Terrestrial Carbon Budget Research Articles

Response of soil greenhouse gas fluxes to warming: A global meta‐analysis of field studies

Climate warming is predicted to stimulate soil greenhouse gas (GHG) fluxes. A growing number of field studies have investigated the effect of warming on GHG fluxes, but the global responses and temperature sensitivities of all three major biogenic GHGs (CO2, CH4 and N2O) to warming and the potential driving factors have not been well synthesized across different biomes. We conducted a meta-analysis of 2423 globally obtained observations across multiple terrestrial ecosystems (i.e., forest, shrubland, grassland, wetland, cropland and tundra) from 224 published studies. Globally, experimental warming significantly stimulated soil GHG fluxes; soil CO2 and N2O emissions increased by 9.9% and 17.9%, respectively, and CH4 emissions in the lowland regions and CH4 uptakes in the upland regions increased by 10.1% and 7.5%, respectively, under warming. These increases amounted to 2289.0 kg, 31.0 kg, and 0.5 kg ha-1 year-1 of CO2, CH4 and N2O emissions and 1.1 kg ha-1 year-1 of CH4 uptake per 1 °C globally, which translates to an additional emission of 30.3 Pg CO2 and 2.3 Pg CO2 equivalent (CO2-eq) of CH4 and N2O fluxes from terrestrial ecosystems annually under 1 °C warming scenarios. We found that the responses and temperature sensitivities of GHG fluxes to warming were highly biome-dependent, and climate and warming duration also impacted the responses and temperature sensitivities of GHG fluxes. Moreover, warming also affected plant biomass, soil moisture, soil microbial substrate availability, and microbial biomass and function, and changes in soil moisture and plant biomass were related to the changes in GHG fluxes under warming. Our results provide strong empirical support that warming significantly increases soil GHG emissions and aboveground biomass but has no effect on soil carbon. Studies focus only on soil GHG fluxes, with no measurements of soil and plant carbon response, would overestimate the net impact of warming on the terrestrial carbon budget.

Carbon fluxes from contemporary forest disturbances in North Carolina evaluated using a grid-based carbon accounting model and fine resolution remote sensing products

Land use/land cover change is a key component in terrestrial carbon cycle, yet there are still large uncertainties in the terrestrial carbon budget. To reduce such uncertainties and refine the spatial distribution of carbon flux, a 30-m Grid-based Carbon Accounting (GCA) model was proposed. We adapted a well-established bookkeeping model into a spatial-explicit model to utilize Landsat time series stacks and to calculate the carbon fluxes resulting from three types of forest disturbances including forest harvesting, forest-to-urban conversion, and fire. Our model results provide spatial details at sub-ha scale that are crucial for carbon management at individual landowner levels. Sensitivity analysis revealed that both pre-disturbance forest carbon and disturbance intensity had large impact on carbon flux estimates arising from forest disturbances that occurred between 1986 and 2010 in North Carolina. At the state level, forest harvesting and fire from 1986 to 2010 released 88.5 MT and 1.6 MT carbon respectively. During the same period, regrowing trees over the logged area absorbed 142.7 MT carbon while those over burned area absorbed 1.6 MT more. The net flux from harvesting, fire, and post-disturbance growth was −52.5 MT. Conversion of forest to urban resulted in a net source of 5.3 MT. Overall, the areas subject to the three types of disturbances and post-disturbance growth was a net sink of 47.2 MT carbon over the entire study period. While our modeling framework was tested at the 30 m spatial resolution in this study, it can be adapted for use with finer spatial and/or temporal resolution remote sensing products that will become more readily available in the coming years, thus further improve the carbon flux estimates.

Global simulation of fine resolution land use/cover change and estimation of aboveground biomass carbon under the shared socioeconomic pathways

Land use change driven by human activities plays a critical role in the terrestrial carbon budget through habitat loss and vegetation change. Despite the projections of the global population and economic growth under the framework of the Shared Socioeconomic Pathways (SSPs), little is known of land use/cover change (LUCC) at a fine spatial resolution and how carbon pools respond to LUCC under different SSPs. This study projected the future global LUCC with 1 km spatial resolution and a 10-year time step from 2010 to 2100 and then explored its direct impacts on aboveground biomass carbon (AGB) under SSPs. Scenario SSP3 yields the highest global cropland expansion, among which approximately 48% and 46% is expected to be located in the current forest land and grassland, respectively. Scenario SSP1 has the largest forest expansion and is mainly converted from grassland (54%) and cropland (30%). Due to the spatial change in land use/cover, global AGB loss is expected to reach approximately 3.422 Pg C in 2100 under scenario SSP3 and increases by approximately 0.587 Pg C under scenario SSP1. Africa is expected to lose 30% of AGB under the scenario SSP3. Aboveground biomass in Asia will fix 0.774 Pg C to reverse the AGB loss in 2100 under scenario SSP1. The global carbon loss estimated by the land use products with 10 km and 25 km resolution are less than that with 1 km by 1.5% (ranging from −11.2% in Africa to +34.0% in Oceania) and 2.9% (ranging from −11.8% in Africa to +24.0% in Oceania), respectively. These findings suggest that sufficient spatial details in the existing SSP scenario projections could reduce the uncertainties of AGB assessment, and reasonable land use development and management is a key measure to mitigate the negative impacts of LUCC on the biomass carbon pool.

The importance of hydrology in routing terrestrial carbon to the atmosphere via global streams and rivers

SignificanceStream/river carbon dioxide (CO2) emission has significant spatial and seasonal variations critical for understanding its macroecosystem controls and plumbing of the terrestrial carbon budget. We relied on direct fluvial CO2 partial pressure measurements and seasonally varying gas transfer velocity and river network surface area estimates to resolve reach-level seasonal variations of the flux at the global scale. The percentage of terrestrial primary production (GPP) shunted into rivers that ultimately contributes to CO2 evasion increases with discharge across regions, due to a stronger response in fluvial CO2 evasion to discharge than GPP. This highlights the importance of hydrology, in particular water throughput, in terrestrial-fluvial carbon transfers and the need to account for this effect in plumbing the terrestrial carbon budget.

Climate Drives Modeled Forest Carbon Cycling Resistance and Resilience in the Upper Great Lakes Region, USA.

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond to (resistance) and recover from (resilience) rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the Ecosystem Demography‐2.2 (ED‐2.2) model to project carbon fluxes for a northern temperate deciduous forest subjected to a real‐world disturbance severity manipulation experiment. ED‐2.2 was run for 150 years, starting from near bare ground in 1900 (approximating the clear‐cut conditions at the time), and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes such as gross primary production (GPP), and interacted with one another. We then calculated resistance and resilience, two dimensions of ecosystem stability. Modeled GPP exhibited a two‐fold decrease in mean resistance across disturbance severities of 45%, 65%, and 85% mortality; conversely, resilience increased by a factor of two with increasing disturbance severity. This pattern held for net primary production and net ecosystem production, indicating a trade‐off in which greater initial declines were followed by faster recovery. Notably, however, heterotrophic respiration responded more slowly to disturbance, and it's highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

Drivers of water erosion-induced lateral soil carbon loss on the Tibetan Plateau

The lateral transport of soil organic carbon (SOC) induced by soil loss has global significance for understanding the terrestrial carbon budget. On the Tibetan Plateau, this is regulated by a complex interplay of environmental factors including soil properties, terrain attributes, climate variables, and vegetation conditions. However, it remains unclear how water erosion-induced SOC detachment responds to ongoing environmental changes. In this study, we used remote sensing, ground observations, and grid datasets to investigate the spatial distribution of lateral SOC loss and its drivers across the Tibetan Plateau from 2001 to 2017. The potential mean annual soil carbon erosion rate of 208.97 kg C ha−1 yr−1 was equivalent to an annual potential SOC removal flux of 40.72 Tg C over the study period. Approximately 95% of lateral SOC loss occurred in grasslands and forests. Soil properties such as bulk density and pH accounted for 31% of the relative influence on lateral SOC transfer, followed by terrain attributes such as terrain ruggedness index and altitude (25%). Climate and vegetation accounted for 22% of the relative influence on lateral SOC transfer, respectively. However, the most influential environmental indicator was the annual mean temperature. The interconnections of soil, terrain, climate, and vegetation in determining lateral SOC loss were identified by a path analysis. There is a need to include environmental drivers when assessing soil carbon dynamics to better inform decision makers developing strategies for managing carbon budgets.

Impact of different ERA reanalysis data on GPP simulation

The performance of the terrestrial biosphere models (TBMs) is limited by the accuracy of climate forcing data. As the reanalysis products of the European Centre for Medium-Range Weather Forecasts (ECMWF), ERA-Interim and ERA5 data are widely used in the simulation of terrestrial carbon budgets and reveal their responses to climate change. However, the discrepancy between simulated carbon budgets driven by ERA-Interim and ERA5 on a global scale has not been evaluated. In this study, driven by ERA-Interim and ERA5, we conducted two simulations by a TBM, BEPS (Boreal Ecosystem Productivity Simulator), to investigate the differences of simulated Gross primary productivity (GPP) in temporal trends and spatial patterns and to identify the differences in climate factors resulted in the spreads of simulated GPPs. We found that by 2015, the relatively stable difference of simulated GPP by ERA-Interim and ERA5 was about 3.55 Pg C yr−1. Since 2016, the differences of simulated GPP increased gradually and peaked in the last year of our simulation in 2018 at 13.16 Pg C yr−1. This significant difference in GPP was due to the changes of GPP in the Amazon Basin, Congo Basin and South Asia, where tropical forests and tropical savannahs & grasslands were widely distributed. In these regions, the GPP of ERA5 in total was at least 3.0 Pg C yr−1 lower than that of ERA-Interim after 2016. The difference of GPP in such regions was the main reason why ERA5 and ERA-Interim GPP showed different interannual variability. And less precipitation and higher temperature of ERA5 in tropical regions mainly results in the reduction of GPP compared with the results driven by ERA-Interim. Our results highlight challenges in using ERA5 and ERA-Interim to evaluate responses of ecosystem to climate change and provide implications for reducing the uncertainty of climate forcing data in simulating terrestrial carbon cycle.

Temporal Pattern Analysis of Cropland Phenology in Shandong Province of China Based on Two Long-Sequence Remote Sensing Data

Vegetation phenology dynamics have attracted worldwide attention due to its direct response to global climate change and the great influence on terrestrial carbon budgets and ecosystem productivity in the past several decades. However, most studies have focused on phenology investigation on natural vegetation, and only a few have explored phenology variation of cropland. In this study, taking the typical cropland in the Shandong province of China as the target, we analyzed the temporal pattern of the Normalized Difference Vegetation Index (NDVI) and phenology metrics (growing season start (SOS) and end (EOS)) derived from the Global Inventory Monitoring and Modeling System (GIMMS) 3-generation version 1 (1982–2015) and the Vegetation Index and Phenology (VIP) version 4 (1981–2016), and then investigated the influence of climate factors and Net Primary Production (NPP, only for EOS) on SOS/EOS. Results show a consistent seasonal profile and interannual variation trend of NDVI for the two products. Annual average NDVI has significantly increased since 1980s, and hugely augmentations of NDVI were detected from March to June for both NDVI products (p < 0.01), which indicates a consistent greening tendency of the study region. SOSs from both products are correlated well with the ground-observed wheat elongation and spike date and have significantly advanced since the 1980s, with almost the same changing rate (0.65/0.64 days yr-1, p < 0.01). EOS also exhibits an earlier but weak advancing trend. Due to the significant advance of SOS, the growing season duration has significantly lengthened. Spring precipitation has a relatively stronger influence on SOS than temperature and shortwave radiation, while a greater correlation coefficient was diagnosed between EOS and autumn temperature/shortwave radiation than precipitation/NDVI. Autumn NPP exhibits a nonlinear effect on EOS, which is first earlier and then later with the increase of autumn NPP. Overall, we highlight the similar capacity of the two NDVI products in characterizing the temporal patterns of cropland phenology.

Spatial and temporal dynamics of soil organic carbon stock and carbon sequestration affected by major land-use conversions in Northwestern highlands of Ethiopia

Soil organic carbon (SOC) is the major component of the terrestrial carbon (C) budget, a key indicator of environmental sustainability. So, estimating SOC stock and soil carbon (C) sequestration dynamics is important for evidence-based and carbon-conscious decisions. Quantification of SOC stock and soil C sequestration affected by land-use changes (LUCs) have received much attention in addressing food and climate security. This study aims to estimate the dynamics of SOC stock, soil C sequestration and associated soil parameters affected by major LUCs from 2012 to 2021 in Awi highlands of Amhara Regional State of Ethiopia. The study area has experienced dramatic LUC, particularly plantation and growing of Acacia decurrens (J.C. Wendl.) tree followed by recurrent deforestation and then cropping and back to the plantation. The study quantified spatial and temporal dynamics of SOC stock, soil C sequestration and associated changes affected by the LUCs. A total of 22 topsoil (0–20 cm) legacy data was obtained from the Ethiopian Soil Information System (EthiSIS) database of 2012. The same number of samples were collected at the same locations in 2021 by using the same sampling procedure as that of 2012. In addition, the same number of core samples were collected in 2021 for bulk density analysis. To estimate the unmeasured bulk density of legacy data, we applied a pedotransfer function. We used empirical equations and basic statistics to assess changes in SOC stock and C sequestration rate between the two periods. Statistically significant variation (P < 0.01) in SOC stock and C sequestration was observed between the two periods. LUC from acacia plantation to croplands caused a decline of SOC stock by −30.16%, and it also caused the decline of total nitrogen stock, available phosphorus, cation exchange capacity (CEC). However, the reverse LUC caused an increase in SOC by 27.74% and the abovementioned soil parameters. LUC from plantation forest to cropland caused emission of 8.3 tons of CO2 year−1. Generally, overall LUCs caused the net negative change in SOC stock by (−2.42 %) and associated soil parameters in the last ten years. Our study provides evidence that overall LUCs in the current study site caused a decline in SOC stock, along with associated soil parameters with carbon emitted to the atmosphere. Hence, sustainable land-use management options which can offset losses in SOC stock should be implemented soon.

Relationship between lake salinity and the climatic gradient in northeastern China and its implications for studying climate change

The rising temperatures, increased evaporation, and altered precipitation patterns associated with global warming pose threats to aquatic ecosystems, especially the salinization of lake water and changes in the terrestrial carbon budget. We studied a series of samples of catchment soils, surface sediments, and sediment cores from 51 lakes and reservoirs covering an extensive climatic range in northeastern China. Measurements included salinity indices (electrical conductivity and pH) and other physicochemical parameters, including magnetic properties and color (chroma). The results indicate that the occurrence of salt minerals and the salinity of the lake sediments are dominated by the arid climatic conditions of the region. This enabled us to develop climatic transfer functions between salinity, precipitation and evaporation, with potential applications in paleoclimatic research. As carbonates are the dominant salts in most of the studied lakes and reservoirs, past salinity variations are likely reflected by changes in HCO3- and CO32- concentrations, which provides the opportunity to study the response of water-CO2-carbonate interactions to climate change. Our findings emphasize the important role of alkaline lakes in carbon burial and carbon neutralization, in the context of ongoing global warming.

Changes of lake organic carbon sinks from closed basins since the Last Glacial Maximum and quantitative evaluation of human impacts

BackgroundClosed basins occupy 21% of the world’s land area and can substantially affect global carbon budgets. Conventional understanding suggests that the terminal areas of closed basins collect water and carbon from throughout the entire basin, and changes in lake organic carbon sinks are indicative of basin-wide organic carbon storages. However, this hypothesis lacks regional and global validation. Here, we first validate the depositional process of organic carbon in a typical closed-basin region of northwest China using organic geochemical proxies of both soil and lake sediments. Then we estimate the organic carbon sinks and human impacts in extant closed-basin lakes since the Last Glacial Maximum (LGM).ResultsResults show that 80.56 Pg organic carbon is stored in extant closed-basin lakes mainly found in the northern mid-latitudes. Carbon accumulation rates vary from 17.54 g C m−2 yr−1 during modern times, 6.36 g C m−2 yr−1 during the mid-Holocene and 2.25 g C m−2 yr−1 during the LGM. Then, we evaluated the influence by human activities during the late Holocene (in the past three thousand years). The ratio of human impacts on lake organic carbon storage in above closed basins is estimated to be 22.79%, and human-induced soil organic carbon emissions in the past three thousand years amounted to 207 Pg.ConclusionsWhile the magnitude of carbon storage is not comparable to those in peatland, vegetation and soil, lake organic carbon sinks from closed basins are significant to long-term terrestrial carbon budget and contain information of climate change and human impact from the whole basins. These observations improve our understanding of carbon sinks in closed basins at various time scales, and provide a basis for the future mitigation policies to global climate change.

A practical topographic correction method for improving Moderate Resolution Imaging Spectroradiometer gross primary productivity estimation over mountainous areas

Time-series Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary productivity (GPP) has been served as an effective tool to assess the terrestrial carbon budget for the entire globe since 2000. However, the current MODIS GPP product neglects the surface heterogeneity in the modeling process and is always generated at 500 m or 1 km resolution, which could cause errors to these estimates over mountainous areas. In this work, the MODIS GPP model (MOD17) was applied to obtain 1 km GPP estimates at eleven mountainous sites. Then, a topographic correction method based on three indexes associated with the spatial heterogeneity of received radiation (TCIAPAR), temperature (TCITMIN), and water (TCIVPD) stresses was developed to reduce GPP errors in these MOD17-simulated estimates. Results showed that a closer relationship between tower-based GPP and MOD17-simulated GPP was achieved after applying the proposed topographic correction method, with the determination coefficient (R2) increased from 0.61 to 0.74 and root mean square error (RMSE) reduced from 24.24 to 14.56 gC m−2 8d−1 at all the eleven mountainous sites. As for the effectiveness of each topographic correction index, an obvious improvement of MOD17-simulated GPP was observed after TCIAPAR correction (increasing R2 by 0.09 and decreasing RMSE by 8.75 gC m−2 8d−1), TCITMIN correction (increasing R2 by 0.05 and decreasing RMSE by 7.80 gC m−2 8d−1), and TCIVPD correction (increasing R2 by 0.06 and decreasing RMSE by 7.89 gC m−2 8d−1), indicating that the spatial heterogeneity information of radiation, temperature, and water within coarse pixels is necessary for improving the MODIS GPP over mountainous areas. It is notable that the combination of the TCIAPAR, TCITMIN, and TCIVPD corrections was found to have the largest improvement for MOD17-simulated GPP (increasing R2 by 0.13 and decreasing RMSE by 9.68 gC m−2 8d−1), indicating that the combined consideration of topographic factors in the correction process might achieve a larger improvement. This study highlights the feasibility of incorporating surface topographic characteristics into current coarse resolution GPP products in obtaining large-scale mountain GPP estimates.

On the Treatment of Soil Water Stress in GCM Simulations of Vegetation Physiology

Current land surface schemes in weather and climate models make use of the so-called coupled photosynthesis–stomatal conductance (A–gs) models of plant function to determine the surface fluxes that govern the terrestrial energy, water and carbon budgets. Plant physiology is controlled by many environmental factors, and a number of complex feedbacks are involved, but soil moisture control on root water uptake is primary, particularly in sub-tropical to temperate ecosystems. Land surface models represent plant water stress in different ways, but most implement a water stress factor, β, which ranges linearly (more recently also curvilinearly) between β = 1 for unstressed vegetation and β = 0 at the wilting point, expressed in terms of volumetric water content (θ). β is most commonly used to either limit A or gs, and hence carbon and water fluxes, and a pertinent research question is whether these treatments are in fact interchangeable. Following Egea et al. (Agricultural and Forest Meteorology, 2011, 151 (10), 1,370–1,384) and Verhoef et al. (Agricultural and Forest Meteorology, 2014, 191, 22–32), we have implemented new β treatments, reflecting higher levels of biophysical complexity in a state-of-the-art LSM, Joint UK Land Environment Simulator, by allowing root zone soil moisture to limit plant function non-linearly and via individual routes (carbon assimilation, stomatal conductance, or mesophyll conductance) as well as any (non-linear) combinations thereof. The treatment of β does matter to the prediction of water and carbon fluxes: this study demonstrates that it represents a key structural uncertainty in contemporary LSMs, in terms of predictions of gross primary productivity, energy fluxes and soil moisture evolution, both in terms of climate means and response to a number of European droughts, including the 2003 heat wave. Treatments allowing ß to act on vegetation fluxes via stomatal and mesophyll routes are able to simulate the spatiotemporal variability in water use efficiency with higher fidelity during the growing season; they also support a broader range of ecosystem responses, e.g., those observed in regions that are radiation limited or water limited. We conclude that current practice in weather and climate modelling is inconsistent, as well as too simplistic, failing to credibly simulate vegetation response to soil water stress across the typical range of variability that is encountered for current European weather and climate conditions, including extremes of land surface temperature and soil moisture drought. A generalized approach performs better in current climate conditions and promises to be, based on responses to recently observed extremes, more trustworthy for predicting the impacts of climate change.

Large Differences in Diffuse Solar Radiation Among Current-Generation Reanalysis and Satellite-Derived Products

AbstractThough the partitioning of shortwave radiation (K↓) at the surface into its diffuse (K↓,d) and direct beam (K↓,b) components is relevant for, among other things, the terrestrial energy and carbon budgets, there is a dearth of large-scale comparisons of this partitioning across reanalysis and satellite-derived products. Here we evaluate K↓, K↓,d, and K↓,b, as well as the diffuse fraction (kd) of solar radiation in four current-generation reanalysis (NOAA-CIRES-DOE, NCEP/NCAR, MERRA-2, ERA5) datasets and one satellite-derived product (CERES) using ≈1400 site years of observations. Although the systematic positive biases in K↓ is consistent with previous studies, the biases in gridded K↓,d and K↓,b vary in direction and magnitude, both annually and across seasons. The inter-model variability in cloud cover strongly explains the biases in both K↓,d and K↓,b. Over Europe and China, the long-term (10-year plus) trends in K↓,d in the gridded products are noticeably differ from corresponding observations and the grid-averaged 35-year trends show an order of magnitude variability. In the MERRA-2 reanalysis, which includes both clouds and assimilated aerosols, the reduction in both clouds and aerosols reinforce each other to establish brightening trends over Europe, while the effect of increasing aerosols overwhelm the effect of decreasing cloud cover over China. The inter-model variability in kd seen here (0.27 to 0.50 from CERES to MERRA-2) suggests substantial differences in shortwave parameterization schemes and their inputs in climate models and can contribute to inter-model variability in coupled simulations. Based on these results, we call for systematic evaluations of K↓,d and K↓,b in CMIP6 models.

Long-term variations in solar radiation, diffuse radiation, and diffuse radiation fraction caused by aerosols in China during 1961-2016.

The effects of atmospheric aerosols on the terrestrial climate system are more regional than those of greenhouse gases, which are more global. Thus, it is necessary to examine the typical regional effects of how aerosols affect solar radiation in order to develop a more comprehensive understanding. In this study, we used global AErosol RObotic NETwork (AERONET) data and robust radiation observational evidence to investigate the impact of aerosols on total radiation, diffuse radiation, and the diffuse radiation fraction in China from 1961 to 2016. Our results showed that there were different temporal changes in the aerosol optical depth (AOD), total solar radiation, diffuse radiation and diffuse radiation fraction over the past 56 years. Specifically, the 550 nm AOD from 2005 to 2016 decreased significantly, with annual average AOD of 0.51. Meanwhile, the average total solar radiation reduced by 2.48%, while there was a slight increase in average diffuse radiation at a rate of 3.10 MJ·m-2·yr-1. Moreover, the spatial heterogeneities of AOD, total radiation, diffuse radiation, and the diffuse radiation fraction in China were significant. Aerosol particle emissions in the developed eastern and southern regions of China were more severe than those in the western regions, resulting in higher total radiation and diffuse radiation in the western plateau than in the eastern plain. In addition, aerosols were found to have negative effects on total radiation and sunshine hours, and positive effects on diffuse radiation and diffuse radiation fraction. Further, the diffuse radiation fraction was negatively correlated with sunshine hours. However, there was a positive correlation between AOD and sunshine hours. These results could be used to assess the impacts of climate change on terrestrial ecosystem productivity and carbon budgets.

Early Growing Season Anomalies in Vegetation Activity Determine the Large‐Scale Climate‐Vegetation Coupling in Europe

AbstractThe climate‐vegetation coupling exerts a strong control on terrestrial carbon budgets and will affect the future evolution of global climate under continued anthropogenic forcing. Nonetheless, the effects of climatic conditions on such coupling at specific times in the growing season remain poorly understood. We quantify the climate‐vegetation coupling in Europe over 1982–2014 at multiple spatial and temporal scales, by decomposing sub‐seasonal anomalies of vegetation greenness using a grid‐wise definition of the growing season. We base our analysis on long‐term vegetation indices (Normalized Difference Vegetation Index and two‐band Enhanced Vegetation Index), growing conditions (including 2m temperature, downwards surface solar radiation, and root‐zone soil moisture), and multiple teleconnection indices that reflect the large‐scale climatic conditions over Europe. We find that the large‐scale climate‐vegetation coupling during the first two months of the growing season largely determines the full‐year coupling. The North Atlantic Oscillation and Scandinavian Pattern phases one‐to‐two months before the start of the growing season are the dominant and contrasting drivers of the early growing season climate‐vegetation coupling over large parts of boreal and temperate Europe. The East Atlantic Pattern several months in advance of the growing season exerts a strong control on the temperate belt and the Mediterranean region. The strong role of early growing season anomalies in vegetative activity within the growing season emphasizes the importance of a grid‐wise definition of the growing season when studying the large‐scale climate‐vegetation coupling in Europe.

Socio-ecological drivers of long-term ecosystem carbon stock trend: An assessment with the LUCCA model of the French case

• Land-use change are driven by socio-ecological processes affecting carbon fluxes. • We assess these drivers and fluxes based on a long-term modelling approach. • Carbon stocks in ecosystem increased by 32 % of in France from 1850 to 2015. • The main drivers are first change in land use intensity and second land conversion. • However, carbon emissions by fossil fuel are 9 times the sink in ecosystems. Land ecosystems can play a crucial role in climate-change mitigation by acting as sinks for carbon. Legacy effects of past land use, including land conversion and changes in land-use intensity, influence the capacity for future ecosystem carbon sequestration. These effects are hard to quantify, however, and the influence of changes in land-use intensity are still largely overlooked. This study assessed the long term dynamics (1850–2015) of the terrestrial carbon budget in France. We developed a new dynamic model: LUCCA (Land Use Change & Conversion Accounting) that robustly quantifies the dynamics of carbon stocks and fluxes. It allows disentanglement of land conversion from land management effects following a socio-ecological perspective. Carbon stocks in terrestrial ecosystems in France increased from 3.5 GtC in 1850 to 4.8 GtC in 2015 as a result of contrasting regional land-use trajectories. Based on five counterfactual scenarios, we unravel that changes in land-use intensity explained 46 % of the observed carbon stock changes since 1850, while land conversion was responsible for 30 %, and the rest can be attributed to changes in forest growth rates induced by both environmental and management changes. The effects of land conversion and changes in land-use intensity on carbon stock accumulation, however, would have been hardly possible in the absence of agricultural intensification and release of harvest pressure following wood-fuel substitution by fossil fuel. In fact, carbon emissions induced by fossil fuel consumption in France from 1850 to 2015 were 9 times the carbon sink in terrestrial ecosystems. These figures highlight the importance of considering long-term trajectories of ecosystem carbon fluxes and their relationship with emissions from other processes for climate action strategies.

Modeling the impacts of diffuse light fraction on photosynthesis in ORCHIDEE (v5453) land surface model

Abstract. Aerosol- and cloud-induced changes in diffuse light have important impacts on the global land carbon cycle, as they alter light distribution and photosynthesis in vegetation canopies. However, this effect remains poorly represented or evaluated in current land surface models. Here, we add a light partitioning module and a new canopy light transmission module to the ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems) land surface model (trunk version, v5453) and use the revised model, ORCHIDEE_DF, to estimate the fraction of diffuse light and its effect on gross primary production (GPP) in a multilayer canopy. We evaluate the new parameterizations using flux observations from 159 eddy covariance sites over the globe. Our results show that, compared with the original model, ORCHIDEE_DF improves the GPP simulation under sunny conditions and captures the observed higher photosynthesis under cloudier conditions in most plant functional types (PFTs). Our results also indicate that the larger GPP under cloudy conditions compared with sunny conditions is mainly driven by increased diffuse light in the morning and in the afternoon as well as by a decreased vapor pressure deficit (VPD) and decreased air temperature at midday. The observations show that the strongest positive effects of diffuse light on photosynthesis are found in the range from 5 to 20 ∘C and at a VPD &lt; 1 kPa. This effect is found to decrease when the VPD becomes too large or the temperature falls outside of the abovementioned range, which is likely due to the increasing stomatal resistance to leaf CO2 uptake. ORCHIDEE_DF underestimates the diffuse light effect at low temperature in all PFTs and overestimates this effect at high temperature and at a high VPD in grasslands and croplands. The new model has the potential to better investigate the impact of large-scale aerosol changes and long-term changes in cloudiness on the terrestrial carbon budget, both in the historical period and in the context of future air quality policies and/or climate engineering.

Biogeophysical and biogeochemical impacts of land-use change simulated by MIROC-ES2L

Land-use change is one of the focal processes in Earth system models because it has strong impacts on terrestrial biogeophysical and biogeochemical conditions. However, modeling land-use impacts is still challenging because of model complexity and uncertainty. This study examined the results of simulations of land-use change impacts by the Model for Interdisciplinary Research on Climate, Earth System version 2 for long-term simulations (MIROC-ES2L) conducted under the Land-Use Model Intercomparison Project protocol. In a historical experiment, the model reproduced biogeophysical impacts such as decreasing trends in land-surface net radiation and evapotranspiration by about 1970. Among biogeochemical impacts, the model captured the global decrease of vegetation and soil carbon stocks caused by extensive deforestation. By releasing ecosystem carbon stock to the atmosphere, land-use change shortened the mean residence time of terrestrial carbon and accelerated its turnover rate, especially in low latitudes. Future projections based on Shared Socioeconomic Pathways indicated substantial alteration of land conditions caused primarily by climatic change and secondarily by land-use change. Sensitivity experiments conducted by exchanging land-use data between different future projection baseline experiments showed that, at the global scale, the anticipated extent of land-use conversion would likely play a modest role in the future terrestrial radiation, water, and carbon budgets. Regional investigations revealed that future land use would exert a considerable influence on runoff and vegetation carbon stock. Further model refinement is required to improve its capability to analyze its complicated terrestrial linkages or nexus (e.g., food, bioenergy, and carbon sequestration) to climate-change impacts.

Microbial dormancy and its impacts on northern temperate and boreal terrestrial ecosystem carbon budget

Abstract. A large amount of soil carbon in northern temperate and boreal regions could be emitted as greenhouse gases in a warming future. However, lacking detailed microbial processes such as microbial dormancy in current biogeochemistry models might have biased the quantification of the regional carbon dynamics. Here the effect of microbial dormancy was incorporated into a biogeochemistry model to improve the quantification for the last century and this century. Compared with the previous model without considering the microbial dormancy, the new model estimated the regional soils stored 75.9 Pg more C in the terrestrial ecosystems during the last century and will store 50.4 and 125.2 Pg more C under the RCP8.5 and RCP2.6 scenarios, respectively, in this century. This study highlights the importance of the representation of microbial dormancy in earth system models to adequately quantify the carbon dynamics in the northern temperate and boreal natural terrestrial ecosystems.