A Comparison of the Impact of Latitude on the Root-Shoot Ratio of Natural and Planted Forests

Abstract

The forest root-shoot ratio (R/S) is an important indicator of the structure and function of forest ecosystems. It reflects the adaptive strategies of plants to environmental changes, and its pattern of change along the latitudinal gradient is of great significance for understanding the response of forest ecosystems to environmental changes. Although numerous studies have addressed the relationship between climate, soil conditions, and the ratio of below-ground biomass to above-ground biomass (R/S) at the local scale, the pattern of R/S variations along the latitudinal gradient in different types of forests, as well as the dominant factors, remain unclear. This study, based on field surveys and literature collected from 2005 to 2020 on 384 planted forests and 541 natural forests in China, investigates the patterns of forest root-shoot ratio variation along latitudinal gradients in planted and natural forests. The study demonstrated a positive correlation between forest R/S ratio and increasing latitudinal gradients across different forest types, including planted and natural forests (p < 0.001). The results demonstrated a negative correlation between R/S in both planted and natural forests and mean annual temperature, annual precipitation and soil phosphorus content. Conversely, a positive correlation was observed between R/S and soil nitrogen content and soil pH. It can be observed that plantation forests are more susceptible to alterations in forest factors than natural forests. Latitudinal patterns can not only directly affect the R/S of planted and natural forests, but also affect forest R/S by influencing climate and forest factors and the interactions of the factors together. Our study distinguishes the pattern of R/S changes along the latitudinal gradient in planted and natural forests and its influencing factors. These findings are important for understanding the pattern changes in different forest ecosystems and provide a theoretical basis for efficiently guiding forest management.

1. Introduction

Forests, as the largest terrestrial ecosystems, play a pivotal role in regulating the global carbon cycle [1]. Within these ecosystems, biomass is generally classified into above-ground and below-ground components. The ratio of root biomass to above-ground biomass—referred to as the root-shoot ratio (R/S)—serves as a critical parameter for elucidating forest developmental dynamics and resource allocation strategies [2,3]. Vegetation resource utilization is profoundly influenced by environmental characteristics, with the R/S ratio mediating nutrient availability. The accessibility of essential resources such as light, soil nutrients, and water is fundamental in determining the patterns of plant biomass allocation. Environmental and topographical factors often dictate the strategies plants employ to access these resources, thereby shaping biomass distribution patterns [4,5,6]. Given that biomass allocation strategies are integral to tree growth [7], the R/S ratio emerges as a crucial indicator for investigating the differential resource utilization strategies among various forest types in response to environmental changes. Although previous studies have demonstrated that both biotic and abiotic factors influence forest biomass distribution [8,9], the effects of these factors on the R/S ratio across forest types of different origins (planted versus natural forests) remain inadequately understood. Enhancing our understanding of these dynamics is essential for informing effective forest management practices.

Biomass allocation between above-ground and below-ground components is intricately regulated by climatic factors, particularly temperature and precipitation [10,11]. Extensive research has demonstrated that temperature impacts vegetation through both direct and indirect pathways [12]. Directly, temperature changes influence photosynthesis, thereby affecting plant growth and biomass accumulation [13]. Indirectly, temperature modulates the availability of soil nutrients, soil temperature, and microbial activity, which together shape vegetation growth and alter biomass allocation patterns [14]. For instance, it has been demonstrated that temperature can influence the capacity of plants to absorb organic matter from the soil by affecting the symbiotic flora of plant roots. As temperature rises, the growth of lateral and adventitious roots is inhibited, which subsequently impairs the plant’s ability to adapt to heat. This, in turn, results in a reduction in the plant’s root-shoot ratio [15]. In colder environments, forests tend to allocate more biomass to the roots, a response to lower nutrient availability due to reduced nutrient cycling rates and constrained soil solution transport at low temperatures [5,13]. Precipitation also plays a significant role in biomass allocation. As precipitation diminishes relative to evapotranspiration demand, limitations on below-ground resources intensify, leading to altered biomass distribution patterns [16,17]. Research has shown that under increasing drought stress, the root-shoot ratio tends to increase, with trees allocating a higher proportion of biomass to the roots to enhance the efficiency of soil water uptake during periods of moisture scarcity [3,18]. Experimental results by Poorter (2012) [19] and colleagues also confirm that plants exhibit higher root-shoot ratio under drought stress. Conversely, research has indicated that as water levels increase, carbon dioxide concentrations in the soil decrease, and roots grow in a carbon-poor environment. This leads to a reduction in root growth, as reflected in a decline in the root-shoot ratio [20].

Soil nutrients are fundamental determinants of forest biomass distribution, exerting a direct influence on growth and allocation strategies. As the immediate medium in which forests thrive, changes in soil nutrient composition have a pronounced impact on vegetation development [21,22]. Nitrogen (N) and phosphorus (P) are the primary limiting nutrients for forest biomass accumulation and allocation [23]. Nitrogen is crucial for chlorophyll production and photosynthesis. In nutrient-poor soils, plants allocate more biomass to roots to enhance nutrient and water absorption, leading to an increased root-shoot ratio (R/S) [24]. Conversely, nitrogen supplementation improves soil fertility, which enables plants to invest more in above-ground biomass for effective light capture [25,26]. Phosphorus, essential for energy transfer and photosynthesis, exerts a distinct influence on biomass allocation. Under phosphorus-deficient conditions, plants typically reduce photosynthesis and increase biomass allocation to roots to maximize nutrient acquisition [27]. In contrast, sufficient phosphorus availability promotes the development of above-ground biomass to optimize photosynthetic efficiency. Soil pH further modulates nutrient dynamics by affecting the chemical forms and solubility of nutrients, particularly nitrogen and phosphorus. In acidic soils, phosphorus often forms insoluble compounds, reducing its bioavailability. Similarly, in soils that are either highly acidic or alkaline, alterations in nitrification and denitrification processes can decrease nitrogen availability. These changes compel plants to adjust their biomass allocation strategies accordingly [28]. In summary, the interplay between soil nutrient availability and plant allocation strategies highlights the critical importance of effective soil management for maintaining forest ecosystem productivity and resilience.

The forest root-shoot ratio (R/S) is influenced by key forest factors, including forest age, average breast diameter and forest density. Research indicates that the accumulation and alteration of vegetation biomass are predominantly influenced by biological determinants, including forest age and tree size [29,30,31]. As forests mature, plants exhibit significant shifts in their resource allocation strategies [29]. In particular, the R/S tends to decline consistently with increasing forest age and plant height across various vegetation types [32]. Moreover, forest density plays a crucial role in influencing photosynthetic efficiency [33], and variations in forest density are closely associated with changes in biomass allocation patterns among different forest types [34]. Empirical studies have conclusively demonstrated that as forest density increases, there is a corresponding rise in root biomass alongside a decrease in stem biomass [35].

The biogeographic patterns of forest biomass allocation are intimately linked to the structure of terrestrial ecosystems [6]. Latitude, which largely determines ecosystem type, is, therefore, a critical factor in shaping the latitudinal variations in forest root-shoot ratios. Previous research has shown that, in natural settings, trees in colder regions typically allocate a greater proportion of their biomass to roots while investing relatively less in leaves [36,37]. This strategy enhances resource acquisition under nutrient-poor conditions. In high-latitude areas, where reduced nutrient cycling rates and limited soil solution movement prevail, plants have evolved to allocate more biomass to their roots, thereby exhibiting elevated root-shoot ratios [36,38].

Based on the foregoing introduction, we analyzed data from 384 planted forests and 541 natural forest ecosystems surveyed in China between 2005 and 2020 to investigate how root-shoot ratio (R/S) patterns vary with latitude across different forest types. We propose the following hypotheses: (1) At a macro-scale, the root-shoot ratio (R/S) of planted and natural forests will be affected by the latitudinal gradient. (2) The direct impact of latitudinal patterns on the root-shoot ratio (R/S) of planted and natural forests is less than its indirect impact. (3) Latitudinal patterns not only directly affect the R/S of planted and natural forests but also jointly influence forest R/S by modulating climate, forest factors, and their interactions.

2. Materials and Methods

2.1. Study Area and Sample Data

This study utilized data from 384 plantations and 541 natural forest ecosystems surveyed across China between 2005 and 2020 to compare the root-to-shoot ratio (R/S) between these two forest types. The study plots covered latitudes from 19.1° N to 53.5° N, longitudes from 79.7° E to 129.3° E, and altitudes ranging from 1 m to 5000 m. Both primary field survey data and secondary literature data were included in the analysis, with the same methodology applied to ensure consistency.

In each forest plot, a minimum of four randomly selected subplots (30 m × 30 m) were established. All trees with a diameter at breast height (DBH) greater than 1 cm within these subplots were identified, enumerated, and measured. For biomass estimation, 10 representative trees per species (DBH > 5 cm) were selected in each subplot. The aboveground biomass (AGB) was divided into three components: bark, branches, and leaves. The trunk was sectioned at 2-m intervals, and the fresh weight of each section was recorded. Representative branches were selected using the mean standard branch method, weighed multiple times to obtain fresh weight, and the leaves were separated and stored in sealed bags with desiccant for subsequent weighing. All components were then dried at 70 °C for 48 h to determine their dry weights, which were used to calculate the total AGB. For belowground biomass (BGB), the entire root system of each sampled tree was excavated to a depth of 50 cm. The roots and root clumps were carefully separated from the soil, and the fresh weight of the roots was recorded. The root samples were then transported to the laboratory for additional weighing. To determine the dry weight, the root samples were placed in a ventilated drying oven at 85 °C until they reached a constant weight. The dry weight of the roots was then used to calculate the BGB.

Finally, the root-shoot ratio (R/S) was calculated as the ratio of BGB to AGB, providing insight into the resource allocation strategy of trees in relation to their aboveground and belowground biomass. The consistent methodology for both the field and literature data ensures the robustness and comparability of the findings across diverse forest ecosystems.

2.2. Environmental Data

The data for annual mean temperature (MAT), annual mean precipitation (MAP), mean air temperature of the hottest month (MAHT), mean annual evaporation (MAE), and mean air temperature of the coldest month (MACT) were sourced from the WorldClim global climate database (version 2.1), which has a spatial resolution of 1 km. Furthermore, the annual sunshine duration (ASD) was procured from the website of the Climate Data Center of China Meteorological Administration (http://data.cma.cn/site/index.html, accessed on 17 February 2025), also with a resolution of 1 km. The soil pH, soil nitrogen (http://soil.geodata.cn/, accessed on 31 October 2023), and soil available phosphorus (https://www.osgeo.cn/data/wc137, accessed on 31 January 2023) in the top 30 cm soil layer were extracted from grids with a resolution of 250 m.

2.3. Data Analysis

The relationships between climate factors, soil nutrient factors, forest factors, and the root-shoot ratio (R/S) in both planted and natural forests were examined using general linear regression models. Climate variables encompassed mean annual temperature (MAT), mean annual precipitation (MAP), mean air temperature of the coldest month (MACT), annual sunshine duration (ASD), mean annual evaporation (MAE), and mean air temperature of the hottest month (MAHT). Soil parameters comprised soil nitrogen content (Soil N), soil phosphorus content (Soil P), and soil pH. Forest factor attributes included forests density, forests age, and average diameter at breast height. The analysis was conducted using the R package agricolae (version 4.1.0, R Core Team, 2020). Multivariate correlation analysis was performed with the R package ‘linkET’. The R² value indicated the goodness of fit for model adjustment, while the p value signified statistical significance.

To investigate the interaction effects among climate, soil, and forest factors on the forest root-shoot ratio (R/S), we employed one-way analysis of variance (ANOVA) to examine the pairwise interaction correlations between each variable affecting R/S in both natural and planted forests. Fisher’s least significant difference (LSD) test was subsequently applied for further analysis. With a significance level set at 0.05 for the significance difference test, we utilized Cytoscape (version 3.10.3) to visualize the network [39], with the ‘linkET’ (version 0.0.7.4) package in R being employed for this purpose.

The Random Forest model and variance decomposition were employed to assess the distinct influence of four categories of factors (climatic factors, soil nutrient factors, forest factors, and latitude) on the root-shoot ratio of natural and planted forests. Climatic factors encompassed MAT, MAP, MAE, MAHT, ASD, and MACT. Soil nutrient factors comprised soil N, soil P, and soil pH. Forest factor attributes included forests density, forests age, and average diameter at breast height. Variance decomposition was utilized to ascertain the contribution capacity of each variable factor to the overall model and the cumulative explanatory power of all variables. This variance decomposition analysis was executed using the ‘vegan’ package in the R language. The independent contribution ability of each individual variable factor to the variation of the forest root-shoot ratio (R/S) was analyzed using random forest, and it was ranked based on the relative contribution size (R²). The random forest analysis was conducted using the ‘randomForest’ (version 4.7.11) packages software package and the ‘rfPermute’ (version 2.5.2) software package.

The Structural Equation Model (piecewiseSEM) (version 2.3.0.1) was employed to investigate the impact pathway of climate factors, soil nutrient elements, forest attributes, and latitude patterns on the root-shoot ratio (R/S) in both natural and planted forests. The variables were consolidated into composite groups, thereby establishing the foundation for the structural equation modeling (SEM). This approach, which was resistant to random sampling variances, provided both “marginal” and “conditional” predictor information using R’s “piecewiseSEM”, “nlme” (version 3.1.166), and “lme4” (version 1.1.35.5). The model fidelity was confirmed by Fisher’s C test with a focus on the significance of path coefficient (r < 0.05) and robustness of the model (0 ≤ Fisher’s C/df ≤ 2 and 0.05 ≤ r ≤ 1).

3. Results

In regions of low latitude, the root-shoot ratio in natural forests exceeds that of planted forests. As latitude increases, both types of forests exhibit an increasing trend in root-shoot ratio, with planted forests showing greater sensitivity to latitudinal changes (p < 0.001, Figure 1).

With increasing temperature and precipitation, both forest types show a notable decline in root-shoot ratio, whereas a positive correlation is observed with the annual average evaporation rate (p < 0.001, Figure 2). Additionally, both soil nitrogen and pH exhibit a positive correlation with root-shoot ratio, with an increasing trend in both natural and planted forests (p < 0.001, Figure 3A,C). In contrast, higher soil phosphorus content results in a decrease in R/S, with a more pronounced decline in planted forests (p < 0.001, Figure 3B).

The root-shoot ratio of natural forests and planted was sensitive to changes in forest factors. The root-shoot ratio of natural forests was significantly affected by forest factor, and was positively correlated with forest age (p = 0.04) and forest density (p < 0.001), but negatively correlated with DBH (p = 0.046) (Figure 4A–C). The root-shoot ratio of planted forest was more significantly affected by DBH and forest age. The root-shoot ratio increased with the increase of DBH (p = 0.011) and forest age (p < 0.001) (Figure 4A,B).

Random forest analysis revealed that, aside from climate factors, forest factors were the main contributors to R/S variation in natural forests, while soil nutrients were the predominant influence in planted forests (Figure 5). A heatmap further confirmed significant correlations between R/S and factors such as climate, soil nutrients, and forest characteristics (Figure 6). Notably, the impact of latitudinal patterns on R/S was more pronounced in natural forests than in planted forests (Figure 7). Structural equation modeling indicated that R/S is influenced directly by latitudinal patterns and indirectly through interactions with climate, soil nutrients, and forest factors, with the direct effect being stronger than the indirect effect (Figure 8).

4. Discussion

Root-shoot ratio (R/S), a critical biometric indicator reflecting plant resource allocation strategies, provides mechanistic insights into the functional equilibrium between autotrophic and heterotrophic plant components [2]. Notably, natural forests exhibit higher R/S values than planted forests at lower latitudes. Moreover, both forest types display an increasing trend in R/S with rising latitude. This pattern is likely attributable to changes in the tree growth environment at higher latitudes, which are characterized by lower temperatures and greater seasonal variability [40,41]. Lower temperatures can promote a shift in resource allocation towards the roots, as plants adapt to harsher growing conditions [42]. In colder environments, the underground biomass plays a crucial role in ensuring efficient absorption of water and nutrients, particularly during periods when water availability is limited, such as in winter [43,44]. Additionally, increased seasonal fluctuations in temperature may stimulate enhanced root growth, enabling plants to stabilize water and nutrient uptake under variable conditions [45]. Collectively, these environmental factors prompt trees to allocate a greater proportion of their biomass to roots, thereby facilitating survival in harsher climates [40,41]. Consequently, it can be inferred that the root-shoot ratio of forests generally escalates with increasing latitude [3].

Temperature is a key determinant of plant growth rate, with elevated temperatures generally promoting increased growth and consequently influencing the root-shoot ratio (R/S) [46,47,48]. As temperatures rise, both natural and planted forests show a marked decline in the root-shoot ratio. This is primarily attributed to intensified evaporation with increasing temperatures, which accelerates soil moisture loss and limits root growth [15,49]. Within the 10–34 °C range, plant photosynthetic rates typically increase, and optimal temperatures further enhance photosynthetic efficiency, resulting in greater canopy biomass accumulation [50,51,52]. Consequently, a larger proportion of biomass is allocated to aboveground structures, thereby decreasing the R/S. Rainfall also exerts a significant impact on R/S [53]. Observations indicate that increased rainfall is associated with a decline in R/S in both natural and planted forests. This trend can be explained by the fact that, under conditions of adequate rainfall, plant roots can efficiently absorb water, reducing the necessity for extensive root growth [54]. With sufficient water availability, plants allocate more energy towards canopy growth, leading to a reduction in the root-shoot ratio [2]. Furthermore, planted forests exhibit heightened sensitivity to increased rainfall compared to natural forests, likely due to their lower species diversity and higher dependence on external water inputs [55,56]. Although temperature and rainfall independently affect the root-shoot ratio, their interaction also plays a role. High temperatures increase evaporation, reducing soil moisture and limiting root growth [57]. However, when rainfall increases, it can help mitigate the effects of temperature by replenishing soil moisture [58]. Under such conditions, both natural and planted forests tend to allocate more biomass to the canopy, further reducing R/S. Notably, the heightened sensitivity of planted forests to rainfall changes may amplify the impact of elevated temperatures on R/S dynamics.

Soil plays a pivotal role in forest growth by serving as the primary source of nutrients essential for plant development and ecological functions [59]. Both organic and inorganic constituents in the soil supply critical nutrients, notably nitrogen and phosphorus, which are fundamental to plant growth and metabolic processes [60,61]. Previous research has demonstrated that an adequate supply of soil nitrogen can stimulate root growth and expand the root surface area, thereby enhancing a plant’s capacity to absorb water and nutrients. This process facilitates improved access to water and nutrients within the soil, promoting overall growth and development [62,63]. These findings align with our own research results. The increase in soil Nitrogen (N) content is shown (Figure 3A) to significantly elevate the root-shoot ratio in both planted and natural forests. Soil Phosphorus (P) content, another crucial factor influencing plant growth, is shown (Figure 3B) to have a negative correlation with the root-shoot ratio of both types of forests. This could be attributed to the fact that an adequate supply of soil phosphorus facilitates leaf growth and development [64,65]. Phosphorus is an important component of chloroplast membranes and biomolecules such as nucleic acids, and is essential for photosynthesis and the conversion of light energy [66,67]. Moreover, an adequate supply of phosphorus can increase leaf area and enhance photosynthetic efficiency, thereby influencing the R/S in forest ecosystems. Soil pH is another crucial factor affecting nutrient availability, microbial activity, and root development. Elevated soil pH has been associated with increased microbial activity, improved organic matter decomposition, and enhanced availability of nutrients such as calcium and magnesium, which are vital for root growth [68,69]. Conversely, low pH levels can lead to the increased availability of toxic ions, such as aluminum, which inhibit root elongation and overall root growth [70]. This aligns with our findings that the root-shoot ratio increases with soil pH. Higher pH levels create a more favorable environment for root development by promoting soil aeration and enhancing the formation of symbiotic relationships between roots and soil microbes, such as mycorrhizal fungi, which facilitate nutrient uptake [71,72,73]. Additionally, higher soil pH can mitigate the suppression of microbial activity, fostering a balanced nutrient cycling process that further supports root growth and development [74].

Forest factors encompass various structural and compositional attributes, including forest density, age structure, and tree diameter at breast height (DBH), all of which significantly influence vegetation distribution, growth dynamics, and competition within forest ecosystems [75]. These factors, in turn, regulate the formation and variation of the root-shoot ratio (R/S). Our findings indicate that in planted forests, the R/S decreases with increasing forest age, whereas no significant correlation is observed between R/S and forest age in natural forests. This discrepancy may be attributed to the role of forest age structure in shaping vegetation growth stages and competitive interactions [76]. Younger forests often exhibit more vigorous vegetation growth and heightened competition among plants, thereby prompting plants to allocate more energy towards root growth in order to access increased water and nutrient resources [77,78]. As the forest matures, ecological niches stabilize, and once the root system’s nutrient utilization reaches equilibrium, energy investment shifts towards canopy growth, resulting in greater aboveground biomass accumulation. This shift underlies the observed negative correlation between forest age and R/S in planted forests. Forest density is another key factor influencing resource competition and biomass allocation in forest ecosystems. Higher forest density intensifies competition among plants, often compelling certain species to invest more in root development to enhance their access to water and nutrients [79,80]. In natural forests, R/S exhibits a significant positive correlation with forest density, suggesting that as tree density increases, heightened competition for light may drive greater root growth. However, no significant linear relationship is observed between forest density and R/S in planted forests. This divergence likely stems from human interventions in planted forests, where management practices regulate tree spacing and maintain prescribed density levels [81]. Consequently, planted forests exhibit lower sensitivity to fluctuations in forest density. The observed increase in the root-shoot ratio of natural forests correlates with escalating forest density. The positive correlation between R/S and forest density in natural forests can be attributed to increased canopy coverage in denser forests, which restricts light penetration and reduces photosynthetic efficiency for understory vegetation [82,83,84]. To optimize the use of limited light energy resources, these plants may enhance the growth of their root systems, thereby influencing the root-shoot ratio of natural forests. Furthermore, our results show that in planted forests, R/S is significantly positively correlated with DBH. This relationship likely arises because trees with larger DBH are generally more competitive and exhibit higher resource utilization efficiency. Specifically, larger trees tend to develop more extensive root systems, enabling them to absorb water and nutrients more effectively from the soil. As a result, trees with larger DBH can exploit a greater proportion of available resources within a given area, leading to an increase in R/S. This trend is clearly illustrated in Figure 4B, which demonstrates the positive correlation between DBH and R/S in planted forests [85,86].

The root-to-shoot ratio (R/S) is influenced by a multitude of factors, including soil nutrient availability, climatic conditions, and species-specific traits. A comprehensive understanding of R/S is essential for assessing forest health and ecosystem functionality, as it serves as a key indicator of resource allocation strategies and forest resilience to environmental stressors. While previous studies have often focused on the effects of individual factors, our research underscores the intricate, multifactorial nature of biomass allocation. Specifically, we demonstrate how temperature, precipitation, soil nutrients, and forest density interact to regulate R/S, offering a more holistic perspective on how forests adapt to environmental pressures. From an ecosystem services perspective, forests with greater root biomass play a crucial role in soil stabilization, carbon sequestration, and nutrient cycling, thereby enhancing ecosystem sustainability. Investigating the variability of R/S in response to environmental factors provides critical insights into the potential impacts of future climate change on forest ecosystems. Such knowledge is instrumental in predicting forest responses to shifting climatic conditions and can inform conservation strategies and policy-making to promote forest resilience and long-term ecological stability.

5. Conclusions

To investigate the latitudinal variation in root-to-shoot ratio (R/S) between planted and natural forests, we analyzed data from 926 forest plots across 163 sites in China. Our findings indicate that R/S in both forest types is shaped by a complex interplay of multiple factors. As latitude increases, both natural and planted forests exhibit an upward trend in R/S, with the increase being more pronounced in planted forests. A hierarchical analysis of influencing factors reveals that climatic and soil variables predominantly regulate R/S in planted forests, whereas forest structural attributes and climatic factors play a more significant role in shaping R/S in natural forests. Latitude exerts both direct and indirect effects on R/S, often interacting with climatic variables to modulate biomass allocation. Notably, the direct influence of latitude on R/S surpasses its indirect effects. These findings contribute to a deeper theoretical understanding of forest biomass allocation and provide valuable insights for the sustainable management and conservation of forest ecosystems under changing environmental conditions.

Author Contributions

J.G.: conceptualization, methodology, and investigation. M.Y., J.X. and X.Z.: formal analysis. J.S.: writing—original draft. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

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Figures

Figure 1. Panel (A) presents an image of a representative sampling site, while Panel (B) illustrates the linear relationship between the root-to-shoot ratio (R/S) and latitude. In Panel (B), red corresponds to natural forests, and blue corresponds to planted forests. The coefficient of determination (R2) quantifies the model’s explanatory power, while p-values indicate the statistical significance of the observed relationships.

Figure 2. The linear relationship between the forest root-to-shoot ratio (R/S) and six climate factors is shown. Panel (A) represents annual mean temperature, Panel (B) represents average sunshine duration, Panel (C) represents the mean temperature of the coldest month, Panel (D) represents the mean air temperature of the hottest month, Panel (E) represents annual mean evaporation, and Panel (F) represents annual mean precipitation. Red corresponds to natural forests, while blue corresponds to planted forests. The coefficient of determination (R2) indicates the model’s explanatory power, and p-values reflect the statistical significance of the relationships.

Figure 3. The linear relationship between the forest root-to-shoot ratio (R/S) and soil factors is shown. Panel (A) represents soil nitrogen (N) content, Panel (B) represents soil phosphorus (P) content, and Panel (C) represents soil pH. Red corresponds to natural forests, while blue corresponds to planted forests. The coefficient of determination (R2) indicates the model’s explanatory power, and p-values reflect the statistical significance of the relationships.

Figure 4. The linear relationship between the forest root-to-shoot ratio (R/S) and three forest factors is depicted. Panel (A) shows forest age, Panel (B) shows the average diameter at breast height, and Panel (C) shows forest density. Red represents natural forests, while blue represents planted forests. The coefficient of determination (R2) indicates the explanatory power of the model, while p-values reflect the statistical significance of the relationships.

Figure 5. This analysis provides insights into the relationship between four key factors (climatic, soil, forest, and latitudinal patterns) and the root-shoot ratio (R/S) in both planted and natural forests. The colors used are as follows: red for forest factors, blue for latitudinal patterns, yellow for climatic factors, and orange for soil factors. Panel (A) represents natural forests, while Panel (B) represents planted forests. R2 indicates the model’s goodness of fit, while p represents the significance level of the relationships. Asterisks indicate significance (* p [less than] 0.05; ** p [less than] 0.01; *** p [less than] 0.001). Mean Squared Error (MSE), used to evaluate model accuracy, is reported in the figure legend to avoid redundancy.

Figure 6. Multivariate correlation analysis of root-shoot ratio in natural and planted forests with potential influencing factors. The influencing factors include climatic factors (Mean Annual Temperature (MAT), Mean Annual Precipitation (MAP), Mean Air Temperature of the Hottest Month (MAHT), Mean Annual Evaporation (MAE), Mean Air Temperature of the Coldest Month (MACT), Average Sunshine Duration (ASD), soil nutrient factors (Soil N content, Soil P content, Soil pH), forest factors (Forest Age, Average Diameter at Breast Height, Forest Density) and latitude factors. (A) refers to natural forests, while (B) refers to planted forests. Detailed explanations of the asterisks (*, **, ***) are provided in Figure 5.

Figure 7. The factors influencing the root-to-shoot ratio (R/S) in both natural and planted forests, along with the relative contribution of each factor, are depicted. On the left side of each figure, the proportion of influence from different factors is represented, with orange indicating soil factors, blue for latitude, red for forest-specific factors, and yellow for climate factors. On the right side of each figure, a significance analysis is provided. Panel (A) corresponds to natural forests, while Panel (B) represents planted forests. The coefficient of determination (R2) reflects the goodness of fit for the model, while p-values indicate the significance level of the results. Detailed explanations of the asterisks (*, **, ***) are provided in Figure 5.

Figure 8. The relationship between the root-shoot ratio of natural and planted forests with climatic factors, soil factors, forest factors. Path diagram represents the standardized results of the final structural equation model (SEM) testing the relationships among variables. The numbers adjacent to arrows are path coefficients, which is the direct normalized effect size of that relationship. (A) refers to natural forests, while (B) refers to planted forests. Asterisks indicate significance (*** p [less than] 0.001; ** p [less than] 0.01; * p [less than] 0.05). R2 indicates the goodness of fit for generalized additive model (GAM).

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