Rapid Effects of Marine Reserves via Larval Dispersal
Richard Cudney-Bueno1,2,3*, Miguel F. Lavı ´n4, Silvio G. Marinone4, Peter T. Raimondi2, William W. Shaw1
1School of Natural Resources, University of Arizona, Tucson, Arizona, United States of America, 2Institute of Marine Sciences, University of California Santa Cruz, Santa
Cruz, California, United States of America, 3Centro Intercultural de Estudios de Desiertos y Oce ´anos (CEDO), Puerto Pen ˜asco, Sonora, Me ´xico, 4Departamento de
Oceanografı ´a Fı ´sica, Centro de Investigacio ´n Cientı ´fica y de Educacio ´n Superior de Ensenada (CICESE). Carretera a Tijuana, Ensenada, Baja California, Me ´xico
Marine reserves have been advocated worldwide as conservation and fishery management tools. It is argued that they can
areas. However, while evidence has shown that marine reserves can meet conservation targets, their effects on fisheries are less
understood. In particular, the basic question of if and over what temporal and spatial scales reserves can benefit fished
populations via larval dispersal remains unanswered. We tested predictions of a larval transport model for a marine reserve
network in the Gulf of California, Mexico, via field oceanography and repeated density counts of recently settled juvenile
commercial mollusks before and after reserve establishment. We show that local retention of larvae within a reserve network
can take place withenhanced,butspatially-explicit, recruitment tolocalfisheries.Enhancementoccurredrapidly (2 yrs), withup
to a three-fold increase in density of juveniles found in fished areas at the downstream edge of the reserve network, but other
fishing areas within the network were unaffected. These findings were consistent with our model predictions. Our findings
underscore the potential benefits of protecting larval sources and show that enhancement in recruitment can be manifested
rapidly. However, benefits can be markedly variable within a local seascape. Hence, effects of marine reserve networks, positive
or negative, may be overlooked when only focusing on overall responses and not considering finer spatially-explicit responses
within a reserve network and its adjacent fishing grounds. Our results therefore call for future research on marine reserves that
addresses this variability in order to help frame appropriate scenarios for the spatial management scales of interest.
Citation: Cudney-Bueno R, Lavı ´n MF, Marinone SG, Raimondi PT, Shaw WW (2009) Rapid Effects of Marine Reserves via Larval Dispersal. PLoS ONE 4(1): e4140.
Editor: Craig R. McClain, Monterey Bay Aquarium Research Institute, United States of America
Received August 2, 2008; Accepted November 21, 2008; Published January 8, 2009
Copyright: ? 2009 Cudney-Bueno et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Research was funded by the David and Lucile Packard Foundation, PADI-Project AWARE, Sandler Family Foundation, Tinker Foundation, Wallace
Research Foundation, and World Wildlife Fund. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org.
As a response to declining fish stocks and threats to marine
ecosystems, marine reserves (areas closed to fishing) have been
widely advocated as conservation tools and means to achieving
more sustainable use of marine resources [1–3]. The rationale
behind their use lies in the dual opportunity they could offer to
protect ecosystems and ecological processes while also enhancing
fisheries via density-dependent spillover and larval dispersal of
target species into fishing areas [1,3–5]. However, while evidence
has shown that marine reserves can meet conservation targets [6–
8], the role they may have on fisheries is less understood. Previous
studies have focused on benefits to adjacent fisheries via density-
dependent spillover of adult fish from reserves [6,9] or have been
based primarily on larval transport models [3,10–12], lacking
validation through field monitoring and oceanographic data.
Models that inform effects of marine reserves via enhanced
larval export rely on (a) assumptions about recruitment limitations
in unprotected populations, and (b) connectivity between reserves
and non-reserve sites [10–12]. If both assumptions are met,
marine reserves could replenish adjacent, fished populations.
However, effects could be localized or widespread depending on
dispersal, which is in turn related to the complex interactions
among local current patterns and larval duration and behavior
[13–16]. Hence, actual effects are difficult to measure and
understand. Furthermore, without explicit model predictions of
patterns of enhanced recruitment, assumptions of reserve effects
can neither be supported nor falsified by empirical results. These
have been fundamental problems in investigations of marine
reserves , and the basic question of if and over what temporal
and spatial scales reserves can benefit fished populations via larval
dispersal remains unanswered.
As a means to test the effects of reserves on adjacent fisheries via
larval dispersal, we coupled predictions from a larval transport
model with in situ field oceanography and monitoring of densities
of individuals recruited since the establishment of a reserve
network in Northwest Mexico. The Puerto Pen ˜asco reserve
network was established in summer 2002 primarily as a means
to protect declining stocks of two commercial species of mollusks:
rock scallop (Spondylus calcifer) and black murex snail (Hexaplex
nigritus). The network includes an offshore reserve (San Jorge
Island), and two coastal reserves (Las Conchas and Sandy) (Fig. 1).
It covers approximately 18 km of coastline composed primarily of
extended beach-rock (coquina) and granite reefs separated by beds
of mussels and rhodoliths and shell/sandy patches.
To assess the effects of the reserve network, we generated a
larval export model and tested its predictions through observations
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of currents and bi-annual density counts of juvenile rock scallops
and murex snails within reserves and fishing grounds prior and
after reserve establishment (summer 2002-summer 2004). We
developed a three-dimensional baroclinic numerical model that
was based on the circulation pattern for the summer (the spawning
season for both species), which is cyclonic overall , with
northwestward flow in the area where the reserve network is
located. We used the model to assess if the network could receive
larvae from southern sources and to predict patterns of larval
recruitment within the network. The model tracked passive
particles for up to four weeks (exceeding the range of larval
duration for both species) after being released (a) in the rocky reef
south of the reserve network (,150 km south of San Jorge Island),
(b) in San Jorge Island, the southern boundary of the network, and
(c) every km from the Island to the northwestern portion of the
In case (a) released particles showed a median south-northwest
travel distance of 148 km in four weeks (Fig. 2A). Larvae of both
species, however, are competent to settle in less time [19,20]. It is
therefore highly unlikely that there could have been any
substantial direct influence from southern reefs, particularly on
coastal reserves which are 180–200 km north of these reefs.
Furthermore, our model predictions are likely an overestimation of
true dispersal distances, as larvae dispersal can be more
constrained once behavior and habitat are accounted for in model
predictions [15,21]. Influence from western sources (Baja Cali-
fornia peninsula) is highly unlikely, as previous studies indicate a
clear cyclonic movement of the water during summer , when
both of these species reproduce [23,24]. On the eastern side of the
Gulf of California, the water mass has a northbound movement
whereas on the western side water moves towards the south and
does not reach the eastern coastline .
Figure 1. Location of reserve network, monitored fishing areas, and observations of regional currents. The three diagrams in the center
represent: track and velocity of a surface drifter (in black), progressive vector diagram (PVD) from velocity measured 15 m above the bottom at ADCP
(Acoustic Doppler Current Profiler) site (in blue, bottom at 25 m), and the PVD from velocity measured 15 m above the bottom at ADP (Acoustic
Doppler Profiler) site (in red, bottom at 18 m). Both PVDs have been shifted west for clarity. These three diagrams are made with hourly-mean data
for the period 19:00:00 (UT) July 12 to 00:10:00 July 16 2006. The black arrows close to the 20 m isobath represent interpolated half-hourly data from
a drifter drogued at 15 m, from 03:00 to 22:30, July 7 2006. The most offshore arrows are 6-hourly drifter data from the same drifter, from 18:00 June
24 to 12:00 June 25 2006 (see Fig. S1 and S2 for additional drifter trajectories and PVDs).
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Particles released in the area surrounding San Jorge Island (case
b), the southern portion of the reserve network, showed a marked
flow toward the coast and northwestern reserve sites (Fig. 2B).
Direct evidence of this flow pattern is provided by the tracks of
surface drifters released near the Island and progressive vector
diagrams (PVDs) from concurrent acoustic current profilers
(ADCPs, ADPs) (Fig. 1; also, see Fig. S1 and S2). Drifter tracks
show the tidal ellipses plus a residual flow toward the coast (tidal
ellipses refer to the trajectory that drifters followed with the ebb
and flow of the tide; while residual flow refers to the net
displacement of drifters over one or more tidal cycles, in this case,
progressively moving north toward the coast). When modeling
larval settlement as a function of distance from the Island to
coastal reserves and monitored fishing areas (case c), for any period
from 1–4 weeks the model predicted more settlement at
northernmost sites (Sandy/La Cholla) (Fig. 3). Following this
same modeling exercise, more settlement in southern reserve and
fishing areas (Las Conchas/Los Tanques) compared to northern
ones would only be evident if larvae were competent to settle no
more than two days after release. However, larvae of both species
are planctonic and competent to settle in .1 week [19,20].
Observed spatial patterns of recruitment of juveniles of both
species (individuals born and recruited since reserve establishment)
were consistent with predictions of our larval transport model.
Only two years after establishment of the reserves, both species
showed evidence of changes in density as a function of time,
protection from fishing (reserve effects) and site effects as a whole
(repeated measures three-way MANOVA, time X protection X
site; rock scallop: Pillai’s Trace F4, 41=2.53, P=0.05; black
murex: Pillai’s Trace F4, 41=3.02, P=0.02). Density of juvenile
rock scallop had increased by up to 40.7% within coastal reserves
and by 20.6% in fished areas (repeated measures two-way
MANOVA, time X protection from fishing, Pillai’s Trace F4, 41=
2.67, P,0.05). Changes were also evident for black murex, with
more than a three-fold increase in density of juveniles within fished
areas (repeated measures two-way MANOVA, time X protection
from fishing, Pillai’s Trace F4, 41=3.28, P,0.05). The pattern of
increase in juveniles, however, was variable in space, evident only
for the northwestern portion of the network (Fig. 4), as predicted
by the larval transport model for any period between one and four
weeks. Density of both species increased markedly in the reserve
and fished northwestern sites (Sandy/La Cholla) and remained
relatively constant in southeastern sites (Las Conchas/Los
Tanques) (repeated measures two-way MANOVA, time X site;
rock scallop: Pillai’s Trace F4, 41=7.09, P,0.001; black murex:
Pillai’s Trace F4, 41=2.95, P,0.05) (Table S1 and S2).
Observed increase in recruitment was spatially-constricted to
the northern portion of the reserve network and consistent with
predictions of our larval transport model and field oceanographic
Figure 2. Final position of particles 1–4 weeks after having been released in (a) the nearest rocky reef located south of the marine
reserve network, and (b) the network’s southern boundary (San Jorge Island). Panels on right show cumulative percentages of particles as
a function of distance 1, 2, 3 and 4 weeks after release.
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observations. This recruitment pattern reflects effects of larval
dispersal within the reserve network rather than other effects such
as density-dependent adult spillover, a good year of high overall
regional recruitment, or wider oceanographic processes. The
restricted adult movement of both species (sessile in the case of
rock scallop) constrains our inference to larval dispersal rather
than density-dependent adult spillover. Furthermore, high overall
recruitment and regional oceanographic processes would likely
have resulted in changes throughout the study area, not only in the
northern portion of the reserve network.
Surveys on San Jorge Island, as well as our modeling and current
measurements(Figs.1and2B)suggestthatthe Island couldbeacting
as a key component of the network, providing a source for larval
export to adjacent coastal reserves and fishing areas. Overall density
of juvenile rock scallops on the Island actually decreased since
reserve establishment (repeated measures 1-way ANOVA; F4, 45=
4.46,P,0.01) and thoseof blackmurex remained relativelyconstant
(repeated measures 1-way ANOVA; F4,
However, although density of juveniles did not increase, even the
lowest average numbers in five monitoring seasons were 80% higher
than those of coastal reserves. Overall densities (adults and juveniles)
were also six times higher than those of all coastal reserves and
fishing sites combined, reaching up to 1.6/m2and exceeding any
others reported for the Gulf of California [23,25]. Given these high
densities, a decrease in juveniles near the Island could be related to
Our findings provide needed insights for theory and empirical
understanding of effects of marine reserves. First, we show
evidence of rapid effects of reserve networks on adjacent fisheries
via larval dispersal. Second, we also show that local retention of
larvae within a network can take place with enhanced but spatially
variable recruitment to local fisheries. Hence, effects should not be
expected across an entire reserve network. Rather, they can be
markedly variable within a local seascape.
These results have important implications for management.
Reserves reduce the total area available for fishing, likely causing
an initial economic cost to fishers. Therefore, in situations where
there is local support for reserve establishment, evidence of rapid
positive reserve effects, as we have here shown, could play a crucial
role in reinforcing cooperation among fishers for further
compliance . Evidence of larval retention and enhanced
recruitment to local fisheries also underscores the benefits of
protecting reproductive larval sources and reconciles local
management with social needs. Reserve networks with strong
support from fishing communities are best designed if they
enhance or maintain recruitment within the area of influence of
these communities, not benefiting others at the expense of local
management initiatives and, ultimately, initial costly decisions. In
some situations, however, this may not be possible, as oceano-
graphic processes could result in larval export outside the area of
influence of the community or communities supporting the reserve
network. Designs of reserve networks that cover broader spatial
scales may be needed in these situations.
Finally, effects of marine reserves, positive or negative, may be
overlooked when only focusing on overall responses and not
considering finer spatially-explicit responses within a reserve
network and its adjacent fishing grounds. Our results therefore
call for future research on marine reserves that addresses this
variability in order to help frame appropriate scenarios for the
spatial management scales of interest. Not doing so could lead to
false expectations among stakeholders.
Materials and Methods
Particle tracking from a three dimensional oceanographic
We released 2000 passive particles in two areas (between 0–
60 m deep): San Jorge Island, and the nearest substantial rocky
reef south of the marine reserve network. Particles were tracked for
four weeks and the temporal scales resolved by the model (due to
forcing) are tidal and seasonal. The model is described in detail for
the Gulf of California by Marinone  and Mateos et al. .
Briefly, the model domain has a mesh size of 2.5962.59
(,3.964.6 km) in the horizontal and 12 layers in the vertical
with nominal lower levels at 10, 20, 30, 60, 100, 150, 200, 250,
350, 600, 1000 and 4000 m. Model equations are solved semi-
implicitly with fully prognostic temperature and salinity fields. The
model is forced with tides, climatological winds, climatological
hydrography at the mouth of the Gulf of California, and
climatological heat and fresh water fluxes at the air-sea interface.
As shown by Marinone , the model adequately reproduces the
main seasonal signals of surface temperature, heat balance, tidal
elevation and surface circulation in the northern Gulf of California
and also the tidal currents as shown by Marinone and Lavı ´n .
Drifter tracks and current profiles
We used two bottom-mounted acoustic current profilers
moored at the sites marked ADCP and ADP in Fig. 1 and six
PacificGyre (www.pacificgyre.com/Lagrangian.aspx) Microstar
surface drifters which drogues were centered at 1 m below the
sea surface. These drifters provided GPS positions every
10 minutes. One PacificGyre ARGOS SVP (Surface Velocity
Program) drifter was used to observe the current field offshore
(west) of San Jorge Island; it was drogued with a 4.8 m- tall Holey
Sock centered at 15 m depth.
Figure 3. Modeled larval settlement (as relative percentages)
within coastal reserves (Las Conchas, Sandy) and fishing areas
(Los Tanques, La Cholla) as a function of the day larvae are
competent to settle. Model larvae were released every kilometer in
the region of interest, from San Jorge Island to La Cholla. Earlier results
suggested that there was no source of larvae to the south of the
network. No sources were used to the north because models showed
that larvae released to the north of the reserve network would be
transported away from the network. The model assumed that larvae
settled on the day of competency. If that assumption is relaxed, the
difference in settlement between northern (Sandy/La Cholla) and
southern (Las Conchas/Los Tanques) sites increases.
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Site ADCP (Fig. 1), equipped with a bottom-mounted 300 KHz
Acoustic Doppler Current Profiler (by RDInstruments), was set
just north of San Jorge Island where the mean bottom depth was
25 m. Site ADP, which contained a bottom-mounted 500 KHz
Acoustic Doppler Profiler (by SonTek), was 8 km further north
with the bottom at ,18 m. Both current profilers measured the
mean velocity of every meter of the water column, every three
minutes, for the periods June 2-July 4 and July 6-August 18 2006.
For the purpose of this article, the best way to present the profiler
current data are the Progressive Vector Diagrams (PVD), which
are constructed by calculating the vector displacement that a water
parcel would experience at the mooring position during each
sampling interval, and drawing them sequentially, the tail of each
vector on the head of the previous one. Note that they are not true
Figure 4. Differences in densities (S.E. bars included) of juvenile rock scallops (a) and black murex snails (b) in southern and
northern sites before (summer 2002) and after (summer 2004) reserve establishment.
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tracks, but they can be plotted over maps to aid in the
interpretation. The PVDs in Fig. S1 correspond to the ADCP
data at 3.6, 9.6, 15.6 and 20.6 m above the bottom (cells 1, 7, 13
and 18) for the period July 6 to July 30 2006; they show the tidal
ellipses plus a residual to the NW (,2 cm/s). This pattern was
consistent throughout the observation periods. In Fig. 1 we plotted
the PVDs at 15 m above the bottom for both the ADCP and the
ADP, from 19:00 UT on July 12 to 00:10 UT on July 16 2006.
The surface drifters were deployed in groups of 4–6 units; several
deployments were made between July 12 and July 23 2006, either
over the ADP or ADCP sites or off the northern end of San Jorge
Island. The tracks of 5 drifters (and their velocities) for the period
July 12 (19:00 UT) to July 16 (00:10 UT) are shown in Fig. S2; in
addition to the (true) tidal ellipses, the tracks also show a residual
flow to the NW. In Fig. 1, the track and velocity of one of the
drifters is plotted together with the PVDs from the two current
profilers, for the period covered by the drifter track. Fig. 1 also
shows the tracks and velocities obtained outside San Jorge Island
with the SVP drifter. Two tracks are shown, the most offshore
comprises 6-hourly data from 18:00 (UT) June 24 to 12:00 (UT)
June 25 2006, and the second interpolates half-hourly data from
02:57 (UT) to 22:23 (UT), July 7 2006.
Estimation of population parameters
We estimated changes in density of rock scallop (Spondylus
calcifer) and black murex snail (Hexaplex nigritus) in reserve and
fishing sites for two consecutive years beginning in May 2002, one
month preceding reserve establishment. The region monitored
encompassed the reefs of San Jorge Island and those found near
the fishing town of Puerto Pen ˜asco (within 3 km from highest tide
line) in the eastern part of the northern Gulf of California, Mexico.
This region extends from 31,22,18.1 N; 113,39,09.4 W to
31,15,03.8 N; 113,20,48.1 W.
We subdivided the region into 5 sampling areas: a) two coastal
reserves (replicates), Las Conchas and Sandy; b) two coastal fishing
areas (‘‘controls’’), Los Tanques and La Cholla; c) one offshore
island reserve, San Jorge Island (Fig. 1). We paired coastal reserves
with appropriate coastal fishing areas (Sandy with La Cholla; Las
Conchas with Los Tanques). We refer to each of these pairs as
‘‘sites’’. Given the lack of adequate comparison areas for San Jorge
Island, we analyzed the response of this off-shore reserve
independently. Assessments are based on bi-annual density counts
in 58 100 m2permanent plots before and after reserve establish-
ment (repeated measures, five monitoring seasons).
To reduce heterogeneity associated with depth, we restricted all
sampling to depths ranging from 40–65 ft. This also reduced health
risks associated with diving and facilitated overall monitoring as we
were able to remain underwater for longer periods of time. In all
cases except San Jorge Island, this depth as well as the established
constrained distance from the tide line covers the entire extension of
the reefs. We restricted sampling in San Jorge Island to the reefs
found on the eastern part of the island, as these are shallower and
more similar to those found on the mainland coast.
Plot design and sample unit selection
We selected plots from within these five areas through simple
random sampling. In the event that a specific plot selected happened
to fall where at least 50% of sand was present, that plot was replaced
by another one by swimming underwater in a straight line along the
reef until reaching sufficient (.50%) rocky substrate. Once selected,
all plots were permanently marked underwater.
Plots were 10610 m subdivided into 16 quadrats of 2.562.5 m
for ease of observation. Testing other sampling methods such as
the use of 5650 m or 5630 m transects, distance sampling or
others typically used for sessile organisms did not prove adequate
for this region given the highly variable visibility of the region, the
strong currents, and the overall patchiness of the reefs (i.e. patches
of reef typically separated by patches of sand). We counted all
individuals visible within each 2.562.5 m quadrat (subplot). For
rock scallop, we estimated size of each individual to fall within one
of three categories: small juveniles (up to 5 cm of height), medium-
sized juveniles and young adults (.5 and ,10 cm of height), and
large adults (.10 cm of height). For black murex, sizes fell into
two categories: juveniles and reproductively mature adults.
To reduce variation in detectability, the same person counted
organisms on each sampling occasion and in the same designated
plots while another diver assisted setting and maintaining the plot
lines in place. To support this work, ten commercial divers with
extensive experience searching for benthic mollusks (.5 years)
were trained to participate in the monitoring process. We
calculated variations in the detection of monitored species (s#3
individuals/plot) and incorporated this variation to calculate
statistical power of our sampling design (see below).
Sampling frequency, sample sizes, and allocation of
We established a total of 58 sampling plots: San Jorge=10, Las
Conchas=10, Los Tanques=10, Sandy=10, La Cholla=18.
Power analyses from baseline data on density of rock scallops found
on these 58 plots gave us a high probability of detecting at least a
10% increase in their density (Power.95% for each reserve and
fishing zone, a=0.05 and s=3 individuals/plot). Given that rock
scallops are harder to detect than black murex (when closed they
resemble rocks), we assume an even higher statistical power for
detection of changes in population densities of black murex. We
monitored each plot twice every year (Spring and Summer) for two
consecutive years (Summer 2002, Spring 03, Summer 03, Spring 04,
Summer 04). These months provide some of the best visibility
underwater and are also usually devoid of algae beds covering the
rocky reefs, which reduce detectability of species monitored.
This is a longitudinal study with a repeated measures research
baseline data and applied square root transformations to improve
homogeneity of variance. We then addressed ‘‘between subject’’ and
‘‘within subject’’ variability of baseline data graphically, determined
the coefficient of variation, and tested for independence of plots and
sampling sites in order to avoid pseudo-replication. We used
multivariate analyses of variance (MANOVA) and relied on
Multivariate Pillai’s Trace P values to help assess time, protection
factors. Univariate estimates were also obtained and analyzed to
further understand observed patterns (see Table S1 and S2).
temporal changes in density of juvenile rock scallops found within
monitored reserve and fishing areas.
Found at: doi:10.1371/journal.pone.0004140.s001 (0.05 MB
Univariate and multivariate tests for the analysis of
temporal changes in density of juvenile black murex found within
monitored reserve and fishing areas.
Found at: doi:10.1371/journal.pone.0004140.s002 (0.05 MB
Univariate and multivariate tests for the analysis of
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ADCP velocity data at 3.6, 9.6, 15.6 and 20.6 m above the bottom
(cells 1, 7, 13 and 18) for the period July 6 to August 18 2006. For
clarity, successive diagrams are shifted to the left by 5 km.
Found at: doi:10.1371/journal.pone.0004140.s003 (0.13 MB TIF)
Progressive vector diagrams (PVD) calculated from the
for the period 19:00 (UT) July 12 to 00:10 July 16 2006. Four of
the five drifters shown were redeployed during the period; the
exception is the green trace, which is used in Fig. 1 of the article.
Found at: doi:10.1371/journal.pone.0004140.s004 (0.02 MB TIF)
Tracks and velocities of the Microstar surface drifters
We thank the Sociedad Cooperativa Buzos de Puerto Punta Pen ˜asco, O. Morales,
and J. Rupnow for their participation in subtidal field monitoring. C.
Cabrera, A. Cinti, J. Duberstein, M. Figueroa, V. Godı ´nez, R. Loaiza, A.
Maldonado, M. Moreno, S. Pe ´rez, E. Polanco, M. Rivera, R. Salazar, and
G. Soria assisted in the field oceanography component of this research. We
thank M. Carr, J. Donlan, F. Michelli, R. Steidl, and J. Tewksbury for
comments on earlier drafts of our paper. This is a scientific contribution of
the PANGAS Project, www.pangas.arizona.edu.
Conceived and designed the experiments: RCB WWS. Performed the
experiments: RCB MFL SGM. Analyzed the data: RCB MFL SGM PTR.
Contributed reagents/materials/analysis tools: RCB MFL SGM. Wrote
the paper: RCB MFL SGM PTR WWS. Conducted subtidal monitoring:
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Reserves and Larval Dispersal
PLoS ONE | www.plosone.org7January 2009 | Volume 4 | Issue 1 | e4140