# Effect of temperature on Temora longicornis swimming behaviour: illustration of seasonal impact in a temperate ecosystem

Maud Moison, François G Schmitt, Sami Souissi

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Maud Moison, François G Schmitt, Sami Souissi. Effect of temperature on Temora longicornis swimming behaviour: illustration of seasonal impact in a temperate ecosystem. Aquatic Biology, 2012, 16 (ISSN: 1864-7790), pp.149-162. 10.3354/ab00438. hal-00806953

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# Effect of temperature on *Temora longicornis* swimming behaviour: illustration of seasonal effects in a temperate ecosystem

Maud Moison<fnref n="1" />,<fnref n="2" />,<fnref n="3" />,<fnref n="4" />*, François G. Schmitt<fnref n="2" />,<fnref n="3" />,<fnref n="4" />, Sami Souissi<fnref n="2" />,<fnref n="3" />,<fnref n="4" />

**ABSTRACT:** The present study investigated the effect of temperature on male and female swimming activity of the calanoid copepod *Temora longicornis*, sampled during winter (February) and summer (August) in the English Channel coastal ecosystem. Video recordings were conducted at 3 temperatures representative of those to which these organisms are normally exposed (13, 16 and 20°C) and one extreme-event temperature (24°C). Examinations of instantaneous velocity and symbolic analysis (i.e. dynamics of swimming states discretized from time series of instantaneous velocity) showed that *T. longicornis* changed its behaviour when confronted with environmental temperature variations. Swimming speed increased as temperature increased. In warmer water, this copepod displayed higher swimming activity, break periods were less frequent, and the frequency of jumps increased. This phenomenon was amplified when the environmental temperature was increased to 24°C. These observations revealed a considerable tolerance to high temperatures and an ability to adjust to environmental temperature changes. The 'summer population' was less active in the low temperature range, but the swimming speed reached a higher value at higher temperatures than that shown by the 'winter population'. The results of the present study highlighted changes in the individual behaviour of this copepod in response to changing seasonal conditions in the form of swimming activity, and thus its ability to maintain biological processes throughout the year, even in a restrictive environment.

**KEY WORDS:** Copepod · Swimming behaviour · Temperature effect · Seasonal variation · *Temora longicornis* · Symbolic dynamics

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## INTRODUCTION

Temperature affects all biological processes, from molecular to population scale, especially in poikilothermic marine invertebrates (Pörtner & Farrell 2008), e.g. copepods (Kinne 1970, Mangum et al. 1972). The physical properties of cellular components, as well as biochemical reaction kinetics, are highly sensitive to temperature (Brown et al. 2004 and references therein), which appears as a key forcing in any life cycle trait. These traits include respiration (Gauld & Raymont 1953, Ikeda et al. 2001), gen-

eration time and stage-specific mortality (Halsband- Lenk et al. 2002, Devreker et al. 2005) and the repro- duction of and predation for poikilothermic organ- isms (Devreker et al. 2005, Holste et al. 2009).

In the marine pelagic ecosystem, copepods are subjected to highly variable and restricted conditions in a 3-dimensional diluted and patchy environment. Their ability to maintain constant life processes, i.e. maximize encounter rate with potential partners or prey and minimize predation risk, in spite of changing environmental conditions, is crucial for their fitness. Consequently, to face such a changing envi-

<footnote n="1">¹Leibniz Institut of Marine Sciences, IFM-GEOMAR, 24105 Kiel, Germany</footnote>

<footnote n="2">²Université Lille Nord de France, 59000 Lille, France</footnote>

<footnote n="3">³Université des Sciences et Technologies de Lille (USTL), Laboratoire d'Océanologie et de Géosciences (LOG), 62930 Wimereux, France</footnote>

<footnote n="4">⁴Centre National de la Recherche Scientifique (CNRS), Unité Mixte de Recherche (UMR) 8187, 62930 Wimereux, France</footnote>
ronment, copepods have developed a range of strategies, including a wide spectrum of swimming behaviour to search for food (Tiselius 1992, van Duren & Videler 1995) and sexual partners (van Duren & Videler 1996, Doall et al. 1998) and to avoid predators (van Duren & Videler 1996, Tiselius et al. 1997). The patterns of zooplankton swimming behaviour may be affected by changing temperature conditions, i.e. either no change (*Metridia longa*, Hirche 1987; *Calanus finmarchicus*, Lenz et al. 2005), or a decrease (*Acartia tonsa*, and *C. glacialis*, Hirche 1987, Larsen et al. 2008) or a rise in swimming activity during warmer conditions (Lenz et al. 2005).

The effect of seasonal temperature variation on the swimming velocity of copepods, especially *Temora longicornis*, is not well known, although this variation may be important in the aquatic environment. With rising temperatures in the northern hemisphere (Levi-tus et al. 2000, 2005), there is a need to study behav-ioural observations in relation to variations in environ-mental temperature. This, in turn, will give us a better understanding of natural selection processes and their implications on larger-scale mechanisms such as spa-tial distribution (Beaugrand et al. 2002), demography and dynamic of the populations and communities (Clark et al. 2003, Molinero et al. 2008), as well as consequences for trophic interactions (Richardson & Schoeman 2004, Frederiksen et al. 2006).

The calanoid copepod *Temora longicornis* is dis-
tributed throughout the North Atlantic Ocean (CPR
Survey Team 2004) and is one of the major copepods
(in terms of number and biomass contribution to the
total zooplankton) in the English Channel (Williams
et al. 1994, John et al. 2001), which is characterized
by large seasonal fluctuations in the temperature of
the surface water (from around 8°C in winter to about
20°C in summer). Although the population size of
this copepod shows marked changes (Brylinski et
al. 1988), it is present year round and dominates
copepod assemblages during the spring bloom of
phytoplankton (Quisthoudt et al. 1987, John et al.
2001). Consistent with its broad spatio-temporal dis-
tribution, this eurythermic species tolerates a wide
range of temperature fluctuations. Thus, the life his-
tory traits (i.e. reproductive event and egg produc-
tion as well as hatching, stage development and
adult survival) take place in waters that range from a
few degrees above 0°C to around 20 to 25°C (Hals-
band & Hirche 2001, Halsband-Lenk et al. 2002,
Devreker et al. 2005). Moreover, a macrotidal (i.e.
highly dynamic system) coastal ecosystem such as
the English Channel is characterized by the multi-
scale intermittent distribution and fluctuation of the

temperature related to different forcings occurring at
different time scales (from minutes to days) such as in
tidal input, river flow fluctuations, meteorology and
turbulence (Dur et al. 2007). In this context of high
variability, the ability to adapt behaviour is crucial.
According to Gill & Crisp (1985), *T. longicornis* seems
able to accommodate its swimming effort: the fre-
quency of the limb movements increases as the tem-
perature rises from 0 to 22.5°C. Nevertheless, the
sampling period may determine the size of the adap-
tive response of the rate of beating to sea tempera-
ture change: the 'summer population' is less active in
the low temperature range than the 'winter popula-
tion', but swimming reaches a higher rate at higher
temperatures (Gill & Crisp 1985).

The aim of the present study was to analyze the ef-
fect of temperature on the swimming velocity of dif-
ferent populations of *Temora longicornis* inhabiting
markedly different environmental conditions. During
summer, high temperature and food availability, as
well as a larger copepod density, characterise the
copepod's environment, which contrasts with winter
environmental conditions, in which temperature is
low and food availability and conspecific density are
noticeably reduced. The approach used here consisted
of video recording *T. longicornis* individuals at differ-
ent temperatures. The individual swimming pathways
were characterized both quantitatively (swimming
speed) and qualitatively (symbolic dynamic analysis).
Finally, the results are discussed in an ecological
framework with regard to the fitness of populations
facing changes in environmental conditions.

MATERIAL AND METHODS

Sampling and acclimation

The influence of temperature was studied on 2
dates, representing 2 seasonal periods: one on 31
August 2007 and the other on 26 February 2008.
Plankton samples were taken by means of a plankton
net (200 µm mesh size) from the eastern English
Channel (coastal point: 1°31' 17" E, 50°40' 75" N).
The samples were immediately placed in a cooler
box, diluted in 20 l of seawater and returned to the
laboratory. On each sampling date, surface seawater
was also collected and filtered through Whatman
GF/C glass fiber filters (0.7 µm) for further use in the
laboratory during the behavioural experiments.

Viscosity is a major hydrodynamic force, especially
important to very small objects, and its effects on
swimming motion are related body size (Gill & Crisp
1985, Granata & Dickey 1991). Therefore, to avoid biased results and obtain comparable and consistent data, adults of *Temora longicornis* were selected according to size (mean ± SE of total length = 1.4 ± 0.1 mm for males and females in August, and 1.4 ± 0.1 mm for males and 1.2 ± 0.3 mm for females in February).

Four life conditions were tested: 2 sea temperatures close to the environmental mean (13 and 16°C), the maximum sea temperature (20°C) measured during the study period and an extreme sea temperature (24°C). Both sexes of *Temora longicornis* adults were distributed among test beakers, each containing 1 l of filtered seawater (Fig. 1). The organisms were then acclimatised for 30 h, during which the temperature was gradually increased by an increment of 2°C h⁻¹ to the desired test value. This was kept constant for at least 22 h. For the 2 lower temperatures (13 and 16°C), each group of copepods was placed into a temperature-controlled chamber. For the 2 samples at 20 and 24°C, temperatures were maintained using 25 W aquarium heaters.

<figure><img src="image_2.png" /><figcaption>Fig. 1. Schematic drawing of the experimental setup for both experiments: (a) 31 August 2007 and (b) 26 February 2008. A: time to bring to the right temperature; B: period of acclimation at constant temperature; C: recovery from handling stress before video recording; D: video recording—performed twice, once for females and once for males—with infrared light and camera during the night; E: image analysis and coordinate extraction</figcaption></figure>

## Video recording process

The same recording protocol was executed during each experimental session. The video recording processes, which were performed during the night to coincide with biological rhythms (e.g. *Temora longicornis* is known to feed predominantly at night, Head et al. 1984), took place in a dark room to avoid phototactic behaviour of these organisms (Head et al. 1984). The copepods were separated by sex to avoid the potential influence of interactions between both sexes (Doall et al. 1998, Weissburg et al. 1998, Goetze & Kiørboe 2008). At 20 min before the beginning of the recording, around 10 males or females were placed into an aquarium (15 × 15 × 15 cm) containing filtered seawater. This relatively important ratio of the number of individuals to the volume of water was chosen so that we could obtain long recording fragments of trajectories (i.e. a fragment without contact with other individuals or the walls). The duration of the recording was about 60 min under infrared light (880 nm light-emitting diode)

using an infrared-sensitive camera (Sony DCR HC 96; temporal resolution: 40 ms, spatial resolution: 720 × 576 pixels).

The horizontal and vertical coordinates were extracted frame by frame using the software Labtrack (Labtrack v.2.1, Bioras). Only trajectories longer than 2 s (50 data points) were kept to calculate statistically significant measurements. The numerical analysis was applied on an average of about 100 sequences for each condition (approximately 150 000 data points per environmental condition) (Table 1).

## Data analysis

### Analysis of trajectories

First, the instantaneous velocity (Vi) was estimated for each time step. X(n) was the 2-dimensional (2D) position of the copepod in the frame n, and $d_i = ||X(i) - X(i-1)||$, which is the distance between the position of the copepod at frame i - 1 and the frame i. Vi is defined as:

$$Vi = \frac{d_i}{\tau} \qquad (1)$$

where τ is the time resolution. Mean and maximum values were considered for each experiment, together with their prob-
<table><caption>Table 1. *Temora longicornis*. Experimental conditions and data collected for each video recording analyzed on 31 August 2007 (summer, S) and 26 February 2008 (winter, W). *In situ* temperatures were 18.2°C and 7.8°C in the summer and winter, respectively. Information recorded included the number of specimens studied (n), the temperature of each experiment (*T*<sub>exp</sub> ± SD), the number of trajectories extracted (no. of tracks) and the total number of data values analysed (no. of values)</caption><thead><tr><th></th><th><i>T</i><sub>exp</sub> (°C)</th><th>n</th><th>No. of tracks</th><th>No. of values</th></tr></thead><tbody><tr><td colspan="5"><strong>Females</strong></td></tr><tr><td>S_1</td><td>13.5 ± 1</td><td>10</td><td>228</td><td>392 907</td></tr><tr><td>S_2</td><td>15.5 ± 1</td><td>10</td><td>141</td><td>238 790</td></tr><tr><td>S_3</td><td>20.4 ± 1</td><td>10</td><td>55</td><td>72 125</td></tr><tr><td>S_4</td><td>24.5 ± 1</td><td>10</td><td>156</td><td>287 564</td></tr><tr><td colspan="5"><strong>Males</strong></td></tr><tr><td>S_1</td><td>13.5 ± 1</td><td>10</td><td>60</td><td>107 506</td></tr><tr><td>S_2</td><td>15.9 ± 1</td><td>10</td><td>76</td><td>88 596</td></tr><tr><td>S_3</td><td>20.9 ± 1</td><td>10</td><td>100</td><td>106 972</td></tr><tr><td>S_4</td><td>24.6 ± 1</td><td>10</td><td>98</td><td>160 983</td></tr><tr><td colspan="5"><strong>Females</strong></td></tr><tr><td>W_1</td><td>13 ± 1</td><td>10</td><td>117</td><td>193 852</td></tr><tr><td>W_2</td><td>15.6 ± 1</td><td>10</td><td>123</td><td>236 543</td></tr><tr><td>W_3</td><td>20 ± 1</td><td>8</td><td>20</td><td>33 234</td></tr><tr><td>W_4</td><td>24.4 ± 1</td><td>7</td><td>23</td><td>14 494</td></tr><tr><td colspan="5"><strong>Males</strong></td></tr><tr><td>W_1</td><td>13.2 ± 1</td><td>10</td><td>57</td><td>99 345</td></tr><tr><td>W_2</td><td>15.8 ± 1</td><td>10</td><td>165</td><td>163 743</td></tr><tr><td>W_3</td><td>20.2 ± 1</td><td>10</td><td>113</td><td>147 820</td></tr><tr><td>W_4</td><td>24.4 ± 1</td><td>7</td><td>25</td><td>42 161</td></tr></tbody></table>

ability density function (pdf), to emphasize extreme event distribution.

Other analyses were performed to consider the dynamics of the copepods' swimming behaviour, for which the ordering of events was important. The first was the Fourier power spectral analysis. The energy spectrum *E*(*f*) associated with frequency *f* was estimated as the Fourier transformation of the autocorrelation function:

$$E(f) = \frac{1}{\pi} \int_{0}^{\infty} \cos(\text{ft})C(t)dt \quad (2)$$

where *C*(*t*) is the autocorrelation function. For a 2D trajectory, the power spectrum of the path was estimated as the half-sum of the power spectrum of each coordinate as:

$$E(f) = \frac{1}{2}((f) + E_y(f)) \quad (3)$$

The power spectrum was useful in identifying possible frequency peaks associated with periodic forcing, or in estimating scaling ranges where the power spectrum was fitted as:

$$E(f) = Kf^{-\beta} \quad (4)$$

where *K* is a constant and *β* is the scaling exponent for the considered frequency range. If the copepod underwent a Brownian motion, *β* = 2, and when Eq. (4) was verified with *β* ≠ 2, the process might have belonged to scaling families such as Lévy motion or multifractal random walk (Schmitt & Seuront 2001).

## Symbolic dynamics

Symbolic dynamics is a method of studying and characterizing the complexity of discrete systems that possess a finite number of symbols. This approach has been well adapted to the study of animal behaviour, and especially that of copepods (Schmitt et al. 2006, Moison et al. 2009, Michalec et al. 2010). Each trajectory can be translated into sequences of successive discrete events; in the present study a swimming state was assigned to each frame based on the velocity information. Three states were chosen, with reference to instantaneous velocity: (1) 'break' (B) for zero velocity, corresponding to no appendage movement; (2) 'fast swimming' (F) corresponding to situations when the instantaneous displacement between 2 frames is larger than the body size of copepods: this corresponds to a threshold of 30 mm s<sup>-1</sup>; (3) 'slow swimming' (S) corresponding to when the velocity was smaller than the threshold, but positive, in which the behaviour was considered as a 'cruise'.

With this approach, the behaviour dynamics were reduced to a succession of symbols, one symbol for each frame. Behaviour was characterized by the percentage of total time spent in one state and the mean of residence time for each state (Moison et al. 2009, Dur et al. 2010, Michalec et al. 2010).

Taking into account the 3 states previously defined, one can extract the rhythm of the series and then perform several analyses. In our case, Shannon entropy analysis of differential swimming states was also used here to characterize the complexity in the dynamics. The Shannon entropy (*H*) was defined as:

$$H = -\sum p(A_i) \log p(A_i) \quad (5)$$

where *p*(*A*<sub>*i*</sub>) is the probability mass function of outcome symbol *A*<sub>*i*</sub>. In Eq. (5) the logarithm used was base 2.

The Shannon entropy analysis quantifies the information contained in the sequence of random variables. If the results are more frequent, then the uncertainty is lower and *H* is also lower. In extreme cases, entropy is equal to 0 when the outcomes are entirely predictable. In our case, higher values could
mean that the evolution of the swimming states was
more chaotic and unpredictable. Conversely, a de-
crease in the value could mean that the degree of
uncertainty decreased, highlighting the emer-
gence of repeating units, and thus an adaptive
behavioural pattern. *H* can be used to express the
predictability of change in a complex system and
has been widely used in time series analysis (Ebel-
ing 1997, Moison et al. 2009).

Statistical testing

Statistical comparisons were carried out using a
non-parametric Mann-Whitney *U*-test with a sig-
nificance level set at *p* < 0.05 for (1) the same sex
and the same season between each temperature
condition, (2) the same sex and the same tempera-
ture between both seasons and (3) the same tem-
perature and the same season between both sexes.
Differences between mean and maximum swim-
ming speed, mean *H* and the results of symbolic
dynamic analysis in all experimental conditions
were quantified.

RESULTS

Use of the term ‘population’

Life cycles of copepods are multigenerational. Each generation, from nauplii to mature adult, presents specific and distinct features (derived from abundance, biomass, body size and biotic potential; Halsband-Lenk et al. 2004, Devreker et al. 2005). *Temora longicornis* is present and breeds continuously throughout the year in the English Channel (Devreker et al. 2005). This species displays a cycle of 5 successive generations per year. However, several generations can overlap and coexist; thus, at a given time and place, sampled individuals may not be from the same generation. For this reason, we chose to call our samples ‘winter population’ and ‘summer population’ and not use the term ‘generation’, even if the 2 studied groups could not clearly belong to the same generation.

Analysis of velocity

Our results indicated changes in Vi, common to
both populations in both male and female *Temora
longicornis*, linked to temperature variation (Fig. 2a,b).

<figure><img src="image_3.png" /><figcaption>Fig. 2. *Temora longicornis*. (a) Average instantaneous velocity (Vi) and (b) maximum Vi (mean ± confidence limits), averaged from trajectories extracted for each experiment (male; black line, female; grey line) on 31 August 2007 (dashed line) and 26 February 2008 (solid line). Significant differences were noted between temperature conditions for the same sex and the same season (\*), between both seasons for the same sex and the same temperature (Δ) and between both sexes for the same temperature and the same season (◊) (Mann-Whitney *U*-test, α = 5%)</figcaption></figure>

The mean and maximum of Vi increased for both
sexes with a rise in temperature. The mean swimming
speed varied from around 3 to 5 mm s⁻¹ (Fig. 2a) and
maximum values reached were 2-fold higher than the
mean values (Fig. 2b). No distinctions were observed
between male and female behaviour. Nevertheless,
for both males and females, the values of the instanta-
neous velocities averaged during the highest temper-
ature were 1.5 and 2 times greater than those meas-
ured during the lowest temperature for both winter
and summer, respectively. In addition, from the
lowest temperature to the highest temperature, the
maximum swimming speeds increased 2-fold and
3-fold for the winter and the summer population, re-
spectively. Thus, winter population individuals swam
faster at 13°C, with an average speed of ca. 3.1 mm
s⁻¹, compared with those from the summer population
(average speed, ca. 2.7 mm s⁻¹). There was an inverse
relationship at 24°C, where the maximum speeds
recorded in summer were higher (75 mm s⁻¹ for fe-
males and 67 mm s⁻¹ for males) than those observed in
winter (52 mm s⁻¹ for females and 48 mm s⁻¹ for males).

These results were confirmed by the probability
density analysis of instantaneous swim speed (Fig. 3).
The experiments performed at intermediate tem-
peratures (16 and 20°C) exhibited a very similar pdf.
Experiments in cold conditions showed low prob-
ability densities for extreme high speed, which was
especially true for those conducted in summer. Con-
versely, extreme values of swimming speed were
more frequent, especially for experiments performed
at warmer temperatures in summer.

Inherent velocity fluctuations in the swimming be-
haviour of *Temora longicornis* were measured by
power spectral analysis. Each spectrum showed simi-
lar features for each temperature condition (Fig. 4).
The spectra followed a power law when frequencies
were below 1 Hz and a slightly flat pattern revealing

a white noise for high frequencies. Power spectra
density plots of swimming velocity also showed a
marked difference for extreme temperatures (Fig. 4).
For temperatures from 13 to 20°C, the slopes of
power spectra law regression for each population and
both sexes were similar and were about 0.4 ± 0.2 SD
(Table 2). In warmer conditions, the values of slopes
were much higher than 0.6, especially during the
summer period when the energy spectra exhibited
a much steeper incline, which was followed by a
change of regime, with a flatter slope from frequen-
cies around 0.1 Hz.

The value of *H* was relatively high for all different
populations and experimental conditions and was
greater than 0.55 (Table 3). *H* increases with a rise
of temperature, indicating a growing variability of
the symbols sequences dynamics (i.e. succession of
time-sequenced states). Such a pattern constitutes an
increasing complexity of the swimming activity in the
presence of elevated temperature. However, this
indicator does not reflect a clear difference between
the sexes or between populations.

Temperature is the main factor determining vis-
cosity. Viscosity tends to fall as temperature rises.
Thus, variations of temperature could have affected
the ability of *Temora longicornis* to sink. In warmer
conditions, organisms may have more pronounced
sinking behaviour, which could be confused with
activity. In order to avoid this potential bias, hypo-
thetical sinking time was considered (Fig. 5) and
defined as the periods when the copepod moved

<figure><img src="image_4.png" /><figcaption>Fig. 3. *Temora longicornis*. Probability density functions, P(Vi), (log/log plot) of the instantaneous velocities (Vi) calculated from the trajectories extracted for each experiment: 26 February 2008 (winter, W, solid line) and 31 August 2007 (summer, S, dashed line), at ca. 13°C (1), 16°C (2), 20°C (3) and 24°C (4), for (a) males and (b) females</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Fig. 4. *Temora longicornis*. Energy spectrum ($E(f)$, Eq. (3), (log/log)) of instantaneous velocity frequencies, *f* (Hz), calculated from the trajectories extracted for each experiment at ca. 13°C (1), 16°C (2), 20°C (3) and 24°C (4), for (a,c) males and (b,d) females, for 2 experiments, (a,b) 26 February 2008 and (c,d) 31 August 2007 and their power-law regressions (dotted lines)</figcaption></figure>

toward the bottom, perpendicular to itself, with a speed equal to or less than 3 mm s⁻¹ (the theoretical top sinking speed for this species; Tiselius & Jonsson 1990). With an overall coverage value between 11 and 17%, there was no significant effect of temperature on the hypothetical state (Mann-Whitney *U*-test).

<table><caption>Table 2. *Temora longicornis*. Value of exponents (β) derived from power law regressions (Eq. 4) of each energy spectrum for experiments at 13°C (1), 16°C (2), 20°C (3) and 24°C (4) on 31 August 2007 (summer) and 26 February 2008 (winter)</caption><thead><tr><th rowspan="2"></th><th colspan="4">Female</th><th colspan="4">Male</th></tr><tr><th>1</th><th>2</th><th>3</th><th>4</th><th>1</th><th>2</th><th>3</th><th>4</th></tr></thead><tbody><tr><th>Summer</th><td>-0.5</td><td>-0.4</td><td>-0.3</td><td>-0.75</td><td>-0.4</td><td>-0.4</td><td>-0.4</td><td>-0.7</td></tr><tr><th>Winter</th><td>-0.35</td><td>-0.4</td><td>-0.4</td><td>-0.6</td><td>-0.3</td><td>-0.4</td><td>-0.4</td><td>-0.75</td></tr></tbody></table>

For all temperatures tested, *Temora longicornis* adopted the usual and expected patterns of swimming behaviour. Breaks dominated the behaviour pattern, a great proportion of time was spent in slow swimming (from 29 to 48% of total time, depending on sex and condition) and rapid movements rarely occurred (<1% of total time was spent in fast swimming) (Table 4). However, the relative importance of these different swimming states varied with temperature. Indeed, the mean of residence time and the total periods allocated to breaks decreased with high temperature. Conversely, the relative importance of slow swimming activity increased with rising temperature, when considering both the mean residence time and the total time spent for this activity. This pattern was true for all experiments and for both sexes but was particularly marked for the summer populations.
<table><caption>Table 3. *Temora longicornis*. Values of Shannon entropy *H* (mean ± confidence limits) estimated for experiments at ca. 13°C (1), 16°C (2), 20°C (3) and 24°C (4) on 31 August 2007 (summer) and 26 February 2008 (winter). Significance differences (*) during summer and winter for females, and winter for males (Mann-Whitney *U*-test, *α* = 5%)</caption><thead><tr><th rowspan="2"></th><th colspan="4">Female</th><th colspan="4">Male</th></tr><tr><th>1</th><th>2</th><th>3</th><th>4</th><th>1</th><th>2</th><th>3</th><th>4</th></tr></thead><tbody><tr><td>Summer</td><td>0.57 ± 0.003*</td><td>0.58 ± 0.01</td><td>0.60 ± 0.005</td><td>0.62 ± 0.01*</td><td>0.56 ± 0.01</td><td>0.57 ± 0.006</td><td>0.58 ± 0.01</td><td>0.58 ± 0.01</td></tr><tr><td>Winter</td><td>0.56 ± 0.007*</td><td>0.58 ± 0.005</td><td>0.61 ± 0.02</td><td>0.61 ± 0.02*</td><td>0.56 ± 0.008*</td><td>0.59 ± 0.009</td><td>0.61 ± 0.006</td><td>0.62 ± 0.008*</td></tr></tbody></table>

<figure><img src="image_6.png" /><figcaption>Fig. 5. *Temora longicornis*. Total time (mean ± confidence limits) spent in potential sink ($t_{pot}$) calculated and averaged from trajectories extracted for each experiment at each temperature for males (black line) and females (grey line), for both experiments: 31 August 2007 (dotted line) and 26 February 2008 (solid line)</figcaption></figure>

The total time allocated to slow swimming was 1.5 times higher in the warmest conditions compared with the coldest conditions for the summer population. Similarly, as temperature increased, the mean residence time in this activity was multiplied by 1.5 and 2 for females and males, respectively. The effect of temperature on the total time spent in fast swimming was particularly noticeable during the summer. Indeed, this measured time was multiplied by 33 and 25 for females and males, respectively, during this period. The magnitude of this increase was mainly due to very low values in cold conditions (0.03%) and high values at 24°C (1% for females and 0.74% for males).

## DISCUSSION

For all tested conditions, *Temora longicornis* spent nearly 100% of its time slowly cruising or 'hanging'

stationary in the water column while moving its feeding appendages. This is in accordance with previous investigations (Tiselius & Jonsson 1990, van Duren & Videler 1995). In the present study, we showed that temperature significantly affected the behaviour of this species in both seasons and for both sexes. The copepods exhibited a reduction in both swimming speed and activity with decreasing temperature and an increase in both as temperatures rose. The behavioural complexity (as indicated by high *H* values) was also enhanced at high temperatures, with a clear intermittence in the swimming activity and high variability. The extremes in swimming speed highlighted by probability density functions and longer time spent in cruise and jump behaviour indicated that this species follows a complex stochastic motion. The copepods exhibited high activity, revealed by the relative importance of slow and fast swimming occurring with a temperature rise.

Gerritsen (1982) found that the activity of *Daphnia* spp., measured as the frequency of upward or downward swimming excursions, was not only dependent on temperature, but also on temperature change, enhancing the diel vertical migration of zooplankton populations. However, in our study, before video recording began, the environmental temperature was changed gradually and slowly to the desired value and copepods were kept under constant temperature in dark conditions for around 1 d, as well as during all the behavioural experiments. Thus, we assume that individuals were well acclimatized and the swimming response was not a consequence of temperature change and was even less of a display of the vertical migration mechanism (Calaban & Makarewicz 1982, Cooke et al. 2008). Moreover, for the same reason, the motility change that occurred at the extreme temperature was neither a reflection of an avoidance response nor a stress response to stress-inducing temperature changes (Hakimzadeh & Bradley 1990, Calaban & Makarewicz 1982)
<table><caption>Table 4. *Temora longicornis*. Main results of symbolic dynamic analysis: Values (mean ± confidence limits) of residence time (t) and proportion of time (PT) spent in each state: break (B), slow swimming (S) and fast swimming (F), at ca. 13°C (W_1, S_1), 16°C (W_2, S_2), 20°C (W_3, S_3) and 24°C (W_4, S_4) on 31 August 2007 (summer, S_1 to S_4) and 26 February 2008 (winter, W_1 to W_4). Significant differences between temperature conditions for the same sex and season (*), between both seasons for the same sex and temperature (Δ) and between both sexes for the same temperature and season (◊) (Mann-Whitney U-test, α = 5%)</caption><thead><tr><th></th><th>t<sub>B</sub> (s)</th><th>PT<sub>B</sub> (%)</th><th>t<sub>S</sub> (s)</th><th>PT<sub>S</sub> (%)</th><th>t<sub>F</sub> (s)</th><th>PT<sub>F</sub> (%)</th></tr></thead><tbody><tr><td colspan="7"><strong>Females</strong></td></tr><tr><td>S_1</td><td>0.16 ± 0.01</td><td>68 ± 1*</td><td>0.06 ± 0.001</td><td>31 ± 1*</td><td>0.05 ± 0.001</td><td>0.7 ± 0.2</td></tr><tr><td>S_2</td><td>0.15 ± 0.004</td><td>67 ± 1</td><td>0.07 ± 0.001</td><td>33 ± 1</td><td>0.05 ± 0.002</td><td>0.3 ± 0.1<sup>Δ</sup></td></tr><tr><td>S_3</td><td>0.11 ± 0.01</td><td>59 ± 3<sup>•Δ◊</sup></td><td>0.07 ± 0.006</td><td>41 ± 3<sup>•Δ◊</sup></td><td>0.07 ± 0.01</td><td>0.03 ± 0.04<sup>•</sup></td></tr><tr><td>S_4</td><td>0.1 ± 0.03</td><td>50 ± 2<sup>•Δ◊</sup></td><td>0.1 ± 0.002</td><td>48 ± 1<sup>•Δ</sup></td><td>0.1 ± 0.001</td><td>2 ± 0.1<sup>•Δ◊</sup></td></tr><tr><td colspan="7"><strong>Males</strong></td></tr><tr><td>S_1</td><td>0.17 ± 0.01</td><td>71 ± 2<sup>•Δ</sup></td><td>0.07 ± 0.002</td><td>29 ± 2<sup>•Δ</sup></td><td>0.09 ± 0.01</td><td>0.1 ± 0.1</td></tr><tr><td>S_2</td><td>0.15 ± 0.009</td><td>67 ± 2<sup>Δ</sup></td><td>0.07 ± 0.002</td><td>33 ± 2<sup>Δ</sup></td><td>0.05 ± 0.002</td><td>0.05 ± 0.02<sup>Δ</sup></td></tr><tr><td>S_3</td><td>0.1 ± 0.003</td><td>66 ± 1<sup>•Δ◊</sup></td><td>0.07 ± 0.001</td><td>34 ± 1<sup>Δ</sup></td><td>0.04 ± 0.001</td><td>0.06 ± 0.02<sup>Δ</sup></td></tr><tr><td>S_4</td><td>0.1 ± 0.006</td><td>52 ± 1<sup>•Δ◊</sup></td><td>0.14 ± 0.006</td><td>48 ± 1<sup>•Δ</sup></td><td>0.04 ± 0.001</td><td>0.2 ± 0.005<sup>•◊</sup></td></tr><tr><td colspan="7"><strong>Females</strong></td></tr><tr><td>W_1</td><td>0.15 ± 0.007</td><td>69 ± 1</td><td>0.07 ± 0.001</td><td>31 ± 1</td><td>0.05 ± 0.003</td><td>0.2 ± 0.05<sup>•◊</sup></td></tr><tr><td>W_2</td><td>0.15 ± 0.007</td><td>68 ± 1</td><td>0.07 ± 0.001</td><td>32 ± 1</td><td>0.05 ± 0.003</td><td>0.02 ± 0.01<sup>Δ◊</sup></td></tr><tr><td>W_3</td><td>0.15 ± 0.02</td><td>67 ± 2<sup>•Δ◊</sup></td><td>0.07 ± 0.004</td><td>33 ± 2<sup>•Δ◊</sup></td><td>0.04 ± 0.003</td><td>0.09 ± 0.05</td></tr><tr><td>W_4</td><td>0.13 ± 0.02</td><td>62 ± 3<sup>•Δ</sup></td><td>0.07 ± 0.01</td><td>37 ± 3<sup>•Δ</sup></td><td>0.06 ± 0.01</td><td>0.6 ± 0.1<sup>•Δ</sup></td></tr><tr><td colspan="7"><strong>Males</strong></td></tr><tr><td>W_1</td><td>0.16 ± 0.01</td><td>70 ± 1<sup>•Δ</sup></td><td>0.07 ± 0.002</td><td>30 ± 1<sup>•Δ</sup></td><td>0.04 ± 0.003</td><td>0.03 ± 0.04<sup>•◊</sup></td></tr><tr><td>W_2</td><td>0.15 ± 0.007</td><td>69 ± 1<sup>•Δ</sup></td><td>0.06 ± 0.0011</td><td>31 ± 1<sup>•Δ</sup></td><td>0.05 ± 0.002</td><td>0.2 ± 0.08<sup>Δ◊</sup></td></tr><tr><td>W_3</td><td>0.14 ± 0.003</td><td>63 ± 2<sup>•Δ◊</sup></td><td>0.08 ± 0.001</td><td>37 ± 1<sup>•Δ◊</sup></td><td>0.05 ± 0.001</td><td>0.2 ± 0.03<sup>Δ</sup></td></tr><tr><td>W_4</td><td>0.14 ± 0.006</td><td>63 ± 1<sup>Δ</sup></td><td>0.08 ± 0.002</td><td>37 ± 1<sup>Δ</sup></td><td>0.05 ± 0.002</td><td>0.2 ± 0.03</td></tr></tbody></table>

## Effect of environmental temperature on swimming behaviour

### Mechanical constraints

The viscosity of seawater is directly controlled by environmental temperature: the dynamic viscosity varies between 1.27 and 0.96 × 10⁻³ kg m⁻¹ s⁻¹ for temperatures ranging from 13 to 25°C. In addition, micro-organisms such as copepods swim under low Reynolds number conditions, thus viscosity effects dominate. It is therefore difficult to differentiate between the direct effect of temperature and the indirect effect of viscosity on the swimming activity of *Temora longicornis*. However, previous results have indicated environmental changes in viscosity associated with temperature can influence the small-scale processes of marine zooplanktonic organisms (Podolsky & Emlet 1993, Bolton & Havenhand 1997), even in free-swimming copepods (Larsen et al. 2008). Thus, the observed decrease in swimming velocity could have been the result of an adaptation to increased viscosity,

which would have involved an increase in the energy required to move the swimming appendages or a mechanical hindrance of the appendages. In fact, copepods swim by vibrating the feeding appendages, and escape jumps are driven by repeated striking of their swimming legs (Strickler 1975). Moreover, copepods, through the mechanical displacement of mechanoreceptor setae on their antennules (which generate a neural signal), are sensitive to hydrodynamic signals generated by predators, prey or conspecifics (Gill & Crisp 1985, Gill 1986). It is plausible that in a strong viscous environment (i.e. during winter), this mechanism may be less efficient and lead to a lesser sensitivity to disturbances and thus a more limited swimming activity (Lenz et al. 2005).

### Ecophysiological aspect: direct effect

The most commonly used method to assess the energy requirements of organisms is to measure their rate of oxygen uptake, which is a function of temperature. Respiration rates are known to be higher in cold seasons than in warm seasons for several copepod species (Gaudy 1973). Furthermore, metabolic performance is sensitive to environmental conditions (Clarke 1991, Johnston et al. 1991, Hawkins 1995, Johnston et al. 1998). Thus, adaptation to a cold environment involves additional energy costs and may explain observed decrease of the potential of some biological processes such as reproduction (Devreker et al. 2005), as well as the observed decrease of the swimming effort.

### Ecological consequences

The consequences of life in a cold environment (i.e. high energetic cost, low movement efficiency and limited mechano-sensitivity), have important
implications in the ecology of copepods, as they are more vulnerable to predators and have a decreased ability to detect and catch potential sexual partners or prey. The ingestion rates of *Temora longicornis* are positively related to temperature (Dam & Peterson 1988) and can be explained by the alteration of the allocated time for feeding movements in suspension-feeding copepods (Cowles & Strickler 1983, Price & Paffenhöfer 1986). Moreover, although *T. longicornis* uses chemical signals to remotely locate mates, hydro-mechanical stimuli may be involved during the final phase of chasing the mate (Doall et al. 1998). The processes associated with reproduction can be dis-turbed by increasing viscosity. By reducing their abil-ity to accomplish biological processes, lower temper-atures may reduce the fitness of the species (Kramer et al. 2011). Consequently, the lower temperature condition could significantly exert selective pres-sures governing *T. longicornis* behaviour.

## Effects of extreme temperature

Environmental factors such as temperature must satisfy minimum and maximum criteria to sustain organism or ecological processes. The maximal criteria represent the level at which factors exert constraints on organism productivity and thereby prevent them from achieving their full biological potential which could be realized under optimal con-ditions. In this sense, maximal criteria can involve toxicity or other biological damages and constitute a type of ecological stress. In the experiments at 24°C, the copepods still showed an increase in swimming speed and activity, especially cruise, indicating an absence of stress and no adverse effect on behaviour. The unfavourable upper-level temperature may not be reached (Schmidt-Nielsen 1997). This demon-strates the ability to cope with changes in tempera-ture by adjusting their swimming behaviour, as well as a tolerance to extremely high environmental tem-peratures. Previous studies on the metabolism and biological processes of this species have shown a tol-erance to a wide range of temperature fluctuations (Peterson & Kimmerer 1994, Devreker et al. 2005). In fact, reproduction of *Temora longicornis* takes place from 2.5 to 20°C, with maximum fertility reached at ca. 18°C (Halsband & Hirche 2001, Halsband-Lenk et al. 2002). The eurythermal nature of this species may explain its extended distribution area on both sides of the North Atlantic Ocean (CPR Survey Team 2004). In our study, there were no significant differences in behaviour between the sexes at temperatures similar

to those found in the eastern English Channel (i.e. from 13 to 20°C). This result was consistent with the work of Gill & Crisp (1985) who observed similar ap-pendage beat frequencies between *T. longicornis* males and females. Examination of spectra and sym-bolic analysis at extreme temperatures, however, revealed a greater responsiveness by females than males, as shown by the slopes of energy spectrum regression at 24°C. Moreover, the maximum swim-ming speed of females was greater. This observation may reflect a lower resistance of males to extreme temperatures. Similar results have been found in other copepod species; for example, males of *Eury-temora affinis* are less tolerant to temperature changes than are females (Bradley 1978). Compared with females, male *Eucyclops agilis* also show a significant reduction in swimming activity at high temperatures (15 to 20°C), which coincides with a marked increase in their respiration rate (Laybourn-Parry & Tinson 1985). Devreker et al. (2005) showed that an increase in temperature has a negative effect on the survival of *T. longicornis* in the eastern English Channel, probably because of a rise in the energy cost of metabolism. A decrease in activity in males at 24°C could have been the result of an adaptation to high temperatures, involving a rise in energy requirements.

## Interseasonal variability

### Seasonal effect

The succession of generations for *Temora longicornis* has been shown by Halsband-Lenk et al. (2004): life history traits, including functional responses, e.g. respiration, vary through generations and seasons (Berner 1962). In fact, the ability to resist changes in temperature may depend on the environmental temperature conditions in which the copepods de-velop and mature. Generally, marine copepod spe-cies which have a maximum biomass during spring and autumn have a lethal temperature lower than that of those with a maximum biomass in summer (Deevey 1960, Gaudy & Thibault-Botha 2007). Dur-ing our experiment, the winter population showed a relatively greater swimming speed at the lowest temperature and less activity at the warmest condi-tion. Similarly, Elphick & Shine (1998) were able to show that lizards *Bassiana duperreyi* acclimatized to warm temperatures could maintain a higher running speed at warmer temperatures than lizards that were not acclimatized to warm conditions. However, the
behaviour of copepods is influenced not only by tem-
perature, but also by factors such as prey availability
and physiological state. Copepods spend less time in
the 'slow swimming' and more time in the 'break'
state when food concentrations decrease (Cowles &
Strickler 1983). The higher activity observed in the
high temperature experiment in the summer popula-
tion may have been the result of a better nutrition
and physiological state compared with the winter
population. In conclusion, these differences between
the populations appear to depend on the food quan-
tity and quality and/or on adaptations to the prevail-
ing temperatures of the habitat.

Ecological implications

*Temora longicornis* is known as a species with a
high metabolic rate, but low energy reserves with
limited lipid accumulation (Fraser et al. 1989, Hel-
land et al. 2003, Kreibich et al. 2008). Therefore, sur-
vival and reproductive success are directly depend-
ent on food availability and feeding behaviour (Koski
& Klein Breteler 2003). Both phytoplankton (Breton
et al. 2000, Gómez & Souissi 2008) and *T. longicornis*
biomass (John et al. 2001) are low during the winter
in the eastern English Channel. Time spent cruising
(e.g. slow swimming) was greater in the winter pop-
ulation than in the summer one. This strategy may
allow the species to increase the potential encounter
rate and thus ensure feeding and mating processes
in ecosystems that present lower food and partner
availability during winter. In fact, *T. longicornis* breed
continuously throughout the year, even in winter
(Halsband-Lenk et al. 2004). In addition to produc-
tion of resting eggs (Lindley 1986, 1990), the egg pro-
duction in winter keeps a stock of premature stages
ready to use the algal spring bloom and may con-
tribute to a rapid recruitment in early spring (Le
Ruyet-Person et al. 1975).

The most abundant copepods in the English Chan-
nel are the genera *Pseudocalanus*, *Temora*, *Calanus*,
*Centropages* and *Acartia* (Quisthoudt et al. 1987,
John et al. 2001). Generally, the maximum numbers
of copepods are recorded at the end of May, and
copepod stocks remain high throughout the summer
(Quisthoudt et al. 1987, Mauchline 1998, John et al.
2001). These species have similar sizes and feeding
modes, being filter-feeders (e.g. *Temora*, *Pseudo-
calanus*) or intermittent filter-feeders depending on
prey size (e.g. *Acartia*, *Calanus*, *Centropages*) (Jon-
son & Tiselius 1990, Hansen et al. 1994). They may
have the same kind of microplanktonic prey. Phyto-

plankton biomass also has a seasonal pattern with a
bloom in early spring and a quick decrease until
summer, after which a stable smaller biomass
remains for the remainder of the season (Gentil-
homme & Lizon 1998). Thus, interspecific and intra-
specific competition becomes more important during
summer as a result of the reduction in the prey:
predator ratio. The most visible result of the present
study was the difference between the 2 populations
at the warmest temperature: mean and maximum
swimming speeds were significantly higher for the
summer population. The ability of *Temora longicor-
nis* to maintain high swimming speeds could allow it
to increase its exploration area, and thus remain
competitive with respect to its foraging behaviour.

Pelagic copepods with a marked seasonality are
challenged with maintaining an effective behav-
ioural performance to carry out essential functions,
such as reproduction and feeding, while facing a
decline in metabolic rate due to the temperature
decrease. This capacity of pelagic copepods could
partly explain the population dynamics pattern of
*Temora longicornis* in the English Channel in which
individuals and egg production continue through-
out the year, ensuring a successful survival of the
overwintering population.

This contribution to the understanding of *Temora longicornis* behaviour and ecology allows us to interpret the life history strategy of this calanoid copepod in English Channel ecosystem. Our results highlight the importance of considering seasonal temperature trends when assessing its potential effects on key biological processes. However, to achieve a complete overview of the effect of temperature, it is necessary to take the different space–time scales into account, in particular the scale on a daily basis. Indeed, zooplanktonic organisms tolerate a specific range of temperatures depending on their recent thermal history (Calaban & Makarewicz 1982, Voznesensky et al. 2004). In addition, zooplankton exposed to weak temperature gradients on a daily cycle exhibit adaptive responses through synchronization of vertical migration processes (Gerritsen 1982). Therefore, a continuation of this work would be to consider the impact of the daily temperature cycle on the seasonal adaptive behaviour of *T. longicornis*.

*Acknowledgements.* A fellowship provided by Deutscher Akademischer Austauschdienst (DAAD) is gratefully acknowledged. Advice and comments supplied by Dr. J. C. Molinero are thankfully acknowledged. The authors also thank P. Magee for his quality English editing (www.englisheditor.webs.com).
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