Terrestrial fluxes of carbon in GCP carbon budgets

Increasing forest carbon sinks in cold and arid northeastern Tibetan Plateau

Arid forest lands account for 6 % of the world's forest area, but their carbon density and carbon storage capacity have rarely been assessed. Forest inventories provide estimates of forest stock and biomass carbon density, improve our understanding of the carbon cycle, and help us develop sustainable forest management policies in the face of climate change. Here, we carried out three forest inventories at five-year intervals from 2006 to 2016 in 104 permanent sample plots covering the Qinghai spruce (Picea crassifolia) distribution in the north slope of Qilian Mountains, northeastern Tibetan Plateau. Results shows that mean biomasses for Qinghai spruce were 133.80, 144.89, and 157.01 Mg ha-1 while biomass carbon densities were 65.52, 70.92, and 76.88 Mg C ha-1, in 2006, 2011, and 2016, respectively. This shows an increase in the Qinghai spruce carbon density of 17.34 % from 2006 to 2016. Both the precipitation and temperature play crucial roles on the increase of aboveground carbon density. The average carbon densities were different among forests with different ages and were higher for older forests. Our results show that the carbon sequestration rate for Qinghai spruce in the Qilian Mountains is significantly higher than the average rates of national forest parks in China, suggesting that this spruce forest has the potential to sequester a significant amount of carbon despite the general harsh growing conditions of cold and arid ecoregions. Our findings provide important insights that are helpful for the assessment of forest carbon for cold and arid lands.

Contribution of land use and cover change (LUCC) to the global terrestrial carbon uptake

Terrestrial carbon uptake is critical to the removal of greenhouse gases and mitigation of global warming, which are closely related to land use and cover change (LUCC). However, understanding terrestrial carbon uptake and the LUCC contribution remains unclear because of complex interactions with other drivers (particularly climate change). By proposing an innovative approach of "trajectory analysis", this study aimed to isolate the LUCC contribution to terrestrial carbon uptake over different scales. Methodologically, global land was first divided into sub-regions of land transformations and stable land trajectories. Then, the carbon uptake change in the stable land trajectory was taken as a synthetic influence of climate change, which was used as a reference to isolate the carbon uptake alternation generated from the LUCC contribution in the land transformation trajectories. Finally, future LUCC and the terrestrial carbon uptake response were predicted under different development pathways. The results showed the global mean net ecosystem production (NEP) was 27.44 ± 36.51 g C m-2 yr-1 in the past two decades (2001-2019), generating 3.15 ± 0.88 Pg C yr-1 of the total terrestrial carbon uptake. Both the NEP and total carbon uptake showed significant increasing trends. Specifically, the mean NEP increased from 17.96 g C m-2 yr-1 in 2001 to 37.37 g C m-2 yr-1 in 2019, with the trend written as y = 1.20× + 15.20 (R2 = 0.62, p < 0.01). Meanwhile, the total carbon uptake increased from 2.35 Pg C yr-1 in 2001 to 4.13 Pg C yr-1 in 2019, which could be written as y = 0.12× + 1.93 (R2 = 0.56, p < 0.01). Climate change acted as the dominant factor for the trends at the global scale, which contributed 21.26 g C m-2 yr-1 and 1.59 Pg C yr-1 of the mean NEP and total carbon uptake changes in the stable land trajectories (94.30 million km2 that covered 63.29 % of the global land area), and the historical LUCC contributed -6.30 g C m-2 yr-1 (-40.85 %) and - 0.046 Pg C yr-1 (-57.50 %) of the mean NEP and the total carbon uptake change in the land transformation trajectories (6.64 million km2 that covered 4.46 % of the global land area), respectively. The maximum LUCC contribution (-61.85 g C m-2 yr-1) to the mean NEP occurred in the land transformations from evergreen needleleaf forests to woody savannas, while the maximum contribution (-0.034 Pg C y-1) to total carbon uptake was in the deforested regions from evergreen broadleaf forests to woody savannas. Eight SSP-RCP scenarios predictions demonstrated that future terrestrial carbon uptake would increase by an average of 0.015 Pg C yr-1 in 2100 due to global afforestation. SSP4-3.4 and SSP5-3.4 had the greatest potential for increasing carbon uptake, which is expected to reach a maximum increase (0.045 Pg C yr-1) in 2100. In contrast, the minimum terrestrial carbon uptake would occur in SSP5-8.5, which had the highest CO2 emissions. In conclusion, although relatively limited at the global scale, LUCC (particularly forest change) exerted an unneglectable role on terrestrial carbon uptake in land transformation regions. The results of this study will help to clarify terrestrial carbon uptake dynamics and provide a basis for carbon neutral and climatic adaptation.

Mind the gap: reconciling tropical forest carbon flux estimates from earth observation and national reporting requires transparency

BACKGROUND

The application of different approaches calculating the anthropogenic carbon net flux from land, leads to estimates that vary considerably. One reason for these variations is the extent to which approaches consider forest land to be "managed" by humans, and thus contributing to the net anthropogenic flux. Global Earth Observation (EO) datasets characterising spatio-temporal changes in land cover and carbon stocks provide an independent and consistent approach to estimate forest carbon fluxes. These can be compared against results reported in National Greenhouse Gas Inventories (NGHGIs) to support accurate and timely measuring, reporting and verification (MRV). Using Brazil as a primary case study, with additional analysis in Indonesia and Malaysia, we compare a Global EO-based dataset of forest carbon fluxes to results reported in NGHGIs.

RESULTS

Between 2001 and 2020, the EO-derived estimates of all forest-related emissions and removals indicate that Brazil was a net sink of carbon (- 0.2 GtCO2yr-1), while Brazil's NGHGI reported a net carbon source (+ 0.8 GtCO2yr-1). After adjusting the EO estimate to use the Brazilian NGHGI definition of managed forest and other assumptions used in the inventory's methodology, the EO net flux became a source of + 0.6 GtCO2yr-1, comparable to the NGHGI. Remaining discrepancies are due largely to differing carbon removal factors and forest types applied in the two datasets. In Indonesia, the EO and NGHGI net flux estimates were similar (+ 0.6 GtCO2 yr-1), but in Malaysia, they differed in both magnitude and sign (NGHGI: -0.2 GtCO2 yr-1; Global EO: + 0.2 GtCO2 yr-1). Spatially explicit datasets on forest types were not publicly available for analysis from either NGHGI, limiting the possibility of detailed adjustments.

CONCLUSIONS

By adjusting the EO dataset to improve comparability with carbon fluxes estimated for managed forests in the Brazilian NGHGI, initially diverging estimates were largely reconciled and remaining differences can be explained. Despite limited spatial data available for Indonesia and Malaysia, our comparison indicated specific aspects where differing approaches may explain divergence, including uncertainties and inaccuracies. Our study highlights the importance of enhanced transparency, as set out by the Paris Agreement, to enable alignment between different approaches for independent measuring and verification.

Multi-scenario simulation of carbon budget balance in arid and semi-arid regions

The carbon budget has emerged as a central focus in global carbon cycle research. The limited understanding of carbon budget balance dynamics has led to an increasing imbalance between ecological and socio-economic benefits. Building upon a comprehensive analysis of carbon storage and emission in Lanzhou from 2000 to 2020, this study develops a novel deep learning model (CNN-LSTM) to simulate carbon budget under various scenarios from 2030 to 2050. Additionally, scientifically grounded recommendations for carbon compensation are provided. The results demonstrate several key findings: (1) The deep learning model exhibits outstanding performance, with an average overall accuracy exceeding 0.93. The coupled model outperforms individual models, underscoring the significance and necessity of incorporating both temporal and spatial features in land use simulation. (2) Under the ecological protection redline scenario from 2030 to 2050, a noteworthy augmentation in carbon storage and a proficient constraint on carbon emissions are observed. This substantiates the effectiveness of ecological protection interventions. (3) Carbon compensation payment areas are predominantly concentrated in built-up land, with the extent of these areas expanding over time. (4) The disparities in carbon balance effects of forest were more conspicuous than that of built-up land across diverse temporal and scenarios.

Spatial heterogeneity of global forest aboveground carbon stocks and fluxes constrained by spaceborne lidar data and mechanistic modeling

Forest carbon is a large and uncertain component of the global carbon cycle. An important source of complexity is the spatial heterogeneity of vegetation vertical structure and extent, which results from variations in climate, soils, and disturbances and influences both contemporary carbon stocks and fluxes. Recent advances in remote sensing and ecosystem modeling have the potential to significantly improve the characterization of vegetation structure and its resulting influence on carbon. Here, we used novel remote sensing observations of tree canopy height collected by two NASA spaceborne lidar missions, Global Ecosystem Dynamics Investigation and ICE, Cloud, and Land Elevation Satellite 2, together with a newly developed global Ecosystem Demography model (v3.0) to characterize the spatial heterogeneity of global forest structure and quantify the corresponding implications for forest carbon stocks and fluxes. Multiple-scale evaluations suggested favorable results relative to other estimates including field inventory, remote sensing-based products, and national statistics. However, this approach utilized several orders of magnitude more data (3.77 billion lidar samples) on vegetation structure than used previously and enabled a qualitative increase in the spatial resolution of model estimates achievable (0.25° to 0.01°). At this resolution, process-based models are now able to capture detailed spatial patterns of forest structure previously unattainable, including patterns of natural and anthropogenic disturbance and recovery. Through the novel integration of new remote sensing data and ecosystem modeling, this study bridges the gap between existing empirically based remote sensing approaches and process-based modeling approaches. This study more generally demonstrates the promising value of spaceborne lidar observations for advancing carbon modeling at a global scale.

Spatiotemporal Patterns and Drivers of the Carbon Budget in the Yangtze River Delta Region, China

Improving our understanding of the patterns and drivers of regional carbon budgets is critical to mitigating climate change regionally and globally. Different from previous research, our study attempts to reveal the comprehensive impact of climate change and human activities factors on the carbon budget. Based on the Carnegie–Ames–Stanford approach (CASA) model, the IPCC inventory method, the ordinary least squares (OLS) regression model, the Geodetector model, and the geographically weighted regression (GWR) method, we investigated the spatiotemporal patterns of the carbon budget in the Yangtze River Delta (YRD) region from 2000 to 2015 and analyzed the effects of climate change and human activities on the carbon budget. The results showed that the carbon budget in the YRD region changed from 271.33 million tons in 2000 to −1193.76 million tons in 2015. During this period, the changes in the carbon budget per unit area in the four provinces all showed a decreasing trend, among which Shanghai decreased the most, followed by Jiangsu, Zhejiang and Anhui. In terms of spatial pattern, the carbon budget of the YRD region has a “core-edge” structural feature. The closer it is to Shanghai, the core area, the more severe the carbon budget deficit; the farther from it, the greater the carbon budget surplus. Overall, we found that human activities have a greater impact on the carbon budget than climate change. The top three drivers were, in order, changes in population density, GDP per capita, and unused land, with q values of 0.3317, 0.1202, and 0.0998, respectively. Locally, the impact of the drivers on the carbon budget shows obvious spatial heterogeneity. In particular, the population density was negatively correlated with carbon budget changes in the entire study area, and the coefficients of GDP per capita and unused land were negative in most counties. Based on the results, we put forward suggestions for restricting population flow among the core area and the peripheral area, promoting industrial innovation in the core area and ecological protection in the peripheral area, as well as implementing three-dimensional space development in the core area and controlling the expansion of construction land in the peripheral area. Our study can provide a scientific basis for low-carbon development in the YRD region. The methodology and findings of this study can provide references for similar studies in other urbanized regions around the world.

Changes in global terrestrial live biomass over the 21st century

Live woody vegetation is the largest reservoir of biomass carbon, with its restoration considered one of the most effective natural climate solutions. However, terrestrial carbon fluxes remain the largest uncertainty in the global carbon cycle. Here, we develop spatially explicit estimates of carbon stock changes of live woody biomass from 2000 to 2019 using measurements from ground, air, and space. We show that live biomass has removed 4.9 to 5.5 PgC year^-1 from the atmosphere, offsetting 4.6 ± 0.1 PgC year^-1 of gross emissions from disturbances and adding substantially (0.23 to 0.88 PgC year^-1) to the global carbon stocks. Gross emissions and removals in the tropics were four times larger than temperate and boreal ecosystems combined. Although live biomass is responsible for more than 80% of gross terrestrial fluxes, soil, dead organic matter, and lateral transport may play important roles in terrestrial carbon sink.

Quantifying and attributing land use-induced carbon emissions to biomass consumption: A critical assessment of existing approaches

Biomass production generates land use impacts in the form of emissions from Forestry and Other Land Use (FOLU), i.e. due to changes in ecosystem carbon stocks. Recently, consumption-based accounting (CBA) approaches have emerged as alternatives to conventional production-based accounts, quantifying FOLU emissions associated with biomass consumption, for example, of particular territories. However, the quantification and allocation of FOLU emissions to individual biomass products, a fundamental part of CBA approaches, is a complex endeavour. Existing studies make diverging methodological choices, which are rarely critically discussed. In this study, we provide a structured overview of existing CBA approaches to estimating FOLU emissions. We cluster the literature in a two-by-two grid, distinguishing the primary element under investigation (impacts of changing consumption patterns in a region vs. impacts of consumption on production landscapes) and the analytical lens (prospective vs retrospective). Further, we identify three distinct dimensions which characterise the way in which different studies allocate FOLU emissions to biomass products: the choice of reference system and the spatial and temporal scales. Finally, we identify three frontiers that require future attention: (1) overcoming structural biases which underestimate FOLU emissions from territories that experienced deforestation in the distant past, (2) explicitly tackling the interdependence of proximate causes and ultimate drivers of land use change, and (3) assessing uncertainties and understanding the effects of land management. In this way, we enable a critical assessment of appropriate methods, support a nuanced interpretation of results from particular approaches as well as enhance the informative value of CBA approaches related to FOLU emissions. Our analysis contributes to discussions on sustainable land use practices with respect to biomass consumption and has implications for informing international climate policy in scenarios where consumption-based approaches are adopted in practice.

Carbon benefits from Forest Transitions promoting biomass expansions and thickening

The growth of the global terrestrial sink of carbon dioxide has puzzled scientists for decades. We propose that the role of land management practices-from intensive forestry to allowing passive afforestation of abandoned lands-have played a major role in the growth of the terrestrial carbon sink in the decades since the mid twentieth century. The Forest Transition, a historic transition from shrinking to expanding forests, and from sparser to denser forests, has seen an increase of biomass and carbon across large regions of the globe. We propose that the contribution of Forest Transitions to the terrestrial carbon sink has been underestimated. Because forest growth is slow and incremental, changes in the carbon density in forest biomass and soils often elude detection. Measurement technologies that rely on changes in two-dimensional ground cover can miss changes in forest density. In contrast, changes from abrupt and total losses of biomass in land clearing, forest fires and clear cuts are easy to measure. Land management improves over time providing important present contributions and future potential to climate change mitigation. Appreciating the contributions of Forest Transitions to the sequestering of atmospheric carbon will enable its potential to aid in climate change mitigation.

Safeguarding our future by protecting biodiversity

The Anthropocene is marked by twin crises: climate change and biodiversity loss. Climate change has tended to dominate the headlines, reflecting, in part, the greater complexity of the biodiversity crisis. Biodiversity itself is a difficult concept. Land plants dominate the global biomass and terrestrial arthropods probably dominate in terms of numbers of species, but most of the Tree of Life consists of single-celled eukaryotes, bacteria, and archaea. Wild plants provide a huge variety of products and services to people, ranging from those that are species-specific, such as food, medicine, and genetic resources, to many which are partly interchangeable, such as timber and forage for domestic animals, and others which depend on the whole community, but not on individual species, such as regulation of water supply and carbon sequestration. The use of information from remote sensing has encouraged a simplified view of the values of nature's contributions to people, but this does not match the way most people value nature. We can currently estimate the proportion of species threatened by human impacts only for a few well-assessed groups, for which it ranges from 14% (birds) to 63% (cycads). Less than 8% of land plants have been assessed, but it has been estimated that 30-44% are threatened, although there are still few (0.2%) well-documented extinctions. Priorities for improving protection of biodiversity include: improving the inventory, with surveys focused on geographical areas and taxonomic groups which are under-collected; expanding the protected area system and its representativeness; controlling overexploitation; managing invasive species; conserving threatened species ex situ; restoring degraded ecosystems; and controlling climate change. The Convention on Biological Diversity (CBD) COP15 and the United Nations Framework Convention on Climate Change (UNFCCC) COP26 meetings, both postponed to 2021, will provide an opportunity to address both crises, but success will require high ambition from all participants.