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Using satellite RS data predicting mangrove vegetation carbon stock (MVC) is the popular and efficient approach at a large scale to protect mangroves and promote carbon trading. Satellite data have performed poorly in predicting MVC due to saturation issues. UAV-LiDAR data overcomes these limitations by providing detailed structural vegetation information. However, how to cross-scale integration of UAV-LiDAR and satellite RS data and the selection of features and machine learning methods hampered the practitioner in making a lightweight but efficient model to predict the MVC. Our study integrated UAV-LiDAR, Sentinel-1, and Sentinel-2 to extract spectral, structural, and textural features at the regional scale. We estimated the influences of different combinations between three vegetation features and machine learning methods (Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Regression Tree (GBDT), and Extreme Gradient Regression Tree (XGBOOST)) on the results of MVC prediction, and constructed a framework for estimating mangrove vegetation aboveground (ACG) and belowground (BCG) carbon storage in Zhanjiang, the largest mangrove area of China. Our research shows: 1) Compared to using satellite remote sensing (RS), integrating UAV and satellite RS data and fusing multiple vegetation features significantly improved the accuracy of mangrove vegetation carbon stock (MVC) predictions. 2) Structural features, particularly canopy height retrieved from UAV and satellite RS, are essential indicators for predicting MVC. Combined with spectral and structural features, regional MVC was precisely predicted. 3)Although the influence of different machine learning methods on MVC prediction was not significant, XGBOOST demonstrated relatively high precision. We recommend that mangrove practitioners integrate UAV and satellite RS data to predict MVC at a regional scale. Importantly, governments should prioritize the application of UAV-LiDAR in forestry monitoring and establish a long-term mangrove monitoring database to aid in estimating blue carbon resources and promoting blue carbon trading. • Build whole and consecutive mangrove vegetation carbon stock (MVC) model fusing vegetation features. • Quantify the influence of vegetation features and methods on predicting MVC. • Optimizing the selection of vegetation features and methods for predicting MVC. • Combined with UAV and Satellite RS data, predicting MVC at a regional scale. • Emphasizing the importance of UAV-LiDAR for predicting MVC. [ABSTRACT FROM AUTHOR]

Forests, the ancient wooden giants, are both symbols of natural beauty and reservoirs of carbon stocks. The current climate crisis has created an urgent need for an in-depth study of forest ecosystems and carbon stocks. Based on forest inventory data from field surveys and four bioclimatic zones [Zone 1 (Z1, humid forest), Zone 2 (Z2, semi-humid forest), Zone 3 (Z3, semi-humid to semi-arid forest-grassland), and Zone 4 (Z4, semi-arid typical grassland)], two methods [Method 1 (M1) and Method 2 (M2)] were used to estimate carbon stocks in forest ecosystems in Shaanxi Province, China, and explored the spatial patterns of carbon pools and potential influences. The total forest ecosystem carbon pool amounted to 520.80 Tg C, of which 53.60% was stored aboveground, 17.16% belowground, and 29.24% in soil (depth of 0–10 cm). Spatially, there were marked north-south gradients in both biomass (Z2 > Z3 > Z1 > Z4) and soil organic carbon densities (Z1 > Z2 > Z3 > Z4). The differences between aboveground and belowground biomass carbon density across broadleaf, needle-leaf, and broadleaf and needle-leaf mixed forest were not pronounced, while soil organic carbon density had the order of broadleaf (18.38 Mg C/ha) > needle-leaf (11.29 Mg C/ha) > broadleaf and needle-leaf mixed forest (10.33 Mg C/ha). Under an ideal scenario that excludes external factors, mainly forest growth, the sequestration potential of forest biomass by 2032 was estimated by M1 as 85.43 Tg, and by M2 to be substantially higher at 176.21 Tg. As of 2062, M1 estimated 155.97 Tg of sequestration potential for forest biomass. The spatial patterns of forest biomass and soil carbon density were closely related to climatic factors, and these relationships allowed the spatial division into two distinct climatic regions. Moreover, biomass carbon density was significantly correlated with the normalized difference vegetation index, soil silt, and elevation. This study provides key information for promoting the strategic shift from light-green to deep-green forest systems in Shannxi Province and updates the estimation methods of forest ecosystems' carbon pools based on field surveys. • Two methods were used to estimate carbon stocks in forest ecosystems. • The estimated total forest ecosystem carbon stock was 520.80 Tg C. • Mixed forest had lower soil organic carbon (0–10 cm depth) than monotypic stands. • Spatial patterns of carbon density can be divided into two climate regions. [ABSTRACT FROM AUTHOR]

The blue carbon ecosystem, including the salt marsh ecosystem, possesses a significant carbon sequestration potential. Therefore, accurately quantifying the carbon storage within such ecosystems is crucial for the adequate accounting of carbon sequestration. The present work chose a Spartina alterniflora ecosystem in the Xiaogan Island (China) as the study area (approximately 11 ha), and employed the Bayesian maximum entropy (BME) approach to assimilate both hard organic carbon (OC) data and soft OC data measured from 2 cm and 10 cm stratified samples. A 3-dimensional model was developed for space-time OC estimation purposes based on the sediment chronology results. The 10-fold BME cross validation results demonstrated a high estimation accuracy, with the R2, RMSE and MAE values equal to 0.8564, 0.1026 % and 0.0748 %, respectively. A noteworthy outcome was the BME-generated carbon storage density maps with 1 m spatial resolution. These maps revealed that the carbon storage density at the top 30 cm sediment depth in the stable zone (with elder stand age of S. alterniflora) was higher than that in the rapid expansion zone, i.e., 71.79 t/ha vs. 69.82 t/ha, respectively. Additionally, the study found that the averaged carbon burial rate and the total carbon storage at the top 30 cm sediment depth across the study area were 266 g C/m2/yr and 781.50 t, respectively. Lastly, the proposed BME-based framework of carbon storage estimation was found to be versatile and applicable to other blue carbon ecosystems. This approach can foster the development of a standardized carbon sink metrological methodology for diverse blue carbon ecosystems. • Carbon storage in salt marsh ecosystem was estimated at a spatial resolution of 1 m. • BME exhibited versatile ability for carbon storage estimation in a space-time domain. • Stand age of Spartina Alterniflora positively related to the carbon storage in sediment. [ABSTRACT FROM AUTHOR]

Despite the progress made in understanding relevant carbon dynamics under grazing exclusion, previous studies have underestimated the role of soil bulk density (BD), and its implications for potential accumulation of soil organic carbon (SOC), especially at regional scale over long term. In this study, we first constructed a database covering a vast majority of the grasslands in northwestern China based on 131 published literatures. A synthesis was then conducted by analyzing the experimental data to comprehensively investigate the mechanisms of vegetation recovery, carbon-nitrogen coupling, and the importance of changed soil BD in evaluating SOC sequestration potential. The results showed that although the recovery of vegetation height and cover were both critical for improving vegetation biomass, vegetation height required a longer recovery period. While the SOC accumulation was found to be greater in surface layers than deeper ones, it exhibited a reduced capacity for carbon sequestration and an increased risk of SOC loss. Grazing exclusion significantly reduced soil BD across different soil profiles, with the rate of change influenced by soil depth, time, geographical and climatic conditions. The potential for SOC accumulation in the top 30 cm of soil based on data of 2003–2022 was 0.78 Mg ha−1 yr−1 without considering BD effects, which was significantly underestimated compared to that of 1.16 Mg ha−1 yr−1 when BD changes were considered properly. This suggests that the efficiency of grazing exclusion in carbon sequestration and climate mitigation may have been previously underreported. Furthermore, mean annual precipitation represented the most relevant environmental factor that positively correlated to SOC accumulation, and a wetter climate may offer greater potential for carbon accumulation. Overall, this study implies grazing exclusion may play an even more critical role in carbon sequestration and climate change mitigation over long-term than previously recognized, which provides essential scientific evidence for implementing stepwise ecological restoration in grasslands. • Grazing exclusion causes significant changes in vegetation, carbon, nitrogen and bulk density. • The changes of carbon, nitrogen and bulk density depend on soil depth, time, and environment. • SOC accumulation has been underestimated by nearly 30% in previous studies. [ABSTRACT FROM AUTHOR]

A displacement factor (DF) may be used to describe the efficiency of using wood-based products or fuels instead of fossil-based ones to reduce net greenhouse gas (GHG) emissions. However, the DFs of individual products and their production volumes could not be used alone to evaluate the climate impacts of forest utilization. For this reason, in this study we have developed a methodology to assess a required displacement factor (RDF) for all wood products and bioenergy manufactured and harvested in a certain country in order to achieve zero CO 2 equivalent emissions from increased forest utilization over time in comparison with a selected baseline harvesting scenario. Input data for calculations were produced with the simulation model, Monsu, capable of predicting the carbon stocks of forests and wood-based products. We tested the calculations in Finnish conditions in a 100-year time horizon and estimated the current average DF of manufactured wood-based products and fuels in Finland for the interpretation of RDF results. The results showed that if domestic wood harvesting will be increased by 17–33% compared to the basic scenario, the RDF will be 2.0 to 2.4 tC tC−1 for increased wood use in 2017–2116. However, the estimated average DF of manufactured wood-based products and fuels currently in Finland was less than 1.1 tC tC−1. The results indicate strongly that the increased harvesting intensity from the current situation would represent a challenge for the Finnish forest-based bioeconomy from the viewpoint of climate change mitigation. For this reason, there is an immediate need to improve reliability and applicability of the RDF approach by repeating corresponding calculations in different circumstances and by improving estimations of DF s on country levels. • Displacement factor (DF) describes the substitution climate impact of wood use. • We estimated required displacement factor (RDF) to achieve zero emissions. • RDF should be 2.0–2.4 tC tC−1 for increased wood use in 2017–2116 in Finland. • RDF appears greater than the estimated current average DF. • This is a threat for forest-based bioeconomy from the climate change viewpoint. [ABSTRACT FROM AUTHOR]

The soil carbon (C) dynamics is strongly influenced by climate and land-use patterns in the Himalayas. Therefore, soils under five prominent land use [e.g., maize (Zea mays), horticulture, natural forest, grassland, and wasteland] were sampled down up to 30 cm depth under two climatic conditions viz., temperate and subtropical to assess the impacts of climate and landuse on soil C dynamics. Results demonstrated that irrespective of land use, temperate soil contains 30.66% higher C than subtropical soils. Temperate soils under natural forests had the higher total organic carbon (TOC, 21.90 g kg−1), Walkley-Black carbon (WBC, 16.42 g kg−1), contents, and stocks (TOC, 66.92 Mg ha−1 and WBC, 50.24 Mg ha−1), and total soil organic matter (TSOM, 3.78%) concentration as compared to other land uses like maize, horticulture, grassland, and wasteland. Under both climatic conditions, maize land use had the lowest TOC 9.63, 6.55 g kg−1 and WBC 7.22, 4.91 g kg−1 at 0–15 and 15–30 cm soil depth, respectively. Horticulture land use had 62.58 and 62.61% higher TOC and WBC over maize-based land use under subtropical and temperate climatic conditions at 0–30 cm soil depth, respectively. However, soils of maize land use under temperate conditions had ∼2 times more TOC than in subtropical conditions. The study inferred that the C-losses is more in the subtropical soil than in temperate soils. Hence, the subtropical region needs more rigorous adoption of C conservation farming practices than the temperate climatic setting. Although, the adoption of C storing and conserving practices is crucial under both climatic settings to arrest land degradation. Horticultural land uses along with conservation effective soil management practices may be encouraged to restore more soil C and to improve the livelihood security of the hill populace in the North Western Himalayas. [Display omitted] • Total organic carbon content in soil was higher in temperate than in subtropical climates. • Conversion of forest to cropland resulted in more soil carbon losses under subtropical climate. • Total organic carbon and Walkley and Black carbon were more in surface soil than subsurface soil in all land uses. • Natural forest and grassland soils had the maximum total organic carbon content. [ABSTRACT FROM AUTHOR]

Fire plays a critical role in biodiversity, carbon balance, soil erosion, and nutrient and hydrological cycles. While empirical evidence shows that fuel reduction burning can reduce the incidence, severity and extent of unplanned fires in Australia and elsewhere, the integration of environmental values into fire management operations is not well-defined and requires further research and development. In practice, the priority for fuel reduction burning is effective mitigation of risk to life and property. Environmental management objectives, including maintenance of high quality water, reduction of CO 2 emissions and conservation of biodiversity can be constrained by this priority. We explore trade-offs between fuel reduction burning and environmental management objectives and propose a framework for optimising fuel reduction burning for environmental outcomes. [ABSTRACT FROM AUTHOR]

Nepal has successfully established more than 370,000 ha of plantations, mostly with Pinus patula, in the last three and a half decades. However, intensive management of these planted forests is very limited. Despite the fact that the Kyoto Convention in 1997 recognized the role of plantations for forest-carbon sequestration, there is still limited knowledge on the effects of management practices and stand density on carbon-sequestration of popular plantation species (i.e. Pinus patula) in Nepal. We carried out case studies in four community forests planted between 1976 and 1990 to assess the impacts of management on forest carbon stocks. The study found that the average carbon stock in the pine plantations was 217 Mg C ha −1 , and was lower in forests with intensively managed plantations (214.3 Mg C ha −1 ) than in traditionally managed plantations (219 Mg C ha −1 ). However, it was the reverse in case of soil carbon, which was higher (78.65 Mg C ha −1 ) in the forests with intensive management. Though stand density was positively correlated with carbon stock, the proportionate increment in carbon stock was lower with increasing stand density, as carbon stock increased by less than 25% with a doubling of stand density (300–600). The total carbon stock was higher in plantations aged between 25 and 30 years compared to those aged between 30 and 35 years. [ABSTRACT FROM AUTHOR]

Numerous analyses have been performed to quantitatively link carbon stock change caused by land-use change (CSC-LUC) to consumption of agricultural products, but results differ significantly, even for studies focussing on the same region or product. This is due to the different focuses and interpretations of the links between direct drivers and underlying causes of CSC-LUC, which can be translated into differences in key functions, i.e. specific methods, algorithms and parameters embedded in the analysis. Using the example of Indonesian palm oil production (often associated with CSC-LUC), this paper carries out a meta-analysis of 12 existing studies, determines the different settings for the key functions embedded in consumption-based CSC-LUC studies and discussed their implications for policymaking. It identifies the underlying reasons of adopting different settings within the eight key functions and their advantages and trade-offs. Examples are the way of determining how deforestation is linked to oil palm, and the inclusion of non-agriculture and non-productive drivers in the accounting to weight their roles in CSC-LUC in comparison to palm oil consumption. Following that, the quantitative results from the selected studies were processed and harmonised in terms of unit, allocation mechanism, allocation key and amortisation period. This resulting in ranges of 0.1–3.8 and −0.1–15.7 tCO 2 /t crude palm oil for historical and projection studies, respectively. It was observed that CSC-LUC allocated to palm oil is typically lower when propagating effects and non-agricultural or non-productive drivers were accounted for. Values also greatly differ when marginal and average allocation mechanisms were employed. Conclusively, individual analyses only answer part of the question about CSC-LUC drivers and have their own strengths and weaknesses. Since the context can be very different, using quantitative results from a single study for accounting purposes in policymaking is not recommended. Instead, insights from different studies should be combined, e.g. the relative role of logging and oil palm or the contribution to CSC-LUC in regional and global perspectives. [ABSTRACT FROM AUTHOR]

Agricultural expansion driven by growing demand has been a key driver for carbon stock change as a consequence of land-use change (CSC-LUC). However, its relative role compared to non-agricultural and non-productive drivers, as well as propagating effects were not clearly addressed. This study contributed to this subject by providing alternative perspectives in addressing these missing links. A method was developed to allocate historical CSC-LUC to agricultural expansions by land classes (products), trade, and end use. The analysis for 1995–2010 leads to three key trends: (i) agricultural land degradation and abandonment is found to be a major (albeit indirect) driver for CSC-LUC, (ii) CSC-LUC is spurred by the growth of cross-border trade, (iii) non-food use (excluding liquid biofuels) has emerged as a significant contributor of CSC-LUC in the 2000's. In addition, the study demonstrated that exact values of CSC-LUC at a single spatio-temporal point may change significantly with different methodological settings. For example, CSC-LUC allocated to ‘permanent oil crops’ changed from 0.53 Pg C (billion tonne C) of carbon stock gain to 0.11 Pg C of carbon stock loss when spatial boundaries were changed from global to regional. Instead of comparing exact values for accounting purpose, key messages for policymaking were drawn from the main trends. Firstly, climate change mitigation efforts pursued through a territorial perspective may ignore indirect effects elsewhere triggered through trade linkages. Policies targeting specific commodities or types of consumption are also unable to quantitatively address indirect CSC-LUC effects because the quantification changes with different arbitrary methodological settings. Instead, it is recommended that mobilising non-productive or under-utilised lands for productive use should be targeted as a key solution to avoid direct and indirect CSC-LUC. [ABSTRACT FROM AUTHOR]

The carbon (C) cycle of forests produces ecosystem services (ES) such as climate regulation and timber production. Mapping these ES using simple land cover -based proxies might add remarkable inaccuracy to the estimates. A framework to map the current status of the C budget of boreal forested landscapes was developed. The C stocks of biomass and soil and the annual change in these stocks were quantified in a 20 × 20 m resolution at the regional level on mineral soils in southern Finland. The fine-scale variation of the estimates was analyzed geo-statistically. The reliability of the estimates was evaluated by comparing them to measurements from the national multi-source forest inventory. The C stocks of forests increased slightly from the south coast to inland whereas the changes in these stocks were more uniform. The spatial patches of C stocks were larger than those of C stock changes. The patch size of the C stocks reflected the spatial variation in the environmental conditions, and that of the C stock changes the typical area of forest management compartments. The simulated estimates agreed well with the measurements indicating a good mapping framework performance. The mapping framework is the basis for evaluating the effects of forest management alternatives on C budget at high resolution across large spatial scales. It will be coupled with the assessment of other ES and biodiversity to study their relationships. The framework integrated a wide suite of simulation models and extensive inventory data. It provided reliable estimates of the human influence on C cycle in forested landscapes. [ABSTRACT FROM AUTHOR]

Bamboo forests provide important ecosystem services and play an important role in terrestrial carbon cycling. Of the approximately 500 bamboo species in China, Moso bamboo ( Phyllostachys pubescens ) is the most important one in terms of distribution, timber value, and other economic values. In this study, we estimated current and potential carbon stocks in China's Moso bamboo forests and in their products. The results showed that Moso bamboo forests in China stored about 611.15 ± 142.31 Tg C, 75% of which was in the top 60 cm soil, 22% in the biomass of Moso bamboos, and 3% in the ground layer (i.e., bamboo litter, shrub, and herb layers). Moso bamboo products store 10.19 ± 2.54 Tg C per year. The potential carbon stocks reach 1331.4 ± 325.1 Tg C, while the potential C stored in products is 29.22 ± 7.31 Tg C a −1 . Our results indicate that Moso bamboo forests and products play a critical role in C sequestration. The information gained in this study will facilitate policy decisions concerning carbon sequestration and management of Moso bamboo forests in China. [ABSTRACT FROM AUTHOR]

Mangrove forests provide important ecosystem services, and play important roles in terrestrial and oceanic carbon (C) cycling. Although the C stocks or storage in terrestrial ecosystems in China have been frequently assessed, the C stocks in mangrove forests have often been overlooked. In this study, we estimated the C stocks and the potential C stocks in China's mangrove forests by combining our own field data with data from the National Mangrove Resource Inventory Report and from other published literature. The results indicate that mangrove forests in China store about 6.91 ± 0.57 Tg C, of which 81.74% is in the top 1 m soil, 18.12% in the biomass of mangrove trees, and 0.08% in the ground layer (i.e. mangrove litter and seedlings). The potential C stocks are as high as 28.81 ± 4.16 Tg C. On average, mangrove forests in China contain 355.25 ± 82.19 Mg C ha−1, which is consistent with the global average of mangrove C density at similar latitudes, but higher than the average C density in terrestrial forests in China. Our results suggest that C storage in mangroves can be increased by selecting high C-density species for afforestation and stand improvement, and even more by increasing the mangrove area. The information gained in this study will facilitate policy decisions concerning the restoration of mangrove forests in China. [Copyright &y& Elsevier]

Any system to compensate countries for reduced emissions from deforestation and forest degradation (REDD+) requires a historical reference level against which future performance can be measured. Here we examine the possibilities Sri Lanka, a small forest country with limited data on forest carbon stocks, has to get ready for REDD+. We construct a historical reference level using available forest inventory data combined with updated 2008 and 2009 in situ carbon density data for Sri Lankan forests. Furthermore, we use a combination of qualitative and quantitative data to attribute the clearing of Sri Lankan forests in the latest years for which national forest inventory data are available, 1992–1996, to various proximate drivers and to estimate the opportunity cost of forest conservation. We estimate that baseline deforestation emissions in Sri Lanka amounted to 17MtCO2 yr−1 in the 1992–1996 period, but conclude that it is challenging for Sri Lanka to produce a robust and accurate reference level due to the lack of nationally based inventories. We find that the majority of forest clearing (87%) is due to small-scale, rainfed farming, with the two other major drivers being rice and tea cultivation. Further, Sri Lankan revenues from REDD+ participation could be substantial, but they are sensitive to REDD+ policy transaction cost, highly uncertain timber revenues, and particularly the carbon price paid for emission reductions. The latter needs to be higher than $5–10/tCO2 if there are to be substantial incentives for Sri Lanka to participate in REDD+. There is, however, a large gap in the knowledge of deforestation drivers that needs to be filled if Sri Lanka is to formulate an effective policy response to forest degradation in REDD+. For successful REDD+ implementation in Sri Lanka to happen, technological assistance, readiness assistance, and continued political momentum are crucial. [Copyright &y& Elsevier]

Forest's ecosystem is changing at an alarming rate and anthropogenic alteration of forests to other land use is a major driver of carbon (C) emission and biodiversity loss. We estimated ecosystem-level C stock and factors affecting C stock in six major forest types; tropical wet evergreen forest, montane subtropical forest, temperate forest, bamboo forest, quercus forest, and jhum land of the eastern Himalayan region (India). We determined ecosystem structure, biodiversity, and plant and soil C stock by laying random plots in each forest site. The average C stock was estimated in the range of 79.0–373.4 Mg C ha−1 and found significantly different among the forest types. Partitioning ecosystem C stocks in plant (24–55%), soils (43–75%), deadwood (1–4.8%) and litter (0.20–1.25%) components varied largely. Pearson correlation analysis shows a significant positive relation of basal area with species diversity, tree density, and ecosystem C stock. Linear mixed-effect model demonstrates the high influence of species density and soil moisture content on the ecosystem C stock. We recommend the inclusion of forest structural attributes and pedological characteristics while predicting synergies between C stock and future climatic conditions. Additionally, conversion of natural forests to jhum land should be minimized because they stored lesser ecosystem C stocks thus plays a minimum role in C accumulation and cycling. The study provides estimates of C stocks in major forests that can be useful in suggesting a path forward to partially fulfill India's commitments to REDD + policy. [Display omitted] • Determining ecosystem-level carbon stock is essential for carbon sink management. • Average carbon stock ranged from 79 Mg C ha−1 to 373 Mg C ha−1 in major forest types. • Tropical wet evergreen forests are major carbon sink in the eastern Himalayas. • Carbon stock is highly influenced by the stand density and soil moisture content. • Jhum forests practices should be reduced to enhance ecosystem carbon sink capacity. [ABSTRACT FROM AUTHOR]

Drought events may induce mangrove mortality and dieback events worldwide as a result of climate extremes. As mangroves sequester large quantities of carbon, quantifying the losses of these stocks following climate disturbances may guide wetland governance strategies globally. In Southeast Brazil, we determined the total ecosystem carbon stocks (TECS) of pristine mangroves that were up to 1851 Mg of carbon per hectare (Mg C ha−1), which are the highest stocks measured from South American and raising estimates of Brazil's mangrove TECS to 0.52 Pg C. A mangrove mortality event in the same estuary resulted in a 14.6 % decrease in TECS (270.5 Mg C ha−1) and loss of 20 % of mangrove soil carbon within less than 2-years. Carbon dioxide emissions from this impact were 992.8 Mg CO 2 e ha−1, which are slightly lower than emissions from land use disturbances on mangroves worldwide. Our results suggest that climate effects on mangroves can become significant sources of greenhouse gases globally. [Display omitted] • The pristine mangroves in SE Brazil stock over 1851 Mg C ha−1. • Climate-relate impacts resulted in 14.6 % decrease in total ecosystem carbon stock. • The mangrove dieback lead to 40.4 % of carbon losses on the 0–30 cm soil. • Carbon dioxide emissions from the climate-relate impact was 992.8 Mg CO 2 e ha−1. • The Brazilian mangroves hold 5 % (0.52 Pg C) of the global mangrove ecosystem stock. [ABSTRACT FROM AUTHOR]

Wetlands are highly productive ecosystem with great potential to store carbon (C) and retain nitrogen (N) and phosphorus (P) in their soil. Changes in vegetation type and land use can affect organic matter inputs and soil properties. This work aimed to examine how these changes affected elemental stoichiometry and C-, N-, and P- associated enzyme activities and wetland soil organic C stock. We quantified organic C concentrations, and stoichiometric ratios of C, N, and P in total and microbial biomass pools, along with the activities and ratios of C-, N-, and P-associated enzymes for soils of natural coastal wetlands with different vegetation types, namely Melaleuca wetland (Melaleuca spp), mangrove forests (Bruguiera spp), and saline marsh (Eleocharis spp). We also compared these natural wetlands to an adjacent sugarcane plantation to understand the effects of vegetation types. Hypothesis-oriented path analysis was used to explore links between these variables and soil organic C stocks. Tidal forested soils (0–30 cm) had the highest organic C, N, and P contents and potential activities of C-, N-, P- acquiring enzymes, compared with other vegetation types. Mangroves soils had the highest total soil C:N and microbial biomass C:P ratios. Microbial biomass C:P ratios were significantly and positively related to total C:P, while microbial biomass N:P ratios were positively associated with total soil C:P and N:P ratios. Path analysis suggested that soil organic C stock was largely explained by total C:P ratio, microbial biomass N:P ratios, total P content, and the ratio of C- and P-associated enzymes. Different types of wetlands have different soil properties and enzymatic activities, implying their different capacity to store and process C and N. The resource quality and stoichiometry direct influence the organic C stock. [Display omitted] • Carbon stock in coastal wetlands under different vegetation types were compared. • The organic carbon stock was the highest in Melaleuca wetland. • Resource stoichiometry governs surface soil organic carbon stock. • Microbial N:P ratios were highly correlated with resources N:P ratio. • A shift in enzyme activity is regulated by change in resources by vegetation types. [ABSTRACT FROM AUTHOR]