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Article

Soil Organic Carbon Stock Assessment for Volunteer Carbon Removal Benefit: Methodological Approach in Chestnut Orchard for Fruit Production

1
Department of Agricultural and Food Sciences, Alma Mater Studiorum-University of Bologna, Viale Fanin 40, 40127 Bologna, Italy
2
Accademia Nazionale di Agricoltura, Via Castiglione 11, 40124 Bologna, Italy
*
Author to whom correspondence should be addressed.
Environments 2023, 10(5), 83; https://doi.org/10.3390/environments10050083
Submission received: 6 April 2023 / Revised: 3 May 2023 / Accepted: 6 May 2023 / Published: 9 May 2023
(This article belongs to the Special Issue Soil Organic Carbon Assessment)

Abstract

:
The implementation of a protocol for supporting a reliable soil C market is needed. This paper aims to propose a methodology for evaluating soil organic C (SOC) stock changes for the C credit market. A 15-year-old chestnut orchard (CO) and a chestnut coppice (CC) as reference land were selected in the northern part of the Apennine chain (Italy). The CO is the result of the CC conversion carried out in 2005. The soil sampling by pedogenetic horizons till parent material was carried out in 2005, 2010, 2015 and 2020 in CO and in 2005 and 2020 in CC. For each sample, the concentration and stock of the total SOC and of the most recalcitrant SOC form were estimated. Unlike the CC, in CO, an increase over time of SOC stocks was observed throughout the entire soil profile indicating the suitability of CO for C credit gaining. Most of the SOC was stored within the deepest soil horizon. The methodology can be considered eligible for the C credit market because, replicable, the CO was intentionally realized by humans after 1990, and the additionality was evaluated. Moreover, soil functionality was considered through the evaluation of SOC forms and of the pedogenetic horizons.

1. Introduction

The Paris Agreement, signed in 2015 by the member states of the United Nations Framework Convention on Climate Change (UNFCCC), contains policy obligations related to the actions against climate change for all countries of the world [1]. The main goal of the agreement is to keep the global mean air temperature increase below 2 °C compared to pre-industrial levels.
Driven by the European Green Deal, the European Mid-Century Strategies foresee net zero-greenhouse gas (GHG) emissions by 2050 [2], highlighting that CO2 emissions must be equal to or lower than the CO2 removal from the atmosphere. Soil, forests, and oceans are the main natural carbon sinks that could be capable of sequestering between 9.5 and 11 gigatons of CO2 per year. This is still not enough to offset the roughly 38 gigatons of CO2eq globally emitted [3]. To cope with this problem, technological solutions have been proposed to “sequester” CO2 both in agricultural and industrial sectors, whose effectiveness is still a field of debate [4].
In terrestrial ecosystems, carbon immobilization is mainly carried out by soil. Globally the organic C stored within soils is about 2.3 and 3.5 times greater than the C in the atmosphere and in all living terrestrial plants, respectively [5].
According to Orgiazzi et al. [6], in the European framework, the results of the land use and coverage area frame survey (LUCAS) project highlighted that agriculture soils had lower organic C amount (17.8 g kg−1, on average) than grassland and woodlands (on average 40.3 and 77.5 g kg−1, respectively). Moreover, the LUCAS project estimated that soils containing less than 2% organic carbon are about 75% of all European cultivated lands [7,8,9].
The overall loss of organic C from soils has raised many concerns [10,11,12,13]. In this regard, soil conservation and restoration practices appear to be very important in limiting organic C loss [14,15,16]. Several soil management proposals have been promoted with this purpose [17,18,19], and most of them also turn out to be climate change adaptation measures [20].
The land use, land use change and forestry (LULUCF) regulation (Reg. EU 842/2018) was adopted in the framework of energy and climate policy (2021–2030) with the main aim of reducing EU CO2 emissions by at least −40% by 2030 compared to 1990 [2]. According to the UNFCCC, LULUCF is a designation encompassing a broad range of activities, including agricultural and forest land management, agricultural land conversion, afforestation, reforestation, and avoided deforestation.
In this view, where many industrialized countries are taking measures to reduce their net emissions of GHGs, a carbon credit-trading scheme was adopted [21]. Generally, this trading involves corporations that buy C credits to offset their own C emissions elsewhere and sellers like landholders and natural ecosystem managers who deliver ecosystem services and commodities that are translated into C credits [22]. A carbon market needs public or private funding to change land management or use and to reduce GHG emissions or increase carbon sequestration and storage [23].
Over the last decade, the potential for sequestering C in agricultural and forestry sinks to generate C credits has received increased attention from policymakers, government and non-government organizations, private companies, and farm managers [22]. The interest in C sequestration mostly regarded soil [24,25,26]. However, nowadays, much uncertainty still remains about soil C estimation because it cannot be measured in the same way as point-source industrial emissions or the creation of above-ground biomass in forests. Therefore, the implementation of a measurement protocol for supporting a reliable soil C market is an important issue remaining to be resolved. In addition, despite bold claims about the potential of soil to sequester C, the science is still mixed on whether soil carbon sequestration is a viable climate solution, particularly in terms of the quantity of carbon that can be stored and for how long. Further, soil is a natural resource whose functions (i.e., C sequestration) strongly depend on pedogenetic factors such as land use, morphology, climate, geology and soil features. Therefore, to ensure that the soil carbon credits are high-quality and the practices that generate them are environmentally beneficial, the credits must undertake a thorough vetting process. Specifically, valuable protocols related to soil sampling and C measurements must be established; otherwise, the soil C market could become inhabited by loopholes that allow polluters to continue to pollute.

1.1. Land Use

The enhanced attention to the role of soil in the C market could push governments and companies to find lands to sequester carbon to avoid making real cuts to their CO2 emissions. In this sense, it is important to highlight the different potential of land use to store carbon [27,28]. Plenty of literature has reported the more significant role of soil under grasslands and forests in storing organic carbon compared to farmlands (e.g., Refs. [29,30,31]). The relatively low soil C storage of farmlands is attributed to the intensive agricultural practices, which are generally characterized by both low organic C and high N input promoting soil organic C loss by mineralization processes [15]. Because of the major role of natural lands (e.g., forestlands, grasslands, and wetlands) in soil organic C sequestration, the C market could create incentives for land-grabbing [32]. To avoid land-grabbing by governments and companies that want to apply their C sequestering projects in non-anthropic lands, the concept of additionality must be taken into account. Specifically, the additionality is the additional soil C sequestration related to the project compared to the C sequestration that can be observed under business-as-usual conditions [33]. This fact suggests the necessity to measure organic carbon concentrations also in “reference lands”, namely lands with similar features and management to those under the C credit market but not affected by the project, to grant only the C sequestered through the application of the project.
Although natural ecosystems are currently storing large amounts of soil organic carbon, agricultural soils have a higher potentiality to play such function compared to the soil of natural ecosystems, having lost in the past decades an important portion of their original soil organic carbon [34]. Because of this high potentiality, the C market should not be applied for land use change projects to avoid risks of food insecurity due to agricultural land reductions.

1.2. Climate

The climate, in terms of mean air temperature, is a key driver of soil organic C, whose accumulation is promoted where low temperatures occur [35]. In fact, more intense mineralization processes occur in warm areas promoting soil organic C loss [36,37]. Because of this, a larger soil organic C storage can be observed at higher latitudes and altitudes compared to the lower ones [36,38,39,40]. The major effect of soils in cold areas to store C might cause investments in forestry and agriculture to be addressed to improve their sustainability only at the northern latitudes. Further, the larger soil organic C storage in cold areas compared to warm ones might cause inequity within the C market system. Specifically, the C market will be more economically advantageous for landholders of cold areas.

1.3. Organic Carbon Forms

Soil organic C (SOC) comprises a large range of compounds characterized by a variable susceptibility to degradation. Some components are rapidly decomposed, whilst others decompose more slowly and accumulate in the soil over time. In this context, it is well recognized the major role of the physical protection mechanisms for SOC preservation [41,42]. Soil organic compounds can be physically protected within aggregates or adsorbed on the surfaces of mineral particles forming organo-mineral complexes [43,44,45,46,47]. These two mechanisms can shield organic compounds from microbial attack because of a physical barrier between the organic compounds and the decomposer. The processes of the inhibition of microbial access to the organic substrate allow the preservation of SOC for thousands of years [48]. In fact, the physically-protected organic C can have turnover times up to 1000 times longer (reaching 10,000 years) than the labile organic carbon [49,50]. Therefore, to get C credits, the physically-protected organic C forms should be considered. However, since soil is a living body [51], the practices addressed to accumulate SOC must also preserve the labile organic C forms. In fact, the labile organic compounds fuel the soil food web and affect nutrient cycles and many biologically related soil properties [52] other than contributing to the accumulation of soil organic C [53]. Further, the labile organic compounds are feed for soil microorganisms [54], which are recognized as an important precursor to the formation of stable SOC [55,56,57].

1.4. Soil Sampling

Appropriate sampling strategies and sampling units are prerequisites for the generation of robust soil organic C data. The sampling approach should reflect the variation of the target soil property (i.e., organic C) in the area under investigation. This is further emphasized by the complexity of the soil, whose properties are controlled by interactions of time, climate, geomorphology, parent materials, vegetation, and humans, which have not been well quantified [58]. To get C credits, temporal samplings are required though this sampling approach must cope with the soil variability, which could be solved by georeferencing the sampling points [59]. Although the natural ecosystems (e.g., forestlands and grasslands) are recognized to store more SOC compared to farmlands [29,30,31], to have comparable data about C accumulation/loss, the organic horizons should be excluded for the calculation of C credits. In fact, although the organic horizons have higher organic C concentrations compared to mineral ones [60,61], they are lacking in farmlands and their mass is characterized by seasonal variations [62].
Recently it has been demonstrated that the sampling by pedogenic horizon is considered more suitable compared to fixed depth layers in organic C assessment because it allows us to gain additional information on the nature of the SOC and the connections between the environment and C dynamics [61]. However, since the C credit market related to soil merely focuses on the amount of C accumulated/lost within a certain soil depth interval, soil sampling by fixed depth intervals can be considered optimal, mainly in an agricultural context, because of its ease of execution and cost-effectiveness.
Another issue related to soil sampling concerns the sampling depth. Several papers reported the major role of deep soil layers in storing C [63,64] and the higher amount of stable forms of C in the subsoil than in the topsoil [46,65]. However, at the global scale, most of the information and studies related to organic C stock refer to the upper 0.3 m of the soil profile [66,67,68]. A shallow sampling depth is usually chosen for financial and practical reasons [69]. Thus, to allow cheap samplings and easy comparisons with other soils, C credit can concern the topsoil layer.

1.5. Aim of the Study

In the framework of C sequestration, the aim of the present work was to propose a methodology for evaluating SOC stock changes for the voluntary C credit market. The proposed methodology was tested on a 15-year-old chestnut (Castanea sativa Mill.) orchard located in the Northern part of the Apennine chain (Italy) resulting from the conversion of a chestnut coppice after clear-cutting.

2. Materials and Methods

2.1. Area of the Study Case and an Example of Soil Sampling Model

In the present work, an area covered by chestnut (Castanea sativa Mill.) plants within the municipality of Alto Reno Terme in Italy was considered (Figure 1). The area was within the National Centre for the Study and Conservation of Forest Biodiversity, located at about 700 m above sea level and had a cold-temperate climate, with a mean annual precipitation of 905 mm and a mean annual air temperature of 12.2 °C (Ref. [70]). The soil was classified as Leptic Skeletic Dystric Regosol (Loamic, Humic) according to the World Reference Base [71].
Within the study area, a 15-year-old chestnut orchard for fruit production (CO) as testing land and a chestnut coppice (CC) as reference land (business-as-usual conditions) were selected (Figure 1). In 2020, the CC and CO had a density of 140 and 150 living stumps ha−1, respectively. The CO is the result of the conversion of CC carried out in 2004. Specifically, the CC was clear-cut in 2004, and the chestnut stumps of the clear-cut trees were grafted in 2005. In CO, the plants were pruned yearly, and the plant residues were shredded onto the soil’s surface. Instead, in CC, the stools are cut roughly every 20–25 years, while the understory is removed yearly and left on the soil’s surface. The choice to take into account the CC to CO conversion was based on the growing interest of farmers to restore chestnut stands [70]. Within CO and CC, a target area 1 ha wide was identified, which was theoretically divided into 4 plots 2500 m2 wide. Within each plot, four georeferenced soil profiles were dug till parent material, and each identified soil mineral horizon was sampled. For each plot, soil samples coming from similar soil horizon types were mixed to obtain a composite sample.
In CO, the soil sampling was performed at orchard establishment (in 2005; T0) and 5 (T1), 10 (T2) and 15 (T3) years later. Whilst, because of the unchanged land use, in CC, the sampling was performed in 2005 and 2020. For each sampling time, soil profiles were dug at about 0.5–1.0 m apart from the previous ones. All the samplings were carried out in July.
The litter layer (Oi) and the organic horizon Oe have not been taken into account for their possible transformations during the seasonal cycles [72,73,74] since they are mostly formed by non-stable organic C forms, which would bias the calculation of organic C stocks. Their mean thickness and organic C content are reported in Table 1.
In addition, undisturbed soil samples were collected by steel cylinders for the determination of the bulk density (BD). The collected samples were oven-dried at 105 °C, and then their mass was weighed. Because of the absence of skeleton in both sites, the bulk density was calculated by dividing the dry weight at 105 °C by the volume of the cylinder.

2.2. Soil Organic Carbon Estimation

All soil samples were air-dried and sieved through a 2 mm mesh to divide skeleton (Ø > 2 mm) from the fine earth (Ø ≤ 2 mm).
The different forms of organic carbon were determined by the loss-on-ignition (LOI) method, according to Schulte and Hopkins [75] and Cambardella et al. [76]. Specifically, 6 g of fine earth was placed in ceramic crucibles and heated at 105 °C for 12 h to remove soil moisture and at 160 °C to remove the interstitial water. The soil organic matter (SOM) was determined at 450 °C, while the recalcitrant organic carbon (ROC) was determined at 550 °C. Two replicates per sample were analyzed in analytical assays to reduce the analytical error.
The organic C forms were calculated as follows:
Interstitial   water   % = P 105   ° C P 160   ° C P 105   ° C × 100
Soil   organic   carbon   ( SOC )   % = P 160   ° C P 450   ° C P 105   ° C × 100 × 1 1.72
Recalcitrant   organic   carbon   ( ROC ) = P 450   ° C P 550   ° C P 105   ° C × 100
The stock of organic C and recalcitrant organic C (SOCstock and ROCstock, respectively) were calculated by the following equation (FAO, 2019):
Stock = C   × BD   × thickness   × ( 1 sk ) × 10
where stock is SOCstock or ROCstock expressed as Mg ha−1, C is SOC or ROC content expressed as g kg−1, BD is bulk density expressed as Mg m3, thickness refers to the 0–30 cm depth or horizon thickness expressed as m, and sk is the volume of skeleton expressed as a percentage.

3. Results

In 2005, the soil under CO had weaker soil development compared to CC, showing the lack of B-like horizons and a thinner A horizon. Conversely, the C horizon showed a larger thickness under CO than under CC. In addition, the A horizon thickness in CO increased from T0 to T1, while the C horizon thickness did not change over time (Table 2). Further, the results showed a higher stock of both SOC and ROC within the deepest soil horizon. No over-time changes in horizons’ thickness were observed in CC. The SOCstock of CO showed an over-time increase, with values that were 108% higher in 2020 compared to 2005 (Table 3). Conversely, the SOCstock in CC did not change from 2005 to 2020 (Table 3). Noteworthy, although at T0, the CO had a lower SOCstock compared to CC, at T3, the SOCstock values resulted in being higher in CO than in CC. Similar to SOCstock, an over-time increase of ROCstock within the 0–30 soil interval depth was observed under CO (116%), whilst the increase under CC was negligible (Table 3).
Taking into consideration the pedogenic horizons, while under CC, the SOCstock and ROCstock values did not change between 2005 and 2020, under CO, the stock values increased for each soil horizon with higher increasing rates for ROCstock compared to SOCstock. Specifically, from 2005 to 2020, the SOCstock increased by 172, 113, and 79% in the A, AC, and C horizons, respectively, and the ROCstock increased by 327, 196, and 89% in the A, AC, and C horizons, respectively.

4. Discussion

According to the IPCC guidelines, the methodology used for the present study can be considered eligible for the C credit market. In fact, the conversion of CC to CO took place later than 1990 and generated a co-benefit for other ecosystem functions such as food production. The additionality criterium was addressed because the CC was set as a baseline that accurately reflects the standard practices. In order to avoid biases over time, the baseline conditions have been updated through the sampling carried out in 2020. Also, the present study can be considered eligible for the C credit market because the methodology used for soil sampling and carbon quantification can be considered robust and replicable. In addition, the present study matched with the proposal for the first EU-wide voluntary framework to reliably certify high-quality carbon removals adopted by European Commission [77]. In fact, the QU.A.L.ITY criteria of quantification, additionality, long–term storage and sustainability [77] were addressed.
Further, in accordance with LULUCF [78], the change from CC to CO can be included within the “land converted to cropland” category due to the conversion of land from natural states to cropland.
The scarce soil development (i.e., lack of B-like horizons and a thinner A horizon) in CO can be attributed to clearcutting practices carried out before CO establishment. In fact, clearcutting can cause the acceleration of the soil erosion processes in mountainous areas [79], and therefore it can prevent soil development [80]. The likely higher soil erosion processes that occurred after clearcutting might explain the lower SOCstock in CO compared to CC in 2005 [81].
The roughly 5.7 Mg ha−1 yr−1 increase of organic C stock observed down to 30 cm soil depth between 2005 and 2020 in CO highlights the key role of soil on C sequestration. The SOCstock increasing rate resulted in being 3.8 Mg ha−1 yr−1 if the CC soil sampled in 2005 was considered. In both cases, such increasing rates were within the range found by previous studies conducted worldwide, both in natural and agricultural lands [82,83,84,85]. The observed soil organic C stock increase fits with the targets of the “4per1000 initiative: Soils for Food Security and Climate” in the United Nations Framework Convention for Climate Change: Conference of the Parties (UNFCCC-COP 21) in Paris. In fact, this plan of action proposed to increase on average globally 0.6 Mg of C ha−1 yr−1 to compensate for the annual CO2-C emissions from fossil fuels [86,87]. In addition to these comforting results, in the present paper, we considered the deepest soil layers, which are recognized to have a noticeable role in organic C sequestration [88,89]. In fact, subsoil is characterized by lower amounts of available oxygen and microbial biomass and higher amounts of no–saturated soil mineral particles, which prevent organic C mineralization and promote C stabilization processes [90]. Despite this, the subsoil is considered susceptible to land use change and management [88,89,91,92,93], which, if not appropriate, could reduce its carbon stock. This fact would point out that the soil organic carbon storage implementation under the carbon credit initiative is feasible, assuming the entire soil profile by applying economically viable agronomic practices and good environmental practices. In our case, the conversion from CC to CO increased the organic C stock from 2005 to 2020 within both the uppermost soil horizon and the deepest ones. Because of the slower turnover of organic C of subsoil compared to that of topsoil [94], the C credit market should pay more attention to the former than to the latter. In this sense, the increase of organic C stock within the subsoil pedogenic horizons of the considered study sites would draw a picture of where chestnut orchards can be considered suitable to gain carbon credits.
Within the CO, the observed increase of SOC concerned both the labile and the most stable form (ROC). The increased amounts of both organic C forms can be considered suitable in view of soil functioning. Specifically, the labile fraction of SOC is considered a quickly reactive indicator of soil fertility and health, acting as an energy supply for soil microorganisms, a short-term reservoir of nutrients and a food source for soil fauna [95]. Therefore, keeping high labile organic C concentrations in the soil can allow for maintaining crop performance and food security. The stable organic C that can be found in both the chemically-recalcitrant and physically-protected forms [96,97,98,99,100,101] helps soil function as a long-term carbon sink. Therefore, in a wider view of soil management practices addressed to increase organic C stock, the application to soil of organic fertilizers should ensure the provisioning of labile organic C other than of the stable one to preserve the soil microbial community. However, the application of organic fertilizers with a high amount of labile organic forms could boost the mineralization of the SOC, including the stable forms [102,103].
Within the CO, most of the organic C stock increase was observed 5 years after plantation, while this rate decreased in the following years. The changing of the C storage rate pointed out the importance of taking into consideration at least 10 years as the time frame for the evaluation of C change into the soil to avoid C credit overestimation. This fact is in accordance with previous studies [104,105,106,107,108], which proposed 10–15 years as the time frame for soil carbon credit calculation.
However, it is important to highlight that in the considered CO, the soil surface was covered by grasses, while plant residues were left on the soil’s surface and shredded. In fact, previous papers reported the important role of grasses in increasing soil organic C content because of their contribution to both organic C input and soil erosion prevention [109,110,111]. Similarly, plenty of literature can be found on the importance of plant residue preservation on the soil’s surface for SOC accumulation [112,113].
The proposed soil sampling scheme used within the selected orchards was in accordance with that suggested by previous studies [114,115]. Specifically, in our proposed methodology, one composite soil sample was collected for an area of 2500 m2. This sampling can be considered ideal for obtaining reliable and representative values about soil properties [114,115]. Further, the use of a relatively small sampling grid is optimal for soil properties assessment because of their high spatial variability [116,117,118].
Regarding the soil sampling methodology, in the present investigation, the soil samples were collected from each identified pedogenic horizon. The B horizons were not observed in CO, likely due to the intense erosion processes that occurred after clear-cutting [119,120]. Despite this, it is important to mention that combining C evaluation with the identification of pedogenic soil horizons should be recommended. It is recognized how the factors of pedogenesis influence soil processes and, in turn, the organization of soil in terms of horizon types [71]. Such an organization has economic value because the processes occurring within the horizons determine soil functionality and produce ecosystem services [121]. In this sense, human activities can negatively modify horizons’ development with the consequence of soil degradation [122]. Therefore, to avoid loss of soil pedodiversity and functionality due to soil degradation processes [122,123], the forest and agricultural practices addressed to increase soil organic carbon stock must prevent the loss of the pedogenic horizons. This fact, within the soil carbon credit framework, will result in the payment of carbon credits only for those stakeholders that promote carbon accumulation, preserving the pedogenic horizons.

5. Conclusions

The present study proposes a reliable methodology helpful for improving the protocols for crediting soil carbon. The proposed methodology can be considered eligible for the C credit market. In fact, the conversion of CC to CO took place later than 1990 and generated a co-benefit for other ecosystem functions such as food production. The additionality criterium was addressed because the CC was set as a baseline that accurately reflects the standard practices. In order to avoid biases over time, the baseline conditions have been updated through the sampling carried out in 2020. Also, the present study can be considered eligible for the C credit market because the methodology used for soil sampling and carbon quantification can be considered robust and replicable.
Besides this, the proposed methodology would result in being accurate from an environmental point of view because both SOC forms and the organic C related to the pedogenetic horizons were considered. In fact, the evaluation of such properties allows us to understand the influence of treatment on soil functionality. Specifically, besides the treatment should promote soil C storage, it should preserve the other soil functions (e.g., to support soil microbial community and its activity). In addition, the proposed methodology highlighted the importance of subsoil within the C credit market mainly because the subsoil is recognized to have a noticeable role in organic C sequestration. Concerning CO, it can be considered suitable to gain carbon credits in mountainous areas. In fact, a quite rapid increase of both SOCstock and ROCstock was observed. Further, a large increase in both stocks was observed within the deeper soil horizons.

Author Contributions

Conceptualization, G.V.; methodology, G.V. and M.D.F.; validation, L.V.A.; investigation, G.V.; resources, L.V.A.; data curation, G.V.; writing—original draft preparation, M.D.F.; writing—review and editing, M.D.F., G.V. and L.V.A.; visualization, G.V. and M.D.F.; supervision, L.V.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available upon request from the corresponding author.

Acknowledgments

We acknowledge the National Centre for the Study and Conservation of Forest Biodiversity of Alto Reno Terme (Italy) that allowed us to conduct this study.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Dimitrov, R.S. The Paris agreement on climate change: Behind closed doors. Glob. Environ. Polit. 2016, 16, 1–11. [Google Scholar] [CrossRef]
  2. Eurpean Commission. 773 A Clean Planet for All—A European Long-Term Strategic Vision for a Prosperous, Modern, Competitive and Climate Neutral Economy; Eurpean Commission: Brussels, Belgium, 2018.
  3. Friedlingstein, P.; Jones, M.W.; Andrew, R.M.; Bakker, C.E.; Hauck, J.; Le Quéré, C.; Peters, G.P.; Pongratz, J.; Sitch, S.; Canadell, J.G.; et al. Carbon budget and trends 2021. Clemens Schwingshackl 2021, 19, 66. [Google Scholar]
  4. Hepburn, C.; Adlen, E.; Beddington, J.; Carter, E.A.; Fuss, S.; Mac Dowell, N.; Minx, J.C.; Smith, P.; Williams, C.K. The technological and economic prospects for CO2 utilization and removal. Nature 2019, 575, 87–97. [Google Scholar] [CrossRef] [PubMed]
  5. Lal, R. Soil Carbon Sequestration Impacts on Global Climate Change and Food Security. Science 2004, 304, 1623–1627. [Google Scholar] [CrossRef] [PubMed]
  6. Orgiazzi, A.; Ballabio, C.; Panagos, P.; Jones, A.; Fernández-Ugalde, O. LUCAS Soil, the largest expandable soil dataset for Europe: A review. Eur. J. Soil Sci. 2018, 69, 140–153. [Google Scholar] [CrossRef]
  7. De Brogniez, D.; Ballabio, C.; Stevens, A.; Jones, R.J.A.; Montanarella, L.; van Wesemael, B. A map of the topsoil organic carbon content of Europe generated by a generalized additive model. Eur. J. Soil Sci. 2015, 66, 121–134. [Google Scholar] [CrossRef]
  8. Panagos, P.; Ballabio, C.; Yigini, Y.; Dunbar, M.B. Estimating the soil organic carbon content for European NUTS2 regions based on LUCAS data collection. Sci. Total Environ. 2013, 442, 235–246. [Google Scholar] [CrossRef]
  9. Lugato, E.; Panagos, P.; Bampa, F.; Jones, A.; Montanarella, L. A new baseline of organic carbon stock in European agricultural soils using a modelling approach. Glob. Chang. Biol. 2014, 20, 313–326. [Google Scholar] [CrossRef]
  10. Rumpel, C.; Amiraslani, F.; Chenu, C.; Garcia Cardenas, M.; Kaonga, M.; Koutika, L.S.; Ladha, J.; Madari, B.; Shirato, Y.; Smith, P.; et al. The 4p1000 initiative: Opportunities, limitations and challenges for implementing soil organic carbon sequestration as a sustainable development strategy. Ambio 2020, 49, 350–360. [Google Scholar] [CrossRef]
  11. Lavallee, J.M.; Soong, J.L.; Cotrufo, M.F. Conceptualizing soil organic matter into particulate and mineral-associated forms to address global change in the 21st century. Glob. Chang. Biol. 2020, 26, 261–273. [Google Scholar] [CrossRef]
  12. Ofiti, N.O.E.; Zosso, C.U.; Soong, J.L.; Solly, E.F.; Torn, M.S.; Wiesenberg, G.L.B.; Schmidt, M.W.I. Warming promotes loss of subsoil carbon through accelerated degradation of plant-derived organic matter. Soil Biol. Biochem. 2021, 156, 108185. [Google Scholar] [CrossRef]
  13. Stockmann, U.; Adams, M.A.; Crawford, J.W.; Field, D.J.; Henakaarchchi, N.; Jenkins, M.; Minasny, B.; McBratney, A.B.; de Remy de Courcelles, V.; Singh, K.; et al. The knowns, known unknowns and unknowns of sequestration of soil organic carbon. Agric. Ecosyst. Environ. 2013, 164, 80–99. [Google Scholar] [CrossRef]
  14. Lal, R. Managing soils for negative feedback to climate change and positive impact on food and nutritional security. Soil Sci. Plant Nutr. 2020, 66, 1–9. [Google Scholar] [CrossRef]
  15. Abbas, F.; Hammad, H.M.; Ishaq, W.; Farooque, A.A.; Bakhat, H.F.; Zia, Z.; Fahad, S.; Farhad, W.; Cerdà, A. A review of soil carbon dynamics resulting from agricultural practices. J. Environ. Manag. 2020, 268, 110319. [Google Scholar] [CrossRef]
  16. Montanarella, L.; Panagos, P. The relevance of sustainable soil management within the European Green Deal. Land Use Policy 2021, 100, 104950. [Google Scholar] [CrossRef]
  17. Lal, R. Soil carbon sequestration to mitigate climate change. Geoderma 2004, 123, 1–22. [Google Scholar] [CrossRef]
  18. FAO—Food and Agriculture Organization. Manual on Integrated Soil Management and Conservation Practices; Food and Agriculture Organization: Yokohama, Japan, 2000; Volume 8, p. 214.
  19. Smith, P. Soils and climate change. Curr. Opin. Environ. Sustain. 2012, 4, 539–544. [Google Scholar] [CrossRef]
  20. Hjerp, P.; Volkery, A.; Lückge, H.; Medhurst, J.; Hart, K.; Medarova-Bergstrom, K.; Tröltzsch, J.; McGuinn, J.; Skinner, I.; Desbarats, J.; et al. Methodologies for Climate Proofing Investments and Measures under Cohesion and Regional Policy and the Common Agricultural Policy; Institute for European Environmental Policy: Bruxelles, Belgium, 2012; p. 279. [Google Scholar]
  21. Michaelowa, A.; Shishlov, I.; Brescia, D. Evolution of international carbon markets: Lessons for the Paris Agreement. Wiley Interdiscip. Rev. Clim. Chang. 2019, 10, e613. [Google Scholar] [CrossRef]
  22. Williams, J.R.; Peterson, J.M.; Mooney, S. The value of carbon credits—Is there a final answer. J. Soil Water Conserv. 2005, 60, 36A–40A. [Google Scholar]
  23. Venter, O.; Laurance, W.F.; Iwamura, T.; Wilson, K.A.; Fuller, R.A.; Possingham, H.P. Harnessing carbon payments to protect biodiversity. Science 2009, 326, 1368. [Google Scholar] [CrossRef]
  24. Lal, R. Sequestering carbon in soils of agro-ecosystems. Food Policy 2011, 36, S33–S39. [Google Scholar] [CrossRef]
  25. Davidson, E.A. Is the transactional carbon credit tail wagging the virtuous soil organic matter dog? Biogeochemistry 2022, 161, 1–8. [Google Scholar] [CrossRef]
  26. Perez, C.; Roncoli, C.; Neely, C.; Steiner, J.L. Can carbon sequestration markets benefit low-income producers in semi-arid Africa? Potentials and challenges. Agric. Syst. 2007, 94, 2–12. [Google Scholar] [CrossRef]
  27. Bellamy, P.H.; Loveland, P.J.; Bradley, R.I.; Lark, R.M.; Kirk, G.J.D. Carbon losses from all soils across England and Wales 1978–2003. Nature 2005, 437, 245–248. [Google Scholar] [CrossRef]
  28. Lettens, S.; Van Orshoven, J.; van Wesemael, B.; Muys, B. Soil organic and inorganic carbon contents of landscape units in Belgium derived using data from 1950 to 1970. Soil Use Manag. 2004, 20, 40–47. [Google Scholar] [CrossRef]
  29. Chen, S.; Martin, M.P.; Saby, N.P.A.; Walter, C.; Angers, D.A.; Arrouays, D. Fine resolution map of top- and subsoil carbon sequestration potential in France. Sci. Total Environ. 2018, 630, 389–400. [Google Scholar] [CrossRef]
  30. Ostle, N.J.; Levy, P.E.; Evans, C.D.; Smith, P. UK land use and soil carbon sequestration. Land Use Policy 2009, 26, S274–S283. [Google Scholar] [CrossRef]
  31. Soleimani, A.; Hosseini, S.M.; Massah Bavani, A.R.; Jafari, M.; Francaviglia, R. Influence of land use and land cover change on soil organic carbon and microbial activity in the forests of northern Iran. Catena 2019, 177, 227–237. [Google Scholar] [CrossRef]
  32. Lyons, K.; Westoby, P. Carbon colonialism and the new land grab: Plantation forestry in Uganda and its livelihood impacts. J. Rural Stud. 2014, 36, 13–21. [Google Scholar] [CrossRef]
  33. Thamo, T.; Pannell, D.J. Challenges in developing effective policy for soil carbon sequestration: Perspectives on additionality, leakage, and permanence. Clim. Policy 2016, 16, 973–992. [Google Scholar] [CrossRef]
  34. Stavi, I.; Lal, R. Agroforestry and biochar to offset climate change: A review. Agron. Sustain. Dev. 2013, 33, 81–96. [Google Scholar] [CrossRef]
  35. Wiesmeier, M.; Urbanski, L.; Hobley, E.; Lang, B.; von Lützow, M.; Marin-Spiotta, E.; van Wesemael, B.; Rabot, E.; Lieβ, M.; Garcia-Franco, N.; et al. Soil organic carbon storage as a key function of soils—A review of drivers and indicators at various scales. Geoderma 2019, 333, 149–162. [Google Scholar] [CrossRef]
  36. Garten, C.T. Comparison of forest soil carbon dynamics at five sites along a latitudinal gradient. Geoderma 2011, 167–168, 30–40. [Google Scholar] [CrossRef]
  37. Nottingham, A.T.; Whitaker, J.; Ostle, N.J.; Bardgett, R.D.; McNamara, N.P.; Fierer, N.; Salinas, N.; Ccahuana, A.J.Q.; Turner, B.L.; Meir, P. Microbial responses to warming enhance soil carbon loss following translocation across a tropical forest elevation gradient. Ecol. Lett. 2019, 22, 1889–1899. [Google Scholar] [CrossRef]
  38. Massaccesi, L.; De Feudis, M.; Leccese, A.; Agnelli, A. Altitude and vegetation affect soil organic carbon, basal respiration and microbial biomass in apennine forest soils. Forests 2020, 11, 710. [Google Scholar] [CrossRef]
  39. Ziegler, S.E.; Benner, R.; Billings, S.A.; Edwards, K.A.; Philben, M.; Zhu, X.; Laganière, J. Climate warming can accelerate carbon fluxes without changing soil carbon stocks. Front. Earth Sci. 2017, 5, 2. [Google Scholar] [CrossRef]
  40. Dorji, T.; Odeh, I.O.A.; Field, D.J. Vertical distribution of soil organic carbon density in relation to land use/cover, altitude and slope aspect in the Eastern Himalayas. Land 2014, 3, 1232–1250. [Google Scholar] [CrossRef]
  41. Dungait, J.A.J.; Hopkins, D.W.; Gregory, A.S.; Whitmore, A.P. Soil organic matter turnover is governed by accessibility not recalcitrance. Glob. Chang. Biol. 2012, 18, 1781–1796. [Google Scholar] [CrossRef]
  42. Six, J.; Paustian, K. Aggregate-associated soil organic matter as an ecosystem property and a measurement tool. Soil Biol. Biochem. 2014, 68, A4. [Google Scholar] [CrossRef]
  43. Wissing, L.; Kölbl, A.; Schad, P.; Bräuer, T.; Cao, Z.H.; Kögel-Knabner, I. Organic carbon accumulation on soil mineral surfaces in paddy soils derived from tidal wetlands. Geoderma 2014, 228–229, 90–103. [Google Scholar] [CrossRef]
  44. Kaiser, K.; Guggenberger, G. Mineral surfaces and soil organic matter. Eur. J. Soil Sci. 2003, 54, 219–236. [Google Scholar] [CrossRef]
  45. Pulleman, M.M.; Marinissen, J.C.Y. Physical protection of mineralizable C in aggregates from long-term pasture and arable soil. Geoderma 2004, 120, 273–282. [Google Scholar] [CrossRef]
  46. De Feudis, M.; Cardelli, V.; Massaccesi, L.; Trumbore, S.E.; Vittori Antisari, L.; Cocco, S.; Corti, G.; Agnelli, A. Small altitudinal change and rhizosphere affect the SOM light fractions but not the heavy fraction in European beech forest soil. Catena 2019, 181, 104091. [Google Scholar] [CrossRef]
  47. Schrumpf, M.; Kaiser, K.; Guggenberger, G.; Persson, T.; Kögel-Knabner, I.; Schulze, E.D. Storage and stability of organic carbon in soils as related to depth, occlusion within aggregates, and attachment to minerals. Biogeosciences 2013, 10, 1675–1691. [Google Scholar] [CrossRef]
  48. Von Lützow, M.; Kögel-Knabner, I.; Ludwig, B.; Matzner, E.; Flessa, H.; Ekschmitt, K.; Guggenberger, G.; Marschner, B.; Kalbitz, K. Stabilization mechanisms of organic matter in four temperate soils: Development and application of a conceptual model. J. Plant Nutr. Soil Sci. 2008, 171, 111–124. [Google Scholar] [CrossRef]
  49. Torn, M.S.; Trumbore, S.E.; Chadwick, O.A.; Vitousek, P.M.; Hendricks, D.M. Mineral control of soil organic carbon storage and turnover. Nature 1997, 389, 170–173. [Google Scholar] [CrossRef]
  50. Kleber, M.; Eusterhues, K.; Keiluweit, M.; Mikutta, C.; Mikutta, R.; Nico, P.S. Mineral-organic associations: Formation, properties, and relevance in soil environments. Adv. Agron. 2015, 130, 1–140. [Google Scholar]
  51. Karlen, D.L.; Ditzler, C.A.; Andrews, S.S. Soil quality: Why and how? Geoderma 2003, 114, 145–156. [Google Scholar] [CrossRef]
  52. Berthrong, S.T.; Buckley, D.H.; Drinkwater, L.E. Agricultural management and labile carbon additions affect soil microbial community structure and interact with carbon and nitrogen cycling. Microb. Ecol. 2013, 66, 158–170. [Google Scholar] [CrossRef]
  53. Kalbitz, K.; Kaiser, K. Contribution of dissolved organic matter to carbon storage in forest mineral soils. J. Plant Nutr. Soil Sci. 2008, 171, 52–60. [Google Scholar] [CrossRef]
  54. Derrien, D.; Plain, C.; Courty, P.E.; Gelhaye, L.; Moerdijk-Poortvliet, T.C.W.; Thomas, F.; Versini, A.; Zeller, B.; Koutika, L.S.; Boschker, H.T.S.; et al. Does the addition of labile substrate destabilise old soil organic matter? Soil Biol. Biochem. 2014, 76, 149–160. [Google Scholar] [CrossRef]
  55. Kallenbach, C.M.; Grandy, A.S.; Frey, S.D.; Diefendorf, A.F. Microbial physiology and necromass regulate agricultural soil carbon accumulation. Soil Biol. Biochem. 2015, 91, 279–290. [Google Scholar] [CrossRef]
  56. Miltner, A.; Bombach, P.; Schmidt-Brücken, B.; Kästner, M. SOM genesis: Microbial biomass as a significant source. Biogeochemistry 2012, 111, 41–55. [Google Scholar] [CrossRef]
  57. Hobara, S.; Osono, T.; Hirose, D.; Noro, K.; Hirota, M.; Benner, R. The roles of microorganisms in litter decomposition and soil formation. Biogeochemistry 2014, 118, 471–486. [Google Scholar] [CrossRef]
  58. Lawrence, G.B.; Fernandez, I.J.; Richter, D.D.; Ross, D.S.; Hazlett, P.W.; Bailey, S.W.; Ouimet, R.; Warby, R.A.F.; Johnson, A.H.; Lin, H.; et al. Measuring environmental change in forest ecosystems by repeated soil sampling: A North American perspective. J. Environ. Qual. 2013, 42, 623–639. [Google Scholar] [CrossRef] [PubMed]
  59. Rodríguez Martín, J.A.Y.; Álvaro-Fuentes, J.; Gabriel, J.L.; Gutiérrez, C.; Nanos, N.; Escuer, M.; Ramos-Miras, J.J.; Gil, C.; Martín-Lammerding, D.; Boluda, R. Soil organic carbon stock on the Majorca Island: Temporal change in agricultural soil over the last 10 years. Catena 2019, 181, 104087. [Google Scholar] [CrossRef]
  60. Grüneberg, E.; Schöning, I.; Kalko, E.K.V.; Weisser, W.W. Regional organic carbon stock variability: A comparison between depth increments and soil horizons. Geoderma 2010, 155, 426–433. [Google Scholar] [CrossRef]
  61. De Feudis, M.; Falsone, G.; Vianello, G.; Agnelli, A.; Vittori Antisari, L. Soil organic carbon stock assessment in forest ecosystems through pedogenic horizons and fixed depth layers sampling: What’s the best one? L. Degrad. Dev. 2022, 33, 1446–1458. [Google Scholar] [CrossRef]
  62. Zanella, A.; Berg, B.; Ponge, J.F.; Kemmers, R.H. Humusica 1, article 2: Essential bases—Functional considerations. Appl. Soil Ecol. 2018, 122, 22–41. [Google Scholar] [CrossRef]
  63. Angst, G.; Messinger, J.; Greiner, M.; Häusler, W.; Hertel, D.; Kirfel, K.; Kögel-Knabner, I.; Leuschner, C.; Rethemeyer, J.; Mueller, C.W. Soil organic carbon stocks in topsoil and subsoil controlled by parent material, carbon input in the rhizosphere, and microbial-derived compounds. Soil Biol. Biochem. 2018, 122, 19–30. [Google Scholar] [CrossRef]
  64. Simo, I.; Schulte, R.; O’Sullivan, L.; Creamer, R. Digging deeper: Understanding the contribution of subsoil carbon for climate mitigation, a case study of Ireland. Environ. Sci. Policy 2019, 98, 61–69. [Google Scholar] [CrossRef]
  65. Inagaki, T.M.; Possinger, A.R.; Schweizer, S.A.; Mueller, C.W.; Hoeschen, C.; Zachman, M.J.; Kourkoutis, L.F.; Kögel-Knabner, I.; Lehmann, J. Microscale spatial distribution and soil organic matter persistence in top and subsoil. Soil Biol. Biochem. 2023, 178, 108921. [Google Scholar] [CrossRef]
  66. Jandl, R.; Rodeghiero, M.; Martinez, C.; Cotrufo, M.F.; Bampa, F.; van Wesemael, B.; Harrison, R.B.; Guerrini, I.A.; Richter, D.d.B.; Rustad, L.; et al. Current status, uncertainty and future needs in soil organic carbon monitoring. Sci. Total Environ. 2014, 468–469, 376–383. [Google Scholar] [CrossRef]
  67. Chien, S.C.; Krumins, J.A. Natural versus urban global soil organic carbon stocks: A meta-analysis. Sci. Total Environ. 2022, 807, 150999. [Google Scholar] [CrossRef] [PubMed]
  68. Stockmann, U.; Padarian, J.; McBratney, A.; Minasny, B.; de Brogniez, D.; Montanarella, L.; Hong, S.Y.; Rawlins, B.G.; Field, D.J. Global soil organic carbon assessment. Glob. Food Sec. 2015, 6, 9–16. [Google Scholar] [CrossRef]
  69. Rumpel, C.; Kögel-Knabner, I. Deep soil organic matter-a key but poorly understood component of terrestrial C cycle. Plant Soil 2011, 338, 143–158. [Google Scholar] [CrossRef]
  70. De Feudis, M.; Falsone, G.; Vianello, G.; Vittori Antisari, L. The conversion of abandoned chestnut forests to managed ones does not affect the soil chemical properties and improves the soil microbial biomass activity. Forests 2020, 11, 786. [Google Scholar] [CrossRef]
  71. FAO. World Reference Base for Soil Resources 2014. International Soil Classification System for Naming Soils and Creating Legends for Soil Maps; FAO: Rome, Italy, 2014.
  72. Kamczyc, J.; Dyderski, M.K.; Horodecki, P.; Jagodziński, A.M. Temperature and precipitation affect seasonal changes in mite communities (Acari: Mesostigmata) in decomposing litter of broadleaved and coniferous temperate tree species. Ann. For. Sci. 2022, 79, 12. [Google Scholar] [CrossRef]
  73. Wood, T.E.; Lawrence, D.; Clark, D.A.; Chazdon, R.L. Rain forest nutrient cycling and productivity in response to large-scale litter manipulation. Ecology 2009, 90, 109–121. [Google Scholar] [CrossRef]
  74. Gavazov, K.S. Dynamics of alpine plant litter decomposition in a changing climate. Plant Soil 2010, 337, 19–32. [Google Scholar] [CrossRef]
  75. Schulte, E.E.; Hopkins, B.G. Estimation of Organic Matter by Weight Loss-on-Ignition; Soil Organic Matter: Analysis and Interpretation; SSSA Inc.: Madison, WI, USA, 1996; pp. 21–31. [Google Scholar]
  76. Cambardella, C.A.; Gajda, A.M.; Doran, J.W.; Wienhold, B.J.; Kettler, T.A. Estimation of particulate and total organic matter by weight loss-on-ignition. In Assessment Methods for Soil Carbon (Advances in Soil Science); CRC Press: Boca Raton, FL, USA, 2001; pp. 349–359. [Google Scholar]
  77. European Comission. European Green Deal: Commission Proposes Certification of Carbon Removals to Help Reach Net Zero Emissions; Press Release; Eurpean Commission: Brussels, Belgium, 2022.
  78. IPCC. Good Practice Guidance for Land Use, Land-Use Change and Forestry; IPCC: Geneva, Switzerland, 2006; p. 590.
  79. Borrelli, P.; Panagos, P.; Märker, M.; Modugno, S.; Schütt, B. Assessment of the impacts of clear-cutting on soil loss by water erosion in Italian forests: First comprehensive monitoring and modelling approach. Catena 2017, 149, 770–781. [Google Scholar] [CrossRef]
  80. Brunner, A.C.; Park, S.J.; Ruecker, G.R.; Vlek, P.L.G. Erosion modelling approach to simulate the effect of land management options on soil loss by considering catenary soil development and farmers perception. L. Degrad. Dev. 2008, 19, 623–635. [Google Scholar] [CrossRef]
  81. Olson, K.R.; Al-Kaisi, M.; Lal, R.; Cihacek, L. Impact of soil erosion on soil organic carbon stocks. J. Soil Water Conserv. 2016, 71, 61A–67A. [Google Scholar] [CrossRef]
  82. Mishra, G.; Sarkar, A.; Giri, K.; Nath, A.J.; Lal, R.; Francaviglia, R. Changes in soil carbon stocks under plantation systems and natural forests in Northeast India. Ecol. Modell. 2021, 446, 109500. [Google Scholar] [CrossRef]
  83. Wellock, M.L.; Rafique, R.; La Perle, C.M.; Peichl, M.; Kiely, G. Changes in ecosystem carbon stocks in a grassland ash (Fraxinus excelsior) afforestation chronosequence in Ireland. J. Plant Ecol. 2014, 7, 429–438. [Google Scholar] [CrossRef]
  84. Justine, M.F.; Yang, W.; Wu, F.; Khan, M.N. Dynamics of biomass and carbon sequestration across a chronosequence of masson pine plantations. J. Geophys. Res. Biogeosci. 2017, 122, 578–591. [Google Scholar] [CrossRef]
  85. Abegaz, A.; Tamene, L.; Abera, W.; Yaekob, T.; Hailu, H.; Nyawira, S.S.; Silva, M.D.; Sommer, R. Soil organic carbon dynamics along chrono-sequence land-use systems in the highlands of Ethiopia. Agric. Ecosyst. Environ. 2020, 300, 106997. [Google Scholar] [CrossRef]
  86. Lozano-García, B.; Francaviglia, R.; Renzi, G.; Doro, L.; Ledda, L.; Benítez, C.; González-Rosado, M.; Parras-Alcántara, L. Land use change effects on soil organic carbon store. An opportunity to soils regeneration in Mediterranean areas: Implications in the 4p1000 notion. Ecol. Indic. 2020, 119, 106831. [Google Scholar] [CrossRef]
  87. Minasny, B.; Malone, B.P.; McBratney, A.B.; Angers, D.A.; Arrouays, D.; Chambers, A.; Chaplot, V.; Chen, Z.S.; Cheng, K.; Das, B.S.; et al. Soil carbon 4 per mille. Geoderma 2017, 292, 59–86. [Google Scholar] [CrossRef]
  88. Smal, H.; Ligęza, S.; Pranagal, J.; Urban, D.; Pietruczyk-Popławska, D. Changes in the stocks of soil organic carbon, total nitrogen and phosphorus following afforestation of post-arable soils: A chronosequence study. For. Ecol. Manage. 2019, 451, 117536. [Google Scholar] [CrossRef]
  89. Kunlanit, B.; Butnan, S.; Vityakon, P. Land-use changes influencing C sequestration and quality in topsoil and subsoil. Agronomy 2019, 9, 520. [Google Scholar] [CrossRef]
  90. Wattel-Koekkoek, E.J.W.; Buurman, P.; Van Der Plicht, J.; Wattel, E.; Van Breemen, N. Mean residence time of soil organic matter associated with kaolinite and smectite. Eur. J. Soil Sci. 2003, 54, 269–278. [Google Scholar] [CrossRef]
  91. Baraket, F.; González-Rosado, M.; Brahim, N.; Roca, N.; Mbarek, H.B.; Świtoniak, M.; Chaker, R.; Sánchez-Bellón, Á.; Rigane, H.; Gargouri, K.; et al. Short and long-term effect of land use and management on soil organic carbon stock in semi-desert areas of North Africa-Tunisia. Agriculture 2021, 11, 1267. [Google Scholar] [CrossRef]
  92. Hobley, E.; Baldock, J.; Hua, Q.; Wilson, B. Land-use contrasts reveal instability of subsoil organic carbon. Glob. Chang. Biol. 2017, 23, 955–965. [Google Scholar] [CrossRef]
  93. González-Rosado, M.; Parras-Alcántara, L.; Aguilera-Huertas, J.; Benítez, C.; Lozano-García, B. Effects of land management change on soil aggregates and organic carbon in Mediterranean olive groves. Catena 2020, 195, 104840. [Google Scholar] [CrossRef]
  94. Jenikinson, D.S.; Coleman, K. The turnover of organic carbon in subsoils. Part 2. Modelling carbon turnover. Eur. J. Soil Sci. 2008, 59, 400–413. [Google Scholar] [CrossRef]
  95. Haynes, R.J. Labile organic matter fractions as central components of the quality of agricultural soils: An overview. Adv. Agron. 2005, 85, 221–268. [Google Scholar] [CrossRef]
  96. Angst, G.; Mueller, K.E.; Kögel-Knabner, I.; Freeman, K.H.; Mueller, C.W. Aggregation controls the stability of lignin and lipids in clay-sized particulate and mineral associated organic matter. Biogeochemistry 2017, 132, 307–324. [Google Scholar] [CrossRef]
  97. Shrestha, B.M.; Singh, B.R.; Forte, C.; Certini, G. Long-term effects of tillage, nutrient application and crop rotation on soil organic matter quality assessed by NMR spectroscopy. Soil Use Manag. 2015, 31, 358–366. [Google Scholar] [CrossRef]
  98. Muñoz-Romero, V.; Lopez-Bellido, R.J.; Fernandez-Garcia, P.; Redondo, R.; Murillo, S.; Lopez-Bellido, L. Effects of tillage, crop rotation and N application rate on labile and recalcitrant soil carbon in a Mediterranean Vertisol. Soil Tillage Res. 2017, 169, 118–123. [Google Scholar] [CrossRef]
  99. Hemingway, J.D.; Rothman, D.H.; Grant, K.E.; Rosengard, S.Z.; Eglinton, T.I.; Derry, L.A.; Galy, V.V. Mineral protection regulates long-term global preservation of natural organic carbon. Nature 2019, 570, 228–231. [Google Scholar] [CrossRef]
  100. Newcomb, C.J.; Qafoku, N.P.; Grate, J.W.; Bailey, V.L.; De Yoreo, J.J. Developing a molecular picture of soil organic matter-mineral interactions by quantifying organo-mineral binding. Nat. Commun. 2017, 8, 396. [Google Scholar] [CrossRef] [PubMed]
  101. Kögel-Knabner, I.; Guggenberger, G.; Kleber, M.; Kandeler, E.; Kalbitz, K.; Scheu, S.; Eusterhues, K.; Leinweber, P. Organo-mineral associations in temperate soils: Integrating biology, mineralogy, and organic matter chemistry. J. Plant Nutr. Soil Sci. 2008, 171, 61–82. [Google Scholar] [CrossRef]
  102. Zhou, J.; Wen, Y.; Shi, L.; Marshall, M.R.; Kuzyakov, Y.; Blagodatskaya, E.; Zang, H. Strong priming of soil organic matter induced by frequent input of labile carbon. Soil Biol. Biochem. 2021, 152, 108069. [Google Scholar] [CrossRef]
  103. Jílková, V.; Jandová, K.; Cajthaml, T.; Devetter, M.; Kukla, J.; Starý, J.; Vacířová, A. Organic matter decomposition and carbon content in soil fractions as affected by a gradient of labile carbon input to a temperate forest soil. Biol. Fertil. Soils 2020, 56, 411–421. [Google Scholar] [CrossRef]
  104. Zheng, J.Y.; Wang, L.; Zhao, J.S.; Niu, Y.H.; Xiao, H.B.; Wang, Z.; Yu, S.X.; Shi, Z.H. Forty-year-old orchards promote carbon storage by changing aggregate-associated enzyme activities and microbial communities. Catena 2022, 213, 106195. [Google Scholar] [CrossRef]
  105. Cardinael, R.; Chevallier, T.; Cambou, A.; Béral, C.; Barthès, B.G.; Dupraz, C.; Durand, C.; Kouakoua, E.; Chenu, C. Increased soil organic carbon stocks under agroforestry: A survey of six different sites in France. Agric. Ecosyst. Environ. 2017, 236, 243–255. [Google Scholar] [CrossRef]
  106. Zanotelli, D.; Vendrame, N.; López-Bernal, Á.; Caruso, G. Carbon sequestration in orchards and vineyards. Italus Hortus 2018, 25, 13–28. [Google Scholar] [CrossRef]
  107. Ramesh, T.; Bolan, N.S.; Kirkham, M.B.; Wijesekara, H.; Kanchikerimath, M.; Srinivasa Rao, C.; Sandeep, S.; Rinklebe, J.; Ok, Y.S.; Choudhury, B.U.; et al. Soil organic carbon dynamics: Impact of land use changes and management practices: A review. Adv. Agron. 2019, 156, 1–107. [Google Scholar] [CrossRef]
  108. Babu, S.; Mohapatra, K.P.; Yadav, G.S.; Lal, R.; Singh, R.; Avasthe, R.K.; Das, A.; Chandra, P.; Gudade, B.A.; Kumar, A. Soil carbon dynamics in diverse organic land use systems in North Eastern Himalayan ecosystem of India. Catena 2020, 194, 104785. [Google Scholar] [CrossRef]
  109. Repullo-Ruibérriz de Torres, M.A.; Carbonell-Bojollo, R.M.; Moreno-García, M.; Ordóñez-Fernández, R.; Rodríquez-Lizana, A. Soil organic matter and nutrient improvement through cover crops in a Mediterranean olive orchard. Soil Tillage Res. 2021, 210, 104977. [Google Scholar] [CrossRef]
  110. Ball, K.R.; Baldock, J.A.; Penfold, C.; Power, S.A.; Woodin, S.J.; Smith, P.; Pendall, E. Soil organic carbon and nitrogen pools are increased by mixed grass and legume cover crops in vineyard agroecosystems: Detecting short-term management effects using infrared spectroscopy. Geoderma 2020, 379, 114619. [Google Scholar] [CrossRef]
  111. Seddaiu, G.; Porcu, G.; Ledda, L.; Roggero, P.P.; Agnelli, A.; Corti, G. Soil organic matter content and composition as influenced by soil management in a semi-arid Mediterranean agro-silvo-pastoral system. Agric. Ecosyst. Environ. 2013, 167, 1–11. [Google Scholar] [CrossRef]
  112. Mayer, M.; Prescott, C.E.; Abaker, W.E.A.; Augusto, L.; Cécillon, L.; Ferreira, G.W.D.; James, J.; Jandl, R.; Katzensteiner, K.; Laclau, J.P.; et al. Influence of forest management activities on soil organic carbon stocks: A knowledge synthesis. For. Ecol. Manag. 2020, 466, 118127. [Google Scholar] [CrossRef]
  113. De Feudis, M.; Falsone, G.; Vittori Antisari, L. Mid-term (30 years) changes of soil properties under chestnut stands due to organic residues management: An integrated study. Catena 2021, 198, 105021. [Google Scholar] [CrossRef]
  114. Asare, E.; Segarra, E. Adoption and extent of adoption of georeferenced grid soil sampling technology by cotton producers in the southern US. Precis. Agric. 2018, 19, 992–1010. [Google Scholar] [CrossRef]
  115. Nanni, M.R.; Povh, F.P.; Demattê, J.A.M.; Oliveira, R.B.d.; Chicati, M.L.; Cezar, E. Optimum size in grid soil sampling for variable rate application in site-specific management. Sci. Agric. 2011, 68, 386–392. [Google Scholar] [CrossRef]
  116. John, K.; Isong, I.A.; Kebonye, N.M.; Ayito, E.O.; Agyeman, P.C.; Afu, S.M. Using machine learning algorithms to estimate soil organic carbon variability with environmental variables and soil nutrient indicators in an alluvial soil. Land 2020, 9, 487. [Google Scholar] [CrossRef]
  117. Panday, D.; Ojha, R.B.; Chalise, D.; Das, S.; Twanabasu, B. Spatial variability of soil properties under different land use in the Dang district of Nepal. Cogent Food Agric. 2019, 5, 1600460. [Google Scholar] [CrossRef]
  118. Silvero, N.E.Q.; Demattê, J.A.M.; Amorim, M.T.A.; Santos, N.V.d.; Rizzo, R.; Safanelli, J.L.; Poppiel, R.R.; Mendes, W.d.S.; Bonfatti, B.R. Soil variability and quantification based on Sentinel-2 and Landsat-8 bare soil images: A comparison. Remote Sens. Environ. 2021, 252, 112117. [Google Scholar] [CrossRef]
  119. Dung, B.X.; Thi, D.; Thanh, K. Runoff and soil erosion response to clear cutting period of acacia plantation in a Headwater Mountain of Vietnam. Appl. Res. Sci. Technol. 2021, 1, 12–25. [Google Scholar]
  120. Gharibreza, M.; Zaman, M.; Porto, P.; Fulajtar, E.; Parsaei, L.; Eisaei, H. Assessment of deforestation impact on soil erosion in loess formation using 137Cs method (case study: Golestan Province, Iran). Int. Soil Water Conserv. Res. 2020, 8, 393–405. [Google Scholar] [CrossRef]
  121. Robinson, D.A.; Lebron, I.; Vereecken, H. On the definition of the natural capital of soils: A framework for description, evaluation, and monitoring. Soil Sci. Soc. Am. J. 2009, 73, 1904–1911. [Google Scholar] [CrossRef]
  122. Costantini, E.A.C.; Mocali, S. Soil health, soil genetic horizons and biodiversity. J. Plant Nutr. Soil Sci. 2022, 185, 24–34. [Google Scholar] [CrossRef]
  123. Vittori Antisari, L.; Trenti, W.; Buscaroli, A.; Falsone, G.; Vianello, G.; De Feudis, M. Pedodiversity and organic matter stock of soils developed on sandstone formations in the Northern Apennines (Italy). Land 2023, 12, 79. [Google Scholar] [CrossRef]
Figure 1. Chestnut (Castanea sativa Mill) coppice (CC) and orchard for fruit production (CO) located in the “National Centre for the Study and Conservation of Forest Biodiversity” (Northern Apennines, Alto Reno Terme, Italy), and soil sampling design applied in both chestnut stand types.
Figure 1. Chestnut (Castanea sativa Mill) coppice (CC) and orchard for fruit production (CO) located in the “National Centre for the Study and Conservation of Forest Biodiversity” (Northern Apennines, Alto Reno Terme, Italy), and soil sampling design applied in both chestnut stand types.
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Table 1. Thickness and organic C content of Oi and Oe horizons in a 15-year-old chestnut orchard for fruit production (CO) and chestnut coppice (CC) recorded in July from 2005 to 2020. The organic C content was measured by the loss-on-ignition (LOI) method, according to Schulte and Hopkins [75] and Cambardella et al. [76].
Table 1. Thickness and organic C content of Oi and Oe horizons in a 15-year-old chestnut orchard for fruit production (CO) and chestnut coppice (CC) recorded in July from 2005 to 2020. The organic C content was measured by the loss-on-ignition (LOI) method, according to Schulte and Hopkins [75] and Cambardella et al. [76].
SiteYearHorizonThicknessOrganic C
cmg kg−1
CO2005Oi0.3369
Oe0.5196
2010Oi0.5380
Oe1.0160
2015Oi0.9388
Oe0.5212
2020Oi1.2396
Oe1.6207
CC2005Oi1.9404
Oe3.0112
2020Oi2.0409
Oe2.5118
Table 2. Values of thickness and bulk density (BD), mean ± standard of total organic carbon content (SOC), recalcitrant organic carbon content (ROC), SOC stock (SOCstock) and ROC stock (ROCstock) of the pedogenic horizons of soil profiles dug from 2005 to 2020 in a 15-year-old chestnut orchard for fruit production (CO) and a chestnut coppice (CC).
Table 2. Values of thickness and bulk density (BD), mean ± standard of total organic carbon content (SOC), recalcitrant organic carbon content (ROC), SOC stock (SOCstock) and ROC stock (ROCstock) of the pedogenic horizons of soil profiles dug from 2005 to 2020 in a 15-year-old chestnut orchard for fruit production (CO) and a chestnut coppice (CC).
SiteYearHorizonThicknessBDSOCROCSOCstockROCstock
cmg cm−3g kg−1g kg−1Mg ha−1Mg ha−1
CO2005A2.31.00773.9 ± 2.10.46 ± 0.0716.7 ± 0.50.11 ± 0.02
AC6.01.02232.5 ± 1.70.41 ± 0.0619.9 ± 1.00.25 ± 0.04
C21.70.99820.3 ± 1.60.74 ± 0.1144.2 ± 3.41.61 ± 0.24
2010A4.71.01875.2 ± 10.30.77 ± 0.0935.8 ± 4.80.37 ± 0.04
AC4.31.01543.8 ± 9.80.67 ± 0.0419.2 ± 4.40.29 ± 0.02
C21.00.99933.0 ± 7.60.85 ± 0.0869.2 ± 2.51.78 ± 0.17
2015A3.31.02486.6 ± 2.90.87 ± 0.0929.3 ± 0.90.29 ± 0.03
AC5.51.01646.6 ± 9.70.89 ± 0.1126.0 ± 3.90.50 ± 0.06
C21.20.98737.2 ± 8.80.94 ± 0.1777.8 ± 18.51.97 ± 0.36
2020A4.71.01894.8 ± 9.90.98 ± 0.0545.4 ± 4.70.47 ± 0.02
AC6.71.01962.1 ± 5.31.08 ± 0.1342.4 ± 3.60.74 ± 0.09
C18.60.97943.1 ± 8.31.66 ± 0.3178.9 ± 15.23.04 ± 0.57
CC2005A16.01.00576.3 ± 6.20.52 ± 0.0947.0 ± 1.80.16 ± 0.03
A29.01.00322.4 ± 5.30.66 ± 0.0737.9 ± 3.00.40 ± 0.04
CB6.00.99012.7 ± 4.40.69 ± 0.1112.5 ± 4.80.82 ± 0.13
C9.00.99110.9 ± 2.20.94 ± 0.1611.6 ± 1.80.84 ± 0.14
2020A16.00.98767.2 ± 7.70.74 ± 0.0845.6 ± 2.80.26 ± 0.03
A28.00.99432.2 ± 7.50.77 ± 0.0732.6 ± 4.00.38 ± 0.04
BC8.01.00514.8 ± 2.10.94 ± 0.1016.9 ± 2.61.23 ± 0.03
C8.01.00211.3 ± 1.40.98 ± 0.0910.4 ± 0.90.83 ± 0.01
Table 3. Values of bulk density (BD), mean ± standard error of total organic carbon content (SOC), recalcitrant organic carbon content (ROC), SOC stock (SOCstock) and ROC stock (ROCstock) of the 0–30 cm interval depth of soil profiles dug from 2005 to 2020 in a 15-year-old chestnut orchard for fruit production (CO) and a chestnut coppice (CC).
Table 3. Values of bulk density (BD), mean ± standard error of total organic carbon content (SOC), recalcitrant organic carbon content (ROC), SOC stock (SOCstock) and ROC stock (ROCstock) of the 0–30 cm interval depth of soil profiles dug from 2005 to 2020 in a 15-year-old chestnut orchard for fruit production (CO) and a chestnut coppice (CC).
SiteYearThicknessBDSOCROCSOCstockROCstock
cmg cm−3g kg−1g kg−1Mg ha−1Mg ha−1
CO200530.01.00726.9 ± 1.80.66 ± 0.0880.8 ± 4.91.97 ± 0.30
201030.01.00441.2 ± 9.20.81 ± 0.07124.2 ± 11.72.44 ± 0.23
201530.00.99644.4 ± 7.10.92 ± 0.12133.1 ± 23.32.76 ± 0.45
202030.00.99755.6 ± 7.81.43 ± 0.16166.7 ± 23.54.25 ± 0.68
CC200530.00.99727.8 ± 4.50.72 ± 0.11109,0 ± 11.42.22 ± 0.34
202030.00.99729.0 ± 4.70.87 ± 0.09105.5 ± 10.32.70 ± 0.11
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De Feudis, M.; Vianello, G.; Vittori Antisari, L. Soil Organic Carbon Stock Assessment for Volunteer Carbon Removal Benefit: Methodological Approach in Chestnut Orchard for Fruit Production. Environments 2023, 10, 83. https://doi.org/10.3390/environments10050083

AMA Style

De Feudis M, Vianello G, Vittori Antisari L. Soil Organic Carbon Stock Assessment for Volunteer Carbon Removal Benefit: Methodological Approach in Chestnut Orchard for Fruit Production. Environments. 2023; 10(5):83. https://doi.org/10.3390/environments10050083

Chicago/Turabian Style

De Feudis, Mauro, Gilmo Vianello, and Livia Vittori Antisari. 2023. "Soil Organic Carbon Stock Assessment for Volunteer Carbon Removal Benefit: Methodological Approach in Chestnut Orchard for Fruit Production" Environments 10, no. 5: 83. https://doi.org/10.3390/environments10050083

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