having

the highest emergence, followed by the April and

dark treatments (ANOVAANOVA with Bonferroni post hoc

tests: F2,27 � 61.7, P < 0.00001; March versus April

P � 0.009; March versus dark P < 0.00001; dark ver-

sus April, P < 0.00001) (Figs 1 & 2). The relative

increase in hatching under conditions of a March ice-

out was also observed in the ®eld (one-tailed t-test,

5 m sites: t3 � ±2.93, P � 0.03; Table 2, CaÂceres, 1998).

Overall, more D. pulicaria emerged in the ®rst as

compared with the second year (ANOVAANOVA: F1,58 � 9.25,

P � 0.004). Because there was minimal hatching after

week 12 in the second year, however, and hatching

appeared to peak earlier in the second year, we

compared just the ®rst 12 weeks of each year and

found no signi®cant difference among years (repeated

measures ANOVAANOVA: F1,58 � 1.88, P � 0.175), but a

signi®cant effects of week (repeated measures

ANOVAANOVA: F11,638 � 7.014, P £ 0.0001) and the week±

year interaction (repeated measures ANOVAANOVA:

F11,638 � 8.19, P £ 0.0001).

At the end of the experiment, the egg banks of the

enclosures were virtually depleted (Table 1). There

were non-viable eggs found in many of the treat-

ments, indicating the senescence of eggs during the

experiment. To assess the degree of senescence for

each of the four daphnid species in each treatment, we

divided the total number hatched over the 3 years by

the average initial egg concentration (Fig. 2). The

remaining fraction of the eggs was then assumed to

have senesced.

In addition to the four Daphnia species, ®ve other

cladoceran taxa were found to emerge: Ceriodaphnia,

Bosmina, Leptodora, Diaphanosoma and Alona (Fig. 3).

Because hatching of these taxa was sporadic, results of

temporal emergence patterns are presented as the

pooled estimates from all three treatments. Daphnia

galeata mendotae, Bosmina, Leptodora, Diaphanosoma and

Ceriodaphnia hatched primarily in the early weeks of

sampling, in both years 1 and 2 (Fig. 3a & c). Daphnia

retrocurva and D. ambigua hatched during the middle

weeks (Fig. 3b & d). Alona was not seen until week 15

of the ®rst year, but was found as early as week 3 in

the second year (Fig. 3b).

Discussion

There are both similarities and differences between

the laboratory data reported here and the results of

CaÂceres (1998). The seasonal timing of hatching was

extended in the laboratory as compared with the ®eld.

In the ®eld, over two full and two partial years of

sampling, Daphnia hatched only in the spring (Fig. 4;

CaÂceres, 1998), whereas they emerged under all

photoperiod±light combinations in the laboratory,

and sporadically in the dark (Fig. 1). In contrast, the

two full years of ®eld data suggest that in both the

laboratory and the ®eld, more D. pulicaria hatch under

Initial eggs

(number/replicate)

Final

March

Final

April

Final

dark

Daphnia pulicaria 46 � 7 0 � 0 0 � 0 1.4 � 0.6

D. galeata mendotae 5 � 1 0 � 0 0 � 0 0 � 0

D. retrocurva 6 � 1 0 � 0 0 � 0 0 � 0

D. ambigua 1 � 1 0 � 0 0 � 0 0 � 0

Table 1 Initial and ®nal numbers of

viable diapausing eggs (�1 SE) for the four

species of Daphnia found in the sediment

of Oneida Lake



conditions re¯ecting ice-out occurring in March as

opposed to April (Table 2; Fig. 4; CaÂceres, 1998).

Unfortunately, low sample sizes of D. galeata mendotae

precluded conclusions about species-speci®c differ-

ences in the breaking of diapause between the ®eld

and the laboratory.

There are several possible explanations for the

discrepancy in the seasonal timing of hatching in

D. pulicaria between the ®eld and the laboratory. First,

although the laboratory experiment reproduced sea-

sonal changes in photoperiod and temperature, sev-

eral other parameters (e.g. sediment dynamics,

Fig. 1 Weekly averages � 1 SE (n � 10) for emerging Daphnia pulicaria in years 1 (®lled diamonds) and 2 (open squares) of sampling.

Only one Daphnia was found in year 3, hence the data are not plotted. The solid lines without symbols represent the `March' and

`April' photoperiods in (a) and (b) respectively, and temperature in (c). The temperature represented in (c) applies to all three

treatments. The crosses indicate peak photoperiod or temperature.



oxygen gradients, chemical signals in the water) were

probably different in the laboratory. It is possible

that the termination of dormancy is inhibited in the

®eld by a stimulus that was not reproduced in

the laboratory. For example, Rengefors, Karlsson

& Hansson (1998) and Hansson (2000) have recently

demonstrated that the recruitment rate of algal species

from the sediment can be reduced by the presence of

zooplankton grazers. Perhaps chemical stimuli from

competitors or predators also inhibit recruitment of

Daphnia from the sediment. Secondly, hatching rates

in the ®eld were low (88 Daphnia collected over

2 years; CaÂceres, 1998), making it possible that emer-

gence did continue for all seasons in the ®eld, just at a

rate below the detection limit [(1 Daphnia) 0.5 m±2].

Thirdly, the fact that the timing of hatching observed

in the ®eld is most similar to the `dark' treatment

suggests that the lighting conditions established in the

laboratory may have increased hatching relative to the

®eld conditions. Light does penetrate to the bottom of

Oneida Lake (C.E. CaÂceres, personal observation),

although the intensity and spectral distribution will

obviously vary between the laboratory and the ®eld.

Finally, the laboratory and ®eld dynamics may have

differed because of the age of the eggs exposed to the

hatching cues. In the ®eld, only the eggs on the

sediment surface are exposed to the hatching cue, and

the majority of these eggs are likely to have been

produced recently (Hairston, Kearns & Ellner, 1996;

CaÂceres & Hairston, 1998). The eggs in the laboratory

Table 2 Comparison of D. pulicaria hatching in the ®eld (5 m

deep sites only) and in the laboratory. Although all counts

are expressed as No. m)2 (�1 SE), the laboratory and ®eld

emergence are not directly comparable because of a con-

centration of eggs above ambient density for the laboratory

experiment. Field data from CaÂceres (1998)

Laboratory

emergence

(No. m)2)

Field

emergence

(No. m)2)

`March' treatment (mimics

1995 ®eld conditions)

1830 � 130 200 � 70

`April' treatment (mimics

1994 ®eld conditions)

1360 � 100 6 � 6

Fig. 2 Average � 1 SE (n � 10) cumulative hatching (expressed as percentage of initial number of eggs) in each of the three

treatments for the four Daphnia species found in the Oneida Lake egg bank. Given the lack of viable eggs at the end of the experiment

in all but the D. pulicaria dark treatment (Table 1), the unhatched fraction of eggs was assumed to have senesced.



Fig. 4 Average in situ emergence rates for Daphnia pulicaria and Daphnia galeata mendotae in Oneida Lake, NY. Error bars

have been omitted for clarity. Data from CaÂceres (1998).

Fig. 3 Weekly averages (n � 10) for emerging zooplankton taxa. Because hatching of these eight taxa was sporadic, emergence is

pooled over the three treatments, and error bars are omitted for clarity. (a, b) Indicate emergence rates for the ®rst year of sampling

whereas (c, d) indicate results for the second year of sampling. Note the difference in scale for Diaphanosoma in (a) and (c) and for

Alona in (b).



experiment were collected from several samples

obtained with an Ekman dredge in 1997, immediately

following production of diapausing eggs in Oneida

Lake. Hence, the laboratory eggs were a mixed sample

of newly produced and deeply buried eggs. It is

unknown how old the collected eggs were, but eggs

buried in the top 5 cm of Oneida Lake sediment can

be over a decade old (CaÂceres, 1998). These older eggs

may respond to cues differently than do newly

produced eggs (Hairston et al., 1996) and break

dormancy immediately upon being returned to the

sediment surface. Because eggs probably need to be

very near the sediment±water interface to hatch

(Kasahara, Onbe & Kamigaki, 1975; Uye, Kasahara

& Onbe, 1979; N. G. Hairston Jr. & C. M. Kearns,

unpublished data), our weekly stirring of the mud

may have continued to bring eggs to the sediment

surface, thus promoting continual hatching all year.

A consideration of egg age may also help to explain

the emergence peak in week 5 of the second year. It

has been suggested that diapausing eggs must remain

dormant for several months before hatching, regard-

less of exposure to the termination cue (Stross, 1965;

Stross & Hill, 19685 ; Schwartz & Hebert, 1987). Because

springtime conditions represent the time of peak

hatching in Oneida Lake (CaÂceres, 1998), the peak

hatching seen early in the second year could result

from eggs produced in May 1997 becoming sensitive

to the termination cues and hatching the year after

they were produced.

By week 15 of the second year, hatching from all

three treatments had ceased almost completely. This

pattern could either result from the remaining eggs

requiring `springtime' cues to terminate dormancy, or

a depletion of viable eggs. Based on the lack of

hatching in the third year, the latter explanation is

most probable. Final examination of the experimental

enclosures revealed a high rate of egg senescence in

all three treatments, despite the fact that the eggs in

the experiment were well within the range of the

maximum viability estimates. It is now well estab-

lished that diapausing eggs can remain viable in situ

for decades or centuries (e.g. Marcus et al., 19946 ;

Hairston et al., 1995; Katajisto, 1996; Weider et al.,

1997; CaÂceres, 1998; Kerfoot et al., 1999). Longevity in

the ®eld may be promoted by sediment conditions

that were not replicated in the laboratory. In working

with diapausing Artemia cysts, Hoffmann & Hand

(19907 ) and Clegg (1992, 1997) have demonstrated that

embryonic development and metabolism are inhibited

by anoxia. The constant stirring of mud in the

laboratory probably kept the sediments oxygenated,

which either resulted in successful completion of

development or an increase in metabolism, which

contributed to rapid senescence. This critical differ-

ence may hamper laboratory investigations of the

effects of long-term dormancy on the ecology and

evolution of natural populations.

Although the seasonal timing of emergence in the

laboratory did not match with that in the ®eld, under

conditions re¯ecting an earlier ice out, more D. pulicaria

hatched relative to a later ice-out in both the laboratory

and the ®eld (Table 2). In a habitat where inter-annual

variation contributes to variation in recruitment

success, long-term dormancy serves as a means of

reducing the effect of this variation on long-term

®tness (Cohen, 1966; Templeton & Levin, 1979;

Venable & Lawlor, 19808 ). Ignoring any potential costs

of remaining dormant, if habitat quality could be

accurately predicted each year, the obvious strategy

would be to terminate dormancy only in years

favourable for recruitment. Recent evidence for ter-

minating dormancy under favorable conditions has

been provided by Rengefors et al. (1998) and Hansson

(2000). Both these studies found that excystment from

dormant cysts of dino¯agellates was reduced in the

presence of zooplankton grazers. In Oneida Lake,

there are considerable year-to-year ¯uctuations in the

number of new diapausing eggs produced by both

D. pulicaria and D. galeata mendotae (CaÂceres, 1997b),

suggesting the bene®t of predictive emergence. Emer-

ging in years with an early ice-out may be bene®cial by

allowing more time for parthenogenetic reproduction

(resulting in large population sizes) before the onset of

diapause in May. However, we found no relationship

between the annual number of diapausing eggs

produced (CaÂceres, 1997b) and the date of ice-out,

suggesting a more complicated relationship between

emergence patterns and reproductive success.

The proximate cue controlling diapause termination

in the laboratory appears to be the photoperiod±

temperature interaction, as opposed to either cue

individually. All three treatments (March, April, dark)

received the same temperature each week (Fig. 1),

suggesting that temperature alone is not the driving

force. Neither is a precise photoperiod evidently

required to terminate dormancy, as animals were

found to emerge all year in the March and April



treatments and, sporadically, in the dark treatment.

Moreover, both March and April treatments experi-

enced nearly the same range of photoperiod

(9 h 45 min±15 h 30 min of light, with the April

treatment also receiving 9 h 15 min and 9 h 30 min

light) further suggesting that the differences in emer-

gence rate are not solely because of photoperiod. For

terrestrial insects, although the timing of diapause is

strongly in¯uenced by photoperiod, temperature is

thought to be a primary modi®er of this photope-

riod response (Lees, 1955; Danilevskii, 1965; Tauber,

Tauber & Masaki, 1986). In aquatic systems, this

photoperiod±temperature interaction may be even

stronger, because of the increased predicative power

of temperature as a result of the thermal buffering of

aquatic systems (Hairston & Kearns, 1995).

The seasonal patterns of emergence of other

zooplankton taxa indicate species-level differences in

response to photoperiod and temperature cues. For

several of the taxa, the laboratory patterns re¯ect the

seasonal timing of in situ emergence in Oneida Lake

(Hairston et al., 2000; C.E. CaÂceres, unpublished data).

In both the laboratory and the ®eld, Bosmina and

Diaphanosoma hatched primarily in the spring. Neither

Hairston et al. (2000) nor C.E. CaÂceres (unpublished

data) recorded Leptodora from the ®eld emergence

traps, and Ceriodaphnia was recorded only rarely by

C.E. CaÂceres (unpublished data). In situ hatching rates

of these taxa may have been below detection limit in

®eld, perhaps because of patchy distribution. The

clear segregation of hatching across taxa indicates

species-level variation in response to hatching cues.

As populations are often completely refounded each

season from the egg bank, this variation in hatching

may contribute to the stable co-existence of compet-

itors (Hutchinson, 1961; De Stasio, 1990; CaÂceres,

1997b).

The results of this laboratory experiment mirrored

the ®eld results in one respect (relative number

hatching) but not in another (timing of hatching).

That laboratory and ®eld data yield different results is

not surprising, but serves as an important caution.

Much of the conventional wisdom regarding the cues

that induce or terminate dormancy in zooplankton

result from data obtained in the laboratory. Our

results suggest caution when applying these laborat-

ory data to the dynamics of natural populations. For

example, whether zooplankton emerge from the

sediment throughout the year, as suggested by the

laboratory data, or in a single pulse, as suggested by

the ®eld data, has very different implications for the

role of dormancy in seasonal population dynamics.

Synchronous hatching provides no opportunity for

within-season recolonization of the water column,

whereas continuous hatching allows populations

to become re-established after a mid-season crash.

Future research that couples laboratory and ®eld

investigations is needed to understand fully the

termination of dormancy in the ®eld.

Acknowledgments

We thank E.L. Mills of the Cornell Biological Field

Station for providing us with access to Oneida Lake to

collect the samples. B. Phillips provided assistance in

the laboratory. A.J. Bohonak, N.G. Hairston Jr., A.G.

Hildrew and an anonymous reviewer provided help-

ful comments on earlier drafts of this manuscript. This

research was supported in part by National Science

Foundation grant DEB-9816047 to CEC.

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