Contrasting drivers of belowground nitrogen cycling in a montane grassland exposed to a multifactorial global change experiment with elevated CO2 , warming, and drought

Indicator metrics and temporal aggregations introduce ambiguities in water scarcity estimates

Water scarcity is a global challenge affecting billions of people worldwide. This study systematically assesses differences in the estimation of the global population exposed to water scarcity based on 7 water scarcity indicators and 11 Environmental Flow Requirements (EFR) evaluated at various spatial and temporal resolutions. All indicators show an increase in water scarcity since 1901. However, considering monthly average water scarcity estimates spatially aggregated at the basin scale found 35% less population exposed than estimates based on a distributed grid over the landscape. Estimates temporally disaggregated to consider water scarcity for at least one month a year found 50% (tenfold) larger population exposed compared to average monthly (annual) estimates. The study illustrates that estimates of the impacts of water scarcity are an artifact of how water scarcity is defined and calculated. This suggests caution is needed when relying on a single method and emphasizes the importance of considering the diversity of factors that can influence estimates of impact when assessing water scarcity.

Long-term soil warming changes the profile of primary metabolites in fine roots of Norway spruce in a temperate montane forest

Climate warming poses major threats to temperate forests, but the response of tree root metabolism has largely remained unclear. We examined the impact of long-term soil warming (>14 years, +4°C) on the fine root metabolome across three seasons for 2 years in an old spruce forest, using a liquid chromatography-mass spectrometry platform for primary metabolite analysis. A total of 44 primary metabolites were identified in roots (19 amino acids, 12 organic acids and 13 sugars). Warming increased the concentration of total amino acids and of total sugars by 15% and 21%, respectively, but not organic acids. We found that soil warming and sampling date, along with their interaction, directly influenced the primary metabolite profiles. Specifically, in warming plots, concentrations of arginine, glycine, lysine, threonine, tryptophan, mannose, ribose, fructose, glucose and oxaloacetic acid increased by 51.4%, 19.9%, 21.5%, 19.3%, 22.1%, 23.0%, 38.0%, 40.7%, 19.8% and 16.7%, respectively. Rather than being driven by single compounds, changes in metabolite profiles reflected a general up- or downregulation of most metabolic pathway network. This emphasises the importance of metabolomics approaches in investigating root metabolic pathways and understanding the effects of climate change on tree root metabolism.

Maize/soybean intercropping increases nutrient uptake, crop yield and modifies soil physio-chemical characteristics and enzymatic activities in the subtropical humid region based in Southwest China

Intercropping, a widely adopted agricultural practice worldwide, aims to increase crop yield, enhance plant nutrient uptake, and optimize the utilization of natural resources, contributing to sustainable farming practices on a global scale. However, the underlying changes in soil physio-chemical characteristics and enzymatic activities, which contribute to crop yield and nutrient uptake in the intercropping systems are largely unknown. Consequently, a two-year (2021-2022) field experiment was conducted on the maize/soybean intercropping practices with/without nitrogen (N) fertilization (i.e., N0; 0 N kg ha-1 and N1; 225 N kg ha-1 for maize and 100 N kg ha-1 for soybean ) to know whether such cropping system can improve the nutrients uptake and crop yields, soil physio-chemical characteristics, and soil enzymes, which ultimately results in enhanced crop yield. The results revealed that maize intercropping treatments (i.e., N0MI and N1MI) had higher crop yield, biomass dry matter, and 1000-grain weight of maize than mono-cropping treatments (i.e., N0MM, and N1MM). Nonetheless, these parameters were optimized in N1MI treatments in both years. For instance, N1MI produced the maximum grain yield (10,105 and 11,705 kg ha-1), biomass dry matter (13,893 and 14,093 kg ha-1), and 1000-grain weight (420 and 449 g) of maize in the year 2021 and 2022, respectively. Conversely, soybean intercropping treatments (i.e., N0SI and N1SI) reduced such yield parameters for soybean. Also, the land equivalent ratio (LER) and land equivalent ratio for N fertilization (LERN) values were always greater than 1, showing the intercropping system's benefits in terms of yield and improved resource usage. Moreover, maize intercropping treatments (i.e., N0MI and N1MI) and soybean intercropping treatments (i.e., N0SI and N1SI) significantly (p < 0.05) enhanced the nutrient uptake (i.e., N, P, K, Ca, Fe, and Zn) of maize and soybean, however, these nutrients uptakes were more prominent in N1MI and N1SI treatments of maize and soybean, respectively in both years (2021 and 2022) compared with their mono-cropping treatments. Similarly, maize-soybean intercropping treatments (i.e., N0MSI and N1MSI) significantly (p < 0.05) improved the soil-based N, P, K, NH4, NO3, and soil organic matter, but, reduced the soil pH. Such maize-soybean intercropping treatments also improved the soil enzymatic activities such as protease (PT), sucrose (SC), acid phosphatase (AP), urease (UE), and catalase (CT) activities. This indicates that maize-soybean intercropping could potentially contribute to higher and better crop yield, enhanced plant nutrient uptake, improved soil nutrient pool, physio-chemical characteristics, and related soil enzymatic activities. Thus, preferring intercropping to mono-cropping could be a preferable choice for ecologically viable agricultural development.

Impact of hydrological drought occurrence, duration, and severity on Murray-Darling basin water quality

The severity and frequency of droughts are projected to increase globally due to climate change, but the effects of this on water quality are uncertain. The Murray-Darling Basin (MDB) is the largest river system in Australia and has been impacted by droughts of varying severity within recent decades. In this study, we assessed the influence of hydrological droughts and their characteristics (severity and duration) on water quality, utilising a long-term (1980-2017) dataset from two monitoring sites. The main drought periods, and their duration and severity, were identified using the calculated Standardised Drought Index values (SDI) from averaged monthly streamflow data. While several hydrological drought periods were identified, the longest duration and greatest severity were during the Millennium Drought (1998-2010). Nutrient loads and concentrations of Total Nitrogen and Total Phosphorus of drought and post-drought periods were significantly different. The drought period showed the lowest median and interquartile range of nutrient (total nitrogen, TN; oxidised nitrogen, NOX; total phosphorus, TP; and soluble reactive phosphorus, SRP) concentrations and loads for both sites, whereas the highest nutrient loads and concentrations were reported during the post-drought period (approx. 1 × 103 to 1 × 105 kg day-1 increase in nutrient loads). Our analysis found significant relationships between nutrient loads and SDI during droughts. The load of N and P in the initial flush post-drought increased with drought at both sites. This suggests that nutrients were retained in the landscape during the drought and released in higher loads post-drought when the catchment became wetter, the hydrology was activated, and nutrients were mobilised. Hydrology is a key driver controlling the water quality within the inter-drought period and the peak nutrient loads post-drought. The duration and the severity of droughts had a significant (p = 0.01) influence on peak TN and TP monthly loads but not cumulative loads over a 12-month period. Hydrological droughts are important factors in controlling the water quality of the MDB. Therefore, management efforts should be focused on reducing the occurrence and duration of these events, along with the implementation of catchment nutrient control measures.

Recent advances in ambient-stable black phosphorus materials for artificial catalytic nitrogen cycle in environment and energy

Nitrogen cycle is crucial for the Earth's ecosystem and human-nature coexistence. However, excessive fertilizer use and industrial contamination disrupt this balance. Semiconductor-based artificial nitrogen cycle strategies are being actively researched to address this issue. Black phosphorus (BP) exhibits remarkable performance and significant potential in this area due to its unique physical and chemical properties. Nevertheless, its practical application is hindered by ambient instability. This review covers the synthesis methods of BP materials, analyzes their instability factors under environmental conditions, discusses stability improvement strategies, and provides an overview of the applications of ambient-stable BP materials in nitrogen cycle, including N2 fixation, NO3- reduction, NOx removal and nitrides sensing. The review concludes by summarizing the challenges and prospects of BP materials in the nitrogen cycle, offering valuable guidance to researchers.

Dissolved organic compounds in shale gas extraction flowback water as principal disturbance factors of soil nitrogen dynamics

Flowback water, a by-product of shale gas extraction, represents an extremely complex industrial wastewater characterized by high organic compounds content and high salinity. The prospect of flowback water entering the soil through various approaches concerns regarding its ecological risk. Nitrogen mineralization (Nmin), a key rate-limiting step in the soil N cycle, might be adversely affected by flowback water. Nonetheless, no previous studies have examined the effects of flowback water on soil Nmin rates, let alone quantified the relative contributions of the major components of flowback water to changes in Nmin rates. Therefore, this study investigated the effects of flowback water and sterile flowback water at two different concentrations on the Nmin rates of three distinct soil types. This study aimed to elucidate the predominant influence of the key constituents within flowback water on the changes in soil Nmin rates. The results showed that soil soluble salt content, dissolved organic carbon (DOC) and dissolved nitrogen (DN) content significantly increased by 8.37 times, 9.5 % and 26.4 %, respectively, in soils contaminated by flowback water. In comparison with the control group, the introduction of flowback water resulted in a significant 25.9 % reduction in Nmin rate in sandy soils. Conversely, in clay and loam soils, there was a significant increase in Nmin rates by 44.9 % and 131.8 % respectively. Throughout the incubation period, leucine-aminopeptidase activity exhibited irregular fluctuations. Analysis of microbial communities demonstrated that flowback water only significant impacted soil rare microbial taxa, inducing a significant increase in alpha diversity for sandy, clay, and loamy soils by -16.9 %, 10.12 %, and 1.63 %, respectively. Linear regression and random forest analyses indicated that alterations in soil DOC:DN ratio and salt content were responsible for changes in soil Nmin rates within flowback water-contaminated soils. In contrast, only salt content significantly contributed to shifts in alpha diversity among soil rare microbial taxa. Structural equation modeling highlighted that the total effect of dissolved organic compounds (DOC and DN, λ = 0.64) from flowback water was greater than the total effect of salinity (λ = 0.24) on soil Nmin rates. In conclusion, our findings imply that dissolved organic compounds within flowback water play pivotal roles in determining soil Nmin rates. To the best of our knowledge, this is the first study to reveal the effects of major components in the flowback water on soil N mineralization rates.

Aridity creates global thresholds in soil nitrogen retention and availability

Identifying tipping points in the relationship between aridity and gross nitrogen (N) cycling rates could show critical vulnerabilities of terrestrial ecosystems to climate change. Yet, the global pattern of gross N cycling response to aridity across terrestrial ecosystems remains unknown. Here, we collected 14,144 observations from 451 15 N-labeled studies and used segmented regression to identify the global threshold responses of soil gross N cycling rates and soil process-related variables to aridity index (AI), which decreases as aridity increases. We found on a global scale that increasing aridity reduced soil gross nitrate consumption but increased soil nitrification capacity, mainly due to reduced soil microbial biomass carbon (MBC) and N (MBN) and increased soil pH. Threshold response of gross N production and retention to aridity was observed across terrestrial ecosystems. In croplands, gross nitrification and extractable nitrate were inhibited with increasing aridity below the threshold AI ~0.8-0.9 due to inhibited ammonia-oxidizing archaea and bacteria, while the opposite was favored above this threshold. In grasslands, gross N mineralization and immobilization decreased with increasing aridity below the threshold AI ~0.5 due to decreased MBN, but the opposite was true above this threshold. In forests, increased aridity stimulated nitrate immobilization below the threshold AI ~1.0 due to increased soil C/N ratio, but inhibited ammonium immobilization above the threshold AI ~1.3 due to decreased soil total N and increased MBC/MBN ratio. Soil dissimilatory nitrate reduction to ammonium decreased with increasing aridity globally and in forests when the threshold AI ~1.4 was passed. Overall, we suggest that any projected increase in aridity in response to climate change is likely to reduce plant N availability in arid regions while enhancing it in humid regions, affecting the provision of ecosystem services and functions.

Cumulative effects of drought have an impact on net primary productivity stability in Central Asian grasslands

Global warming has exacerbated the threat of drought in Central Asia, amplifying its ecological implications within the region's grassland ecosystems. This has become an increasingly prominent issue that requires attention and action. The temporal link between grassland development and drought is asymmetric. However, a quantitative assessment of the temporal effects of multiscale drought on Central Asian grasslands has yet to be explored. Based on correlation analysis and the coefficient of variation method, this study analysed the cumulative and lag effects of multitimescale drought on grassland NPP (net primary productivity) under different climatic zones, altitudes and water availabilities in Central Asia from 1982 to 2018, and discussed the impact of temporal effects on grassland NPP stability. Our results on the cumulative effects of drought on grasslands indicate the 6.72 months preceding NPP measurement was the duration for which, on average, drought was most strongly correlated with NPP. Additionally, we found a mean lagged effect of 5.36 months, meaning that the monthly drought 5.36 months prior to NPP measurement was, on average, most strongly correlated with NPP. The degree to which grassland NPP was affected by cumulative drought at a given level of water availability was inversely proportional to the number of cumulative drought months. Under different water availabilities, the lagged effect of grassland NPP was stronger in dry areas than in wet areas, and the number of lag months tended to decrease and then increase as the water availability increased. The percentage of areas where grassland NPP was dominated by the cumulative and lagging effects of drought was 30.02% and 69.98%, respectively. The stability of grassland NPP was adversely affected by the drought accumulation effect. The findings of this study contribute to a deeper understanding of the long-term effects of drought on grassland ecosystems. Additionally, it will aid in the development of strategies for mitigating and adapting to drought events, thereby minimizing their negative impacts on agriculture, livestock, and ecosystems.

Microbial growth under drought is confined to distinct taxa and modified by potential future climate conditions

Climate change increases the frequency and intensity of drought events, affecting soil functions including carbon sequestration and nutrient cycling, which are driven by growing microorganisms. Yet we know little about microbial responses to drought due to methodological limitations. Here, we estimate microbial growth rates in montane grassland soils exposed to ambient conditions, drought, and potential future climate conditions (i.e., soils exposed to 6 years of elevated temperatures and elevated CO2 levels). For this purpose, we combined 18O-water vapor equilibration with quantitative stable isotope probing (termed 'vapor-qSIP') to measure taxon-specific microbial growth in dry soils. In our experiments, drought caused >90% of bacterial and archaeal taxa to stop dividing and reduced the growth rates of persisting ones. Under drought, growing taxa accounted for only 4% of the total community as compared to 35% in the controls. Drought-tolerant communities were dominated by specialized members of the Actinobacteriota, particularly the genus Streptomyces. Six years of pre-exposure to future climate conditions (3 °C warming and + 300 ppm atmospheric CO2) alleviated drought effects on microbial growth, through more drought-tolerant taxa across major phyla, accounting for 9% of the total community. Our results provide insights into the response of active microbes to drought today and in a future climate, and highlight the importance of studying drought in combination with future climate conditions to capture interactive effects and improve predictions of future soil-climate feedbacks.

Climatic seasonality challenges the stability of microbial-driven deep soil carbon accumulation across China

Microbial residues contribute to the long-term stabilization of carbon in the entire soil profile, helping to regulate the climate of the planet; however, how sensitive these residues are to climatic seasonality remains virtually unknown, especially for deep soils across environmental gradients. Here, we investigated the changes of microbial residues along soil profiles (0-100 cm) from 44 typical ecosystems with a wide range of climates (~3100 km transects across China). Our results showed that microbial residues account for a larger portion of soil carbon in deeper (60-100 cm) vs. shallower (0-30 and 30-60 cm) soils. Moreover, we find that climate especially challenges the accumulation of microbial residues in deep soils, while soil properties and climate share their roles in controlling the residue accumulation in surface soils. Climatic seasonality, including positive correlations with summer precipitation and maximum monthly precipitation, as well as negative correlations with temperature annual range, are important factors explaining microbial residue accumulation in deep soils across China. In particular, summer precipitation is the key regulator of microbial-driven carbon stability in deep soils, which has 37.2% of relative independent effects on deep-soil microbial residue accumulation. Our work provides novel insights into the importance of climatic seasonality in driving the stabilization of microbial residues in deep soils, challenging the idea that deep soils as long-term carbon reservoirs can buffer climate change.

Concurrence of microplastics and heat waves reduces rice yields and disturbs the agroecosystem nitrogen cycle

Microplastic pollution and heat waves, as damaging aspects of human activities, have been found to affect crop production and nitrogen (N) cycling in agroecosystems. However, the impacts of the combination of heat waves and microplastics on crop production and quality have not been analyzed. We found that heat waves or microplastics alone had slight effects on rice physiological parameters and soil microbial communities. However, under heat wave conditions, the typical low-density polyethylene (LDPE) and polylactic acid (PLA) microplastics decreased the rice yields by 32.1% and 32.9%, decreased the grain protein level by 4.5% and 2.8%, and decreased the lysine level by 91.1% and 63.6%, respectively. In the presence of heat waves, microplastics increased the allocation and assimilation of N in roots and stems but decreased those in leaves, which resulted in a reduction in photosynthesis. In soil, the concurrence of microplastics and heat waves induced the leaching of microplastics, which resulted in decreased microbial N functionality and disturbed N metabolism. In summary, heat waves amplified the disturbance induced by microplastics on the agroecosystem N cycle and therefore exacerbated the decreases in rice yield and nutrients induced by microplastics, which indicates that the environmental and food risks of microplastics deserve to be reconsidered.

Drought is threatening plant growth and soil nutrients of grassland ecosystems: A meta-analysis

As a widespread direct effect of global warming, drought is currently wreaking havoc on terrestrial ecosystems' structure and function, however, the synthesized analysis is lacked to explore the general rules between drought changes and main functional factors of grassland ecosystems. In this work, meta-analysis was used to examine the impacts of drought on grassland ecosystems in recent decades. According to the results, drought greatly reduced aboveground biomass (AGB), aboveground net primary production (ANPP), height, belowground biomass (BGB), belowground net primary production (BNPP), microbial biomass nitrogen (MBN), microbial biomass carbon (MBC) and soil respiration (SR), and increased dissolved organic carbon (DOC), total nitrogen (TN), total phosphorus (TP), nitrate nitrogen (NO3^--N), and the ratio of microbial biomass carbon and nitrogen (MBC/MBN). The drought-related environmental factor mean annual temperature (MAT) was negatively correlated with AGB, height, ANPP, BNPP, MBC, and MBN, however, mean annual precipitation (MAP) had positive effect on these variables. These findings indicate that drought is threatening the biotic environment of grassland ecosystem, and the positive steps should be taken to address the negative effects of drought on grassland ecosystems due to climate change.

Nitrification, denitrification, and related functional genes under elevated CO2 : A meta-analysis in terrestrial ecosystems

Global change may have profound effects on soil nitrogen (N) cycling that can induce positive feedback to climate change through increased nitrous oxide (N₂ O) emissions mediated by nitrification and denitrification. We conducted a meta-analysis of the effects of elevated CO₂ on nitrification and denitrification based on 879 observations from 58 publications and 46 independent elevated CO₂ experiments in terrestrial ecosystems. We investigated the effects of elevated CO₂ alone or combined with elevated temperature, increased precipitation, drought, and N addition. We assessed the response to elevated CO₂ of gross and potential nitrification, potential denitrification, and abundances of related functional genes (archaeal amoA, bacterial amoA, nirK, nirS, and nosZ). Elevated CO₂ increased potential nitrification (+28%) and the abundance of bacterial amoA functional gene (+62%) in cropland ecosystems. Elevated CO₂ increased potential denitrification when combined with N addition and higher precipitation (+116%). Elevated CO₂ also increased the abundance of nirK (+25%) and nirS (+27%) functional genes in terrestrial ecosystems and of nosZ (+32%) functional gene in cropland ecosystems. The increase in the abundance of nosZ under elevated CO₂ was larger at elevated temperature and high N (+62%). Four out of 14 two-way interactions tested between elevated CO₂ and elevated temperature, elevated CO₂ and increased precipitation, and elevated CO₂ and N addition were marginally significant and mostly synergistic. The effects of elevated CO₂ on potential nitrification and abundances of bacterial amoA and nirS functional genes increased with mean annual temperature and mean annual precipitation. Our meta-analysis thus suggests that warming and increased precipitation in large areas of the world could reinforce positive responses of nitrification and denitrification to elevated CO₂ and urges the need for more investigations in the tropical zone and on interactive effects among multiple global change factors, as we may largely underestimate the effects of global change on soil N₂ O emissions.

Pattern recognition describing spatio-temporal drivers of catchment classification for water quality

Classification using spatial data is foundational for hydrological modelling, particularly for ungauged areas. However, models developed from classified land use drivers deliver inconsistent water quality results for the same land uses and hinder decision-making guided by those models. This paper explores whether the temporal variation of water quality drivers, such as season and flow, influence inconsistency in the classification, and whether variability is captured in spatial datasets that include original vegetation to represent the variability of biotic responses in areas mapped with the same land use. An Artificial Neural Network Pattern Recognition (ANN-PR) method is used to match catchments by Dissolved Inorganic Nitrogen (DIN) patterns in water quality datasets partitioned into Wet vs Dry Seasons and Increasing vs Retreating flows. Explainable artificial intelligence approaches are then used to classify catchments via spatial feature datasets for each catchment. Catchments matched for sharing patterns in both spatial data and DIN datasets were corroborated and the benefit of partitioning the observed DIN dataset evaluated using Kruskal Wallis method. The highest corroboration rates for spatial data classification with DIN classification were achieved with seasonal partitioning of water quality datasets and significant independence (p < 0.001 to 0.026) from non-partitioned datasets was achieved. This study demonstrated that DIN patterns fall into three categories suited to classification under differing temporal scales with corresponding vegetation types as the indicators. Categories 1 and 3 included dominance of woodlands in their datasets and catchments suited to classify together change depending on temporal scale of the data. Category 2 catchments were dominated by vineforest and classified catchments did not change under different temporal scales. This demonstrates that including original vegetation as a proxy for differences in DIN patterns will help guide future classification where only spatially mapped data is available for ungauged catchments and will better inform data needs for water modelling.

Rapid, sensitive analysis method for determining the nitrogen stable isotope ratio of total free amino acids in soil

RATIONALE

The amino acid-nitrogen (AA-N) isotope analysis of naturally abundant or isotope-labeled samples is indispensable for tracing nitrogen transfer in soil nitrogen biogeochemical cycling processes. Despite the usefulness of AA-N isotope analysis, the preparation methods are complex and time-consuming, and necessitate the use of toxic reagents.

METHODS

We present an improved, rapid method for AA-N isotope analysis with high precision. At a high pH, AA-N was released and oxidized to N₂ O using ClO^- under vacuum. Additionally, purge-and-trap isotope ratio mass spectrometry was used to analyze N₂ O. Moreover, we investigated the effect of various factors on the N₂ O conversion process with glycine and applied the results to seven representative single-N AAs (alanine, serine, cysteine, aspartic acid, glutamic acid, leucine, and phenylalanine) and five poly-N AAs (lysine, arginine, histidine, tryptophan, and asparagine), as well as side-chain analogs, blank reagent, and other N forms.

RESULTS

The concentration of ClO^- and the pH were determined to be crucial factors for achieving desirable AA-N to N₂ O conversion efficiencies. Glycine-N had the highest N₂ O yield of 70%, with isotopic results consistent with those of the reference values at a high precision (within 0.5‰ for natural abundance and 0.01 atom% for ¹⁵ N-enrichment) at the nanomolar N level. Additionally, the α-NH₂ AAs were labile, and the single-N AAs were more easily converted to N₂ O than poly-N AAs. With the exception of γ-aminobutyric acid, the N₂ O conversion efficiencies of the side-chain N analogs were very low (below 5%). This method was also applicable to the ¹⁵ N analysis of the total free AAs in complex soil samples without interference from analytical blanks and other forms of N.

CONCLUSIONS

Our method is highly selective for the α-NH₂ groups of an amino acid, and the oxidation of the side chain is difficult. In addition, the method is sensitive, rapid, and convenient, and does not require toxic reagents.