Allometric models to estimate above-ground biomass and carbon stocks in Rhizophora apiculata tropical managed mangrove forests (Southern Viet Nam)

Forest Ecology and Management 434 (2019) 131–141

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Allometric models to estimate above-ground biomass and carbon stocks in Rhizophora apiculata tropical managed mangrove forests (Southern Viet Nam)

T

⁎

Truong Van Vinha,b,d, , Cyril Marchandb,d, Tran Vu Khanh Linha, Duong Dang Vinhc, Michel Allenbachd a

Department of Forest Resources Management, Faculty of Forestry, Nong Lam University HCMC, Thu Duc District, Ho Chi Minh City, Viet Nam IMPMC, Institut de Recherche pour le Développement (IRD), UPMC, CNRS, MNHN, Noumea, New Caledonia, France Ca Mau Forest Rangers Department, Ca Mau Province, Viet Nam d Université de la Nouvelle-Calédonie (UNC), PPME, EA 3325, BP R4, 98 851 Noumea, New Caledonia, France b c

A B S T R A C T

Mangrove forests can fix and store high quantities of carbon both in their soil and in their biomass, the latter peaking in the equatorial regions and decreasing with latitude. In Vietnam, more than 80% of the mangroves develop either in the Mekong Delta or in the Can Gio Estuary, which are characterized by tropical monsoon climates. Most of these mangroves were planted and are dominated by Rhizophora apiculata Blume. The main objectives of this study were to determine forest structure, above-ground biomass and carbon conversion factors for each tree component in order to obtain allometric equations and to derive carbon stocks for managed Rhizophora stands of different ages developing within this context. Thirty-six trees, having a diameter at breast height (DBH) ranging from 7.0 to 36.2 cm, from a planted mangrove forest were harvested in Ca Mau (Mekong Delta) to determine allometric equations. In addition, thirteen plots were established in both Ca Mau and Can Gio mangrove forests, to determine above-ground carbon densities. We proposed the following specific allometric equation to estimate total aboveground biomass (kg) for managed R. apiculata mangrove stands in Southern Vietnam: WTotal = 0.38363 * DBH2.2348 (R2 = 0.976, SE = 1.17, F = 1401, P < 0.001). The total above-ground biomass ranged from 135.4 to 523.6 Mg ha−1 depending on forest age and tree density. Consequently, and taking into account a carbon conversion factor of 44.09%, carbon stocks in the above-ground biomass of R. apiculata mangrove forests in Southern Vietnam ranged from 59.7 to 230.9 Mg C ha−1. The mean carbon partitioning in the tree biomass was: 77.11% for trunks, 11.87% for branches, 8.66% for prop roots, and 2.36% for leaves. However, this distribution, as well as annual height increments and biomass increase rates, also varied with forest age and tree densities. We suggested that tree density reduction through thinning activities allowed easier tree development, resulting in an increased biomass with enhanced allocation to branches and above-ground prop roots for the stability of the trees. Using the specific allometric equation and specific carbon conversion factor reduced the uncertainty in the estimation of above-ground biomass and carbon stocks.

1. Introduction Mangrove forests develop at the interface between land and ocean in tropical and subtropical zones. Their total area was estimated at 167,387 km2 in 2012 (Hamilton and Casey, 2016). Although mangrove forests occupy only 2% of the world’s coastal ocean area (Alongi and Mukhopadhyay, 2015), they account for about 5% of its net primary production, with high carbon burial rates (Alongi, 2002). Consequently, mangrove ecosystems play a key role in the global and oceans carbon cycle, acting both as a sink for atmospheric CO2 (storing carbon in above-ground and below-ground biomasses, and in the soil) and as a source of organic and inorganic carbon for adjacent ecosystems, and a source of CO2 for the atmosphere via fauna/flora respiration and also due to land use changes and forest fires (Kristensen et al., 2017;

Murdiyarso et al., 2015). Along with seagrass beds and salt marshes, mangroves have been termed ‘‘blue carbon” (Mcleod et al., 2011). Blue carbon refers to the carbon captured and stored over the short term in biomass and over longer time scales in sediments by the world’s ocean and coastal ecosystems. However, mangrove forests are being lost globally at a mean rate close to 1% per year (Alongi, 2002; Atwood et al., 2017; Donato et al., 2011; Duke et al., 2007; Hamilton and Casey, 2016; Hamilton and Friess, 2018; Rovai et al., 2018; Spalding, 2010), and in some countries this rate can be as high as 8% annually (Polidoro et al., 2010), which may strongly influence carbon dynamics along their coastlines. In Vietnam, mangrove forests covered an area of about 400,000 ha in 1943, but only 252,500 ha remained in 1983 (Hong and San, 1993) and 270,000 ha in 2015 (FAO, 2015). Most of these mangroves were

⁎ Corresponding author at: Department of Forest Resources Management, Faculty of Forestry, Nong Lam University HCMC, Thu Duc District, Ho Chi Minh City, Viet Nam. E-mail address: [email protected] (T.V. Vinh).

https://doi.org/10.1016/j.foreco.2018.12.017 Received 20 June 2018; Received in revised form 7 December 2018; Accepted 9 December 2018 0378-1127/ © 2018 Published by Elsevier B.V.

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Fig. 1. Map showing the location of the study sites. (A) Mekong delta in Vietnam, (B) Can Gio Estuary, (C) Ca Mau province, the light green is natural regeneration mangrove and dark green is replanted mangrove + shrimp farm. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

models using DBH together with the height of the trees (Suzuki and Tagawa, 1983; Tamai et al., 1986) and, recently, adding wood density and crown volume (Kauffman and Cole, 2010; Ross et al., 2001; Soares and Schaeffer-Novelli, 2005). Chave et al. (2005) and Komiyama et al. (2005) have developed common allometric equations for mangrove using wood density and DBH, they also recommended the use of sitespecific wood density for species. The choice between these methods should depend on field conditions and forest type. In addition, they are destructive and labor-intensive, especially in mangrove forests with a muddy substrate and with the tides going in and out. However, recent studies showed that aboveground biomass of large mangrove trees can be estimated from terrestrial Lidar measurements (Olagoke et al., 2016), which is a promising non-destructive method. As a consequence, and despite the importance that specific allometric equations and carbon conversion factors may have on the degree of uncertainty of carbon inventories in mangrove forests, few allometric equations have been determined for mangrove trees (see the review of Komiyama et al., 2008). Most of the recent studies on the carbon cycle in vietnamese mangrove forests have used generic carbon content and common allometric equations to estimate above-ground dry weight (DW) biomass and C storage (Dung et al., 2016; Nam et al., 2016; Tue et al., 2014). Komiyama et al. (2008) suggested that the allometric equations for mangrove species are highly species-specific but less site-specific. However, Alongi (2002) demonstrated that mangrove biomass can be highly variable depending on several edaphic factors, in relation to rainfall, tide-dominated, wave-dominated and rive-dominated. The total above-ground biomass per hectare should also varies with the stand age. In addition, using generic carbon content to convert biomass

planted in the late 70s and early 90s, after their destruction during the war. More than 80% of the total mangrove forest area in Vietnam develop in the south of the country, either in the Mekong Delta or in the Can Gio Estuary (Hawkins et al., 2010). These planted mangrove forests are dominated by Rhizophora apiculata Blume, and all woody parts are exploited for firewood, charcoal, poles, wood chips, and construction materials. Moreover, the environmental value of mangrove forest was taken into account in the national strategy on climate change and sea level rise by the Vietnamese government. Recently, Vietnam was the first country in Asia to implement a national program of payment for forest environmental services (PFES). In addition, Vietnam develops national REDD+ strategies and policies, including the reduction of mangrove deforestation and the enhancement of mangrove forest carbon stocks. Participation in REDD+ will require Vietnam to produce robust estimates of mangrove above ground-biomass (AGB). Therefore, developing specific allometric equations to have more precise values would be highly relevant. In the context of elevated CO2 concentrations in the atmosphere, the carbon cycle in mangrove forest ecosystems now receives considerable attention, both to quantify the carbon fixed and stored but also the carbon release, either through natural processes or anthropogenic perturbation of the ecosystem. A number of methods have been developed to estimate mangrove forest biomass and to evaluate carbon allocation rates. Based on strong correlations between biomass and trunk diameter at breast height (DBH), allometric equations for mangrove trees have been developed for several decades to estimate biomass and subsequent growth (Clough and Scott, 1989; Komiyama et al., 2008; Putz and Chan, 1986). Other studies have developed allometric 132

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Table 1 Stand characteristic of R. apiculata in Southern Vietnam. CM is the plots in Ca Mau, CG is the plots in Can Gio, Dq: quadratic mean diameter. Plots

Ages

Latitude

Longitude

Tree density ha−1

Mean ± SD Dq (cm)

Mean ± SD height (m)

Basal Area m2 ha−1

Mean ± SD DBH increment (cm yr−1)

Mean ± SD height increment (m yr−1)

CM7 CM4 CM3 CM5 CM1 CM8 CG7 CG5 CG4 CG6 CG3 CG1 CG2

10 14 14 20 24 39 16 25 25 25 37 37 37

8°35.33′N 8°40.16′N 8°40.29′N 8°35.84′N 8°38.97′N 8°42.02′N 10°29.21′N 10°28.75′N 10°28.81′N 10°28.66′N 10°28.80′N 10°28.70′N 10°28.97′N

104°55.69′E 105°4.33′E 105°4.44′E 104°57.85′E 105°3.90′E 105°4.30′E 106°47.65′E 106°47.33′E 106°47.35′E 106°47.33′E 106°48.03′E 106°48.16′E 106°48.16′E

11,000 8800 16,100 3800 2500 1900 9120 6180 3400 2820 1260 860 1260

7.7 ± 2.3 7.2 ± 1.9 6.4 ± 1.4 11.5 ± 3.8 10.0 ± 2.1 19.6 ± 5.8 6.0 ± 2.0 6.3 ± 1.5 9.5 ± 3.0 11.1 ± 3.1 17.6 ± 3.3 20.6 ± 3.6 18.3 ± 2.8

13.6 ± 1.3 13.3 ± 1.2 12.9 ± 1.0 15.5 ± 1.8 15.0 ± 1.2 18.5 ± 2.1 8.9 ± 2.5 12.9 ± 0.9 14.6 ± 1.5 15.4 ± 1.4 19.3 ± 1.5 19.4 ± 1.7 19.6 ± 1.6

46.5 32.8 48.9 35.6 18.9 52.7 22.8 18.3 21.9 25.1 24.9 27.8 32.5

0.73 0.49 0.44 0.55 0.41 0.48 0.35 0.25 0.36 0.43 0.47 0.55 0.49

1.4 1.0 0.9 0.8 0.6 0.5 0.6 0.5 0.6 0.6 0.5 0.5 0.5

5307

11.7

15.5

31.4

0.5

Average

± ± ± ± ± ± ± ± ± ± ± ± ±

0.14 0.14 0.10 0.19 0.09 0.15 0.13 0.06 0.12 0.13 0.09 0.10 0.08

± ± ± ± ± ± ± ± ± ± ± ± ±

0.08 0.09 0.07 0.09 0.05 0.05 0.16 0.04 0.06 0.06 0.04 0.05 0.04

0.7

2. Materials and methods

2016). Mangrove forests are planted in high density with 20,000 trees ha−1 (0.5 m × 0.5 m). After ∼5 years, the canopy leaves start to overlap and the competition for light affects tree growth inducing the first silvicultural treatment (Tri et al., 2000). The first thinning is conducted when trees reach 9 to 10 m, with trunk DBH ranging from 6 to 8 cm. The intensity of this first thinning ranges between 40 and 50%. The second thinning occurs between 14 and 15 years after planting, when the DBH is around 12–14 cm, and the intensity of the thinning varies from 25 to 35 %. The final felling is performed when the forest is between 19 and 20 years old, with a DBH around 14–16 cm. The expected tree density after the last thinning ranges from 2000 to 2500 trees ha−1.

2.1. Study area

2.3. Collection of stands characteristics

The study was conducted in Southern Vietnam, both in the Mekong Delta (9°24′N to 10°37′N) and in the Can Gio Estuary (10°22′N to 10°40′N) (Fig. 1). The Mekong Delta is among the world’s largest deltas, encompassing about 39,000 km2 with a population of ∼17 million people. Ca Mau province is located in the southernmost tip of Vietnam (Fig. 1) and is a deltaic lobe of the Mekong River. Ca Mau has the largest total area of mangrove forests in the Mekong Delta (Vo et al., 2015). The Can Gio Estuary is located downstream of Ho Chi Minh City, the biggest city in Vietnam. It covers an area of almost 70,000 ha, half of it being mangrove forests. This region is characterized by a tropical monsoon climate with a wet season lasting from May to October and a dry season lasting from November to April. Approximately 80% of the annual rainfall occurs during the rainy season. The mean annual rainfall is ∼1800 mm, while the mean daily air temperature is around 27 – 28 °C. During the dry season, fresh water flow is strongly reduced, and the coastal areas are severely affected by saline intrusion. Before the Vietnam war, most of Southern Vietnam’s mangrove forests were pristine, with up to 69 mangrove species (Hong and San, 1993), and dominated by Rhizophora, Sonneratia, and Bruguiera genera. During the war (1964–1969), most of these forests were destroyed by the spraying of defoliants, particularly in Can Gio, where ∼57% of the mangrove areas were destroyed (Ross, 1975). However, these areas have been reforested since 1978. In Can Gio, ∼20,000 ha were planted with Rhizophora apiculata, using propagules that were collected in the Ca Mau mangrove forests.

In Ca Mau, three plots (25 × 20 m) were measured in the Dat Mui Protected Mangrove Forest and three plots in the forest managed by the Ngoc Hien Forestry Company (CM1, CM3, CM4, CM5, CM7, CM8). Those stands were planted between the early 1980s and the 2000s. The oldest R. apiculata stand was 39 years old. Furthermore, seven plots were measured at the Can Gio Mangrove Board (CG1, CG2, CG3, CG4, CG5, CG6, and CG7) (Table 1). These Rhizophora stands were planted between the late 70s and the early 90s. In each plot, all trees were numbered. Stand density per hectare was obtained by multiplying the number of trees per plot with 20. Quadratic mean diameter (Dq) was calculated using the quadratic mean formula: Dq = sqrt (ΣDBHi2/n), where DBHi is the diameter at breast height of the ith tree, n is the number of tree per plot. The basal area of each tree was determined using function: BA = πDBH2/40000, where BA is basal area (m2), π is constant (3.14) and DBH is the diameter at breast height. Total basal area per hectare was obtained by multiplying the total basal area per plot with 20. The height of each tree was measured using telemeter Haglof Vertex IV, with an error of approximately 1%; DBH measured using a tree calipier (Haglof Matax Blue Calipiers)”. Mean DBH and height increment was determined by dividing the mean DBH and mean height of each stand by its age.

into carbon stocks may lead to bias in the estimation of vegetation carbon stocks (Rodrigues et al., 2015). The objectives of this study were: (i) to determine biomass partitioning between the different compartments of the above-ground biomass, i.e., the branch, trunk, prop roots, and leaves, (ii) to develop allometric equations to estimate the above-ground biomass of Rhizophora apiculata Blume of planted mangrove forests in Southern Vietnam, and (iii) to determine the carbon conversion factor to determine the above-ground carbon stock. These results are discussed as a function of stand age, tree density, and silvicultural practices.

2.4. Determination of biomass partitioning, allometric equations and carbon stocks in the above-ground biomass 2.4.1. Biomass partitioning Thirty-six R. apiculata trees, with DBH at 1.3 m or just above the highest prop root ranging from 7.0 cm to 36.2 cm, and heights ranging from 13.0 to 23.5 m, were felled by sawing machine in Ca Mau province. For each felled tree, the prop root, trunk and branch were cut separately. The trunk and branch were cut in 1 m length parts using sawing machine. The fresh weight of prop roots, trunks, branches, and

2.2. Silvicultural practices In Southern Vietnam, plantation objectives include timber production, coastline protection, channel stabilization, fisheries, and wildlife enhancement. The silvicultural treatments applied in Ca Mau and Can Gio are similar, leading to similar stand characteristics (Nam et al., 133

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leaves (combined with stipules, fruits, and the few flowers present) were sorted and weighed separately in the field using a balance Nhon Hoa, CĐH-100 ( ± 0.1 kg). Subsamples of every component weighed in the field were dried in an oven at 105 °C until a constant weight was reached to obtain the dry biomass and dry-wet biomass ratio. For each component, triplicate subsamples were collected to determine their carbon content. These subsamples were stored in a frozen box in the field, taken back to the laboratory, and then freeze dried at −52 °C until reaching a constant weight.

natural logarithm transformation (ln) was used for all predictors (above-ground biomass of branches, trunks, prop roots, leaves, and total biomass), and the significance of each predictor in the total model was tested using the stepwise procedure at the 0.05 level of confidence. In addition, the one-way analysis of variance (One-way ANOVA) was used to find differences between biomass allocation in compartments. 3. Results and discussions 3.1. Structural characteristics of planted Rhizophora stands in Southern Vietnam

2.4.2. Allometric equation In the present study, the trunk DBH (at 1.3 m or just above the highest prop root) was used as a predictive variable. A natural logarithm transformation model gave the best description of the relationship between above-ground biomass and DBH based on the statistical characteristics, such as coefficient of determination (R2), small standard errors (SE), and F-ratio values higher than those in the F-table at a 95% confidence level. The linear transformation Ln (Biomass) = a + b Ln (DBH) was used to describe the relationship between trunk biomass, branch biomass, prop root biomass, leaf biomass and total aboveground biomass with DBH, where DBH is an independent variable and biomass is a dependent variable. Raw data are given in supplementary material 1.

In both Ca Mau and Can Gio mangrove forests, tree density varied with forest age, ranging from 1900 trees ha−1 for a 39 year old forest to 16,100 trees ha−1 for a 14 year old forest in Ca Mau and from 886 trees ha−1 for a 37 year old forest to 9120 trees ha−1 for a 16 year old forest in Can Gio (Table 1). Tree densities declined with forest age, notably because of the silvicultural treatments, especially the thinning that was applied at both sites as described earlier (Nam et al., 2016; Tri et al., 2000) and in the method section. However, tree density also declined in natural forests due to physiological tolerances and competitive interactions (Alongi, 2002). In French Guiana Fromard et al. (1998) showed that the tree density of a Laguncularia and Avicennia species mixed forest declined from 11,778 trees ha−1 for a young stand to 883 trees ha−1 for a mature stand and to 222 trees ha−1 for a senescent stand. Additionally, Walcker et al. (2018) showed that species composition were influenced by the age of the forest, Laguncularia racemosa could dominate in young forest with approximately 25,000 trees ha−1, and Rhizophora spp. density appeared to increase compared to Avicennia germinans and Laguncularia racemosa in older stands. Similarly, the quadratic mean diameter (Dq) and mean height increment varied with the age of the stands and with tree density (Fig. 2 b, c), but they were similar between Ca Mau and Can Gio mangrove forests for a same age and a same tree density (Table 1). For instance, in Ca Mau, the average height and the Dq of CM1 plot were 15.0 ± 1.2 m and 10.0 ± 2.1 cm, respectively, while for CG6 plot in Can Gio, they were 15.4 ± 1.4 m and 11.1 ± 3.1 cm, respectively. Goessens et al. (2014) found that the mean height of R. apiculata planted in Matang (Malaysia) were 12.8, 13.3 and 14.8 m at 15, 20 and 30 years old, respectively. These heights are relatively elevated for mangrove trees and are related to the specific climate of Southern Vietnam. According to Novitzky (2010), the height of mangrove trees increases as temperature and precipitation increase and as latitude decreases. Cintron and Novelli (1984) also found that the height of mangrove trees is increased at lower latitudes in the neotropics. However, Cintron et al. (1978) concluded that height of mangrove trees varied with the soil salinity, decreasing when the latter was too high, like along the semi-arid coastline of New Caledonia (Leopold et al., 2016). The annual height increments and Dq increments were also not significantly different between the two sites (P > 0.05). In Ca Mau, both height and Dq increments were elevated in the young forests and decreased with forest age (Table 1). The annual height increment ranged from 1.4 m yr−1 for a 10 year old forest having a density of 11,000 trees ha−1 to 0.5 m yr−1 for a 39 years old forest having a density of 1900 trees ha−1. For the Can Gio Estuary, the annual height increment was stable around 0.5 to 0.6 m yr−1 for our data set. Dq increments ranged from 0.41 to 0.73 in Ca Mau and from 0.25 to 0.55 in Can Gio (Table 1). There was a negative correlation between annual height increment and age (R2 = 0.77) (Fig. 2f) and a slight positive correlation between annual height increment and tree density (R2 = 0.48) (Fig. 2c). In these two mangrove forests planted with a high density, competition for light is elevated between neighboring plants, and crown expansion is restricted by the crowns of the neighbors. As a result, the young forests with high tree density present with higher values for height increments as they compete for light.

2.4.3. Carbon conversion factors The total carbon contents of the powdered samples of the different Rhizophora apiculata components (trunk, branch, leaf, and prop root) were determined using a Total Organic Carbon Analyzer coupled to a SSM-5000A Solid Sample Module (TOC-LCPH-SSM500A, Shimadzu Corporation, Japan) at the mangrove lab, IRD – Noumea, New Caledonia. The analytical precision was checked using a glucose standard (Sigma Aldrich), and the error was less than 1%. The carbon conversion factor for the above-ground biomass of an entire R. apiculata tree was calculated as follows:

AGB [C] % [(Trunk [C ] × Trunk %) + (Branch [C ] × Branch %) + (Prop root [C ] × Prop root %) + (Leaf [C ] × Leaf %)] = 100

(1)

where AGB [C] = carbon conversion factor for the above-ground biomass of a tree; Trunk [C] = carbon content of the trunk; Trunk % = biomass allocation to the trunk; Branch [C] = carbon content of the branches; Branch % = biomass allocation to the branches; Prop root [C] = carbon content of the prop root; Prop root % = biomass allocation to the prop root; Leaf [C] = carbon content of the leaves; and Leaf % = biomass allocation to the leaves. 2.4.4. Carbon stocks In addition, we were interested in the total above-ground biomass per tree (kg) and the carbon stocks per hectare (Mg C ha−1) of Ca Mau (CM) and Can Gio (CG) mangrove forests. The tree above-ground biomass was estimated from tree DBH by using the species-specific allometric equation determined in this study. We determined the carbon stocks per tree by multiplying the tree above-ground biomass (kg) with the carbon conversion factor for R. apiculata determined in this study. The carbon stock per area (Mg C ha−1) was then calculated using tree density. 2.5. Statistical analyses We calculated the statistical measures, including weighted mean, arithmetic mean, and standard deviation (SD) of carbon content, carbon stock, and above-ground biomass, i.e., branch, trunk, prop roots, and leaves. Basal area, biomass accumulation, and carbon stock were used to test significant differences (P < 0.05) across sites (CM and CG). The 134

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Fig. 2. Relationship between: Dq (quadratic mean diameter) and tree density per ha (a), tree density per ha and age (b), annual height increment and tree density per ha (c), annual height increment and age (d) accumulation AGB and tree density per ha (e), above-ground biomass and age (f) of R. apiculata stands in Southern Vietnam. Orange dots are site CM (Ca Mau) and blue dots are site CG (Can Gio). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

components (trunks, branches, prop roots and leaves) were significantly different (p < 0.001) (Table 2). Trunks represented the largest contribution to the total dry weight (DW) above-ground biomass with 76.25 ± 5.13% (mean ± SD), while the branches represented

3.2. Evolution of biomass partitioning with forest development Considering the entire data set of the 36 trees felled in Ca Mau mangrove forest, the biomass of the different Rhizophora tree

Table 2 Biomass allocation in the different tree compartments, carbon content, and carbon stock allocation of R. apiculata in mangrove forest of Southern Vietnam. Compartments

DBH range (cm)

Biomass allocation (%) (Mean ± SD)

Carbon content (%)

AGB generic carbon content (%)

Carbon stock allocation (Mean % ± SD)

Trunk parts Branch parts Prop root parts Leaf parts

7.0–36.2

76.25 ± 5.13 12.58 ± 3.35 8.71 ± 2.52 2.46 ± 0.45

44.60 41.59 43.77 42.30

44.09 ± 1.37

77.11 ± 5.00 11.87 ± 3.19 8.66 ± 2.52 2.36 ± 0.43

p-value

< 0.001

< 0.001

135

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(DBH = 1.3 cm) but only 1.4% for trees having a DBH of 32.0 cm, while it constituted an insignificant share of the total above-ground biomass estimates (Olagoke et al., 2016). Biomass allocated to foliage may depend on resource availability, hydraulic capacity, and growing space available to an individual tree (Copenhaver and Tinker, 2014). Low foliage biomass may have an influence on the photosynthetic activity of the tree and, therefore, on its primary productivity. In the present study, in contrast to trunk and leaves, the proportion of biomass in the branches and in the prop roots increased with the trunk diameter, from 6.65 to 20.29%, and from 4.54 to 11.89% (Fig. 3), respectively. Biomass distribution in the different compartments of the trees as well as the evolution of this distribution with tree development may be explained by tree requirements developing on specific substrates. An increased biomass allocation to above-ground prop roots with tree development is a common feature of Rhizophora trees as they increase their stability as their biomass increases (Clough, 1992). Prop roots arise from the trunk and from the lower branches to provide support for the tree on a muddy substrate; as the trunk and the canopy crown develop, the prop root biomass increases. In addition to increasing stability, prop roots also allow the exchange between the tree and the atmosphere through lenticels and aerenchyma on anoxic soil (Mendez-Alonzo et al., 2015). Regarding the branches, the young dense stands may limit the lateral growth of mangrove trees, and this may explain the reduced partitioning of biomass to branches. We suggest that the tree density reduction through thinning activities allowed an easier development of the trees as the crowns of individual trees were less restricted by those of their neighbors, resulting in biomass development and an increased biomass allocation to the branches (Fig. 3c).

12.58 ± 3.35%, the prop roots 8.71 ± 2.52%, and the leaves 2.46 ± 0.45% (Table 2). These results were similar to the biomass partitioning measured for R. apiculata and R. stylosa in Australia (Clough and Scott, 1989), with the above-ground biomass of trunks representing 65.3 ± 5.57%, the branches representing 17.6 ± 6.24%, and 13.3 ± 3.47 and 3.70 ± 1.82% attributed to the prop roots and the leaves, respectively. In Malaysian mangroves, Ong et al. (2004) reported that trunk biomass of R. apiculata represented between 60 and 70% of the total aboveground biomass and the branches between 10 and 15%. However, some authors reported different results because biomass partitioning depends on mangrove types (managed or not) and on edaphic characteristics. For example, prop roots biomass can be much more developed, as observed in a Rhizophora stand in Malaysia, where they represented 39% of the total above-ground biomass (Christensen, 1978), while in a mature Rhizophora stand in Southern Thailand, their biomass represented almost half of the total above-ground biomass (Komiyama et al., 1987). In the Guianese mangrove forests, Fromard et al. (1998) showed that the prop roots of Rhizophora spp. constituted up to 30% of the total above-ground biomass, but these authors also demonstrated that biomass partitioning varied with the stage of mangrove development. Clough (1992) reported that, for Rhizophora species, biomass partitioning between trunks, leaves, branches, and above-ground prop roots varied with DBH (Clough, 1992). In the present study, the evolution of the proportion of biomass in trunks and leaves presented the same trend, decreasing with DBH (Fig. 3a and b). When trunk diameter increased from 7.0 to 36.2 cm, the proportion of the trunk in the total above-ground biomass decreased from 84.86 to 67.05%, while the proportion attributed to the leaves decreased from 3.33% to 1.75%. Clough and Scott (1989) observed the same trends; and in their review, Komiyama et al. (2008) highlighted that, in mature mangrove forests, the leaf biomass is usually quite low. In French Guiana, Fromard et al. (1998) reported that leaf biomass of the Rhizophora spp. represented 9.7% of the total above-ground biomass for young individuals

3.3. Biomass allometric equation Thirty-six trees, having a DBH ranging from 7.0 to 36.2 cm, were cut to determine the total above-ground biomass and DW biomass allocations of R. apiculata stands in Southern Vietnam. The allometric

Fig. 3. Partitioning of above-ground biomass in relation to trunk diameter for R. apiculata in Southern Vietnam, percentage of (a) trunk mass, (b) leaf mass, (c) branch mass and (d) prop root mass of total above-ground biomass. 136

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Fig. 4. Allometric relationships between diameter at breast height (DBH) and dry weight biomass components (W) of R. apiculata according to the equation W = aDBHb. Lines are fitted models and symbols are actual data of total above ground biomass (a), trunk biomass (b), leaf biomass (c), branch biomass (d) and prop root biomass (e).

that they provide a reliable means to estimate the total above-ground biomass and biomass of the different components from DBH for Rhizophora in Southern Vietnam. These allometric equations were compared to those obtained in Malaysia (Ong et al., 2004; Putz and Chan, 1986), in Indonesia (Komiyama et al., 1988), in Australia (Clough and Scott, 1989), and to the common allometric equation proposed by Komiyama et al. (2005) (Fig. 5). For trees having a DBH < 15 cm, relationships between DBH and above-ground biomass were similar for all equations. However, for trees having a higher DBH, the relationship differed between studies. For the same DBH, the models obtained in Australia (Clough and Scott, 1989), in Malaysia (Ong et al., 2004) and in Indonesia (Komiyama et al., 1988) gave higher average above-ground biomass values than average values in this study. The biomass of mangrove trees depends on the structural characteristics and stages of forest development (pioneer, young, mature, and senescent) (Fromard et al., 1998). The mangrove trees carbon sink capacity varies with ecosystem age (Walcker et al., 2018) and also on environmental parameters and climatic factors, such

relationships between total above-ground biomass or biomass of the different compartments and DBH are shown in Fig. 4. There was a significant relationship between total above-ground DW biomass, biomass of the different compartments, and DBH (P < 0.05). The equations for fitted models are:

Ln (WTotal) = −0.95807 + 2.2348 ∗ Ln (DBH) or WTotal = 0.38363 ∗ DBH2.2348 R2 = 0.976, SE = 1.17, F = 1401, P < 0.001 (2)

Ln (WTrunk) = −0.954817 + 2.1396 ∗ Ln (DBH) or WTrunk = 0.38488 ∗ DBH2.1396 R2 = 0.976, SE = 1.17, F = 1370, P < 0.001 (3)

Ln(WBranch) = −4, 09305 + 2.5856 ∗ Ln (DBH) or WBranch = 0.01669 ∗ DBH2.5856 R2 = 0.941, SE = 1.34, F = 1544, P < 0.001 (4)

Ln (WProp WProp

root

root)

= −4, 86791 + 2.7227 ∗ Ln (DBH) or

= 0.00769 ∗ DBH2.7227 R2 = 0.935, SE = 1.38, F = 490,

P < 0.001 (5)

Ln (WLeaf ) = −3, 59151 + 1.8732 ∗ Ln (DBH) or WLeaf = 0.02756 ∗ DBH1.8732 R2 = 0.942, SE = 1.24, F = 547, P < 0.001

(6)

where W is the biomass (kg) and DBH is the diameter at breast height (at 1.3 m or just above the highest prop root). All of these allometric equations have high coefficients of determination (R2), small standard errors (SE), and F-ratio values higher than those in the F-table at 95% confidence level. Consequently, we consider

Fig. 5. Comparative regression of total above ground biomass for R. apiculata obtained from different studies. 137

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269.8 ± 106.7 Mg ha−1. The differences in the total above-ground biomass between stands were related to different forest ages and tree densities as observed in South East Asia (Clough, 1992). In Malaysia, the total above-ground biomass of up to 460 t ha−1 was reported for a Rhizophora dominated stand that was greater than 80 years old (Putz and Chan, 1986), 372 t ha−1 for a 30 years old (Goessens et al., 2014), while for a 27 years old forest, it was only 211.8 t ha−1 (Ong et al., 1982). The total above-ground biomass in Indonesian mangrove stands ranged from 40.7 t ha−1 to 356 t ha−1 (Komiyama et al., 1988; Kusmana and Sabiham, 1992), while in Thailand, it ranged from 62.2 to 298.5 t ha−1 (Komiyama et al., 1987; Kristensen et al., 1995). The mean above-ground biomass of mangrove is highest in Southeast Asia and Pacific Islands with 230.9 and 233.3 t ha−1, respectively, and lowest value in East Asia, while the mean global is 184.8 t ha−1 (Hutchison et al., 2014). Walcker et al. (2018) also showed that above-ground biomass of stands > 66 years old in French Guiana reached up to 874.77 t ha−1. In South East Asia, where the products of thinning activities are useful for firewood, charcoal, poles, wood chips, and construction materials (Saenger, 2002), mangrove forests are planted with high density (from 10,000 to 20,000 trees ha−1) and then silvicultural treatment are applied. For example, in the Matang forest (Malaysia), the first thinning occurs 15 years after planting and the second thinning after 20 years for Rhizophora stands (Saenger, 2002). The thinning is expected to improve tree diameter because of less competition and more space for its development; however, on the contrary, the thinning obviously results in the loss of above-ground biomass through mangrove tree removal. In an undisturbed mangrove forest in northeastern Australia, the total above-ground biomass of a Rhizophora forest has reached a value of 700 t ha−1 (Clough, 1992) (Fig. 5 and Table 4), which is much higher than for planted and managed mangrove forest in South East Asia. The increase rate of the above-ground biomass varied with tree densities and ranged from 5.4 to 37.2 Mg ha−1 yr−1 (Table 3), with a mean value of 13.2 ± 9.3 Mg ha−1 yr−1. These results are similar to those obtained for Rhizophora stands in Matang (Malaysia), where the mean annual increment in biomass was 16.1 Mg ha−1 yr−1 (Putz and Chan, 1986). The increase rate of above-ground biomass is influenced by a combination of global and local factors, such as latitude, climatic conditions, nutrient inputs. (Alongi, 2002; Saenger and Snedaker, 1993; Twilley et al., 1992). For example, the accumulation of above-ground biomass in mangrove forests growing in areas of high rainfall on the

Table 3 Biomass and accumulation of above-ground dry weight (DW), and aboveground carbon stock of R. apiculata in Southern Vietnam. CM is the plots in Ca Mau, CG is the plots in Can Gio, AGB is above-ground biomass. Plots

Ages

DW biomass (Mg ha−1)

DW biomass accumulation rate (Mg ha−1 yr−1)

Carbon stock in AGB density (Mg C ha−1)

CM1 CM3 CM4 CM5 CM7 CM8 CG1 CG2 CG3 CG4 CG5 CG6 CG7

24 14 14 20 10 39 37 37 37 25 25 25 16

146.6 358.4 250.5 313.3 372.3 523.6 260.9 293.7 267.1 188.0 135.4 217.6 179.4

6.1 25.6 17.9 15.7 37.2 13.4 7.1 7.9 7.2 7.5 5.4 8.7 11.2

64.6 158.0 110.4 138.2 164.2 230.9 115.0 129.5 117.8 82.9 59.7 96.0 79.1

269.8 0.49

13.2 0.02

118.9 0.07

Average p-value

as rainfall, radiation, day length, and air temperature, as well as seasonal variability (Clough, 1992). Additionally, wood density may explain the difference between above-ground biomass. Komiyama et al. (2005) suggested that wood density differs significantly between mangrove species, but less for individuals within a species. However, wood density can differ between the different tree compartments, with the density of branches and props roots being lower than that of the trunk. We, therefore, suggest that the specific biomass partitioning of R. apiculata in Southern Vietnam, which is partly the consequence of the silvicultural treatments, results from trees with high DBH being characterized as having lower total above-ground biomass compared to those in other studies. 3.4. Above-ground biomass, carbon conversion factors, and carbon stocks There was no significant difference in the total above-ground biomass between planted Rhizophora stands in Ca Mau and in Can Gio (P > 0.05). In these mangrove forests, the total above-ground biomass ranged from 135.4 to 523.6 Mg ha−1 (Table 3), with a mean value of

Table 4 Coefficients for allometric relationships between diameter at breast height (DBH, cm) and above-ground dry weight biomass (kg) for various parts of R. apiculata, with equation y = a*xb where the diameter at breast height (x) is independent variable and the dependent variable (y) is biomass, derived from different studies. Variable

a

b

R2

SE

Range DBH (cm)

Countries/latitudes

Reference

Trunk Branch Prop root Leaf Total Trunk Branch Prop root Leaf Total Trunk Branch Prop root Leaf Total Prop root Total Total

0.3849 0.0170 0.0077 0.0276 0.3836 0.0886 0.0127 0.0068 0.0139 0.1049 0.0089 – 0.0011 0.0233 0.0147 0.0006 0.0111 0.1709

2.1396 2.5856 2.7227 1.8732 2.2348 2.5621 2.5621 3.1353 2.1072 2.6848 2.4770 – 2.5460 1.3780 2.4200 2.7680 2.5080 2.5160

0.976 0.941 0.935 0.942 0.976 0.991 0.912 0.968 0.857 0.995 0.980 – 0.840 0.730 0.980 0.960 0.990 0.980

1.17 1.34 1.38 1.24 1.17 1.14 1.57 1.32 1.59 1.11 1.03 – 1.15 1.23 1.02

7–36.2 n = 36

Vietnam 9°24′N to 10°37′N

This study 2018

3–23 n = 21

Australia 16°16′S–18°16′S

Clough and Scott (1989)*

5–28 n = 57

Malaysia 4°45′N

Ong et al. (2004)

5–44.5 n = 22 5–35

Total

0.2510

2.4600

0.980

–

n = 84

Thailand 9°58′N Malaysia 4°48′N 1°10′N–12°12′N

Komiyama et al. (1987)**

– –

Putz and Chan (1986) Komiyama et al. (2005)***

* Mixture forest of R. apiculata and R. stylosa; **Girth at breast height; ***Common allometric equation for estimating the above-ground weight biomass; n is the number of trees sampled within the indicated DBH range; R2 is coefficient of determination; SE is the standard error of biomass estimate.

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Daintree River (Australia) can be extremely high at 45.5 t ha−1 yr−1 (Clough, 1992). In addition, the accumulation of above-ground biomass decreases significantly with forest age, from 37.2 to 13.4 Mg ha−1 yr−1 and 11.2 to 7.1 Mg ha−1 yr−1 for forests that are 10–39 years old and 17–37 years old in Ca Mau and Can Gio, respectively. Alongi (2012) also observed that above-ground biomass increase rates vary with forest age in Malaysia, with values of 3.5, 9.7, and 15.8 Mg ha−1 yr−1 for Rhizophora stands that are 80, 18, and 5 years old, respectively. These results confirm that the above-ground biomass of tropical mangrove forest asymptotes with age. In tropical terrestrial forests, Ryan et al. (2004) conclude that the decline in above-ground wood production is proportionally greater than the decline in canopy photosynthesis. The fraction of growth primary productivity partitioned to below-ground allocation and foliar respiration increases with stand age and contributes to the decline in above-ground wood production. Alongi (2009) shows that net canopy production of planted R. apiculata forests in Southeast Asia follows a log-phase for about 25–30 years, after which production levels off but does not diminish for over 80 years. Consequently, from an economic perspective, the choice of a final felling performed when the forest is older than 20 years seems to be adequate. From an ecological perspective, mangroves are among the most efficient carbon sinks because of their high productivity, they store more carbon in their biomass and the sediments in mature forest than many other ecosystems. Accordingly, mangroves potentially contribute to mitigating climate gas-driven climate change. Carbon stocks in the above-ground biomass of mangrove forests are usually estimated by multiplying generic carbon contents with DW biomass. However, the use of generic carbon content may lead to biases in carbon stock estimation by more than 10% (Rodrigues et al., 2015). The default value of carbon contents suggested by the IPCC for mangrove forests is 45.1% (IPCC, 2014), mean deviation resulting from the use of generic (45.1%) instead of specific carbon contents (44.09%) to convert the above-ground biomass of thirteen plots into carbon stock is 2.7 ± 1.00 Mg C ha−1, slightly lower than that for tropical and subtropical forests of 47%, with mean deviation 7.8 ± 2.87 Mg C ha−1 (IPCC, 2006). Twilley et al., (1992) had already suggested the value of 45%, with mean deviation 2.5 ± 0.90 Mg C ha−1; but in their recent review, Bouillon et al. (2008) suggested 44%, with mean deviation − 0.2 ± 0.09 Mg C ha−1 and Kauffman and Donato (2012) also suggested 46% to 50%, with mean deviation an increase of 5.2 ± 1.89–15.9 ± 5.84 Mg C ha−1. In Southern Vietnam, the carbon contents slightly vary by compartment, with the trunks containing 44.60% C, the branches 42.59% C, the prop roots 43.77% C, and the leaves 42.30% C. Based on these results and on biomass partitioning (Eq. (1)), we calculate a generic carbon conversion factor for R. apiculata of 44.09 ± 1.37% (Table 2). A similar result was obtained by Rodrigues et al. (2015), when studying the carbon content of mangrove species Sepetiba Bay (Brazil). He proposed a value of 44.1 ± 1.4% for the woody parts of mangrove trees. By multiplying carbon contents by the DW of the biomass of the different components of the R. apiculata tree, we calculate the carbon stock allocation. The trunks represent 77.11 ± 5.00% of the carbon stock in the above-ground biomass, the branches 11.87 ± 3.19%, the prop roots 8.66 ± 2.52%, and the leaves 2.36 ± 0.43% (Table 2). Tropical mangrove forests play a key role in carbon cycling in the coastal ocean and represent potentially important carbon sinks in the biosphere, storing carbon in their biomass and in their soils. The global mean above-ground carbon stock for mangroves is 159 Mg C ha−1 and can reach a maximum value of 435 Mg C ha−1 (Donato et al., 2011). In Southern Vietnam, carbon stocks in the above-ground biomass vary with tree density (from 860 to 16,100 trees per hectare) and forest development, ranging from 59.7 to 230.9 Mg C ha−1, with a mean value of 118.9 ± 47.0 Mg C ha−1. These results are similar to those published in other studies in the Mekong Delta using common allometric equations and conversion factors, with values ranging from 13.4 to

210.7 Mg C ha−1, tree density ranging from 812 to 4539 per hectare (Dung et al., 2016; Nam et al., 2016; Tue et al., 2014). However, the above-ground carbon stocks of the studied mangroves are remarkably higher than that of a mangrove forest older than the 80 year old forest in Peninsular Malaysia, which has a stock of 202.9 Mg C ha−1, with a tree density of 681 per hectare (Putz and Chan, 1986). Clough (1992) found that the mean above-ground carbon stock in an undisturbed forest is 313.5 Mg C ha−1 in northeastern Australia. Additionally, Donato et al. (2012) also showed that the mean above-ground carbon stock in western Micronesian islands ranged from 152 to 345 Mg C ha−1. Consequently, even if the carbon stocks in the aboveground biomass of mangrove forests in Southern Vietnam are relatively high, due to the tropical climate, the relatively young age of these planted forests (< 40 years old) and the silvicultural practices limit these stocks. 4. Conclusions Planted mangrove forests in Southern Vietnam can store a high amount of carbon in their biomass, confirming the environmental value of this ecosystem and management by the Vietnamese authorities. However, carbon stocks in the above-ground biomass as well as biomass partitioning varied with forest age and tree density, which depend on thinning activities. Nevertheless, to accurately determine the ability of mangroves in Southern Vietnam to fix and store carbon, one has to determine their productivity, including soil respiration and tidal export, which will be conducted in a future research effort. The main conclusions of this study can be summarized as follow: 1. R. apiculata mangrove forest structures and characteristics are similar between Can Gio and Ca Mau. The propagules used for mangrove afforestation in Can Gio were collected in Ca Mau. 2. Allometric equations with DBH as a predictor variable provide an accurate means of estimating above-ground biomass of planted R. apiculata trees in Southern Vietnam. The following allometric model was determined:

WTotal = 0.38363 ∗ DBH2.2348 (R2 = 0.976, SE = 1.17, F = 1401, P < 0.001) 3. Trunks represent the largest contribution to the total DW aboveground biomass and the leaves represent the lowest contribution. Biomass partitioning varies with forest age, with a higher allocation to the branches and to the prop roots as the tree develops in order to maintain its stability on a muddy substrate. 4. The height increment is the highest for the young stands because of the competition for light in stands that are planted with high density. 5. Silvicultural practices allow for an easier development of the trees; the crowns of individual trees are less restricted by those of their neighbors, resulting in biomass development. 6. Because of tree density reduction though thinning activities and the young ages of the forests, carbon stocks in the above-ground biomass are lower than for unmanaged tropical mangrove forests. 7. The increase rate of above-ground biomass decreases significantly with forest age, confirming that mangrove forest productivity asymptotes when reaching a mature stage of development. Acknowledgements The authors would like to thank Tran Nhat Toan, Nguyen Quoc Van for their valuable assistance during fieldwork. We also thank Dr. Adrien Jacotot for his assistance in lab analyses at UR206, IRD, Noumea - New Caledonia. We also would like to express our gratitude to the authorities of Ca Mau Forest Rangers Department, Dat Mui Protection Mangrove Board, Ngoc Hien Forestry Company - Ca Mau province, and 139

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to the Can Gio Mangrove Board and Vam Sat Tourist Company of Ho Chi Minh city, who facilitated the fieldwork. The research was supported by an ARTS grant from IRD, France and by the Air Liquide Foundation, France.

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