Soil thawing regulates the spring growth onset in tundra and alpine biomes

Soil temperature remains isothermal at 0 °C and water shifts to a liquid phase during soil thawing. Vegetation may receive this process as a signal and a key to restore physiological activity. We aimed to show the relationship between the timing of soil thawing and the spring growth onset. We estimated the delay between the soil thawing and the spring growth onset in 78 sites of the FLUXNET network. We built a soil thawing map derived from modeling for the northern hemisphere and related it to the greenness onset estimated with satellite imagery. Spring onset estimated with GPP time series occurred shortly after soil surface thawing in tundra (1.1 ± 3.5 days) and alpine grasslands (16.6 ± 5.8 days). The association was weaker for deciduous forests (40.3 ± 4.2 days), especially where soils freeze infrequently. Needleleaved forests tended to start the growing season before the end of thawing (-17.4 ± 3.6 days), although observations from remote sensing (MODIS Land Cover Dynamics) indicated that the onset of greenness started after the thawing period (26.8 ± 3.2 days). This study highlights the role of soil temperature at the spring growth onset at high latitudes. Soil thawing becomes less relevant in temperate forests, where soil is occasionally frozen and other climate factors become more important.

Could Global Intensification of Nitrogen Fertilisation Increase Immunogenic Proteins and Favour the Spread of Coeliac Pathology?

Fertilisation of cereal crops with nitrogen (N) has increased in the last five decades. In particular, the fertilisation of wheat crops increased by nearly one order of magnitude from 1961 to 2010, from 9.84 to 93.8 kg N ha-1 y-1. We hypothesized that this intensification of N fertilisation would increase the content of allergenic proteins in wheat which could likely be associated with the increased pathology of coeliac disease in human populations. An increase in the per capita intake of gliadin proteins, the group of gluten proteins principally responsible for the development of coeliac disease, would be the responsible factor. We conducted a global meta-analysis of available reports that supported our hypothesis: wheat plants growing in soils receiving higher doses of N fertilizer have higher total gluten, total gliadin, α/β-gliadin, γ-gliadin and ω-gliadin contents and higher gliadin transcription in their grain. We thereafter calculated the per capita annual average intake of gliadins from wheat and derived foods and found that it increased from 1961 to 2010 from approximately 2.4 to 3.8 kg y-1 per capita (+1.4 ± 0.18 kg y-1 per capita, mean ± SE), i.e., increased by 58 ± 7.5%. Finally, we found that this increase was positively correlated with the increase in the rates of coeliac disease in all the available studies with temporal series of coeliac disease. The impacts and damage of over-fertilisation have been observed at an environmental scale (e.g., eutrophication and acid rain), but a potential direct effect of over-fertilisation is thus also possible on human health (coeliac disease).

Near-real-time global gridded daily CO2 emissions 2021

We present a near-real-time global gridded daily CO2 emissions dataset (GRACED) throughout 2021. GRACED provides gridded CO2 emissions at a 0.1° × 0.1° spatial resolution and 1-day temporal resolution from cement production and fossil fuel combustion over seven sectors, including industry, power, residential consumption, ground transportation, international aviation, domestic aviation, and international shipping. GRACED is prepared from the near-real-time daily national CO2 emissions estimates (Carbon Monitor), multi-source spatial activity data emissions and satellite NO2 data for time variations of those spatial activity data. GRACED provides the most timely overview of emissions distribution changes, which enables more accurate and timely identification of when and where fossil CO2 emissions have rebounded and decreased. Uncertainty analysis of GRACED gives a grid-level two-sigma uncertainty of value of ±19.9% in 2021, indicating the reliability of GRACED was not sacrificed for the sake of higher spatiotemporal resolution that GRACED provides. Continuing to update GRACED in a timely manner could help policymakers monitor energy and climate policies' effectiveness and make adjustments quickly.

From regional to parcel scale: A high-resolution map of cover crops across Europe combining satellite data with statistical surveys

The reformed Common Agricultural Policy of 2023-2027 aims to promote a more sustainable and fair agricultural system in the European Union. Among the proposed measures, the incentivized adoption of cover crops to cover the soil during winter provides numerous benefits such as improved soil structure and reduced nutrient leaching and erosion. Despite this recognized importance, the availability of spatial data on cover crops is scarce. The increasing availability of field parcel declarations in the European Union has not yet filled this data gap due to its insufficient information content, limited public availability and a lack of standardization at continental scale. At present, the best information available is regionally aggregated survey data, which although indicative, hinders the development of spatially accurate studies. In this work, we propose a statistical model relating Sentinel-1 data to the existence of cover crops at the 100-m spatial resolution over the entirety of the European Union and United Kingdom and estimate its parameters using the spatially aggregated survey data. To validate the method in a spatially-explicit way, predictions were compared against farmers' registered declarations in France, where the adoption of cover crops is widespread. The results indicate a good agreement between predictions and parcel-level data. When interpreted as a binary classifier, the model yielded an Area Under the Curve (AUC) of 0.74 for the whole country. When the country was divided into five regions for the evaluation of regional biases, the AUC values were 0.77, 0.75, 0.74, 0.70, and 0.65 for the North, Center, West, East, and South regions respectively. Despite limitations such as the lack of data for validation outside France, and the non-standardized nomenclature for cover crops among Member States, this work constitutes the first effort to obtain a relevant cover crop map at a European scale for researchers and practitioners.

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.

Country-Level Relationships of the Human Intake of N and P, Animal and Vegetable Food, and Alcoholic Beverages with Cancer and Life Expectancy

BACKGROUND

The quantity, quality, and type (e.g., animal and vegetable) of human food have been correlated with human health, although with some contradictory or neutral results. We aimed to shed light on this association by using the integrated data at country level.

METHODS

We correlated elemental (nitrogen (N) and phosphorus (P)) compositions and stoichiometries (N:P ratios), molecular (proteins) and energetic traits (kilocalories) of food of animal (terrestrial or aquatic) and vegetable origin, and alcoholic beverages with cancer prevalence and mortality and life expectancy (LE) at birth at the country level. We used the official databases of United Nations (UN), Food and Agriculture Organization of the United Nations (FAO), Organization for Economic Co-operation and Development (OECD), World Bank, World Health Organization (WHO), U.S. Department of Agriculture, U.S. Department of Health, and Eurobarometer, while also considering other possibly involved variables such as income, mean age, or human development index of each country.

RESULTS

The per capita intakes of N, P, protein, and total intake from terrestrial animals, and especially alcohol were significantly and positively associated with prevalence and mortality from total, colon, lung, breast, and prostate cancers. In contrast, high per capita intakes of vegetable N, P, N:P, protein, and total plant intake exhibited negative relationships with cancer prevalence and mortality. However, a high LE at birth, especially in underdeveloped countries was more strongly correlated with a higher intake of food, independent of its animal or vegetable origin, than with other variables, such as higher income or the human development index.

CONCLUSIONS

Our analyses, thus, yielded four generally consistent conclusions. First, the excessive intake of terrestrial animal food, especially the levels of protein, N, and P, is associated with higher prevalence of cancer, whereas equivalent intake from vegetables is associated with lower prevalence. Second, no consistent relationship was found for food N:P ratio and cancer prevalence. Third, the consumption of alcoholic beverages correlates with prevalence and mortality by malignant neoplasms. Fourth, in underdeveloped countries, reducing famine has a greater positive impact on health and LE than a healthier diet.

Declining Amazon biomass due to deforestation and subsequent degradation losses exceeding gains

In the Amazon, deforestation and climate change lead to increased vulnerability to forest degradation, threatening its existing carbon stocks and its capacity as a carbon sink. We use satellite L-Band Vegetation Optical Depth (L-VOD) data that provide an integrated (top-down) estimate of biomass carbon to track changes over 2011-2019. Because the spatial resolution of L-VOD is coarse (0.25°), it allows limited attribution of the observed changes. We therefore combined high-resolution annual maps of forest cover and disturbances with biomass maps to model carbon losses (bottom-up) from deforestation and degradation, and gains from regrowing secondary forests. We show an increase of deforestation and associated degradation losses since 2012 which greatly outweigh secondary forest gains. Degradation accounted for 40% of gross losses. After an increase in 2011, old-growth forests show a net loss of above-ground carbon between 2012 and 2019. The sum of component carbon fluxes in our model is consistent with the total biomass change from L-VOD of 1.3 Pg C over 2012-2019. Across nine Amazon countries, we found that while Brazil contains the majority of biomass stocks (64%), its losses from disturbances were disproportionately high (79% of gross losses). Our multi-source analysis provides a pessimistic assessment of the Amazon carbon balance and highlights the urgent need to stop the recent rise of deforestation and degradation, particularly in the Brazilian Amazon.

Setting priorities for land management to mitigate climate change

BACKGROUND

No consensus has been reached how to measure the effectiveness of climate change mitigation in the land-use sector and how to prioritize land use accordingly. We used the long-term cumulative and average sectorial C stocks in biomass, soil and products, C stock changes, the substitution of fossil energy and of energy-intensive products, and net present value (NPV) as evaluation criteria for the effectiveness of a hectare of productive land to mitigate climate change and produce economic returns. We evaluated land management options using real-life data of Thuringia, a region representative for central-western European conditions, and input from life cycle assessment, with a carbon-tracking model. We focused on solid biomass use for energy production.

RESULTS

In forestry, the traditional timber production was most economically viable and most climate-friendly due to an assumed recycling rate of 80% of wood products for bioenergy. Intensification towards "pure bioenergy production" would reduce the average sectorial C stocks and the C substitution and would turn NPV negative. In the forest conservation (non-use) option, the sectorial C stocks increased by 52% against timber production, which was not compensated by foregone wood products and C substitution. Among the cropland options wheat for food with straw use for energy, whole cereals for energy, and short rotation coppice for bioenergy the latter was most climate-friendly. However, specific subsidies or incentives for perennials would be needed to favour this option.

CONCLUSIONS

When using the harvested products as materials prior to energy use there is no climate argument to support intensification by switching from sawn-wood timber production towards energy-wood in forestry systems. A legal framework would be needed to ensure that harvested products are first used for raw materials prior to energy use. Only an effective recycling of biomaterials frees land for long-term sustained C sequestration by conservation. Reuse cascades avoid additional emissions from shifting production or intensification.

Quantifying the biophysical effects of forests on local air temperature using a novel three-layered land surface energy balance model

The well-documented energy balance dynamics within forest ecosystems are poorly implemented in studies of the biophysical effects of forests. This results in limitations to the accurate quantification of forest cooling/warming on local air temperature. Taking into consideration the forest air space, this study proposes a three-layered (canopy, forest air space and soil [CAS]) land surface energy balance model to simulate air temperature within forest spaces (T_af) and subsequently to evaluate its biophysical effects on forest cooling/warming, i.e., the air temperature gradient (∆T_a) between the T_af and air temperature of open spaces (T_ao) (∆T_a = T_af - T_ao). We test the model using field data for 23 sites across 10 cities worldwide; the model shows satisfactory performance with the test data. High-latitude forests show greater seasonal dynamics of ∆T_a, generating considerable cooling of local air temperatures in warm seasons but minimal cooling or even warming effects during cool seasons, while low-latitude tropical forests always exert cooling effects with less interannual variability. The interannual dynamics of ∆T_a are significantly related to the seasonality of solar geometry and canopy leaf phenology. The differences between forest canopy temperature (T_c) and T_ao, which are the two most important terms attributed by the CAS model in impacting T_af, explain a large part of forest cooling and warming (May-July: R² = 0.35; November-January: R² = 0.51). The novel CAS model provides a feasible way to represent the energy balance within forest ecosystems and to assess its impacts on local air temperatures globally.

Deep learning enables image-based tree counting, crown segmentation, and height prediction at national scale

Sustainable tree resource management is the key to mitigating climate warming, fostering a green economy, and protecting valuable habitats. Detailed knowledge about tree resources is a prerequisite for such management but is conventionally based on plot-scale data, which often neglects trees outside forests. Here, we present a deep learning-based framework that provides location, crown area, and height for individual overstory trees from aerial images at country scale. We apply the framework on data covering Denmark and show that large trees (stem diameter >10 cm) can be identified with a low bias (12.5%) and that trees outside forests contribute to 30% of the total tree cover, which is typically unrecognized in national inventories. The bias is high (46.6%) when our results are evaluated against all trees taller than 1.3 m, which involve undetectable small or understory trees. Furthermore, we demonstrate that only marginal effort is needed to transfer our framework to data from Finland, despite markedly dissimilar data sources. Our work lays the foundation for digitalized national databases, where large trees are spatially traceable and manageable.

Matrix-Based Sensitivity Assessment of Soil Organic Carbon Storage: A Case Study from the ORCHIDEE-MICT Model

Modeling of global soil organic carbon (SOC) is accompanied by large uncertainties. The heavy computational requirement limits our flexibility in disentangling uncertainty sources especially in high latitudes. We build a structured sensitivity analyzing framework through reorganizing the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE)-aMeliorated Interactions between Carbon and Temperature (MICT) model with vertically discretized SOC into one matrix equation, which brings flexibility in comprehensive sensitivity assessment. Through Sobol's method enabled by the matrix, we systematically rank 34 relevant parameters according to variance explained by each parameter and find a strong control of carbon input and turnover time on long-term SOC storages. From further analyses for each soil layer and regional assessment, we find that the active layer depth plays a critical role in the vertical distribution of SOC and SOC equilibrium stocks in northern high latitudes (>50°N). However, the impact of active layer depth on SOC is highly interactive and nonlinear, varying across soil layers and grid cells. The stronger impact of active layer depth on SOC comes from regions with shallow active layer depth (e.g., the northernmost part of America, Asia, and some Greenland regions). The model is sensitive to the parameter that controls vertical mixing (cryoturbation rate) but only when the vertical carbon input from vegetation is limited since the effect of vertical mixing is relatively small. And the current model structure may still lack mechanisms that effectively bury nonrecalcitrant SOC. We envision a future with more comprehensive model intercomparisons and assessments with an ensemble of land carbon models adopting the matrix-based sensitivity framework.

Field-based tree mortality constraint reduces estimates of model-projected forest carbon sinks

Considerable uncertainty and debate exist in projecting the future capacity of forests to sequester atmospheric CO₂. Here we estimate spatially explicit patterns of biomass loss by tree mortality (LOSS) from largely unmanaged forest plots to constrain projected (2015–2099) net primary productivity (NPP), heterotrophic respiration (HR) and net carbon sink in six dynamic global vegetation models (DGVMs) across continents. This approach relies on a strong relationship among LOSS, NPP, and HR at continental or biome scales. The DGVMs overestimated historical LOSS, particularly in tropical regions and eastern North America by as much as 5 Mg ha⁻¹ y⁻¹. The modeled spread of DGVM-projected NPP and HR uncertainties was substantially reduced in tropical regions after incorporating the field-based mortality constraint. The observation-constrained models show a decrease in the tropical forest carbon sink by the end of the century, particularly across South America (from 2 to 1.4 PgC y⁻¹), and an increase in the sink in North America (from 0.8 to 1.1 PgC y⁻¹). These results highlight the feasibility of using forest demographic data to empirically constrain forest carbon sink projections and the potential overestimation of projected tropical forest carbon sinks.

Here the authors use broad-scale tree mortality data to estimate biomass loss, constraining uncertainty of projected forest net primary productivity in 6 models, finding weaker tropical forest carbon sinks with climate change.

Cost-effective implementation of the Paris Agreement using flexible greenhouse gas metrics

Greenhouse gas (GHG) metrics, that is, conversion factors to evaluate the emissions of non-CO₂ GHGs on a common scale with CO₂, serve crucial functions in the implementation of the Paris Agreement. While different metrics have been proposed, their economic cost-effectiveness has not been investigated under a range of pathways, including those substantially overshooting the temperature targets. Here, we show that cost-effective metrics for methane that minimize the overall mitigation costs are time-dependent, primarily determined by the pathway, and strongly influenced by temperature overshoot. Parties to the Paris Agreement have already adopted the conventional GWP100 (100-year global warming potential), which is shown to be a good approximation of cost-effective metrics for the coming decades. In the longer term, however, we suggest that parties consider adapting the choice of common metrics to the future pathway as it unfolds, as part of the recurring global stocktake, if global cost-effectiveness is a key consideration.

Global maps and factors driving forest foliar elemental composition: the importance of evolutionary history

Consistent information on the current elemental composition of vegetation at global scale and the variables that determine it is lacking. To fill this gap, we gathered a total of 30 912 georeferenced records on woody plants foliar concentrations of nitrogen (N), phosphorus (P) and potassium (K) from published databases, and produced global maps of foliar N, P and K concentrations for woody plants using neural networks at a resolution of 1 km² . We used data for climate, atmospheric deposition, soil and morphoclimatic groups to train the neural networks. Foliar N, P and K do not follow clear global latitudinal patterns but are consistent with the hypothesis of soil substrate age. We additionally built generalized linear mixed models to investigate the evolutionary history effect together with the effects of environmental effects. In this comparison, evolutionary history effects explained most of the variability in all cases (mostly > 60%). These results emphasize the determinant role of evolutionary history in foliar elemental composition, which should be incorporated in upcoming dynamic global vegetation models.

Causes of slowing-down seasonal CO2 amplitude at Mauna Loa

Changing amplitude of the seasonal cycle of atmospheric CO₂ (SCA) in the northern hemisphere is an emerging carbon cycle property. Mauna Loa (MLO) station (20°N, 156°W), which has the longest continuous northern hemisphere CO₂ record, shows an increasing SCA before the 1980s (p < .01), followed by no significant change thereafter. We analyzed the potential driving factors of SCA slowing-down, with an ensemble of dynamic global vegetation models (DGVMs) coupled with an atmospheric transport model. We found that slowing-down of SCA at MLO is primarily explained by response of net biome productivity (NBP) to climate change, and by changes in atmospheric circulations. Through NBP, climate change increases SCA at MLO before the 1980s and decreases it afterwards. The effect of climate change on the slowing-down of SCA at MLO is mainly exerted by intensified drought stress acting to offset the acceleration driven by CO₂ fertilization. This challenges the view that CO₂ fertilization is the dominant cause of emergent SCA trends at northern sites south of 40°N. The contribution of agricultural intensification on the deceleration of SCA at MLO was elusive according to land-atmosphere CO₂ flux estimated by DGVMs and atmospheric inversions. Our results also show the necessity to adequately account for changing circulation patterns in understanding carbon cycle dynamics observed from atmospheric observations and in using these observations to benchmark DGVMs.

Increasingly negative tropical water-interannual CO2 growth rate coupling

Terrestrial ecosystems have taken up about 32% of the total anthropogenic CO2 emissions in the past six decades1. Large uncertainties in terrestrial carbon-climate feedbacks, however, make it difficult to predict how the land carbon sink will respond to future climate change2. Interannual variations in the atmospheric CO2 growth rate (CGR) are dominated by land-atmosphere carbon fluxes in the tropics, providing an opportunity to explore land carbon-climate interactions3-6. It is thought that variations in CGR are largely controlled by temperature7-10 but there is also evidence for a tight coupling between water availability and CGR11. Here, we use a record of global atmospheric CO2, terrestrial water storage and precipitation data to investigate changes in the interannual relationship between tropical land climate conditions and CGR under a changing climate. We find that the interannual relationship between tropical water availability and CGR became increasingly negative during 1989-2018 compared to 1960-1989. This could be related to spatiotemporal changes in tropical water availability anomalies driven by shifts in El Niño/Southern Oscillation teleconnections, including declining spatial compensatory water effects9. We also demonstrate that most state-of-the-art coupled Earth System and Land Surface models do not reproduce the intensifying water-carbon coupling. Our results indicate that tropical water availability is increasingly controlling the interannual variability of the terrestrial carbon cycle and modulating tropical terrestrial carbon-climate feedbacks.

Improvement of the Irrigation Scheme in the ORCHIDEE Land Surface Model and Impacts of Irrigation on Regional Water Budgets Over China

In China, irrigation is widespread in 40.7% cropland to sustain crop yields. By its action on water cycle, irrigation affects water resources and local climate. In this study, a new irrigation module, including flood and paddy irrigation technologies, was developed in the ORCHIDEE-CROP land surface model which describes crop phenology and growth in order to estimate irrigation demands over China from 1982 to 2014. Three simulations were performed including NI (no irrigation), IR (with irrigation limited by local water resources), and FI (with irrigation demand fulfilled). Observations and census data were used to validate the simulations. Results showed that the estimated irrigation water withdrawal ( W ) based on IR and FI scenarios bracket statistical W with fair spatial agreements ( r = 0 . 68 ± 0 . 07 ; p < 0 . 01 ). Improving irrigation efficiency was found to be the dominant factor leading to the observed W decrease. By comparing simulated total water storage (TWS) with GRACE observations, we found that simulated TWS with irrigation well explained the TWS variation over China. However, our simulation overestimated the seasonality of TWS in the Yangtze River Basin due to ignoring regulation of artificial reservoirs. The observed TWS decrease in the Yellow River Basin caused by groundwater depletion was not totally captured in our simulation, but it can be inferred by combining simulated TWS with census data. Moreover, we demonstrated that land use change tended to drive W locally but had little effect on total W over China due to water resources limitation.

Soil carbon sequestration or biofuel production: new land-use opportunities for mitigating climate over abandoned Soviet farmlands

Although the CO(2) mitigation potential of biofuels has been studied by extrapolation of small-scale studies, few estimates exist of the net regional-scale carbon balance implications of biofuel cultivations programs, either growing conventional biofuel crops or applying new advanced technologies. Here we used a spatially distributed process-driven model over the 20 Mha of recently abandoned agricultural lands of the Former Soviet Union to quantify the GHG mitigation by biofuel production from Low Input/High Diversity (LIHD) grass-legume prairies and to compare this GHG mitigation with the one of soil C sequestration as it currently occurs. LIHD has recently received a lot of attention as an emerging opportunity to produce biofuels over marginal lands leading to a good energy efficiency with minimal adverse consequences on food security and ecosystem services. We found that, depending on the time horizon over which one seeks to maximize the GHG benefit, the optimal time for implementing biofuel production shifts from "never" (short-term horizon) to "as soon as possible" (longer-term horizon). These results highlight the importance of reaching agreement a priori on the target time interval during which biofuels are expected to play a role within the global energy system, to avoid deploying biofuel technology over a time interval for which it has a detrimental impact on the GHG mitigation objective. The window of opportunity for growing LIHD also stresses the need to reduce uncertainties in soil C inputs, turnover, and soil organic matter stability under current and future climate and management practices.

Increasing riverine export of dissolved organic carbon from China

River transport of dissolved organic carbon (DOC) to the ocean is a crucial but poorly quantified regional carbon cycle component. Large uncertainties remaining on the riverine DOC export from China, as well as its trend and drivers of change, have challenged the reconciliation between atmosphere-based and land-based estimates of China's land carbon sink. Here, we harmonized a large database of riverine in-situ measurements and applied a random forest model, to quantify riverine DOC fluxes (FDOC ) and DOC concentrations (CDOC ) in rivers across China. This study proposes the first DOC modeling effort capable of reproducing well the magnitude of riverine CDOC and FDOC , as well as its trends, on a monthly scale and with a much wider spatial distribution over China compared to previous studies that mainly focused on annual-scale estimates and large rivers. Results show that over the period 2001-2015, the average CDOC was 2.25 ± 0.45 mg/L and average FDOC was 4.04 ± 1.02 Tg/year. Simultaneously, we found a significant increase in FDOC (+0.044 Tg/year2 , p = .01), but little change in CDOC (-0.001 mg/L/year, p > .10). Although the trend in CDOC is not significant at the country scale, it is significantly increasing in the Yangtze River Basin and Huaihe River Basin (0.005 and 0.013 mg/L/year, p < .05) while significantly decreasing in the Yellow River Basin and Southwest Rivers Basin (-0.043 and -0.014 mg/L/year, p = .01). Changes in hydrology, play a stronger role than direct impacts of anthropogenic activities in determining the spatio-temporal variability of FDOC and CDOC across China. However, and in contrast with other basins, the significant increase in CDOC in the Yangtze River Basin and Huaihe River Basin is attributable to direct anthropogenic activities. Given the dominance of hydrology in driving FDOC , the increase in FDOC is likely to continue under the projected increase in river discharge over China resulting from a future wetter climate.

Paris Agreement requires substantial, broad, and sustained policy efforts beyond COVID-19 public stimulus packages

It has been claimed that COVID-19 public stimulus packages could be sufficient to meet the short-term energy investment needs to leverage a shift toward a pathway consistent with the 1.5 °C target of the Paris Agreement. Here, we provide complementary perspectives to reiterate that substantial, broad, and sustained policy efforts beyond stimulus packages will be needed for achieving the Paris Agreement long-term targets. Low-carbon investments will need to scale up and persist over the next several decades following short-term stimulus packages. The required total energy investments in the real world can be larger than the currently available estimates from integrated assessment models (IAMs). Existing databases from IAMs are not sufficient for analyzing the effect of public spending on emission reduction. To inform what role COVID-19 stimulus packages and public investments may play for reaching the Paris Agreement targets, explicit modelling of such policies is required.

Respiratory loss during late-growing season determines the net carbon dioxide sink in northern permafrost regions

Warming of northern high latitude regions (NHL, > 50 °N) has increased both photosynthesis and respiration which results in considerable uncertainty regarding the net carbon dioxide (CO₂) balance of NHL ecosystems. Using estimates constrained from atmospheric observations from 1980 to 2017, we find that the increasing trends of net CO₂ uptake in the early-growing season are of similar magnitude across the tree cover gradient in the NHL. However, the trend of respiratory CO₂ loss during late-growing season increases significantly with increasing tree cover, offsetting a larger fraction of photosynthetic CO₂ uptake, and thus resulting in a slower rate of increasing annual net CO₂ uptake in areas with higher tree cover, especially in central and southern boreal forest regions. The magnitude of this seasonal compensation effect explains the difference in net CO₂ uptake trends along the NHL vegetation- permafrost gradient. Such seasonal compensation dynamics are not captured by dynamic global vegetation models, which simulate weaker respiration control on carbon exchange during the late-growing season, and thus calls into question projections of increasing net CO₂ uptake as high latitude ecosystems respond to warming climate conditions.

The northern high latitude permafrost region has been an important contributor to the carbon sink since the 1980s. A new study finds that as tree cover increases, respiratory CO2 loss during late-growing season offsets photosynthetic CO2 uptake and leads to a slower rate of increasing annual net CO2 uptake.

Atmospheric phosphorus deposition amplifies carbon sinks in simulations of a tropical forest in Central Africa

Spatial redistribution of nutrients by atmospheric transport and deposition could theoretically act as a continental-scale mechanism which counteracts declines in soil fertility caused by nutrient lock-up in accumulating biomass in tropical forests in Central Africa. However, to what extent it affects carbon sinks in forests remains elusive. Here we use a terrestrial biosphere model to quantify the impact of changes in atmospheric nitrogen and phosphorus deposition on plant nutrition and biomass carbon sink at a typical lowland forest site in Central Africa. We find that the increase in nutrient deposition since the 1980s could have contributed to the carbon sink over the past four decades up to an extent which is similar to that from the combined effects of increasing atmospheric carbon dioxide and climate change. Furthermore, we find that the modelled carbon sink responds to changes in phosphorus deposition, but less so to nitrogen deposition. The pronounced response of ecosystem productivity to changes in nutrient deposition illustrates a potential mechanism that could control carbon sinks in Central Africa. Monitoring the quantity and quality of nutrient deposition is needed in this region, given the changes in nutrient deposition due to human land use.