Natural Secondary Forest Research Articles

A Study on the Growth Model of Natural Forests in Southern China Under Climate Change: Application of Transition Matrix Model

This study establishes a climate-sensitive transition matrix growth model and predicts forest growth under different carbon emission scenarios (representative concentration pathways RCP2.6, RCP4.5, and RCP8.5) over the next 40 years. Data from the Eighth (2013) and Ninth (2019) National Forest Resource Inventories in Chongqing and climate data from Climate AP are utilized. The model is used to predict forest growth and compare the number of trees, basal area, and stock volume under different climate scenarios. The results show that the climate-sensitive transition matrix growth model has high accuracy. The relationships between the variables and forest growth, mortality, and recruitment correspond to natural succession and growth. Although the number of trees, basal area, and stock volume do not differ significantly for different climate scenarios, the forest has sufficient seedling regeneration and large-diameter trees. The growth process aligns with succession, with pioneer species being replaced by climax species. The proposed climate-sensitive transition matrix growth model fills the gap in growth models for natural secondary forests in Chongqing and is an accurate method for predicting forest growth. The model can be used for long-term prediction of forest stands to understand future forest growth trends and provide reliable references for forest management. Forest growth can be predicted for different harvesting intensities to determine the optimal intensity to guide natural forest management in Chongqing City. The results of this study can help formulate targeted forest management policies to deal more effectively with climate change and promote sustainable forest health.

Development of Polymorphic Index Model for Assessing Subtropical Secondary Natural Oak Forest Site Quality Under Complex Site and Climate Variables

Site and climate conditions are the key determinants controlling dominant height growth and forest productivity, both independently and interactively. Secondary natural oak forests are a typical forest type in China, especially in Hunan Province, but little is known about the site index of this forest under the complex site and climate variables in the subtropics. Based on survey data of dominant trees and site variables from 101 plots in Hunan oak natural secondary forests and climate data obtained using spatial interpolation, we used the random forest method, correlation analysis, and the analysis of variance to determine the main site and climate factors affecting oak forest dominant height and proposed a modeling method of an oak natural secondary forest site index based on the random effect of site–climate interaction type. Of the site variables, elevation affected stand dominant height the most, followed by slope direction and position. Winter precipitation and summer mean maximum temperature had the greatest impact on stand dominant height. To develop the modeling method, we created 10 popular base models but found low performance (R2 ranged from 0.1731 to 0.2030). The optimal base model was Mitscherlich form M3 (R2 = 0.1940) based on parameter significance tests. Since site and climate factors affect the site index curve, the dominant site and climate factors were combined into site types and climate types, respectively, and a nonlinear mixed-effects approach was used to simulate different site types, climate types, site–climate interaction types, and their combinations as random effects. Site–climate interaction type as a random factor enhanced model (M3.4) performance and prediction accuracy (R2 from 0.1940 to 0.8220) compared to the optimum base model. After clustering the 62 site–climate interaction types into three, five, and eight groups using hierarchical clustering, a mixed-effects model with the random effects of eight groups improved model performance (R2 = 0.8265) and applicability. The modeling method developed in this study could be used to assess a regional secondary natural oak forest site index under complex site and climate variables to evaluate the forest productivity.

Ecological Restoration Increases the Diversity of Understory Vegetation in Secondary Forests: An Evidence from 90 Years of Forest Closures

Ecological restoration and biodiversity are currently hot issues of global environmental concern. However, knowledge about the specific impacts of restoration duration on understory vegetation diversity remains limited. Therefore, this study comprehensive employed a spatial approach to compare the differences in understory plant diversity and species composition among secondary forests with varying ecological restoration ages (0, 10, 30, 60, and 90-year-old stands) in Huangfu Mountain National Forest Park. This methodology allowed us to clarify the key factors affecting the composition of the understory plant community and investigate the regulatory mechanisms influencing changes in understory plant diversity. The results showed that shrub Shannon’s index value, shrub evenness, herb Shannon’s index value, herb richness, and herb evenness were significantly affected by the years of restoration, with 10 years and 90 years being the highest and 60 years being the lowest. Substrate diversity was the main factor influencing plant diversity in the shrub layer. Overstory richness, soil C/N, soil C, soil N, soil bacterial Observed OTUs, soil bacterial Chao1, soil bacterial Pielou_e, and substrate diversity were the drivers of plant diversity in the herb layer. Overstory evenness had a direct effect (0.256) and an indirect effect (0.284) on herb evenness through light availability and fungal Simpson’s index value. Light availability directly negatively affected herb evenness (−0.360). In addition, 52.6% of the factors affecting the herb evenness index were from the arboreal layer evenness, light availability, and fungal Simpson’s index value. To sum up, moderate disturbance of the understory environment of natural secondary forests can be carried out after 10 years of restoration, which is more conducive to the increase of understory plant diversity. This comprehensive study provides a theoretical basis for formulating ecological restoration measures for secondary forests, particularly in understanding the optimal timing and nature of disturbance in the restoration process, reassuring the audience about the validity and reliability of the findings.

Environmental Driving Mechanism and Response of Soil’s Fungal Functional Structure to Near-Naturalization in a Warm Temperate Plantation

In this study, the near-naturalization process of Pinus tabulaeformis plantations in Baxianshan National Nature Reserve was divided into three stages depending on the proportion of P. tabulaeformis present, resulting in the following categories: the P. tabulaeformis forest stage, the mixed forest stage, and the near-natural forest stage. Natural secondary forests were selected as a control. We assessed alterations in the soil’s fungal functional structures from three aspects: functional mode, vegetative mode, and growth mode, and their responses to vegetation and soil factors were also explored. The results showed that ectomycorrhizal, saprophytic, and plant pathogen types were dominant in the functional mode, and plant pathogens were most abundant in the P. tabulaeformis forest stage. Meanwhile, ectomycorrhizal fungi were the least abundant in the near-natural forest stage. In the vegetative mode, saprophytic, pathophysiological, and symbiotic types were dominant, and pathophysiological types were the most abundant in the P. tabulaeformis forest stage. In the growth mode, microfungi dominated, and the abundance of clavarioid decreased with near-naturalization. The degree of variation in functional structure in the three dimensions increased with near-naturalization, but the structure of natural secondary forests converged. The species composition of tree layer obviously affected the abundance and functional structure of fungi in the three modes, among which Quercus mongolia and Carpinus hornbeam were the most significant. The soil’s pH and nitrate content significantly affected the structure of the functional mode, and the soil’s dry matter content and C/N ratio significantly affected the structure of the vegetative mode. In this study, we explored the interaction between the plant community and soil ecological system during the near-naturalization process of plantations in terms of soil fungi functions, further clarifying the role of soil functions in the succession of plant communities and providing a new perspective on the in-depth exploration of ecosystem interactions during the succession of plantations.

The advantage of afforestation using native tree species to enhance soil quality in degraded forest ecosystems

Different vegetation restoration methods have improved soil quality to varying degrees. This study, focused on the forest–grassland–desert transition zone in the Hebei–Inner Mongolia border region, and employed a systematic grid sampling method to establish fixed monitoring plots in the Saihanba Mechanized Forest Farm and the Ulan Buh Grassland. The differences in soil quality evolution across various vegetation restoration methods under the same climatic and soil historical conditions were analyzed, elucidating the roles of these vegetation restoration methods in degraded forest ecosystems, with the aim of providing a reference for ecological restoration under similar land conditions. This study used a grid method to establish sample points in the forest–grassland–desert transitional zone and assessed five methods of vegetation restoration sites: artificial forest composed of native species of Larix principis-rupprechtii (FL), artificial forest composed of exotic Pinus sylvestris var. mongolica (FP), natural secondary broad-leaved forest (FN), open grassland (GO), and enclosed grassland (GC). The differences in soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkaline hydrolysis nitrogen (AN), rapidly available phosphorus (AP) and rapidly available potassium (AK) among the different vegetation restoration sites were compared via variance analysis, and the soil quality index (SQI) was calculated to assess the soil quality at the sample points. The SOC, TN, and AN contents of forest soil were significantly greater than those of grassland, and the TN, TP, AN, AK, and SOC contents of FL, FN, and GC were significantly greater than those of FP and GO. Among them, the TN, TP, and SOC contents were the highest in the FL, reaching 2.74, 0.39, and 47.27 g kg−1, respectively. In terms of ecological stoichiometric characteristics, the average N:P ratio in the study area was 6.68, indicating a serious lack of N in the study area. Among the different types of restoration sites, the effect was stronger in the FP than in the FL, and the TN and AN contents were only 1.48 g kg−1 and 116.69 mg kg−1, respectively. The SQI in the FL was not significantly different from that in the FN or GC, but it was significantly greater than that in the FP and GO. These findings indicate that native tree species restoration in degraded forest ecosystems significantly improved soil quality, while the introduction of exotic tree species for afforestation had a minimal effect on improving soil quality.

Determinants of carbon sequestration in thinned forests

Given global climate change and the projected increases in the greenhouse effect, enhancing the carbon storage capacity of forest ecosystems is especially critical. To fully realize the potential carbon sequestration, it is imperative to understand the drivers affecting carbon storage in forest ecosystems, particularly with disturbances that disrupt existing balance. In this study, we explored the effects of stem-only harvest at various thinning intensities on forest structure and carbon density in middle-aged natural secondary forests, located in the northern temperate zone. Carbon density included aboveground carbon density (ACD), soil organic carbon stocks (SOCD), and total carbon density (TCD), which was the sum of ACD and SOCD. We employed the random forest analysis method to identify significant variables influencing changes in carbon density. Structural equation modelling (SEM) was then used to determine the drivers of changes in forest carbon density. The results showed that moderate thinning (20 %–35 % trees removed), is an effective management practice for increasing the TCD in forests. Although heavy thinning (35.1 %–59.9 % trees removed) accelerated individual growth, it did not fully offset the carbon removed due to thinning. It is noteworthy that light thinning (0–19.9 % trees removed) not only reduced the species richness but also caused a significant number of tree deaths. Large live trees were an important direct determining factor of ACD, but not the only one. In addition, thinning indirectly influenced ACD by reducing canopy density and deformed tree density. The increase in dead tree density had an adverse impact on SOCD, and this phenomenon increased with the passage of recovery time. Conversely, greater thinning intensity enhanced SOCD. Moreover, TCD was directly influenced by tree height, large live trees, and stand density. Furthermore, thinning altered the conifer ratio, thereby influencing tree growth and indirectly controlling the TCD. We believe that this knowledge will be highly beneficial for successful forest management and enhancing the carbon sequestration capacity of forest ecosystems.

Individual tree diameter growth modelling for natural secondary forest in Changbai Mountains, Northeast China

Individual modelling is a foundational approach to study the natural forest growth and in this paper, we develop a serial distance-depended individual tree model for some species in natural forest which would provide prediction and characteristics for natural species. The data used to develop individual model for natural mixed forests were collected from 712 remeasured 10-year periodic permanent sample plots of in Baihe Forest Bureau of Changbai Mountains, northeast China. Based on analyzing relationship between diameter increment of individual trees with tree size, competitive status, and site condition and finding out the major independent variables, the growth models for individual trees of 15 species in the natural mixed forests, that have good predicting precision, and easily applicable, were developed using stepwise regression method. The individual growth model developed in this study can reflect the tree increment of 15 species and be generally well suited for simulating tree and stand growth for natural mixed forests in Changbai Mountains. The research results for individual trees growth model of each species showed that main variable to influence on diameter increment of individual trees for natural mixed forests were tree size (D) and then competition index. The site condition was not related with diameter increment. The natural logarithm of DBH (lnD) and square diameter (D2) were included in the predicting models of diameter increment for all 15 species. The diameter increment was directly proportional to tree diameter for each species. For the competitive indexes in growth model, the relative diameter (RD), canopy closure (P), and the ratio of diameter of subject tree with maximum diameter (DDM) were related to diameter increment and the stand density measures were not significantly influenced on diameter increment. As canopy closure increase, tree increment decreases. The site conditions were performance less of factors in increment predictions in the model.

Shifts in fungal community diversity and potential function under natural forest succession and planted forest restoration in the Kunyu Mountains, East China.

Soil fungi participate in various ecosystem processes and are important factors driving the restoration of degraded forests. However, little is known about the changes in fungal diversity and potential functions under the development of different vegetation types during natural (secondary forest succession) and anthropogenic (reforestation) forest restoration. In this study, we selected typical forest succession sequences (including Pinus densiflora Siebold & Zucc., pine-broadleaf mixed forest of P. densiflora and Quercus acutissima Carruth., and Q. acutissima), as well as natural secondary deciduous broadleaved mixed forests and planted forests of Robinia pseudoacacia on Kunyu Mountain for analysis. We used ITS rRNA gene sequencing to characterize fungal communities and used the FUNGuild database to predict fungal functional groups. The results showed that forest succession affected fungal β-diversity, but not the α-diversity. There was a significant increase in Basidiomycota and a decrease in Ascomycota in the later successional stage, accompanied by an increase in the functional groups of ectomycorrhizal fungi (ECM). Conversely, planted forests exhibited decreased fungal α-diversity and altered community compositions, characterized by fewer Basidiomycota and more Ascomycota and Mucoromycota. Planted forests led to a decrease in the relative abundances of ECM and an increase in animal pathogens. The TK content was the major factor explaining the distinction in fungal communities among the three successional stages, whereas pH, AP, and NH4 + were the major factors explaining community variations between natural and planted forests. Changes in vegetation types significantly affected the diversity and functional groups of soil fungal communities during forest succession and reforestation, providing key insights for forest ecosystem management in temperate forests.

Japanese Oak Wilt Disease decreased survival probability and mean lifetime of tree populations in a secondary natural forest

ABSTRACT The purpose of this study was to assess the effects of Japanese Oak Wilt Disease on mortality in a tree population. The study site was the permanent plot of 0.26 ha established in the secondary forest dominated by Abies firma, Tsuga sieboldii and Quercus serrata at the University of Tokyo Chiba Forest in the southeastern part of the Boso peninsula, Japan. We set the two observation periods of 1999–2008 and 2009–2021, and Japanese Oak Wilt Disease invaded the study site in the middle of the second period. We collected tree age data for both alive and dead trees in the two periods based on semi-nondestructive drilling measurements for trees using a RESISTOGRAPH. Survival analyses were conducted on the second-period data, and the demographic metrics such as mortality ratios and mean lifetimes were compared between the two periods. The results showed that: the mortality ratio of the tree population at old ages, where oaks (Quercus serrata) concentrated in their age distribution, significantly increased; the effect of the oak group was significant on mortality in the tree population; the hazard for the oak group was 24 times the hazard for the other tree species group; the survival curve reflected the mass mortality in oaks at old ages, which led to the decrease of mean lifetime less than half. Consequently, it was implied that the effects of Japanese Oak Wilt Disease impacted the demographic metrics of oak trees.

Forest restoration effects on soil preferential flow in the paleo-periglacial eastern liaoning mountainous regions, China

To provide a practical reference index for the protection of water conservation forests and the establishment of vegetation in different forest restoration areas, we seek to clarify the preferential flow development and its influencing factors under different rainfall events in the forest restoration areas of paleo-periglacial landform in eastern Liaoning Province of China. To quantify the preferential flow development (PFI) in soil profile-scale through soil profile indexes, we carried out dual-tracer experiments with dyeing in two types of forest restoration lands (plantation forest, PF, and natural secondary forest, NSF) in the paleo-periglacial landform forestland to obtain the soil water infiltration trajectories and water-solute transport characteristics. The indexes of preferential flow morphology and pathway diversity (solute migration) were integrated to construct a more complete evaluation system of the PFI. In addition, we explored factors affecting the PFI through soil physical properties and root characteristics. The results showed that: (1) There were obvious preferential flows in both PF and NSF. Compared with NSF, preferential flow in PF diverged earlier, had greater non-equilibrium degree, more paths and higher development degree, and preferential flow was the main infiltration form. (2) Changes in infiltration amount played a key role in altering the PFI, i.e., increasing infiltration amount reduced the PFI, especially in PF (p < 0.05); (3) After water infiltration, the solute Br− diffusion range of the soil profile was wider than that of Brilliant Blue tracer, thus the development of preferential flow was better synthetical reflected by the indexes of water flow morphology and solute distribution characteristics; (4) Differences in the PFI can be explained by variations in clay content, total porosity (TP), and root volume density (RVD), with total path coefficients of 0.824, 0.462, and 0.624, respectively. In addition to establishing different forest restoration types in similar areas, it would be worthwhile to strengthen the prevention and control measures of soil and water loss in NSF, and properly manage PF in a near-natural model to enhance ecologically sustainable development of forest land. The results of this study contribute to the understanding of the hydrological processes of forest ecosystems in paleo-periglacial landforms, and provide theoretical support for the proposed forest management strategies.

Response of Soil CO2 Emission to Addition of Biochar and Dissolved Organic Carbon along a Vegetation Restoration Gradient of Subtropical China

Biochar, as a soil amendment, has been widely confirmed to increase soil carbon sequestration. However, how biochar addition affects soil carbon changes during the vegetation restoration process is still unclear, which constrains our ability to explore biochar’s application in the technology of soil carbon sequestration in forests. We conducted an incubation experiment on biochar and dissolved organic matter (DOM) addition to soil at three stages of revegetation (degraded land (DS), plantation forest (PS), and secondary natural forest (NS) in Changting County in Fujian province, China) to investigate the effects of vegetation restoration, biochar, DOM, and their interaction on soil CO2 emission and its relative mechanisms. We found that the accumulative release of CO2-C in the NS and PS soils was 7.6 and 6.8 times higher, respectively, in comparison to that from the DS soil. In the DS, biochar addition significantly increased the accumulative release of CO2-C, soil pH, NH4+-N content, qCO2, phenol oxidase, and peroxidase activities. Peroxidase activities were positively correlated with the accumulative release of CO2-C, and oxidase was the most important direct factor influencing the accumulative release of CO2-C in the DS. However, the accumulative release of CO2-C, soil NH4+-N content, qCO2, β-glucosidase, and N-acetylglucosaminidase activities was significantly reduced after the application of biochar in the PS and NS. These two hydrolases were positively associated with the accumulative release of CO2-C, and hydrolase was the most vital direct factor influencing the accumulative release of CO2-C from the PS and NS soils. The positive effect of DOM addition on CO2 emission under biochar application declined with a vegetation restoration age increase. Our results indicated that biochar could alter microbial physiological processes, inhibit qCO2 and hydrolase activities, and further decrease CO2 emission in relatively fertile soil from the PS and NS; but in the relatively barren soil from the DS, biochar might promote CO2 emission by stimulating microorganisms to enhance qCO2 and oxidase activities.

Soil quality assessment of oak forests invaded by moso bamboo (Phyllostachys edulis) in the northern subtropics

Soil quality is closely related to the evolution of forest ecosystems, especially in the context of global warming; therefore, it is essential to study the changes in soil quality caused by the invasion of moso bamboo in its habitat. In this study, we selected plantation forests and natural secondary forests with typical vegetation of the northern subtropics, Quercus acutissima plantation (QAP) and oak secondary forest (OSF), collected plant community and soil physicochemical data, and established a soil quality index (SQI) to assess how moso bamboo invasion affects soil quality. In addition, the mechanisms driving the moso bamboo invasion effects on soil quality were investigated using a partial least squares structural equation model (PLS-SEM). The results demonstrated that: (1) Moso bamboo invasion significantly affected community structure and soil physicochemical properties, there were inconsistent changes in soil physicochemical indicators in oak forests of different origins, and in general the effects of moso bamboo expansion on soil physicochemical properties were concentrated in the topsoil (0–20 cm). (2) Soil bulk density (BD), total soil porosity (TSP), total nitrogen (TN), and available potassium (AK) comprised the minimum data set (MDS) used to calculate the SQI, and the SQI of oak forests of different origins ranged from 0.48 to 1, and the invasion of moso bamboo led to a significant decrease in the SQI of the surface layer of QAP. A redundancy analysis (RDA) showed that soil quality assessment factors were closely related to community structure and the PLS-SEM indicated that moso bamboo invasion indirectly affected surface soil quality through its effects on community and soil factors. The results showed that moso bamboo invasion had different effects on oak forests of different origins. They also showed that soil quality was strongly affected by aboveground biomass (AGB), the tree Shannon-Wiener index (TH'), and available potassium (AK).

Suitability assessment for forest landscape restoration based on species diversity conservation

Forest landscape fragmentation poses a significant challenge to the conservation of species diversity. Evaluating the suitability of forest landscape restoration (FLR) becomes essential as it promotes effective management of forest resources and protects species diversity. This study focused on deploying and testing a suitability evaluation framework system for FLR in the Saihanba area of Hebei, China. The framework system incorporated factors such as land cover type, landscape structure, soil quality, and topography. Using the matter-element model, the study evaluated the restoration suitability and identified priority restoration areas. The results revealed that land cover type and landscape structure were the primary factors influencing FLR in the study area. The suitable area for FLR in the study area was about 519.20 km2, accounting for 55.55% of the total area. The area of moderate, marginal, and unsuitable restoration accounted for 17.30%, 23.96%, and 3.18% of the study area, respectively. The suitable restoration areas predominantly consisted of natural secondary forest characterized by large patch areas, short distances between patches, and complex patch shapes. In the study area, the objective of FLR should be protect large and complex shaped patches of natural secondary forests for better conservation of species diversity. The FLR suitability evaluation conducted in this study provide a valuable guidance for promoting species-diversity conservation and restoration of forest ecosystems at the landscape scale in the study area and other similar regions.

Determining Water Use Patterns for the Betula platyphylla in the Southern Greater Khingan Mountains and Its Adaptation to Drought

Due to global climate change, seasonal droughts have intensified and become more frequent in certain semi-arid regions, and plants often adjust their water uptake depths to adapt to shifting environmental conditions. The southern Greater Khingan Mountains have a large natural secondary forest area and act as an important ecological barrier. This study focused on examining the water use patterns of the primary plant species, Betula platyphylla, within the natural secondary forest of the southern Greater Khingan Mountains. The investigation utilized oxygen stable isotope techniques and covered a timeframe spanning from July 2019 to September 2020. The findings indicate that the adaptable water utilization strategies and rapid response to precipitation could facilitate plants fully utilizing water from all depths, thereby enabling them to better adapt to arid environments. When the rainfall was low (390.4 mm in the growing season of 2019), the developed shallow roots quickly absorbed shallow soil water (0–20 cm, with a utilization ratio of 40.4% for the entire root depth), but when the rainfall increased (501.5 mm in the growing season of 2020), Betula platyphylla gradually transitioned to extracting soil water from deeper soil layers (40–60 cm) and deepened its root system (with a utilization ratio of 39.4%), indicating its adaptability to semi-arid environments. Therefore, the flexible water use strategy of Betula platyphylla in the same habitat may give it a competitive advantage during low rainfall periods. The findings are important for the protection of natural forests and water management in the southern Greater Khingan Mountains.

Assessing the effect of ensemble learning algorithms and validation approach on estimating forest aboveground biomass: a case study of natural secondary forest in Northeast China

ABSTRACT Accurate estimation of forest aboveground biomass is essential for the assessment of regional carbon cycle and the climate change in the terrestrial ecosystem. Currently, ensemble learning algorithms and cross-validation methods have been widely applied to estimate regional forest Above Ground Biomass (AGB). However, the effects of ensemble learning algorithms, validation methods, and their interactions on forest AGB estimation were rarely investigated. Based on Landsat 8 Operational Land Imager (OLI) imagery, Airborne Laser Scanning (ALS) data and China’s National Forest Continuous Inventory data, this study explored the effects of five ensemble learning algorithms, including Simple Averaging (SA), Weighted Averaging (WA), Stacked Generalization (SG), Random Forest (RF) and Extreme Gradient Boosting (XGBoost), and two validation approaches (i.e. 10-fold and leave-one-out cross-validation) on the AGB estimation of the Natural Secondary Forests (NSFs) in northeast China. The results revealed that the ensemble learning algorithms that combine heterogenous-based models (i.e. SA, WA, SG) generally produced higher accuracy than the base models (i.e. Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Regression (SVR), Convolutional Neural Network (CNN)). Among all ensemble learning algorithms, the SG algorithm has the highest accuracy whereas the XGBoost algorithm has the lowest accuracy. Although prediction models considerably impact the accuracy of AGB estimation, the validation approach also plays a non-negligible role in AGB estimation. The leave-one-out cross-validation produced much higher accuracy than the 10-fold cross-validation using the same prediction model and tends to generate over-optimistic AGB estimates compared to 10-fold cross-validation, especially for the averaging and stacking ensemble learning algorithms (i.e. SA, WA, SG). This study highlights the potential challenges of applying a leave-one-out cross-validation approach and provides a scientific foundation for the feasibility of different ensemble learning algorithms and cross-validation approaches for accurate AGB estimation.

Microbial community interactions determine the mineralization of soil organic phosphorus in subtropical forest ecosystems.

In subtropical forest ecosystems with few phosphorus (P) inputs, P availability and forest productivity depend on soil organic P (Po) mineralization. However, the mechanisms by which the microbial community determines the status and fate of soil Po mineralization remain unclear. In the present study, soils were collected from three typical forest types: secondary natural forest (SNF), mixed planting, and monoculture forest of Chinese fir. The P fractions, Po-mineralization ability, and microbial community in the soils of different forest types were characterized. In addition, we defined Po-mineralizing taxa with the potential to interact with the soil microbial community to regulate Po mineralization. We found that a higher labile P content persisted in SNF and was positively associated with the Po-mineralization capacity of the soil microbial community. In vitro cultures of soil suspensions revealed that soil Po mineralization of three forest types was distinguished by differences in the composition of fungal communities. We further identified broad phylogenetic lineages of Po-mineralizing fungi with a high intensity of positive interactions with the soil microbial community, implying that the facilitation of Po-mineralizing taxa is crucial for soil P availability. Our dilution experiments to weaken microbial interactions revealed that in SNF soil, which had the highest interaction intensity of Po-mineralizing taxa with the community, Po-mineralization capacity was irreversibly lost after dilution, highlighting the importance of microbial diversity protection in forest soils. In summary, this study demonstrates that the interactions of Po-mineralizing microorganisms with the soil microbial community are critical for P availability in subtropical forests.IMPORTANCEIn subtropical forest ecosystems with few phosphorus inputs, phosphorus availability and forest productivity depend on soil organic phosphorus mineralization. However, the mechanisms by which the microbial community interactions determine the mineralization of soil organic phosphorus remain unclear. In the present study, soils were collected from three typical forest types: secondary natural forest, mixed planting, and monoculture forest of Chinese fir. We found that a higher soil labile phosphorus content was positively associated with the organic phosphorus mineralization capacity of the soil microbial community. Soil organic phosphorus mineralization of three forest types was distinguished by the differences in the composition of fungal communities. The positive interactions between organic phosphorus-mineralizing fungi and the rest of the soil microbial community facilitated organic phosphorus mineralization. This study highlights the importance of microbial diversity protection in forest soils and reveals the microbial mechanism of phosphorus availability maintenance in subtropical forest ecosystems.

Effects of stand ages on soil enzyme activities in Chinese fir plantations and natural secondary forests.

Forest type and stand age are important biological factors affecting soil enzyme activities. However, the changes in soil enzyme activities across stand ages and underlying mechanisms under the two forest restoration strate-gies of plantations and natural secondary forests remain elusive. In this study, we investigated the variations of four soil enzyme activities including cello-biohydrolase (CBH), β-1,4-glucosidase (βG), acid phosphatase (AP) and β-1,4-N-acetylglucosaminidase (NAG), which were closely associated with soil carbon, nitrogen, and phosphorus cycling, across Cunninghamia lanceolata plantations and natural secondary forests (5, 8, 21, 27 and 40 years old). The results showed that soil enzyme activities showed different patterns across different forest types. The acti-vities of AP, βG and CBH in the C. lanceolata plantations were significantly higher than those in the natural secon-dary forests, and there was no significant difference in the NAG activity. In the plantations, AP activity showed a decreasing tendency with the increasing stand ages, with the AP activity in the 5-year-old plantations significantly higher than other stand ages by more than 62.3%. The activities of NAG and CBH decreased first and then increased, and βG enzyme activity fluctuated with the increasing stand age. In the natural secondary forests, NAG enzyme activity fluctuated with the increasing stand age, with that in the 8-year-old and 27-year-old stand ages being significantly higher than the other stand ages by more than 14.9%. βG and CBH enzyme activities increased first and then decreased, and no significant difference was observed in the AP activity. Results of the stepwise regression analyses showed that soil predictors explained more than 34% of the variation in the best-fitting models predicting soil enzyme activities in the C. lanceolata plantations and natural secondary forests. In conclusion, there would be a risk of soil fertility degradation C. lanceolata plantations with the increasing stand age, while natural secondary forests were more conducive to maintaining soil fertility.

Mapping tree species diversity in a typical natural secondary forest by combining multispectral and LiDAR data

Accurate monitoring of tree species diversity is crucial for understanding the dynamic changes in tree species diversity and its relationships with other services and functions in forest ecosystems. Traditional optical remote sensing data have been widely used for monitoring tree species diversity based on the spectral variation hypothesis (SVH). However, this method cannot capture the three-dimensional structural variations in complex species compositions under different stand conditions. In this study, we modeled tree species diversity in terms of spectral variation and stand structural complexity in a typical natural secondary forest in Northeast China by combining Sentinel-2 data and UAV-borne light detection and ranging (LiDAR) point cloud data. First, species diversity indices (including the Shannon index H' and Simpson index D1) were derived from 60 field-measured plots. Second, recursive feature elimination (RFE) was utilized for feature filtering of ten spectral bands and four vegetation indices extracted from Sentinel-2 data and Rao's Q index, as well as eleven features extracted from LiDAR point clouds reflecting the complexity of the stand structure. Subsequently, the random forest method was utilized to fit and predict the relationship between the remote sensing feature set and tree species diversity. The results showed that the use of multisource remote sensing feature set to estimate tree species diversity had the highest accuracy (R2 = 0.44, RMSE = 0.28 for H') compared to the use of only one data source. Moreover, when using a single remote sensing feature set, the estimation accuracy of the optical remote sensing feature set is higher than that of the LiDAR feature set for H' and D1, and the NIRv is the most influential spectral feature. This study clarified the value of spectral variation and productivity heterogeneity embodied in optical remote sensing features for monitoring tree species diversity, as well as evaluating the shortcomings and possibilities of using LiDAR point cloud features independently, and fully confirmed the positive significance of complementary effects between multisource remote sensing feature sets.

Soil phosphorus improved the soil organic carbon of converted forestland from cropland within southern Qinling-Daba Mountains, China

Previous studies showed that the program of converted forestland from cropland (CFC), initiated by the Chinese government in 1999, has been a significant contributor to China’s efforts towards carbon neutrality. Here, the 20-year CFCs of two aspects (sunny and shady) and three positions (upper, middle, and lower) hillslopes, adjacent maize ( Zea mays L.) cropland, and natural secondary Castanea mollissima forest (CCF) within southern Qinling-Daba Mountains region (Qinba) had been selected as the targets. The soil bulk density (SBD), soil organic carbon concentration (SOCC), total nitrogen (TN), and total phosphorus (TP) had been determined. The results showed that SBD increased with depth, and other parameters decreased, which varied largely with the aspect and position. The SOC stocks (SOCS) of CCF, cropland, and CFC were 152.81 ± 5.17, 168.19 ± 11.87, and 183.92 ± 35.69 Mg C hm−2, respectively. The SOCCs of CCF, cropland, and CFC were 17.71 ± 4.38, 20.23 ± 5.28, and 21.89 ± 7.33 g kg−1, respectively. The CFC increased the correlations between SOC and TP, and decreased the correlations between SOC and TN. The CFC shifted the relationships of lg SOC versus lg N:P and lg SOC versus lg TP from decreasing returns of cropland to isometric. Overall, the CFCs enhanced SOC, especially in the middle shady hillslopes within the southern middle-mountain of Qinba. In contrast, SOC levels decreased in the sunny upper hillslopes. We presented the evidence that hillslopes aspect and position had significant effects on SOC, which was regulated by soil phosphorus.

Afforestation, Natural Secondary Forest or Dehesas? Looking for the Best Post-Abandonment Forest Management for Soil Organic Carbon Accumulation in Mediterranean Mountains

Forest expansion in Mediterranean mountain areas is a widespread phenomenon resulting from the abandonment of agricultural and pastoral activities during the last century. Therefore, knowledge of the long-term storage capacity of soil organic carbon (SOC) in Mediterranean forests is of great interest in the context of global change. However, the effects of these land uses and covers (natural secondary forest, afforestation with conifers and silvo-pastoral ecosystems (dehesas)) on SOC dynamics are still uncertain. The main objectives of this study were to evaluate physico-chemical soil properties, SOC and nitrogen stocks, and SOC fractions in Mediterranean forests and to assess the effects of tree species, the soil environment (acidic and alkaline), and land management. We selected five land uses and land covers: managed and non-managed afforestation and dehesa (except for alkaline dehesa) and a stage of succession when tree species begin to become established after abandonment. This study concludes that although total SOC stocks are higher in afforested systems with conifers, SOC is stored in less stable carbon pools than in broadleaf forests. In addition, this study confirms that there are marked differences in the results between acidic and alkaline environments. Finally, the management system is also a significant factor, particularly for afforested sites.