Blue-Carbon Stocks in Arid Mangroves of La Cruz Lagoon,Gulf of California,Mexico

Abstract

Background and Research Aims: Mangroves and other blue-carbon ecosystems have recently raised considerable interest for their potential contribution to the mitigation of CO₂ emissions. One service of global impact provided by mangrove ecosystems is their role as carbon sinks. Most carbon in mangrove ecosystems is stored belowground as peat, which, unlike shorter-lived aboveground biomass, often remains undecomposed for centuries or millennia. The objective of this study was to estimate the carbon stock (biomass) and its storage in soil in La Cruz Lagoon, at the arid region of the Gulf of California.

Methods: Aboveground biomass was estimated based on mangrove structure, pneumatophores, and litter-based primary-productivity; belowground biomass was measured by extracting root cores (45 cm deep), soil cores (1 m deep) and estimating the production of in-growth core roots. Total biomass values were converted to carbon using allometric equations and soil carbon stores by means of laboratory elemental analyzers.

Results: The main results showed a low structural development with a litter productivity of 2.21 Mg·ha·year^-1, with a carbon aboveground biomass of 29.8 ± 3.4 Mg C_org·ha^-1 and a belowground biomass of 35.1 ± 88 Mg C_org·ha^-1, with a root:shoot ratio slightly greater than 1, meaning that belowground carbon associated with mangrove biomass is higher than aboveground carbon. The estimated total carbon was 207.21 ± 42.4 Mg C_org·ha^-1.

Conclusion: These results suggest a higher content of BGB than AGB is a function of aridity, that is, allocating C belowground rather than aboveground, which helps justifying conservation and restoration strategies to improve or recover the ecosystem services of mangrove ecosystems.

Implications for conservation: Implications for conservation of the mangrove ecosystem in tropical and/or subtropical regions has its importance in maintaining forests with high capacity to capture atmospheric CO₂ that serves as a carbon sink and storage facility, as a nature-based ecosystem service.

Introduction

The concept of blue-carbon was first raised in 2009 to alude coastal ecosystems that capture and store (‘sequester’) organic carbon and include mangrove forests, tidal marshes, and seagrass meadows as the main players (Mcleod et al., 2011; Nellemann et al., 2009). Mangroves and other blue-carbon ecosystems have raised considerable interest for their potential contribution to the mitigation of anthropogenic CO₂ emissions (Thomas, 2014). A major service of global impact provided by mangrove ecosystems is their role as carbon sinks (Chmura et al., 2003), allowing carbon to be stored in soil for centuries to millennia, as opposed to the decadal scales typical of carbon stored in plant biomass, which makes up the majority of organic carbon (C_org) stocks in terrestrial systems (Duarte et al., 2013; Mateo et al., 1997; Pedersen et al., 2011).

The evidence available to date suggests that carbon stocks in mangrove forests can be highly variable, and a diversity of factors influence carbon sequestration and storage, such as differences in soil type, infauna, hydrology, forest type, salinity, forest age, and geomorphological setting (Adame et al., 2017; Donato et al., 2011; Ouyang & Lee, 2020; Saintilan et al., 2013). Mangrove carbon stocks also vary between species. Species with higher primary productivity can have greater carbon stocks and higher rates of organic matter input into soil (Gress et al., 2017; Liu et al., 2014; Owers et al., 2016). Several studies have measured increases in soil C_org density and content with increasing age of individual stands (Chen & Twilley, 1999; Kathiresan et al., 2021; Ray et al., 2023; Wang et al., 2021; Wiarta et al., 2019), highlighting large local and regional differences in age-related soil C_org stock patterns (Alongi & Zimmer, 2024).

Several studies have reported positive relationships between aboveground and belowground organic carbon (Donato et al., 2011; Wang et al., 2013). Most carbon in mangrove ecosystems is stored belowground as peat (Donato et al., 2011), which, unlike shorter-lived aboveground biomass (AGB), often remains undecomposed for millennia (Ezcurra et al., 2016; McKee et al., 2007). The belowground biomass (BGB) of mangrove forests is affected by forest age (Ha et al., 2018; McKee, 2001), plant characteristics (Ezcurra et al., 2016; McKee et al., 2007) and environmental conditions (Cahoon et al., 2003; Otero et al., 2009). However, there is high uncertainty in the estimation of BGB and production, as most estimates have been derived primarily from allometric equations (Adame et al., 2017; Li et al., 2018).

Field research to estimate carbon stocks in mangrove ecosystems has focused primarily on study sites located in humid regions in temperate and tropical latitudes (Alongi & Dixon, 2000; Chmura et al., 2003; Donato et al., 2011), with relatively few studies in subtropical or arid regions (Adame et al., 2013; Ezcurra et al., 2016) where low rainfall, high temperatures, evapotranspiration, and soil conditions could affect carbon storage. The high importance of coastal ecosystems for carbon sequestration services in arid environments requires identifying the factors that account for their relatively small soil carbon stocks (Schile et al., 2017). In addition, the correct assessment of the spatial variation of mangrove forest carbon stocks is needed for ecosystem service valuations (Friess et al., 2022). The objectives of this study were 1) to determine the aboveground and belowground carbon stocks of the mangrove ecosystem and 2) to determine how the arid environment influences storage levels.

Methods

Study Area

The La Cruz Lagoon, located in the Gulf of California, in the town of Bahía de Kino, Sonora (111°52′52.65″ W– 28°47′14.76″ N), is a coastal lagoon with hypersaline conditions in summer, with low river water inputs (Glenn et al., 2006). It is of global importance due to its physical characteristics, location, and high species diversity, having been designated as Ramsar site number 2154, with an approximate area of 6,665.15 ha (Ramsar, 2013). The mangrove forest of the La Cruz estuary is dominated by black mangrove (Avicennia germinans L. Stearn), with little coverage of red mangrove (Rhizophora mangle L.) concentrated in the southwest, near the estuary mouth; in addition, there are associated species such as Batis maritima, Salicornia sp., and Distichlis palmeri (Meling-López et al., 1993). The maximum ambient temperature recorded in the locality is 48.5°C in July, and the minimum temperature is 15.0°C in February, with an annual precipitation of 161.3 mm (CONAGUA, 2016). The local climate is warm and dry with summer rainfall, BW (h’) hw according to Köppen’s classification (García, 2004). We delimited two sampling sites in the mangrove forest: Site 1 and Site 2 (Figure 1). Two monitoring units (MU1 and MU2) were established at each site. The study comprised an annual sampling period from May 2021 to April 2022.

Figure 1.

Sampling Sites in the Mangrove Ecosystem, La Cruz Lagoon, Gulf of California. Climograph.

Field Study

Physicochemical Parameters in Water and Soil

The physicochemical variables of surface and interstitial water were measured using a Hanna HI9828 multiparameter (Moreno-Casasola & Warner, 2009). For interstitial water, 4 piezometers were installed at a depth of 0.5 m, while surface water was collected during flood tide. At each site, we recorded salinity using the classification according to Cowardin et al. (1979) in practical units of salinity, redox potential (mV), temperature (°C), and pH.

Two soil samples were collected in each MU monthly from the upper 20 cm of soil using a 4″ diameter nucleator. The samples were transported to the laboratory, dried, and ground for texture analysis using the Bouyucos method (Klute, 1982), organic matter (% OM) by wet digestion (Walkley & Black, 1934), and total phosphorus content using the method of Bray and Kurtz (1945), and total nitrogen with the Kjeldahl method (SEMARNAT, 2000). In addition, two soil samples of known volume were collected in each MU (96 samples) to determine the bulk density and moisture content of the soil according to Moreno-Casasola and Warner (2009). Soil moisture content is the percentage of water stored in one gram of soil; a value of 100% means that 1 g of soil stores 1 g of water (Infante, 2011).

Mangrove Forest Structure

To estimate the structure of the mangrove forest, a 10 m × 10 m quadrant was established in each sampling unit (4 in total). The species identity, height, and diameter at breast height (DBH) of each tree were recorded at each quadrant; with this data, tree density, coverage, and basal area were calculated (CONABIO, 2013).

Primary Productivity Based on Litterfall

Four litter traps were placed in each MU, for a total of 16 traps (Moreno-Casasola & Warner, 2009). Litter samples were collected each month and transported to the laboratory. These samples were dried at 60°C, and each component was weighed, leaves, stipules, wood, branches, flowers, and fruits. Litter production values are ex-pressed as g·m²·month^-1 and Mg·ha·year^-1.

Belowground Root Biomass

Soil root samples were extracted at a depth of 45 cm with a stainless-steel corer measuring 0.45 m long by 11 cm in diameter, using the methodology of Adame et al. (2014). Three cores were extracted from each sampling unit (12 cores in total); each nucleus was divided according to depth strata: 0 cm to 15 cm, 15 cm to 30 cm, and 30 to 45 cm (Castañeda-Moya et al., 2011). The samples were refrigerated and transported to the laboratory, where they were immersed in water, separating floating living roots from dead roots (considered necromass) that sank to the bottom. Living roots were classified into three diameter classes: fine (<2 mm), medium (2 mm–5 mm), and large (>5 mm) diametric classes; then, they were dried and weighed to obtain root biomass (gDw·m²) (Castañeda-Moya et al., 2011). An approach to gain a greater understanding of root biomass distribution has been to explore the root/shoot ratios (BRB:AGB), defined as root biomass (including necromass) divided by aboveground biomass (Mokany et al., 2006).

The total pneumatophore sample was collected at ground level in 50 cm × 50 cm quadrants distributed at random within the MU, with two quadrants in each UM (8 quadrants in total). Pneumatophores were kept at 4°C and transported to the laboratory for height measurement; they were then oven-dried at 60°C and weighed. The density (no. of pneumatophores·m²) and biomass (grams of dry weight per square meter of soil; gDw·m²) were determined.

Root Production

In each MU, two 0.5 cm mesh cores filled with peat moss were placed (Adame et al., 2014). One bag per MU was removed six months later, at Time 1 (T1); 12 months later (T2), the second bag was removed. Root production was determined as the difference between the initial biomass (T0) and that observed at T1 and T2. The samples were transported to the laboratory to determine biomass; to this end, the samples were immersed in water to separate the living roots from dead roots as the belowground root biomass procedure. The roots were dried and weighed (Dw·m^-2·d^-1).

Carbon Estimates

In the allometric equations, carbon conversion factors were considered for each component. Blue carbon estimation used the allometric equations for Avicennia germinans (Ag) proposed by Smith and Whelan (2006) for mangroves in South Florida, USA, (Table 1) due to their similarity to the ecosystem studied.

Table 1.

Allometric Equations Used to Determine Mangrove Tree Biomass.

Component	Species	Equation	Reference
BA: Living trees	Ag	B = 0.403*ρ*(DBH)1.934	Smith & Whelan (2006)

BA= basal area; Ag; Avicennia germinans; B = biomass; DBH = diameter at breast height (cm); ρ = wood density (g·cm³).

The conversion factor used to determine the carbon content from tree biomass was proposed by Kauffman and Donato (2012): Carbon content of each tree (MgC·ha^-1) = tree biomass * carbon conversion factor (0.48). For leaf litter and pneumatophores, we used a factor of 0.45 (Howard et al., 2014); organic carbon concentrations between 38% and 49% stored in this component are reported (Kauffman et al., 1995). Carbon stored in living roots stores between 36 % and 42 % of carbon in tropical forests (Jaramillo et al., 2003), so we considered a conversion factor of 0.39. For necromass, a conversion factor of 0.5 was considered (Howard et al., 2014) because the carbon content stored in dead wood in tropical forests is around 50 %. All carbon contents were expressed as MgC_org·ha^-1, biomass was expressed in gDw·m^-2, and area in ha, and estimated as follows:

${\mathrm{C}}_{\text{Litter}}\hspace{0.17em}({\text{MgC}}_{\text{org}}·{\text{ha}}^{-1})=\left(\text{Average}\hspace{0.17em}\text{litter}\hspace{0.17em}\text{biomass}\hspace{0.17em}*\hspace{0.17em}0.45\right)\hspace{0.17em}/\hspace{0.17em}\text{Area}$

${\mathrm{C}}_{\text{Pneumatophores}}\hspace{0.17em}({\text{MgC}}_{\text{org}}·{\text{ha}}^{-1})=\left(\text{Pneumatophore}\hspace{0.17em}\text{biomass}\hspace{0.17em}*\hspace{0.17em}0.39\right)\hspace{0.17em}/\hspace{0.17em}\text{Area}$

${\mathrm{C}}_{\text{Root}\hspace{0.17em}\text{biomass}}\hspace{0.17em}({\text{MgC}}_{\text{org}}·{\text{ha}}^{-1})=\left(\text{Root}\hspace{0.17em}\text{biomass}\hspace{0.17em}*\hspace{0.17em}0.39\right)\hspace{0.17em}/\hspace{0.17em}\text{Area}$

${\mathrm{C}}_{\text{Necromass}}\hspace{0.17em}({\text{MgC}}_{\text{org}}·{\text{ha}}^{-1})=\left(\text{Necromass}\hspace{0.17em}*\hspace{0.17em}0.5\right)\hspace{0.17em}/\hspace{0.17em}\text{Area}$

We followed the standardized laboratory and calculation protocols established by Howard et al. (2014). In each monitoring unit, one soil core was extracted at a depth of 1 m (Howard et al., 2014); it was divided into 4 samples according to the depth stratum: 0 cm–15 cm, 15 cm–30 cm, 30 cm–50 cm, and 50 cm–100 cm (Marín-Muñiz et al., 2014). The samples were stored at 4°C and transported to the laboratory for analysis (Howard et al., 2014; Marín-Muñiz et al., 2014). The percentages of total C and organic C were determined by flash combustion on a Flash 2000 Elemental Analyzer (Thermo Fisher Scientific) Waltham, MA, USA (https://www.thermofisher.com, retrieved November 16, 2023). The inorganic carbon content was determined by calcinating a sample in a muffle oven at 550°C for four hours and the organic carbon content was obtained as the difference of the percent of total carbon and the percent inorganic carbon from the calcinated sample.

Statistical Analysis

We analyzed spatial and temporal differences in the physicochemical parameters of water and soil, mangrove forest structure, pneumatophores, litter, living roots, necromass, and root production, using a one-way ANOVA and Tukey’s tests (Steel & Torrie, 1996). Kolmogorov-Smirnov & Levene tests were applied to verify data normality and homoscedasticity. The statistical analysis was performed with the IBM SPSS Statistics software.

Results

Variation of Physicochemical Parameters in Soil

The temporal variation (monthly) of physical and chemical elements in Soil (phosphorus, nitrogen, organic matter and moisture content) can be observed in Figure 2. Spatially, a low Soil sand content was recorded in the monitoring sites, with an average of 18.9 ± 1.1%, 61.5 ± 1.4 % clay, and 19.6 ± 0.6 % silt, with no significant differences between sites (F = 7.6, N = 288, p = 0.9) (Table 2). The mean bulk density was 0.59 ± 0.2 g·m^-3, with significant differences between sites (F = 13.2, N = 88, p = 0.002).

Figure 2.

Monthly Variation of Total Phosphorus, Total Nitrogen, Organic Matter, and Humidity Content in Sediment in the Monitoring Sites of the La Cruz Lagoon.

Table 2.

Texture, Bulk Density, and Electrical Conductivity of Soil at Monitoring Sites.

		Site 1	Site 2
Texture %	Sand	12.0 ± 1.1	25.8 ± 1.2
	Clay	72.1 ± 1.5	50.9 ± 1.2
	Silt	15.9 ± 0.6	23.3 ± 0.6
	Bulk density (g·m−3)	0.6 ± 0.01	0.57 ± 0.02
	Electric conductivity (mV)	55.8 ± 1.9	74.3 ± 1.3

Physicochemical Variation in Surface and Interstitial Water

During the monitoring cycle, low precipitation was recorded, with 130.5 mm·year^-1 (Figure 1). The monthly physicochemical characteristics of surface water showed temperature values from 12.2 to 30.07°C, again with no significant differences (Table 3). Regarding salinity, the highest level was recorded in March, with 46.9 ± 0.2 psu, and the lowest in December, with 38.58 ± 0.2 psu. In relation to the variation of physicochemical parameters in interstitial water, salinity ranged from 47.8 to 43.2 psu; only the redox potential showed significant differences, with more oxidative values in May (150 ± 0.2 mV) and more reductive values in March (-110 ± 10.5 mV) (Table 3).

Table 3.

Variation of Physicochemical Parameters in Surface and Interstitial Water During the Monitoring Months.

		Months												Statistic
		M	J	J	A	S	O	N	D	J	F	M	A	F	p
Superficial water	pH	5.7 ± 0.3	7.1 ± 0.1	7.2 ± 0.1	7.3 ± 0.1	7.1 ± 0.1	7.4 ± 0	7.5 ± 0	7.8 ± 0.1	7.2 ± 0.1	7.7 ± 0.2	7.3 ± 0.1	6.9 ± 0	19	0.9
	Temperature	21.6 ± 0.1	28.7 ± 0.3	29.4 ± 0.3	30.1 ± 0.4	29.1 ± 0.2	21.7 ± 0.2	14 ± 0.4	14.3 ± 0.2	13.7 ± 0.7	12.2 ± 0.5	16.1 ± 0.2	22.3 ± 0.2	17	0.39
	Salinity	38.6 ± 0	40 ± 0.3	39.5 ± 0.6	39.1 ± 0.9	40.8 ± 2	39.7 ± 1.1	40.7 ± 0.8	38.6 ± 0.2	42.8 ± 1.4	41.3 ± 0.6	46.9 ± 0.2	45.5 ± 0.3	9.1	0.13
	Redox	144.7 ± 0.2	123.5 ± 0.8	126 ± 1	128.5 ± 1.2	117.6 ± 1.6	136.8 ± 3	45.9 ± 26.7	156.1 ± 4.5	−64.3 ± 48.8	30.8 ± 32.5	−147.5 ± 0.1	−65.3 ± 16.6	17.1	0.01
Interstitial water	pH	6.9 ± 0.03	6.9 ± 0.01	7 ± 0.12	7 ± 0.23	6.8 ± 0	6.9 ± 0.04	6.9 ± 0.02	6.9 ± 0.09	6.8 ± 0.04	6.8 ± 0.03	6.5 ± 0.06	6.2 ± 0.12	7.2	0.05
	Temperature	25.6 ± 0	28.9 ± 0.1	29 ± 0.1	29.1 ± 0.2	28.9 ± 0.1	24.1 ± 0.1	18.2 ± 0.3	19.3 ± 0.2	17.2 ± 0.4	16 ± 0.3	18.3 ± 0.1	22.7 ± 0.2	6.2	0.39
	Salinity	43.2 ± 0.1	46.2 ± 1.9	46.1 ± 1.3	45.9 ± 0.8	47.4 ± 1.2	47.2 ± 1.2	45.6 ± 1.4	46.9 ± 1.3	44.3 ± 1.4	44.3 ± 1	47.7 ± 0.8	47.8 ± 0.8	1.6	0.82
	Redox	150 ± 0.2	125 ± 0.9	127 ± 0.8	129 ± 0.7	116 ± 2.2	102 ± 6.3	−3 ± 8.7	88 ± 4.8	−95 ± 10.5	62 ± 2.8	−110 ± 10.5	−94 ± 10.4	18	0.04

p < 0.05, N = 96, ± SE = standard error, Temperature = °C, Redox = mV.

Mangrove Forest Structure

The structural characteristics of the mangrove forests showed no significant differences in tree height and stem diameter across MUs (N = 419, p > 0.05) and presented a mean height of 1.83 ± 0.05 m and a mean stem diameter of 4.86 ± 0.17 cm . However, the basal area did record significant differences (F = 12, N = 419, p < 0.05), with 5.5 ± 0.47 m·ha^-1 (Table 4).

Table 4.

Structural Attributes of Mangroves.

Site	MU	Density	Height (m)	DBH (cm)	Basal area (m·ha−1)
1	1	1110	1.91 ± 0.06	5.29 ± 0.2	6.37 ± 0.52
	2	1150	2.03 ± 0.05	5.66 ± 0.24	7.59 ± 0.87
2	3	880	1.54 ± 0.04	4.09 ± 0.13	3.55 ± 0.24
	4	1050	1.87 ± 0.04	4.41 ± 0.13	4.17 ± 0.28

MU: Monitoring unit (±SE = standard error).

Leaf Litter Production

A decrease in the mean litter content, 2.21 Mg·ha^-1·year^-1, was recorded; the leaf component recorded the highest value, 15.5 ± 1.5 g·m^-2·month^-1, with no significant differences (F = 1.56, N = 24, p = 0.34). The largest number of flowers was recorded from June to September, with a cumulative amount of 1.03 ± 0.4 g· g·m^-2·month^-1, corresponding to 68.2 % of the annual total. Fruit production was only recorded from July to December, with the highest production in September (14.7 ± 1.8 g·m^-2·month^-1 (Figure 3). Monthly surface water temperature was positively correlated with litter production (r = 0.85, p = 0.04).

Figure 3.

Leaf Litter Production by Components and Water Temperature.

Belowground Root Biomass (BRB)

We found a mean root biomass of 7251 ± 1529 gDw·m^-2, where the highest total biomass corresponded to fine roots (3609 ± 701 gDw·m^-2). No significant differences were observed between stratum depths, and the lowest biomass was recorded in the large diameter class (872 ± 147 gDw·m^-2). The largest number of roots was found in the upper stratum (2815 ± 766 gDw·m^-2), with the highest proportion of fine roots (1593 ± 446 gDw·m^-2). Root biomass decreased with depth: upper stratum 3610 ± 609 gDw·m^-2, medium stratum 2780 ± 678 gDw·m^-2, and bottom stratum 860 ± 149 gDw·m^-2 (Table 5). The mean necromass content was 1334 ± 253 gDw·m^-2, with the highest value in the upper stratum (487 ± 114 gDw·m^-2) (Figure 4).

Table 5.

Root Biomass at Each Site by Diameter Class and Depth Stratum (gDw·m⁻²).

		La Cruz Lagoon estuary
Class	Strata	S1	S2	F	p
Fine	0–15	1593 ± 446	963 ± 218	1.6	0.58
	15–30	1174 ± 203	962 ± 223	0.6	0.48
	30–45	948 ± 158	1579 ± 152	8.2	0.95
	Sum	3715 ± 807	3504 ± 593
Medium	0–15	981 ± 260	865 ± 198	0.12	0.37
	15–30	1034 ± 225	1055 ± 205	0.15	0.7
	30–45	714 ± 245	906 ± 220	0.34	0.57
	Sum	2729 ± 730	2826 ± 623
Large	0–15	240 ± 59	267 ± 32	0.16	0.69
	15–30	253 ± 27	374 ± 69	1.6	0.23
	30–45	168 ± 60	443 ± 48	12	0.67
	Sum	661 ± 146	1084 ± 149
	TOTAL	7105 ± 1683	7414 ± 1365

(p < 0.05, N = 72) (±SE = standard error). S = Site.

Figure 4.

Necromass Content at Sites by Depth Strata.

Significant differences in root production were recorded between diameter classes (F = 30, N = 36, p = 0.012) due to the high production of large roots at 12 months (T2), 2.6 ± 0.06 g·m^-2·day^-1, compared to fine roots (0.58 ± 0.2 g·m^-2·day^-1) and medium roots (1.3 ± 0.09 g·m^-2·day^-1); regarding the biomass produced per year, significant differences were observed (F = 28, N = 36, p = 0.03), which can be attributed to the high biomass of thick roots relative to the other root diameter classes (fine roots, 2.1 ± 0.13; medium roots, 4.6 ± 0.04; large roots, 9.1 ± 0.17 Mg·ha^-1·year^-1), with a mean production of 5.2 ± 0.11 Mg·ha^-1·year^-1 (Table 6). Pneumatophore height showed mean values of 12.8 ± 0.5 cm, with no significant differences (F = 9.5, N = 214, p = 0.71), and density recorded a mean value of 496 ± 12 pneumatophores per square meter, with a biomass of 534.5 ± 41 g·m^-2, with no significant differences between monitoring units (F = 8, N = 214, p = 0.06).

Table 6.

Root Production at the Monitoring Sites by Diameter Class.

Locality	Site	Class	T1 (g·m−2·day−1)	T2 (g·m−2·day−1)	Annual biomass (Mg·ha−1·year−1)
La Cruz Estuary	1	<2	0.47 ± 0.01	0.57 ± 0.2	1.01 ± 0.047
		x2–5	0.21 ± 0.01	1.4 ± 0.1	2.5 ± 0.22
		>5	0.96 ± 0.015	2.5 ± 0.05	4.43 ± 0.09
	2	<2	0.49 ± 0.02	0.59 ± 0.03	1.04 ± 0.06
		x2–5	0.28 ± 0.03	1.19 ± 0.08	2.1 ± 0.15
		>5	0.98 ± 0.03	2.7 ± 0.05	4.74 ± 0.09

(±SE = standard error), T1= 6 months, T2 = 12 months.

Carbon Stock in Mangrove Biomass

Total biomass carbon averaged 64.77 ± 5.3 MgC_org·ha^-1. The carbon stored in the aboveground components recorded mean values of 29.8 ± 3.4 MgC_org·ha^-1, while the belowground components yielded 35.1 ± 88 MgC_org·ha^-1. The root:shoot ratio was slightly greater than 1, meaning that the amount of belowground carbon in mangrove biomass was higher than the aboveground level (Table 7).

Table 7.

Carbon Stock by Mangrove Component (MgC_org·ha⁻¹).

	AGC			BGC
Site	Litter	Live trees	Pneumatophores	Roots	Necromass	Root/Shoot	Total
1	1.33 ± 1.16	27.64 ± 2.41	2.45 ± 0.23	27.71 ± 0.66	6.3 ± 1.1	1.08 ± 0.46	65.43 ± 5.57
2	1.06 ± 1.11	25.39 ± 1.86	1.72 ± 0.08	28.91 ± 0.55	7.05 ± 1.4	1.28 ± 0.64	64.12 ± 5

± SE = standard error, aboveground carbon (AGC), and belowground carbon (BGC). BGC includes live roots and necromass; AGC includes carbon in litter, live trees, and pneumatophores.

Carbon in Soil

The organic carbon store in soil at a depth of 1 m was 142.4 ± 37.1 MgC_org·ha^-1 on average, with a bulk density of 0.65 g cm^-3 and a mean carbon percentage of 2.9 ± 1.8 (Table 8).

Table 8.

Organic Carbon Store in Soil.

	C stock MgCorg ha−1	Bulk density g cm−3	Corg%
Site 1	138.23 ± 26.31	0.60 ± 0.16	3.26 ± 2.08
Site 2	146.60 ± 47.89	0.71 ± 0.33	2.59 ± 1.69

±SE = standard error.

Discussion

In coastal regions with dry climate and precipitation deficit, freshwater runoff is crucial for mangrove establishment and development (Smith, 1992; Twilley et al., 1986). Thus, precipitation plays a central role in the arid and semi-arid areas of Mexico, and a minimal change in rainfall dynamics can influence productivity in these areas (Mitsch & Gosselink, 1993). In the La Cruz Lagoon, the annual cumulative precipitation is low (130.5 mm); however, it is similar to the precipitation recorded in estuarine areas surrounding the Gulf of California, as El Soldado, Tóbari, and Moroncarit, where annual precipitation was approximately 324.3 mm in 2020, most of the rainfall occurred from June to October (Torres et al., 2021).

In the present study, high levels of salinity and low contents of organic matter in the soil were identified. Mangrove forests located in arid zones face high salinity and nutrient scarcity, growing at their physiological limits (Torres, Frausto-Illescas, et al., 2023). High soil salinity creates stressful conditions for mangroves and, consequently, leads to low structural development and lower primary productivity (Twilley et al., 1986). The results confirm the analysis carried out in a review article on mangroves in arid regions, which showed that they have high densities, limited height, and are dominated mainly by Avicennia spp. (Adame et al., 2021).

In La Cruz Lagoon, the mangrove species Avicennia germinans and Rhizophora mangle are present, with A. germinans being the dominant mangrove species. Our measurements showed a monospecific forest of A. germinans with structural attributes characteristic of the dwarf-scrub mangrove type found in arid zones of the Gulf of California (Lugo & Snedaker, 1974), similar to those reported by Bautista-Olivas et al. (2018) in Bahía del Tóbari and Torres, Sanchez-Mejia, et al. (2023) in the Lobos-Guásimas lagoon system. In the La Cruz Estuary, the low structural development can be attributed to the high surface and interstitial salinity that inhibits mangrove growth, as identified by Adame et al. (2021) and Torres, Sanchez-Mejia, et al. (2023). In addition, Agraz-Hernández et al. (2011) identified A. germinans as a species tolerant to hyperhaline interstitial water, allowing it to reach high densities at highly saline sites.

Several studies have identified high litter production in sites near tropical areas (Morrisey et al., 2010). However, there have been few studies on litter productivity in arid mangroves (Sánchez-Andrés et al., 2010; Torres et al., 2022, 2023b) that transition from tropical to subtropical latitudes (López-Medellín & Ezcurra, 2012) where evaporation (∼3000 mm·year^-1) exceeds precipitation (∼300 mm·year^-1), and a microtidal regime predominates (Torres et al., 2022). Monospecific Avicennia germinans sites studied in the Gulf of California by Arreola-Lizárraga et al. (2004) identified low litter productivity (1.75 Mg·ha^-1·year^-1), similar to the level estimated in the present study. However, higher values were reported at sites with three mangrove species (A. germinans, Rhizophora mangle, and Laguncularia racemosa), as identified by Torres, Sanchez-Mejia, et al. (2023), with 4.9 Mg·ha^-1·year^-1 in the Lobos-Guásimas lagoon system. Félix-Pico et al. (2006) estimated 8.05 Mg·ha^-1·year^-1 in El Conchalito, and Torres et al. (2022) recorded 4.9 Mg·ha^-1·year^-1 in Moroncarit, 3.5 Mg·ha^-1·year^-1 in Tóbari, and 3.2 Mg·ha^-1·year^-1 in El Soldado.

Low structural development leads to low litter-based productivity (Lovelock & Duarte, 2019). Litter productivity depends on the structure of the tree (i.e., height) (Kathiresan & Bingham, 2001). Woodroffe (1982) characterized the relationship between litter productivity and tree height, observing that the higher the tree, the more leaf-litter it produces. In addition, A. germinans showed the lowest productivity compared to R. mangle and L. racemosa (Bouillon et al., 2008; Torres et al., 2017), which can be attributed to leaf morphology. In dwarf mangroves, litter contribution to soil carbon stocks is important but the belowground root turnover is especially important.

Plants in nutrient-poor soils tend to allocate more biomass to roots, maximizing the efficiency to capture the most limiting resource and increasing the proportion of belowground roots (Gleeson & Tilman, 1992). The low organic matter content in La Cruz Lagoon (8.1 % on average) promotes high root production that results in high belowground biomass, as identified by Torres, Frausto-Illescas, et al. (2023) in the El Vizcaíno biosphere reserve, with a root-biomass value of 8.65 Mg·ha^-1 in El Dátil Lagoon and 6.05 Mg·ha^-1 in Laguna San Ignacio. Torres, Sanchez-Mejia, et al. (2023) recorded an average of 52.12 ± 9.2 Mg·ha^-1 in the Lobos-Algodones-Guásimas lagoon system in the Gulf of California. Torres et al. (2021) studied and documented root biomass in El Soldado (5.12 Mg ha^-1), El Tóbari (5.51 Mg·ha^-1) and Moroncarit (5.79 Mg·ha^-1). However, a study in the temperate zone of the Gulf of Mexico (Torres et al., 2019) recorded a higher soil organic matter content of 16.2 ± 1.8 % with a lower belowground root biomass of 1.91 Mg·ha^-1.

The belowground biomass of mangroves may have been affected by forest age (McKee, 2001), plant characteristics (Ezcurra et al., 2016; McKee et al., 2007), environmental conditions (Otero et al., 2009; Sherman et al., 1998) and measurement methods (Muhammad-Nor et al., 2019). In mangroves, the contribution of roots of different size classes to total biomass is variable; it has also been found that root biomass decreases with soil depth (Adame et al., 2017). In La Cruz Lagoon, fine roots showed the greatest contribution to root biomass, with the highest biomass in the upper 15 centimeters; similarly, total root biomass decreased with depth. As reported in Florida by Castañeda-Moya et al. (2011) and Kenya by Tamooh et al. (2008), higher necromass contents have also been observed in the upper depth stratum (0–20 cm) while it decreases with depth. High belowground root biomass may show a greater contribution to soil organic carbon than leaf litter production, due to its faster production rate. The present study recorded a BGB:AGB ratio greater than one, meaning that more than half of the biomass is allocated to the underground stratum. As pointed out by Castañeda-Moya et al. (2011) and Virgulino-Júnior et al. (2020), in dwarf-scrub mangroves, vegetation height and belowground production are negatively correlated.

Several studies have reported higher root productivity and biomass related to high salinity values (Adame et al., 2014; Sherman et al., 2003), and these results have been interpreted as a mechanism to tolerate stress associated with highly saline conditions (Chapin, 1991). This condition appears to vary among mangrove species and according to the environmental conditions (Krauss et al., 2014). However, our estimates of BGB production indicate a pattern that contrasts sharply with the one recorded by Saintilan (1997), who found an increase in the contribution of BGB with increasing salinity. High variability in the values reported in the underground biomass (roots) can be attributed to global and local factors (Clough, 1992) and non-uniformity in the methodologies may also be reflected in these data (Giraldo, 2005), such as harvesting plots (Golley et al., 1962), soil cores (Briggs, 1977), trench (Tabuchi et al., 1983), stratified coring (Saintilan, 1997), and allometric equations (Matsui, 1998). It is recommended to use a combination of methods to reduce uncertainty, increase depth and number of samples for the soil cores method.

Carbon storage in mangroves is a function of the amount of biomass, which varies according to tree age and growth efficiency (Banerjee et al., 2020). Most of the carbon in mangrove ecosystems is stored underground as peat (Donato et al., 2011), which, unlike shorter-lived aboveground biomass, often remains undecomposed for millennia (Ezcurra et al., 2016; McKee et al., 2007). Herrera-Silveira et al. (2020) mention that the North Pacific recorded the lowest aboveground organic carbon stock (58.9 ± 12 MgC_org·ha^-1), similar to the values recorded in La Cruz Lagoon, with a carbon stock related to aboveground and belowground biomass of 64.8 ± 5.3 MgC_org·ha^-1, which accounts for 142.41 ± 37.1 MgC_org·ha^-1 of the carbon stored in soil, as reported by Alongi (2020), who mentioned that aboveground and underground C biomass accounted for 14.8 % and 8.7 % of the ecosystem total C stocks. Herrera-Silveira et al. (2020) mentioned that the mean belowground C_org consisted of approximately 77 % of the total C_org stock for Mexico.

Mangroves have the highest C reserves (386 Mg·ha^-1) compared to other coastal ecosystems such as salt marshes (255 Mg·ha^-1) or seagrasses (108 Mg·ha^-1) (Howard et al., 2014). Managing coastal ecosystems for carbon sequestration services in arid environments requires identifying the factors that explain their relatively small soil carbon stocks (Schile et al., 2017). The La Cruz Lagoon shows aboveground and belowground carbon stocks of 207.21 ± 42.4 Mg·ha^-1, which can be considered low related to the low structural development and, consequently, a low primary productivity based on leaf litter, being belowground roots the component that represented the greatest contribution to belowground C_org. These data indicate that mangrove C_org levels increase in soils as roots grow, die, and accumulate, suggesting that mangrove C is best preserved if mature mangrove forests are maintained undisturbed (Alongi, 2020). Herrera-Silveira et al. (2020), in their review of carbon stocks and stores in Mexico, identified that the mean aboveground tree biomass was 113.6 ± 5.2 MgC_org·ha^-1, while the mean belowground C_org (soils and roots) was 385.2 ± 22 MgC_org·ha^-1, for a combined total of 498.8 MgC_org·ha^-1.

This study showed the blue-carbon stock related to the biomass and soil stores in the mangrove ecosystem in an arid ecosystem of the Gulf of California. Results recorded the La Cruz Lagoon showed a low structural development with a litter productivity of 2.21 Mg·ha·year^-1, with aboveground carbon biomass of 29.8 ± 3.4 MgC_org·ha^-1 and a belowground biomass value of 35.1 ± 88 MgC_org·ha^-1, with a root:shoot ratio slightly greater than 1. These results suggest that belowground carbon related to mangrove biomass is higher than aboveground biomass. The estimated total carbon was 207.21 ± 42.4 MgC_org·ha^-1. The mangrove ecosystem in the La Cruz Lagoon has high belowground biomass values that represent a greater belowground carbon storage, which helps justifying promoting conservation and restoration strategies to improve or recover the ecosystem services it provides. It is recommended to evaluate other components that store carbon, such as dead wood, mulch, and seedlings, among others, which were not considered in the present study. Furthermore, the methods for studying dwarf-scrub mangroves should be standardized, especially with respect to their structural attributes and litter production.

Implications for Conservation

Recently, the role of mangrove forests in carbon storage has raised interest as they store four times more carbon than any other tropical forest, including rainforests (Donato et al., 2011). The information provided in this study reveals the blue carbon storage capacity of the mangrove ecosystem both in structural biomass and in soil. Managing coastal ecosystems for carbon sequestration services in arid environments requires characterizing the diverse components where carbon is stored (Schile et al., 2017).

The implications for conservation of our findings on mangrove ecosystems in tropical and/or subtropical regions lies in their importance in maintaining a high capacity to capture atmospheric CO₂, to serve as a carbon sink and storage facility, thus providing a nature-based ecosystem service. This information also serves as baseline knowledge to justify the restoration of areas degraded by anthropogenic activities.