Response Of Carbon Cycle Research Articles

Asymmetry in the climate–carbon cycle response to positive and negative CO2 emissions

Asymmetry in the climate–carbon cycle response to positive and negative CO2 emissions

Recent vegetation browning and its drivers on Tianshan Mountain, Central Asia

The strong signal of vegetation increases since the 1980s is considered as reliable evidence of anthropogenic climate change. However, some studies have alerted us to the recent stalling or even reversal of vegetation greening. To determine whether vegetation browning exists on Tianshan Mountain, we investigated the changes in the Normalized Difference Vegetation Index (NDVI) based on long-term satellite-derived NDVI data series from 1982 to 2015. Although the trend of growing season NDVI was statistically significant throughout the study period (0.0006a−1, p < 0.01), two different periods with opposite trends were evident around 1998. The NDVI showed a significant increase before 1998 but a reversal after 1998, when vegetation browning began to appear. The strong correlation between the interannual variability of vegetation and growing season temperature only existed in wet years, indicating that vegetation on Tianshan Mountain is extremely vulnerable and sensitive to water deficits. Our results also suggest that relative to high vapor pressure deficit, soil moisture deficit played a greater role in the recent browning of vegetation on Tianshan Mountain. This study is of scientific value in understanding the response of vegetation growth and carbon cycling to environmental changes and predicting future developments.

Pulse Effect of Precipitation: Spatial Patterns and Mechanisms of Soil Carbon Emissions

The rapid and strong release of CO2 caused by precipitation (known as the pulse effect) is a common phenomenon that significantly affects ecosystem C cycling. However, the degree to which the pulse effect occurs overlarge regional scales remains unclear. In this study, we conducted continuous and high-frequency measurements of soil CO2 release rates (Rs) for 48 h after simulated precipitation, along a precipitation gradient of different grassland types (i.e., meadow, typical, and desert) in Inner Mongolia, China. Pulse effects were assessed using the maximum Rs (Rsoil–max) and accumulated CO2 emissions (ARs–soil). Strong precipitation pulse effects were found in all sites; however, the effects differed among grassland types. In addition, an apparent decrease in both Rsoil–max and ARs–soil was observed from the east to west, i.e., along the decreasing precipitation gradient. ARs–soil values followed the order: temperate meadow grassland (0.097 mg C g–1 soil) &amp;gt; typical temperate grassland (0.081 mg C g–1 soil) &amp;gt; temperate desert grassland (0.040 mg C g–1 soil). Furthermore, Rsoil–max and ARs–soil were significantly positively correlated with soil quality (SOC, POC, and N, etc.; P &amp;lt; 0.01). ARs–soil (P &amp;lt; 0.05) and ARs–SOC (P &amp;lt; 0.01) were significantly affected. ARs–soil and ARs–SOC were also positively correlated with soil microbial biomass significantly (P &amp;lt; 0.05). Rsoil–max and ARs–soil had similar spatial variations and controlling mechanisms. These results greatly support the substrate supply hypothesis for the effects of precipitation pulses, and provide valuable information for predicting CO2 emissions. Our findings also verified the significant effect of soil CO2 release from precipitation pulses on the grasslands of arid and semi-arid regions. Our data provide a scientific basis for model simulations to better predict the responses of ecosystem carbon cycles in arid and semi-arid regions under predicted climate change scenarios.

Effects of Earth system feedbacks on the potential mitigation of large-scale tropical forest restoration

Abstract. To achieve the Paris Agreement requires aggressive mitigation strategies alongside negative emission technologies. Recent studies suggest that increasing tree cover can make a substantial contribution to negative emissions, with the tropics being the most suitable region from a biogeophysical perspective. Yet these studies typically do not account for subsequent carbon cycle and climate responses to large-scale land-use change. Here we quantify the maximum potential temperature and CO2 benefits from pantropical forest restoration, including the Earth system response, using a fully coupled, emission-driven Earth system model (HadGEM2-ES). We perform an idealised experiment where all land use in the tropics is stopped and vegetation is allowed to recover, on top of an aggressive mitigation scenario (RCP2.6). We find that tropical restoration of 1529 Mha increases carbon stored in live biomass by 130 Pg C by 2100 CE. Whilst avoiding deforestation and tropical restoration in the tropics removes 42 Pg C compared to RCP2.6, the subsequent reduction in extratropical and ocean carbon uptake means that carbon in the atmosphere only reduces by 18 Pg C by 2100. The resulting small CO2 (9 ppm) benefit does not translate to a detectable reduction in global surface air temperature compared to the control experiment. The greatest carbon benefit is achieved 30–50 years after restoration before the Earth system response adjusts to the new land-use regime and declining fossil fuel use. Comparing our results with previous modelling studies, we identify two model-independent key points: (i) in a world where emission reductions follow the Paris Agreement, restoration is best deployed immediately, and (ii) the global carbon cycle response to reduced emissions limits the efficacy of negative emissions technologies by more than half. We conclude that forest restoration can reduce peak CO2 mid-century, but it can only modestly contribute to negative emissions.

Responses of soil carbon and nitrogen cycles to the physical influences of rock fragment in soils

Rock fragments (RFs, mineral particles with diameter > 2 mm) can substantially influence soil carbon (C) and nitrogen (N) cycles through different physical mechanisms. These physical mechanisms include changing soil hydraulic parameters (vSH) by reducing fine earth bulk density (vSHBD) and volume (vSHVo), and affecting soil C and N stocks (vCN) by reducing fine earth bulk density (vCNBD) and volume (vCNVo), and increasing fine earth C and N concentrations (vCNCo). In this study, based on soil and climate data in a typical hilly area of China, we construct scenarios by considering these physical mechanisms to investigate the responses of key soil C and N outputs (carbon dioxide or CO2, and nitrous oxide or N2O emissions, and N leaching) to RF content (RFC) in DNDC and DayCent models. Results showed that when considering vSH and vCN, parabolic relationships were observed between these soil C and N outputs and RFC, with maximum in RFC = 0.3–0.6 g g−1. The vCN dominated the responses of soil CO2 emission to RFC, while vSH exerted comparative contributions to the responses of soil N2O emission and N leaching. When only considering vSH, opposite contributions of vSHBD and vSHVo were observed in DNDC model, and contributions of vSHBD overwhelmed those of vSHVo. However, vSHVo dominated these responses in DayCent model. When only considering vCN, the vCNCo dominated these responses, though considerable superimposed influences of vCNBD and vCNVo appeared under high RFC. The discrepancies between these responses to RFC in DNDC and DayCent models might be due to the different model complexities in simulating soil hydrology, biogeochemistry, and the role of bulk density in these models. Relatively, more distinct responses were achieved in DNDC model. These findings can extend our understandings of RFs and soil C and N cycles.

Large‐Scale Reductions in Terrestrial Carbon Uptake Following Central Pacific El Niño

AbstractThe El Niño–Southern Oscillation (ENSO) affects global climate and ecosystems, but a recent shift toward more frequent central Pacific (CP) El Niño events could alter these relationships. Here, we show strong responses of the terrestrial carbon cycle to CP ENSO, exceeding even those to canonical eastern Pacific (EP) ENSO. Annual GPP of both global tropical forests and semiarid ecosystems were reduced by ∼0.3–0.5 Pg C yr−1 K−1 increase in CP sea surface temperatures (SSTs), which also reduced net ecosystem production of key tropical and semiarid regions like the Amazon and Australia, but with smaller (and generally not significant) responses to EP SSTs. Given these large negative responses of ecosystem production to CP SSTs, our results suggest that a recent shift toward CP‐dominated ENSO events could further alter Earth's terrestrial carbon cycle, especially when coupled with possible increases in ENSO amplitude with continued warming.

Compatible Fossil Fuel CO2 Emissions in the CMIP6 Earth System Models’ Historical and Shared Socioeconomic Pathway Experiments of the Twenty-First Century

AbstractWe present the compatible CO2 emissions from fossil fuel (FF) burning and industry, calculated from the historical and Shared Socioeconomic Pathway (SSP) experiments of nine Earth system models (ESMs) participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The multimodel mean FF emissions match the historical record well and are close to the data-based estimate of cumulative emissions (394 ± 59 GtC vs 400 ± 20 GtC, respectively). Only two models fall inside the observed uncertainty range; while two exceed the upper bound, five fall slightly below the lower bound, due primarily to the plateau in CO2 concentration in the 1940s. The ESMs’ diagnosed FF emission rates are consistent with those generated by the integrated assessment models (IAMs) from which the SSPs’ CO2 concentration pathways were constructed; the simpler IAMs’ emissions lie within the ESMs’ spread for seven of the eight SSP experiments, the other being only marginally lower, providing confidence in the relationship between the IAMs’ FF emission rates and concentration pathways. The ESMs require fossil fuel emissions to reduce to zero and subsequently become negative in SSP1-1.9, SSP1-2.6, SSP4-3.4, and SSP5-3.4over. We also present the ocean and land carbon cycle responses of the ESMs in the historical and SSP scenarios. The models’ ocean carbon cycle responses are in close agreement, but there is considerable spread in their land carbon cycle responses. Land-use and land-cover change emissions have a strong influence over the magnitude of diagnosed fossil fuel emissions, with the suggestion of an inverse relationship between the two.

Predicting gross primary productivity and PsnNet over a mixed ecosystem under tropical seasonal variability: a comparative study between different machine learning models and correlation-based statistical approaches

The global interaction of CO2 flux was highly dynamic under seasonal and inter-annual variability. Thus, precise estimation of gross primary productivity (GPP) and net photosynthesis (PsnNet) under seasonal variations was important to understand the global carbon cycle and ecosystem response to climate variability. Considering this significance, in our paper, we have conducted a comparative investigation of correlation (i.e., Pearson product, Spearman rank, and Kendall rank) and supervised machine learning models (i.e., random forest, conditional inference forests, and quantile regression forests) to explore the agreement and prediction of GPP and PsnNet under seasonal variability from spectral indices, tasseled cap transformations, and reflectances over a mixed ecosystem assembling moderate resolution imaging spectroradiometer and Landsat data. Associated uncertainties and errors have been also compared. Our study was carried out in a tropical moist ecosystem under pre-monsoon (March) and post-monsoon (October) conditions. Overall outcome revealed that seasonal differentiation does not affect the simple correlations; however, it has a significant impact on the GPP/PsnNet prediction process. Near-infrared (NIR)-based spectral indices have been found with the best agreements and statistically significant (p < 0.001) for GPP/PsnNet during March and October ranging coefficients from 0.85 to 0.44 in all three correlation models. However, Landsat 8 OLI band reflectances in different regions of the electromagnetic spectrum have gained importance as best predictors during March, whereas NIR-based indices have been found as best predictors for GPP/PsnNet during October. We have found that anomalies in environmental and meteorological conditions have a strong impact on plant functional activities that significantly differs prediction process rather than simple correlations.

The response of terrestrial ecosystem carbon cycling under different aerosol-based radiation management geoengineering

Abstract. Geoengineering has been discussed as a potential option to offset the global impacts of anthropogenic climate change and at the same time reach the global temperature targets of the Paris Agreement. Before any implementation of geoengineering, however, the complex natural responses and consequences of such methods should be fully understood to avoid any unexpected and potentially degrading impacts. Here we assess the changes in ecosystem carbon exchange and storage among different terrestrial biomes under three aerosol-based radiation management methods with the baseline of RCP8.5 using an Earth system model (NorESM1-ME). All three methods used in this study (stratospheric aerosol injection, marine sky brightening, cirrus cloud thinning) target the global mean radiation balance at the top of the atmosphere to reach that of the RCP4.5 scenario. The three radiation management (RM) methods investigated in this study show vastly different precipitation patterns, especially in the tropical forest biome. Precipitation differences from the three RM methods result in large variability in global vegetation carbon uptake and storage. Our findings show that there are unforeseen regional consequences under geoengineering, and these consequences should be taken into account in future climate policies as they have a substantial impact on terrestrial ecosystems. Although changes in temperature and precipitation play a large role in vegetation carbon uptake and storage, our results show that CO2 fertilization also plays a considerable role. We find that the effects of geoengineering on vegetation carbon storage are much smaller than the effects of mitigation under the RCP4.5 scenario (e.g., afforestation in the tropics). Our results emphasize the importance of considering multiple combined effects and responses of land biomes while achieving the global temperature targets of the Paris Agreement.

Reduced photosynthetic thermal acclimation capacity under elevated ozone in poplar (Populus tremula) saplings.

The sensitivity of photosynthesis to temperature has been identified as a key uncertainty for projecting the magnitude of the terrestrial carbon cycle response to future climate change. Although thermal acclimation of photosynthesis under rising temperature has been reported in many tree species, whether tropospheric ozone (O3 ) affects the acclimation capacity remains unknown. In this study, temperature responses of photosynthesis (light-saturated rate of photosynthesis (Asat ), maximum rates of RuBP carboxylation (Vcmax ), and electron transport (Jmax ) and dark respiration (Rdark ) of Populus tremula exposed to ambient O3 (AO3 , maximum of 30ppb) or elevated O3 (EO3 , maximum of 110ppb) and ambient or elevated temperature (ambient +5°C) were investigated in solardomes. We found that the optimum temperature of Asat (ToptA ) significantly increased in response to warming. However, the thermal acclimation capacity was reduced by O3 exposure, as indicated by decreased ToptA , and temperature optima of Vcmax (ToptV ) and Jmax (ToptJ ) under EO3 . Changes in both stomatal conductance (gs ) and photosynthetic capacity (Vcmax and Jmax ) contributed to the shift of ToptA by warming and EO3 . Neither Rdark measured at 25°C ( ) nor the temperature response of Rdark was affected by warming, EO3 , or their combination. The responses of Asat , Vcmax , and Jmax to warming and EO3 were closely correlated with changes in leaf nitrogen (N) content and N use efficiency. Overall, warming stimulated growth (leaf biomass and tree height), whereas EO3 reduced growth (leaf and woody biomass). The findings indicate that thermal acclimation of Asat may be overestimated if the impact of O3 pollution is not taken into account.

Comment on "Correlation of the stratigraphic cover of the Pilbara and Kaapvaal cratons recording the lead up to Paleoproterozoic Icehouse and the GOE" by Andrey Bekker, Bryan Krapež, and Juha A. Karhu, 2020, Earth Science Reviews, https://doi.org/10.1016/j.earscirev.2020.103389

Triple oxygen isotope (∆17O with δ18O) signals of H2O and O2 found in sulfate of oxidative weathering origin offer promising constraints on modern and ancient weathering, hydrology, atmospheric gas concentrations, and bioproductivity. However, interpretations of the sulfate-water-O2 system rely on assuming fixed oxygen-isotope fractionations between sulfate and water, which, contrastingly, are shown to vary widely in sign and amplitude. Instead, here we anchor sulfate-water-O2 triple oxygen isotope systematics on the homogeneous composition of atmospheric O2 with empirical constraints and modeling. Our resulting framework does not require a priori assumptions of the O2- versus H2O‑oxygen ratio in sulfate and accounts for the signals of mass-dependent and mass-independent fractionation in the ∆17O and δ18O of sulfate's O2‑oxygen source. Within this framework, new ∆17O measurements of sulfate constrain ~2.3 Ga Paleoproterozoic gross primary productivity to between 6 and 160 times present-day levels, with important implications for the biological carbon cycle response to high CO2 concentrations prevalent on the early Earth.

Sea-level rise enhances carbon accumulation in United States tidal wetlands

Sea-level rise enhances carbon accumulation in United States tidal wetlands

Litter Decomposition Rates of Biocrust-Forming Lichens Are Similar to Those of Vascular Plants and Are Affected by Warming

Despite the high relevance of communities dominated by lichens, mosses and cyanobacteria living on the soil surface (biocrusts) for ecosystem functioning in drylands, no study to date has investigated the decomposition of biocrust-forming lichen litter in situ. Thus, we do not know whether the drivers of its decomposition are similar to those for plant litter (for example, importance of abiotic degradation through UV radiation), the magnitude of lichen decomposition rates and whether they will be affected by ongoing climate change. Here we report the results from a litter decomposition experiment carried out with two biocrust-forming lichens (Diploschistes diacapsis and Cladonia convoluta) that differ in litter chemical quality (C:N ratio) in central Spain. We evaluated how lichen decomposition was affected by warming, rainfall exclusion and their combination. We also manipulated the incidence of UV radiation using mesh material that blocked 10% or 90% of incoming UV radiation. Our results indicate that lichens decompose as fast as some plants typical of the study area (k ~ 0.3 y−1). We observed differences among the species studied in line with what is expected according to their chemical composition. Warming increased decomposition rates of both lichen species by 28% and mediated the effects of photodegradation. Although UV exposure accelerated the decomposition of D. diacapsis, it slowed that of C. convoluta. Our results indicate that biocrust-forming lichens can decompose in the field at a rate similar to that of vascular plants and that this process will be affected by warming. The findings presented emphasize the need of considering biocrusts and the decomposition of their tissues when honing ecosystem models aiming to forecast carbon cycling responses to climate change in drylands.

Responses of vegetation greenness and carbon cycle to extreme droughts in China

Increasing drought stress under climate change exerting large impacts on vegetation has aroused growing concern, yet how vegetation greenness and carbon cycle respond to extreme drought is not well understood. In this paper, we studied this issue with various data sources including satellite observation, flux sites upscaling estimation, atmospheric inversion, and Dynamic Global Vegetation Model (DGVM) simulations over China during the period 2000–2015. We found a highly consistent negative response of greenness and carbon fluxes to extreme droughts, with the largest reduction in Gross Primary Productivity (GPP, a standardized anomaly of -1.26 ~ -0.33), a slightly smaller extent decrease of Net Ecosystem Productivity (NEP, -0.74 ~ -0.14) due to concurrent decrease of respiration, and reduced Leaf Area Index (LAI, -0.39 ~ -0.20). Besides, there was a large spatial heterogeneity across different regions and biomes, where Loess Plateau was one of the most vulnerable regions. The ambient climate conditions were found to modulate the drought response. Drought sensitivity of greenness and GPP peaked where mean annual temperature is around 25 °C, while that of NEP decreased along increasing precipitation gradients.

About this title - Carbon Cycle and Ecosystem Response to the Jenkyns Event in the Early Toarcian (Jurassic)

The Toarcian Oceanic Anoxic Event, also known as the Jenkyns Event, was a hyperthermal episode which occurred during the early Toarcian (c. 183 Ma; Early Jurassic) and resulted in numerous collateral effects including global warming, enhanced weathering, sea-level change, carbonate crisis, marine anoxia–dysoxia, and a second-order mass extinction. This volume presents the last advances for understanding early Toarcian environmental changes through different disciplines: biostratigraphy, micropalaeontology, palaeontology, ichnology, palaeoecology, sedimentology, integrated stratigraphy, inorganic, organic and isotopic geochemistry, and cyclostratigraphy. The study of this abrupt climate change is critical for predicting future global changes, and for understanding the complex biogeochemical interactions through time between geosphere, atmosphere, hydrosphere and biosphere.

The Toarcian Oceanic Anoxic Event: where do we stand?

Abstract The study of past climate changes is pivotal for understanding the complex biogeochemical interactions through time between the geosphere, atmosphere, hydrosphere and biosphere, which are critical for predicting future global changes. The Toarcian Oceanic Anoxic Event, also known as the Jenkyns Event, was a hyperthermal episode that occurred during the early Toarcian ( c. 183 Ma; Early Jurassic) and resulted in numerous collateral effects including global warming, enhanced weathering, sea-level change, carbonate crisis, marine anoxia–dysoxia and biotic crisis. The IGCP-655 project of the IUGS–UNESCO has constituted an international network of researchers with different disciplinary skills who have collaborated and shared conceptual advances on uncovering drivers of the environmental changes and ecosystem responses. This volume, Carbon Cycle and Ecosystem Response to the Jenkyns Event in the Early Toarcian (Jurassic) , presents 16 works that investigate the early Toarcian environmental changes related to the global warming, sea-level rise, carbon cycle perturbation and second-order mass extinction through biostratigraphy, micropalaeontology, palaeontology, ichnology, palaeoecology, sedimentology, integrated stratigraphy, inorganic, organic and isotopic geochemistry, and cyclostratigraphy.

Active layer depth and soil properties impact specific leaf area variation and ecosystem productivity in a boreal forest.

Specific leaf area (SLA, leaf area per unit dry mass) is a key canopy structural characteristic, a measure of photosynthetic capacity, and an important input into many terrestrial process models. Although many studies have examined SLA variation, relatively few data exist from high latitude, climate-sensitive permafrost regions. We measured SLA and soil and topographic properties across a boreal forest permafrost transition, in which dominant tree species changed as permafrost deepened from 54 to >150 cm over 75 m hillslope transects in Caribou-Poker Creeks Research Watershed, Alaska. We characterized both linear and threshold relationships between topographic and edaphic variables and SLA and developed a conceptual model of these relationships. We found that the depth of the soil active layer above permafrost was significantly and positively correlated with SLA for both coniferous and deciduous boreal tree species. Intraspecific SLA variation was associated with a fivefold increase in net primary production, suggesting that changes in active layer depth due to permafrost thaw could strongly influence ecosystem productivity. While this is an exploratory study to begin understanding SLA variation in a non-contiguous permafrost system, our results indicate the need for more extensive evaluation across larger spatial domains. These empirical relationships and associated uncertainty can be incorporated into ecosystem models that use dynamic traits, improving our ability to predict ecosystem-level carbon cycling responses to ongoing climate change.

Plant Hydraulic Stress Strategy Improves Model Predictions of the Response of Gross Primary Productivity to Drought Across China

AbstractThe response of the terrestrial carbon cycle to droughts, which have recently increased in incidence and severity, is a hot topic in research, but the role played by vegetation water use strategies remains unclear. Both the soil moisture stress (SMS) and plant hydraulic stress (PHS) strategies are used in land surface models, but their performance in simulating the terrestrial carbon cycle and its response to droughts in various climatic zones remains uncertain. In this study, we used Community Land Model Version 5 to simulate gross primary productivity (GPP) across four different climatic subregions of China during 2000–2015 to investigate the roles played by PHS and SMS in the response of GPP to dry events and dry or rainy years in various climate zones. Simulated GPP with the two strategies were overestimated by 2.0–2.3% for the entire China compared to Moderate Resolution Imaging Spectroradiometer (MODIS) data. GPP simulated using PHS configuration fit eddy covariance and MODIS data better than that obtained using SMS across China, except for the Qinghai‐Tibet Plateau. PHS increased simulated GPP by 0.10–0.63 g C m−2 day−1 during dry events across different climatic regions because of root hydraulic lift but decreased GPP by 0.37–0.45 g C m−2 day−1 during growing season in the humid southeastern region because of high atmospheric vapor pressure deficit and root hydraulic descent. Simulations forced by data collected locally in China performed better than those forced by CRUNCEP7 global data at the site but worse at the regional scale, in particular for the Qinghai‐Tibet Plateau.

Spatiotemporal LUCC Simulation under Different RCP Scenarios Based on the BPNN_CA_Markov Model: A Case Study of Bamboo Forest in Anji County

Simulating spatiotemporal land use and land cover change (LUCC) data precisely under future climate scenarios is an important basis for revealing the carbon cycle response of forest ecosystems to LUCC. In this paper, a coupling model consisting of a back propagation neural network (BPNN), Markov chain, and cellular automata (CA) was designed to simulate the LUCC in Anji County, Zhejiang Province, under four climate scenarios (Representative Concentration Pathway (RCP) 2.6, 4.5, 6.0, 8.5) from 2024 to 2049 and to analyze the temporal and spatial distribution of bamboo forests in Anji County. Our results provide four outcomes. (1) The transition probability matrices indicate that the area of bamboo forests shows an expansion trend, and the largest contribution to the expansion of bamboo forests is the cultivated land. The Markov chain composed of the average transition probability matrix could perform excellently, with only small errors when simulating the areas of different land-use types. (2) Based on the optimized BPNN, which had a strong generalization ability, a high prediction accuracy, and area under the curve (AUC) values above 0.9, we could obtain highly reliable land suitability probabilities. After introducing more driving factors related to bamboo forests, the prediction of bamboo forest changes will be more accurate. (3) The BPNN_CA_Markov coupling model could achieve high-precision simulation of LUCC at different times, with an overall accuracy greater than 70%, and the consistency of the LUCC simulation from one time to another also had good performance, with a figure of merit (FOM) of approximately 40%. (4) Under the future four RCP scenarios, bamboo forest evolution had similar spatial characteristics; that is, bamboo forests were projected to expand in the northeast, south, and southwest mountainous areas of Anji County, while bamboo forests were projected to decline mainly around the junction of the central and mountainous areas of Anji County. Comparing the simulation results of different scenarios demonstrates that 74% of the spatiotemporal evolution of bamboo forests will be influenced by the interactions and competition among different land-use types and other driving factors, and 26% will come from different climate scenarios, among which the RCP8.5 scenario will have the greatest impact on the bamboo forest area and spatiotemporal evolution, while the RCP2.6 scenario will have the smallest impact. In short, this study proposes effective methods and ideas for LUCC simulation in the context of climate change and provides accurate data support for analyzing the impact of LUCC on the carbon cycle of bamboo forests.

Soil erosion significantly reduces organic carbon and nitrogen mineralization in a simulated experiment

Soil erosion has important influence on soil processes and particularly soil nutrient dynamics, which in turn affects the terrestrial C and N cycling and greenhouse gases emission. However, the responses of carbon (C) and nitrogen (N) cycling in soils and soil fractions to erosion remain largely unclear, hindering the precise prediction of the fate of C and N in the terrestrial ecosystem. Herein, we compared the mineralization of organic carbon (OC) and N at two different temperatures (15 and 25 °C) in bulk soils and aggregate fractions of 19 soils before and after a simulated rainstorm. The temperature sensitivity (Q10) of OC and N mineralization was calculated. Soil samples were collected from 9 sites across China, with soil types of Alfisols, Inceptisols, Mollisols, Ultisols, and land uses of croplands, grasslands, and woodlands. The soil aggregate fractions were >2, 2-1, 1-0.25 and <0.25 mm, respectively. We hypothesized that erosion will decrease OC and N mineralization due to the loss of labile organic matter from soils and that the effects of erosion would decrease with clay content and vary with different aggregate fractions. In support of these hypotheses, the cumulative mineralized OC and N (Cm and Nm) in the soils and aggregate fractions were decreased of 78-85% and 37-52% after erosion, and the temperature sensitivities of OC and N mineralization were decreased of 80-84% and 4-43%, respectively. The effects of erosion varied with site where the soil was collected. The decreases in Cm and Nm mainly occurred in small aggregate sizes (1-0.25 and <0.25 mm fractions). The Cm and Nm in bulk soils and aggregates increased significantly with the contents of OC, N, labile OC and mineral N but were texture independent. These results highlighted significantly reduction of OC and N mineralization at eroding sites, which should be carefully considered when assessing emissions of greenhouse gases in eroding environments.