Dynamics of greenhouse gas fluxes and soil physico-chemical properties in agricultural and forest soils

Greenhouse gas (GHG) emissions in the atmosphere have been predicted to result in significant climatic and ecological consequences (IPCC 2021). Climate change can also have an impact on variance in soil consumption and the release of major GHGs (Blankinship et al. 2010; van Groenigen et al. 2011; Feng et al. 2022). GHGs such as carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) have been accumulating at an alarming rate in the atmosphere in recent decades as a result of human activity (IPCC 2021). A greater knowledge of GHG cycles is necessary for more accurate estimation of future global change, as climate-induced instability of ecosystem functioning (above- and below-ground biomass production; Hossain & Li 2020; Hossain et al. 2022; Jabal et al. 2022) may alter GHG fluxes in soils. For example, in recent years, carbon uptake in grassland (Hossain et al. 2022) and forest (Smith et al. 2020) ecosystems in Germany has been found to be affected by extreme droughts and heatwaves, which ultimately impair GHG fluxes by reducing soil organic matter in these ecosystems.

Organic matter retains over 1,500 Pg of carbon on the earth's surface, roughly double the amount of carbon retained in the atmosphere (Jin et al. 2000). As a result, both the carbon pool in soils and soil carbon loss through emissions have a significant effect on atmospheric CO₂ concentrations. A considerable influence on the process of carbon balance between the pedosphere and atmosphere is exerted by land use changes and soil degradation (Zhang et al. 2020). The nutrient cycles (i.e., carbon and nitrogen), as well as the variations in GHG concentrations that result from them, are significant components of the biogeochemical cycle (Ekeleme et al. 2021). Environmental worries are currently concentrated on the steadily increasing levels of these GHGs in the atmosphere (Hashimoto et al. 2011; IPCC 2021; Carrillo et al. 2022), which are primarily the result of human activity. Thus, concerns of GHG sinks and sources have risen to the top of the global priority list in recent years (Chang et al. 2021; Harris et al. 2021; Hossain & Li 2021a; Barthel et al. 2022). A closer examination of the organic carbon and nitrogen stored in the global GHG reservoir, as well as the processes that control it, will enable researchers to gain a better understanding of the soil carbon and nitrogen cycle's role in global warming and climate change (Hossain et al. 2021, 2023a, 2023b). Despite the growing evidence of climate change impacts on grassland and forest ecosystems (Hossain et al. 2021, 2023a, 2023b; Carrillo et al. 2022), understanding of how GHG fluxes in these ecosystems change under increasing frequency and intensity of extreme climatic conditions remains poorly defined. Numerous studies have been conducted on the local and regional scales to determine the relationship between soil organic carbon, nitrogen, and site factors (Hashimoto et al. 2011; Tellez-Rio et al. 2017; Harris et al. 2021; Barthel et al. 2022; Līcīte et al. 2022). These studies established that connections varied according to the land use types, vegetation types, environment, and soil types (Busman et al. 2023).

CO₂ is a notably powerful GHG, and soil respiration is the major pathway through which terrestrial ecosystems (e.g., forests, shrublands, and grasslands) release CO₂ into the atmosphere (Schlesinger & Andrews 2000). Net soil CO₂ exchange is a consequence of root respiration and decomposition, soil organic matter, and microbial community composition in the soil. A growing number of studies indicate that microbial communities can adapt their metabolic and substrate demands in response to available carbon and nitrogen (Manzoni et al. 2008; Eberwein et al. 2015). Methane accounts for more than 20% of the total radiative forcing of GHG emissions (IPCC 2013). Soil CH₄ emissions and consumption are influenced by a variety of factors, including moisture, oxygen, and nitrogen concentrations that are readily available in the soil (Aronson et al. 2013; Aronson et al. 2019). Environmental factors such as anaerobic conditions and the availability of precursor chemicals such as ammonia (NH₃), nitrite (NO₂), nitrate (NO₃), and nitric oxide (NO) encourage the production of N₂O and nitrogen gas (N₂). On the other hand, aerobic conditions, as well as the presence of ammonia (NH₃⁻) for ammonia oxidation and nitrite (NO₂⁻) for nitrite oxidation, enhance the production of N₂O and N₂ through the nitrification process.

Forest and agricultural soils are critical in terms of GHG sources and sinks (Hashimoto et al. 2011; Harris et al. 2021; Hossain & Li 2021b; Barthel et al. 2022). Forest soils act as a sink of CH₄ and a source of CO₂ and N₂O (van Groenigen et al. 2011). Despite agricultural soils sequestering large amount of carbon (4 × 10⁸ − 9 × 10⁸ Mg C yr⁻¹; Chen et al. 2016), this sector is thought to be a substantial source of GHGs worldwide, accounting for 10–12% of all anthropogenic GHGs (Tellez-Rio et al. 2017). Land use (e.g., agriculture and forest), and environmental conditions both influence GHG fluxes, rendering it susceptible to soil pH, organic nitrogen and carbon content, soil temperature and moisture, as well as the type and size of soil microbial communities (Braun et al. 2013; Aronson et al. 2019; Hossain & Li 2021a, 2021c). N₂O fluxes, for example, have been found to be significantly lower in grasslands in central Saskatchewan (Corre et al. 1999) than in cultivated soils in central Alberta (Nyborg et al. 1997) and in south central Saskatchewan (Izaurralde et al. 2004). This has been observed in both grassland and farmland locations throughout the world, including the United States (Dass et al. 2018), China (Genxu et al. 2002), and Central Europe (Hörtnagl et al. 2018). The amount of CO₂ released by vegetation and soil respiration varies depending on the type of vegetation, ranging from 1–15 kg C ha⁻¹ d⁻¹ in mixed grass prairie (LeCain et al. 2000) to 2–106 kg C ha⁻¹ d⁻¹ in tallgrass prairie (LeCain et al. 2000). Summer peak respiration rates in the mixed grass prairie range from 13 kg C ha⁻¹ d⁻¹ in Saskatchewan to 69 kg C ha⁻¹ d⁻¹ in North Dakota (Frank et al. 2002). Soils that have not been disturbed, on the other hand, consume CH₄ more frequently than they produce it (Wang & Bettany 1995). A mixed grass prairie in North Dakota absorbed 7.2 g of CH₄ ha⁻¹ d⁻¹ (Liebig et al. 2008).

For climate policy purposes, reliable quantification of the key GHGs is critical. As part of the Paris Climate Agreement, each signatory country is required to properly record GHG emissions from several fields, including farmland, forests, and other land uses. Additionally, countries must explore feasible GHG mitigation strategies, particularly establishing protected areas (Nila et al. 2019). Long-term GHG emissions measurements from different land uses, particularly agriculture and forest, are uncommon. In-situ data have the potential to adequately capture the small-scale variability of GHG emissions in agriculture and forest, which is necessary for stakeholders to receive targeted mitigation advice. The availability and consistency of such direct ecosystem GHG flow data are critical for evaluating the potential for GHG reductions associated with various management techniques (Luyssaert et al. 2014; Hörtnagl et al. 2018; Zhao et al. 2023). By understanding the relationships between soil properties, land use, and GHG fluxes, we can develop more effective strategies for mitigating GHG and promoting carbon sequestration in soil.

Soils are highly variable in their physico-chemical properties, which can influence GHG fluxes (Rütting et al. 2021). This variability can make it challenging to identify consistent relationships between soil properties and GHG emissions. GHG emissions from soils are influenced by a complex interplay of biotic and abiotic factors, including soil microbes, climate, and management practices. It can be challenging to disentangle the effects of these factors and identify the specific mechanisms that drive GHG emissions. Previous studies provide information on the relationships between GHG fluxes and soil properties at a single land use type (Drewer et al. 2021; Soosaar et al. 2022), however, the information on how these relationships may differ or be consistent across different land use types is poorly defined.

The study of GHG fluxes in soils is critical for understanding the relationships between soil physico-chemical properties and GHG emissions (Busman et al. 2023). The conceptual framework for this study is based on the premise that soil properties such as NH₄⁺, soil temperature, pH, soil organic carbon, total nitrogen, plant-available phosphorous, microbial biomass nitrogen, and bulk density may influence GHG fluxes from soils. These soil properties can be influenced by factors such as land use, management practices, and climate. Understanding the relationships between GHG fluxes and physico-chemical properties is crucial for several reasons. Firstly, it can help identify the drivers of GHG emissions in different ecosystems, which is essential for developing effective strategies to mitigate climate change. For instance, knowing that nitrogen fertilization in agricultural soils is a major source of N₂O emissions can inform the development of targeted fertilizer management practices to reduce emissions (Soosaar et al. 2022). Secondly, understanding the linkages between GHG fluxes and physico-chemical properties can help predict the response of ecosystems to environmental changes, such as climate variability or land use change. For example, changes in soil temperature or moisture due to climate change can alter the activity of soil microorganisms, leading to changes in GHG emissions. Thirdly, knowledge of the relationships between GHG fluxes and physico-chemical properties can help identify potential feedback between ecosystems and the climate system. For instance, increased CO₂ emissions from soil respiration due to climate warming can lead to further warming, creating a positive feedback loop. Overall, understanding the complex and multifaceted relationships between GHG fluxes and physico-chemical properties is essential for developing effective strategies to mitigate climate change and anticipate the impacts of environmental changes on ecosystems.

The theoretical framework for this study draws on existing theories related to soil biogeochemistry and microbial ecology. Soil biogeochemical processes such as nitrification and denitrification can contribute to N₂O emissions (Rütting et al. 2021), while methanogenesis and methanotrophy can influence CH₄ emissions. Microbial communities in soil play a crucial role in mediating these biogeochemical processes. The study also incorporates theories related to the physical properties of soil, such as soil porosity and bulk density, which can influence gas diffusion and transport in soil. The research framework proposes that GHG fluxes from soils are influenced by a complex interplay of biotic and abiotic factors. Forest and agricultural soils may exhibit different patterns of GHG fluxes due to differences in soil properties and management practices.

The study aims to (i) identify the specific soil physico-chemical properties that are strongly linked to GHG fluxes in different types of soils and (ii) quantify the changes in soil GHG fluxes in forest and agricultural soils. The overarching goal is to develop a more comprehensive understanding of the factors that drive GHG emissions from soils and to identify strategies for reducing these emissions.

The study identified specific soil properties such as NH₄⁺, soil temperature, pH, soil organic carbon, total nitrogen, plant-available phosphorous, microbial biomass nitrogen, and bulk density that are strongly linked with GHG fluxes in different types of soils. This information can be used to develop more targeted strategies for mitigating GHG emissions. The study identified forest soils as a CH₄ sink due to their negative CH₄ fluxes, which are connected with increased porosity and decreased bulk density. This finding highlights the potential role of forests in mitigating GHG emissions. The study provided insights into the complex interactions between soil properties and GHG emissions, highlighting the need for a more comprehensive approach to understanding the factors that drive GHG emissions from soils.

The scientific novelty of this research is the identification of specific physico-chemical properties that are closely linked with GHG fluxes in different types of soils. The study highlights the complex relationships between soil properties and GHG emissions and provides new insights into the mechanisms driving these relationships. The finding that forest soils have a higher CO₂ flux than agricultural soils and are a CH₄ sink due to negative CH₄ fluxes, while agricultural soils have a higher N₂O flux due to fertilizer application and heterotrophic nitrification, provides important information for understanding the differences in GHG emissions between these soil types. Additionally, the study identifies specific soil properties such as NH₄⁺, soil temperature, pH, soil organic carbon, total nitrogen, plant-available phosphorous, and microbial biomass nitrogen that are strongly linked with CO₂ and N₂O fluxes in agricultural soils, and with CH₄ fluxes in forest soils. This information can be used to develop more targeted strategies for mitigating GHG emissions in different types of soils, which could have important implications for climate change mitigation efforts. Overall, the study provides a valuable contribution to the scientific understanding of the relationships between soil properties and GHG emissions, and the potential for soil management practices to reduce these emissions.

The study was conducted on two land use types (agriculture and forest) in Goettingen, Germany. The study site is situated on the Nord (North) Campus, University of Goettingen in the Goettinger Wald (Lower Saxony, Germany) on a plateau around 400–420 m above sea level (Wolters 1999). The agriculture site (grassland ecosystems) was used for hay meadow production during the last 60 years, which received moderate fertilizers. In the forest site, the main tree species are beech (Fagus sylvatica) with a combination of ash (Fraxinus excelsior) and maple (Acer campestre). A considerable number of the regeneration, composed of broad-leaved species, was observed during the field study. The climate data were obtained from the Goettingen weather station, which is run by the German Weather Service. Goettingen has a mean annual air temperature of 7.9 °C and receives 720 mm of mean annual rainfall. According to the FAO and USDA classification systems, the soil is classified as Chromo-Calcic Cambisol and Lithic Rendoll, respectively (Wolters 1999). The bedrock is shell-lime, and the humus form is mull.

The parameters used in this study were chosen based on their known or potential relationships with GHG emissions and soil physico-chemical properties. The rationale behind the selection of each parameter is because of the following reasons. GHG fluxes are the focus of this study, as they are the ultimate indicator of soil emissions (Barthel et al. 2022). CO₂ is a product of respiration and decomposition, N₂O is produced during nitrification and denitrification, and CH₄ is produced during anaerobic decomposition. ECEC is a measure of the soil's ability to hold and release positively charged ions, which can influence nutrient availability and microbial activity. Total carbon and total nitrogen are important indicators of soil organic matter, which can influence nutrient cycling and microbial activity. Soil pH can influence microbial activity and nutrient availability, and it has been shown to influence GHG emissions. Bulk density is a measure of soil compaction, which can influence gas diffusion and transport in soil. Base saturation is a measure of the proportion of cation exchange sites that are occupied by basic cations such as calcium and magnesium, which can influence nutrient availability and microbial activity. WFPS is a measure of the amount of pore space in soil that is filled with water, which can influence gas diffusion and transport in soil. Plant-available phosphorus is an important nutrient for plant growth and can influence microbial activity. Microbial biomass C and N are important indicators of microbial activity, which can influence nutrient cycling and GHG emissions. Mineral N in NO₃ is an important indicator of nitrogen availability, which can influence microbial activity and GHG emissions. The microbial C:N ratio is a measure of the relative amounts of carbon and nitrogen in the microbial biomass, which can influence nutrient cycling and GHG emissions. Ammonium is an important source of nitrogen for plants and microbes, and can influence microbial activity and GHG emissions. Overall, the selected parameters represent a comprehensive set of indicators that can provide insight into the complex relationships between soil physico-chemical properties and GHG fluxes.

While the parameters used in this study provide a comprehensive set of indicators, there are several other parameters that could also be relevant for understanding the relationships between soil physico-chemical properties and GHG emissions. Some potential parameters that are not included in the study are: soil texture, land management practices, soil moisture, redox potential, soil enzymes, trace elements, and soil respiration. Although these parameters can influence nutrient availability, nutrient cycling, CO₂ production from soil, gas diffusion, and microbial activity, they may not have been deemed critical for understanding the relationships between the physico-chemical properties and GHG fluxes investigated in this study. However, future studies could explore the relationships between GHG fluxes and these additional parameters to further enhance our understanding of soil processes and GHG fluxes.

The bulk density of the soil was measured using the core method at a depth ranging from 0 to 5 cm (Blake & Hartge 1986). The soil-to-water ratio was 1:2.50 for the purpose of determining the pH of the soil. Because soils contain Triassic limestone, we utilized acid fumigation to remove carbonates from the limestone before analyzing the soil organic carbon (Harris et al. 2001). The C and N contents of three separate samples, including air-dried, ground, and acid fumigated soils, were determined using a CN analyser (Elementar Vario EL; Elementar Analysis Systems GmbH, Hanau, Germany). An inductively coupled plasma-atomic emission spectrometer was used to calculate resin-exchangeable P (iCAP 6300 Duo VIEW ICP Spectrometer, Thermo Fischer Scientific GmbH, Dreieich, Germany). The chloroform fumigation-extraction method was used to estimate soil microbial biomass C and N in the top 5 cm of depth. Soil samples were divided into two parts: one part with 0.5 M K₂SO₄ under laboratory conditions, and another part fumigated with CHCl₃ period of 5 days. Extraction was done after that. Organic C was analyzed in the extracts by using UV-enhanced persulfate oxidation with the use of a Total Organic Carbon Analyzer (TOC-Vwp, Shimadzu Europa GmbH, Duisburg, Germany). The organic nitrogen content of the extracts was measured using UV-enhanced persulfate digestion followed by hydrazine sulfate reduction and colorimetry with a continuous flow injection (Method G-157-96; SEAL Analytical AA3, SEAL Analytical GmbH, Norderstedt, Germany). Fumigated and unfumigated soils were separated by kC = 0.45 and kN = 0.68 during a 5-day fumigation period to determine the soil microbial biomass C and N, as well as the difference in organic C and N extraction (Brookes et al. 1985). From unfumigated soil extracts, using continuous flow injection colorimetry, NH₄⁺ and NO₃⁻ concentrations were determined (SEAL Analytical AA3, SEAL Analytical GmbH, Norderstadt, Germany); NH₄⁺ was determined using a salicylate and dicloroisocyanuric acid reaction (Autoanalyzer Method G-102-93); and NO₃⁻ was analyzed using the cadmium reduction method with NH₄Cl buffer (Autoanalyzer Method G-254-02).

GHG fluxes were measured using vented static chambers. All agricultural and forest sites were identified for the purpose of collecting gas samples utilizing chambers. Chambers were put into the soil and samples were collected every 10 min at 2, 12, 22, and 32 min. The sample of chamber gas was then transferred to 20 ml pre-evacuated glass vials (Exetainer; Labco Limited, Lampeter, UK). Within 48 h, the concentrations of the soil CO₂, N₂O, and CH₄ fluxes were determined using gas chromatography (GC 6000 Vega series 2, Carlo Erba Instruments, Milan, Italy). To determine gas concentrations, three to four standard gases were used to compare integrated samples (1,002, 2,999 and 4,998 for CH₄ ppb, 359, 1,004, and 1,601 for N₂O ppb, and 402, 1,501, and 3,008 for CO₂ ppb; Deuste Steiniger GmbH, Germany).

Negative fluxes depict the consumption of the gas by the soil, and positive gas fluxes represent the emission of the gas from the soil. As a control, zero fluxes were included.

The data were analyzed using statistical methods to determine the distribution characteristics of the GHG fluxes and physico-chemical parameters in forest and agricultural soils. The distribution characteristics of the statistics included the skewness, mean, standard deviation, standard error, confidence interval, and coefficient of variation, which have been shown in Table 1. Nash–Sutcliffe efficiency, root mean square error, and r-squared are the common metrics to evaluate the performance of the model, of which r-squared is widely used to measure the goodness of fit of a regression model and to identify the most important predictors in the model (Moriasi et al. 2007; Burgan & Aksoy 2022). As our study aims to assess the relationships between soil physico-chemical properties and GHG fluxes, we considered r-squared values to identify the most important predictors in the model for forest (Supplementary Table S1) and agricultural (Supplementary Table S2) soils. Statistical analyses were performed in R (R Development Core Team 2020). A Wilcoxon test was performed to explore the variations of GHG fluxes in two land use types (Wilcoxon 1945). Here, GHG fluxes were the dependent variables, and land use types were the independent variables. To investigate the degree of association between soil physico-chemical parameters and GHG fluxes in each land use type, we conducted a Pearson's correlation analysis (Das et al. 2023) using the ‘corrplot’ package in R (R Development Core Team 2020). For each land use category, a correlation matrix was created to represent the relationships between GHG fluxes and soil physico-chemical properties. The correlation matrix identifies the variables in the datasets that are highly associated. Each of the correlation coefficients was color-coded based on its value (blue for positive correlation, red for negative correlation) and displayed in the upper triangle of the correlogram. Using the ‘psych’ package, the p-values of Pearson's correlation coefficients between the variables were calculated and displayed.

Agricultural soils showed significantly higher ECEC, pH, bulk density, base saturation, WFPS, plant-available P, and microbial biomass C compared to forest soils (Table 2, all p < 0.05). However, the concentrations of total C, NH₄⁺, and microbial C:N ratio were significantly higher in forest soils than in agricultural soils (Table 2, all p < 0.05). Although forest soils showed higher total N than agricultural soils, the difference in concentration of total N between these two land use types was not significant (Table 2, p > 0.05). Likewise, microbial biomass C was higher in agricultural soils than in forest soils, but it was not significantly different between these two land uses (Table 2, p > 0.05).

The laboratory measurements of GHG fluxes were made from the collected samples of agricultural and forest lands. The results of this study show that there are significant differences in GHG fluxes between two land use types, with forest soils acting as a sink for CH₄ and having higher CO₂ fluxes compared to agricultural soils. The average CO₂ flux in forest soils was more than 4 times higher than in agricultural soils, indicating that forest soils have a higher rate of CO₂ production. For CO₂ fluxes, the pattern seen is that forests have higher concentrations than agricultural lands, which is consistent with previous findings (Dass et al. 2018; Aronson et al. 2019). This is likely due to the higher organic matter content and microbial biomass in forest soils, which can lead to higher rates of decomposition and respiration. The presence of litter, microbiological activity, and root activities all contributed to enhanced soil CO₂ fluxes in the forest (Van Straaten et al. 2011). Furthermore, fungi, living roots, and microorganisms all contribute to the increase in soil CO₂ fluxes in a similar manner. As there is no vegetative cover on an agricultural site, there is less microbial activity, which results in lower CO₂ fluxes. Because of the use of heavy machinery, the soil becomes more compact, reducing the amount of oxygen available in agricultural fields. The presence of oxygen has an effect on the process of respiration. The pace of decomposition is affected by a variety of parameters such as soil temperature, pH, soil texture, and water content (Aronson et al. 2013; Braun et al. 2013; Hossain & Beierkuhnlein 2018; Aronson et al. 2019), all of which have an impact on CO₂ fluxes (Dass et al. 2018).

Examination of fluxes of N₂O showed that N₂O concentrations were greater in the agricultural soils compared to the forest soils. This could be due to agricultural practices such as tillage, which can increase soil N₂O emissions. The input of fertilizer into agriculture may be one of the contributing factors, and this pattern is consistent with earlier research that has found fertilizer application to be correlated with N₂O fluxes (Jennifer et al. 2012). The presence of water in the pore space has an effect on N₂O fluxes as well. In our experiment, we found it within the range of 61.1–75.6%. It is well known that soil microorganisms are responsible for both the generation and consumption of N₂O (Davidson 1991; Aronson et al. 2019). The process of heterotrophic nitrification is carried out by bacteria and fungi, with a byproduct created by N₂O as a consequence (Dass et al. 2018). The nitrification process is crucial in the release of N₂O into the atmosphere, and it is also connected with the decrease of NO₂ in the environment (Poth & Focht 1985). The negative N₂O fluxes in forest soils indicate that these soils are taking up N₂O from the atmosphere, potentially due to denitrification occurring in anaerobic soil conditions.

The CH₄ fluxes also differed significantly between the land use types, with agricultural soils acting as a source of CH₄ emissions and forest soils acting as a sink. This could be due to the presence of anaerobic microsites in agricultural soils, which can support methanogenic microbial activity and lead to CH₄ emissions. It has been demonstrated in previous investigations that microorganisms create and consume CH₄ in the forest environment (Hashimoto et al. 2011; Harris et al. 2021). The release of CH₄ into the environment results in oxygen deficiency. Agricultural sites produce more methane than non-agricultural sites, despite the fact that microorganisms consume more of it. Land conversion has resulted in a reduction in methane uptake. In contrast, the high CH₄ uptake in forest soils could be due to the presence of methanotrophic microbial communities that can consume CH₄ from the atmosphere. High levels of CH₄ absorption in the forest are associated with high porosity and low bulk density in the forest. Methane is a significant trace gas because of its effects on global warming (Veldkamp et al. 2013), and as a result, the effects of methane on land use changes must be taken into consideration.

These findings highlight the importance of considering land use type in GHG mitigation strategies. Forest conservation and reforestation efforts could play a significant role in mitigating GHG emissions by acting as sinks for CO₂ and CH₄, while reducing agricultural practices that contribute to N₂O emissions could also help mitigate GHG emissions. Further research could investigate the underlying factors that drive GHG fluxes in different land use types, such as soil physico-chemical properties and microbial communities, to better inform land use management and mitigation strategies.

The differential findings of GHG fluxes in agricultural and forest soils necessitate the examination of variations in soil physico-chemical properties for several reasons. Firstly, the physico-chemical properties of soil, such as nutrient availability, soil moisture, and organic matter content, can influence the activity of soil microorganisms, which in turn affect GHG fluxes. For instance, nitrogen fertilization in agricultural soils can stimulate the activity of denitrifying bacteria, leading to higher N₂O emissions. Secondly, land use practices, such as tillage, crop rotation, and grazing, can alter soil physico-chemical properties and GHG fluxes. For example, forest soils tend to have higher porosity and lower bulk density than agricultural soils, which can enhance CH₄ uptake and reduce CO₂ emissions. Finally, climate and weather conditions, such as temperature and precipitation, can also influence both soil physico-chemical properties and GHG fluxes. For instance, higher temperatures can increase the activity of soil microorganisms, leading to higher GHG emissions. Overall, these complex and interconnected factors highlight the need for a comprehensive understanding of the variations of soil physico-chemical properties in different land use types to develop effective strategies for mitigating climate change.

The results of this study show that there are significant differences in soil properties between agricultural and forest soils (Table 2). Agricultural soils had significantly higher values for ECEC, pH, bulk density, base saturation, WFPS, plant-available P, and microbial biomass C compared to forest soils. These differences can be attributed to the differences in land use and management practices between these two types of soils. Agricultural soils are typically subjected to more intensive management practices, such as tillage and fertilization, which can lead to higher nutrient availability and microbial biomass. Organic matter is exposed in agricultural sites as a result of decomposition, and this has an impact on pH as well (Havlin et al. 2014). In the case of pH measurements, there are statistically significant differences between two land use types. The alkaline content of agricultural soil is higher, whereas the acidic content of forest soil is lower. Litter and plant residues are the elements that contribute to the high pH levels found in the forest. pH is regulated by the decomposition of organic matter in plants, microbial activity, and the release of ions, such as cations and anions (Xu et al. 2005). Furthermore, the ammonification process results in the production of hydroxyl ions, which causes the pH of the soil to rise (Xu et al. 2005). Consequently, it can be concluded that plant organic matter is the most important element influencing pH, which explains why our study discovered a difference between the two sites.

However, the concentration of total C, NH₄⁺, and microbial C:N ratio were significantly higher in forest soils than in agricultural soils. This suggests that forest soils have a higher level of organic matter accumulation and lower rates of mineralization compared to agricultural soils. The higher microbial C:N ratio in forest soils may indicate a slower rate of microbial decomposition, which could be due to the lower nutrient availability and lower levels of disturbance in forest soils. Although forest soils showed higher total N than agricultural soils, the difference was not significant. This could be due to the fact that N is a relatively mobile nutrient in soil and can be easily lost through leaching or volatilization. The higher microbial biomass C in agricultural soils compared to forest soils, although not significantly different, could indicate a higher level of microbial activity and nutrient cycling in agricultural soils.

It demonstrates that the bulk density of agricultural soils is higher than that of forest soils. Bulk density plays a critical role in the conductivity of soil carbon stocks (Blecourt et al. 2013). Organic matter has been depleted as a result of land use changes, and land that has been devoid of vegetation has become more vulnerable (Hossain 2022). As a result, soil erosion occurs, and the soil structure becomes weaker over time. As a result of the conversion process, the soil's porosity and bulk density rose, as reported by Kuykendall (2008). Agricultural soils become compacted as a result of the use of heavy machinery, resulting in a high bulk density on the agricultural site.

The total carbon in the soil was substantially higher in forest soils than it was in agricultural soils. A similar trend may be seen in the comparison between forests and plantations, with forests having higher carbon stocks than crop plantations (Blecourt et al. 2013). When comparing carbon stocks between agriculture and forest, the pattern is identical (Manning et al. 2015; Hörtnagl et al. 2018; Raturi et al. 2022). The presence of high carbon concentrations in the forest may be due to the presence of a low pH, as acidity increases, carbon concentrations in the site increase as well (Hörtnagl et al. 2018). When comparing two land use types that were relatively close to each other, the difference in nitrogen stocks was reported to be slightly higher for forest sites compared to agricultural sites.

It also demonstrates that soil microbial biomass carbon and nitrogen concentrations were higher in agricultural sites than in forest sites, respectively. However, because of the high root respiration and microbial activity in forests, it is expected that microbial biomass carbon will be higher in forests (Kemmitt et al. 2005). The ratio of microbial carbon to nitrogen was lower in the agricultural location. There is a relationship between the C:N ratio and the change in pH. The C:N ratio is growing, followed by acidity (Kemmitt et al. 2005). Previous studies found that the amount of ions rose as a result of the increase in pH (Hörtnagl et al. 2018; Harris et al. 2021).

Overall, these findings suggest that land use and management practices can have a significant impact on soil properties and nutrient cycling. Agricultural practices can lead to higher nutrient availability and microbial biomass, but also higher soil disturbance and potential for nutrient loss. In contrast, forest soils have a higher level of organic matter accumulation and lower nutrient availability, but also lower rates of disturbance and potential for nutrient loss. Understanding these differences in soil properties between land use types can help inform land management practices and nutrient management strategies to optimize soil health and productivity.

In this study, we found that all three GHG fluxes in agricultural soils showed significant correlations with all physio-chemical variables while they were significantly negatively correlated with bulk density, and microbial biomass C. These findings suggest that the physico-chemical properties of the soil play an important role in GHG fluxes from agricultural soils. This result is consistent with Aronson et al. (2019), which claimed that in addition to CH₄, CO₂, and N₂O fluxes, there are strong negative relationships between soil temperature and SOC and total N, and positive relationships of soil temperature with bulk density, microbial biomass C, pH, plant-available P, and microbial biomass N. Interestingly, there was a positive correlation between soil moisture and respiration. The negative correlation between GHG fluxes and bulk density suggests that compacted soils may reduce gas diffusion and increase the anaerobic conditions that favor GHG production. Similarly, the negative correlation between GHG fluxes and microbial biomass C suggests that microbial activity may play a role in GHG emissions from agricultural soils. CH₄ intake grew with increasing soil moisture content during dry conditions (Aronson et al. 2019). The maximum CO₂ generation was reported in depressions due primarily to their more favorable soil water conditions (Braun et al. 2013). Specifically, the resistance of grasslands to climate warming, droughts, and fire, together with the preference for carbon capture below ground, helps to protect terrestrial carbon sequestration. In contrast, California forests looked incapable of adapting to uncontrolled global climate change, converting from large carbon sinks to carbon sources by at least the middle of the 21st century (Dass et al. 2018). The results demonstrated that CO₂, N₂O, and CH₄ fluxes differed significantly between different sites. The soil GHG fluxes were substantially influenced by daily precipitation and soil temperature. Along a gradient of altitude, rainfall and soil temperature are positively correlated with soil GHG fluxes (Fatumah et al. 2019).

Our result showed that the CO₂ flux in forest soil showed strong positive correlations with soil temperature, microbial biomass N, and microbial biomass C, while ECEC, bulk density, and WFPS showed a negative correlation with the CO₂ flux in forest soils. This suggests that higher soil temperatures and greater microbial biomass may lead to increased CO₂ emissions from forest soils. This result is consistent with recent study findings (Carrillo et al. 2022), which reported that drought stress enhances CO₂ emission through increasing root decomposition in an experimental site in Australia. The N₂O flux in forest soils was negatively correlated with bulk density and pH. The positive correlations of N₂O flux with soil temperature, SOC, total N, ECEC, plant-available P, WFPS, microbial biomass N, and microbial biomass C were found. These findings are consistent with the findings of Sgouridis & Ullah (2017), which reported that the overall N₂O fluxes in the intensive grasslands were almost 40 times higher than those in the peatlands and were positively correlated with most of the soil physico-chemical properties. The amount that denitrification contributed to net N₂O emissions varied depending on the kind of land use and ranged anywhere from 9 to 60%. They also contended that the moisture content of the soil (e.g., aridity in grasslands: Hossain & Li 2023) was the most important factor in determining how N₂O sources were distributed. In contrast, Yan et al. (2018) found that a rise in precipitation resulted in a substantial increase in N₂O emissions (+154.0%) and CO₂ fluxes (+112.2%) while simultaneously resulting in a significant drop in CH₄ absorption (41.4%). With the exception of CO₂, there was no evidence of any geographical variation in the fluxes of GHGs. Positive connections were found between soil moisture and all GHG fluxes, with the exception of N₂O (Raturi et al. 2022). A significant increase in CO₂ and CH₄ fluxes was caused by an increase in surface temperature, as well as an increase in the moisture content of soil and manure. CH₄ fluxes were shown to be linked to all of the parameters, although the association with TN was by far the highest. It is interesting to note that the amount of N₂O fluxes had a weak but substantial inverse correlation with the amount of moisture present, total organic carbon, total nitrogen, microbial biomass C, and microbial biomass N (Liu et al. 2017). This finding has important implications for understanding the drivers of N₂O emissions from soils and developing strategies to mitigate these emissions. For example, management practices that increase soil moisture or add organic matter to the soil may help reduce N₂O emissions. Similarly, practices that promote microbial activity, such as adding nitrogen fertilizer or using cover crops, may also help reduce N₂O emissions.

Overall, these results highlight the importance of considering multiple GHG fluxes and soil physico-chemical properties when developing strategies to mitigate GHG emissions from land use practices. They also emphasize the need for continued research to better understand the complex interactions between soil and ecosystem processes and to inform more effective land management and policy decisions that promote both productivity and environmental sustainability. Practitioners should consider soil properties and management practices, such as reducing soil compaction and fertilizer application, to mitigate GHG emissions from land use practices.

Agricultural and forest soils are both sources and sinks of GHGs, and they have a considerable impact on the global budget of GHGs. Using observation data from the agricultural and forest soils, we estimated GHG fluxes, physico-chemical properties, and their relationships in the respective land use types in Gottingen, Germany. Higher CO₂ flux in forest soils compared to agricultural soils highlights that the presence of litter, living roots, and more microbial activities have enhanced soil CO₂ flux in forest floors. Conversely, higher N₂O flux in agricultural soils than that in forest soils suggests that the application of fertilizer may be the root cause of higher N₂O flux in agricultural soils, along with the heterotrophic nitrification process. Forest soils have been found to sink CH₄ as CH₄ fluxes in forest soils are negative, which is associated with higher porosity and lower bulk density in forest soils. The high porosity and low bulk density indicate high O₂ in the soils, thus leading to high activity of methanooxidizing bacteria in the forest soils. Agricultural soils showed a slight CH₄ source, as the CH₄ flux was positive in this land use. Irrespective of land use types, all three GHGs showed a differential correlation with soil physico-chemical properties. For instance, CO₂ and N₂O fluxes in agricultural soils were significantly positively correlated with NH₄⁺, soil temperature, pH, SOC, total N, plant-available P, WFPS, and microbial biomass N, while negatively correlated with bulk density and microbial biomass C. Unlike CO₂ and N₂O fluxes, CH₄ flux in agricultural soils showed opposite interactions with all physico-chemical variables. For forest soils, CO₂ and CH₄ fluxes showed positive relationships with soil temperature, microbial biomass C, and microbial biomass N, and N₂O flux was negatively correlated with bulk density and pH. This study implies that differences in soil physico-chemical properties and levels of microbial activity are the primary causes of the observed higher CO₂ and CH₄ but lower N₂O in forest soils compared to agricultural soils. Our study highlights the importance of considering land use type and soil properties in developing effective management practices to reduce GHG emissions. For example, reducing soil compaction and fertilizer application in agricultural soils and promoting high porosity and lower bulk density in forest soils can help reduce GHG emissions. This study provides valuable insights into the complex interactions between soil physico-chemical properties and GHG fluxes in forest and agricultural soils and can guide policy decisions to promote sustainable land management practices.

We would like to express our sincere gratitude to the students who participated in this study, providing invaluable assistance with fieldwork, data collection, and laboratory works. We are also grateful for the support of the Burckhardt Institute, Tropical Silviculture and Forest Ecology, Faculty of Forest Sciences and Forest Ecology, University of Göttingen, Göttingen, Germany, which provided resources to carry out this research. Without their contributions, this study would not have been possible. We would also like to acknowledge the valuable feedback and guidance provided by our colleagues, three anonymous reviewers, and editor, which helped to improve the quality and rigor of this work.

This work was supported by research grants from the Guangdong-Hong Kong Joint Laboratory for Water Security [project number 2020B1212030005] and the Research Grants Council of the Hong Kong Special Administrative Region, China [project number HKBU12301220].

Conceptualization: A.R., M.L.H., M.H.K.; Methodology: A.R., M.L.H.; Software: M.L.H., J.L.; Validation: A.R., M.L.H.; Visualization: M.L.H., M.H.K., M.M.A.S.; Formal analysis and investigation: M.L.H., J.L.; Writing – original draft preparation: A.R., M.L.H.; Writing – review and editing: M.L.H., M.H.K., M.M.H.S., M.M.A.S., J.L.; Resources: A.R., M.M.H.S.; Supervision: M.L.H., J.L., Funding acquisition: A.R., J.L.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.