# Modeling spatio-temporal dynamics of Patagonian toothfish spawning in Kerguelen waters using CPUE data

Fanny Ouzoulias, Clara Péron, Félix Massiot-Granier

► To cite this version:

Fanny Ouzoulias, Clara Péron, Félix Massiot-Granier. Modeling spatio-temporal dynamics of Patagonian toothfish spawning in Kerguelen waters using CPUE data. Fisheries Research, 2025, 288, pp.107422. 10.1016/j.fishres.2025.107422. hal-05373526

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Full length article

# Modeling spatio-temporal dynamics of Patagonian toothfish spawning in Kerguelen waters using CPUE data

Fanny Ouzoulias* , Clara Péron, Félix Massiot-Granier

Laboratoire de Biologie des Organismes et des Écosystèmes Aquatiques-BOREA. Muséum national d'Histoire naturelle (MNHN), SU, CNRS, IRD, UA, F-75005 Paris, France

## ARTICLE INFO

Handled by Beatriz Morales-Nin

**Keywords:**
Spawning
Toothfish
Longline fishery
GAM
Southern Ocean
CPUE

## ABSTRACT

The act of spawning of fish can be influenced by a variety of factors, including environmental conditions and human activities, particularly fishing. Patagonian toothfish (*Dissostichus eleginoides*) is a commercially exploited fish species, occupying the southern Patagonian and Chilean shelves, as well as the sub-Antarctic submarine plateaux. It is characterized by a late maturity and slow body growth, which are key considerations in its management and conservation. In this study, we investigated the spatio-temporal dynamics of Patagonian toothfish spawners in the Kerguelen region using fishery observer data, from 2020 to 2024. We predicted spawner hotspots and seasonal trends of spawner abundance using spatially-explicit Generalized Additive Models (GAMs) that modeled the spawner CPUE (Catch Per Unit of Effort). Our results suggest that toothfish female spawners aggregate at specific locations from early June to the end of July. Hotspots of male spawners were found from mid-June to mid-July and then from mid-August to mid-September. The main spatial overlap between male and female spawner hotspots is located on the western slopes and the north of Skiff bank (along the 1500 m isobath) and in the north-western region (near the 500 m isobath). Our findings enabled the formulation of hypotheses concerning the ecological drivers influencing Patagonian toothfish spawning and emphasize the importance of considering seasonal localized closures to avoid mortality and disturbance during spawning.

## 1. Introduction

The act of spawning of fish can be influenced by a variety of factors, including environmental conditions and human activities, particularly fishing. Gaining a comprehensive understanding of the spatio-temporal dynamics of fish reproduction is essential for effective fisheries management, as it enables the mitigation of pressures on processes to which the future of the population relies on.

Patagonian toothfish (*Dissostichus eleginoides*) is a demersal fish species within the Nototheniidae family, inhabiting the southern Patagonian and Chilean shelves, slopes and deepwater plains, as well as sub-Antarctic islands (Gon and Heemstra, 1990). Its life cycle is closely tied to depth: larvae are pelagic, and juveniles settle at shallow depths (< 200 m) before migrating progressively to deeper waters, reaching depths of up to 2500 m (Collins et al., 2010). This ontogenetic shift in habitat has been documented on the Kerguelen Plateau where toothfish size increases with depth (Péron et al., 2016).

Patagonian toothfish is characterized by a long lifespan (up to 50 years old), an absolute fecundity ranging from about 50,000 to 500,000 eggs (on the Kerguelen Plateau, Chikov and Mel'nikov (1990)),

a late maturity, and a slow growth for adults, which are key considerations for fishery management. Females reach larger sizes than males (Ashford et al., 2005) and mature later (Arana, 2009). In Kerguelen waters, male toothfish reach sexual maturity at around 6 years old (630 mm) whilst females mature at around 14 years old (850 mm) (Ouzoulias and Massiot-Granier, 2024; Lord et al., 2006). In Kerguelen, Chikov and Mel'nikov (1990) found a positive and allometric relationship between the size of females and the number of eggs produced, as commonly observed in many fish species. This means that the overall fecundity is markedly influenced by the size composition of the population.

Compared to other deep-sea species, the reproductive characteristics of toothfish are poorly understood, and information on their reproductive biology remains limited. Throughout its habitat, Patagonian toothfish has been shown to spawn in austral winter. However, the timing and location of spawning differ slightly among the regions. In South Georgia, Bamford et al. (2024) showed evidence of a dual peak happening in April/May and August/September along the shelf break at both South Georgia and Shag Rocks (west of South Georgia).

<footnote>* Corresponding author.
E-mail address: fanny.ouzoulias@mnhn.fr (F. Ouzoulias).</footnote>
Spawners from South Sandwich Islands seem to move to South Georgia to spawn and defer reproductive investment until they reach South Georgia (Soeffker et al., 2022). In the Falkland Islands, spawning was found to occur on slopes of the Burdwood Bank around 1000 m depth with a major peak in July to August (Laptikhovsky et al., 2006). In Heard and McDonald Islands, spawning hotspots have previously been identified along the slopes of the Kerguelen Plateau by Welsford et al. (2012), Mori et al. (2016) and Yates et al. (2018). In Kerguelen waters (French Exclusive Economic Zones, EEZ), Lord et al. (2006) indicated that spawning activity occurs in April/May and mid-July for females and from May to August for males; high densities of large, mature adults were found near Skiff bank, located west of Kerguelen Island (Fig. 1) but spawning locations were not assessed precisely. It is still unclear whether there are restricted areas of spawning, and if seasonal movements of spawners toward the spawning grounds can be observed. Individual-based approaches using tagging data have been undertaken in the Falkland Islands and highlighted movements from slopes to spawning grounds, with spawners moving repeatedly into shallower waters of 900–1200 m (Brown et al., 2013; Lee et al., 2022).

Due to its large body size and the high quality of its flesh, Patagonian toothfish has been targeted by fisheries since the mid-1980s, initially in Chilean waters and subsequently in South Georgia, on the Patagonian shelf, in the Falkland Islands, in the Kerguelen Plateau and then in Crozet Island, in Prince Edward Islands, and in Macquarie Island. In the Kerguelen Plateau, Patagonian toothfish exploitation started with trawl fisheries operating in the northern part (French EEZ, Kerguelen) and southern part (Australian EEZ, Heard and McDonald Islands) of the Kerguelen Plateau. In the Kerguelen EEZ, the trawl fishery was gradually replaced by a longline fishery in the late 1990s. Since 2000, only longline fishing has been conducted, with legal catches reaching 7000 tonnes in 1998, 6000 tonnes in 1999 and stabilizing around 5000 tonnes annually since 2000 (Lord et al., 2006; CCAMLR, 2023). In 2024/2025, the Total Allowable Catches (TAC) was set at 4610 tonnes (TAAF, 2024). In Kerguelen, between 1996 and 2004, toothfish was targeted by a high level of Illegal, Unreported and Unregulated (IUU) fishing leading to rapid depletion of the stock up to 50% of the spawning biomass pre-exploitation level (Duhamel et al., 2005). The impact of this depletion on the toothfish life cycle remains incompletely understood, particularly concerning long-term recruitment patterns. In 2024, the completion of a 4-year otolith age-reading program enabled the estimation, in the stock assessments, of the first recruitment time series from 2000 to 2017, revealing persistent low recruitment levels since 2007 (Ouzoulias et al., 2024). In Kerguelen waters, juvenile settlement zones have been explored and seem to be in shallow areas around Kerguelen (Duhamel et al., 2019). Yet a consistent spatial distribution has not been established. Consequently, further focus on recruitment dynamics, particularly on spawning patterns, is essential to understand and manage the sustainability of the Kerguelen Patagonian toothfish stock.

This study represents the first investigation to leverage observer and catch data to elucidate the spatial and temporal dynamics of Patagonian toothfish spawning in the northern part of the Kerguelen Plateau. We modeled the spatial and temporal distributions of toothfish spawning to identify periods and locations of peak in spawner abundance and assess spatial overlap between male and female spawner hotspots. These findings provide critical insights to inform management strategies that align with natural processes and fishery operations.

## 2. Material and methods

All data analyzed in this study were collected by fishery inspectors during commercial fishing trips of French longliners operating in the Kerguelen EEZ. Fishery inspectors are mandatory on each vessel and are in charge of control (compliance with fishing regulations) and scientific monitoring. Scientific monitoring is supervised by the Muséum national

d'Histoire naturelle (MNHN, BOREA Lab) which also trains the inspectors in scientific protocols. Scientific data are recorded into electronic logbooks which are verified (data quality control) by the MNHN at the end of each commercial trip and integrated into the "Pecheker" database (Martin et al., 2021). All data analyzed for this study were extracted from this database.

While catch and biological data have been monitored since the start of the fishery, until 2020 most of the TAC was reached in May/June and fishing effort was extremely low during the peak of spawning in July/August. We therefore selected data from 2020 to 2024 only (Figures S2 and S3).

### 2.1. Fishery description

The Kerguelen EEZ Fishery targeting Patagonian toothfish operates all year round except during a period of 1.5 months in February–March when the fishery closes to avoid seabird bycatch. Fishing occurs on slope areas between 500 and 2100 m all around the continental shelf (plateau) and is prohibited in waters shallower than 500 m and within the strictly protected areas of the Southern French Territories Marine reserve (RNN TAF, Réserve Nationale Naturelle des Terres Australes Françaises, Fig. 1). Since 2000, up to 9 longliners (60 m long) have operated in the Kerguelen French EEZ. All longliners used integrated weight autolines with thousands of hooks (Fiskevegn® Eagle or Eagle Claw hooks of nominal sizes 14/0 and 15/0), each attached to a snood (40 cm) laying on the seafloor. Hooks are baited using an automated machine with pieces of mackerel (Scomber scombrus) and occasionally squids (Illex argentinus). Longlines set are typically 10 km long with 7000 hooks (on average) separated by about 1 m and soak for 38 h on average. They are always set at night to avoid seabird bycatch while hauling can occur both night and day. Gear characteristics (hook model and distance between hooks) and baits were consistent across vessels, seasons, and years during the study period (2020–2024). Two types of longliners operated: 5 bunker vessels where lines are hauled on one side of the vessel and 3 moonpool vessels, which have a trunking system built into the longliner's hull, providing a safer working environment for the crew.

### 2.2. Data collection and analysis

#### 2.2.1. Catch and effort data

Each captain declares the total catch fished in each line (number and weight). Information on fishing activities is also recorded at setting (number of hooks set, date, depth from the vessel sounder, longitude, latitude at the start and end locations of the line) and hauling (number of hooks hauled, date, depth from the vessel sounder, longitude, latitude at the start and end locations of the line).

#### 2.2.2. Biological data collection

Fishery inspectors typically collect biological data on one or two of the five lines hauled each day. For these lines, the inspector samples fish randomly from the catch (mean = 65 individuals line⁻¹). All the fish from this representative sample are measured (total length, TL, in cm), and dissected for determination of sex and maturity stage. Maturity stage is determined according to the system developed by Kock and Kellermann (1991) and Gasco (2010) (Table 1).

#### 2.2.3. Sex ratios and maturity stages in the catch

We calculated the sex ratios among the different maturity stages. We also explored the seasonal variations in the sampling effort and composition of the catch.
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Study area with locations of the strictly protected areas (in red), the isobaths 100, 500, 1000, 2000 and 3000 m (in blue lines) and aggregated fishing effort from April to October 2020–2024 (green areas). The black dashed line indicates the contours of the Kerguelen EEZ. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

<table><caption>**Table 1**
Maturity scale for male and female Patagonian toothfish, based on Kock and Kellermann (1991).</caption><thead><tr><th rowspan="2">Stage</th><th colspan="2">Males</th><th colspan="2">Females</th></tr><tr><th>Maturity</th><th>Description</th><th>Maturity</th><th>Description</th></tr></thead><tbody><tr><td>1</td><td>Immature</td><td>Testis small, translucent, whitish, or long with thin strips lying close to vertebral column</td><td>Immature</td><td>Ovary small, firm, no eggs visible to the naked eye</td></tr><tr><td>2</td><td>Developing or regenerating</td><td>Testis white, flat, convoluted, easily visible to the naked eye, about a quarter of the length of the body cavity</td><td>Developing or regenerating</td><td>Ovary extended, firm, small oocytes visible, giving the ovary a grainy appearance</td></tr><tr><td>3</td><td>Developed</td><td>Testis large, white, and convoluted, no milt produced when pressed or cut</td><td>Developed</td><td>Ovary large, starting to swell in the body cavity</td></tr><tr><td>4</td><td>Ripe</td><td>Testis large, opalescent white, drops of milt produced when pressed or cut</td><td>Ripe</td><td>Ovary large, filling or swelling in the body cavity, when opened large ova spill out</td></tr><tr><td>5</td><td>Spent</td><td>Testis shrunk, flabby, dirty white in color</td><td>Spent</td><td>Ovary shrunken, flaccid, contains few residual eggs and many small ova</td></tr></tbody></table>

## 2.3. Modeling spatial and temporal dynamics of spawning

### 2.3.1. Estimation of spawner abundance

We used the Catch Per Unit Effort (CPUE) of the spawners (stage 4) as a measure of the spawner abundance and selected the data collected from April to October, when spawning is supposed to occur (Laptikhovsky et al., 2006; Arana, 2009; Brigden et al., 2017). Then, we selected the lines for which the fishery inspector collected biological data. The total number of spawners caught on these lines

was estimated by multiplying the ratio of the number of spawners to the total number of fish sampled by the total number of fish caught (captain's declaration):

$$N_{spawners} = \frac{N_{spawners sampled}}{N_{total sampled}} \times N_{total catch} \quad (1)$$

As a result, we constructed a dataset (n = 10,653) that included the estimated number of spawners caught per line, the number of hooks hauled, the geographic location of each line (calculated as the midpoint
between the start and end of hauling), the depth at its midpoint, and the date of fishing (end of hauling). To calculate the spawner CPUE, we divided the estimated number of spawners by the total number of hooks hauled in each line.

### 2.3.2. Model development

We used spatial Generalized Additive Models (GAMs) with the *gam()* function from the *mgcv* package in R 4.3.3 (Wood, 2023). Most lines did not catch stage 4 fish (76%). Spawner CPUE was considered null for each of these lines. It resulted in a zero-inflated data set. A Tweedie family distribution with a log link function was therefore applied, as it accommodates datasets with a high proportion of ze-ros (Tweedie, 1984; Jorgensen, 1997; Candy, 2004; Dunn and Smyth, 2005). The response variable was the spawner abundance (CPUE, individuals per hook), and we tested the effects of latitude, longitude, fishing depth and week. An interaction between week and latitude/lon-gitude was included in the model (with thin plate splines), as evidence suggests that toothfish aggregate during the spawning season (Lord et al., 2006; Arana, 2009; Duhamel et al., 2011; Brigden et al., 2017; Bamford et al., 2024). Also, including an interaction between latitude, longitude and time generates more stable predictions, even for areas where data are incomplete (Hoyle et al., 2024). Thin plate splines are commonly used in GAMs to model spatio-temporal distributions (Berg et al., 2014; Earl et al., 2021; Núñez-Riboni et al., 2021). We tested several types of smoothers and interactions. A summary of the models tested and their associated AIC and percentage of deviance explained is available in Table S1. We ran one model for females and one for males to account for sex-specific spawning patterns.

For the smooth terms latitude, longitude, week, and depth, the dimensional basis of the spline was selected to ensure the model adequately captured the underlying processes while avoiding overfitting and maintaining computational efficiency. The choice of *k* was validated by comparing it to the effective degrees of freedom (EDF) and assessing the sensitivity of *k* to the results using the *k.check* function (Wood, 2017). The goodness of the fit was evaluated by examining the residual patterns with the *gam.check()* function, as well as considering the percentage of explained deviance. The significance of each model term was also tested, and the contribution of each explanatory variable was visualized. The most parsimonious models were selected based on the minimum Akaike's Information Criterion (AIC) value (Akaike, 1974), Table S1.

The structure of the model selected by AIC for both sexes was:

$$g(CPUE_i) \sim f_1(\text{Depth}_i) + f_2(\text{Lon}_i, \text{Lat}_i, \text{Week}_i) \quad (2)$$

*i* identifies data specific to a line (where biological sampling occurred), *f*₁ is a thin plate spline and *f*₂ is a full product tensor smooth, using thin plate splines. A log-link (*g*) provided the link between CPUE and each predictor.

## 2.4. Predicting spatial and temporal dynamics of spawning

### 2.4.1. Production of the prediction dataset

The best GAM models were used to predict monthly spatial distributions of male and female spawners in each 10 km x 10 km cell of a grid encompassing the core fishing area, defined by using Kernel Density Estimation (KDE, Parzen (1962)) applied to the fishing effort (number of hooks hauled) to avoid predicting in areas where fishing was low.

The dataset used for predictions included all explanatory variables from the model, namely: longitude, latitude, depth and week. The depth was obtained from a bathymetric grid (2022 "GEBCO", 0.0083° × 0.0083°<fnref n="1" />). This generalization dataset contained 49,152 lines (combination of latitude, longitude, week and depth with a resolution of 10 × 10 km).

<table><caption>**Table 2**
Sex ratios by maturity stage, for 2020–2024, from January to December.</caption><thead><tr><td>Maturity stage</td><td>Female proportion</td><td>Male proportion</td></tr></thead><tbody><tr><td>1</td><td>0.70</td><td>0.30</td></tr><tr><td>2</td><td>0.34</td><td>0.66</td></tr><tr><td>3</td><td>0.27</td><td>0.73</td></tr><tr><td>4</td><td>0.19</td><td>0.81</td></tr><tr><td>5</td><td>0.39</td><td>0.61</td></tr><tr><td>all</td><td>0.48</td><td>0.52</td></tr></tbody></table>

### 2.4.2. Spawning distribution

One prediction map was generated for each sex and each month (April, May, June, July, August, September, October) by aggregating the weeks and calculating the average predicted spawner abundance. The effect of depth on spawner abundance was also plotted separately. To identify seasonal variations in the latitudinal distribution of spawner hotspots, we computed, for each week, the mean latitude of the centroid weighted by the predicted CPUE.

### 2.4.3. Phenology of spawning

The phenology of spawning was estimated for each sex, using the same dataset as for the spatial predictions. We selected the lines for which the longitude was west of 69° E, since spawners were absent from the eastern region during the spawning season. Associated with latitude and longitude, the dataset for predictions also included the depth. Mean predictions of weekly CPUE were calculated on this dataset. Uncertainty associated with the predicted CPUE was quantified using a Metropolis-Hastings posterior simulation, with the function *posterior samples* of the package *gratia* in R (Simpson and Singmann, 2024).

## 3. Results

In total, 465,733 fish were measured between 2020 and 2024 and 354,110 between the 1st of April 2020 and the 30th of October 2024, with sex and maturity stages recorded. Fish in stages 3, 4, and 5 were generally larger than those in stages 1 and 2 (Fig. 2). Among the 354,110 individuals measured, 34,018 fish (9.6%) were identified as spawners (stage 4). We used this extensive dataset to remove staging errors for stage 4 by excluding all values lower than the 1% TL quantiles (77 cm for females and 61 cm for males) (n = 673 individuals removed, 1.9% of the dataset).

### 3.1. Sex ratios and maturity stages in the catch

Overall, toothfish sex ratio was balanced in the total catch (48% of females and 52% of males); however, this ratio varied greatly between stages (Table 2). Stage 1, immature fish, were largely dominated by females (70%), while males were more abundant among the other stages, particularly among spawners (stage 4): 81% of the spawners were males (Table 2).

Fig. 3 shows seasonal variations in the sampling effort and composition of the catch. The number of fish sampled varied over time since sampling was proportional to catch; it was close to zero between the 6th and the 9th week when the Kerguelen toothfish fishery closes (February–March) (Fig. 3).

Proportion of immature female (stage 1) in the weekly catch varied between 47 and 77%. The highest proportion of immature was observed in June (week 25) and April (week 13). Females in stage 2 (developing or regenerating) represented 9 to 36% of the female weekly catch. The highest proportions were observed at the end of the year, in December (week 49). Females in stage 3 (developed) were observed throughout the year in significant proportion (5%–10%) except between the 30th week to the 33th week (August), where they were at very low levels. This period was characterized by the highest

<footnote n="1">¹ https://www.gebco.net/data_and_products/historical_data_sets/#gebco_2022</footnote>
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Length frequencies of the different maturity stages, for females (on the top) and males (on the bottom), based on the sampled lines from 2020 to 2024 (all months, from January to December).</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Observed proportion of maturity stages in the weekly toothfish catches during the period 2020–2024 and the total number of fish sampled for biological measurements, for females and males.</figcaption></figure>

proportions of stage 4 (spawners) in the catch (15%). By the end of August, females in stage 4 were gradually replaced by stage 5 (spent individuals), with proportions of stage 5 reaching 16% in the 42th week (October) (Fig. 3).

Proportion of immature males varied between 11 and 37% over the year. Males in stage 2 occurred throughout the year in high proportions (39% on average) with the highest proportion in December. Proportions of males in stage 3 were very low from June to August (from 1 to

7%), medium from September to November (6 to 12%) and high from December to June (12 to 73%). Proportions of stage 4 were the highest in July (52%). Stage 5 replaced stage 4 gradually over the austral winter.

Overall, stage 4 individuals were mostly found in small proportions in June/July for females and from July to September for males. Male spawners were four times more frequent in the catch than female spawners. Female spawners started to be observed earlier in the year,
<figure><img src="image_6.png" /><figcaption>Fig. 4. Effects of depths on female and male spawner CPUE.</figcaption></figure>

although in weak proportions, from week 16 (mid April), compared to the first male spawners observed from week 20 (one month later). Interestingly, from mid August to mid October, stage 4 males stayed dominant in the catch while most of the females were already spent.

## 3.2. Dynamics of spawning

### 3.2.1. Spatial distribution

Based on AIC and deviance explained, the best model for spatial dynamics included week, depth and the interaction (tensor) between latitude, longitude and week. Model parameters are given in Tables S2 and S3. The residuals were randomly distributed (Figures S4 and S5) and the interaction between geographic position and week was significant for both sexes.

The depth range where both male and female spawners were more abundant was 1500–1800 m. Female spawners stayed abundant below 1800 m and were also present in shallow waters between 500 and 600 m (Fig. 4). Male spawner CPUE indicated that they were more frequent from 1300 m to 1800 m, with a peak at 1600 m (Fig. 4).

The prediction maps of spawner CPUE illustrate the spatial dynamics of spawners from April to October (Fig. 5 for females and Fig. 6 for males). Overall, spawner CPUE was higher for males (maximum of 40 individuals per 1000 hooks⁻¹) than for females (maximum of 20 individuals per 1000 hooks⁻¹), reflecting the higher proportion of male spawners in the catches (Table 2).

For females, spawner hotspots varied over time: a distinct pattern emerged in June, with one main area of high spawner CPUE in the deeper fishing grounds located north of Skiff bank. This signal gained strength from April–May up to June. Hotspots were also predicted in June very locally in shallow waters on the west slopes of Kerguelen Plateau. The predicted CPUE decreased and spread in July and was near zero in September and October.

For males, several hotspots of high spawner CPUE were predicted along the western slopes of the plateau, around 700 m in June and along the 1500 m isobath in July. In August, the model predicted high values of CPUE in the south and in September between the eastern part of Skiff bank and the 1500 m isobath. The predicted CPUE was near zero in April, May, and October.

Overall, male and female spawner hotspots overlapped mostly in July along the 1500 m isobath and very locally in shallow waters.

### 3.2.2. Phenology of spawning

The predicted female spawner CPUE increased from late May, reached a maximum from week 24 (June) to week 29 (July) and then decreased to smaller levels after week 30 (August) (Fig. 7).

For males, the model predicted two peaks of predicted spawner CPUE: one around the 27th week (first week of July) and another between the weeks 35 and 37 (late August–early September). The spawner CPUE increased sharply between June and July, remaining at high levels (greater than 8 individuals per 1000 hooks) from the end of June through the end of September.

## 3.3. Overlap between male and female spawner hotspots

The interaction between a temporal covariate (week) and spatial covariates (longitude, latitude) allowed us to predict the spatial distribution of spawners during the two key spawning seasons identified in Fig. 7: weeks 22–30 (June–July) and weeks 34–39 (August–September). Fig. 8 highlights the areas of highest spawner abundance (predicted CPUE), which together represent 50% of the total estimated spawner abundance of males (blue) and females (red).

### 3.3.1. First peak of spawner abundance (June–July)

Between weeks 22 and 30 (June–July), while the presence of male spawners was predicted to be occurring in most of the western part of Kerguelen Plateau, two distinct hotspots of female spawners were identified. The first and larger hotspot was located in the western part of Kerguelen, at depths ranging from 515 to 2114 m. The second, smaller and shallower area was situated around 48° S/67° E (mean depth 533 m). The average density of female spawners in the second area was 1.3 times higher than the average density of the first larger hotspot (13.2 v.s 10.2 individuals per 1000 hooks).

Males hotspots were located in between these two hotspots and overlap a significant portion of them (20%), with depth ranging from 513 to 2114 m. While the 50% abundance threshold corresponds to 6.75 individuals per 1000 hooks for females, it is 8.4 for males. In the overlap areas (Fig. 8), there are on average 10.2 females per 1000 hooks and 13.7 males per 1000 hooks.

The overlap between male and female hotspots was observed between the 1500 and 1800 m isobaths on the west side of the Kerguelen Plateau, as well as in shallower areas around 48° S/67° E. These shared
<figure><img src="image_7.png" /><figcaption>Fig. 5. Map of predictions of female spawning CPUE of Patagonian toothfish. The blue lines correspond to the 500, 700, 1500 and 1800 m isobaths. The small black dots correspond to lines observed for biological sampling, from 2020 to 2024. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Fig. 6. Map of predictions of male spawning CPUE of Patagonian toothfish. The blue lines correspond to the 500, 700, 1500 and 1800 m isobaths. The small black dots correspond to lines observed for biological sampling, from 2020 to 2024. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>Fig. 7. Predictions of the weekly spawner CPUE of Patagonian toothfish for females and males.</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>Fig. 8. Regions where spawner abundance exceeds 50% of the total spawner estimated abundance, for the males (in blue) and the females (in red). The overlap between males and females is in purple. The black dashed contours indicate the spatial extent of male abundance when applying the female threshold (1.2 individuals/1000 hooks). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

areas correspond to an average of 14.1 fish per 1000 hooks and 9.9 fish per 1000 hooks for males and females, respectively. Furthermore, 75% abundance threshold areas for both females and males overlap the 50% abundance threshold area of the opposite sex (not shown).

### 3.3.2. Second peak of spawner abundance (August–September)

Between weeks 34 to 39, the hotspots shifted southwards compared to the hotspots identified in June and July. Additionally, the 50% abundance thresholds changed significantly, decreasing to 1.2 individuals per 1000 hooks for females and increasing for males to 11.8 individuals per 1000 hooks. The spatial overlap was reduced to more limited areas, specifically in the northeastern side of Skiff bank and in the south, with a sex ratio of 1 female for 8 males. In August/September, if the female threshold (1.2 individuals per 1000 hooks) were applied to the male distribution, the presence of male spawners would extend from the North to the South of Kerguelen waters (dashed line in Fig. 8).

## 4. Discussion

Our findings suggest that toothfish female spawners aggregate at specific locations from the beginning of July to mid-July. Hotspots of

male spawners appear to be larger than females, from June 17 to July 21 and then from August 19 to September 21. The synchronicity of the peak abundance of male and female spawners seems to occur mainly in July. The spatial overlap between male and female spawners seems to be concentrated in a shared area along the 1500 m isobath and in the north-western region near the 500 m isobath (Fig. 8).

### 4.1. Spawner hotspots

Our findings are consistent with studies conducted on Patagonian toothfish spawning in other regions, with slight variations. We identified hotspots along the 1500 m isobath in the north of Skiff bank. In Heard and McDonald Islands, Welsford et al. (2012), Mori et al. (2016) and Yates et al. (2018) found that spawning occurs on the deeper slopes on the western side of the Kerguelen Plateau, with a preference for depths between 1700 and 1800 m. The western part of the Kerguelen Plateau appears to be a suitable spawning ground: Mori et al. (2016) hypothesized that the dominant currents in this region may transport eggs released in the west toward the northeastern part of the Kerguelen Plateau, where recruitment areas have been identified. In our study, we
also identified localized areas of high densities of spawners in shallow
areas (530 m) in June. In Heard and McDonald Islands, Welsford
et al. (2012), Mori et al. (2016) and Yates et al. (2018) found that
there was no evidence of spawners' preference for shallow areas: Yates
et al. (2018) hypothesized that spawning in deeper slopes may provide
greater benefits via reduced predation pressure from elephant seals
(Mirounga leonina) and sperm whales (Physeter macrocephalus), which
generally forage in depths shallower than 1000 m (Watwood et al.,
2006; McIntyre et al., 2011). In South Georgia, Brigden et al. (2017)
and Bamford et al. (2024) showed that for the males, greater abundance
was associated with shallower depth, but they did not highlight any
significant relationship between female spawners and depth. In our
case, the pattern we observe in June, with high densities of spawners in
shallow areas, is common to both males and females. Since the fishery
is limited to areas deeper than 500 m, setting up protocols (including
microscopic analysis of the gonads) that target the shallow areas on
the western side of Kerguelen waters would enable us to confirm these
results.

Previous investigations by Lord et al. (2006) suggested that female spawners were found from late April/May to mid-July, while male spawners were found from May to August. Our results refine and support these observations. In South Georgia, Brigden et al. (2017) and Bamford et al. (2024) identified an early spawning peak in April and a major peak in July and August. Lord et al. (2006) highlighted early signs of spawning in late April in Kerguelen. Despite good sampling coverage in the spawner hotspots, we did not observe this early peak in our study, but it could be due to differences in spawning behavior between the South Georgia and Kerguelen populations. In the Falkland Islands, Laptikhovsky et al. (2006) found that spawning occurs in July and August, while a study conducted by Arana (2009) in southern Chile determined that spawning takes place in June and July.

The fishing data used in this study covers depths ranging from
500 to 2100 m, yet spawners might occupy shallower or deeper areas.
Dedicated sampling programs targeting spawners at depths outside the
present range could provide further insights into this issue.

The maturity scale proposed by Kock and Kellermann (1991) is rel-
atively simple and allows observers to quickly estimate maturity stages.
However, it is based on macroscopic observations, and Yates et al.
(2018) showed that, compared to females, there is a greater discrep-
ancy in the estimation of maturity stages when comparing macroscopic
and microscopic assessments in males. This may be due to a continuum
of sperm development and renewal in males throughout the spawning
season. It is therefore possible that the spawning peak observed in
August for the males corresponds to the identification of stage 5 indi-
viduals rather than stage 4 individuals in the catch. *In situ* histological
observations could help verify the trends we observed.

Our results (Figure S6) also revealed that in May (weeks 18–21),
reproductive females were exclusively found in the northern region:
the latitude of the centroid weighted by the predicted abundance
was 48.1° S. During June and July, when the models predicted the
highest abundance of spawners, the centroid was 49.1° S. Later in
the season, during August and September (weeks 33–39), reproductive
females were only present, in very small quantities, in the southern
region: the centroid was 49.8° S. These spatial variations may reflect
differences in regional phenology, potentially driven by environmental
gradients (Figure S6). Park et al. (2014) demonstrated the existence of a
latitudinal gradient of temperature at 200 m in the Kerguelen region. If
a similar gradient is present at the seafloor, warmer climatic conditions
in the north may allow for an earlier increase in the abundance of
reproductive individuals, whereas colder southern regions experience
a later peak. But rather than migrating to predetermined spawning
areas, adult fish may remain resident and initiate spawning locally once
environmental conditions become favorable.

Fig. 8 illustrates the spatial overlap between spawner hotspots of
males and females. The highlighted areas represent 50% of the total

estimated spawner abundance. However, it is important to note that
in August and September, the spatial overlap was reduced, with an
expected sex ratio of 1 female for 8 males. The minimum abundance of
females required for successful spawning remains unclear; it is possible
that spawning can still occur even when the number of female spawners
is very low. This consideration is critical to understanding the spatial
patterns of egg emission and larval dispersion.

## 4.2. Cryptic spawners hypothesis

For this study, we excluded the stage 5 (spent individuals) and
focused on the stage 4 (spawners), considering that the presence of
the spawners is a proxy of spawning. Fig. 3 illustrates an expected
inverse temporal relationship between spawner and spent individual
proportions: spawners are progressively replaced by spent individuals
as spawning occurs. The decline in spawner proportions aligns with
the steepest rise in spent proportions and could be an indication of
spawning. However, it is worth noting that we also observed that the
overall CPUE of both spent and spawner individuals dropped after the
peaks in spawner abundance. To explore this finding, we developed an
indicator to quantify the potential shortfall in the spawning population
following the peaks (see Figure S1 for details). Our results revealed that
after these peaks, a portion of the spawners appears to be missing from
the pool of fish that spawn in a given year. This suggests that some
spawners may have become temporarily inaccessible to the fishery. In
South Georgia, Bamford et al. (2024) suggested that spawner feeding
behavior could significantly contribute to the observed decline in total
CPUE (all maturity stages) of Patagonian toothfish in July. A similar
mechanism could be at play in Kerguelen, where spawners may ex-
hibit different feeding behaviors compared to other maturity stages. If
spawners reduce feeding activity during the spawning season, they may
become less susceptible to being caught by fishing vessels. A dedicated
analysis focusing on the transitions between different maturity stages
— including estimating transition probabilities — would be valuable
to better assess which stages may be underrepresented during the
spawning season.

4.3. *Imbalanced sex-ratio among the spawners*

In the reproductive population, the sex ratio is strongly male-
biased, with males accounting for nearly 80% of individuals. This
imbalance can be primarily attributed to the significantly smaller size
at first maturity in males (60 cm) compared to females (80 cm) (Yates
et al., 2018). This male-biased sex ratio could also be explained by
the occurrence of skip spawning, when oocyte development begins
but is interrupted (Rideout et al., 2005), among the females. Yates
et al. (2018) showed that some Patagonian toothfish females fail to
commence vitellogenesis or resorb oocytes entering into vitellogenesis,
leading to fewer female spawners than males in a given year. Similarly,
in South Georgia, Everson and Murray (1999) reported that 25 to 43%
of sexually mature females did not reach spawning condition. This be-
havior has also been observed in the Northeast Arctic stock of Atlantic
cod (Gadus morhua), where Jørgensen et al. (2006) and Skjæraasen
et al. (2012) found that up to 30% of the sexually mature biomass
(males and females) may skip spawning. Factors such as food avail-
ability or environmental conditions could also influence the frequency
of skip spawning. Analysis of the spawners’ histology is required to
quantify the frequency of skip spawning. Also, comparing maturity
stage assessment on vessels and histology assessments in the lab could
also help to evaluate the reliability of the maturity stages observed on
the vessels.
## 4.4. Movements of spawners

In the Falkland Islands, Lee et al. (2022) showed that only 10% of the recaptured fish from a 5-year satellite tags program undertook southbound movements towards spawning grounds and suggested that spawners may move toward spawning grounds only a few times in their life cycle rather than annually. Brown et al. (2013) used satellite tags on Patagonian toothfish around the Falkland Islands to investigate movements of toothfish and indicated spawners repeatedly moved into shallower waters during the spawning season. In the Kerguelen Plateau, in Heard and McDonald Islands, Ziegler et al. (2021) conducted an analysis of tag-recapture data and found that only a few female Patagonian toothfish spawners moved into the French EEZ and it seems that the sex of an individual likely influences its capacity to undertake long-distance movement. In South Georgia, Brigden et al. (2017) highlighted movements of spawners during spawning, but these seemed to be linked to the depth, with spawning females demonstrating upslope movements from May to June and from July to August.

## 4.5. Inter-annual variability of spawning and impact of environmental conditions

Due to limited and sporadic fishing during austral winter before 2020, our analysis focused on five years (2020 to 2024). Although recent increases in fishing effort improved the spatial resolution of spawner data, yearly coverage remained insufficient to assess inter-annual variations. In contrast, long-term monitoring around South Georgia has revealed some temporal variability in spawning, with spawning occurring slightly later in the season. Brigden et al. (2017), Bamford et al. (2024). With more consistent data, future analyses could evaluate spawning site fidelity, a key factor for assessing vulnerability to environmental and anthropogenic pressures (Lowerre-Barbieri et al., 2017). Limited pre-2020 sampling also hindered the integration of environmental covariates, despite growing evidence of climate change impacts in the Southern Ocean. The Antarctic Polar Front (APF) has shifted south during warmer interglacial periods, intensifying surface warming (Civel-Mazens et al., 2021). Marine heatwaves and increased climate velocities are also predicted in the region (Su et al., 2021; Azarian et al., 2023). Rising ocean temperatures can alter spawning phenology, reproductive success, and gamete quality (Sims et al., 2004; Donelson et al., 2010; Fincham et al., 2013; Luo et al., 2017). In Kerguelen, our analysis revealed that female spawner hotspots were displaced south from May to September (Figure S6), potentially linked to temperature gradients. As ocean warming continues, southern areas may become more favorable for spawning, possibly reducing reproductive activity in the western sector.

## 4.6. Contributions of the spawning grounds to effective larval recruitment

Mori et al. (2016) reported high levels of self-recruitment as well as connectivity from the western to the eastern areas. Our research suggests that eggs are released in deep areas, at depths between 1500 and 1800 m and in shallow areas in the north, with hatching occurring several months post-spawning. The larval stage appears to be pelagic (Koubbi et al., 1990; North, 2002; Collins et al., 2010). The nursery areas seem to be located on the eastern and northern side of the plateau (Lord et al., 2006; Duhamel and Hautecoeur, 2009; Mori et al., 2016). However, it remains unclear which specific spawning areas contribute most effectively to successful recruitment and how the Polar Front may influence the trajectories of eggs released from these areas.

## 4.7. Fishery management implications

Patagonian toothfish stock inhabiting the northern part of the Kerguelen Plateau (French EEZ) is assessed each year using a stock assessment model developed with Casal2 software (Massiot-Granier et al., 2023). This model integrates a wide range of data and estimates the spawning stock biomass (SSB) from the recruitment process and the catches. However, currently, the SSB does not account for sex ratios between males and females or differences in spawning dynamics. An initial step to improve the stock assessment models would be the transition to a sex-specific model that distinguishes between females and males in life history phases. Additionally, the spatial and temporal dynamics of spawning, as identified in this study, could be integrated into the model to better reflect actual biological processes. For example, Grüss et al. (2024) used a spatially explicit population model (SPM) to evaluate the impacts of a MPA on the Ross Sea region (Antarctic toothfish fishery). Under the MPA scenarios, the SPM predicted larger immature, mature, and total biomasses than under the no-MPA scenarios.

Understanding where and when spawning occurs is an integral part of sustainable management. Our models predicted high densities of spawners at a detailed scale (weekly and with a resolution of 10 km). In the French Kerguelen EEZ, five MPAs with prohibited fishing are in force; they include the top part of Skiff bank and a large part of the shelf (< 500 m) (TAAF, 2006) (Fig. 1). However, the spawner hotspot and the Skiff MPA only partially overlap, and an area between the Skiff Bank and the 500 m isobath remains open to fishing while being identified as a spawning aggregation zone (Fig. 8). The effects of fishing closures during spawning are well-documented: they reduce the fishing mortality on spawners, reduce the risk of over-exploitation, avoid negative effects on spawning habitats (van Overzee and Rijnsdorp, 2015). Fishing on spawning grounds can disrupt aggregation behavior, cause high mortality among spawners, or damage spawning habitats (Dean et al., 2012; Clarke et al., 2015; van Overzee and Rijnsdorp, 2015). Various measures can be implemented to protect the spawners. In South Georgia, benthic closed areas (BCA) and toothfish spawning areas overlap, thereby reducing fishing pressure on spawners (Bamford et al., 2024). In Burdwood Bank (south of the Falkland Islands), fishing is closed during spawning time. When the duration and sites of spawning aggregations are well defined, seasonal fishery closures may be well-suited (Grüss et al., 2014) potentially leading to increases in catch and abundance (Eklöf et al., 2023). Moreover, seasonal spawning closures are appropriate for fisheries where spawning behavior and the impacts of fishing on spawning dynamics are not well understood (Eero et al., 2019). Before implementing seasonal closures, the consequences on fleet behavior should be investigated, as suggested by Rybicki et al. (2021), since bycatch could increase if fishing effort is shifted to other locations. Additionally, it is crucial to ensure that seasonal fishing closures do not result in increased pressure on juveniles. To summarize, seasonal fishing closures targeting the most critical spawning areas could be an effective tool to increase Patagonian toothfish recruitment. Such measures should have a limited impact on fishing activity while protecting spawners from disruption and overfishing (Armstrong et al., 2013).

## 4.8. Conclusion

Our models revealed strong spatial and temporal patterns in the distribution of toothfish spawners in the Kerguelen EEZ. We showed that the spawners tend to aggregate in June and July in restricted areas located in the western side of Kerguelen waters, along the 1500 m isobath and very locally in shallow areas around 500 m. Moreover, we found that there was an overlap between male and female hotspots, but further investigation is needed to understand the movement patterns and potentially assess differences between movements of male and female spawners. The knowledge gained from our models is important
for defining spawning areas and refining spatial management in the Kerguelen EEZ. Our findings are also the first steps toward a better understanding of the recruitment process, in which spawning plays a major role.

### CRediT authorship contribution statement

**Fanny Ouzoulias:** Writing – original draft, Visualization, Validation, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.
**Clara Péron:** Writing – review & editing, Supervision, Investigation, Funding acquisition, Conceptualization.
**Félix Massiot-Granier:** Writing – review & editing, Validation, Methodology, Investigation, Formal analysis, Conceptualization.

### Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Acknowledgments

This work was financially supported by the administration of the Terres australes et antarctiques françaises (TAAF) and the direction générale des affaires maritimes, de la pêche et de l'aquaculture (DGAMPA). We thank the fishery inspectors who collected the data as well as the fishing companies for their support and involvement. We are grateful to Charlotte Chazeau, Nicolas Gasco, Marion Kauffmann and Alexis Martin for their useful comments and contribution to database management. We also thank the reviewers for their helpful comments on this manuscript.

### Appendix A. Supplementary data

Supplementary material related to this article can be found online at https://doi.org/10.1016/j.fishres.2025.107422.

### Data availability

The authors do not have permission to share data.

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