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# Divergences and complementarities between eDNA versus passive acoustic marine mammal monitoring

Sara Vieira, Sandrine Gaillard, Renata Sousa-Lima, Hervé Glotin

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Sara Vieira, Sandrine Gaillard, Renata Sousa-Lima, Hervé Glotin. Divergences and complementarities between eDNA versus passive acoustic marine mammal monitoring. Ecological Informatics, 2025, 93, pp.103582. 10.1016/j.ecoinf.2025.103582. hal-05477214

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# Divergences and complementarities between eDNA versus passive acoustic marine mammal monitoring

Sara Vieira<sup>a,c,d,*</sup>, Sandrine Gaillard<sup>b</sup>, Renata Sousa-Lima<sup>c,d,*</sup>, Hervé Glotin<sup>a,d,*</sup>

## ARTICLE INFO

**Keywords:**

Bioacoustics

Environmental DNA (eDNA)

Mediterranean Sea

Biodiversity

Deep learning

Autonomous Surface Vehicle (ASV)

## ABSTRACT

The integration of eDNA with passive acoustics offers both divergence and complementarity in monitoring marine mammals. The 9-month "Sphyrna Odyssey 2019-2020" mission in the Mediterranean Sea assessed these methods for detecting cetacean presence, distribution, and diversity. Two drones 'autonomous laboratory ves- sels' equipped with 5 broad band frequency hydrophones sampled at 256 kHz, were complemented by an acoustic antenna with four additional hydrophones and deployed from an equipped accompanying vessel. Pas- sive acoustics enabled detection of vocalizing species within a few nautic miles. The eDNA samples collected from surface waters, analyzed via qPCR, identified species across broader spatial scales, despite being affected by ocean currents and DNA degradation. Visual observations completed this multimodal protocol. Notable eDNA detections included *Balaenoptera physalus*, *Ziphius cavirostris* (22 % and 20 % respectively), and *Physeter mac- rocephalus*. Other detected marine mammals were *Tursiops truncatus*, *Stenella coeruleoalba*, *Delphinus delphis*, *Globicephala melas*, and *Grampus griseus*. Moreover, we also considered the pinniped *Monachus monachus* but without the acoustic protocol. Automatic classification of acoustic signals using convolutional neural networks achieved over 80 % accuracy for most target species. Pooling detections by spatial clusters of 40 nm × 20 nm, we estimate the agreement between the eDNA with the other types of detections to 58 %, (higher than random, which is 31 %). We then discuss the complementarities of the eDNA versus the acoustic plus visual detections. By combining the spatial and temporal precision of acoustics with the broad detection capacity of eDNA, this multimodal approach from drones offers new insights into cetacean distribution and abundance, supporting conservation in marine ecosystems.

## 1. Introduction

Assessing cetacean populations is essential for evaluating the health of marine ecosystems, particularly in a context where marine biodiver- sity is increasingly threatened by rapid environmental changes and growing anthropogenic pressures. Cetaceans, as key indicators of marine ecosystem health, play an essential role in structuring, maintaining, and balancing trophic networks (Kiszka et al., 2022; Reeves and Nota- rbartolo di Sciara, 2006). To date, 21 different cetacean species have been recorded in the Mediterranean Sea (Conigliaro and Otero, 2012; Di Sciara and Birkun, 2010; Reeves and Notarbartolo di Sciara, 2006), none are endemic. Ten species have resident populations regularly present in

the region, such as *Tursiops truncatus* (Tt), *Stenella coeruleoalba* (Sc), and *Physeter macrocephalus* (Pm), while others, like *Pseudorca crassidens* (Pc) and *Megaptera novaeangliae* (Mn), are considered rare or occasional (Di Sciara and Birkun, 2010). These species inhabit diverse and complex environments, including submarine canyons, abyssal plains where food is abundant, and coastal areas (Glotin et al., 2020; Laran et al., 2012).

Monitoring cetaceans is challenging due to their mobility, elusive behavior, and habitat diversity, further complicated by environmental constraints. These challenges highlight the need for complementary methodologies to address individual biases and to enhance ecological understanding or conservation efforts.

This study integrates two non-invasive approaches: passive acoustics

<footnote><sup>a</sup> University Toulon, Aix Marseille Univ, CNRS, LIS, DYNI Team, Toulon, France</footnote>

<footnote><sup>b</sup> BioTechServices, Université de Toulon, Toulon, France</footnote>

<footnote><sup>c</sup> Laboratory of Bioacoustics / EcoAcoustic Research Hub, Biosciences Centerer, Universidade Federal do Rio Grande do Norte, Natal, Brazil</footnote>

<footnote><sup>d</sup> Cent. int. d'Intelligence Artificielle en Acoustique Naturelle, https://cian.lis-lab.fr, Toulon, France</footnote>

<footnote>* Corresponding authors at: University Toulon, Aix Marseille Univ, CNRS, LIS, DYNI Team, Toulon, France.
*E-mail addresses:* sara-vieira@etud.univ-tln.fr (S. Vieira), sandrine.gaillard@univ-tln.fr (S. Gaillard), sousa.lima@ufrn.br (R. Sousa-Lima), glotin@univ-tln.fr (H. Glotin).</footnote>
and environmental DNA (eDNA). To achieve this, a 9-month data collection campaign was conducted during the “Sphyrna Odyssey 2019-2020” mission (SOM), mostly drifting at 1 knot, on a vast area from Monaco to Majorca via the Gulf of Lion. This campaign, conducted at an average speed of 3 knots, represents a unique opportunity to evaluate these methods on an unprecedented spatio-temporal scale, under varying sea conditions, from calm to very rough seas.

Passive acoustics, employed since the 1970s, involves recording cetacean vocalizations, enabling species identification, behavioral studies, and long-term monitoring (Giraudet and Glotin, 2006; Sousa-Lima et al., 2013; Glotin et al., 2018–2023; Vieira, 2024). Using Sphyrna Autonomous Surface Vehicles (ASV) (or ‘Autonomous Laboratory

Vessels’), equipped with hydrophones, this study benefited from stable, autonomous monitoring with minimal environmental disturbance. These drones allowed for extended acoustic sampling, offering insights into vocal activity within a radius influenced by the properties of the water column.

Conversely, eDNA, a rapidly growing method, detects genetic material in water, providing the ability to identify species even in the absence of vocalizations or direct observations (Ficetola et al., 2008; Juhel et al., 2021; Székely et al., 2022). While eDNA offers a broader spatial perspective, its reliability can be affected by environmental factors, including degradation and dispersion, which vary depending on salinity, temperature, and water currents (Murakami et al., 2019;

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** (Top) Locations of passive acoustic, eDNA sampling, and visual observation during the SOM in 2019 and 2020. Acoustic drift recordings refer to the passive acoustic monitoring. (Bottom). The transects in the North area. Supp. material zoom Baleares area.</figcaption></figure>
Thomsen et al., 2012).

The objective of this study is to evaluate complementarity and divergence between passive acoustics and eDNA in detecting species diversity across Mediterranean habitats. By combining the spatial and temporal precision of acoustics with the broad detection range of eDNA, this multimodal approach offers a more comprehensive understanding of cetacean distribution and abundance. Together, these methods provide a robust framework for improving biodiversity assessments, addressing methodological limitations, and offering valuable guidance for conservation strategies in marine ecosystems.

## 2. Materials and methods

### 2.1. Geographical context and transects for cetacean monitoring

The study was conducted in the Mediterranean Sea, encompassing diverse habitats such as continental slopes, submarine canyons, and abyssal plains. This geographical diversity enabled a comparative analysis of detection methods under varying environmental conditions. This SOM started on Sept. 25th, 2019, ended on May 10th, 2020, covering a vast maritime zone from Monaco to Majorca via the Gulf of Lion. Sampling efforts were concentrated along the Ligurian current, between 8 and 40 nautical miles (nm) from the coast. Particular attention was given to submarine canyons, which served as critical hunting grounds for deep-diving teuthophagous cetaceans (e.g., species preying on cephalopods such as squid and cuttlefish).

Acoustic recordings targeted key marine features such as cliffs, canyons, and frontal zones, selected based on their ecological relevance to the study's objectives (Fig. 1, Table A1). These regions were identified as critical habitats for cetacean monitoring, offering insights into species distribution and behavior in distinct mediterranean habitats.

### 2.2. The Sphyrna drones, autonomous laboratory vessels (ALV)

The Sphyrna ALVs were designed by the naval design office of Sea Proven. Two models were used for this mission: the Sphyrna 55 (17 m) and the Sphyrna 70 (21 m). Recognized as the largest civilian autonomous ships globally, these vessels were developed with an eco-design approach to minimize environmental impact throughout their life-cycle. The ALVs were deployed from our accompanying catamaran OneCat (19 m) with hybrid propulsion, primarily operating in electric mode. The OneCat served as the operational hub, accommodating the scientific team, storing eDNA samples, and relaying real-time data from the ALVs over 7 nm.

The Sphyrna ALVs demonstrated remarkable stability and hydrodynamic efficiency. Their asymmetrical hulls significantly reduced pitching and rolling, enhancing onboard instrument stability and reducing noise. Equipped with hybrid solar and wind energy systems, they maintained low-energy operations for extended missions, minimizing disturbances while capturing cetacean vocalizations under optimal conditions.

### 2.3. Material for the detection and identification of cetaceans

Each ALV was equipped with five hydrophones connected to a high-performance sound card, capable of capturing data at an exceptional rate. Additionally, an acoustic antenna with four hydrophones further enhanced detection capabilities. This setup enabled real-time detection of cetacean vocalizations, allowing for immediate identification and localization. The high sampling rate and optimized hydrophone configuration were critical for detecting complex vocalizations across wide areas, enhancing the ability to monitor multiple cetacean species simultaneously.

The ALVs and the accompanying vessel were specifically equipped to detect a broad range of cetacean vocalizations, from high-frequency clicks to low-frequency vocalizations. The multi-hydrophone array

provided enhanced spatial resolution, minimizing blind spots and improving detection accuracy. This configuration facilitated the complementarity between acoustic detections and eDNA results, assessing the spatial and temporal coverage of cetacean populations.

Acoustic data were acquired using 14 hydrophones from Cetacean Research Technology (2 spherical C75 hydrophones usable up to 1 Hz to 150 kHz, and 12 cylindrical C57 hydrophones usable from 1 Hz to 100 kHz). Five hydrophones were placed on each drone: 4 at -2 m deep under the keel, the C75 the deepest, spaced from 35 cm to 70 cm apart, the 5th was located under the stern, 7 m behind the others (Glotin et al., 2020). To enhance signal accuracy, the high-temporal-resolution 'QHB' sound card, developed by the SMIoT technology platform (Barchasz et al., 2020), enabled synchronization and multi-channel recording with a capacity of 5 × 512 kHz frequency sampling. The OneCat was equipped with 4 C57.

The acoustic detection ranges for different marine mammal species were estimated based on the frequency and power of their vocalizations (Table 1). These detection ranges are depending on other various factors, such as sea state, salinity, and water column temperature.

Since the drones drifted during recordings, flow noise caused by water movement around the hydrophones was minimized, enhancing the quality of acoustic recordings. The homogeneous temperature and salinity profiles during the mission in winter minimized thermocline effects on sound propagation, creating stable recording conditions.

Acoustic detections were obtained under sea states ranging from 0 to 4 on the Beaufort scale, demonstrating the robustness of the recording system in diverse environments. However, sea states from force 3 onwards limited the detection of low-frequency signals, such as those emitted by Bp. These low frequencies, particularly sensitive to wave-induced interference, are quickly corrupted in rough sea conditions as in Gulf of Lion. Also, the similarity of the signals among delphinid species Sc or Dd, combined with acoustic disturbances caused by waves,

<table><caption>**Table 1**
Estimated acoustic detection range of the targeted cetacean species.</caption><thead><tr><th>Species</th><th>Frequency range, kHz</th><th>Est. detection range, Naut. Miles</th><th>References towards the range detection // References towards the used acoustic detectors in this study and their last versions</th></tr></thead><tbody><tr><td>Physeter macrocephalus (Pm)</td><td>0.1 to 30</td><td>7</td><td>Madsen et al., 2002; Au and Hastings, 2008; Glotin et al., 2023 // Giraudet and Glotin, 2006; Glotin et al., 2018, 2020, 2023; Ferrari et al., 2020, Poupard et al., 2019, 2022.</td></tr><tr><td>Globicephala melas (Gm)</td><td>0.5 to 10</td><td>3</td><td>Weilgart and Whitehead, 1990; Jensen et al., 2009 // Ferrari et al., 2020; Poupard et al., 2024</td></tr><tr><td>Balaenoptera physalus (Bp)</td><td>0.015 to 0.030</td><td>14</td><td>Clark et al., 2002; Varga et al., 2018 // Best et al., 2022; Glotin et al., 2023</td></tr><tr><td>Ziphius cavirostris (Zc)</td><td>20 to 80</td><td>1</td><td>Au and Hastings, 2008; Johnson et al., 2009 // Ferrari et al., 2020</td></tr><tr><td>Tursiops truncatus (Tt)</td><td>1 to 150</td><td>1 clicks, 3 vocalizations</td><td>Au, 1993; Richardson et al., 2013 // Ferrari et al., 2020</td></tr><tr><td>Stenella coeruleoalba (Sc)</td><td>5 to 100</td><td>1 clicks, 2 vocalizations</td><td>Au, 1993; Richardson et al., 2013 // Ferrari et al., 2020</td></tr><tr><td>Delphinus delphis (Dd)</td><td>5 to 100</td><td>1 clicks, 2 vocalizations</td><td>Au, 1993; Richardson et al., 2013 // Ferrari et al., 2020</td></tr><tr><td>Grampus griseus (Gg)</td><td>6 to 60</td><td>1 clicks, 2 vocalizations</td><td>Estimated from Ferrari et al., 2020 // Ferrari et al., 2020</td></tr></tbody></table>
further complicated their identification.

Visual observations were performed opportunistically from the deck of the OneCat, at 2 m high from sea level, by 2 or 3 marine mammal observers.

## 2.4. Methods for automatic acoustic detections and pooling with visual detections

The acoustic detections and species classification have been processed in two steps. First, our DOCC10 model (Ferrari et al., 2020) has been used to provide the acoustic detections and classification of the clicks of the odontocetes. It has been trained on thousands of annotated samples from previous studies with a convolutional neural net including 3D kernels allowing a direct analysis of the waveform of the transients. It yields to an accuracy of more than 80 % for the Pm, Sc, Zc, Tt, Gm (Ferrari et al., 2020). The Pm detections have been enhanced by averaging with the detector trained (Glotin et al., 2020, 2023; Poupard et al., 2019, 2022). Note that whereas the cumulation of maximum of training data, the detector of the Gg has only 30 % accuracy. However, because this study is a comparison between the distribution in space and time scales of the eDNA versus usual detections, we integrate the Gg acoustic sampling in this study. Whistles of the odontocetes Gm, Tt, Sc, Dd have been classified from trained samples after annotation and integration of various datasets including Ferrari et al., 2020, the CARIMAM data set (Glotin et al., 2021). We also used our CETACNN model used in several of our studies (Poupard et al., 2024), yielding an average accuracy of 80 % for Bp, Gm. The detection of Bp voicing has been processed as in previous studies (Best et al., 2022; Glotin et al., 2023), but due to weather conditions it resulted in zero acoustic detection of Bp. All detections in this paper have been inspected with the expertise of the authors.

The complete detection and classifications before pooling are given in the supplemental material (Table A2). As the recordings were running on the two drones drifting simultaneously from 2 nm to 4 nm apart to each other, and sometimes from our admiral boat OneCat (with similar hydrophones) in the same area and time period, we therefore pool by union the respective detections that occur in a same leg or time period (the yellow rows in Table A2 demonstrate this process). This union of detections prevents artificial duplication of detections occurring in the same area and period. The visual detection has been compiled such that they are not duplicated. This normalization yields into the final detections that are used to produce the maps and the statistics in the following sections.

## 2.5. Collection of environmental DNA data

We used the eDNA tool to identify and list species in the Mediterranean Sea. We focused on nine species: Bp, Sc, Dd, Tt, Gg, Gm, Zc, Pm, Mm (Table 2). The aim of this study is to test a water sampling method, a nucleic acid extraction method and a PCR amplification method, in order to detect the presence of marine mammals in the Mediterranean Sea (Fig. 2). All eDNA samples were collected under standardized conditions: seawater was sampled at surface level and filtration was performed immediately on board.

Prior to filtration and extraction, bench surfaces and all equipment were wiped with bleach (10 %), to reduce the risk of contamination, for 10 min, then rinsed with distilled water. For eDNA extraction, a volume of 10 L of seawater was filtered for each sample, except for sample 4, for which 20 L were processed due to a temporary issue with the filtration system, through one or more 0.45 µm pore-size filters immediately after collection to preserve sample integrity and maximize eDNA capture. The filters were then stored in Qiagen ATL® buffer at 4 °C for 2 weeks

<table><caption>**Table 2**
Summary of species-specific primers used in this study.</caption><thead><tr><th>Cetacean</th><th>- Mysticetes</th><th>Amplicon length (bp)</th></tr></thead><tbody><tr><td><strong>Species</strong></td><td>Latin name</td><td>DNA Sequence by species</td></tr><tr><td>Fin whale</td><td>Balaenoptera physalus (Bp)</td><td>Bal-Dir:<br>CGACCCAATTAATAGAAGCA<br>Bal-Rev:<br>TGATCGGGGTTTATCGGTTACAG</td></tr><tr><td><strong>Cetacean</strong></td><td>- Odontocetes</td><td></td></tr><tr><td>Sperm whale</td><td>Physeter macrocephalus (Pm)</td><td>Phyr-Dir:<br>GGAGTGTTAAGAGTTATAC<br>Phyr-Rev:<br>TCTAGGGGGTATGAAGCAC</td></tr><tr><td>Cuvier's beaked w.</td><td>Ziphius cavirostris (Zc)</td><td>Zip-Dir:<br>GAAAGCCATAATTAAAACTAAAC<br>Zip-Rev:<br>CAGTCTTGTTTTGTGACTGTTTAGG</td></tr><tr><td>Pilot whale</td><td>Globicephala melas (Gm)</td><td>Glo-Dir:<br>ACCATAAACCGAATACACGATAAC<br>Glo-Rev:<br>TAGTCTTGTTCTAGGACTATTTAAG</td></tr><tr><td>Bottlenose dolphin</td><td>Tursiops truncatus (Tt)</td><td>Tur-Dir:<br>TGACCCAACTAATAGATAC<br>Tur-Rev:<br>TCTTAGTTGTCGTGTATTCAG</td></tr><tr><td>Common dolphin</td><td>Delphinus delphis (Dd)</td><td>Del-Dir:<br>TGACCCAACTAATAGACACC<br>Del-Rev:<br>CTTGTTTTGGGATTATTTAAGT</td></tr><tr><td>Striped dolphin</td><td>Stenella coeruleoalba (Sc)</td><td>Ste-Dir:<br>ACCACAACTGAGTACACGACAAC<br>Ste-Rev:<br>CTTGTTTTAGGATTATTTAAG</td></tr><tr><td>Risso's dolphin</td><td>Grampus griseus (Gg)</td><td>Gra-Dir:<br>ACCTAAATAGTTCTCAAACAAG<br>Gra-Rev:<br>TAATCGTGGTTTATCGTTTACAG</td></tr><tr><td><strong>Pinniped</strong></td><td>-Phocidae</td><td></td></tr><tr><td>Monk seal</td><td>Monachus monachus (Mm)</td><td>Mon-Dir:<br>TGTTAAGATTTAATTTACAC<br>Mon-Rev:<br>CTATCGGGGTTTATCGATTATAG</td></tr></tbody></table>

onboard the accompanying vessel, before being transferred to the laboratory in a - 80 °C freezer until analysis.

A total of 33 seawater samples were collected from Toulon to the Gulf of Lion during January to May 2020 (Table 3). eDNA samples were collected in spatial and temporal proximity to the acoustic recordings, within the same survey areas and time windows during the Sphyrna Oceanographic Mission, from the accompanying vessel under Beaufort 0-4 conditions. Seawater samples were classified into four categories based on their geographical location. The majority of the sampling effort (23 samples) was focused along the continental slopes and in the sub-marine canyons, while four samples were collected less than 1 nm from the coast, three up to 2 nm, and three up to 12 nm, in order to cover a broad range of marine areas.

## 2.6. Method for the eDNA extraction of nucleic acids and detection of species by PCR

Digestion took place directly in the vials containing the filters and lysis buffer.

When several filters were required for a single environmental sample, due to water turbidity or clogging during filtration, all filters corresponding to that sample were digested together in the same lysis buffer until complete dissolution. The lysate was then divided into four
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Schematic overview from eDNA sampling to sample processing and data generation options explaining the methods to detect the presence of cetaceans with eDNA, including: (A) determination of the presence of target species DNA with e.g. qPCR (used in this study), (B) metabarcoding for species detection and community inference (not performed in this study), (C) SNP identification and haplotype sequencing for population genetics (not performed in this study) (credit Székely et al., 2022, NAMMCO Scientific Publ., licensed CC BY 4.0).</figcaption></figure>

<caption>**Table 3**</caption>

Summary of marine mammal species detected among the 33 eDNA collected samples.

<table><thead><tr><th>eDNA Samples</th><th>Date yyyy/mm/dd</th><th>hh:mm</th><th>Latitude (North)</th><th>Longitude (East)</th><th>eDNA detection</th></tr></thead><tbody><tr><td>1</td><td>2020/01/09</td><td>17:27</td><td>43°54'000</td><td>006°17'000</td><td>Bp, Zc</td></tr><tr><td>2</td><td>2020/01/12</td><td>07:00</td><td>43°19'675</td><td>007°11'562</td><td>Zc</td></tr><tr><td>3</td><td>2020/01/12</td><td>10:00</td><td>43°17'822</td><td>007°09'776</td><td>Bp, Tt</td></tr><tr><td>4</td><td>2020/01/14</td><td>11:00</td><td>43°22'000</td><td>007°16'000</td><td>Tt, Dd</td></tr><tr><td>5</td><td>2020/01/27</td><td>11:15</td><td>43°32'263</td><td>007°18'216</td><td>Tt, Zc, Mm</td></tr><tr><td>6</td><td>2020/01/30</td><td>18:00</td><td>43°27'000</td><td>007°25'000</td><td>Bp, Tt</td></tr><tr><td>7</td><td>2020/01/31</td><td>10:00</td><td>43°39'379</td><td>007°34'885</td><td>Bp</td></tr><tr><td>8</td><td>2020/02/02</td><td>12:30</td><td>43°23'820</td><td>007°22'660</td><td>Bp, Sc</td></tr><tr><td>9</td><td>2020/02/06</td><td>13:15</td><td>43°21'000</td><td>007°11'600</td><td>0</td></tr><tr><td>10</td><td>2020/02/19</td><td>08:02</td><td>43°23'280</td><td>007°16'150</td><td>Zc</td></tr><tr><td>11</td><td>2020/02/21</td><td>19:35</td><td>43°34'110</td><td>007°20'904</td><td>Bp</td></tr><tr><td>12</td><td>2020/02/22</td><td>09:37</td><td>43°24'757</td><td>007°03'953</td><td>Bp, Zc</td></tr><tr><td>13</td><td>2020/02/25</td><td>03:30</td><td>43°31'312</td><td>007°23'172</td><td>0</td></tr><tr><td>14</td><td>2020/03/06</td><td>10:45</td><td>42°57'185</td><td>006°13'055</td><td>Tt, Mm, Pm</td></tr><tr><td>15</td><td>2020/04/23</td><td>16:45</td><td>43°02'998</td><td>006°14'950</td><td>Sc, Zc</td></tr><tr><td>16</td><td>2020/04/23</td><td>18:44</td><td>43°04'962</td><td>006°23'338</td><td>Sc, Bp</td></tr><tr><td>17</td><td>2020/04/25</td><td>06:25</td><td>43°33'547</td><td>007°16'186</td><td>0</td></tr><tr><td>18</td><td>2020/04/26</td><td>07:48</td><td>43°30'707</td><td>006°56'802</td><td>Zc, Sc, Mm</td></tr><tr><td>19</td><td>2020/04/26</td><td>22:00</td><td>43°14'545</td><td>007°30'565</td><td>Pm</td></tr><tr><td>20</td><td>2020/04/27</td><td>12:53</td><td>43°32'464</td><td>007°22'981</td><td>Bp</td></tr><tr><td>21</td><td>2020/04/27</td><td>21:30</td><td>43°35'693</td><td>007°16'493</td><td>0</td></tr><tr><td>22</td><td>2020/04/28</td><td>15:00</td><td>43°34'539</td><td>007°07'797</td><td>Bp, Gm, Sc</td></tr><tr><td>23</td><td>2020/05/03</td><td>08:00</td><td>43°34'552</td><td>007°07'908</td><td>0</td></tr><tr><td>24</td><td>2020/05/04</td><td>10:40</td><td>43°14'078</td><td>006°55'050</td><td>Bp, Gm, Tt</td></tr><tr><td>25</td><td>2020/05/04</td><td>23:05</td><td>43°11'636</td><td>006°59'093</td><td>Dd, Sc, Pm</td></tr><tr><td>26</td><td>2020/05/05</td><td>14:50</td><td>43°04'551</td><td>006°12'275</td><td>Zc, Sc, Pm</td></tr><tr><td>27</td><td>2020/05/06</td><td>17:10</td><td>42°58'780</td><td>005°54'042</td><td>Zc, Dd</td></tr><tr><td>28</td><td>2020/05/07</td><td>12:50</td><td>43°11'918</td><td>005°27'340</td><td>Tt</td></tr><tr><td>29</td><td>2020/05/08</td><td>07:53</td><td>42°31'785</td><td>004°28'317</td><td>0</td></tr><tr><td>30</td><td>2020/05/08</td><td>17:05</td><td>42°30'046</td><td>004°12'109</td><td>Pm</td></tr><tr><td>31</td><td>2020/05/08</td><td>17:32</td><td>42°30'041</td><td>004°12'067</td><td>Pm, Zc</td></tr><tr><td>32</td><td>2020/05/08</td><td>17:50</td><td>42°29'968</td><td>004°10'768</td><td>0</td></tr><tr><td>33</td><td>2020/05/09</td><td>11:45</td><td>42°30'607</td><td>003°47'839</td><td>0</td></tr></tbody></table>

subsamples, each processed through independent purification columns, and the resulting eluates were pooled to obtain a single homogenized DNA extract per sample. This extract was subsequently used for PCR and qPCR analyses, ensuring consistency across all samples and avoiding partial detections from individual filters.

Digestion was carried out in the presence of PK and SDS, under

agitation at 56 °C for 4 h. The eDNA extraction and purification was performed using the NucleoSpin Tissue® kit (Macherey-Nagel) according to the supplier's recommendations. Each sample was subjected to an internal control to verify extraction efficiency. At the end of the extraction step, samples were recovered in a 70 µL buffer (5 mM Tris/HCl, pH 8.5) and stored at -80 °C until PCR is performed.

To detect the presence of DNA specific to the target species, a “nested” PCR approach adapted from the GoFish protocol was used. Nested PCR used two pairs of primers (“forward” and “reverse” primers) directed at the same metabarcode (the target) and two separate PCR cycles (Table 2).

This first step of PCR amplifications was performed on a Mastercycler Nexus Gradient (Eppendorf). The reaction mix consisted of 0.25 µL of HOT FIREPol® DNA polymerase (5 U/µL, Solis Biodyne), 2.5 µL of 10× Buffer, 1 µL of DNTP (25 mM), 2.5 µL of MgCl2 (25 mM), 1 µL of each primer (10 µM), 14.25 µL of molecular-grade water, and 2.5 µL of DNA, in a final volume of 25 µL. All assays were carried out in duplicate, and we included a negative control. 12S primers were 12S-Fwd: 5'-GTTGGTAAATTTCGTGCCAGC-3' and 12S-Rev: 5'-GATGGCGGTATA-TAGACTG-3' (amplicon length is 397 bp). PCR conditions were 10 min at 95 °C followed by 35 cycles of 45 s at 95 °C, 35 s at 55 °C and 45 s at 72 °C with a final extension of 10 min at 72 °C. Some selected first-round PCR products were sequenced for confirmation.

The second PCR also targeted part of the DNA coding for 12S rRNA, but was specific to each of the species to be identified. A pair of primers was designed for each species (Table 2). After the first PCR, the amplified products were purified using the QIAquick PCR Purification Kit (Qiagen), to remove any remaining primers and re agents that might interfere with the second amplification. The PCR products were then diluted 100-fold to increase the specificity of the primers specific to each species. Each purified and diluted amplification product was then amplified with each of the nine species-specific primer pairs. The second amplification was performed by real-time PCR (qPCR), which provided greater sensitivity and made it easier to eliminate any false positives that could appear.

Real-time PCR amplifications were performed using the SYBRgreen technology on a LightCycler 480 (Roche). The reaction mix consisted of 5 µL of 2× GoTaq® qPCR Master Mix (Promega), 1 µL of each primer (10 µM), 1 µL of molecular-grade. The molecular approach showed high sensitivity water, and 2 µL of diluted PCR product, in a final volume of
10 µL. All assays were carried out in triplicate, and we included a negative control for each pair of primers. qPCR conditions for the 9 pairs of primers were 10 min at 95 °C followed by 45 cycles of 1 min at 95 °C, 1 min at 60 °C and 1 min to 72 °C.

An amplification was considered valid when (i) ≥2/3 replicates crossed the threshold with Ct < 40 and (ii) the melt curve showed a single peak. Ambiguous signals (late Ct or atypical Tm/shape) were excluded a priori. Melting-curve analyses were systematically examined to ensure that only a single specific amplicon was amplified, and the observed Tm values matched the expected profiles for each target species, serving as an internal control of specificity.

Out of 264 tested reactions (33 samples × 8 primer pairs), 123 amplifications (≈ 46%) fulfilled these validation criteria, leading to 25 environmental samples with one or more confirmed detections. This multi-step filtering, combined with the nested PCR design and partial sequencing verification, ensured a high level of confidence in amplification specificity while minimizing the risk of cross-species detection.

To further evaluate the discriminatory power and specificity of the species-specific primers, we compared the amplicon sequences resulting from the first round PCR with each species-specific primer pair. Table A.4 (Supplementary Material) summarizes the number of nucleotide differences between the amplicons obtained after the first round of

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** The marine mammal species detections using acoustic, eDNA, or visual observation of SOM. The 5 'Leg Boxes' L1 to L5 (40nm x 20 nm), includes few continuous observations during drifts of several hours, and at least one eDNA run (A: **Teuthophage** (Pm, Gm, Zc, Gg). (B: **Epipelagic feeders** (Bp) and **coastal specialists** (Mm). (C: **Epipelagic and neritic delphinids** (Sc, Tt, Dd). The acoustic category of Ud (Sc or Dd) is delphinid species that could not be determined. eDNA did not run in 2019. The colored circle is for acoustics detections, diamond eDNA, and square visual ones.</figcaption></figure>
PCR (12S) and each primer-specific sequence, highlighting potential limitations in distinguishing closely related taxa, particularly within Delphinidae.

# 3. Results

## 3.1. Distribution map of multimodal species detection

This section presents the distribution of marine mammals detected by passive acoustics, eDNA, or visual observations during the SOM in the western Mediterranean. These results are detailed by ecological groups to better illustrate the detection zones and methods used (Fig. 3).

### 3.1.1. Teuthophage species: *Pm*, *Gm*, *Zc* and *Gg* (Fig. 3A)

**Pm:** Primarily detected by acoustics and confirmed visually along the Provençal coastline, specifically to the East of the island of Levant and South of Nice, as well as South of Porquerolles and Toulon, between the -1500 m to -2000 m isobaths, at the junction of the continental slope and the abyssal plain. These areas correspond to sampling efforts along the continental slope, in the Cannes canyon, and in a valley parallel to the Ligurian current.

**Gm:** Primarily detected by acoustics in Liguria, South of Cannes and Antibes, along the continental slope between the -1500 m and -2000 m isobaths. Acoustic detections and visual confirmations were also recorded in the Sète canyons, located in the Gulf of Lion, at the junction of the slope and abyssal plain. Interestingly the eDNA of Gm has been detected 50 nm West some Gm acoustic detections made three days before, which is in agreement with the direction and speed of the Ligurian current.

**Zc:** Primarily detected through eDNA between Toulon and Monaco, and detected acoustically south of Cap d'Antibes, at a depth of -2000 m.

These three species were detected by eDNA in areas that do correspond to their typical habitat, except Zc not so present in the West, supporting the hypothesis of their genetic material being transported by the dynamics of the Ligurian current from East to West. But **Gg** was not detected by either method.

### 3.1.2. Epipelagic feeders: *Bp* and coastal specialists: *Mm* (Fig. 3B)

**Bp:** Detected by eDNA in shallow coastal areas between Cannes and Monaco, as well as at Hyères, with visual observations in the Gulf of Lion. The acoustic detector did not detect Bp, certainly due to the low frequency noise in medium to high Beaufort sea state during these recordings.

**Mm:** Exclusively detected by eDNA in specific samples (samples 5, 14, 18). No acoustic detector was trained or tested for this species due to our current lack of references.

### 3.1.3. Epipelagic and neritic delphinids: *Sc*, *Dd*, *Tt* (Fig. 3C)

**Sc** and **Tt**: Detected by both methods and visually confirmed between Monaco and Marseille, but primarily in eDNA samples. These species show a broad distribution from coastal areas to deeper zones.

**Dd:** eDNA positive detections may confirm its presence particularly in coastal areas. Acoustic detections of Dd shall be read as the general "Ud = Sc or Dd" detector.

**"Ud=Sc or Dd" not separable group detection:** Primarily detected in the Gulf of Lion, Liguria, and south of the Balearic Islands. This acoustic detection includes species whose acoustic signals could not be identified due to similarities or overlaps of voicings.

These results underscore the complementarity of eDNA and acoustic methods in documenting species distributions, with eDNA revealing species that were not detected by the acoustic alone due to lack of acoustic references data (*Mm*), or no emissions, or too much low frequency noise (*Bp*).

## 3.2. Detection frequency of species estimated by passive acoustics versus eDNA

The results of this study show that passive acoustics detected five cetacean species, as well as an unidentified category of delphinids (Sc or Dd), between Sept. 2019 and May 2020: Sc, Tt, Gm, Zc, and Pm. In contrast, eDNA detected eight species between January 2020 and May 2020: Bp, Sc, Dd, Tt, Gm, Zc, Pm, Mm. Fig. 4 illustrates the differences in detection frequency between the two methods, calculated as the proportion of detections for each species relative to the total number of detections made by each method (119 samples for acoustics and 33 for eDNA). The category of merged acoustic Sc or Dd (in black) accounted for the majority of acoustic detections (59 %), explained by the high presence of Sc and the similarity of their vocalizations. Pm represented 25 % of acoustic detections, followed by Gm (8 %), Tt (4 %), Sc (2 %), and Zc (1 %).

In contrast, eDNA analysis identified eight species, with Bp (22 %) and Zc (20 %) being the most frequently detected species. These results align with acoustic detections in regions with high species diversity. Tt and Sc each accounted for 14 % of eDNA detections, and Dd and Gm for 6 % and 4 %, respectively. Finally, due to no acoustic protocol available for Mm, it was exclusively detected in eDNA samples for 6 %, even to South of Toulon where it was unexpected. The reduced anthropic activities during the COVID-19 lockdown could have led Mn individuals to perform larger travels in Genoa Gulf, resulting in wider drifted eDNA.

Among the nine target species analyzed via eDNA, Gg was the only species not identified in the 33 collected samples. Marine mammal DNA was successfully amplified in 25 of the 33 seawater samples (Table 3). The remaining samples showed no visible amplification or ambiguous sequences at the first PCR step, although qPCR analyses were performed on all samples. For samples 2, 3, 4, 6, 8, and 12, species or genus-level ambiguities remained. For instance, it was challenging to distinguish in sample 4 *Delphinus delphis* (Dd) from *D. capensis* (Dc), while samples 3, 6, and 12 showed overlap between *Balaenoptera physalus* (Bp) and *B. borealis* (Bb). In sample 2, the amplified sequence matched both Zc and species such as *Mesoplodon bidens* (Mb) and *M. ginkgodens* (Mg). Finally, sample 8, targeted with primers specific to *Stenella coeruleoalba* (*Sc*), also corresponded to sequences from *Tursiops aduncus* (*Ta*), *T. truncatus* (*Tt*), and *Sousa teuszii* (*St*). From all these possible species, we only kept the species known to be present in the Mediterranean Sea, thus rejecting St, Mg, Mb, Bb, and Dc.

The remaining eDNA detections demonstrate the complementarities of the two methods: eDNA can provide a broader species identification, compensates for the limitations of acoustic detections, especially in cases where species' vocal signatures overlap or are corrupted by unfavorable environmental conditions.

## 3.3. Agreement scores (AS) between eDNA and acoustic or visual detections

We score the agreement between eDNA detections versus the merged acoustic or visual detections, by pooling them in areas where we ran the eDNA protocol. To pool detections in similar space and time ranges, we define five 'Leg Boxes' (L), of about 40 nm × 20 nm, oriented in the main direction of the local current. Then each L is roughly corresponding to a drift of 1 day at the maximum drifting speed (1.5 knots). Hence, each L includes several continuous sequence observations of daily drifts. Then we define the Agreement Score (AS) between eDNA and (Audio or Visual) detections. AS equals the percentage of zero detections in both modalities, plus non zero detections in both modalities. The AS is dependent on the species, and the Leg Boxes. For L at the 40 nm × 20 nm scale, results show that the AS = 58 % STD 29 % by species, 21 % STD by L (Table 4). AS decreases to 54 % for the half pooling scale of the Leg Boxes (Table A3). In both cases, AS is slightly above the random AS (31 % STD 15 % by species, STD 20 % by L, for normal distribution). Note that at the scale of the pooling of the Leg Boxes AS = 88 % Mn has been
<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Comparison of the % of detections over the species and the acoustics versus eDNA detectors (Left) acoustic detections over the 119 samples; (Right) eDNA detections over the 33 samples. No acoustic detector was trained for *Monachus monachus* (Mm) which explains the 0 % detection by the acoustic method. Tt - *Tursiops truncatus*, Sc - *Stenella coeruleoalba*, Dd - *Delphinus delphis*, Zc - *Ziphius cavirostris*, Gm - *Globicephala melas*, Pm - *Physeter macrocephalus*, Bp - *Balaenoptera physalus*, *Stenella coeruleoalba* or *Delphinus delphis* (unidentified delphinids).</figcaption></figure>

<caption>**Table 4**</caption>

Counts of (Audio or Visual) and eDNA detections, of each species in each Leg Box (L). The coherent detections are underlined (=both null or both non null). The Agreement Score AS =58 % STD 29 % by species, STD 21 % by Leg Boxes.

<table><thead><tr><th>Species detections (Audio or Visual; eDNA)</th><th>L1 Gulf Lion</th><th>L2 Marseille</th><th>L3 Toulon</th><th>L4 St-Tropez</th><th>L5 Monaco</th><th><strong>AS</strong><br>58 %<br>std 29 %</th></tr></thead><tbody><tr><td>Pm</td><td>0; 2</td><td><u>0; 0</u></td><td><u>4; 2</u></td><td><u>14; 1</u></td><td><u>11; 1</u></td><td><strong>80 %</strong></td></tr><tr><td>Gm</td><td>5; 0</td><td><u>0; 0</u></td><td><u>0; 0</u></td><td><u>2; 2</u></td><td>3; 0</td><td><strong>60 %</strong></td></tr><tr><td>Zc</td><td>0; 1</td><td><u>0; 0</u></td><td>0; 4</td><td><u>1; 4</u></td><td><u>1; 3</u></td><td><strong>60 %</strong></td></tr><tr><td>Gg</td><td><u>0; 0</u></td><td><u>0; 0</u></td><td><u>0; 0</u></td><td><u>0; 0</u></td><td><u>0; 0</u></td><td><strong>100 %</strong></td></tr><tr><td>Bp</td><td>2; 0</td><td><u>0; 0</u></td><td><u>0; 0</u></td><td>0; 8</td><td>0; 4</td><td><strong>40 %</strong></td></tr><tr><td>Mm (no Acous.)</td><td><u>0; 0</u></td><td><u>0; 0</u></td><td>0; 1</td><td>0; 1</td><td>0; 1</td><td><strong>40 %</strong></td></tr><tr><td>Tt</td><td>2; 0</td><td><u>1; 1</u></td><td><u>3; 1</u></td><td><u>2; 1</u></td><td><u>1; 2</u></td><td><strong>80 %</strong></td></tr><tr><td>Dd (union Ud)</td><td>4; 0</td><td>2; 0</td><td><u>3; 1</u></td><td><u>17; 2</u></td><td><u>10; 1</u></td><td><strong>60 %</strong></td></tr><tr><td>Sc (union Ud)</td><td>5; 0</td><td>2; 0</td><td>5; 0</td><td>22; 0</td><td>10; 0</td><td><u>0 %</u></td></tr><tr><td><strong>AS</strong><br><u>58 % std 21 %</u></td><td><u>22 %</u></td><td><u>78 %</u></td><td><u>67 %</u></td><td><u>67 %</u></td><td><u>56 %</u></td><td><strong>58 %</strong></td></tr></tbody></table>

detected only by eDNA.

## 4. Discussion

### 4.1. Complementarity and limitations between passive acoustics and eDNA

Passive bioacoustics is a well-established approach for estimating population density, distribution, and movements of marine mammals while documenting their behavioral and cultural interactions (Sousa-Lima et al., 2013; Vieira, 2024). It also enables precise localization of vocal species in ecologically important habitats such as continental slopes and submarine canyons (Glotin et al., 2020). However, its detection range is constrained by sound propagation, which depends on both source frequency and oceanographic conditions. This limitation is particularly evident for high-frequency species such as *Ziphius cavirostris* (Zc), whose clicks are detectable only within about two nautical miles (Johnson et al., 2009; Table 1). During the COVID-19 lockdown, the marked reduction in maritime traffic created a quieter acoustic environment, which likely enhanced the range of low-frequency signals and

improved the detectability of cetacean vocalizations in our study. This effect primarily concerned low-frequency calls; we estimate that fin whale calls could be detected within the first miles from the coast, at approximately twice the usual range in normal coastal noise conditions (Glotin et al., 2020).

Conversely, environmental DNA (eDNA) provides a broader yet indirect view of species presence within a marine basin. It effectively identifies concentration zones and allows large-scale detection of elusive or transient species. As shown in Fig. 5, eDNA identified eight species, compared to five detected acoustically, confirming its wider taxonomic coverage. Previous studies have shown that eDNA provides a binary assessment of species presence or absence (Juhel et al., 2021; Székely et al., 2022; Watts and Miksis-Olds, 2018). However, it cannot yet quantify abundance, as the relationship between the amount of DNA and the number of individuals remains uncertain (Watts and Miksis-Olds, 2018). Our analyses therefore focused on detection frequency rather than abundance, to reflect each method's resolution. Emerging molecular tools such as digital PCR or direct sequencing could improve quantification accuracy in future studies (Lafferty et al., 2018; Thomsen et al., 2016).

Together, these findings highlight the complementarity between both methods, each compensating for the other's limitations. Passive acoustics efficiently locates vocal taxa in specific habitats, whereas eDNA provides a broader snapshot of biodiversity, detecting eight species compared to five by the acoustic approach. This multimodal framework therefore offers a more comprehensive view of marine mammal presence and distribution across the study area.

While species-specific primers were designed to maximize sequence divergence from sympatric taxa (Table 2), comparative analysis showed that Delphinidae primers (for *Tursiops truncatus*, *Stenella coeruleoalba*, and *Delphinus delphis*) differ by only one or zero nucleotides from closely related species. This high genetic similarity increases the risk of cross-amplification, complicating taxonomic assignment when several species co-occur. Although stringent validation criteria - replicate consistency, cycle threshold (Ct), melting temperature (Tm), and expected amplicon size - were applied, some false positives or ambiguous detections cannot be excluded. When uncertainty occurred, detections were conservatively attributed to taxa known in the Mediterranean (Table 3). Although only a subset of first-round 12S PCR products was sequenced, and qPCR amplicons were not, the specificity of detections
<figure><img src="image_8.png" /><figcaption>**Fig. 5.** Current map and simulated detection of Zc by eDNA in the Ligurian Sea, with theoretical drift of 48 h of genetic material. Black arrows represent surface currents. It also shows evidence of the current from Capraia Mn habitat to Toulon's area at an average of 0.4 m/s, 10 days travel (credit: map adapted from Mercator Ocean).</figcaption></figure>

was supported by single-peak melt-curve profiles and consistent amplification thresholds across replicates. This approach provided a practical alternative to direct sequencing, ensuring reliable species assignments despite logistical constraints. Future refinements could include more discriminating primers and systematic sequencing of qPCR amplicons, which would further strengthen species-level confidence. Despite these constraints, the protocol yielded robust results meeting current eDNA monitoring standards.

Moreover, environmental DNA (eDNA) proved particularly valuable for detecting rare or elusive species (Ficetola et al., 2008; Thomsen et al., 2012) such as the Cuvier's beaked whale (Ziphius cavirostris, Zc) and the Mediterranean monk seal (Monachus monachus, Mm). The latter, although extremely rare along the Provençal coastline, was detected in several samples, illustrating the high detection potential of eDNA even for species present at low concentrations or transported from distant areas. The possible advection of its genetic material by regional currents is discussed in Section 4.2.

Recent comparative works confirm that eDNA, acoustics, and visual surveys each detect overlapping but distinct subsets of taxa (Closek et al., 2019; Székely et al., 2022). For instance, Closek et al. (2019) showed species-specific detections unique to each method, underscoring the necessity of integrated frameworks. Tang et al. (2019) and Valsecchi et al. (2021) demonstrated that eDNA detection is highly sensitive to environmental conditions such as dispersion and degradation, whereas metabarcoding approaches can underperform compared to species-specific qPCR for low-abundance targets. Our Western Mediterranean results (Table 3, Fig. 4) reinforce these findings, revealing that detection concordance depends on hydrodynamics and method resolution. Altogether, these observations emphasize the need for multimodal and cross-validated monitoring strategies, with region-specific validation to ensure robust biodiversity assessments.

Inasmuch, these studies underline the necessity of multi-modal survey strategies and call for cross-validation between eDNA, passive acoustics, and visual datasets under varying ecological and

oceanographic conditions and scales to ensure robust assessments of marine mammal biodiversity. Although eDNA metabarcoding provides valuable insights into species presence, its quantitative interpretation remains challenging due to environmental influences, intra- and inter-species variability in DNA shedding, and PCR amplification biases. In our study, interpretation was therefore based on detection frequencies rather than on signal strength, given the methodological limitations previously described.

## 4.2. Geographical distribution and dispersion analysis of marine mammal eDNA

Analysis of eDNA samples revealed marine mammal occurrences in both expected habitat zones and unexpected areas, reflecting the complex influence of marine dynamics on eDNA dispersion. To better interpret these results, the samples were grouped into four categories based on their geographical and environmental configuration.

**Coastal zones (< 1 nm from the shore):** Samples collected near the coast (18, 22, 23, 28) showed variability in species detection. For example, Zc was identified in sample 18, and Gm in sample 22. No DNA was detected in sample 23, although it was collected a few days later in a similar area, illustrating the spatio-temporal variability of eDNA persistence in dynamic environments. In contrast, Tt was detected in the Marseille Calanques (sample 28), corresponding to its known habitat.

**Intermediate zones (up to 2 nm):** Samples collected at an intermediate distance from the coast (15, 16, 26) in the Hyères harbor showed the presence of Sc in all samples, although this species is primarily associated with pelagic habitats. Additionally, Zc and Pm were detected in certain samples (16, 26), highlighting the contribution of marine currents, such as the Ligurian current, in transporting genetic material from distant habitats to coastal areas.

**Continental slopes and submarine canyons:** Biodiversity-rich zones like the continental slopes and submarine canyons allowed identification of a variety of species in many samples (e.g., 20, 21, 24, 25),
including Bp, Zc, Tt, Sc, Pm, Gm, and Dd. However, the complex cur-
rents in these habitats can disperse eDNA over large spatio-temporal
scales, introducing uncertainty regarding the precise location of the
detected species.

**Deep abyssal plain (>= 12 nm):** Samples collected more than 12 miles from the coast, above the abyssal plain (3, 4, 19), revealed species such as Bp, Tt, and Dd. These results underscore eDNA's ability to be transported over long distances by deep currents and ocean gyres, challenging the direct correlation between eDNA detection and the location of species.

**Mm:** Detection of this species, absent from the Mediterranean Pro-
vençal coastline, in samples 5, 14, and 18, suggests a distant origin,
potentially from NE Corsica where it has been observed (Valsecchi et al.,
2022), with dispersion facilitated by marine currents.

These observations underscore the necessity of integrating oceano-
graphic dynamics into the interpretation of eDNA data. These results
suggest that the DNA of this species was transported by currents from
Capraia (Fig. 5) to the Toulon area, at an average of 0.4 m/s, nearly a
travel of 10 days. This distance seems incompatible with eDNA resil-
ience; thus, Mn may have visited the Genoa Gulf around the COVID-19
lockdown.

4.3. Spatio-temporal detection correspondence between passive acoustics and eDNA

Cross-comparison between acoustic and molecular datasets revealed
limited but meaningful spatio-temporal overlap. Of the 33 eDNA sam-
ples analyzed, 27 yielded cetacean detections (48 occurrences in total,
including between one and three species per sample), but only 7 (≈ 21
%) corresponded with acoustic detections collected within similar time
windows (Table 3, Fig. 5)). For instance, Dd was detected both acous-
tically (samples 28–30) and by eDNA (sample 4) on January 14, and
again on May 6 (acoustic 111 and eDNA 27). Sc was identified by both
methods on February 2 (acoustic 44 and eDNA 8), April 23 (acoustic 83
and eDNA 15), May 4 (acoustic 105–106 and eDNA 25), and May 5
(acoustic 108 and eDNA 26). Additionally, Pm was jointly detected on
March 5 (acoustic 79–80 and eDNA 14). These correspondences high-
light the spatio-temporal limitations of both approaches. eDNA analysis
revealed the presence of certain species outside their known habitats,
likely due to the transport of genetic fragments by marine currents.

The Leg Box analysis demonstrates an AS = 58 % (random would be
31 %) (Table 4). Half scale of the Leg Boxes gives AS = 54 %. Moreover,
it is not possible to determine if the genetic and acoustic detections
correspond to the same individual or group, further complicating spatio-
temporal comparisons. Thus, the comparisons of eDNA with acoustics of
visual methods shall be considered at the population or basin level. This
demonstrates the complexity of interpreting eDNA data in dynamic
marine environments, where factors such as eDNA dispersion and
degradation, as well as the influence of marine currents, play a crucial
role and affect the observed correspondences.

These findings emphasize that, despite their complementarity, eDNA
and acoustics provide distinct yet compatible insights. In summary, both
approaches capture different ecological dimensions: eDNA reflects
broad spatial occurrence, whereas acoustics describes fine-scale tem-
poral dynamics and behavior. Integrating both methods – supported by
oceanographic modeling - enhances the reliability of marine mammal
monitoring, particularly in regions where field access or visibility is
limited.

5. Conclusion

5.1. A navigation strategy for joint acoustic and eDNA protocols using *two ASLs*

For a multi-year data collection campaign aimed at monitoring the
distribution and abundance of marine mammals, it would be pertinent

to separate the protocols into two consecutive phases: the eDNA pro-
tocol followed by the acoustic protocol. An initial eDNA campaign
tracking the Ligurian-Provençal current, with regular sampling intervals
of 10 to 15 nautical miles, could help to identify key zones. Once the
eDNA sample results are obtained, this information would allow for
programming the trajectory and drift of the drones for acoustic data
collection above the theoretical eDNA excretion points.

We recommend leveraging the large-scale detection potential of
eDNA to strategically plan the drift of acoustic devices on the Sphyrna
ALV drones, allowing for precise mapping of key areas for each species,
along with complementary behavioral studies (Vieira et al., 2025a,
2025b) This setup can be adjusted depending on target species and their
detection range, requiring specific distances for optimal acoustic de-
tections (Fig. 6).

As during the SOM, two drones equipped with acoustic devices can
be positioned to act either as distinct antennas or as a single large
network, accounting for detection ranges according to target species.
This configuration allows for wider, more precise detections through
azimuthal intersections in overlap zones (Glotin et al., 2020). However,
drone spacing shall not exceed 6 nm for wifi communication and azi-
muth crossings of the same target.

5.2. eDNA and conservation areas in the Mediterranean Sea

The research efforts of SOM including eDNA has been concentrated
in the North-Western part of the Pelagos Sanctuary, along a maritime
route between Genoa and Marseille, in an area with a high species
density located above the continental slope and submarine canyons. The
Pelagos Sanctuary is a transboundary area between France, Monaco, and
Italy, aiming at protecting marine mammals in the Mediterranean Sea. It
stands out for its high biological productivity, driven by currents like the
Ligurian-Provençal current, which supply prey to cetacean habitats
(Notarbartolo-di-Sciara and Van Klaveren, 2008). Our results corroborate previous studies by confirming that these areas constitute strategic
habitats for cetacean species. The eDNA suggests some movement into
the Genoa gulf of Mm around the COVID-19 lockdown. This endangered
species (Bundone et al., 2019; Karamanlidis et al., 2016) could benefit
from more eDNA surveys. Pelagos habitats, particularly submarine
canyons and nutrient-rich zones, promote the concentration of prey,
such as cephalopods for Pm, krill for Bp (Laran et al., 2012). However,
these ecosystems face increasing anthropogenic pressures from heavy
maritime traffic and pollution, raising the risk of collisions and generating noise disturbances that affect cetaceans.

Our findings highlight the need to intensify surveillance and adap-
tive management efforts, particularly in the Pelagos Sanctuary, to

<figure><img src="image_9.png" /><figcaption>**Fig. 6.** Joint use of antennae of the Sphyrna drones illustrating two configurations: wide detection (Left), and finer detection using azimuth crossing (Right) enabling localization of cetaceans within the water column. Detection range varies by species.</figcaption></figure>
enhance the mapping of critical habitats using innovative technologies such as the integration of acoustic and eDNA data. These high-traffic maritime routes, frequented by numerous cetacean species, increase the risk of collisions, particularly for Pm and Bp, and generate noise disturbances from ship engines and propellers. To reduce collision risks and anthropogenic disruption between marine mammals and large commercial vessels, we recommend a speed limit of 10 knots for vessels longer than 10 m, from the shore up to 12 nm offshore (Sarano et al., 2025).

### 5.3. Future work on eDNA

The combination of passive acoustics and eDNA methods allows for a better understanding of marine biodiversity depending on current dynamics in the area. This study demonstrated that in large dynamic basins such as the Ligurian Sea or Gulf of Lion, pooling the eDNA and acoustic or visual detections by 40 nm × 20 nm areas, AS reached 58 %. For smaller dynamic basins, the complementarity of these modalities could generate even more coherent detections. To maximize the complementarity, consecutive campaigns of eDNA sampling followed by acoustic detections could be considered. These strategies would optimize the positioning of acoustic devices, whether they are marine surface drones, fixed devices, or drifting buoys, based on the key zones identified by eDNA. In conclusion, integrating acoustic and eDNA approaches represents a significant advancement in non-invasive cetacean monitoring. Although improvements are needed, this methodology offers an opportunity to better understand and protect marine ecosystems. The potential applications of this approach extend beyond the Mediterranean Sea, paving the way for similar initiatives in other marine ecosystems.

## Adherence to animal welfare protocols

This research was conducted in accordance with institutional and national animal welfare laws and protocols applicable in the jurisdictions where the work was carried out.

## Grants

This research was granted by the SAS Prince Albert II of Monaco Foundation (Fondation Prince Albert II de Monaco, FPA2); the Monaco Explorations Society (Société des Explorations de Monaco, EdM); the Nat. Chair of H.G. on Artificial Intelligence for Marine Bioacoustics ADSIL ANR-20-CHIA-0014 from the French Nat. Research Agency and AID DGA; ANR Cochlea ANR-21-CE04-0020-01; and ACCOBAMS; the CIAN and LIS CNRS, the University of Toulon.

## CRediT authorship contribution statement

**Sara Vieira:** Data curation, Formal analysis, Investigation, Methodology, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing. **Sandrine Gaillard:** Conceptualization, Data curation, Formal analysis, Methodology, Resources, Software, Validation, Visualization, Writing – review & editing. **Renata Sousa-Lima:** Formal analysis, Methodology, Supervision, Validation, Visualization, Writing – review & editing. **Hervé Glotin:** Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing.

## 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

We thank the SMIoT platform of the University of Toulon (intelli gent-acoustics.com) for their co-design of the onboard acoustic system, in particular V. Gies and V. Barchasz. We thank M. Poupard, P. Best, and M. Ferrari for their contributions to the acoustic and visual data collected during the marine expeditions, as well as for their involvement in real-time acoustic signal detection. We thank SAS Prince Albert II and the Monaco Foundation (FPA2), the Société des Explorations de Monaco (EdM), and the Agreement on the Conservation of Cetaceans of the Black Sea, Mediterranean Sea and Contiguous Atlantic Area (ACCOBAMS), for their logistical support and grants to SOM. We thank the Italian Ministry for the Environment, and the Spanish Government, for their permits, LemerPax for their logistical support and grants, and the Centre Nat. d'Études Spatiales (CNES), and the European Space Agency, Dr. J. Benveniste for their support and expertise in spatial data. We thank M. Lelievre for providing his OneCat catamaran. We also thank the Pure Ocean Foundation for its support and commitment to innovative marine research and ocean conservation. We thank the Port-Cros National Park, Dr. A. Barcelo and his team, for their logistical support, and are grateful to the Maritime Prefect of Var for accepting our research permit applications, in particular the unique ones during the COVID-19 lockdown.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.ecoinf.2025.103582.

## Data availability

This article is associated with several datasets and scripts that support the analyses presented in the manuscript.

**(a) Code and acoustic models:** The Python scripts and the complete trained models used for the detection of several marine mammal species during the *Sphyrna Odyssey* missions are available through the CETACNN framework developed by Best et al. (2022).

These models were implemented in the acoustic detection process and are hosted on the permanent university NAS and the dedicated GitHub repository created for this study.

Any reuse of this code should cite: CETACNN - Paul Best, 2022.

https://gitlab.lis-lab.fr/herve.

glotin/cianpub-/blob/main/cetacnnS/README.md?ref_type=heads

**(b) DOCC10 dataset:** Additional acoustic detections were performed using the DOCC10 detector (Ferrari et al., 2020), trained on open-access annotated datasets of marine mammal transient sounds.

The full dataset (100,000 annotated samples) used for this study is publicly available at: https://sabiod.lis-lab.fr/pub/challenges/DOCC10/

**(c) Geographic and detection data:** The complete GPS coordinates and metadata for all acoustic and eDNA analyses – including positive and negative detections per species - are provided in the supplementary CSV file.

https://sabiod.lis-lab.fr/pub/cianscapes/Sphyrna_Mission20192020/SphyrnaMission_eDNAAndAcousticsSpecies_detection_2019_2020_andNonDetection_with GPStag.csv

**(d) eDNA detection results:** The raw qPCR data (Cp_Tm values) are available in the supplementary XLS file.

This dataset includes all primer-sample combinations, with bold yellow cells corresponding to validated detections reported in the manuscript and red-boxed entries indicating uncertain results (Ct < 40 or non-specific Tm).

These raw data support the evaluation of eDNA detection quality and specificity.

https://sabiod.lis-lab.

fr/pub/cianscapes/Sphyrna_Mission20192020/SphyrnaMission_qPCR.xls
All data and scripts are archived on the University of Toulon NAS and mirrored on the project's GitHub repository to ensure long-term accessibility and reproducibility.

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