Advanced Pollution Prevention

Marine Mammal Impacts in Exploited Ecosystems: Would Large Scale Culling Benefit Fisheries? Lyne Morissette1,2*, Villy Christensen2, Daniel Pauly2

1 Institut des Sciences de la Mer de Rimouski, Université du Québec à Rimouski, Rimouski, Québec, Canada, 2 Fisheries Centre, University of British Columbia, Vancouver,

British Columbia, Canada

Abstract

Competition between marine mammals and fisheries for marine resources—whether real or perceived—has become a major issue for several countries and in international fora. We examined trophic interactions between marine mammals and fisheries based on a resource overlap index, using seven Ecopath models including marine mammal groups. On a global scale, most food consumed by marine mammals consisted of prey types that were not the main target of fisheries. For each ecosystem, the primary production required (PPR) to sustain marine mammals was less than half the PPR to sustain fisheries catches. We also developed an index representing the mean trophic level of marine mammal’s consumption (TLQ) and compared it with the mean trophic level of fisheries’ catches (TLC). Our results showed that overall TLQ was lower than TLC (2.88 versus 3.42). As fisheries increasingly exploit lower-trophic level species, the competition with marine mammals may become more important. We used mixed trophic impact analysis to evaluate indirect trophic effects of marine mammals, and in some cases found beneficial effects on some prey. Finally, we assessed the change in the trophic structure of an ecosystem after a simulated extirpation of marine mammal populations. We found that this lead to alterations in the structure of the ecosystems, and that there was no clear and direct relationship between marine mammals’ predation and the potential catch by fisheries. Indeed, total biomass, with no marine mammals in the ecosystem, generally remained surprisingly similar, or even decreased for some species.

Citation: Morissette L, Christensen V, Pauly D (2012) Marine Mammal Impacts in Exploited Ecosystems: Would Large Scale Culling Benefit Fisheries? PLoS ONE 7(9): e43966. doi:10.1371/journal.pone.0043966

Editor: Steven J. Bograd, National Oceanic and Atmospheric Administration/National Marine Fisheries Service/Southwest Fisheries Science Center, United States of America

Received October 16, 2011; Accepted July 30, 2012; Published September 6, 2012

Copyright: � 2012 Morissette et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This research was carried out as a contribution to a doctoral thesis at the Fisheries Centre of the University of British Columbia, with financial support from the Lenfest Ocean Program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: [email protected]

Introduction

Interactions between marine mammals and fisheries have

received growing attention during the last decades [1–4]. Many

studies have examined how fisheries may impact marine mammal

populations [5–7], but the degree to which marine mammals

compete for food with fisheries is still poorly known [5,8–9].

Nevertheless, competition for fish resources may be a primary

source of current and future conflicts [10–14]. Even though many

authors now document a growing concern about the widespread

decline of many marine mammal populations [8,15–19], there is a

serious need to address their competition with fishery for the same

food resources.

Understanding how, where, and when marine mammals and

fisheries compete is not an easy task [20–21]. First of all, detailed

information on predation rates and how these relate to fluctuations

in fish availability or marine mammal population size is lacking

[22–23]. Furthermore, it is usually very difficult to observe marine

mammal feeding and/or interacting with fisheries [24–25].

Quantifying their diets with estimation models (scats, stomach

contents, fatty acids, etc.) is also problematic as diets can vary

substantially over time and space [26–29]. Finally, even on the

fisheries side, exhaustive data on yield and precise estimates on

catches, bycatch (especially the commercially less important

species), or discards are relatively hard to obtain [30–31].

Ecosystem models can be used address the trophic role of

marine mammals in ecosystems, and their potential competition

with fisheries. Ecopath with Ecosim (EwE) models are generally

constructed to address fisheries questions, and merely consider the

commercially important species, but in some cases marine

mammal are included, providing a better representation of the

trophic interactions in the upper trophic levels of ecosystems [32–

33]. They then become useful to address questions about the

competition between marine mammals and fisheries.

The present analysis has the following objectives: 1) to calculate

the target species (prey or catch) overlap between marine

mammals and fisheries; 2) to examine the global trophic impacts

of marine mammals and fisheries on the commercially important

species of each ecosystem; and 3) to simulate the extirpation of

marine mammal populations and analyze the resulting changes on

the structure of the food web. Also, we examine the impact of

whales versus pinnipeds in ecosystems, in order to investigate if

whaling and seal culling would have the similar impacts on

ecosystems.

Materials and Methods

Modeling approach and ecosystem representation EwE is a widespread software package widely used for the

analysis of exploited aquatic ecosystems ([34], freely available

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through http://www.ecopath.org). This modeling approach

creates a simple static model to describe the average interactions

of the populations within an ecosystem during a certain period.

The model assumes mass-balance, i.e., that we account for all

energy flows in a food web. Such an approach is different and

much easier to implement than attempts to model multispecies

interactions such as multispecies virtual population analysis

(MSVPA; [35]) for which an enormous quantity of catch-at-age

data and stomach contents analyses is required [36].

While there is spectrum of models ranging from single species

assessments through so-called ‘minimum realistic ecosystem

models’ to very complex end-to-end models, EwE models

generally represent a less-data intensive approach that allows

evaluation of ecosystem-level questions with focus on the higher

trophic levels [37]. In EwE models, input values (mainly biomass,

production, consumption, diet composition and harvest) often are

available for several species or groups in the ecosystem, and it is an

approach allowing the construction and rapid evaluation of

balanced ecosystem models [38]. EwE has the advantage of

including all/most of the important species groups in contrast to

minimum realistic models (MRM), and allows evaluation of

unexpected indirect interactions that an MRM could miss.

For this study we used a series of ecosystem models. Each

Ecopath model was based on mass balance principles, assuming that

production of a given prey group (i) was equal to the biomass lost

to fishing or export, predation, and natural mortality other than

predation (other mortality). This mass balance can be expressed as:

Consumption~productionzrespirationz

unassimilated food ð1Þ

and

Production~predationzfishing mortalityz

other mortality ð2Þ

where consumption is composed of consumption within the system

and consumption of imports (i.e., consumption ‘‘outside the

system’’), and production may be consumed by predators, be

exported from the system or contribute to the detritus. The terms

of these equations may be replaced by:

Production by i~Bi:Pi=Bi ð3Þ

Predatory losses of i~ S j (Bj � Qj=Bj � DCij) ð4Þ

and

Other losses of i~ 1{EEið Þ:Bi:Pi=Bi ð5Þ

For any species or group of species of the system, this leads to

the linear equation:

Bi :Pi=Bi:EEi{

X j

Bj :Qj

� Bj :DCij

� � {Exi~0 ð6Þ

where:

i indicates a component (stock, species, group of species)

of the model;

j indicates any of the predators of I;

Bi indicates the biomass of I;

Pi/Bi indicates the production/biomass ratio, which is

equivalent to total mortality; (Z) under the most

circumstances [39];

Qi/Bi indicates the food consumption per unit biomass

of i;

DCij indicates the contribution of i to the diet of j (in

terms of mass);

EEi indicates the ecotrophic efficiency of i, or the

fraction of production that is consumed or caught within

the system;

Exi indicates the export of i from the system (by

emigration or fisheries catches).

Algorithms in the model also allow for the estimation of one

missing parameter (Bi, Qi/Bi, Pi/Bi, or EEi) in each group [38].

In Ecopath, several system indices (see below) are computed to

describe the food web, its complexity, and the way trophic groups

interact with one another. The software also allows dynamic

simulations through the Ecosim module, a dynamic modelling

approach for exploring past and future impacts of fishing and

environmental disturbances [40].

Ecosim provides temporal simulations using the initial parame-

ters of the Ecopath master equation (Eq. 7). It works with a couple

of differential equations to estimate biomass fluxes as follows:

dBi

dt ~gi

X j

Qij{ X j

QijzIi{(MizFizei)Bi ð7Þ

where dBi/dt is the biomass growth rate of group (i) during the

interval dt, gi is the net growth efficiency (production/consumption

ratio), Ii is the immigration rate, Mi and Fi are natural and fishing

mortality rates of group (i), ei is emigration rate [41]. Ecosim

describes the interactions between predators and prey by

attributing a density-dependent term (‘vulnerability’) for each of

these interactions. This vulnerability parameter sets the maximum

increase in predation mortality a given predator can cause on a

given prey [40].

Because there is good coverage based on the same modelling

methodology available from throughout the world’s oceans, we

chose EwE models as our sample units to quantify and analyze the

impact of marine mammals in marine food webs. This approach is

important because it also represents a rational way of quantifying

the trade-offs between sustainable exploitation of natural marine

resources and conservation of charismatic fauna [42]. The models

also have the advantageous possibility of being validated to

conventional stock assessment data or surveyed biomass estimates

[33].

Seven models are part of this analysis, selected in terms of their

location and the quality of their documentation (Table 1).

Particular effort was made to cover both northern and southern

hemispheres, in an attempt to have a wide coverage of the world’s

oceans for the global extrapolation. Kaschner and Pauly [43] have

shown that the prominent hotspots of overlap and potential

competition between marine mammals and fisheries include the

Bering Sea where the potential negative impacts of the US

groundfish fisheries on the endangered western population of

Steller sea lions (Eumetopias jubatus) have been of great concern [44–

45], the Benguela system off southwest Africa with the potential

impacts of the increasing population of South African fur seals on

the hake stocks [46] and the east coast of North America where the

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largest annual marine mammal cull worldwide is in part being

justified based on the perception that the growing harp seal (Phoca

groenlandica) population impedes the recovery of the northwest

Atlantic cod (Gadus morhua) stocks (see review in [47]). To these

three ecosystems, we added other ecosystems models that didn’t

necessarily featured a marine mammal-fisheries issue, but that

were characterized by important and well-documented fisheries

and marine mammals: the eastern tropical Pacific Ocean; the

North Sea; the Gulf of Thailand and the Strait of Georgia

(Figure 1). The seven models show different levels of aggregation

(how the species are grouped to represent the whole foodweb) and

cover from 26 to 40 trophic groups. They were selected because

they included marine mammals and used high-pedigree data to

describe their diet of these groups. The ‘pedigree’ of an Ecopath

input is here understood as a coded statement categorizing the

origin a given input (i.e., the type of data on which it is based), and

specifying the likely uncertainty associated with the input, for diet

data, it varies between 0 (general knowledge) to 1 (qualitative,

detailed, diet composition) for diet composition [48] (Table 1).

They were also selected based on the fact that they have been

shown to reproduce well the past patterns of change in relative

biomass of major species given historical disturbance patterns

(fishing mortality rates and/or effort over time, and in some cases

changes in oceanographic or nutrient-loading indices of relative

primary productivity). For these seven ecosystems, an EwE model

was obtained from the scientists who created it, and verified for its

ability to reproduce observed time series of biomass changes

(Table 1).

Ecosystem indicators For each model, a comparison of the Ecopath outputs for food

consumption by marine mammals versus the catch by fisheries was

performed. The estimated annual catches (i.e., ‘food consump-

tion’) of fisheries and marine mammals was calculated for each

ecosystem. We also compared the estimated catch composition of

the fisheries to the diet of marine mammals. Finally, the primary

production required (PPR) to sustain fisheries was compared with

the PPR to sustain marine mammals groups.

The mean trophic level of marine mammals’ consumption

(TLQ) and of fisheries catches (TLC) were derived from Ecopath

outputs. TLC is an indicator of the ecosystem health and the state

of the fisheries [49], based on Lindeman’s [50] concept of trophic

levels, and calculated as:

TLC~ X i

TLi YiP Y

� �� � ð8Þ

where Yi is the total landings of species i (in tonnes), SY is the sum of landings for all species, and TLi is the trophic level for species i,

which can be fractional as suggested by Odum and Heald [51].

Similarly, the trophic level of consumption (TLQ) by marine

mammals was computed:

TLQ~ X i

TLi :

Pn j~1

Qij

Pn j~1

Qj

0 BBB@

1 CCCA

0 BBB@

1 CCCA ð9Þ

where Qij is the consumption of prey i (in tonnes) by marine

mammal j, Qj is the total consumption of all species by marine

mammal j, and TLi is the trophic level for species i. This equation

represents the average trophic level on which marine mammals

feed, i.e., the average TL of each species, multiplied by their

proportion in the consumption matrix (tonnes?km 22

?year 21

that

marine mammals consume).

Using estimates of fisheries catches and marine mammal

consumption, the assessment of overlap between marine mammal

and fisheries for each ecosystem was performed using an equation

derived from Kaschner and Pauly [43]:

af ,m~

2 � P k

(pm,k � pf ,k) P k

p2 m,k

z P k

p2 f ,k

0 B@

1 CA � Qm

(QmzCf ) � Cf (QmzCf )

� � ð10Þ

where af,m is the quantitative overlap between a fishery f and a marine mammal group m in the ecosystem, and the first term

expresses the qualitative similarity in diet/catch composition

between the marine mammal group m and fisheries f sharing the

resource or food type k, with pm,k and pf,k representing the

proportions of group k in the diet of marine mammals m or the

catch by fishery f. This term is multiplied by the product of the

proportion of total food consumption by marine mammals Qm and

the proportion of total fisheries catches Cf in the ecosystem. This

index scales from 0 (no overlap) to 0.250 (identical resource).

When resource use is identical between two groups, the first term

of equation 10 is equal to 1, and each proportion of the second

term is 0.5 (or 0.25 for the product). In order to make ecosystems

comparable despite their different trophic structures, overlap by

food types was also calculated, based on food categories that were

first described in Pauly et al. [52]: benthic invertebrates (all

crustaceans except krill, seasquirts, bivalves, gastropods, octopus,

etc.), large zooplankton (mainly krill), small squid (mantle length

,50 cm), large squid (mantle length . = 50 cm), miscellaneous fishes (Fishbase [53] habitat attributes: demersal, benthic,

benthopelagic, bathydemersal, reef-associated, pelagic .80 cm), mesopelagic fishes, small pelagic fishes (fishbase attributes: pelagic

,80 cm). The details on how the trophic groups of each model were classified into these different food categories are given in

Table S1.

The mixed trophic impact (TI) analysis of Ecopath was used to

compare the ‘with/without’ impact of predation by marine

mammals on the whole ecosystem [54]. This quantifies all the

direct and indirect trophic impacts of all groups in the system:

MTIij~DCij{FCj,i ð11Þ

where DCij is the diet composition term expressing how much j

contributes to the diet of i, and FCj,i is a host composition term

giving the proportion of the predation on j that is due to i as a

predator. When calculating the host compositions, the fishing

fleets are included as ‘predators’.

Beneficial predation refers to a situation where a predator may

have a direct negative impact on its prey, which is counterbal-

anced by indirect positive effects through the consumption of other

predators and competitors of the prey [14]. It was calculated as the

percentage of the overall trophic impact by marine mammals that

is positive for any prey group of this predator.

Dynamic simulations In Ecosim, the predator-prey relationships are based on the

foraging arena theory, dividing the prey biomass into vulnerable

and invulnerable pools [55]. The vulnerability parameter (v)

represents the transfer rate between these two pools, and has

implications for how a given predator will impact predation

mortality for a given prey, and can range from 1 to ‘. Low

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vulnerability factors (e.g. = close to 1) imply that an increase in

predator biomass will not cause any noticeable increase in the

predation mortality the predator will cause on the given prey.

High vulnerability factors (e.g. = 100) contrarily indicate that if the

predator biomass is for instance doubled, it will cause close to a

doubling in the predation mortality rate on a given prey. This then

relates directly to assumptions about the carrying capacity for the

predator in question [40], and Ecosim predictions are very sensitive

to this parameter [4]. The default vulnerability (2.0) assumes that

each predator group can at most increase the predation mortality

they impose on their prey by a factor of 2.0, while a lower value

implies a donor-driven density-dependent interaction, and a much

higher value involves a predator-driven density-independent

interaction, in which predation mortality is proportional to the

product of prey and predator abundance (i.e., Lotka-Volterra).

Here, we used a set of models whose vulnerabilities were derived

by fitting to historical data following Walters et al [56]. In order to

quantify the potential impact of marine mammal predation on the

ecosystem, and to examine if there really is strong competition

with the fisheries, Ecosim simulations were run for 22 to 89 years,

depending on the time series available. The seven ecosystem

models were first analyzed with Ecosim using time series of fishing

mortality (F) to see which groups’ biomass decline or increase over

time. The models covered different sources of fishing mortality or

fishing fleets (trawls, long lines, coastal, deep-water, whaling, etc),

which were combined in every model to see the overall effect of

fisheries on the entire ecosystem. A first simulation was done with

the original ecosystem structure (and original catches of fish and

marine mammals), while a second was performed with a very high

catch of marine mammals, with the purpose of driving them

extinct. Vasconcellos et al. [57] showed that for fish species, a 5-

fold increase in fishing mortality leads to serious depletion. Also,

such an extreme scenario is routinely applied to many fish

populations and often associated with stock collapse [58].

Consequently, an F value of 1.0 year-1 (representing an average

five-fold increase for marine mammal species that were already

hunted) was applied to each marine mammal group in the models.

The higher values of F were kept constant for the first 20% of the

Figure 1. Location of the ecosystem modeled with Ecopath and used for this analysis. doi:10.1371/journal.pone.0043966.g001

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time series, and then returned to the baseline, with the model

running for the remaining 80% of the time.

Results

Total food consumption by marine mammals vs fisheries catches At the global scale, when considering all ecosystems at once, the

major source of overlap between marine mammals and fisheries

for all models combined was for ‘miscellaneous fish’ (i.e., demersal;

benthic; benthopelagic; bathydemersal; reef-associated habitat &

common length ,150 cm; or pelagic habitat & common length .60 cm and ,150 cm) and ‘small pelagic’ (pelagic habitat & common length ,60 cm). Marine mammals’ consumption was diversified and represented a great array of marine organisms

(36% of miscellaneous fish, 21% of small squids, and approx-

imately equal proportions [10–16%] of benthic invertebrates,

large zooplankton, meso-pelagic, and small pelagic fish), while

fisheries catches were concentrated at 51% on ‘miscellaneous fish’,

13% of small pelagic fish, and 11% of benthic invertebrates. While

marine mammals could consume different prey groups (mainly

large zooplankton, cephalopods, small pelagic fish and macro-

benthos), fisheries in the seven studied ecosystems combined were

mainly targeting small crustaceans such as shrimp, pelagic fish

(redeye, Etrumeus whiteheadi; redfish, Sebastes spp.; anchovy, Eugraulis

capensis; sprat, Sprattus sprattus), and demersal species such as hake

species, lingcod (Ophiodon elongates), and sandeel (Ammodytes tobianus).

The detail of each ecosystem is given below.

In the Eastern Bering Sea system (Figure 2A), all fisheries

catches fell into three types: mostly miscellaneous fishes (91%), but

also mesopelagic fishes and higher vertebrates. In contrast, these

food types accounted for less than a third of marine mammal

consumption, which was more diverse and principally composed

of large zooplankton (25%), benthic invertebrates (24%), and

miscellaneous fish. In the Northern Gulf of St. Lawrence

(Figure 2B), miscellaneous fish were the main target, accounting

for 32% and 74% for marine mammal consumption and fisheries

catches, respectively. However, the remaining marine mammal

consumption was shared between three important groups (small

pelagics, benthic invertebrates, and large zooplankton), while the

fishery mainly caught miscellaneous fish (cod, redfish, and large

Greenland halibut), benthic invertebrates (shrimp, crab, and

molluscs) and small pelagics (herring). Marine mammal harvest

(mainly seal hunt) also occurred in the Gulf of St. Lawrence,

accounting for about 1% of the total catch. In the Benguela system

(Figure 2C), more than 95% of all fisheries catches fell into three

food types: small pelagic (57%), miscellaneous,(40%) and meso-

pelagic (2%) fishes. These food types were also the most important

for marine mammals of this ecosystem (50% miscellaneous, 28%

small pelagic, and 3% mesopelagic fish), whose diets also included

an important proportion (17%) of small squids. In the eastern

tropical Pacific model (Figure 2D) most fisheries catches were of

Table 1. Ecopath models used for analyses of marine mammals consumption.

Ecosystems Area covered (km 2 ) No of trophic groups

Marine mammals groups

Average pedigree or marine mammals’ diets Reference

Eastern Bering 484,500 26 1) Baleen whales 0.7 National Research

Sea 2) Toothed whales Council [30]

3) Sperm whales

4) Beaked whales

5) Walrus and bearded seals

6) Other seals

7) Steller sea lions

Northern Gulf 103,812 32 1) Cetaceans 0.6 Morissette et al. 2003

of St. 2) Harp seals [109]

Lawrence 3) Hooded seals

4) Grey seals

5) Harbour seals

Benguela 179,000 32 1) Seals 0.7 Shannon et al. 2004 [78]

system 2) Cetaceans

Eastern 32,800,000 39 1) Baleen whales 0.8 Olson and Watters [93]

tropical Pacific 2) Toothed whales

3) Spotted dolphins

4) Meso. dolphins

North Sea 570,000 32 1) Seals 0.7 Christensen et al. 2002 [77]

Gulf of Thailand 101,384 40 1) Marine mammals 0.5 FAO/FISHCODE 2001 [110]

Strait of 6,900 27 1) Transient orcas 0.6 Martell et al. 2002 [111]

Georgia 2) Dolphins & Resident orcas

3) Seals

4) Sea lions

doi:10.1371/journal.pone.0043966.t001

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two types: non-mammal food and mesopelagic, accounting for 70

and 28%, respectively. There, marine mammals fed on a variety of

food types, mainly small squids (44%), mesopelagic (33%), and

miscellaneous fish (19%). The North Sea model (Figure 2E)

showed that about 75% of resources taken by marine mammals or

by fisheries was composed of miscellaneous fish. However, the

difference between marine mammals and fisheries was in what

kind of miscellaneous fish they exploited. The main fishes eaten by

marine mammals were dab and cod, while fisheries (at the time)

mostly targeted Norway pout (Trisopterus esmarkii), sprat and

sandeel. In the Gulf of Thailand (Figure 2F), marine mammals

fed on a great variety of groups, while fisheries mainly caught

miscellaneous fish (46%) and benthic invertebrates (32%). These

two food types represented about a third of consumption by

marine mammals, which was mainly composed of small pelagic

fish (45%). ‘Trash fish’ (bycatch catches that are used in the

production of fishmeal) was one of the most important miscella-

neous fish to be taken by fisheries and marine mammals, but then

the two competing groups differed as marine mammals consumed

more small pelagic and benthos, and fisheries caught more

shellfish and shrimp. In the Strait of Georgia ecosystem, almost all

fish caught by the fisheries were miscellaneous fish (96%;

Figure 2G), which also represented 72% of the consumption by

marine mammal. The marine mammal prey was dominated by

adult hake and demersal fishes, which was different from the

miscellaneous fish (adult herring) caught by the fisheries.

Overall, the degree of overlap depended largely on the

resolution of the marine mammals’ prey and fisheries catches.

Instances of direct overlap at the level of a trophic group (species of

group of similar species) occurred in the Eastern Bering Sea

(mainly for small flatfish, large flatfish, adult pollock [Pollachius

virens], and other demersal fish), Gulf of St. Lawrence (planktivor-

ous small pelagics, piscivorous small pelagics, shrimps and large

crustaceans), Benguela (anchovy, redeye, and sardine [Sardinops

sagax]), eastern tropical Pacific (small yellowfin tuna [Thunnus

albacares], skipjack [Katsuwonus pelamis], and Auxis sp.), Gulf of

Thailand (‘trashfish’, Rastrelliger spp., cephalopods, small demer-

sals, and small pelagics), and Strait of Georgia (resident coho

salmon [Oncorhynchus kisutch], resident chinook salmon, and

lingcod). On the other hand, little overlap occurred between

marine mammals prey and fisheries catches in the North Sea, even

at the species level.

Trophic interactions between marine mammals and fisheries In most ecosystems, marine mammals fed on lower trophic level

species than what was caught by fisheries (Table 2). Except for the

northern Gulf of St. Lawrence and the Strait of Georgia, TLQ had

lower values than TLC. The largest discrepancy between these two

values was observed in the eastern tropical Pacific, where TLC is

one trophic level higher than the TLQ (4.70 versus 3.76).

The primary production required (PPR) to sustain marine

mammal consumption was always lower than PPR to sustain the

fisheries (Table 2). Globally, PPR for fisheries was twice as high as

PPR for marine mammals’ consumption (20% vs. 10%). Marine

mammals of the Benguela system had the lowest PPR, requiring

only 2.2% of total primary production of the system, compared to

marine mammals in the Eastern Bering Sea, where the PPR was

31.8% of total primary production. For fisheries, the lowest value

was in the Benguela system (3.2%), while the highest PPR for

fisheries catch was in the Eastern Bering Sea (53.9%), closely

followed by the North Sea (50.1%).

When marine mammals were considered all together, their

resource overlap with the fisheries varied considerably within the

seven ecosystems (Table 2). Ecosystems with higher resources

overlap had a lower diversity of food groups caught/eaten by

fisheries/marine mammals. Models with a very high proportion of

miscellaneous fish had a higher resource overlap than systems

where other food types were more important. When analyzed per

trophic group instead than per food type, the overlap was always

lower. Highest overlap value was seen in the Benguela system,

while lowest overlap was in the eastern tropical Pacific.

Interestingly, the North Sea ecosystem, which had the highest

overlap per food type, had the third lowest value when overlap was

calculated by trophic group. The number of trophic links in the

ecosystem also had an effect on the resource overlap between

marine mammal and fisheries. Indeed, food webs with lower

connectance (less trophic links) generally showed higher overlap

values (Table 2).

Marine mammals, fisheries and their impact on the trophic structure The mixed trophic impact evaluated direct and indirect trophic

effects. In the Eastern Bering Sea both marine mammals and

fishery had an overall negative impact on the entire ecosystem

(MM = 22.98; fishery = 23.04). The groups that were mostly impacted by marine mammal consumption were deep-water fish,

large flatfish and other demersal fish. Conversely, small flatfish,

deep pelagics and flatfish trawl seemed to benefit from the

presence of marine mammals while marine mammals and flatfish

were the most impacted by fisheries (Table S1).

In the Northern Gulf of St. Lawrence, fisheries had an overall

negative impact (24.93) that was much higher than that of marine mammals (22.93). The groups that were the most negatively impacted by marine mammals were large demersals, large

pelagics, and Greenland halibut (Reinhardtius hippoglossoides; large

and small). In contrast, skates, small demersals, shrimp and most

benthic invertebrates seemed to benefit from marine mammals. All

marine mammals and seabirds, large cod, shrimp, small demersals

and most benthic invertebrates were negatively impacted by

fisheries in the Gulf of St. Lawrence. Small Greenland halibut,

large demersals, and small cod seemed to benefit from fisheries

(Table S1).

In the Benguela model, fisheries’ negative impact on the groups’

biomass was larger than that of marine mammals by an order of

magnitude (20.105 vs 20.011, respectively). The groups that were most negatively impacted by marine mammal consumption were

cape hake (Merluccius capensis), horse mackerel (Trachurus capensis),

and cephalopods. Conversely, apex chondrichthyans, mesopela-

gics, and redeye seemed to benefit from marine mammals. The

fleet ‘‘other fisheries’’ would also benefit from an increase in

marine mammal biomass in terms of mixed trophic impacts (Table

S1). The main groups negatively impacted by fisheries in the

Benguela ecosystem were snoek (Thyrsites atun), sardine, other large

pelagics, shallow-water cape hake, and deep-water cape hake

(Merluccius paradoxus) (Table S1).

In the eastern tropical Ocean, the TI of marine mammals and

fisheries showed that fishery (21.869) and marine mammals (22.334) had an overall negative impact on the whole ecosystem. Groups that were the most negatively impacted by marine

mammal consumption were small bigeye (Priacanthus arenatus),

small wahoo (Acanthocybium solandri), albacore (Thunnus alalunga),

and skipjack. On the other hand, large bigeye, large dorado

(Coryphaena hippurus), large wahoo, large sharks, rays, and flyingfish

(Cypselurus naresii) all benefited from the presence of marine

mammals, while fisheries negatively affected them. Some fisheries

also benefit from the presence of marine mammals in the system:

the horse mackerel fisheries (midwater and demersal fleets) and

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snoek trawls (Table S1) are examples. The TI also showed that

groups that were the most positively impacted by the combined

effect of all fisheries were mainly the juveniles of important

commercial fish (wahoo, dorado, swordfish [Xiphias gladius], sailfish

[Istiophorus platypterus], marlins, bigeye). When all the fisheries were

grouped, their combined effect on the individual fishing fleets was

mostly negative, suggesting a high level of competition between the

fleets.

In the Gulf of Thailand, the TI of the fisheries was overall

negative (27.735), and much higher than that of marine mammals (21.899). Marine mammals had larger negative impact on small pelagics, jacks (Carangidae), Rastrelliger spp., and on the purse seine

fishery (Table S1).

In the North Sea model, the negative impact of fisheries (27.79) was three times larger than the impact of seals (22.22). Many of the groups that were seriously impacted by fisheries showed

positive impact by seals; for instance, for gurnards (Lepidotrigla

spp.), horse mackerel (Trachurus trachurus), sole (Solea solea), juvenile

saithe (Pollachius virens), rays, and herring. Some groups were

positively impacted by fisheries, such as dab (Limanda limanda),

sandeel, juvenile haddock (Melanogrammus aeglefinus), juvenile cod,

and birds. All of the groups (except for dab) were also positively

impacted by seals. Negative impacts from seals were mainly

observed for cod, saithe, plaice and dab (Table S1). Here again,

the overall impact of all fisheries grouped together was damaging

for each single fishing fleets.

In the Strait of Georgia, the TI analysis showed that while the

overall trophic impact of marine mammals was near neutral

(20.83), there was a strong negative impact by fisheries on the food web (27.79). This negative impact of fisheries affected almost all fish species in the ecosystem (Table S1), except for dogfish

(Squalus acanthias), juvenile herring, and juvenile coho salmon,

which seemed to benefit from fisheries. Marine mammals’ negative

impact on fish was always smaller than fisheries’ impact on the

same groups. Interestingly, the overall effect of marine mammal

on fishing was positive for trawlers, gill nets, seiners and industrial

fleets. Total marine mammals impact was also strongly negative

for resident killer whales, seals and sea lions (Table S1).

Dynamic simulations Different simulations were done for each model (eradication of

all marine mammals, or of their component groups), and changes

in biomass trends were recorded (see, e.g., Figures 3A and 3B). In

both examples, the complete eradication of different groups of

marine mammals created a change in the biomass trajectory of fish

species, however this specific change was less than 15%, and could

approach zero even after 50 years of simulations.

After simulating marine mammal extirpation in the eastern

Bering Sea ecosystem, there was an increase in biomass (compared

to the simulation without marine mammal extirpation) in the other

demersal fish, deep pelagics, deep-water fish, jellyfish, and

cephalopods, but all other groups showed a decrease in biomass

(Figure 4A). Over a period of 51 years, there was an overall

decrease of 6% of total biomass if marine mammals were

eradicated (Btot = 316 t?km 22

with marine mammals, and

298 t?km 22

without them). This represents of course the complete

extirpation of marine mammals biomass itself, but also seabirds,

and other fish species such as small flatfish, as well as a critical

biomass decrease for shallow pelagics (299%), and epifauna (297%). Our simulation also predicted that there were less fish to catch for the main species targeted by fisheries (adult pollock and

shallow-water pelagics) without marine mammals (a decrease of

16% and 99%, respectively) (Figure 4A). Five fisheries out of eight

suffered from a decrease in the biomass of their target species if

there were no marine mammals in the ecosystem.

In the Gulf of St. Lawrence, when all seal and cetacean species

were removed from the ecosystem, its structure changed. There

was an explosion in the biomass of Greenland halibut, and an

increase in large pelagic and demersal groups. Most groups that

originally had lower biomasses appeared to increase their biomass

after the extirpation of marine mammals. However, for commer-

cially important groups, (e.g., adult cod, capelin, and small

Figure 2. Estimated mean annual catch and food consumption by food types expressed as proportions of total amounts taken (t?km22) in the Eastern Bering Sea (A), Gulf of St. Lawrence (B), Benguela (C), Eastern tropical Pacific (D), Gulf of Thailand (E), North Sea (F), and Strait of Georgia (G) ecosystems. Food types categories defined by Pauly et al. 1998a): Non-marine mammal food (NM), miscellaneous fishes (MF), small pelagic fishes (SP), benthic invertebrates (BI), small squids (SS), large squids (LS), mesopelagic fishes (MP) large zooplankton (LZ), higher vertebrates (HV). doi:10.1371/journal.pone.0043966.g002

Table 2. Mean trophic level of marine mammals’ consumption (TLQ), Mean trophic level of fisheries’ catches (TLC), primary production required (PPR), and overlap indices (aj,l) for marine mammals and fisheries, and connectance in our study areas.

Ecosystem model TLQ TLC

PPR Marine mammals’ Q (% of total PP)

PPR Fisheries catch (% of total PP) aj,l per food type

aj,l per trophic group Connectance

Eastern Bering Sea 2.83 3.42 31.8 53.9 0.031 0.006 0.274

Gulf of St. Lawrence 3.24 3.71 9.8 18.4 0.161 0.034 0.298

Benguela 3.65 3.73 2.2 3.2 0.714 0.120 0.231

Eastern tropical Pacific 3.76 4.70 14.1 6.3 0.005 0.0003 0.218

North Sea 3.25 3.44 3.0 50.1 0.890 0.020 0.219

Gulf of Thailand 2.08 2.46 1.8 2.3 0.468 0.100 0.139

Strait of Georgia 3.36 3.25 6.0 6.7 0.163 0.024 0.250

Global average 2.88 3.42 9.7 20.1 0.149 0.043 -

The overlap index scales from 0 (no overlap) to 0.250 (identical resource). Connectance is an index of ecosystem complexity that represents the proportion of possible links between groups that are realized (links/species

2 ).

doi:10.1371/journal.pone.0043966.t002

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planktivorous pelagics), the increase was limited (Figure 4B). The

most important fishery in terms of landings in the 1980s was for

cod, redfish, small planktivorous pelagics (herring), and shrimp.

Without marine mammals, most of these target species showed no

significant change, or decreased slightly (Figure 4B).

On the one hand, in the Benguela system, the removal of the

cetaceans and seals groups seemed to generate an explosion of

sardine, as well as anchovy, snoek, other pelagics and seabirds. On

the other hand, groups such as mesopelagics (264%), other small pelagics (227%), redeye (220%), and pelagic demersals (219%) showed decrease in biomass (Figure 4C). Increase in biomass was

observed for snoek (47%), other large pelagics (28%), seabirds

(27%), and large M. capensis (20%). The main targeted species in

the Benguela ecosystem were anchovy, sardine, redeye (all caught

by purse seine) and large deep-water Cape hake (caught by

offshore trawl). When marine mammals were removed from the

ecosystem, most of these commercially important fish ended up

with less biomass than in the initial ecosystem, except for anchovy

(Figure 4C). Out of 15 different fisheries in the Benguela

ecosystem, eight underwent notable loss in the biomass of their

target species after 25 years without marine mammals. Moreover,

four of these were in the top-five fisheries with the most important

catch at the beginning of the simulation.

In the eastern tropical Pacific, when marine mammals (here

dolphins) were removed from the ecosystem, there was an increase

in the biomass and hence predation of large fish such as wahoo

(strongest increase in biomass; 248%), yellowfin tuna, bigeye,

sharks, skipjack, albacore, bluefin tuna (Thunnus orientalis), and

dorado (Figure 4D). The most important fish in terms of biomass

(Auxis sp., flyingfish, and miscellaneous epipelagic fish) would

decline if marine mammals were removed from the ecosystem

(Figure 4D). However, commercially important species (especially

bigeye, wahoo and skipjack), which tend to have lower biomasses,

would benefit from the extirpation of marine mammals.

The Gulf of Thailand model showed that when all marine

mammals were extirpated, this lead to an explosion in demersal

benthivore species, but also to large variation in the biomass of

small demersals, small pelagics and Rastrelliger spp. The remaining

groups seemed to stabilize around equilibrium after the 24-year

simulation. The most important groups in the Gulf of Thailand in

terms of landings were ‘trash fish’, shellfish, shrimps, Rastrelliger

spp., cephalopods, small pelagics, and crabs & lobsters. In a

scenario without marine mammals in the ecosystem, most of these

target species increased, except for shrimp, which was commer-

cially very important (Figure 4E).

Figure 3. Change in commercially important fish biomass before (grey line) and after (black line) the simulated eradication of all marine mammals. Examples for pollock and cetaceans in the Eastern Bering Sea (A) and for cod and seals in the North Sea (B). doi:10.1371/journal.pone.0043966.g003

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In the North Sea model, after the simulated seal extirpation

(Figure 4F), the dynamics remained approximately the same. No

fish species showed a clear increase in biomass. Their biomass may

have been replaced by cod and saithe, which showed an increase

in biomass following the decline of seals (Figure 4F). The main

species targeted by the North Sea fisheries were adult Norway

pout, sandeel, sprat, saithe, herring, whiting, and haddock. When

marine mammals were absent from the system, Ecosim predicted

that these fisheries caught about the same amount of fish than if

marine mammals were present in the system (the largest changes

were increases of 11% and 14% for whiting and saithe,

respectively). Out of four fisheries, one (seiners, catching herring

and mackerel) was definitely decreasing in terms of catch if there

were no marine mammals in the ecosystem. In general, all trophic

groups stayed at approximately the same level of biomass, with or

without marine mammals in the ecosystem (Figure 4F).

Finally, in the Strait of Georgia, at the end of the simulation

extirpating marine mammals, there was strong variations in

halibut biomass, and the biomass of small pelagics, jellyfish,

eulachon (Thaleichthys pacificus), and adult hake (Urophycis tenuis)

came close to zero. All other groups appeared to stabilize at lower

levels at the end of the 50-years simulation. The main targeted

species were herring, resident Chinook salmon, lingcod, and

resident Coho salmon. When marine mammals were removed

from the ecosystem, most of these commercially important fish

ended up with more biomass than in the initial ecosystem, except

for herring, which decreased by 13% (Figure 4G).

Differences between groups of marine mammals In order to have noticeable effect on the biomass of

commercially important fish, we would need to eradicate all

marine mammals of the ecosystem (Table 3). However, even in

that case, unexpected effects occurred, such as decreases of all

commercially important fish in the Benguela and Strait of Georgia

ecosystem. When removing only whale species, some ecosystems

showed an increase in biomass for commercially important species,

(e.g., Gulf of St. Lawrence), while some showed an (expected)

increase in biomass, (e.g., predator fish and benthos in the Bering

Sea). However, this effect was mainly done to the eradication of

toothed whales, while baleen whales had almost no effect on these

systems (Table 3). The eradication of marine mammals also had

important impacts on fish that were not targeted by fisheries

(Table 4). Indeed, most species that were not fished suffered from a

decrease in biomass when marine mammals were removed from

their respective ecosystem. This included depletion of forage fish in

the eastern Bering Sea, and to a lesser extent a noticeable

reduction of predatory fishes in the Gulf of St. Lawrence.

Interestingly, the slight increases in biomass were more noted

after eradicating baleen whales than any other marine mammal

groups, while the most cases of a biomass decrease of non-

Figure 4. Biomass changes simulations with (white) and without (grey) marine mammals in the Eastern Bering Sea (A), Gulf of St. Lawrence (B), Benguela (C), Eastern tropical Pacific (D), Gulf of Thailand (E), North Sea (F), and Strait of Georgia (G) ecosystems. doi:10.1371/journal.pone.0043966.g004

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exploited species was when eradicating pinnipeds and dolphins

(Table 4).

When all the simulations were pooled and analyzed by type of

marine mammals (seals, dolphins, toothed whales, or baleen

whales), the percentage of change in the biomass of commercially

important fish (the groups with fishing mortality in the original

models) increased differently according to the type of eradication

simulated (Figure 5). When eradicating all marine mammals, the

average response from all studied ecosystems showed the most

important increase (Figure 5). However, the general response

could vary from a slight decrease in biomass to an increase of

about 20% of commercially important fishes. Similarly, when

eradicating all whale species from the ecosystems, the overall

response was a slight increase (less than 10%) in the biomass of

commercially important fish. However, this was mainly driven by

the removal of toothed whales, for which eradication leads to more

chances of a positive effect (increase) on commercial fish species.

When removing baleen whales from these systems, the response

was almost null, but represented a negative effect on commercial

fish biomass. Interestingly, the same effect was seen for seals,

whose eradication would suggest an overall decrease of commer-

cial fish biomass in most of the studied systems (Figure 5).

Mixed trophic impact versus catch or consumption When mixed trophic impacts were plotted against consumption

(for marine mammals) or catch (for fisheries), it appeared that

marine mammals consumed generally less than fisheries catch, and

that their TI was less negative than that of fisheries for the same

Table 3. Percentages of change in biomass for unfished trophic groups of prey, by different marine mammals groups, in the seven study ecosystems.

Ecosystem model Trophic groups No MM No pinnipeds No dolphins No whales No toothed whales No baleen whales

Bering Sea Predator fish - - - - - -

Forage fish 297.0 238.1 - 254.9 236.0 210.0

Cephalopods 215.9 218.3 - 16.9 0.7 17.2

Benthos 214.9 11.0 - 29.4 27.4 3.6

Plankton 1.1 0.2 - 0.4 0.2 0.1

Northern Gulf of Predator fish 218.3 218.8 - 22.2 - -

St. Lawrence Forage fish 25.1 2.4 - 22.7 - -

Cephalopods - 5.7 - - - -

Benthos 0.02 20.6 - 0.1 - -

Plankton 20.03 20.3 - 20.1 - -

Benguela Predator fish 4.9 9.8 - 2.4 - -

system Forage fish - - - - - -

Cephalopods - - - - - -

Benthos 22.9 22.3 - 20.6 - -

Plankton 26.5 25.4 - 23.1 - -

Eastern tropical Predator fish 21.9 - 21.6 - 20.4 0.03

Pacific Forage fish 20.7 - 0.1 - 20.9 0.1

Cephalopods 5.1 - 5.1 - 20.2 0.2

Benthos 0.03 - 20.02 - 20.1 0.04

Plankton 0.2 - 20.01 - 0.1 0.02

North Sea Predator fish - - - - - -

Forage fish - - - - - -

Cephalopods - - - - - -

Benthos 20.1 20.1 - - - -

Plankton 20.1 20.1 - - - -

Gulf of Predator fish - - - - - -

Thailand Forage fish - - - - - -

Cephalopods 22.1 - - - - -

Benthos 0.2 - - - - -

Plankton 0.1 - - - - -

Strait of Georgia Predator fish 14.1 14.4 - - 23.7 -

Forage fish 5.4 2.4 - - 2.3 -

Cephalopods 7.4 5.7 - - 1.3 -

Benthos 20.7 20.6 - - 20.1 -

Plankton 20.1 20.3 - - 0.1 -

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consumption or catch level (Figure 6). Moreover, the overall mixed

trophic impacts of the marine mammals on the whole ecosystem

became less negative with increasing consumption. This was a

rather surprising result, to be discussed further below.

Discussion

The trophic impact of marine mammals on food webs is

generally seen as a direct relationship between the predators and

their prey. Many studies [59–62] have addressed the question of

the trophic role of top predators without taking into account the

indirect trophic effects that they can have on their prey. The

results presented here suggest that marine mammals can have

important indirect effects on trophic structure. Therefore, our

analysis offers a new perspective on the function of these predators

in marine food webs, and their interaction with fisheries. This

simulation modeling exercise proved to be a very informative

aspect of our study, because it allowed us to capture the dynamic

behavior of the system and the way in which trophic interactions

might reconfigure when marine mammals are removed from these

ecosystems.

We clearly see from results presented above that a change in

marine mammal biomass can lead to important alterations in the

structure of the ecosystem. In a time where marine ecosystems are

overexploited [63–64], polluted [65–67] and subject to climate

change [68], improving our ability to understand ecological

Table 4. Percentages of change in biomass for commercially important trophic groups of prey, by different marine mammals groups, in the seven study ecosystems.

Ecosystem model Trophic groups No MM No pinnipeds No dolphins No whales No toothed whales

No baleen whales

Bering Sea Predator fish 160.2 39.0 - 18.5 13.3 4.1

Forage fish 221.0 233.6 - 248.4 245.6 0.5

Cephalopods - - - - - -

Benthos 53.1 15.4 - 38.0 35.4 23.9

Plankton - - - - - -

Gulf of St. Predator fish 19.7 8.3 - 6.7 - -

Lawrence Forage fish 4.2 0.7 - 223.67 - -

Cephalopods - - - - - -

Benthos 0.01 20.1 - 0.1 - -

Plankton 29.0 26.5 - 23.9 - -

Benguela Predator fish 28.9 27.1 - 25.1 - -

Forage fish 24.5 21.5 - 11.4 - -

Cephalopods 28.7 211.1 - 215.4 - -

Benthos - - - - - -

Plankton - - - - - -

Eastern tropical Predator fish 8.9 - 1.5 - 7.1 0.2

Pacific Forage fish - - - - - -

Cephalopods - - - - - -

Benthos - - - - - -

Plankton - - - - - -

North Sea Predator fish 2.0 2.0 - - - -

Forage fish 1.5 1.5 - - - -

Cephalopods - - - - - -

Benthos - - - - - -

Plankton - - - - - -

Gulf of Predator fish 90.1 - - - - -

Thailand Forage fish 181.2 - - - - -

Cephalopods 74.1 - - - - -

Benthos 3.1 - - - - -

Plankton 218.6 - - - - -

Strait of Georgia Predator fish 27.5 26.0 - - 22.2 -

Forage fish - - - - - -

Cephalopods - - - - - -

Benthos - - - - - -

Plankton - - - - - -

doi:10.1371/journal.pone.0043966.t004

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processes involving marine mammals and fisheries becomes

crucial.

Strengths and weaknesses of the modeling approach Studying marine mammals – fisheries interactions through a

modelling approach can enhance our understanding of effect of

relationships that would otherwise be very difficult to study. Our

approach allowed to compare different ecosystems constructed

using a common EwE framework. The level of detail included in

the Ecopath model structure and equations is a real asset and

represent a rigorous analytical framework [69].

There is a general, background controversy about appropriate

levels of model complexity for the management of marine

resources in the context of marine mammals – fisheries

interactions [10,69–70]. While single-species approaches to

modeling fish stocks are more or less bound to conclude that

marine mammals are detrimental to the stocks, because such

models cannot incorporate the effects of indirect interactions,

more complex multi-species models (which potentially can capture

the behavior of the whole system) are more difficult to

parameterize; also, EwE depends greatly on assumptions and

parameter estimateswhich often cannot be rigorously tested by

comparing with data.

Our results and conclusions are the product of the quality of

data sources, assumptions and results of the seven EwE models

that were used for this study. The level of aggregation, for

example, was different from one model to another, depending on

the original authors’ choices, and the context or ecological

Figure 5. Total percentage of increase in the biomass of commercially important fishes when removing different groups of marine mammals. Boxes represent the lower 25% quartile up to the higher 75% quartile, while lines represent the smallest and the largest observations. doi:10.1371/journal.pone.0043966.g005

Figure 6. Total consumption by marine mammals (black dots) or total catch by fisheries (open dots) versus their respective overall mixed trophic impact for each studied ecosystem. Density ellipses represent the 90% confidence intervals. doi:10.1371/journal.pone.0043966.g006

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question each model was built for. These differences in aggrega-

tion could lead to different prediction in dynamic models [71], and

could be problematic for global comparisons. We did not re-

aggregate the models but kept them with the same structure they

had in their published version, mainly focusing on the fact that

they covered marine mammal groups. This was therefore

important to select the models that had the highest quality of

data, and that showed a high accuracy in projecting biomass

trends over time (i.e. they were fitted to time series in Ecosim).

Another potential issue with the way EwE models generally are

constructed is that there is no possibility to discriminate between

trophic levels that represent juveniles of larger fish or species that

are truly occupying this trophic level at adult stage. Although this

can be partly addressed with multi-stanza categorizations in Ecosim

[34], most of the groups do not feature ontogenetic differences in

the dynamics and diet. However, most of the marine mammals’

diets used here are detailed to the species level, not often to the life

stage or size of each prey. When diet information is entered in a

non multi-stanza Ecopath model, a prey species, even juvenile, will

be entered in the diet composition at the trophic level where the

whole group (i.e., adult species) is. The groupings in Ecopath are

done like this because information is based on adult diet. The

juveniles are thus assumed to have the same diets than the adults,

and their trophic levels represent the ‘potential trophic level’ they

can reach at adult stage.

Some authors have warned modellers that caution must be

taken in applying EwE models to marine mammal populations,

because their life history is very different from most fish [69].

However here, the simulations we performed consisted in

removing all marine mammals, and thus releasing their predation

on other trophic groups in the ecosystem. The temporal variation

of marine mammals’ abundance itself was not addressed here (the

simulated scenarios always presented how the system would react

to the extirpation of marine mammal species, not with the possible

causes and modalities of such extirpation). In Ecosim runs with

original fishing effort (where marine mammals are present in

ecosystems), we assume the vulnerabilities and the ecological

reliability of each model is representative of the species dynamics

and life cycles. The marine mammals groups present in the models

are assumed to have realistic ecological parameters. However, the

analysis done with these seven Ecopath models did not include any

environmental effects that may affect ecosystem dynamics. We

thus assumed that everything was explained by fisheries impact

and species interactions, which is definitely not the case [72].

There is indeed strong evidence that climate change, for example,

has an important impact on the availability of marine mammals’

prey [73], as well as on their distribution and abundance [74–75].

One shortcoming of our approach is that we grouped all marine

mammals together instead of analyzing pinnipeds, toothed whales,

and baleen whales separately. Doing so, we masked the major

differences in their feeding ecology. Also, analyzing marine

mammals as a whole group could not show what effects their

relative abundance have on the trophic impacts. The relative

proportions of different marine mammal species would also affect

the trophic level. For example, a large biomass of baleen whales,

which would mainly consume krill, would significantly lower our

estimate of trophic level of consumption. However, since we used

the structure of the models directly as they were constructed, we

could not separate these effects.

The calculated overlap index has the disadvantage of repre-

senting very large categories of species. Aggregation into large

functional groups does not well represent the dynamics of the

ecosystem. Thus, while the overlap index represents a good way to

obtain a global and simple representation of the interaction

between fisheries and marine mammals, the in-depth analysis of

the structure of ecosystems remains crucial. The overlap index

calculated at the species level showed that in the case of the North

Sea, this can lead to opposite conclusions. Finally, the fact that the

overlap index was calculated for marine mammals as a combined

group presents, once again, a difficulty. Indeed, as most overlap

with fisheries occurs among pinnipeds and dolphins, our estimates

of the global overlap between fisheries and marine mammals may

be underestimated.

The simulations are exploratory and represent extreme

scenarios (the complete eradication of marine mammals). We

did not explore any alternative or intermediate scenario.

Consequently these last results should not be perceived as

management strategies in any way.

Resource overlap and trophic levels On a global scale, most food consumed by marine mammals

consists of prey types that are not the main target of fisheries, and

whales seem to consume most of their food in areas where

commercial vessels do not fish [43]. In areas where competition

between marine mammals and fisheries is evident (identified as

hotspots of resource overlap by Kaschner and Pauly [43]), our

results show that the resource overlap is indeed higher than the

global average presented in Kaschner and Pauly [43]. However,

most overlap appears to occur between fisheries and larger, deep-

diving toothed whales [43], so when marine mammals are

analyzed overall, their overlap is not as strong as may be expected.

Depending on the ecosystem, the overlap between marine

mammals and fisheries index involves different food types. In the

North Sea, the Benguela, and the Strait of Georgia systems,

marine mammals and fisheries compete mainly for the ‘miscella-

neous fish’. This group includes demersal, benthic, benthopelagic

and bathydemersal fish that are less than 150 cm, and pelagic fish

that are between 60 cm and 150 cm [76]. For the purpose of this

analysis, this prey group is clearly over-aggregated; and it is

necessary to look at the composition of the ‘miscellaneous fish’

group in different ecosystems. In the North Sea, the Benguela and

the Strait of Georgia ecosystems, there were important fisheries for

larger fish [77–79], and the marine mammal species in these

ecosystems are higher trophic-level predators, who mostly feed on

these large fish [77–78,80]. These ecosystems are quite different in

terms of structure from the Gulf of St. Lawrence, where the

intense fishing activity in the 1980s has lead to the depletion of

most groundfish stocks, leaving mainly smaller planktivorous fish

and crustaceans for fisheries and marine mammals [32,81].

Consequently, in this ecosystem, small pelagics are the main

overlapping resource. In the Gulf of Thailand, benthic inverte-

brates and miscellaneous fish are the food types that are most

overlapping. Here again, the major development of trawl fisheries

in the 1960s has lead to a shift to lower trophic levels such as ‘trash

fish’ and shrimps [82], and most marine mammals are dolphins

and whales that mainly eat smaller fish [83]. There may have been

a time when fisheries and marine mammals did not overlap much

in terms of food resources, but now that fisheries have moved

down the food web [63], the target food types might have become

very similar. Finally, in the eastern tropical Pacific Ocean, where

the resource overlap is the lowest, there is not much competition

between fisheries and marine mammal. Fisheries target mainly

miscellaneous fish and large species such as tuna, and marine

mammals feed mostly on small squids, mesopelagics and small

pelagic fish. The number of trophic links in the ecosystem also has

an effect on the resource overlap between marine mammal and

fisheries. Indeed, food webs with lower connectance (less trophic

links) tend to have higher overlap values.

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Some ecosystems show major overlap between marine mam-

mals and fisheries when analyzed by food types: the North Sea,

Benguela and Gulf of Thailand most clearly. When the same

analysis is done per trophic group (using the complete structure of

the catch and the consumption matrix of marine mammals), the

overlap index is reduced, but most ecosystems showing major

overlap between marine mammals and fisheries remain the same.

However, in the case of the North Sea, the overlap index

calculated per trophic group is very low compared to the index

calculated by food type, suggesting that there could be no overlap

at the species level. However, diet studies on grey seals [84] show

that sandeels, gadoids and other flatfish (targeted by fisheries) are

important part of the diet. Grellier and Hammond [85] also

showed that applying some digestion correction factors on grey

seals diet in the North Sea reveal that some of its prey might in fact

be similar to what is taken by the fisheries. This reduced overlap

when we look at trophic group caught rather than food types

might indicate that what seems to be similar in terms of type of fish

caught by fisheries and eaten by marine mammals might in fact,

when looked at it more specifically, be different species of fish.

While EwE is suited to indicate general ecosystem properties, it is

important to look at the species-specific results to have a clearer

portrait of the situation.

Even at the trophic group level, the way the aggregations were

done by the different authors who constructed the models seem to

be important for our conclusions. Indeed, when fish species are

aggregated onto trophic groups (i.e., large demersal feeders in the

Gulf of St. Lawrence), chances are that even if this covers a group

of species that are eaten by marine mammals and caught by

fisheries, these could represent different fish species. Our study

cannot address that level of detail, but this is definitely worth

investigating. The real question in fisheries management is ‘‘are

marine mammals stealing our fish?’’. To this, our study provides

part of an answer, showing that marine mammals and fisheries do

not have the same targets. And the closer we look at aggregation

levels, the clearer it gets that they target different species of fish.

Overall, landings from global fisheries are shifting gradually

from large piscivorous fish toward smaller invertebrates and

planktivorous fish [63]. Our results further show that overall the

trophic level of marine mammals prey is lower than the trophic

level of the catch (2.88 versus 3.42). Thus, as fisheries continue to

move further down in terms of the trophic level of species caught,

the competition for food resources with marine mammals may

become more important. In ecosystems such as the eastern tropical

Pacific where the mean trophic level of the catch still is high, the

overlap with marine mammals is negligible. Interestingly, in the

Strait of Georgia the marine mammals’ consume prey at a higher

trophic level than is caught by the fisheries. This is because of

transient killer whales, which mainly feed on pinnipeds, at a very

high trophic level.

Lately, some studies have stressed that whales globally consume

3 to 5 times more marine fish and invertebrates annually than is

fished for direct human consumption or for reduction into fish

meal and oil [86]. This situation, it is alleged, is not ‘‘in balance’’

with the world’s increasing need for a stable food supply. Such

arguments are used extensively to justify whaling activity, as it is

shown in this quote by Mr. Masayuki Komatsu, formerly the

executive director of the Japanese Marine Fisheries Research and

Development Department, to BBC on ‘‘the forces that drive

Japanese whaling’’, 15 June 2006: ‘‘Whale [are] abundant. The number

of fish is falling while the number of whales is rising. Surely, the rapid increase

in the whale population influences the level of fish stocks? We need to know

more about it’’.

Our results show that there is no clear and direct relationship

between marine mammals’ predation and the potential fish catch

in the world’s oceans. Many whales do eat fish, but the species that

they eat are not necessarily targeted by fisheries. In fact the global

overlap of food resources, representing the main ‘hotspots’ of

competition between marine mammals and fisheries [43], is

relatively low. Moreover, as the simulation results showed, it is not

that clear whether the extirpation of marine mammals in

ecosystems would even increase the biomass of the fish targeted

by most fisheries.

Primary production required to sustain marine mammals and fisheries In the ecosystems studied, the primary production required to

sustain marine mammals represents an average of 9.7% of total

primary production, less than half the PPR to sustain fisheries

catch (20.1%). The latter value represents nearly three times the

estimate by Pauly and Christensen [87] for global fisheries, as our

analysis focuses on zones where fishing activity is intense.

In most ecosystems, PPR for marine mammals is lower than

PPR for the catch, excepted in the eastern tropical Pacific Ocean.

This model represents a very large area, and information about

marine mammals (biomass, consumption rates, diet, production,

etc.) is applied directly on the populations known to be within this

area, while fisheries’ effects might be more ‘diluted’ and less

important in high sea.

The highest PPR for fisheries catch occurs in the North Sea

(50%) and in the Eastern Bering Sea, (54%). PPR required by

marine mammals is also the highest in the Bering Sea, followed by

the eastern tropical Pacific. At the opposite end of the spectrum,

the Benguela ecosystem, with the lowest PPR values for marine

mammals as well as fisheries, is known to be a very productive

ecosystem, due to the seasonal, wind-driven upwelling, and hence

PPR is low [88].

Comparing the mixed trophic impact of different marine mammals types (seals, toothed whales, small cetaceans, baleen whales) While there is a growing concern about the potential impact of

marine mammal populations on fisheries catches [11,15,43,86,89],

our results show that the highest overlap occurs between fisheries

and pinnipeds or dolphins. Whales, especially baleen whales, have

the lowest impact on the ecosystem, and reducing their population

would not benefit fisheries in any way. Even if it is known that

baleen whales do eat fish in some areas [90–92], their impact on

the ecosystem is still minimal, and they don’t seem to be a threat to

fisheries, even in high overlap areas.

Comparing the mixed trophic impact of marine mammals and fisheries The effect of marine mammals on their prey and consequently

on available resources for fisheries is not only a direct predator-

prey relationship. Rather their effect is also indirect, for example

through feeding both on a prey and the competitors of the prey.

Even if negative for all studied ecosystems, the overall trophic

impact of marine mammals on the different trophic groups of the

ecosystem was always less strong than that of fisheries, except in

the eastern tropical Pacific Ocean where fisheries target mainly

large tunas (important predators of many trophic groups in the

ecosystem), while marine mammals feed on a larger array of

smaller prey [93].

For marine mammals, there is a paradoxical trend suggesting

that the more they consume, the less they tend to reduce overall

Would Culling Marine Mammals Benefit Fisheries?

PLOS ONE | www.plosone.org 15 September 2012 | Volume 7 | Issue 9 | e43966

biomass. This is possible due to the fact that if marine mammals

have to increase their consumption, they will feed on a wider array

of prey and induce beneficial predation. In contrast, the mixed

trophic impact of fisheries on the entire ecosystem is always

strongly negative.

What if there were no marine mammals? The mixed trophic impact routine of EwE provides a first

overview of the negative or positive impacts that marine mammals

have in the systems when they are at equilibrium, and considering

indirect effects. This represents a first step in understanding their

trophic role. The second step is to explore if these effects are

creating any reconfiguration in terms of structure in the long term,

if marine mammals are removed. When the extirpation of marine

mammals was simulated, the biomass of other species in the food

web also changed. In some ecosystems, commercially important

species increased significantly after the eradication of marine

mammals, (e.g., halibut and large pelagics in the Gulf of St.

Lawrence, tuna species in the eastern tropical Pacific, tuna and

pelagic species in the Gulf of Thailand, and cod and plaice in the

North Sea). However, when all commercial species were

considered, there was no obvious benefit for the fisheries. Indeed,

total biomass, with no marine mammals in the ecosystem,

remained generally and surprisingly similar or even decreased

(as it is the case with the Eastern Bering Sea and the Gulf of St.

Lawrence). Indeed, the extirpation of marine mammals may lead

to reduced abundances of commercial important fish in some

ecosystems. Cape hake, sardine, redeye in the Benguela upwelling,

and herring in the North Sea and in the Strait of Georgia

decreased when marine mammals were removed from these

systems. In the case of the Gulf of Thailand, the Plectorhynchidae

group became totally depleted when marine mammals were

absent. On the other hand, when species or groups increased as a

result of the extirpation of marine mammals in the ecosystem,

these species or groups were not necessarily the most important

commercially (deep-water fish, jellyfish and cephalopods in the

Eastern Bering Sea; cephalopods, juvenile pelagics, or juvenile

carangids (jacks) in the Gulf of Thailand). Finally, when

commercially important species increased following the extirpation

of marine mammals, it was not necessarily a stable equilibrium

[94]. There might be more fish to catch, but once overfished, these

ecosystems could become unstable and at risk of severe losses in

biodiversity.

In certain areas, (e.g., in Eastern Canada), there has been a

heated debate on culling marine mammals in an attempt to

rebuild stocks of once commercially important fish species, notably

of cod [95–96]. In that particular case, at least for the Gulf of St.

Lawrence ecosystem, our results suggested that culling of marine

mammals would not have led to recovery of the stocks of cod, nor

otherwise benefited the commercial fishery. This corroborates the

findings of Trzcinski et al. [97], who suggested that even the

complete removal of grey seal predation in the eastern Scotian

Shelf (Northwest Atlantic) would not assure the recovery of the cod

population, given the high levels of other sources of natural

mortality.

Are marine mammals a threat to fisheries? Even in areas where there could be a competition between

marine mammals and fisheries, the problem is mostly due to

human use of marine resources. Over time, we have exploited and

depleted the best marine resources, and now we are turning to

what is left. In the process, we have moved from a zone of ‘no

conflict’ to an area of higher overlap, as result of changing

fisheries, and the collapse of overexploited large predatory fish.

At the International Whaling Commission, it has been proposed

that baleen whales were a threat to fisheries, and that they should

be culled. Regrettably, in this debate, it is difficult to assess

whether it is based on any scientific evidence, considering the lack

of evidence for existing large-scale competition between whales

and fisheries [43], the well documented fact that the world’s

oceans increasingly are overexploited [63,98–102], and the

unpredictable consequences of culling [103–105]. Moreover, the

areas where this argument is used the most are the Caribbean and

Northwest Africa (L. Morissette, unpublished data), two regions

where baleen whales are breeding, and where they reduce their

consumption rate to about 10% of what it is in their high latitude

feeding areas [106].

Conclusions

Our analysis identified that marine mammals are important top

predators in marine ecosystems, and that they play an important

role in structuring the trophic relationships within food webs. Our

results showed that even in hotspots of competition between

marine mammals and fisheries, the overlap for food resources was

lower than earlier presumed. Our results confirmed the findings of

Kaschner and Pauly [43], who suggested that even the complete

eradication of all marine mammals, from all oceans, would likely

not increase fisheries catches. Hence, large-scale culling, as

advocated in various Japanese studies (see, e.g., [86]) would

probably not increase fisheries catches.

This study has focused on the top-down influences of marine

mammals and fisheries on the fish species in different ecosystems.

Although ‘bottom-up’ changes were not investigated here, their

effects might just be additive and alter even more the structure of

ecosystems. This is particularly true in the actual context of climate

change, which can affect the productivity of the world’s oceans

[107–108]. There is still much debate about this idea and it will be

important to find different ways of addressing this issue. The

analysis presented here provided an insight into the problem, but

further work on this needs to be pursued.

Supporting Information

Table S1 Trophic groups of the seven ecosystem models used in

this study and how they fall into food types categories defined by

Pauly et al. [75]: Non-marine mammal food (NM), miscellaneous

fishes (MF), small pelagic fishes (SP), benthic invertebrates (BI),

small squids (SS), large squids (LS), mesopelagic fishes (MP) large

zooplankton (LZ), higher vertebrates (HV). The mixed trophic

impact (MTI) of marine mammals and fisheries is given for each

impacted trophic group.

(DOCX)

Acknowledgments

This research was carried out as a contribution to the doctoral thesis of the

first author at the Fisheries Centre of the University of British Columbia.

Such a global approach would not have been possible without the precious

collaboration of all the colleagues who made their model and data available

for the analyses, and the Ecopath Consortium for development of the

modeling techniques used.

Author Contributions

Conceived and designed the experiments: LM VC DP. Performed the

experiments: LM. Analyzed the data: LM. Contributed reagents/

materials/analysis tools: LM VC DP. Wrote the paper: LM.

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Would Culling Marine Mammals Benefit Fisheries?

PLOS ONE | www.plosone.org 18 September 2012 | Volume 7 | Issue 9 | e43966

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