Carbon Budget Estimates Research Articles

Lateral carbon fluxes and CO2 evasion from a subtropical mangrove-seagrass-coral continuum

Mangrove, seagrass, and coral habitats often lie adjacent to each other in the tropics and subtropics. Lateral carbon fluxes and their consecutive effects on CO2 dynamics and air–water fluxes along the ecosystem continuum are often overlooked. We measured the partial pressure of CO2 in water and associated biogeochemical parameters with a high temporal resolution and estimated air–water CO2 fluxes along the ecosystem continuum. Their lateral fluxes were estimated by using a biogeochemical mass-balance model. The results showed that the waters surrounding mangrove, seagrass, and coral habitats acted as a strong, moderate, and weak source of atmospheric CO2, respectively. The mangrove zone acted as a net source for TAlk, DIC, and DOC, but as a net sink for POC. The contribution of riverine and mangrove-derived OM was substantially high in mangrove sediment, indicating that net transport of POC towards the coastal sea was suppressed by the sediment trapping function of mangroves. The seagrass zone acted as a net source of all carbon forms and TAlk, whereas the coral zone acted as a net sink of TAlk, DIC, and DOC. The lateral transport of carbon from mangroves and rivers offset atmospheric CO2 uptake in the seagrass zone. DOC degradation might increase DIC, and other biogeochemical processes facilitate the functioning of the coral zone as a DOC sink. However, as a result of DIC uptake by autotrophs, mainly in the coral zone, the whole ecosystem continuum was a net sink of DIC and atmospheric CO2 evasion was lowered. We conclude that lateral transport of riverine and mangrove-derived DIC, TAlk, and DOC affect CO2 dynamics and air–water fluxes in seagrass and coral ecosystems. Thus, studies of lateral carbon fluxes at local and regional scales can improve global carbon budget estimates.

Dynamics of water-stable aggregates associated organic carbon assessed from delta C-13 changes following temperate natural forest development in China

In the context of global climate change, the preservation of soil productivity and the estimation of carbon budgets and cycles, the quantification of changes in carbon has important significance. In this study, we investigated the dynamics of soil aggregate associated organic carbon (OC) following temperate natural forest development in China. The objectives of this study were to examine the variation of soil aggregate associated OC decomposition rates, quantify the changes in the proportion of new and old soil aggregate OC, and explore the effects of controlling factors on SOC stocks, rate of total SOC increase and decomposition rate constants. The results showed that soil aggregate associated OC sequestration increased in 0−10 cm soil depth, while decreased in 10−30 cm soil depth. However, rate of aggregate associated OC increase, decomposition rate constants, and proportion of new OC increased at the early stage and then decreased along with the natural vegetation restoration. In addition, land use change had an important effect on soil aggregate associated OC dynamics, and soil particles, BD, MWD, C: N, plant diversity also played an important role. Moreover, SOC stocks had a negative relationship with clay and silt, while had a positive relationship with MWD and sandy soils. decomposition rate constants had a negative relationship with plant diversity, silt, and sand, while had a positive relationship with C: N and MWD. The proportions of new SOC had significant positive relationships with C: N, and it had a negative relationship with clay and silt. Therefore, it is necessary to clarify the formation mechanism of soil particles and aggregates, improve plant biodiversity, regulate the soil C: N ratio, and improve soil particle structure to increase soil carbon sequestration.

Trophic sources and linkages to support mesozooplankton community in the Kuroshio of the East China Sea

AbstractMany migratory fishes reproduce and recruit around the Kuroshio, and their survival of early life stages is supported by mesozooplankton. Mesozooplankton standing stocks and productivity equivalent to those on the continental shelf have been found in the Kuroshio; however, there is limited information on trophic sources and linkages to support the mesozooplankton community. Here, we evaluate mesozooplankton feeding on protists and their trophodynamics importance by removal bottle experiments in the Kuroshio of the East China (ECS‐Kuroshio). Pico‐ and nano‐autotrophs dominated chlorophyll a concentrations throughout the study sites across the continental shelf, within the Kuroshio path and in adjacent waters. Calanoid and poecilostomatoid copepods comprised more than 85% of mesozooplankton biomass. Significant mesozooplankton ingestion rates were found for nano‐autotrophs based on size‐fractionated chlorophyll; for haptophytes, chrysophytes, chlorophytes, and diatoms from pigment‐based phytoplankton analysis; and for naked ciliates in the microzooplankton. Based on the estimates of individual carbon budgets, nano‐autotrophs and naked ciliates ingested by mesozooplankton composed 39% of their food requirements, suggesting other available prey like nano‐heterotrophs. These results imply that mesozooplankton ingestion in the ECS‐Kuroshio has great impacts on protozoan and phytoplankton communities and their major trophic pathways are from nano‐sized auto‐ and heterotrophs and ciliates to copepods.

Tissue type and location within forest together regulate decay trajectories of Abies faxoniana logs at early and mid-decay stage

Deadwood decomposition plays a crucial role in global carbon and nutrient cycles. Factors controlling deadwood decomposition at local scales could also have strong effects at broader scales. We tested how trait variation within stems (i.e. tissue types) and forest habitat heterogeneity (i.e. location within forest) together influence the deadwood decay trajectory and decay rate. We conducted an in situ decomposition experiment of Abies faxoniana logs in an alpine forest on the eastern Qinghai-Tibetan Plateau, decomposing logs from a series of decay classes I-III (on a 5-class scale) for five years on the forest floor in canopy gap, gap edge and under closed canopy (each sized 25 ± 3 × 25 ± 3 m). We found strong differences in density and chemical composition between tissue types at least across decay classes I-III, which revealed the distinct contribution of each tissue type to carbon and nutrient cycling. There were remarkable interactions of tissue types and locations within forest. We found bark always decomposed faster than wood, while heartwood can decompose faster than sapwood in canopy edge and canopy gap. Locations within forest influenced the best fit decay model and decay rate of bark and sapwood in the same way, while it had no corresponding effects for heartwood decay dynamics. The largest difference in T0.25 and T0.4 (time to 25% and 40% mass loss) between locations were 1.52 and 3.21 (bark), 19.41 and 37.61 (wood overall), 31.82 and 60.15 (sapwood), and 12.86 and 22.84 (heartwood), respectively. We also found that pH was significantly negatively related with sapwood and heartwood mass loss, demonstrating that pH can potentially be applied to evaluate sapwood and heartwood mass loss when density correction is difficult to achieve at least at early to mid-decay stages. However, whether pH is a powerful predictor of decomposition trajectory across more species and biomes remains to be tested. We strongly recommend that further model predictions of coarse log decay include radial positions within stem and locations within forest as factors to increase the reliability of carbon budget estimates.

Empirical estimates of regional carbon budgets imply reduced global soil heterotrophic respiration

Resolving regional carbon budgets is critical for informing land-based mitigation policy. For nine regions covering nearly the whole globe, we collected inventory estimates of carbon-stock changes complemented by satellite estimates of biomass changes where inventory data are missing. The net land–atmospheric carbon exchange (NEE) was calculated by taking the sum of the carbon-stock change and lateral carbon fluxes from crop and wood trade, and riverine-carbon export to the ocean. Summing up NEE from all regions, we obtained a global ‘bottom-up’ NEE for net land anthropogenic CO2 uptake of –2.2 ± 0.6 PgC yr−1 consistent with the independent top-down NEE from the global atmospheric carbon budget during 2000–2009. This estimate is so far the most comprehensive global bottom-up carbon budget accounting, which set up an important milestone for global carbon-cycle studies. By decomposing NEE into component fluxes, we found that global soil heterotrophic respiration amounts to a source of CO2 of 39 PgC yr−1 with an interquartile of 33–46 PgC yr−1—a much smaller portion of net primary productivity than previously reported.

Quantifying process-level uncertainty contributions to TCRE and carbon budgets for meeting Paris Agreement climate targets

To achieve the goals of the Paris Agreement requires deep and rapid reductions in anthropogenic CO2 emissions, but uncertainty surrounds the magnitude and depth of reductions. Earth system models provide a means to quantify the link from emissions to global climate change. Using the concept of TCRE—the transient climate response to cumulative carbon emissions—we can estimate the remaining carbon budget to achieve 1.5 or 2 °C. But the uncertainty is large, and this hinders the usefulness of the concept. Uncertainty in carbon budgets associated with a given global temperature rise is determined by the physical Earth system, and therefore Earth system modelling has a clear and high priority remit to address and reduce this uncertainty. Here we explore multi-model carbon cycle simulations across three generations of Earth system models to quantitatively assess the sources of uncertainty which propagate through to TCRE. Our analysis brings new insights which will allow us to determine how we can better direct our research priorities in order to reduce this uncertainty. We emphasise that uses of carbon budget estimates must bear in mind the uncertainty stemming from the biogeophysical Earth system, and we recommend specific areas where the carbon cycle research community needs to re-focus activity in order to try to reduce this uncertainty. We conclude that we should revise focus from the climate feedback on the carbon cycle to place more emphasis on CO2 as the main driver of carbon sinks and their long-term behaviour. Our proposed framework will enable multiple constraints on components of the carbon cycle to propagate to constraints on remaining carbon budgets.

Influence of sun zenith angle on canopy clumping and the resulting impacts on photosynthesis

Addressing the impact of vegetation architecture on shortwave radiation transfer in land surface models is important for accurate weather forecasting, carbon budget estimates, and climate predictions. This paper investigates to what extent it is possible to retrieve structural parameters of two different parameterization schemes from direct transmittance derived from digital hemispherical photography and 3D radiative transfer modeling for two study sites with different vegetation canopy architectures. Neglecting the representation of 3D canopy structure in radiative transfer schemes leads to significant errors in shortwave radiation partitioning (up to 3.5 times more direct transmittance in the 3D model). Structural parameters, referred to as whole canopy ‘clumping indices’, were obtained in order to evaluate the impact of angular variation in clumping on shortwave radiation transfer. Impacts on photosynthesis were evaluated at site level with the UKESM land surface model, JULES. A comparison between flux tower derived and modeled photosynthesis indicates that considering zenith angular variations of structural parameters in the radiative transfer scheme of the UKESM land surface model significantly improves photosynthesis prediction in light limited ecosystems (from RMSE = 2.91 μmol CO2.m− 2.s − 1 to RMSE = 1.51 μmol CO2.m − 2.s − 1, 48% smaller), typically with enhanced photosynthesis from bottom layers.

Non-CO2 forcing changes will likely decrease the remaining carbon budget for 1.5\u2009\xb0C

One key contribution to the wide range of 1.5 °C carbon budgets among recent studies is the non-CO2 climate forcing scenario uncertainty. Based on a partitioning of historical non-CO2 forcing, we show that currently there is a net negative non-CO2 forcing from fossil fuel combustion (FFC), and a net positive non-CO2 climate forcing from land-use change (LUC) and agricultural activities. We perform a set of future simulations in which we prescribed a 1.5 °C temperature stabilisation trajectory, and diagnosed the resulting 1.5 °C carbon budgets. Using the historical partitioning, we then prescribed adjusted non-CO2 forcing scenarios consistent with our model’s simulated decrease in FFC CO2 emissions. We compared the diagnosed carbon budgets from these adjusted scenarios to those resulting from the default RCP scenario’s non-CO2 forcing, and to a scenario in which proportionality between future CO2 and non-CO2 forcing is assumed. We find a wide range of carbon budget estimates across scenarios, with the largest budget emerging from the scenario with assumed proportionality of CO2 and non-CO2 forcing. Furthermore, our adjusted-RCP scenarios produce carbon budgets that are smaller than the corresponding default RCP scenarios. Our results suggest that ambitious mitigation scenarios will likely be characterised by an increasing contribution of non-CO2 forcing, and that an assumption of continued proportionality between CO2 and non-CO2 forcing would lead to an overestimate of the remaining carbon budget. Maintaining such proportionality under ambitious fossil fuel mitigation would require mitigation of non-CO2 emissions at a rate that is substantially faster than found in the standard RCP scenarios.

A review of soil carbon dynamics resulting from agricultural practices

Literature related to the carbon cycle and climate contains contradictory results with regard to whether agricultural practices increase or mitigate emission of greenhouse gases (GHGs). One opinion is that anthropogenic activities have distinct carbon footprints – measured as total emissions of GHGs resulting from an activity, in this case, “agricultural operations”. In contrast, it is argued that agriculture potentially serves to mitigate GHGs emissions when the best management practices are implemented. We review the literature on agricultural carbon footprints in the context of agricultural practices including soil, water and nutrient management. It has been reported that the management practices that enhance soil organic carbon (SOC) in arid and semi-arid areas include conversion of conventional tillage practices to conservation tillage approaches. We found that agricultural management in arid and semi-arid regions, which have specific characteristics related to high temperatures and low rainfall conditions, requires different practices for maintenance and restoration of SOC and for control of soil erosion compared to those used in Mediterranean, tropical regions. We recommend that in order to meet the global climate targets, quantification of net global warming potential of agricultural practices requires precise estimates of local, regional and global carbon budgets. We have conducted and present a case study for observing the development of deep soil carbon profile resulting from a 10-year wheat-cotton and wheat-maize rotation on semi-arid lands. Results showed that no tillage with mulch application had 14% (37.2 vs 43.3 Mg ha−1) higher SOC stocks in comparison to conventional tillage with mulch application. By implementing no tillage in conjunction with mulch application, lower carbon losses from soil can mitigate the risks associated with global warming. Therefore, it is necessary to reconsider agricultural practices and soil erosion after a land-use change when calculating global carbon footprints.

Glomalin-related soil protein enriched in δ13C and δ15N excels at storing blue carbon in mangrove wetlands

Glomalin-related soil protein (GRSP) derived from arbuscular mycorrhizal fungi can be transported from land to sea and captured in mangrove wetlands, thereby contributing to soil C and N pools. However, the stable isotope signatures of GRSP and the key influencing factors that affect its isotope values in coastal wetlands remain unknown. In this study, the results showed that total-GRSP (T-GRSP) was a significant contributor of C and N content to mangrove soil. We first compared stable isotope (δ13C and δ15N) values and C/N ratios of GRSP with those of other blue carbon sources in a typical mangrove wetland. The isotope fingerprints of T-GRSP, mangrove soils, mangrove plants, and tidal waters were identified. Unlike those of the conventional sources, the δ13C and δ15N values of T-GRSP were −25.04‰ to −22.83‰ and 3.22‰ to 7.24‰, respectively, and the mean C/N ratio was 12.95 in the mangrove cover sites. These findings indicated that T-GRSP is a novel blue carbon source mainly originating from terrestrial ecosystems. Moreover, the δ13C and δ15N values of T-GRSP in mangrove wetlands were affected by vegetation interception and soil properties. Redundancy analysis results indicated that pH, moisture, depth, and salinity were key factors influencing the T-GRSP isotope fingerprints in mangrove wetlands. Additionally, the simultaneous changes in T-GRSP content, isotope values, and C/N ratios among mangrove cover sites, a mudflat, and tidal waters suggested that this protein is a sensitive tracer between land and sea. Overall, the isotope signatures of GRSP captured by mangroves were identified for the first time, which will have important implications for the estimation of the blue carbon budget and identification of the blue carbon sources in global coastal regions.

Incorporating climate effects in Larix gmelinii improves stem taper models in the Greater Khingan Mountains of Inner Mongolia, northeast China

Estimating timber volume and carbon stock in forests is fundamental for silviculture and for accurate estimation of national and global carbon budgets. Taper models are important tools for predicting diameter at any height along a tree bole. Mean annual temperature (MAT) and mean annual precipitation (MAP) influence tree growth, but their precise effects on stem shape are still poorly understood and climatic factors are seldom included in taper models. To evaluate the effect of climate on tree stems, we incorporated MAT and MAP as covariates in the Kozak (2004) model to improve model performance in goodness-of-fit. The Kozak (2004) model with the incorporation of MAT and MAP was refitted using nonlinear mixed-effects (NLME) modeling techniques to account for within-sample tree heteroscedasticity and autocorrelation structure in residuals from data measured at different points along the same individual tree stem of Larix gmelinii (Rupr.). Results showed that the predictive accuracy of the Kozak (2004) model was improved by incorporating MAT and MAP as covariates. The Kozak (2004) model incorporating both MAT and MAP had the highest prediction accuracy for stem diameter, closely followed by the model incorporating only MAT and then the model incorporating only MAP. MAT effect on tree stem shape was stronger than that of MAP. The NLME Kozak (2004) model incorporating MAT and MAP with exponential variance function and first-order continuous autoregressive correlation structure (CAR(1) model) removed the heteroscedasticity and autocorrelation in the residuals, had the best prediction performance. Therefore, such refined model is recommended for planning and management of natural L. gmelinii forests. In conclusion, incorporating the effect of climate variables in stem taper equations could significantly improve timber volume and biomass estimations, particularly in harsh environments, such as natural boreal forests.

Gap-filling continuously-measured soil respiration data: A highlight of time-series-based methods

Soil respiration is an important ecosystem process that releases carbon dioxide into the atmosphere. While soil respiration can be measured continuously at high temporal resolutions, gaps in the dataset are inevitable, leading to uncertainties in carbon budget estimations. Therefore, robust methods used to fill the gaps are needed. The process-based non-linear least squares (NLS) regression is the most widely used gap-filling method, which utilizes the established relationship between the soil respiration and temperature. In addition to NLS, we also implemented three other methods based on: 1) artificial neural networks (ANN), driven by temperature and moisture measurements, 2) singular spectrum analysis (SSA), relying only on the time series itself, and 3) the expectation-maximization (EM) approach, referencing to parallel flux measurements in the spatial vicinity. Six soil respiration datasets (2017–2019) from two boreal forests were used for benchmarking. Artificial gaps were randomly introduced into the datasets and then filled using the four methods. The time-series-based methods, SSA and EM, showed higher accuracies than NLS and ANN in small gaps (<1 day). In larger gaps (15 days), the performance was similar among NLS, SSA and EM; however, ANN showed large errors in gaps that coincided with precipitation events. Compared to the observations, gap-filled data by SSA showed similar degree of variances and those filled by EM were associated with similar first-order autocorrelation coefficients. In contrast, data filled by both NLS and ANN exhibited lower variance and higher autocorrelation than the observations. For estimations of the annual soil respiration budget, NLS, SSA and EM resulted in errors between −3.7% and 5.8% given the budgets ranged from 463 to 1152 g C m−2 year−1, while ANN exhibited larger errors from −11.3 to 16.0%. Our study highlights the two time-series-based methods which showed great potential in gap-filling carbon flux data, especially when environmental variables are unavailable.

Generating Spatially Robust Carbon Budgets From Flux Tower Observations

AbstractEstimating global terrestrial productivity is typically achieved by rescaling individual flux tower measurements, traditionally assumed to represent homogeneous areas, using gridded remote sensing and climate data. Using 154 locations from the FLUXNET2015 database, we demonstrate that variations in spatial homogeneity and nonuniform sampling patterns introduce variability in carbon budget estimates that propagate to the biome scale. We propose a practical solution to quantify the variability of vegetation characteristics and uniformity of sampling patterns and, moreover, account for contributions of sampling variations over heterogeneous surfaces to carbon budgets from flux towers. Our proposed space‐time‐equitable budgets reduce uncertainty related to heterogeneities, allow for more accurate attribution of physiological variations in productivity trends, and provide more representative grid cell averages for linking fluxes with gridded data products.

Impact of disturbance on vegetation, biomass and carbon stock in tropical forests of Tripura, Northeast India

In this study, the impact of anthropogenic disturbances on vegetation, soil characteristics, biomass and carbon stock was studied in tropical mixed deciduous forests of Tripura, North-east India. The forests stands were selected based on the presumed disturbance index and categorized in three distinct categories viz. Least Disturbed Forests (LDF), Moderately Disturbed Forests (MDF) and Highly Disturbed Forests (HDF). The study revealed that species diversity is much higher in LDF followed by MDF and HDF sites. Few species like Anogeissus accuminata, Lannea coromandelica, Schima wallichii, and Syzygium cumini are common in all the three categories of forests. The Shannon–Wiener diversity index ranged from 1.32 to 2.51 in all the stands. The phytosociological parameters varied along the disturbance gradient in different stands. The maximum tree density was 198.57 trees ha−1 in LDF, 176.67 trees ha−1 in MDF and least in HDF (111.67 trees ha−1). Soil Organic Carbon (SOC %) recorded maximum in LDF (1.41–1.67%) and minimum in HDF (0.91–1.36%). Tree biomass showed a significant relation with soil organic carbon stock (r = 0.998, p < 0.05). Furthermore, the present study suggests the need for quantification of forest disturbance and biomass which will improve carbon budget estimates and lead to better parameterization of forest carbon cycle models.

Land use conversion influences soil respiration across a desert-oasis ecoregion in Northwest China, with consideration of cold season CO2 efflux and its significance

Quantifying annual soil CO2 emissions and the effects of physical and geochemical factors on soil CO2 efflux will improve the carbon budget estimates, as well as enhance predictions of how soil CO2 emission will response to climate change in arid areas. To data, variability in soil respiration rates caused by land use conversion in the desert-oasis ecoregion of Northwest China remains poorly characterized, especially the contribution of cold season (November-February) CO2 emission. Soil respiration was measured in a Haloxylon ammodendron desert shrubland, a Zea mays cropland, a Populus gansuensis forest, and a Tamarix chinensis Lour wetland using a LI-COR 8100 Soil Respiration Observation System from April 2016 to March 2019. Annual soil CO2 emissions totaled 176, 778, 918, and 397 g C m−2 in the desert shrubland, cropland, forest, and wetland, respectively. The ratio of cold season CO2 emissions to the annual varied from 6 to 15% across ecosystems. Therefore, ignoring cold season CO2 emissions would lead to underestimates of carbon losses in the desert-oasis ecoregion. The soil respiration rate at 10 °C was influenced by soil organic carbon content in all four ecosystems. In the cropland and forest, soil respiration rate was affected by the interaction of soil moisture and soil temperature, while in the wetland and desert shrubland, soil respiration was sensitive to a single factor, soil temperature. Land use conversion induced differences in organic matter accumulation, soil temperature, and soil moisture, and as a consequence, produced variability in soil respiration rates across the desert-oasis ecoregion.

Estimation of Global Grassland Net Ecosystem Carbon Exchange Using a Model Tree Ensemble Approach

AbstractUnderstanding the net ecosystem CO2 exchange (NEE) between terrestrial ecosystems and the atmosphere is crucial for accurate estimation of carbon budgets, which remains unclear for grassland ecosystems. Here we upscaled site‐level NEE from 44 grassland flux towers (1,457 site‐months) to the global scale by using a model tree ensemble approach that considers the management activities (grazing and cutting) (MTE‐GM). Cross‐validation showed that MTE‐GM performs reasonably well in terms of among‐site variability and seasonal variation, with a Nash‐Sutcliffe efficiency of 0.90 and 0.86 and an R2 of 0.91 and 0.86, respectively. Radiation (shortwave and longwave), temperature, leaf area index, and fraction of absorbed photosynthetic active radiation had the highest relative explanatory power in predicting NEE. Based on MTE‐GM, mean annual NEE of global grassland was 72 ± 4 g C m−2 year−1 (1.9 ± 0.11 Pg C year−1) during 1982–2011, suggesting that the grassland ecosystems have been acting as a small carbon source during the past three decades. However, grasslands in temperate and continental regions had the largest carbon sink of −61.9 ± 5.7 and −51.8 ± 7.9 g C m−2 year−1, respectively. Moreover, we found that elimination of grassland management effect resulted in an extra emission of 1.7% CO2 to the atmosphere (CO2 sink from the management is 0.03 Pg C year−1). From the 1980s to the 2000s, 38% (22%) and 17% (18%) of pixels showed an increased (decreased) carbon uptake and decreased (increased) carbon release, respectively. Uncertainty assessment suggested that there would be higher confidence in NEE estimates in most parts of middle‐ to high‐latitude regions in the Northern Hemisphere.

Environmental influences on light response parameters of net carbon exchange in two rotation croplands on the North China Plain

The ecosystem light response parameters, i.e. apparent quantum yield (α), maximum rate of ecosystem gross photosynthesis (Amax), and daytime ecosystem respiration (Rd), are very important when estimating regional carbon budgets. But they are not well understood in double cropping systems. Here, continuous flux data were collected from two rotation croplands in Yucheng (YC) and in Luancheng (LC) to describe the among-year variations in α, Amax, and Rd, and to investigate variation mechanism on an annual scale. The three parameters exhibited marked fluctuations during the observation years. The annual α, Amax, and Rd ranged from 0.0022–0.0059 mg CO2 μmol photon−1, from 2.33–4.43 mg CO2 m−2 s−1, and from 0.19–0.47 mg CO2 m−2 s−1 at YC, and from 0.0016–0.0021 mg CO2 μmol photon−1, from 3.00–6.30 mg CO2 m−2 s−1, and from 0.06–0.19 mg CO2 m−2 s−1 at LC, respectively. Annual α and Rd declined significantly when vapor pressure deficit (VPD) exceeded 1.05 kPa and increased significantly when canopy conductance (gc) exceed 6.33 mm/s at YC, but changed slightly when VPD and gc exceeded 1.16 kPa and 7.77 mm/s at LC, respectively. The fact that the negative effects of VPD and gc on α and Rd at LC were not as significant as they were at YC may be attributed to different climate conditions and planting species. A negative relationship (R2 = 0.90 for YC and 0.89 for LC) existed between VPD and gc. Therefore, the VPD, through its negative effect on gc, inhibited α and Rd indirectly. Among-year Amax variation was mainly influenced by the annual mean surface soil temperature (Ts) of non-growing season of wheat significantly (R2 = 0.59, P < 0.01). Therefore, in future climate change scenarios, these environmental effects need to be included in carbon cycle models so that the accuracy of the carbon budget estimation can be improved.

Recommended temperature metrics for carbon budget estimates, model evaluation and climate policy

Recent estimates of the amount of carbon dioxide that can still be emitted while achieving the Paris Agreement temperature goals are larger than previously thought. One potential reason for these larger estimates may be the different temperature metrics used to estimate the observed global mean warming for the historical period, as they affect the size of the remaining carbon budget. Here we explain the reasons behind these remaining carbon budget increases, and discuss how methodological choices of the global mean temperature metric and the reference period influence estimates of the remaining carbon budget. We argue that the choice of the temperature metric should depend on the domain of application. For scientific estimates of total or remaining carbon budgets, globally averaged surface air temperature estimates should be used consistently for the past and the future. However, when used to inform the achievement of the Paris Agreement goal, a temperature metric consistent with the science that was underlying and directly informed the Paris Agreement should be applied. The resulting remaining carbon budgets should be calculated using the appropriate metric or adjusted to reflect these differences among temperature metrics. Transparency and understanding of the implications of such choices are crucial to providing useful information that can bridge the science–policy gap. Different methods for determining global mean temperature change are preferable for different purposes, such as estimating carbon budgets versus consistency with the achievement of the Paris Agreement, argues a Perspective that outlines methodological choices and recommends decision pathways.

Soil organic carbon stock in different urban land uses: high stock evidence in urban parks

Urban areas are major producers of atmospheric CO2 emissions, but at the same time they can offset some of the associated C losses by retaining stable organic carbon in their soils (SOC). Despite the importance of urban SOC there are still many uncertainties associated, resulting in low accuracy of SOC stock estimations or in its neglection in the regional and national carbon budgets. We focused on one of the most extended urban areas of Italy (Milan) estimating SOC stock in the topsoil and comparing it for different urban land uses (park/non-park) and covers (woodland/grassland). We also compared urban SOC stocks with other typologies of natural and semi-natural land use in the region. We found generally high variability in urban soil properties. Average SOC of urban parks was higher (7.9 ± 2.4 kg m−2) than urban non-parks (5.3 ± 2.5 kg m−2); while SOC stock did not significantly differ for urban land cover types. Urban parks had SOC stock values comparable with forest, pasture and grasslands of the same region and higher than SOC of croplands. At the same time, urban non-parks had the lower SOC stocks values found in the region. The results highlighted the significant contribution of urban SOC stock to carbon budget estimations and differences based on urban land use types. Furthermore, we described the main pedological characteristics of investigated urban soils and we identified the factors that contribute to limiting our capacity to model urban SOC stock that can be partially overcome by the addressed strategies.

A 3-Year In-Situ Measurement of CO2 Efflux in Coastal Wetlands: Understanding Carbon Loss through Ecosystem Respiration and its Partitioning

Understanding the link between ecosystem respiration (Reco) and its influential factors is necessary to evaluate the sources of gaseous carbon loss in coastal wetlands. Seablite (Suaeda salsa Pall.) is the main vegetation type pioneering temperate coastal wetlands in northeast China, and is generally an understudied wetland type. To evaluate the influence of environmental factors on Reco, a multi-year in-situ experiment was carried out during the growing seasons of 2012 to 2014. Total CO2 efflux was measured and separated further into soil microbial and belowground root respiration (Rs + r) and plant respiration (Rplant). Reco displayed strong seasonal variation, with effluxes as high as 845 to 1150 mg CO2 m−2 h−1 during summer months and as low as 32 to 111 mg CO2 m−2 h−1 during spring (when new shoots are sprouting) and fall (when plants are senescing) months. Aboveground plant structures contributed on average 79% to total plant biomass, and accounted for most of the Reco measured; i.e., 62–96% was associated as Rplant. Plant activity was strongly seasonal, accordingly driving Reco, with 1 g of soil-emergent S. salsa biomass (dry weight) producing approximately 1.58 mg CO2 per hour toward Reco during mid-summer. When water level was below the soil surface, Rs + r was exponentially correlated to air temperature. Because Reco for S. salsa marsh in the Liaohe Delta is controlled by plant growth cycles, inundation regime, and air temperature, this finding may be applied for national carbon budget estimation purposes from S. salsa wetlands throughout Northeast China and potentially close a key gap in understanding the role of this large wetland area in contributing to respiratory CO2 emissions globally.