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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

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The first Unusual Mortality Event (UME) related to fishing activity along the Atlantic coast recorded by the French Stranding Network was in 1989: 697 small delphinids, mostly common dolphins, washed ashore, most of them with evidence of having been bycaught. Since then, UMEs of common dolphins have been observed nearly every year in the Bay of Biscay; unprecedented records were broken every year since 2016. The low and unequally distributed observation efforts aboard fishing vessels in the Bay of Biscay, as well as the lack of data on foreign fisheries necessitated the use of complementary data (such as stranding data) to elucidate the involvement of fisheries in dolphin bycatch. The aim of this work was to identify positive spatial and temporal correlations between the likely origins of bycaught stranded common dolphins (estimated from a mechanistic drift model) and fishing effort statistics inferred from Vessel Monitoring System (VMS) data on vessels >12 m long. Fisheries whose effort correlated positively with dolphin mortality areas after 2016 included French midwater trawlers, French Danish seiners, French gillnetters, French trammel netters, Spanish bottom trawlers, and Spanish gillnetters. For the French fleet only, logbook declarations, sales, and surveys carried out by Ifremer were integrated into fishing effort data. Six fleets were active in common dolphin bycatch areas at least twice between 2016 and 2019: gillnetters fishing hake, trammel netters fishing anglerfish, bottom pair trawlers fishing hake, midwater pair trawlers fishing sea bass and hake, and Danish seiners fishing whiting. Except for changes in hake landings in some fisheries, there were no notable changes in total fishing effort practice (gear or target species) based on the data required by the ICES and Council of the European Union that could explain the large increase in stranded common dolphins recorded along the French Atlantic coast after 2016. Small scale or unrecorded changes could have modified interactions between common dolphins and fisheries, but could not be detected through mandatory data-calls. The recent increase in strandings of bycaught common dolphins could have been caused by changes in their distribution and/or ecology, or changes in fishery practices that were undetectable through available data.
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ORIGINAL RESEARCH
published: 28 April 2021
doi: 10.3389/fmars.2021.617342
Edited by:
Jeremy Kiszka,
Florida International University,
United States
Reviewed by:
Graham Pierce,
Instituto de Investigaciones Marinas
(CSIC), Spain
Maria Grazia Pennino,
Spanish Institute of Oceanography,
Spain
*Correspondence:
Helene Peltier
hpeltier@univ-lr.fr
Specialty section:
This article was submitted to
Marine Megafauna,
a section of the journal
Frontiers in Marine Science
Received: 14 October 2020
Accepted: 19 March 2021
Published: 28 April 2021
Citation:
Peltier H, Authier M, Caurant F,
Dabin W, Daniel P, Dars C, Demaret F,
Meheust E, Van Canneyt O, Spitz J
and 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.
Front. Mar. Sci. 8:617342.
doi: 10.3389/fmars.2021.617342
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
Helene Peltier1,2*, Matthieu Authier1,2 , Florence Caurant1,3 , Willy Dabin1, Pierre Daniel4,
Cecile Dars1,2 , Fabien Demaret1,2, Eleonore Meheust1, Olivier Van Canneyt1,
Jerome Spitz1,3 and Vincent Ridoux1,3
1Observatoire Pelagis, UMS 3462-Université de La Rochelle-CNRS, La Rochelle, France, 2ADERA, Pessac, France,
3Centre d’Études Biologiques de Chizé-La Rochelle, UMR 7372-Université de La Rochelle-CNRS, La Rochelle, France,
4Météo-France, DirOP/MAR, Toulouse, France
The first Unusual Mortality Event (UME) related to fishing activity along the Atlantic
coast recorded by the French Stranding Network was in 1989: 697 small delphinids,
mostly common dolphins, washed ashore, most of them with evidence of having
been bycaught. Since then, UMEs of common dolphins have been observed nearly
every year in the Bay of Biscay; unprecedented records were broken every year since
2016. The low and unequally distributed observation efforts aboard fishing vessels in
the Bay of Biscay, as well as the lack of data on foreign fisheries necessitated the
use of complementary data (such as stranding data) to elucidate the involvement of
fisheries in dolphin bycatch. The aim of this work was to identify positive spatial and
temporal correlations between the likely origins of bycaught stranded common dolphins
(estimated from a mechanistic drift model) and fishing effort statistics inferred from
Vessel Monitoring System (VMS) data on vessels >12 m long. Fisheries whose effort
correlated positively with dolphin mortality areas after 2016 included French midwater
trawlers, French Danish seiners, French gillnetters, French trammel netters, Spanish
bottom trawlers, and Spanish gillnetters. For the French fleet only, logbook declarations,
sales, and surveys carried out by Ifremer were integrated into fishing effort data. Six
fleets were active in common dolphin bycatch areas at least twice between 2016 and
2019: gillnetters fishing hake, trammel netters fishing anglerfish, bottom pair trawlers
fishing hake, midwater pair trawlers fishing sea bass and hake, and Danish seiners
fishing whiting. Except for changes in hake landings in some fisheries, there were no
notable changes in total fishing effort practice (gear or target species) based on the data
required by the ICES and Council of the European Union that could explain the large
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Peltier et al. Co-occurence of Bycatch and Fisheries
increase in stranded common dolphins recorded along the French Atlantic coast after
2016. Small scale or unrecorded changes could have modified interactions between
common dolphins and fisheries, but could not be detected through mandatory data-
calls. The recent increase in strandings of bycaught common dolphins could have been
caused by changes in their distribution and/or ecology, or changes in fishery practices
that were undetectable through available data.
Keywords: bycatch, fishing effort, strandings, reverse drift, Bay of Biscay, VMS data
INTRODUCTION
The first multiple stranding event along the French Atlantic coast
was recorded in winter 1989: 697 delphinids, mostly common
dolphins, washed ashore, most of them presenting evidence of
having been bycaught (Figure 1). Since then, severe mortality
events of common dolphins have been recorded almost every
year in the Bay of Biscay. Multiple stranding events, or “Unusual
Mortality Events” (UMEs), are events in which a high number of
strandings occur in a limited area with a common cause of death.
The threshold was set at 30 cetaceans over 10 consecutive days
recorded along a distance of up to 200 km of coastline in the Bay
of Biscay (Peltier et al., 2014).
French driftnet fisheries, fishing for albacore tuna, began
operating in the eastern North Atlantic in the mid-eighties
(Northridge, 1991). This fishery operated between June and late
September, more than 200 NM off the coast of the Bay of Biscay.
The fleet had as many as 64 vessels in 1994, with nets up to 12 km
long (average 7 km) (Antoine et al., 1997). Under NGO pressure,
this fishery was subjected to a high degree of scrutiny: at-sea
monitoring suggested total bycatch estimates of 400 dolphins
per year, including both striped and common dolphins (Stenella
coeruleoalba and Delphinus delphis). High levels of strandings
reported in the Bay of Biscay in winter and the increase of driftnet
fishing effort in summer were two independent processes that
were erroneously confused in the media and public opinion. This
likely influenced the Council of the European Union’s decision to
reduce driftnet length in the Bay of Biscay to 2.5 km in 1991, and
in 1997 to announce a ban of the fishery from January 1, 2002
(Council of the European Union, 1998).
Despite the driftnet ban, continued common dolphin UMEs
in the winter led to the creation of a national working group
on cetacean bycatch in 2004. This group was made up of
scientists, representatives of the fishing industry, officers of the
Ministry in charge of the Environment and the Ministry in
charge of Fisheries. EU funded projects were carried out in
order to estimate bycatch numbers, to explore the circumstances
most associated with dolphin captures, and to test technological
developments (acoustic repellents, or pingers, and excluder
devices) that would reduce bycatch by midwater pair trawlers—
considered at that time to have been responsible for the majority
of cetacean bycatch (Northridge et al., 2006;NECESSITY Report,
2008). The dolphin bycatch issue lost salience in France in the
late 2000s, probably due to the relative decrease in strandings
recorded along the Atlantic coast, and the dedicated national
working group was disbanded.
In 2004, under the Common Fishery Policy (CFP), European
Commission (EC) Regulation no. 812/2004 (Council of the
European Union, 2004) framed the monitoring of cetacean
bycatch through compulsory on-board observers and the
mandatory use of pingers on nets when fishing in latitudes north
of 48N. Member States were required to design and implement
monitoring schemes for the incidental capture of cetaceans in
selected fisheries and on fishing vessels with an overall length
15 m. By selecting focal fisheries for the implementation of
on-board monitoring programs while excluding others, the EC
Regulation 812/2004 precluded any possibility of providing a
synoptic view of cetacean bycatch in EU fisheries. An observer
program dedicated to marine mammal bycatch was implemented
in France from 2005 until 2009, and was then merged with an
at-sea observer program required by the European Commission
under the Data Collection Framework (DCF; Council of the
European Union, 2008). Designed to collect information on
commercial catch, this revised observer program was no longer
dedicated to cetacean bycatch and was thus less likely to assess
the extent and magnitude of the issue. Within the framework of
the DCF, fishing operations are classified into métiers according
to their target species, gear used, fishing season and fishing area
(Deporte et al., 2012). Of these métiers, those considered to
pose the greatest risk of bycatch are generally under-sampled
by general observer programs, leading to an underestimation
of bycatch (ICES, 2020a). In 2014 in United Kingdom waters,
comparisons between observer programs dedicated to bycatch
and DCF observers highlighted an underestimation of fisheries’
impact on dolphins in non-dedicated programs (ICES, 2016).
Two main biases were identified in non-dedicated fishery bycatch
observation programs with low enforcement: (1) the deployment
effect that results from skippers’ discretion to accept an observer
on board, which produces non-random sampling and non-
representative data and (2) the observer effect, i.e., a change in
fishing practices when an observer is present, which also results
in the collection of non-representative data (Benoît and Allard,
2009;Faunce and Barbeaux, 2011;Amandè et al., 2012;Murphy
et al., 2019). In 2019, EC Regulation 812/2004 was repealed and
replaced by the Technical Conservation Measures, EU Regulation
1241/2019 (Council of the European Union, 2019).
Since 2016, strandings of small cetaceans with evidence of
bycatch occurred in unprecedented numbers along the Bay
of Biscay coast, breaking annual records (Dars et al., 2019).
During the winter of 2019 (January–April), 1,200 strandings of
small cetaceans were recorded by the French Stranding Network
(Réseau National Échouages), 1,089 of which were along the
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1985 1990 1995 2000 2005 2010 2015 2020
1986: French drinet
fishery begins
operaon in the Bay
of Biscay
1989: First UME
in the
Bay of Biscay
Since 1997: Winter UMEs
in the
Bay of Biscay
2004: 1st French
Naonal working group
on bycatch
2004: EC
812/2004
2004-2009: Dedicated
French bycatch observer
program
2009-today: French DCF observer program
2017-today: 2nd French
Naonal working group on
bycatch
2019: EU 1241/2019
2016-today:
Unprecedented winter
UMEs in the Bay of Biscay
2004-2007: EU
funded projects to
reduce bycatch
2018-today: Naonal and
EU funded projects to
reduce bycatch
Stranding events
Fishery involvement
1991: Reducon of
drinet length
2002: Drifnet ban
French iniaves
EU regulaons
FIGURE 1 | Main historical events in common dolphin bycatch management in the Bay of Biscay. DCF, Data Collection Framework; EC, European Commission;
UME, unusual mortality event.
French Atlantic coast.1Between 5,000 and 10,000 strandings of
bycaught common dolphins were recorded along the French
Atlantic coast each year from 2016 to 2018 (ICES, 2020b;Peltier
et al., 2020). Being one of the most abundant species in the
North-East Atlantic (Hammond et al., 2017;Laran et al., 2017),
common dolphins are among the most vulnerable to being caught
in fishing gear (De Boer et al., 2008;Fernández-Contreras et al.,
2010;Peltier et al., 2016;ICES, 2020b).
In 2017, a new national working group, comprising the same
actors as in 2004, was set up with similar terms of reference: (1)
improve knowledge of cetacean bycatch in the Bay of Biscay, (2)
develop mitigation strategies to reduce bycatch, and (3) involve
fishermen to raise awareness of the bycatch issue.
Today, in addition to Regulation 2019/1241 that set the
obligation to “minimize, and where possible, eliminate” bycatch,
various regulations frame the Member States’ obligations in term
of bycatch mitigation. The objectives of the Common Fisheries
Policy (Regulation 1380/2013, 2013) include implementation
of “the ecosystem-based approach to fisheries management so
as to ensure that negative impacts of fishing activities on the
marine ecosystem are minimized” (Regulation 1380/2013, 2013).
The Habitat Directive (Directive 92/43/EEC) requires Member
States to establish protection measures to prohibit “all forms of
deliberate capture or killing of specimens of these species in the
wild.” The Good Environmental Status (Commission Decision
2017/848) required by the Marine Strategy Framework Directive
(Directive 2008/56/EC) aims to ensure “the mortality rate per
species from incidental bycatch is below levels which threaten
the species, such that its long-term viability is ensured” and “the
population abundance of the species is not adversely affected due
to anthropogenic pressures, such that its long-term viability is
ensured.”
1http://pelagis.in2p3.fr/public/histo-carto/index.php
Faced with the hurdles of enforcing efficient at-sea monitoring
of the impact of fisheries on cetaceans, the use of complementary
data was sought (IWC, 2016;ICES, 2017;Murphy et al., 2019).
Stranding records are an important source of information
on marine mammals, and can provide critical information to
estimate a minimum level of bycatch across fisheries (Lopez et al.,
2003;Leeney et al., 2008;Adimey et al., 2014). Methodological
developments have allowed us to infer the likely origin of
stranded carcasses using drift modeling (Peltier and Ridoux,
2015). Drift modeling, along with a better understanding of drift
conditions, observation pressure and carcass floatation (Hart
et al., 2006;Peltier et al., 2012;Authier et al., 2014;Moore et al.,
2020), has broadened the use of stranding data for quantitative
approaches (Peltier et al., 2016).
Since strandings can be used to model the likely mortality
areas of small cetaceans, the possibility of identifying the potential
fisheries involved has become a prominent topic of debate among
scientists, stakeholders, NGOs and the fishing industry. The
low coverage of non-dedicated observer programs in France
has meant that the collected data could not be used to identify
fisheries posing the greatest risk of bycatch. Therefore, a new
methodology relying on independent data provided by strandings
was developed to detect positive spatial correlations between
common dolphin mortality areas and fishing effort (Peltier et al.,
2020). This methodology, initially tested on the winter UME of
2017, is further developed here and was applied to every UME
recorded along the Atlantic coast of France since 2010. This was
done in order to identify spatial and temporal co-occurrence
between bycaught dolphin mortality areas and fishing effort, and
the change thereof since 2010. The aim of this expanded analysis
is to identify candidate fisheries potentially involved in UMEs,
and to discuss whether the recent evolution of these fisheries
could explain the observed stranding levels.
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MATERIALS AND METHODS
The study area covered the French Atlantic coast along the Bay of
Biscay (ICES sub-areas 27.8a and 27.8b)2(Figure 2).
The analyses, detailed in the following sections and
represented in Figure 3, involved four main steps:
(1) Predicting the reverse trajectories of stranded common
dolphin carcasses with bycatch evidence to estimate the
mortality area of each animal;
(2) Inferring the trajectories of fishing vessels longer than 12 m
from VMS data and estimating fishing effort;
(3) Aggregating the dolphin bycatch areas during an UME
(Figure 3a) and the total fishing effort (Figure 3b) on a
regular grid spanning the Bay of Biscay;
(4) Fitting Spatial Generalized Additive Models within a
Bayesian framework to explore the spatial and temporal
co-occurrence of fishing effort and the origins of stranded
bycaught dolphins.
All analyses were performed in the R software environment,
version 4.0 (Ihaka and Gentleman, 1996;R Core Team, 2020);
bathymetric maps were plotted with the R library marmap
(Pante and Simon-Bouhet, 2013).
Estimating Mortality Areas From
Strandings
Data on marine mammal strandings in France are collected by
the French Stranding Network (Réseau National Echouages),
coordinated by Observatoire Pelagis (CNRS/La Rochelle
University), as mandated by the French Ministry in charge of
the Environment. More than 400 trained volunteers collect
2https://www.ices.dk/data/Documents/Maps/ICES-Ecoregions- hybrid-
statistical-areas.png
information on stranded animals along the entire French coast
following a standardized protocol (Van Canneyt et al., 2015).3
The details of a stranding can be used to infer where the carcass
originated by calculating its reverse drift trajectory from the
location where it stranded.
The common dolphin carcasses retained for analyses included
only fresh or slightly decomposed individuals with evidence of
bycatch and/or which stranded during a UME (Peltier et al.,
2020). Evidence of bycatch includes: net marks; good nutritional
condition; evidence of recent feeding; jaw and rostrum fractures;
froth in the airways; edematous lungs; and amputations of the
dorsal fin, pectoral fins or tail fluke (see details in Kuiken, 1994;
Bernaldo de Quirós et al., 2018). A combination of several of the
above criteria and the lack of evidence for any other cause of
death indicate bycatch to be the cause of death. All diagnoses
are validated by Observatoire Pelagis based on data collected,
examination reports and detailed photographs.
The reverse drift trajectories of stranded common
dolphins with bycatch evidence were calculated using the
drift prediction model MOTHY (Modele Oceanique de Transport
d’HYdrocarbures), initially developed by Météo-France to predict
the drift of oil spills and later adapted to solid object drift
prediction (Daniel et al., 2002). MOTHY predicts the drift of a
floating object under the influence of tides and winds, based on a
global meteorological model validated by observations.
The drift duration of carcasses was inferred from the
decomposition status and visual criteria describing body
decomposition (Peltier et al., 2012). Animals categorized as
“fresh” were estimated to be <5 days post-mortem and animals
classified as “slightly decomposed” to be 5–15 days post-
mortem. One location was retained for each day within the
time window corresponding to the decomposition code of each
3https://www.observatoire-pelagis.cnrs.fr/IMG/pdf/GuideEchouages2015.pdf
FIGURE 2 | North-East Atlantic Ocean including study area (ICES subareas 27.8.a and 27.8.b) in blue boxes. ICES, International Council for the Exploration of the
Sea.
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FIGURE 3 | Schematic representation of methodology used. UME, unusual mortality event; VMS, Vessel Monitoring System. (1) Reverse trajectory of stranded
dolphins; (2) Inferred trajectory of fishing vessel; (3a) Origin of bycaught dolphins found stranded during a UME (n); (3b) Fishing effort at the time of UME (hours);
(4) Bayesian variable prediction and selection using spike-and-slab LASSO | Spatial and temporal correlations.
individual, and locations were weighted in order to obtain a total
weight of 1 animal per drift. Locations of carcass drifts were
summed in each cell of a 0.4×0.4grid covering the Bay
of Biscay. Locations of fresh and slightly decomposed animals
were summed separately: carcasses found stranded at the same
time but in different decomposition states (in other words with
different drift durations) would have died on different dates and
potentially in different areas.
Fishing Effort Data
European fishing vessels longer than 12 m have been required
under EU regulation to be equipped with VMS transmitters
since 2010. Data from vessels in French waters are collected
and archived by Ifremer’s Fisheries Information System (Système
d’Informations Halieutiques, SIH),4managed by the Directorate
of Marine Fisheries and Aquaculture (Direction des Pêches
Maritimes et de l’Aquaculture, DPMA). The VMS data recorded
includes the date, time and position of the fishing vessels at an
hourly resolution. Ifremer analyzes these locations to compute
fishing effort, mostly from vessel speed: vessels are considered to
be actively fishing if their mean traveling speed is less than 4.5
knots, and in transit otherwise.
Fishing effort is provided at a daily resolution in a
0.05×0.05grid, and anonymized information related to
fishing vessels is given (flag, size category, harbor, and gear
classification). Only trawls, nets and seines were considered,
4http://sih.ifremer.fr/
because dredges, longlines and pots are not believed to generate
small cetacean bycatch in the Bay of Biscay. Combinations of nine
different gears and nine different flags were tested (Table 1).
Available VMS data of non-French fisheries operating in
French waters (ICES subareas 27.8.a and 27.8.b) could not be
linked to the actual gear used during fishing operations, only to
the gear identified in the initial description of the EU fishing fleet
register. For the French fleet only, VMS data are complemented
by declarative landing statistics (logbooks and sales provided by
the Ministry in charge of Fisheries) and Ifremer survey data in
order to provide fishing effort data related to the species and
quantity of fish landed. Note that fishing effort (in hours) in a
TABLE 1 | Fishing gear included in the study and their ICES abbreviation.
Gear abbreviation Gear
GNS Set gillnets
GTR Trammel nets
OTB Bottom otter trawls
OTM Midwater otter trawls
OTT Otter twin trawls
PS Purse seines
PTB Bottom pair trawls
PTM Midwater pair trawls
SDN Danish seines
ICES, International Council for the Exploration of the Sea.
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Peltier et al. Co-occurence of Bycatch and Fisheries
dedicated cell is equally allocated to every fish species caught in
that cell, irrespective of the caught quantity.
Several hundreds of gear/species associations can be recorded
within a UME and they cannot all be tested. As a first filter, only
caught species constituting more than 10% of fishing effort in
at least 50% of events recorded within a year were retained. In
the end, 22–37 gear/species combinations were tested for spatial
correlation with strandings (Table 2). Maps of fishing efforts
tested are available online (see Shiny appendix http://pelabox.
univ-lr.fr:3838/pelagis/ShinyApp_v2/). Correlations were tested
at the temporal resolution of the different UMEs in ICES subareas
27.8.a and 27.8.b (Table 3).
Aggregation of Data on a Common Grid
Covering the Bay of Biscay
A “block averaging” method was used in order to spatially smooth
the raw sums computed as above (Petitgas et al., 2014;Peltier
et al., 2020). This method averages the data by block over the
0.4×0.4grid, spanning 43N–47N and 1W–4W. The value
in the first block (block 0, origin = x0) is the sum of the weighted
locations within the block. The point origin (x0) from block 0,
in the lower left corner, was randomized 100 times. At each
randomization k, the grid origin xkvaries and the sum of animals
that died in each cell is calculated. Each block then has 100 sums
associated with it. The mean of all 100 sums was then calculated
and assigned to the location at the center of the block. This block-
averaged dataset is similar to a kernel interpolation (Petitgas
et al., 2014) and was used to smooth the response variable to
mimimize the potential effects of outliers at the boundary of
the study area. This procedure also produced spatial correlation
in the smoothed data, which was considered in downstream
analyses (see section “Co-occurrence Analysis”). Fishing effort
data, initially on a 0.05×0.05grid, were upscaled to the same
0.4×0.4grid as the dolphin bycatch data.
Co-occurrence Analysis
Spatial Generalized Additive Models (sGAMs) were used to
explore the spatial overlap between fishing effort and bycatch
locations estimated from strandings. Each year was considered
independently, but could include several UMEs (combinations of
UME dates and decomposition statuses of dolphins) (Table 4).
For each event, a grid of dolphin bycatch locations at sea was
built and analyzed with corresponding fishing effort datasets on
the same grid over the same dates. Each cell in the grid thus
constituted an individual datapoint for the correlation analyses.
The response variable was the density of bycaught dolphins
inferred from strandings, and the explanatory covariate was
fishing effort in hours. All variables were log (1 + x) transformed
before analysis, and a Gaussian likelihood was assumed for the
sGAM. In contrast to the Peltier et al. (2020) study, which
focused on a single event in 2017 and 10 fisheries, we investigated
nine years and also included information on commercial species
targeted by fisheries. This increased the number of covariates
to consider. Consequently, we used a Bayesian framework with
penalized regression and performed automatic variable selection
fitted with spike-and-slab priors (O’Hara and Sillanpää, 2009)
to assess associations between multiple fisheries and dolphin
bycatch. The variable selection and model choice with a spike-
and-slab prior structure enables the selection or deselection
of single coefficients or blocks of coefficients (Scheipl, 2011).
These features are key, since a large number of covariates
can be included in the model, and non-linear relationships
TABLE 2 | Caught fish species included in the study and their ICES abbreviations.
Species abbreviation Species name Species abbreviation Species name
BOG Bogue/Boops boops BRB Black seabream/Spondyliosoma cantharus
BSS European sea bass/Dicentrarchus labrax COE European conger/Conger conger
CPR Common prawn/Palaemon serratus CTC European common cuttlefish/Sepia officinalis
HKE European hake/Merluccius merluccius HMM Mediterranean horse mackerel/Trachurus mediterraneus
HOM Atlantic horse mackerel/Trachurus trachurus MAC Atlantic mackerel/Scomber scombrus
MAS Chub mackerel/Scomber japonicus MGR Meagre/Argyrosomus regius
MNZ Anglerfish/Lophius piscatorius MUR Striped red mullet/Mullus surmuletus
PIL European pilchard/Sardina pilchardus POL European pollock/Pollachius pollachius
SPU Spotted sea bass/Dicentrarchus punctatus SQZ Coastal squids/Teuthida spp.
SOL Common sole/Solea solea WHG Whiting/Merlangius merlangus
Note that some species were only presented in Shiny appendix—http://pelabox.univ-lr.fr:3838/pelagis/ShinyApp_v2/. ICES, International Council for the
Exploration of the Sea.
TABLE 3 | Description of data used, including the temporal and spatial resolution.
Common dolphin strandings Fishing effort (VMS data)
Spatial description French Atlantic coast ICES subareas 27.8.a and 27.8.b
Temporal description Annual –
Winter (January to April) Winter (January to April) (see Shiny appendix)
Co-occurrence UMEs in ICES subareas 27.8.a and 27.8.b
VMS, Vessel Monitoring System; ICES, International Council for the Exploration of the Sea; UME, unusual mortality event.
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TABLE 4 | Details of unusual mortality events (UMEs) used to identify correlations with fishing effort.
Year UME Dates of
stranding
events
Dates of mortality
events – fresh
animals
Dates of mortality
events – slightly
decomposed animals
Common dolphins with
bycatch evidence
Fishing efforts used as covariates
(number of fisheries)
Total fishing effort French fishing effort –
caught species
2010 No multiple stranding event
2011 1 12/01 to 19/01 08/01 to 19/01 28/12/10 to 14/01 30 21 25
2 15/02 to 07/03 11/02 to 07/03 31/01 to 02/03 114
2012 3 21/01 to 25/01 17/01 to 25/01 06/01 to 20/01 40 20 24
4 15/02 to 27/02 11/02 to 27/02 31/01 to 22/02 33
5 04/03 to 21/03 29/02 to 21/03 18/02 to 16/03 89
2013 6 11/01 to 23/02 07/01 to 23/02 27/12/12 to 18/02 316 20 31
2014 7 23/01 to 13/02 19/01 to 13/02 08/01 to 08/02 101 16 27
8 26/02 to 06/03 22/02 to 06/03 11/02 to 01/03 53
2015 9 24/02 to 10/03 20/02 to 10/03 09/02 to 05/03 46 19 28
2016 10 01/02 to 16/02 28/01 to 16/02 17/01 to 11/02 178 19 23
11 04/03 to 12/03 29/02 to 12/03 18/02 to 07/03 65
2017 12 03/02 to 10/02 30/01 to 10/02 19/01 to 05/02 210 18 23
13 28/02 to 14/03 24/02 to 14/03 13/02 to 09/03 182
2018 14 13/02 to 22/02 09/02 to 22/02 29/01 to 17/02 65 18 20
15 12/03 to 23/03 08/03 to 23/03 25/02 to 18/03 145
2019 16 28/01 to 20/02 24/01 to 20/02 13/01 to 15/02 332 14 24
17 03/03 to 22/03 27/02 to 22/03 16/02 to 17/03 345
Dates of the actual mortality events were estimated from the dates of stranding events (stranding/examination date) according to the drift duration inferred from the
decomposition status of carcasses.
between fishing effort and dolphin mortality are allowed and
estimated from data.
These two requirements, namely (i) the need to allow for
non-linear relationships and (ii) the ability to select the most
important covariates among a large number of covariates,
motivated the use of Bayesian variable selection, model choice
and regularized estimation with spike-and-slab priors in an
additive mixed model framework (Scheipl, 2011). Importantly,
within the framework of regularized regression, covariate
selection is achieved in a single model run (Authier et al.,
2017). The expression ‘spike-and-slab’ refers to a mixture prior
distribution for model coefficients. This prior is made up of
a diffuse and vague distribution (the slab) and a degenerate
distribution at 0 (the spike). The spike pulls coefficients for
which there is no information in the data on their effects
to 0, thereby achieving variable selection. The slab allows
important coefficients to escape this pull towards 0 and to
be accurately estimated. Spike-and-slab regression requires
fitting only one model to achieve model selection compared
with alternative procedures based on information criteria.
The interested reader is referred to O’Hara and Sillanpää
(2009) for an overview of Bayesian model selection methods,
and to Scheipl (2011) for all details on GAMs with spike-
and-slab priors. Finally, an important feature of the dolphin
bycatch data to be accounted for is spatial autocorrelation.
SpikeSlabGAM allows for the inclusion of spatially correlated
residuals with a Gaussian Markov Random Field (GMRF) model
whereby the neighboring structure intrinsic to our grid data is
taken into account.
For sGAM modeling, we used the spikeSlabGAM package
(Scheipl, 2011). By default, SpikeSlabGAM uses cubic B-splines
with 2nd order difference penalties to model non-linear
relationships. Data analyses were carried out on a per year
basis: for each dataset, 4 chains were run for 5,000 iterations,
discarding the first 1,000 as burn-in. Thinning was set to 4
(that is, one iteration kept out of 4) yielding a final sample of
1,000 values from the posterior for further inference. All sGAMs
included a GRMF term to account for spatial autocorrelation.
Upon convergence of all parameters in each model, results
were then visualized using the built-in plotting capabilities of
SpikeSlabGAM to visually assess the sign of the (potentially non-
linear) relationship between dolphin bycatch and fishing effort.
For statistical reasons, the low fishing effort of some European
fleets in winter prevented the testing of the co-occurrence of
their fishing effort with the origin of bycaught dolphins. For
brevity, estimated relationships were presented only for gears that
positively correlated with mortality areas in at least two years
between 2016 and 2019.
RESULTS
Strandings
Common dolphin strandings varied greatly over the study
period (Figure 4). The average over the entire study period
(1990–2019) was 340 ±SD 256 stranded individuals
per year, while the average between 2010 and 2019 was
542 ±SD 303, and 860 ±SD 206 between 2016 and 2019.
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FIGURE 4 | Long term time series of common dolphin strandings along the French Atlantic coast, from 1990 to 2009. Dark blue bars represent all common dolphin
strandings, light blue bars represent examined common dolphin strandings (fresh or slightly decomposed) with bycatch evidence. The dark blue box incorporates
the years included in the study to identify positive correlations between mortality areas and fishing effort.
The last four years in the study period had the highest
numbers of strandings.
Numbers of fresh and slightly decomposed carcasses with
evidence of bycatch followed a pattern similar to total stranding
numbers. The average number of strandings with bycatch
evidence was estimated at 205 ±SD 177 common dolphins per
year for the entire study period (1990–2019), while the average in
the last four years increased to 520 ±SD 172.
Since 2011, 17 common dolphin UMEs were recorded along
the French Atlantic coast, all related to bycatch (Table 4). The
magnitude of these events, both in duration and in number of
individuals varied greatly. No multiple stranding events were
recorded in 2010, but one to three events were observed along
the French Atlantic coast each year starting in 2011, with an
average of 138 ±SD 104 common dolphins showing evidence of
bycatch per event.
The proportion of common dolphins with bycatch evidence
recorded during a UME ranged from 49 to 92% of the total
bycaught dolphins found stranded within a year.
Likely Origin of Stranded Common
Dolphins
At least 75% of stranded common dolphins with bycatch evidence
originated from the continental shelf of the Bay of Biscay.
Some came from the Western Channel, but to a lesser extent
(Figure 5). In 2011, 2012, and 2013, more than half of common
dolphin carcasses originated from the southern Bay of Biscay.
Between 2014 and 2016, the origins of bycaught dolphins were
homogeneously distributed between the Spanish border and
southern Brittany. During the last three years of the study
period, the highest densities of dolphin mortality locations (>40
individuals/1,000 km2) were inferred between 46N and 47.5N.
Co-occurrence of Dolphin Mortality
Areas and Fishing Effort
During UMEs, French trammel netters (GTR) were positively
correlated with dolphin mortality areas in eight of the nine
years tested (Table 5 and Figure 6). French gillnetters (GNS)
and Spanish bottom trawlers (OTB) were positively correlated
with mortality areas in six years. French pair midwater trawlers
(PTM), Spanish gillnetters (GNS), and Danish seiners (SDN) co-
occurred with common dolphin bycatch events in three to four of
the years, mostly in the years with the highest bycatch numbers
(between 2016 and 2019). Six other fishing gears correlated
positively with mortality areas in only one or two years after
2010, and among them.
For the French fleets, fishing efforts of gillnetters catching hake
(Merluccius merluccius) were positively correlated with mortality
areas every year except 2014, and the efforts of midwater pair
trawlers targeting sea bass (Dicentrarchus labrax) were positively
correlated in six of the nine years tested (Table 6 and Figure 7).
The correlations were positive in all of the last four years which
had the highest levels of bycaught dolphin strandings (2016–
2019). Trammel netters catching anglerfish (Lophius spp.) were
positively correlated in six of the nine years too, including 2016–
2018. Midwater pair trawlers were positively correlated when
catching mackerel (Scomber scombrus) in four of the tested years,
and in three years (including 2017 and 2018) when catching
hake. Positive correlations were detected in bottom pair trawlers
catching hake in three of the years, only after 2016. Danish seiners
catching various species [sea bass, cuttlefish (Sepia officinalis),
mackerel and whiting (Merlangius merlangus)] only correlated
positively in two of the years. Nevertheless, this fishing gear
appeared correlated only in recent years, mostly when catching
whiting (2017 and 2018). Midwater otter trawlers, twin otter
trawlers and otter bottom trawlers—all targeting various species,
as well as purse seiners catching pilchards (Sardina pilchardus)
and trammel netters catching sea bass and sole (Solea solea)
were all positively correlated with mortality areas only once in
the time series.
Hake constituted the most recurrent target species in fishing
efforts positively correlated with mortality areas, being targeted
by four different fishing gears. Sea bass and mackerel were also
regularly targeted in positively correlated fishing efforts.
The year 2014 was unusual in that the fishing efforts of
two fisheries—bottom otter trawlers catching mackerel and
midwater otter trawlers catching hake—correlated positively with
dolphin mortality areas, but these two fisheries were never
identified in other years.
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FIGURE 5 | Origin of stranded common dolphins with bycatch evidence. Densities are presented in dead dolphins/1,000 km2. The areas defined by solid lines
included 50% of stranded dolphins, dashed lines included 75% of stranded dolphins and dotted lines 95% of stranded dolphins.
DISCUSSION
General
The recent increase in common dolphin strandings along
the French Atlantic coast occurred mostly in ICES subareas
27.8.a and 27.8.b. The use of reverse drift modeling to infer
the likely at-sea origins of stranded dolphins highlighted
the continental shelf of the Bay of Biscay as a mortality
hotspot, in particular the area between latitudes 46N and
47.5N in recent years. The expansion of bycaught common
dolphin mortality areas from the southern into the northern
Bay of Biscay and the sharp increase in stranding numbers
happened simultaneously after 2016. The boundaries of the
likely mortality areas must be carefully interpreted as the
grid used is rather coarse (0.4×0.4). The West-East
extension, mostly in the oceanic area (beyond the continental
slope) can be attributed to reverse drift modeling and
methodological uncertainties such as the absence of current
modeling in coastal areas, time-of-death estimates, or the
grid resolution.
Unusual mortality event detection is based on the analysis
of cetacean carcasses following a standardized protocol. The
decomposition state of carcasses is a major factor in diagnosing
bycatch (Peltier et al., 2020). Net marks can easily be missed
on decomposed carcasses, as the epidermis may be damaged or
missing, and edematous lungs can be indistinguishable due to
decomposition processes. The proportion of carcasses that are
fresh or slightly decomposed is directly related to the distance
to shore and drift conditions at the time of death (Bibby and
Lloyd, 1977;Hlady and Burger, 1993;Peltier et al., 2013).
Because of seasonal changes in fishing practices and dolphin
distribution, the fisheries involved could differ between spring or
summer bycatch events.
Estimates of fishing effort were derived from locations
recorded by VMS transmitters on larger vessels. Fishing effort
must be carefully interpreted because VMS transmitters have
been mandatory only on vessels >12 m long since 2010
(Commission Regulation (EC), 2009). In 2018, 73% of the
French fleet operating from Atlantic harbors was constituted
of vessels <12 m long; 1,090 smaller fishing vessels were
registered in the community fishing fleet register (IFREMER,
2019). Smaller vessels and small scale or artisanal fisheries are
still largely overlooked, despite their potential threat to cetacean
populations having been demonstrated (Zappes et al., 2013;
Cruz et al., 2018).
The calculation based on vessel speed is applied to all gears,
both towed and static. The assumption that vessels under
4.5 knots are actively fishing is mostly relevant for towed
gears, as trawl, seine or dredge operations require slow speeds.
Nevertheless, false-positive results, i.e., vessels traveling at low
speed but not engaged in fishing, can be generated using
this vessel speed filter. However, false-positive results probably
represent a low fraction of estimated fishing time (Bertrand et al.,
2008;Gerritsen and Lordan, 2011). Applying this methodology
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TABLE 5 | Time series of positive correlations (in blue) between fishing effort and origin of bycaught common dolphins in ICES subareas 27.8.a and 27.8.b (2010–2019).
Country Gear 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2011–2019
occurrence (%)
2016–2019
occurrence (%)
France
GTR 89 100
GNS 67 100
OTB 33 0
PTB 22 50
PTM 44 75
SDN 33 75
OTM 22 25
OTT 11 25
PS 11 0
Spain
OTB 67 50
GNS 33 75
PS 11 0
UK
GNS 11 0
Gears positively
correlated
4 4 4 3 3 5 6 5 7
No Multiple Stranding Event
Common dolphin
strandings with
bycatch evidence
(Fresh and slightly
decomposed
animals, during
UMEs)
37
144
162
316
154
46
243
392
210
677
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Total fishing effort of the different fishing gears and flags were tested. Occurrence over the whole time series and during the past four years (with highest stranding
records) were calculated, as well as the percentage of the total number of years in which a positive correlation was found. Gear abbreviations are available in Table 1.
Stranding numbers of common dolphins with bycatch evidence are also presented (2010–2019). ICES, International Council for the Exploration of the Sea; UME, unusual
mortality event. Gray cells indicate neutral or negative correlations.
FIGURE 6 | Functional relationships between the origin of bycaught common dolphins and fishing effort in ICES subareas 27.8.a and 27.8.b for Spanish gillnetters
(GNS_ESP), French trammel netters (GTR_FRA), French gillnetters (GNS_FRA), Spanish bottom trawlers (OTB_ESP), French midwater pair trawlers (PTM_FRA),
French Danish seiners (SDN_FRA). Note that only fisheries which correlated positively at least twice since 2016 are presented. ICES - International Council for the
Exploration of the Sea.
to static gears probably produces fishing effort data that are more
difficult to interpret. The low speed of vessels operating static
gear can be detected when the gears are set or hauled. Still, the
use of VMS data to assess fishing effort is relevant to highlight
changes within years, as long as fishing efforts are not directly
compared between gears.
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TABLE 6 | Time series of positive correlations (in red) between fishing effort and origin of bycaught common dolphins in ICES subareas 27.8.a and 27.8.b (2010–2019).
Gear Caught
species
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2011–2019
occurrence (%)
2016–2019
occurrence (%)
GNS HKE 89 100
GTR
BSS 11 0
MNZ 67 75
SOL 11 0
OTB
CTC 22 0
MAC 11 0
MNZ 11 0
SQZ 11 0
OTM HKE 11 0
OTT CTC 11 25
MNZ 11 25
PS PIL 11 25
PTB HKE 33 75
PTM
BSS 67 100
HKE 33 50
MAC 44 25
SDN
BSS 11 25
CTC 22 50
MAC 22 25
WHG 22 50
Gears positively
correlated
5 5 7 3 3 5 6 8 6
No Multiple Stranding Event
Common dolphin
strandings with
bycatch evidence
(Fresh and slightly
decomposed
animals, during
UMEs)
37
144
162
316
154
46
243
392
210
677
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
The fishing effort of French vessels using different gears related to caught species were tested. Occurrence over the whole time series and during the past four years
(with highest stranding records) were calculated, as well as the percentage of the total number of years in which a positive correlation was found. Gear abbreviations are
available in Tables 1,2. Strandings of common dolphins with bycatch evidence are also presented (2010–2019). ICES, International Council for the Exploration of the
Sea, UME; unusual mortality event. Gray cells indicate neutral or negative correlations.
The long-term analysis highlighted seven different fisheries
whose fishing efforts positively correlated with dolphin mortality
areas in at least two years between 2016 and 2019, the period
with the highest numbers of strandings recorded since the
establishment of the French Stranding Network in the 1980s.
For the French fleet, correlations within the two fishing
effort datasets were consistent overall (total effort per gear
and fishing effort per landed species and gear). Nevertheless,
positive correlations of fishing efforts from these two datasets
with dolphin mortality areas did not necessarily occur
simultaneously (Figure 8).
The joint analysis of VMS data and the origins of
stranded bycaught common dolphins in the Bay of Biscay
provide relevant and realistic information with regards to
fisheries potentially responsible for common dolphin bycatch.
Nevertheless, co-occurrence does not imply causality, merely that
both phenomena occurred at the same place at the same time.
In fact, positive correlations can be identified for fisheries that
cannot generate dolphin bycatch (e.g., longlines, traps, pods,
etc.) but shared common fishing grounds with the fisheries
responsible. Moreover, the degree of correlation does not indicate
the intensity of the interaction, as bycatch events can be intense
and limited in space and time.
Fisheries of the Bay of Biscay
The Bay of Biscay is an important area for the fishing industry,
fishing effort is intense in this region (Kroodsma et al., 2018). The
fisheries operating in ICES subareas 27.8.a and 27.8.b are highly
diverse in terms of their flags, gears used, and species targeted
(SIH—Système d’informations halieutiques, http://sih.ifremer.fr/).
Around 2,000 fishing vessels were active in this area in the year
2018 (Demanèche et al., 2019). The breakdown by flag was as
follows: 1,486 French vessels, including 1,072 vessels <12 m; 300
Spanish vessels (average size of 25 m); 22 Irish vessels (average
size of 33 m); 18 British vessels (average size of 37 m); 12 Belgian
vessels (average size of 37 m); 5 German vessels (average size of
41 m); 3 Dutch vessels (average size of 113 m) and one Danish
trawler (size of 70 m). Because of the great diversity of vessels
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FIGURE 7 | Functional relationships between the origin of bycaught common dolphins and fishing effort in ICES subareas 27.8.a and 27.8.b for French fleets
according to caught species: gillnetters catching hake (GNS_HKE), trammel netters catching anglerfish (GTR_MNZ), bottom pair trawlers catching hake (PTB_HKE),
midwater pair trawlers catching sea bass (PTM_BSS), midwater pair trawlers catching mackerel (PTM_MAC), Danish seiners catching whiting (SDN_WHG). ICES,
International Council for the Exploration of the Sea.
operating in the Bay of Biscay, only fisheries positively correlated
with likely common dolphin bycatch areas will be described.
Most of the French vessels deployed nets (39%; gillnets and
trammel nets). Only 17% of them were equipped with VMS
transmitters (Demanèche et al., 2019). The maximum activity
was recorded in spring and summer. The number of netters in
the Bay of Biscay decreased over the study period, but “fishing
effort” (or “indicator of set and haul time”) remained quite stable
for vessels >12 m after 2010 (Supplementary Figure 1). The
decrease in netters was mostly due to the reduction of smaller
vessels, whereas the number of larger vessels above 15 m was
stable or even increased (>24 m). Fishing activity of smaller
vessels (<12 m) remained mostly coastal, within the 12 NM
limit. The main species landed by smaller netters in winter were
sole, pollock and sea bass, whereas hake, sole and anglerfish were
mostly landed by larger netters, Hake landings doubled between
2013 and 2018 for netters of all size categories (Demanèche
et al., 2019;Supplementary Figure 2). Bottom trawlers (single
and paired) constituted 30% of the vessels operating in the
Bay of Biscay in winter, and 57% of them were equipped with
VMS transmitters. The main species landed by bottom trawlers
were anglerfish and hake. Bottom pair trawlers targeted mostly
hake, and landings remained stable after 2010 (Supplementary
Figure 2). Midwater pair trawlers represented 5% of fishing
vessels in ICES subareas 27.8.a and 27.8.b in 2018; 84% of
which were above 12 m. Catches of sea bass by midwater pair
trawlers decreased greatly after the 2010 winter, whereas hake
landings increased between 2014 and 2017, and decreased in 2018
and 2019. Fishing effort associated with hake catches occurred
mostly in winter along the 100 m isobath, south of 46N in
2016 and north of 45.5N after 2017 (see Shiny appendix http://
pelabox.univ-lr.fr:3838/pelagis/ShinyApp_v2/). Similar patterns
were highlighted for sea bass catches. French Danish seiners,
operating in the Bay of Biscay since 2009, constituted a small fleet
(<1% of vessels in ICES subareas 27.8.a and 27.8.b) and were
all equipped with VMS transmitters. They fish both demersal
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FIGURE 8 | Theoretical co-occurrence of the origin of stranded dolphins and fishing effort in two distinct scenarios. The red box represents the origin of stranded
bycaught dolphins. In panel (A), the total effort of gear A is presented and only the effort dedicated to catching species 3 correlates with the origin of the strandings.
In panel (B), the origin of the strandings is positively correlated with the total fishing effort including all three species; individually considered, fishing effort for each of
the different species is not correlated.
and pelagic species, mostly whiting, mackerel and sea bass. Their
main fishing grounds were located between 45N and 48N,
within the 100 m isobath. Depending on the vessel and target
species, the vertical opening of seines can reach several meters
while hauling. Although irregular, fishing effort of Danish seiners
have been increasing, mostly in 2018 and 2019.
The Spanish fleet operated all year in the study area, with
the highest fishing effort recorded between April and November.
Almost half of the Spanish vessels operated purse seines targeting
anchovies in spring (ICES, 2018). The other half of the fleet
included 28% longliners, 21% gillnetters, and 9% bottom trawlers,
both pair and single. The trawl fleet operated across the whole
Bay of Biscay (see Shiny appendix http://pelabox.univ-lr.fr:
3838/pelagis/ShinyApp_v2/), but total fishing effort in winter
decreased slightly after 2010 (Appendix 1). The main species
landed by Spanish trawlers are hake, anglerfish and megrim
(Argyrosomus regius) (ICES, 2019). Winter fishing effort of
Spanish gillnetters was relatively stable between 2010 and 2019.
The main target species of Spanish vessels using static gear was
hake (ICES, 2019).
The fishing effort of British vessels was low but constant
throughout the study period, and quite stable after 2010. Only 5
vessels were registered as gillnetters (Demanèche et al., 2019) and
generally operated over the whole Bay of Biscay.
Relevance of Identified Fisheries
Fisheries whose fishing efforts correlated positively with dolphin
mortality areas were consistent with métiers of concern identified
by ICES in subareas 27.8.a and 27.8.b, based on at-sea
observations (ICES, 2020c,Table 7). French Danish seiners were
the only métier positively correlated with bycatch areas for which
no bycatch was recorded by observers between 2016 and 2018.
The highest bycatch numbers were observed on trammel netters
(GTR) targeting demersal fishes (DEF). Demersal fishes include
hake, sea bass, whiting and anglerfish, all of which were positively
correlated with bycatch areas. Bottom pair trawlers, targeting
a mix of pelagic and demersal species, included a variety of
gears and flags (Spanish bottom pair and otter trawlers, and
French bottom pair trawlers). Common dolphin bycatch has
been documented in bottom pair trawl fisheries targeting hake in
North-Western Spain (Fernández-Contreras et al., 2010), which
is consistent with the above correlation findings. The fishing
efforts of vessels using midwater pair trawls and gillnets to
target demersal fish (Table 7) also correlated positively with
the mortality areas of bycaught dolphins. Interactions between
midwater pair trawls and common dolphins in the Bay of Biscay
were documented 20 years ago (Morizur et al., 1999;Northridge
et al., 2006): various EU funded projects, including PETRACET
(Pelagic TRAwl and CETaceans) and NECESSITY, revealed that
in the early 2000s most bycatch of common dolphins in the Bay
of Biscay and the Celtic Sea occurred in midwater pair trawls
targeting sea bass in winter (Northridge et al., 2006). High levels
of common dolphin bycatch were reported in the early 1990s
on pair trawling fisheries targeting hake (Murphy et al., 2013;
ASCOBANS, 2015).
Midwater pair trawlers targeting large pelagic fish, mostly
tuna, operate in the oceanic waters of the Bay of Biscay during
summer (ICES, 2020b). Distance from the coast as well as
drift conditions in summer make it unlikely that strandings of
common dolphins bycaught in tuna fisheries along the French
Atlantic coast would be detected (Morizur et al., 1999;Peltier
et al., 2013), although high numbers of bycaught common and
striped dolphins were recorded in these fisheries in the late
1990s (Rogan and Mackey, 2007), and more recently by at-
sea monitoring on midwater pair trawlers targeting albacore
(Thunnus alalunga) (ICES, 2020c).
Areas where several predatory fish species were caught - such
as sea bass, hake, anglerfish or whiting—correlated positively
with common dolphin bycatch areas. Of these predatory species,
sea bass, mackerel, hake and whiting have common prey
species, including anchovy, sardine, or sprat (Sprattus sprattus)
(Quéro and Vayne, 1997;Mahe et al., 2007;Murua, 2010;
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TABLE 7 | Summary of the bycatch rate and mortality of common dolphins for métiers of concern from at-sea monitoring (ICES subareas 27.8.a and 27.8.b, data
pooled 2016–2018), raised using the annual mean of available fishing effort from the Regional DataBase (RDB, i.e., data collected in the context of the Data Collection
Framework; in ICES, 2020b).
Gear (Métier 4a) Target species
(Métier 5b)
Fishing effort (RDB,
DaS)
Bycatch rate
(animals/DaS fished)
At-sea monitoring
estimates (95% CI)
% coverage of RDB
fishing effort (DaS)
GTR DEF 58,365 0.035 2,061 (1,203–3,092) 0.194
PTB MPD 5,195 0.149 775 (388–1,163) 0.43
PTM DEF 682 0.71 481 (408–555) 8.2
OTM DEF 243 1.22* 297 (0–890) 0.112
PS SPF 35,564 0.0060 213 (0–532) 0.31
GNS DEF 36,836 0.0037 137 (0–343) 0.49
PTM LPF 510 0.0153 8 (0–23) 4.3
Total 3,973 (1,998–6,598)
ICES, International Council for the Exploration of the Sea; DEF, Demersal Fish; MPD, Mixed Pelagic and Demersal fish; SPF, Small Pelagic Fish; LPF, Large Pelagic Fish.
aSee https://vocab.ices.dk/?ref=1498 for gear description.
bSee https://vocab.ices.dk/?ref=1499 for target species description.
*Bycatch rate calculated from 1 day-at-sea observed.
Spitz et al., 2013). Small pelagic fishes are a large proportion of
the common dolphin diet, suggesting a likely ecological and
spatial overlap between common dolphins and the correlated
catches identified (Pusineri et al., 2007;Meynier et al., 2008;
Spitz et al., 2013;Murphy et al., 2019). Schooling behavior in
small pelagic fishes can lead to high local densities of various
predatory species due to possible mutualism and facilitation
processes in aggregation of both prey and predator species
(Astarloa et al., 2019).
Management and Conservation
Implications
Except for changes in hake landings by various fisheries, no
change in either overall fishing effort or general fishing practice
(gear or target species) was observed, based on ICES and
European Commission required data, that could explain the large
increase in stranded common dolphins along the French Atlantic
coast after 2016. The increase in bycatch could be the result of
changes in fishing practices after 2015 that were not covered
by national or EU data requirements. Fishing data required
by the EU Data Collection Framework include, among other
things: days at sea, fishing days, landed species and weight, and
métiers at level 5 of the ICES classification (gear type +target
species assemblage, see https://vocab.ices.dk/?ref=1498 for gear
description). These data are available at a trimester temporal
resolution. Changes in these parameters at large spatial and
temporal scales have not been detected in the past 10 years (ICES,
2020b), but small scale changes in fishing practices (height of nets,
setting strategies, depth of gear, etc.) could modify interactions
with common dolphins. So far, no long-term data have been
collected to test these hypotheses. Requirements of robust and
relevant at-sea observation data (observer/Remote Electronic
Monitoring, REM), supported by a random sampling strategy,
are crucial in order to refine studies of the interactions between
cetaceans and fishing vessels and therefore to establish effective
mitigation strategies (Dolman et al., 2021).
Another possible explanation for the recent increase in
bycatch could be a change in dolphin distribution relative to
the fishing grounds where fisheries posing the greatest risk of
bycatch operate. Driven by ecological factors—such as changes
in prey behavior or distribution, or a shift of common dolphins
to the coastal waters of the Bay of Biscay - could increase the
risk of bycatch. Possible small-scale changes in common dolphin
prey distribution could be supported by oceanographic data and
fishery surveys in winter.
CONCLUSION
The fisheries identified to have been actively fishing in
the mortality area at the time of bycatch events included
three using towed gear (French midwater trawlers, French
Danish seiners and Spanish bottom trawlers) and three using
static gear (French gillnetters, French trammel netters and
Spanish gillnetters). Among the French vessels, seven fisheries
occurred simultaneously with common dolphin bycatch at
least twice in the years between 2016 and 2019: gillnetters
fishing hake, trammel netters fishing anglerfish, bottom pair
trawlers fishing hake, midwater pair trawlers fishing sea bass,
hake and mackerel, and Danish seiners fishing whiting. Some
of these fisheries’ efforts correlated positively with dolphin
mortality areas nearly each year since 2010, including French
gillnetters (especially those targeting hake), French trammel
netters (especially those targeting anglerfish), Spanish bottom
trawlers, and French midwater pair trawlers in sea bass fishing
areas. The characteristics common to all of these fisheries include
high vertical heights (nets) or openings (trawls) and the targeting
of predatory fishes in winter.
The diversity of the fisheries this study identified as the
potential culprits behind the bycatch events between 2010 and
2019 makes it difficult to suggest specific and adapted mitigation
strategies to implement. At-sea observation of fishing vessels,
either by on-board observers or Remote Electronic Monitoring
(REM), is therefore crucial to further investigate and validate
studies related to the bycatch issue and help mitigate the threat of
bycatch more effectively and precisely in the future. At this point,
it seems that only the closure of certain fishing areas at specific
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Peltier et al. Co-occurence of Bycatch and Fisheries
times following different potential scenarios could achieve EU
requirements in terms of bycatch reduction (ICES, 2020c).
DATA AVAILABILITY STATEMENT
The data analyzed in this study is subject to the following
licenses/restrictions: VMS data used in this article are subject
to specific convention with French ministry in charge of
agriculture and fisheries. Therefore, these data cannot be
freely and fully available online as Supplementary Material.
Agregated data are avalaible online (http://pelabox.univ-lr.fr:
3838/pelagis/ShinyApp_v2/). Stranding data are freely available
online (location, date and species) (http://seamap.env.duke.edu/
dataset/1406). For detailed stranding data, please send request to
corresponding author or Pelagis. Requests to access these datasets
should be directed to pelagis@univ-lr.fr or HP, hpeltier@univ-
lr.fr.
ETHICS STATEMENT
Ethical review and approval was not required for the animal
study because this work required no particular permit, and so,
the authors have adhered to general guidelines for the ethical
use of animals in research, the legal requirements in France and
respective institutional guidelines.
AUTHOR CONTRIBUTIONS
HP: perform analyses, conception, and writing of the paper. WD,
CD, FD, EM, and OV: coordination of the French stranding
network and collect of stranding data. MA: support in analysis,
support in paper conception and correction. PD: conception of
the drift prediction model. JS, FC, VR: support in manuscript
conception and correction. All authors contributed to the article
and approved the submitted version.
ACKNOWLEDGMENTS
We would like to thank the Fisheries Information System
team from IFREMER (http://sih.ifremer.fr/), especially Emilie
Leblond for preparing and providing the data on fishing effort
distribution and for her availability and help in managing and
analyzing this data set. We also thank the Direction des Pêches
Maritimes et de l’Aquaculture for allowing data to be made
available by IFREMER. We are grateful to all the members
of the French stranding scheme for their continuous effort
in collecting data on stranded cetaceans. We thank Auriane
Virgili for creating the Shiny appendix, and Bruno Mansoux
for uploading it. The Observatoire PELAGIS is funded by the
Ministry in charge of the Environment, the French Office for
Biodiversity (Office Français pour la Biodiversité—AFB) and the
Communauté d’Agglomération de la Ville de La Rochelle.
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fmars.
2021.617342/full#supplementary-material
REFERENCES
Adimey, N. M., Hudak, C. A., Powell, J. R., Bassos-Hull, K., Foley, A., Farmer,
N. A., et al. (2014). Fishery gear interactions from stranded bottlenose dolphins,
Florida manatees and sea turtles in Florida, U.S.A. Mar. Pollut. Bull. 81,
103–115. doi: 10.1016/j.marpolbul.2014.02.008
Amandè, M. J., Chassot, E., Chavance, P., Murua, H., de Molina, A. D., and Bez, N.
(2012). Precision in bycatch estimates: the case of tuna purse-seine fisheries in
the Indian Ocean. ICES J. Mar. Sci. J. Cons. 69, 1501–1510. doi: 10.1093/icesjms/
fss106
Antoine, L., Goujon, M., and Massart, G. (1997). Captures Accidentelles de
Dauphins Dans les Filets Dérivants à Thon en Atlantique Nord-Est (No.
M1997/Q:10), By-Catch of Marine Mammals: Gear Technology, Behaviour and
Kill Rates. West Bengal: CIEM.
ASCOBANS (2015). Report of the ASCOBANS Expert Workshop on the
Requirements of Legislation to Address Monitoring and Mitigation of Small
Cetacean Bycatch. Bonn: ASCOBANS, 37.
Astarloa, A., Louzao, M., Boyra, G., Martinez, U., Rubio, A., Irigoien, X., et al.
(2019). Identifying main interactions in marine predator–prey networks of
the Bay of Biscay. ICES J. Mar. Sci. 76, 2247–2259. doi: 10.1093/icesjms/
fsz140
Authier, M., Peltier, H., Dorémus, G., Dabin, W., Canneyt, O. V., and 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. Biodivers. Conserv.
23, 2591–2612. doi: 10.1007/s10531-014- 0741-3
Authier, M., Saraux, C., and Péron, C. (2017). Variable selection and accurate
predictions in habitat modelling: a shrinkage approach. Ecography 40, 549–560.
doi: 10.1111/ecog.01633
Benoît, H. P., and Allard, J. (2009). Can the data from at-sea observer surveys be
used to make general inferences about catch composition and discards? Can. J.
Fish. Aquat. Sci. 66, 2025–2039. doi: 10.1139/F09-116
Bernaldo de Quirós, Y., Hartwick, M., Rotstein, D. S., Garner, M. M., Bogomolni,
A., Greer, W., et al. (2018). Discrimination between bycatch and other causes of
cetacean and pinniped stranding. Dis. Aquat. Organ. 127, 83–95. doi: 10.3354/
dao03189
Bertrand, S., Díaz, E., and Lengaigne, M. (2008). Patterns in the spatial distribution
of Peruvian anchovy (Engraulis ringens) revealed by spatially explicit fishing
data. Prog. Oceanogr. 79, 379–389. doi: 10.1016/j.pocean.2008.10.009
Bibby, C. J., and Lloyd, C. S. (1977). Experiments to determine the fate of
dead birds at sea. Biol. Conserv. 12, 295–309. doi: 10.1016/0006-3207(77)90
048-9
Commission Regulation (EC) (2009). No 1224/2009 of 20 November 2009
Establishing a Community Control System for Ensuring Compliance with the
Rules of the Common Fisheries Policy, Amending Regulations (EC). Bruxelles:
Council of the European Union.
Council of the European Union (1998). Council Regulation (EC) No. 1239/98
of 8 June 1998 Amending Regulation (EC) No. 894/97 Laying Down Certain
Technical Measures for the Conservation of Fishery Measures. Bruxelles: Council
of the European Union.
Council of the European Union (2004). COUNCIL REGULATION (EC) No
812/2004 of 26.4.2004, L 150/12. Bruxelles: Council of the European Union.
Council of the European Union (2008). COUNCIL REGULATION (EC) No
665/2008 of 14.7.2008, L 186/3. Bruxelles: Council of the European Union.
Council of the European Union (2019). RÈGLEMENT (UE) 2019/1241 DU
PARLEMENT EUROPÉEN ET DU CONSEILdu 20.6.2019, L 198/105. Bruxelles:
Council of the European Union.
Frontiers in Marine Science | www.frontiersin.org 15 April 2021 | Volume 8 | Article 617342
fmars-08-617342 April 28, 2021 Time: 16:24 # 16
Peltier et al. Co-occurence of Bycatch and Fisheries
Cruz, M. J., Machete, M., Menezes, G., Rogan, E., and Silva, M. A. (2018).
Estimating common dolphin bycatch in the pole-and-line tuna fishery in the
Azores. PeerJ 6:e4285. doi: 10.7717/peerj.4285
Daniel, P., Jan, G., Cabioc’h, F., Landau, Y., and Loiseau, E. (2002). Drift Modeling
of Cargo Containers. Spill Sci. Technol. Bull. 7, 279–288. doi: 10.1016/s1353-
2561(02)00075-0
Dars, C., Dabin, W., Demaret, F., Doremus, G., Meheust, E., Mendez-Fernandez,
P., et al. (2019). Les Échouages de Mammifères marinssur le Littoral Français en
2018 (Rapport Scientifique de L’observatoire PELAGIS, Université de La Rochelle
et CNRS), Rapport Annuel.
De Boer, M. N., Leaper, R., Keith, S., and Simmonds, M. P. (2008). Winter
abundance estimates for the common dolphin (Delphinus delphis) in the
western approaches of the English Channel and the effect of responsive
movement. J. Mar. Anim. Environ. 1, 15–21.
Demanèche, S., Berthou, P., Le Blond, S., Bégot, E., Weiss, J., Biseau, A., et al.
(2019). Amélioration de la Connaissance de L’activité desFileyeurs dasn le golfe de
Gascogne – Analyse préliminaire (No. DPMA-Direction des Pêches Maritimes et
de l’Aquaculture, La Défense, Ref. DG/2019.350-saisine DPMA 19-14259). Brest:
IFREMER
Deporte, N., Ulrich, C., Mahévas, S., Demanèche, S., and Bastardie, F. (2012).
Regional métier definition: a comparative investigation of statistical methods
using a workflow applied to international otter trawl fisheries in the North Sea.
ICES J. Mar. Sci. 69, 331–342. doi: 10.1093/icesjms/fsr197
Dolman, S. J., Evans, P. G. H., Ritter, F., Simmonds, M. P., and Swabe, J.
(2021). Implications of new technical measures regulation for cetacean bycatch
in European waters. Mar. Policy 124:104320. doi: 10.1016/j.marpol.2020.10
4320
Faunce, C. H., and Barbeaux, S. J. (2011). The frequency and quantity of Alaskan
groundfish catcher-vessel landings made with and without an observer. ICES J.
Mar. Sci. J. Cons. 68, 1757–1763. doi: 10.1093/icesjms/fsr090
Fernández-Contreras, M. M., Cardona, L., Lockyer, C. H., and Aguilar, A. (2010).
Incidental bycatch of short-beaked common dolphins (Delphinus delphis) by
pairtrawlers off northwestern Spain. ICES J. Mar. Sci. J. Cons. 67, 1732–1738.
doi: 10.1093/icesjms/fsq077
Gerritsen, H., and Lordan, C. (2011). Integrating vessel monitoring systems (VMS)
data with daily catch data from logbooks to explore the spatial distribution of
catch and effort at high resolution. ICES J. Mar. Sci. 68, 245–252. doi: 10.1093/
icesjms/fsq137
Hammond, P. S., Lacey, C., Gilles, A., Viquerat, S., Börjesson, P., Herr, H.,
et al. (2017). Estimates of Cetacean Abundance in European Atlantic Waters in
Summer 2016 from the SCANS-III Areial and Shipboard Surveys.
Hart, K. M., Mooreside, P., and Crowder, L. B. (2006). Interpreting the spatio-
temporal patterns of sea turtle strandings: going with the flow. Biol. Conserv.
129, 283–290. doi: 10.1016/j.biocon.2005.10.047
Hlady, D. A., and Burger, A. E. (1993). Drift-Block experiments to analyse the
mortality of oiled seabirds off vancouver Island, British Columbia. Mar. Pollut.
Bull. 26, 495–501. doi: 10.1016/0025-326x(93)90466- w
ICES (2016). Report of the Working Group on Bycatch of Protected Species (WGBYC)
(No. ICES CM 2016/ACOM:27). Copenhagen: ICES.
ICES (2017). Report of the Working Group on Bycatch of Protected Species (WGBYC)
(ICES WGBYC REPORT 2017 No. CES CM 2017/ACOM:24). Woods Hole, MA:
ICES.
ICES (2018). Report of the Working Group on Southern Horse Mackerel, Anchovy
and Sardine (WGHANSA) (No. ICES CM 2018/ACOM:17.). Lisbon: ICES.
ICES (2019). Bay of Biscay and Iberian Coast ecoregion – Fisheries overview,
including mixed-fisheries considerations (ICES Fisheries OverviewsBay of Biscay
and Iberian Coast ecoregion). Copenhagen: ICES.
ICES (2020c). EU request on emergency measures to prevent bycatch of common
dolphin (Delphinus delphis) and Baltic Proper harbour porpoise (Phocoena
phocoena) in the Northeast Atlantic. (Report of the ICES Advisory Committee,
2020. No. ICES Advice 2020, sr.2020.04.). Copenhagen: ICES.
ICES (2020a). Report of the working group on bycatch of protected species (WGBYC)
(ICES WGBYC REPORT 2020 No. CES CM 2020/ACOM:26). Den Helder: ICES.
ICES (2020b). 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) [Draft Report]. (ICES Scientific Reports). Vol. 2,
Copenhagen: ICES.
IFREMER (2019). Systèmes d’Informations Halieutiques, 2019. Flotte de la Façade
Atlantique. 2018. Synthèse des Flottilles de Pêche. Brest: Ifremer. Systèmes
d’Informations Halieutiques.
Ihaka, R., and Gentleman, R. (1996). R: a language for data analysis and graphics.
J. Comput. Stat. Graph. Anal. 5, 299–314.
IWC (2016). Report of the 66th Meeting of the International Whaling Commission
and Associated Meetings and Workshops. IWC 66th, Slovenia. Portoroz: IWC.
Kroodsma, D. A., Mayorga, J., Hochberg, T., Miller, N. A., Boerder, K., Ferretti, F.,
et al. (2018). Tracking the global footprint of fisheries. Science 359, 904–908.
doi: 10.1126/science.aao5646
Kuiken, T. (1994). Diagnosis of Bycatch in Cetaceans, Proceedings of the Second ECS
Workshop on Cetacean Pathology. Montpellier: European Cetacean Society.
Laran, S., Authier, M., Blanck, A., Dorémus, G., Falchetto, H., Monestiez, P., et al.
(2017). Seasonal distribution and abundance of cetaceans within French waters:
Part II: the bay of biscay and the english channel. Deep Sea Res. Part II 141,
31–40. doi: 10.1016/j.dsr2.2016.12.012
Leeney, R. H., Amies, R., Broderick, A. C., Witt, M. J., Loveridge, J., Doyle, J., et al.
(2008). Spatio-temporal analysis of cetacean strandings and bycatch in a UK
fisheries hotspot. Biodivers. Conserv. 17, 2323–2338. doi: 10.1007/s10531-008-
9377-5
Lopez, A., Pierce, G. J., Santos, M. B., Gracia, J., and Guerra, A. (2003). Fishery
by-catches of marine mammals in Galician waters: results from on-board
observations and an interview survey of fishermen. Biol. Conserv. 111, 25–40.
doi: 10.1016/s0006-3207(02)00244- 6
Mahe, K., Amara, R., Bryckaert, T., Kacher, M., and Brylinski, J. M. (2007).
Ontogenetic and spatial variation in the diet of hake (Merluccius merluccius)
in the Bay of Biscay and the Celtic Sea. ICES J. Mar. Sci. 64, 1210–1219.
doi: 10.1093/icesjms/fsm100
Meynier, L., Pusineri, C., Spitz, J., Santos, M. B., Pierce, G. J., and Ridoux, V. (2008).
Intraspecific dietary variation in the short-beaked common dolphin Delphinus
delphis in the Bay of Biscay: importance of fat fish. Mar. Ecol. Prog. Ser. 354,
277–287. doi: 10.3354/meps07246
Moore, M. J., Mitchell, G. H., Rowles, T. K., and Early, G. A. (2020). Dead cetacean?
Beach, bloat, float, sink. Front. Mar. Sci. 7:333. doi: 10.3389/fmars.2020.00333
Morizur, Y., Berrow, S. D., Tregenza, N. J. C., Couperus, A. S., and Pouvreau,
S. (1999). Indidental catches of marine-mammals in pelagic trawl fisheries of
the northeast Atlantic. Fish. Res. 41, 297–307. doi: 10.1016/s0165-7836(99)00
013-2
Murphy, S., Evans, P. G. H., Pinn, E., and Pierce, G. J. (2019). Conservation
management of common dolphins: lessons learned from the North-East
Atlantic. Aquat. Conserv. Mar. Freshw. Ecosyst. 96, 1–30. doi: 10.1002/aqc.3212
Murphy, S., Pinn, E. H., and Jepson, P. D. (2013). The short-beaked common
dolphin (Delphinus delphis) in the North-East Atlantic: distribution, ecology,
management and conservation status. Oceanogr. Mar. Biol. Annu. Rev. 51,
193–280.
Murua, H. (2010). “Chapter two - the biology and fisheries of European Hake,
Merluccius merluccius, in the North-East Atlantic,” in Advances in Marine
Biology. ed. M. Lesser (Cambridge, MA: Academic Press), 97–154. doi: 10.1016/
B978-0- 12-381015- 1.00002-2
NECESSITY Report (2008). Rapport D’activité final NECESSITY sur l’interaction
entre le Chalutage Pélagique et els Populations de cétacés: Impact et
Mitigation. (Soutien Scientifique á la Réglementation No. SSP8-CT-2003-
501605). IFREMER/CRMM-ULR. Bruxelles: Council of the European Union.
Northridge, S. P. (1991). “Driftnet fisheries and their impacts on non-target species:
a worldwide review,” in FAO Fisheries Technical Paper, No.320 (Rome: FAO),
115.
Northridge, S. P., Morizur, Y., Souami, Y., and Van Canneyt, O. (2006).
PETRACET: Project EC/FISH/2003/09 FinalRepor t to theEuropean Commission
1735R07D. Lymington: MacAliser Elliott and Partners Ltd.
O’Hara, R. B., and Sillanpää, M. J. (2009). A review of Bayesian variable selection
methods: what, how and which. Bayesian Anal. 4, 85–117. doi: 10.1214/09-
BA403
Pante, E., and Simon-Bouhet, B. (2013). marmap: A package for importing, plotting
and analyzing bathymetric and topographic data in R. PLoS One 8:e73051.
doi: 10.1371/journal.pone.0073051
Peltier, H., Authier, M., D abin,W., Dars, C., Demaret, F., Doremus, G., et al. (2020).
Can modelling the drift of bycaught dolphin stranded carcasses help identify
Frontiers in Marine Science | www.frontiersin.org 16 April 2021 | Volume 8 | Article 617342
fmars-08-617342 April 28, 2021 Time: 16:24 # 17
Peltier et al. Co-occurence of Bycatch and Fisheries
involved fisheries? An exploratory study. Glob. Ecol. Conserv. 21:e00843. doi:
10.1016/j.gecco.2019.e00843
Peltier, H., Authier, M., Deaville, R., Dabin, W., Jepson, P. D., van Canneyt, O.,
et al. (2016). Small cetacean bycatch as estimated from stranding schemes: the
common dolphin case in the northeast Atlantic. Environ. Sci. Policy 63, 7–18.
doi: 10.1016/j.envsci.2016.05.004
Peltier, H., Baagøe, H. J., Camphuysen, K. C. J., Czeck, R., Dabin, W., Daniel,
P., et al. (2013). The Stranding Anomaly as Population Indicator: the case
of harbour porpoise phocoena phocoena in north-western europe. PLoS One
8:e62180. doi: 10.1371/journal.pone.0062180
Peltier, H., Dabin, W., Daniel, P., Van Canneyt, O., Dorémus, G., Huon, M., et al.
(2012). The significance of stranding data as indicators of cetacean populations
at sea: modelling the drift of cetacean carcasses. Ecol. Indic. 18, 278–290. doi:
10.1016/j.ecolind.2011.11.014
Peltier, H., Jepson, P. D., Dabin, W., Deaville, R., Daniel, P., Van Canneyt, O., et al.
(2014). The contribution of stranding data to monitoring and conservation
strategies for cetaceans: developing spatially explicit mortality indicators for
common dolphins (Delphinus delphis) in the eastern North-Atlantic. Ecol. Indic.
39, 203–214. doi: 10.1016/j.ecolind.2013.12.019
Peltier, H., and 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. Environ. Sci.
Policy 54, 240–247. doi: 10.1016/j.envsci.2015.07.013
Petitgas, P., Doray, M., Huret, M., Massé, J., and Woillez, M. (2014). Modelling
the variability in fish spatial distributions over time with empirical orthogonal
functions: anchovy in the Bay of Biscay. ICES J. Mar. Sci. 71, 2379–2389.
doi: 10.1093/icesjms/fsu111
Pusineri, C., Magnin, V., Meynier, L., Spitz, J., Hassani, S., and Ridoux, V. (2007).
Food and feeding ecology of the common dolphin (delphinus Delphis) in the
Oceanic Northeast Atlantic and Comparison with Its Diet in Neritic Areas. Mar.
Mammal Sci. 23, 30–47. doi: 10.1111/j.1748-7692.2006.00088.x
Quéro, J.-C., and Vayne, J.-J. (1997). Les Poissons de Mer des Pêches Françaises.
Paris: Delachaux et Niestlé.
R Core Team. (2020). R: A language and Environment for Statistical Computing.
Vienna: R Foundation for Statistical Computing.
Regulation 1380/2013 (2013). Regulation (EU) No 1380/2013 of the European
Parliament and of the Council of 11 December 2013 on the Common Fisheries
Policy, Amending Council Regulations (EC) No 1954/2003 and (EC) No
1224/2009 and Repealing Council Regulations (EC) No 2371/2002 and (EC) No
639/2004 and Council Decision 2004/585/EC, 2013. , OJ L. Bruxelles: Council of
the European Union.
Rogan, E., and Mackey, M. (2007). Megafauna bycatch in drift nets for albacore
tuna (Thunnus alalunga) in the NE Atlantic. Fish. Res. 86, 6–14. doi: 10.1016/j.
fishres.2007.02.013
Scheipl, F. (2011). spikeSlabGAM: bayesian variable selection, model choice and
regularization for generalized additive mixed models in R. ArXiv [Preprint]
ArXiv: 11055253 Stat
Spitz, J., Chouvelon, T., Cardinaud, M., Kostecki, C., and Lorance, P.
(2013). Prey preferences of adult sea bass Dicentrarchus labrax in the
northeastern Atlantic: implications for bycatch of common dolphin Delphinus
delphis.ICES J. Mar. Sci. J. Cons. 70, 452–461. doi: 10.1093/icesjms/
fss200
Van Canneyt, O., Dabin, W., Dars, C., Dorémus, G., Gonzalez, L., Ridoux, V.,
et al. (2015). Guide des Échouages de Mammifères Marins., Cahier Technique
de l’Observatoire PELAGIS sur le suivi de la Mégafaune Marine. La Rochelle:
Université de La Rochelle, CNRS.
Zappes, C. A., de Sa Alves, L. C. P., da Silva, C. V., de Azevedo, A., Di Beneditto,
A. P. M., and Andriolo, A. (2013). Accidents between artisanal fisheries and
cetaceans on the Brazilian coast and Central Amazon: proposals for integrated
management. Ocean Coast. Manag. 85(Pt A), 46–57. doi: 10.1016/j.ocecoaman.
2013.09.004
Conflict of Interest: HP, MA, CD, and FD were employed by company ADERA.
The remaining authors declare that the research was conducted in the absence of
any commercial or financial relationships that could be construed as a potential
conflict of interest.
The reviewer GP declared a past co-authorship with one of the author VR to the
handling editor.
Copyright © 2021 Peltier, Authier, Caurant, Dabin, Daniel, Dars, Demaret, Meheust,
Van Canneyt, Spitz and Ridoux. This is an open-access article distributed under the
terms of the Creative Commons Attribution License (CC BY). The use, distribution
or reproduction in other forums is permitted, provided the original author(s) and
the copyright owner(s) are credited and that the original publication in this journal
is cited, in accordance with accepted academic practice. No use, distribution or
reproduction is permitted which does not comply with these terms.
Frontiers in Marine Science | www.frontiersin.org 17 April 2021 | Volume 8 | Article 617342
... Stranding data further revealed possible association between bycatch events and common dolphin preys. The reverse drift modelling of carcasses allowed the identification of some potentially high-risk fisheries and their caught fish species (Peltier et al. 2020(Peltier et al. , 2021. The analysis of stomach content of by caught stranded animals suggested that most dolphins were feeding when death occurred. ...
... duke. edu), and high mortality areas were previously identified on the continental shelf (Peltier et al. 2021). Moreover, most of highest MI values were located offshore of the coast from the south of the Finistère region to the south French border (not shown, see http://pelabox.univ-lr.fr:3838/pelagis/DdSeaByc/; ...
... In other words, we will assess the potential of regularized multilevel regression with post-stratification to estimate accurately bycatch numbers with samples preferentially collected either during lowor high-bycatch risk periods. Our investigation is largely framed from our knowledge on small cetacean bycatch in European waters, such as short-beaked common dolphin (Delphinus delphis, lower observer coverage when bycatch risk is higher) in the Bay of Biscay (Peltier et al., 2021) or harbor porpoises (Phocoena phocoena, higher observer coverage when bycatch risk is higher) in the Celtic Seas (Tregenza et al., 1997). In the remainder, we first introduce methods and notations to detail the proposed model to perform multilevel regression with post-stratification with bycatch data, using dolphins as an example. ...
Thesis
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Elusive species are notoriously difficult to monitor individually and therefore it is difficult to estimate their anthropogenic mortality and to implement management policies. As an elusive species, the common dolphin, Delphinus delphis is a good example of these conservation challenges. The North-East Atlantic population is affected by bycatch that threatens its viability. However, demographic information on this population is very limited and our understanding of the spatio-temporal structure and dynamics of bycatch is insufficient to set appropriate management objectives. This project aims to determine the current status of this common dolphin population with regard to conservation objectives in European waters with a focus on the Bay of Biscay. First a flexible vital rates estimation approach has been developed in order to highlight variations in vital rates over time and the effects of covariates while taking into account individual heterogeneity. Second, using such a methodological approach through a cross-sectional monitoring, allowed us to highlight both the temporal variations of the population vital rates and the impact of bycatch on the common dolphin population demography. The population is not viable and the population growth rate seems to have deteriorated since the mid 2000's. Third, using biased data from on-board observers, the number of incidental catches on a weekly basis was quantified for ten ICES sub-area over sixteen years. Fourth, the resulting vital rates combined with bycatch estimates finally allowed the production of sustainable bycatch thresholds through a Management Strategy Evaluation approach in line with the European conservation objective.
... Stranding data further revealed possible association between bycatch events and common dolphin preys. The reverse drift modelling of carcasses allowed the identification of some potentially high-risk fisheries and their caught fish species (Peltier et al. 2020(Peltier et al. , 2021. The analysis of stomach content of by caught stranded animals suggested that most dolphins were feeding when death occurred. ...
... duke. edu), and high mortality areas were previously identified on the continental shelf (Peltier et al. 2021). Moreover, most of highest MI values were located offshore of the coast from the south of the Finistère region to the south French border (not shown, see http://pelabox.univ-lr.fr:3838/pelagis/DdSeaByc/; ...
Article
By transferring energy and nutrients from plankton to top predators, forage species play a major ecological role in marine food webs. While large differences in energy densities have been demonstrated among these species, other determinants of their quality remain poorly explored. We analysed 78 forage species from the Bay of Biscay, NE Atlantic, for their concentrations in various chemical elements with a documented biological role (i.e. micro‐nutrients). Species encompassed jellyfish, crustaceans, cephalopods, cartilaginous and bony fish. Elements included two essential macro‐minerals (nitrogen and phosphorous) and nine trace elements (arsenic (As), cobalt, copper (Cu), chromium, iron, manganese, nickel, selenium (Se), zinc). We showed a broad range of elemental composition values across forage species, partly driven by taxonomy (fish versus crustaceans/cephalopods) or their habitat (coastal versus oceanic, pelagic versus benthic). Some elements (As, Cu or Se) were more variable than others, especially in fish for Cu and Se. The 78 forage species were then classified by hierarchical clustering analysis (HCA) into different nutritional groups, based on their composition in eleven elements. Mean concentrations of each element in the diet of eight cetacean species was finally calculated, as well as the importance of each nutritional group (as defined by HCA including all elements) for each predator species. We revealed contrasting diets in terms of exposure to elements. Neritic common dolphins and harbour porpoises but also minke whales were thus mainly supplied by the Se‐enriched nutritional group composed of small (pelagic) schooling fish (including sandeels, (horse) mackerel and also some Clupeids), while the diets of pilot whales or Risso's dolphins that mostly consume benthic cephalopods were clearly Cu‐enriched. This study raises the issue of essential element composition as another determinant of food quality, and the risk associated with changes in forage species' availability for the proper functioning of marine food webs and ecosystems.
... In the Northeast Atlantic, common dolphins in the BoB (mid-latitude European shelf ) in winter also face a particularly high level of fisheries-induced mortality [30,31]. The by-catches in fishing gears are the most critical threat to the species in the area, with common dolphins experiencing high mortality in late winter (February-March) through several peaks of one or two weeks each winter [32]. This inter-annual fluctuation suggests by-catch risk varies over space and time, and potentially with environmental conditions [33]. ...
Article
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Cetaceans adjust their distribution and abundance to encountered conditions across years and seasons, but we poorly understand such small-scale changes for many species, especially in winter. Crucial challenges confront some populations during this season, such as the high levels of fisheries-induced mortality faced by the common dolphin (Delphinus delphis) in the Northeast Atlantic shelves. For such species, understanding the winter fine-scale dynamics is crucial. We aimed to identify the dolphin distribution drivers during the winters of 2020 and 2021, with a focus on determining the lag between changes in oceanographic conditions and dolphin distribution. The changes were related to temporal delays specific to the nature and cascading effects that oceanographic processes had on the trophic chain. By determining the most important conditions and lags to dolphin distributions, we shed light on the poorly understood intrusions of dolphins within coastal waters during winter: they displayed a strong preference for the coastal-shelf waters front and extensively followed its spatial variations, with their overall densities increasing over the period and peaking in March-April. The results presented here provide invaluable information on the winter distribution dynamics and should inform management decisions to help reduce the unsustainable mortalities of this species in the by-catch of fisheries.
... Ecological risk assessments, such as ERAEF, are increasingly popular methods used for assessing the potential vulnerability of species impacted directly, or indirectly, by fisheries. In the BoB, several studies aimed to perform ecological risk assessments, albeit focused in the short-beaked common dolphin (Delphinus delphis; Mannocci et al., 2012;Peltier et al., 2016Peltier et al., , 2021, whilst to the best of our knowledge, this paper represents the first attempt to perform an ecological risk assessment for a seabird species in the area aiming to provide new insights to implement conservation strategies and to inform EBFM and mitigation measures. ...
Article
Fishery bycatch is a serious threat to several protected, endangered, and threatened species (PETs), requiring urgent action to develop and implement conservation measures. This study performs an Ecological Risk Assessment for the Effects of Fishing (ERAEF) using a spatially and temporally Productivity–Susceptibility Analysis (PSA) to calculate the potential risk to great shearwaters (Ardenna gravis) from direct interaction with the metiers of the artisanal tuna fishing fleet at the Bay of Biscay (baitboats and trollers). The PSA incorporates productivity attributes based on the Fecundity Factor Index; and susceptibility attributes calculated from the species spatio-temporal abundance patterns obtained developing density surface models and distribution and intensity of fishing activity based on pooled Vessel Monitoring System and logbook data. The PSA shows an overall moderate risk to great shearwaters by the artisanal tuna fishery also revealing that baitboats are less risky than trollers (risk score of 3.12 ± 0.09 and 2.70 ± 0.05, respectively). Spatially, the likelihood of presence of high potential risk areas was associated with prey availability for both the PET and the commercial fish species. The systematic, repeatable, and standardized ERAEF followed in this study can be used to advice for ecosystem-based fisheries management to improve management measures for reducing bycatch of PETs around the world.
... Studies using megafauna strandings to assess the impacts of marine pollution are often inconclusive when suggesting how this pollution affects the TSP of strandings (Fort et al., 2015;Dron et al., 2022;Pennino et al., 2022), except when linked to specific events such as oil spills (Venn-Watson et al., 2015). On the other hand, fisheries bycatch cause direct mortality, which can translate into the TSP of strandings; as such, stranding numbers are often related to fluctuations of fishing effort in space and time (Leeney et al., 2008;Fruet et al., 2012;Monteiro et al., 2016;Simeone et al., 2021), and there is mounting evidence linking fisheries-related mortality with strandings (Prado et al., 2013;Peltier et al., 2021). As such, even when fisheries data and precise causes of death investigations are not available, TSP of strandings deviating from normal patterns can suggest anthropogenic drivers of mortality, helping to find seasons/areas worth investigating, particularly for known fisheries-impacted species. ...
Article
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We describe the temporal and spatial patterns of three tetrapod groups (sea turtles, seabirds, and cetaceans) stranded in southeast Brazil, based on daily beach surveys of over >800 km of coastline between 2015 and 2020. Patterns were analysed by stranding rates (individuals/1000 km of coastline) of groups and species; for the 14 most numerous species, we also fitted generalized additive models for location, scale, and shape (GAMLSS) using temporal and spatial explanatory variables. We recorded 53850 animals (22738 sea turtles, 28155 birds, and 2957 cetaceans) of 78 species. Higher stranding numbers were observed during winter/spring for all groups, and could be an effect of a higher occurrence/abundance at the region, driven by productive waters, jointly with higher stranding probabilities due to stronger drifting forces. Most modelled species showed temporal and spatial stranding patterns most likely related to their general occurrence/abundance cycles in southeast Brazil, but for Caretta caretta, Chelonia mydas, Pontoporia blainvillei, and Sotalia guianensis local mortality factors may be influencing stranding numbers. By using intensive, wide ranging beach surveys and including survey effort in the analysis, we provide a comprehensive baseline for stranding numbers in the region, and open a pathway for future hypothesis-testing studies to investigate its drivers.
... In the next decade, there was an estimated 98% reduction in sea lion bycatch mortality from gillnet interactions and an apparent stabilization of the decline in sea lion pup abundances at some impacted breeding sites. There was an almost complete transition in the INTRODUCTION Incidental catch or bycatch in fisheries presents a major threat to many marine species and is one of the most significant sources of anthropogenic mortality of marine mammals (Read et al., 2006;Sims et al., 2008;Lewison et al., 2009;Kovacs et al., 2012;Komoroske and Lewison, 2015;Peltier et al., 2016Peltier et al., , 2021Gray and Kennelly, 2018;Luck et al., 2020). Although marine mammals are known to interact with most fishing gear types, interactions with gillnets are particularly pervasive and a significant source of marine mammal mortality (Read et al., 2006;Reeves et al., 2013). ...
Article
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Globally, the bycatch of marine mammals in fisheries represents the greatest source of human-caused mortality that threatens the sustainability of many populations and species. The Australian sea lion (Neophoca cinerea) is an endangered species, whose populations off South Australia (SA) have been subject to bycatch in a demersal gillnet fishery targeting sharks since the 1960s. A comprehensive assessment was undertaken of sea lion bycatch mortality that combined independent fishery observer data with species distribution models (underpinned by satellite tracking, abundance data and population modeling) to model the relationship between at-sea foraging effort and bycatch rate. Combined with the distribution of fishing effort, these models enabled the overall level of bycatch mortality to be estimated by age, sex and subpopulation, facilitating population viability analyses that indicated most subpopulations were declining, and subject to unsustainable levels of bycatch mortality. To reduce this mortality, the Australian Fisheries Management Authority implemented an Australian Sea Lion Management Strategy that included an independent observer program (ultimately 100% electronic monitoring of gillnet fishing off SA), permanent spatial gillnet closures around all sea lion breeding sites, bycatch mortality limits that triggered temporal (18 months) spatial closures when zone-specific bycatch trigger limits were reached, and incentives for gillnet fishers to switch to an alternate fishing method (longlines). The Strategy had immediate impacts on the fishery: it resulted in significant reductions in gillnet fishing effort and on the reported bycatch of sea lions. In the next decade, there was an estimated 98% reduction in sea lion bycatch mortality from gillnet interactions and an apparent stabilization of the decline in sea lion pup abundances at some impacted breeding sites. There was an almost complete transition in the Frontiers in Marine Science | www.frontiersin.org 1 February 2022 | Volume 9 | Article 799102 Goldsworthy et al. Sea Lion Gillnet Fishery Bycatch fishery from gillnets to longlines, and fishing catches returned to pre-management levels. The successful implementation of management measures to mitigate sea lion bycatch mortality in the gillnet fishery off SA was rapid, science informed, adaptive, comprehensive, and backed by strong compliance and monitoring of the fishery. It provides an important case study which demonstrates how management measures can be effectively applied to mitigate bycatch mortality of marine mammals and other marine protected species.
... This pattern is largely congruent with the pattern seen in strandings of common dolphins in the Bay of Biscay (Gilbert et al., 2021). Both stranding and observer data, which are independent, identified 2017 and 2019 as years with the highest risk of bycatch (Gilbert et al., 2021;Peltier et al., 2021). A limitation of stranding data is how the location of bycatch events must be inferred with reverse drift modelling (Peltier and Ridoux, 2015). ...
Article
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Marine megafauna plays an important functional role in marine ecosystems as top predators but are threatened by a wide range of anthropogenic activities. Bycatch, the incidental capture of non-targeted species in commercial and recreational fisheries, is of particular concern for small cetacean species, such as dolphins and porpoises. In the North-East Atlantic, common dolphin ( Delphinus delphis , Linné 1758) bycatch has been increasing and associated with large numbers of animals stranding during winter on the French Atlantic seashore since at least 2017. However, uncertainties around the true magnitude of common dolphin bycatch and the fisheries involved have led to delays in the implementation of mitigation measures. Current data collection on dolphin bycatch in France is with non-dedicated observers deployed on vessels for the purpose of national fisheries sampling programmes. These data cannot be assumed representative of the whole fisheries' bycatch events. This feature makes it difficult to use classic ratio estimators since they require a truly randomised sample of the fishery by dedicated observers. We applied a newly developed approach, regularised multilevel regression with post-stratification, to estimate total bycatch from unrepresentative samples and total fishing effort. The latter is needed for post-stratification and the former is analysed in a Bayesian framework with multilevel regression to regularise and better predict bycatch risk. We estimated the number of bycaught dolphins for each week and 10 International Council for the Exploration of the Sea (ICES) divisions from 2004 to 2020 by estimating jointly bycatch risk, haul duration, and the number of hauls per days at sea (DaS). Bycatch risk in pair trawlers flying the French flag was the highest in winter 2017 and 2019 and was associated with the longest haul durations. ICES divisions 8.a and 8.b (shelf part of the Bay of Biscay) were estimated to have the highest common dolphin bycatch. Our results were consistent with independent estimates of common dolphin bycatch from strandings. Our method show cases how non-representative observer data can nevertheless be analysed to estimate fishing duration, bycatch risk and, ultimately, the number of bycaught dolphins. These weekly-estimates improve upon current knowledge of the nature of common dolphin bycatch and can be used to inform management and policy decisions at a finer spatio-temporal scale than has been possible to date. Our results suggest that limiting haul duration, especially in winter, could serve as an effective mitigation strategy.
... In the Bay of Biscay, sardine, anchovy (Engraulis encrasicolus), sprat (Sprattus sprattus) and horse mackerel (Trachurus trachurus) are important prey for common dolphin (Meynier et al., 2008) and targeted by fisheries (e.g. Peltier et al., 2021). No European sea bass was recorded in the stomach contents of common dolphin bycaught in the UK sea bass fishery (Northridge et al., 2003). ...
Technical Report
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Bycatch is a major conservation and welfare issue for cetaceans in European waters. Harbour porpoises and common dolphins are frequently reported to be bycaught in static nets (gillnets and entangling nets) and trawls. Despite European legislation to monitor and mitigate cetacean bycatch in fisheries where it has a negative impact on the conservation status of a species, bycatch still occurs at high rates in several fisheries in the ASCOBANS Agreement Area. The lack of compliance by some countries has resulted in legal challenges from the European Commission for implementation of the required measures. There are two main parts covered in this report. The first part reviews different mitigation measures (acoustic deterrent devices, porpoise alerting devices, reflective nets, acrylic echo enhancers, lights and various technical modifications and changes to fishing practices) that have been trialed in the ASCOBANS region. The cost of implementation and pros and cons of each method are discussed in detail in the relevant sections. The second part of the report reviews alternative fishing methods to replace static nets (i.e. gillnets and entangling nets). The cost of implementation, and pros and cons of the different gears, are discussed in depth in the relevant sections.
Article
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By-catch is the most direct threat to marine mammals globally. Acoustic repellent devices (pingers) have been developed to reduce dolphin by-catch. However, mixed results regarding their efficiency have been reported. Here, we present a new bio-inspired acoustic beacon, emitting returning echoes from the echolocation clicks of a common dolphin ‘Delphinus delphis’ from a fishing net, to inform dolphins of its presence. Using surface visual observations and the automatic detection of echolocation clicks, buzzes, burst-pulses and whistles, we assessed wild dolphins’ behavioural responses during sequential experiments (i.e., before, during and after the beacon’s emission), with or without setting a net. When the device was activated, the mean number of echolocation clicks and whistling time of dolphins significantly increased by a factor of 2.46 and 3.38, respectively (p < 0.01). Visual surface observations showed attentive behaviours of dolphins, which kept a distance of several metres away from the emission source before calmly leaving. No differences were observed among sequences for buzzes/burst-pulses. Our results highlight that this prototype led common dolphins to echolocate more and communicate differently, and it would favour net detection. Complementary tests of the device during the fishing activities of professional fishermen should further contribute to assessment of its efficiency.
Article
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Several populations of odontocete cetaceans, including at least 19 species, have modified their behavior and adapted to foraging in association with trawlers. We review information on odontocete interactions with different types of trawlers across 13 Food and Agriculture Organization fishing areas around the world. We also review knowledge gaps, the effects on odontocete ecology, distribution, behavior and social organization, the main mitigation options, and some management avenues that could help reduce incidental mortality. Trawlers involved in the interactions varied greatly in gear and target species, implying odontocetes have developed behavioral specializations to forage under a variety of conditions. Specialized behavior included venturing into a moving trawl net to feed on the organisms trapped in the net, feeding on fish stirred up by the net, extracting fish from the outer mesh, feeding on catch lost during hauling, and scavenging on discarded catch. Foraging behind trawlers facilitates access to prey, and in some instances may compensate for scarcity of natural prey within areas exposed to intensive fishing or environmental degradation. This opportunistic foraging strategy, however, exposes the animals to potential harm and mortality in trawl gear. The combined effect of facilitated foraging and bycatch on the status and trends of odontocete populations is unknown. The economic damage caused by odontocetes, e.g. in terms of loss of marketable catch and gear damage, remains largely conjectural. Attempts to reduce depredation and/or bycatch in trawl gear have included acoustic deterrents and exclusion devices installed in nets, although neither technique has proven to be consistently effective. --- https://doi.org/10.1007/s11160-022-09712-z
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Variably buoyant, dead Cetacea may float, or sink and later bloat to refloat if ambient temperature and pressure allow sufficient decomposition gas formation and expansion. Mortality can result from acute or chronic disease, fishery entanglement, vessel collision, noxious noises, or toxicant spills. Investigators often face the daunting task of elucidating a complex series of events, in reverse order, from when and where an animal is found, and to diagnose the cause of death. Various scenarios are possible: an animal could die at sea remaining there or floating ashore, or strand on a beach alive, where it dies and, if cast high enough, remain beached to be scavenged or decompose. An animal that rests low on a beach may refloat again, through increased buoyancy from decomposition gas and favorable tides, currents, and wind. Here we review the factors responsible for the different outcomes, and how to recognize the provenance of a cetacean mortality found beached, or floating at sea. In conclusion, only some carcasses strand, or remain floating. Negatively buoyant animals that die at depth, or on the surface, and sink, may never surface, even after decomposition gas accumulation, as in cold, deep waters gas may fail to adequately reduce the density of a carcass, precluding it from returning to the surface.
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Identifying the role that environmental factors and biotic interactions play in species distribution can be essential to better understand and predict how ecosystems will respond to changing environmental conditions. This study aimed at disentangling the assemblage of the pelagic predator-prey community by identifying interspecific associations and their main drivers. For this purpose, we applied the joint species distribution modelling approach, JSDM, to the co-occurrence patterns of both prey and top predator communities obtained from JUVENA surveys during 2013-2016 in the Bay of Biscay. Results showed that the co-occurrence patterns of top predators and prey were driven by a combination of environmental and biotic factors, which highlighted the importance of considering both components to fully understand the community structure. In addition, results also revealed that many biotic interactions, such as schooling in prey (e.g. anchovy-sardine), local enhancement/facilitation in predators (e.g. Cory's shearwater-fin whale), and predation between predator-prey species (e.g. northern gannet-horse mackerel), were led by positive associations, although predator avoidance behaviour was also suggested between negatively associated species (e.g. striped dolphin-blue whiting). The identification of interspecific associations can therefore provide insights on the functioning of predators-prey network and help advance towards an ecosystem-based management.
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The short‐beaked common dolphin is one of the most numerous cetacean species in the North‐East Atlantic and plays a key functional role within the ecosystem as a top predator. However, in 2013, its conservation status for the European Marine Atlantic, under Article 17 of the Habitats Directive, was assessed as ‘Unfavourable‐Inadequate’. Of key concern for this species is fishery bycatch, with pollution also being an issue. There are, however, major knowledge gaps concerning the extent of the effects of such pressures on the species. Implementation of national observer bycatch programmes and bycatch mitigation measures under EC Regulation 812/2004 has been important. The responsibility for this is currently being transferred to the EU fisheries Data Collection Framework and Technical Measures Framework, the potential advantages and disadvantages of which are discussed. Collection of data and samples through national stranding schemes in some countries has enabled assessments of life‐history parameters, dietary requirements, and the effects of stressors such as pollutants. Nevertheless, in order to improve the conservation status of the North‐East Atlantic population, a number of key actions are still required. These include the implementation of a species action plan, finalization of a management framework procedure for bycatch, and coordination between member states of monitoring programmes. It is important that there is monitoring of the state of the common dolphin population in the North‐East Atlantic management unit through regular surveys spanning the range of the management unit, as well as continued assessment of the independent and interactive effects of multiple stressors. Above all, conservation status would be improved through application and enforcement of existing legislation in European waters. This paper provides a summary of the current state of our knowledge of common dolphins in the North‐East Atlantic along with recommendations for conservation management that may also be relevant to the species in the Mediterranean Sea.
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Small-scale artisanal fisheries can have a significant negative impact in cetacean populations. Cetacean bycatch has been documented in the pole-and-line tuna fishery in the Azores with common dolphins being the species more frequently taken. Based on data collected by observers on ∼50% of vessels operating from 1998 to 2012, we investigate the influence of various environmental and fisheries-related factors in common dolphin bycatch and calculate fleet-wide estimates of total bycatch using design-based and model-based methods. Over the 15-year study dolphin bycatch occurred in less than 0.4% of the observed fishing events. Generalized additive modelling results suggest a significant relationship between common dolphin bycatch and duration of fishing events, sea surface temperature and location. Total bycatch calculated from the traditional stratified ratio estimation approach was 196 (95% CI: 186–205), while the negative binomial GAM estimated 262 (95% CI: 249–274) dolphins. Bycatch estimates of common dolphin were similar using statistical approaches suggesting that either of these methods may be used in future bycatch assessments for this fishery. Our work shows that rates of common dolphin bycatch in the pole-and-line tuna fishery in the Azores are low, despite considerable variations between years. Dolphins caught were released alive although the fate of these individuals is unknown. Continued monitoring will provide a better understanding of dolphin bycatch and more accurate estimates essential in the development of potential mitigation measures.
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More than half the fish in the sea As the human population has grown in recent decades, our dependence on ocean-supplied protein has rapidly increased. Kroodsma et al. took advantage of the automatic identification system installed on all industrial fishing vessels to map and quantify fishing efforts across the world (see the Perspective by Poloczanska). More than half of the world's oceans are subject to industrial-scale harvest, spanning an area four times that covered by terrestrial agriculture. Furthermore, fishing efforts seem not to depend on economic or environmental drivers, but rather social and political schedules. Thus, more active measures will likely be needed to ensure sustainable use of ocean resources. Science , this issue p. 904 ; see also p. 864
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The challenge of identifying cause of death in discarded bycaught marine mammals stems from a combination of the non-specific nature of the lesions of drowning, the complex physiologic adaptations unique to breath-holding marine mammals, lack of case histories, and the diverse nature of fishing gear. While no pathognomonic lesions are recognized, signs of acute external entanglement, bulging or reddened eyes, recently ingested gastric contents, pulmonary changes, and decompression-associated gas bubbles have been identified in the condition of peracute underwater entrapment (PUE) syndrome in previous studies of marine mammals. We reviewed the gross necropsy and histopathology reports of 36 cetaceans and pinnipeds including 20 directly observed bycaught and 16 live stranded animals that were euthanized between 2005 and 2011 for lesions consistent with PUE. We identified 5 criteria which present at significantly higher rates in bycaught marine mammals: external signs of acute entanglement, red or bulging eyes, recently ingested gastric contents, multi-organ congestion, and disseminated gas bubbles detected grossly during the necropsy and histologically. In contrast, froth in the trachea or primary bronchi, and lung changes (i.e. wet, heavy, froth, edema, congestion, and hemorrhage) were poor indicators of PUE. This is the first study that provides insight into the different published parameters for PUE in bycatch. For regions frequently confronted by stranded marine mammals with non-specific lesions, this could potentially aid in the investigation and quantification of marine fisheries interactions.
Article
For decades, cetacean bycatch has been a major conservation and welfare concern in the European Union with high numbers of harbour porpoises, dolphins and whales dying each year. Despite binding legal requirements to monitor and reduce bycatch, cetacean bycatch monitoring has been insufficient in most fisheries and areas to generate reliable estimates of bycatch rate. Measures to reduce bycatch have been limited and not always directed at the most problematic fisheries. EU cetacean bycatch legislation (Council Regulation (EC) No. 812/ 2004) was repealed and replaced by a new Regulation, Regulation on the conservation of fishery resources and the protection of marine ecosystems through technical measures (2019/1241). Whilst some improvements have been made in the new Regulation, tscientific advice of the ICES Bycatch Working Group (ICES WGBYC), and other expert regional bodies, such as ASCOBANS and ACCOBAMS, were not incorporated explicitly and some measures in the adopted Technical Measures Regulation weaken both the provisions of the existing cetacean bycatch legislation and the Commission's original proposal. The bycatch measures adopted for cetaceans are not sufficient to mitigate bycatch effectively in European waters. Management solutions to reduce bycatch are identified and a number of general recommendations towards development of national and regional management plans, implementation and enforcement to that end are made.
Article
Between the 1st of February and the March 31, 2017, 793 stranded cetaceans were found along the French Atlantic coasts. Common dolphins made up 84% of these strandings, and most of these presented evidence of death in fishing gear. The aim of this work is to test an approach that could help identify the fisheries potentially involved in a given stranding event. To do this we examined how the distributions of likely areas of mortality of bycaught dolphins, inferred from carcass drift modelling, coincide with fishing effort statistics of various fleets, generated from the Vessel Monitoring System, in the area over the same dates. Using reverse drift modelling, two main mortality areas were identified. A total of 3690 common dolphins (IC95% [2230; 6900]) were estimated to have died in fishing gear within the Bay of Biscay during this unusual stranding event. There was a positive correlation between the origin of stranded bycaught dolphins and the fishing effort distribution of French midwater pair trawlers, Spanish otter bottom trawlers and French Danish seiners. This co-occurrence highlights a risk and identifies fisheries that require further investigation (through observers or e-monitoring). These fisheries differed in their fishing gear, but two characteristics appear to be shared: they targeted predatory fishes (sea bass and hake) in winter and used high vertical opening gear. Keywords: Common dolphins, Strandings, Bycatch, Fishing effort, Reverse drift, Vessel monitoring system
Article
From the Habitat Directive to the recent Marine Strategy Framework Directive, the conservation status of cetaceans in European water has been of concern for over two decades. In this study, a seasonal comparison of the abundance and distribution of cetaceans was carried out in two contrasted regions of the Eastern North Atlantic, the Bay of Biscay and the English Channel. Estimates were obtained in the two sub-regions (375,000 km²) from large aerial surveys conducted in the winter (November 2011 to February 2012) and in the summer (May to August 2012). The most abundant species encountered in the Channel, the harbour porpoise, displayed strong seasonal variations in its distribution but a stable abundance (18,000 individuals, CV=30%). In the Bay of Biscay, abundance and distribution patterns of common / striped dolphins varied from 285,000 individuals (95% CI: 174,000–481,000) in the winter, preferentially distributed close to the shelf break, to 494,000 individuals (95% CI: 342,000 − 719,000) distributed beyond the shelf break in summer. Baleen whales also exhibited an increase of their density in summer. Sseasonal abundances of bottlenose dolphins were quite stable, with a large number of ‘pelagic’ encounters offshore in winter. No significant seasonal difference was estimated for pilot whales and sperm whale. These surveys provided baseline estimates to inform policies to be developed, or for existing conservation instruments such as the Habitats Directive. In addition, our results supported the hypothesis of a shift in the summer distributions of some species such as harbour porpoise and minke whale in European waters.
Article
Habitat modelling is increasingly relevant in biodiversity and conservation studies. A typical application is to predict potential zones of specific conservation interest. With many environmental covariates, a large number of models can be investigated but multi-model inference may become impractical. Shrinkage regression overcomes this issue by dealing with the identification and accurate estimation of effect size for prediction. In a Bayesian framework we investigated the use of a shrinkage prior, the Horseshoe, for variable selection in spatial generalized linear models (GLM). As study cases, we considered 5 datasets on small pelagic fish abundance in the Gulf of Lion (Mediterranean Sea, France) and 9 environmental inputs. We compared the predictive performances of a simple kriging model, a full spatial GLM model with independent normal priors for regression coefficients, a full spatial GLM model with a Horseshoe prior for regression coefficients and 2 zero-inflated models (spatial and non-spatial) with a Horseshoe prior. Predictive performances were evaluated by cross-validation on a hold-out subset of the data: models with a Horseshoe prior performed best, and the full model with independent normal priors worst. With an increasing number of inputs, extrapolation quickly became pervasive as we tried to predict from novel combinations of covariate values. By shrinking regression coefficients with a Horseshoe prior, only one model needed to be fitted to the data in order to obtain reasonable and accurate predictions, including extrapolations.