Assessment of Carbon Sequestration by Herbs and Soil in Wetlands of Bhopal District of Central India

doi:10.21203/rs.3.rs-5078304/v1

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Assessment of Carbon Sequestration by Herbs and Soil in Wetlands of Bhopal District of Central India

https://doi.org/10.21203/rs.3.rs-5078304/v1

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Wetlands in urban areas act as natural buffers that control floods, mitigate fire risks, and regulate local climates, helping to reduce the impact of extreme weather events on communities. Quantification of carbon stocks is critical to evaluate the potential of an ecosystem to mitigate the impact of global climate change and the emission of carbon dioxide (CO2) concentration from industries, burning of fossil fuels and deforestation causes greenhouse gases (GHGs). Hence, vegetation near wetlands in terms of agroforestry, plantation, and reforestation has been suggested as one of the most appropriate land management systems for mitigating atmospheric CO2 through the photosynthesis process. Forest ecosystems also contribute to storing more than 80% of all terrestrial aboveground Carbon and more than 70% of all soil organic carbon (SOC). We studied natural herbs, grasses, and soil near the wetland ecosystem in Madhya Pradesh, India to understand how much vegetation and soil are applicable for the capturing of carbon in urban areas as a carbon pool or carbon reservoir among the sites. Results indicated that the biomass of the wetland (near natural ecosystem) was 1.68 t ha-1 while the wetland (near manmade ecosystem) was 0.83 t ha-1. The total carbon stock in wetlands ranges between 16.34 t C ha^− 1 to 23.28 t C ha^− 1. Higher biomass accumulation and carbon stock were recorded in wetlands which are near natural ecosystems or away from human interferences. Proper efforts are required to manage these diverse ecosystems to obtain higher biomass and sustainable ecological services.

Forestry

Carbon Sequestration

Herb carbon stock

Soil carbon stock

Biomass

Wetlands.

It is well known that atmospheric CO2 is increasing at some 2ppmv p.a., mainly because of human activities such as fossil fuel combustion, and that this has taken its values from ca 280 ppmv at ‘pre-industrial’ levels to more like 400 ppmv today. To avoid the predicted increases in global temperature contingent upon ‘greenhouse gas’ effects we need not only to lower the emissions but preferably to find means of sequestering atmospheric CO2 over extended periods (Smith et al., 2008; Gayathri et al., 2021). Carbon sequestration is the process by which carbon dioxide (CO₂) is captured and stored, thereby reducing the amount of CO₂ in the atmosphere. This is crucial in mitigating the impacts of climate change. Wetlands, which include marshes, swamps, bogs, and fens, play a significant role in this natural process (Bassi et al., 2014).

Wetlands are unique ecosystems characterized by water saturation that influences the soil and vegetation. They are incredibly efficient at sequestering carbon due to their dense plant life and anaerobic (oxygen-poor) soil conditions (Chen et al., 2015). Plants in wetlands absorb CO₂ from the atmosphere through photosynthesis. When these plants die, they decay slowly in the waterlogged, anaerobic soil, which prevents the carbon from being released back into the atmosphere (Du et al., 2017). Instead, the carbon is stored in the form of organic matter, often for thousands of years.

This natural mechanism makes wetlands one of the most effective carbon sinks on the planet, sequestering more carbon per unit area than forests (Nag et al., 2023). However, wetlands are under threat from human activities such as agriculture, urban development, and drainage for land use, which can lead to the release of stored carbon back into the atmosphere, exacerbating climate change.

Soil in wetlands plays a pivotal role in carbon sequestration, contributing significantly to global carbon storage and climate regulation. Soils are one of the major carbon sinks on earth, because of their higher organic matter content (Rosli et al., 2017). Soils can act as sinks or as a source for carbon in the atmosphere depending on the changes happening to soil organic matter. The equilibrium between the rate of decomposition and the rate of supply of organic matter is disturbed when forests are cleared and land use is changed. Soil organic matter can also increase or decrease depending on numerous factors, including climate, vegetation type, nutrient availability, disturbance, and land use and management practice (Lal R., 2021). Wetland soils accumulate organic matter over time, derived from plant debris, roots, and microbial activity. This organic matter contains carbon that is stored in the soil in the form of humus and other organic compounds. Wetlands are known to store a large amount of carbon per unit area, often more than terrestrial ecosystems like forests due to their waterlogged conditions that slow down decomposition rates (Malak et al., 2021). The anaerobic (low oxygen) conditions in wetland soils slow down the decomposition of organic matter. As a result, carbon that enters wetland soils through plant biomass and organic inputs tends to accumulate rather than being rapidly released back into the atmosphere as CO₂. This process effectively sequesters carbon over long periods, contributing to climate change mitigation. In certain wetlands, particularly bogs and fens, conditions favour the formation of peat—a type of soil composed primarily of partially decayed plant material (Kell D. B., 2012; Chen et al., 2017). Peat soils can store immense amounts of carbon over millennia because the decomposition of organic matter is extremely slow under waterlogged, acidic conditions. Wetland soils are integral to the global carbon cycle. They act as significant carbon sinks, offsetting carbon dioxide emissions from human activities such as fossil fuel combustion and land-use changes. By sequestering carbon, wetlands help regulate atmospheric CO₂ concentrations, thereby mitigating climate change impacts. Healthy soils in wetlands support the growth of vegetation, including sedges, rushes, and other wetland-adapted plants. These plants contribute to carbon sequestration through photosynthesis, where atmospheric CO₂ is absorbed and converted into plant biomass.

Herbs and grasses in wetlands contribute significantly to carbon sequestration, enhancing the ecosystem's ability to mitigate climate change. Herbs and grasses in wetlands engage in photosynthesis, absorbing carbon dioxide (CO₂) from the atmosphere. This process converts CO₂ into organic carbon compounds, which are stored in plant tissues and roots (Yao et al., 2021; Acosta et al., 2020). These plants accumulate biomass over time as they grow and reproduce. The carbon stored in their biomass remains sequestered as long as the plants are alive and continues to increase with their growth. The root systems of herbs and grasses play a crucial role in carbon sequestration. They penetrate the soil, where they contribute organic matter to the soil carbon pool (Gogoi et al., 2021; Jhariya et al., 2018). This organic matter is often protected from decomposition due to the waterlogged conditions typical of wetlands, thus enhancing long-term carbon storage. The presence of herbs and grasses in wetlands increases the overall soil organic carbon stocks. Through root exudates and decomposition of their organic matter, they enrich the soil with carbon, contributing to the formation of humus and stable soil organic matter.

In summary, soil in wetlands serves as a vital reservoir for carbon sequestration, playing a critical role in global carbon cycling and climate regulation. Protecting and conserving wetland soils is essential for maintaining their capacity to store carbon and mitigate climate change impacts on a global scale. Herbs and grasses in wetlands are crucial components of carbon sequestration processes. Their ability to absorb CO₂, accumulate biomass, enrich soil carbon stocks, stabilize soil structure, and support biodiversity underscores their importance in mitigating climate change impacts and maintaining the health of wetland ecosystems (Bazezew et al., 2015). Protecting and restoring these plant communities is essential for maximizing their carbon sequestration potential and ensuring the long-term sustainability of wetland habitats.

Understanding the role of wetlands in carbon sequestration is vital for developing strategies to protect and restore these ecosystems. By conserving and rehabilitating wetlands, we can enhance their capacity to sequester carbon, contributing to climate change mitigation and the preservation of biodiversity.

2.1.1 Study Area:

The study area is located in Bhopal, Madhya Pradesh (Fig. 1). It is known as the City of Lakes due to various natural and artificial lakes. It is also one of the greenest cities in India. Bhopal is in the central part of India, surrounded by lakes and hills, the district is famous for its natural beauty. The city has uneven elevation and has small hills within its boundaries. The city’s geography has in it two lakes namely the upper lake and the lower lake. Bhopal has an average elevation of 500 meters (1401 ft) and the city hosts a humid subtropical climate in general. The flora of the Bhopal area is changing frequently with human activities and land use. The physiographic divisions of the regions are highlands, uplands, and central plain. The climate of the district is characterized by hot summer and well-distributed rainfall during the monsoon season. The soil of Bhopal district can be broadly classified into four major classes: red and yellow soils, alluvial soils, laterite soils, and mixed soils, respectively. The study was conducted in eight selected wetlands of Bhopal (Fig. 2) for a period of 4 months from February to May 2023 detailed in Table 1.

Table 1

Geographic information of study sites
Serial No.	Site Name	Latitude	Longitude
01.	Shahpura Lake	23°12'23.4"N	77°25'26.7"E
02.	Bhadbhada Dam	23°12'25.0"N	77°13'47.4"E
03.	Kerwa Dam	23°09'59.3"N	77°22'17.1"E
04.	Kaliasot Dam	23°11'39.7"N	77°24'13.0"E
05.	Laharpur Dam	23°11'48.3"N	77°28'47.4"E
06.	Hataikheda Dam	23°16'34.8"N	77°29'55.7"E
07.	University Pond	23°11'44.9"N	77°27'12.6"E
08.	Jawahar Bal Udyan Lake	23°13'29.3"N	77°25'17.1"E

2.1.2 Sampling Design

Wetlands present in Bhopal city were first identified and each study site’s GPS coordinates were recorded using Google Maps. The herbs and grasses collected as samples were identified with the help of two books i.e., Hand Book on Weed Identification by Dr. V. S. G. R. Naidu and Common Plants of the Riparian Zone of the River Narmada by U. Umrao and others. The live components i.e., herbs and grass near the wetland (outside the flood plain) were collected destructively by clipping all the vegetation down to ground level from a nested sub-plot of 1x1m. Sample plots were randomly overlaid to carry out the sampling in the field. The fresh weight of each sample was recorded within 0.1 g precision. Then, a sub-sample of about 100 g was wrapped in a marked bag and taken to the laboratory to calculate its oven-dry weight. (Pearson et al., 2005; Meena et al., 2019).

Afterward, the percent of carbon content was determined by the Loss of Ignition (LOI) method of Allen et al., 1986. In this method, the fresh weight samples were taken and brought to the laboratory to oven dry them the oven was set at 80ºC for 48 hours after which the dry weight of the sample was noted. The oven-dried samples were ground and 5 grams were taken in pre-weighted crucibles. The crucible containing the sample was put into the furnace for ignition at 550ºC for two hours (Negash and Star, 2015; Wei et al., 2021).

For soil carbon analysis a core sampler of height 15cm long and diameter 4.04 cm was used in obtaining soil core samples for bulk density estimation. Soil samples were collected from a depth of 12 cm from all study sites. Soil samples collected were transferred from core sampler to zip lock bags and the wet weight (W1) of each soil sample was noted to determine the soil organic carbon (SOC), Loss on Ignition (LOI) method was applied (Allen et al., 1986). In this method, initially, fresh weighed samples were taken and brought to the laboratory to oven dry them. The oven was set at 80℃ for 48 hrs, after which the dry weight (W2) of each sample was noted. Oven-dried grind samples were taken (5.00 g) in pre-weighted crucibles, and after that put in the furnace at 550°C for 1 h to ignite. The crucibles were cooled slowly inside the furnace. The weight of ash (W3) after cooling was noted, the crucibles with ash were weighed and the percentage of organic carbon was calculated (Bhattacharyya et al., 2023).

2.2 Methodology

Calculation of Biomass of Herb and Grass

Biomass is the mass of living biological organisms in a given area or ecosystem at a given time. Here we calculate the biomass of herbs and grasses to further know about the carbon stock they store by the Eq. (1)-

$$\:\text{H}\text{G}\text{B}=\frac{{\text{W}}_{\text{f}\text{i}\text{e}\text{l}\text{d}}}{\text{A}}\times\:\frac{{\text{W}}_{\text{s}\text{u}\text{b}-\text{s}\text{a}\text{m}\text{p}\text{l}\text{e},\text{d}\text{r}\text{y}}}{{\text{W}}_{\text{s}\text{u}\text{b}-\text{s}\text{a}\text{m}\text{p}\text{l}\text{e},\text{w}\text{e}\text{t}}}\times\:\frac{1}{10000}$$

Where ‘HGB’ is Herb and grass biomass (t ha-1). ‘W field’ is the weight of a wet field sample of herb and grass sampled within an area of size A (g). ‘A’ is the size of the area in which herb and grass was collected (ha). ‘W-subsample dry’ is the weight of the oven-dry subsample of herb and grass (g), and ‘W subsample wet’ is the weight of the fresh sub-sample of herb and grass.

Calculation of % of Ash

$$\:\text{%}\:\text{o}\text{f}\:\text{A}\text{s}\text{h}=\frac{\left\{(\text{W}\text{e}\text{i}\text{g}\text{h}\text{t}\:\text{o}\text{f}\:\text{a}\text{s}\text{h}\:+\:\text{C}\text{r}\text{u}\text{c}\text{i}\text{b}\text{l}\text{e})\:-\:\text{W}\text{e}\text{i}\text{g}\text{h}\text{t}\:\text{o}\text{f}\:\text{e}\text{m}\text{p}\text{t}\text{y}\:\text{c}\text{r}\text{u}\text{c}\text{i}\text{b}\text{l}\text{e}\:\:\right\}}{{\text{W}}_{\text{d}\text{r}\text{y}\:\text{w}\text{e}\text{i}\text{g}\text{h}\text{t}}}\times\:\:100$$

Where ‘% of ash’ is the percentage of ash left from the dry weight of the sample after ignition in Eq. (2).

Calculation of % of Carbon

% C = 0.5 * (100 - % of Ash) (3)

Where ‘% C’ is the Carbon fraction and ‘% Ash’ is the percentage of ash left from the dry weight in Eq. (3).

Calculating Hg Carbon Stock

Carbon stock refers to the amount of carbon stored in the environment (here, wetlands) typically in plants, soils, and aquatic systems. The more carbon stock, the higher would be the wetland’s capacity to absorb and sequester carbon dioxide (CO2), the main greenhouse gas in the atmosphere, through photosynthesis (Atsbha et al., 2019).

HG Carbon stock = HGB * %C (4)

Where, ‘HG Carbon stock’ is herb and grass carbon stock (t C/ha), ‘HGB’ refers to herb and grass biomass (t/ha), Eq. (4).

For Calculating the Bulk Density of the Soil:

Bulk density is an estimate of soil compaction, important for understanding the suitability of soil for root penetration, soil permeability, physical behavior of soil, and soil porosity (Pearson et al., 2005).

BD = W2 / V (5)

(V = πr² x h ) (6)

where, BD = Bulk density (G/cm³); W2 = weight of oven dried sample(g), V = Volume of core sampler (cm³); r = radius of the core sampler (cm); h = height of the Core sampler (cm) in Eq. (5,6).

For calculating %C of the Soil:

%Ash = [ $\:\frac{W3-W2}{W2-W1}$ ] x 100 (7)

%C = (100 − %Ash) × 0.58 (8)

By considering 58% Carbon in ash-free soil material for Eq. (7,8), where, W1 = Weight of crucible(g), W2 = Weight of the oven-dried grind sample and crucible (g), and W3 = Weight of ash and crucible(g).

For calculating Soil Organic Carbon (SOC) stock:

Soil organic carbon refers only to the carbon component of organic compounds, it remains in the soil after the decomposition of any material produced by living organisms, which is calculated by using Eq. (9).

SOC stock = BD * d * %C (9)

where, SOC = soil organic carbon stock per unit area (t C/ ha), BD = bulk density (g cm³),

d = the total depth at which the sample was taken (cm), and %C = Carbon concentration (%).

Calculating Total Carbon Stock:

The carbon values for each carbon pool were summed to estimate the total carbon stock of the wetland. The following Eq. (10) was used to calculate the total wetland carbon stock:

TCS = SOC + C (HG) (10)

where ‘TCS’ is the Total Carbon Stock of the wetland (t C/ha), ‘SOC’ is Soil organic carbon (t C/ha), ‘C(HG)’ is carbon stock in herbs and grasses of the wetland (t C/ha).

Calculating Co ₂ Eq (Carbon Dioxide Equivalent):

CO₂ equivalent (CO₂ eq) is a measure used to compare the warming potential of different greenhouse gases by converting them into the amount of carbon dioxide that would have the same impact. The CO₂ eq of the total carbon stock was obtained by multiplying the carbon stock by (molar conversion factor of) 3.67 or 44/12 (Pearson et al., 2007).

CO₂ eq = TC x 3.67 (11)

where, CO₂ eq is carbon dioxide equivalent (t CO₂/ha) and TC is total carbon stock (t C/ha).

2.3 Statistical Analysis

Multivariate ordination analysis was utilized to statistically examine the data. The Box Plot Model and Principal Component Analysis (PCA) were utilized to express the statistical differences and similarities between the various carbon pools in the wetland sites. A correlation matrix was utilized to assess the relationship between the carbon stocks in the soil and plants by expressing overall trends in the total carbon stock among the forests under study. ƿ = 0.05 was the significance level that was applied (Chave et al., 2014; Chopra et al., 2023).

3.1 Biomass and Carbon Stock in Herbs or Grass

The vegetation assessment showed that some of the species were recurring in almost every study site like Cynodon dactylon, Parthenium hysterophorus, Cassia tora, Rumex dendatus, etc. Meanwhile, as the summer months came by, we could see that the vegetation around started drying up and most study sites were victims to pollution due to anthropogenic activities and for being a tourist spot. Cattle grazing was common as well. The average total biomass of all the study sites was calculated and it ranged from 0.83 t ha^− 1 to 1.75 t ha^− 1 and the average carbon stock of the study sites came out to be between 0.41 t C ha^− 1 to 0.87 t C ha^− 1 described in Table 2.

Table 2

Average biomass and average carbon stock of herbs, and grass in wetlands of Bhopal
S. No.	Study Site Name	Total Biomass (Average) (t Ha^− 1)	Carbon Stock (Average) (t C Ha^− 1)
01.	Shahpura Lake	1.2	0.59
02.	University Lake	0.83	0.41
03.	Laharpur Dam	1.16	0.58
04.	Hataikheda Dam	1.68	0.84
05.	Char Imli Park	0.94	0.46
06.	Bhadbhada Dam	1.41	0.70
07.	Kerwa Dam	1.75	0.87
08.	Kaliasot Dam	1.31	0.65

3.2 Bulk Density and Carbon Stock of Soil

The average bulk density of each wetland was calculated (Table 3), it ranged from 0.9g/ cm³ to 1.33 g/cm³. The highest bulk density was found in Jawahar bal Udhyan (Charimlli Park) and the lowest in Laharpur Dam. This generally indicates that the organic matter content of Laharpur Dam is high and low in Charimlli Park (as low bulk density indicates high porosity and in general high organic matter content).

Table 3

Average bulk density and average carbon stock of soil in wetlands of Bhopal
S. No.	Sites Name	BD (Average) (g/cm3)	SOC (Average) (t C/ha)
01.	Shahpura Lake	1.1	19.69
02.	University Lake	1.09	20.56
03.	Laharpur Dam	0.91	15.75
04.	Hataikheda Dam	1.18	21.28
05.	Char Imli Park	1.33	17.54
06.	Bhadbhada Dam	1.01	18.31
07.	Kerwa Dam	1.24	22.41
08.	Kaliasot Dam	1.18	21.39

The average Soil Organic Carbon (SOC) of each wetland was calculated (Table 3), it ranged between 15.75 t C/ha to 22.41 t C/ha. Factors that increase soil carbon content are no-tillage, less anthropogenic activities, reduced grazing, and forest restoration, and mostly all these factors were in place around and at Kerwa Dam, and as per data collected highest carbon content was found in Kerwa Dam. The organic carbon content of the soil depends on substrate availability, temperature, and climate, due to which there is variation in the carbon content of the soil in the soils of study areas. Laharpur Dam has the lowest soil carbon, as factors that decrease soil carbon content are cultivation, grazing, pollution, and degradation, and mostly all of these present in Laharpur Dam.

3.3 Total Carbon Stock

The total carbon stock was calculated by combining the vegetation data (HG Carbon stock) along with the soil data obtained (SOC). It ranged from 16.34 t C ha^− 1 to 23.28 t C ha^− 1. In Fig. 4, the graph shows the total carbon stock of both soil and herbs and shrubs, according to this, it is clear that wetland soil carbon stock is more compared to the carbon stock of wetland vegetation.

Assessing CO₂ equivalents during carbon sequestration analysis involves quantifying the amount of carbon dioxide (CO₂) that is captured and stored in various forms such as soil organic carbon, biomass, and other carbon sinks. This process helps in understanding the impact of different agricultural practices on climate change mitigation. CO₂ equivalent values ranged from 59.96 tons to 85.43 tons. Hataikhedha Dam, Kerwa Dam, and Kaliasot Dam show the highest percent of CO₂ eq i.e. 14% which are followed by University Lake with 13% CO₂ eq (Fig. 5)

3.4 Statistical calculation

Principal Component Analysis (PCA) was used to site-specific data, yielding 52.103% and 25.45% variances, respectively, with the first two components' respective Eigenvalues of 18.397 and 37.664 reflecting the test's statistical power. With respect to the total biomass and carbon stocks along the X-axis, PCA identified and distinguished the locations of Kaliasot Dam, Hathaikhedha Dam, and Kerwa Dam based on the maximum carbon stock values. The segregation of the Kerwa Dam site, which is located on the upper right and has maximum biomass values of 1.75 t/ha, with maximum SOC values of 22.14 t/ha, is another noteworthy finding of the PCA biplot. The Laharpur Dam site, which had the lowest values of PCS (Plant Carbon Stock) and SCS (Soil Carbon Stock), 0.58 and 15.75 t/ha, was placed separately on the bottom, indicating non-significant associations with any variable. In contrast, the sites with very similar and moderate carbon stock values were clustered near the center top. Herbs, grasses, and soil constituents were found to be non-significant contributors to the local carbon stocks because they showed limited vector length on the PCA biplot (Fig. 6).

The provided image (Fig. 7) is a correlation matrix heatmap that visualizes the relationships between various carbon-related parameters across different locations. The heatmap includes parameters such as Soil Carbon Stock, Soil Carbon Stock Bulk Density, Plant Carbon Stock, and Plant Carbon Stock Biomass. Each of these parameters is measured at multiple sites, including University Lake, Shahapura Lake, Laharpur Dam, Kerwa Dam, Kaliasot Dam, Hataikhedha Dam, Char Imli Park, and Bhadbhada Dam. Scientific Description: Axes and Labels: Y-axis (Variable 1): Lists various parameters related to Soil Carbon Stock, Soil Carbon Stock Bulk Density, Plant Carbon Stock, and Plant Carbon Stock Biomass, each measured at different locations. X-axis (Variable 2): Mirrors the Y-axis, listing the same parameters and locations. Color Scale: Blue Shades: Indicate positive correlations (ranging from 0 to 1.0). Red Shades: Indicate negative correlations (ranging from 0 to -1.0). White: Represents no correlation (correlation coefficient around 0). Interpretation: Positive Correlations (Blue Shades): Strong positive correlations are represented by dark blue shades, suggesting that as one variable increases, the other variable also increases. For example, parameters like Plant Carbon Stock at various sites show high positive correlations with Plant Carbon Stock Biomass at corresponding sites, indicating that higher plant carbon stock tends to associate with higher plant biomass. Negative Correlations (Red Shades): Strong negative correlations are depicted by dark red shades, suggesting that as one variable increases, the other decreases. Some soil carbon stock bulk density measurements might show negative correlations with certain plant carbon stock measurements, indicating that higher soil bulk density could be associated with lower plant carbon stock. No Correlation (White): White areas indicate no significant linear relationship between the variables. Some parameters, particularly those from different sites, might show little to no correlation, suggesting independent variation. Statistical Significance (Asterisks): Asterisks (*) mark statistically significant correlations, indicating that the observed correlation is unlikely to be due to random chance. This is particularly useful for identifying which relationships are robust and worth further investigation. Summary: The heatmap provides a comprehensive overview of how different carbon-related parameters interact across various locations. The visualization helps identify patterns and relationships, such as: Consistent positive correlations between plant carbon stock and plant biomass at the same sites. Varied correlations between soil carbon stock and plant-related parameters, depending on the location and specific measurement. The presence of statistically significant correlations highlights important relationships that could inform further ecological or environmental studies. This correlation matrix heatmap is a valuable tool for identifying and interpreting the complex interdependencies between different ecological variables across multiple study sites.

In the box-plot tests the discrimination power of the parameters was examined by their degrees of interquartile (IQ) overlap in the box-plot tests. The box plots were based on the values between the reference sites and impaired sites for each index, and the 25% quartile (Q1), median values (Q2), and 75% quartile (Q3) of each “box” were compared. The parameters were considered to have significant discrimination if the Q2 of each “box” was not between Q1 and Q3 of the other “box”.

The image (Fig. 8) displays four box plots illustrating the variation in four different carbon-related parameters across four distinct sampling periods. The parameters evaluated are Plant Carbon Stock, Plant Carbon Stock Biomass, Soil Carbon Stock, and Soil Carbon Stock Bulk Density. The data is categorized by four sampling periods: 1st Sampling, 2nd Sampling, 3rd Sampling, and 4th Sampling, each distinguished by a unique color. Scientific Description of Each Box Plot: Plant Carbon Stock: Y-axis: Value (arbitrary units) X-axis: Sampling Period Sampling Periods: 1st Sampling: Red 2nd Sampling: Green 3rd Sampling: Cyan 4th Sampling: Purple Interpretation: The 1st Sampling period displays a lower median value compared to the other periods, with a relatively wide interquartile range. The 2nd Sampling period shows the highest median value and a moderate interquartile range. The 3rd Sampling period has a median value similar to the 2nd but with a narrower interquartile range. The 4th Sampling period indicates a lower median value, with the interquartile range indicating less variability compared to earlier periods. Plant Carbon Stock Biomass: Y-axis: Value (arbitrary units) X-axis: Sampling Period Sampling Periods: 1st Sampling: Red 2nd Sampling: Green 3rd Sampling: Cyan 4th Sampling: Purple Interpretation: The 1st Sampling period shows a relatively low median value with a moderate interquartile range. The 2nd Sampling period has the highest median value, indicating a significant increase in biomass, with a wide interquartile range. The 3rd Sampling period presents a high median value with considerable variability. The 4th Sampling period shows a decrease in the median value, with a moderate interquartile range. Soil Carbon Stock: Y-axis: Value (arbitrary units) X-axis: Sampling Period Sampling Periods: 1st Sampling: Red 2nd Sampling: Green 3rd Sampling: Cyan 4th Sampling: Purple Interpretation: The 1st Sampling period shows a moderate median value with some variability. The 2nd Sampling period has a slightly lower median value and reduced variability. The 3rd Sampling period shows an increase in the median value, with a broad interquartile range. The 4th Sampling period indicates the highest median value and the greatest variability, suggesting an increase in soil carbon stock over time. Soil Carbon Stock Bulk Density: Y-axis: Value (arbitrary units) X-axis: Sampling Period Sampling Periods: 1st Sampling: Red 2nd Sampling: Green 3rd Sampling: Cyan 4th Sampling: Purple Interpretation: The 1st Sampling period shows a moderate median value with some variability. The 2nd Sampling period has a slightly lower median value and reduced variability. The 3rd Sampling period shows an increase in the median value with a moderate interquartile range. The 4th Sampling period indicates the highest median value and variability, suggesting an increase in soil bulk density over time. Summary: These box plots provide a detailed visualization of the distribution and variability of Plant Carbon Stock, Plant Carbon Stock Biomass, Soil Carbon Stock, and Soil Carbon Stock Bulk Density across four different sampling periods. The variations in median values and interquartile ranges indicate dynamic changes in these parameters over time, highlighting potential trends in carbon sequestration and soil properties.

3.5 Discussion

The results of our research underline the pivotal role wetlands play in carbon sequestration through both plant biomass and soil organic matter. This discussion delves into the findings, comparing them with existing literature, exploring the implications for climate change mitigation, and identifying areas for further research. The study was conducted in eight wetlands of Bhopal where the carbon sequestration was measured with the help of biomass and carbon stock calculation of surrounding vegetation, here, herbs, shrubs, and grass. Some of the wetlands were scanty in vegetation (herbs, shrubs, and grass) like the Hataikheda Dam, while some of them sported medium vegetation like in Kaliasot Dam, and Laharpur Dam.

Our study demonstrated that wetland herb/grass biomass, including aboveground and belowground components, significantly contributes to carbon sequestration. The average biomass was calculated for each wetland and it ranged from 0.83 t/ha to 1.75 t/ha, and carbon stock it ranged between 0.41 t C/ha to 0.87 t C/ha, the lowest being recorded at University Lake and the highest at Kerwa Dam. This indicated that University Lake had the lowest mass present in the plants during the study and Kerwa Dam had plants having more biomass. Our study indicates that herbaceous wetlands have considerable potential for carbon storage, consistent with findings from similar studies (e.g., Mitsch & Gosselink, 2000; Bridgham et al., 2006). The aboveground biomass of herbs, though often seasonal, can sequester significant amounts of carbon during peak growing periods (Salunkhe et al., 2014). The belowground biomass, including roots and rhizomes, is particularly important for long-term carbon storage. These structures contribute to soil organic matter as they decay, enhancing soil carbon stocks over time. Herbaceous plants exhibit seasonal growth patterns, with carbon sequestration rates peaking during the growing season and declining during dormancy. This variability underscores the need for year-round monitoring to accurately assess annual carbon sequestration rates (Baggaley et al., 2022). Annual changes in climate conditions, hydrology, and nutrient availability can also influence the carbon sequestration potential of herbaceous wetlands. Our findings suggest that inter-annual variability should be considered in long-term carbon budgeting for these ecosystems. Herbaceous wetlands differ from forested wetlands, such as mangroves and peatlands, in terms of their carbon storage dynamics. Studies by Chmura et al., (2003) and Donato et al., (2011) have shown that while mangroves and peatlands are more effective in storing carbon aboveground, herbaceous wetlands can be equally effective when considering belowground carbon stocks.

Several factors can be blamed for these results as the University Lake though secluded but anthropogenic activities take place there. It is also a spot for cattle grazing and fishing activities and is quite polluted i.e., both the lake water and surrounding area. In the case of Kerwa Dam and Hataikheda Dam, fewer anthropogenic activities, reduced cattle grazing, a good amount of forest cover, and high temperatures as herbs store more biomass in high temperatures (Sangma et al., 2014) were in place.

Our results support the extensive body of literature on wetland soil carbon dynamics (Mitsch et al., 2013; Lal, 2004). The total carbon stock of each wetland was calculated by combining data on average carbon stock in herbs, shrubs, and grass (HGC) and soil organic carbon (SOC). It ranged from 16.34 t C/ha to 23.28 t C/ha. We know that in general terms, soil captures more carbon than vegetation in wetlands and the results showed that the SOC was greater than the carbon stock of vegetation (Khan et al., 2021). After combining the both, results showed that Kerwa dam had the highest stock of carbon stored followed by Hataikheda dam and Kaliasot dam and Laharpur dam was the one which stored the least amount of carbon.

Reasons that can be listed for Kerwa dam having the highest carbon stock include appropriate land use practices like less deforestation, less urbanization near the dam along with no to minimum soil tillage, optimum temperature and moisture content for more sequestration, minimum grazing, and pollution around. Laharpur dam, first and foremost was under constant tilling, covered with invasive weed all over i.e., water hyacinth, prominent cattle grazing and agricultural practices near the dam were observed which does not provide enough room for carbon capturing. CO₂ equivalent values ranged from 59.96 tons to 85.43 tons. Herbaceous wetlands play a crucial role in carbon sequestration through both aboveground and belowground biomass. Protecting and restoring these ecosystems is vital for enhancing their carbon storage capacity and mitigating climate change (Gautam and Mandal, 2016). Continued research and adaptive management are essential to optimize the carbon sequestration potential of herbaceous wetlands and to integrate them effectively into global carbon management strategies.

Wetlands act as the major carbon reservoirs on Earth. They play an important role in the circulation of different resources. Plants in the wetland take up atmospheric CO2 during photosynthesis and convert them into carbohydrates. In this way, atmospheric carbon dioxide will enter the food web and be consumed by other organisms. According to Ramsar secretariat about 1/3rd of the world terrestrial carbon is trapped and stored in wetlands, double of that of forests. This study highlights the importance of wetlands as a reliable source for capturing carbon and mitigating climate issues. Also, study of herbs, shrubs and grass has been generally ignored in the context of biomass and carbon sequestration that too in wetlands, as they comprise a small fraction in the whole process but they play an important role in the carbon cycle, therefore, more study is necessary as on a global level, they would be significant in carbon sequestration. Talking about the wetlands, they have the potential to sequester carbon and store it for long periods but it would take some necessary action to be taken in the first place. Sustainable land-use planning, considering the ecological value of wetlands, is crucial for their conservation. The integration of traditional ecological knowledge with scientific research can provide valuable insights into wetland management. Minimizing human interference and all related anthropogenic activities, strict laws enforcing no pollution near these sites, and restricting tourist spots are one way to go. Some wetlands such as Jawahar Bal Udyan Park, Bhadbhada Dam, and Laharpur Dam need urgent attention as they have been affected the most. Citizens should be made aware of our wetlands and how the wetlands can prove to be saviors in the crisis of climate change.

Acknowledgement:

We would like to thank the anonymous reviewers of the manuscript for their feedback, which helped us to improve the paper in multiple ways.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing Interest

The authors declare no competing interests.

Ethics approval and consent to participate

Not applicable.

Author Contributions

All authors shared experiences, wrote, and revised the manuscript in equal proportions.

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The authors declare no competing interests.

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Assessment of Carbon Sequestration by Herbs and Soil in Wetlands of Bhopal District of Central India

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Abstract

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1. INTRODUCTION

2. DATA AND METHODS

2.1.1 Study Area:

2.1.2 Sampling Design

2.2 Methodology

2.3 Statistical Analysis

3. RESULTS AND DISCUSSION

3.1 Biomass and Carbon Stock in Herbs or Grass

3.2 Bulk Density and Carbon Stock of Soil

3.3 Total Carbon Stock

3.4 Statistical calculation

3.5 Discussion

4. Conclusion

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