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The possible impacts of the European Commission’s proposed North Sea Multi-Annual Plan are evaluated in terms of its likely outcomes to achieve management objectives for fishing pressure, species’ biomass, fishery yield, the landed value of key species and ecosystem objectives. The method applies management strategy evaluation procedures that employ an ecosystem model of the North Sea and its fisheries as the operating model. Taking five key dimensions of the proposed plan, it identifies those areas that are key to its successful performance. Overwhelmingly, choices in the options for the implementation of regulatory measures on discarding practices outweigh the effects of options related to fishing within ranges associated with ‘pretty good yield’, the way that biomass conservation safeguard mechanisms are applied and the timeframe for achieving fishing mortality targets. The impact of safeguard options and ranges in fishing mortality become important only when stock biomass is close to its reference points. The fifth dimension–taking into account wider conservation and ecosystem objectives—reveals that discard policy has a big impact on conservation species, but also that the type of harvest control rule can play an important role in limiting risks to stocks by ‘applying the brakes’ early. The consequences to fisheries however is heightened risk to their viability, thus exposing the sustainability trade-offs faced with balancing societal pressures for blue growth and enhanced conservation. It also reveals the wider ecosystem impacts that emphasise the connectivity between the demersal and pelagic realms, and thus, the importance of not treating the demersal NSMAP in isolation from other management plans. When stocks are below their biomass reference points, low F strategies lead to better long term economic performance, but for stocks consistently above biomass reference points, high F strategies lead to higher long term value. Nephrops and whiting often show contradictory responses to the strategies because changes in their predators abundance affects their abundance and success of their fisheries.
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RESEARCH ARTICLE
Evaluating the fishery and ecological
consequences of the proposed North Sea
multi-annual plan
Steven Mackinson
1¤
*, Mark Platts
2
, Clement Garcia
1
, Christopher Lynam
1
1Centre for Environment, Fisheries and Aquaculture Science, Lowestoft, Suffolk, United Kingdom, 2Ardent
Data Analytics, Sheffield, South Yorkshire, United Kingdom
These authors contributed equally to this work.
¤Current address: Scottish Pelagic Fishermen’s Association, Heritage House, Fraserburgh, Aberdeenshire,
United Kingdom.
‡ SM and CL are joint senior authors.
*steve.mackinson@scottishpelagic.co.uk
Abstract
The possible impacts of the European Commission’s proposed North Sea Multi-Annual Plan
are evaluated in terms of its likely outcomes to achieve management objectives for fishing
pressure, species’ biomass, fishery yield, the landed value of key species and ecosystem
objectives. The method applies management strategy evaluation procedures that employ
an ecosystem model of the North Sea and its fisheries as the operating model. Taking five
key dimensions of the proposed plan, it identifies those areas that are key to its successful
performance. Overwhelmingly, choices in the options for the implementation of regulatory
measures on discarding practices outweigh the effects of options related to fishing within
ranges associated with ‘pretty good yield’, the way that biomass conservation safeguard
mechanisms are applied and the timeframe for achieving fishing mortality targets. The
impact of safeguard options and ranges in fishing mortality become important only when
stock biomass is close to its reference points. The fifth dimension–taking into account wider
conservation and ecosystem objectives—reveals that discard policy has a big impact on
conservation species, but also that the type of harvest control rule can play an important role
in limiting risks to stocks by ‘applying the brakes’ early. The consequences to fisheries how-
ever is heightened risk to their viability, thus exposing the sustainability trade-offs faced with
balancing societal pressures for blue growth and enhanced conservation. It also reveals the
wider ecosystem impacts that emphasise the connectivity between the demersal and
pelagic realms, and thus, the importance of not treating the demersal NSMAP in isolation
from other management plans. When stocks are below their biomass reference points, low
F strategies lead to better long term economic performance, but for stocks consistently
above biomass reference points, high F strategies lead to higher long term value. Nephrops
and whiting often show contradictory responses to the strategies because changes in their
predators abundance affects their abundance and success of their fisheries.
PLOS ONE | https://doi.org/10.1371/journal.pone.0190015 January 2, 2018 1 / 23
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OPEN ACCESS
Citation: Mackinson S, Platts M, Garcia C, Lynam
C (2018) Evaluating the fishery and ecological
consequences of the proposed North Sea multi-
annual plan. PLoS ONE 13(1): e0190015. https://
doi.org/10.1371/journal.pone.0190015
Editor: Andrea Belgrano, Sveriges
lantbruksuniversitet, SWEDEN
Received: September 27, 2017
Accepted: December 6, 2017
Published: January 2, 2018
Copyright: ©2018 Mackinson 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.
Data Availability Statement: Data for the study are
available via the internet via CefasDataHub (http://
data.cefas.co.uk/#/View/18782). Note that the
results are in excess of 50 gigabytes.
Funding: The work was supported through funding
from UK Department of Food and Rural Affairs
project title: From Physics to fisheries (“Fizzyfish”
M1228) and GAP2 project EC FP7 Grant
Agreement 266544 to Steven Mackinson. The
funders had no role in study design, data collection
and analysis, decision to publish, or preparation of
the manuscript.
Introduction
Without additional legislation, the Basic Regulation of Europe’s Common Fisheries Policy
(CFP) [1] could lead to under-utilisation of quota in the North Sea mixed fisheries if the imple-
mentation of the landing obligation lead to choke species (i.e. species whose catches quickly
exceed available quota), halting fishing activity as a result. Faced with the risk of dis-agreeable
and unworkable management that this implies, the European Commission (EC) has taken the
initiative to propose a mixed fisheries multi-annual managemement plan for demersal species
in the North Sea [2]; the objective being to acheive sustainable exploitation of principal demer-
sal stocks by exploiting them according to the principles of maximum sustainable yield (CFP
Article 2.2) and the ecosystem approach to fisheries management (CFP Article 2.3). The plan
is also intended to facilitate the introduction of the landing obligation (CFP Article 15)
through measures to eliminate unwanted discarding of commercial stocks. Solving the choke
species problem is implicit in this objective.
We evaluated the performance of alternative strategies for implementation of the proposed
North Sea multi-annual plan (NSMAP) using a multi-species, multi-fleet ecosystem model.
Following the definitions in the proposed NSMAP, the alternative strategies were specified
according to the ranges of F
msy
(i.e. fishing rates associated with ‘pretty good yields’; [3,4,5,6],
safeguard mechanisms, discard policy and application of F
msy
for other assessed species in the
North Sea—in accordance with MSY policy, Article 2.2 of the CFP.
The performance of the strategies was measured by their ability to meet regulatory targets
for sustainable exploitation (F
msy
, total allowable catches, eliminating discards), their effect on
resource conservation targets (stock biomass relative to biological reference points), their eco-
nomic performance (fisheries value) and their risk to conservation species and ecosystem
effects (Good Environmental Status (GES) indicators of food-webs). Consideration of these
multiple objectives classifies the evaluation as taking a postmodern view of sustainability [7],
aiming to contribute to the progress in developing more comprehensive evaluations of man-
agement plans (Sensu Trenkel et al. [8]).
We used a bespoke routine developed inside the ecosystem modelling framework Ecopath
with Ecosim (EwE) [9,10,11], specifically designed to assess the robustness of management
strategies to the uncertainties in model predictions arising from model error, observation
error, and implementation error [12]. Core to the routine is the Management Strategy Evalua-
tion (MSE) methodology [13,14,15], which addresses the need to provide decision makers
with the risks and uncertainties associated with alternative strategies, and thus identify where
trade-offs may lie. Within MSE, an operating model which represents a realisation of a biologi-
cal model for the ‘real world’ is used as the platform for testing the performance of alternative
management strategies.
The purpose of using a multi-species, multi-fleet model as the operating model in this
impact assessment exercise is to be able to simultaneously take in to account the interactions
among species and among fleets, thus making it possible to diagnose possible ecological and
fishery trade-offs resulting from both direct and indirect fishing and food-web effects. This is
particularly pertinent in light of the commitment of the CFP to implement regional sea-basin
management (Article 18) based on an ecosystem approach. Articles 9 and 10 provide the basis
for establishment of multi-annual plans; stating that they shall cover ‘. . .in the case of mixed
fisheries or where the dynamics of stocks relate to one another,fisheries exploiting several stocks
in a relevant geographical area,taking into account knowledge about the interactions between
fish stocks,fisheries and marine ecosystems’. This commitment underpins the salience of this
evaluation of the proposed multi-annual plan for mixed demersal fisheries in the North Sea.
Evaluating the North Sea multi-annual plan
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Competing interests: The authors have declared
that no competing interests exist.
Because ecology dictates that the collateral impacts of the proposed NSMAP will extend
beyond the demersal species that it is focussed upon, the wider ecosystem and fishery conse-
quences also need to be brought in to the light for decision making. Again, this is particularly
pertinent now because integration of fisheries and environmental policy is front and centre in
shaping research approaches (e.g. [16]) and delivery of integrated scientific advice in Europe
[17,18,19] and beyond. In particular, we looked at the food-web indicators relevant to deter-
mining GES [20,21] and impact on the pelagic species and fisheries as reflection of intimately
linked dynamics between the demersal and pelagic realms of the North Sea ecosystem [22,23].
Materials and methods
Process overview
The procedure of the routines used to assess the performance of the management strategies
and their robustness to uncertainties in the model predictions depicts a 2 stage process (Fig 1):
stage 1 generates multiple plausible versions of the ecosystem model by sampling distributions
of input parameters (biomass, feeding, production and consumption rates and predator-prey
interaction rates), stage 2 simulates the application of alternative management strategies—
defined by their harvest control rules and regulatory mechanisms—to each of the plausible
models generated in stage 1 for the specified period (Fig 2). Upper and lower biomass bounds
based on long term biomass trends are used to screen out the strategies whose trajectories are
Fig 1. Flow chart showing an overview of the two main stages of the plugin.
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unrealistic. Full technical details of the routines are reported in Platts and Mackinson (2017,
[12]), and the supporting information describes the key elements necessary to understand how
the alternative strategies were implemented and behave in the model.
Operating model(s)
For stage 1, the 2015 Key Run of the North Sea ecosystem model [24] was resampled to gener-
ate 1000 alternative plausible operating models for the management strategy evaluation. The
Key Run is parameterised for the period 1991–2013 using stock assessment and survey data
Fig 2. Flowchart for the evaluation of management strategies.
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from the area defined in the NSMAP. It includes 69 functional groups and 10 fishing fleets.
Fish groups subjected to stock assessment are specified at the species level, and international
fleet segments are specified according to level 2 definitions of the EU Data Collection Frame-
work. Economic data on fish prices and fleet costs from the 2015 EU Annual Economic report
[25] were included in the model to support the evaluation of economic performance based on
recent data.
While the historical simulation of the model is conditioned with the inclusion of environ-
mental time series such as temperature, it is currently not possible to include these effects in
forward simulations used in the evaluation of harvest strategies. Therefore, environmental
conditions are assumed to remain constant from 2013 onward and their effects to apply
equally to all the harvest strategies; this places the focus of the analysis on the contrast in per-
formance among them.
Species and their reference points for management and conservation
(Table A in S1 Supporting information)
The analysis centres on the demersal species in the North Sea (cod, haddock, saithe, whiting,
plaice, sole—defined as Group 1 in the NSMAP—and Nephrops—Group 2 -). We defined the
lower, middle and upper ranges of fishing mortality, and the biomass target (B
msy
) and limit
(B
lim
) values defined in Annex 1 & 2 of the proposed NSMAP as the management and conser-
vation reference points. In the case of whiting, which has undefined reference points, we used
F
lower
= 0.14, F
target (msy)
= 0.15 and F
upper
= 0.33 based on ICES (2014), and B
msy
= 250 kt, B
lim
184 kt based on Table 10.5.1 in ICES (2012, [26]). For Nephrops, we calculated an average of
the functional units in the Annexes and converted the abundance to biomass based on a mean
weight published in the International Council for Exploration of the Sea (ICES) Nephrops
working group report [27].
To fully represent the CFP objectives on implementation of MSY policy and to take account
of the fishery and ecosystem interactions that affect the proposed NSMAP, we included fishing
and conservation reference points for other assessed demersal species subject to catch limits
(Group 3, 7), as well as pelagic species (herring, mackerel, sprat, sandeels and horse-mackerel).
Finally, we included conservation reference targets for prohibited elasmobranchs (Group 6)
which were utilised in a particular set of strategies.
For species subject to catch limits but for which no reference points were available, we used
the ecosystem model to estimate internally consistent reference points that could be used to
calculate the Total Allowable Catch (TAC) and fleet quotas for each of the alternative manage-
ment strategies. Using the model to calculate the equilibrium biomass and catch associated
with fishing mortalities from zero to 5 times initial F (see [28]), we recorded F
msy
and defined
B
lim
= 20% of the unfished biomass for each species. We set F
lower
and F
upper
equal to F
msy
, and
set B
msy
equal to the next highest thousand above B
lim
. We consider this approach to be accept-
able given that the NSMAP states ‘In the absence of scientific advice on fishing mortality rates
consistent with maximum sustainable yield,fishing opportunities shall be consistent with scien-
tific advice to ensure the sustainability of the stocks in line with the precautionary approach.’
Note that a Precautionary Approach (PA) is described in the UN Fish Stocks Agreement (UN,
1995) as follows: “States shall be more cautious when information is uncertain,unreliable or
inadequate.The absence of adequate scientific information shall not be used as a reason for post-
poning or failing to take conservation and management measures.” This implies that as informa-
tion becomes increasingly limited and/or less certain, ICES advice on management will be
more conservative with respect to possible impact on the marine ecosystem [29].
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Management strategies
Alternative management strategies (Table B in S1 Supporting Information) were configured
based on different choices along the five key dimensions specified in the proposed NSMAP:
1. Contributing to the elimination of discards for species subject to catch limits
Three scenarios on discard regulation were considered. Both “strict no discarding” and
“avoiding discarding” represent no discard policies, differing only in the way they represent
two extremes among the range of possibilities of fleet responses. Continued discarding rep-
resents a scenario of discarding akin to former years. In summary the three scenarios are:
Strict no discarding. Fishing stops when the quota of the weakest stock is exhausted.
(Note: this is referred to as the minimum option under ICES mixed fisheries scenarios).
Avoiding discarding. Fisheries are able to take measures to fish more selectively,
avoiding catching any fish whose quota is exhausted while continuing to fish for
those that remain.
Continued discarding. Fishing continues until all the quotas are taken. Any fish
caught over quota are discarded. (Note: this is referred to as the maximum option
under ICES mixed fisheries scenarios).
Technical details of each of these scenarios application in the evaluation routine are
given in the supplementary material.
2. Flexibility to set the F on each species within a range
(see above and Table A in S1 Supporting Information)
For each species, ranges in the fishing mortality reference points were taken from values as
defined in Annex 1 & 2 of the proposed NSMAP. Terminology used in the modelled strate-
gies is such that F
lower
= F
low
, F
middle
= F
target
= F
msy
, and F
upper
= F
high
. (Fig 3). The strategies
explore the contrast when the target F for all species are applied simultaneously at either
their lower, middle or upper values for the duration of the simulation. This represents a test
of the sensitivity to the effects of the minimum and maximum conditions, which is suitable
for assessing the impacts of changes in target F relative to those of other dimensions.
3. Allowing for safeguards, whereby fishing pressure is reduced if stocks fall below safe bio-
logical limits
The way safeguards are applied to control the rate of fishing mortality at given stock bio-
mass levels is called a Harvest Control Rule (HCR), or Advice Rule in ICES terminology.
Four types of HCRs that are consistent interpretations of the definitions in the proposed
NSMAP, were considered in the evaluation (Fig 4).
Type 1 is the ICES standard advice rule–where F declines linearly to zero when biomass
is below MSY B
trigger
.
Type 2 is Precautionary, easing the rate of reduction in F between MSY B
trigger
and B
lim.
The slope is initially equivalent to that in Type 1, however, at B
lim
immediate action is
taken to stop targeted fishing, with the result that F = 0 at and below B
lim
.
Type 3 is most Protective, applying the most severe reductions in F, which declines linearly
from F
msy
at MSY B
trigger
to zero at B
lim
(i.e. with a steeper slope than in Type 1 and 2).
Type 4 is considered the most Realistic, similar to Precautionary, but recognises that a
small level of residual non-target by-catch mortality may remain on a stock at B B
lim
even once those fleets targeting the stocks have been stopped from fishing.
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4. Time to achieve Fmsy
The proposed NSMAP states ‘The target fishing mortality shall be achieved as soon as possible,
and on a progressive, incremental basis by 2020 for the stocks of Groups 1 and 2.’ We
Fig 4. HCR types used in defining alternative strategies.
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Fig 3. Example of a curve showing landings (as a percentage of MSY) as a function of fishingmortality (F). The
location of F
msy
, F
lower
and F
upper
are indicated, the latter two corresponding to 95% of the peak of the median landings
curve. Units are standardised to a scale of 0–100.
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compared two options for the timing of adjusting fishing mortality to achieve F
msy
when
the current F is higher than the target F. Option 1 adjusts F in equal yearly steps to achieve
F
msy
by 2015, Option 2 adjusts F in equal yearly steps so that F
msy
is achieved by 2020.
5. Contribute to implementation of the ecosystem-based approach to fisheries manage-
ment
The proposed NSMAP has the specific objective to implement the ecosystem-based
approach to fisheries management in order to ensure that negative impacts of fishing activi-
ties on the marine ecosystem are minimised. In particular, it stresses that this should be
coherent with EU environmental legislation objectives of achieving GES by 2020 as set out
in Article 1(1) of Directive 2008/56/EC.
To consider the wider effect of the plan on biodiversity, we evaluated a strategy specifically
designed to address objectives for the conservation of protected skates and ray and we
investigated how choices in the other dimensions affected the outcomes of this strategy. In
this ‘conservation’ strategy, conservation HCRs (see supplementary material) were used to
override the setting of fishing rates on commercial stocks if the biomass of any conservation
species falls below a lower threshold, which we set at 20% of the unfished model biomass
determined from equilibrium simulations. The effect is that fishing rates on target species
become contingent upon the biomass of the conservation species.
A second conservation strategy, called ‘cod god’ uses the same principles as applied in the
skates and rays conservation strategy but puts the management of cod above all other stocks
with conservation measures on all fished species activated when cod biomass reaches its
limit reference point, B
lim
. This mimics the former cod-recovery plan where increasingly
restrictive measures were put in place as the cod stock declined. The purpose of this strategy
was to examine the impact of cod management measures on the other stocks and fisheries,
as well as to see the effect on cod recovery.
We also investigated the broader ecosystem impacts of the strategy options on food webs by
looking at their effects on GES indicators of change in the fish community.
Each strategy was simulated forward for 20 years in each of the 1000 possible operating
models of the North Sea ecosystem, and their performance measured in relation to:
The efficacy of management in terms of the contrast between the fishing mortality realized
by the management strategy versus that set by the HCR. Note that fishing mortality associ-
ated with landings (landed F) was accounted for separately from that due to discarding
(discard F). Choke species whose quota limited the effort of fleets under the strict no dis-
card option were recorded.
The biomass of the target stocks relative to their conservation reference points.
The fishery performance, measured in terms of value to the demersal fleet (Demersal
trawl and seine, beam trawlers, Nephrops trawlers), pelagic fleet and overall.
The risk to conservation species, any species in groups 3 to 7 that have conservation refer-
ence limits breached and thus require remedial action (see Article 9, p19).
The ecological impact on the marine ecosystem measured in relation to objectives for
achieving GES. In particular, performance of indicators for Descriptors D1 biodiversity
and D4 food webs were quantified.
Based on the combinations among the 5 dimensions, more than 60 different strategies were
evaluated in total, each providing results for 69 functional groups and 11 fleets—amounting to
10s of gigabytes of output. To draw out the salient features from the contrast among the 5
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dimensions and their relevance to the species and fleets in the proposed NSMAP, the analysis
below distils the results from the 10 main strategies described in Table B in S1 Supporting
information.
Results
Comparison between the five key dimensions of the proposed NSMAP strategies show over-
whelmingly that the choice of discard regulation (dimension 1) has the largest impact on the
contrast in performance among the strategies. The weakest impact is related to the time to
achieve F
msy
(dimension 4). Allowing flexibility in the range of target fishing (dimension 2)
and alternative configuration of safeguard options (dimension 3) have detectable but small
effects, the impact of which becomes more apparent when stock biomass is close to its refer-
ence points. The fifth dimension reveals that discard policy has a substantial impact on conser-
vation species and fishery sustainability. The type of harvest control rule implemented can
play an important role in limiting risks to species by ‘applying the brakes early’ but such an
approach may lead to greater risk to fishery sustainability. It also reveals the wider community
impacts that emphasise the connectivity between the demersal and pelagic realms of the
ecosystem.
1. Contributing to the elimination of discards for species subject to catch limits
For cod, only the strict no discard policy leads to the projected stock recovery above MSY
B
trigger
(Fig 5). Discard avoidance strategies are projected to maintain biomass consistently
above B
lim
(~10% risk of B <B
lim
) and on average close to MSY B
trigger
, while continued dis-
carding leads on average to a long-term decline in biomass with a high risk (>60% of
B<B
lim
). Continued discarding means that management targets for F are entirely ineffective,
because although the plots show that there is a limited risk of a landed F value being greater
than the target F (<10%), and (somewhat confusingly) this is lower than the risk of landed F>
target F under discard avoidance, when discard F is included, the total realized mortality is in
fact above the target F in almost every simulation. Looking across the other species in Fig 5,
there are other examples where the risk that landed F exceeding target F is similar under dis-
card avoidance and continued discarding. However, this risk represents the frequency of
exceptions rather than the magnitude which is always greater under continued discarding. The
exceptions arise as a consequences of representation of the uncertainties in the model
expressed as implementation errors.
Similar patterns are seen in the other species, with the exception of Nephrops and whiting
that respond in the opposite way. Here the indirect effects that emerge from the predator-prey
relationships in the ecosystem model are seen. They have an impact both on the stock status
and performance of fisheries that target them.
The highest average value to the key fleet that fishes for cod (i.e. the demersal trawl and
seine fleet) is achieved under the discard avoidance scenario because biomass and fishing
opportunities are sustained at higher levels over the long-term (Fig 6). The strict no discarding
scenario results on average in lower value because effort of the fleet becomes constrained when
cod becomes a choke species (Fig 7), denying the value of other quotas to be fulfilled. Cod are
also the primary choke species for many other fleets; with the exception of pelagic and indus-
trial trawlers for which blue whiting become the primary choke species.
Under a strict no discard policy, the choke effects of cod mean that the value of Nephrops
fisheries is reduced. In contrast, when discarding occurs, the fleet achieves its highest value, (i)
because it can uptake its quota, and (ii) because the abundance of Nephrops is higher due to a
reduction in predation on them resulting from lower cod abundance (‘predation release’).
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Fig 5. Contrast between 3 NSMAP strategies with safeguard using Realistic HCR type 4 (see Fig 4) and fishing at F
msy
by 2020 in each. Strict no
discards (red and left bar/box in each pane), discard avoidance (green and middle bar/box), discard continues (blue and right bar/box). The solid black
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Overall however, the total value of landings by all fleets in the plan is highest under the strict
no discard policy (Fig 8).
2. Flexibility to set the F on each species within a range
In comparison with the discard regulation options (Fig 5) ranges of fishing mortality have a
much lesser effect on the biomass or the risk of exceeding management targets for any of the
key target species in the plan. If discarding were to continue then even fishing continually at a
low F scenario would result in a declining trend in biomass in the majority of species in the
plan, with for example, cod falling below B
lim
during the course of the forecast (Fig 9). The rea-
son for this is that the realised F almost always exceed the target F when discarding continues.
High F strategies consistently lead to lower long-term biomass of target species with saithe fall-
ing below MSY B
trigger
in the forecast. In contrast, whiting and Nephrops attain higher bio-
masses through release from predation by depleted species, particularly cod.
line in the first column of plots shows B
lim
and dotted line MSY B
Trigger
. The plots of risk of high F show the proportion of simulations (but do not reflect
the magnitude) with landed F>the target F defined by the harvest control rule used in the strategy.
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Fig 6. Contrast in risk-reward between 3 strategies. Strict no discards (red), discard avoidance (green), discard
continues (blue). Risk by stock and reward by value to the key fleettargeting the stock in the NSMAP scenario, fishing
at F
msy
by 2020 and safeguarded by HCR Type 4 (See Fig 4). The red vertical line in each panel shows B
lim
and the
black line in MSY B
trigger
. Each small point represents an outcome for a single model parameterisation from the full set
given coloured with respect to the strategy implemented. The large squares showthe mean response averaged across
the parameter set and coloured with respect to the strategy implemented. (Key fleets: cod, haddock, whiting,
saithe = demersal trawl and seine; Nephrops = Nephrops trawls; plaice and sole = beam trawls).
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The risk of landed F >target F is less when the target F is high because the higher level is
rarely achieved. When stock biomass has a high risk of going below its reference points, long
term economic performance of the fleets is reduced, lower value being obtained because quo-
tas get reduced as fishing rates are adjusted downwards by the harvest control rule. High F
strategies reinforce this, while low F strategies lead to improved long term fisheries values as
stock size and quotas increase.
3. Allowing for safeguards
The choice of the configuration of harvest control rule types to implement safeguarding
becomes of importance only when the biomass of the species is close to its reference point. As
is the case for cod when fished at F
msy
by 2020 with discard avoidance measures included so
that the total available quota is always taken (Fig 10). For this scenario, only the Protective
HCR (Fig 3, Type 3) on cod leads to a biomass above biomass MSY B
trigger
. The ICES standard
advice rule (Fig 3, Type 1) is the least precautionary leading to the greatest risk of B <B
lim
.
4. Time to achieve Fmsy
Moving to implement F
msy
sooner rather than later in general results in faster changes in
stock biomass, but like F ranges and harvest control rule types, the effects are overshadowed by
choices in the discard policies. In the short-term, moving to F
msy
quickly requires the fishery
to forgo some catch as evidenced by the reduction in the value generated by the fishery. In the
long-term, the model converges to similar solutions.
5. Contribute to the ecosystem-based approach to fisheries
Fishing on commercial stocks also poses risks for the by-catch of species of conservation
concern such as skates and rays. The risk that these species fall to biomass levels lower than
B
lim
was reduced when an NSMAP strict no discard strategy or a ‘Cod god’ strategy was mod-
elled (Fig 11). Incorporating safeguards to the NSMAP no discard strategy, so that fishing
effort is reduced as the biomass of target stocks falls below MSY B
trigger
, can further greatly
Fig 7. Choke species in NSMAP scenario fishing at F
msy
by 2020 safeguarded by HCR Type 4 with strict no
discards (See Fig 4). Each section within a single bar shows the percentage of years in which each stock forms the
choke species (averaged across each model simulation for this single strategy).
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reduce the risk to conservation species: even a simple ICES standard advice rule Type 1 can be
effective and a Realistic HCR Type 4 can eliminate the risk of depletion of conservation species
in the model (given our approximate model generated reference points, Table A in S1 Support-
ing Information). Similarly, the risks to skate and ray biomasses can be successfully managed
down through a ‘Save the rays’ strategy. Little difference between the NSMAP strategies with
continued discarding and discard avoidance strategies was found and both can lead to higher
risk to conservation species since non-commercial species caught as by-catch may continue to
be discarded unless they are explicitly defined with a zero TAC.
As the risk to conservation species is managed down so the risk that the fishery becomes
unsustainable goes up (Fig 11). For example, when continued discarding and discard avoid-
ance policies are implemented in the NSMAP strategy with a Realistic HCR or strictly no dis-
cards are allowed without an advice rule, there is little risk to the fishery. However, if the
strictly no discard policy is included in the ‘Cod god’ or ‘Save the rays’ conservation strategies
using a Realistic HCR, then the risk that the fishery effort reaches <1% of 1990 values is
greater (>25%) and particularly so for the conservation HCRs (>50%). A trade-off can be
found between conservation and fishery sustainability if the NSMAP strictly no discard, Cod
god or Save the rays strategies are coupled with an ICES standard rule (<1% risk to skates and
rays and <5% risk to the fishery). In this instance, the Realistic control rule with a conservation
Fig 8. Contrast in risk by stock and total reward (combined value of the species in the NSMAP across all fleets)
between 3 strategies. Strict no discards (red), discard avoidance (green), discard continues (blue). The red vertical line
in each pane shows B
lim
and the black line in MSY B
Trigger
. Each small point represents an outcome for a single
parameterisation from the full set coloured by strategy implemented. The large squares show the mean response
averaged across parameterisations and coloured by strategy implemented.
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Fig 9. Contrast between fishing effect of ranges in fishing mortality. Low F (red), high F (green) and F
msy
(blue) implemented with
NSMAP strategies with safeguard and using realistic harvest control rule type 4 (see Fig 4) and fishing at target levels by 2020 with
discarding continuing. The solid black line in the first column of plots shows B
lim
and the dotted line MSY B
trigger
.
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species (cod or skates and rays) leads to a step change from fishing at F
msy
to near zero fishing
at B
lim
with the net effect that the main fleets catching species of conservation concern are
reduced to very low effort from which it can take many years for the fishery to recover. A less
protective rule such as the ICES standard HCR more gradually reduces fishing effort, which
although slightly risker leads typically to biomass of species above B
lim
.
Recent management has contributed to an increase in biomass of demersal species such
that the ratio of demersal to pelagic species biomass in the ecosystem has increased (Fig 12,
panel (a), black line). Interestingly, the effect of a strict no discards scenario appears to be
greater for pelagic species (including herring, mackerel and horse mackerel), the proportion of
demersal species relative to pelagic species increasing less than when discarding continues.
Despite this, the proportion of large bodied demersal fish species (cod, haddock, plaice, saithe,
monkfish, spurdog, hake, catfish (wolf-fish), turbot, brill, thornback and spotted ray) is great-
est under a strict no discards scenario (Fig 12B) since this indicator is driven strongly by the
biomass of the large piscivorous species cod. Among the additional species of interest, sprat,
blue whiting and megrim are all depressed when discards are strictly forbidden, while hake,
herring, Horse mackerel, mackerel, monkfish, skate and Cuckoo ray, Thornback and spotted
ray all increase in biomass (Fig 13). Possible changes in the community structure of the North
Sea reveal again the impact of the strict no discard scenario (Fig 14). The biomasses of most
trophic guilds increase under the no discard scenario, leading to an increase in biomass over-
all, but a relative decrease in bentho-piscivores (dominated by Norway pout an important prey
species for larger piscivores). Finally, a comparison of the risks and reward to species in the
proposed NSMAP versus a broader ecosystem perspective that considers impacts on all
assessed species, shows similar scale impacts and that while discard avoidance reduced the risk
to the number of stock where B<Blim, they maintain a positive reward to long term catches
(Fig 15).
Discussion
Fully implemented, the Basic Regulation of the CFP means it is illegal (under the Landing
Obligation) to discard any catches in excess of quota, so fishing vessels would have to stop fish-
ing early in the year once their quota for the most limiting stock becomes exhausted. However,
various mechanisms serve to soften this hard implementation and allow them continue fishing
such as de minimis and high survivability exemptions, inter-species quota flexibility and quota
swapping. There is also evidence that the discard ban may be difficult to enforce [30,31]. Our
comparison between the strict no discard and discard avoidance modelled strategies represent
different degrees of implementation or fleet response to the landing obligation, or the effects of
its staged implementation from 2016 to 2019.
Fig 10. Modelled effect of HCR types on cod metrics for a scenario implementing the NSMAP with fishing at F
msy
by 2020 and incorporating discard
avoidance.
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Overwhelmingly, results of our evaluation of the contrasting impacts of 5 key dimensions
of the proposed NSMAP show that the choice of discard implementation option has the largest
effect on the risk to commercial species biomass and reward to fisheries. Flexibility to set
ranges in F and the way in which safeguards are applied have limited impact, being most effec-
tive at times when stock biomass is close to conservation reference values. Although some
Fig 11. Contrast in risk to conservation species biomass (top) and sustainability of the principalfishery (bottom). Conservation species—common skate and
cuckoo ray). Principal fishery—demersal trawl and seine fleet. Low effort is defined as 10% of fishing effort in 1990) between 9 strategies each fishing at F
msy
by 2020.
The contrast between bars 1, 2 and 7 shows the change in risk due to change in discard regulationoptions only as each is safeguarded by HCR Type 4. Bars 3 and 4
contrast the change in risk when the safeguard as applied in column 7, is either removed or altered to HCR Type 1 (See Fig 4). Bars 5 and 8 demonstrate the effect of a
management strategy focused on reducing risk to the depletion of cod (‘Cod god’ strategy, see text, using HCR Type 1 and 4 respectively). Bars 6 and 8 demonstrate the
effect of a management strategy focused on reducing risk to the depletion of skates and rays (‘Save the rays’ scenarios, see text, using HCR Type 1 and 4 respectively).
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yield to demersal fisheries would be lost in the short-term, results also indicate that a strict pol-
icy on stopping the discarding of over-quota fish should lead to further recovery of exploited
stocks and sustainable fisheries in the long-term, with the total value landed by all fisheries
combined increasing (Fig 8) despite decreases in total tonnage caught (Fig 15). Positive bene-
fits are also seen to occur in the discard avoidance strategies, which perhaps reflect more
closely the reality of discard policy implementation given the various mechanisms that aim to
keep the fleet operational while minimising discards. In particular, results indicate that the risk
of stock conservation limits being compromised is typically lower than when discarding con-
tinues, while the fisheries value—and thus their sustainability—is always higher than under
strict no discards, and often higher or on a par with continued discard scenarios (Figs 5,6and
15).
Importantly, the risk of depletion of species of conservation concern (skates and rays) is
also diminished when the strict no discard option is implemented, leading to a win-win for
commercial and conservation species. Model simulations suggest that the risk can be elimi-
nated by implementing Realistic safeguards through a harvest control rule (Type 4), which is
more conservative than the ICES standard advice rule (Type 1). Mirroring the risk to stock
sustainability, conservation strategies for protecting above all others cod or skates and rays
poses an obvious risk to the sustainability of dependent fisheries, which is intensified when
precautionary harvest control rules are applied (Fig 11). In this case the ICES standard HCR is
more beneficial to the sustainability of fisheries. This contrast illuminates the stock-fishery sus-
tainability trade-offs.
Fig 12. The Large Species Indicator (LSI, right) and ratio (left) of biomass of demersal species to pelagic species
contrasted across multiple strategies. Strategies include all NSMAP with ICES standard advice rule Type 1 as the
safeguard and constant time frame rule. Pelagic groups include sprat, herring, blue whiting, miscellaneous filter
feeding fish, mackerel and horse mackerel and demersal fish include all other fish and elasmobranch groups. LSI
includes only those species surveyed by the North Sea International Bottom Trawl Survey (see Lynam and Mackinson,
2015). Note all scenarios are equal for the period 1991–2012.
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Even in the strategy most likely to reflect implementation of the NSMAP (i.e where discards
are avoided but not wholly eliminated) as the model ecosystem adjusts to a new equilibrium,
the indirect food-web effects arising from changes in demersal predators result in declines in
some prey species. Particularly bentho-piscivorous species such as Norway pout, some plankti-
vores such as Blue whiting and sprat, and some smaller bodied demersal piscivores such as
megrim (Figs 13 and 14). Such changes in the food-web structure are an inevitable conse-
quence of objectives to sustain important commercial fish stocks and their fisheries.
The implementation of the “Avoiding Discarding’ option gives quite a generous appraisal
of the fleets ability to selectively target species at lower risk. Modelling fleet behaviour is notori-
ously difficult due the vast array of regulatory and human decision-making process that affect
the outcome, and are thus subsumed as implementation errors. Here we have made a transpar-
ent, albeit simplified representation of the mechanism for avoiding discards, and have chosen
not to set implementation error a priori, but to allow it to emerge from the interaction among
the HCRs and regulatory conditions (see section 3.6 of supplementary material). There are
some slight inconsistencies in the proportions of catch discarded for each regulation (see sec-
tion 3.6 of supplementary material), however since the behavioural response to each regulation
has a far more significant effect on the results and there is a clear order of ranking between
results from each regulation, this does not affect our conclusions.
Fig 13. Biomass trajectories of additional species of interest. Shows the contrast in outcomes between 3 strategies, strict no discards (red); discard avoidance (green)
and discard continues (blue) with 95% confidence interval.
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The management strategy evaluation approach applied here is state-of-the-art in screening
the possible risks associated with alternative policy options, despite some controversy and mis-
understanding on its use and utility [15,32,33]. As a tool best suited for comparing and rank-
ing the performance of strategies it is not intended for making specific short-term predictions
about stock-specific biological and fishery outcomes. More detailed models incorporating
more structure in the biological dynamics of stocks and behavioural dynamics of fleets are
required for that. For example, while changes in the maximum range of F values have a small
impact on the overall risk and rewards relative discard policy, our analysis does not explore the
myriad of possible combinations of F within the ranges among species, and how these might
be adjusted from year to year in order to resolve specific problems such as reducing fishing
pressure on one species or avoiding another being a choke to the fishery (see point 12 and 13
in the proposed NSMAP). In such cases, optimisation procedures with clearly defined objec-
tive functions are required to search for options with desirable outcomes. Since the way a fleet
is able to respond to a discard policy has an important impact, being able to make good predic-
tions of fleet behaviour is important for models. Tools such as FLBEIA (among others) are
being constructed specifically with this purpose in mind (see [34] and references therein).
The NSMAP presents biological reference points generated by single-species methods,
despite the scientific consensus that these would not be simultaneously achievable due to bio-
logical interactions among species and changes in the environment affecting productivity [35,
5]. While other reference points determined from multi-species models in the North Sea such
as SMS, LeMans and EwE (e.g. [36]) could be evaluated along with the single species reference
points, that comparison would be about testing alternative ‘interpretations’ of reference points
and not the evaluation of the NSMAP as it stands. Nonetheless, it would make for a relevant
and interesting future comparison given that the move toward multi-annual plans has implica-
tions for the increased use (and utility of) multi-species models in advice.
Fig 14. Foodweb indicators contrasted across multiple strategies. All NSMAP strategies with ICES standard advice rule Type 1 as the safeguard and constant time
frame rule. Left—total biomass of fish and elasmobranchs and right—biomass by trophic guild, including only those species surveyed by the North Sea International
Bottom Trawl Survey (see Lynam and Mackinson, 2015). Note all scenarios are equal for the period 1991–2012.
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The scale of the modelled impacts in the North Sea EwE key run model are sensitive to
specification of P/B parameters [26]. However in this analysis the P/B parameters, along with
all the other Ecopath and Ecosim parameters are sampled from distributions so that the
robustness of the strategies to uncertainties in the model can be measured. Of the 1000 para-
meterisations of the North Sea model evaluated, around 25% passed the criteria for acceptable
dynamic behaviour when the alternative policies were applied. One of the features that
emerges from letting the parameters ‘run free’ is the occurrence of adult-juvenile oscillatory
dynamics, which occurs in the future projections. Parameter combinations that led to unstable
oscillatory behaviours are the main reason that approximately 80% were screened out as hav-
ing unacceptable trajectories. It should also be noted that the model simulations should not be
treated as reliable future forecasts of stocks because they do not incorporate possible scenarios
for how changes in the environment may affect biological process of individual stocks and the
resulting cascade through the food web [37,38].
Recognition of these technical shortcomings does not negate the findings of the MSE analy-
sis which illuminates the relative impacts of the 5 management dimension of the proposed
NSMAP. The results imply that when defining and implementing the detail of the North Sea a
multi-annual plan, effort expended on getting the discard regulation options right will lead to
greater measurable effects for stocks, fisheries and other environmental objectives than fine
tuning targets for fishing mortality and the way in which they are adjusted.
Fig 15. Contrast in risk of depletion of stocks against the reward of total landed catch. Risk is the number of stock below their individual B
lim
reference
points. The vertical axis shows the ratio of total tonnage caught at the end of the forecast, i.e. the average of the last five years, to the initial catch at the start of
the forecast period. The pane of the left is specific to the stocks in the NSMAP, whereas the pane on the right includes all species with a reference level in the
estimate of risk and all fish and elasmobranch stocks caught by fisheries in the catch ratio. The risks and rewards are contrasted between 3 strategies; strict no
discards (red), discard avoidance (green), discard continues (blue). The black horizontal line shows the level at which the tonnage caught at the end of the
simulation is equal to the start, points above this line represent runs with increased tonnage caught. Each small point represents an outcome for a single
parameterisation from the full set coloured by strategy implemented. The large circles show the mean response averaged across parameterisations and coloured
by strategy implemented.
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Using a multi-species multi-fleet model allowed us to take account of the species and fleet
interactions, even if it was not possible to tease apart the role that these interactions may play
in every result. They have however, shown clearly that changes observed by fishermen can be
captured, such as the predation effect of cod on Nephrops having a bearing on the stock and
performance of fisheries that depend upon it [39]. It also enabled us to present information rel-
evant to assessing the ecological and fishery trade-offs that might arise from implementation
of the plan by revealing the impacts on demersal and pelagic assemblages and different fleets.
In doing so we’re taking one-step closer to being able to provide scientific evidence to support
ICES integrated advice approach founded upon the ecosystem approach to fisheries. The
important message is that because fish and fisheries do not exist in isolation, neither should
plans for their management. Any future multi-annual plans (e.g. for pelagic stocks) should be
evaluated in terms of how consistent they are with this one for demersal stocks.
Supporting information
S1 Supporting Information. Technical methods of the uncertainty and MSE routine.
(DOCX)
Acknowledgments
The authors acknowledge the input of the North Sea Advisory Council during early stages of
this conceptualization of this work and their continued interest in exploring this kind of
investigation.
Author Contributions
Conceptualization: Steven Mackinson.
Data curation: Clement Garcia.
Formal analysis: Steven Mackinson, Mark Platts, Christopher Lynam.
Funding acquisition: Steven Mackinson.
Investigation: Steven Mackinson, Christopher Lynam.
Methodology: Steven Mackinson, Mark Platts, Christopher Lynam.
Project administration: Steven Mackinson.
Software: Mark Platts.
Supervision: Steven Mackinson.
Validation: Christopher Lynam.
Visualization: Mark Platts, Clement Garcia, Christopher Lynam.
Writing – original draft: Steven Mackinson, Mark Platts, Christopher Lynam.
Writing – review & editing: Clement Garcia.
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Supplementary resource (1)

... How are EwE Models informing the issue? EwE models are being used to evaluate the sustainability of mixed-species fisheries in the North Sea (Heymans et al., 2011;Mackinson et al., 2009Mackinson et al., , 2018Stäbler et al., 2016Stäbler et al., , 2019 and off the west coast of Scotland (Alexander et al., 2015;Baudron et al., 2019). Similar to other north temperature ecosystems Lucey et al., 2012;Mueter & Megrey, 2006), the general conclusion from these models is that simultaneously achieving MSY from single-species stock assessments for all species in a mixed-species fishery is not possible due to Significant effort reductions (i.e., 20%-50%) may be required for some fleets in order to achieve sustainable harvest rates for all species (Mackinson et al., 2009;Stäbler et al., 2019). ...
... However, linked EwE and species distribution models suggest more significant positive and negative effects of limiting discards that differ across species (Pennino et al., 2020). Whether the LO has net positive or negative effects may also differ between fisheries that are regulated by effort controls compared to those regulated by catch limits due to different incentives for selective harvesting (Celić et al., 2018;Mackinson et al., 2018). EwE models also suggest the effects of the LO will depend on the status of the relevant populations, with overfished species benefiting more from reductions in fishing effort than in discarding, whereas limiting discards has greater effects for species where landed catch is near sustainable levels Moutopoulos et al., 2018). ...
... EwE models also suggest the effects of the LO will depend on the status of the relevant populations, with overfished species benefiting more from reductions in fishing effort than in discarding, whereas limiting discards has greater effects for species where landed catch is near sustainable levels Moutopoulos et al., 2018). A general result that has emerged from EwE models of multiple ecosystems is the potential negative effects of limiting discards on scavenger populations, particularly marine birds but also marine mammals and sea turtles, that have come to rely on discards as a food resource (Celić et al., 2018;Fondo et al., 2015;Mackinson et al., 2018;Moutopoulos et al., 2018). ...
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The implementation of ecosystem management requires ecosystem modelling within the context of a natural resource management process. Ecopath with Ecosim (EwE) is the most widely used modelling platform for investigating the dynamics of marine ecosystems, but has played a limited role in fisheries management and in multi‐sector resource decision‐making. We review 10 case studies that demonstrate the use of EwE to support operational resource management. EwE models are being used to inform tactical decision‐making in fisheries and other ocean use sectors, as well as to identify key trade‐offs, develop appropriate policy objectives, and reconcile conflicting legislative mandates in a variety of ecosystems. We suggest the following criteria to enhance the use of EwE and other ecosystem models in operational resource management: (1) a clear management objective that can be addressed through modelling; (2) an important trade‐off and a receptive policy context amenable to trade‐off evaluation; (3) an accessible and well‐documented model that follows best practices; (4) early and iterative engagement among scientists, stakeholders, and managers; (5) integration within a collaborative management process; (6) a multi‐model approach; and (7) a rigorous review process. Our review suggests that existing management frameworks are as much or more of a limitation to the operational use of EwE than technical issues related to data availability and model uncertainty. Ecosystem models are increasingly needed to facilitate more effective and transparent decision‐making. We assert that the requisite conditions currently exist for enhanced strategic and tactical use of EwE to support fisheries and natural resource management.
... The North Sea ecosystem has been extensively studied and there are several extant ecosystem models of the region. For the quantitative analysis, we chose to use two end-to-end ecosystem models built using the Ecopath with Ecosim (EwE) modelling framework, one for the Kattegat (ICES, 2019) and another for the North Sea (Mackinson et al., 2018). Similar scenarios for future human activities were run using both the FCMs and EwE models, and model results were compared based on the responses to individual model components as well as multivariate forcing. ...
... In addition to modelling the predatory mortality between groups, the impact of 11 fishing fleets that represent the major international fleets operating in the North Sea was considered, with functional groups and fishing fleets interconnected through 1521 links [Supplementary Figure S5A and Table 1 ( Mackinson et al., 2018)]. ...
... tics also further elucidate the understanding of key ecosystem processes that might otherwise be overlooked by proceeding to the dynamic phase of food-web modelling without pausing to rigorously evaluate these diagnostics (Link, 2010). The North Sea model was also approved by ICES (2016b) as a "key-run" and uncertainty was investigated by Mackinson et al. (2018). As presented by Uusitalo et al. (2022) for the central Baltic Sea EwE model (Bauer et al., 2018), a Monte Carlo approach was used to see if model parametrization varied within reasonable limits. ...
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The complexities of ecosystem-based management require stepwise approaches, ideally involving stakeholders, to scope key processes, pressures, and impact in relation to sustainability and management objectives. Use of qualitative methods like Fuzzy Cognitive Mapping (FCM) with a lower skill and data threshold than traditional quantitative models afford opportunity for even untrained stakeholders to evaluate the present and future status of the marine ecosystems under varying impacts. Here, we present the results applying FCM models for subregions of the North Sea. Models for the southern North Sea, Skagerrak, Kattegat, and the Norwegian Trench were developed with varying level of stakeholder involvement. Future scenarios of increased and decreased fishing, and increased seal biomass in the Kattegat, were compared with similar scenarios run on two quantitative ecosystem model. Correspondence in response by the models to the same scenarios was lowest in the southern North Sea, which had the simplest FCM model, and highest in Norwegian Trench. The results show the potential of combining FCM and quantitative modelling approaches in integrated ecosystem assessments (IEAs) and in future ecosystem-based management advice, but to facilitate such comparisons and allow them to complement and enhance our IEAs, it is important that their components are aligned and comparable.
... Uncertainty within individual ecosystem models has previously been explored (e.g. Thorpe et al. 2015, Spence et al. 2016, Mackinson et al. 2018; however, these attempts are likely to underestimate the uncertainty, as uncertainty across models is often ignored. Management advice should ideally consider the outputs of a suite of models, but combining them is not as easy as averaging over their outputs or ascribing a simple weight to each, as we do not expect the discrepancies of each of the models to be independent (Rougier 2007, Christiansen 2020. ...
... It contains >10 fishing fleets and > 60 functional groups, some of which are split into multiple age stanzas. We used parameter uncertainty from Mackinson et al. (2018). EwE was able to predict ZB, Z:P, BM and TFB from 1991 until 2050. ...
Article
To effectively implement ecosystem-based fisheries management, tools are needed that are capable of exploring the likely consequences of potential management action for the whole ecosystem. Quantitative modelling tools can be used to explore how ecosystems might respond to potential management measures, but no one model can reliably forecast all aspects of future change. To build a robust basis for management advice, a suite of models can be used, but the interpretation of the joint output of multiple models can be difficult. We employ a newly developed ensemble approach to integrate 5 different ecosystem models and estimate changes in ecosystem state within a single probabilistic forecast. We provide evidence on the response of ecosystem state (measured using ecological indicators relating to plankton, fish and top predators) to potential fisheries management scenarios. We demonstrate that if future fishing mortality is consistent with maximum sustainable yield policy, the North Sea fish community will recover in terms of its size structure and species composition. However, there is currently large uncertainty in trends of future fish biomass, plankton and top predators. We conclude that (1) this ensemble approach can be applied directly to policy-relevant questions and add value for decision makers, as multiple aspects of uncertainty are considered; (2) future research should prioritise improvements in model skill via a reduction in uncertainty surrounding biomass estimates; and (3) fisheries management that leads to sustainable fishing levels can be considered appropriate for 2 crucial aspects of fish biodiversity: species composition and size structure.
... One way this can be done is through management strategy evaluations (MSE), where multispecies models can be used as the operating model (e.g. Grüss et al., 2016;Mackinson et al., 2018;Kaplan et al., 2021;Pérez-Rodríguez et al., 2022) and can provide a strategic evaluation of the long-term consequences of alternative management actions across a suite of species. However, we note that projections of multispecies models can be useful in revealing tradeoffs associated with particular policy choices or sets of expectations about reference points (e.g. stock size or goals for other species) on their own, without having to be connected to a feedback management control mechanism as done within an MSE. ...
Article
Multispecies models have existed in a fisheries context since at least the 1970s, but despite much exploration, advancement, and consideration of multispecies models, there remain limited examples of their operational use in fishery management. Given that species and fleet interactions are inherently multispecies problems and the push towards ecosystem-based fisheries management, the lack of more regular operational use is both surprising and compelling. We identify impediments hampering the regular operational use of multispecies models and provide recommendations to address those impediments. These recommendations are: (1) engage stakeholders and managers early and often; (2) improve messaging and communication about the various uses of multispecies models; (3) move forward with multispecies management under current authorities while exploring more inclusive governance structures and flexible decision-making frameworks for handling tradeoffs; (4) evaluate when a multispecies modelling approach may be more appropriate; (5) tailor the multispecies model to a clearly defined purpose; (6) develop interdisciplinary solutions to promoting multispecies model applications; (7) make guidelines available for multispecies model review and application; and (8) ensure code and models are well documented and reproducible. These recommendations draw from a global assemblage of subject matter experts who participated in a workshop entitled “Multispecies Modeling Applications in Fisheries Management”.
... MSMs also have considerable utility as operating models (OMs) within Management Strategy Evaluation (MSE) frameworks (semianalogous to Operational Management Procedures (OMP) (Rademeyer et al., 2007;Punt et al., 2016;Smith et al., 2017;Kaplan et al., 2021) but this aspect is not discussed in detail in this paper and the reader is referred to examples of multispecies MSEs such as Mackinson et al. (2018), Thorpe and De Oliveira (2019) as well as to Kaplan et al. (2021) who provide a more in-depth review. When used with multispecies models, MSE has been shown to be an effective risk management tool for simulation testing the robustness of harvest control rules to a range of uncertainties, including due to changing climate, economic drivers and trophic interactions (Dichmont et al., 2008;Plagányi et al., 2013;Punt et al., 2014;Ono et al., 2018;ICES, 2019ICES, , 2021. ...
Article
Stock assessment models often assume natural mortality rates (M) are constant and attribute the variability in a stock’s overall mortality rate to variability in fishing mortality and recruitment. However, this assumption may not be valid if M varies due to both direct and indirect trophic interactions as well as environmental variability. This is particularly the case when there are substantial changes in the overlapping abundances of a key predator or prey species, or extreme environmental changes impacting an ecosystem. Hence multispecies models (MSMs) are used to explicitly capture variations in natural mortality rates and improve the ability to discriminate between mortality due to fishing versus natural mortality, plus quantify the influences of fishing on the broader ecosystem, consistent with an ecosystem approach to fishing (EAF). There are a growing number of approaches to modelling natural mortality rates in MSMs, with models developed for tactical applications requiring a higher level of rigour and consideration of uncertainty than broad strategic ecosystem models. We overview approaches to modelling natural mortality in Models of Intermediate Complexity for Ecosystem assessments (MICE) and use four case studies to highlight lessons learnt, applications and provide some guidelines going forward. We identify ten broad application categories for MSMs (incorporating explicit representation of components of M), to advance EAF. These include: (1) quantify variability in natural mortality by age and over time as inputs to single species stock assessment models, because of the recognition that predation mortality (M2) is a large and variable portion of total M; (2) inform ecosystem reference points; (3) use as operating models in Management Strategy Evaluation frameworks; (4) simulation test broader management levers; (5) optimise multispecies harvest strategies; (6) inform on management of bycatch and ‘choke’ species; (7) represent and forward project trajectories and model recovery scenarios for threatened and protected species; (8) correctly attribute sources of mortality to support management efforts; (9) pest management and (10) broader applications (e.g. habitat alterations). Using well-constructed MSMs to correctly specify M reduces bias in model parameters, reference points and projections and is increasingly important as ecosystems respond to a more variable and changing climate.
... Therefore, we included a management component. We used the broken stick harvest control rule that defines a stock's biomass thresholds below which management rules are applied, reducing the effort allowed (Dichmont et al., 2016;Mackinson et al., 2018). While managing a multispecies fishery based on single species criteria that do not consider species and fleet interactions is a limitation, it reflects the current management framework of the Australian Southern and Eastern Scalefish and Shark Fishery as of many other fisheries worldwide (e.g. ...
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Ecosystem‐based fisheries management aims to ensure ecologically sustainable fishing while maximising socio‐economic benefits. Achieving this goal for mixed fisheries requires better understanding of the effects of competing fishing fleets on shared resources and economic performance. Proposed management strategies that promote either specialisation or diversification of catches may result in unintended consequences for ecosystem‐based management. Here, we ask: does increased or decreased competition among fleets lead to better ecological and socio‐economic fishery outcomes? How effective are currently proposed management strategies for achieving these outcomes? We integrated fleet dynamics into a multispecies size‐spectrum model and parameterised this model to represent Australian Southern and Eastern Scalefish and Shark Mixed Fishery. We compared the fishery status quo to two extreme scenarios: no competition, where each species is fished only by one fleet (specialisation); and maximal competition, where all fleets catch all species (diversification). To answer our second question, we considered three more plausible scenarios resulting from proposed management strategies: decreased competition due to reduced bycatch, and increased competition due to increased catches of under‐utilised or valuable species. We used indicators to explore scenarios’ outcomes. Our model reproduced observed trends in fishing effort and yield. Extreme scenarios showed that a fishery dependent on single species management structures is more likely to achieve ecosystem‐based management objectives if fleets do not compete, while maximal competition can lead to the fishery collapse as management buffers the ecological impact of diversifying. The more plausible scenarios showed little improvement over the status quo, with mixed ecological and negative economic effects. Synthesis and applications: Our model can be applied to assess mixed fisheries ecosystem‐based management strategies. Our results show that, under single species management approaches, greatest outcomes can be achieved when fleets are specialised, whereas managing fleets that catch similar species is unlikely to be successful. They question the effectiveness of these management approaches in providing resilience for mixed fisheries facing changes and highlight the need to account for fleet interactions in the evaluation of management strategies to avert unintended risks.
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Ecosystem-based fisheries management (EBFM) aims to go beyond single-species management by incorporating ecosystem considerations to guarantee the sustainable use of marine resources. Although many countries have formally committed to the implementation of EBFM, at a practical level progress has been very slow. At the analytical level, many advances have been made, developing sophisticated ecosystem models and, on the other side, rigorous stock assessment models. Yet it is still unclear how these two parallel approaches can be brought together to provide an efficient EBFM. Here we first present the two groups of models, we then discuss ways to integrate both approaches and their resulting possible implications for fisheries advice towards sustainable management, with a special focus on spatially explicit information.
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Integrated fisheries risk analysis method for ecosystems (IFRAME) was originally developed to accomplish the goals of an ecosystem approach to fisheries (EAF) to overcome the limitations of the single-species approach. This approach performs ecosystem-based fisheries assessment, forecasting, and management. However, this IFRAME approach does not explain spatial variations in ecosystem components. Although this approach has a number of advantages in mitigating the risks associated with developing macroscopic management measures, its limitation is apparent when microscopic management measures that reflect the spatial features of the species or the fisheries within the ecosystem are required. In this study, the IFRAME was extended to assess and forecast ecosystem dynamics and risk indices in a spatio-temporal context. The distribution of biomass and changes in risk of chub mackerel were predicted using the extended IFRAME, based on scenarios considering changes in climate and variations in fishing mortality. A total of 87% of chub mackerel resources were distributed in the East China Sea in 2019, but they are expected to rise northward due to the rise of the average sea surface water temperature (SST) as per the RCP4.5 and RCP8.5 IPCC scenarios. Based on these scenarios, a major fishing ground was predicted to form around the Yellow Sea in 2069. The species risk index (SRI) of mackerel in 2069 showed relatively low in the East and Yellow Seas, but as climate change continues, the risks in the East China Sea increased. The forecasting results can be used in the management component of IFRAME to assess alternative harvest strategies and tactics in the rapidly changing marine ecosystems. Since food web relationships and water temperature scenarios were only considered as input data for the Ecospace module used in the prediction of mackerel biomass distribution, more quantitative spatial information should be incorporated in the analysis to better explain the complex nature of the marine ecosystems. In conclusion, based on the spatio-temporal IFRAME approach, it could be possible to establish a proper fisheries management plan by incorporating spatial variations in the ecosystem for sustainable fisheries.
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Anarhichas lupus is a boreo-Arctic species with biological characteristics often associated with vulnerability to over-exploitation. Although not commercially targeted in the North Sea, A. lupus is a bycatch species in mixed demersal fisheries. Here we provide an overview of the status of A. lupus in the North Sea, as observed from commercial landings and fishery-independent trawl survey data. A. lupus was once common across much of the central and northern North Sea but, since the 1980s, have declined in abundance, demographic characteristics (reduced size) and geographical range, with the shallower and more southerly parts of its range most impacted. A. lupus is still relatively frequent in the northern North Sea, where fishing intensity, though decreasing, is high. Bycatch through fishing remains a potential threat and, considering the likely impacts of predicted climate change on cold-water species, risks of further regional depletion and/or range contraction remain. Whether or not A. lupus is able to re-establish viable populations in former habitat in UK coastal waters is unknown. Given the lack of data, the precautionary principle would suggest that manageable pressures be minimised where the species and its habitat are at risk of further impacts, and more regular assessments of population status be undertaken. This article is protected by copyright. All rights reserved.
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Multispecies mixed fisheries catch ecologically interacting species with the same gears at the same time. We used an ensemble of size-based multispecies models to investigate the effects of different rates of fishing mortality (F) and fleet configurations on yield, biomass, risk of collapse and community structure. Maximum sustainable yield (MSY) and FMSY for 21 modelled species’ populations in the North Sea were defined at the Nash equilibrium, where any independent change in F for any species would not increase that species’ MSY. Fishing mortality ranges leading to “Pretty Good Yield” (F-PGY), by species, were defined as ranges yielding ≥0.95 × MSY. Weight and value of yield from the entire fishery increased marginally when all species were fished at the upper end of F-PGY ranges rather than at FMSY, but risk of species’ collapse and missing community targets also increased substantially. All risks fell markedly when fishing at the lower end of F-PGY ranges, but with small impacts on total fishery yield or value. While fishing anywhere within F-PGY ranges gives managers flexibility to manage trade-offs in multispecies mixed fisheries, our results suggest high long-term yields and disproportionately lower risks of stock collapse are achieved when F ≤ FMSY for all component stocks.
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Significance Whether environmental conditions, harvesting, or predation pressure primarily regulate an ecosystem is still a question of much debate in marine ecology. Using a wealth of historical records, we describe how climate and fishing interact in a complex marine ecosystem. Through an integrative evidence-based approach, we demonstrate that indirect effects are key to understanding the system. Planktivorous forage fish provide an important role in the system, linking bottom-up and top-down processes such that fishing can indirectly impact the plankton and environmental effects can cascade up to impact demersal fish and predatory seabirds. Cascading trophic interactions can be mediated by opposing bottom-up and top-down forces; this combination has the potential to avert regime wide shifts in community structure and functioning.
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The European fisheries management is currently undergoing a fundamental change in the handling of catches of commercial fisheries with the implementation of the 2013 Common Fisheries Policy. One of the main objectives of the policy is to end the practice of discarding in the EU by 2019. However, for such changes to be successful, it is vital to ensure stakeholders acceptance, and it is prudent to consider possible means to verify compliance with the new regulation. Remote Electronic Monitoring (REM) with Closed-Circuit Television (CCTV) has been tested in a variety of fisheries worldwide for different purposes and is currently considered as one possible tool to ensure compliance with a European ban on discards.
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MSY principles for marine fisheries management reflect a focus on obtaining continued high catches to provide food and livelihoods for humanity, while not compromising ecosystems. However, maintaining healthy stocks to provide the maximum sustainable yield on a single-species basis does not ensure that broader ecosystem, economic, and social objectives are addressed. We investigate how the principles of a “pretty good yield” range of fishing mortalities assumed to provide >95% of the average yield for a single stock can be expanded to a pretty good multispecies yield (PGMY) space and further to pretty good multidimensional yield to accommodate situations where the yield from a stock affects the ecosystem, economic and social benefits, or sustainability. We demonstrate in a European example that PGMY is a practical concept. As PGMY provides a safe operating space for management that adheres to the principles of MSY, it allows the consideration of other aspects to be included in operational management advice in both data-rich and data-limited situations. PGMY furthermore provides a way to integrate advice across stocks, avoiding clearly infeasible management combinations, and thereby hopefully increasing confidence in scientific advice.
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Demands for management advice on mixed and multispecies fisheries pose many challenges, further complicated by corresponding requests for advice on the environmental impacts of alternate management options. Here, we develop, and apply to North Sea fisheries, a method for collectively assessing the effects of, and interplay between, technical interactions, multispecies interactions, and the environmental effects of fishing. Ecological interactions involving 21 species are characterized with an ensemble of 188 plausible parameterizations of size-based multispecies models, and four fleets (beam trawl, otter trawl, industrial, and pelagic) characterized with catch composition data. We use the method to evaluate biomass and economic yields, alongside the risk of stock depletion and changes in the value of community indicators, for 10 000 alternate fishing scenarios (combinations of rates of fishing mortality F and fleet configuration) and present the risk vs. reward trade-offs. Technical and multispecies interactions linked to the beam and otter trawl fleets were predicted to have the strongest effects on fisheries yield and value, risk of stock collapse and fish community indicators. Increasing beam trawl effort led to greater increases in beam trawl yield when otter trawl effort was low. If otter trawl effort was high, increases in beam trawl effort led to reduced overall yield. Given the high value of demersal species, permutations of fleet effort leading to high total yield (generated primarily by pelagic species) were not the same as permutations leading to high catch values. A transition from F for 1990 to 2010 to FMSY, but without changes in fleet configuration, reduced risk of stock collapse without affecting long-term weight or value of yield. Our approach directly addresses the need for assessment methods that treat mixed and multispecies issues collectively, address uncertainty, and take account of trade-offs between weight and value of yield, state of stocks and state of the environment.
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Pretty good yield (PGY) is a sustainable fish yield corresponding to obtaining no less than a specified large percentage of the maximum sustainable yield (MSY). We investigated 19 European fish stocks to test the hypothesis that the 95% PGY yield range is inherently precautionary with respect to impairing recruitment. An FMSY range was calculated for each stock as the range of fishing mortalities (F) that lead to an average catch of at least 95% of MSY in long-term simulations. Further, a precautionary reference point for each stock (FP.05) was defined as the F resulting in a 5% probability of the spawning-stock biomass falling below an agreed biomass limit below which recruitment is impaired (Blim) in long-term simulations. For the majority of the stocks analysed, the upper bound of the FMSY range exceeded the estimated FP.05. However, larger fish species had higher precautionary limits to fishing mortality, and species with larger asymptotic length were less likely to have FMSY ranges impairing recruitment. Our study shows that fishing at FMSY generally is precautionary with respect to impairing recruitment for highly exploited teleost species in northern European waters, whereas the upper part of the range providing 95% of MSY is not necessarily precautionary for small- and medium-sized teleosts.