Future Carbon Fluxes Research Articles

Tree ring segmentation using UNEt TRansformer neural network on stained microsections for quantitative wood anatomy.

Forests are critical in the terrestrial carbon cycle, and the knowledge of their response to ongoing climate change will be crucial for determining future carbon fluxes and climate trajectories. In areas with contrasting seasons, trees form discrete annual rings that can be assigned to calendar years, allowing to extract valuable information about how trees respond to the environment. The anatomical structure of wood provides highly-resolved information about the reaction and adaptation of trees to climate. Quantitative wood anatomy helps to retrieve this information by measuring wood at the cellular level using high-resolution images of wood micro-sections. However, whereas large advances have been made in identifying cellular structures, obtaining meaningful cellular information is still hampered by the correct annual tree ring delimitation on the images. This is a time-consuming task that requires experienced operators to manually delimit ring boundaries. Classic methods of automatic segmentation based on pixel values are being replaced by new approaches using neural networks which are capable of distinguishing structures, even when demarcations require a high level of expertise. Although neural networks have been used for tree ring segmentation on macroscopic images of wood, the complexity of cell patterns in stained microsections of broadleaved species requires adaptive models to accurately accomplish this task. We present an automatic tree ring boundary delineation using neural networks on stained cross-sectional microsection images from beech cores. We trained a UNETR, a combined neural network of UNET and the attention mechanisms of Visual Transformers, to automatically segment annual ring boundaries. Its accuracy was evaluated considering discrepancies with manual segmentation and the consequences of disparity for the goals of quantitative wood anatomy analyses. In most cases (91.8%), automatic segmentation matched or improved manual segmentation, and the rate of vessels assignment to annual rings was similar between the two categories, even when manual segmentation was considered better. The application of convolutional neural networks-based models outperforms human operator segmentations when confronting ring boundary delimitation using specific parameters for quantitative wood anatomy analysis. Current advances on segmentation models may reduce the cost of massive and accurate data collection for quantitative wood anatomy.

Forcing the Global Fire Emissions Database burned-area dataset into the Community Land Model version 5.0: impacts on carbon and water fluxes at high latitudes

Abstract. Wildfires influence not only ecosystems but also carbon and water fluxes on Earth. Yet, the fire processes including the occurrence and consequences of fires are still limitedly represented in land surface models (LSMs). In particular, the performance of LSMs in estimating burned areas across high northern latitudes is poor. In this study, we employed the daily burned areas from the satellite-based Global Fire Emissions Database (version 4) (GFED4) into the Community Land Model (version 5.0) with a biogeochemistry module (CLM5-BGC) to identify the effects of accurate fire simulation on carbon and water fluxes over Alaska and Eastern Siberia. The results showed that the simulated carbon emissions with burned areas from GFED4 (i.e., experimental run) were significantly improved in comparison to the default CLM5-BGC simulation, which resulted in opposite signs of the net ecosystem exchange for 2004, 2005, and 2009 over Alaska between the default and experimental runs. Also, we identified that carbon emissions were more sensitive to the wildfires in Alaska than in Eastern Siberia, which could be explained by the vegetation distribution (i.e., tree cover ratio). In terms of water fluxes, canopy transpiration in Eastern Siberia was relatively insensitive to the size of the burned area due to the interaction between leaf area and soil moisture. This study uses CLM5-BGC to improve our understanding of the role of burned areas in ecohydrological processes at high latitudes. Furthermore, we suggest that the improved approach will be required for better predicting future carbon fluxes and climate change.

Determining optimal forest rotation ages and carbon offset credits: Accounting for post‐harvest carbon storehouses

AbstractSequestering carbon in forest ecosystems is important for mitigating climate change. A major policy concern is whether forests should be left unharvested to avoid carbon dioxide (CO2) emissions and store carbon, or harvested to take advantage of potential carbon storage in post‐harvest wood product sinks and removal of CO2 from the atmosphere by new growth. The issue is addressed in this paper by examining carbon rotation ages that consider commercial timber as well as carbon values. A discrete‐time optimal rotation age model is developed that employs data on carbon fluxes stored in both living and dead biomass as opposed to carbon as a function of timber growth. Carbon is allocated to several ecosystem and post‐harvest product pools that decay over time at different rates. In addition, the timing of carbon fluxes is taken into account by weighting future carbon fluxes as less important than current ones. Using simple formulae for determining optimal rotation ages, we find that: (1) Reducing the price of timber while increasing the price of carbon will increase rotation age, perhaps to infinity (stand remains unharvested). (2) An increase in the rate used to discount physical carbon generally reduces the rotation age, but not in all cases. (3) As a corollary, an increase in the price of carbon increases or reduces rotation age depending on the weight chosen to discount future carbon fluxes. (4) Site characteristics and the mix of species on the site affect conclusions (2) and (3). (5) A large variety of carbon offset credits from forestry activities could be justified, which makes it difficult to accept any.

Impact of rubber-based land use changes on soil properties and carbon pools: A meta-analysis

The rapid expansion of rubber plantations may have greatly influenced the carbon stocks of the ecosystem, with potential impacts on mitigating climate change and future carbon fluxes. Therefore, soil carbon pools and other properties must be reliably estimated after rubber-based land cover transitions. The aim of this meta-analysis is to understand how various land use changes based on rubber plantations affect soil physicochemical properties, especially soil organic carbon (SOC) pools. This study focuses on three land use changes: (1) forest-to-rubber conversion; (2) rubber monoculture vs. intercropping; and (3) the age and altitude of the rubber stand over a chronosequence in rubber plots. Results showed that the conversion of forest to rubber plantation significantly reduced the SOC, microbial carbon (MBC), total nitrogen (TN) and total magnesium pools by 24%, 35%, 13% and 94% respectively, whereas rubber intercropping with different crops profoundly increased the SOC and MBC pools by 6% and 24% on average, respectively. The improvement of rubber intercropping on SOC and properties mainly occurred in the surface soil at 0–20 cm and at altitudes of 500–800 m, but these effects were diminished in the subsurface soil at 20–60 cm and at altitudes higher than 800 m. Rubber intercropping plantations can significantly alleviate soil acidification. Changes in the response ratio of SOC were closely related to the variations in soil clay, bulk density, and C/N ratio. These results suggest that rubber-based land use management policies should promote intercropping plantations, especially those with woody plants, and the altitude of rubber planting should be manipulated to minimize the loss of soil C, N, and other nutrients.

How the future of the global forest sink depends on timber demand, forest management, and carbon policies

Deforestation has contributed significantly to net greenhouse gas emissions, but slowing deforestation, regrowing forests and other ecosystem processes have made forests a net sink. Deforestation will still influence future carbon fluxes, but the role of forest growth through aging, management, and other silvicultural inputs on future carbon fluxes are critically important but not always recognized by bookkeeping and integrated assessment models. When projecting the future, it is vital to capture how management processes affect carbon storage in ecosystems and wood products.This study uses multiple global forest sector models to project forest carbon impacts across 81 shared socioeconomic (SSP) and climate mitigation pathway scenarios. We illustrate the importance of modeling management decisions in existing forests in response to changing demands for land resources, wood products and carbon. Although the models vary in key attributes, there is general agreement across a majority of scenarios that the global forest sector could remain a carbon sink in the future, sequestering 1.2–5.8 GtCO2e/yr over the next century. Carbon fluxes in the baseline scenarios that exclude climate mitigation policy ranged from −0.8 to 4.9 GtCO2e/yr, highlighting the strong influence of SSPs on forest sector model estimates. Improved forest management can jointly increase carbon stocks and harvests without expanding forest area, suggesting that carbon fluxes from managed forests systems deserve more careful consideration by the climate policy community.

Dynamics and fluxes of dissolved carbon under short-term climate variabilities in headwaters of the Changjiang River, draining the Qinghai-Tibet Plateau

Carbon-climate feedback is sensitive in the Qinghai-Tibet Plateau. A series of temporal measurements from Jinsha River and Yalong River, in conjunction with flow information, were used to study the carbon dynamics and predict future carbon fluxes under ongoing climate change. DIC and DOC concentrations showed considerable temporal variations, with low DIC and high DOC concentrations in the high-flow season, and vice versa. DIC and DOC concentrations had negative and positive relationships with runoff changes, respectively, showing the hydro-biogeochemical controls on carbon dynamics. With the increase of runoff, the accelerated chemical weathering and the high carbonate buffering capacity should be responsible for the chemostatic behaviors of DIC. Meanwhile, warm weather would enhance organic carbon degradation, and also thicken the active layer of permafrost in the source area, both of which would produce DOC. In addition, organic carbon degradation in the high-flow season would produce DIC with 13C-depleted values. δ13CDIC also had significant temporal variations, synchronous with runoff changes (i.e., light values under high runoff conditions), supporting that biological carbon plays an important role in carbon dynamics during the warm season. Based on the clear positive correlations between carbon fluxes and runoff, we predicted that the sensitivities of DOC fluxes to temperature changes are 12.2%/°C and 8.3%/°C for the Jinsha River and Yalong River, respectively. The sensitivities of DIC fluxes to temperature changes are much lower, which are 5.5%/°C and 6.1%/°C for the Jinsha River and Yalong River, respectively. This study sheds lights on the alpine riverine carbon cycling based on runoff-shifting concentration-isotope (q-C-I) relationships in the Qinghai-Tibet Plateau, which has implications on the understanding of climate forcing on carbon fluxes in alpine areas.

Implications of different nitrogen input sources for potential production and carbon flux estimates in the coastal Gulf of Mexico (GOM) and Korean Peninsula coastal waters

Abstract. The coastal Gulf of Mexico (GOM) and coastal sea off the Korean Peninsula (CSK) both suffer from human-induced eutrophication. We used a nitrogen (N) mass balance model in two different regions with different nitrogen input sources to estimate organic carbon fluxes and predict future carbon fluxes under different model scenarios. The coastal GOM receives nitrogen predominantly from the Mississippi and Atchafalaya rivers and atmospheric nitrogen deposition is only a minor component in this region. In the CSK, groundwater and atmospheric nitrogen deposition are more important controlling factors. Our model includes the fluxes of nitrogen to the ocean from the atmosphere, groundwater and rivers, based on observational and literature data, and identifies three zones (brown, green and blue waters) in the coastal GOM and CSK with different productivity and carbon fluxes. Based on our model results, the potential primary production rate in the inner (brown water) zone are over 2 gC m−2 d−1 (GOM) and 1.5 gC m−2 d−1 (CSK). In the middle (green water) zone, potential production is from 0.1 to 2 (GOM) and 0.3 to 1.5 gC m−2 d−1 (CSK). In the offshore (blue water) zone, productivity is less than 0.1 (GOM) and 0.3 (CSK) gC m−2 d−1. Through our model scenario results, overall oxygen demand in the GOM will increase approximately 21 % if we fail to reduce riverine N input, likely increasing considerably the area affected by hypoxia. Comparing the results from the USA with those from the Korean Peninsula shows the importance of considering both riverine and atmospheric inputs of nitrogen. This has direct implications for investigating how changes in energy technologies can lead to changes in the production of various atmospheric contaminants that affect air quality, climate and the health of local populations.

Will U.S. Forests Continue to Be a Carbon Sink?

This paper develops structural dynamic methods to project future carbon fluxes in forests. These methods account for land management changes on both the intensive and extensive margins, both of which are critical components of future carbon fluxes. When implemented, the model suggests that U.S. forests remain a carbon sink through most of the coming century, sequestering 128 Tg C y-1. Constraining forestland to its current boundaries and constraining management to current levels reduce average sequestration by 25 to 28 Tg C y-1. An increase in demand leads to increased management and greater sequestration in forests. The results are robust to climate change. (JEL Q23, Q54).

Soil respiration simulation based on soil temperature and water content in artificial smooth brome grassland

Correctly quantifying the relationships between soil respiration and environmental factors and their sources of variability is essential to predict future carbon fluxes and climate feedback. Soil water conditions and soil temperature strongly affect soil respiration and the dynamics of soil organic matter. Despite this, simulation of soil respiration (Rs) based on soil temperature (Ts) and soil volumetric water content (θ) must still be improved, as demonstrated by its discrepant model performance among different seasons. With the objective of gaining a further understanding of the relationships of Rs with Ts and θ and providing an improved model to simulate Rs variations, we measured hourly Rs, Ts and θ using the chamber technique in artificial smooth brome grassland for analysis. We began by dividing the four seasons of a year according to the daily mean air temperature, followed by representing the seasonal variation of Rs, Ts and θ. We found that Rs correlated significantly with Ts in an exponential relationship and with θ in a parabolic relationship seasonally, where the determination coefficient of the Rs-θ relationship was significantly larger than that of the Rs-Ts relationship. We also discovered that the shape of the Rs-θ relationship was seasonally dependent because the optimal θ and the width of the peak Rs around the optimal θ were seasonally specific. Finally, by considering seasonality, the combinational simulation model explained more variation of soil respiration. Thus, seasonality should be considered for more reliable model simulations of soil respiration. These findings are relevant for more accurate predictions and modelling of soil respiration, particularly in temperate artificial grasslands with a continental monsoon climate, where the ‘Birch effect’ strengthens seasonality, and these findings further our understanding of changes in the rates of soil carbon losses as artificial grassland is established.

Strong dependence of CO2 emissions from anthropogenic land cover change on initial land cover and soil carbon parametrization

AbstractThe quantification of sources and sinks of carbon from land use and land cover changes (LULCC) is uncertain. We investigated how the parametrization of LULCC and of organic matter decomposition, as well as initial land cover, affects the historical and future carbon fluxes in an Earth System Model (ESM). Using the land component of the Max Planck Institute ESM, we found that the historical (1750–2010) LULCC flux varied up to 25% depending on the fraction of biomass which enters the atmosphere directly due to burning or is used in short‐lived products. The uncertainty in the decadal LULCC fluxes of the recent past due to the parametrization of decomposition and direct emissions was 0.6 Pg C yr−1, which is 3 times larger than the uncertainty previously attributed to model and method in general. Preindustrial natural land cover had a larger effect on decadal LULCC fluxes than the aforementioned parameter sensitivity (1.0 Pg C yr−1). Regional differences between reconstructed and dynamically computed land covers, in particular, at low latitudes, led to differences in historical LULCC emissions of 84–114 Pg C, globally. This effect is larger than the effects of forest regrowth, shifting cultivation, or climate feedbacks and comparable to the effect of differences among studies in the terminology of LULCC. In general, we find that the practice of calibrating the net land carbon balance to provide realistic boundary conditions for the climate component of an ESM hampers the applicability of the land component outside its primary field of application.

Past and future carbon fluxes from land use change, shifting cultivation and wood harvest

Carbon emissions from anthropogenic land use (LU) and land use change (LUC) are quantified with a Dynamic Global Vegetation Model for the past and the 21st century following Representative Concentration Pathways (RCPs). Wood harvesting and parallel abandonment and expansion of agricultural land in areas of shifting cultivation are explicitly simulated (gross LUC) based on the Land Use Harmonization (LUH) dataset and a proposed alternative method that relies on minimum input data and generically accounts for gross LUC. Cumulative global LUC emissions are 72 GtC by 1850 and 243 GtC by 2004 and 27–151 GtC for the next 95 yr following the different RCP scenarios. The alternative method reproduces results based on LUH data with full transition information within <0.1 GtC/yr over the last decades and bears potential for applications in combination with other LU scenarios. In the last decade, shifting cultivation and wood harvest within remaining forests including slash each contributed 19% to the mean annual emissions of 1.2 GtC/yr. These factors, in combination with amplification effects under elevated CO2, contribute substantially to future emissions from LUC in all RCPs.

Microbes in thawing permafrost: the unknown variable in the climate change equation

Considering that 25% of Earth s terrestrial surface is underlain by permafrost (ground that has been continuously frozen for at least 2 years), our understanding of the diversity of microbial life in this extreme habitat is surprisingly limited. Taking into account the total mass of perennially frozen sediment (up to several hundred meters deep), permafrost contains a huge amount of buried, ancient organic carbon (Tarnocai et al., 2009). In addition, permafrost is warming rapidly in response to global climate change (Romanovsky et al., 2010), potentially leading to widespread thaw and a larger, seasonally thawed soil active layer. This concern has prompted the question: will permafrost thawing lead to the release of massive amounts of carbon dioxide (CO2) and methane (CH4) into the atmosphere? This question can only be answered by understanding how the microbes residing in permafrost will respond to thaw, through processes such as respiration, fermentation, methanogenesis and CH4 oxidation (Schuur et al., 2009). Predicting future carbon fluxes is complicated by the diversity of permafrost environments, ranging from high mountains, southern boreal forests, frozen peatlands and Pleistocene ice complexes (yedoma) up to several hundred meters deep, which vary widely in soil composition, soil organic matter (SOM) quality, hydrology andmore » thermal regimes (Figure 1). Permafrost degradation can occur in many forms: thaw can progress downward from seasonally-thawed active layer soils in warming climates or laterally because of changes in surface or groundwater flow paths (Grosse et al., 2011). Permafrost degradation can sometimes lead to dramatic changes in ecosystem structure and function« less

Post-Soviet farmland abandonment, forest recovery, and carbon sequestration in western Ukraine

Land use is a critical factor in the global carbon cycle, but land-use effects on carbon fluxes are poorly understood in many regions. One such region is Eastern Europe and the former Soviet Union, where land-use intensity decreased substantially after the collapse of socialism, and farmland abandonment and forest expansion have been widespread. Our goal was to examine how land-use trends affected net carbon fluxes in western Ukraine (57 000 km 2 ) and to assess the region’s future carbon sequestration potential. Using satellite-based forest disturbance and farmland abandonment rates from 1988 to 2007, historic forest resource statistics, and a carbon bookkeeping model, we reconstructed carbon fluxes from land use in the 20th century and assessed potential future carbon fluxes until 2100 for a range of forest expansion and logging scenarios. Our results suggested that the low-point in forest cover occurred in the 1920s. Forest expansion between 1930 and 1970 turned the region from a carbon source to a sink, despite intensive logging during socialism. The collapse of the Soviet Union created a vast, but currently largely untapped carbon sequestration potential (up to � 150 Tg C in our study region). Future forest expansion will likely maintain or even increase the region’s current sink strength of 1.48 Tg C yr � 1 . This may offer substantial opportunities for offsetting industrial