# Identifying and quantifying unexpected deep zooplankton diel vertical migration in a large deep lake

Violaine Piton, Rafael Reiss, Ulrich Lemmin, Orlane Anneville, Gaël Many, Jérémy Keller, Valentin Kindschi, Htet Kyi Wynn, Serena Rasconi, Leslie Laine, et al.

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## To cite this version:

Violaine Piton, Rafael Reiss, Ulrich Lemmin, Orlane Anneville, Gaël Many, et al. Identifying and quantifying unexpected deep zooplankton diel vertical migration in a large deep lake. Limnology and Oceanography, 2025, 70 (2), pp.259-274. 10.1002/lno.12736. hal-05044912

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https://hal.inrae.fr/hal-05044912v1

Submitted on 24 Apr 2025

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Distributed under a Creative Commons Attribution 4.0 International License
LIMNOLOGY
and
OCEANOGRAPHY

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Limmol. Oceanogr. 70, 2025, 259-274

© 2024 The Author(s). *Limmology and Oceanography* published by Wiley Periodicals LLC on behalf of Association for the Sciences of Limnology and Oceanography.

doi: 10.1002/lno.12736

# Identifying and quantifying unexpected deep zooplankton diel vertical migration in a large deep lake

Violaine Piton,<fnref n="1" />* Rafael Reiss,<fnref n="1" /> Ulrich Lemmin,<fnref n="1" /> Orlane Anneville,<fnref n="2" /> Gaël Many,<fnref n="3" /> Jérémy Keller,<fnref n="3" /> Valentin Kindschi,<fnref n="1" /> Htet Kyi Wynn,<fnref n="1" /> Serena Rasconi,<fnref n="2" /> Leslie Laine,<fnref n="2" /> David Andrew Barry<fnref n="1" />

## Abstract

Diel Vertical Migration (DVM), a widespread zooplankton behavior in freshwater and marine systems, affects ecological interactions and biogeochemical cycles. In lakes, DVM has mainly been studied in the upper 50 m of the water column. However, based on acoustic and net sampling data collected in Lake Geneva, Switzerland (~309 m depth) during summer 2022, we demonstrate that DVM occurs down to ~125 m depth daily throughout the summer season. The daily descents terminated at around zenith when the Relative Rate of light Change (RRC) was the lowest, and the late afternoon ascent started when RRC values exceeded -0.005 s⁻<fnref n="1" />. DVM migration descent/ascent rates were asymmetric with faster mean upward rates (4.5 × 10⁻<fnref n="3" /> m s⁻<fnref n="1" />) than downward rates (-3.5 × 10⁻<fnref n="3" /> m s⁻<fnref n="1" />). Migration rates overall increased as summer progressed, corresponding to the intra-seasonal increase in RRC. Cyclopoid copepods *Cyclops prealpinus* abundances correlated with the observed deep DVM and their migration responded to exogenous light cues. These new findings, which can also be expected to be relevant for other deep lakes, indicate that Lake Geneva's DVM greatly exceeds maximum migration depths previously reported for a lake. Thus, it is important to study zooplankton DVM dynamics throughout the entire water column in large, deep lakes since it plays an important role in buffering global climate change effects. Furthermore, it is suggested that present zooplankton DVM sampling protocols in large, deep lakes should be revised accordingly.

Diel Vertical Migration (DVM) of zooplankton is a ubiquitous phenomenon in marine and freshwater pelagic zones (e.g., Meester 2009), and is known as “one of the most profound coordinated movements of organisms on the planet” (Häfker et al. 2017). Zooplankton either follow a preferred light level during migration or are cued to migration by

changes in the rate and direction of light intensity (Cohen and Forward 2019). The DVM amplitude (depth to which zooplankton descend) varies depending on the organism (Barbiero et al. 2019) and on “triggers” such as light intensity, daylength, season, temperature, dissolved oxygen concentration, buoyancy, food availability, predation risk, and internal clocks (Ringelberg 2010; Bandara et al. 2021).

DVM measurements traditionally rely on zooplankton samples collected using nets (e.g., Rudstam et al. 2015; Barbiero et al. 2019). In recent years, acoustic measurements have become a widely used tool for the observation of zooplankton distributions over extended periods, providing information on changes in zooplankton abundance as well as migration rates. By following the vertical displacement of sound scattering layers in oceans, acoustic data, for example from Acoustic Doppler Current Profilers (ADCPs), show coherent DVM (e.g., van Haren and Compton 2013; Bianchi and Mislan 2016).

There is a significant difference between zooplankton DVM amplitude reported for oceans and lakes. In oceans, DVM is studied down to depths of 200 m or more (e.g., Osgood and Frost 1994; van Haren and Compton 2013; Skreslet

Additional Supporting Information may be found in the online version of this article.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

**Author contribution statement:** VP: Conceptualization; Methodology; Investigation; Data curation; Formal analysis; Writing – original draft preparation; Writing – review and editing. RR: Investigation; Writing – review and editing. UL: Conceptualization; Methodology; Writing – review and editing. OA: Resources; Methodology; Writing – review and editing. GM: Investigation. JK: Investigation; Resources. VK: Investigation. HKW: Investigation. SR: Resources. LL: Investigation. DAB: Conceptualization; Methodology; Funding; Supervision; Writing – review and editing.

<footnote n="1">¹Faculty of Architecture, Civil and Environmental Engineering (ENAC), Ecological Engineering Laboratory (ECOL), Ecole Polytechnique Fédérale de Lausanne (EPFL), Environmental Engineering Institute (IIE), Lausanne, Switzerland</footnote>

<footnote n="2">²Université Savoie Mont Blanc, INRAE, UMR CARRTEL, Thonon-les-Bains, France</footnote>

<footnote n="3">³Institute of Earth Surface Dynamics, University of Lausanne, Lausanne, Switzerland</footnote>

<footnote>*Correspondence: violaine.piton@epfl.ch; vpiton@mercator-ocean.fr</footnote>
et al. 2020), whereas in lakes measurements are typically lim-
ited to ~ 50 m or less (e.g., Angeli et al. 1995; Lorke
et al. 2004; Huber et al. 2011). Documentation of deeper mea-
surements is scarce. In Lake Constance (Germany/
Switzerland/Austria), Stich (1989) carried out a very detailed
DVM assessment covering several species. *Daphnia longispina*
migrated during daytime down to 40–60 m depth (Stich 1989;
Huber et al. 2011). Barbiero et al. (2019) collected samples
down to 100 m depth in the Laurentian Great Lakes, but did
not investigate DVM. Watkins et al. (2017) reported mean
day/night populations of different taxa, with the deepest taxa
observed at ~ 70 m depth during daytime in Lake Ontario
(Canada/USA).

In Lake Geneva, western Europe's largest lake, zooplank-
ton population dynamics in the upper 50-m layer have been
regularly monitored for decades with net hauls by the Com-
mission Internationale pour la Protection des Eaux du Léman
(CIPEL) at station SHL2 (Fig. 1), but the measurement proto-
col is not designed for DVM assessments (CIPEL 2022). Based
on net hauls collected over 24 h between 0 and 50 m depth
in Lake Geneva, Angeli et al. (1995) found that adult cladoc-
eran *Daphnia* spp. performed the deepest DVM (between
30 and 50 m depth) and followed relative changes in light
intensity.

Since there appear to be no published studies on DVM
reaching below ~ 60 m depth in lakes, this investigation was
carried out in large, deep Lake Geneva (maximum depth
309 m). Based on long-term acoustic data, net hauls, and
high-resolution light measurements, we address the following
questions:

* Does deep zooplankton DVM occur in Lake Geneva during summer? If so, which depth layers are reached?

* Can the observed DVM be characterized in terms of zooplankton community/species? Does the community/species vary along the water column?

* Can vertical migration rates be quantified based on acoustic data? Do these rates vary during the summer season?

* Does light intensity or the change in rate and direction of light intensity limit the maximum DVM depth?

* Can the factor(s) triggering and limiting the DVM be identified and quantified?

Supporting Information figures, tables, and texts provide
details and clarifications on certain topics discussed in the
main text.

Methods

Study site

Lake Geneva (*Lac Léman*), situated between Switzerland and France, is a deep, perialpine, oligomictic lake (Fig. 1a). The lake is strongly thermally stratified from April to September with a thermocline deepening from ~ 3 to ~ 30 m depth.

Field data and analysis

Acoustic and temperature mooring data

Acoustic and temperature data were collected on a mooring
at station ML (located near CIPEL monitoring station SHL2,
see Fig. 1a) from June 1, 2022 to September 15, 2022. A pre-
liminary study in 2021 showed (Supporting Information
Fig. S4) that, during summer, the maximum DVM depth
remains nearly constant, allowing for a statistical analysis
and a quantification of the processes involved. Since this
study is limited to the summer season and systematic
changes were observed within that period, the term “intra-
seasonal” will be used hereinafter when referring to those
changes. The mooring consisted of an upward-looking
300-kHz Teledyne-RDI Workhorse Sentinel ADCP deployed
at 180 m depth (Fig. 1b). Full-depth measurements were
recorded every 20 min (averaged over 300 pings taken every
2 s) with 5-m high-beam bins. The received level of the
acoustic return signal along each beam of the ADCP was
converted into the Backscattering Index (BI) in dB
(Supporting Information Text S1). Days with spurious
spikes in the raw BI were removed, resulting in 97 d (out of
107) that were analyzed. From the surface down to ~ 30 m
depth, BI time series exhibit intense scattering (BI > 65 dB),
which could be due to zooplankton displacement, as well as
surface reflection, phytoplankton abundance, fish, bubbles,
suspended sediments, and turbulent microstructures
(Warren et al. 2003). Therefore, this layer was excluded
from the analysis.

To study the variability of the BI signal, the BI maximum (maxBI) in each depth bin was determined every day for each downward migration period (4:00 to 15:00; all times given in CET) and upward migration period (15:20 to 23:00). For each maxBI, the corresponding time was extracted. The same treatment methodology was applied to vertical velocity *w*, with the maximum denoted as maxw.

A line of 14 RBRsolo *T* temperature loggers (10-m interval,
measuring every minute) was attached to the top of the ADCP
frame (at 180 m depth) and reached up to 50 m depth (Fig. 1b).

Biological data

On June 21, 2022, July 5, 2022, August 1, 2022, August
17, 2022, and August 31, 2022, zooplankton samples were col-
lected at station SHL2 (Fig. 1a) between 11:00 and 12:30 using
a 200-µm mesh net in vertical tows from 50 m depth to the
surface; net towing speed was ~ 0.5 m s⁻¹. Additional samples
were collected with closing nets from 50 to 100 m depth and
from 100 to 150 m depth, resulting in three net hauls per sam-
pling day (Fig. 1b). The samples were stored in formalin and
later divided into subsamples and counted and identified (spe-
cies level) under a dissecting microscope. Copepod develop-
ment stages were systematically identified. Individuals in the
developmental stages of nauplii I, II, or III are categorized as
“juveniles.” Those in stages IV, V, and adulthood are catego-
rized as “adults,” which correspond to organisms > 1 mm in
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length. The abundance (in individuals m⁻²) of each species was computed as:

$$Abundance = N_{SS} \frac{V_S H}{V_{SS} V} \qquad (1)$$

where V_S and V_{SS} are the volume of the sample and of the subsample (in mL), respectively, N_{SS} is the number of individuals in the subsample, H is the layer thickness (here 50 m), and V is the volume of water filtered by the net (here 4.81 m³).

Samples collected on July 5 were then digitized with a ZooScan (Gorsky et al. 2010) to document the composition of the zooplankton community and obtain images of the different organisms.

## Environmental data

In DVM studies dealing with migrators that are broadly sensitive to visible light, measuring photosynthetically available c (PAR) is a reasonable alternative to measuring light in a spectrally relevant range (Cohen and Forward 2005a). An Apogee Quantum Sensor SQ-522 was installed on the rooftop of an Ecole Polytechnique Fédérale de Lausanne building located close to the Lake shore and at about the same longitude as mooring ML (location GR, see Fig. 1a). It measured PAR values (in µmol photons m⁻² s⁻¹) at 1 Hz throughout the mooring deployment period. The relative rate of change of PAR, Sr (in s⁻¹, t is time), was estimated using:

$$Sr = \frac{1}{PAR} \frac{dPAR}{dt} \qquad (2)$$

On July 5, 2022 and July 19, 2022, PAR profiles along the water column were measured at station ML (see Fig. 1a) with an MPE-PAR (Micro class, Profiling [in water], E [irradiance]— PAR) sensor (Biospherical Instruments Inc.) sampling at 1 Hz in the 400–700 nm spectral range. The sensor detection limit is 10⁻⁶ µmol photons m⁻² s⁻¹. Measured PAR values were corrected with a dark offset value (~ 1.36 × 10⁻⁵ µmol photons m⁻² s⁻¹) estimated from a profile taken at station ML on July 20, 2022 at 1:00 with the sensor wrapped in aluminum foil. The upward looking PAR sensor was equipped with a depth sensor and was mounted on a CTD (Conductivity, Temperature and Depth) probe (Sea & Sun Marine Tech CTD 75 M) sampling at 1 Hz. Profiles of PAR and temperature were collected at 11:00, 14:00, 16:00, and 18:00 on July 5, 2022,

and at 15:00, 20:00, and 24:00 on July 19, 2022 (Fig. 1b; Supporting Information Fig. S1).

Full depth profiles of temperature, dissolved oxygen, and chlorophyll a (Chl a) were taken at station SHL2 on June 7, 2022, June 21, 2022, July, 5, 2022, August 17, 2022, August 31, 2022, and September 13, 2022 (Fig. 1b; Supporting Information Fig. S1).

## Results

### Environmental conditions

Temperature profiles taken at stations SHL2 and ML show that the lake remained thermally stratified throughout the mooring deployment period (Fig. 1b), with a thermocline located at ~ 25 m depth (Supporting Information Figs. S1a, S2). Dissolved oxygen concentrations measured at SHL2 were above 8 mg L⁻¹ at all depths throughout the study period (Supporting Information Fig. S1b).

The PAR profiles measured at station ML during daytime show steadily decreasing values along the water column to the detection limit of the instrument at ~ 150 m depth (Supporting Information Fig. S2a). The nighttime profile (Supporting Information Fig. S2b) presents small values all along the water column. These are the first PAR measurements that have been taken in a lake down to this depth. The attenuation coefficient of PAR, K<sub>PAR</sub>, was calculated for individual profiles (Supporting Information Fig. S2). Values of K<sub>PAR</sub> ~ 0.15 m⁻¹ indicate that the water in the center of Lake Geneva is clear, with low concentrations of Chl a and suspended materials in the deeper layers (Supporting Information Text S4). This is confirmed by low Chl a values measured below the thermocline (Supporting Information Fig. S1c).

### Backscattering intensity

#### Diurnal backscattering variation

From June 1, 2022 to September 15, 2022, a sound scattering layer (SSL) with BI values ranging ~ 50–63 dB, oscillated on a diurnal time scale between 30 and > 100 m depth (Fig. 2). It moved consistently downward after sunrise, reaching its maximum depth at or shortly after zenith (Fig. 3a,b). Lower BI values were observed over a wider depth range around the maximum depth. Upward migration started when the relative rate of PAR change, Sr, exceeded −0.005 (s⁻¹) (Figs. 2, 3). An asymmetrical BI pattern is evident with the SSL descent being slower than the ascent most of the time (Fig. 3a,b). During nighttime, after the end of the ascent and

(Figure legend continued from previous page.)

**Fig. 1.** (a) Bathymetric map of Lake Geneva, which is surrounded by the Jura and Alps mountain chains. Red triangle: Commission Internationale pour la Protection des Eaux du Léman (CIPEL) limnological survey station SHL2; green triangle: mooring location ML where Acoustic Doppler Current Profiler (ADCP) data were collected; yellow triangle: photosynthetically available radiation (PAR) sensor location GR. Colorbar: depth range. The Swiss coordinate system (CH1903+) is used (SwissTopo, http://www.swisstopo.admin.ch, last accessed September 16, 2024). (b) Schematic of measurement layout. The ADCP and thermistor nodes were mounted on mooring ML. ML profiles were taken at different times of the day, SHL2 profiles were taken close to noon. Dates and times are indicated. For details, see “Field data and analysis” section.
<figure><img src="image_6.png" /><figcaption>**Fig. 2.** Time series of raw Backscattering Index (BI; dB) measured by the 300-kHz Acoustic Doppler Current Profiler (ADCP) at mooring location ML (see Fig. 1) from June 1, 2022 to September 15, 2022. The layer marked by red and white slanted lines near the surface corresponds to the strong scattering surface layer that was not included in the analysis. Black solid line: 6.8°C isotherm. Times of profile measurements at stations SHL2 and ML are indicated by the vertical black and pink dashed lines, respectively. Black boxes (A, B) correspond to time periods that are detailed in Fig. 3.</figcaption></figure>

before the beginning of the descent, values of BI along the water column remained < 50 dB most of the time and have no particular structure. The maximum depth of SSL rarely exceeded the depth of the 6.8°C isotherm (Figs. 2, 3).

A mooring deployment in 2021 with a similar configuration showed comparable BI patterns of well-developed, regular, deep DVM from April to October (Supporting Information Fig. S4).

Sr changes strongly throughout the day (Fig. 3c). As summer progressed, sunrise occurred later and sunset, earlier. After sunrise and before sunset, Sr changes more strongly than at around zenith (Fig. 3c). At around zenith, when the slope of Sr is almost linear, the rate of change also increases as the summer season advances (Fig. 3d).

## Intra-seasonal backscattering variation

BI maximum (maxBI) values extracted for each day exhibit decreasing values with depth during downward migration periods (Fig. 4a), suggesting changes in biomass with depth.

Below 97 m depth, as migration approached its maximum depth, signal variability was too high to determine clear maxBI patterns (discussed below). Furthermore, the range of maxBI values decreased from June to September at all depths, suggesting a continuous biomass decrease (Fig. 4a). Similar patterns are observed for the upward migration period (Fig. 4b).

The corresponding time of maxBI for each day indicates that downward migration starts later as the summer advances (Fig. 4c), in agreement with the intra-seasonal shift in Sr (Fig. 3c). The downward migration time at 37 m depth closely followed the variations in sunrise time after July (Fig. 4e). This agrees with the intra-seasonal shift in Sr (Fig. 3c,d). Note that maxBI at 47 m depth occurs later after sunrise than at 37 m depth (Fig. 4e; Supporting Information Table S1). The same intra-seasonal pattern is also found at deeper depths.

The timing of maxBI is less clear for the upward migration, showing a wider scatter (Fig. 4d). Migration appears to be less correlated with the intra-seasonal change in sunset timing
<figure><img src="image_7.png" /><figcaption>**Fig. 3.** (a, b) Upper panels: photosynthetically available radiation (PAR; µmol photons m⁻² s⁻¹) measured at station GR (gray: 1-min values, red: 2-h mean. For station location, see Fig. 1). Middle panels: Sr (s⁻¹), the relative rate of PAR change (gray: 1-min values, red: 2-h mean), and Sr value of -0.005 s⁻¹ (horizontal purple line). Lower panels: patterns of BI from the 300-kHz ADCP (black curve: 6.8°C isotherm) for selected time periods: (a) June 18–20, (b) July 21–23 (corresponding to black boxes marked A, B in Fig. 2). Vertical black solid lines: times of local sunrise and sunset; vertical black dotted lines: time of zenith; vertical purple dashed lines: times at which Sr is -0.005 min⁻¹. (c) Monthly mean of relative rate of PAR change, Sr (2-h mean) and (d) corresponding mean slopes computed between 9:00 and 18:00. Colors are identified in the legend.</figcaption></figure>

(Fig. 4f; Supporting Information Table S1). The absence of out-
liers on the left side of the whiskers in the downward migra-
tion, and on right side of the whiskers in the upward migration
(Fig. 4c,d) confirms that there is a light-intensity threshold that
controls DVM (discussed below).

Vertical velocities

Diurnal variation

The time series of vertical velocities w between 32 and
~100 m depth, measured by the moored ADCP, show alter-
nating narrow bands of upward and downward velocities
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(Figure legend continues on next page.)
ranging from ~0.002 to 0.006 m s⁻¹ on a daily timescale (Fig. 5a; full season in Supporting Information Fig. S3). Vertical velocities are predominantly downward in the morning and upward in the afternoon. Velocity bands match the downward and upward movement of the SSL pattern (Figs. 2, 3) and are consistently repeated throughout the entire time series. Patches of missing values (due to low scatterer concentration; white areas) during nighttime coincide with low values in the BI profiles (Figs. 2, 3).

## Intra-seasonal variation

Monthly mean maxw depth profiles indicate that upward velocities are systematically higher than downward ones throughout the summer and at all depths with a slight increase in speed in the late summer (Fig. 5b). Mann-Whitney U test results, with a *p*-value < 0.05, indicate that the velocity difference between the two migration periods is statistically significant. This reveals migration pattern asymmetry with faster migration rates in the upward direction as confirmed by vertical SSL propagation converted into time after sunrise and before sunset (Fig. 5c). Furthermore, estimates of average upward (4.9 × 10⁻³ m s⁻¹) and downward (−2.4 × 10⁻³ m s⁻¹) SSL displacement velocities between 32 and 97 m depth (Fig. 4c,d) are of the same order of magnitude as the mean of the monthly downward and upward velocities maxw (Fig. 5d; Supporting Information Table S2). The profile shape is also significantly different, but does not change during summer, that is, downward velocities are nearly constant over most of the depth and decrease only slightly in the lowest layers when approaching maximum depth, whereas upward velocities continually increase from the onset of upward migration (Fig. 5b).

Monthly-averaged mean values of maxw and the monthly-averaged relative rate of PAR change, Sr, present comparable intra-seasonal variability with slope values decreasing from June to July, and thereafter increasing toward September (Fig. 5d). Significant correlations were observed between Sr slope values and the rates of downward (*R* = 0.99) and upward (*R* = 0.94) migrations (Fig. 5d). These results indicate that intra-seasonal variations in migration rates are likely associated with intra-seasonal Sr changes (discussed below). As days become shorter, the rate of PAR change increases, leading to faster downward and upward migrations.

It appears that upward migration started at about the time when $Sr = -0.005 s^{-1}$ (Fig. 3a,b). This was further investigated by determining the time of the day this Sr value was reached. The maxw values at that time and corresponding depths were then extracted, and monthly mean values and standard deviations were calculated. Even though there is some scatter and a slight variation between mean values for different months (Fig. 5e), migrators were usually close to 90 m depth at ~17:00 when $Sr = -0.005 s^{-1}$. Thus, upward migration started well after downward migration had terminated at zenith.

## Zooplankton abundance

Figure 6 displays the abundance of zooplankton per species and per depth layers (average of vertical tows over 50-m thick layers) measured at SHL2 at around noon on five different days during the mooring deployment. These measurements represent “snapshots” of the zooplankton community at approximately midday, and therefore cannot provide a complete picture of the diurnal or intra-seasonal dynamics of zooplankton. However, they give an indication of the zooplankton distribution in the water column, which can be matched with the acoustic data.

The total zooplankton abundance and the composition of the zooplankton community varied with depth during the summer season (Fig. 6). In the 0–50 m depth layer, the community was dominated by calanoid copepod *Eudiaptomus gracilis* (> 40% of the total abundance), followed by cyclopoid copepod *C. prealpinus* and the cladoceran *D. longispina*, each contributing ~ 25% (Fig. 6a). From June 21 to August 31, the abundance of *E. gracilis* increased from ~ 4000 to ~ 10,000 ind m⁻² and from ~ 1600 to ~ 4600 ind m⁻² for *C. prealpinus*. At the same time, the abundance of *D. longispina* decreased from ~ 4200 to ~ 1800 ind m⁻² (Fig. 6b). This zooplankton composition is similar to previous CIPEL observations (CIPEL 2022), indicating that the conditions during our study are typical for the summer season in Lake Geneva.

From 50 to 100 m depth, cyclopoid *C. prealpinus* was the dominant species accounting for > 70% of the total abundance, with values ranging from ~ 4700 to ~ 8200 ind m⁻² (Fig. 6a,b). *Eudiaptomus gracilis* and *Eubosmina longispina* each contributed

(Figure legend continued from previous page.)

**Fig. 4.** Intra-seasonal and depth variability of maximum Backscatter Intensity, maxBI, extracted from the BI time series measured by the 300-kHz Acoustic Doppler Current Profiler (ADCP) for each day from June 1, 2021 to September 15, 2021. Left column: downward migration (morning); right column: upward migration (afternoon). (a, b) Box plots of maxBI for each day show a decrease with depth and as the summer season advances. (c, d) Corresponding time of maxBI for each day display the same depth/seasonal pattern as maxBI in (a) and (b). Colorbar: intra-seasonal range of the day of the measurement. The red line in each box indicates the median and thus the median profiles for the whole summer season; left and right edges of the box, 25th and 75th percentiles. Whiskers extend to 1.5 times the interquartile range. (e, f) Time of maxBI (gray dots) for each day from June 1 to September 15 at 37 and 47 m depth and local sunrise/sunset (black dotted line). Note that maxBI at 47 m depth occurs later after sunrise than at 37 m depth. Regression lines and corresponding slopes for the time of maxBI computed between July 1 and September 15 are shown with gray solid lines, and in red solid lines for the local sunrise/sunset. Slope values and regression coefficients for each depth bin between 37 and 92 m depth are given in Supporting Information Table S1.
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**Fig. 6.** (a) Histograms of the relative proportion (in % of the total abundance) of each species to the total abundance per day (dates in 2022 are indicated on the top right side) and per depth layer (left side) sampled at station SHL2 (for location, see Fig. 1). The bars are color-coded according to the species given in the legend. Red dots: total abundance (red horizontal axis on top, in ind m⁻²) at each depth layer for each day. (b) Abundance (in ind m⁻²) of the zooplankton species per day and per depth layer, sampled at SHL2. The bars are color-coded corresponding to the sampling dates given in the legend. Bars outlined in black: abundance of juveniles in the sample. A zoom is shown for *Leptodora kindtii* and *Bythotrephe longimanus* due to their low abundance. (c) Ratio between adults and juveniles for *Cyclops prealpinus* in depth layers 0–50 m (black solid line) and 50–100 m depth (blue dotted line).

~ 10%. The contribution of *D. longispina* to the total community in this depth layer remained < 2%.

From 100 to 150 m depth, the total abundance was the lowest with values < 1100 ind m⁻² (Fig. 6a). The dominant species in this depth range was again *C. prealpinus*, which showed a decreasing trend in abundance as the summer progressed (Fig. 6a,b). Cladocerans *Leptodora kindtii* and *Bythotrephe longimanus* abundance was consistently low (< 2%) at all depth layers and times considered (Fig. 6a,b).

For *C. prealpinus*, the ratio of “adults” to “juveniles” changes in layers 0–50 and 50–100 m (Fig. 6c). In the 0- to 50-m layer, the adult to juvenile ratio remained < 0.6

throughout the season, indicating that juveniles dominated over adults. The opposite was observed in the 50–100 m depth layer, with a ratio always > 5 throughout the season, indicating that adults dominated the *C. prealpinus* population (Fig. 6b,c). In addition, the ratio showed an intra-seasonal decrease from June 21 to July 7, followed by a gradual twofold increase until August 31 (Fig. 6c). In the images of the different organisms and their depth distribution (Fig. 7), an increase in average size from the near surface layer to the maximum DVM depth layer is evident, with *C. prealpinus* being the only species in the deepest layers.

(Figure legend continued from previous page.)

**Fig. 5.** Intra-seasonal and depth variability of vertical velocity. (a) Time series of raw vertical velocity (w, m s⁻¹) measured by the 300-kHz ADCP at mooring ML (see Fig. 1) from July 10, 2022 to July 20, 2022. Data from the surface to 30 m depth were removed. Positive values: upward motion. The entire time series from June 1, 2022 to September 15, 2022 is shown in Supporting Information Fig. S3. (b) Monthly mean profiles of maxw (m s⁻¹) measured by the ADCP for the downward and upward migrations. Lines: mean values; shaded areas: variance intervals for each month. Color legend: month. (c) Scatter plots of the time of maxBI for each day at each depth (from Fig. 4c,d; color-coded) converted into minutes after sunrise and before sunset. Black circles: mean values for each depth; bars: corresponding standard deviations. Blue solid line: regression line through mean values (R = 0.78). The gray solid line is the 1:1 line. Colorbar: depth range. (d) Monthly mean values of maxw (m s⁻¹) for the downward (black solid line) and upward (black dashed line) migration, and monthly mean values of Sr slopes from Fig. 3d (red solid line). Correlation coefficients R are between monthly mean maxw values and Sr slopes. (e) Relation between monthly mean maxw in different depth layers (color) and depth of maxw when Sr = -0.005 s⁻¹ as a function of different months. Legend: month and depth range.
<figure><img src="image_17.png" /><figcaption>**Fig. 7.** Examples of zooplankton organisms from the ZooScan imagery, representative of the samples collected on July 5, 2022, for different layers in the water column and their length. The legend identifies the different species. Images were selected based on good contrast and sharp focus.</figcaption></figure>

Discussion

The results demonstrate for the first time that during the summer season, zooplankton DMV in a large, deep lake (Lake Geneva) reached below 100 m depth every day. Below, the driving/limiting mechanisms related to this deep DVM are discussed.

DVM and zooplankton abundance

DVM pattern determined from acoustic backscattering

Time series of BI and associated vertical velocities showed SSL migration patterns that indicate regular DVM down to more than 100 m depth in summer 2022 (Figs. 2–5; Supporting Information Fig. S4). The daily BI pattern does not change much during the summer. This allowed for a sound analysis of the characteristics of the DVM, in particular its intra-seasonal variability related to light intensity levels, and the time of sunrise and sunset. These recordings and the results of the present analysis confirm that ADCP-generated BI monitoring is an excellent tool for determining and characterizing zooplankton deep DVM dynamics over extended periods.

Zooplankton characteristics determined from net sampling

Based on net samples, the total abundance of zooplankton in Lake Geneva decreased with depth (Fig. 6b). In the 0–50 m depth layer, the zooplankton community was mostly composed of copepods *E. gracilis* (> 40% of the total abundance) and *C. prealpinus* (25%) and cladoceran *D. longispina* (25%) (Figs. 6a,b, 7). These species are characteristic of the zooplankton community in the upper layer of Lake Geneva (Angeli et al. 1995; CIPEL 2022) and are comparable to those of Lake Constance (Stich 1989; Huber et al. 2011).

In the 50- to 100-m depth layer, *C. prealpinus* was by far the most abundant species (> 70% of the total abundance) at around midday (Fig. 6a,b). The population of *C. prealpinus* in this depth layer was dominated by adults (Fig. 6b,c, 7), that is, individuals longer than 1 mm corresponding to development stages IV, V, and adulthood. Copepods were found at depths of up to 300 m in the ocean (Hure et al. 2022).

Given the significantly higher abundance of adult *C. prealpinus*, the backscattering signal observed between 50 and 100 m depth can be attributed to them. This is supported by the correlation coefficient of 0.75 obtained between the abundance of *C. prealpinus* and the BI values
averaged in this depth layer (Supporting Information Fig. S5); however, since *p* = 0.14, it is not significant. This is mainly due to the limited net sampling database. Although *C. prealpinus* profiles best fit maxBI profiles and thus give additional support beyond regression, some uncertainty remains and requires further investigation, in particular by increasing the number and depth resolution of net samples. Huber et al. (2011) and Rinke et al. (2007) obtained a good correlation between ADCP backscattering and zooplankton distribution when detailed net sampling was conducted. The 300-kHz ADCP used here is an appropriate tool to study cyclopoid copepod DVM (Lavery et al. 2010).

## DVM timing

The observed DVM follows the diurnal cycle of light intensity (Fig. 3). This is confirmed by the timing of maxBI during the downward migration, which shows a good correlation with the local sunrise (Fig. 4e) and exhibits the same intra-seasonal variation at all depths (Supporting Information Table S1). Downward migration and thus maxBI occurs later in the morning as the summer season advances (Fig. 4c). Such a pattern is not as clear for the timing of the upward migration, which has wider scattering and poorer correlations of maxBI with the local sunset (Fig. 4d,f; Supporting Information Table S1), suggesting that another factor may control the timing of the upward migration (discussed below). Overall, these results are consistent with previous studies that reported that the duration of the migration cycle usually corresponds to light intensity changes (Ringelberg 1999; Cohen and Forward 2005a).

The data show that the maximum DVM depth is reached at around zenith, and therefore at RRC values approaching 0 s⁻¹ (Fig. 3). These results imply that *C. prealpinus* migrate downward as long as RRC > 0 s⁻¹. They stop their descent at about zenith or slightly thereafter and remain at that depth as long as RRC ranges between 0 and -0.005 s⁻¹, thus entering a dispersal phase. Ringelberg (2010) pointed out that dispersion sets in after migration stops, that is, zooplankton swim in different directions resulting in a more diffusive distribution during this phase, whereas vertical swimming during DVM concentrates animals. This agrees with the lower BI during this phase over a wider depth range (Figs. 2, 3). Zooplankton then migrate upward when RRC > -0.005 s⁻¹.

Both absolute light and the relative rate of light change have been proposed as exogenous control parameters in the migration of crustacean zooplankton (Forward 1988; Ringelberg 1999; Frank and Wider 2002). Ringelberg (1999) suggested RRC as a stimulus for migration if it exceeds a certain threshold value, called the rheobase. According to this hypothesis, migrators should ascend in the water column when exposed to species-specific relative rates of light decrease above the rheobase. The afternoon ascent starts when the rheobase exceeds ~ -0.005 s⁻¹, suggesting that *C. prealpinus* is sensitive to RRC as low as this value (Fig. 3a,b). This explains

why the timing of the upward migration is not closely related to the timing of local sunset (Fig. 4f; Supporting Information Table S1).

The pattern is less evident on cloudy days such as on 23 July, when Sr varied strongly and the rheobase value was reached on multiple occasions throughout the day (Fig. 3b). Although the light pattern did not match its “typical” daily pattern, DVM followed its typical diurnal pattern, and showed a stronger coherent upward BI signal (Fig. 3b). These observations suggest that endogenous circadian rhythms also play a role (Bandara et al. 2021). Endogenous circadian clocks were found not to be entirely accurate and thus need to be “trained” (calibrated) by exogenous cues, such as the change in ambient irradiance (e.g., Zeng et al. 1996).

No rheobase values for *C. prealpinus* exist in the literature. Our proposed value of -0.005 s⁻¹ is intermediate with respect to the rheobase observed for *Daphnia* spp. (-0.0017 s⁻¹, Ringelberg 1964) and for the zoea of the crab *Rhithropanopeus harrisii* (-0.0044 to -0.0086 s⁻¹, Forward 1985), and is similar to the rheobase of the calanoid *Calanopia americana* (-0.0046 s⁻¹, Cohen and Forward 2005b). It could also be hypothesized that *C. prealpinus* follows specific isolumes (i.e., levels of constant light) during the descent, as is the case for *R. harrisii* (Forward 1985). However, the nonlinear rate of Sr change during downward migration (Fig. 3c) is not reflected in the observed constant speed of downward motion throughout the summer (Fig. 5b). Further laboratory and field measurements are needed to assess the role of RRC and/or of isolumes in the start of the descent and the deep migratory pattern of *C. prealpinus*.

## Amplitude limitations of DVM

### Seasonal variability

The summer 2022 recordings show that the depth of deep DVM changes little during the summer (Fig. 2). However, it is evident from recordings taken in 2021 at mooring ML (Supporting Information Fig. S4) that a clear, deep DVM was already established in April (spring) albeit with weaker BI strength than in summer. DVM also continued into Fall (October, Supporting Information Fig. S4). In early spring and late fall, the maximum migration depth is shallower than in summer (Figs. 2, 3). This is due to lower light levels and later sunrise and earlier sunset times in those seasons. The progressive decrease in BI strength from mid-August to September in 2022 (Fig. 2) and October in 2021 (Supporting Information Fig. S4) suggests that the abundance of the migrating zooplankton decreased into the fall.

### Role of light

Previous literature suggested that both absolute light and RRC serve as exogenous cues in the migration of crustacean zooplankton. In the present case of *C. prealpinus*, RRC was identified as a factor controlling the end of its descent and the start of its ascent (Fig. 3). This implies that *C. prealpinus* is
capable of perceiving light at the depth where it stops its descent (maximum depth ~ 125 m; Fig. 2). Photosynthetically available radiation profiles (Supporting Information Fig. S2) show values ranging between $10^{-5}$ and $10^{-4}$ µmol photons m$^{-2}$ s$^{-1}$ at 125 m depth. The results suggest that *C. prealpinus* can detect and respond to these low light levels.

PAR values measured at 125 m depth and above during daytime are higher than the visual thresholds of zooplankton (~$10^{-7}$ µmol photons m$^{-2}$ s$^{-1}$) reported in the literature (Swift and Forward 1983; Stearns and Forward 1984; Buskey et al. 1989). Visual threshold values are not available in the literature for *C. prealpinus* but can be expected to be similar. The measured levels of available PAR along the water column until 125 m depth during daytime can therefore be perceived by *C. prealpinus* in clear water. However, when water clarity decreases, the maximum depth of DVM also decreases, as can be seen for the 1-week period after 27 July 2022 when the background intensity of BI increases in the whole water column (Fig. 2; Supporting Information Fig. S3). This event may have been caused by the advection of turbid Rhône River water (Piton et al. 2022).

## Role of oxygen

In addition to light intensity, dissolved oxygen concentration is thought to play a role in vertical zooplankton migration, since low oxygen areas can serve as a refuge against fish predation (Kobayashi and Gonoi 1985; Wright and Shapiro 1990). Wright and Shapiro (1990) reported that the downward migration by zooplanktivore fish predators is restricted by an oxygen concentration of ~3 mg L$^{-1}$. However, in the present case, dissolved oxygen values remained > 8 mg L$^{-1}$ from the surface down to 150 m depth throughout the study period (Supporting Information Fig. S1b). This indicates that the availability of dissolved oxygen in Lake Geneva during summer period 2022 did not affect DVM depth.

Temperature (Supporting Information Text S2), predation, and kairomones (Supporting Information Text S3) are also considered to play a role in DVM dynamics. However, information about their role is not available for Lake Geneva.

## Migration rates

The mean speeds of downward ($-3.5 \times 10^{-3}$ m s$^{-1}$) and upward ($4.3 \times 10^{-3}$ m s$^{-1}$) migration computed from maxw (Supporting Information Table S2) are comparable with measured cyclopoid zooplankton swim speeds (between 1.0 and $5.0 \times 10^{-3}$ m s$^{-1}$; Strickler 1975).

The asymmetry in migration rates and vertical speeds in Lake Geneva is evident with faster upward migration compared to downward migration throughout the summer season (Figs. 4, 5; Supporting Information Table S2). At ~17:00, migrators are still at ~90 m depth (Fig. 5e). The time interval from ~17:00 to sunset to reach the surface layer is much shorter than the time interval of the descent to maximum depth between sunrise and zenith, resulting in the difference

in vertical velocities. Downward speed is nearly constant over the depth range, whereas it continuously increases in the upward motion (Fig. 5b). These results could support the hypothesis that *C. prealpinus* does not follow isolumes during migration, but instead is sensitive to RRC, as discussed above. The observed increase in migration rates with progressing summer season (Supporting Information Table S2; Fig. 5b,d) could also be attributed to the progressive increase in the ratio of adult *C. prealpinus* to juveniles within the 50- to 100-m depth layer (Fig. 6c); adult cyclopoids have better swimming abilities than juvenile cyclopoids (Mauchline 1998).

## Significance of deep DVM

DVM generates active vertical transport in the water column due to the movement of large numbers of zooplankton. They release surface-derived carbon and nutrients as respiratory CO$_2$ and other excretory waste products at depth (Longhurst and Harrison 1988; Steinberg et al. 2000; Bianchi et al. 2013), which in turn can enhance the efficiency of the biological pump (e.g., Buesseler and Boyd 2009). This vertical export of organic carbon to deeper waters therefore can contribute to buffering global warming effects (Bandara et al. 2021). In the ocean, this process is estimated to account for 15-40% of the total global organic carbon export from the surface (Bianchi et al. 2013; Aumont et al. 2018). Furthermore, deep DVM reduces the availability of nitrogenous compounds to phytoplankton in surface waters due to zooplankton excretion at depth (Longhurst and Harrison 1988).

At present, zooplankton abundance and its effect on the biological pump in Lake Geneva may be underestimated since only the upper 50 m of the water column are usually considered, whereas DVM reaches below 100 m depth. Therefore, this may greatly extend the range and the efficiency of the biological pump. Furthermore, at present, zooplankton are most often sampled close to noon when, due to the deep DVM, a large fraction of the zooplankton community may already have migrated below 50 m depth (Fig. 6). Consequently, traditional sampling protocols (down to 50 m depth) cannot capture the entire zooplankton community, and thus should be revised. In addition, the present results should be considered when interpreting data for Lake Geneva based on the current sampling protocol.

## Summary and conclusions

The results of this field study provide unique insight into the deep DVM of crustacean zooplankton in a large, deep, temperate lake. Acoustic data collected at a mooring in the center of Lake Geneva over a period of 107 d during summer 2022 captured, for the first time in a lake, regular large vertical amplitudes (~100 m) of nocturnal DVM. Net sampling allowed the characterization of the zooplankton population responsible for this migration. From simultaneous measurements
of vertical speed, light, temperature and dissolved oxygen, the zooplankton migration rates and the factors triggering and limiting DVM during the summer season could be determined. The analysis revealed that:

* During summer 2022, a nocturnal DVM took place daily in the pelagic zone of Lake Geneva from the surface down to ~100 m (max. 125 m) depth, as was also evident in mooring data from 2021.

* The descent of the migrators from the near-surface waters to greater depths began shortly after sunrise, and their ascent back to the near-surface waters began at ~17:00 (CET). The daily timing of the downward migrations closely followed the intra-seasonal changes in sunrise time. The intensity of this DVM decreased as the summer season advanced.

* Daytime zooplankton net samples from the surface down to 150 m depth revealed that mainly adult cyclopoid copepods *C. prealpinus* correlate with this deep DVM.

* The end of the descent of *C. prealpinus* was related to low RRC values ranging between ~0 and -0.005 s⁻¹. The time that the ascent begins depends on a threshold of RRC. We were able to determine a threshold (rheobase) value of -0.005 s⁻¹ for *C. prealpinus* for which at present, no threshold value is given in the literature.

* Asymmetrical migration rates were measured, with faster upward than downward rates. Furthermore, migrations rates varied throughout the season with slowest rates in July, and fastest rates in September. These changes were found to be linked to the intra-seasonal changes in RRC. However, the increasing proportion of adult *C. prealpinus* (which are stronger swimmers) within the zooplankton population as the season advanced may have also contributed.

* Adequate levels of light (PAR) and oxygen were available throughout the water column, indicating that those factors do not limit the vertical extent of the DVM.

This newly gained knowledge is important since deep DVM migration plays a role in the functioning of the lake biological pump, that is, zooplankton actively transport surface-derived carbon and nutrients to deeper waters where they are released as respiratory CO₂ and excretory waste products, thus buffering global warming effects. The results of this study should be taken into consideration in the development of sampling protocols and effective lake management concepts for Lake Geneva and similar deep lakes and water bodies.

## Data availability statement

In situ samples at SHL2 were collected and processed by the long-term Observatory and experimentation on LAkes (OLA). Data from integrated samples, covering the depth range of 0–50 m, are stored and made available by the © OLA-IS,

AnaEE-France, INRAE of Thonon-les-Bains, CIPEL. The in situ data of this study are archived on Zenodo (Piton et al. 2024).

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Acknowledgments

The authors would like to thank Karsten Rinke and the anonymous reviewers for their constructive comments and suggestions that helped improve the manuscript, as well as CIPEL for providing data.

Conflict of Interest

None declared.

Submitted 04 December 2023

Revised 29 March 2024

Accepted 26 October 2024

Associate editor: Maren Striebel