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Worldwide bivalve aquaculture is expanding rapidly. Simultaneously, there has been a loss of natural bivalve reefs due to anthropogenic activities. As bivalve reefs support several ecosystem functions disproportionate to the area they cover, there is interest in their restoration. The Firth of Thames (FoT) in northern New Zealand once supported dense populations of green lipped mussels Perna canaliculus , which were extirpated by a dredge fishery in the mid-20 th century. Efforts to restore these biogenic habitats are underway. The largest standing populations of this species in the area currently exist in aquaculture. This study aimed to determine if larval spill-over from aquaculture can provide a larval subsidy to bivalve reef restoration efforts in the FoT. We used a combination of trace elemental fingerprinting and biophysical modelling techniques to determine patterns of larval dispersal in the area. Results of both approaches indicated that the larval pool in the area is well mixed with larvae produced at aquaculture locations capable of settling throughout the study area. Overall this shows, for the first time, that larval spill-over from aquaculture may provide a subsidy to restoration efforts and assist with establishing sustainable populations. When determining restoration locations, the potential for aquaculture populations to act as a larval source should be explicitly considered. Conversely, when considering the location of new aquaculture sites, the consequences of larval spill-over to surrounding wild populations should be assessed. We recommend that restoration efforts and aquaculture be carefully integrated in a network approach which could provide both ecological and economic benefits.
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Aquacult Environ Interact
Vol. 12: 231–249, 2020 Published online June 18
At a global scale, coastal shellfish aquaculture is
rapidly expanding in order to help meet the protein
needs of a growing human population (FAO 2018).
As cultured biomass of shellfish increases, it will in -
evitably affect ecosystem dynamics in the local area in
which this culturing is taking place (van der Schatte
Olivier et al. 2020). These aquaculture−environment
interactions may be perceived as either negative or
positive. Effects viewed as negative may include the
organic enrichment of the benthos through biode-
posits (Giles & Pilditch 2006, Cranford et al. 2009),
alteration of the genetic composition of populations
through the escape of larvae or adults (Gausen &
Moen 1991, Apte et al. 2003, Heino et al. 2015), or the
© The authors 2020. Open Access under Creative Commons by
Attribution Licence. Use, distribution and reproduction are un -
restricted. Authors and original publication must be credited.
Publisher: Inter-Research ·
*Corresponding author:
Spill-over from aquaculture may provide a larval
subsidy for the restoration of mussel reefs
Craig Norrie1, 6,*, Brendon Dunphy1, 2, Moninya Roughan3, Simon Weppe4,
Carolyn Lundquist1, 5
1Institute of Marine Science, University of Auckland, Auckland 1010, New Zealand
2School of Biological Sciences, University of Auckland, Auckland 1010, New Zealand
3School of Mathematics and Statistics, UNSW Sydney, NSW 2052, Australia
4Meteorological Service of New Zealand (MetOcean Division), Raglan 3225, New Zealand
5National Institute of Water and Atmospheric Research (NIWA), Hamilton 3216, New Zealand
6Present address: Hatfield Marine Science Center, Cooperative Institute for Marine Resources Studies,
Oregon State University, Newport, OR 97365, USA
ABSTRACT: Worldwide bivalve aquaculture is expanding rapidly. Simultaneously, there has been
a loss of natural bivalve reefs due to anthropogenic activities. As bivalve reefs support several eco-
system functions disproportionate to the area they cover, there is interest in their restoration. The
Firth of Thames (FoT) in northern New Zealand once supported dense populations of green lipped
mussels Perna canaliculus, which were extirpated by a dredge fishery in the mid-20th century.
Efforts to restore these biogenic habitats are underway. The largest standing populations of this
species in the area currently exist in aquaculture. This study aimed to determine if larval spill-over
from aquaculture can provide a larval subsidy to bivalve reef restoration efforts in the FoT. We
used a combination of trace elemental fingerprinting and biophysical modelling techniques to
determine patterns of larval dispersal in the area. Results of both approaches indicated that the
larval pool in the area is well mixed with larvae produced at aquaculture locations capable of set-
tling throughout the study area. Overall this shows, for the first time, that larval spill-over from
aquaculture may provide a subsidy to restoration efforts and assist with establishing sustainable
populations. When determining restoration locations, the potential for aquaculture populations to
act as a larval source should be explicitly considered. Conversely, when considering the location
of new aquaculture sites, the consequences of larval spill-over to surrounding wild populations
should be assessed. We recommend that restoration efforts and aquaculture be carefully inte-
grated in a network approach which could provide both ecological and economic benefits.
KEY WORDS: Larval dispersal · Population connectivity · Bivalve larvae · Biophysical modelling ·
Trace elemental fingerprinting · Restoration · OpenDrift · Shell chemistry
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Aquacult Environ Interact 12: 231–249, 2020
alteration of flow regimes by the structures on which
aquaculture is taking place (Gibbs et al. 1991, Plew
2011). Effects perceived as positive may involve nutri-
ent remediation in eutrophied systems (Petersen et
al. 2014, Nielsen et al. 2016) or providing habitat for
other species (McLeod et al. 2014, Fariñas-Franco &
Roberts 2018). Although often overlooked in studies
investigating the effects of aquaculture on the local
environment (see reviews by Newell 2004, van der
Schatte Olivier et al. 2020), larval production from
these dense aggregations of bivalves may contribute
to regional larval pools and thereby modify popula-
tion dynamics in the area in which they are growing.
Knowledge of potential larval dispersal pathways
from these cultured populations is essential to gain
an understanding of how larvae from aquaculture
may interact with local wild bivalve populations.
Understanding these interactions is of particular
interest in areas where natural populations of
bivalves have been depleted but cultured popula-
tions exist; e.g. the Firth of Thames (FoT) in northern
New Zealand for green lipped mussel or Chesapeake
Bay for Virginia oysters (Beck et al. 2011, Turner et
al. 2019).
Shellfish beds perform a number of ecosystem
functions disproportionate to their size (Lundquist et
al. 2017). They contribute to water filtration (zu
Ermgassen et al. 2013, Ehrich & Harris 2015), nutri-
ent cycling (Giles & Pilditch 2006, Nielsen et al.
2016), provide habitat structure (Dumbauld et al.
2009), and can influence food web dynamics and bio-
diversity (McLeod et al. 2014, Fariñas-Franco &
Roberts 2018). However, several common anthro-
pogenic stressors are recognised worldwide which
have resulted in degradation or removal of these bio-
genic habitats with a corresponding loss of ecosys-
tem functions (Beck et al. 2011, Alleway & Connell
2015). These stressors include sedimentation, eutro -
phication, overfishing, and dredging. Accordingly,
there is interest in restoring degraded populations
and the ecosystem functions they provide (e.g.
French McCay et al. 2003, Coen et al. 2007, North et
al. 2010). In order for restoration programmes to have
the highest chances of success, an understanding of
larval dispersal and population connectivity is essen-
tial (Lipcius et al. 2008). Understanding larval dis-
persal dynamics allows us to determine the self-
sustainability of restored populations and also select
optimal restoration locations (Elsäßer et al. 2013, Tet-
telbach et al. 2013, Puckett et al. 2018).
Although it is important to track the dispersal of
larvae, in situ tracking of larval movement is complex
due to the small size, high mortality, and large scales
over which larval transport is possible (Gawarkiewicz
et al. 2007, Cook et al. 2014). Thus, several tech-
niques have been developed which allow larval dis-
persal and population connectivity to be indirectly
inferred (reviewed by Kool et al. 2013). Currently,
biophysical models (e.g. Cowen et al. 2000, Werner
et al. 2007, Elsäßer et al. 2013, Thomas et al. 2016)
and trace elemental fingerprinting (e.g. Thorrold et
al. 2002, Becker et al. 2007, Ricardo et al. 2015, Gomes
et al. 2016) are among the most widely applied tech-
niques used to infer the dispersal of larvae. Biophys-
ical modelling couples oceanographic data (e.g.
ocean currents and temperature) with information on
the biology and behaviour of larvae to estimate larval
dispersal over spatial and temporal scales that would
be impossible to measure empirically. Biophysical
models have been used in a number of management
scenarios, such as the design of marine reserves
(Puckett et al. 2014), examining larval export from
marine reserves (Le Port et al. 2014), determining
restoration locations (Tettelbach et al. 2013, Puckett
et al. 2018), predicting the spread of invasive species
(Inglis et al. 2006), and projecting changes under
future climate scenarios (Cetina-Heredia et al. 2015,
Coleman et al. 2017). Trace elemental fingerprinting
is based on the premise that carbonate structures
such as shell or otolith deposited in water masses
with differing physiochemical properties reflect these
differences in the trace elemental composition of
these structures (e.g. Cathey et al. 2012, Kroll et al.
2016, Norrie et al. 2019). Through the sequential
analysis of these structures, the movement of individu-
als can be inferred (e.g. Lazareth et al. 2003, Kroll et al.
Each method of indirectly estimating larval dis-
persal, however, comes with intrinsic uncertainties
(Ashford et al. 2010, Nolasco et al. 2018). Biophysical
particle tracking models, for example, are limited
by the availability and accuracy of the hydrody-
namic and biological data used in their para -
meterisation (Cetina-Heredia et al. 2019). In con-
trast, trace elemental fingerprinting may be limited
by the characterisation of all potential natal loca-
tions (Werner et al. 2007). Therefore, the incorpora-
tion of larval dispersal estimates obtained though
different methods is likely to provide a more accu-
rate picture of larval dispersal. Here, we incorpo-
rated results from both trace elemental fingerprint-
ing and biophysical models to track the dispersal of
green lipped mussels Perna canaliculus (Gmelin,
1791), hereafter mussels, in the FoT in northern
New Zealand, an area with an active shellfish res-
toration effort (Wilcox et al. 2018).
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Norrie et al.: Larval dispersal from bivalve aquaculture
The FoT once supported dense populations of mus-
sels, which were estimated to cover up to 1300 km2;
these were almost completely extirpated by a dredge
fishery in the 1960s (Paul 2012). Despite the cessation
of fishing 50 yr ago, these populations have not
recovered and only a few small remnant wild mussel
beds remain, which cover an area of approximately
0.64 km2(Morrison 2002, McLeod 2009). Currently,
the largest populations of mussels in the FoT are
those farmed on longline aquaculture, which covers
an area of approximately 29 km2and produced
27 196 t of harvested mussels in 2016 (Hauraki Gulf
Forum 2017). There are currently active restoration
efforts in the area which focus on the translocation of
adults and juveniles, primarily from aquaculture,
with the aim of establishing self-sufficient popula-
tions and recovering lost ecosystem function (Wilcox
et al. 2018). Understanding the potential for larval
spill-over from aquaculture to contribute to restora-
tion efforts will provide important information for the
design of restoration programmes in areas where
aquaculture is present, as it will in form locations for
mussel translocations.
The aim of this study was to examine the potential
for larval spill-over of mussels from aquaculture to
provide a larval subsidy to the restoration efforts in
the FoT. This was achieved using a combination of
elemental fingerprinting techniques and biophysical
modelling approaches. We addressed the following
specific questions: (1) What is the potential for disper-
sal of mussles from aquaculture locations throughout
the FoT? (2) How do larval dispersal patterns gener-
ated by 2 different methods, biophysical modelling
and trace elemental fingerprinting, differ? (3) What
are the overall implications of any larval spill-over for
restoration and aquaculture?
2.1. Study species
Green lipped mussels Perna canaliculus are found
in a variety of habitats throughout New Zealand,
both subtidally and intertidally (Morton & Miller
1973). Mussels are broadcast spawners with peak
spawning occurring from late in the austral spring to
early autumn (Alfaro et al. 2001), have a pelagic lar-
val duration of between 3 and 5 wk (Hayden 1995),
and prefer to settle on filamentous substrates such as
macroalgae and hydroids (Alfaro & Jeffs 2002, Alfaro
et al. 2004). Settlement is complete once byssal
threads have attached, after which mussels are
known as plantigrades or spat. Secondary settlement
may then occur through bysso-pelagic drifting from
primary settlement substrate into adult beds (Jeffs et
al. 1999). The distances over which secondary disper-
sal takes place, however, is likely to be orders of
magnitude lower than primary dispersal in the
plankton (Lane et al. 1985, Le Corre et al. 2013,
Pilditch et al. 2015).
2.2. Study area
The FoT is a large estuarine embayment in north
eastern New Zealand, approximately 30 km long and
20 km wide (Fig. 1). Circulation in the region is
tidally driven and predominantly flows north−south,
with current speeds on the ebb and flood tides gen-
erally well balanced (Supplement 1 at
com/ articles/ suppl/ q012 p231 _ supp.pdf [all supple-
ments], Black et al. 2000). East−west flows also occur
but are typically around 10 times weaker than the
north−south currents (Oldman et al. 2007). The FoT
is generally thought to be well mixed with limited
seasonal stratification in late summer (Black et al.
2000, Zeldis et al. 2005). Primary freshwater inputs
are from the Waihou and Piako Rivers, which drain
into the south eastern FoT. These rivers have a com-
bined mean flow of 89 m3 s−1 (O’Callaghan & Stevens
2017). The area zoned for mussel aquaculture oc -
cupies an area of 29 km2and accounts for 30% of
New Zealand’s GreenshellTM (the trade name of P.
canaliculus) mussel production (Hauraki Gulf Forum
2017). These farms are primarily located on the
northern end of the Coromandel Peninsula centred
on Wilson Bay. There are additional farms located
within and around Coromandel Harbour and Man-
aia Harbour and on the western FoT at Waimang
2.3. Biophysical particle tracking
2.3.1. Hydrodynamic model
An 11 yr (1995−2005) hindcast hydrodynamic
model configuration of the regional ocean modelling
system (ROMS), developed by the Meteorological
Service of New Zealand (MetOcean Division), was
used in this study. For a full description of this model
and its validation, see Supplement 1. Briefly, the
model has a spatial grid resolution of 250 × 250 m
over the study area, with hourly model output. Both
atmospheric and tidal forcing were included in the
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Aquacult Environ Interact 12: 231–249, 2020
model, which used bathymetry sourced from Land In-
formation New Zealand (https:// data. linz. govt. nz/ layer/
51278-chart-nz-533-firth-of-thames/). Atmospher ic
forcing was applied at a temporal resolution of 60 min
and spatial resolution of 1 km. Due to the limited
stratification in the FoT (Black et al. 2000, Zeldis et al.
2005), a 2-dimensional approach was used which was
followed by a post-process transformation to obtain
estimates of the depth-dependent currents. A logarith-
mic velocity profile was added to depth-averaged
currents to simulate variations in horizontal water
flow (Le Port et al. 2014). This high-resolution model
was nested within a larger regional model of New
Zealand-wide circulation at a grid size of 5 × 5 km.
The high-resolution model was validated using tidal
elevations obtained from a tide gauge at Tiritiri
Matangi, located approximately 50 km northwest of
the study site (36.605° S, 174.888° E) (Supplement 1).
2.3.2. Lagrangian particle tracking
Using the open source Lagrangian particle track-
ing software OpenDrift v.1.0 (Dagestad et al. 2018),
we simulated individual dispersal trajectories for
particles (representing recently spawned larvae)
re leased from 5 selected aquaculture sites through-
out the FoT (COR, MAN, WP, WB1, WB2; Fig. 1).
Sites were selected to represent areas at which
mussel aquaculture occurs in the FoT. Two sites
were within (COR) or close to the entrance (MAN)
of sheltered harbours; 2 sites represented the large
exposed blocks of mussel farms in the eastern FoT
(WB1 and WB2), and one site represented the
small mussel farms in the western FoT (WP). The
OpenDrift particle trajectory model was coupled to
the hydrodynamic model. A new OpenDrift sub-
model based on the already available ‘PelagicEgg’
Firth of
Waiheke Is.
Ponui Is.
100 km0
New Zealand
Manaia Harbour
36° 50`
36° 50`
36° 40`
37° 10`
36° 59`
175° 28` E
175° 20` 175° 30`175° 10`
175° 30` E
37° 20`
36° 30`
175° E
Wilson Bay
River W1
20 km 10 km
2.5 km
Fig. 1. The Firth of Thames in northern New Zealand, indicating sites used in this study. Blue rectangles: locations from which
particles were released for biophysical modelling; red points: locations at which trace elemental fingerprinting sampling of
Perna canaliculus was undertaken
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Norrie et al.: Larval dispersal from bivalve aquaculture
module was de veloped specifically for mussel larvae
(‘Bivalvelarvae’ model) and is available at https://
github. com/ simonweppe/ opendrift/ blob/ master/
opendrift/ models/ bivalvelarvae. py.
The model operated with an internal timestep
of 15 min. A horizontal diffusion coefficient of
0.1176 m2s−1 was included based on the equations
of Okubo & Ebbesmeyer (1976) to account for
subgrid- scale diffusion. A vertical diffusion con-
stant of 0.01 m2s−1 over a 15 min timestep was in -
cluded to account for turbulence in the fluid envi-
ronment (based on parameters previously used for
bivalve larval dispersal in Lundquist et al. 2004). A
total of 4.9 million particles were released between
the months of December and June, when peak set-
tlement occurred over the years 1995−2005 (Alfaro
et al. 2001, Smith 2019). Release sites were selected
to represent all general areas in which mussel
aquaculture occurs. Particles were evenly released
within polygons delineated by mussel farming oper-
ations (Fig. 1). As management and harvest prac-
tices are consistent within New Zealand (Jeffs et al.
1999) and therefore across the study area, the num-
ber of particles re leased from each site was scaled
to the surface area occupied by each farm. Particles
were released at a density of 10 particles km−2 of
surface area of mussel farm at 2 h intervals to
ensure particles were seeded across the tidal cycle.
Full model parameters are presented in Table 1.
Particles were seeded at random depths within the
water column between 1 and 10 m to simulate the
depth of the dropper lines on which mussels are culti-
vated (Jeffs et al. 1999). No robust information exists
on whether these mussels exhibit active horizontal or
vertical swimming behaviour, though New Zealand
bivalve larvae have been observed to be well distrib-
uted throughout the water column in a large harbour
(Lundquist & Broekhuizen 2012). Particles were
therefore given a terminal sinking velocity of 0.0025
m s−1, which is at the lower range of settling velocities
of larger bivalve larvae and may take into account
some active settlement behaviour (Chia et al. 1984,
Lundquist et al. 2009). Particles were released every
2 h for the full 7 mo settling period (Dec−June) every
year from 1995−2005 and tracked for up to 5 wk.
Age-dependent settlement was included in the model;
if a particle encountered the seafloor or the coast
(settlement habitat) between 3 and 5 wk after release
(the settlement competency window) (Jeffs et al.
1999), it was deemed to have settled and remained at
this location. Particles which did not en counter set-
tlement habitat within this period were re tired from
the model as this is beyond the known pelagic larval
duration of this species (Hayden 1995). Due to the
unavailability of data regarding the survival of mussel
larvae, we assumed that mortality was spatially and
temporally uniform. Thus, we did not include potential
variations in daily mortality rates, but rather report
proportional larval transport from each site.
2.3.3. Biophysical model analysis
Analysis of the OpenDrift output ‘netcdf’ files was
conducted in MATLAB R2018a (MathWorks). Kernel
density estimations (KDEs) were calculated using the
methods of Botev et al. (2010). KDEs represented the
probability that a released particle would settle in a
given location. A total KDE was calculated for all par-
ticles released from all sites in the model. As the total
KDE was dominated by particles released from areas
with high surface area (WB1 and WB2), individual
KDEs for particles released from each site were also
calculated. The total proportion of particles which
encountered suitable settlement habitat relative to
the total number of particles released from each site
over the 11 yr modelled period was also calculated.
2.4. Trace elemental fingerprinting
2.4.1. Study sites
A total of 8 sites within the FoT were selected for
trace elemental fingerprinting (C1−C7, W1; Fig. 1).
Four of these sites were selected as they were within
Variable Value
Horizontal diffusivity 0.1176 m2s−1
Vertical diffusivity 0.01 m2s−1
Turbulent mixing timestep 900 s
Terminal fall velocity 0.0025 m s−1
Minimum settlement age 3 wk
Maximum settlement age 5 wk
Internal timestep 15 min
External timestep 6 h
Density of particles 1 particle per 500 m2of aqua-
released per timestep culture surface area
Particle release depth Randomly between 1 and
10 m depth
Particle release timestep Every 2 h during release
months and years
Release months December−April
Years modelled 1995−2005
Table 1. Parameters used in biophysical modelling of Perna
canaliculus in the Firth of Thames
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Aquacult Environ Interact 12: 231–249, 2020
areas used for longline aquaculture and therefore
potential larval sources. These included 3 of the mod-
elled release sites (C3, C5, and W1). One of these
aquaculture locations was situated in the western
FoT at Waimang Point (W1), 2 were situated within
Coromandel Harbour (C5 and C6), and 1 was situ-
ated within the large mussel farm blocks at Wilson
Bay (C3). The remaining sites were selected as pre-
liminary hydrodynamic modelling indicated they were
within distances over which larvae from these aqua-
culture sites were able to disperse. Additionally, due
to significant and varied anthropogenic modi fication
of the study area over the last 100 yr (Hauraki Gulf
Forum 2017), shell material produced at these sites is
likely to differ in its trace elemental composition. Sites
were generally between 2 and 5 km apart, although
the largest distance between sites was 14.6 km
(W1−C3) and the shortest was 1.5 km (C5−C6).
2.4.2. Field sampling
To determine natural variation in the trace elemen-
tal composition of mussels and establish reference
trace elemental fingerprints within the study area, an
in situ culturing technique was used (e.g. Becker et
al. 2007, Kroll et al. 2018). Whilst previous studies
have employed both moored and drifting in situ cul-
turing methods to develop reference trace elemental
fingerprints with differing results, it is difficult to
establish which is more accurate (Kroll et al. 2018).
We therefore elected to use a moored in situ cultur-
ing method for the development of reference trace
elemental fingerprints. Macroalgae with juvenile
mussels attached were harvested from the low inter-
tidal zone at M ori Bay on the west coast of northern
New Zealand (36.837° S, 174.427° E). This site was
selected due to consistent year-round supply of juve-
niles and spat. Mussels were transported to the
School of Biological Sciences at The University of
Auckland, where individuals between 2 and 8 mm
shell height were removed from the macroalgae and
placed into in situ culturing containers (ICCs).
Although incorporation of elements into shell mate-
rial may vary with age (Strasser et al. 2008), previous
research has shown that these ontogenetic differ-
ences in trace elemental fingerprints are unlikely to
mask spatial differences (Norrie et al. 2016). ICCs
were constructed from 750 ml food-grade, high-
density polyethylene jars with the lids and bases
removed. Each end of the jar was covered with
500 µm Nitex®mesh. This mesh size allowed for flow
of water carrying nutrients but prevented the escape
of animals. At least 20 juveniles were placed into
each ICC, however up to 30 were translocated if
enough animals were collected.
At each site, artificial settlement substrates (SSs)
were deployed in order to collect recent settlers at
each site. Plastic mesh tuffy scrubbing pads (SOS
Tuffy, Clorox) were used as they have been exten-
sively employed in previous settlement studies (re -
viewed by South 2016). Settlement on these substrates
is widely accepted to be a proxy for larval supply
(South 2016). These SSs were deployed with ICCs to
form an experimental unit. To create an experimental
unit, one ICC was attached to a rope at a depth of 7 m
with one SS approximately 10 cm above the ICC and
one 10 cm below. At each site, 3 of these experimental
units were deployed on each sampling event (nSS = 3,
nICC = 3 site−1 per sampling event). Experimental units
were deployed for ap proximately 5 wk, although in-
clement weather events resulted in different deploy-
ment lengths on each sampling occasion (ranging
from 29−55 d) and the loss of all equipment at some
sites for some dates. All sampling occurred over the
austral summer and autumn (Jan−May) in a single
year (2018), as this is a period of high settlement in the
study area (Smith 2019). After retrieval, animals were
removed from each ICC, placed into plastic zip lock
bags, and frozen at −20°C until analysis. Each SS was
placed into a zip lock bag in its entirety, as mussels
are easier to remove from settlement substrate after
freezing and thawing (Smith 2019).
2.4.3. Sample preparation for trace elemental
Mussels from each ICC were defrosted and the
shells were split open. One valve was randomly
selected from each individual and any adhering par-
ticles were removed using stainless steel forceps. We
inspected shells prior to translocation to ensure that
shell material was a dark green. After recovery of
ICCs, shell material with a distinct lighter green
colour band following dark colourations was deemed
to have been deposited in situ (Fig. 2a). The most
recently formed portion of shell with a light green
colour band along the axis of maximum growth was
broken off and mounted onto microscope slides using
double sided adhesive tape. If no distinct colour
changes were observed, shells were not used for ele-
mental analysis.
Settlers collected from 3 SSs at each site on each
sampling occasion were analysed. In the laboratory,
each SS was defrosted and all material was washed
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Norrie et al.: Larval dispersal from bivalve aquaculture
with tap water through a 200 µm sieve. All material
washed off each SS was placed into deionised water
(maintained at a resistivity of <1 MΩcm), and mus-
sels were sorted from this material. Mussels from
each SS were selected and fixed to a microscope
slide with double sided adhesive tape.
2.4.4. Trace element analysis
To determine the trace elemental composition of shell
material, laser ablation inductively coupled plasma
mass spectrometry (LA-ICP-MS) was used. Elemental
analyses were performed using a New Wave deep
ultraviolet (193 nm) laser ablation system (Elemental
Scientific Industries) coupled to an Agilent 7700 ICP-
MS (Agilent Technologies). The laser operated with a
spot size of 50 µm, a repetition rate of 5 Hz, and a
dwell time of 30 s. Laser power was 45% and fluence
was between 7 and 7.5 J cm−2. National Institute of
Standards and Tech nology (NIST) 610 and 612 glass
standards were analysed every 20 spots for standardi-
sation, calculation of internal precision, and calibra-
tion purposes. For full laser operating parameters and
detection limits, see Supplement 2 (Tables S2 & S3).
All analyses were performed at the University of
Auckland Plasma Mass Spectrometry Centre. Initially,
13 elements were monitored (Mn, Li, Co, Mg, B, Ca, Sr,
Zn, Cu, Ti, Ni, Ba, Al). However, preliminary experi-
ments revealed potential contamination from ICCs of
Li, B, and Cu in shell cultured in these containers (Sup-
plement 3), therefore these elements were excluded
from further analyses. On reference shell material de -
posited in ICCs, one LA-ICP-MS spot was performed
on the section of broken off shell approximately 200 µm
from the ventral margin of shells (Fig. 2a). This mate-
rial represented the most recently formed shell. On
naturally settled individuals collected on the SS, the
prodissoconch was analysed (Fig. 2b), as this reflects
shell material formed at the individual’s natal loca-
tion (Becker et al. 2007, Carson et al. 2011).
Data was processed using IOLITE trace elemental
reduction software (Paton et al. 2011). Backgrounds
were monitored for 30 s prior to each analysis. Data
was then background-corrected by subtracting back-
ground average counts from the ablation counts. A
pre-ablation procedure where the first 5 s of the
ICP-MS signal was not included in the data was used
to ensure that possible surface contamination or the
periostracum was not included in the data (Marr et
al. 2011, Norrie et al. 2016). To minimise the possibil-
ity of laser burn through to lower layers in the shell
(Strasser et al. 2007), only the next 10 s of the laser
dwell time was included in analyses. Data was then
standardised using the most recent published NIST610
and NIST612 values (Jochum et al. 2005). All data
was standardised to a trace element:calcium ratio
(TE:Ca) in µmol of each TE to mol of Ca.
2.4.5. Statistical analyses
A discriminant function analysis (DFA) was per-
formed on the TE:Ca ratios of shell material de posited
in the ICCs. This allowed the examination of spatial
variation in trace elemental fingerprints and develop-
ment of site-specific reference signals. Due to differing
covariances, a quadratic DFA (QDFA) was performed.
2 mm
1 mm
Fig. 2. Example of individual Perna canaliculus used for
trace elemental fingerprinting. (a) Individual grown in an
in situ culturing container to develop a reference elemen-
tal fingerprint. Dashed red line: separation between shell
formed prior to translocation and that deposited in situ. (b)
Recently settled individual from an artificial settlement
substrate. Red dots: location of LA-ICP-MS analysis on
each individual
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Aquacult Environ Interact 12: 231–249, 2020
Elements were included stepwise into this QDFA to
determine the optimal suite of elements for classifica-
tion of shell material to its formation location (Dunphy
et al. 2015, Norrie et al. 2016). QDFA statistical analy-
ses were performed in JMP v.13 (SAS Institute). Due to
the loss of sampling equipment at some sites through
weather events over the study period, a QDFA was
performed in which all samples collected from each
site were binned together, regardless of the date col-
lected. This allowed the development of mean trace
elemental fingerprints for each site.
To predict natal origins, the discriminant function
trained with the TE:Ca ratios of shell material de po -
sited in ICCs was then used to assign
the shell material at the umbo of each
shell to a predicted formation location.
As the loss of sampling equipment re -
sulted in differing deployment dura-
tions for SSs, the number of settlers
predicted to have originated from each
site was standardised to a per day set-
tlement rate. Receiver operating char-
acteristic (ROC) curves were generated
for each site to estimate the diagnos-
tic ability of the QDFA. These ROC
curves compared the true positive rate
against the false positive rate. Poste-
rior probabilities of each individual
being correctly assigned to its forma-
tion location relative to other sites
were also calculated in order to pro-
vide estimates of the confidence of
the estimates.
3.1. Biophysical modelling
3.1.1. Lagrangian KDEs
The total KDE of all particles
released from all sites over the 11 yr
modelled period (Fig. 3) indicates the
area with the highest probability of
receiving settlers was located on the
eastern FoT to the north and south of
the WB1 and WB2 release sites. Par-
ticles are likely to settle on the east
and west coasts of the FoT (but not
the south) with a higher likelihood of
coastal settlement on the eastern FoT
than the western FoT. The KDE indi-
cated that benthic settlement is possible throughout
the FoT, although it is concentrated in the east. The
model also suggested a low probability of larvae
being transported from the FoT to the greater Hau-
raki Gulf, particularly the area north of Coromandel
Harbour and between Ponui Island and the main-
land. This total KDE is dominated by particles
released at areas with a high surface area from which
more particles were released, therefore individual
KDEs were generated for particles released from
each site (Fig. 4).
The site-specific KDEs (Fig. 4) indicated that parti-
cles released from sites which were more sheltered
Fig. 3. Kernel density estimates of all settled particles from all Perna canalicu-
lus model release sites over all release dates in the Firth of Thames. Colour
scale: probability that a particle will settle at a given location relative to the to-
tal number of parties released. Arrows: location of particle release locations
that are difficult to see due to their size
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Norrie et al.: Larval dispersal from bivalve aquaculture
settled over a smaller area than those released from
more exposed sites. This can be seen by particles
released from COR exhibiting the highest probability
of settlement in the relatively small area close to the
mouth of Coromandel Harbour (Fig. 4a). Particles
released from MAN also exhibited a high likelihood
of settlement over a relatively small area close to
their release site (Fig. 4b). A number of these parti-
cles, however, settled throughout the FoT, particu-
larly in the area north of Coromandel Harbour.
Fig. 4. Site-specific kernel density estimates of settled Perna canaliculus particles released from (a) COR, (b) MAN, (c) WP,
(d) WB1, and (e) WB2. All settled particles released over the December−June release window during the entire 11 yr period
are shown. Colour scale: portion of particles that settled at each location relative to the total number of particles released from
that site. Arrows: locations of particle release locations
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Aquacult Environ Interact 12: 231–249, 2020
The 3 more exposed sites (WP, WB1, and WB2) had
predicted settlement over wide areas throughout the
FoT. Particles from WP (Fig. 4c) exhibited high settle-
ment probabilities to the south and south east of the
release site, including on the western coast of the
FoT. A number of particles also settled on the eastern
side of the FoT, particularly in the area south of Man-
aia Harbour. Particles released from the WB1 and
WB2 sites (Fig. 4d,e) also settled throughout the FoT.
The settlement patterns of particles released from
these sites was broadly similar, with areas of high
settlement probability located close to their release
site as well as along the eastern coast of the FoT as
far south as the town of Thames. Differences in in the
settlement probabilities between the 2 sites were most
evident in the south and northwest of the FoT. Particles
released from WB1 were likely to settle in the south-
ern FoT close to the Waihou River (Fig. 4d), whilst
particles released from WB2 had a higher probability
of settling in the north western FoT (Fig. 4e).
3.1.2. Spatial differences in the proportion
of settled particles
Only 30% of the 4.9 million particles released be-
tween December and April across the years
1995−2005 encountered suitable settlement habitat
(the coast or seafloor) during the settlement com -
petency window. The remaining 70% of particles
which did not settle were retired from the model. Dif-
ferential settlement rates were observed between
sites (Fig. 5). Highest settlement rates were pre-
dicted for particles released from the relatively shel-
tered sites COR (77% of particles settled) and MAN
(53% settled). Conversely, the more exposed sites
had a much lower proportion of settled particles
which decreased as their distance from the coast in-
creased: 35% of particles released from WP settled,
33% of those released from WB1 settled, and only
23% of particles released from WB2 encountered suit-
able settlement habitat during the settlement compe-
tency period.
3.2. Trace elemental fingerprinting
3.2.1. Spatial variation in trace elemental
Overall, the QDFA on reference shells correctly
classified 72% of individuals to their growth location
using 7 TE:Ca ratios (Mn:Ca, Co:Ca, Ba:Ca, Ti:Ca,
Mg:Ca, Sr:Ca, Zn:Ca) (Table 2). This is highlighted
by the plot of the canonical scores from the QDFA
(Fig. 6) indicating differences between elemental fin-
gerprints of shell grown at different sites. However,
individual site-level classification success was vari-
able. High levels of classification success were
observed at C2 (89%), C3 (100%), C5 (90%), and W1
(92%), indicating unique trace elemental finger-
prints in shells deposited at these sites. Classification
rates of shell material deposited at C1 was moderate,
with 71% of individuals correctly classified. Approx-
imately half of individuals grown at C4 (53%), C6
(55%), and C7 (52%) were correctly classified. The
variability observed in the trace elemental finger-
prints of shell material at C4, C6, and C7 shows that
these sites are more difficult to differentiate based on
their trace elemental fingerprint. The ROC curves
were high for all sites (0.89−0.99), indicating the sen-
sitivity of the QDFA was high (Table 2). Despite the
relatively short distance between C5 and C6 (1.2 km),
there were large differences in the trace elemental
fingerprint of shell material deposited at these sites.
Overall, 90% of individuals from C5 were correctly
classified to their growth site. Classification success at
C6, however, was only 55 % with the majority of mis-
classified individuals attributed to C1, which was
located furthest from C6 at approximately 16 km away.
Release site
Percent of released particles
Fate of
Fig. 5. Percent of Perna canaliculus particles released from
each site which encounter suitable settlement habitat (de-
fined as the seafloor or coast) during the settlement compe-
tency window 3−5 wk after release. Retired: the particle did
not encounter suitable settlement substrate within the set-
tlement competency window and was therefore removed
from the model
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Norrie et al.: Larval dispersal from bivalve aquaculture
3.2.2. Natal locations of recent settlers
The predicted larval origins of recent settlers col-
lected at each of the sites monitored (Fig. 7, Table 3)
suggested that the larval pool in the FoT is well mixed.
Settlers collected at each site were a combination of
larvae produced throughout the study region. A min-
imum of 5 and a maximum of 7 potential natal loca-
tions were predicted for settlers at each site. No set-
tlers at any of the sites collected over the study period
of January−May 2018 were predicted to have origi-
nated at C3. The confidence of the model in assign-
ing individuals to their natal location was high, as
shown by the mean posterior probabilities of correct
assignment to each group ranging from 0.73−0.83
(Table 3) in agreement with the overall classification
success rates of reference shell material (Table 2).
Although overall the larval pool was well mixed,
some sites acted as larval sources and sinks relative to
others. The most important larval source from the per-
spective of the highest number of larvae produced
was C7. Of the individuals which settled at monitored
sites, 30% were predicted to have originated from this
location (1.63 settlers d−1) (Table 3). The high contri-
butions made by C7 were primarily driven by the high
number of settled larvae originating from C7 at W1,
which had the highest settlement rates of all sites
monitored with 2.66 mussels d−1 settling at this loca-
tion (Table 3). A large proportion of larvae which
settled at C1 (48%; 0.28 settlers d−1) and C2 (46%;
0.25 settlers d−1) were also predicted to have origi-
nated from this location. A large proportion of larvae
which settled throughout the study region were also
predicted by the QDFA to have originated at W1 in
the western FoT (0.95 settlers d−1) (Table 3). Self-re-
cruitment was generally low throughout the FoT with
C7 (20% self-recruitment), W1 (14%), and C2 (15%)
exhibiting the highest levels of the sites monitored.
No settlers throughout the FoT were predicted to
have originated at C3 despite the moderate settlement
at this location. Only small numbers of larvae were
predicted to have originated at both C2 and C5; al-
though settlement at C5 was low, a moderate number
of larvae settled at C2. These 3 sites can be considered
larval sinks as few larvae from throughout the FoT
were predicted to have originated at these locations.
This study set out to answer the following ques-
tions. (1) What is the potential for dispersal of Perna
Collection Predicted collection location No. collected No. correct % Correctly classified ROC curve
location C1 C2 C3 C4 C5 C6 C7 W1
C1 89 8 0 2 2 11 6 7 125 89 71.2 0.92
C2 0 25 0 0 0 1 1 1 28 25 89.2 0.97
C3 0 0 13 0 0 0 0 0 13 13 100 0.99
C4 7 5 0 29 2 3 4 4 54 29 53.7 0.93
C5 1 0 0 0 19 1 0 0 21 19 90.4 0.99
C6 3 7 4 2 3 28 1 3 51 28 54.9 0.89
C7 2 0 0 0 4 7 23 8 44 23 52.2 0.94
W1 1 1 0 0 1 2 0 66 71 66 92.9 0.97
No. predicted 103 46 17 33 31 53 35 89 407 292 71.74
Table 2. Classification success rates of Perna canaliculus shell material deposited in the in situ culturing containers between
January and May 2018. All individuals were grouped by site regardless of the dates on which they were collected. Bold values
indicate correct classification to growth site. ROC: receiver operating characteristic
−1 0 1
Canonical score 1
Canonical score 2
Fig. 6. Mean (±SEM) canonical scores from the quadratic
discriminant function analysis examining trace element to
Ca ratios in the shell material of all Perna canaliculus indi-
viduals collected from monitored sites between January and
May 2018
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Aquacult Environ Interact 12: 231–249, 2020
canaliculus from aquaculture locations throughout
the FoT? (2) How do larval dispersal patterns gener-
ated by biophysical modelling and trace elemental
fingerprinting differ? (3) What are the overall impli-
cations of any larval spill-over for restoration and
aquaculture? The results of both the trace elemental
fingerprinting study and the biophysical modelling
indicated that there is potential for larval spill-over
from aquaculture to areas throughout the FoT. The
larval pool in the FoT is likely to be well mixed, with
larvae from all sites potentially contributing settlers to,
and receiving settlers from, other locations. Al though
the results of both approaches showed similar broad-
scale results, different dispersal pathways were pre-
dicted by each technique. These dif-
ferences high light the importance of
incorporating multiple tracking tech-
niques for a holistic un der standing of
larval dispersal patterns. Together, our
results provide the first evidence, to
our knowledge, that larvae produced
in aquaculture can assist in the resto-
ration of degraded wild bivalve popu-
lations through a larval subsidy).
4.1. What is the potential for
dispersal of P. canaliculus
from aquaculture locations
throughout the FoT?
Both biophysical modelling and trace
elemental fingerprinting indicated the
Waimang Point mussel farms (WP, W1)
were likely to be a source of mussel lar-
vae which settle throughout the study
area. In addition to contributing larvae
to several sites, high settlement rates at
this location also indicate that Wai -
mang Point receives settlers from sev-
eral locations. In a restoration context,
the fact that this location may both re-
ceive and contribute larvae highlights
the potential importance of this site in
regional population dynamics. Restora-
tion of benthic mussel beds at this site
may provide habitat for larvae pro-
duced in other areas of the FoT as well
as contribute larvae to other popula-
tions in the area.
Trace elemental fingerprinting pre-
dicted that the area to the north of
Coromandel Harbour (C7) is an impor-
tant larval source for settlers throughout the study
area despite no known populations existing at this
location. The biophysical model predicted settlement
at this location was likely to be high, particularly for
larvae released from Manaia and Coromandel Har-
bours (MAN and COR). One such explanation for this
result may be that early stage larvae dispersing past
this location incorporate elemental fingerprints from
this site, although this is unlikely as hydrodynamic
modelling indicated larvae in this area are retained
close to their natal location for several days. Alterna-
tively, these results present the possibility that a pop-
ulation exists at this location supported by aquacul-
ture which may then in turn act as a source of larvae
10 km
2.5 km
Manaia Harbour
Firth of
Fig. 7. Proportional natal locations of Perna canaliculus settling at monitored
locations throughout the Firth of Thames as predicted by the quadratic dis-
criminant function analysis trained using shell material deposited in situ at
these locations. Coloured square adjacent to the site names (W1−C7): colour
codes of settlers originating from these sites. Note the size of circle indicates
the number of settlers at each site standardised per day (Table 3)
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Norrie et al.: Larval dispersal from bivalve aquaculture
for other sites in the FoT. This demonstrates the
power of integrating the results of the 2 methods. The
possibility of this stepping stone dispersal (Kimura &
Weisss 1964, Palumbi 2003) highlights the need to
consider system-wide connectivity into management
actions based on source−sink dynamics (Kininmonth
et al. 2011). Future surveys of potential mussel popu-
lations in the FoT should investigate this location to
determine the presence of a population at this location
which may supply larvae throughout the study area.
There are several larval sinks in the FoT study
area. The area with the highest probability of settle-
ment as predicted by the biophysical model was
located to the south of Manaia Harbour, with larvae
from each release site capable of settling at this loca-
tion. Trace elemental fingerprinting also demonstrated
that larvae settling in this area (C1, C2) likely origi-
nated from multiple sources. This finding is impor-
tant as the area is known to support one of the few
extant populations of mussels in the FoT (A. Jeffs,
University of Auckland, pers. comm.), suggesting that
aquaculture may already be supporting this popula-
tion. The biophysical model also predicted that the
area to the south of the Wilson Bay mussel farms
would have high rates of settlement. Although this
location currently supports no known populations of
mussels, it is anecdotally known by local mussel
farmers to be an area of high spat settlement (Smith
2019). Moderate settlement was also observed on
artificial SSs in this area (C1, C2).
The similarity between the 2 methods of estimating
larval dispersal shows that decisions on management
in the study area based on this data can be made with
a high degree of confidence and highlights the
advantages of employing multiple techniques. The
restoration of settlement habitat at these sink loca-
tions may allow the recovery of benthic mussel pop-
ulations in this area due to high larval supply. Al -
though adults are able to survive in this area (McLeod
et al. 2012), it is important to consider factors which
may prevent the survival of larvae or juveniles both
during and after dispersal (Brandt et al. 2008, Pineda
et al. 2010, Shima et al. 2015).
4.2. How do the 2 methods of estimating larval
dispersal differ?
Although the overall pattern of a well-mixed larval
pool in the FoT was demonstrated by both methods of
tracking larvae, several differences in the pathways
of dispersal were observed. These differences high-
light the need to integrate multiple techniques of
estimating larval dispersal and population connectiv-
ity to obtain a clearer picture of dispersal patterns
(Ashford et al. 2010, Nolasco et al. 2018). The pri-
mary difference was the lack of settlers attributed to
the large mussel farm blocks off Wilson Bay (WB1,
WB2, C3) by trace elemental fingerprinting despite
the prediction of the biophysical model that settlers
Collection Predicted natal location Total No. of days settlement Settlement
location C1 C2 C3 C4 C5 C6 C7 W1 no. substrate deployed rate
settled (no. of deployments) (mussels d−1)
C1 7 3 0 8 0 3 28 9 58 98 (2) 0.59
C2 6 12 0 8 5 2 36 8 77 139 (3) 0.55
C3 8 0 0 10 0 16 9 13 56 84 (2) 0.67
C4 3 2 0 2 0 6 4 5 22 98 (2) 0.22
C5 1 1 0 1 0 3 14 4 24 84 (2) 0.29
C6 8 3 0 0 0 3 2 1 17 139 (3) 0.12
C7 4 0 0 1 0 12 9 19 45 139 (3) 0.32
W1 43 10 0 39 14 34 61 36 237 89 (2) 2.66
Total no. predicted 80 31 0 69 19 79 163 95 536 0.6775
natal origin
Settler contribution 0.82 0.28 0 0.74 0.2 0.82 1.63 0.95
rate (mussels d−1)
Mean posterior prob- 0.8 0.73 0.77 0.8 0.77 0.83 0.82
ability (±SEM) (±0.02) (± 0.03) (±0.02) (± 0.05) 0.02) 0.01) 0.01)
Table 3. Predicted formation locations of Perna canaliculus shell material at the prodissoconch of individuals which settled at
monitored sites in the Firth of Thames between January and May 2018. As weather events resulted in non-standard deploy-
ment times for settlement substrates, standardised settlement per day was calculated. Settler contribution rate was calculated
as the number of settlers per day of sampling which were predicted to have originated at each site
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Aquacult Environ Interact 12: 231–249, 2020
from this location would dominate settlement patterns
throughout the study area. The biophysical model
also predicted that larvae produced within Coroman-
del Harbour (COR, C5, C6) would be retained in this
area, although this was not shown to be the case in
by trace elemental fingerprinting techniques. Several
possible explanations exist for the differences be -
tween the 2 methods of tracking the dispersal of lar-
vae in the FoT.
It is likely that the variation in temporal scales over
which the 2 studies were conducted was responsible
for the differences observed. While the biophysical
model considered circulation patterns over a 10 yr
period, trace elemental fingerprinting only examined
settlement patterns over a single spawning season. It
is unlikely that dispersal patterns within a single year
will fit with the 10 yr mean, as inter-annual variation
in potential dis persal distances exists (Norrie 2019).
This suggests that an extended sampling period
should be undertaken to determine if long-term
trends ob served through different techniques agree.
In addition to possible variations in circulation, envi-
ronmental conditions in areas of predicted high set-
tlement may not have been suitable for the survival
and settlement of larvae. The study area experienced
heat wave conditions over the period in which field
sampling was conducted (Jan−May 2018) (Herring et
al. 2019), with reports of high mortality of mussels in
aquaculture operations. This may have reduced both
larval production at some locations as well as re -
duced the survival of larvae.
Additionally, there was variation in settlement
rates predicted by the biophysical model between
sites. These differences were driven by the rate at
which larvae encountered potential settlement habi-
tat within the time period in which settlement is pos-
sible. These results show that sites which produce
the highest numbers of larvae may not necessarily
contribute the highest numbers of settlers to popula-
tions. These differences in the rates at which larvae
encounter settlement habitat have the potential to
interact with direct stresses placed on an individual
as it disperses, such as predation, as well as indirect
dispersal stresses which may reduce post-settlement
survival (Nanninga & Berumen 2014). Differences
between the results of biophysical modelling and
trace elemental fingerprinting highlight the need to
consider realised dispersal and include empirical
data into predictions of larval dispersal (Pineda et al.
2007). The similarities in overall patterns between
the 2 methods employed in the current study high-
light the utility of using computer-based simulations
to guide the application of empirical validation
experiments. These empirical experiments may then
provide feedback towards validation and parameter-
isation of future models.
4.3. What are the implications overall for restoration
and aquaculture?
The overall finding of larval spill-over from aqua-
culture has important consequences for the restora-
tion and recovery of depleted bivalve populations. To
our knowledge, this is the first study which demon-
strates that bivalve aquaculture in coastal waters has
the potential to provide a larval subsidy to relict and
restored bivalve reefs and therefore assist with their
recovery. This research shows that if bivalve aqua-
culture is conducted in an area with degraded bi -
valve populations, spill-over from these locations
should be explicitly considered in restoration pro-
grammes. This research also shows that a network
approach should be taken to restoration which in -
cludes connectivity between sites.
If larval spill-over from aquaculture to natural pop-
ulations results in the recovery of degraded popula-
tions or assists with restoration efforts, connectivity to
these locations should be maximised. This highlights
the potential benefits of a network approach to resto-
ration. The need for network approaches in marine
reserve design is well known (e.g. Almany et al.
2007, Gaines et al. 2010, Green et al. 2015, Puckett &
Eggleston 2016, Coleman et al. 2017), and these
approaches should be translated to the design of
restoration programmes. Where larval spill-over is
desirable, additional bivalve aquaculture locations
should be carefully planned in the context of the sys-
tem in which this culturing takes place to ensure that
larval spill-over to natural populations is enhanced.
New restoration efforts should also be considered in
the context of new or existing bivalve aquaculture to
determine locations at which effort should be applied
in order to maximise the chances of success (Arnold
et al. 2017). The inclusion of aquaculture populations
may simplify these network approaches, as many
aquaculture populations are restocked after harvest
resulting in relatively stable populations without the
need to receive settlers.
It is also important to consider the possibility that
larval export from aquaculture may negatively affect
local populations of bivalves. The escape of finfish
from farming operations has been shown to have
potentially deleterious consequences on wild popula-
tions through the reduction of genetic diversity
(Jørstad et al. 2008, Morris et al. 2008, Jensen et al.
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Norrie et al.: Larval dispersal from bivalve aquaculture
2010). In bivalves, genetic introgression to wild stocks
has also been demonstrated which may result in
reduced fitness in the wild population (Apte et al.
2003). In cases where natural populations of a bi -
valve species exist, strategies which minimise poten-
tial larval export from aquaculture should be imple-
mented. Potential strategies may include careful
placement of aquaculture where settlement of larvae
is unlikely, or the implementation of hatchery tech-
niques such as spawning triploid bivalves with lower
reproductive fitness (e.g. Honkoop 2003, Jouaux et
al. 2010). In the case of the FoT, however, no large
natural populations exist, making negative conse-
quences less likely at present.
4.4. Future directions
This study has provided important insight into lar-
val dispersal patterns from aquaculture and their
interactions with restoration. However, to under-
stand the ecological consequences of this dispersal it
is essential that the survival to reproduction is quan-
tified (Pineda et al. 2007, Nanninga & Berumen
2014). Several stressors may prevent the establish-
ment of mussel reefs despite high larval supply
(Burgess et al. 2012). In addition to spatio-temporal
variation in mortality (White et al. 2014, Pineda &
Reyns 2018), physiological stresses placed on an indi-
vidual during dispersal, or post-settlement stresses
may result in decreased fitness or lower reproductive
output (Baker & Rao 2004, Burgess & Marshall 2011,
Shima et al. 2015). Quantifying these stressors is
essential for the selection and further assessment of
viability of restoration sites, as larval supply and set-
tlement will not result in a sustainable population if
settlers do not survive. It is also important to quantify
larval production in order to more accurately para-
meterise biophysical models and reconcile differ-
ences between modelled and empirically determined
dispersal. For example, to better parameterise mod-
els, sites likely to receive high settlement as deter-
mined by modelling and empirical methods should
now be monitored over long time scales in order to
better understand inter- and intra-annual variation in
larval production over the spatial extent of this study.
Additionally, some locations are likely to result in
lower larval output due to differences in the size
structure of the population and age-dependent fecun-
dity (Ren & Ross 2005). This is particularly important
in an aquaculture setting where harvests occur at a
relatively small size, which may reduce larval pro-
duction relative to wild populations.
Understanding the consequences of varying dis-
persal distances is also important in the context of cli-
mate change. Changing ocean conditions such as
salinity and temperature may result in changes in
hydrodynamic flows on a number of scales (Wu et al.
2012, Sen Gupta et al. 2015). As these changes in
hydrodynamic flows will directly affect the potential
dispersal of larvae, it is important that changes in
realised connectivity are considered (Coleman et al.
2011, 2017). Modelling exercises, for example, have
shown that while oceanic circulation changes may
affect larval transport, faster development and there-
fore earlier settlement (related to temperature) could
override the effects of these changed transport path-
ways (Cetina-Heredia et al. 2015) or vice versa. It is
also important to consider that faster development of
larvae in warmer waters will only occur if the supply
of nutrients is high enough to support this develop-
ment; however, the distribution of plankton is also
likely to change, which may decrease larval growth
rates and even possibly increase mortality rates
(Munday et al. 2009, Andrello et al. 2015). Finally, the
possibility of employing methods such as those used
by Nolasco et al. (2018), which explicitly incorporate
the results of biophysical models and trace elemental
fingerprinting into a single statistical framework,
could prove very powerful.
Acknowledgements. C.N. was supported by a UoA doc-
toral scholarship. Funding for fieldwork and laser analyses
were provided by NIWA Coasts and Oceans core funding
(COME1903). The hydrodynamic model was developed
by MetOcean Solutions. M.R. was partially supported by
the Moana Project (, funded by
the New Zealand Ministry of Business Innovation and
Employment, contract number METO1801. Stuart Morrow
from the UoA mass spectrometry centre aided with ele-
mental analyses. Alex Vincent aided with figures. Jessica
Bailey assisted in the laboratory. Fieldwork assistance
was provided by Scott Edhouse, David Bremner, Peter
Schlegel, Esther Stuck, Peter Browne, Errol Murray, and
Jenny Hillman. Alan Bartrom of Gulf Mussels provided
logistical support. Thanks to the Miller lab at OSU for
their input on a draft of the manuscript. We also thank 2
anonymous reviewers and the editor for their constructive
feedback which greatly improved previous versions of the
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Submitted: February 27, 2020; Accepted: May 7, 2020
Proofs received from author(s): June 10, 2020
Author copy
... While much of the shellfish aquaculture industry re lies on wild mussel settlement, it also has the potential to impact this same supply, as cultured mussels may produce or consume enough larvae to influence local settlement levels (Norrie et al. 2020, Ridlon et al. 2021. However, the direction and extent of the influence that aquaculture-based shellfish populations may have on mussel settlement is largely unknown. ...
... Larval production from dense aquaculture aggregations is often overlooked in research into benefits of shellfish aquaculture (e.g. Newell 2004, van der Schatte Olivier et al. 2020, despite some modelling demonstrating that enhanced larval subsidies from mussel farms have the potential to increase the settlement rates of local larvae (Norrie et al. 2020). Conversely, shellfish aquaculture may also reduce settlement rates, as farmed shellfish may exhaust the local carrying capacity (Waite et al. 2005, Duarte et al. 2008, Wijsman et al. 2018, hindering the survival of wild settlers. ...
... Previous biophysical modelling and trace elemental fingerprinting indicated that mussel aquaculture in northern New Zealand could provide a source of larvae capable of settling throughout the surrounding environment (Norrie et al. 2020). However, it was not possible in this previous study to distinguish whether the captured settled mussels were sourced from broodstock in aquaculture or wild populations. ...
Full-text available
Wild shellfish reefs have been decimated in many parts of the world over the last century, diminishing their vital ecological roles as habitat generators and the ecosystem services they provide, such as water filtration. Over this same timescale, shellfish aquaculture has rapidly expanded to become an impressive global industry with an annual worldwide production worth US$35.4 billion in 2020. Both wild reefs and aquaculture operations typically rely on abundant shellfish settlement levels to maintain their respective populations. At the same time, shellfish aquaculture has the potential to influence settlement, as the addition of cultured shellfish to an ecosystem increases the quantity of reproductive adults and may therefore increase settlement rates. Alternatively, shellfish aquaculture may lead to an overall reduction in settlement in an ecosystem, either directly through cannibalistic consumption of larvae or indirectly by straining carrying capacity. We assessed the role of marine shellfish aquaculture on settlement by comparing changes in the abundance of settling green-lipped mussels Perna canaliculus with the expansion of mussel farms at the north end of New Zealand’s South Island over a 47 yr timespan. Overall, mussel settlement did not increase over this period despite an estimated 16000-fold increase in the number of mussels living in the region as mussel aquaculture proliferated. The disconnect between the extent of mussel settlement and mussel aquaculture was consistent across 3 separate areas within the region, suggesting that aquaculture mussels may be unable to produce larvae capable of settlement and emphasizing the importance of wild mussel populations for ecosystem resilience.
... This complementary approach illustrates how oceanographic drivers have the potential to influence genetic exchange among populations, including those separated by long distances. Many particle modelling studies have focused on the larval dispersal of shallow-water, coastal marine invertebrates (e.g., mussels 46,47 ; scallops 35,48,49 ; and lobsters 36,50 ), which are typically influenced by more physically complex coastline and associated hydrodynamic processes compared with generally less complex bathymetry of deep water on continental shelf margins. In contrast, in deep sea species, which frequently have enormous distribution ranges, larval dispersal relies on broad scale hydrographic processes. ...
... We selected particle tracking parameters based on previous hydrodynamic modelling of invertebrate larval dispersal in New Zealand 46,105,106 . One hundred representative particles were released on the surface from evenly spaced locations within each sampled area (encapsulating the trawl area; Fig. 1) on each release step (every 6 h between 1 January 2008 and 31 December 2008; n = 146,100), and their movements tracked to estimate the mean direction and duration of particle movement between SCIs. ...
Full-text available
The emergence of high resolution population genetic techniques, such as genotyping-by-sequencing (GBS), in combination with recent advances in particle modelling of larval dispersal in marine organisms, can deliver powerful new insights to support fisheries conservation and management. In this study, we used this combination to investigate the population connectivity of a commercial deep sea lobster species, the New Zealand scampi, Metanephrops challengeri , which ranges across a vast area of seafloor around New Zealand. This species has limited dispersal capabilities, including larvae with weak swimming abilities and short pelagic duration, while the reptant juvenile/adult stages of the lifecycle are obligate burrow dwellers with limited home ranges. Ninety-one individuals, collected from five scampi fishery management areas around New Zealand, were genotyped using GBS. Using 983 haplotypic genomic loci, three genetically distinct groups were identified: eastern, southern and western. These groups showed significant genetic differentiation with clear source-sink dynamics. The direction of gene flow inferred from the genomic data largely reflected the hydrodynamic particle modelling of ocean current flow around New Zealand. The modelled dispersal during pelagic larval phase highlights the strong connectivity among eastern sampling locations and explains the low genetic differentiation detected among these sampled areas. Our results highlight the value of using a transdisciplinary approach in the inference of connectivity among populations for informing conservation and fishery management.
... yet few studies have documented such contributions. 59,60 In perhaps the best-known example of restorative aquaculture, Norrie et al. 60 found quantitative evidence, both from validated larvae dispersal models and trace elemental shell fingerprinting, that green lipped mussel (Perna canaliculus) larvae originating from shellfish farms contribute to the wild settlement of mussel spat and the rebuilding of mussel reefs in New Zealand. Incorporating ecosystem services and spatial planning in farm design can improve restoration feasibility and outcomes for nature, 13,60 but additional research is necessary to confirm the effectiveness of this type of restorative aquaculture contribution. ...
... yet few studies have documented such contributions. 59,60 In perhaps the best-known example of restorative aquaculture, Norrie et al. 60 found quantitative evidence, both from validated larvae dispersal models and trace elemental shell fingerprinting, that green lipped mussel (Perna canaliculus) larvae originating from shellfish farms contribute to the wild settlement of mussel spat and the rebuilding of mussel reefs in New Zealand. Incorporating ecosystem services and spatial planning in farm design can improve restoration feasibility and outcomes for nature, 13,60 but additional research is necessary to confirm the effectiveness of this type of restorative aquaculture contribution. ...
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Aquaculture is the fastest growing form of food production across the globe. The expansion of the industry has brought about a diversity of approaches to mitigate social and ecological impacts associated with aquaculture production systems. At the same time, there is a growing interest in utilizing aquaculture for conservation purposes including species recovery, habitat restoration and offsetting the impacts of wild capture on vulnerable harvested species. The diversification of the aquaculture sector and the overlapping use of terminology to describe alternative aquaculture approaches can create challenges for policy makers, managers and industry practitioners. Clear distinction between alternative aquaculture approaches and intent may improve regulatory, permitting, monitoring and consumer awareness outcomes. Here, we examine the use of four primary aquaculture approaches in the scientific literature: ‘commercial aquaculture’, ‘conservation aquaculture’, ‘restorative aquaculture’ and ‘regenerative aquaculture’ to elucidate the similarities and differences and improve understanding of the approaches. We propose definitions for the terms based on empirical analysis of related words used in scientific texts and fitness into a particular initiative. In addition, we discuss the use of those terms within the context of benefits to ‘people and nature’, namely activities that include economic, social and environmental outcomes and the variability therein. Clear definition of terms and related activities in a burgeoning field can minimize semantic confusion while improving opportunities to craft robust policy guidelines and improve stakeholder understanding and practice of aquaculture activities.
... The outcomes below are also not mutually exclusive; a single aquaculture activity may deliver several. For example, a native shellfish farm operating in an area where wild counterparts have undergone historical declines may deliver positive outcomes for species recovery and habitat restoration, especially if the farmed shellfish carry locally adapted wild-type genes (e.g., Norrie et al., 2020). Further, if the area is eutrophic or turbid, filtering and nutrient assimilation by farmed shellfish can also provide a bioremediation outcome (e.g., Petersen et al., 2014). ...
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A range of conservation and restoration tools are needed to safeguard the structure and function of aquatic ecosystems. Aquaculture, the culturing of aquatic organisms, often contributes to the numerous stressors that aquatic ecosystems face, yet some aquaculture activities can also deliver ecological benefits. We reviewed the literature on aquaculture activities that may contribute to conservation and restoration outcomes, either by enhancing the persistence or recovery of one or more target species or by moving aquatic ecosystems toward a target state. We identified 12 ecologically beneficial outcomes achievable via aquaculture: species recovery, habitat restoration, habitat rehabilitation, habitat protection, bioremediation, assisted evolution, climate change mitigation, wild harvest replacement, coastal defense, removal of overabundant species, biological control, and ex situ conservation. This list may be expanded as new applications are discovered. Positive intentions do not guarantee positive ecological outcomes, so it is critical that potentially ecologically beneficial aquaculture activities be evaluated via clear and measurable indicators of success to reduce potential abuse by greenwashing. Unanimity on outcomes, indicators, and related terminology will bring the field of aquaculture-environment interactions into line with consensus standards in conservation and restoration ecology. Broad consensus will also aid the development of future certification schemes for ecologically beneficial aquaculture.
... Larval dispersal events were simulated using OpenDrift, an open source Lagrangian particle tracking tool implemented in Python (Dagestad et al., 2018). All simulations were performed offline using a module specifically developed for bivalve larvae (a version of the module described in Norrie et al., 2020). The domain of the model was divided into a 0.1 x 0.1 degree grid (~10 x 10 km), and one grid cell was chosen to represent each of the mussel sampling sites. ...
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Understanding how ocean currents affect larval transport is crucial for understanding population connectivity in sessile marine invertebrates whose primary dispersal opportunity occurs during the pelagic larval stage. This study used Lagrangian particle tracking experiments to examine population connectivity in New Zealand green-lipped mussels (Perna canaliculus) at the national scale. Predicted patterns of larval dispersal were compared to published multi-locus microsatellite data of observed population genetic structure. Estimates of oceanographic circulation correlated significantly with FST, and we conclude that hydrodynamic processes are important in driving genetic connectivity. However, no evidence was found for an oceanographic barrier to gene flow south of Cook Strait, an important feature of genetic structure observed across several marine invertebrate species. Discrepancies between genetic and biophysical data may be explained by several factors including the different timescales of connectivity described by the two methods and the impact of localised ecological conditions and corresponding adaptations in genetic structure not captured by the bipohysical model. Population genetic analyses provide empirical data on realised connectivity and Lagrangian particle tracking experiments reveal information about directionality and asymmetry of connections that often cannot be determined by molecular analyses alone, thus a multidisciplinary approach is recommended.
... Examining these past dispersal events alongside oceanographic conditions can show both patterns and drivers of connectivity and recruitment. Particle tracking techniques have been applied successfully in many investigations at scales from small embayments (Norrie et al. 2020) to global oceans (Doblin and van Sebille 2016). Further, these techniques have been applied to a variety of taxa including microbes (Doblin and van Sebille 2016), kelp (Coleman et al. 2013), invertebrates (Everett et al. 2017; and fish (Schilling et al. 2020). ...
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Context. The spanner crab (Ranina ranina) stock of eastern Australia is distributed across two state jurisdictions and, as a non-migratory species with a pelagic larval phase, connectivity within this stock is likely to occur by larval dispersal, driven by ocean currents. Aims. To understand connectivity and patterns of larval supply in the eastern Australian spanner crab stock. Methods. Lagrangian particle tracking methods were used to simulate larval transport around the key spanner crab fishing regions in eastern Australia. Key results. Spawning off central Queensland (Qld) supplies a large proportion of recruits, supporting both the Qld and New South Wales (NSW) fisheries. Lagged larval settlement showed significant correlations to catch-per-unit-effort and the proportion of total harvest taken within the NSW fishery, providing evidence to suggest that the NSW fishery may be reliant on spawning activity in Queensland. Conclusions. The Qld and NSW fisheries are highly connected and the broad-scale patterns identified by the current modelling approach could provide an indicator of potentially good or bad recruitment years, particularly as finer resolution, and refined reproductive biology knowledge on spanner crabs becomes available. Implications. The Qld and NSW fisheries are highly connected with a source-sink structure and it is recommended that a co-management strategy be adopted.
... Quantitative estimates of population connectivity can be obtained by coupling high-resolution oceanographic models with Lagrangian particle tracking to simulate larval dispersal (North et al., 2009;van Sebille et al., 2018). These methods have been applied from regional Schilling et al., 2020) to global scales (Doblin & Van Sebille, 2016), providing estimates of connectivity for a variety of taxa, such as macroalgae (Coleman et al., 2011(Coleman et al., , 2013, sea urchins (Coleman et al., 2017), crustaceans Everett et al., 2017;Roughan et al., 2005), bivalves (Norrie et al., 2020) and fish (Schilling et al., 2020). When spawning locations (i.e., 'sources') are known, particles can be tracked forwards-in-time, providing estimates of settlement magnitude that can be related to observed settlement and recruitment or patterns in fisheries productivity (Everett et al., 2017;Schilling et al., 2020). ...
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Larval dispersal and connectivity have important implications for fisheries management , especially for species with life cycles influenced by ocean boundary currents. Giant Mud Crab (Scylla serrata) and Blue Swimmer Crab (Portunus armatus) are two estuarine portunid crabs (Family: Portunidae) that support significant commercial and recreational harvest in eastern Australia. Giant Mud Crab migrate to coastal waters to spawn, and while Blue Swimmer Crab spawn primarily within estuaries they occasionally migrate to coastal waters to spawn, followed by larval dispersal in the East Australian Current (EAC). Here, we coupled a high-resolution oceanographic model with a Lagrangian particle tracking framework to simulate larval dispersal and determine the extent of population connectivity in this region. Our simulations indicate broad-scale connectivity (~40-400 km), characterised by high inter-estuary connec-tivity. Overall, our results suggest a north-to-south source-sink structure for both species, with contributions of particles from the north ranging from 51% to 99%. Recruitment to a given estuary is dependent on the proximity of mesoscale oceanographic features of the EAC. Most notably, the EAC separation acts as a barrier to recruitment between spawning and settlement to the north/south of this region. This significantly limits interjurisdictional connectivity for these species, especially Blue Swimmer Crab, likely due to a shorter pelagic larval duration than Giant Mud Crab. Our results provide evidence to inform the assessment and management of these species.
... Although, traditional benthic survey methods (e.g., grabbing, diving or video) may not be feasible and cost-effective at large spatial scales, other approaches, such as acoustics surveys (Morrison et al., 2010) and remote sensing (Herlyn, 2005;Westinga et al., 2021), may be applicable. If wild populations of adult mussels can be identified and delimited, adults can be compared to industry-caught spat using molecular approaches or shell biochemistry to ascertain parental relationships (Dunphy et al., 2011;Gardner et al., 2021;Norrie et al., 2020). For example, parent populations of M. edulis in the Gulf of Maine have been successfully identified using shell biochemistry (Sorte et al., 2013). ...
Mussel aquaculture is heavily reliant on wild mussel populations that supply juveniles (spat) for seeding farms. However, little is often known about parent populations, representing a risk for the sustainability of the industry. We used hydrodynamic back-tracking models to identify potential parental areas that provision green-lipped mussel (Perna canaliculus) spat across a range of settlement sites in New Zealand's largest aquaculture area. Median parental area varied considerably between 19 km² for sites located in enclosed bays and a maximum of >1150 km² for sites located in open bays. Median distance to parent populations ranged between 1.8 and 21.4 km, with a maximum larval dispersal estimated to be ca. 100 km. Small seasonal variations in parental area and dispersal distance were detected in some regions, whereas inter-annual variability was relatively minor. Regional connectivity between settlement and parental regions ranged between a minimum of 45% of larvae originating in the same parental region, to maximum retention rates of 99.9% for sites in enclosed bays, implying a considerable regional variation in the potential for self-seeding and exporting mussel larvae other areas. Our results also delineate areas that support spatfall by identifying likely locations for wild or farmed parental populations, and by establishing the spatial extent where mussel reproduction and larval development through to settlement take place. These dispersal and connectivity patterns are crucial to support management decisions for the conservation and restoration of parental populations, and other environmental constraints, such as water quality, which are necessary to ensure the sustainability of spat catching operations that enable shellfish farming.
... Lagrangian particle tracking driven by velocity outputs from a hydrodynamic ocean circulation model is a useful tool with which to investigate the transport pathways of water and particulates in space and time (e.g., Roughan et al., 2003Roughan et al., , 2011Cowen et al., 2006;Cetina-Heredia et al., 2019). Passive particles can be used to represent zooplankton (Roughan et al., 2005a;Cetina-Heredia et al., 2019b;Norrie et al., 2020), nutrients (e.g., Cetina-Heredia et al., 2018), kelp (e.g Coleman et al., 2011, watermasses (Roughan et al., 2003;Cetina-Heredia et al., 2014), oil (Paris et al., 2012) or other tracers in order to identify typical dispersal pathways under present and future scenarios (e.g., Cetina-Heredia et al., 2015). ...
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The region where the East Australian Current (EAC) separates from the coast is dynamic and the shelf circulation is impacted by the interplay of the western boundary current and its eddy field with the coastal ocean. This interaction can drive upwelling, retention or export. Hence understanding the connection between offshore waters and the inner shelf is needed as it influences the productivity potential of valuable coastal rocky reefs. Near urban centres, artificial reefs enhance fishing opportunities in coastal waters, however these reefs are located without consideration of the productivity potential of adjacent waters. Here we identify three dominant modes of mesoscale circulation in the EAC separation region (~31.5−34.5°S); the ‘EAC mode’ which dominates the flow in the poleward direction, and two eddy modes, the ‘EAC eddy mode’ and the ‘Eddy dipole mode’, which are determined by the configuration of a cyclonic and anticyclonic eddy and the relationship with the separated EAC jet. We use a Lagrangian approach to reveal the transport pathways across the shelf to understand the impact of the mesoscale circulation modes and to explore the productivity potential of the coastal waters. We investigate the origin (position and depth) of the water that arrives at the inner-mid shelf over a 21-day period (the plankton productivity timescale). We show that the proportion of water that is upwelled from below the euphotic zone varies spatially, and with each mesoscale circulation mode. Additionally, shelf transport timescales and pathways are also impacted by the mesoscale circulation. The highest proportion of upwelling (70%) occurs upstream of 32.5°S, associated with the EAC jet separation, with vertical displacements of 70–120 m. From 33 to 33.5°S, water comes from offshore above the euphotic layer, and shelf transport timescales are longest. The region of highest retention over the inner shelf is immediately downstream of the EAC separation region. The position of the EAC jet and the location of the cyclonic eddy determines the variability in shelf-ocean interactions and the productivity of shelf waters. These results are useful for understanding productivity of temperate rocky reefs in general and specifically for fisheries enhancements along an increasingly urbanised coast.
In this study, a high-resolution one-way nested, hindcast ROMS model was developed to analyse the coastal circulation and Lagrangian statistics within the Bay of Plenty (BoP) region in Aotearoa, New Zealand. The Bay of Plenty Model (BoPM) was statistically evaluated against a set of multiple remote sensing and in situ observations from 2003-2004, forming the analysis period for this study. Overall, the BoPM possesses good skill reproducing ocean water temperature, salinity, sea level and water column velocity over tidal and non-tidal timescales (Willmot skill ¿0.8 for most variables). Root-mean-squared errors of <1 °C for ocean water temperature, ≈0.15 for salinity (an exception present during winter), <8 cm s⁻¹ for water column velocity and 0.09 m for non-tidal sea surface height are achieved. Over the 2-year period, nearshore modelled sea surface currents are correlated to local wind forcing on the western and central region of the BoP consistent with coastal wind-driven upwelling dynamics. Up to 30% of the cross-shelf current variability is explained by along-shore wind stress, consistent with previous observational studies. Meanwhile, the eastern region has no significant correlation to the along-shore winds, suggesting other forcings must be considered. Circulation patterns and Lagrangian statistics under two distinct atmospheric conditions over the two years were analysed: January, with predominantly moderate upwelling-favourable winds and July, with highly variable and stronger winds. January conditions show an eastward flowing large-scale boundary current, the East Auckland Current (EAUC), and a quasi-stationary eddy, the East Cape Eddy (ECE), close to the shelf break, while July conditions show the EAUC and ECE located further from shore. A series of particle release experiments from inner-, mid-shelf, and shelf break locations are used to identify trajectory and dispersion variability between western, central, and eastern sections of the BoP under January and July conditions. Particles released under January conditions tend to flow eastward following the EAUC. Under July conditions, inner- and mid-shelf releases converge towards the central BoP, where bathymetric changes and islands create pathways for particles to exit the continental shelf. Relative dispersion (R2) under January conditions shows a ballistic dispersion regime (R2≈t2) over the first 10 days followed by a diffusive regime (R2≈t1) after 15 days. Under July conditions, a ballistic-like regime is maintained throughout a 30-day period, likely due to strong mixing in the BoP associated with submesoscale processes. Particles released in proximity to East Cape headland that remain in the water column for >5 days show higher dispersion relative to releases from the central and western regions of the BoP. However, 70%–90% of particles released on the eastern inner-shelf strand to the coastline in <5 days. This suggests that the eastern region can act as a retention zone, constraining the particles towards the shore. Drift duration increases for particles released further from the shore, where offshore mesoscale currents influence them more, and islands become important receptor locations.
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The trace elemental composition of biogenic calcium carbonate (CaCO3) structures is thought to reflect environmental conditions at their time of formation. As CaCO3 structures such as shell are deposited incrementally, sequential analysis of these structures allows reconstructions of animal movements. However, variation driven by genetics or ontogeny may interact with the environment to influence CaCO3 composition. This study examined how genetics, ontogeny, and the environment influence shell composition of the bivalve Perna canaliculus. We cultured genetically distinct families at two sites in situ and in the laboratory. Analyses were performed on shell formed immediately prior to harvest on all animals as well as on shell formed early in life only on animals grown in the laboratory. Discriminant analysis using 8 elements (Co, Ti, Li, Sr, Mn, Ba, Mg, Pb, Ci, Ni) classified 80% of individuals grown in situ to their family and 92% to growth site. Generalised linear models showed genetics influenced all elements, and ontogeny affected seven of eight elements. This demonstrates that although genetics and ontogeny influence shell composition, environmental factors dominate. The location at which shell material formed can be identified if environmental differences exist. Where no environmental differences exist, genetically isolated populations can still be identified.
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The influence of physical oceanographic processes on the dispersal of larvae is critical for understanding the ecology of species and for anticipating settlement into fisheries to aid long-term sustainable harvest. This study examines the mechanisms by which ocean currents shape larval dispersal and supply to the continental shelf-break, and the extent to which circulation determines settlement patterns using Sagmariasus verreauxi (Eastern Rock Lobster, ERL) as a model species. Despite the large range of factors that can impact larval dispersal, we show that within a Western Boundary Current system, mesoscale circulation explains broad spatio-temporal patterns of observed settlement including inter-annual and decadal variability along 500 km of coastline. To discern links between ocean circulation and settlement, we correlate a unique 21- year dataset of observed lobster settlement (i.e., early juvenile & pueruli abundance), with simulated larval settlement. Simulations use outputs of an eddy-resolving, data-assimilated, hydrodynamic model, incorporating ERL spawning strategy and larval duration. The latitude where the East Australian Current (EAC) deflects east and separates from the continent determines the limit between regions of low and high ERL settlement. We found that years with a persistent EAC flow have low settlement while years when mesoscale eddies prevail have high settlement; in fact, mesoscale eddies facilitate the transport of larvae to the continental shelf-break from offshore. Proxies for settlement based on circulation features observed with satellites could therefore be useful in predicting broadscale patterns of settlement orders of magnitudes to guide harvest limits.
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Bivalve shellfish aquaculture provides many benefits to society, beyond their traditional market value. This study collates the evidence available on the provisioning, regulating and cultural ecosystem services provided by the bivalve species commonly used in aquaculture. For the first time, it synthesises this evidence to provide a global assessment of the potential market and non‐market economic value of bivalve aquaculture. Bivalves are filter feeders, filtering water and particulates, creating substrates which provide habitat to act as nursery grounds for other species. Goods from provisioning services include meat, worth an estimated $23.9 billion as well as, pearls, shell and poultry grit, with oyster shell being the most important, with a global potential worth of $5.2 billion. The most important regulating services are nutrient remediation. Cultivated bivalves remove 49,000 tonnes of nitrogen and 6,000 tonnes of phosphorus, worth a potential $1.20 billion. Currently, there is little evidence on the cultural services per year of bivalve aquaculture, but we argue that these cultural values are broad ranging, although difficult to quantify. Our assessment indicates that the global, non‐food bivalve aquaculture services are worth $6.47 billion ($2.95 billion–9.99 billion) per annum. However, this is likely to be an underestimate of the true value of bivalve aquaculture as there are significant gaps in evidence of the value for a number of key services. The analysis presented here can be used to indicate the likely scale of payments for ecosystem services provided by bivalve aquaculture, prior to more detailed assessments.
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OpenDrift is an open-source Python-based framework for Lagrangian particle modelling under development at the Norwegian Meteorological Institute with contributions from the wider scientific community. The framework is highly generic and modular, and is designed to be used for any type of drift calculations in the ocean or atmosphere. A specific module within the OpenDrift framework corresponds to a Lagrangian particle model in the traditional sense. A number of modules have already been developed, including an oil drift module, a stochastic search-and-rescue module, a pelagic egg module, and a basic module for atmospheric drift. The framework allows for the ingestion of an unspecified number of forcing fields (scalar and vectorial) from various sources, including Eulerian ocean, atmosphere and wave models, but also measurements or a priori values for the same variables. A basic backtracking mechanism is inherent, using sign reversal of the total displacement vector and negative time stepping. OpenDrift is fast and simple to set up and use on Linux, Mac and Windows environments, and can be used with minimal or no Python experience. It is designed for flexibility, and researchers may easily adapt or write modules for their specific purpose. OpenDrift is also designed for performance, and simulations with millions of particles may be performed on a laptop. Further, OpenDrift is designed for robustness and is in daily operational use for emergency preparedness modelling (oil drift, search and rescue, and drifting ships) at the Norwegian Meteorological Institute.
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Habitat suitability index (HSI) models are increasingly used to guide ecological restoration. Successful restoration is a byproduct of several factors, including physical and biological processes, as well as permitting and logistical considerations. Rarely are factors from all of these categories included in HSI models, despite their combined relevance to common restoration goals such as population persistence. We developed a Geographic Information System (GIS)-based HSI for restoring persistent high-relief subtidal oyster (Crassostrea virginica) reefs protected from harvest (i.e., sanctuaries) in Pamlico Sound, North Carolina, USA. Expert stakeholder input identified 17 factors to include in the HSI. Factors primarily represented physical (e.g., salinity) and biological (e.g., larval dispersal) processes relevant to oyster restoration, but also included several relevant permitting (e.g., presence of seagrasses) and logistical (e.g., distance to restoration material stockpile sites) considerations. We validated the model with multiple years of oyster density data from existing sanctuaries, and compared HSI output with distributions of oyster reefs from the late 1800's. Of the 17 factors included in the model, stakeholders identified four factors—salinity, larval export from existing oyster sanctuaries, larval import to existing sanctuaries, and dissolved oxygen—most critical to oyster sanctuary site selection. The HSI model provided a quantitative scale over which a vast water body (~6,000 km2) was narrowed down by 95% to a much smaller suite of optimal (top 1% HSI) and suitable (top 5% HSI) locations for oyster restoration. Optimal and suitable restoration locations were clustered in northeast and southwest Pamlico Sound. Oyster density in existing sanctuaries, normalized for time since reef restoration, was a positive exponential function of HSI, providing validation for the model. Only a small portion (10–20%) of historical reef locations overlapped with current, model-predicted optimal and suitable restoration habitat. We contend that stronger linkages between larval connectivity, landscape ecology, stakeholder engagement and spatial planning within HSI models can provide a more holistic, unified approach to restoration.
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Marine larval dispersal is a complex biophysical process that depends on the effects of species biology and oceanography, leading to logistical difficulties in estimating connectivity among populations of marine animals with biphasic life cycles. To address this challenge, the application of multiple methodological approaches has been advocated, in order to increase confidence in estimates of population connectivity. However, studies seldom account for sources of uncertainty associated with each method, which undermines a direct comparative approach. In the present study we explicitly account for the statistical uncertainty in observed connectivity matrices derived from elemental chemistry of larval mussel shells, and compare these to predictions from a biophysical model of dispersal. To do this we manipulate the observed connectivity matrix by applying different confidence levels to the assignment of recruits to source populations, while concurrently modelling the intrinsic misclassification rate of larvae to known sources. We demonstrate that the correlation between the observed and modelled matrices increases as the number of observed recruits classified as unknowns approximates the observed larval misclassification rate. Using this approach, we show that unprecedented levels of concordance in connectivity estimates (r = 0.96) can be achieved, and at spatial scales (20-40 km) that are ecologically relevant.
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The early life history of many marine organisms includes a dispersive planktonic larval phase which allows for the exchange of individuals among subpopulations. Knowledge of the degree of exchange, or connectivity, is critical to understanding the abundance and distribution of marine populations. Here, we applied geochemical tagging to assess estuarine‐scale larval connectivity among subpopulations of the commercially and ecologically important eastern oyster, Crassostrea virginica. To generate an “atlas” of geochemical signatures associated with spawning sites and potential dispersal pathways from spawning sites, we outplanted recently spawned oyster larvae to stationary moorings and surface drifters, respectively. Using the atlases generated from both outplant methods, we predicted natal origin, and thus larval connectivity, for newly settled oysters (spat) during three field trials over two summers (June 2013, June 2014, and August 2014), within three regions (∼ 35 km × 15 km quadrants) of Pamlico Sound, North Carolina, U.S.A. Patterns of larval connectivity varied both between months and annually but were predominately directed south to north following wind patterns. Predicted self‐recruitment was variable, as up to 100% of spat in a given region displayed signatures consistent with natal origin within that same region. Predicted connectivity patterns varied significantly based on atlases generated from outplanting on stationary moorings vs. surface drifters. For example, drifter‐predicted connectivity followed biophysical larval dispersal models more closely than mooring‐predicted connectivity, while mooring‐predicted connectivity displayed a higher diversity in larval sources. Both connectivity models highlight the need for resource management strategies such as reserve networks to incorporate designs that account for inherent variability in dispersal pathways.
Larval transport is fundamental to several ecological processes, yet it remains unresolved for the majority of systems. We define larval transport, and describe its components, namely larval behavior and the physical transport mechanisms accounting for advection, diffusion, and their variability. We then discuss other relevant processes in larval transport, including swimming proficiency, larval duration, accumulation in propagating features, episodic larval transport, and patchiness and spatial variability in larval abundance. We address challenges associated with understanding larval transport, and recent approaches, including autonomous sampling, imaging, ’omics’, and the exponential growth in the use of poorly-tested numerical simulation models to examine larval transport and population connectivity. Thus, we discuss the promises and pitfalls of numerical modelling, concluding with recommendations to move forward, including a need for more process-oriented understanding of the mechanisms of larval transport, and use of emergent technologies.
The success of restoration initiatives to restore bivalve beds relies on sufficient recruitment of larvae to offset mortality of re-established populations. Individuals of the nearly extirpated green-lipped mussel are capable of surviving within the current environment of the Hauraki Gulf, New Zealand; however, it is uncertain what potential factors might inhibit the establishment and persistence of restored mussel beds. Four experimental mussel beds were established within a shallow soft-sediment embayment and assessments of population dynamics were conducted approximately every 6 months over a 2-year period. Deployed mussels quickly congregated into contiguous mussel beds that persisted throughout the study; however, only 26.2% of mussels that were initially established survived until the end of the study. The cause of this overall loss of mussels can be attributed to a near lack of observed recruitment, with only three individual recruiting mussels observed throughout the entire study. Despite similar mortality rates within the restored mussel beds to that of natural populations, these populations will be unsustainable long term given the lack of recruitment. Potential causes of the observed mortality and lack of recruitment are discussed, including environmental factors affecting non-natal mussel stock and sea star predation. This research provides a foundation for the development of best-practice methods in the restoration of green-lipped mussels. However, further investigation into recruitment pathways and sources of mortality for adult mussels will be necessary to overcome the observed limitations if future restoration is to be successful.