The isotopic composition of carbon in macroalgae (
Macroalgae show a wide diversity of thallus morphologies (e.g., filamentous,
articulated, flattened), structural organization (e.g., surface area
In marine environments, where pH
The habitat features and environmental conditions in marine ecosystems
modify the main macroalgae photosynthesis drivers, such as light (Anthony et
al., 2004; Johansson and Snoeijs, 2002), DIC (Brodeur et al., 2019; Zeebe
and Wolf-Gladrow, 2001), and inorganic nutrients (Ochoa-Izaguirre and
Soto-Jiménez, 2015; Teichberg et al., 2010). These factors could
generate negative consequences for their productivity, principally when they
cause resource limitation. Each factor varies from habitat to habitat
(e.g., local scale: from intertidal to subtidal zone; and global scale: from
temperate to tropical regions), and in response to these environmental
changes, macroalgae can modulate their photosynthetic mechanism (Dudgeon et
al., 1990; Kübler and Davison, 1993; Lapointe and Duke, 1984; Young and
Beardall, 2005). The modulation, to increase their photosynthetic activity
(up-and-down regulation processes), implies a physiological acclimation
enhancing the transport of DIC (CO
The
The Gulf of California is a subtropical, semi-enclosed sea of the Pacific
coast of Mexico, with exceptionally high productivity making it the most
important fishing region for Mexico and one of the most biologically diverse
worldwide marine areas (Espinosa-Carreón and Valdez-Holguín, 2007;
Lluch-Cota et al., 2007; Páez-Osuna et al., 2017; Zeitzschel, 1969). The
Gulf of California represents only 0.008 % of the area covered by the seas
of the planet (265 894 km
Regionalization criteria of the GC include phytoplankton distribution (Gilbert and Allen, 1943), topography (Rusnak et al., 1964) and depth (Álvarez-Borrego, 1983), oceanographic characteristics (Álvarez-Borrego, 1983; Marinone and Lavín, 2003; Roden and Emilson, 1979), biogeography (Santamaría-del-Ángel et al., 1994), and bio-optical characteristics (Bastidas-Salamanca et al., 2014). The topography is variable along the GC and includes submarine canyons, basins, and variable continental platforms. Besides, the GC presents complex hydrodynamic processes, including internal waves, fronts, upwelling, vortices, and mixing of tides. The gulf's coastline is divided into three shores: extensive rocky shores, long sandy beaches, numerous scattered estuaries, coastal lagoons, open muddy bays, tidal flats, and coastal wetlands (Lluch-Cota et al., 2007).
The Gulf of California is different in the north and the south, related to a
wide range of physicochemical factors. The surface currents seasonally
change direction and flow to the southeast with maximum intensity during the
winter and to the northwest in summer (Roden, 1958). The northern part is
very shallow (
Site collection along the continental (C1–C3) and peninsular
(P1–P3) Gulf of California coastlines
In the GC around 669 macroalgae species exist, including 116 endemic species
(Espinoza-Avalos, 1993; Norris, 1975; Pedroche and Sentíes, 2003). Many
endemic species currently have a wide distribution along the Pacific Ocean
coast but with GC origin (Aguilar-Rosas et al., 2014; Dreckman, 2002).
Based on oceanographic characteristics (Roden and Groves, 1959) and in the
endemic species distribution (Aguilar-Rosas and Aguilar-Rosas, 1993;
Avalos, 1993), the GC can be classified into three phycofloristic
zones: (1) the first zone located from the imaginary line connecting San
Francisquito Bay, B.C. (Baja California), to Guaymas, Sonora, with 51 endemic species; (2) the
second zone with an imaginary line from La Paz Bay (B.C.S.; Baja California Sur) to Topolobampo
(Sinaloa) with 41 endemic species; (3) the third zone is located with an
imaginary line from Cabo San Lucas (B.C.S.) to Cabo Corrientes (Jalisco)
with 10 endemic species. Besides, 14 endemic species are distributed
throughout the GC (Espinoza-Ávalos, 1993). The macroalgal communities
are subject to the changing environmental conditions in the diverse habitats
in the GC that delimit their zonation, which tolerates a series of
anatomical and physiological adaptations to water movement, temperature, sun
exposure, light intensities, low
In this study, the GC coastline (21–30
Based on the local environmental factors, four to five macroalgae specimens of the most representative species were gathered by hand (free diving) during low tide. A total of 809 composite samples were collected from marine habitats along both GC coastlines. The percentages of specimens collected for the substrate type were 28 % sandy-rock and 72 % rocky shores based on the habitat features. In the hydrodynamic, 30 % of the specimens were collected in habitats with slow to moderate and 70 % with moderate to fast water movement. Regarding the protection level, 57 % were exposed specimens, and 43 % were protected. Finally, 56 % were intertidal and 44 % subtidal macroalgae organisms concerning the emersion level. About half of the protected specimens were collected in isolated rock pools, which was noted.
In four to five sites of each habitat, we measured in situ the salinity, temperature, and pH
by using a calibrated multiparameter sonde (Y.S.I. 6600V) and the habitat
characteristics mentioned above noted. Besides, composite water samples were
collected for a complementary analysis of nutrients, alkalinity (and their
chemical components), and
The collected material was washed in situ with surface seawater to remove the
visible epiphytic organisms, sediments, sand, and debris and then thoroughly
rinsed with Milli-Q water. The composite samples were double-packed in a
plastic bag, labeled with the locality's name and collection date, placed in
an ice cooler to be kept to 4
In the laboratory, macroalgae samples were immediately frozen at
The variability in
Macroalgae were grouped according to their morphofunctional characteristics
proposed initially by Littler and Littler (1980) and modified by Balata et
al. (2011). Most of the macroalgae species showed a limited distribution
along the GC coastlines. Few cosmopolites' species included
A basic statistical analysis of
The relationships between
Sampled specimens belong to 3 phyla, 63 genera, and 170 species. The
phyla were identified as Chlorophyta (25 %), Ochrophyta (22 %), and
Rhodophyta (53 %). The most representative genera (and their species) were
An analysis of the biogeographical diversity among sectors evidenced that P3 (43 genera of 63, 68 %) and C3 (63 %) in the north recorded the highest number of the genus, followed by C1 (38 %) and P1 (29 %) in the south, and P2 (27 %) and C2 (22 %). The same pattern was observed in the species diversity: zones P3 (94 of 167 species, 56 %) and C3 (52 %) in the north, C1 (34 %) and P1 (25 %) in the south, and C2 and P2 (19 %–20 %) in the center.
The morphofunctional groups identified were 21. The most common were
C-Tubular (6 species,
The variability in
Variability in
Variability in
Multiple comparison analyses revealed significant differences in the
Aggrupation of
Variability in
High intraspecific variability in
Carbon isotopic composition (‰) in species of phylum Chlorophyta collected along the Gulf of California coastlines.
Carbon isotopic composition (‰) in species of phylum Ochrophyta collected along the Gulf of California coastlines.
Carbon isotopic composition (‰) in species of phylum Rhodophyta collected along the Gulf of California coastlines.
A diversity of macroalgal assemblages were documented along the GC
coastlines, with differences in the taxonomic composition according to their
fico-floristic region. Multiple comparison analyses of
Proportion of species using different DIC sources according to their
carbon uptake strategies: HCO
Variability in
Variability in
Non-significant differences were observed for the same genera at different
temperature ranges except for
Variability in
Significant differences were observed among the genera related to the pH
level in seawater (Fig. 7b). Under typical pH seawater,
We analyzed the carbon uptake strategies on macroalgal assemblages as a
function of environmental factors like temperature, pH, and salinity (Fig. 8). The temperature and salinity non-significantly explained the
Proportion of species using different DIC sources according to their
carbon assimilation strategies: HCO
Summary of the estimated regression coefficients for each simple
linear regression analysis and of the constant of fitted regression models.
Estimated regression coefficients include degree of freedom for the error
(DFE), root-mean-square error (RMSE), coefficient of determination
(
The
Trends in the
In the most representative morphofunctional groups, significant correlations
(
Trends in the
The
Results of the analysis of the relationships between
The biogeographical collection zone, featured by coastline (continental versus peninsular) and coastal sectors (C1–C3 and P1–P3), explained a maximum of
5 % variability. Only the emersion level (6 %) contributed to the
Multiple regression analyses were also performed to interpret the complex
relationships among
Summary of the estimated regression coefficients for each
multivariate linear regression analysis and of their constant of fitted
regression models performed in individuals binned by genus. Estimated
regression coefficients include degree of freedom for the error (DFE),
root-mean-square error (RMSE), coefficient of determination (
Summary of the estimated regression coefficients for each
multivariate linear regression analysis and of their constant of fitted
regression models performed in individuals binned by coastline sector and
genus. Estimated regression coefficients include degree of freedom for the
error (DFE), root-mean-square error (RMSE), coefficient of determination
(
Summary of the estimated regression coefficients for each
multivariate linear regression analysis and of their constant of fitted
regression models performed in individuals binned in coastline sector,
habitat features, environmental conditions, and physiological state
separately by morphofunctional group and genus. Estimated regression
coefficients include degree of freedom for the error (DFE),
root-mean-square error (RMSE), coefficient of determination (
Considering the combined effect of the coastline sector
The combined effect of environmental conditions on the
Constant of fitted regression model explaining the
Constant of fitted regression model explaining the
Constants of fitted regression model explaining the
Concurrent analysis of surface seawater for alkalinity, proportions of the
chemical species of DIC (CO
Based on the subtraction of
A high variability in the
Most authors studying the isotopic composition of C in macroalgae have
reported the high isotopic variability, which has been attributable to the
taxon-specific photosynthetic DIC acquisition properties (Díaz-Pulido
et al., 2016; Lovelock et al., 2020; Marconi et al., 2011; Mercado et al.,
2009; Raven et al., 2002a; Stepien, 2015). Our study observed that the
intrinsic characteristics of each morphofunctional group of macroalgae
(e.g., thallus structure, growth form, branching pattern, and taxonomic
affinities) also influence the
The
Many species that recorded high
Changes in the habitat features and environmental conditions, such as light
intensity and DIC availability, influencing the growth rate and
photosynthetic intensity, have a strong influence on
The
The effect of other environmental factors, such as salinity and pH, on
Based on pH, differences in
In our study, the
Macroalgae collected in GC also involved only HCO
Only three non-calcifying species (
Few calcifying macroalgae species using HCO
Measurements of
Based on the
Changes in the
Light is not limited along the GC latitudes. Most of the shallow habitats
occupied by macroalgal communities in the GC were high-light environments.
In agreement with the literature, the surface seawater temperature across
the GC varies by only 1
The proportion of specimens with different carbon uptake strategies also
showed regional variations. For example, the facultative uptake of
HCO
In conclusion, we observed high
Most macroalgae inhabiting in GC displayed the presence of CO
Finally, diverse authors have reported significant correlations between
Our research is the first approximation to understand the
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RVO participated in the collection, processing, and analysis of the samples as a part of his master's degree thesis. MJOI also participated in sample collections and identified macroalgae specimens. MFSJ coordinated the research, was the graduate thesis director, and prepared the manuscript with contributions from all co-authors.
The contact author has declared that neither they nor their co-authors have any competing interests.
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The authors would like to thank Humberto Bojórquez-Leyva, Yovani Montaño-Ley, and Arcelia Cruz-López for their invaluable field and laboratory work assistance. Thanks to Sarahí Soto-Morales for the English revision. UNAM-PAPIIT IN206409 and IN208613 provided financial support, and UNAM-PASPA supported MF Soto-Jimenez for a sabbatical year. Thanks to CONACYT for a graduate fellowship to Roberto Velázquez-Ochoa.
This research has been supported by the Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México (grant nos. PAPIIT IN206409 and PAPIIT IN208613).
This paper was edited by Aninda Mazumdar and reviewed by Matheus C. Carvalho, Michael Roleda, and one anonymous referee.