# Small in the heat, transparent in the bloom: copepod morphological responses in the California upwelling ecosystem

Rubén Tournier-Broer, Sakina Dorothée-Ayata, Tristan Biard

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Rubén Tournier-Broer, Sakina Dorothée-Ayata, Tristan Biard. Small in the heat, transparent in the bloom: copepod morphological responses in the California upwelling ecosystem. Journal of Plankton Research, 2026, 48 (1), pp.fbaf070. 10.1093/plankt/fbaf070. hal-05502057

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1 **Title**

2 Small in the Heat, Transparent in the Bloom: Copepod Morphological Responses in the

3 California Upwelling Ecosystem

4

5 **Authors**

6 Rubén Tournier-Broer 1*

7 Sakina Dorothée-Ayata 2,3 #

8 Tristan Biard 1,3 #

9 #contributed equally as co-last authors.

10

11 **Affiliation**

12 1. Laboratoire d'Océanologie et de Géosciences, Université du Littoral Côte d'Opale,
13 Université de Lille, CNRS, IRD, UMR 8187, Wimereux, France

14 2. Sorbonne Université, MNHN, CNRS, IRD, Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques, LOCEAN, F-75005 Paris,
15 France
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17 3. Institut Universitaire de France (IUF), Paris, France

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19 *Correspondence: ruben.tournier-broer@univ-littoral.fr

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21 **Running head**

22 Upwelling copepod morphology
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**Key words**

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Copepods, Traits Ecology, Imagery, Upwelling Ecosystem

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**Abstract**

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Copepods are central to marine food webs as they link primary producers to higher trophic levels. This study used in situ images collected with an Underwater Vision Profiler during four cruises (2008, 2012, 2014, and 2016) in the California Current Ecosystem to investigate how copepod morphologies relate to environmental conditions. Consistent with Bergmann's rule, our results indicate that smaller copepods were associated with warmer environments.

Copepods with more complex body shapes, owing to extended appendages, were observed in waters with higher fluorescence and diatom concentrations. Finally, more transparent copepods were found in shallower waters with higher fluorescence, potentially suggesting predatory avoidance of darker copepods found deeper in the water column. These findings support the power of imaging-based functional trait-based approaches to link zooplankton morphological variability with environmental gradients, enhancing our understanding of zooplankton dynamics in productive upwelling systems.

**Introduction**

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Mesozooplankton are important in marine ecosystem functioning by linking primary producers to higher trophic levels while contributing to the biological carbon pump (Steinberg and Landry, 2017; Brandão et al., 2021). Traditionally studied using taxonomic approaches, recent studies have stressed the relevance of focusing on functional traits (Martini et al., 2021), i.e., individual characteristics influencing organismal fitness (Violle et
al., 2007). Mesozooplankton functional traits can be classified into four categories: physiological, life history, behavioural, and morphological (Litchman et al., 2013). Among the many ways to measure traits, imaging techniques enable the automated measurement of morphological descriptors (e.g., size, transparency, complexity, and shape) at the individual level (Martini et al., 2021; Orenstein et al., 2022). In situ imaging additionally enables direct observation of organisms in their natural habitats (Ohman, 2019). It prevents morphological damage caused by traditional sampling methods (e.g., physical perturbations by nets or formalin fixatives; Beaulieu, 1999; Picheral et al., 2010; Ohman, 2019; Martini et al., 2021).
Copepods often dominate mesozooplankton abundance and biomass. Trait-based approaches applied to copepods have primarily investigated body size (Litchman et al., 2013). Copepods are typically smaller in warmer environments, as described by Bergmann's rule (Campbell et al., 2021), and during lower food conditions (Blake and Marshall, 2023). In situ imaging of Arctic copepods revealed darker individuals at the ice edge, due to increased gut contents and red pigmentation (Vilgrain et al., 2021). Conversely, in ice-free waters, more complex shapes were observed because of visible appendages. Similar images from the Sargasso Sea revealed that smaller copepods had weaker amplitudes of diel vertical migration (DVM) compared to larger organisms (Barth et al., 2023). While copepod morphological-based approaches have been applied to polar and oligotrophic ecosystems, there is a lack of studies investigating morphological traits in productive and dynamic regions such as upwelling systems.
Eastern Boundary Upwelling Systems (EBUS) are highly productive wind-driven upwelling regions shaped by equatorial currents (Fréon et al., 2009). These continuous upwellings create sharp environmental gradients, ranging from cold, high-nutrient water near the coast to warm, oligotrophic conditions offshore up to several hundred kilometres (Kämpf and Chapman, 2016). The elevated phytoplankton production resulting from the upwelled nutrients is typically sharper at the surface, above the Mixed Layer Depth (MLD) (Ohman et
al., 2013; Sallée et al., 2021). One of the four main EBUS is the coastal region of the California Current Ecosystem (CCE) (Checkley and Barth, 2009). Despite extensive investigations of zooplankton communities in the CCE, trait-based studies of copepods in the CCE have mainly focused on the relationship between body size and DVM (Ohman and Romagnan, 2016), ignoring the full spectrum of morphological traits.

By studying in situ imaging data of surface copepods from the CCE, our study aimed to test two hypotheses. We expected (1) smaller copepods with increasing temperatures following Bergmann's rule (Campbell et al., 2021) and (2) darker copepods in waters with higher fluorescence and prey concentrations because of increased gut content (Vilgrain et al., 2021).

## Material and Method

Data were collected during four CCE-LTER cruises held in September-October 2008 (P0810), July-August 2012 (P1208), August-September 2014 (P1408), and April-May 2016 (P1604) (Fig. S1). The detailed methodology is provided in the Supporting Material. Briefly, each month-long cruise used a quasi-Lagrangian design tracking a drifting line and comprised 3-6 water-mass “cycles”. Replicate CTD-rosette profiles (0-500 m) were sampled during the day and night. The environmental data included continuous vertical profiles of temperature, salinity, conductivity, oxygen, fluorescence, and particle concentration. Discrete samples of nitrate, phosphate and silicate were interpolated to continuous profiles. The surface layer for each profile was defined as the deepest value among three metrics: euphotic depth from the fluorescence profile, euphotic depth from the Photosynthetically Active Radiation (PAR) profile, and mixed layer depth from the potential density profile (Fig. S2; Panaïotis et al., 2023). Phytoplankton and picoplankton abundances were measured concurrently using epifluorescence microscopy and flow cytometry following CCE-LTER process cruises methodology.
96 Zooplankton images were captured in situ with an Underwater Vision Profiler 5 (UVP5)
97 mounted to the CTD-rosette, recording images every 20 cm during descent (~1 m s⁻¹). Images
98 were processed using the Zooprocess software (Gorsky et al., 2010) and uploaded to the
99 EcoTaxa web platform (Picheral et al., 2017). A random forest classifier provided
100 preliminary identifications of copepod images (Irisson et al., 2022), which were then
101 validated by human annotators, resulting in a total of 4,687 individual copepod images for the
102 surface layer, with body lengths ranging from 1,000 to 9,800 µm. Morphological analysis
103 was performed following Vilgrain et al. (2021) using 16 morphological descriptors related to
104 size, shape, opacity, and complexity, and calculated using the ZooProcess software (Gorsky
105 et al., 2010; Table S1). Transparency descriptors were standardised to account for different
106 versions of the UVP used across cruises (Fig. S3). A weighted Principal Component Analysis
107 (PCA) was performed on the Yeo-Johnson transformed and scaled morphological descriptors
108 to define a morphological space. The significant principal components (eigenvalue >1) were
109 interpreted as synthetic morphological traits. Environmental and categorical variables were
110 then projected to the PCA space as complementary variables.
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112 Results

113 Four significant Principal Components (PCs) described the morphological space of surface
114 copepods (Fig. 1-2; Fig. S4). The first two axes of the morphological space explained 60% of
115 the total variance (Fig. 1A). PC1 (40.7% of the variance) distinguished between smaller (PC1
116 < 0) and larger copepods (PC1 > 0). The anti-correlation between size and circularity along
117 PC1 could be attributed to pixel resolution, with smaller copepods being more circular. PC2
118 (19.3% of variance) distinguished between less elongated copepods with more complex
119 shapes, mostly due to deployed antennae (PC2 < 0), and more elongated copepods with no
120 visible appendages (PC2 > 0). The third and fourth axes explained 28.4% of the total variance
and represented body transparency (Fig. 2A). PC3 (16.7% of variance) distinguished between transparent copepods with narrower shapes (PC3 < 0) compared to darker and wider ones (PC3 > 0). PC4 (11.7% of variance) distinguished between copepods with more heterogeneous (PC4 < 0) and more homogeneous grey levels (PC4 > 0) (Fig. S4).

Larger copepods were observed at night in 2008 and 2014 (Fig. 1A). Copepod morphological variations were correlated with abiotic variables (Fig. 1B; Fig. 2B). Smaller copepods (PC1 < 0) were associated with warmer temperatures, whereas larger copepods (PC1 > 0) were associated with colder ones (see all significant correlations in Table S2). Copepods with more complex shapes and visible antennae were observed when fluorescence was higher (PC2 < 0). Conversely, elongated copepods with a torpedo shape (PC2 > 0) were associated with lower fluorescence. Finally, more transparent copepods were observed in more oxygenated and saltier waters (PC3 < 0) and at shallower depths (PC4 > 0). Nitrate, phosphate, and silicate exhibited mostly significant but weak associations with the morphological variables.

The morphological variations of surface copepods were also correlated with biotic variables (Fig. 1C; Fig. 2C). Larger copepods with more complex shapes (PC1 > 0 and PC2 < 0) were associated with higher abundances of potential prey (dinoflagellates and diatoms), small eukaryotes, and bacteria (Fig. 1C). More transparent copepods with more homogeneous grey levels (PC3 < 0 and PC4 > 0) were associated with higher abundances of heterotrophic and autotrophic (*Synechococcus*) bacteria (Fig. 2C). Notably, along all morphological axes, *Synechococcus* and diatoms (i.e., abundance of phytoplankton communities) were strongly correlated with fluorescence, which supports a potential link between copepod morphology and productivity.
<figure><img src="image_2.png" /><figcaption>Fig. 1. First two dimensions of the morphological space of surface copepods in the California Current Ecosystem. The first two significant axes of the PCA (PC1 and PC2), constructed from 16 individual morphological variables of 4,687 individuals, are represented. A subset of</figcaption></figure>

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the copepod images is displayed according to their positions in the morphological space. To do so, we divided the morphological space into a regular 20-by-20 grid. For each grid cell, the copepod image closest to that position was selected and displayed at the corresponding grid point using the `morphr` package (https://github.com/jiho/morphr). The arrows in panel A represent morphological variables coloured by their type: complexity, shape, size, and transparency. The symbols in panel A represent categorical supplementary variables (sampling season and diel). The arrows in panels B and C represent continuous supplementary abiotic (B) and biotic (C) variables. Variables were plotted if they sufficiently contributed to the morphological space, with a threshold of 10% for morphological trait contribution to PCs and for supplementary variable correlation to PCs. Temp: temperature, Sal: salinity, Oxy: oxygen, Flu: fluorescence, Bact: heterotrophic bacteria, Syne: Synechococcus, Pico: picoeukaryotes, Prymn: prymnesiophytes, Cili: ciliates, A_Dino: autotrophic dinoflagellates, H_Dino: heterotrophic dinoflagellates, H_Euk: heterotrophic eukaryotes.
<figure><img src="image_3.png" /><figcaption>Fig. 2. Third and fourth dimensions of the morphological space of surface copepods in the California Current Ecosystem. The last two significant axes of the PCA (PC3 and PC4), constructed from 16 individual morphological variables of 4,687 individuals, are represented.</figcaption></figure>
A subset of the copepod images is displayed according to their positions in the morphological space. To do so, we divided the morphological space into a regular 20-by-20 grid. For each grid cell, the copepod image closest to that position was selected and displayed at the corresponding grid point using the `morphr` package (https://github.com/jiho/morphr). The arrows in panel A represent morphological variables coloured by their type: complexity, shape, size, and transparency. The symbols in panel A represent categorical supplementary variables (sampling season and diel). The arrows in panels B and C represent continuous supplementary variables, respectively abiotic (B) and biotic (C) variables. Variables were plotted if they sufficiently contributed to the morphological space, with a threshold of 10% for morphological trait contribution to PCs and for supplementary variable correlation to PCs.

Temp: temperature, Sal: salinity, Oxy: oxygen, Flu: fluorescence, Nitrate: NO3, Phosphate: PO4, Silicate: SiOH4, Bact: heterotrophic bacteria, Syne: *Synechococcus*, Pico: picoeukaryotes, H_Euk: heterotrophic eukaryotes.

## Discussion

Using in situ imaging, we described the morphological space of surface copepods in the CCE. The proportion of morphological variation explained by each axis of the morphological space was within a similar range as that in similar studies (e.g., Vilgrain *et al.*, 2021; Barth *et al.*, 2023; Perhirin *et al.*, 2024). The first morphological axis reflected copepod body size, which is consistent with earlier applications of comparable morphological space approaches in Arctic copepods (Vilgrain *et al.*, 2021) and Sargasso Sea zooplankton (Barth *et al.*, 2023; Perhirin *et al.*, 2024). The second morphological axis captured elongation and body complexity, mostly because of appendage visibility, whereas transparency variations were represented along the third and fourth axes.
The results confirmed our expectation that smaller copepods were associated with higher temperatures supporting the Bergmann's rule and previous global studies (Brun et al., 2016; Campbell et al., 2021). Smaller copepods were particularly prevalent in the CCE during the 2014-2015 marine heatwave, a period characterised by an increased abundance of small tropical copepod species (Beltrán-Castro et al., 2020). Smaller copepods were found deeper in the surface layer, whereas larger copepods were found shallower and in colder waters.

Larger copepods were also more frequently observed at night in 2008 and 2014, which suggested that larger copepods displayed a higher DVM amplitude, consistent with in situ observations from the Sargasso Sea (Barth et al., 2023). Using individual images of fixed organisms collected using plankton nets in the CCE, it was also shown that mid-sized copepods (2,500-7,000 µm), which match the largest copepods sampled here, had the highest DVM amplitude (Ohman and Romagnan, 2016). However, this relationship was not observed during the 2012 or 2016 cruises, suggesting a potential seasonal or interannual effect.

Along the second axis, copepods with more complex body shapes were found in shallower waters with higher fluorescence and prey concentrations (second axis of the morphological space). Higher complexity was linked to the presence of visible appendages, such as legs and first pair of antennae (e.g., A1s or antennules; Boxshall and Jaume, 2015). Antennule posture varies among taxa and behavioural states. For example, *Calanus* often retains extended antennules when dormant, whereas some species, such as *Eucalanus*, may fold them when inactive (Giuffre et al., 2019; Ohman, 2019). Therefore, although visible appendages should not be considered a definitive indicator of feeding activity, more complex morphologies could partly suggest active swimming, prey handling, and foraging, since they were observed in waters with higher fluorescence and prey concentration. This observation is consistent with that of a previous study on Arctic copepods using the same in situ imaging system (Vilgrain et al., 2021). In contrast, copepods with more elongated and simpler shapes (i.e., torpedo-like
forms lacking visible appendages) occurred deeper in the surface layer, where potential prey were less abundant, which could indicate a potential resting behaviour.

Along the third axis, copepods with more transparent bodies and homogeneous grey levels were found in shallower waters, along with higher fluorescence and potential prey concentrations. Such observations contradict our second hypothesis since copepods were not darker with higher fluorescence. Previous studies have linked darker copepods with the presence of red pigments, mature gonads, or a full gut (Vilgrain *et al.*, 2021). Such individuals were typically found alongside increased *Chlorophyll a* concentrations. However, because UVP5 images lack the detail required to resolve gut content of California copepods, the grey-level patterns observed here likely reflect alternative mechanisms. One possible explanation is a higher proportion of carcasses and moults were identified as living copepods (Frangoulis *et al.*, 2005; Vilgrain *et al.*, 2023). However, distinguishing living transparent individuals from recently moulted or dead specimens is difficult with in situ UVP5 imagery, so the carcass/moult hypothesis is difficult to confirm based on the images alone. An alternative explanation is that transparent copepods may benefit from their lack of pigmentation by remaining less visible to predators in surface waters (Caramujo *et al.*, 2012; Vilgrain *et al.*, 2023). Clarifying the interpretation of the variations in transparency has broader biogeochemical implications, as enhanced mesozooplankton transparency has been associated with increased carbon export (Perhirin *et al.*, 2024).

Despite the large range of potential habitats caused by intense environmental gradients, analyses of copepod morphological space mostly align with previous studies in different environments (Vilgrain *et al.*, 2021; Barth *et al.*, 2023; Perhirin *et al.*, 2024). A common limitation of UVP5-based studies is the under-representation of copepods and juvenile stages smaller than 600 µm due to pixel resolution (Picheral *et al.*, 2010). Given that the CCE
community is dominated by small copepods (>96% with prosome length <450 µm; Hopcroft
et al., 2001), this size-selective bias likely contributed to the weak morphological patterns
observed, even under the strong environmental gradients of EBUS. Higher-resolution in situ
imaging instruments (e.g., zooglider) would help resolve the morphology of smaller copepods
and their relationships with the environment (Ohman, 2019). Despite sampling limitations,
our findings align with prior reported patterns in copepod trait distribution. The limited
spatiotemporal sampling (over four years, during various seasons, and in different locations;
Fig. S1) may also have contributed to the lack of distinct diel patterns. Nonetheless, this study
provides an initial view of surface copepod morphological variation alongside environmental
gradients in the CCE. Future work should use higher-resolution imaging devices and broader
sampling in time, depth, season, and/or cross-shore gradients to better quantify how copepod
and mesozooplankton morphology respond to environmental gradients in the CCE and other
EBUS.
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**Author Contribution Statement**

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The authors confirm their contribution to the paper as follows: study conceptualisation and

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design by Tristan Biard and Sakina-Dorothée Ayata; formal analysis by Rubén Tournier-

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Broer, Sakina-Dorothée Ayata and Tristan Biard; writing original draft by Rubén Tournier-

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Broer; writing- review and editing by Tristan Biard and Sakina-Dorothée Ayata.

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All authors reviewed the results and approved the final version of the manuscript.

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**Acknowledgments**

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We wish to thank public taxpayers who fund our salaries as French state employees. The

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authors acknowledge the support of the French Agence Nationale de la Recherche (ANR)

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under grant ANR-22-CE02-0023-1 (project TRAITZOO). This project was made possible by

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the data collected through the CCE-LTER programme (supported by National Science

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Foundation grants OCE-10-26607, OCE-1637632, and OCE-1614359) and all the personnel

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who participated in the different oceanographic campaigns. We thank all the personnel who

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participated in the UVP deployments, picture validations, and taxonomical attributions.

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RTB's PhD grant was funded through the ANR TRAITZOO and the ULCO. We also thank

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the members of the ANR TRAITZOO project for their insights, as well as Emeritus Professor

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Mark Ohman (UCSD), Jean-Olivier Irisson (LOV), Sebastien Villeger (MARBEC) and

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Francesco d'Ovidio (LOCEAN-IPSL) for their insight and advice on different aspects of our

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research. This work is part of the Graduate School IFSEA that benefits from grant ANR-21-

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EXES-0011 operated by the French National Research Agency under the France 2030

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program. RTB gratefully acknowledges the financial support for this research from the

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Fulbright Program, which is sponsored by the U.S. Department of State and the Franco-

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American Commission - Fulbright France. The authors also thank Patrick Pata for english
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proofreading and the three anonymous reviewers for their constructive comments on a

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previous version of this manuscript.

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**Data Availability Statement**

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R scripts used in this manuscript are available at;

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https://github.com/RubenTournierBroer/Copepod_Traits_Supp_Info.

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Individual mesozooplankton images, their metadata and morphological descriptors are stored

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in EcoTaxa web application https://ecotaxa.obs-vlfr.fr/ (project 'UVP5 CCELTER (Iter2008

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ccelter_2012 ccelter_2014)' and 'UVP5 CCELTER 2016'). Environmental data are stored in

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the Datazoo website https://oceaninformatics.ucsd.edu/datazoo/catalogs/ccelter/datasets

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(project CTD Downcast Data (Process Cruise)).

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Phytoplankton and microplankton data are available on Datazoo web application

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https://oceaninformatics.ucsd.edu/datazoo/catalogs/ccelter/datasets (project 'Nano and

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Microplankton Abundance (Process cruise)' and 'Picoplankton and Bacteria Abundance').

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Carbon flux data are also available on the Datazoo web application (Project 'Sediment Trap

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(Process Cruise)').
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