A regional forest ecosystem carbon budget model: impacts of forest age structure and landuse history

Mapping of secondary forest age in China using stacked generalization and Landsat time series

A national distribution of secondary forest age (SFA) is essential for understanding the forest ecosystem and carbon stock in China. While past studies have mainly used various change detection algorithms to detect forest disturbance, which cannot adequately characterize the entire forest landscape. This study developed a data-driven approach for improving performances of the Vegetation Change Tracker (VCT) and Continuous Change Detection and Classification (CCDC) algorithms for detecting the establishment of forest stands. An ensemble method for mapping national-scale SFA by determining the establishment time of secondary forest stands using change detection algorithms and dense Landsat time series was proposed. A dataset of national secondary forest age for China (SFAC) for 1 to 34 and with a 30-m spatial resolution was produced from the optimal ensemble model. This dataset provides national, continuous spatial SFA information and can improve understanding of secondary forests and the estimation of forest carbon storage in China.

The Role of Wildfires in the Interplay of Forest Carbon Stocks and Wood Harvest in the Contiguous United States During the 20th Century

Wildfires and land use play a central role in the long-term carbon (C) dynamics of forested ecosystems of the United States. Understanding their linkages with changes in biomass, resource use, and consumption in the context of climate change mitigation is crucial. We reconstruct a long-term C balance of forests in the contiguous U.S. using historical reports, satellite data, and other sources at multiple scales (national scale 1926-2017, regional level 1941-2017) to disentangle the drivers of biomass C stock change. The balance includes removals of forest biomass by fire, by extraction of woody biomass, by forest grazing, and by biomass stock change, their sum representing the net ecosystem productivity (NEP). Nationally, the total forest NEP increased for most of the 20th century, while fire, harvest and grazing reduced total forest stocks on average by 14%, 51%, and 6%, respectively, resulting in a net increase in C stock density of nearly 40%. Recovery from past land-use, plus reductions in wildfires and forest grazing coincide with consistent forest regrowth in the eastern U.S. but associated C stock increases were offset by increased wood harvest. C stock changes across the western U.S. fluctuated, with fire, harvest, and other disturbances (e.g., insects, droughts) reducing stocks on average by 14%, 81%, and 7%, respectively, resulting in a net growth in C stock density of 14%. Although wildfire activities increased in recent decades, harvest was the key driver in the forest C balance in all regions for most of the observed timeframe.

Pinus tabulaeformis Forests Have Higher Carbon Sequestration Potential Than Larix principis-rupprechtii Forests in a Dryland Mountain Ecosystem, Northwest China

Carbon sinks in terrestrial ecosystems can be significantly increased by afforestation, which will slow global warming. However, it is still unclear how different plantations influence the carbon sink and how they respond to environmental factors, especially in drylands. In this study, eddy correlation method (EC) was used to measure carbon and water fluxes and environmental factors of two artificial forests (Larix principis-rupprechtii and Pinus tabulaeformis) in the dryland of Northwest China, and the responses of evapotranspiration (ET), net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RECO) to environmental factors were also assessed. Results showed that the L. principis-rupprechtii forest ecosystem had higher water use efficiency (WUE), light use efficiency (LUE), GPP, and RECO than the P. tabulaeformis forest ecosystem. However, the proportion of net ecosystem production (NEP) to GPP in the P. tabulaeformis forest ecosystem (62.89%) was higher than that in the L. principis-rupprechtii forest ecosystem (47.49%), indicating that the P. tabulaeformis forest ecosystem had the higher carbon sequestration efficiency. In addition, the CO2 and H2O fluxes in the L. principis-rupprechtii forest ecosystem were more sensitive to environmental factors, compared with the P. tabulaeformis forest ecosystem. Further, the RECO of the L. principis-rupprechtii forest ecosystem was more sensitive to temperature changes, which implies that the L. principis-rupprechtii forest ecosystem will release more CO2 than the P. tabulaeformis forest ecosystem with a warming climate. Therefore, the P. tabulaeformis forest ecosystem may have better carbon sequestration potential. These results are important for understanding the effects of climate change on the CO2 and H2O cycles in coniferous plantation ecosystems in drylands.

Forest Canopy Height and Gaps from Multiangular BRDF, Assessed with Airborne LiDAR Data

Both vegetation multi-angular and LiDAR (light detection and ranging) remote sensing data are indirectly and directly linked with 3D vegetation structure parameters, such as the tree height and vegetation gap fraction, which are critical elements in above-ground biomass and light profiles for photosynthesis estimation. LiDAR, particularly LiDAR using waveform data, provides accurate estimates of these structural parameters but suffers from not enough spatial samplings. Structural parameters retrieved from multiangular imaging data through the inversion of physical models have larger uncertainties. This study searches for an analytical approach to fuse LiDAR and multiangular data. We explore the relationships between vegetation structure parameters derived from airborne vegetation LiDAR data and multiangular data and present a new potential angle vegetation index to retrieve the tree height and gap fraction using multi-angular data in Howland Forest, Maine. The BRDF (bidirectional reflectance distribution factor) index named NDMM (normalized difference between the maximum and minimum reflectance) linearly increases with the tree height and decreases with the gap fraction. In addition, these relationships are also dependent on the wavelength, tree species, and stand density. The NDMM index performs better in conifer (R = 0.451 for tree height and R = 0.472 for the gap fraction using the near infrared band) than in deciduous and mixed forests. It is superior in sparse (R = 0.569 for tree height and R = 0.604 for the gap fraction using the near infrared band) compared to dense forest. Moreover, the NDMM index is more strongly related to tree height and the gap fraction at the near infrared band than at the three visible bands. This study sheds light on the possibility of using multiangular data to map vegetation’s structural parameters in larger regions for carbon cycle studies through the fusion of LiDAR and multiangular remote sensing data.

Age alters uptake pattern of organic and inorganic nitrogen by rubber trees

Several studies have explored plant nutrient acquisition during ecosystem succession, but it remains unclear how age affects nitrogen (N) acquisition by the same tree species. Clarifying the age effect will be beneficial to fertilization management through improving N-use efficiency and reducing the risk of environmental pollution due to NO3- leaching. To clarify the effect of age on N uptake, rubber (Hevea brasiliensis (Willd. ex A. Juss.) Muell. Arg.) plantations of five ages (7, 16, 24, 32 and 49 years) were selected in Xishuangbanna of southern China for brief 15N exposures of intact roots using field hydroponic experiments. 15N-labeled NH4+, NO3- or glycine were applied in this study. All targeted rubber trees uptake rates followed an order of NH4+ > glycine > NO3-. As age increased, NH4+ uptake increased first and then decreased sharply, partly consistent with the pattern of soil NH4+ concentrations. Uptake of glycine decreased first and then increased gradually, while no significant change of NO3- uptake rates existed with increasing age. Overall, rubber trees with ages from 7 to 49 years all showed a preference for NH4+ uptake. Young rubber trees (7 and 16 years) had higher NH4+ and lower glycine preferences than older trees (24, 32 and 49 years). Mycorrhizal colonization rates of rubber trees were higher in intermediately aged plantations (16, 24 and 32 years) than in plantations aged 7 and 49 years. A positive relationship was observed between arbuscular mycorrhizal colonization rates and NO3- preference. The results from this study demonstrate that rubber trees do not change their preference for NH4+ but strongly decreased their reliance on it with age. These findings indicate that the shift of N uptake patterns with age should be taken into account for rubber fertilization management to improve N-use efficiency and reduce the risk of environmental pollution during rubber production.

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 forest type to estimate the effects of forest age and climate change on total forest biomass, under three different scenarios based on the fifth phase of the Coupled Model Intercomparison Project (CMIP5). 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 the 2040s). We show that rising CO₂ concentrations could further increase the 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.

Evaluating carbon fluxes of global forest ecosystems by using an individual tree-based model FORCCHN

The carbon budget of forest ecosystems, an important component of the terrestrial carbon cycle, needs to be accurately quantified and predicted by ecological models. As a preamble to apply the model to estimate global carbon uptake by forest ecosystems, we used the CO₂ flux measurements from 37 forest eddy-covariance sites to examine the individual tree-based FORCCHN model's performance globally. In these initial tests, the FORCCHN model simulated gross primary production (GPP), ecosystem respiration (ER) and net ecosystem production (NEP) with correlations of 0.72, 0.70 and 0.53, respectively, across all forest biomes. The model underestimated GPP and slightly overestimated ER across most of the eddy-covariance sites. An underestimation of NEP arose primarily from the lower GPP estimates. Model performance was better in capturing both the temporal changes and magnitude of carbon fluxes in deciduous broadleaf forest than in evergreen broadleaf forest, and it performed less well for sites in Mediterranean climate. We then applied the model to estimate the carbon fluxes of forest ecosystems on global scale over 1982-2011. This application of FORCCHN gave a total GPP of 59.41±5.67 and an ER of 57.21±5.32PgCyr^-1 for global forest ecosystems during 1982-2011. The forest ecosystems over this same period contributed a large carbon storage, with total NEP being 2.20±0.64PgCyr^-1. These values are comparable to and reinforce estimates reported in other studies. This analysis highlights individual tree-based model FORCCHN could be used to evaluate carbon fluxes of forest ecosystems on global scale.

Effects of rapid urban sprawl on urban forest carbon stocks: integrating remotely sensed, GIS and forest inventory data

Research on the effects of urban sprawl on carbon stocks within urban forests can help support policy for sustainable urban design. This is particularly important given climate change and environmental deterioration as a result of rapid urbanization. The purpose of this study was to quantify the effects of urban sprawl on dynamics of forest carbon stock and density in Xiamen, a typical city experiencing rapid urbanization in China. Forest resource inventory data collected from 32,898 patches in 4 years (1972, 1988, 1996 and 2006), together with remotely sensed data (from 1988, 1996 and 2006), were used to investigate vegetation carbon densities and stocks in Xiamen, China. We classified the forests into four groups: (1) forest patches connected to construction land; (2) forest patches connected to farmland; (3) forest patches connected to both construction land and farmland and (4) close forest patches. Carbon stocks and densities of four different types of forest patches during different urbanization periods in three zones (urban core, suburb and exurb) were compared to assess the impact of human disturbance on forest carbon. In the urban core, the carbon stock and carbon density in all four forest patch types declined over the study period. In the suburbs, different urbanization processes influenced forest carbon density and carbon stock in all four forest patch types. Urban sprawl negatively affected the surrounding forests. In the exurbs, the carbon stock and carbon density in all four forest patch types tended to increase over the study period. The results revealed that human disturbance played the dominant role in influencing the carbon stock and density of forest patches close to the locations of human activities. In forest patches far away from the locations of human activities, natural forest regrowth was the dominant factor affecting carbon stock and density.

Evaluating spatial-temporal dynamics of net primary productivity of different forest types in northeastern China based on improved FORCCHN

An improved individual-based forest ecosystem carbon budget model for China (FORCCHN) was applied to investigate the spatial-temporal dynamics of net primary productivity of different forest types in northeastern China. In this study, the forests of northeastern China were categorized into four ecological types according to their habitats and generic characteristics (evergreen broadleaf forest, deciduous broadleaf forest, evergreen needleleaf forest and deciduous needleleaf forest). The results showed that distribution and change of forest NPP in northeastern China were related to the different forest types. From 1981 to 2002, among the forest types in northeastern China, per unit area NPP and total NPP of deciduous broadleaf forest were the highest, with the values of 729.4 gC/(m(2)•yr) and 106.0 TgC/yr, respectively, followed by mixed broadleaf- needleleaf forest, deciduous needleleaf forest and evergreen needleleaf forest. From 1981 to 2002, per unit area NPP and total NPP of different forest types in northeastern China exhibited significant trends of interannual increase, and rapid increase was found between the 1980s and 1990s. The contribution of the different forest type's NPP to total NPP in northeastern China was clearly different. The greatest was deciduous broadleaf forest, followed by mixed broadleaf- needleleaf forest and deciduous needleleaf forest. The smallest was evergreen needleleaf forest. Spatial difference in NPP between different forest types was remarkable. High NPP values of deciduous needleleaf forest, mixed broadleaf- needleleaf forest and deciduous broadleaf forest were found in the Daxing'anling region, the southeastern of Xiaoxing'anling and Jilin province, and the Changbai Mountain, respectively. However, no regional differences were found for evergreen needleleaf NPP. This study provided not only an estimation NPP of different forest types in northeastern China but also a useful methodology for estimating forest carbon storage at regional and global levels.

Relationships between net primary productivity and stand age for several forest types and their influence on China's carbon balance

Affected by natural and anthropogenic disturbances such as forest fires, insect-induced mortality and harvesting, forest stand age plays an important role in determining the distribution of carbon pools and fluxes in a variety of forest ecosystems. An improved understanding of the relationship between net primary productivity (NPP) and stand age (i.e., age-related increase and decline in forest productivity) is essential for the simulation and prediction of the global carbon cycle at annual, decadal, centurial, or even longer temporal scales. In this paper, we developed functions describing the relationship between national mean NPP and stand age using stand age information derived from forest inventory data and NPP simulated by the BEPS (Boreal Ecosystem Productivity Simulator) model in 2001. Due to differences in ecobiophysical characteristics of different forest types, NPP-age equations were developed for five typical forest ecosystems in China (deciduous needleleaf forest (DNF), evergreen needleleaf forest in tropic and subtropical zones (ENF-S), deciduous broadleaf forest (DBF), evergreen broadleaf forest (EBF), and mixed broadleaf forest (MBF)). For DNF, ENF-S, EBF, and MBF, changes in NPP with age were well fitted with a common non-linear function, with R(2) values equal to 0.90, 0.75, 0.66, and 0.67, respectively. In contrast, a second order polynomial was best suitable for simulating the change of NPP for DBF, with an R(2) value of 0.79. The timing and magnitude of the maximum NPP varied with forest types. DNF, EBF, and MBF reached the peak NPP at the age of 54, 40, and 32 years, respectively, while the NPP of ENF-S maximizes at the age of 13 years. The highest NPP of DBF appeared at 122 years. NPP was generally lower in older stands with the exception of DBF, and this particular finding runs counter to the paradigm of age-related decline in forest growth. Evaluation based on measurements of NPP and stand age at the plot-level demonstrates the reliability and applicability of the fitted NPP-age relationships. These relationships were used to replace the normalized NPP-age relationship used in the original InTEC (Integrated Terrestrial Ecosystem Carbon) model, to improve the accuracy of estimated carbon balance for China's forest ecosystems. With the revised NPP-age relationship, the InTEC model simulated a larger carbon source from 1950-1980 and a larger carbon sink from 1985-2001 for China's forests than the original InTEC model did because of the modification to the age-related carbon dynamics in forests. This finding confirms the importance of considering the dynamics of NPP related to forest age in estimating regional and global terrestrial carbon budgets.

Assessment of forest net primary production through the elaboration of multisource ground and remote sensing data

This paper builds on previous work by our research group which demonstrated the applicability of a parametric model, Modified C-Fix, for the monitoring of Mediterranean forests. Specifically, the model is capable of combining ground and remote sensing data to estimate forest gross primary production (GPP) on various spatial and temporal scales. Modified C-Fix is currently applied to all Italian forest areas using a previously produced data set of meteorological data and NDVI imagery descriptive of a ten-year period (1999-2008). The obtained GPP estimates are further elaborated to derive forest net primary production (NPP) averages for 20 Italian Regions. Such estimates, converted into current annual increment of standing volume (CAI) through the use of specific coefficients, are compared to the data of a recent national forest inventory (INFC). The results obtained indicate that the modelling approach tends to overestimate the ground CAI values for all forest types. The correction of a drawback in the current model implementation leads to reduce this overestimation to about 9% of the INFC increments. The possible origins of this overestimation are investigated by examining the results of previous studies and of older forest inventories. The implications of using different NPP estimation methods are finally discussed in view of assessing the forest carbon budget on a national basis.

Ecophysiological modelling of leaf level photosynthetic performance for three Mediterranean species with different growth forms

A leaf gross photosynthesis (A) model for three Mediterranean species from different functional groups (the evergreen sclerophyll Arbutus unedo L., the deciduous tree Quercus frainetto Ten. and the semi-deciduous shrub Phlomis fruticosa L.) has been developed through a 3-year seasonal study of gas exchange and plant ecophysiological parameters. The model estimates photosynthesis through four easily measured ecophysiological parameters (chlorophyll content, leaf mass per area (LMA), pre-dawn water potential, leaf temperature) and two meteorological parameters (PAR and average temperature of the 33-day period before measurement (T33)), with a coefficient of determination r2=0.88 (P<0.001). The enhanced accuracy of the presented model may be ascribed to the incorporation of (i) water potential effects on A and (ii) temperature effects on A not only in the short term, but also in the long term (acclimation). Water potential and temperature effects may be considered especially important for species of Mediterranean ecosystems, where strong seasonal variation of these parameters often have a major role in plant growth and survival.