Rotation age extension synergistically increases ecosystem carbon storage and timber production of Chinese fir plantations in southern China.

Afforestation is an effective method to increase carbon (C) sinks and address climate change. It is crucial to understand how the stand growth affects C sequestration capacity, especially when the trade-offs with timber production from plantations have not been fully examined. We used a chronosequence approach to estimate C storage in Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantations (including the trees, understory, litter, and soils) at seven stand ages (3, 8-11, 16, 21, 25, 29, and 32 years). Ecosystem C storage increased nonlinearly from 76.4 to 282.2 t ha-1 with stand age and was fitted with a logistic model that had a maximum C storage and age of 271.9 t ha-1 and 33 years, respectively, to reach 95% of the maximum stored C. The C increment was mainly contributed by an increase in tree biomass, which ranged from 2.8 to 177.7 t ha-1 and comprised 4-64% of the total ecosystem C. Live root C (sum of the stump, coarse, and fine root C) showed a logistic increase from 2.0 to 26.3 t ha-1 with stand age and constituted 2.5-9.3% of ecosystem C. Understory plants and litter represented a small pool (<2% of ecosystem C). The C storage in shrubs and litter slightly increased, while that in herbs decreased as the stands aged. Soil C storage was an important and relatively stable pool, ranging from 69.6 to 130.1 t ha-1. Stand volume was also best fitted with a logistic model with a maximum value of 552.6 m3 ha-1. Additionally, the time needed to reach 95% of the maximum volume was 25 years. Hence, extending the rotation age to over 30 years for Chinese fir plantations could potentially maximize the synergistic benefits of C storage to mitigate climate change and obtain timber products for economic profit.

Contrasting patterns and drivers of soil fungal communities in subtropical deciduous and evergreen broadleaved forests.

Subtropical broadleaved forests play a crucial role in supporting terrestrial ecosystem functions, but little is known about their belowground soil fungal communities despite that they have central functions in C, N, and P cycles. This study investigated the structures and identified the drivers of soil fungal communities in subtropical deciduous and evergreen broadleaved forests, using high-throughput sequencing and FUNGuild for fungal identification and assignment to the trophic guild. Fungal richness was much higher in the deciduous than in the evergreen forest. Both forests were dominated by Ascomycota and Basidiomycota phyla, but saprophytic fungi were more abundant in the deciduous forest and ectomycorrhizal fungi predominated in the evergreen forest. Fungal communities had strong links to plant and soil properties. Specifically, plant diversity and litter biomass were the main aboveground drivers of fungal diversity and composition in the deciduous forest, while host effects were prominent in the evergreen forest. The belowground factors, i.e., soil pH, water content, and nutrients especially available P, were identified as the primary drivers of soil fungal communities in the broadleaved forests. Co-occurrence network analysis revealed assembly of fungal composition in broadleaved forest soils was non-random. The smaller modularity of the network in the deciduous forest reflects lower resistance to environment changes. Concluding, these results showed that plant community attributes, soil properties, and potential interactions among fungal functional guilds operate jointly on the divergence of soil fungal community assembly in the two broadleaved forest types.

Temporal changes of fine root overyielding and foraging strategies in planted monoculture and mixed forests.

BACKGROUND: Mixed forests are believed to enhance ecosystem functioning and sustainability due to complementary resource use, environmental benefits and improved soil properties. The facilitation between different species may induce overyielding. Meanwhile, the species-specific fine root foraging strategies and tradeoffs would determine the structure and dynamics of plant communities. Here the aim was to investigate the admixing effects of fine-root biomass, vertical distribution and morphology in Pinus massoniana-Cinnamomum camphora mixed plantations and corresponding monocultures at 10-, 24- and 45-year old stands. RESULTS: The fine root biomass in the Pinus-Cinnamomum mixed forest exerted a certain degree of overyielding effect. These positive admixing effects, however, did not enhance with forest stand development. The overall relative yield total ranged from 1.83 and 1.51 to 1.33 in 10-, 24- and 45-year-old stand, respectively. The overyielding was mainly attributed to the over-performance of late successional species, Cinnamomum, in mixed stands. The vertical fine root biomass distribution model showed fine roots of pioneer species, Pinus, shifted to the superficial layer when mixed with Cinnamomum. Furthermore, the specific root length (SRL) of Pinus was significantly higher in Pinus-Cinnamomum mixed stands than that in monocultures, and the magnitude of differences increased over time. However, the vertical fine-root distribution and SRL for Cinnamomum did not show significant differences between monoculture and mixtures. CONCLUSIONS: Our results indicated that the magnitude of fine root overyielding in mixed forests showed a high degree of consistency with the total amount of fine root biomass itself, suggesting the overyielding effects in mixed forests were correlated with the degree of belowground interaction and competition degree involved. The late successional species, Cinnamomum, invested more carbon to belowground by increasing the fine root biomass in mixtures. While the pioneer species, Pinus, adapted to the presence of the species Cinnamomum by modification of vertical distribution and root morphological plasticity in the mixtures. These species-specific fine root foraging strategies might imply the differences of forest growth strategies of co-occurring species and contribute to the success and failure of particular species during the succession over time.

Plantations thinning: A meta-analysis of consequences for soil properties and microbial functions.

Thinning is a widely-used management practice to reduce tree competition and improve wood production and quality in forest plantations. Thinning affects the soil ecosystem by changing the microclimate and plant growth, as well as litter inputs above and belowground, with all the resulting consequences for microbial communities and functions. Although many case studies have been carried out, a comprehensive understanding of the thinning effects on soil properties and microbial communities and functions in plantations remains to be explored. In this study, a meta-analysis was performed on 533 paired observations based on 90 peer-reviewed articles to evaluate the general responses of soil (mainly 0-20 cm depth) physicochemical properties, microbial biomass and community structure, and enzyme activities to thinning. Results showed that thinning increased soil temperature (13 %), moisture (8.0 %), electric conductivity (13 %), and the contents of total nitrogen (TN, 4.1 %), dissolved organic carbon (DOC, 9.7 %), nitrate N (NO3--N, 27 %) and available phosphorous (22 %). For microbial properties, thinning decreased the fungi to bacteria ratio (F:B, -28 %) and the gram-positive bacteria to gram-negative bacteria ratio (G+:G-, -12 %), while increased microbial biomass C (7.1 %), microbial respiration (13 %), and nutrient-cycle related enzyme activities, including phenol oxidase (14 %), cellobiohydrolase (21 %), urease (10 %), and acid phosphatase (9 %). In particular, moderate thinning (30-60 % intensity) has higher conservation benefits for soil C and nutrients than light and heavy intensity, thus being recommended as the optimal thinning activity. This meta-analysis suggests that thinning consistently altered soil properties, shifted microbial community compositions from K- to-r strategist dominance, and stimulated microbial activities. These results are essential for optimizing plantation thinning management and provide evidence for applying the macro-ecology theory to ecosystem disturbance in soil microbial ecology.

The effect of tree species diversity on fine-root production in a young temperate forest.

The phenomenon of overyielding in species-diverse plant communities is mainly attributed to complementary resource use. Vertical niche differentiation belowground might be one potential mechanism for such complementarity. However, most studies that have analysed the diversity/productivity relationship and belowground niche differentiation have done so for fully occupied sites, not very young tree communities that are in the process of occupying belowground space. Here we used a 5­6 year old forest diversity experiment to analyse how fine-root (<2 mm) production in ingrowth cores (0­30 cm) was influenced by tree species identity, as well as the species diversity and richness of tree neighbourhoods. Fine-root production during the first growing season after the installation of ingrowth cores increased slightly with tree species diversity, and four-species combinations produced on average 94.8% more fine-root biomass than monocultures. During the second growing season, fine-root mortality increased with tree species diversity, indicating an increased fine-root turnover in species-rich communities. The initial overyielding was attributable to the response to mixing by the dominant species, Pseudotsuga menziesii and Picea abies, which produced more fine roots in mixtures than could be expected from monocultures. In species-rich neighbourhoods, P. abies allocated more fine roots to the upper soil layer (0­15 cm), whereas P. menziesii produced more fine roots in the deeper layer (15­30 cm) than in species-poor neighbourhoods. Our results indicate that, although there may be no lasting overyielding in the fine-root production of species-diverse tree communities, increasing species diversity can lead to substantial changes in the production, vertical distribution, and turnover of fine roots of individual species.

Vegetation dynamics and their relationships with climatic factors in the "Golden Triangle" region.

The "Golden Triangle" is located on the border between Myanmar, Laos, and Thailand, and slash-and-burn cultivation is an ancient and typical land type in this region. With the development of the "The Belt and Road" strategy of China and the climate change, the vegetation information is bound to change intensively under the combined influence of alternative plantation projects and economic policies. Here we used MOD13Q1-normalized differential vegetation index (NDVI) and meteorological data to analyze the variation of vegetation coverage and its correlation with climatic factors (temperature and precipitation) during the period of 2000-2018 by using trend analysis, stability analysis, and partial correlation analysis. The results showed that the overall vegetation coverage of this region exerted the trend of improvement and became more stable over time. Spatially, the agglomeration degree became weaker as time goes during 2000-2018. The precipitation was more closely correlated with NDVI than temperature, indicating that precipitation could be the main limiting factor influencing vegetation change in this area. The correlation between NDVI and climatic factors exhibited differences among different seasons, with NDVI being less correlated with temperature and precipitation in spring and summer and more correlated with them in autumn and winter. Investigating the long-term vegetation coverage of this region and analyzing the trend of climate change is beneficial to understand the development trend of the ecological environment and resource potential in this region. Simultaneously, it can provide a favorable ecological evaluation for The Belt and Road strategy and provide important scientific suggestions and guidance for the sustainable development of ecosystems and human society under the drastic environmental changes.

Stand carbon storage and net primary production in China's subtropical secondary forests are predicted to increase by 2060.

BACKGROUND: Forest ecosystems play an important role in carbon sequestration, climate change mitigation, and achieving China's target to become carbon (C) neutral by 2060. However, changes in C storage and net primary production (NPP) in natural secondary forests stemming from tree growth and future climate change have not yet been investigated in subtropical areas in China. Here, we used data from 290 inventory plots in four secondary forests [evergreen broad-leaved forest (EBF), deciduous and evergreen broad-leaved mixed forest (DEF), deciduous broad-leaved forest (DBF), and coniferous and broad-leaved mixed forest (CDF)] at different restoration stages and run a hybrid model (TRIPLEX 1.6) to predict changes in stand carbon storage and NPP under two future climate change scenarios (RCP4.5 and RCP8.5). RESULTS: The runs of the hybrid model calibrated and validated by using the data from the inventory plots suggest significant increase in the carbon storage by 2060 under the current climate conditions, and even higher increase under the RCP4.5 and RCP8.5 climate change scenarios. In contrast to the carbon storage, the simulated EBF and DEF NPP declines slightly over the period from 2014 to 2060. CONCLUSIONS: The obtained results lead to conclusion that proper management of China's subtropical secondary forests could be considered as one of the steps towards achieving China's target to become carbon neutral by 2060.

Photosynthetic and hydraulic traits influence forest resistance and resilience to drought stress across different biomes.

Drought events lead to depressions in gross primary productivity (GPP) of forest ecosystems. Photosynthetic and hydraulic traits are important factors governing GPP variation. However, how these functional traits affect GPP responses to drought has not been well understood. We quantified the capacity of GPP to withstand changes during droughts (GPP_resistance) and its post-drought responses (GPP_resilience) using eddy covariance data from the FLUXNET2015 dataset, and investigated how functional traits of dominant tree species that comprised >80% of the biomass (or composition) influenced GPP_resistance or GPP_resilience. Light-saturated photosynthetic rate of dominant tree species was negatively related to GPP_resistance, and was positively correlated with GPP_resilience. Forests dominated by species with higher hydraulic safety margins (HSM), smaller vessel diameter (Vdia) and lower sensitivity of canopy stomatal conductance per unit land area (Gs) to droughts had a higher GPP_resistance, while those dominated by species with lower HSM, larger Vdia and higher sensitivity of Gs to droughts exhibited a higher GPP_resilience. Differences in functional traits of forests located in diverse climate regions led to distinct GPP sensitivities to droughts. Forests located in humid regions had a higher GPP_resilience while those in arid regions exhibited a higher GPP_resistance. Forest GPP_resistance was negatively related to drought intensity, and GPP_resilience was negatively related to drought duration. Our findings highlight the significant role of functional traits in governing forest resistance and resilience to droughts. Overall, forests dominated by species with higher hydraulic safety were more resistant to droughts, while forests containing species with higher photosynthetic and hydraulic efficiency recovered better from drought stress.

Tree functional types simplify forest carbon stock estimates induced by carbon concentration variations among species in a subtropical area.

Forests contain one of the world's largest carbon (C) pools and represent opportunities for cost-effective climate change mitigation through programmes such as the United Nations-led "Reducing Emissions from Deforestation and Forest Degradation" Programme (REDD). Generic estimates for the conversion of forest biomass into C stock are not sufficiently accurate for assessing the utility of harvesting forest to offset carbon dioxide emissions, currently under consideration by the REDD Programme. We examined the variation in C concentration among tree species and tree functional types (classified based on leaf morphological and phenological traits) in a subtropical forest and evaluated the effects of these variations on stand-level estimations of C stock. This study was conducted in the Paiyashan Forest State Farm and the Dashanchong Forest Park, Hunan Province, China. C concentrations differed significantly among tree species (P < 0.0001) and were significantly higher in gymnosperm than angiosperm species. Estimations of stand C stocks were similar using either functional types or species- and tissue-specific C concentrations. The use of functional type classification to estimate stand C stock is an effective tool for implementing C sequestration trade and C credit programmes and the UN-REDD Programme in subtropical forests.

Tree growth traits and social status affect the wood density of pioneer species in secondary subtropical forest.

Wood density (WD) is not only an important parameter to estimate aboveground biomass but also an indicator of timber quality and plant adaptation strategies to stressful conditions (i.e., windthrow, pests, and pathogens). This study had three objectives: (1) to compare WD among seven subtropical tree species; (2) to determine how tree growth traits may influence possible differences in WD between the pioneer and shade-tolerant species; and (3) to examine whether or not WD differs by tree social status (dominant vs. suppressed trees) within species. To do this, 70 trees were destructively harvested. From each tree, disks at different stem heights were obtained and subjected to a method of stem analysis to measure whole tree level WD. The results showed that WD differed significantly among the seven species (p < .001). Their average WD was 0.537 g/cm3, ranging from 0.409 g/cm3 for Choerospondias axillaris to 0.691 g/cm3 for Cyclobalanopsis glauca. The average WD of the four pioneer species (0.497 ± 0.13 g/cm3) was significantly lower (p < .01) than that of the three shade-tolerant species (0.589 ± 0.12 g/cm3). The WD of the pioneers had a significant positive correlation with their stem diameter at breast height (DBH), tree height (H), and tree age, but WD had a significant negative correlation with relative growth rate (RGR). In contrast, the WD of the shade-tolerant tree species had no significant relationships with DBH, H, tree age, or RGR. The dominant trees of the pioneer species had a higher WD than the suppressed trees, whereas the shade-tolerant species had a lower WD for dominant trees than the suppressed trees. However, the differences in WD between dominant and suppressed trees were not significant. Taken together, the results suggest that classifying species into pioneer and shade-tolerant groups to examine the effects of tree growth traits and social status could improve our understanding of intra- and interspecific variation in WD among subtropical tree species.

A molecular method to identify species of fine roots and to predict the proportion of a species in mixed samples in subtropical forests.

Understanding of belowground interactions among tree species and the fine root (≤2 mm in diameter) contribution of a species to forest ecosystem production are mostly restricted by experimental difficulties in the quantification of the species composition. The available approaches have various defects. By contrast, DNA-based methods can avoid these drawbacks. Quantitative real-time polymerase chain reaction (PCR) is an advanced molecular technology, but it is difficult to develop specific primer sets. The method of next-generation sequencing has several limitations, such as inaccurate sequencing of homopolymer regions, as well as being time-consuming, and requiring special knowledge for data analysis. This study evaluated the potential of the DNA-sequence-based method to identify tree species and to quantify the relative proportion of each species in mixed fine root samples. We discriminated the species by isolating DNA from individual fine roots and amplifying the plastid trnL(UAA; i.e., tRNA-Leu-UAA) intron using the PCR. To estimate relative proportions, we extracted DNA from fine root mixtures. After the plastid trnL(UAA) intron amplification and TA-cloning, we sequenced the positive clones from each mixture. Our results indicated that the plastid trnL(UAA) intron spacer successfully distinguished tree species of fine roots in subtropical forests. In addition, the DNA-sequence-based approach could reliably estimate the relative proportion of each species in mixed fine root samples. To our knowledge, this is the first time that the DNA-sequence-based method has been used to quantify tree species proportions in mixed fine root samples in Chinese subtropical forests. As the cost of DNA-sequencing declines and DNA-sequence-based methods improve, the molecular method will be more widely used to determine fine root species and abundance.

Development and Evaluation of Models for the Relationship between Tree Height and Diameter at Breast Height for Chinese-Fir Plantations in Subtropical China.

Tree diameter at breast height (dbh) and height are the most important variables used in forest inventory and management as well as forest carbon-stock estimation. In order to identify the key stand variables that influence the tree height-dbh relationship and to develop and validate a suit of models for predicting tree height, data from 5961 tree samples aged from 6 years to 53 years and collected from 80 Chinese-fir plantation plots were used to fit 39 models, including 33 nonlinear models and 6 linear models, were developed and evaluated into two groups. The results showed that composite models performed better in height estimate than one-independent-variable models. Nonlinear composite Model 34 and linear composite Model 6 were recommended for predicting tree height in Chinese fir plantations with a dbh range between 4 cm and 40 cm when the dbh data for each tree and the quadratic mean dbh of the stand (Dq) and mean height of the stand (Hm) were available. Moreover, Hm could be estimated by using the formula Hm = 11.707 × l n(Dq)-18.032. Clearly, Dq was the primary stand variable that influenced the height-dbh relationship. The parameters of the models varied according to stand age and site. The inappropriate application of provincial or regional height-dbh models for predicting small tree height at local scale may result in larger uncertainties. The method and the recommended models developed in this study were statistically reliable for applications in growth and yield estimation for even-aged Chinese-fir plantation in Huitong and Changsha. The models could be extended to other regions and to other tree species only after verification in subtropical China.

Growth and heavy metal accumulation of Koelreuteria paniculata seedlings and their potential for restoring manganese mine wastelands in Hunan, China.

The planting of trees on mine wastelands is an effective, long-term technique for phytoremediation of heavy metal-contaminated wastes. In this study, a pot experiment with seedlings of Koelreuteria paniculata under six treatments of local mine wastes was designed to determine the major constraints on tree establishment and to evaluate the feasibility of planting K. paniculata on manganese mine wastelands. Results showed that K. paniculata grew well in mine tailings, and also under a regime of equal amounts of mine tailings and soil provided in adjacent halves of pots. In contrast, mine sludge did not favor survival and growth because its clay texture limited fine root development. The bio-concentration factor and the translocation factor were mostly less than 1, indicating a low phytoextraction potential for K. paniculata. K. paniculata is suited to restore manganese mine sludge by mixing the mine sludge with local mine tailings or soil.

[Estimating individual tree aboveground biomass of the mid-subtropical forest using airborne LiDAR technology].

Taking Wugang forest farm in Xuefeng Mountain as the research object, using the airborne light detection and ranging (LiDAR) data under leaf-on condition and field data of concomitant plots, this paper assessed the ability of using LiDAR technology to estimate aboveground biomass of the mid-subtropical forest. A semi-automated individual tree LiDAR cloud point segmentation was obtained by using condition random fields and optimization methods. Spatial structure, waveform characteristics and topography were calculated as LiDAR metrics from the segmented objects. Then statistical models between aboveground biomass from field data and these LiDAR metrics were built. The individual tree recognition rates were 93%, 86% and 60% for coniferous, broadleaf and mixed forests, respectively. The adjusted coefficients of determination (R(2)adj) and the root mean squared errors (RMSE) for the three types of forest were 0.83, 0.81 and 0.74, and 28.22, 29.79 and 32.31 t · hm(-2), respectively. The estimation capability of model based on canopy geometric volume, tree percentile height, slope and waveform characteristics was much better than that of traditional regression model based on tree height. Therefore, LiDAR metrics from individual tree could facilitate better performance in biomass estimation.