Global Carbon Cycle Research Articles

Structural transitions of calcium carbonate by molecular dynamics simulation.

Calcium carbonate (CaCO3) plays a crucial role in the global carbon cycle, and its phase diagram is of significant scientific interest. We used molecular dynamics to investigate selected structural phase transitions of calcium carbonate. Using the Raiteri potential, we explored the structural transitions occurring at the constant pressure of 1bar, with temperatures ranging from 300 to 2500K, and at the constant temperature of 1600K, with pressures ranging from 0 to 13GPa. With increasing temperature, the transitions between calcite, CaCO3-IV, and CaCO3-V were characterized. In the calcite structure, the carbonate ions are ordered in a planar triangular arrangement, alternating with layers of calcium ions. As the temperature increases, the transition from calcite to CaCO3-IV occurs, leading to partial disordering of the carbonate ions. At higher temperatures, CaCO3-IV transforms into CaCO3-V. Through free energy analysis, we classified the latter transition as a continuous phase transition. At a temperature of 2000K, a "disordered CaCO3" structure appears, characterized by low order within the calcium and carbonate sublattices and the free rotation of the carbonate ions. With increasing pressure, two calcium carbonate transformations were observed. At P = 2GPa, the CaCO3-V phase undergoes a phase transition into CaCO3-IV, demonstrating that the model can describe the transition between these two phases as pressure- and temperature-driven. At P = 4.25GPa, CaCO3-IV undergoes a phase transition into the CaCO3-Vb phase. This transition is classified as first-order based on free energy calculations.

Drivers of biomass stocks and productivity of tropical secondary forests.

Young tropical secondary forests play an important role in the local and global carbon cycles because of their large area and rapid biomass accumulation rates. This study examines how environmental conditions and forest attributes shape biomass compartments and the productivity of young tropical secondary forests. We compared 36 young secondary forest stands that differed in the time since agricultural land abandonment (2.3-3.6 years) from dry and wet regions in Ghana. We quantified biomass stocks in living and dead stems, roots, and soil, and aboveground biomass and litter productivity. We used structural equation models to evaluate how macroclimate, soil nutrients (N, P), and forest attributes (structure, diversity, and functional composition) affect ecosystem functioning. After three years of succession, tropical wet forests stored on average 115 t biomass ha-1 (the sum of aboveground living and dead biomass, belowground fine root biomass, and soil organic matter), and dry forests stored 99 t ha-1. These values represent 31% (in the wet forest) and 39% (in the dry forest) of the biomass compared with neighboring old-growth forests. The majority of forest ecosystem biomass was stored in the soil (70%) and aboveground living vegetation (25%). Macroclimate strongly shaped forest attributes, which in turn determined biomass stocks and productivity. Soil phosphorus strongly increased litter production and soil organic matter, confirming that it is a limiting element in tropical ecosystems. Tree density and species diversity increased forest biomass stocks, suggesting crown packing and complementary resource use enhance forest functioning. A more conservative trait composition (high wood density) increased biomass stocks but reduced productivity, indicating that quantity, identity, and quality of species affect ecosystem functioning.

A new approach in soil organic carbon estimation using machine learning algorithms: a study in a tropical forest in Vietnam

ABSTRACT Soil organic carbon (SOC) dataset augmentation, which enables the comprehensive monitoring of carbon sinks at regional and global scales, is vital for global carbon cycle management and soil fertility. SOC maps built by conventional laboratory or field measurements are time- and cost-consuming and especially difficult in forests. A new approach to build SOC maps with good accuracy and time efficiency and promptly respond to changes in SOC dynamics is, therefore, being identified. This study aimed to evaluate the ability of SOC estimation using a multiple linear regression model (MLR) and four machine learning algorithms: artificial neural networks (ANN), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) with satellite data sources and soil nutrient indicator data to find the optimal method. The results indicate that the SVM and XGBoost models demonstrated the best predictive abilities (R2 = 0.70 and 0.74, %RMSE = 8.8 and 8.3, MAE = 0.176 and 0.155) when using remote sensing variables and soil property variables, respectively. Band7_IDM, Band 5, Band4_IDM, RVI, NSMI, NDVI, Band 6, Band 7, and Band 4 were the most valuable variables in the SVM model, while NDVI, DVI, GVMI, NSMI, and Band4_Dive in the XGBoost model. The SVM model using remote sensing data may be applied to build SOC maps in Vietnamese forests instead of using conventional methods with a high accuracy (R2 = 0.74).

Tree species controls over nitrogen and phosphorus cycling in a wet tropical forest

AbstractWet tropical forests play an important role in the global carbon (C) cycle, but given current rates of land‐use change, nitrogen (N) and phosphorus (P) limitation could reduce productivity in regenerating forests in this biome. Whereas the strong controls of climate and parent material over forest recovery are well known, the influence of vegetation can be difficult to determine. We addressed species‐specific differences in plant traits and their relationships to ecosystem properties and processes, relevant to N and P supply to regenerating vegetation in experimental plantations in a single site in lowland wet forest in Costa Rica. Single‐tree species were planted in a randomized block design, such that climate, soil (an Oxisol), and land‐use history were similar for all species. In years 15–25 of the experiment, we measured traits regarding N and P acquisition and use in four native, broad‐leaved, evergreen tree species, including differential effects on soil pH, in conjunction with biomass and soil stocks and fluxes of N and P. Carbon biomass stocks increased significantly with increasing soil pH (p = 0.0184, previously reported) as did biomass P stocks (p = 0.0011). Despite large soil N pools, biomass P stocks were weakly dependent on traits associated with N acquisition and use (N2 fixation and leaf C:N, p < 0.09). Mass‐balance budgets indicated that soil organic matter (SOM) could supply the N and P accumulated in biomass via the process of SOM mineralization. Secondary soil P pools were weakly correlated with biomass C and P stocks (R = 0.47, p = 0.08) and were large enough to have supplied sufficient P in these rapidly growing plantations, suggesting that alteration of soil pH provided a mechanism for liberation of soil P occluded in organo‐mineral soil complexes and thus supply P for plant uptake. These results highlight the importance of considering species' effect on soil pH for restoration projects in highly weathered soils. This study demonstrates mechanisms by which individual species can alter P availability, and thus productivity and C cycling in regenerating humid tropical forests, and the importance of including traits into global models of element cycling.

Earth system responses to different levels of greenhouse gas emissions mitigation

Anthropogenic carbon dioxide (CO2) emissions are the main driver of climate change, with global warming increasing almost linearly with cumulative CO2 emissions. Hence, future warming will primarily result from future emissions of CO2 with contributions from other greenhouse gases (mostly CH4 and N2O) and aerosols. Climate projections of the 21st century, such as those assessed by the IPCC, are provided from comprehensive climate models, also called Earth System models, driven by scenarios of the 21st century evolution of emissions from those climate forcers. While it seems now inevitable that the world will reach 1.5°C of warming above pre-industrial levels by the early 2030s, the extent to which we exceed this warming level and how quickly we may be able to reduce temperatures again depends strongly on global activity taken now to limit emissions. In this paper, we review the current understanding on Earth system changes under two highly contrasted possible future worlds. We first focus on high-end scenarios, where anthropogenic emissions continue to increase over the course of the 21st century, leading to large warming levels, associated impacts on all components of the Earth System, and increased risks of triggering tipping points. We then assess low-end scenarios, where anthropogenic emissions rapidly decline, reaching net zero and potentially becoming net negative before the end of the 21st century. Such “overshoot” scenarios lead to a peak in global warming followed by a slow decline in global temperature, with some degree of reversibility in the global carbon cycle and key Earth system components. We also review paleoclimatic information relevant to these two contrasting future worlds. Paleoclimate evidence for geo-biosphere interactions shows that stabilizing feedbacks operate on millennial or longer timescales, whereas destabilizing feedbacks and tipping cascades occurred also on shorter timescales.

Net primary productivity of paleo-peatlands linked to deep-time glacial periods in the late Carboniferous and early Permian icehouse interval

Peatlands, an important organic carbon reservoir, play a crucial role in the global carbon cycle. The carbon accumulation of peatlands, reflected by net primary productivity (NPP), can have an impact on global carbon cycling and climate change. The late Carboniferous - early Permian is an icehouse period, during which numerous thick coal beds were accumulated in the North China Block (NCB) located within a low-latitude area, providing an opportunity for studying the carbon cycling under the glacial and interglacial climates. In this study, spectral analysis was performed on the natural gamma-ray (GR) logs of the Benxi, Taiyuan and Shanxi formations of the late Carboniferous to early Permian in a borehole section located within the Ordos Basin in western NCB. Cyclic signals related to astronomical orbital parameters were identified, including long eccentricity (~405 kyr), short eccentricity (~125 kyr and ~ 95 kyr), and obliquity (~35.5kyr). A floating astronomical time scale was established by using the long eccentricity signal, and this time scale was further used to constrain the durations of the accumulation of coal-forming paleo-peatlands. The paleo-peatland for the C8 + 9 coal seam (9 m thick) of the Taiyuan Formation lasted approximately 203 kyr, and the paleo-peatland for the C5 coal seam (4 m thick) of the Shanxi Formation lasted approximately 46 kyr. Using this timeframe and an estimation of carbon loss during coalification, the carbon accumulation rates of the late Carboniferous - early Permian low-latitude peatlands are calculated to be 104.7 ± 14.9 g·C·m−2·a−1for the C8+9 coal seam and 192.6 ± 11.6 g·C·m−2·a−1for the C5 coal seam. The NPP of the paleo-peatlands, which deducts a part of carbon loss caused by the loss of CO2 and CH4, can be calculated from the carbon accumulation rates. The calculated average NPP of the paleo-peatlands for the C8+9 seam was 199 ± 28 g·C·m−2·a−1, and that of the C5 seam was 366 ± 22 g·C·m−2·a−1. In combination of the absolute time scale calibrated by high-precision UPb dates from Palougou section in western NCB, the depositional time of the investigated strata was constrained to be from 300.1 ± 0.5 Ma to 294.3 ± 0.5 Ma. The coal seams of the late Carboniferous to early Permian in the NCB corresponds to interglacial interval around ~298 Ma. The peatland with a lower NPP corresponds to the warming stage and the peatland with a higher NPP corresponds to the cooling stage. This implies that a lower NPP of paleo-peatland tend to be less efficient in carbon storage, and could not reduce the atmospheric CO2 substantially. In contrast, a higher NPP of paleo-peatland tend to accelerate carbon fixation, leading to temperature decrease and the termination of interglacial interval in early Permian. The results of this study could provide insights into the relationship between the development of paleo-peatlands and the record of the paleoclimates during the same period, and could be helpful for the prediction of future climate change.

Analysis of spatiotemporal evolution characteristics and recovery patterns of mangrove forests in China since 1978

Mangrove ecosystems have garnered significant attention for their pivotal role in the global carbon cycle and their contributions to multiple UN Sustainable Development Goals. In China, the strategic pivot towards comprehensive ecological restoration in mangrove management underscores an urgent need for a nuanced understanding of mangrove evolutionary patterns. However, existing remote sensing-based information on mangrove dynamics exhibits discrepancies, lacking a cohesive and precise understanding. Accordingly, this study utilized high-resolution GaoFen imagery and precise visual interpretation methods to meticulously update an existing mangrove dataset through 2022, ensuring high accuracy and improved timeliness. Building on this, the study conducted a rigorous spatiotemporal analysis of mangrove dynamics from 1978 to 2022, developed an index to assess recovery status, and ultimately proposed targeted recommendations for conservation and restoration. Findings reveal that between 2018 and 2022, China’s mangrove expanse witnessed an average annual net increase of 2.82%, marking an unprecedented high. Breaking down the net change, the rate of gain accelerated, averaging 878.63 ha per year, but it is noteworthy that the losses also increased rapidly, tripling that of the previous period, mainly in regions with intense human activities such as the Pearl River Estuary. This finding complements the general perception of a continuous net increase in mangrove areas, highlighting the paradox of significant contraction occurring alongside rapid expansion. Additionally, by 2022, mangrove extent had recovered to 28,641 ha, essentially returning to the 1978 level, yet characterized by poor stability and significant spatial heterogeneity, with Guangdong and Hainan exhibiting recovery indices below the average. The study emphasizes that the ecosystem’s intrinsic restorative capabilities have emerged as a critical factor in offsetting losses and signaling a positive trend. The latest data provided by this study can offer actionable insights and support for mangrove conservation and restoration initiatives, serving the goal of ecosystem recovery and affirming their indispensable role in environmental governance.

Disentangling the response of species diversity, forest structure, and environmental drivers to aboveground biomass in the tropical forests of Western Ghats, India

Tropical forests are crucial to the global carbon cycle, but a significant knowledge gap in the precise distribution patterns of forest aboveground biomass (AGB) hinders our ability to formulate effective conservation efforts. A key unresolved issue is the lack of understanding of how forest AGB interacts with biotic and abiotic factors on large spatial scale. To address this, we used Structural Equation Modeling to disentangle the direct and indirect effects of environmental, anthropogenic, structural diversity species diversity and edaphic factors on AGB of trees, lianas and regenerating communities using the data from 96 1-ha plots in the central Western Ghats biodiversity hotspot, India. We hypothesized that the effect of structural attributes overrides AGB distribution, with relative contributions varying among plant communities. The landscape-level mean AGB was 245.12 ± 19.74 Mg ha−1, with SEM explaining 68–85 % of variations across the three vegetation communities. Structural diversity emerged as the primary mediator of the positive effects of taxonomic diversity on AGB in the regeneration community, whereas canopy cover and stem density linked diversity to AGB in adult tree and liana communities. Further, AGB showed a positive association with soil organic carbon in adult tree and regeneration communities, underscoring the significance of belowground resource availability on AGB. The results indicate that structural features were consistently the strongest AGB predictors at all levels of data aggregation, indicating the predominant role of niche complementarity and efficient space utilization in driving AGB, albeit differently across the plant communities. Our study emphasizes the importance of maintaining high structural features and managing taxonomic diversity while promoting soil fertility and minimizing disturbances to support AGB in tropical forests. We recommend testing the effects of predictor variables on biomass of vegetation communities independently to better understand the ecological principles of forest functioning.

Medium term hydrochemical and CO2 responses to anthropogenic and environmental changes in karst headwater streams.

This study investigates the intricate effects of lithology, temperature, discharge, and land use changes on headwater stream chemistry by analysing two decades of hydrochemical data from twenty karst headwater catchments in the Garonne River basin, France. Focused on the Pyrenees and the lowland (LM) and upland (UM) regions of the Massif Central, this study identified significant regional variations and commonalities in water chemistry. The headwater streams were clustered based on their hydrological and hydrochemical profiles, revealing strong similarities between upland sites, i.e. UM and Pyrenees, despite their geographical distance. The findings revealed a predominance of water driven by calcite dissolution, with specific influences from minor lithologies. Seasonal variations in water chemistry were primarily driven by hydrological conditions. Trend analyses highlighted increased pCO2 concentration in both the Pyrenees and UM, linked to higher forest density and agricultural activities, respectively. In contrast, LM exhibited increasing Ca2+ and HCO3- concentrations alongside decreasing trends in pCO2 and discharge, and increased nitrate concentration. While overall water temperatures increase, only a few sites exhibited significant warming trends, consistent with similar studies in the region and worldwide. These findings underscore the complex interplay between land use changes and hydrochemical dynamics in karst headwaters. They reveal that rising pCO2 concentration trends in upland regions are driven by reforestation and agricultural practices, which have significant implications in CO2 emissions, and consequently for regional and global carbon budgets and carbon-related policies. In lowland areas, declining water resources and increasing ion concentrations highlight potential challenges for water management, particularly in sensitive karst catchments. This study provides a baseline for understanding how karst headwaters respond to environmental changes. Expanding this research to other karst systems worldwide, under different climates, would help validate and model these findings, and improve our understanding of the global carbon cycle.

Effects of Prescribed Burns on Soil Respiration in Semi-Arid Grasslands

Carbon fluxes are valuable indicators of soil and ecosystem health, particularly in the context of climate change, where reducing carbon emissions from anthropogenic activities, such as forest fires, is a global priority. This study aimed to evaluate the impact of prescribed burns on soil respiration in semi-arid grasslands. Two treatments were applied: a prescribed burn on a 12.29 ha paddock of an introduced grass (Eragostis curvula) with 11.6 t ha−1 of available fuel, and a simulation of three fire intensities, over 28 circular plots (80 cm in diameter) of natural grasslands (Bouteloua gracilis). Fire intensities were simulated by burning with butane gas inside an iron barrel, which represented three amounts of fuel biomass and an unburned treatment. Soil respiration was measured with a soil respiration chamber over two months, with readings collected in the morning and afternoon. Moreover, CO2 emissions by combustion and productivity after fire treatment were quantified. The prescribed burns significantly reduced soil respiration: all fire intensities resulted in a decrease in soil respiration when compared with the unburned area. Changes in albedo increased the soil temperature; however, there was no relationship between changes in temperature and soil respiration; in contrast, precipitation highly stimulated it. These findings suggest that fire, under certain conditions, may not lead to more CO2 being emitted into the atmosphere by stimulating soil respiration, whereas aboveground biomass was reduced by 60%. However, considering the effects of fire in the long-term on changes in nutrient deposition, aboveground and belowground biomass, and soil properties is crucial to effectively quantify its impact on the global carbon cycle.

Changes in accumulation of land-based organic matter under recent climate change and anthropogenic impact: A tropical coastal perspective

Tropical continental shelves play an important role in the global carbon cycle especially in the context of increased anthropogenic interference and climate change. However, the long-term fate and response of sedimentary organic carbon (OC) in these regions remain poorly understood. In this study, we analyzed bulk OC and molecular biomarkers in a sediment core collected from the lower Gulf of Thailand, and compiled with several published records of sedimentary organic matter (OM) from other tropical Asian margins. Our results reveal a dramatic ∼ 40 % increase in terrestrial OC inputs since the 1980s, likely driven by the effects of accelerated coastal erosion from rising sea levels and the degradation of mangrove ecosystems. In addition, shifts in regional human activities, including changes in energy consumption patterns, have altered the sources of pyrogenic OM, contributing to the observed spatial and temporal variability of anthropogenic OM across tropical coastal margins. Molecular fingerprints highlight recent changes in the accumulation of land-based OM, showing an increased presence of erosion-derived and degraded OC, along with pyrogenic OM. This shift is linked to the combined effects of coastal retreat and basin-wide emissions, influenced by both natural climate forces and anthropogenic activities.

Molecular principles of the assembly and construction of a carboxysome shell.

Intracellular compartmentalization enhances biological reactions, crucial for cellular function and survival. An example is the carboxysome, a bacterial microcompartment for CO2 fixation. The carboxysome uses a polyhedral protein shell made of hexamers, pentamers, and trimers to encapsulate Rubisco, increasing CO2 levels near Rubisco to enhance carboxylation. Despite their role in the global carbon cycle, the molecular mechanisms behind carboxysome shell assembly remain unclear. Here, we present a structural characterization of α-carboxysome shells generated from recombinant systems, which contain all shell proteins and the scaffolding protein CsoS2. Atomic-resolution cryo-electron microscopy of the shell assemblies, with a maximal size of 54 nm, unveil diverse assembly interfaces between shell proteins, detailed interactions of CsoS2 with shell proteins to drive shell assembly, and the formation of heterohexamers and heteropentamers by different shell protein paralogs, facilitating the assembly of larger empty shells. Our findings provide mechanistic insights into the construction principles of α-carboxysome shells and the role of CsoS2 in governing α-carboxysome assembly and functionality.

Improving ecosystem respiration estimates for CO2 flux partitioning by discriminating water and temperature controls on above- and below-ground sources

Empirical models for estimating ecosystem respiration (ER) are widely used in CO2 flux partitioning algorithms that partition net ecosystem CO2 exchange (NEE) into gross primary productivity (GPP) and ER due to advantages of simple structures. However, empirical ER models remain limited due to single-source conceptualization that doesn’t discriminate different responses of aboveground respiration (AGR) and belowground respiration (BGR) to environmental factors (i.e., temperature and/or soil moisture). In this study, a dual-source module with only one parameter α was proposed and incorporated into six widely used ER models to enhance model capabilities. Long-term flux measurements of six typical terrestrial ecosystems and soil chamber respiration data at two sites were collected to evaluate models. Results showed that integration of the dual-source module can significantly improve the performance of empirical models in selected ecosystems with mean R2 improvement of 0.10 ± 0.16. The site years with relative increased R2 (ΔR2) larger than 10 % range from 6 % to 79 % amongst different models. Further validation between soil respiration and estimated BGR showed good correlations (r > 0.7) and demonstrated that proposed method can provide robust estimate of above/belowground respiration. Calibrated α varies amongst ecosystem types. Further analysis indicates variation of α is largely influenced by ratio of above/belowground biomass and annual average moisture conditions. Our findings highlight the critical need for partitioning ER models into dual-source for developing CO2 flux partitioning algorithms and support the approach as an effective means to enhance the understanding of global carbon cycles with changing climate.

The Dynamic Characteristics and Influencing Factors of Soil Respiration in Different Types of Grasslands in the Barkol Lake Basin

Determining regional and global carbon cycles hinges on investigating the dynamic characteristics and influencing factors of soil respiration in various types of natural grasslands located in arid regions, and these characteristics are important indicators for assessing the structural and functional health of grassland ecosystems. Such investigations also provide theoretical support for carbon sink monitoring, energy conservation, emission reduction and low-carbon development in the western arid zone and are important for obtaining an in-depth understanding of the carbon cycle, as well as for ecosystem management, restoration and the reconstruction of arid areas. In this study, during the growing season (from May to October) of 2022, the LI-8100A automated soil CO2 flux system was used to measure the soil respiration rate (Rs), temperature from 1.5 m above the surface to depths of 5–25 cm (T, T5, T10, T15, T20 and T25) and the soil moisture content (SM) at a depth of 20 cm in four types of grasslands: lowland meadow, alpine meadow, temperate desert steppe and temperate steppe desert. Five replicates were established for each plot, and the responses of Rs to T and SM were fitted to construct the optimal regression model. The results revealed that (1) the daily average soil respiration was highest in the lowland meadow (0.07 to 5.76 μmol·m−2·s−1), followed by the alpine meadow (−0.57 to 0.95 μmol·m−2·s−1), the temperate desert steppe (−0.45 to 3.0 μmol·m−2·s−1) and the temperate steppe desert (−1.29 to 1.61 μmol·m−2·s−1); (2) the soil respiration rates of the four grassland types were significantly correlated with the temperature in the 5–15 cm soil layer, and the best model was an exponential function; the peak values generally appeared between 13:00 and 17:00 (h), with the minimum values at 2:00 or 8:00 (h); the maximum value was observed in July–August, and the minimum value was observed in October; and the soil respiration in the lowland meadow was higher than that in the other three types of grassland during the same period. The average variation intensities of the soil respiration from May to October were as follows: temperate steppe desert (91.78%) > temperate desert steppe (76%) > alpine meadow (58.77%) > lowland meadow (43.93%). (3) The partial correlation analysis revealed that when soil temperature was used as a control, the correlation between SM and soil respiration in the four types of grasslands changed, and the coefficient of determination (R2) increased to varying degrees, explaining up to 80% of the variation in the soil respiration in the lowland meadows. The correlation between soil respiration and the SM normalized to 10 °C explained up to 93.8% of the variation in soil respiration; the two-factor fitting equations revealed that the model with soil temperature and SM was superior to the single-factor model with either soil temperature or SM.

Automated Stock Volume Estimation Using UAV-RGB Imagery

Forests play a critical role in the global carbon cycle, with carbon storage being an important carbon pool in the terrestrial ecosystem with tree crown size serving as a versatile ecological indicator influencing factors such as tree growth, wind resistance, shading, and carbon sequestration. They help with habitat function, herbicide application, temperature regulation, etc. Understanding the relationship between tree crown area and stock volume is crucial, as it provides a key metric for assessing the impact of land-use changes on ecological processes. Traditional ground-based stock volume estimation using DBH (Diameter at Breast Height) is labor-intensive and often impractical. However, high-resolution UAV (unmanned aerial vehicle) imagery has revolutionized remote sensing and computer-based tree analysis, making forest studies more efficient and interpretable. Previous studies have established correlations between DBH, stock volume and above-ground biomass, as well as between tree crown area and DBH. This research aims to explore the correlation between tree crown area and stock volume and automate stock volume and above-ground biomass estimation by developing an empirical model using UAV-RGB data, making forest assessments more convenient and time-efficient. The study site included a significant number of training and testing sites to ensure the performance level of the developed model. The findings underscore a significant association, demonstrating the potential of integrating drone technology with traditional forestry techniques for efficient stock volume estimation. The results highlight a strong exponential correlation between crown area and stem stock volume, with a coefficient of determination of 0.67 and mean squared error (MSE) of 0.0015. The developed model, when applied to estimate cumulative stock volume using drone imagery, demonstrated a strong correlation with an R2 of 0.75. These results emphasize the effectiveness of combining drone technology with traditional forestry methods to achieve more precise and efficient stock volume estimation and, hence, automate the process.

Soil plastisphere: The nexus of microplastics, bacteria, and biofilms

Bacteria are one of the oldest life forms on Earth, dating back to more than 3.5 billion years ago. They control the global cycling of carbon, nitrogen, and oxygen. They provide plants, fungi and other organisms with the necessary nutrients and elements. They help us digest our food, protect us against pathogens, and even affect our behavior. Microplastics, however, have disrupted the bacterial ecosystems across the globe, from the soil to the oceans. Microplastics are tiny plastic particles formed as a result of the breakdown of the consumer products and plastic waste. Due to their stability and persistence, they can travel long distances in the soil and subsurface environments, ultimately making their way to the water resources, rivers, and oceans. In this journey, they interact with bacteria and other micro/macro-organisms, become ingested or colonized, and act as carriers for contaminants and pathogens. How and whether bacteria adapt to these new microplastic-rich ecosystems are open questions with far-reaching implications for the health of our planet and us. Therefore, there is an urgent need for improving our fundamental understanding of bacterial interactions with the microplastics in complex environments. In this commentary, we focus on the nexus of bacteria, biofilms, and microplastics, also known as the “plastisphere”, and discuss the challenges and opportunities.

Smithian–Spathian carbonate geochemistry in the northern Thaynes Group influenced by multiple styles of diagenesis

AbstractThe Smithian–Spathian boundary interval is characterised by a positive carbon isotopic excursion in both δ13Ccarb and δ13Corg, concurrent with a major marine ecosystem reorganisation and the resurgence of microbialite facies. While these δ13C records have been traditionally interpreted as capturing global carbon cycle behaviour, recent studies have suggested that at least some excursions in early Triassic δ13C values may incorporate influences from authigenic or early diagenetic processes. To examine the mechanistic drivers of Smithian–Spathian boundary geochemistry, the carbonate geochemistry of a core from Georgetown, Idaho (USA), was analysed using a coupled δ44/40Ca, δ26Mg and trace‐metal framework. While the δ13C record in the Georgetown core is broadly similar to other Smithian–Spathian boundary sections, portions of the record coincide with substantial shifts in δ44/40Ca, δ26Mg and trace‐metal compositions that cannot feasibly be interpreted as primary. Furthermore, these geochemical variations correspond with lithology: The δ13C record is modulated by variations in the extent of dolomitisation, and the diagenetic styles recognised here coincide with individual lithostratigraphic units. A primary shift in local sea water δ13C values is inferred from the most geochemically unaltered strata, from ca 3‰ in the middle Smithian to ca 5‰ in the early Spathian, although the timing and pathway through which this occurs cannot be readily identified nor extrapolated globally. Therefore, the Georgetown core may not directly record exogenic carbon cycle evolution, showing that there is a need for the careful reconsideration of the Smithian–Spathian boundary—and more broadly, Early Triassic—geochemical records to examine potential local and diagenetic influences on sedimentary geochemistry.

Adaptive expression of phage auxiliary metabolic genes in paddy soils and their contribution toward global carbon sequestration

Habitats with intermittent flooding, such as paddy soils, are crucial reservoirs in the global carbon pool; however, the effect of phage-host interactions on the biogeochemical cycling of carbon in paddy soils remains unclear. Hence, this study applied multiomics and global datasets integrated with validation experiments to investigate phage-host community interactions and the potential of phages to impact carbon sequestration in paddy soils. The results demonstrated that paddy soil phages harbor a diverse and abundant repertoire of auxiliary metabolic genes (AMGs) associated with carbon fixation, comprising 23.7% of the identified AMGs. The successful annotation of protein structures and promoters further suggested an elevated expression potential of these genes within their bacterial hosts. Moreover, environmental stressors, such as heavy metal contamination, cause genetic variation in paddy phages and up-regulate the expression of carbon fixation AMGs, as demonstrated by the significant enrichment of related metabolites (P < 0.05). Notably, the findings indicate that lysogenic phages infecting carbon-fixing hosts increased by 10.7% under heavy metal stress. In addition, in situ isotopic labeling experiments induced by mitomycin-C revealed that by increasing heavy metal concentrations, 13CO2 emissions from the treatment with added lysogenic phage decreased by approximately 17.9%. In contrast, 13C-labeled microbial biomass carbon content increased by an average of 35.4% compared to the control. These results suggest that paddy soil phages prominently influence the global carbon cycle, particularly under global change conditions. This research enhances our understanding of phage-host cooperation in driving carbon sequestration in paddy soils amid evolving environmental conditions.

Structure and identification of the native PLP synthase complex from Methanosarcina acetivorans lysate.

Many protein-protein interactions behave differently in biochemically purified forms as compared to their in vivo states. As such, determining native protein structures may elucidate structural states previously unknown for even well-characterized proteins. Here, we apply the bottom-up structural proteomics method, cryoID, toward a model methanogenic archaeon. While they are keystone organisms in the global carbon cycle and active members of the human microbiome, there is a general lack of characterization of methanogen enzyme structure and function. Through the cryoID approach, we successfully reconstructed and identified the native Methanosarcina acetivorans pyridoxal 5'-phosphate (PLP) synthase (PdxS) complex directly from cryogenic electron microscopy (cryo-EM) images of fractionated cellular lysate. We found that the native PdxS complex exists as a homo-dodecamer of PdxS subunits, and the previously proposed supracomplex containing both the synthase (PdxS) and glutaminase (PdxT) was not observed in cellular lysate. Our structure shows that the native PdxS monomer fashions a single 8α/8β TIM-barrel domain, surrounded by seven additional helices to mediate solvent and interface contacts. A density is present at the active site in the cryo-EM map and is interpreted as ribose 5-phosphate. In addition to being the first reconstruction of the PdxS enzyme from a heterogeneous cellular sample, our results reveal a departure from previously published archaeal PdxS crystal structures, lacking the 37-amino-acid insertion present in these prior cases. This study demonstrates the potential of applying the cryoID workflow to capture native structural states at atomic resolution for archaeal systems, for which traditional biochemical sample preparation is nontrivial.IMPORTANCEArchaea are one of the three domains of life, classified as a phylogenetically distinct lineage. There is a paucity of known enzyme structures from organisms of this domain, and this is often exacerbated by characteristically difficult growth conditions and a lack of readily available molecular biology toolkits to study proteins in archaeal cells. As a result, there is a gap in knowledge concerning the mechanisms governing archaeal protein behavior and their impacts on both the environment and human health; case in point, the synthesis of the widely utilized cofactor pyridoxal 5'-phosphate (PLP; a vitamer of vitamin B6, which humans cannot produce). By leveraging the power of single-particle cryo-EM and map-to-primary sequence identification, we determine the native structure of PLP synthase from cellular lysate. Our workflow allows the (i) rapid examination of new or less characterized systems with minimal sample requirements and (ii) discovery of structural states inaccessible by recombinant expression.

Thermal degradation of 18 amino acids during pyrolytic processes

Biomass pyrolysis greatly impacts climates, ecosystem dynamics, air quality, human health, global carbon and nitrogen cycle. The emissions of nitrogen-containing compounds from biomass pyrolysis highly depend on the protein nitrogen existing in biomass. However, the quantitative kinetic information, including the rate constant and apparent activation energy of individual amino acid induced by pyrolysis are still yet to be well-constrained. Towards this, we performed a series of controlled pyrolysis experiments where 18 equimolar free amino acids standard mixtures were pyrolyzed under ambient oxygen at temperatures between 160 and 240 °C. Additionally, straw samples were pyrolyzed to understand the mechanism of combined amino acids in protein liberation to free amino acids during pyrolytic processes. Our observations indicated that an increase in heating duration and temperature promote the degradation of free amino acids. Further, the heating stability of the 18 examined amino acids varied, which could be related to the length and functional groups present in their side chains. Our result shows that the degradation processes of all examined 18 amino acids followed irreversible first-order reaction kinetics in air within the given temperature range, with their activation energy ranging from 88.5 to 137.44 kJ mol−1. The distinct distribution patterns of both combined and free amino acids in aerosol samples from straw pyrolytic processes were obtained. The kinetic information of amino acids garnered herein helps to elucidate the transformation mechanisms of nitrogenous compounds during biomass burning.