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Interactive webpage on three-dimensional connectivity 1
Lat. Am. J. Aquat. Res., 45(2): 322-328, 2017
DOI: 10.3856/vol45-issue2-fulltext-8
Research Article
Three-dimensional connectivity in the Gulf of California: an online
interactive webpage
Carolina Montaño-Cortés1, Silvio G. Marinone1 & Ernesto Valenzuela1
1Department of Physical Oceanography, Ensenada Center of Scientific
Research and Higher Education (CICESE), Tijuana, Mexico
Corresponding author: Silvio G. Marinone (marinone@cicese.mx)
ABSTRACT. This paper presents an online interactive webpage [http://connectivity-dispersion.cicese.mx/] that
provides users with results of both the three-dimensional connectivity and spatial dispersion of particles in the
Gulf of California (GC). These results were originated by means of a three-dimensional numerical model of
circulation adapted to the GC from which the advection of particles were generated between different regions
of the gulf. Particle connectivity and dispersion results were generated for and are limited to temporal scales to
seasonal tides, which may aid in the interpretation of larval connectivity and contaminants within the gulf.
Keywords: interactive webpage, three-dimensional connectivity, particles dispersion, Gulf of California.
INTRODUCTION
Three-dimensional connectivity studies are an impor-
tant research topic for the different branches of
oceanography because they provide information about
the location of moving particles based on the
hydrodynamics of a water body.
This study considers connectivity to be that which
“connects” different areas to different times, describing
some type of trajectory. These trajectories can serve as
the basis for understanding contaminant propagation
and the dispersion of larvae from different marine
species and their nutrients and can aid in the sound
development of protected marine areas, among other
applications (Cudney-Bueno et al., 2009; Marinone et
al., 2008).
The objective of this study is to demonstrate the
manner in which an interactive online webpage
[http://conectividad-dispersion.cicese.mx/] displays the
evolution of three-dimensional connectivity between
the areas composing the Gulf of California (GC), as
well as to present a visualization of the dispersion of
particles from a particular region based on the results
obtained through the HAMburg Shelf Ocean Model
(HAMSOM), which is an Eulerian numerical circu-
lation model, and a Lagrangian particle dispersion
model. Both models were validated as described in the
following section.
__________________
Corresponding editor: Nelson Silva
MATERIALS AND METHODS
Particles underwent advection for eight weeks, being
released the first day of each month of the year through
a Lagrangian advection-diffusion model (Visser, 1997;
Proehl et al., 2005) over a field of Eulerian currents
obtained from a three-dimensional baroclinic circu-
lation model (HAMSOM) adapted to the GC by
Marinone (2003, 2008). The model has a spatial
horizontal resolution of ~1.3×1.5 km and 12 layers
vertically, and is forced by tides, winds, seasonal
warming and water flows at the surface, and seasonal
hydrography at the mouth of the gulf (Marinone 2003,
2006, 2008; Marinone & Lavín, 2005; Santiago-García
et al., 2014; Montaño, 2015). Given this forcing, there
is no interannual or mesoscale variability beyond that
which is obtained from nonlinear interactions between
the currents produced by tides and seasonal currents
produced by wind and forcing at the mouth. In
particular, at these scales, the trajectories of particles
are dominated by seasonal circulation, and tides only
produce oscillations along the length of a trajectory
(Marinone et al., 2008). For calculations, at different
scales, forcing in the numerical model will need to be
changed to produce circulation during, for example, an
El Niño event.
The particles release was performed within the 17
areas into which the Gulf of California was divided
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Table 1. Names of the regions that correspond to the Gulf of California (Santiago-García et al., 2014). Names are shown
in both Spanish and English, as the webpage includes both options.
Acronym
English
Spanish name
UG
Upper Gulf
Alto Golfo
BZ
Buffer Zone
Conexión Alto Golfo y Remolino Estacional
PE
Peninsular Eddies
Remolinos Peninsulares
SE
Seasonal Eddy
Remolino Estacional
SO
Sonora Coast
Sonora
DB
Delfín Basin
Cuenca Delfín
TI
North of Tiburón Island
Norte de Isla Tiburón
AG
East of Ángel de la Guarda Island
Ángel de la Guarda
BC
Ballenas-Salsipuedes Channel
Canal de Ballenas
SZ
Sills Zone
Zona de los Umbrales
CP
Central Peninsular Region
Región Peninsular Central
GB
Guaymas Basin
Cuenca Guaymas
CC
Central Continental Region
Región Continental Central
SC
South Continental Region
Región Continental Sur
FB
Farallón Basin
Cuenca Farallón
SP
South Peninsular Region
Región Peninsular Sur
PB
La Paz Bay
Bahía la Paz
(Table 1; according to Santiago-García et al., 2014).
The final positions of the particles were determined
(longitude, latitude and depth) at 2, 4, 6 and 8 weeks
after being released. Then, the results were presented in
connectivity matrices between the different areas,
including the average depths and standard deviation, as
well as in final position maps of all the particles and
histograms of the percentage of particles corresponding
to the different areas of arrival, as subsequently
explained.
The connectivity matrices quantify the particles that
reached different regions and those that returned or
remained in the area where they were released for each
of the final periods (2, 4, 6 and 8 weeks), shown as
percentages. For each connectivity matrix, Cij(t), i is the
horizontal axis, which defines the area of arrival or final
destination of the particles, j is the vertical axis, which
represents the provinces or release areas, and t is the
week at which the positions of released particles are
observed during the different months of the year. The
summation of the percentages in each of the rows of the
matrix represents the total release percentage of each
area, except when the particles leave the model domain.
(In the connectivity figures, cells with less than 5% of
the particles were excluded from the matrices for clarity
purposes).
Associated to the connectivity matrices, the mean
and standard deviation of the depths reached by the
particles for each of the different cells of the matrix
were calculated. Based on the information attained,
matrices were developed for mean depth and standard
deviation, which maintain the same format as the
connectivity matrix. The sequence of matrices is such
that both the abscissa (x) and ordinate (y) axes group
the regions as north, large islands and south. These
divisions are presented in the figures as dashed lines.
The principal diagonal line represents the retention and
indicates the particles that ended up inside the release
area.
To complement the portrayal of the connectivity
results, mean depth, and standard deviation matrices,
maps were developed of the final geographic position
of the particles at different times (2, 4, 6 and 8 weeks),
presented as color codes of depth at which each particle
was found. Similarly, histograms were used to represent
the connectivity percentages of a location compared to
all other regional divisions that compose the GC.
Therefore, for the model’s 12 layers, the results
represent all months of the year as well as the periods
of 2, 4, 6 and 8 weeks.
RESULTS
Model validation
The results obtained using the Eulerian and Lagrangian
models upon which the calculations presented for this
webpage are based have been validated in several
studies. The Eulerian model used by Marinone (2003)
reproduces several circulation phenomena from the
GC. For example, it adequately reproduces seasonal
circulation patterns, which consist of a reversible
rotation in the northern GC (NGC) that is anticyclonic
in the winter and cyclonic in the summer, as reported
by Lavín et al. (1997) and Carrillo et al. (2002), and a
similar circulation pattern in the southern part of the
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Interactive webpage on three-dimensional connectivity 3
GC, as noted by Beier (1997). Similarly, Marinone
(2008) validates the numerical results of the deep
circulation present around the large islands obtained by
López et al. (2006), which consisted of a trajectory
from Umbral de San Esteban to the northern end of the
channel formed between Ángel de la Guarda Island and
the Baja California Peninsula (Ballenas-Salsipuedes
Channel, or BC), exhibiting convergence in deep areas
and divergence on the surface.
The tidal currents (barotropic and baroclinic), and
their harmonic components reproduced by the model,
exhibited similar behaviors with respect to the data
obtained by Marinone & Lavín (2005). The numerical
results were compared with 124 time series corres-
ponding to 62 stations, of which 68 time series
correspond to NGC, 31 correspond to the region of
large islands and 25 correspond to the central gulf. A
comparison indicates that the semidiurnal components
were better modeled than the diurnal components. For
example, in Table 2 from Marinone & Lavín (2005),
the semi-major axis of the modeled M2 exhibits an
underestimation of only 3.9%, whereas the underes-
timation for K1 is 26%. However, as mentioned in the
study, when examining the means of the semi-major
axis values together with their corresponding error bars,
there is markedly a high number of overlapping data
points, indicating better modeling than what is
indicated by the significant differences. The numerical
results obtained for sea level were validated with
respect to the observations of Ripa (1990) and Beier
(1997). The mean amplitude of the annual component
in the coastal stations was 18.8 ± 4.5 cm for the model,
whereas it was 18.6 ± 4.5 for the observations
(Marinone, 2003). The comparison of sea surface
temperatures obtained from the model with sea surface
temperatures obtained from the region studied by Soto-
Mardones et al. (1999) revealed that the evolution of
warm and cold water pools was reproduced in the
central part of the NGC, as well as the presence of a
lateral temperature gradient during the summer in the
southern part of the GC (Marinone, 2003). For further
validation of the currents obtained by the model, refer
to [http://gulfcal.cicese.mx/].
The Lagrangian behavior obtained from particle
advection was also validated by comparing the results
obtained for the trajectories of buoys (ARGOS) released
in the NGC in September (1995) and March (1996) by
Lavin et al. (1997), where one cyclonic and one
anticyclonic rotation were observed. Additionally,
Calderon-Aguilera et al. (2003) described the
migratory patterns of the blue shrimp by associating the
circulation patterns during the summer in the northern
part of the GC. In that study, every day and during two
periods (July 12–27, 1995 and June 30 to July 16,
1996), simultaneous samples of post-larval shrimp
were collected in two locations of the NGC (San Felipe
on the peninsula side, and Santa Clara on the
continental side of the GC). To simulate circulation, the
output of the HAMSOM model was used. From the
significant results, it was determined that the model
served as an important tool to explain why the post
larvae found in the continental sector were bigger
(apparently, they were older) than those found on the
peninsula side. Similarly, Cudney-Bueno et al. (2009)
used this model to evaluate the possible effects of the
reserve network of the upper gulf’s continental sector
on adjacent areas. The results of the model were
compared with oceanographic experiments and the
changes observed in the density of commercial juvenile
mollusks before and after establishing the reserves. In
that respect, the model suggested that San Jorge Island,
on the southern side, in particular, could be responsible
for exporting larvae to the reserves and fishing areas
along the coast. Munguia-Vega et al. (2014) hypothe-
sized that the source-sink metapopulation dynamic of
the Mycteroperca rosacea larvae in 17 zones
distributed across the Great Islands describes the
direction and frequency of larval dispersion based on
an oceanographic model (HAMSOM) that favors the
understanding of empirical genetic data.
The comparison of model results (Eulerian and
Lagrangian), with the described observations reported in
the different studies cited, lends qualitative confidence to
using this online tool to examine connectivity matrices
and dispersion patterns throughout a climatological
year.
Webpage
The webpage [http://conectividad-dispersion.cicese.
mx/] presents results for connectivity, dispersion, etc.
both in English and Spanish. The page content was
divided into four sections: the first (Start) provides a
brief explanation of the methodology of products
obtained as well as visualization options for the results
presented in the second section (Interactive Map). The
third section (Help) provides a brief explanation of how
to use the webpage as well as some concepts, and the
fourth section (Contacts) acknowledges collaborators
involved in developing the page.
Interactive map
In this section (Fig. 1), the user can select:
Matrix – Connectivity matrices for mean depth and
standard deviation
Dispersion – Maps of final particle positions and
histograms
To display the figures, one must first select the type
of graph: matrix or dispersion. This option is located in
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Figure 1. Image of the webpage’s interactive map section.
Figure 2. Example of a connectivity matrix. The release was completed in March at the first layer (0–10 m). In this case,
the final time selected was the end of the sixth week.
the top central area of the webpage. Following,
examples of both types of figures are described.
a) Matrix
For this graph, the matrix type must be selected:
connectivity, mean depth or standard deviation; the
option is found at the top central part of the page. The
release options are found at the top right, in which the
user selects the depth (1 to 12 layers), the month (1 to
12 months) and the final visualization time (2, 4, 6 or 8
weeks). For example, Fig. 2 shows a connectivity
matrix for March, releasing particles at a depth range of
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Interactive webpage on three-dimensional connectivity 5
Figure 3. Example of a particle’s final position map and its corresponding histogram. The release was performed in the
Central Peninsular Region (CP) in March at the first layer (0–10 m). In this case, the final time selected was the end of the
sixth week.
Figure 4. Example of a particle’s final position map and its corresponding histogram. The release was done in the Central
Peninsular Region (CP) in March at the first layer (0–10 m). In this case, the option “All” was selected, displaying the four
different final periods.
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0–10 m and displaying the results for the sixth week
after release. In contrast, Fig. 2 shows that the particles
released in the Central Peninsular Region (CP) moved
towards the Sills Zone (SZ), Guaymas Basin (GB) and
Central Continental Region (CC), and a small
percentage of the particles are found in the same sector
in which they were released. Similarly, north of
Tiburón Island (TI), six weeks after release, the
particles moved towards the regions of GB, CC,
Farallón Basin (FB) and the South Continental Region
(SC).
The data for each connectivity, mean depth and
standard deviation matrix may be downloaded by
selecting the option “Data” located in the top center of
the page. The format of the data is the same as that of
the figure, that is, the horizontal axis represents the
particle arrival location, and the vertical axis represents
release areas.
b) Dispersion
First, a release area must be selected; this is
accomplished using the map located at the upper left of
the page. This map shows the 17 regions into which the
GC was divided, each with its associated acronym. The
results are shown for the different depths of the GC and
for the 12 months of the year. However, in the case of
a particle’s final position, there are two options for
displaying the results: specific, by selecting 2, 4, 6 and
8 weeks; and general, by selecting “all”, whereby all
four results are displayed in a single image. Finally, in
the lower left of the page there is an option for
information, which provides the full name and number
of layers of the area selected.
Figures 3 and 4 show examples of a specific map
and a general map, respectively, of the final position of
the particles and their corresponding histogram. This
provides a visual representation of the steps described
previously. It is important to note that the dispersion
maps complement the matrix analysis.
Figure 3 shows the position of the particles six
weeks after being released in the CP, which more
precisely presents the particles’ paths, as well as depths
at which they are located. In this case, the majority of
the particles are found at depths greater than 40 m and
predominantly moved in the direction of the GB sector.
Fig. 4 depicts the four periods, permitting the trajectory
of the particles to be inferred. In this case, at the end of
the eighth week, a higher percentage of the particles
released moved towards the east of the CP, CC and GB
sectors. It was also observed that in the second region,
the majority of the particles were located at depths >50
m; however, in the following weeks, most of these
particles were located at depths <60 m.
Finally, it is possible to download the data from
each map depicting the particles’ final positions by
selecting the option “Data” located in the upper center
of the page. The format of this document is presented
in three columns (longitude, latitude, depth). The
heading of the first row provides the Julian hour of the
final positions, that is, the second, fourth, sixth and
eighth weeks correspond to the hours 336, 672, 1008
and 1344, respectively. The remaining rows provide the
positions of each particle.
FINAL CONSIDERATIONS
The interactive online webpage developed in this study
presents the three-dimensional connectivity results
among 17 areas of the GC and the spatial distribution
of particles released from each of the areas. These
results were realized based on the advection of particles
obtained from a 12-layer three-dimensional numerical
model that was validated with respect to the primary
circulation characteristics of the GC. The associated
temporal scales are limited to model forcing, which
correspond to the seasonal variations in tides; therefore,
fluctuations in other frequencies are not considered for
the model used in this interactive webpage. The results
presented here are qualitative and should not be used as
a key tool for decision making. However, the results
offer an approximation of the connectivity and
dispersion patterns in the GC, which may help in the
understanding of dispersion patterns for marine
organism larvae as well as contaminants.
ACKNOWLEDGEMENTS
This study is part of the Masters of Science thesis of
CMC, who was supported by a CONACyT scholarship.
Financial support is part of the regular budget of the
CICESE and of project CONACyT No. 44055.
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Received: 20 December 2015; Accepted: 27 December 2016
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