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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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Soil organic carbon (SOC) accrual, and particularly the formation of fine fraction carbon (OCfine), has a large potential to act as sink for atmospheric CO2. For reliable estimates of this potential and efficient policy advice, the major limiting factors for OCfine accrual need to be understood. The upper boundary of the correlation between fine mineral particles (silt + clay) and OCfine is widely used to estimate the maximum mineralogical capacity of soils to store OCfine, suggesting that mineral surfaces get C saturated. Using a dataset covering the temperate zone and partly other climates on OCfine contents and a SOC turnover model, we provide two independent lines of evidence, that this empirical upper boundary does not indicate C saturation. Firstly, the C loading of the silt + clay fraction was found to strongly exceed previous saturation estimates in coarse-textured soils, which raises the question of why this is not observed in fine-textured soils. Secondly, a subsequent modelling exercise revealed, that for 74% of all investigated soils, local net primary production (NPP) would not be sufficient to reach a C loading of 80 g C kg-1 silt + clay, which was previously assumed to be a general C saturation point. The proportion of soils with potentially enough NPP to reach that point decreased strongly with increasing silt + clay content. High C loadings can thus hardly be reached in more fine-textured soils, even if all NPP would be available as C input. As a pragmatic approach, we introduced texture-dependent, empirical maximum C loadings of the fine fraction, that decreased from 160 g kg-1 in coarse to 75 g kg-1 in most fine-textured soils. We conclude that OCfine accrual in soils is mainly limited by C inputs and is strongly modulated by texture, mineralogy, climate and other site properties, which could be formulated as an ecosystem capacity to stabilise SOC.

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Groundwater aquifers are ecological hotspots with diverse microbes essential for biogeochemical cycles. Their ecophysiology has seldom been studied on a basin scale. In particular, our knowledge of chemosynthesis in the deep aquifers where temperatures reach 60 °C, is limited. Here, we investigated the diversity, activity, and metabolic potential of microbial communities from nine wells reaching ancient groundwater beneath Israel's Negev Desert, spanning two significant, deep (up to 1.5 km) aquifers, the Judea Group carbonate and Kurnub Group Nubian sandstone that contain fresh to brackish, hypoxic to anoxic water. We estimated chemosynthetic productivity rates ranging from 0.55 ± 0.06 to 0.82 ± 0.07 µg C L-1 d-1 (mean ± SD), suggesting that aquifer productivity may be underestimated. We showed that 60% of MAGs harbored genes for autotrophic pathways, mainly the Calvin-Benson-Bassham cycle and the Wood-Ljungdahl pathway, indicating a substantial chemosynthetic capacity within these microbial communities. We emphasize the potential metabolic versatility in the deep subsurface, enabling efficient carbon and energy use. This study set a precedent for global aquifer exploration, like the Nubian Sandstone Aquifer System in the Arabian and Western Deserts, and reconsiders their role as carbon sinks.

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Human activities and climate change impact ecosystem services, thereby affecting economic and social sustainable development. Measuring the heterogeneity in space and time of how human activities affect ecosystem services poses a challenge for the sustainable management of land resources. Based on "human appropriation of net primary production (HANPP) - Fractional Vegetation Cover (FVC) - Soil Conservation Service (SCS)" cascading effect, first, a geographically and temporally weighted regression (GTWR) model was employed to assess the impact of HANPP in percent of potential NPP (hereafter HANPP%) on the FVC; second, changes in the FVC caused by human activities were quantified; and third, the potential soil conservation service (SCSp) and actual soil conservation service (SCSa) were estimated using the Revised Universal Soil Loss Equation (RUSLE) model, and the difference between them represented the changes in soil conservation service caused by human activities (SCSh). Taking the Qinghai-Tibet Plateau as a case study, we found that the GTWR model was well suited for analyzing the relationship between the HANPP% and the FVC (R2 = 0.897). The HANPP resulted in a decrease in the FVC from 0.222 in 2001 to 0.199 in 2019 and correspondingly resulted in a decrease in the ratio of SCSh to SCSp from 8.95% to 7.24%. This study provides a quantitative method that allows quantifying the influence of human activity on ecosystem services closely related to the FVC.

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Many evidences have shown that both atmospheric and soil droughts can constrain vegetation growth and further threaten its ability to sequester carbon. However, the trigger thresholds of vegetation production loss under different atmospheric and soil drought conditions are still unknown. In this study, we proposed a Copula and Bayesian equations-based framework to investigate trigger thresholds of various vegetation production losses under different atmospheric and soil drought conditions. The trigger thresholds dynamics and their possible causes were also investigated. To achieve this goal, we first simulated the gross primary production, soil moisture, and vapor pressure deficit over China during 1961-2018 using an individual-based, spatially explicit dynamic global vegetation model. The main drivers of the dynamic change in trigger thresholds were then explored by Random Forest model. We found that soil drought caused greater stress on gross primary production loss than atmospheric drought, with a larger impact area and higher probability of damage. In terms of spatial distribution, the risk probability of gross primary production loss was higher in eastern China than in western China, and the drought trigger threshold was also smaller in eastern China. In addition, the trigger thresholds for atmospheric and soil drought in most regions exhibited a decreasing trend from 1961 to 2018, while the CO2 fertilization enhanced the drought tolerance of vegetation. The reduction in CO2 fertilization effect slowed down the downward trend of trigger threshold for soil drought, while the increase in temperature exacerbated the downward trend of trigger threshold for atmospheric drought. This study highlighted the larger effect of soil drought on vegetation production loss than atmospheric drought and implied that climate change can modulate the trigger threshold of vegetation production losses under drought conditions. These findings provide scientific guidance for managing the increasing risk of drought on vegetation and optimizing watershed water allocation.

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The dune ecosystem plays a significant role in the global carbon cycle. The Horqin Sandy Land is a typical semi-arid fragile ecosystem in northern China. Understanding the magnitudes and dynamics of carbon dioxide fluxes within this region is essential for understanding the carbon balance. Used 6 years (2013-2018) measurements from an eddy-covariance system, we analyzed the dynamic patterns of net ecosystem carbon exchange (NEE), gross primary production (GPP), and ecosystem respiration (Reco) of the dune ecosystem in Horqin Sandy Land and examined their responses to climate factors with a focus on the precipitation. The results showed that the NEE of the dune ecosystem fluctuated from -166 to 100 gCO2·m-2·year-1 across the 6 growing seasons, with an average of -56 gCO2·m-2·year-1. The precipitation was not a key factor influencing the carbon flux variability. During the mid-growth stage, GPP was primarily affected by the effective precipitation frequency (R2 ranging from 0.65 to 0.85, P < 0.05), followed by fractional vegetation cover (R2 ranging from 0.65 to 0.68, P < 0.05). However, in the early and late growth stages, temperature predominantly drove the carbon flux (R2 = 0.75, P < 0.01). The interannual variability of carbon flux can be predominantly elucidated by phenological indicators such as CO2 uptake (CUstart), end of CO2 uptake (CUend), CO2 uptake period (CUP), and Spring lag. The results demonstrated the dune ecosystem is a weak carbon sink in semi-arid ecosystems. Furthermore, we emphasized the significance of effective precipitation frequency in regulating carbon fluxes. Our results provide a foundational understanding of the carbon balance in semi-arid ecosystems.

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Recent climate warming has significantly affected the sensitivity of Gross Primary Productivity (GPP) to precipitation within China's agricultural ecosystems. Nonetheless, the spatial and temporal nonlinear evolution patterns of GPP-precipitation sensitivity under climate change, as well as the underlying drivers and long-term trends of this sensitivity, are not well understood. This study employs correlation analysis to quantify the sensitivity between GPP and precipitation in China's agricultural ecosystems, and utilizes nonlinear detection algorithms to examine the long-term changes in this sensitivity. Advanced machine learning techniques and frameworks are subsequently applied to analyze the driving factors of GPP-precipitation sensitivity in China's agricultural ecosystems. The findings reveal that approximately 49.00 % of the analyzed pixels exhibit a significant positive correlation between GPP and precipitation. Nonlinear change analysis indicates spatial heterogeneity in GPP-precipitation sensitivity across China's agricultural ecosystems, with patterns showing initial increases followed by decreases accounting for 25.12 %, and patterns of initial decreases followed by increases at 13.27 %. Machine learning analysis identifies temperature, soil moisture, and crop water footprint as the primary factors influencing GPP-precipitation sensitivity in agricultural ecosystems. This study is the first to introduce crop water footprint as a significant factor in the analysis of GPP-precipitation sensitivity. It not only offers new insights into the temporal nonlinear changes and driving factors of GPP-precipitation sensitivity but also underscores the importance of enhancing agricultural water efficiency to maintain agricultural ecosystem health and ensure food security under climate change.

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Little is known of primary production in dark hypersaline ecosystems despite the prevalence of such environments on Earth today and throughout its geologic history. Here, we generated and analyzed metagenome-assembled genomes (MAGs) organized as operational taxonomic units (OTUs) from three depth intervals along a 30-cm sediment core from the north arm of Great Salt Lake, Utah. The sediments and associated porewaters were saturated with NaCl, exhibited redox gradients with depth, and harbored nitrogen-depleted organic carbon. Metabolic predictions of MAGs representing 36 total OTUs recovered from the core indicated that communities transitioned from aerobic and heterotrophic at the surface to anaerobic and autotrophic at depth. Dark CO2 fixation was detected in sediments and the primary mode of autotrophy was predicted to be via the Wood-Ljungdahl pathway. This included novel hydrogenotrophic acetogens affiliated with the bacterial class Candidatus Bipolaricaulia. Minor populations were dependent on the Calvin cycle and the reverse tricarboxylic acid cycle, including in a novel Thermoplasmatota MAG. These results are interpreted to reflect the favorability of and selectability for populations that operate the lowest energy requiring CO2-fixation pathway known, the Wood-Ljungdahl pathway, in anoxic and hypersaline conditions that together impart a higher energy demand on cells.

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This comprehensive study examines primary production (PP) within the Spitsbergen fjords, Hornsund, and Kongsfjord, over a 25-year period (1994-2019), across 45 stations and 348 incubation levels at various depths. PP and hydrological parameters were measured at 28 sampling stations in Kongsfjorden and 17 in Hornsund, with the locations of "Glacier," "Inner," and "Outer" zones defined to reflect the varying influence of glacial meltwater. Our study revealed spatial and temporal variability in PP, both at the surface and within the water column with very high depth resolution. The highest PP values were observed in the Glacier and Inner zones of Hornsund, particularly in the water layer up to 3 m depth, exceeding 20 mgC m-3 h-1. A notable decline in PP with increasing depth was observed in both fjords, with the Glacier zones displaying the highest productivity at the surface. The study also highlights the influence of glacial meltwater on surface water conditions, affecting the PP in the upper layers of both fjords. The observed gradient in the depth of maximum PP toward the mouth of the fjord varied between the two fjords, with Kongsjord displaying more dynamic variations. The spatial distribution of integrated primary production (Pi) suggested lower productivity in the glacial regions, likely due to light limitation caused by high concentrations of mineral particulate matter. The values of Pi were considerably higher in Hornsund, approximately twice as high overall, with specific emphasis on the Glacier and Inner zones where Pi values were about 6.5 and 2.5 times higher, respectively, when compared to those observed in Kongsfjord.

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Understanding what regulates ecosystem functional responses to disturbance is essential in this era of global change. However, many pioneering and still influential disturbance-related theorie proposed by ecosystem ecologists were developed prior to rapid global change, and before tools and metrics were available to test them. In light of new knowledge and conceptual advances across biological disciplines, we present four disturbance ecology concepts that are particularly relevant to ecosystem ecologists new to the field: (a) the directionality of ecosystem functional response to disturbance; (b) functional thresholds; (c) disturbance-succession interactions; and (d) diversity-functional stability relationships. We discuss how knowledge, theory, and terminology developed by several biological disciplines, when integrated, can enhance how ecosystem ecologists analyze and interpret functional responses to disturbance. For example, when interpreting thresholds and disturbance-succession interactions, ecosystem ecologists should consider concurrent biotic regime change, non-linearity, and multiple response pathways, typically the theoretical and analytical domain of population and community ecologists. Similarly, the interpretation of ecosystem functional responses to disturbance requires analytical approaches that recognize disturbance can promote, inhibit, or fundamentally change ecosystem functions. We suggest that truly integrative approaches and knowledge are essential to advancing ecosystem functional responses to disturbance.

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Water quality modeling can help to understand the source, transport, transformation and fate of dissolved organic matter (DOM) in aquatic systems. However, water quality models typically use biological oxygen demand as the state variable for DOM, which poorly represents the bio-refractory fraction of the DOM pool. Furthermore, photodegradation, which has a significant impact on the fate of DOM, is often neglected in water quality models. To fill these gaps, we developed the FLOTATION (FLuorescent dOm Transport And TransformatION) model, which includes three processes: biodegradation, photodegradation, and primary production formation. We applied the model to the Nanfei River to understand the source, spatial distribution, and fate of DOM under low flow conditions. The model was set up and calibrated with the longitudinal measurements of four humic-like components (C1-C4) and one protein-like component (C5) identified by excitation-emission matrix parallel factor analysis (EEM-PARAFAC). The results showed that the simulation reproduced the longitudinal variations of all components well. The photodegradation process removed 18 %, 15 % and 21 % of the total input loadings of the humic-like components C1, C2 and C4, respectively. Algal primary production contributed 18 % of the downstream transport loading, constituting an important autochthonous source. For the protein-like C5, photodegradation and biodegradation together removed 7 % of the input loading. Our newly developed FLOATATION model can facilitate a comprehensive understanding of the fate and transport of DOM in aquatic environments.

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Ongoing warming is leading to the accelerated shrinkage of glaciers located on Arctic islands. Consequently, the influence of glacial meltwater on phytoplankton primary production in Arctic bays becomes critically important in an era of warming. This work studies the spatiotemporal variation of primary production and chlorophyll a concentration in the bays along the eastern coast of the Novaya Zemlya archipelago. Data were collected during nine cruises performed from July to October (2013-2022). The effect of underwater photosynthetically available radiation (PAR) and nutrients on primary production was assessed separately for bays influenced by glacial meltwater (glacial bays) and those without such influence (non-glacial bays). The median value of water column-integrated primary production (IPP) for all bays was 38 mgC m-2 d-1, characterizing them as oligotrophic areas. IPP in non-glacial bays was found to be 2.3-fold and 1.4-fold higher than that in glacial bays during summer and autumn, respectively. Underwater PAR was the main abiotic factor determining IPP during the ice-free period. In the entire bays nutrient concentrations were high, exceeding the limiting values for growth and photosynthesis of phytoplankton. It was concluded that the high turbidity from glacial meltwater runoff leads to decreased underwater PAR and, consequently, to a decline in IPP. This study demonstrates that rapid warming could have a negative impact on the productivity of high Arctic bays and their adjacent areas.

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The eastern Arabian Sea (EAS) is known for its unique oceanographic features such as the seasonal monsoonal winds, upwelling of nutrient-rich waters and a significant increase in primary productivity during the monsoon season. In this study, we utilised the shotgun metagenomics approach to determine the seasonal variations in bacterial taxonomic and functional profiles during the non-monsoon and monsoon seasons in the EAS. Significant seasonal variations in the bacterial community structure were observed at the phylum and genera levels. These findings also correspond with seasonal shifts in the functional profiles of the bacterial communities based on the variations of genes encoding enzymes associated with different metabolic pathways. Pronounced seasonal variation of bacterial taxa was evident with an increased abundance of Idiomarina, Marinobacter, Psychrobacter and Alteromonas of Proteobacteria, Bacillus and Staphylococcus of Firmicutes during the non-monsoon season. These taxa were linked to elevated nucleotide and amino acid biosynthesis, amino acid and lipid degradation. Conversely, during the monsoon, the taxa composition changed with Alteromonas, Candidatus Pelagibacter of Proteobacteria and Cyanobacteria Synechococcus; contributing largely to the amino acid and lipid biosynthesis, fermentation and inorganic nutrient metabolism which was evident from functional analysis. Regression analysis confirmed that increased seasonal primary productivity significantly influenced the abundance of genes associated with carbohydrate, protein and lipid metabolism. These highlight the pivotal role of seasonal changes in primary productivity in shaping the bacterial communities, their functional profiles and driving the biogeochemical cycling in the EAS.

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Carbon dioxide sequestration from the atmosphere is commonly assessed using the eddy covariance method. Its net flux signal can be decomposed into gross primary production and ecosystem respiration components, but these have seldom been tested against independent methods. In addition, eddy covariance lacks the ability to partition carbon sequestration among individual trees or species within mixed forests. Therefore, we compared gross primary production from eddy covariance versus an independent method based on sap flow and water-use efficiency, as measured by the tissue heat balance method and δ13C of phloem contents, respectively. The latter measurements were conducted on individual trees throughout a growing season in a mixed broadleaf forest dominated by three tree species, namely English oak, narrow-leaved ash and common hornbeam (Quercus robur L., Fraxinus angustifolia Vahl, and Carpinus betulus L., respectively). In this context, we applied an alternative ecophysiological method aimed at verifying the accuracy of a state-of-the-art eddy covariance system while also offering a solution to the partitioning problem. We observed strong agreement in the ecosystem gross primary production estimates (R2 = 0.56; P < 0.0001), with correlation being especially high and nearly on the 1:1 line in the period before the end of July (R2 = 0.85; P < 0.0001). After this period, the estimates of gross primary production began to diverge. Possible reasons for the divergence are discussed, focusing especially on phenology and the limitation of the isotopic data. English oak showed the highest per-tree daily photosynthetic rates among tree species, but the smaller, more abundant common hornbeam contributed most to the stand-level summation, especially early in the spring. These findings provide a rigorous test of the methods and the species-level photosynthesis offers avenues for enhancing forest management aimed at carbon sequestration.

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Diatoms are key components of freshwater ecosystems and are regularly used for paleolimnological reconstructions, in which defining species optima and tolerances is fundamental for interpreting assemblage shifts in a sediment record. Here, we examined responses of diatoms across three major environmental gradients-dissolved inorganic carbon (range: 0.1-230.5 mg · L-1), total phosphorus (range: 3-326 µg · L-1), and maximum lake depth (range: 0.9-55.0 m)-taken from 158 lakes from across Canada. The lakes were sampled as part of the LakePulse Network, which conducted a standardized sampling of lakes spanning 12 Canadian ecozones. Hierarchical logistic regression was used to model the species responses of 37 common taxa, and species optima and tolerances were calculated with weighted average modeling. The most common response detected was the symmetrical unimodal model, suggesting we likely captured the full environmental ranges for many species, although skewed unimodal responses were also common. Indicator species analyses identified taxa with high predictive values and fidelities to particular ecozones, with high-nutrient-adapted taxa such as Stephanodiscus spp. and Cyclotella meneghiniana characteristic of the agriculturally productive Prairie region. The Prairies stood out in the dataset as the region with the most unique flora from the local contribution to beta diversity analysis. Overall, the autecological data provided by our study will allow for improved interpretations of paleolimnological records and other biomonitoring efforts, addressing management concerns and contributing to a better understanding of our changing environment.

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Primary production is an important driver of marine carbon storage. Besides the major nutrient elements nitrogen, phosphorus, and silicon, primary production also depends on the availability of nutrient-type metals (e.g., Cu, Fe, Mo) and the absence of toxicologically relevant metals (e.g., Ni, Pb). Especially in coastal oceans, carbon storage and export to the open ocean is highly variable and influenced by anthropogenic eutrophication and pollution. To model future changes in coastal carbon storage processes, a solid baseline of nutrient and metal concentrations is crucial. The North Sea is an important shelf sea, influenced by riverine, atmospheric, Baltic Sea, and North Atlantic inputs. We measured the concentrations of dissolved nutrients (NH4+, NO3-, PO43-, and SiO44-) and 26 metals in 337 water samples from various depths within the entire North Sea and Skagerrak. A principal component analysis enabled us to categorize the analytes into three groups according to their predominant behavior: tracers for seawater (e.g., Mo, U, V), recycling (e.g., NO3-, PO43-, SiO44-), and riverine or anthropogenic input (e.g., Ni, Cu, Gd). The results further indicate an increasing P-limitation and increasing anthropogenic gadolinium input into the German Bight.

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The high uncertainty regarding global gross primary production (GPP) remains unresolved. This study explored the relationships between phenology, physiology, and annual GPP to provide viable alternatives for accurate estimation. A statistical model of integrated phenology and physiology (SMIPP) was developed using GPP data from 145 FLUXNET sites to estimate the annual GPP for various vegetation types. By employing the SMIPP model driven by satellite-derived datasets of the global carbon uptake period (CUP) and maximal carbon uptake capacity (GPPmax), the global annual GPP was estimated for the period from 2001 to 2018. The results demonstrated that the SMIPP model accurately predicted annual GPP, with relative root mean square error values ranging from 11.20 to 19.29% for forest types and 20.49-35.71% for non-forest types. However, wetlands, shrublands, and evergreen forests exhibited relatively low accuracies. The average, trend, and interannual variation of global GPP during 2001-2018 were 132.6 Pg C yr-1, 0.25 Pg C yr-2, and 1.57 Pg C yr-1, respectively. They were within the ranges estimated in other global GPP products. Sensitivity analysis revealed that GPPmax had comparable effects to CUP in high-latitude regions but significantly greater impacts at the global scale, with sensitivity coefficients of 0.85 ± 0.23 for GPPmax and 0.46 ± 0.28 for CUP. This study provides a simple and practical method for estimating global annual GPP and highlights the influence of GPPmax and CUP on global-scale annual GPP.

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Rangelands are the dominant land use across a broad swath of central North America where they span a wide gradient, from <350 to >900 mm, in mean annual precipitation. Substantial efforts have examined temporal and spatial variation in aboveground net primary production (ANPP) to precipitation (PPT) across this gradient. In contrast, net secondary productivity (NSP, e.g., primary consumer production) has not been evaluated analogously. However, livestock production, which is a form of NSP or primary consumer production supported by primary production, is the dominant non-cultivated land use and an integral economic driver in these regions. Here, we used long-term (mean length = 19 years) ANPP and NSP data from six research sites across the Central Great Plains with a history of a conservative stocking to determine resource (i.e., PPT)-productivity relationships, NSP sensitivities to dry-year precipitation, and regional trophic efficiencies (e.g., NSP:ANPP ratio). PPT-ANPP relationships were linear for both temporal (site-based) and spatial (among site) gradients. The spatial PPT-NSP model revealed that PPT mediated a saturating relationship for NSP as sites became more mesic, a finding that contrasts with many plant-based PPT-ANPP relationships. A saturating response to high growing-season precipitation suggests biogeochemical rather than vegetation growth constraints may govern NSP (i.e., large herbivore production). Differential sensitivity in NSP to dry years demonstrated that the primary consumer production response heightened as sites became more xeric. Although sensitivity generally decreased with increasing precipitation as predicted from known PPT-ANPP relationships, evidence suggests that the dominant species' identity and traits influenced secondary production efficiency. Non-native northern mixed-grass prairie was outperformed by native Central Great Plains rangeland in sensitivity to dry years and efficiency in converting ANPP to NSP. A more comprehensive understanding of the mechanisms leading to differences in producer and consumer responses will require multisite experiments to assess biotic and abiotic determinants of multi-trophic level efficiency and sensitivity.

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Chlorophyll fluorescence is the long-wave light released by the residual energy absorbed by vegetation after photosynthesis and dissipation, which can directly and non-destructively reflect the photosynthetic state of plants from the perspective of the mechanism of photosynthetic process. Moso bamboo has a substantial carbon sequestration ability, and leaf-expansion stage is an important phenological period for carbon sequestration. Gross primary production (GPP) is a key parameter reflecting vegetation carbon sequestration process. However, the ability of chlorophyll fluorescence in moso bamboo to explain GPP changes is unclear. The research area of this study is located in the bamboo forest near the flux station of Anji County, Zhejiang Province, where an observation tower is built to monitor the carbon flux and meteorological change of bamboo forest. The chlorophyll fluorescence physiological parameters (Fp) and fluorescence yield (Fy) indices were measured and calculated for the leaves of newborn moso bamboo (I Du bamboo) and the old leaves of 4- to 5-year-old moso bamboo (Ⅲ Du bamboo) during the leaf-expansion stage. The chlorophyll fluorescence in response to the environment and its effect on carbon flux were analyzed. The results showed that: Fv/Fm, Y(II) and α of Ⅰ Du bamboo gradually increased, while Ⅲ Du bamboo gradually decreased, and FYint and FY687/FY738 of Ⅰ Du bamboo were higher than those of Ⅲ Du bamboo; moso bamboo was sensitive to changes in air temperature(Ta), relative humidity(RH), water vapor pressure(E), soil temperature(ST) and soil water content (SWC), the Fy indices of the upper, middle and lower layers were significantly correlated with Ta, E and ST; single or multiple vegetation indices were able to estimate the fluorescence yield indices well (all with R2 greater than 0.77); chlorophyll fluorescence (Fp and Fy indices) of Ⅰ Du bamboo and Ⅲ Du bamboo could explain 74.4% and 72.7% of the GPP variation, respectively; chlorophyll fluorescence and normalized differential vegetation index of the canopy (NDVIc) could estimate GPP well using random forest (Ⅰ Du bamboo: r = 0.929, RMSE = 0.069 g C·m-2; Ⅲ Du bamboo: r = 0.899, RMSE = 0.134 g C·m-2). The results of this study show that chlorophyll fluorescence can provide a basis for judging the response of moso bamboo to environmental changes and can well explain GPP. This study has important scientific significance for evaluating the potential mechanisms of growth, stress feedback and photosynthetic carbon sequestration of bamboo.

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Discharge of gas-rich brines fuels productive chemosynthetic ecosystems in the deep sea. In these salty, methanic and sulfidic brines, microbial communities adapt to specific niches along the physicochemical gradients. However, the molecular mechanisms that underpin these adaptations are not fully known. Using metagenomics, we investigated the dense (∼106 cell ml-1) microbial communities that occupy small deep-sea brine pools found in the Southeastern Mediterranean Sea (1150 m water depth, ∼22 °C, ∼60 PSU salinity, sulfide, methane, ammonia reaching millimolar levels, and oxygen usually depleted), reaching high productivity rates of 685 µg C L-1 d-1 ex-situ. We curated 266 metagenome-assembled genomes of bacteria and archaea from the several pools and adjacent sediment-water interface, highlighting the dominance of a single Sulfurimonas, which likely fuels its autotrophy using sulfide oxidation or inorganic sulfur disproportionation. This lineage may be dominant in its niche due to genome streamlining, limiting its metabolic repertoire, particularly by using a single variant of sulfide: quinone oxidoreductase. These primary producers co-exist with ANME-2c archaea that catalyze the anaerobic oxidation of methane. Other lineages can degrade the necromass aerobically (Halomonas and Alcanivorax), or anaerobically through fermentation of macromolecules (e.g., Caldatribacteriota, Bipolaricaulia, Chloroflexota, etc). These low-abundance organisms likely support the autotrophs, providing energy-rich H2, and vital organics such as vitamin B12.

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