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Nitrogen is the most limiting nutrient in wetland ecosystems. Changing in nitrogen nutrient status has a great effect on wetland carbon and nitrogen cycling. However, there is much uncertainty as to wetland greenhouse gas emissions response to nitrogen inputs in China. In this study, we synthesized 177 paired observations from 27 studies of greenhouse gases emissions related to nitrogen additions across wetland in China. The results showed nitrogen inputs significantly contributed to wetland carbon dioxide (CO2) and nitrous oxide (N2O) emissions but had no significant effect on methane (CH4). We further analyze the relationship between greenhouse gases emissions and soil properties, climate factors under nitrogen inputs. Regression analyses introducing explanatory variables showed that high nitrogen inputs (12 g N m-2 yr-1-24 g N m-2 yr-1) contributed more significantly to wetland CO2 and N2O emissions. Compared to other wetland types, alpine peatlands have a greater impact on CO2 and N2O emissions following nitrogen input. In addition, high altitude (> 1500 m and ≤ 3500 m) could promote wetland CO2 and N2O emissions more significantly after nitrogen input, but ultra-high altitude (> 3500 m) reduced CO2 emissions. CO2 and N2O emissions were more significantly promoted when mean annual temperature (MAT) was positive, and CO2 emissions increased with increasing mean annual precipitation (MAP). Wetland CO2 emissions can be significantly promoted when soil is acidic, while N2O emissions can be significantly promoted when soil is alkaline. N2O emissions increased with increasing of soil total nitrogen (TN) and soil organic carbon (SOC) contents. These findings highlight the characteristics of wetland greenhouse gas emissions following nitrogen input, and improve our ability to predict greenhouse gas emissions and help meet carbon neutrality targets.

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The successful utilization of stable carbon isotope approaches in investigating forest carbon dynamics has relied on the assumption that the carbon isotope compositions (δ13C) therein have detectable temporal variations. However, interpreting the δ13C signal transfer can be challenging, given the complexities involved in disentangling the effect of a single environmental factor, the isotopic dilution effect from background CO2, and the lack of high-resolution δ13C measurements. In this study, we conducted continuous in-situ monitoring of atmospheric CO2 (δ13Ca) across a canopy profile in an old-growth temperate forest in northeast China during the normal year 2020 and the wet year 2021. Both years exhibited similar temperature conditions in terms of both seasonal variations and annual averages. We tracked the natural carbon isotope composition from δ13Ca to photosynthate (δ13Cp) and to ecosystem respiration (δ13CReco). We observed significant differences in δ13Ca between the two years. Contrary to in 2020, in 2021 there was a δ13Ca valley in the middle of the growing season, attributed to surges in soil CO2 efflux induced by precipitation, while in 2020 values peaked during that period. Despite substantial and similar seasonal variations in canopy photosynthetic discrimination (Δ13Ccanopy) in the two years, the variability of δ13Cp in 2021 was significantly lower than in 2020, due to corresponding differences in δ13Ca. Furthermore, unlike in 2020, we found almost no changes in δ13CReco in 2021, which we ascribed to the imprint of the δ13Cp signal on above-ground respiration and, more importantly, to the contribution of stable δ13C signals from soil heterotrophic respired CO2. Our findings suggest that extreme precipitation can impede the detectability of recent photosynthetic δ13C signals in ecosystem respiration in forests, thus complicating the interpretation of above- and below-ground carbon linkage using δ13CReco. This study provides new insights for unravelling precipitation-related variations in forest carbon dynamics using stable isotope techniques.

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Background: Sequestering carbon dioxide (CO2) in agricultural soils promises climate change mitigation as well as sustainable ecosystem services. In order to stabilize crop residues as soil carbon (C), addition of mineral nutrients in excess to crop needs is suggested as an inevitable practice. However, the effect of two macronutrients i.e., nitrogen (N) & phosphorus (P), on C cycling has been found contradictory. Mineral N usually decreases whereas mineral P increases the soil organic C (SOC) mineralization and microbial biomass. How the addition of these macronutrients in inorganic form to an organic-matter poor soil affect C cycling remains to be investigated. Methods: To reconcile this contradiction, we tested the effect of mineral N (120 kg N ha-1) and/or P (60 kg N ha-1) in presence or absence of maize litter (1 g C kg-1 soil) on C cycling in an organic-matter poor soil (0.87% SOC) in a laboratory incubation. Soil respiration was measured periodically during the incubation whereas various soil variables were measured at the end of the incubation. Results: Contrary to literature, P addition stimulated soil C mineralization very briefly at start of incubation period and released similar total cumulative CO2-C as in control soil. We attributed this to low organic C content of the soil as P addition could desorb very low amounts of labile C for microbial use. Adding N with litter built up the largest microbial biomass (144% higher) without inducing any further increase in CO2-C release compared to litter only addition. However, adding P with litter did not induce any increase in microbial biomass. Co-application of inorganic N and P significantly increased C mineralization in presence (19% with respect to only litter amended) as well as absence (41% with respect to control soil) of litter. Overall, our study indicates that the combined application of inorganic N and P stabilizes added organic matter while depletes the already unamended soil.

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Soil respiration (Rs) is projected to be substantially affected by climate change, impacting the storage, equilibrium, and movement of terrestrial carbon (C). However, uncertainties surrounding the responses of Rs to climate change and soil nitrogen (N) enrichment are linked to mechanisms specific to diverse climate zones. A comprehensive meta-analysis was conducted to address this, evaluating the global effects of warming, increased precipitation, and N enrichment on Rs across various climate zones and ecosystems. Data from 123 studies, encompassing a total of 10,377 worldwide observations, were synthesized for this purpose. Annual Rs were modeled and their uncertainties were associated with a 1-km2 resolution global Rs database spanning from 1961 to 2022. Calibrating Rs using ensemble machine learning (EML) and employing 10-fold cross-validation, 13 environmental covariates were utilized. The meta-analysis findings revealed an upsurge in Rs rates in response to warming, with tropical, arid, and temperate climate zones exhibiting increases of 12 %, 13 %, and 16 %, respectively. Furthermore, increased precipitation led to stimulated Rs rates of 11 % and 9 % in tropical and temperate zones, respectively, while N deposition affected Rs in cold (+6 %) and tropical (+5 %) climate zones. The machine learning technique estimated the global soil respiration to range from 91 to 171 Pg C yr-1, with an average Rs of 700 ± 300 g C m-2 yr-1. The values ranged between 314 and 2500 g C m-2 yr-1, with the lowest and highest values observed in cold and tropical zones, respectively. Spatial variation in Rs was most pronounced in low-latitude areas, particularly in tropical rainforests and monsoon zones. Temperature, precipitation, and N deposition were identified as crucial environmental factors exerting significant influences on Rs rates worldwide. These factors underscore the interconnectedness between climate and ecosystem processes, therefore requiring explicit considerations of different climate zones when assessing responses of Rs to global change.

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Soil respiration (RS) is crucial for releasing carbon dioxide (CO2) from terrestrial ecosystems to atmosphere. Prescribed burning (a common forest management tool), along with its important by-product pyrogenic carbon (PyC), can influence the carbon cycle of forest soil. However, few studies explore RS and PyC spatial correlation after prescribed burning. In this study, we investigated the spatial pattern of RS and its influencing factors by conducting prescribed burnings in a temperate artificial Pinus koraiensis forest. RS was measured 1 day (1 d) pre-prescribed burning, 1 d, 1 year (1 yr) and two years (2 yr) after prescribed burning. Significant decrease in RS were observed 1-2 yr After burning (reductions of 65.2% and 41.7% respectively). The spatial autocorrelation range of RS decreased pre-burning (2.72m), then increased post-burning (1 d: 2.44m; 1 yr: 40.14m; 2 yr: 9.8m), indicating a more homogeneous distribution of patch reduction. Pyrogenic carbon (PyC) in the soil gradually decreased in the short term after burning with reductions of 19%, 52%, and 49% (1d., 1 yr And 2 yr After the fire, respectively). However, PyC and RS exhibited a strong spatial positive correlation from 1 d.- 1 yr post-burning. The spatial regression model of dissolved organic carbon (DOC) on RS demonstrated significant positive spatial correlation in all measurements (pre- and post-burning). Microbial carbon to soil nitrogen ratio (MCN) notably influenced RS pre-burning and 1-2 yr post-burning. RS also showed significant spatial correlation in cross-variance with NH4+-N and NO3--N post-burning. The renewal of the PyC positively influenced RS, subsequently affecting its spatial distribution in 1d.- 1yr. Introducing PyC into RS studies helps enhances understanding of prescribed fire effects on forest soil carbon (C) pools, and provides valuable information regarding regional or ecosystem C cycling, facilitating a more accurate prediction of post-burning changes in forest soil C pools.

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Over the last century, many peatlands in northern Europe have been drained for forestry. Forest management with different harvesting regimes has a significant impact on soil water status and consequently on greenhouse gas emissions from peat soils. In this paper, we have used the process-based JSBACH-HIMMELI model to simulate the effects of alternative harvesting regimes, namely non-harvested (NH), selection harvesting (SH; 70 % of stem volume harvested) and clear-cutting (CC; 100 % of stem volume harvested), on soil CH4 and CO2 fluxes in peatland forests. We modified the model to account for the specific characteristics of peatland forests, where the water level (WL) is generally low and is regulated by the amount of aboveground vegetation through evapotranspiration. Multi-year measurements before and after the forest harvesting in a nutrient-rich peatland forest in southern Finland were used to constrain the model. The results showed that the modified model was able to reproduce the seasonal dynamics of water level, soil CH4 and soil CO2 fluxes under alternative harvesting regimes with reasonable accuracy. The averaged Pearson's r (Pearson correlation coefficient) and RMSE (Root Mean Square Error) between the model and the measurement were 0.75 and 7.3 cm for WL, 0.75 and 0.23 nmol m-2 s-1 for soil CH4 flux, 0.73 and 0. 88 µmol m-2 s-1 for soil CO2 flux. The modified model successfully reproduced soil CH4 uptake at both NH and SH sites and soil CH4 emission at the CC site, as observed in the measurements. Our study showed that increasing harvesting intensity (NH â†’ SH â†’ CC) in the model increased soil CH4 emission and decreased soil CO2 emission on an annual basis, but the magnitude of the decreased soil CO2 emission was much larger than that of the increased soil CH4 emission when comparing their global warming potentials. Therefore, in the short term as in our study (first three years after the harvest), the climate impacts of the soil GHG was reduced more in CC than in SH, which yet can be fundamentally different when considering in the long term.

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Enhanced silicate rock weathering (ERW) is an emerging strategy for carbon dioxide removal (CDR) from the atmosphere to mitigate anthropogenic climate change. ERW aims at promoting soil inorganic carbon sequestration by accelerating geochemical weathering processes. Theoretically, ERW may also impact soil organic carbon (SOC), the largest carbon pool in terrestrial ecosystems, but experimental evidence for this is largely lacking. Here, we conducted a 2-year field experiment in tropical rubber plantations in the southeast of China to evaluate the effects of wollastonite powder additions (0, 0.25, and 0.5 kg m-2) on both soil organic and inorganic carbon at 0-10 cm depth. We found that ERW significantly increased the concentration of SOC and HCO3 -, but the increases in SOC were four and eight times higher than that of HCO3 - with low- and high-level wollastonite applications. ERW had positive effects on the accrual of organic carbon in mineral-associated organic matter (MAOM) and macroaggregate fractions, but not on particulate organic matter. Path analysis suggested that ERW increased MAOM mainly by increasing the release of Ca, Si, and Fe, and to a lesser extent by stimulating root growth and microbial-derived carbon inputs. Our study indicates that ERW with wollastonite can promote SOC sequestration in stable MOAM in surface soils through both the soil mineral carbon pump and microbial carbon pump. These effects may have been larger than the inorganic CDR during our experiment. We argue it is essential to account for the responses of SOC in the assessments of CDR by ERW.

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Long-term atmospheric nitrogen (N) deposition has been known to enhance plant productivity by increasing available N in terrestrial ecosystems. However, the response of carbon process to N deposition in terrestrial ecosystems remains unclear, particularly about different climate regions and biomes. In this study, we synthesized 1281 pairwise observations from 218 published articles on experimental N addition globally, aiming to quantify the responses of the carbon process and its mechanisms to N addition. Our results revealed a significant overall increase in net ecosystem productivity (NEP) by 31.42 % following N addition treatment, owing to increased aboveground net primary productivity (ANPP, 16.46 %), belowground net primary productivity (BNPP, 27.74 %), and reduced soil respiration (Rs, -2.56 %), soil heterotrophic respiration (Rh, -6.24 %). Furthermore, the effects of N addition on NEP varied with biomes and climate regions. The positive effect of N addition on NEP was more pronounced in arid regions (28.67 %) compared to humid regions (21.92 %), primarily driven by a higher increase in vegetation productivity. Additionally, N addition exhibited a higher increase in NEP (33.95 %) in forest compared to grassland (31.80 %), resulting from a more reduction in respiratory processes. However, the positive effects of N addition on NEP diminished with increasing experimental duration. Furthermore, ANPP and BNPP displayed a convex relationship with N addition rates, with the optimum BNPP addition rate exceeding that of ANPP. In contrast, Rs exhibited a concave response to addition rates. These findings suggest that carbon sink in terrestrial ecosystems could be enhanced under future atmospheric N deposition, especially in arid regions and forest ecosystems. Our study provided insight for predicting how N deposition influences terrestrial ecosystem carbon process.

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Exploring the influences of nitrogen deposition on soil carbon (C) flux is necessary for predicting C cycling processes; however, few studies have investigated the effects of nitrogen deposition on soil respiration (Rs), autotrophic respiration (Ra) and heterotrophic respiration (Rh) across urban-rural forests. In this study, a 4-year simulated nitrogen deposition experiment was conducted by treating the experimental plots with 0, 50, or 100 kg·ha-1·year-1 of nitrogen to check out the mechanisms of nitrogen deposition on Rs, Ra, and Rh in urban-rural forests. Our finding indicated a positive association between soil temperature and Rs. Soil temperature sensitivity was significantly suppressed in the experimental plots treated with 100 kg·ha-1·year-1 of nitrogen only in terms of the urban forest Rs and Ra and the rural forest Ra. Nitrogen treatment did not significantly increase Rs and had different influencing mechanisms. In urban forests, nitrogen addition contributed to Rh by increasing soil microbial biomass nitrogen and inhibited Ra by increasing soil ammonium­nitrogen concentration. In suburban forests, the lack of response of Rh under nitrogen addition was due to the combined effects of soil ammonium­nitrogen and microbial biomass nitrogen; the indirect effects from nitrate­nitrogen also contributed to a divergent effect on Ra. In rural forests, the soil pH, dissolved organic C, fine root biomass, and microbial biomass C concentration were the main factors mediating Rs and its components. In summary, the current rate of nitrogen deposition is unlikely to result in significant increases in soil C release in urban-rural forests, high nitrogen deposition is beneficial for reducing the temperature sensitivity of Rs in urban forests. The findings grant a groundwork for predicting responses of forest soil C cycling to global change in the context of urban expansion.

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Climate influences near-surface biogeochemical processes and thereby determines the partitioning of carbon dioxide (CO2) in shale, and yet the controls on carbon (C) weathering fluxes remain poorly constrained. Using a dataset that characterizes biogeochemical responses to climate forcing in shale regolith, we implement a numerical model that describes the effects of water infiltration events, gas exchange, and temperature fluctuations on soil respiration and mineral weathering at a seasonal timescale. Our modeling approach allows us to quantitatively disentangle the controls of transient climate forcing and biogeochemical mechanisms on C partitioning. We find that ~3% of soil CO2 (1.02 mol C/m2/y) is exported to the subsurface during large infiltration events. Here, net atmospheric CO2 drawdown primarily occurs during spring snowmelt, governs the aqueous C exports (61%), and exceeds the CO2 flux generated by pyrite and petrogenic organic matter oxidation (~0.2 mol C/m2/y). We show that shale CO2 consumption results from the temporal coupling between soil microbial respiration and carbonate weathering. This coupling is driven by the impacts of hydrologic fluctuations on fresh organic matter availability and CO2 transport to the weathering front. Diffusion-limited transport of gases under transient hydrological conditions exerts an important control on CO2(g) egress patterns and thus must be considered when inferring soil CO2 drawdown from the gas phase composition. Our findings emphasize the importance of seasonal climate forcing in shaping the net contribution of shale weathering to terrestrial C fluxes and suggest that warmer conditions could reduce the potential for shale weathering to act as a CO2 sink.

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Green manure with appropriate amount of chemical nitrogen fertilizer can increase crop yield, but also aggravate soil carbon emissions. However, it is unclear whether incorporation of green manure into the cropping pattern with reduced nitrogen amount can alleviate this situation and enhance carbon sequestration potential. So, a field experiment with split-plot design was set up in 2018 of northwest China, and studied the effects of nitrogen reduction on crop productivity, carbon emissions, and carbon sequestration potential in 2021-2023. The main plots were two cropping patterns, including multiple cropped green manure after wheat harvest (W-G) and fallow after wheat harvest (W). Three nitrogen application levels formed the split-plots, including local conventional nitrogen amount (N3, 180 kg ha-1), nitrogen amount reduced by 15% (N2, 153 kg ha-1) and 30% (N3, 126 kg ha-1). The results showed that W-G increased grain yield of wheat and energy yield of wheat multiple cropped green manure pattern. The multiple cropped green manure after wheat harvest with local conventional nitrogen amount reduced by 15% (W-GN2) had the significant increasing-effect, and increased grain yield of wheat by 9.6% and increased total energy yields by 39.3% compared to fallow after wheat harvest with local conventional nitrogen amount (W-N3). Relative to W-N3, W-GN2 did not significantly increase carbon emissions of wheat season, and increased total carbon emissions of cropping pattern by 11.1%. Compared to multiple cropped green manure after wheat harvest with local conventional nitrogen amount (W-GN3), W-GN2 decreased carbon emissions by 5.8% in wheat season and decreased by 3.9% in the whole cropping pattern. Therefore, W-GN2 gained high carbon emission efficiency based on grain yield, and were 9.9% and 11.2% higher than W-N3 and W-GN3, respectively. In addition, W-GN2 enhanced soil total nitrogen, carbon, and organic carbon contents, compared with W-N3, thus increasing soil carbon sequestration potential index (net primary productivity/carbon emissions). We conclude that multiple cropped leguminous green manure after wheat harvest with local conventional nitrogen amount reduced by 15% can enhance crop productivity and carbon sequestration potential of farmland in arid areas.

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Soil respiration (Rs) represents the greatest carbon dioxide flux from terrestrial ecosystems to the atmosphere. However, its environmental drivers are not fully understood, and there are still significant uncertainties in soil respiration model estimates. This study aimed to estimate the spatial distribution pattern and driving mechanism of global soil respiration by constructing a machine learning model method based on ecological big data. First, we constructed ecological big data containing five categories of 27-dimensional environmental factors. We then used four typical machine learning methods to develop the performance of machine learning models under four training strategies and explored the relationship between soil respiration and environmental factors. Finally, we used the RF machine learning algorithm to estimate the global Rs spatial distribution pattern in 2021, driven by multiple dimensions of environmental factors, and derived the annual soil respiration values. The results showed that RF performed better under the four training strategies, with a coefficient of determination R2 = 0.78216, root mean squared error (RMSE) = 285.8964 gCm-2y-1, and mean absolute error (MAE) = 180.4186 gCm-2y-1, which was more suitable for the estimation of large-scale soil respiration. In terms of the importance of environmental factors, unlike previous studies, we found that the influence of geographical location was greater than that of MAP. Another new finding was that enhanced vegetation index 2 (EVI2) had a higher contribution to soil respiration estimates than the enhanced vegetation index (EVI) and normalized vegetation index (NDVI). Our results confirm the potential of utilizing ecological big data for spatially large-scale Rs estimations. Ecological big data and machine learning algorithms can be considered to improve the spatial distribution patterns and driver analysis of Rs.

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Livestock grazing can strongly determine how grasslands function and their role in the carbon cycle. However, how ecosystem carbon exchange responds to grazing and the underlying mechanisms remain unclear. We measured ecosystem carbon fluxes to explore the changes in carbon exchange and their driving mechanisms under different grazing intensities (CK, control; HG, heavy grazing; LG, light grazing; MG, moderate grazing) based on a 16-year long-term grazing experimental platform in a desert steppe. We found that grazing intensity influenced aboveground biomass during the peak growing season, primarily by decreasing shrubs and semi-shrubs and perennial forbs. Furthermore, grazing decreased net ecosystem carbon exchange by decreasing aboveground biomass, especially the functional group of shrubs and semi-shrubs. At the same time, we found that belowground biomass and soil ammonium nitrogen were the driving factors of soil respiration in grazed systems. Our study indicates that shrubs and semi-shrubs are important factors in regulating ecosystem carbon exchange under grazing disturbance in the desert steppe, whereas belowground biomass and soil available nitrogen are important factors regulating soil respiration under grazing disturbance in the desert steppe; this results provide deeper insights for understanding how grazing moderates the relationships between soil nutrients, plant biomass, and ecosystem CO2 exchange, which provide a theoretical basis for further grazing management.

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As the climate warms, the thickening of the active layer of permafrost has led to permafrost melting and surface collapse, forming thermokarst landforms. These changes significantly impact regional vegetation, soil physicochemical properties, and hydrological processes, thereby exacerbating regional carbon cycling. This study analyzed the relationship between soil respiration rate (Rs), soil temperature (T), and volumetric water content (VWC) in the thermokarst depression zone of the headwater wetlands of Qinghai Lake, revealing their influence on these soil parameters. Results showed a significant positive correlation between soil temperature and Rs (p < 0.001), and a significant negative correlation between VWC and Rs (p < 0.001). The inhibitory effect of VWC on Rs in the thermokarst depression zone was stronger than under natural conditions (p < 0.05). Single-factor models indicated that the temperature-driven model had higher explanatory power for Rs variation in both the thermokarst depression zone (R2 = 0.509) and under natural conditions (R2 = 0.414), while the humidity-driven model had lower explanatory power. Dual-factor models further improved explanatory power, slightly more so in the thermokarst depression zone. This indicates that temperature and humidity jointly drive Rs. Additionally, during the daytime, temperature had a more significant impact on Rs under natural conditions, while increased VWC inhibited Rs. At night, the positive correlation between Rs and temperature in the thermokarst depression zone increased significantly. The temperature sensitivity (Q10) values of Rs were 3.32 and 1.80 for the thermokarst depression zone and natural conditions, respectively, indicating higher sensitivity to temperature changes at night in the thermokarst depression zone. This study highlights the complexity of soil respiration responses to temperature and humidity in the thermokarst depression zone of Qinghai Lake's headwater wetlands, contributing to understanding carbon cycling in wetland ecosystems and predicting wetland carbon emissions under climate change.

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Mollisols rich in natural organic matter are a significant sink of carbon (C) and selenium (Se). Climate warming and agricultural expansion to the cold Mollisol regions may enhance soil respiration and biogeochemical cycles, posing a growing risk of soil C and Se loss. Through field-mimicking incubation experiments with uncultivated and cultivated soils from the Mollisol regions of northeastern China, this research shows that soil respiration remained significant even during cold seasons and caused co-emission of greenhouse gases (CO2 and CH4) and methylated Se. Such stimulus effects were generally stronger in the cultivated soils, with maximum emission rates of 7.45 g/m2/d C and 1.42 µg/m2/d Se. For all soil types, the greatest co-emission of CO2 and dimethyl selenide occurred at 25 % soil moisture, whereas measurable CH4 emission was observed at 40 % soil moisture with higher percentages of dimethyl diselenide volatilization. Molecular characterization with three-dimensional fluorescence and ultra-high resolution mass spectrometry suggests that CO2 emission is sensitive to the availability of microbial protein-like substances and free energy from organic carbon biodegradation under variable moisture conditions. Predominant Se binding to biodegradable organic matter resulted in high dependence of Se volatilization on rates of greenhouse gas emissions. These findings together highlight the importance of dynamic organic carbon quality for soil respiration and consequent Mollisol Se loss risk, with implications for science-based management of C and Se resources in agricultural lands to combat with Se deficiency.

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Microplastics (MPs) are emerging pollutants of terrestrial ecosystems. The impacts of MP particle size on terrestrial systems remain unclear. The current study aimed to investigate the effects of six particle sizes (i.e., 4500, 1500, 500, 50, 5, and 0.5 µm) of polyethylene (PE) and polyvinyl chloride (PVC) on soil respiration, enzyme activity, bacteria, fungi, protists, and seed germination. MPs significantly promoted soil respiration, and the stimulating effects of PE were the strongest for medium and small-sized (0.5-1500 µm) particles, while those of PVC were the strongest for small particle sizes (0.5-50 µm). Large-sized (4500 µm) PE and all sizes of PVC significantly improved soil urease activity, while medium-sized (1500 µm) PVC significantly improved soil invertase activity. MPs altered the soil microbial community diversity, and the effects were especially pronounced for medium and small-sized (0.5-1500 µm) particles of PE and PVC on bacteria and fungi and small-sized (0.5 µm) particles of PE on protists. The impacts of MPs on bacteria and fungi were greater than on protists. The seed germination rate of Brassica chinensis decreased gradually with the decrease in PE MPs particle size. Therefore, to reduce the impact of MPs on soil ecosystems, effective measures should be taken to avoid the transformation of MPs into smaller particles in soil environmental management.

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Global warming modulates soil respiration (RS) via microbial decomposition, which is seasonally dependent. Yet, the magnitude and direction of this modulation remain unclear, partly owing to the lack of knowledge on how microorganisms respond to seasonal changes. Here, we investigated the temporal dynamics of soil microbial communities over 12 consecutive months under experimental warming in a tallgrass prairie ecosystem. The interplay between warming and time altered (P < 0.05) the taxonomic and functional compositions of microbial communities. During the cool months (January to February and October to December), warming induced a soil microbiome with a higher genomic potential for carbon decomposition, community-level ribosomal RNA operon (rrn) copy numbers, and microbial metabolic quotients, suggesting that warming stimulated fast-growing microorganisms that enhanced carbon decomposition. Modeling analyses further showed that warming reduced the temperature sensitivity of microbial carbon use efficiency (CUE) by 28.7% when monthly average temperature was low, resulting in lower microbial CUE and higher heterotrophic respiration (Rh) potentials. Structural equation modeling showed that warming modulated both Rh and RS directly by altering soil temperature and indirectly by influencing microbial community traits, soil moisture, nitrate content, soil pH, and gross primary productivity. The modulation of Rh by warming was more pronounced in cooler months compared to warmer ones. Together, our findings reveal distinct warming-induced effects on microbial functional traits in cool months, challenging the norm of soil sampling only in the peak growing season, and advancing our mechanistic understanding of the seasonal pattern of RS and Rh sensitivity to warming.

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The effects of nitrogen application or earthworms on soil respiration in the Huang-Huai-Hai Plain of China have received increasing attention. However, the response of soil carbon dioxide (CO2) emission to nitrogen application and earthworm addition is still unclear. A field experiment with nitrogen application frequency and earthworm addition was conducted in the Huang-Huai-Hai Plain. Results showed nitrogen application frequency had a significant effect on soil respiration, but neither earthworms nor their interaction with nitrogen application frequency were significant. Low-frequency nitrogen application (NL) significantly increased soil respiration by 25%, while high-frequency nitrogen application (NH), earthworm addition (E), earthworm and high-frequency nitrogen application (E*NH), and earthworm and low-frequency nitrogen application (E*NL) also increased soil respiration by 21%, 21%, 12%, and 11%, respectively. The main reason for the rise in soil respiration was alterations in the bacterial richness and keystone taxa (Myxococcales). The NH resulted in higher soil nitrogen levels compared to NL, but NL had the highest bacterial richness. The abundance of Corynebacteriales and Gammaproteobacteria were positively connected with the CO2 emissions, while Myxococcales, Thermoleophilia, and Verrucomicrobia were negatively correlated. Our findings indicate the ecological importance of bacterial communities in regulating the carbon cycle in the Huang-Huai-Hai Plain.

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Sustainable farming is one of the priority goals of the "4 per 1000" concept with regard to the preservation of soil fertility and carbon sequestration. This paper presents a study on the use of a mixture of cover crops of self-grown oats (Avena sativa L.) and sown white mustard (Sinapis alba L.) in organic farming under the agroecological conditions of Serbia. The main objective was to identify sensitive carbon pools (microbial carbon and nitrogen, basal respiration and a number of specific groups of soil microorganisms) in organic farming with and without cover crops. The inclusion of a mixture of white mustard and self-grown oats as a cover crop led to a significantly increased biogenity of the soil compared to a control after only a few years of investigation. The number of microorganisms, soil respiration and microbial biomass carbon were significantly higher in the cover crop treatment compared to the control soil on an organic farm in Serbia. This is the first study in Serbia to investigate the effect of self-grown oats as a cover crop. Further research will incorporate a wider range of variables and factors in order to develop a sustainable and effective site-specific system for organic crop production in Serbia.

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Climate change has a discernible influence on rainfall patterns, thus potentially affecting the intricate dynamics of soil respiration (Rs) and soil carbon storage. However, we still lack a profound understanding of the determinants of Rs response to rainfall events. Here, utilizing a comprehensive 10-year dataset (2004-2013), we explored the direction and magnitude of Rs response to rainfall events and the underlying determinants in a temperate forest. Based on the identified 368 rainfall events over the study period, we demonstrate that rainfall suppresses Rs when the soil moisture is optimal and moist in the growing season, whereas its effect on Rs during the non-growing season is minimal. Notably, antecedent soil moisture, rather than rainfall amount, shows a substantial impact on Rs during the growing season (coefficient of determination (R2) = 0.37 for antecedent soil moisture, and R2 < 0.01 for rainfall amount). Incorporating antecedent soil moisture significantly enhances the explanatory power (R2) from 0.09 to 0.45 regarding the relative changes in Rs following rainfall events. Our results highlight the environmental dependency of Rs response to rainfall events and suggest that incorporating the role of antecedent soil moisture could enhance predictability and reduce uncertainty in ecosystem modeling.