Aboveground carbon sequestration of Cunninghamia lanceolata forests:Magnitude and drivers

Understanding the spatial variation,temporal changes,and their underlying driving forces of carbon sequestration in various forests is of great importance for understanding the carbon cycle and carbon management options.How carbon density and sequestration in various Cunninghamia lanceolata forests,extensively cultivated for timber production in subtropical China,vary with biodiversity,forest structure,environment,and cultural factors remain poorly explored,presenting a critical knowledge gap for realizing carbon sequestration supply potential through management.Based on a large-scale database of 449 permanent forest inventory plots,we quantified the spatial-temporal heterogeneity of aboveground carbon densities and carbon accumulation rates in Cunninghamia lanceolate forests in Hunan Province,China,and attributed the contributions of stand structure,environmental,and management factors to the heterogeneity using quantile age-sequence analysis,partial least squares path modeling(PLS-PM),and hot-spot analysis.The results showed lower values of carbon density and sequestration on average,in comparison with other forests in the same climate zone(i.e.,subtropics),with pronounced spatial and temporal variability.Specifically,quantile regression analysis using carbon accumulation rates along an age sequence showed large differences in carbon sequestration rates among underperformed and outperformed forests(0.50 and 1.80 Mg·ha^(-1)·yr^(-1)).PLS-PM demonstrated that maximum DBH and stand density were the main crucial drivers of aboveground carbon density from young to mature forests.Furthermore,species diversity and geotopographic factors were the significant factors causing the large discrepancy in aboveground carbon density change between low-and high-carbon-bearing forests.Hotspot analysis revealed the importance of culture attributes in shaping the geospatial patterns of carbon sequestration.Our work highlighted that retaining largesized DBH trees and increasing shade-tolerant tree species were important to enhance carbon sequestration in C.lanceolate forests.

Predicting stand age in managed forests using National Forest Inventory field data and airborne laser scanning

Background: The aim of this study was to construct a nationwide stand age model by using National Forest Inventory(NFI) data and nationwide airborne laser scanning(ALS) data. In plantation forestry, age is usually known.While this is not the case in boreal managed forests, age is still seldom predicted in forest management inventories.Measuring age accurately in situ is also very laborious. On the other hand, tree age is one of the accurately measured sample tree attributes in NFI field data. Many countries also have a nationwide coverage of airborne laser scanning(ALS) data. In this study, we merged these data sources and constructed a nationwide, area-based model for stand age.Results: While constructing the model, we omitted old forests from the data, since the correlation between ALS height metrics and stand age diminished at stands with age > 100 years. Additionally, the effect of growth conditions was considerable, so we also utilized different geographical and NFI variables such as site fertility and soil type in the modeling. The resultant nationwide model for the stand age of managed forests yielded a root mean square error(RMSE) of about 14 years. The model could be improved further by additional forest structure variables, but such information may not be available in practice.Conclusions: The results showed that the prediction of stand age by ALS, geographical and NFI information was challenging, but stil possible with moderate success. This study is an example of the joint use of NFI and nationwide ALS data and re-use of NFI data in research.

Aged forests could still act as carbon sinks

Old-growth forests are traditionally negligible as carbon sinks, but CAS scientists recently reported that

Forest management required for consistent carbon sink in China’s forest plantations

Background:Forest is the largest biomass carbon(C)pool in China,taking up a substantial amount of atmospheric carbon dioxide.Although it is well understood that planted forests(PFs)act as a large C sink,the contribution of human management to C storage enhancement remains obscure.Moreover,existing projections of forest C dynamics suffer from spatially inconsistent age and type information or neglected human management impacts.In this study,using developed PF age and type maps and data collected from 1371 forest plantation sites in China,we simulated biomass C stock change and quantified management impacts for the time period 2010-2050.Results:Results show that future forest biomass C increment might have been overestimated by 32.5%-107.5% in former studies.We also found that age-related growth will be by far the largest contributor to PF biomass C increment from 2010 to 2050(1.23±0.002 Pg C,1 Pg=10^(15) g=1 billion metric tons),followed by the impact of human management(0.57±0.02 Pg C),while the contribution of climate is slight(0.087±0.04 Pg C).Besides,an additional 0.24±0.07 Pg C can be stored if current PFs are all managed by 2050,resulting in a total increase of 2.13±0.05 Pg C.Conclusions:Forest management and age-related growth dominate the biomass C change in PFs,while the effect of climatic factors on the accumulation is minor.To achieve the ambitious goal of forest C stock enhancement by 3.5 Pg from 2020 to 2050,we advocate to improve the management of existing forests and reduce the requests for more lands for forest expansion,which helps mitigate potential conflicts with agricultural sectors.Our results highlight that appropriate planning and management are required for sustaining and enhancing biomass C sequestration in China’s PF.

Mapping forest age using National Forest Inventory,airborne laser scanning,and Sentinel-2 data

Background:The age of forest stands is critical information for forest management and conservation,for example for growth modelling,timing of management activities and harvesting,or decisions about protection areas.However,area-wide information about forest stand age often does not exist.In this study,we developed regression models for large-scale area-wide prediction of age in Norwegian forests.For model development we used more than 4800 plots of the Norwegian National Forest Inventory(NFI)distributed over Norway between latitudes 58°and 65°N in an 18.2 Mha study area.Predictor variables were based on airborne laser scanning(ALS),Sentinel-2,and existing public map data.We performed model validation on an independent data set consisting of 63 spruce stands with known age.Results:The best modelling strategy was to fit independent linear regression models to each observed site index(SI)level and using a SI prediction map in the application of the models.The most important predictor variable was an upper percentile of the ALS heights,and root mean squared errors(RMSEs)ranged between 3 and 31 years(6%to 26%)for SI-specific models,and 21 years(25%)on average.Mean deviance(MD)ranged between^(−1) and 3 years.The models improved with increasing SI and the RMSEs were largest for low SI stands older than 100 years.Using a mapped SI,which is required for practical applications,RMSE and MD on plot level ranged from 19 to 56 years(29%to 53%),and 5 to 37 years(5%to 31%),respectively.For the validation stands,the RMSE and MD were 12(22%)and 2 years(3%),respectively.Conclusions:Tree height estimated from airborne laser scanning and predicted site index were the most important variables in the models describing age.Overall,we obtained good results,especially for stands with high SI.The models could be considered for practical applications,although we see considerable potential for improvements if better SI maps were available.

Conceptual models of forest dynamics in environmental education and management:keep it as simple as possible,but no simpler

Background：Conceptual models of forest dynamics are powerful cognitive tools,which are indispensable for communicating ecological ideas and knowledge,and in developing strategic approaches and setting targets for forest conservation,restoration and sustainable management.Forest development through time is conventionally described as a directional,or ＂linear＂,and predictable sequence of stages from ＂bare ground＂ to old forest representing the ＂climax-state＂.However,this simple view is incompatible with the current knowledge and understanding of intrinsic variability of forest dynamics.Hypothesis：Overly simple conceptual models of forest dynamics easily become transformed into biased mental models of how forests naturally develop and what kind of structures they display.To be able to communicate the essential features and diversity of forest dynamics,comprehensive conceptual models are needed.For this end,Kuuluvainen（2009） suggested a relatively simple conceptual model of forest dynamics,which separates three major modes of forest dynamics,and incorporates state changes and transitions between the forest dynamics modes depending on changes in disturbance regime.Conclusions：Conceptual models of forest dynamics should be comprehensive enough to incorporate both longterm directional change and short-term cyclic forest dynamics,as well as transitions from one dynamics mode to another depending on changes in the driving disturbance regime type.Models that capture such essential features of forest dynamics are indispensable for educational purposes,in setting reference conditions and in developing methods in forest conservation,restoration and ecosystem management.

Eucalyptus carbon stock estimation in subtropical regions with the modeling strategy of sample plots–airborne LiDAR–Landsat time series data

Updating eucalyptus carbon stock data in a timely manner is essential for better understanding and quantifying its effects on ecological and hydrological processes.At present,there are no suitable methods to accurately estimate the eucalyptus carbon stock in a large area.This research aimed to explore the transferability of the eucalyptus carbon stock estimation model at temporal and spatial scales and assess modeling performance through the strategy of combining sample plots,airborne LiDAR and Landsat time series data in subtropical regions of China.Specifically,eucalyptus carbon stock estimates in typical sites were obtained by applying the developed models with the combination of airborne LiDAR and field measurement data;the eucalyptus plantation ages were estimated using the random localization segmentation approach from Landsat time series data;and regional models were developed by linking LiDAR-derived eucalyptus carbon stock and vegetation age(e.g.,months or years).To examine the models’robustness,the developed models at the regional scale were transferred to estimate carbon stocks at the spatial and temporal scales,and the modeling results were evaluated using validation samples accordingly.The results showed that carbon stock can be successfully estimated using the age-based models(both age variables in months and years as predictor variables),but the month-based models produced better estimates with a root mean square error(RMSE)of 6.51 t⋅ha1 for Yunxiao County,Fujian Province,and 6.33 t⋅ha1 for Gaofeng Forest Farm,Guangxi Zhuang Autonomous Region.Particularly,the month-based models were superior for estimating the carbon stocks of young eucalyptus plantations of less than two years.The model transferability analyses showed that the month-based models had higher transferability than the year-based models at the temporal scale,indicating their possibility for analysis of carbon stock change.However,both the month-based and year-based models expressed relatively poor transferability at a spatial scale.This study provides new insights for cost-effective monitoring of carbon stock change in intensively managed plantation forests.

How forest age impacts on net primary productivity: Insights from future multi-scenarios

Forest net primary productivity(NPP)constitutes a key flux within the terrestrial ecosystem carbon cycle and serves as a significant indicator of the forests carbon sequestration capacity,which is closely related to forest age.Despite its significance,the impact of forest age on NPP is often ignored in future NPP projections.Here,we mapped forest age in Hunan Province at a 30-m resolution utilizing a combination of Landsat time series stack(LTSS),national forest inventory(NFI)data,and the relationships between height and age.Subsequently,NPP was derived from NFI data and the relationships between NPP and age was built for various forest types.Then forest NPP was predicted based on the NPP-age relationships under three future scenarios,assessing the impact of forest age on NPP.Our findings reveal substantial variations in forest NPP in Hunan Province under three future scenarios:under the age-only scenario,NPP peaks in 2041(133.56​Tg​C·yr^(−1)),while NPP peaks three years later in 2044(141.14​Tg​C·yr^(−1))under the natural development scenario.The maximum afforestation scenario exhibits the most rapid increase in NPP,with peaking in 2049(197.95​Tg​C·yr^(−1)).However,with the aging of the forest,NPP is projected to then decrease by 7.54%,6.07%,and 7.47%in 2060,and 20.05%,19.74%,and 28.38%in 2100,respectively,compared to their peaks under the three scenarios.This indicates that forest NPP will continue to decline soon.Controlling the age structure of forests through selective logging,afforestation and reforestation,and encouraging natural regeneration after disturbance could mitigate this declining trend in forest NPP,but implications of these measures on the full forest carbon balance remain to be studied.Insights from the future multi-scenarios are expected to provide data to support sustainable forest management and national policy development,which will inform the achievement of carbon neutrality goals by 2060.

Study on Soil Properties of Eucalyptus Plantation inHainan

Taking Hainan Eucalyptus plantation as the research object with 4 other kinds of plantations or natural forest as reference plots, the effects of different forest land types on soil nutrient contents were analyzed, and the differences of soil properties were discussed. The results showed that: (1) Eucalyptus plantations were relatively helpful to reduce soil bulk density and enhance the stability of water-stable aggregates;(2) Eucalyptus plantations can improve the content of soil organic matter;(3) Soil pH showed an overall acidi fication trend under forest land conditions in Hainan;total nitrogen and alkali-hydrolyzed nitrogen content of Eucalyptus plantations showed a downward trend with the deepening of soil layer;total phosphorus and available phosphorus content showed a downward trend, while organic matter, total potassium and available K showed an upward trend. (4) The contents of total phosphorus and available phosphorus in the soil of Eucalyptus plantations of different ages did not change significantly, whereas the contents of other nutrients decreased gradually with the increase of soil depth.

Biomass and Nutrient Accumulation Characteristics of Young Stands of Alnus cremastogyne

To investigate plant biomass and nutrient distribution and accumulation in organs of Alnus cremastogyne at different ages from 1 to 4 years, the biomass, N, P, K, Ca, Mg, Fe and Zn were tested. The results showed that the average biomass of the whole tree and the biomass of leaf, branch, stem, and root were in positive correlation with tree age, but the growth rate of biomass had a decreasing trend with the tree age increasing, and only the biomass proportion of the trunk in the whole individual plant showed an increasing trend with age. The contents of nutrient elements in organs showed an order of N 〉 Ca 〉 K 〉 Mg 〉 P 〉 Fe 〉 Zn ; and the contents of N, P and K were higher in the leaf than in other organs, and the contents of Ca, Mg and Fe in the root were higher than in other organs. The accumulations of N, P, K, Ca, Mg and Zn were the highest in the trunk, and that of Fe was the highest in the root. The annual net accumulations of N, P, K, Ca and Mg in the average trees from 1 to 4 years old were 17.07, 40.79, 95.82 and 106.71 g, respectively, and the annual net accumulations of microelements （Fe and Zn） were 335.04, 577.26, 1267 and 1525.27 mg, respectively.

Future biomass carbon sequestration capacity of Chinese forests

Chinese forests, characterized by relatively young stand age, represent a significant biomass carbon （C） sink over the past several decades. Nevertheless, it is unclear how forest biomass C sequestration capacity in China will evolve as forest age, climate and atmospheric CO2 concentration change continuously. Here, we present a semi-empirical model that incorporates forest age and climatic factors for each lbrest type to estimate the effects of forest age and climate change on total forest biomass, under three different sce-narios based on the fifth phase of the Coupled Model Intercomparison Project （CMIPS）. We estimate that age-related forest biomass C sequestration to be 6.69 Pg C （~0.17 Pg C a^-1） from the 2000s to the 2040s. Climate change induces a rather weak increase in total forest biomass C sequestration （0.52-0.60 Pg C by tile 2040s）. We show that rising CO2 concentrations could further increase tile total forest biomass C sequestration by 1.68-3.12 Pg C in the 2040s across all three scenarios. Overall, the total forest biomass in China would increase by 8.89-10.37 Pg C by the end of 2040s. Our findings highlight the benefits of Chinese afforestation programs, continued climate change and increasing CO2. concentration in sustaining the forest biomass C sink in the near future, and could therefore be useful for designing more realistic climate change mitigation policies such as continuous forestation programs and careful choice of tree species.

Variations of root and heterotrophic respiration along environmental gradients in China’s forests

Aims Root and heterotrophic respiration may respond differently to environmental variability,but little evidence is available from largescale observations.Here we aimed to examine variations of root and heterotrophic respiration across broad geographic,climatic,soil and biotic gradients.Methods We conducted a synthesis of 59 field measurements on root and heterotrophic respiration across China’s forests.Important Findings Root and heterotrophic respiration varied differently with forest types,of which evergreen broadleaf forest was significantly different from those in other forest types on heterotrophic respiration but without statistically significant differences on root respiration.The results also indicated that root and heterotrophic respiration exhibited similar trends along gradients of precipitation,soil organic carbon and satellite-indicated vegetation growth.However,they exhibited different relationships with temperature:root respiration exhibited bimodal patterns along the temperature gradient,while heterotrophic respiration increased monotonically with temperature.Moreover,they showed different relationships with MOD17 GPP,with increasing trend observed for root respiration whereas insignificant change for heterotrophic respiration.In addition,root and heterotrophic respiration exhibited different changes along the age sequence,with insignificant change for root respiration and decreasing trend for heterotrophic respiration.Overall,these results suggest that root and heterotrophic respiration may respond differently to environmental variability.Our findings could advance our understanding on the different environmental controls of root and heterotrophic respiration and also improve our ability to predict soil CO_(2) flux under a changing environment.

Impact of land use conversion on soil organic carbon stocks in an agro-pastoral ecotone of Inner Mongolia

Soil organic carbon （SOC） stocks in terrestrial ecosystems vary considerably with land use types. Grassland, forest, and cropland coexist in the agro-pastoral ecotone of Inner Mongolia, China. Using SOC data compiled from literature and field investigations, this study compared SOC stocks and their vertical distributions among three types of ecosystems. The results indicate that grassland had the Largest SOC stock, which was 1.5- and 1.8-folds more than stocks in forest and cropland, respectively. Relative to the stock in 0-100 cm depth, grassland held more than 40% of its SOC stock in the upper 20 cm soil layer; forest and cropland both held over 30% of their respective SOC stocks in the upper 20 cm soil layer. SOC stocks in grazed grasslands were remarkably promoted after -〉20 years of grazing ex- clusion. Conservational cultivation substantially increased the SOC stocks in cropland, espe- cially in the 0-40 cm depth. Stand ages, tree species, and forest types did not have obvious impacts on forest SOC stocks in the study area likely due to the younger stand ages. Our study implies that soil carbon loss should be taken into account during the implementation of ecological projects, such as reclamation and afforestation, in the arid and semi-arid regions of China.

Recovery of Collembola in Pinus tabulaeformis Plantations

Large areas of forest plantations have been developed in China. It is important to evaluate the soil fauna in plantations and the conditions needed for their recovery in view of the large areas of plantations in China. Three Pinus tabulaeformis forests, a 26-year-old plantation （P26） and a 45-year-old plantation （P45）, exposed to clear-cutting before plantation, and an 80 260-year-old natural forest （N260）, were chosen to study the effects of different forest ages/types on Collembola community in the lifter and soil layers during 2008 and 2009. Soil conditions in P26 and P45 were significantly deteriorated when compared to N260. A higher value of soil bulk density and lower values of soil organic matter, soil N, litter depth, soil pH, and soil water content were observed in P26 and P45. Totally, the same genera of Collembola tended to occur in the forests of all ages studied; however, the Collembola community structure was significantly impacted by the differences in forest age. Both in the litter and soil layers, the density and generic richness of the Collembola were the highest in N260 and the lowest in P26. Some collembolan groups were sensitive to soil conditions in particular forest ages. N260 was associated with relatively high abundance of Plutomus collembolans and P45 with relatively high abundance of Pseudofolsomia collembolans. The canonical correspondence analysis showed that the community structure of Collembola was mainly affected by forest age in both litter and soil layer. The ordination analysis of non-metric multidimensional scaling also found that the Collembola community did not recover to the level of natural forests in 26-year regeneration after clear-cutting. Even in 45-year regeneration after clear-cutting, the Collembola community only showed a slight recovery to the level of natural forests. Our results clearly showed that both Collembola community and soil conditions did not recover in 26- and 45-year regeneration after clear-cutting in P. tabulaeforrnis plantations; however, they might have the potential to recover in the future because the same genera of Collembola were distributed in the plantations and natural forests.

Modeling Long-term Forest Carbon Spatiotemporal Dynamics With Historical Climate and Recent Remote Sensing Data

Forests have long life cycles of up to several hundred years and longer.They also have very different growth rates at different stages of their life cycles.Therefore the carbon cycle in forest ecosystems has long time scales,making it necessary to consider forest age in estimating the spatiotemporal dynamics of carbon sinks in forests.The focus of this article is to review methods for combining recent remote sensing data with historical climate data for estimating the forest carbon source and sink distribution.Satellite remote sensing provides useful data for the land surface in recent decades. The information derived from remote sensing data can be used for short-term forest growth estimation and for mapping forest stand age for longterm simulations.For short-term forest growth estimation, remote sensing can provide forest structural parameters as inputs to process-based models,including big-leaf,two-leaf,and multi-layered models. These models use different strategies to upscale from leaf to canopy,and their reliability and suitability for remote sensing applications will be examined here.For long-term forest carbon cycle estimation, the spatial distribution of the forest growth rate（net primary productivity,NPP） modeled using remote sensing data in recent years is a critical input.This input can be combined with a forest age map to simulate the historical variation of NPP under the influence of climate and atmospheric changes. Another important component of the forest carbon cycle is heterotrophic respiration in the soil,which depends on the sizes of soil carbon pools as well as climate conditions.Methods for estimating the soil carbon spatial distribution and its separation into pools are described.The emphasis is placed on how to derive the soil carbon pools from NPP estimation in current years with consideration of forest carbon dynamics associated with stand age variation and climate and atmospheric changes.The role of disturbance in the forest carbon cycle and the effects of forest regrowth after disturbance are also considered in this review.An example of national forest carbon budget estimation in Canada is given at the end.It illustrates the importance of forest stand age structure in estimating the national forest carbon budgets and the effects of climate and atmospheric changes on the forest carbon cycle.