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Review

A Bibliometric Analysis of Research on the Sources and Formation Processes of Forest Soil Organic Matter Under Climate Change

by
Zhentao Shen
1,2,
Kai Yue
3,
Yan Peng
3,
Hui Zhang
1,2,
Cuihuan Li
1,2,* and
Yan Li
1,2
1
State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou 311300, China
2
Tianmushan Forest Ecosystem Orientation Observation and Research Station of Zhejiang Province, Hangzhou 311300, China
3
Key Laboratory of Humid Subtropical Eco-Geographical Processes of the Ministry of Education, Fujian Normal University, Fuzhou 350007, China
*
Author to whom correspondence should be addressed.
Forests 2025, 16(2), 336; https://doi.org/10.3390/f16020336
Submission received: 25 November 2024 / Revised: 11 February 2025 / Accepted: 13 February 2025 / Published: 13 February 2025
(This article belongs to the Special Issue Soil Organic Carbon and Nutrient Cycling in the Forest Ecosystems)
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Abstract

:
Forest soil organic matter (SOM) is a critical component of forest ecosystems and plays a vital role in the global carbon (C) cycle. Global climate change profoundly affects forest SOM dynamics, particularly its sources and formation processes, which are crucial initial stages of the forest soil C cycle. Therefore, understanding these processes and the impacts of climate change is essential for developing effective forest management strategies and climate policies. In this study, VOSviewer 1.6.18 was used to conduct a bibliometric analysis of research published from 1975 to 2024, retrieved from the Web of Science (WoS) Core Collection database, focusing on the sources and formation processes of forest SOM under climate change. The analysis covers annual publication trends, author co-occurrence networks, publication distributions by country and region, keyword clustering, and evolving keyword trends, integrating both quantitative results and a literature review to provide an understanding of the research progress in the field. The results highlight continuous growth in research publications, which can be categorized into four stages: initial emergence, sustained exploration, rapid development, and deep expansion. A solid theoretical foundation and good research strength have been established, driven by prominent academic groups led by researchers such as Jari Liski, as well as leading countries, including the United States and China. The research progress is divided into four topics: the sources of forest SOM; the formation processes of forest SOM; the impacts of climate change; and measurement methods and model-based analysis techniques, which mainly elaborate upon plant-, microbial-, and soil fauna-derived aspects. Research hotspots have evolved from basic C and nitrogen (N) cycles to in-depth studies involving microbial mechanisms and multiparameter climate change interactive effects. This study provides an overview of the research progress and hotspots in the field, offering basic knowledge and theoretical support for potential future research and climate change mitigation strategies.

1. Introduction

SOM is the largest C pool in terrestrial ecosystems, playing a crucial role in the global C cycle [1]. SOM broadly refers to organic substances in the soil that are typically derived from aboveground and belowground organic debris and microbial biomass, all of which are vital to the intricate web of the C cycle [2]. Changes in SOM reflect the balance between exogenous organic matter (OM) input and soil C output, along with the intensity of interfering factors such as environmental change [3,4]. Therefore, the dynamics of forest SOM have received considerable attention, leading to in-depth studies on the sources, formation, transformation, stabilization, sequestration, and loss of forest SOM and on the factors controlling the soil C cycle [5,6,7,8]. For example, Adamczyk et al. [9] explored boreal forests and revealed that plant root activities accelerated SOM decomposition and altered its stability, illustrating the intricate interplay between plant biology and SOM dynamics. In tropical forests, Nottingham et al. [10] reported that experimental warming on Barro Colorado Island, Panama, led to soil C loss, demonstrating the sensitivity of soil C to warming and its potential feedback to climate change. Qafoku et al. [11] evaluated the adsorption capacity of the main SOM compounds, including lauric acid and pentaglycine, to soil minerals at a molecular scale and explained the molecular mechanism of mineral action on soil C stabilization. Understanding the dynamics of forest SOM and the formation of a closed loop for flow is crucial for elucidating soil C–climate feedback.
The forest SOM cycle is a multifaceted process involving various components and transformations that essentially shape soil C sequestration and release [12]. The inputs, such as tree and shrub litter, undergo various transformations, including decomposition and mineralization, leading to C sequestration within SOM [13]. Conversely, outputs or losses include soil biota respiration and the leaching of dissolved organic C, maintaining a balance between C influx and efflux that determines SOM accumulation or depletion [14]. This balance profoundly influences ecological functions. However, the globe is already experiencing apparent warming, and this trend is expected to continue over the next century, potentially disrupting that balance and expanding the scope, duration, and severity of extreme events [15,16]. It is still not clear what the fate of forest SOM will be under climate warming and whether forest ecosystems will become a net C source or sink [17]. Some of the major uncertainties are due to the changes in SOM properties and dynamics caused by climate change, which pose challenges to global analysis models. For example, soil respiration rates and SOM bioreactivity decline after years of warming, accompanied by changes in the chemical composition of SOM [18,19]. The concentration of cutin-derived compounds increases, which alters the SOM decomposition rate. However, in C-rich forests, in situ warming experiments increased soil respiration without reducing SOM bioreactivity, suggesting that other processes such as root deposition, may regulate SOM composition and dynamics [20]. As the origin and cornerstone of soil C inputs, the sources and formation processes of forest SOM are particularly important. Clarifying these processes will help elucidate SOM stability mechanisms and sequestration dynamics, providing insights for addressing changes in the forest soil C pool under climate change and human interference and preventing further C loss [21].
The sources and formation processes of forest SOM are affected by various factors, including climate change, soil properties, vegetation types, land use change, and other anthropogenic factors, as recognized by many researchers. For example, the molecular structure and chemical composition of OM, such as leaves and roots from different forests, affect the decomposition rate and the quantity and quality of SOM. Plant species that produce lignin-rich or phenolic compounds may exhibit slower decomposition rates, thereby increasing SOM stability [22]. The interactions among the physical, chemical, and biological properties of SOM are complex and often site-specific and are influenced by the soil pH, moisture, and nutrient availability. These factors collectively determine the rate of SOM turnover and its capacity for long-term C storage. As climate change profoundly affects the structure and function of forest ecosystems, different climate change scenarios have become crucial concerns [23,24]. Factors such as global warming, altered precipitation, and N deposition lead to fluctuations in temperature, moisture, atmospheric CO2 levels, and other variables, which increase the complexity and uncertainty of SOM dynamics [25]. For example, changes in temperature and precipitation can alter aboveground vegetation productivity and subsequently affect SOM formation and C flux [26]. The temperature sensitivity of SOM decomposition (Q10 is usually used to represent the response of the decomposition rate to a temperature increase of 10 °C) has become a critical focus in research on the C cycle in terrestrial ecosystems [27]. Therefore, studying forest SOM dynamics under climate change is essential for formulating effective forest management strategies and addressing climate change impacts.
Despite numerous studies on the sources and formation processes of forest SOM, an overview summarizing the current research progress and hotspots under climate change is lacking. Traditional literature synthesis methods have been used for reviews, with limited incorporation of meta-analyses or bibliometric analyses in the field. These reviews have focused on specific aspects, such as the dynamics of dissolved OM, SOM stabilization mechanisms, the effects of ecological restoration on C sequestration, and the temperature sensitivity of SOM decomposition [4,28,29,30]. However, they have failed to provide a holistic overview of the sources and formation processes of forest SOM under climate change and to reveal the research progress through data mining and visualization processing [31]. To fill this gap, this study employs the bibliometric software VOSviewer, which focuses primarily on capturing the evolution of keywords and their characteristic changes, in conjunction with traditional literature synthesis methods, to provide a holistic review. The goal of this study is to clarify the research progress and hotspots in the field by combining quantitative and qualitative findings, thereby providing a reference for future theoretical and practical research related to forest SOM.

2. Materials and Methods

2.1. Data Collection

The literature data were obtained from the WoS Core Collection database, given its complete coverage of high-quality research literature. A systematic search was conducted on 31 August 2024. The search terms used were as follows: TS = (forest* soil organic matter OR forest* SOM OR forest* soil organic carbon OR forest* SOC) AND TS = (form* OR origin OR source* OR dynamic* OR develop* OR plant-derived OR microbial-derived OR soil fauna-derived OR litter OR root input OR vegetation input) AND TS = (climate change) NOT TS = (agriculture* OR wetland* OR grassland* OR meadow* OR permafrost*). These terms were determined by a thorough review of the literature and the expansion of the core terms (forest, soil organic matter, and climate change). The index used was the Science Citation Index Expanded, with the search spanning the period from 1 January 1975 to 31 August 2024. After performing a search with detailed terms, any irrelevant literature, such as editorial materials, corrections, and data papers (which focus on the methodology and sharing of datasets rather than presenting original research), was excluded. Furthermore, the inclusion criteria for literature selection were as follows: peer-reviewed articles related to the source or formation process of SOM identified by reviewing titles and abstracts; articles that contained the search terms, including extended synonyms; and articles that focused specifically on forest ecosystems or compared other ecosystems with forest ecosystems. Ultimately, 2778 journal articles and reviews met the requirements and were saved as plain text in the format of “Full Record and Cited References” for further analysis (Supplementary Information). The data collection and software analysis processes are illustrated in Figure 1.

2.2. Data Analysis Methods

VOSviewer is a Java-based bibliometric visualization software developed by Nees Jan van Eck and Ludo Waltman from Leiden University, The Netherlands. It was selected because it can integrate mathematical, statistical, and bibliometric knowledge to quantitatively analyze the characteristics and dynamic evolution of research literature and prepare scientific knowledge maps of different topics [32]. Compared with other bibliometric tools, VOSviewer stands out because of its intuitive interface, ease of use, and capacity to process large datasets efficiently. For example, VOSviewer offers superior graphical capabilities compared with HistCite, providing a wider range of visualization options. While CiteSpace has a relatively complex interface and usage process, VOSviewer is more user-friendly and easier to operate. Additionally, VOSviewer has been extensively utilized in various academic research fields, demonstrating scientific rigor and adherence to academic standards in literature analysis. As open-source software, VOSviewer’s algorithms and data processing methods are publicly available, allowing for full verification and adjustment, which ensures the transparency and reproducibility of the analysis process. Therefore, VOSviewer 1.6.18 was used to analyze the author co-occurrence networks, keyword clustering, and evolving keyword trends to obtain an overview of research progress and hotspots. Price’s formula (N = 0.749 (Nmax)1/2, where Nmax refers to the maximum value of an indicator) [33], was used to calculate the threshold for core authors and high-frequency keywords. GraphPad Prism 10.1.1 and Microsoft Excel 2024 were used for the statistical analysis and data presentation.
It is important to acknowledge the methodological limitations, including potential biases, incompleteness, and the inclusion of publications with low relevance, which may stem from varying literature search strategies and the inherent limitations of the WoS database. For example, the WoS database might have incomplete coverage across various disciplines, which could compromise the comprehensiveness of the analysis. To mitigate this, data from additional databases, such as Scopus and PubMed, could be retrieved and integrated in future analyses. Each selected publication should be subjected to rigorous review to ensure high relevance during the selection process. All the data and software used are fully replicable, allowing other researchers to follow the outlined procedures to replicate the analysis and verify the results.

3. Results

3.1. Annual Publication Trends

The annual number of publications showed a continuous upward trend, indicating increasing attention over time (Figure 2). The research progress can be divided into four stages. In the initial emergence stage (1975–2000), the topic of interest received limited recognition, with fewer than 10 publications annually and slow growth. In the sustained exploration stage (2001–2012), the number of published documents began to increase gradually, showing a definite growth trend. In the rapid development stage (2013–2020), the global consensus on coping with climate change increased, further driving SOM research and leading to a significant rise in academic output. In the deep expansion stage (2021–2024), research output grew rapidly, indicating active research progress in the field. The total citation frequency also showed a clear upward trend, indicating increased academic interest and the establishment of mature citation networks and knowledge bases. In 2023, 248 articles were published, with a total citation frequency of 13,556, the highest to date.

3.2. Author Co-Occurrence Network Analysis

The literature data include 11,676 authors. According to Price’s formula, scholars with four or more publications are considered core authors. Owing to the large number of authors, Figure 3 shows only those with five or more publications, excluding isolated or unconnected author nodes. The results reveal a close collaborative network centered on key authors, including Yakov Kuzyakov, Guoyi Zhou, Guirui Yu, Yiqi Luo, Josep Peñuelas, Changhui Peng, and Philippe Ciais. Several groups with close collaborations are also evident, with key contributors such as Jari Liski, Hjalmar Laudon, Qingkui Wang, and Zsolt Kotroczo. The most prolific authors include Jari Liski (19 publications) from the Finnish Meteorological Institute, Changhui Peng (18 publications) from the University of Quebec at Montreal, and Hjalmar Laudon (18 publications) from the Swedish University of Agricultural Sciences, whose work focuses on the impacts of climate change on forest SOM, nutrient cycling, and the development of C models (e.g., the Yasso soil C model).

3.3. National and Regional Publication Characteristics

A total of 109 countries and regions are involved in this field. The United States of America (USA) stands out, with the highest number of publications (849 publications, 30.61% of the total) and significant influence, with a total link strength of 893, as calculated by VOSviewer (Figure 4). Most of the research is concentrated in Europe, East Asia, and North America, with strong international cooperation. Specifically, the USA and Canada serve as the primary research hubs in North America. In Asia, China has made outstanding contributions. European countries, including Germany, the United Kingdom, and France, have closely collaborated to advance the field. Australia and Brazil, representing Oceania and South America, respectively, have been leaders in studying the effects of extreme climate events (e.g., droughts and wildfires) on SOM. In Africa, research performance is limited, characterized by a low volume of publications and weaker research strength. Countries with 100 or more publications include the USA, China, Germany, the United Kingdom, Canada, Spain, France, Sweden, Australia, Brazil, Italy, Finland, and Switzerland. These countries have made outstanding contributions, with a total link strength of greater than 200.

3.4. High-Frequency Keyword Analysis

According to Price’s formula, the threshold for high-frequency keywords was 29. A total of 48 high-frequency keywords appeared more than 100 times (Table 1). The most frequently occurring keyword was “climate change” (1401 times), along with “temperature sensitivity”, “elevated CO2”, “organic matter”, “forest”, “leaf litter”, “dynamics”, and “model”, reflecting the key research subject, the sources of forest SOM, and a focus on understanding SOM dynamics via various models. Furthermore, all high-frequency keywords (178 in total) were clustered into five clusters (Figure 5). Cluster 1 (green) included “climate change”, “elevated CO2”, “temperature sensitivity”, and “nitrogen deposition”, which are related to different types and impacts of climate change. Cluster 2 (red) included “organic matter”, “decomposition”, “litter”, and “microbial biomass” and focused on SOM sources. Cluster 3 (yellow) encompassed “forest”, “boreal forest”, “tropical forest”, and “spruce forest”, which are related to the SOM dynamics in different forest types. Cluster 4 (blue) included “carbon sequestration”, “soil respiration”, “carbon cycle”, and “mechanisms”, with an emphasis on the C cycle and SOM formation. Cluster 5 (purple) included “model”, “pattern”, “extraction method”, and “stable isotope”, focused on the measurement methods and model-based analysis. In summary, research has focused primarily on the sources of forest SOM, the formation processes of forest SOM, the impacts of climate change, and measurement methods and model-based analysis techniques.

3.5. Evolution of Research Hotspots

The evolution of high-frequency keywords reflects the development of research hotspots. Early studies focused on fundamental ecological topics, with keywords such as “atmospheric CO2”, “photosynthesis”, and “net primary production” (Figure 6). As research progressed, keywords such as “soil organic matter”, “litter”, and “lignin” emerged, indicating a shift toward forest SOM, including its sources and chemical composition. Moreover, research on C cycle processes, including soil respiration and C sequestration, has expanded. Subsequently, “climate change”, “temperature sensitivity”, and “bacterial” became prominent keywords, with a particular focus on the impact of climate change on SOM and the contributions of plants, microbes, and enzyme activities to SOM formation. Recently, the keywords “mechanisms”, “microbial community”, and “stoichiometry” have emerged, indicating a shift toward more complex research areas, such as SOM formation mechanisms and microbial functions.

4. Discussion

4.1. Research Foundation

There is a solid research foundation and a favorable upward trend for in-depth research related to SOM and C in forests, owing to the increasing number of publications and total citation frequency, scientific contributions from academic collaboration and pioneering countries, and positive evolution of high-frequency keywords. The four-stage research progress is based mainly on publication numbers and major events in the field. For the initial emergence stage, interest began to rise in the mid-1990s, following the adoption of the United Nations Framework Convention on Climate Change and the Kyoto Protocol [34]. In the sustained exploration stage, the Third Assessment Report published by the Intergovernmental Panel on Climate Change (IPCC) highlighted the effects of climate change, including its impact on SOM, sparking intensified research on forest soils as vital C sinks [35]. The rapid development stage saw increased academic achievement following the Paris Agreement. In the deep expansion stage, there is a focus on interdisciplinary studies, data integration, and modeling applications to address climate change challenges [36]. Overall, the analysis of the evolution of high-frequency keywords indicated that research on the sources and formation processes of forest SOM under climate change has evolved from basic research on C and N cycles to in-depth studies on microbial mechanisms and climate interactive effects. Future research should focus on systematic studies of forest SOM dynamics under multifactor interactions, further explore microscopic mechanisms, and conduct long-term monitoring at the macro scale integrated with the application of smart technologies to address and mitigate climate change.
The different stages of research have strengthened the scientific research foundation. Outstanding authors and pioneering countries have significantly advanced the field and laid the groundwork for further exploration. In the USA and Canada, research has focused on the relationship between boreal forest SOM and climate change, using techniques such as nuclear magnetic resonance (NMR) to explore global warming, N deposition, and microbial effects on SOM formation [37,38,39], as well as a stable isotope analysis to trace C and N cycles in SOM, particularly to track SOM source, microbial processing, and the impacts of N deposition and climate change on the C and N dynamics in boreal soils. For example, Hobbie and Ouimette [40] reported that N deposition significantly changes the soil N isotope composition, while climate change affects the C stability and microbial decomposition efficiency of SOM. In China, scholars have investigated SOM dynamics across various forest types (e.g., subtropical and temperate forests) under climate change [41,42], providing critical insights into SOM stability and interactions. For example, research conducted in the subtropical forests of southern China has shown that rising temperatures and increased precipitation intensity can lead to faster decomposition of OM, reducing the stability of SOM [43]. In Europe, building on multiscale research and long-term monitoring and simulations, researchers have explored the relationship between SOM and climate change, especially in boreal forests [44]. For example, Lindroth et al. [45] reported that extreme weather events such as storms can significantly reduce forest C sink capacity and affect the stability of SOM. In Oceania and South America, studies have focused on the effects of extreme climate events (e.g., droughts and forest wildfires) on SOM and the C cycle in tropical rainforests [46,47], whereas in Africa, despite limited scientific outputs, efforts have been made to study SOM dynamics and the impacts of climate change and land use on C storage and cycling in tropical forests [48,49]. Moving forward, strengthening pioneering research and international collaboration is essential.

4.2. Sources of Forest SOM

SOM sources can be divided into three types (Figure 7a). (1) Plant-derived SOM is derived mainly from aboveground litter (e.g., branches, leaves, bark, and fruits), subsurface roots (residues of dead roots), and root exudates. Aboveground litter often falls and accumulates on the soil surface, where it is decomposed by soil microbes and fauna, alongside underground plant-derived OM, all contributing to SOM [50,51]. Plant litter is the main initial source [4,52]. (2) Microbial-derived SOM includes mainly microbial necromass (e.g., bacterial and fungal necromass) and extracellular polymeric substances. Recently, the contribution of microbes to SOM has been widely recognized. Microbial humification and extracellular polymers promote SOM formation and accumulation [30]. Wu et al. [53] reported that microbial residues have a long turnover time in soil, which is critical for the formation and long-term stability of SOM, contributing as much as 50%–80% of the total SOM. (3) Soil fauna-derived SOM, including residues; fecal remains; secretions; and decomposition products of other fauna-derived forms of biological C. Soil fauna, such as earthworms and ants, affects OM import and retention through feeding and soil mixing [54]. However, the contribution of soil fauna to SOM is usually small compared to that of plant- and microbial-derived OM, so most studies have focused on plant- and microbial-derived OM [55,56,57]. Although litter decomposition is largely controlled by both soil fauna and microbes, empirical studies have focused more on the role of microbes than on that of soil fauna [58]. Filser et al. [59] emphasized that greater attention should be dedicated to understanding the important regulatory role of soil fauna in SOM dynamics and that incorporating soil fauna into SOM models could improve the accuracy of simulations. In general, plants and microbes are the most significant contributors, with relatively few studies on the role of soil fauna in SOM dynamics.

4.3. Formation Processes of Forest SOM

The formation processes of forest SOM are highly complex and can be divided into three types according to the source.

4.3.1. Formation Processes of Plant-Derived SOM

According to the classical theory of humification, aboveground litter such as dead branches and leaves is decomposed and transformed into complex materials such as humus by microbes (Figure 7b); the relevant steps include the mineralization of fresh OM; the secondary synthesis of residues; polymerization; condensation; and, finally, humus formation [60]. This process relies mainly on microbial “in vitro modification”; that is, microbes secrete extracellular enzymes (e.g., cellulase and lignin peroxidase) to decompose plant-derived OM into small molecule OM, recalcitrant OM, etc., ultimately leading to deposition [61]. Among plant-derived OM, unstable residues have relatively high microbial C utilization efficiency. Additionally, Lehman and Kleber [62] proposed the SOM continuum model, which argues that the transformation of plant residues to SOM involves stepwise decomposition from macromolecular biopolymers to small molecular compounds. Prescott and Vesterdal [63] revealed that decomposition comprises not only simple degradation but also synthesis processes involving multiple cyclic transformations, such as the cycling of plant litter, partial decomposition products, and microbial assimilation products. After humus is formed, it is transferred to the surrounding or deeper mineral soils, where it becomes stabilized within soil aggregates and clay minerals under the influence of soil fauna, leaching, and other factors, ultimately forming stable SOM [64]. Inputs from plant roots and exudates are primarily converted into stable SOM by the rhizospheric microbial community. Exudates and mycorrhizae also enhance the physical protection of soil minerals and aggregates, thereby promoting stable SOM accumulation [65]. Additionally, soil fauna plays important roles in the formation of plant-derived SOM by transporting, crushing, feeding on, and metabolizing litter, among other processes [66].

4.3.2. Formation Processes of Microbial-Derived SOM

Soil microbes act as “decomposers” and “contributors” in SOM formation. Several theories, such as the microbial efficiency-matrix stability model and the microbial C pump hypothesis, emphasize the key role of microbes [57,67]. Small-molecule OM, including plant-derived and decomposable OM, is a key factor affecting microbial growth and metabolism [54]. In soils with available substrates, microbes generate and accumulate a large amount of microbial-derived C through the iterative processes of cell formation, growth, and death (microbial burial effect), contributing continuously to SOM [68]. This process can be divided into two parts (Figure 7c): (1) assimilation, in which non-microbial-derived OM is transformed into microbial biomass and metabolites, forming microbial biomass C, and (2) in vivo turnover, wherein microbes continue to accumulate in the soil as microbial residues (including metabolites) after death, contributing to the soil C pool. Soil microbial residues include ribosomes, enzymes, small molecule polymers, and other colloidal progenitor solutes, as well as cell envelope fragments. Microbial-derived OM is an important source of forest SOM [68]. Rumpel et al. [69] reported that mineral-bound OM contains a relatively high proportion of microbial-derived polysaccharides, which readily combine with minerals to form stable SOM. Soil microbes significantly promote SOM formation and accumulation by decomposing non-microbially derived OM, assimilating OM, and performing continuous microbial cycling.

4.3.3. Formation Processes of Soil Fauna-Derived SOM

Soil fauna, such as earthworms, ants, fly larvae, nematodes, and millipedes, are important links in the intricate food web of forest soil and contribute to SOM formation. The processes through which soil fauna contributes to SOM formation can be summarized as follows (Figure 7d) [66,70]: (1) after the death of soil fauna, the remains are gradually decomposed by microbes, releasing C that contributes to SOM; (2) the fecal residues are decomposed by microbes and gradually transformed into stable SOM, such as humus and colloidal OM; and (3) decomposing residues of soil fauna secretions and dead residues interact with microbial metabolites (e.g., extracellular polymers) and OM in the soil (e.g., humus), forming more complex compounds that contribute to the SOM pool. The decomposition of soil faunal residues promotes SOM formation and stabilization. However, research on the specific processes of soil fauna-derived SOM formation remains limited.

4.4. Impacts of Climate Change on the Sources and Formation Processes of Forest SOM

According to high-frequency keyword clustering and analyses of existing research, global warming, elevated CO2, N deposition, and precipitation changes are important climate change factors affecting forest SOM, and their influences can be divided into three aspects.

4.4.1. Impacts of Climate Change on Plant-Derived SOM

Climate change affects the sources and formation processes of plant-derived SOM by altering the plant community composition, structure, growth cycle, productivity, and root dynamics (e.g., fine root turnover rate). These dynamics are highly sensitive to climate change factors, with complex and nonlinear interactions that have more profound implications than the simple sum of individual factors. Global warming accelerates plant growth and increases the activity of heat-tolerant species, which increases plant-derived OM input through root shedding [71]. However, warming also enhances the activities of soil microbes and enzymes, accelerating OM decomposition and increasing net SOM loss [72,73]. For example, in boreal forests, a low-temperature environment leads to SOM accumulation in the form of incompletely decomposed OM, peat, and frozen soil [74]. Permafrost melting caused by warming stimulates the N cycle (N limitation is common in boreal forest productivity), increases plant-derived OM inputs, and enhances microbial activity to accelerate SOM decomposition; thus, SOM in boreal forests is more vulnerable than that in other regions [38]. Additionally, the temperature response can be influenced by moisture availability and other factors, which are often overlooked in studies. For example, in arid and semiarid forests, warming can lead to increased evapotranspiration, reduced soil moisture, limited microbial decomposition, SOM formation, and long-term accumulation [75]. Elevated CO2 levels stimulate plant photosynthesis; boost productivity and biomass; and increase inputs of aboveground litter, roots, and exudates, thus promoting SOM formation [76]. However, excessive CO2 concentrations may inhibit SOM formation. Increased root turnover and altered root traits owing to elevated CO2 levels and warming are particularly important in forests. Accelerated root shedding may increase OM input in the short term, but the long-term effects are more complex. In nutrient-limited environments, increased plant growth and root turnover can initially increase SOM inputs. However, if root decomposition exceeds the rate of OM formation, it could lead to net SOM loss, especially if root exudates, which contribute significantly to SOM stabilization, are not effectively preserved by soil microbes [77]. N deposition affects plant growth by altering N availability. For example, continuous N deposition can initially promote plant productivity and OM input but can increase soil acidification, alter the stoichiometry of litter by increasing the N content, and reduce the C:N ratio of litter, which may change the plant element balance and influence the microbial decomposition rates, thereby affecting SOM formation [78]. Most studies on the effects of N deposition on plant-derived SOM are based on short-term fertilization experiments, but its indirect effects on SOM dynamics, particularly in the context of long-term nutrient cycling, are still poorly understood. Increased precipitation promotes litter input and root biomass, increasing SOM sources. In contrast, reduced precipitation and frequent droughts can negatively affect biomass production in forests and shrubs, decreasing plant productivity and SOM inputs [25]. Prolonged droughts can further reduce SOM availability, alter species composition, and accelerate SOM loss. Delayed precipitation increases fungal and bacterial biomass, accelerating SOM formation. However, both extreme precipitation or drought events can accelerate SOM loss or reduce plant-derived OM inputs, thus inhibiting SOM formation and accumulation [79].

4.4.2. Impacts of Climate Change on Microbial-Derived SOM

Climate change influences the sources and formation processes of microbial-derived SOM by regulating soil microbes, enzyme activities, community composition, and nutrient availability. Global warming can increase soil microbial metabolic and extracellular enzyme activities and accelerate the transformation of plant residues and microbial iterative processes, thus increasing microbial-derived OM inputs [80]. However, long-term enhancement of microbial decomposition accelerates SOM loss, releases more CO2, and exacerbates the negative impact of climate change. Elevated CO2 levels alter the soil microbial community composition, affecting microbial-derived SOM formation. Specifically, increased CO2 concentrations promote plant-derived OM inputs, whereas the inputs of abundant litter and root C favor the activity of R-strategy microbes, which shifts the microbial community composition and influences the SOM dynamics [81]. Additionally, elevated CO2 levels and N deposition affect the C and N balance of forest soil, impacting microbial composition and SOM dynamics. Long-term N deposition leads to soil acidification, which inhibits microbial growth and enzyme activity, thereby reducing microbial contributions to SOM. Precipitation changes regulate soil microbial activities through soil moisture. For example, increased precipitation enhances microbial activities, but excessive or extreme precipitation can cause anoxia and inhibit microbial metabolism. In contrast, drought reduces microbial activity and disrupts the source and formation of microbial-derived SOM [82]. Finally, a deeper understanding of these interactions suggests that the effects on microbial-derived SOM are not merely additive but rather involve complex feedback. Shifts in microbial communities driven by changes in factors such as temperature, nutrient availability, and moisture could alter the resilience of forest soils to climate extremes, potentially affecting the input and long-term stability of soil C [83]. Therefore, future research should not only investigate the direct effects of climate change on microbial communities but also elucidate the underlying mechanisms driving microbial responses and their implications for soil C dynamics.

4.4.3. Impacts of Climate Change on Soil Fauna-Derived SOM

Although soil fauna contributes less directly to SOM than plants and microbes, they still play a critical role in forest soil. For example, soil fauna alters the chemical composition of litter, reduces soluble polyphenols levels, and decreases the C/N ratio through their intestinal activities, thereby affecting SOM formation and decomposition [84]. However, research on the impact of climate change on soil fauna-derived SOM remains limited. Some studies suggest that climate change affects soil fauna-derived SOM by influencing the abundance, diversity, habitat, and spatial distribution of soil fauna. Temperature changes caused by climate warming and extreme climate events strongly impact soil fauna. For example, during the freezing period in cold forest soils, the dominant species of soil fauna vary at different stages, and the density, diversity, and composition of the soil faunal community are significantly altered by temperature fluctuations [85], influencing the dynamics of soil fauna-derived SOM. Additionally, soil fauna is very sensitive to natural drought, which can hinder the formation and retention of SOM [86]. Precipitation changes can also inhibit soil fauna activity by destroying their habitats, thus reducing SOM input. Changes in plants and microbes also indirectly affect the sources and formation of soil fauna-derived SOM. For example, N deposition changes the plant nutrient balance and soil faunal community structure, whereas variations in litter quality affect decomposition processes involving benthic fauna [87,88]. In summary, while soil fauna contributes less directly to SOM than other factors, they still play a crucial role in SOM formation. Through various direct and indirect mechanisms, climate change affects soil faunal populations and activities, which in turn can influence SOM dynamics.
Overall, the sources and formation processes of forest SOM are affected by multiple climate change factors simultaneously. Hyvönen et al. [89] suggested that, owing to the strong interactions among various factors, single-factor studies and responses may be misleading, and the intensity of future feedback effects may exceed the short-term responses of single factors. Therefore, future research should comprehensively consider the combined effects of various climate change scenarios and simulate dynamic changes in multiple dimensions.

4.5. Measurement Methods and Model-Based Analysis Techniques

The measurement and monitoring methods can be divided into four categories: biomarker and indicator analysis, organic matter component and quantitative analysis, in situ monitoring analysis, and mathematical model-based dynamic analysis.

4.5.1. Biomarker and Indicator Analysis

Biomarkers and stable isotope labeling are used to trace and identify SOM dynamics. Common plant-derived biomarkers include lignin phenols, lipids, and sugars. Specifically, lignin phenols or their monomers (e.g., vanillyl, syringyl, and cinnamyl) are indicators of plant-derived SOM [90,91], while keratin, cork, and plant wax (e.g., long-chain alkanes and fatty acids) can be used to characterize OM from different plant tissues [92]. Amino sugars, amino acids, and lipids are biomarkers for microbial-derived SOM [93], with amino sugars being more stable and widely used for microbial residues. Phospholipid fatty acids are key biomarkers for studying living microbes. Isotopes 13C and 15N and the natural abundances δ13C and δ15N are often used to trace the sources and formation processes of SOM. For example, Jensen et al. [94] used 13C isotope labelling to examine the impact of elevated CO2 on SOM and reported that newly formed C is incorporated into the pool of granular OM and mineral-associated OM and that increased CO2 concentrations stimulate rapid turnover of the soil C pool.

4.5.2. Organic Matter Component and Quantitative Analysis

The standard methods used to qualitatively study SOM include a range of analytical techniques to characterize its chemical bonds and functional groups. NMR and infrared spectroscopy (e.g., Fourier transform infrared spectroscopy and Fourier transform ion cyclotron resonance mass spectrometry) are widely used for this purpose, with the NMR signals or infrared absorption peaks of C and hydrogen being examined in different chemical environments; other methods, such as pyrolysis gas chromatography/mass spectrometry (GC–MS) and differential scanning calorimetry–thermogravimetry (DSC–TG), are also used to investigate the sources and composition of SOM [95,96,97]. To determine the SOM content, the potassium dichromate oxidation method is most widely used, which includes the potassium dichromate sulfuric acid oxidation method and the hydration thermal potassium dichromate oxidation–volumetric method [98]. Additionally, the SOM content can be determined from the soil organic C content using the van Bemmelen conversion coefficient (typically 0.58) and methods such as dry burning and alkali solution colorimetry, although these techniques tend to have lower accuracy [99]. Imaging techniques (e.g., scanning electron microscopy) and physical fractionation (e.g., light and recombination fractionation) are also used to assess the contributions of different sources and components of SOM [100].

4.5.3. In Situ Monitoring Analysis

In situ monitoring mainly includes the litter collection and decomposition bag method, in situ soil respiration monitoring, and in situ manipulation experiments (e.g., climate change scenario simulation). These techniques enable continuous observation of SOM dynamics without disturbing the natural environment and comparison of climate change effects. The monitoring scales vary, with various methods suited for different levels of observation, such as plot-scale studies to examine local dynamics, regional-scale studies to assess broader ecosystem impacts, or global-scale monitoring to understand large-scale changes in SOM across diverse ecosystems. For example, the litter collection and litterbags method is often used for local-scale monitoring. Pan et al. [101] employed the decomposition bag method to study temperate broad-leaved tree root decomposition over 7 years. These findings revealed a significant positive linear correlation between the birch root decomposition coefficient and root diameter. In situ soil respiration monitoring has been widely used at various scales to study the relationships between soil C cycle and environmental changes. Meyer et al. [102] monitored soil respiration under both live birch trees and dead trees killed by insect pests in northern Finland. The results revealed faster SOM turnover under live trees, which positively impacted C storage, whereas dead trees led to slower SOM turnover but greater soil C storage owing to the continuous input of dead wood OM. In situ experiments controlling for ecological variables (e.g., temperature and precipitation) can also be used to understand their impacts on forest SOM. For example, Marty et al. [103] conducted a 9-year experiment in a boreal forest, in which samples were cultured at different temperatures. They reported a strong response of soil respiration to temperature changes, although the soil organic C content remained largely unchanged, possibly due to microbial adaptation to warming. Furthermore, SOM monitoring analyses should include indices and SOC components that provide relevant information about soil health, such as the carbon management index (CMI), which uses native forests as a reference and can help assess the sustainability of soil C management practices [104].

4.5.4. Mathematical Model-Based Dynamic Analysis

Models based on key indicators, measured data, and statistical methods can accurately analyze and predict the contributions of various sources to SOM and their dynamic changes. LiDAR data combined with SOM data measured from multiple sample points can be analyzed using partial least squares regression to establish a mode for rapid investigation and inversion of the surface SOM content [105]. The Bayesian tracer mixing model MixSIAR has been used to quantify OM contributions from different sources. For example, higher organic C burial rates and reserves were measured in mangrove cores in Mexico that were less affected by rivers and had more forest debris input [106]. The decomposition and formation dynamics of SOM have been simulated using models such as Rothamsted C (RothC), Yasso, and CENTURY. For example, the RothC model, which is based on SOM fractionation, can divide SOM into different components to assess its decomposition dynamics and responses to climate change [107]. Additionally, statistical analysis methods such as the stochastic forest model and structural equation model are widely used to analyze the complex relationships between SOM dynamics and variables (e.g., climate and stand structure) [108]. The spatial distribution model of SOM, derived from remote sensing image data (e.g., hyperspectral images) and geographic information system (GIS) technology, also supports large-scale research on the sources and formation of SOM [109].
In general, owing to the complex composition and slow decomposition of SOM, combining multiple techniques to study SOM dynamics and further explore its feedback effects on climate change across large spatial and temporal scales is necessary.

5. Conclusions

Although there were some limitations associated with the tools used and the datasets available, the results clearly and meaningfully showed the following. (1) There is a solid knowledge base and research foundation, and a favorable upward trend in in-depth research related to SOM and C in forests, driven by increasing scientific contributions. Research hotspots have shifted to microbial mechanisms and multiparameter climate change interactive effects. (2) Forest SOM is derived mainly from plants, whereas soil microbes play a vital role in the C cycle and the final contributions, and soil fauna also makes great contributions to these processes but receive less attention. (3) The formation of SOM is a complex and multifaceted process involving contributions from plant-, microbial-, and soil fauna-derived OM. These OM components undergo decomposition, synthesis and stabilization and are finally transformed into stable SOM. (4) The impacts of climate change on the sources and formation processes of forest SOM are complex, involving both positive and negative feedback, necessitating scientific trade-offs. (5) Measurement and monitoring technology is constantly advancing in an effort to detect more profound changes. Similar analyses in the future should broaden the scope of literature databases, diversify keyword searches, and select highly relevant literature accurately. The findings still provide valuable insights into the current research status and fill the research gap by providing an overview through quantitative data mining and visualization methods.
Future research should focus on the following directions: (1) strengthen cooperation across different research teams and countries and regions under interdisciplinary integration; (2) strengthen research on the composition and dynamics of soil fauna-derived SOM, specific and convenient biomarkers, the impacts of climate change on soil fauna-derived SOM formation, and the interactions of this SOM with other biotic and abiotic factors, given the significant contributions of soil fauna to SOM; (3) strengthen the study of the impacts of extreme climate change on forest SOM dynamics, as forest ecosystems face the greatest net impact under frequent extreme climate events, which may have great direct, indirect, or delayed impacts on SOM; (4) strengthen research on the impacts of multiple aspects of climate change (multifactor interactions) on forest SOM dynamics, as these nonlinear interactions—such as warming, precipitation changes, and N deposition—have profound implications; and (5) strengthen the integration of multiple technologies and monitoring methods, further explore the change mechanisms at the microscale, implement long-term monitoring combined with smart technology at the macroscale, and explore the potential changes and feedback effects on climate change in depth from the perspective of large spatial and temporal scales.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f16020336/s1.

Author Contributions

Conceptualization, Z.S. and C.L.; methodology, Z.S. and Y.L.; validation, Z.S.; formal analysis, Z.S. and K.Y.; investigation, Z.S., Y.P. and H.Z.; data curation, Z.S., K.Y., H.Z. and C.L.; writing—original draft preparation, Z.S.; writing—review and editing, Z.S., K.Y., Y.P., H.Z. and Y.L.; visualization, Z.S.; supervision, Y.L.; funding acquisition, Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the National Natural Science Foundation of China (42330503, 32271633, and 32201342) and the “Pioneer” and “Leading Goose” R&D Program of Zhejiang (2022C02019).

Data Availability Statement

No data were used for the research described in this article and the data are available from the authors upon reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

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Forests 16 00336 g001
Figure 1. Research framework.
Figure 1. Research framework.
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Forests 16 00336 g002
Figure 2. Trends in annual publications and total citations. No studies from before 1984 were retrieved.
Figure 2. Trends in annual publications and total citations. No studies from before 1984 were retrieved.
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Forests 16 00336 g003
Figure 3. Author co-occurrence networks. Nodes represent authors. The node size reflects the number of documents published by the author. The thickness of the links between nodes represents the degree of academic collaboration between authors. Thicker lines indicate closer collaboration.
Figure 3. Author co-occurrence networks. Nodes represent authors. The node size reflects the number of documents published by the author. The thickness of the links between nodes represents the degree of academic collaboration between authors. Thicker lines indicate closer collaboration.
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Forests 16 00336 g004
Figure 4. National and regional publication distribution. Countries with 100 or more publications are marked, and the number of publications is shown in parentheses. Below the horizontal line is the total link strength of countries calculated by VOSviewer, which represents the frequency and closeness of cooperation between that country and others. The publication data for England, Scotland, Wales, and Northern Ireland are uniformly classified as the United Kingdom, whereas the publication data for Hong Kong, Macao, and Taiwan are uniformly classified as China.
Figure 4. National and regional publication distribution. Countries with 100 or more publications are marked, and the number of publications is shown in parentheses. Below the horizontal line is the total link strength of countries calculated by VOSviewer, which represents the frequency and closeness of cooperation between that country and others. The publication data for England, Scotland, Wales, and Northern Ireland are uniformly classified as the United Kingdom, whereas the publication data for Hong Kong, Macao, and Taiwan are uniformly classified as China.
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Forests 16 00336 g005
Figure 5. High-frequency keyword clustering network. Synonymous keywords (e.g., “climate change” and “climate-change”) were merged. Nodes represent high-frequency keywords. The node size represents the occurrence frequency of keywords. The node color represents the cluster of keywords. The thickness of the links between nodes represents the strength of their connection.
Figure 5. High-frequency keyword clustering network. Synonymous keywords (e.g., “climate change” and “climate-change”) were merged. Nodes represent high-frequency keywords. The node size represents the occurrence frequency of keywords. The node color represents the cluster of keywords. The thickness of the links between nodes represents the strength of their connection.
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Forests 16 00336 g006
Figure 6. Evolving keyword trends. The occurrence time of keywords is based on the default average publication year from the software, that is, the sum of the occurrence year of each keyword divided by the number of occurrences.
Figure 6. Evolving keyword trends. The occurrence time of keywords is based on the default average publication year from the software, that is, the sum of the occurrence year of each keyword divided by the number of occurrences.
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Forests 16 00336 g007
Figure 7. Sources and formation processes of forest SOM. (a) SOM sources; (b) plant-derived SOM formation; (c) microbial-derived SOM formation; (d) soil fauna-derived SOM formation. POM represents particulate organic matter. MAOM represents mineral-associated organic matter.
Figure 7. Sources and formation processes of forest SOM. (a) SOM sources; (b) plant-derived SOM formation; (c) microbial-derived SOM formation; (d) soil fauna-derived SOM formation. POM represents particulate organic matter. MAOM represents mineral-associated organic matter.
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Table 1. High-frequency keywords occurring more than 100 times.
Table 1. High-frequency keywords occurring more than 100 times.
KeywordFrequencyTotal Link StrengthKeywordFrequencyTotal Link Strength
Climate change14018582Vegetation1771093
Dynamics5833864Land use change1711110
Organic matter5373181Stock1701138
Forest5303371Carbon sequestration1651142
Nitrogen4993410Soil respiration1651223
Carbon4402840Temperature sensitivity1591165
Decomposition4072948Boreal forest148969
Soil organic carbon3282135Dissolved organic carbon142805
Organic carbon3111965Growth135852
Biomass3082119Impact135823
Soil organic matter2771727Responses135964
Litter decomposition2561752Litter129874
Storage2551788Leaf litter128895
Soil2471497Model120775
Respiration2461819Management119805
Sequestration2461680Microbial community119836
Matter2351574Pattern115762
Forest soils2181376Net primary production109741
Ecosystems2161449Terrestrial ecosystems109755
Temperature2111522Turnover108774
Land use1891219Elevated CO2106694
Microbial biomass1881310Mineralization105712
Soil carbon1801304Diversity103659
CO21771198Carbon cycle102749
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MDPI and ACS Style

Shen, Z.; Yue, K.; Peng, Y.; Zhang, H.; Li, C.; Li, Y. A Bibliometric Analysis of Research on the Sources and Formation Processes of Forest Soil Organic Matter Under Climate Change. Forests 2025, 16, 336. https://doi.org/10.3390/f16020336

AMA Style

Shen Z, Yue K, Peng Y, Zhang H, Li C, Li Y. A Bibliometric Analysis of Research on the Sources and Formation Processes of Forest Soil Organic Matter Under Climate Change. Forests. 2025; 16(2):336. https://doi.org/10.3390/f16020336

Chicago/Turabian Style

Shen, Zhentao, Kai Yue, Yan Peng, Hui Zhang, Cuihuan Li, and Yan Li. 2025. "A Bibliometric Analysis of Research on the Sources and Formation Processes of Forest Soil Organic Matter Under Climate Change" Forests 16, no. 2: 336. https://doi.org/10.3390/f16020336

APA Style

Shen, Z., Yue, K., Peng, Y., Zhang, H., Li, C., & Li, Y. (2025). A Bibliometric Analysis of Research on the Sources and Formation Processes of Forest Soil Organic Matter Under Climate Change. Forests, 16(2), 336. https://doi.org/10.3390/f16020336

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