# I sink therefore I am: 20 years of tagging small cetacean carcasses in the North-East Atlantic for bycatch estimation

Hélène Peltier, Matthieu Authier, Willy Dabin, Pierre Daniel, Cécile Dars, Fabien Demaret, Eleonore Meheust, Vincent Ridoux, Jérôme Spitz, Olivier Van Canneyt

<figure><img src="image_1.png" /></figure>

## To cite this version:

Hélène Peltier, Matthieu Authier, Willy Dabin, Pierre Daniel, Cécile Dars, et al.. I sink therefore I am: 20 years of tagging small cetacean carcasses in the North-East Atlantic for bycatch estimation. Journal for Nature Conservation, 2025, 87, 10.1016/j.jnc.2025.127005. hal-05221520

HAL Id: hal-05221520

https://hal.science/hal-05221520v1

Submitted on 25 Aug 2025

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

Check for
updates

# I sink therefore I am: 20 years of tagging small cetacean carcasses in the North-East Atlantic for bycatch estimation

Hélène Peltier<sup>a, *</sup>, Matthieu Authier<sup>a</sup>, Willy Dabin<sup>a</sup>, Pierre Daniel<sup>b</sup>, Cécile Dars<sup>a</sup>, Fabien Demaret<sup>a</sup>, Eleonore Meheust<sup>a</sup>, Vincent Ridoux<sup>a, c</sup>, Jérôme Spitz<sup>a, c</sup>, Olivier Van Canneyt<sup>a</sup>

## ARTICLE INFO

**Keywords:**

Bycatch
Common dolphins
Harbour porpoises
Plastic tags
Drift modelling
Bay of Biscay

## ABSTRACT

For common dolphin (*Delphinus delphis* Linnaeus, 1758) and harbour porpoise (*Phocoena phocoena* Linnaeus, 1758), bycatch levels exceed the thresholds in the North-East Atlantic. Reverse drift modelling was developed to infer bycatch from stranding data. It is then necessary to define three parameters: the proportion of carcasses that float, the probability of a floating carcass drifting until stranding; and finally, the proportion of beached carcasses that are discovered and reported. The proportion of floating carcasses is the most influential corrective factor in the reverse drift modelling process. The objective of this study is to provide a better estimation of this proportion following bycatch in fishing gear. The predicted drift of 455 common dolphins and harbour porpoises that were tagged and discarded by fishing vessels was calculated by a drift prediction model (MOTHY). Of the tags deployed, stranding was predicted for 309 carcasses (278 common dolphins and 31 harbour porpoises), and 84 animals were discovered (78 common dolphins and 6 harbour porpoises). Bycatch in trammel nets and in midwater pair trawls resulted in a higher probability of these carcasses being recovered stranded. The predicted duration of the drift, on the other hand, had a negative effect on the number of strandings observed. The percentage of harbour porpoises that float was 27% (95% CI [12%,43%]), while it was 31% (95% CI [24%, 39%]) for common dolphins. These results contribute to the improvement of estimates of bycatch of small cetaceans inferred from strandings, which are used to inform conservation measures, particularly for the common dolphin in the North-East Atlantic.

## 1. Introduction

All European directives governing cetacean conservation are largely based on the idea of keeping the level of removals due to anthropogenic activities below a threshold such that long-term population viability is maintained with high probability (Marine Strategy Directive (Directive 2008/56/EC)). The Habitats Directive (Directive 92/43/EEC) and the Common Fisheries Policy (Regulation 1380/2013) require 'bycatch of sensitive species is minimised and where possible eliminated' (Article 12 of Habitats Directive, and Article 3 of the Technical Measures Regulation of the Common Fisheries Policy). This requires a good understanding of anthropogenic mortality, which needs to be estimated both to set thresholds such as those calculated by the Removals Limit Algorithm

and to assess whether or not conservation measures need to be taken (Ouzoulias et al., 2024). In European waters, death in fishing gear remains the main cause of mortality for many species of small cetaceans (Bjørge et al., 2013; Carlén et al., 2021; de Boer et al., 2012; Fernández-Contreras et al., 2010; Peltier et al., 2016). For some of them, such as common dolphin (*Delphinus delphis* Linnaeus, 1758) and harbour porpoise (*Phocoena phocoena* Linnaeus, 1758), the two most abundant species in the North-East Atlantic and the North Sea, these bycatch levels exceed the thresholds set according to the different conservation objectives used in the various national and international agreements and regulations (ICES, 2021, 2023a; Taylor et al., 2022). Currently available bycatch estimates are based usually on observer programmes onboard fishing vessels governed by Regulation 2019/1241 of the Common

<footnote><sup>a</sup> Observatoire Pelagis, UAR 3462, La Rochelle Université/CNRS, 5 allées de l'Océan, 17000 La Rochelle, France</footnote>

<footnote><sup>b</sup> Météo-France, Direction des Opérations pour la Prévision, Département Prévision Marine et Océanographique, 42 Avenue Coriolis, BP 45712, 31057 Toulouse, Cedex 1, France</footnote>

<footnote><sup>c</sup> Centre d'Etudes Biologiques de Chizé, UMR 7372, La Rochelle Université/CNRS, 5 allées de l'Océan, 17000 La Rochelle, France</footnote>

<footnote>* Corresponding author.
E-mail address: hpeltier@univ-lr.fr (H. Peltier).</footnote>
Fisheries Policy (Regulation 1380/2013).

Although observer data are theoretically the most direct source of information on small cetacean bycatch at fishery-scale, it is often hampered by logistical and human constraints. The deployment of observers according to a predefined sampling plan is very rarely adhered to (due to non-compliance or security reasons for example), and the embarkation of observers remains at the discretion of the captain. The refusal to take observers on board may be linked to the space available on board, the absence of administrative documents allowing them to be taken on board, or simply the refusal of the captain (Amandè et al., 2012; Benoît and Allard, 2009; Faunce and Barbeaux, 2011; ICES, 2023a; Murphy et al., 2019). Possible changes in fishing practices in the presence of an observer have also been described (Benoît and Allard, 2009). Any method able to generate accurate bycatch estimates from data whose collection does not depend on fisheries themselves is thus desirable. One important source of data on marine mammal mortality is strandings, and a new method, named reverse drift modelling, was developed to capitalize on these data (Peltier et al., 2016). The method seeks to infer bycatch at sea from stranding data. The observed number of stranded dead cetaceans ($N_{stranding}$) is a function of the total population size (Abundance), the mortality rate (including both natural and anthropogenic sources), the probability of a dead animal floating (buoyancy), the probability of a floating dead animal drifting to a coast and getting stranded (drift), and the probability of a stranded carcass being discovered and reported (discovery) (eq. (1)).

$$N_{stranding} = f(\text{Abundance}, \text{mortalityrate}, \text{buoyancy}, \text{drift}, \text{discovery}) \quad (1)$$

(eq. (1), from (Peltier et al., 2016))

The number of animals that die at sea is the result of the abundance of the population multiplied by the mortality rate at sea. In order to estimate the mortality, it is necessary to define three parameters: the probability of floating (or the proportion of carcasses that float just after death), the probability of a floating carcass drifting until it reaches a coast; and finally, the proportion of beached carcasses that are discovered and reported. If all parameters can be estimated, the estimation of deaths at sea can be achieved on the basis of stranded animals.

In practice, this approach has been applied to strandings of marine megafauna ($N_{stranding}$), using a drift model to identify the spatial origin of their death (inferring the duration of the drift from the state of decomposition) (Peltier and Ridoux, 2015). The distribution of this mortality is then corrected by probability of stranding, derived from theoretical calculations designed to identify the probability of a floating dead dolphin drifting ashore (drift). Finally, the discovery and the proportion of floating animals (buoyancy) constitute the last two corrective parameters. This approach makes it possible to obtain maps of bycaught animals, as well as total numbers of bycatch at sea inferred from strandings.

In France, a stranding network has been in operation for more than 40 years all along the coast; all the protocols and data collected are centralised at national level. The probability of discovery of a stranded cetacean on the French seaboard is assumed to range between 80 % and 97.5 % (Peltier et al., 2016). The drift of animals under the influence of drift currents can be calculated using the MOTHY model, which was developed by Météo-France and subsequently adapted for use with cetacean drift (Daniel et al., 2002; Peltier et al., 2012). Despite the development of numerous drift models since the 1970 s, these models have been primarily designed to predict the drift of particles that drift at the same speed as the body of water in which they are located. MOTHY in its object-based version, is distinguished by its unique capacity to model the drift of a solid object of known dimensions, thereby accounting for the effects of wind, tides and currents on the surface layer and the emerged portion of the object. Whilst the other models in existence are consistent in their ability to predict the drift of particles (including oil spills, plankton or currents alone), the object-based version of MOTHY is more relevant in terms of predicting the drift of cetacean carcasses.

Between 2004 and 2009, 100 small cetaceans were tagged with plastic tags onboard fishing vessels; the majority were common dolphins (n = 86) bycaught on board pelagic pair trawls (Peltier et al., 2016, 2012). The drift of these marked carcasses was predicted by MOTHY (from bycatch location to the potential stranding site) in order to ascertain whether the drift conditions would result in stranding. Among the carcasses for which stranding was predicted, the proportion of those that were actually found could be estimated (8 recovered on 62 predicted to strand, Peltier et al., 2016). Given the heavy use of French coastlines, it was assumed that the animals that were not found when the stranding was predicted had sunk. The percentage of animals that float and may drift has then been estimated as 18 %. The 95 % confidence interval spanned 9 % – 29 % highlighting uncertainty in this key parameter to estimate at-sea bycatch. Given the current conservation challenge posed by high levels of bycatch of small cetaceans in Europe, it is essential to have the most robust estimates available. The probability of floating is the most influential corrective factor in the reverse drift modelling process, and with the resumption of the at-sea carcass tagging programme in 2018, this parameter will need to be updated.

The objective of this study is to provide a better estimation of the proportion of animals that float during the drift process following bycatch in fishing gear, based on six additional years of data collected through the tagging deployment programme. Furthermore, these tags will help reduce the existing uncertainty surrounding the drift predictions of the MOTHY model, which serves as the central tool in this reverse drift method (Peltier et al., 2016).

## 2. Material and methods

The study area covered the Bay of Biscay, the Western Channel and the Celtic Sea in the North-East Atlantic (Fig. 1).

### 2.1. Bycatch and tag deployment

Since 2004, uniquely numbered non-releasable plastic tags are distributed systematically to fisheries observers during their training and to representatives of local fisheries committees or producers' organisations, who then distribute them to fishers. The responsibility for deploying the tags on the bycaught cetacean rests with the observers or fishers themselves. No target number of tagged animals is set, and tagging remains on a voluntary basis. It is therefore not possible to control the deployment of the tags, or how representative they are of all the fleets. The deployment of tags also depends on the involvement of fishing professionals in various programmes to study bycatch, which has fluctuated significantly since 2004. It is still underway in 2025.

The tags comprise a plate with a unique identifier and the telephone number of the national stranding network, which is available 7 days a week (Fig. 2). A tag weighs just 6 g, and is unlikely to have any effect on the buoyancy of individuals.

When a cetacean is bycaught and subsequently brought into the boat as a dead specimen and a tag is attached, the optimal method of attachment involves a non-releasable tag sealed around the caudal peduncle, except in instances where disentanglement measures have resulted in damage to the caudal fin, in which case the pectoral fin serves as a suitable alternative site for attaching the tag. Standardized data are gathered either by the fisheries observer or the fisherman as appropriate, and include the tag release date and time, as well as the latitude and longitude of the location, the gear used and targeted fish species.

Data are conveyed through either direct transmission by fisheries observers or via local referents. It is important to note that all information shared remains anonymous.

When a tagged animal is discovered stranded, the national stranding network is alerted and follows the standardized protocol for small cetacean strandings.

When the release positions seem inconsistent with the fishing habits
<figure><img src="image_5.png" /><figcaption>**Fig. 1.** European waters and study area (red rectangle). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

of the fleet or with the place where the tagged animal was found, then the position of the carcass release is checked using the positions of the boats via the Vessel Monitoring System. If the position is consistent with that of the boat, then the data is retained, otherwise it is deleted.

the stranding network or the Observatoire Pelagis can intervene based on the cetacean's level of decomposition. The intervention protocol is followed accordingly.

## 2.2. The French stranding network

The French stranding network (Réseau National Echouages, named RNE), established in the 1970s and deemed stable since 1990 (Authier et al., 2014), consists of 400 members who participate in stranding interventions as part of their professional duties or voluntary efforts. The network comprises numerous agents of marine protected areas, veterinarians, biologists, and naturalists who have all been trained in accordance with standardised protocols (https://www.observatoire-pelagis.cnrs.fr/wp-content/uploads/2021/03/GuideEchouages2015.pdf).

Strandings are subject to regulatory oversight with regard to protected species, and there is an obligation to report them (Ministère de l'Environnement, de l'Energie et de la Mer, 2017). They are usually reported by individuals who frequent the coastline, such as walkers or regular users, but also by local councils, fire brigades or police officers, when they are warned directly by the general public.

Once the animal is transported to municipal facilities, members from

## 2.3. The drift prediction model MOTHY

The MOTHY model was originally designed to predict the drift of oil slicks and has since been adapted to predict the drift of floating objects, including containers, drifting boats, and even human bodies (Daniel et al., 2002). Subsequently, the model was parameterised to simulate the drift of small cetacean carcasses (Peltier et al., 2012).

On the continental shelf of the Bay of Biscay, wind and tidal currents are the primary factors influencing the drift of carcasses. Meteorological data are provided at six-hour intervals by the European Centre for Medium-range Weather Forecasts (ECMWF), while the bathymetry used is supplied by the French hydrographic and oceanographic service of the Navy (Service Hydrographique et Océanique de la Marine, SHOM).

In this study, the direct version of the MOTHY model is employed, whereby the trajectory is predicted from the bycatch zone at sea to the potential stranding site.

In order to calculate the drift, MOTHY requires the coordinates of the start of the drift, the diameter of the animal (set at 32 cm for common
<figure><img src="image_6.png" /><figcaption>Fig. 2. Photos of deployed tags.</figcaption></figure>

dolphins based on a set of *in situ* measurements, Peltier et al., 2012), and finally its immersion rate (proportion of the carcass immersed, based on *in situ* measurements and modelling, Peltier et al., 2012). As it is not always possible to take measurements on board fishing vessels, it was decided to assign the same average diameter to all individuals.

## 2.4. Stranding and trajectory modelling

The predicted drift of tagged animals was calculated by MOTHY for a maximum of 25 days (Fig. 3). This time interval represents the upper limit for a dolphin discovered in an advanced state of decomposition, thereby rendering it impossible to ascertain with certainty whether the tag deployed around the dolphin peduncle remains in situ.

In the case of animals whose stranding is predicted and for which the tag has been found, the shortest distance between the observed stranding point and the predicted trajectory is calculated using the *distm* function from *geosphere* package version 1.5–18 (Hijmans, 2022). This function is employed to estimate the shortest distance between two points on a WGS84 ellipsoid. Additionally, the difference in days between the predicted grounding date and the actual stranding date was calculated. All analyses were performed in the R software environment (version 4.3.1; (R Core Team, 2023)). Maps and graphs were produced with the *ggplot2* package (Wickham, 2016).

## 2.5. The apparent stranding rate

The apparent stranding rate is defined as the proportion of dead animals that are stranded. In this case, it is calculated as the ratio between the number of animals tagged and the number of tagged individuals reported stranded to the French stranding network within 25 days of tag deployment.

## 2.6. Parameters influencing carcass recovery

The underlying assumption for the stranding or not of a carcass whose drift model predicts stranding is that those not found have sunk. This analysis therefore evaluates indirectly the effect of different parameters on the buoyancy of carcasses through actual strandings.

Among carcasses whose stranding is predicted, the effect of each parameter on their actual stranding at the coast (and indirectly their

buoyancy) is modelled by logistic regression with a logit link. The discovery of a carcass on the coast when its stranding is predicted is considered to be a process that follows a binomial distribution (0: unobserved stranding, 1: observed stranding). Bias-Reduced Generalized Linear Models (brglm) were used to reduce the parameter estimation bias often induced by binomial models (package *brglm* version 0.7.2, Kosmidis, 2021; Kosmidis and Firth, 2021). Bias reduction procedures are a set of statistical methods that are employed to calculate estimates with improved frequentist properties (i.e. bias and mean squared error). These estimates are always finite, even in cases where the maximum likelihood estimates are infinite (i.e. data separation). Tested parameters are distance from the coast, longitude and latitude of the release, gear used, target fish species, bycaught species, type of tagging (fishery observer or fisherman self-sampling), and duration of predicted drift.

The level of significance was set at *P*-values < 0.05.

Particularly well-suited to logistic regressions, we used McFadden's pseudo-R2 to assess the fit of the model (Smith and McKenna, 2013).

It is calculated following equation (2):

$$R2McF = 1 - \ln(LM) / \ln(L0) \qquad (2)$$

where $L_M$ is the likelihood for the model being estimated, and $L_0$ is the value of the likelihood function for a model with no predictors.

Its value lies between 0 and 1, being the value for maximum model fit. In practice, however, the value of 1 is never reached and a McFadden's pseudo-R2 of between 0.2 and 0.4 is considered good for logistic regression (Hu et al., 2006; Veall and Zimmermann, 1996).

## 2.7. Proportion of buoyant animals

The method employed to estimate the proportion of animals that either float or sink during stranding process is that described by Peltier et al. (2016).

As there are currently no direct measurements of the proportion of animals that float, this is linked to the probability of a stranded carcass being discovered.

This proportion of floating carcasses can be considered the outcome of a binomial process:

$$n_{\text{found}} \text{ Binomial}(N_{\text{predicted}}, p_{\text{buoyant}}, p_{\text{discovery}}) \qquad (3)$$
<figure><img src="image_7.png" /><figcaption>Fig. 3. Different examples of trajectories of tags predicted to strand and found stranded (A) and tags not predicted to strand (B).</figcaption></figure>

where $p_{discovery}$ is the probability to report a stranding and $p_{buoyant}$ is the probability that a tagged carcass float after release from fishing gear and along its drift. An informative prior was elicited for $p_{discovery}$: given the stability of the French National Stranding Network since 1990 (Authier et al., 2014), $p_{discovery}$ was elicited to have a 95 % credible interval of 0.800–0.975 with 0.95 probability using the software Parameter Solver v3.0 (Cook et al., 2013). The resulting beta distribution is $p_{discovery}$ Beta(36, 3.71).

To improve the estimation of $P_{buoyant}$, we used the ‘add two successes and two failures’ rule (Agresti and Coull, 1998) and implemented the following model in WinBUGS v1.4.3 (Lunn et al., 2000):

$$ \begin{cases} (n_{\text{found}} + 2) \text{Binomial}(N_{\text{predicted}} + 4, p_{\text{buoyant}}p_{\text{discovery}}) \\ p_{\text{discovery}} \text{Beta}(36, 3.71) \\ p_{\text{buoyant}} \text{Beta}(1, 1) \end{cases} \quad (4) $$

The cut() function was used on the parameter $p_{discovery}$ to ensure that the estimate of $P_{buoyant}$ is conditional on $P_{discovery}$. Four chains were run for 20,000 iterations. The first 10,000 were discarded as burn-in, and 1 iteration out of 10 was kept for posterior inference. The final posterior sample was thus 1,000 iterations per chain. The Gelman-Rubin

diagnostic suggested model convergence (Cowles and Carlin, 1996).

### 3. Results

#### 3.1. Tag deployment

Between 2004 and 2023, 455 tags were deployed on 407 common dolphins and 48 harbour porpoises (Fig. 4). The majority of carcasses were tagged in the waters of the Bay of Biscay (96.3 % in ICES areas 8abd), and nearly all tags were deployed in the continental shelf area, as only four of them were released in waters with bathymetry exceeding 200 m depth (0.9 %) (Fig. 4).

More than half of individuals were tagged during bycatch events involving a single individual (54.0 % of tags deployed), while 32.2 % of tags were deployed during the bycatch of 2 to 5 individuals during the same fishing operation. Finally, 51 cetaceans (11.1 %) were tagged during a bycatch event involving 6 to 11 individuals simultaneously (raw data in supplementary material, but waiting for DOI). Hence, the tagged individuals have been released at 310 different locations.

In addition to these individuals, 55 deployed tags were excluded from the analysis. These were 33 individuals tagged in 2004 and 2005,
<figure><img src="image_8.png" /><figcaption>**Fig. 4.** Tags deployed between 2004 and 2023 on bycaught common dolphins (n = 407) and harbour porpoises (n = 48).</figcaption></figure>

but from which internal samples (stomach, kidneys, gonads, etc.) had been taken. As these could potentially affect the buoyancy and decomposition of the carcasses, these data were excluded from further analysis. In addition, 29 individuals tagged between 2018 and 2023 could not be used due to missing information (tag number or location of tag release).

The majority of tags were deployed in the recent period between 2018 and 2023 (82.7 %, n = 378), while 79 were deployed between 2004 and 2009 (17.3 %) (Fig. 5).

There is a notable seasonal variation, with 40 % (n = 185) of carcasses having been tagged in February alone (Fig. 6) and 73.9 % (n = 338) if the entire winter period is considered (December to March inclusive). It is considered that winter covers the entire risk period for common dolphin bycatch in the Bay of Biscay, i.e. more than the calendar seasons. Spring is considered to be from April to June, summer from July to September, and autumn during October and November. Additionally, there was a slight increase in tagging activity during August and September (11.4 %, n = 52) compared to the spring and autumn periods.

The data indicate that nearly half of the tagged common dolphins were bycaught in midwater pair trawls (48 %), while 50 % were

bycaught in all trawl gear (bottom otter trawls and midwater otter trawls). They are widely distributed on the Bay of Biscay continental shelf, with some being bycaught as far as the continental slope (Fig. 7). But the average bathymetry of tagging areas is 88 ± 102 m and at an average distance of 53.1 ± 35.8 km from the coast, i.e. globally in the central zone of the Bay of Biscay continental shelf (Fig. 4). Only 9 individuals came from the western Channel, from 4 bycatch events. The remaining tags were deployed when fishing with nets (trammel nets, gillnets or undetermined nets). Lastly, for 4 % of tags deployed on common dolphins, the gear used remains unknown. These individuals are generally bycaught closer to the coast, mainly north of 46°N for gillnets, between 46 and 47°N for trammel nets, and north of 47°N for undetermined nets.

For harbour porpoises, all tags were deployed on carcasses bycaught in nets, with the majority (71 %) bycaught in trammel nets, 10 % in gillnets and 2 % in undetermined nets.

The distribution of tagged porpoises bycaught in trammel nets is characterised by an even spread between 44°N and 48°N, encompassing a coastal band with an average distance from the coast of 28.7 ± 27.0 km and bathymetry of 54 ± 29 m (Fig. 8, Table 1).
<figure><img src="image_9.png" /><figcaption>**Fig. 5.** Annual distribution of tag deployment on bycaught common dolphins (pink) and harbour porpoises (turquoise). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>**Fig. 6.** Monthly distribution of tag deployment on bycaught common dolphins (pink) and harbour porpoises (turquoise). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

The species targeted by midwater pair trawls are mainly seabass (*Dicentrarchus labrax* Linnaeus, 1758) and hake (*Merluccius merluccius* Linnaeus, 1758). Trammel nets mainly target sole (*Solea solea* Linnaeus, 1758) and monkfish (*Lophius spp*.), while gillnets mainly target hake and to a lesser extent seabass and pollack (*Pollachius pollachius* Linnaeus, 1758).

## 3.2. *Tags recovery and stranding prediction*

Of the 455 tags deployed, stranding was predicted for 309 carcasses (278 common dolphins and 31 harbour porpoises). A total of 84 animals were discovered: 78 were common dolphins and 6 were harbour porpoises (Table 1). The apparent stranding rate is therefore 19 % for common dolphins, 13 % for harbour porpoises, and 18 % for both
<figure><img src="image_11.png" /><figcaption>Fig. 7. Spatial distribution of tag deployment on bycatch common dolphins according to fishing gears.</figcaption></figure>

species combined.

All the strandings observed on the coast had been predicted by the drift model.

The tags deployed on common dolphins and subsequently found stranded were distributed throughout the continental shelf at an average perpendicular distance of 44.8 ± 32.9 km from the coast (Fig. 9A). Of these, 94.9 % were located north of 45°N. The bycatch was distributed equally between midwater pair trawls and nets (8 % gillnets, 35 % trammel nets and 6 % undetermined nets).

All of the tagged harbour porpoises that were found stranded had been bycaught within a very short distance of the coast (4.2 ± 3.3 km) (Fig. 9B). Two-thirds (67 %) of the animals found were bycaught in trammel nets, while the remainder were caught in gillnets and undetermined nets in equal proportions (17 %).

The mean distance between predicted and observed strandings was 34.9 ± 31.4 km for both species. In particular, the difference in distance was 36.9 ± 31.2 km for common dolphins and 8.4 ± 10.1 km for harbour porpoises (Table 1). The mean predicted drift duration for each species was found to be three days shorter than the observed duration.

### 3.3. Parameters influencing carcass recovery

Of all the parameters tested, bycatch in trammel nets (1.223, p = 0.034) and in midwater pair trawls (1.344, p = 0.042) had a small but significant positive effect on the strandings recorded (Table 2). The predicted duration of the drift, on the other hand, had a negative effect on the strandings observed (−0.09948, p < 0.001).

The extreme coefficients (−1.126e + 15) calculated for bycatch in undetermined nets and bottom otter trawls are associated with very low numbers. They lead to extremely high statistical significance (p < 2e-16), but these coefficients are not reliable.

McFadden's pseudo-R2 was estimated at 0.28. Given its characteristics, this value indicates a good model fit (Veall and Zimmermann, 1996).

### 3.4. Proportion of buoyant animals

For both species together, the proportion of animals that float and are likely to strand as a result of drifting currents was estimated to be 30 % (95 % CI [23 %, 36 %]). The proportion of harbour porpoises that float was 27 % (95 % CI [12 %, 43 %]), while it was 31 % (95 % CI [24 %, 39 %]) for common dolphins.

The limited number of harbour porpoises that have been found stranded does not allow for an examination of the proportion of animals floating at a finer resolution than that of the years 2004 to 2023 as a whole.

For common dolphins, this proportion appears to be slightly higher during the winter and spring period (December to May), reaching 33 % (95 % CI [25 %, 42 %]). The proportion of buoyant is 30 % (95 % CI [17 %, 45 %]) during the summer and autumn months (June to November). The annual distribution of tags found stranded precludes the calculation of an annual estimate of this proportion

The proportion of buoyant common dolphin carcasses that were bycaught in midwater pair or otter trawls was found to be lower (29 %, 95 % CI [21 %, 38 %]) than in trammel nets, gillnets and nets ind. (37 %, 95 % CI [27 %, 49 %]).

## 4. Discussion

### 4.1. Tag deployment

The heterogeneity of tagging since 2004 is mainly linked to the different research programmes that have been followed, which in turn are directly related to the level of strandings of small cetaceans as bycatch in fishing gear. The high levels of bycatch observed at the end of the 1990s led to a major mobilisation of scientists, managers and fishers, who initiated or wanted to take part in programmes to test technical devices and deploy tags. The reduction that followed at the end of the 2000s led to a decline in interest in these issues and probably in the mobilisation of the fishing industry (Peltier et al., 2021). Their massive increase since 2016 has brought the issue back into the spotlight, mobilising all the actors previously involved. The bimodal structure of the number of tagged animals since 2004 is largely explained by this chronology.

The first studies on the bycatch of common dolphins in the early 2000s showed that they were mainly bycaught in pelagic trawls (ICES, 2020; Morizur et al., 1999). In the early 1990s, up to 130 exclusive pelagic trawlers were operating simultaneously in the Bay of Biscay
<figure><img src="image_12.png" /><figcaption>Fig. 8. Spatial distribution of tag deployment on bycaught harbour porpoises according to fishing gears.</figcaption></figure>

<table><caption>**Table 1**
Summary of tag deployment and associated parameters between 2004 and 2023 on bycaught common dolphins and harbour porpoises.</caption><thead><tr><th>Parameter</th><th>Common dolphins</th><th>Harbour porpoises</th><th>Total small cetaceans</th></tr></thead><tbody><tr><td>Tags released</td><td>407</td><td>48</td><td>455</td></tr><tr><td>Bathymetry of release</td><td>88 m<br/>±102 m</td><td>54 m<br/>±30 m</td><td>84 m<br/>±98 m</td></tr><tr><td>Distance from coast of release</td><td>53.1 km<br/>±35.8 km</td><td>28.7 km<br/>±27 km</td><td>50.5 km<br/>±35.7 km</td></tr><tr><td>Stranding predicted</td><td>278</td><td>31</td><td>309</td></tr><tr><td>Stranding observed</td><td>78</td><td>6</td><td>84</td></tr><tr><td>Apparent stranding rate</td><td>19 %</td><td>13 %</td><td>18 %</td></tr><tr><td>Distance obs. vs. pred. strandings (km)</td><td>36.9 km<br/>±31.3 km</td><td>8.4 km<br/>±10.1 km</td><td>34.9 km<br/>±31.4 km</td></tr><tr><td>Time difference obs. minus pred. strandings (days)</td><td>3 days<br/>±4 days</td><td>3 days<br/>±4 days</td><td>3 days<br/>±4 days</td></tr><tr><td>Proportion of buoyant animals</td><td>31 %<br/>95 %CI [24 %, 39 %]</td><td>27 %<br/>95 %CI [12 %, 43 %]</td><td>30 %<br/>95 %CI [23 %, 37 %]</td></tr></tbody></table>

(Morizur et al., 1999). This fishery, which mainly targeted anchovy, switched to other species such as sea bass, hake and horse mackerel (*Trachurus ssp*) outside the anchovy fishery period. In 1992, up to 70

boats were operating simultaneously in winter, targeting sea bass. The anchovy crisis and the closure of this fishery between 2005 and 2010 never allowed the French fleet to return to pre-crisis levels (Beckensteiner et al., 2024). By 2022, only 5 exclusive pelagic trawlers were operating in the Bay of Biscay, and 55 trawlers were alternating between bottom trawling and pelagic trawling (Demanèche, 2024).

Various national and European programmes have made great efforts to monitor this fishery by 2018. Midwater pair trawlers have been particularly involved in these observation programmes, carrying out most of the tagging themselves or through on-board observers until 2020. It was only from these years that better sampling of gillnets by fishery observers began in the French fishery, highlighting a high number of common dolphin bycatch in the net fisheries (ICES, 2021). Netters constitute the largest fleet in the Bay of Biscay. In 2022, there were 199 exclusive netters and 239 boats operating at least some of the year with nets, alternating with other gears (Demanèche, 2024). While exclusive netters have tended to decrease slightly since 2012, netters diversifying their gears have tended to increase over the same period.

Although the risk of bycatch per day at sea is lower in net fisheries than for midwater trawls, the size of the fleet seems to result in a high number of bycatch (ICES, 2021). Since the end of 2020, the number of small cetaceans tagged on board gillnets and trammel net vessels has increased significantly. It seems that this phenomenon is more related to
<figure><img src="image_13.png" /><figcaption>**Fig. 9.** Spatial distribution of tags deployed (circles) on bycaught common dolphins (A) and harbour porpoises (B), and stranding locations of recovered tags (diamonds).</figcaption></figure>
<table><caption>**Table 2**
Summary of logistic regression model for tagged carcass strandings.</caption><thead><tr><th></th><th>Estimates</th><th>Std. Error</th><th>Z-value</th><th>P-value</th></tr></thead><tbody><tr><td>Intercept</td><td>-13.25</td><td>12.56</td><td>-1.055</td><td>0.291213</td></tr><tr><td>Distance to the coast</td><td>9.681 x 10<sup>-3</sup></td><td>6.414 x 10<sup>-3</sup></td><td>1.509</td><td>0.131218</td></tr><tr><td>GTR</td><td>1.233</td><td>0.5777</td><td>2.117</td><td>0.034230</td></tr><tr><td>Nets ind.</td><td>-1.126 x 10<sup>15</sup></td><td>6.711 x 10<sup>7</sup></td><td>-1.678 x 10<sup>7</sup></td><td>&lt; 2 x 10<sup>-16</sup></td></tr><tr><td>OTB</td><td>-1.126 x 10<sup>15</sup></td><td>6.711 x 10<sup>7</sup></td><td>-1.678 x 10<sup>7</sup></td><td>&lt; 2 x 10<sup>-16</sup></td></tr><tr><td>OTM</td><td>0.3801</td><td>1.937</td><td>0.1960</td><td>0.844448</td></tr><tr><td>PTM</td><td>1.344</td><td>0.6617</td><td>2.032</td><td>0.042181</td></tr><tr><td>P. phocoena</td><td>-2.439</td><td>1.535</td><td>-1.589</td><td>0.111979</td></tr><tr><td>Self-sampling</td><td>0.5496</td><td>0.4994</td><td>1.101</td><td>0.271082</td></tr><tr><td>Longitude</td><td>0.3136</td><td>0.2568</td><td>1.221</td><td>0.221971</td></tr><tr><td>Latitude</td><td>0.2654</td><td>0.2768</td><td>0.9590</td><td>0.337691</td></tr><tr><td>Drift duration predicted</td><td>-9.948 x 10<sup>-2</sup></td><td>2.633 x 10<sup>-2</sup></td><td>-3.778</td><td>0.000158</td></tr></tbody></table>

the growing involvement and awareness of fishers than to a sudden increase in the risk of bycatch in 2020.

The seasonality of tag deployment is very strongly correlated with the known seasonality of bycatch, as indicated by stranding monitoring (ICES, 2020, 2023a). It is therefore not surprising that the number of tags deployed is higher in the winter months and, to a lesser extent, in August, when stranding events have been observed in southern Brittany since 2017 (Dars et al., 2023).

The analysis of these tags is not a reliable method for quantifying the risk of bycatch or for identifying the fisheries that are most at risk of impacting small cetaceans. Indeed, as tagging is voluntary, the data do not provide quantitative information on the prevalence of bycatch events. It seems probable that not all fisheries deploy tags in the same way, and that in the absence of a regulatory framework this practice remains relatively sporadic. The discrepancy between the number of tags deployed and the number of strandings of small cetaceans with evidence of bycatch, and above all with the estimated mortalities due to bycatch at sea, confirms the likely low representativeness in terms of metiers of the sampling carried out (Dars et al., 2023; ICES, 2023a).

Nevertheless, it can be reasonably deduced that the dataset of carcasses collected in French waters is the largest published and was collected over the longest time interval, thus allowing for the study of the drift and buoyancy of marine animals (da Cunha Ramos et al., 2024).

Numerous studies have been carried out to interpret the representativeness of strandings in relation to deaths at sea (Bibby and Lloyd, 1977; Hart et al., 2006; Koch et al., 2013; Santos et al., 2018), particularly in the case of oil spill consequences (Degange et al., 1994; Flint and Fowler, 1997; Hlady and Burger, 1993; Hope Jones et al., 1978). These approaches mainly consist of releasing into the sea carcasses found stranded or artefacts (tyres, foam, blocks of wood), in order to assess the apparent stranding rate. It can be highly variable depending on wind and current conditions, which may or may not favour stranding (Flint and Fowler, 1997).

A very similar study was carried out in the Galicia region of North-Western Spain, at a much smaller scale. Between 2007 and 2012, 24 plastic tags were deployed on common dolphins bycaught in fishing gear using a protocol similar to that used in France (Deslias et al., 2024). Of these carcasses, 10 were predicted to be stranded by the MOTHY drift model adapted to the Iberian Peninsula, and only 5 were found stranded. This approach suggests an apparent stranding rate of 21 %.

## 4.2. The discovery of strandings

Of the 455 tags deployed in the Bay of Biscay, 309 were predicted to result in stranding, yet only 83 were observed to be stranded. The difference between predicted and observed strandings could be influenced by factors other than the fact that a proportion of the animals sink.

Firstly, it is possible that the animals were not detected by the French national stranding network. Nevertheless, while some animals may be undetected, it appears that the reporting of strandings in France has remained consistent since the 1990s (Authier et al., 2014). Indeed, since 1988, the reporting of strandings to the RNE by local administrations has been mandatory (https://www.legifrance.gouv.fr/loda/id/J ORFTEXT000024396902). Moreover, in 2020, coastal municipalities constituted 10 % of the population of mainland France and exhibited a considerably higher population density (289 inhabitants per km² in coastal municipalities compared to 113 inhabitants per km² in the rest of mainland France) (Léger, 2024). The advent of the pandemic has seemingly precipitated an acceleration in the process of intensification of coastal uses (Guibert et al., 2024).

The widespread availability of the Internet and the RNE hotline enables the prompt reporting of many strandings, with information transmitted in situ. Furthermore, the Landes county in southern Atlantic coasts of France employs a systematic approach to carcass collection and reporting on a weekly basis. These are then conveyed directly to the RNE. A comparative analysis of strandings reports across French counties reveals no discernible pattern for this region, indicating a consistency in the documentation of cetacean strandings along the French coastline (Authier et al., 2014).

Considering also that strandings are reported all along the French coast, even in inaccessible areas, and also the high rate of re-reporting of stranded carcasses, even during the winter period, it seems implausible that a significant proportion of tagged animals would go unreported. While it remains possible that some stranded animals may not be detected, the incidence of such cases is, in all likelihood, very low especially in recent years given the saliency of the bycatch issue in France where media coverage of cetacean strandings has been high.

Secondly, to mitigate the risk of animals not being detected due to the potential detachment of the tag from the caudal fin as a consequence of decomposition, carcasses that have been identified as being stranded after a period exceeding 25 days (in line with the criteria for a highly putrefied animal, (Peltier et al., 2020) have been excluded from the calculation of the proportion of buoyant animals.

A third factor may be that the model may have incorrectly predicted the drift of these animals, and that stranding was not, in fact, expected. As MOTHY had predicted the stranding of all the animals that were found, it thus seems unlikely that it was inaccurate for all those that were not found. Nevertheless, the five-minute resolution of the model may restrict its capacity to predict drifts in highly coastal areas with specific currents, such as baïnes, longshore drift or river plumes (Peltier et al., 2012). It is notable that these coastal systems play a particularly significant role in the region south of the Gironde estuary (45.5°N). They are capable of generating strong local north-south currents that are not fully captured by the model. In the region north of the Gironde estuary, 70.6 % of the animals predicted to have stranded were not found (n = 180). In contrast, this proportion reached 83.3 % in the region south of 45.5°N (n = 45). Although this hypothesis appears plausible at the regional level, it is unlikely to explain the fate of all the animals that were not found stranded.

The action of scavengers is also a natural process that can lead to the disappearance or sinking of carcasses whose stranding was predicted. In European waters, a significant proportion of scavengers are demersal species (Depestele et al., 2019). Furthermore, it appears that the activity of scavengers is more intense in deep areas than in coastal habitats, likely due to the limited availability of food sources (Reisdorf et al., 2012). Consequently, the consumption of cetacean carcasses is more likely to occur when they sink and lie on the ocean floor.

Taken together, these factors could limit strandings and the detection of tagged carcasses that are predicted to strand. However, they appear to be marginal in Bay of Biscay waters and it can be concluded that carcass buoyancy remains the main factor influencing stranding when drift conditions are favourable.
### 4.3. To float or to sink

If we assume that the majority of tagged cetaceans whose predicted stranding was not observed sank, then 31 % (95 % CI [23 %, 36 %]) of common dolphins and only 27 % (95 % CI [12 %, 43 %]) of harbour porpoises float and can strand on the Atlantic seaboard of mainland France. The proportion of buoyant animals calculated for common dolphins on the basis of the gear in which they were bycaught are of interest in understanding the phenomenon, as strandings rarely enable us to identify the gear responsible for the animal death. Logistic regression shows that drift duration has a negative influence on animal stranding.

The last estimate of this rate was made in 2016, based on 100 tags deployed on common dolphins and harbour porpoises bycaught on fishing vessels between 2004 and 2009 (Peltier et al., 2016). It was then estimated to be 17.9 % (95 % CI [9.3 %, 28.8 %]). This estimated rate is lower than that calculated using the full data set up to 2023. Although the set of 455 tags used in the period 2009–2023 is not representative of all vessels, it was used on a greater variety of gears and seasons than the tags used in the period 2004–2009 alone.

It is widely accepted that the buoyancy of cetaceans is a function of several factors such as body condition, fat content (particularly in bones and blubber), or lung inflation (Moore et al., 2020).

While a few studies have been conducted on the buoyancy of large whale carcasses, there is a paucity of research on the topic in the context of small cetaceans. From the historical record of whaling, it is evident that right whales and sperm whales exhibit positive buoyancy, whereas porqual whales display negative buoyancy at the beginning of the whaling season and float at the end (Nowacek et al., 2001).

Studies of the buoyancy of small cetaceans are generally carried out to understand the physiology of diving. It seems that bottlenose dolphins and porpoises have positive buoyancy (Kipps et al., 2002), but this rapidly becomes negative with depth (70 m for bottlenose dolphins, (Skrovan et al., 1999; Williams et al., 2000). Because of the pressure exerted on the tissues at the moment of death, it is possible that the depth at which death occurred may have an impact on the buoyancy of the dead animal (Moore et al., 2020), as well as the fat content of its bones and blubber.

The speed and quantity of putrefaction gases produced during the decomposition of large whales is often cited as a factor in bringing sunken carcasses to the surface. The internal temperature of large whales after their death rises, reaching 48 °C after 3 days post-mortem, and encourages bacterial production, which promotes decomposition gases (Tonnessen and Johnsen, 1982). The increase in temperature causes fat cells to rupture and leak into the tissues. This reduces the layer of blubber, which in turn reduces buoyancy. This seems to be a more important phenomenon in small individuals, due to the ratio between body surface area and volume (Smith et al., 2015). Although there are no studies on the post-mortem temperature of small cetaceans, those conducted on humans indicate that a body cools twice as fast in water as in air. It reaches ambient temperature in 12 h (Pounder, 1992).

Moreover, below 15 °C decomposition is greatly reduced, as is gas production (Allison et al., 1991; Moore et al., 2020). In the Bay of Biscay, the average surface temperature only exceeds 15 °C between the months of June and November (Costoya et al., 2015), while most intense stranding events occur between December and March (Peltier et al., 2021). To sum up, cetaceans that sink and then rise to the surface under the effect of decomposition gases only do so in specific circumstances: shallow waters, high temperatures and low necrophagous activity, but also the type of bacterial decomposition activity. It thus seems that cetaceans that float and strand constitute a restricted sub-set, with large cetaceans being the most likely to float (Moore et al., 2020).

Despite being tagged and released closer to the shore, the proportion of floating porpoises is less than that of common dolphins. The tagged individuals were found to have been bycaught in bottom fishing gear at an average bathymetry of 23 ± 6 m depth. This result is corroborated by

the preliminary data collected through the Remote Electronic Monitoring programme (REM) on board select gillnet vessels operating in the Bay of Biscay. Between January 2021 and February 2023, REM programme observed more than 4,450 days at sea and 14,000 fishing operations on approximately 20 gillnets and trammel nets in the Bay of Biscay (ICES, 2023b; Vignard and Tachoires, 2023). It is important to note that the sampling effort of the REM programme is based on volunteers and therefore does not represent all fishing gears operated in the Bay of Biscay. During the course of this REM study, 250 marine mammals were observed to have been bycaught, 63 % of which were common dolphins and 19 % harbour porpoises (ICES, 2023b). In comparison, the proportion of harbour porpoise strandings among all cetacean strandings along the French coast of the Bay of Biscay over the period 2019–2022 was found to be only 6 % (Dars et al., 2023). Given the absence of a sampling strategy for the REM equipment, the hypothesis of a higher proportion of porpoises bycaught on board these vessels compared with all the fleets in the Bay of Biscay due to chance cannot be ruled out. Nevertheless, these results are consistent with those obtained from tags deployed since 2004, and suggest that harbour porpoise buoyancy may be more likely to be negative. Previous research on the immersion rate of harbour porpoises (proportion of the carcass immersed) indicated an average immersion of 90 % over 40 days, with a very close to 100 % immersion rate during the first five days after death. However, this study was conducted on a single individual (Peltier et al., 2012).

Finally, whatever the reasons for carcasses not being found stranded, the fact remains that only 19 % of tagged common dolphins and 13 % of tagged porpoises have been found stranded. While the rate in question does indeed fluctuate from year to year, depending on a number of factors including weather conditions and the proportion of animals that float, it nevertheless remains low on average over the period 2004–2023.

### 4.4. What are the implications for the conservation of these species?

While the extensive strandings observed in winter along the coasts of the Bay of Biscay have generated considerable interest and concern among the general public, as well as among non-governmental organisations (NGOs) and managers, the results of this study indicate that they represent only a small proportion of the mortalities that occur at sea. The reverse drift modelling method enables the estimation of bycatch of common dolphins in French waters over a time series extending back to 1990 (Peltier et al., 2016, ICES WKEMBYC 2023). This method is complementary to work derived from observer programmes, incorporating weather conditions prior to stranding, the probability of stranding in the bycatch area, and the proportion of carcasses that float. This parameter represents the most significant corrective factor applied throughout the process. Although it has been possible to calculate the proportions of carcasses floating according to the fishing gear used, these cannot be used operationally. This is because bycatch marks observed on carcasses are rarely gear-specific. However, the proportions calculated for each species can be used to infer bycatch from common dolphins and harbour porpoises strandings.

A significant increase in the number of tags deployed in other areas of the common dolphin and harbour porpoise management units will enable the future estimation of a regionally different proportion for these two species. This is likely to be particularly the case for the harbour porpoise, whose habitat extends from Senegal waters to Svalbard. It is therefore reasonable to assume that the proportion of carcasses that float may be different, given the differing climatic conditions and their consequences for the physiology of these animals.

The deployment of GPS beacons and pressure sensors to estimate the trajectory and depth of the carcasses may assist in refining the estimated parameters and elucidating the various hypotheses regarding the disappearance of the carcasses at sea. An improvement in this knowledge will facilitate a further improvement in estimates of bycatch from
strandings, which are of particular importance given that they form part of the core of management decisions for fisheries in the Bay of Biscay (Conseil d'État, Juge des référés, 22/12/2023, 489926, Inédit au recueil Lebon).

## 5. Conclusion

Since the results of this tagging programme were last published in 2012 and 2016, a total of 355 new tags have been deployed. This has enabled the proportion of individuals floating to be adjusted to 31 % (95 % CI [24 %, 39 %]) for common dolphins and 27 % (95 % CI [12 %, 43 %]) for harbour porpoises. This work thus showed an uncertainty around the MOTHY model's drift predictions of 34.9 km. Despite the deployment of a significantly larger number of tags than in the 2012 study, this uncertainty remains relatively small at the scale of the Bay of Biscay and is accurate enough at the local administrative level of France ("département").

The results of this new work contribute to the improvement of estimates of bycatch of small cetaceans inferred from strandings, which are used to inform conservation measures, particularly for the common dolphin in the North-East Atlantic.

Deploying tags on a larger scale, as well as telemetric beacons to track entire trajectories, particularly for harbour porpoises, could make it possible to provide bycatch estimates throughout European waters, and help to meet the conservation challenges of these protected species.

## Declaration of Generative AI and AI-assisted technologies in the writing process

During the preparation of this work the author(s) used DeepL Write in order to improve the readability and language of the manuscript. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.

## CRediT authorship contribution statement

**Hélène Peltier:** Writing – review & editing, Writing – original draft, Formal analysis, Conceptualization.
**Matthieu Authier:** Writing – review & editing, Formal analysis. **Willy Dabin:** Writing – review & editing, Data curation.
**Pierre Daniel:** Writing – review & editing, Software.
**Cécile Dars:** Writing – review & editing, Data curation.
**Fabien Demaret:** Writing – review & editing, Data curation.
**Eleonore Meheust:** Writing – review & editing, Data curation.
**Vincent Ridoux:** Writing – review & editing, Conceptualization.
**Jérôme Spitz:** Writing – review & editing, Conceptualization.
**Olivier Van Canneyt:** Writing – review & editing, Data curation, Conceptualization.

## Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Helene Peltier reports a relationship with International Council for the Exploration of the Sea that includes: paid expert testimony and travel reimbursement. Helene Peltier reports a relationship with International Whaling Commission that includes: paid expert testimony and travel reimbursement. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgement

This research was funded by the French ministry in charge of environment and by the Office Français de la Biodiversité, France as part of the implementation of the Marine Strategy Framework Directive monitoring programme. Stranding data were collected by the French

stranding scheme Réseau National de suivi des Echouages and its numerous voluntary contributors.

The tags were deployed thanks to the participation of many fishing professionals, whom we would like to thank, as well as the representatives of their producer organizations (Les Pêcheurs de Bretagne, Les Pêcheurs d'Aquitaine, Aglia, OPPAN, OP Vendée) or local committees (CDMEMP 29).

We would also like to thank the fisheries observers from the programs Petracet, Procet, Necectepro, Obsmam, Necessity, Obsmer, PIC, LICADO and DolphinFree for their work on board fishing vessels. And finally, we would like to thank the association CAPENA (Centre pour l'Aquaculture, la Pêche et l'Environnement de Nouvelle Aquitaine), who initiated this program in 2004.

## Appendix A. Supplementary material

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jnc.2025.127005.

## Data availability

Data are attached pending DOI

## References

Agresti, A., & Coull, B. A. (1998). Approximate is better than “exact” for interval estimation of binomial proportions. *The American Statistician*, **52**, 119–126. https://doi.org/10.1080/00031305.1998.10480550

Allison, P. A., Smith, C. R., Kukert, H., Deming, J. W., & Bennett, B. A. (1991). Deep-water taphonomy of vertebrate carcasses: a whale skeleton in the bathyal santa catalina basin. *Paleobiology*, **17**, 78–89.

Amande, M. J., Chassot, E., Chavance, P., Murua, H., de Molina, A. D., & Bez, N. (2012). Precision in bycatch estimates: The case of tuna purse-seine fisheries in the Indian Ocean. *ICES Journal of Marine Science*, **69**, 1501–1510. https://doi.org/10.1093/icesjms/fss106

Authier, M., Peltier, H., Dorémus, G., Dabin, W., Canneyt, O. V., & Ridoux, V. (2014). How much are stranding records affected by variation in reporting rates? a case study of small delphinids in the Bay of Biscay. *Biodiversity and Conservation*, **23**, 2591–2612. https://doi.org/10.1007/s10531-014-0741-3

Beckensteiner, J., Villasante, S., Charles, A., Petitgas, P., Le Grand, C., & Thébaud, O. (2024). A systemic approach to analyzing post-collapse adaptations in the Bay of Biscay anchovy fishery. *Canadian Journal of Fisheries and Aquatic Sciences*, **81**, 1154–1173. https://doi.org/10.1139/cjas-2023-0087

Benoît, H. P., & Allard, J. (2009). Can the data from at-sea observer surveys be used to make general inferences about catch composition and discards? *Canadian Journal of Fisheries and Aquatic Sciences*, **66**, 2025–2039. https://doi.org/10.1139/F09-116

Bibby, C. J., & Lloyd, C. S. (1977). Experiments to determine the fate of dead birds at sea. *Biological Conservation*, **12**, 295–309.

Bjørge, A., Skern-Mauritzen, M., & Rossman, M. C. (2013). Estimated bycatch of harbour porpoise (Phocoena phocoena) in two coastal gillnet fisheries in Norway, 2006–2008. Mitigation and implications for conservation. *Biological Conservation*, **161**, 164–173. https://doi.org/10.1016/j.biocon.2013.03.009

Carlén, I., Nunny, L., & Simmonds, M. P. (2021). Out of sight, out of mind: How conservation is failing european porpoises. *Frontiers in Marine Science*, **8**. https://doi.org/10.3389/fmars.2021.617478

Cook, J., Wathen, J.K., Nguyen, H., 2013. ParameterSolver.

Costoya, X., deCastro, M., Gómez-Gesteira, M., & Santos, F. (2015). Changes in sea surface temperature seasonality in the Bay of Biscay over the last decades (1982–2014). *Journal of Marine Systems*, **150**, 91–101. https://doi.org/10.1016/j.jmarsys.2015.06.002

Cowles, M. K., & Carlin, B. P. (1996). Markov chain monte carlo convergence diagnostics: A comparative review. *Journal of the American Statistical Association*, **91**, 883–904. https://doi.org/10.1080/01621459.1996.10476956

da Cunha Ramos, H. G., Colosio, A. C., Marcondes, M. C. C., Schmidt, A. J., Ghisolfi, R. D., Michalski, B. E., Gonçalves, M. I. C., Baumgarten†, J. E., & Bovendorp, R. S. (2024). An overview of forensic ecology applied for marine megafauna conservation. *Forensic Sci. Int. Anim. Environ.*, **5**, Article 100085. https://doi.org/10.1016/j.fisae.2024.100085

Daniel, P., Jan, G., Cabioc'h, F., Landau, Y., & Loiseau, E. (2002). Drift modeling of cargo containers. *Spill Science and Technology Bulletin*, **7**, 279–288.

Dars, C., Meheust, E., Genu, M., Mendez-Fernandez, P., Peltier, H., Wund, S., Caurant, F., Dabin, W., Demaret, F., Spitz, J., Van Canneyt, O., 2023. Les échouages de mammifères marins sur le littoral français en 2022, Rapport scientifique de l'Observatoire Pelagis. Observatoire Pelagis (UMS 3462 - La Rochelle Université et CNRS).

de Boer, M., Saulino, J., Leopold, M., Reijnders, P., Simmonds, M., 2012. Interactions Between Short-Beaked Common Dolphin (Delphinus delphis) and the Winter Pelagic Pair-Trawl Fishery ff Southwest England (UK). Aquac. Collect.
Degange, A. R., Doroff, A. M., & Monson, D. H. (1994). Experimental recovery of sea otter carcasses at Kodiak Island, Alaska, following the Exxon Valdez oil spill. *Marine Mammal Science*, **10**, 492–496.

Demanèche, S., 2024. Fiche tendance des activités de pêche professionnelle embarquée. Golfe de Gascogne. Années 2012 à 2022 (No. Delmoges project.). IFREMER.

Depestele, J., Feekings, J., Reid, D.G., Cook, R., Gascuel, D., Girardin, R., Heath, M., Hernvann, P.-Y., Morato, T., Soszynski, A., 2019. The impact of fisheries discards on scavengers in the sea. Eur. Land. Oblig. 129.

Deslias, C., Daniel, P., López, A., Martínez-Cedeira, J., Ridoux, V., & Peltier, H. (2024). Predicting the drift of small cetaceans stranded along the Atlantic coast of the Iberian Peninsula: Parametrization of the MOTHY drift model. *PLoS One*, 19, Article e0315593. https://doi.org/10.1371/journal.pone.0315593

Faunce, C. H., & Barbeaux, S. J. (2011). The frequency and quantity of alaskan groundfish catcher-vessel landings made with and without an observer. *ICES Journal of Marine Science*, **68**, 1757–1763. https://doi.org/10.1093/icesjms/fsr090

Fernández-Contreras, M. M., Cardona, L., Lockyer, C. H., & Aguilar, A. (2010). Incidental bycatch of short-beaked common dolphins (Delphinus delphis) by pairtrawlers off northwestern Spain. *ICES Journal of Marine Science*, **67**, 1732–1738. https://doi.org/10.1093/icesjms/fsq077

Flint, P. L., & Fowler, A. C. (1997). A drift experiment to assess the influence of wind on recovery of oiled seabirds on st paul island Alaska. *Marine Pollution Bulletin*, **36**, 165–166.

Guibert, C., Jouve, J., Martel, L., Sébleau, A., 2024. Mobilités et logiques de résidentialisation dans l'après CoVid-19. Le cas des surfeurs et des kitesurfeurs sur les littoraux français. Presented at the Horizons partagés : défis et opportunités des espaces littoraux Tourisme, nomadisme numérique, sociétés, sports et entrepreneuriel.

Hart, K. M., Mooreside, P., & Crowder, L. B. (2006). Interpreting the spatio-temporal patterns of sea turtle strandings: Going with the flow. *Biological Conservation*, **129**, 283–290.

Hijmans, R., 2022. geosphere: Spherical Trigonometry. R package version 1.5-18.

Hlady, D. A., & Burger, A. E. (1993). Drift-block experiments to analyse the mortality of oiled seabirds off vancouver island, British Columbia. *Marine Pollution Bulletin*, **26**, 495–501.

Hope Jones, P., Monnat, J.-Y., Cadbury, C. J., & Stowe, T. J. (1978). Birds oiled during the AMOCO CADIZ incident - an Interim Report. *Marine Pollution Bulletin*, **9**, 307–310.

Hu, B., Shao, J., & Palta, M. (2006). Pseudo-R 2 in Logistic Regression Model. *Statistica Sinica*, **16**, 847–860.

ICES, 2023a. Workshop on mitigation measures to reduce bycatch of short-beaked common dolphins in the Bay of Biscay (WKEMBYC2). ICES Scientific Reports. ICES.

ICES, 2023b. Report of the working group on bycatch of protected species (WGBYC) (ICES WGBYC REPORT 2023 No. ICES Scientific Reports. 5:111). ICES.

ICES, 2021. Workshop on estimation of MORTality of Marine Mammals due to Bycatch (WKMOMA). (ICES Scientific Reports. 3:106.).

ICES, 2020. Workshop on fisheries Emergency Measures to minimize ByCatch of short-beaked common dolphins in the Bay of Biscay and harbour porpoise in the Baltic Sea (WKEMBYC). (ICES Scientific Reports No. 2:43). ICES.

Kipp, E. K., McLellan, W. A., Rommel, S. A., & Pabst, D. A. (2002). Skin density and its influence on buoyancy in the manatee (Trichechus manatus latirostris), harbor porpoise (Phocoena phocoena), and bottlenose dolphin (Tursiops truncatus). *Marine Mammal Science*, **18**, 765–778.

Koch, V., Peckham, H., Mancini, A., & Eguchi, T. (2013). Estimating At-Sea Mortality of Marine Turtles from Stranding Frequencies and Drifter Experiments. *PLoS One*1, 8, Article e56776. https://doi.org/10.1371/journal.pone.0056776

Kosmidis, I. (2021). brglm: Bias Reduction in Binary-Response Generalized Linear Models. R package.

Kosmidis, I., & Firth, D. (2021). Jeffreys-prior penalty, finiteness and shrinkage in binomial-response generalized linear models. *Biometrika*, **108**, 71–82. https://doi.org/10.1093/biomet/asa052

Léger, J.-F. (2024). Les littoraux en France : Un dynamisme démographique porté par les seniors. *Popul. Avenir*, **767**, 4–7. https://doi.org/10.3917/popav.767.0004

Lunn, D. J., Thomas, A., Best, N., & Spiegelhalter, D. (2000). WinBUGS - a Bayesian modelling framework: Concepts, structure, and extensibility. *Statistics and Computing*, **10**, 325–337. https://doi.org/10.1023/A:1008929526011

Ministère de l'Environnement, de l'Énergie et de la Mer, 2017. Note du 27 avril 2017 relative au signalement des mammifères marins échoués ou à la dérive, morts ou en détresse, pour leur exploitation scientifique.

Moore, M. J., Mitchell, G. H., Rowles, T. K., & Early, G. A. (2020). Dead cetacean? beach, bloat, float sink. *Frontiers in Marine Science*, 7. https://doi.org/10.3389/fmars.2020.00333

Morizur, Y., Berrow, S. D., Tregenza, N. J. C., Couperus, A. S., & Pouvreau, S. (1999). Incidental catches of marine-mammals in pelagic trawl fisheries of the northeast Atlantic. *Fisheries Research*, **41**, 297–307.

Murphy, S., Evans, P. G. H., Pinn, E., & Pierce, G. J. (2019). Conservation management of common dolphins: Lessons learned from the North-East Atlantic. *Aquatic Conservation: Marine and Freshwater Ecosystems*, 1–30. https://doi.org/10.1002/ aqc.3212

Nowacek, D. P., Johnson, M. P., Tyack, P. L., Shorter, K. A., & McLellan, W. A. (2001). Buoyant balaenids: The ups and downs of buoyancy in right whales. *Proceedings of the Royal Society of London - Series B: Biological Sciences*, **268**, 1811–1816. https://doi.org/10.1098/rspb.2001.1730

Ouzoulias, F., Bousquet, N., Genu, M., Gilles, A., Spitz, J., & Authier, M. (2024). Development of a new control rule for managing anthropogenic removals of protected, endangered or threatened species in marine ecosystems. *PeerJ*, **12**, Article e16688. https://doi.org/10.7717/peerj.16688

Peltier, H., Authier, M., Caurant, F., Dabin, W., Daniel, P., Dars, C., Demaret, F., Meheust, E., Van Canneyt, O., Spitz, J., & Ridoux, V. (2021). In the wrong place at the wrong Time: Identifying Spatiotemporal Co-occurrence of Bycaught Common Dolphins and Fisheries in the Bay of Biscay (NE Atlantic) from 2010 to 2019. *Frontiers in Marine Science*, 8. https://doi.org/10.3389/fmars.2021.617342

Peltier, H., Authier, M., Dabin, W., Dars, C., Demaret, F., Doremus, G., Van Canneyt, O., Laran, S., Mendez-Fernandez, P., Spitz, J., Daniel, P., & Ridoux, V. (2020). Can modelling the drift of bycaught dolphin stranded carcasses help identify involved fisheries? *An exploratory study. Glob. Ecol. Conserv.*, 21, Article e00843. https://doi.org/10.1016/j.gecco.2019.e00843

Peltier, H., Authier, M., Deailleur, R., Dabin, W., Jepson, P. D., van Canneyt, O., Daniel, P., & Ridoux, V. (2016). Small cetacean bycatch as estimated from stranding schemes: The common dolphin case in the northeast Atlantic. *Environmental Science and Policy*, **63**, 7–18. https://doi.org/10.1016/j.envsci.2016.05.004

Peltier, H., Dabin, W., Daniel, P., Van Canneyt, O., Dorémus, G., Huon, M., & Ridoux, V. (2012). The significance of stranding data as indicators of cetacean populations at sea: Modelling the drift of cetacean carcasses. *Ecological Indicators*, **18**, 278–290.

Peltier, H., & Ridoux, V. (2015). Marine megavertebrates adrift: A framework for the interpretation of stranding data in perspective of the European Marine Strategy Framework Directive and other regional agreements. *Environmental Science and Policy*, **54**, 240–247. https://doi.org/10.1016/j.envsci.2015.07.013

Founder, E. J. (1992). The effect of water on body cooling. *Journal of Forensic Sciences*, **37**, 116–120.

R Core Team. 2023. R: A language and environment for statistical computing.

Reisdorf, A. G., Bux, R., Wyler, D., Benecke, M., Klug, C., Maisch, M. W., Fornaro, P., & Wetzel, A. (2012). Float, explode or sink: Postmortem fate of lung-breathing marine vertebrates. *Palaeobiodiversity Palaeoenvironments*, **92**, 67–81. https://doi.org/10.1007/s12549-011-0067-z

Santos, B. S., Kaplan, D. M., Friedrichs, M. A. M., Barco, S. G., Mansfield, K. L., & Manning, J. P. (2018). Consequences of drift and carcass decomposition for estimating sea turtle mortality hotspots. *Ecological Indicators*, **84**, 319–336. https://doi.org/10.1016/j.ecolind.2017.08.064

Skrovan, R. C., Williams, T. M., Berry, P. S., Moore, P. W., & Davis, R. W. (1999). The diving physiology of bottlenose dolphins (Tursiops truncatus): II. Biomechanics and changes in buoyancy at depth. *The Journal of Experimental Biology*, **202**, 2749–2761. https://doi.org/10.1242/jeb.202.20.2749

Smith, C. R., Glover, A. G., Treude, T., Higgs, N. D., & Amon, D. J. (2015). Whale-fall ecosystems: Recent insights into ecology, paleoecology, and evolution. *Annual Review of Marine Science*, **7**, 571–596. https://doi.org/10.1146/annurev-marine-010213-135144

Smith, T.J., McKenna, C.M., 2013. Smith, T. J., & McKenna, C. M. (2013). A comparison of logistic regression pseudo R2 indices. Mult. Linear Regres. Viewp. 39, 17–26.

Taylor, N., Authier, M., Banga, R., Genu, M., Gilles, A., 2022. Marine Mammal By-catch, OSPAR, 2023: The 2023 Quality Status Report for the Northeast Atlantic. O. OSPAR Commission, London.

Tonnessen, J. N., & Johnsen, A. O. (1982). The history of modern whaling. *Polar Record*, **21**, 301–302. https://doi.org/10.1017/S0032247400019069

Veall, M. R., & Zimmermann, K. F. (1996). Pseudo-R2 measures for some Common Limited Dependent Variable Models. *Journal of Economic Surveys*, **10**, 241–259. https://doi.org/10.1111/j.1467-6419.1996.tb00013.x

Vignard, C., & Tchoires, S. (2023). OBServation pour mieux comprendre les Captures Accidentelles de Mammifères marins par les fileyeurs du golfe de Gascogne, au travers de l'observation électronique à distance, Rapport final du projet OBSCAme phase 2. *Office Français de la Biodiversité*.

Wickham, H., 2016. ggplot2: Elegant Graphics for Data Analysis.

Williams, T. M., Davis, R. W., Fuiman, L. A., Francis, J., Le, B. J., Boeuf, Horning, M., Calambokidis, J., & Croll, D. A. (2000). Sink or Swim: strategies for cost-efficient diving by marine mammals. *Science*, **288**, 133–136. https://doi.org/10.1126/science.288.5463.133