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CONTRIBUTED PAPER
Fishing gear entanglement threatens recovery of critically
endangered North Atlantic right whales
Amy R. Knowlton
1
| James S. Clark
2
| Philip K. Hamilton
1
|
Scott D. Kraus
1
| Heather M. Pettis
1
| Rosalind M. Rolland
1
|
Robert S. Schick
2,3
1
Anderson Cabot Center for Ocean Life,
New England Aquarium, Central Wharf,
Boston, Massachusetts, USA
2
Nicholas School of the Environment,
Duke University, Durham, North
Carolina, USA
3
Centre for Research into Ecological and
Environmental Modelling, School of
Mathematics and Statistics, University of
St Andrews, St Andrews, UK
Correspondence
Amy R. Knowlton, Anderson Cabot
Center for Ocean Life, New England
Aquarium, Central Wharf, Boston, MA,
USA.
Email: aknowlton@neaq.org
Robert S. Schick, Marine Geospatial
Ecology Lab, Nicholas School of the
Environment, Duke University, Durham,
NC, USA.
Email: rss10@duke.edu
Funding information
Office of Naval Research, Grant/Award
Numbers: N000141126207,
N000141210286, N000141210389,
N000141712817; Strategic Environmental
Research and Development Program,
Grant/Award Number: RC20-C2-1097;
National Oceanic and Atmospheric
Administration
Abstract
North Atlantic right whales frequently become entangled in fishing gear, which
can negatively affect their reproductive output and probability of survival. We
estimated individual whale health from a hierarchical Bayesian model fit to pho-
tographic indices of health. We reviewed 696 whales sighted from 1980 to 2011
and assigned 1196 entanglement events to 573 individuals in six categories of
increasing injury severity and estimated monthly median health scores (0–100
scale) for the duration of their life within the study period. We then quantified
the relationship between entanglement injury events and their severity with sur-
vival, reproduction, and population health. Severe entanglements resulted in
worse health for all whales—males and females with severe injuries were eight
times more likely to die than males with minor injuries. Females with severe
injuries that survived had the lowest birth rates. Though the relationship
between entanglement and fecundity was complex, we found that as the health
of reproductively active females declined, their calving intervals increased.
Unimpacted whale health scores declined significantly over three decades,
1980s, 1990s, and 2000s, suggesting food limitations may be contributing to
population-wide health declines. Decadal health scores of entangled whales
showed a more notable reduction in health suggesting a clear and perhaps
synergistic effect.
KEYWORDS
entanglement, fixed fishing gear, health, injury severity, reproduction, survival
1|INTRODUCTION
The North Atlantic right whale (Eubalaena glacialis;
hereafter NARW) has faced a millennium of hunting
pressure (Reeves et al., 2007); all that remains of this
Amy R. Knowlton and Robert S. Schick contributed equally to
this work.
Received: 1 October 2021 Revised: 4 May 2022 Accepted: 10 May 2022
DOI: 10.1111/csp2.12736
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided
the original work is properly cited.
© 2022 The Authors. Conservation Science and Practice published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.
Conservation Science and Practice. 2022;4:e12736. wileyonlinelibrary.com/journal/csp2 1of14
https://doi.org/10.1111/csp2.12736
long-lived, critically endangered species is a small and
vulnerable population that recently declined from close to
500 individuals in 2010 to fewer than 350 in 2020 (Pace III
et al., 2017;Pettisetal.,2022). Although protected from
hunting by international regulations which came into force
in the 1930s (Reeves et al., 2007), the NARW now faces
multiple stressors in the highly industrialized waters of the
western North Atlantic where this remnant population is
primarily distributed. These stressors include collisions by
vessels and entanglements in fishing gear (Kraus &
Rolland, 2007). As compared to southern hemisphere right
whales (Eubalaena australis), which inhabit less industrial-
ized waters, NARW has shown limited recovery as a result
of these human impacts (Corkeron et al., 2018). This spe-
ciesisalsofacingthemorerecenteffectsofclimatechange
including shifting and less predictable food resources
(Record et al., 2019).
Entanglements of NARW typically occur in fixed fish-
ing gear, including lobster and crab pots, and gillnets after
the whale collides with ropes in the water column
(Johnson et al., 2005). The resulting injuries can range
from superficial wounds with no attached gear to cases in
which the line becomes tightly wrapped multiple times
around the whale, resulting in deep wounds, impaired
feeding, and energetic costs caused by increased drag
(Cassoff et al., 2011; Knowlton et al., 2016; Knowlton &
Kraus, 2001; van der Hoop et al., 2017;Lysiaketal.,2018).
NARW are entangled frequently—a 30-year assessment of
entanglement scars (1980–2009) showed 82.9% of the pop-
ulation has been entangled at least once, and some indi-
viduals as many as seven times (Knowlton et al., 2012).
While most gear interactions result in only scars, the rate
of serious entanglements (those with attached gear or
severe injuries) has been increasing (Knowlton et al.,
2012) and entanglements are now the leading cause of
serious injury and mortality in this species (Henry
et al., 2019; Kraus et al., 2016; Pace III et al., 2021). There
is no sign of abatement in the frequency or severity of
entanglement despite decades of dedicated management
efforts in the United States (Henry et al., 2019;Kraus
et al., 2016; Pace III et al., 2014). Entanglements also occur
in Canadian waters (Wimmer & Maclean, 2021), where,
until recently (Davies & Brillant, 2019), there had been lit-
tle effort to change how the fisheries operate in relation to
reducing large whale entanglements.
Assessing the sub-lethal effect of fishing gear interac-
tions on individual and population health has been diffi-
cult due to the challenges of collecting blood or other
health data from large free-ranging whales although an
assessment of fecal glucocorticoids showed that chronic
entanglements lead to highly elevated stress levels in this
species (Rolland et al., 2017). Another recent study found
evidence of stunted growth in young right whales (<10
years old) that were observed with attached gear or
whose mothers had attached gear or severe entanglement
injuries while nursing (Stewart et al., 2021) indicating an
additional sub-lethal effect. This stunted growth effect
has also impacted the reproductive output of females
(Stewart et al. 2022). Here we apply another tool—
photographic evidence of health—to assess how entan-
glements are affecting right whale health. Pettis et al.
(2004) developed the Visual Health Assessment (VHA),
which is an approach for monitoring the health of individ-
ual whales over the course of their lifespan by ranking pho-
tographic observations of health for four categories: body
condition, skin condition, the presence of cyamids in the
blowholes, and the presence of rake marks around the
blowholes. Within each health category, ordinal classes
describe the severity of the health status (Pettis
et al., 2004). In addition, Pettis et al. (2017) assessed the
rate at which a whale's health, measured by assessing body
condition, can change, including those that are entangled.
Robbins et al. (2015) assessed survival in 50 right whales
carrying fishing gear, and found that declining health, as
evidenced by graying skin, higher cyamid levels, or signs of
emaciation, was predictive of reduced survival.
To expand the utility of the VHA scoring efforts, Schick
et al. (2013) developed a state-space model to estimate a
continuous latent health state in individual right whales
using the VHA data. In addition, information from
observed rates of change in body condition (Pettis
et al., 2017) was used to inform health progression (Schick
et al., 2016). The model is hierarchical in that inference,
with uncertainty, was made on the true monthly health
state of the animal; parameters that govern the relationship
between the observed photographic class and the underly-
ing state were estimated at the population level. The model
also included estimates of the geographic location of the
animal (resolved to a regional level), as well as estimates of
survival. Further details are provided in Schick et al.
(2013), Rolland et al. (2016), and Schick et al. (2016).
For this study, we apply the Schick et al. (2013)model
to link these individual health estimates and fishery entan-
glement interactions, quantify the effect of entanglement
on subsequent NARW health and life history and compare
these findings on a decadal scale to the overall population
health. Herein, we provide the first quantitative summary
of the effects of entanglement in fishing gear on NARWs—
one of the most well-studied and imperiled large whale
species in the world (Cooke, 2020).
2|METHODS
Individual NARWs can be identified by natural markings
on their heads (Kraus et al., 1986) and have been
2of14 KNOWLTON ET AL.
monitored throughout much of their range since 1980
(Kraus & Rolland, 2007). All photographed sightings of
right whales that were contributed to the North Atlantic
Right Whale Consortium's Identification Database have
been reviewed and—if a match was confirmed—linked
to a cataloged individual. All photographed sightings of
identified individual right whales were combined within
a sighting season and habitat area into a “batch”and a
detailed assessment of this suite of images was carried
out to look for human-related scarring (Knowlton
et al., 2012), and to conduct a VHA (Pettis et al., 2004) for
that batch. Using the technique developed by Schick
et al. (2013) and applied to the VHA data, we estimated
health on a monthly scale for each individual whale.
To explore entanglement effects on health, we combined
these health estimates with photographic data on entangle-
ments (either of still-attached gear or scars from a prior
entanglement where the entangling gear was shed) to assess
the effects of the varying levels of entanglement severity on
an individual (Knowlton et al., 2016). We then evaluated
how each entanglement event affected survival and repro-
duction in six ways: (1) documenting changes in estimated
health during and following the entanglement; (2) compar-
ing the health of entangled animals in specific demographic
classesasafunctionofentanglement severity; (3) examining
the effect of entanglement on survival according to injury
severity and by sex; (4) determining the number of months
that the health of reproductive females who experienced an
entanglement was below the calving threshold health value
identified by Rolland et al. (2016); (5) examining the effect
of entanglement on calving intervals; and (6) comparing the
health of unimpacted and entangled whales by decade. We
begin by describing the data followed by the methods used
in each analysis. Although entanglement data exists for the
period after 2013, there was a dramatic shift in NARW dis-
tribution in 2011 (Record et al., 2019) which confounded the
Schick et al. (2013) model outputs for subsequent data.
Therefore, we analyzed entanglement effects for the three
decades of time when NARW movement patterns were
more stable.
2.1 |Visual health assessment data
A total of 16,569 batches of 696 individual right whales
photographed from 1980 to 2013 were reviewed and
coded for VHA. All four parameters—body condition,
skin condition, rake marks, and cyamids around the
blowholes were used in the model to estimate latent
health. Briefly, in the state-space model, there is an
observation model for each of these ordinal VHA catego-
ries. This component of the state-space model links the
observed score to the estimates of latent health. We use a
multinomial logit formulation to evaluate the range of
true health over which we may observe each of the ordi-
nal values. In the observation model, we estimate both the
center of these breaks between classes, as well as the slope
of the curves describing the conditional probability of true
health given these parameters. Here, we use informed
priors to determine where in the latent heath range we
estimate breaks from one of the observed ordinal classes to
the next. See Schick et al. (2013) for further details.
We updated the monthly individual health curves
described in Rolland et al. (2016) using sighting and
health data for these 696 individual right whales.
2.2 |Entanglement data
Entanglement events were documented through a
detailed assessment of all photographs of each individual
whale following methods described by Knowlton et al.
(2012). Entanglements were documented through 2011
with VHA scoring carried out through 2013 to help
define the effects post-entanglement. A total of 1196
entanglement interactions involving 573 whales were cat-
egorized according to injury severity and the presence or
absence of entangling gear (Table 1). Injury severity was
coded as minor,moderate,orsevere based on the exten-
siveness and the depth of the injuries (Appendix S1; see
Knowlton et al., 2016, supplementary materials). Six
entanglement injury categories were used in these ana-
lyses: (1) minor no gear, (2) minor with gear, (3) moderate
no gear, (4) moderate with gear, (5) severe no gear, and
(6) severe with gear, and compared to unimpacted whales
(i.e., the period of time before a given individual experi-
enced its first entanglement). For each case, we deter-
mined the timeframe within which the entanglement
occurred and the duration of time when the gear was
attached. In some cases, we could not determine the
likely start of the entanglement event, for example, when
we lacked sufficient photographic evidence of the animal
in an uninjured state. When this happened in known age
whales, who are typically born in the winter months off
the southeastern U.S. coast, we bounded the started the
entanglement timeframe on December 1 prior to their
calving year, as this represents the beginning of the calv-
ing season (Kraus et al., 1986). Many whales endured
multiple entanglements but, in this study, each entangle-
ment event was evaluated independently.
2.3 |Analyses
The following analyses are focused first on describing
how entanglements affect modeled health as a function
KNOWLTON ET AL.3of14
of severity level and demographic groupings, and then
we apply these findings to explore how health affects sur-
vival and fecundity. Lastly, we assess how the health of
unimpacted whales (individuals prior to their first entan-
glement event) in relation to entangled whales has chan-
ged over three decades.
2.4 |Effect of entanglement category on
health and recovery
To characterize the relative health effect and recovery for
the six entanglement categories (Table 1), we assessed
individual health at three time points: (1) at the
uninjured sighting prior to the entanglement detection of
a whale (if this timeframe was greater than 12 months,
health was assessed at 12 months), (2) either the first date
observed with new scars or, for those whales with
attached gear, the last date seen carrying gear (this latter
date reflects health when the whale was closer to
the start of recovery if the gear was later shed), and (3)
12 months after either entanglement scar detection or the
last date observed with attached gear. The goal of this
assessment was to capture glimpses of health at similar
points of time around the injury detection date, especially
to investigate recovery. A 12-month period would ensure
an impacted whale had experienced an annual feeding
cycle which should support recovery. Slope graphs were
created to depict the median health scores at these three
different points of time for all events falling into each of
the six entanglement categories.
2.5 |Comparison of entanglement
effects on different demographic groups
To further analyze the health effects of entanglements on
different demographic groups, we created entanglement
health windows for each entanglement event to assess
health scores for a period of time bracketing the date
when each event was first detected and the likely dura-
tion (if the gear was attached) to capture the presumed
injury effect period (Appendix S2). Entanglement health
windows for events that resulted in scars only, that is, the
animal was not carrying gear, included health scores at
the month of detection and up to a maximum of 3 months
prior (if the whale was sighted within 3 months of detec-
tion, the entanglement health window was narrowed to
that timeframe). For events with attached gear, the
entanglement health window included health scores at
the time of detection and up to 3 months prior, through
the period that the whale carried the gear, and 3 months
past the last date observed with attached gear. For each
entanglement event, the health scores for all the months
in the given entanglement health window were averaged,
and the average for all events within each entanglement
category were displayed as boxplots.
For the analyses, we grouped animals by demo-
graphic categories, following Rolland et al. (2016). The
first group, “reproductive females”includes females from
their first successful pregnancy year (i.e., the year prior to
giving birth to a calf) onward. The second group, “non-
reproductive all”includes adult males, juveniles, and
adult females prior to their first pregnancy. Both groups
TABLE 1 Summary of the data by entanglement category and reproductive status with mean and maximum duration (in months) of the
entanglement health windows
Reproductive status
Entanglement
category
Total # of
events
Average length
(months)
Maximum length
(months)
Reproductive female Minor no gear 92 4 4
Minor gear 4 10 11
Moderate no gear 27 4 4
Moderate gear 7 17 56
Severe no gear 4 4 4
Severe gear 5 10 13
Nonreproductive all Minor no gear 828 4 4
Minor gear 21 11 61
Moderate no gear 140 4 4
Moderate gear 21 15 112
Severe no gear 13 3 4
Severe gear 34 15 77
Note: Reproductive female is a female from first pregnancy (as evidenced by successful calving) onward; nonreproductive all includes all males, females before
first pregnancy, and juveniles.
4of14 KNOWLTON ET AL.
were compared to unimpacted individuals (whales in the
given demographic grouping recorded in the period prior
to their first entanglement detection). We summarized
the health during entanglement health windows and com-
pared the six different entanglement categories and the
reference category of the monthly health estimates of
unimpacted individuals.
2.6 |Effect of entanglement on survival
The survival component of the model in Schick et al. (2013)
is based on the capture-recapture model from Dupuis (1995)
and Clark et al. (2005). Model output includes an estimated
monthly survival probability for each individual whale not
known to have died. Twenty-four whales killed by ship strike
and five entangled carcasses not seen entangled when alive
were removed from this analysis. To compare survival
between entanglement categories, we estimated individual
survival probability from the end of the last entanglement
experienced by each individual whale for a period of 6 years.
By the end of the 6-year assessment period, animals experi-
enced one of four fates: (1) they survived; (2) they were
removed (“right-censored”) from the study at a given point
(due to shortened life history data); (3) they experienced a
known death; or (4) they experienced an estimated death
event, that is, it was not estimated to survive to the next
month. Capture-recapture models obtain information on
survival probability from a random effect on individual
detection—the probability that an individual with a high
detection rate has died increases with the elapsed time since
last sighted. The temporal extent of the modeling stopped in
December 2013, at which point survival was right-censored.
Time to death or censoring was calculated as the difference
(in months) between the end of the last entanglement event
documented for an individual and the death or censoring
event. From the monthly estimates of survival probability,
we constructed survival curves grouped by sex and entangle-
ment injury categories, resulting in three curves (minor,
moderate,andsevere) for both males and females. We tested
the differences between the curves using a Cox proportional
hazards model, where the time to event (death) was a func-
tion of sex and entanglement severity. Analyses were per-
formed with the survival package in R (Therneau, 2020;
Therneau & Grambsch, 2000).
2.7 |Proportion of time below calving
threshold
For reproductive females, we assessed the percentage of
months within entanglement health windows that fell
below an estimated health score of 67, the score
below which no calvings have been detected (Rolland
et al., 2016). First, we took the average health scores for
each entanglement health window in the six entangle-
ment categories and compared those to the average
health score of unimpacted reproductive females. We
defined unimpacted reproductive females as those who
have had a successful pregnancy but had not yet experi-
enced an entanglement. To account for uncertainty in
the health estimates in this process, for each animal, we
drew 1000 health estimates from posterior predictive
distribution, whose parameters were the posterior
monthly health and standard deviation. For each of
these1000predictions,wecomparedthepredicted
health vector to tally the number of months below the
threshold.
2.8 |Effect of entanglement on
fecundity
To investigate whether entanglements of different injury
severity levels affect fecundity, several investigations were
conducted. This was a retrospective analysis, whereby we
first estimated health and survival following Schick et al.
(2013), and then intersected observed entanglement and
fecundity evidence with the posterior estimates. We used
two types of regression analyses to examine the effect of
latent health and entanglement status on (1) the probabil-
ity of becoming pregnant in any given available year, that
is, all years except the calving year and resting year after
each calving and not including the year before their first
calving event, as a function of scaled estimated health,
entanglement severity, year, number of months during the
interval where health was below 67 (this was scaled to
reflect the differing length of the windows across individ-
uals), and decade and (2) the length of time between preg-
nancy events as a function of the same covariates. To scale
health, we took the estimated latent health on the 0–100
scale, and simply used the scale function in R to center
and scale the estimated values. For the first analysis, we
conducted a binomial generalized linear model (GLM)
with pregnancy status as a 0/1 variable, and scaled latent
health, entanglement severity, scaled year, decade (as a
factor variable), and time since the last entanglement as
covariates. In the second analysis, we conducted a) a nor-
mal GLM on the time between pregnancies (in years). The
first of these analyses examine the annual probability of
getting pregnant but does not consider a time-dependent
response. The second analysis examines whether the
health and increasing entanglement severity covariates
affect the length of the interval between observed pregnan-
cies. That is, we do not censor animals that are alive but
not actively calving.
KNOWLTON ET AL.5of14
2.9 |Effect of entanglement on
population health
To further investigate the reported declines in health and
reproductive output over time documented by Meyer-
Gutbrod and Greene (2018)andRollandetal.(2016), the
health of individuals in each decade—1980s, 1990s, and
2000s—was broken out by category of unimpacted, and
minor,moderate,andsevere injuries with average health
scores summarized during the entanglement health windows
that originated during the given decade. We ran a GLM on
these data to examine the impact of entanglement status
(as a factor variable—unimpacted vs. entangled), decade,
and an interaction between the two.
3|RESULTS
3.1 |Health in relation to entanglement
severity
The health of right whales that experienced an entan-
glement event declined as injury severity increased (see
Figure 1for an individual case example). The most dra-
matic decline was observed among whales in the severe
with gear category (Figures 2and 3). Whales with
severe entanglement injuries—both with attached gear
and without—were in worse health than unimpacted
whales (Figure 2). Statistically, for the non-reproductive
all group, health declines with entanglement. The
amount of decline was lowest in minor no gear,minor
with gear,moderate no gear,andmoderate with gear
injuries with large declines in the severe no gear and
severe with gear categories (Appendix S3). The pvalues
for all but the minor with gear and moderate with gear
were significant. For reproductive females, all entangle-
ment categories were negative with generally higher
negative health estimates than the nonreproductive
group although no pronounced increase in the severe no
gear and severe with gear categories were seen in the
estimates. This may be due to the smaller sample sizes
in certain categories and the wider range of standard
errors; only the minor no gear and moderate no gear cat-
egories were significant.
3.2 |Recovery from entanglements
No health declines were detected in the minor no gear,minor
with gear,or moderate no gear categories (Figure 3). For mod-
erate with gear and severe no gear and severe with gear catego-
ries, health declined in all cases and was especially
precipitous for severe with gear cases. Also, the medians of
estimated health scores for each of these three categories
showed no recovery 12 months after the entanglement.
3.3 |Effects of entanglement on
reproductive females
Females who had never experienced an entanglement
or had experienced a minor no gear entanglement had
median health values below the calving threshold of
67 in only 9.5% and 12.7% of the months assessed,
respectively (Figure 4;AppendixS4),whereasthose
whales in the minor with gear category were below the
threshold in 18% of assessed months. Whales in the
severe with gear category were below the calving thresh-
old in 76.9% of the assessed months. There is consider-
able variability in the estimates of numbers of months
below 67, which may be influenced by how the entan-
glement coincides with their reproductive cycle and is
likely affected by the sample sizes in the different
categories.
FIGURE 1 Timeline for entanglement of #3911, a 2-year-old female. She was last seen in good health with no gear on February
23, 2010 (a), with attached gear and severe injuries on December 25, 2010 (b) and was found dead on February 1, 2011 (c) after a
disentanglement effort was unsuccessful (Moore et al., 2013). Photo credits: Florida Fish and Wildlife Conservation Commission, taken
under NOAA research permits #594-1759 and #932-1905/MA009526
6of14 KNOWLTON ET AL.
3.4 |Effects of entanglement on calf
production
Results from the binomial regression indicated that animals
in better health were more likely to successfully calve. The
coefficient relating severe entanglements and calving was neg-
ative but was not significant owing to a wide standard error
(Table 2). The role of time was also significant—as the years
of the study progressed, animals were less likely to calve in
any given year. On the decadal scale, where the 1980s were
the reference category, animals were significantly less likely
to calve in the 1990s and significantly more likely to calve in
the 2000s (Table 2). As with the binomial regression, the coef-
ficient describing the relationship of the interval between
calving and entanglement severity shows an increase in the
interval, but the result was not significant (Table 2).
3.5 |Survival costs of entanglement
Comparing the effects of entanglement on survival using
males with a minor entanglement as the baseline, or refer-
ence case, both males and females with severe entanglements
were eight times more likely to die (Appendix S5). Only 44%
of males and just 33% of females with severe injuries survived
longer than 36 months (Figure 5). Entangled females had
poorer survival than males in all three categories (Figure 5).
The difference in survivorship narrowed as entanglement
severity increased, suggesting males with minor and moder-
ate injuries fared much better than females, whereas severe
injuries are equally impactful for both sexes (Appendix S6).
Using a Cox proportional hazards model, where males with
minor entanglements are the reference class, results indicate
that the survival of females is significantly lower than males
(Table 3). There was no difference in survival between males
with minor and moderate injuries. Females with minor injury
have significantly lower survival than males with a minor
injury. Females with moderate injury have lower survival,
though this difference was not as pronounced. Differences in
survival are strongest in the severe category, regardless of sex.
3.6 |Population-wide health
A decadal comparison of health indicated a significant
decline in average median health scores during each
FIGURE 2 Boxplots of health scores categorized by entanglement impact categories and demographic groupings show that health during
entanglement health windows declines with increasingly severe injuries, with the impact significantly worse for reproductively active females
(Appendix S2). The boxes contain the middle 50% of the measurements collected in each category, the line through the box is the median, and
the whiskers show the 95% confidence interval. The numbers above the bars represent the number of cases assessed in each impact category
KNOWLTON ET AL.7of14
decade—1980s, 1990s, and 2000's for both unimpacted
whales and entangled whales with minor,moderate, and
severe injuries combined (Appendix S6). Each decade
showed slightly different patterns (Figure 6). In the
1980's, the median health scores were similar across all
the categories although the minor and moderate catego-
ries showed greater variability. Only one severe entangle-
ment was documented in that decade. In the 1990s,
minor entanglements showed a similar median and vari-
ability as the 1980's but moderate events had a notably
lower median score than the 1980's and the severe events,
which were more numerous, showed dramatically lower
health scores well below any of the other categories. For
the 2000s, the median scores for both minor and moder-
ate were below unimpacted and again the severe scores
were well below any of the other categories. The
unimpacted category declined significantly over each
decade (Appendix S6) but the median scores remained
high, ranging from a median of 81.6 in the 1980s to 75.7
in the 2000s, which for reproductive females is well above
the calving threshold of 67 (Rolland et al., 2016). The
median health estimate for all entanglements combined
was higher than unimpacted in the 1980s (82.0 vs. 81.6)
whereas in the 1990s and 2000s, the health estimate for
the entangled group was lower than unimpacted (76.1
vs. 78.6 in the 1990s and 74.9 vs. 75.7 in the 2000s indicat-
ing that entanglements are playing a role in population
health declines (Rolland et al., 2016) as the frequency of
moderate and severe injuries increase.
4|DISCUSSION
This study documents the negative effects of entangle-
ments on the health and survival of NARW. By coupling
longitudinal monitoring data on NARW with a unique
modeling approach utilizing visual health assessment
data (Schick et al., 2013), we investigated the effects of all
entanglements, including cases with only scars which
comprise the majority of documented entanglement
FIGURE 3 As entanglement injury severity increases, the health of entangled animals worsens with no sign of recovery. Here we depict
the health scores prior to, during, and after entanglement events. The six panels represent the median group category health score (black
line) and individual health scores (gray lines) for the six entanglement impact categories. On the x-axis, P refers to either the date prior
within 12 months detected without scars or gear or a maximum of 12 months prior to the detection date if the prior observation date is
greater than 12 months, S or G is the first sighting with scars (S) or last date with gear (G), and L is 12 months after the S or G date
8of14 KNOWLTON ET AL.
FIGURE 4 As entanglement severity increases reproductively active females have longer periods of time within their entanglement
health windows with health scores below the calving threshold of 67 (Rolland et al., 2016). The graph represents the median (dots) and inter
quartile range of percentages below the threshold. See Appendix S3 for the number of events and the number of months used to calculate
these percentages
TABLE 2 Estimated regression parameters for effects of health and entanglement on the probability of getting pregnant, and the
interval between successful pregnancies
Regression Covariate Coefficient Standard error p-value
Probability of becoming pregnant Intercept 1.137 0.348 .001
Health 0.124 0.064 .053
Minor 0.777 0.277 .005
Moderate 0.804 0.486 .098
Severe 13.859 366.317 .97
Year 0.716 0.194 .0002
Decade: 1990 0.564 0.276 .041
Decade: 2000 1.395 0.446 .002
Decade: 2010 0.833 0.611 .172
Length of time between pregnancies Intercept 3.603 0.236 <<.001
Health 0.07 0.527 .8935
Decade: 1990 1.304 0.327 <<.001
Decade: 2000 0.71 0.287 .014
Decade: 2010 0.634 0.372 .09
Severity 0.047 0.039 .223
Note: Decade: 1980 is the reference category.
KNOWLTON ET AL.9of14
events (Knowlton et al., 2012). Through an evaluation of
all cases, we determined that sub-lethal effects are more
pronounced than previously reported. Entanglements
affect right whales in three ways: (1) they compromise
individual health even when the gear is not present;
(2) they reduce survival—especially in females; and
(3) they reduce fecundity in females that survive.
An important finding of this study is the comparison
of injury severity versus health. By categorizing each
entanglement event into a severity level of minor,moder-
ate,orsevere wounds and whether gear was attached or
not and further grouping by reproductive status, we
learned that entanglement has a negative effect on both
reproductive and non-reproductive groups although not
all of these comparisons were significant. Yet the nega-
tive health estimates were more pronounced and signifi-
cant for reproductive females in both minor and
moderate no gear categories when compared with
unimpacted reproductive females who already experience
lower health scores due to the costs of lactation (Pettis
et al., 2004; Rolland et al., 2016). As severity worsened
and when entanglement events included attached gear,
FIGURE 5 Survival probability declines after entanglement and is consistently worse for females (Table 3; Appendix S4). The data
shown include both with and without gear events. The lines depict the survival curves following the last entanglement of each individual.
Colored regions indicate the uncertainty around the survival curves; specifically, the regions depict the upper and lower bounds of 1000
draw from the posterior distribution. Tick marks on each line indicate when whales were right-censored, that is, left the study because the
modeling timeframe ended before an estimated death. The legend shows the number of individuals assessed for each injury category
TABLE 3 Estimated regression parameters from a cox proportional hazards test on the effects of sex and entanglement on survival
Entanglement class Coefficient Exponentiated coefficient Standard error p-value
Male—moderate 0.052 1.05 0.27 .85
Male—severe 1.81 6.1 0.28 <<.001
Female—minor 0.55 1.74 0.177 .002
Female—moderate 0.46 1.57 0.26 .08
Female—severe 1.86 6.45 0.27 <<.001
Note: Males with minor entanglements are the reference category. Results indicate significant differences between males and females, with female survival
being lower than males.
10 of 14 KNOWLTON ET AL.
health declined for all demographic groups in the severe
cases and that decline was highly significant for the non-
reproductive category. For all three injury categories, sur-
vival in relation to entanglement was much lower for
females than for males. However, in the severe category,
both females and males showed dramatic declines in sur-
vival. Similarly, as injury severity got worse, the health of
reproductive females was more likely to be below the
calving threshold of 67 (Rolland et al., 2016). These find-
ings amplify the recent studies that suggest that human
activities, especially entanglements, are the primary con-
tributor to the current population decline (Corkeron
et al., 2018; Kraus et al., 2016; Moore et al., 2021; Pace III
et al., 2021). Further, significantly reduced survival in
females in relation to entanglements shown here is con-
sistent with Pace III et al.'s (2017) findings of lower sur-
vival for female NARWs.
The effects of entanglement on fecundity for those
reproductive females that survived suggest a complex and
non-linear interplay between entanglement, latent
health, and time, as the mean health of successful calving
females declined over time. While available animals in
better health were significantly more likely to success-
fully calve and whales with minor and moderate injuries
did not experience a reduction in the ability to calve, our
findings suggest whales with severe entanglements were
much less likely to be reproductively successful, though
the latter relationship was not significant. We suspect
that this is most likely due to significantly worse survival,
that is, so few reproductive females actually survived a
severe entanglement that there were relatively few
instances to make this comparison. In those limited num-
ber of cases where females survived a severe injury and
continued to reproduce, calving intervals were longer. It
is important to note that the analysis of event duration is,
by definition, looking at successful calving intervals, and
does not factor in females that have been entangled and
never go on to calve again (though the binomial regres-
sion does include these cases). Nevertheless, the results
indicate that over the duration of the study, animals were
less likely to calve and calving intervals have increased—
both worrisome trends for the long-term survival of the
species.
The decadal assessment shows that entanglements
lead to lower health scores in comparison to the
unimpacted category as the frequency of moderate and
severe entanglements increases. In addition, the health of
unimpacted NARW showed a significant decline in each
decade suggesting this model is detecting food limitation,
which has been described in other studies (Meyer-
FIGURE 6 Summary of median health scores by decade for unimpacted whales prior to first entanglement detection and for entangled
whales according to injury severity with health scores measured during each whale's entanglement health window. Values in each show the
upper and lower whiskers (the most extreme point no more than 1.5 times the box range), the upper and lower hinge (approximately the
first and third quantiles), and the median (Appendix S5)
KNOWLTON ET AL.11 of 14
Gutbrod & Greene, 2018; Rolland et al., 2016; Stewart
et al., 2021), or other factors that could affect health. If
food limitations or other factors were not occurring, we
would have expected the unimpacted category to remain
unchanged. Rolland et al. (2016) showed a health decline
over the 30-year period with some dramatic health
declines linked to poor calf output but indicated further
work would be needed to tease out the role that anthropo-
genic events were having on that decline. What this assess-
ment indicates is that the decline is likely the result of
both the increasing rate of moderate and severe entangle-
ments (Knowlton et al., 2016) as well as other factors.
Other factors such as non-lethal vessel strikes, anthropo-
genic noise, and the cumulative effects of repeated entan-
glements experienced by individuals could also be playing
a role in this decline but were not explored in this study.
This study measured the effects of entanglement only
through 2011 despite the fact that entanglement and VHA
data exist through 2019 and are updated annually. The
movement components of the model developed by Schick
et al. (2013) were based on a well-defined pattern of right
whale movements between habitats which began to shift
starting in 2010 (Record et al., 2019). Sensitivity analysis
indicates the informed priors we used are no longer appro-
priate with more recent data after the apparent shift in
habitat use (results not shown). This component of the
model is being actively developed as part of a new research
effort. However, the findings of this study provide a base-
line characterization of the sublethal effects of entangle-
ments, especially as injury severity increases. Since 2011,
there continue to be high levels of entanglements, espe-
cially of moderate and severe injuries. Of 476 documented
fishing gear entanglements from 2012 to 2019, 78 resulted
in severe injuries (including 11 documented deaths) and
74 resulted in moderate injuries (Hamilton et al., 2020;
NEAq unpublished data) indicating this issue is showing
no signs of abatement despite efforts at mitigation (Pace
III et al., 2014). As part of this ongoing research, our focus
will be on ensuring that the effects of multiple human
activities and climate change on this beleaguered species
are better understood. Considering that some NARWs
have experienced at least seven entanglements in their life-
time (Knowlton et al., 2012) as well as sublethal vessel
strikes, there may be an even greater cumulative impact
than we have noted here.
If we are going to save the right whales from immi-
nent extinction, dramatic changes to how fixed fishing
activities are presently conducted are required. Between
ropes getting stronger (Knowlton et al., 2016) and
expanded offshore fishing efforts overlapping with the
NARW range, the fishing activity could lead to the ulti-
mate demise of this species. There are solutions to this
crisis including ropeless fishing methods (Myers
et al., 2019) and reduced breaking strength ropes
(Knowlton et al., 2016), both of which are available and
could be integrated with area closures and fishing effort
reduction to reduce entanglement risk to this species. For
too long, the burden has been on the research commu-
nity and management to provide evidence that a given
fishery is the problem. Yet, it is clear that wherever
NARWs range, if there is overlap with fixed-fishing gear
that is not modified to protect whales, the risk remains.
These results also have negative implications for
large whale species worldwide. Evidence is mounting
that entanglements occur wherever fixed-gear fisheries
and large whales overlap (Thomas et al., 2016).
Although most large whale populations do not have the
extensive data needed to analyze effects on individuals,
entanglements are under-reported (Ramp et al., 2021)
and their impacts are probably grossly underestimated.
Entanglements not only threaten individual whales or
species but also have broader ecological consequences
in regions with diminishing whale populations. Whales
are nutrient recyclers in marine ecosystems, supporting
primary productivity (Roman et al., 2016), fisheries
(Lavery et al., 2014), and mitigating climate change
(Nicol et al., 2010; Pershing et al., 2010). Thus, if world-
wide fisheries-related entanglements of large whales
continue unabated, the resilience and productivity of
marine ecosystems could be permanently altered
(Thomas et al., 2016).
AUTHOR CONTRIBUTIONS
Amy R. Knowlton and Robert S. Schick designed the
model framework. Robert S. Schick, with guidance from
James S. Clark, carried out the programming and run-
ning of the model and conducted the analyses. Amy
R. Knowlton and Robert S. Schick co-wrote the manu-
script. All authors discussed the results and contributed
to the final manuscript.
ACKNOWLEDGMENTS
The data used in this analysis are from three different
sources. First, the list of entanglement events and associ-
ated metadata are created and curated by A.R.K. with
support from National Oceanic and Atmospheric Admin-
istration. Second, the estimates of health come from the
model (Schick et al., 2013). Third, the raw sightings and
effort data are maintained by the North Atlantic Right
Whale Consortium (NARWC). We thank the NARWC
for access and B. Kenney for helping to process the data.
WethankA.Read,P.Thompson,E.Burgess,B.Kaiser,
S. Thananopavarn, and B. McWeeny for helpful comments
on earlier drafts of this manuscript. We also thank two
anonymous reviewers who provided helpful feedback on
the submitted version of the manuscript. Lastly, we thank
members of the PCAD/PCOD working group for construc-
tive comments throughout this analysis.
12 of 14 KNOWLTON ET AL.
CONFLICT OF INTEREST
The authors have no conflict of interest to declare.
DATA AVAILABILITY STATEMENT
Data and analyses conducted for this study are available
at https://github.com/robschick/tangled.
ORCID
Amy R. Knowlton https://orcid.org/0000-0001-9124-
4315
James S. Clark https://orcid.org/0000-0002-5677-9733
Philip K. Hamilton https://orcid.org/0000-0002-0643-
039X
Scott D. Kraus https://orcid.org/0000-0003-4367-6548
Heather M. Pettis https://orcid.org/0000-0003-2206-
979X
Rosalind M. Rolland https://orcid.org/0000-0003-0910-
5813
Robert S. Schick https://orcid.org/0000-0002-3780-004X
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SUPPORTING INFORMATION
Additional supporting information may be found in the
online version of the article at the publisher's website.
How to cite this article: Knowlton, A. R., Clark,
J. S., Hamilton, P. K., Kraus, S. D., Pettis, H. M.,
Rolland, R. M., & Schick, R. S. (2022). Fishing gear
entanglement threatens recovery of critically
endangered North Atlantic right whales.
Conservation Science and Practice,4(8), e12736.
https://doi.org/10.1111/csp2.12736
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