Carbon stocks and changes of dead organic matter in China's forests

Amount, distribution and controls of the soil organic carbon storage loss in the degraded China's grasslands

More than 80 % of China's grasslands are classified as degraded, and the loss of soil carbon storage due to degradation has a significant impact on China's terrestrial carbon sinks as well as carbon neutrality targets. The loss of soil carbon storage in degraded grasslands can serve as a benchmark for quantifying the carbon sequestration capacity of restored grasslands in the future. Here, above- and below-ground biomass, soil organic carbon (SOC) content at various depths (0-100 cm) and soil bulk density were collected from 226 degradation sequences around China. The above information was integrated and statistically analyzed to quantify the difference of SOC storage between the degraded and natural grassland at national scale. The result showed that grassland degradation led to a significant reduction in SOC storage across different depths. SOC (0-100 cm) of degraded grassland decreased by 39 % compared to that of natural grassland, ranging from 21 % in the lightly degraded sites to 59 % of the extremely degraded sites. 15 potential predictors were used to estimate the national amount of these differences of 0-20 cm depth SOC storage as 5.29 ± 1.59 Pg C. This considerable carbon storage gap implies the necessity of China's grassland restoration project in achieving carbon neutrality goals in the future.

A new circa 2007 biomass map for China differs significantly from existing maps

The forest area of China is the fifth largest of any country, and unlike in many other countries, in recent decades its area has been increasing. However, there are substantial differences in estimates of the amount of carbon this forest contains, ranging from 3.92 to 17.02 Pg C for circa 2007. This makes it unclear how the changes in China's forest area contribute to the global carbon cycle. We generate a circa 2007 aboveground biomass (AGB) map at a resolution of 50 m using optical, radar and LiDAR satellite data. Our estimates of total carbon stored in the forest in China was 9.52 Pg C, with an average forest AGB of 104 Mg ha-1. Compared with three existing AGB maps, our AGB map showed better correlation with a distributed set of forest inventory plots. In addition, our high resolution AGB map provided more details on spatial distribution of forest AGB, and is likely to help understand the carbon storage changes in China's forest.

Afforestation increased the microbial necromass carbon accumulation in deep soil on the Loess Plateau

Microbial necromass carbon (MNC) is a stable part of SOC that makes up most of the C pool in land ecosystem. However, the contribution of MNC to SOC accumulation during afforestation is still unclear, particularly in the deep soil. Based on the collection and biomarker analysis of the forest succession sequence and soil profiles with significant depth on the Loess Plateau located China, we study the vertical distribution characteristics and control of MNC. The results found that MNC content increased with succession and decreased with soil depth. On average, the MNC content of a climax forest was 2.23 times higher than that of farmland. The FNC:BNC ratio increased with vegetation succession and decreased with soil depth. Although the MNC content decreased with soil depth, the necromass accumulation coefficient increased. The contribution of MNC to SOC in deep soil (60-100 cm) of pioneer forest was more than 10 % higher than that of farmland, suggesting that afforestation had a relatively positive effect on MNC stabilization and accumulation in deep soils. The microbial biomass and soil nutrient characteristics (i.e., TN, SOC, DOC, and DON) are important factors in mediating the accumulation of MNC in the succession of farmland to forest. These findings demonstrate the potential of MNC in deep soil and provide scientific guidance for sustainable reforestation management based on the carbon pump theory at regional scales.

Reducing spatial resolution increased net primary productivity prediction of terrestrial ecosystems: A Random Forest approach

Net primary production (NPP) is a pivotal component of the terrestrial carbon dynamic, as it directly contributes to the sequestration of atmospheric carbon by vegetation. However, significant variations and uncertainties persist in both the total amount and spatiotemporal patterns of terrestrial NPP, primarily stemming from discrepancies among datasets, modeling approaches, and spatial resolutions. In order to assess the influence of different spatial resolutions on global NPP, we employed a random forest (RF) model using a global observational dataset to predict NPP at 0.05°, 0.25°, and 0.5° resolutions. Our results showed that (1) the RF model performed satisfactorily with modeling efficiencies of 0.53-0.55 for the three respective resolutions; (2) NPP exhibited similar spatial patterns and interannual variation trends at different resolutions; (3) intriguingly, total global NPP varied greatly across different spatial resolutions, amounting 57.3 ± 3.07 for 0.05°, 61.46 ± 3.27 for 0.25°, and 66.5 ± 3.42 Pg C yr-1 for 0.5°. Such differences may be associated with the resolution transformation of the input variables when resampling from finer to coarser resolution, which significantly increased the spatial and temporal variation characteristics, particularly in regions within the southern hemisphere such as Africa, South America, and Australia. Therefore, our study introduces a new concept emphasizing the importance of selecting an appropriate spatial resolution when modeling carbon fluxes, with potential applications in establishing benchmarks for global biogeochemical models.

Forestation at the right time with the right species can generate persistent carbon benefits in China

Previous evaluations on the biophysical potential of forest carbon sink have focused on forestation area distribution and the associated carbon stock for equilibrium-state forests after centuries-long growth. These approaches, however, have limited relevance for climate policies because they ignore the near-term and mid-term decadal carbon uptake dynamics and suitable forest species for forestation. This study developed a forestation roadmap to support China's "carbon neutrality" objective in 2060 by addressing three key questions of forestation: where, with what forest species, and when to afforest. The results yielded a high-confidence potential forestation map for China at a resolution of 1 km with the identified optimal native forest type or species. Our analysis revealed an additional 78 Mha suitable for forestation up to the 2060s, a 43% increase on the current forest area. Selecting forest species for maximal carbon stock in addition to maximizing local environmental suitability enabled almost a doubling in forest carbon sink potential. Progressive forestation of this area can fix a considerable amount of CO2 and compensate for the carbon sink decline in existing forests. Altogether, the entire forest ecosystem can support a persistent biophysical carbon sink potential of 0.4 Pg C y-1 by 2060 and 0.2 Pg C y-1 by 2100, offsetting 7 to 14% of the current national fossil CO2 emissions. Our research provides an example of building a forestation roadmap toward a sustained forest carbon sink, which creates a critical time window for the emission cuts required by the goal of carbon neutrality.

Organic matter biomarker and 13C NMR characteristics of soil and sediment standard reference materials from China

Soil and sediment organic matter (OM) in terrestrial environments represent two critical organic carbon pools on Earth and are likely subject to distinct degrees of oxidation and modification. However, few studies have identified critical molecular-level characteristics that differentiate soil and sediment OM from various climate zones. Using biomarkers and solid-state ¹³C nuclear magnetic resonance (NMR) spectroscopy analyses, we studied the OM characteristics of 11 soil and 7 sediment standard reference materials (SRMs) originating from various geographical locations in China. Results showed significantly higher concentrations of lignin phenols in sediment OM than in soil OM, which may result from protection by higher contents of CaO and less microbial degradation in sediments. Nevertheless, the relative abundances of solvent-extractable lipids (alkanes, alkanols, and alkanoic acids) and ester-bound cutin and suberin biomarkers did not differ significantly between soil and sediment SRMs. The concentrations of lignin biomarkers decreased with increasing weathering degree of the soil, while cutin biomarkers increased with mean annual temperature and precipitation. This phenomenon was not observed in sediment SRMs. This study reveals the distinct OM characteristics between Chinese soil and sediment SRMs and provides fundamental data for future studies to link OM characteristics and functions.

Effect of Climate on Carbon Storage Growth Models for Three Major Coniferous Plantations in China Based on National Forest Inventory Data

Forest inventory data (FID) are important resources for understanding the dynamics of forest carbon cycling at regional and global scales. Developing carbon storage growth models and analyzing the difference and climate effect on carbon sequestration capacity have a great importance in practice, which can provide a decision-making basis for promoting high-quality development of forestry and implementing the carbon emission peak and carbon neutralization strategy. Based on the carbon storage dataset of 2680 sample plots from the ninth national forest inventory (NFI) of China, the carbon storage growth models and climate-sensitive variable-parameter carbon storage growth models for three major coniferous plantations (Larix spp., Pinus massoniana, and Pinus tabuliformis) were developed by using weighted nonlinear regression method. The effects of two climate factors (mean annual temperature (MAT) and mean annual precipitation (MAP)) on carbon storage growth and carbon sequestration capacity were analyzed and compared. The mean prediction error (MPE) of carbon storage growth models for three major coniferous plantations was less than 5%, and total relative error (TRE) was approximately less than 2% for self- and cross- validation. The maximum current annual increment of carbon storage for P. massoniana, Larix, and P. tabuliformis was 2.29, 1.89, and 1.19 t/(ha·a), respectively, and their corresponding age of inflection point was 9a, 14a, and 30a, respectively. The maximum average increment of carbon storage for P. massoniana, Larix, and P. tabuliformis was 1.85, 1.50, and 0.94 t/(ha·a), respectively, and their corresponding age of quantitative maturity was 16a, 24a, and 53a, respectively. The maximum average increment of carbon storage for the P. massoniana and Larix plantations was approximately 1.97 and 1.60 times, respectively, that of P. tabuliformis plantation. The average increment of carbon storage for the P. massoniana and Larix plantations reduced approximately by 4.5% and 3.8%, respectively, when the MAT decreases by 1 °C. The average increment of carbon storage for the Larix and P.tabuliformis plantations decreased by approximately 6.5% and 3.6%, respectively, when the MAP decreases by 100 mm. Our findings suggest that: the carbon sequestration capacity is from highest to lowest in the P. massoniana, Larix, and P. tabuliformis forests. MAT and MAP have different effects on the carbon growth process and carbon sequestration capacity of these plantations. The greatest impact on carbon sequestration capacity was detected in the Larix plantation, followed by the P. massoniana and P. tabuliformis plantations. It is essential to coordinate regional development and employ scientific management strategies to fully develop the maximum carbon sequestration capacity in terms of plantations in China. In the present study, we estimate the carbon storage in major coniferous plantations in China and describe a useful methodology for estimating forest carbon storage at regional and global levels.

Alpine Grassland Reviving Response to Seasonal Snow Cover on the Tibetan Plateau

Season snow cover plays an important role in vegetation growth in alpine regions. In this study, we analyzed the spatial and temporal variations in seasonal snow cover and the start of the growing season (SOS) of alpine grasslands and preliminarily studied the mechanism by which snow cover affects SOS changes by modifying the soil temperature (ST) and soil moisture (SM) in spring. The results showed that significant interannual trends in the SOS, snow end date (SED), snow cover days (SCD), ST, and SM existed over the Tibetan Plateau (TP) in China from 2000 to 2020. The SOS advanced by 2.0 d/10 a over the TP over this period. Moreover, the SOS showed advancing trends in the eastern and central parts of the TP and a delayed trend in the west. The SED and SCD exhibited an advancing trend and a decreasing trend in high-elevation areas, respectively, and the opposite trends in low-elevation areas. The ST showed a decreasing trend in low-elevation areas and an increasing trend in high-elevation areas. The SM tended to increase in most areas. The effects of the seasonal snow cover on the ST and SM indirectly influenced the SOS of alpine grasslands. The delayed SEDs and more SCD observed herein could provide increasingly wet soil conditions optimal for the advancement of the SOS, while less snow and shorter snow seasons could delay the SOS of alpine grasslands on the TP.

Terrestrial carbon sinks in China and around the world and their contribution to carbon neutrality

Enhancing the terrestrial ecosystem carbon sink (referred to as terrestrial C sink) is an important way to slow down the continuous increase in atmospheric carbon dioxide (CO₂) concentration and to achieve carbon neutrality target. To better understand the characteristics of terrestrial C sinks and their contribution to carbon neutrality, this review summarizes major progress in terrestrial C budget researches during the past decades, clarifies spatial patterns and drivers of terrestrial C sources and sinks in China and around the world, and examines the role of terrestrial C sinks in achieving carbon neutrality target. According to recent studies, the global terrestrial C sink has been increasing from a source of (-0.2±0.9) Pg C yr^-1 (1 Pg=10¹⁵ g) in the 1960s to a sink of (1.9±1.1) Pg C yr^-1 in the 2010s. By synthesizing the published data, we estimate terrestrial C sink of 0.20-0.25 Pg C yr^-1 in China during the past decades, and predict it to be 0.15-0.52 Pg C yr^-1 by 2060. The terrestrial C sinks are mainly located in the mid- and high latitudes of the Northern Hemisphere, while tropical regions act as a weak C sink or source. The C balance differs much among ecosystem types: forest is the major C sink; shrubland, wetland and farmland soil act as C sinks; and whether the grassland functions as C sink or source remains unclear. Desert might be a C sink, but the magnitude and the associated mechanisms are still controversial. Elevated atmospheric CO₂ concentration, nitrogen deposition, climate change, and land cover change are the main drivers of terrestrial C sinks, while other factors such as fires and aerosols would also affect ecosystem C balance. The driving factors of terrestrial C sink differ among regions. Elevated CO₂ concentration and climate change are major drivers of the C sinks in North America and Europe, while afforestation and ecological restoration are additionally important forcing factors of terrestrial C sinks in China. For future studies, we recommend the necessity for intensive and long term ecosystem C monitoring over broad geographic scale to improve terrestrial biosphere models for accurately evaluating terrestrial C budget and its dynamics under various climate change and policy scenarios.

Loss of soil microbial residue carbon by converting a tropical forest to tea plantation

Land-use change can lead to profound changes in the storage of soil organic carbon (SOC) in the tropics. Soil microbial residues make up the majority of persistent SOC pools, yet the impact of land-use change on microbial residue C accumulation in the tropics is not well understood. Here, we investigated how the conversion of tropical primary montane rainforest to secondary forest and the conversions of secondary forest to Prunus salicina plantation and tea plantation, influence the accumulation of soil microbial residue C (indicated by amino sugars). Our results showed that the secondary forest had a higher SOC than that of the primary forest (+63%), while they had no difference in microbial residue C concentration, indicating a relatively slow microbial-derived C accrual during secondary succession. Moreover, the P. salicina plantation and tea plantation had lower SOC than the secondary forest (-53% and -57%, respectively). A decrease in fungal biomass (-51%) resulted in less fungal and total residue C concentrations in the tea plantation than in the secondary forest (-38% and -35%, respectively), indicating microbial-derived C loss following the forest conversion. The change in microbial residue C depended on litter standing crop rather than soil nutrient and root biomass. Litter standing crop affected microbial residue C concentration by regulating fungal biomass and hydrolytic enzyme activities. Taken together, our results highlight that litter-microbe interactions drive microbial residue C accumulation following forest conversions in the tropics.

Functional fungal communities dominate wood decomposition and are modified by wood traits in a subtropical forest

Wood decomposition is a fundamental process of the carbon cycle in forest ecosystems and differs under varying environmental conditions. However, it remains unclear whether exposure situation and litter removal affect wood decomposition, especially in subtropical forests. Therefore, we chose wood from four dominant species and carried out an experiment with treatments consisting of placing wood in ground contact with and without litter input and above ground exposure. The experiment was performed for 2.5 consecutive years in the subtropical forest of Southwest China to reveal the potential effects of microenvironmental changes due to above ground exposure and nutrient input changes due to litter removal. In this study, neither above ground exposure nor litter removal significantly changed the fungal communities, microbial respiration rates or decomposition rates of the wood, but significant differences among tree species were observed. The abundance of Ascomycota (70.2%) was higher than that of Basidiomycota (24.3%), and there was a significant negative relationship between their abundances, suggesting competition. Moreover, negative (Ascomycota) and positive (Basidiomycota) relationships with microbial respiration and explained 21.5 and 25.5% of the variation in microbial respiration, respectively. The wood density was directly controlled by the sugar, cellulose, and lignin contents and influenced the water content in the wood. The abundances of saprotrophic and pathotrophic fungi were significantly and directly regulated by the water content of the wood. The abundance of pathotrophic fungi was unaffected by wood traits, but these fungi may limit saprotrophic fungal colonization, thereby affecting microbial respiration and decomposition processes. We confirmed that the saprotrophic fungal abundance, rather than fungal diversity, determined wood microbial respiration. These results are of great significance for the comprehensive assessment of wood decomposition and the carbon cycle in subtropical forests, although long-term fungal community dynamics and decomposition rates under different conditions require further study.

Characteristics and Drivers of Soil Organic Carbon Saturation Deficit in Karst Forests of China

Karst forests have complex and unique carbon cycle characteristics. Soil organic carbon saturation deficit (CSD) is an important indicator of soil organic carbon (SOC) sequestration potential; exploring its characteristics and driving factors is a priority theme in current research on the carbon cycles of terrestrial ecosystems. In this study, 171 topsoil samples from typical karst forests in southwest China were used as the study objects. A SOC maximum saturation capacity model was constructed using the boundary line method. The CSD is equal to the maximum saturated capacity of SOC minus the current SOC. We analyzed the CSD and its main driving factors in different regions and succession stages. The results showed that the fractions of carbon and SOC contents in the karst forests at different successional stages in descending order were as follows: climax stage > arbor stage > shrub stage > herb stage. The CSD was the highest at the herb stage in Maolan, Yuntai Mountain, and Dashahe at 83.04%, 89.99%, and 89.97%, respectively, followed by the shrub stage with 48.69%, 78.50%, and 84.95%, and the lowest at the arbor stage with 25.69%, 43.44%, and 60.49%. The main drivers of CSD in the karst forest of Maolan were litter carbon input, total nitrogen, total phosphorus, and total SOC, and were litter carbon input at Yuntai Mountain and litter carbon input and neutral phosphatase at Dashahe. The results indicate that the core driver of CSD in the karst forest is litter carbon input, and this can be adjusted in the future to regulate the carbon sequestration capacity of SOC.

Effects of soil fauna on litter decomposition in Chinese forests: a meta-analysis

Litter quality and climate have been presumed to be the dominant factors regulating litter decomposition rates on broad spatial scales. However, the role of soil fauna on litter decomposition is poorly understood, despite the fact that it could strongly influence decomposition by fragmentation and subsequent modification of the activities of microorganisms.In this study, we carried out a meta-analysis on the effects of soil fauna on litter decomposition rates in Chinese forests, ranging from boreal to tropical forests, based on data from 20 studies. The effects of climatic factors on decomposition rate were assessed by comparing the contribution of soil fauna to litter decomposition from studies carried out at different latitudes.The degree of influence of the soil fauna was in the order tropical (200%) > subtropical (47%) > temperate forest (28%). Comparing the effect size of soil fauna, it was found that when soil fauna was excluded, the decomposition rate, calculated using Olson's equation, was most affected in tropical forest (-0.77), while the litter decomposition rate both subtropical (-0.36) and temperate forest (-0.19) were also suppressed to varying degrees (P < 0.001). These results highlight that soil fauna could promote litter decomposition to different extents. Using stepwise multiple linear regression, the effect size of the soil fauna was negatively correlated with the cellulose and nitrogen concentrations of the initial litter material. In Chinese forests, litter decomposition rates were reduced, on average, by 65% when soil fauna was excluded. The impact of soil fauna on decomposition was shown to be closely related to climate and litter quality.

Predicting downed woody material carbon stocks in forests of the conterminous United States

Downed woody material (DWM) is a unique part of the forest carbon cycle serving as a pool between living biomass and subsequent atmospheric emission or transference to other forest pools. Thus, DWM is an individually defined pool in national greenhouse gas inventories. The diversity of DWM carbon drivers (e.g., decay, tree mortality, or wildfire) and associated high spatial variability make this a difficult-to-predict component of forest ecosystems. Using the now fully established nationwide inventory of DWM across the United States (US), we developed models, which substantially improved predictions of stand-level DWM carbon density relative to the current national-reporting model ('previous' model, here). The previous model was developed from published DWM carbon densities prior to the NFI DWM inventory. Those predictions were tested using NFI DWM carbon densities resulting in a poor fit to the data (coefficient of determination, or R² = 0.03). We present new random forest (RF) and stochastic gradient boosted (SGB) regression models to prediction DWM carbon density on all NFI plots and spatially on all forest land pixels. We evaluated various biotic and abiotic regression predictors, and the most important were standing dead trees, long-term annual precipitation, and long-term maximum summer temperature. A RF model scored best for expanding predictions to NFI plots (R² = 0.31), while an SGB model was identified for DWM carbon predictions based on purely spatial data (i.e., NFI-plot-independent, with R² = 0.23). The new RF model predicts conterminous US DWM carbon stocks to be 15% lower than the previous model and 2% higher than NFI data expanded according to inventory design-based inference. The new NFI data-driven models not only improve the predictions of DWM carbon density on all plots, they also provide flexibility in extending these predictions beyond the NFI to make spatially explicit and spatially continuous estimates of DWM carbon on all forest land in the US.

Variation of Soil Organic Carbon Density with Plantation Age and Initial Vegetation Types in the Liupan Mountains Areas of Northwest China

Carbon sequestration of plantations formed by three kinds of forestation (natural forest to plantation (NP), grassland to plantation (GP), and cropland to plantation (CP)) greatly depends on the change of soil organic carbon density (SOCD) compared with its initial SOCD before forestation. However, this dependence was rarely studied, especially in semi-humid/arid regions with strong site variation. This limits the precise assessment and management of SOCD. Therefore, the SOCD variations of 0–100 cm soil layers in these three kinds of plantations were studied in the semi-humid/arid Liupan Mountains in northwestern China. The NP with high initial SOCD showed firstly a decrease and then an increase of SOCD up to 293.2 t·ha−1 at 40 years. The CP and GP with low and relatively high initial SOCD showed negligible and slight SOCD decrease after forestation, but then an increase up to 154.5 and 266.5 t·ha−1 at 40 years. After detecting the main factors influencing SOCD for each forestation mode, statistic relationships were fitted for predicting SOCD variation. This study indicates that besides forest age and biomass growth, the effects of initial vegetation, site-dependent initial SOCD, and SOCD capacity, also precipitation and air temperature in some cases, should be considered for more precise assessment and management of SOCD of plantations.

Temperature Sensitivity of CO2 and CH4 Fluxes from Coarse Woody Debris in Northern Boreal Forests

Carbon dioxide (CO2) and methane (CH4) are recognized as the main greenhouse gases causing climate warming. In forest ecosystems, the death of trees leads to the formation of coarse woody debris (CWD) that is one of the sources of greenhouse gas emissions due to wood decomposition. We quantified the CO2 and CH4 fluxes from CWD of larch (Larix gmelinii (Rupr.)) and birch (Betula tortuosa Ledeb.) collected in the northern boreal forests of Central Siberia. The CWD samples were incubated at +5, +15 and +25 °C. The CO2 and CH4 fluxes showed strong correlations with temperature, moisture, decomposition stage and the type of wood’s rot. The temperature coefficient Q10 indicated higher temperature sensitivity of CO2 flux within the temperature interval from +5 to +15 °C than from +15 to +25 °C. Methane flux had higher temperature sensitivity within the interval from +15 to +25 °C. It was found that, in boreal forests, CWD of early decay stage can serve as a source of methane to the atmosphere when air temperatures increased above +15 °C. Strong positive correlation between CH4 production and CO2 emission indicated a biological source and supported findings on aerobic origin of the main process contributing to the CH4 flux from decomposing CWD.

Traits mediate drought effects on wood carbon fluxes

CO₂ fluxes from wood decomposition represent an important source of carbon from forest ecosystems to the atmosphere, which are determined by both wood traits and climate influencing the metabolic rates of decomposers. Previous studies have quantified the effects of moisture and temperature on wood decomposition, but these effects were not separated from the potential influence of wood traits. Indeed, it is not well understood how traits and climate interact to influence wood CO₂ fluxes. Here, we examined the responses of CO₂ fluxes from dead wood with different traits (angiosperm and gymnosperm) to 0%, 35%, and 70% rainfall reduction across seasonal temperature gradients. Our results showed that drought significantly decreased wood CO₂ fluxes, but its effects varied with both taxonomical group and drought intensity. Drought-induced reduction in wood CO₂ fluxes was larger in angiosperms than gymnosperms for the 35% rainfall reduction treatment, but there was no significant difference between these groups for the 70% reduction treatment. This is because wood nitrogen density and carbon quality were significantly higher in angiosperms than gymnosperms, yielding a higher moisture sensitivity of wood decomposition. These findings were demonstrated by a significant positive interaction effect between wood nitrogen and moisture on CO₂ fluxes in a structural equation model. Additionally, we ascertained that a constant temperature sensitivity of CO₂ fluxes was independent of wood traits and consistent with previous estimates for extracellular enzyme kinetics. Our results highlight the key role of wood traits in regulating drought responses of wood carbon fluxes. Given that both climate and forest management might extensively modify taxonomic compositions in the future, it is critical for carbon cycle models to account for such interactions between wood traits and climate in driving dynamics of wood decomposition.

Multi-criteria decision making for sustainability assessment of boxboard production: A life cycle perspective considering water consumption, energy consumption, GHG emissions, and internal costs

Papermaking is a capital-intensive industry that requires a high consumption of plant fibers, energy, and water. Previous sustainability assessments of papermaking industry primarily focused on separate evaluations for multiple criteria without the integration for criteria and could not compare the overall priority of the production alternatives. The life cycle sustainability for the most representative boxboard production is analyzed as a case study in this work. Life cycle water consumption, energy consumption, greenhouse gas emissions, and internal costs are selected as the assessment criteria. The two multi-criteria decision-making methods are applied to integrate the above criteria to obtain the sustainability sequence under different production pathways. When the papermaking enterprises are regarded as decision-makers, the alternative using waste paper as raw material to manufacture boxboard is the most sustainable, following by mixed fiber. The sustainability sequence of the alternatives using wood and straw as raw materials is controversial due to the different calculation models. Changing the proportion of raw materials and the criteria weights might adjust sustainability sequence of the alternatives.

Allometric Equations for Estimating the Above-Ground Biomass of Five Forest Tree Species in Khangai, Mongolia

Understanding the contribution of forest ecosystems to regulating greenhouse gas emissions and maintaining the atmospheric CO2 balance requires the accurate quantification of above-ground biomass (AGB) at the individual tree species level. The main objective of this study was to develop species-specific allometric equations for the total AGB and various biomass components, including stem, branch, and foliage biomass in Khangai region, northern Mongolia. We destructively sampled a total of 183 trees of five species (22–74 trees per species), including Siberian stone pine (Pinus sibirica Du Tour.), Asian white birch (Betula platyphylla Sukacz.), Mongolian poplar (Populus suaveolens Fisch.), Siberian spruce (Picea obovata Ldb.), and Siberian larch (Larix sibirica Ldb.), across this region. The results showed that for the five species, the average biomass proportion for the stems was 75%, followed by branches at 20% and foliage at 5%. The species-specific component and total AGB models for the Khangai region were developed using tree diameter at breast height (D) and D² and tree height (H) combined ( D 2 H ); and both D and H were used as independent variables. The best allometric model was lnŶ = lna + b × lnD + c × lnH for the various components and total AGB of B. platyphylla and L. sibirica, for the stems and total AGB of P. suaveolens, and for the stem and branch biomass of P. obovata. The equation lnŶ = lna + b × ln( D 2 × H ) was best for the various components and total AGB of P. sibirica, for the branch and foliage biomass of P. suaveolens, and for AGB of P. obovata. The equation lnŶ = lna + b × ln(D) was best only for the foliage biomass of P. obovata. Our results highlight that developing species-specific tree AGB models is very important for accurately estimating the biomass in the Khangai forest region of Mongolia. Our biomass models will be used at the tree level inventories with sample plots in the Khangai forest region.

Phytolith-Occluded Carbon Storages in Forest Litter Layers in Southern China: Implications for Evaluation of Long-Term Forest Carbon Budget

Phytolith-occluded carbon (PhytOC) can be preserved in soils or sediments for thousands of years and might be a promising potential mechanism for long-term terrestrial carbon (C) sequestration. As the principal pathway for the return of organic matters to soils, the forest litter layers make a considerable contribution to terrestrial C sequestration. Although previous studies have estimated the phytolith production fluxes in the above-ground vegetations of various terrestrial ecosystems, the storages of phytoliths and PhytOC in litter layers have not been thoroughly investigated, especially in forest ecosystems. Using analytical data of silica, phytoliths, return fluxes and storages of forest litter, this study estimated the phytolith and PhytOC storages in litter layers in different forest types in southern China. The results indicated that the total phytolith storage in forest litter layers in southern China was 24.34 ± 8.72 Tg. Among the different forest types, the phytolith storage in bamboo forest litter layers (15.40 ± 3.40 Tg) was much higher than that in other forests. At the same time, the total PhytOC storage reached up to 2.68 ± 0.96 Tg CO2 in forest litter layers in southern China, of which approximately 60% was contributed by bamboo forest litter layers. Based on the current litter turnover time of different forest types in southern China, a total of 1.01 ± 0.32 Tg of PhytOC per year would be released into soil profiles as a stable C pool during litter decomposition, which would make an important contribution to the global terrestrial long-term biogeochemical C sink. Therefore, the important role of PhytOC storage in forest litter layers should be taken into account in evaluating long-term forest C budgets.

Airborne LIDAR-Derived Aboveground Biomass Estimates Using a Hierarchical Bayesian Approach

Conventional ground survey data are very accurate, but expensive. Airborne lidar data can reduce the costs and effort required to conduct large-scale forest surveys. It is critical to improve biomass estimation and evaluate carbon stock when we use lidar data. Bayesian methods integrate prior information about unknown parameters, reduce the parameter estimation uncertainty, and improve model performance. This study focused on predicting the independent tree aboveground biomass (AGB) with a hierarchical Bayesian model using airborne LIDAR data and comparing the hierarchical Bayesian model with classical methods (nonlinear mixed effect model, NLME). Firstly, we chose the best diameter at breast height (DBH) model from several widely used models through a hierarchical Bayesian method. Secondly, we used the DBH predictions together with the tree height (LH) and canopy projection area (CPA) derived by airborne lidar as independent variables to develop the AGB model through a hierarchical Bayesian method with parameter priors from the NLME method. We then compared the hierarchical Bayesian method with the NLME method. The results showed that the two methods performed similarly when pooling the data, while for small sample sizes, the Bayesian method was much better than the classical method. The results of this study imply that the Bayesian method has the potential to improve the estimations of both DBH and AGB using LIDAR data, which reduces costs compared with conventional measurements.

Effects of Predominant Tree Species Mixing on Lignin and Cellulose Degradation during Leaf Litter Decomposition in the Three Gorges Reservoir, China

The aim of this study was to investigate the potential mixing effects on degradation of lignin and cellulose in mixed leaf litter from Pinus massoniana Lamb., Cupressus funebris Endl., and/or Quercus variabilis Bl., and elucidate the interactions with abiotic factors. The litter bag method was used in the field experiment, and the three predominant species in the Three Gorges Reservoir region were treated as single-, pair-, and tri-species combinations with equal proportions of litter mass. Lignin and cellulose losses in the litter treatments were measured, and the mixing effects were evaluated based on the sampling phase and decomposition period. At the end of the one-year decomposition period, mixing species increased lignin loss by 3.3% for the cypress + oak combination and cellulose loss by 3.9%, 1.8%, and 0.8% for the pine + oak, cypress + oak, and pine + cypress + oak combinations, respectively. The pine + oak and cypress + oak combinations exhibited greater lignin and cellulose loss than the tri-species mixture. Accelerated lignin degradation also apparently occurred in the pine + cypress combination as decomposition proceeded. Generalized linear models suggested that the investigated environmental factors (in terms of average temperature and cumulative precipitation) and changing litter quality (lignin, cellulose, and lignin/cellulose) had significant effects on nonadditive lignin loss, whereas only the changing litter quality factors significantly affected nonadditive cellulose loss. In summary, mixing two or three of the studied species alters cycling of recalcitrant substrates in plantations, and mixed planting with Quercus appears to strengthen both the lignin and cellulose degradation processes.

Estimating uncertainty in the volume and carbon storage of downed coarse woody debris

Downed coarse woody debris, also known as coarse woody detritus or downed dead wood, is challenging to estimate for many reasons, including irregular shapes, multiple stages of decay, and the difficulty of identifying species. In addition, some properties are commonly not measured, such as wood density and carbon concentration. As a result, there have been few previous evaluations of uncertainty in estimates of downed coarse woody debris, which are necessary for analysis and interpretation of the data. To address this shortcoming, we quantified uncertainties in estimates of downed coarse woody debris volume and carbon storage using data collected from permanent forest inventory plots in the northeastern United States by the Forest Inventory and Analysis program of the USDA Forest Service. Quality assurance data collected from blind remeasurement audits were used to quantify error in diameter measurements, hollowness of logs, species identification, and decay class determination. Uncertainty estimates for density, collapse ratio, and carbon concentration were taken from the literature. Estimates of individual sources of uncertainty were combined using Monte Carlo methods. Volume estimates were more reliable than carbon storage, with an average 95% confidence interval of 15.9 m³ /ha across the 79 plots evaluated, which was less than the mean of 31.2 m³ /ha. Estimates of carbon storage (and mass) were more uncertain, due to poorly constrained estimates of the density of wood. For carbon storage, the average 95% confidence interval was 11.1 Mg C/ha, which was larger than the mean of 4.6 Mg C/ha. Accounting for the collapse of dead wood as it decomposes would improve estimates of both volume and carbon storage. On the other hand, our analyses suggest that consideration of the hollowness of downed coarse woody debris pieces could be eliminated in this region, with little effect. This study demonstrates how uncertainty analysis can be used to quantify confidence in estimates and to help identify where best to allocate resources to improve monitoring designs.

Spatial modeling of litter and soil carbon stocks on forest land in the conterminous United States

Forest ecosystems contribute substantially to carbon (C) storage. The dynamics of litter decomposition, translocation and stabilization into soil layers are essential processes in the functioning of forest ecosystems, as these processes control the cycling of soil organic matter and the accumulation and release of C to the atmosphere. Therefore, the spatial distribution of litter and soil C stocks are important in greenhouse gas estimation and reporting and inform land management decisions, policy, and climate change mitigation strategies. Here we explored the effects of spatial aggregation of climatic, biotic, topographic and soil variables on national estimates of litter and soil C stocks and characterized the spatial distribution of litter and soil C stocks in the conterminous United States (CONUS). Litter and soil variables were measured on permanent sample plots (n = 3303) from the National Forest Inventory (NFI) within the United States from 2000 to 2011. These data were used with vegetation phenology data estimated from LANDSAT imagery (30 m) and raster data describing environmental variables for the entire CONUS to predict litter and soil C stocks. The total estimated litter C stock was 2.07 ± 0.97 Pg with an average density of 10.45 ± 2.38 Mg ha^-1, and the soil C stock at 0-20 cm depth was 14.68 ± 3.50 Pg with an average density of 62.68 ± 8.98 Mg ha^-1. This study extends NFI data from points to pixels providing spatially explicit and continuous predictions of litter and soil C stocks on forest land in the CONUS. The approaches described illustrate the utility of harmonizing field measurements with remotely sensed data to facilitate modeling and prediction across spatial scales in support of inventory, monitoring, and reporting activities, particularly in countries with ready access to remotely sensed data but with limited observations of litter and soil variables.

Effects of mixed leaf litter from predominant afforestation tree species on decomposition rates in the Three Gorges Reservoir, China

To determine whether mixed plantations can improve nutrient cycling and to elucidate the mechanisms of such effects, a field litterbag experiment with seven treatments involving Pinus massoniana (P.), Cupressus funebris (C.) and Quercus variabilis (Q.) litter in equal mass proportions (pure litter; pairwise combinations; and the combination of all three species) was conducted in a Pinus massoniana plantation in the region of the Three Gorges Reservoir, China. We measured mass loss and the release of C, N and P from the litter treatments and assessed the effects of mixing litter in each sampling phase and for various decomposition periods. At the end of the study, the mass loss and release of C, N and P among the treatments relative to their initial contents ranged from 47.6% to 62.8%, 59.5% to 75.2%, 63.5% to 78.2% and 58.9% to 72.6%, respectively. Primary mass loss and nutrient release occurred during a phase with high temperatures and precipitation, and decomposition was closely correlated with the initial lignin/N ratio and N concentration. Compared with the decay values of Quercus litter, mixing litter increased N release by 1.2% for the P. + Q. and C. + Q. combinations and increased P release by 3.0-6.3% for the three litter mixture combinations. Additionally, the P. + Q. and C. + Q. two-species mixtures exhibited greater decay than the three-species mixture. Mixing the two coniferous species (P. + C.) also increased decomposition. Furthermore, positive nonadditive mass loss occurred after incubation for 240 d, and mixing effects on the nonadditive release of C, N and P occurred immediately in 60 d incubations in all treatments. In conclusion, mixing these three species or two of species can improve material cycling in plantations, and Quercus appears to be a priority candidate for mixed planting with Pinus and/or Cupressus.

Estimation of Forest Carbon Stocks for National Greenhouse Gas Inventory Reporting in South Korea

The development of country-specific emission factors in relation to the Agriculture, Forestry, and Other Land Use (AFOLU) sector has the potential to improve national greenhouse gas inventory systems. Forests are carbon sinks in the AFOLU that can play an important role in mitigating global climate change. According to the United Nations Framework Convention on Climate Change (UNFCCC), signatory countries must report forest carbon stocks, and the changes within them, using emission factors from the Intergovernmental Panel on Climate Change (IPCC) or from country-specific values. This study was conducted to estimate forests carbon stocks and to complement and improve the accuracy of national greenhouse gas inventory reporting in South Korea. We developed country-specific emissions factors and estimated carbon stocks and their changes using the different approaches and methods described by the IPCC (IPCCEF: IPCC default emission factors, CSFT: country-specific emission factors by forest type, and CSSP: country-specific emission factors by species). CSFT returned a result for carbon stocks that was 1.2 times higher than the value using IPCCEF. Using CSSP, CO2 removal was estimated to be 60,648 Gg CO2 per year with an uncertainty of 22%. Despite a reduction in total forest area, forests continued to store carbon and absorb CO2, owing to differences in the carbon storage capacities of different forest types and tree species. The results of this study will aid estimations of carbon stock changes and CO2 removal by forest type or species, and help to improve the completeness and accuracy of the national greenhouse gas inventory. Furthermore, our results provide important information for developing countries implementing Tier 2, the level national greenhouse gas inventory systems recommended by the IPCC.

Aboveground carbon sequestration in dry temperate forests varies with climate not fire regime

The storage of carbon in plant tissues and debris has been proposed as a method to offset anthropogenic increases in atmospheric [CO₂ ]. Temperate forests represent significant above-ground carbon (AGC) "sinks" because their relatively fast growth and slow decay rates optimise carbon assimilation. Fire is a common disturbance event in temperate forests globally that should strongly influence AGC because: discrete fires consume above-ground biomass releasing carbon to the atmosphere, and the long-term application of different fire-regimes select for specific plant communities that sequester carbon at different rates. We investigated the latter process by quantifying AGC storage at 104 sites in the Sydney Basin Bioregion, Australia, relative to differences in components of the fire regime: frequency, severity and interfire interval. To predict the potential impacts of future climate change on fire/AGC interactions, we stratified our field sites across gradients of mean annual temperature and precipitation and quantified within- and between-factor interactions between the fire and climate variables. In agreement with previous studies, large trees were the primary AGC sink, accounting for ~70% of carbon at sites. Generalised additive models showed that mean annual temperature was the strongest predictor of AGC storage, with a 54% near-linear decrease predicted across the 6.1°C temperature range experienced at sites. Mean annual precipitation, fire frequency, fire severity and interfire interval were consistently poor predictors of total above-ground storage, although there were some significant relationships with component stocks. Our results show resilience of AGC to frequent and severe wildfire and suggest temperature mediated decreases in forest carbon storage under future climate change predictions.

New endoperoxides highly active in vivo and in vitro against artemisinin-resistant Plasmodium falciparum

BACKGROUND

The emergence and spread of Plasmodium falciparum resistance to artemisinin-based combination therapy in Southeast Asia prompted the need to develop new endoperoxide-type drugs.

METHODS

A chemically diverse library of endoperoxides was designed and synthesized. The compounds were screened for in vitro and in vivo anti-malarial activity using, respectively, the SYBR Green I assay and a mouse model. Ring survival and mature stage survival assays were performed against artemisinin-resistant and artemisinin-sensitive P. falciparum strains. Cytotoxicity was evaluated against mammalian cell lines V79 and HepG2, using the MTT assay.

RESULTS

The synthesis and anti-malarial activity of 21 new endoperoxide-derived compounds is reported, where the peroxide pharmacophore is part of a trioxolane (ozonide) or a tetraoxane moiety, flanked by adamantane and a substituted cyclohexyl ring. Eight compounds exhibited sub-micromolar anti-malarial activity (IC₅₀ 0.3-71.1 nM), no cross-resistance with artemisinin or quinolone derivatives and negligible cytotoxicity towards mammalian cells. From these, six produced ring stage survival < 1% against the resistant strain IPC5202 and three of them totally suppressed Plasmodium berghei parasitaemia in mice after oral administration.

CONCLUSION

The investigated, trioxolane-tetrazole conjugates LC131 and LC136 emerged as potential anti-malarial candidates; they show negligible toxicity towards mammalian cells, ability to kill intra-erythrocytic asexual stages of artemisinin-resistant P. falciparum and capacity to totally suppress P. berghei parasitaemia in mice.

The response of tree growth to nitrogen and phosphorus additions in a tropical montane rainforest

Rapid increase of global nitrogen (N) deposition has greatly altered carbon cycles and functioning of forest ecosystems. Previous studies have focused on changes in carbon dynamics of temperate and subtropical forests through N enrichment experiments; however, the effects of N deposition on tree growth remain inconsistent, especially in tropical forests. Here, we conducted a five-year N addition experiment (0 and 50kgNha^-1yr^-1) in a tropical montane rain forest in Hainan Island, China, to explore the effects of enhanced N deposition on growth of trees. We also set phosphorus (P) treatment (50kgPha^-1yr^-1) and N+P treatment (50kgNha^-1yr^-1+50kgPha^-1yr^-1) to examine potential P limitation driven by N deposition. Our results showed that N addition has not significantly influenced tree growth, while P addition significantly increased the relative growth rate of small (diameter at breast height, DBH≤10cm) and medium (10<DBH≤20cm) trees. The combined N and P addition accelerated the growth of small trees, but did not affect the growth of medium and large (20cm<DBH) trees. These contrasting effects of N and P addition on tree growth indicate that the tropical montane forest is mainly limited by P, which suggests the importance of P in regulating growth of trees in tropical forests.