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Some macroalgae drift on the ocean and are stranded on coasts, and these stranded brown macroalgae are regarded to be degraded by organisms. Alginate is a major component of brown macroalgae. An uncovering of how carbon is cycled through brown macroalgae is needed to deeply understand coastal ecosystems. In this study, to gain insights into metabolism of brown macroalgae and alginate in the organisms, we initially confirmed that supralittoral talitrid amphipods (beach fleas or sandhoppers collected on the Shibagaki coast in Ishikawa Prefecture, Japan) fed on the brown macroalgae. We then isolated bacteria such as Vibrio sp. with alginate-assimilating capability from the gut of the amphipods. Metagenomic analysis of the gut of amphipods housed in several conditions (e.g. macroalgae or paper as feed, non-sterilized or sterilized environment) showed no condition-dependent compositions of bacteria and fungi, but Vibrio sp. were detected at high frequency, in good agreement with the isolation of Vibrio sp. An intervention study using antibiotics showed that amphipods fed on algae or paper at about the same rate in the presence or absence of antibiotics, and that the antibiotics had no effects on the life span. Moreover, intervention with antibiotics completely killed Vibrio sp. and some other bacteria, and had significant effects on the composition of the flora in the gut, with elimination of the variations observed in the guts of amphipods housed without antibiotics. These data suggest that microbes that were killed by antibiotics, including Vibrio sp., in the gut of talitrid amphipods are not essential for assimilation of brown macroalgae. [ABSTRACT FROM AUTHOR]

Motivation: Determining intracellular metabolic flux through isotope labeling techniques such as 13C metabolic flux analysis (13C-MFA) incurs significant cost and effort. Previous studies have shown transcriptomic data coupled with constraint-based metabolic modeling can determine intracellular fluxes that correlate highly with 13C-MFA measured fluxes and can achieve higher accuracy than constraint-based metabolic modeling alone. These studies, however, used validation data limited to E. coli and S. cerevisiae grown on glucose, with significantly similar flux distribution for central metabolism. It is unclear whether those results apply to more diverse metabolisms, and therefore further, extensive validation is needed., Results: In this paper, we formed a dataset of transcriptomic data coupled with corresponding 13C-MFA flux data for 21 experimental conditions in different unicellular organisms grown on varying carbon substrates and conditions. Three computational flux-balance analysis (FBA) methods were comparatively assessed. The results show when uptake rates of carbon sources and key metabolites are known, transcriptomic data provides no significant advantage over constraint-based metabolic modeling (average correlation coefficients, transcriptomic E-Flux2 0.725 and SPOT 0.650 vs non-transcriptomic pFBA 0.768). When uptake rates are unknown, however, predictions obtained utilizing transcriptomic data are generally good and significantly better than those obtained using constraint-based metabolic modeling alone (E-Flux2 0.385 and SPOT 0.583 vs pFBA 0.237). Thus, transcriptomic data coupled with constraint-based metabolic modeling is a promising method to obtain intracellular flux estimates in microorganisms, particularly in cases where uptake rates of key metabolites cannot be easily determined, such as for growth in complex media or in vivo conditions., Competing Interests: The authors have declared that no competing interests exist.

Background and Aims: This paper was primarily devoted to understand the interactions of soil aggregates, organic carbon (C) and carbon cycle enzymes in aggregates under different fertilization managements, aiming to identify the effects of organic and inorganic fertilizer amendments on soil organic C accumulation and the activities of carbon cycle enzymes within aggregates in Vertisol., Methods: A Vertisol soil following 4-year compost and inorganic fertilizer amendments, i.e. no fertilizer (CK), mineral fertilizer (FR) and 60% compost N plus 40% fertilizer N (FRM), was collected to identify the dynamics of organic C, enzymes activities and their associations with macroaggregation using aggregate fractionation techniques., Results: The organic C content in all FR and FRM treatments was 8.24-41.15% higher than that in CK. An increased amounts of carbon cycle enzymes in aggregates or 0-20 cm bulk soil were also observed in FRM plots. Compared to FR, FRM significantly strengthened the structural stability of macroaggregates and the intimate connection between enzyme activities and macroaggregates., Conclusions: As a recommended measure, supplementation with organic manure such as compost strengthened the process of mutual promotion between carbon cycle enzymes and macroaggregates, and the synergistic effect would be highly beneficial to soil organic C sequestration., Competing Interests: The authors have declared that no competing interests exist.

Although depolymerization of complex carbohydrates is a growth-limiting bottleneck for microbial decomposers, we still lack understanding about how the production of different types of extracellular enzymes affect individual microbes and in turn the performance of whole decomposer communities. In this work we use a theoretical model to evaluate the potential trade-offs faced by microorganisms in biopolymer decomposition which arise due to the varied biochemistry of different depolymerizing enzyme classes. We specifically consider two broad classes of depolymerizing extracellular enzymes, which are widespread across microbial taxa: exo-enzymes that cleave small units from the ends of polymer chains and endo-enzymes that act at random positions generating degradation products of varied sizes. Our results demonstrate a fundamental trade-off in the production of these enzymes, which is independent of system's complexity and which appears solely from the intrinsically different temporal depolymerization dynamics. As a consequence, specialists that produce either exo- or only endo-enzymes limit their growth to high or low substrate conditions, respectively. Conversely, generalists that produce both enzymes in an optimal ratio expand their niche and benefit from the synergy between the two enzymes. Finally, our results show that, in spatially-explicit environments, consortia composed of endo- and exo-specialists can only exist under oligotrophic conditions. In summary, our analysis demonstrates that the (evolutionary or ecological) selection of a depolymerization pathway will affect microbial fitness under low- or high substrate conditions, with impacts on the ecological dynamics of microbial communities. It provides a possible explanation why many polysaccharide degraders in nature show the genetic potential to produce both of these enzyme classes. Author summary: The decomposition of polysaccharides by microbes is a key process in the global carbon cycle. It requires the joint action of a variety of microbially-produced extracellular enzymes. They can be broadly classified into endo-enzymes, that act in the middle of polymers, and exo-enzymes, that cleave units from polymer ends. Little is known about the benefits for microbes producing a certain enzyme type and the interplay between enzyme producing strategies in mixed communities. This hampers our comprehensive understanding of decomposition in terrestrial and marine ecosystems and thus limits the prediction of decomposition processes, for example in a changing climate. Based on theoretical modelling, we revealed a fundamental trade-off in the action of these enzymes. While exo-enzymes are more efficient at high substrate conditions, endo-enzymes perform better when substrate is low. Generalists producing both enzymes expand their ecological niche of substrate availability compared to specialists only producing one of the two types. Complementary specialists only co-exist in oligotrophic conditions. We conclude that producing enzymes for specific steps within polymer degradation represents relevant ecological strategies for microbes in decomposer communities. [ABSTRACT FROM AUTHOR]

Forest ecosystems store large amounts of carbon and can be important sources, or sinks, of the atmospheric carbon dioxide that is contributing to global warming. Understanding the carbon storage potential of different forests and their response to management and disturbance events are fundamental to developing policies and scenarios to partially offset greenhouse gas emissions. Projections of live tree carbon accumulation are handled differently in different models, with inconsistent results. We developed growth-and-yield style models to predict stand-level live tree carbon density as a function of stand age in all vegetation types of the coastal Pacific region, US (California, Oregon, and Washington), from 7,523 national forest inventory plots. We incorporated site productivity and stockability within the Chapman-Richards equation and tested whether intensively managed private forests behaved differently from less managed public forests. We found that the best models incorporated stockability in the equation term controlling stand carrying capacity, and site productivity in the equation terms controlling the growth rate and shape of the curve. RMSEs ranged from 10 to 137 Mg C/ha for different vegetation types. There was not a significant effect of ownership over the standard industrial rotation length (~50 yrs) for the productive Douglas-fir/western hemlock zone, indicating that differences in stockability and productivity captured much of the variation attributed to management intensity. Our models suggest that doubling the rotation length on these intensively managed lands from 35 to 70 years would result in 2.35 times more live tree carbon stored on the landscape. These findings are at odds with some studies that have projected higher carbon densities with stand age for the same vegetation types, and have not found an increase in yields (on an annual basis) with longer rotations. We suspect that differences are primarily due to the application of yield curves developed from fully-stocked, undisturbed, single-species, "normal" stands without accounting for the substantial proportion of forests that don't meet those assumptions. The carbon accumulation curves developed here can be applied directly in growth-and-yield style projection models, and used to validate the predictions of ecophysiological, cohort, or single-tree style models being used to project carbon futures for forests in the region. Our approach may prove useful for developing robust models in other forest types. [ABSTRACT FROM AUTHOR]

There have been many calls for community participation in MRV (measuring, reporting, verification) for REDD+. This paper examines whether community involvement in MRV is a requirement, why it appears desirable to REDD+ agencies and external actors, and under what conditions communities might be interested in participating. It asks What's in it for communities? What might communities gain from such an involvement? What could they lose? It embraces a broader approach which we call community MMM which involves mapping, measuring and monitoring of forest and other natural resources for issues which are of interest to the community itself. We focus on cases in México because the country has an unusually high proportion of forests under community communal ownership. In particular, we refer to a recent REDD+ initiative-CONAFOR-LAIF, in which local communities select and approve local people to participate in community-based monitoring activities. From these local initiatives we identify the specific and the general drivers for communities to be involved in mapping, measuring and monitoring of their own territories and their natural resources. We present evidence that communities are more interested in this wider approach than in a narrow focus on carbon monitoring. Finally we review what the challenges to reconciling MMM with MRV requirements are likely to be.

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics. [ABSTRACT FROM AUTHOR]

Root turnover is an important carbon flux component in grassland ecosystems because it replenishes substantial parts of carbon lost from soil via heterotrophic respiration and leaching. Among the various methods to estimate root turnover, the root's radiocarbon signature has rarely been applied to grassland soils previously, although the value of this approach is known from studies in forest soils. In this paper, we utilize the root's radiocarbon signatures, at 25 plots, in mountain grasslands of the montane to alpine zone of Europe. We place the results in context of a global data base on root turnover and discuss driving factors. Root turnover rates were similar to those of a subsample of the global data, comprising a similar temperature range, but measured with different approaches, indicating that the radiocarbon method gives reliable, plausible and comparable results. Root turnover rates (0.06-1.0 y(-1)) scaled significantly and exponentially with mean annual temperatures. Root turnover rates indicated no trend with soil depth. The temperature sensitivity was significantly higher in mountain grassland, compared to the global data set, suggesting additional factors influencing root turnover. Information on management intensity from the 25 plots reveals that root turnover may be accelerated under intensive and moderate management compared to low intensity or semi-natural conditions. Because management intensity, in the studied ecosystems, co-varied with temperature, estimates on root turnover, based on mean annual temperature alone, may be biased. A greater recognition of management as a driver for root dynamics is warranted when effects of climatic change on belowground carbon dynamics are studied in mountain grasslands.

Estimating gross primary production (GPP) and net primary production (NPP) are significant important in studying carbon cycles. Using models driven by multi-source and multi-scale data is a promising approach to estimate GPP and NPP at regional and global scales. With a focus on data that are openly accessible, this paper presents a GPP and NPP model driven by remotely sensed data and meteorological data with spatial resolutions varying from 30 m to 0.25 degree and temporal resolutions ranging from 3 hours to 1 month, by integrating remote sensing techniques and eco-physiological process theories. Our model is also designed as part of the Multi-source data Synergized Quantitative (MuSyQ) Remote Sensing Production System. In the presented MuSyQ-NPP algorithm, daily GPP for a 10-day period was calculated as a product of incident photosynthetically active radiation (PAR) and its fraction absorbed by vegetation (FPAR) using a light use efficiency (LUE) model. The autotrophic respiration (Ra) was determined using eco-physiological process theories and the daily NPP was obtained as the balance between GPP and Ra. To test its feasibility at regional scales, our model was performed in an arid and semi-arid region of Heihe River Basin, China to generate daily GPP and NPP during the growing season of 2012. The results indicated that both GPP and NPP exhibit clear spatial and temporal patterns in their distribution over Heihe River Basin during the growing season due to the temperature, water and solar influx conditions. After validated against ground-based measurements, MODIS GPP product (MOD17A2H) and results reported in recent literature, we found the MuSyQ-NPP algorithm could yield an RMSE of 2.973 gC m-2 d-1 and an R of 0.842 when compared with ground-based GPP while an RMSE of 8.010 gC m-2 d-1 and an R of 0.682 can be achieved for MODIS GPP, the estimated NPP values were also well within the range of previous literature, which proved the reliability of our modelling results. This research suggested that the utilization of multi-source data with various scales would help to the establishment of an appropriate model for calculating GPP and NPP at regional scales with relatively high spatial and temporal resolution. [ABSTRACT FROM AUTHOR]

Biomass partitioning is important for illustrating terrestrial ecosystem carbon flux. West, Brown and Enquist (WBE) model predicts that an optimal 3/4 allometric scaling of leaf mass and total biomass of individual plants will be applied in diverse communities. However, amount of scientific evidence suggests an involvement of some biological and environmental factors in interpreting the variation of scaling exponent observed in empirical studies. In this paper, biomass information of 1175 forested communities in China was collected and categorized into groups in terms of leaf form and function, as well as their locations to test whether the allocation pattern was conserved or variable with internal and/or environmental variations. Model Type II regression protocol was adopted to perform all the regressions. The results empirically showed that the slopes varied significantly across diverse forested biomes, between conifer and broadleaved forests, and between evergreen and deciduous forests. Based on the results, leaf form and function and their relations to environments play a significant role in the modification of the WBE model to explore more accurate laws in nature.

Animals translocate nutrients by consuming nutrients at one point and excreting them or dying at another location. Such lateral fluxes may be an important mechanism of nutrient supply in many ecosystems, but lack quantification and a systematic theoretical framework for their evaluation. This paper presents a mathematical framework for quantifying such fluxes in the context of mammalian herbivores. We develop an expression for lateral diffusion of a nutrient, where the diffusivity is a biologically determined parameter depending on the characteristics of mammals occupying the domain, including size-dependent phenomena such as day range, metabolic demand, food passage time, and population size. Three findings stand out: (a) Scaling law-derived estimates of diffusion parameters are comparable to estimates calculated from estimates of each coefficient gathered from primary literature. (b) The diffusion term due to transport of nutrients in dung is orders of magnitude large than the coefficient representing nutrients in bodymass. (c) The scaling coefficients show that large herbivores make a disproportionate contribution to lateral nutrient transfer. We apply the diffusion equation to a case study of Kruger National Park to estimate the conditions under which mammal-driven nutrient transport is comparable in magnitude to other (abiotic) nutrient fluxes (inputs and losses). Finally, a global analysis of mammalian herbivore transport is presented, using a comprehensive database of contemporary animal distributions. We show that continents vary greatly in terms of the importance of animal-driven nutrient fluxes, and also that perturbations to nutrient cycles are potentially quite large if threatened large herbivores are driven to extinction.

Stable isotope analysis is a powerful tool for dietary modeling and trophic ecology research. A crucial piece of information for isotopic dietary modeling is the accurate estimation of trophic discrimination factors (TDFs), or the isotopic offset between a consumer's tissue and its diet. In order to parameterize stable isotope dietary models for future climate scenarios, we investigated the effect of water temperature and dietary protein and lipid content on TDFs in juvenile Pacific cod (Gadus macrocephalus). Pacific cod are a commercially and ecologically important species, with stock numbers in the northeast Pacific recently having dropped by more than 70%. We tested four water temperatures (6, 8, 10, and 12°C) and two dietary regimens (low and high lipid content), representing a range of potential ocean temperature and prey quality scenarios, in order to determine carbon and nitrogen TDFs in juvenile Pacific cod. Additionally, we assessed dietary intake and proximate composition of the experimental fish in order to estimate consumption, assimilation, and retention of dietary nutrients. The results of this study suggest that dietary protein catabolism is a primary driver of nitrogen TDF variability in juvenile Pacific cod. Across all temperature treatments from 6 to 12°C, fish reared on the lower quality, lower lipid content diet had higher nitrogen TDFs. The mean TDFs for fish raised on the higher lipid, lower protein diet were +3.40 ‰ for nitrogen (Δ15N) and +0.36 ‰ for lipid-corrected carbon (Δ LC 13C). The mean TDFs for fish raised on the lower lipid, higher protein diet were +4.09 ‰ for nitrogen (Δ15N) and 0.00 ‰ for lipid-corrected carbon (Δ LC 13C). Lipid-corrected carbon isotope data showed that, regardless of temperature, fish consuming the lower lipid diet had essentially no trophic discrimination between diet and bulk tissues. We found no ecologically meaningful differences in TDFs due to water temperature across the 6°experimental range. The results of this experiment demonstrate that dietary quality, and more specifically the use of dietary protein for energetic needs, is a primary driver of trophic discrimination factors. The TDFs determined in this study can be applied to understanding trophic ecology in Pacific cod and closely related species under rapidly changing prey availability and ocean temperature conditions. [ABSTRACT FROM AUTHOR]

A new moisture adjusted vegetation index (MAVI) is proposed using the red, near infrared, and shortwave infrared (SWIR) reflectance in band-ratio form in this paper. The effectiveness of MAVI in retrieving leaf area index (LAI) is investigated using Landsat-5 data and field LAI measurements in two forest and two grassland areas. The ability of MAVI to retrieve forest LAI under different background conditions is further evaluated using canopy reflectance of Jack Pine and Black Spruce forests simulated by the 4-Scale model. Compared with several commonly used two-band vegetation index, such as normalized difference vegetation index, soil adjusted vegetation index, modified soil adjusted vegetation index, optimized soil adjusted vegetation index, MAVI is a better predictor of LAI, on average, which can explain 70% of variations of LAI in the four study areas. Similar to other SWIR-related three-band vegetation index, such as modified normalized difference vegetation index (MNDVI) and reduced simple ratio (RSR), MAVI is able to reduce the background reflectance effects on forest canopy LAI retrieval. MAVI is more suitable for retrieving LAI than RSR and MNDVI, because it avoids the difficulty in properly determining the maximum and minimum SWIR values required in RSR and MNDVI, which improves the robustness of MAVI in retrieving LAI of different land cover types. Moreover, MAVI is expressed as ratios between different spectral bands, greatly reducing the noise caused by topographical variations, which makes it more suitable for applications in mountainous area. [ABSTRACT FROM AUTHOR]

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets. [ABSTRACT FROM AUTHOR]

The conversion of farmland to forestland not only changes the ecological environment but also enriches the soil with organic matter and affects the global carbon cycle. This paper reviews the influence of land use changes on the soil organic carbon sink to determine whether the Chinese “Grain-for-Green” (conversion of farmland to forestland) project increased the rate of SOC content during its implementation between 1999 and 2010 in the hilly and gully areas of the Loess Plateau in north-central China. The carbon sink was quantified, and the effects of the main species were assessed. The carbon sink increased from 2.26×106 kg in 1999 to 8.32×106 kg in 2010 with the sustainable growth of the converted areas. The black locust (Robinia pseudoacacia L.) and alfalfa (Medicago sativa L.) soil increased SOC content in the top soil (0–100 cm) in the initial 7-yr period, while the sequestration occurred later (>7 yr) in the 100–120 cm layer after the “Grain-for-Green” project was implemented. The carbon sink function measured for the afforested land provides evidence that the Grain-for-Green project has successfully excavated the carbon sink potential of the Shaanxi province and served as an important milestone for establishing an effective organic carbon management program. [ABSTRACT FROM AUTHOR]

The ability to down-regulate leaf maximum net photosynthetic capacity (Amax) and dark respiration rate (Rdark) in response to shading is thought to be an important adaptation of trees to the wide range of light environments that they are exposed to across space and time. A simple, general rule that accurately described this down-regulation would improve carbon cycle models and enhance our understanding of how forest successional diversity is maintained. In this paper, we investigated the light response of Amax and Rdark for saplings of six temperate forest tree species in New Jersey, USA, and formulated a simple model of down-regulation that could be incorporated into carbon cycle models. We found that full-sun values of Amax and Rdark differed significantly among species, but the rate of down-regulation (proportional decrease in Amax or Rdark relative to the full-sun value) in response to shade was not significantly species- or taxon-specific. Shade leaves of sun-grown plants appear to follow the same pattern of down-regulation in response to shade as leaves of shade-grown plants. Given the light level above a leaf and one species-specific number (either the full-sun Amax or full-sun Rdark), we provide a formula that can accurately predict the leaf's Amax and Rdark. We further show that most of the down regulation of per unit area Rdark and Amax is caused by reductions in leaf mass per unit area (LMA): as light decreases, leaves get thinner, while per unit mass Amax and Rdark remain approximately constant. [ABSTRACT FROM AUTHOR]

The addition of pyrogenic carbon (C) in the soil is considered a potential strategy to achieve direct C sequestration and potential reduction of non-CO2 greenhouse gas emissions. In this paper, we investigated the long term effects of charcoal addition on C sequestration and soil physico-chemical properties by studying a series of abandoned charcoal hearths in the Eastern Alps of Italy established in the XIX century. This natural setting can be seen as an analogue of a deliberate experiment with replications. Carbon sequestration was assessed indirectly by comparing the amount of pyrogenic C present in the hearths (23.3±4.7 kg C m−2) with the estimated amount of charcoal that was left on the soil after the carbonization (29.3±5.1 kg C m−2). After taking into account uncertainty associated with parameters’ estimation, we were able to conclude that 80±21% of the C originally added to the soil via charcoal can still be found there and that charcoal has an overall Mean Residence Time of 650±139 years, thus supporting the view that charcoal incorporation is an effective way to sequester atmospheric CO2. We also observed an overall change in the physical properties (hydrophobicity and bulk density) of charcoal hearth soils and an accumulation of nutrients compared to the adjacent soil without charcoal. We caution, however, that our site-specific results should not be generalized without further study. [ABSTRACT FROM AUTHOR]

Dynamics of soil organic carbon (SOC) are associated with soil erosion, yet there is a shortage of research concerning the relationship between soil erosion, SOC, and especially microbial biomass carbon (MBC). In this paper, we selected two typical slope landscapes including gentle and steep slopes from the Sichuan Basin, China, and used the 137Cs technique to determine the effects of water erosion and tillage erosion on the dynamics of SOC and MBC. Soil samples for the determination of 137Cs, SOC, MBC and soil particle-size fractions were collected on two types of contrasting hillslopes. 137Cs data revealed that soil loss occurred at upper slope positions of the two landscapes and soil accumulation at the lower slope positions. Soil erosion rates as well as distribution patterns of the <0.002-mm clay shows that water erosion is the major process of soil redistribution in the gentle slope landscape, while tillage erosion acts as the dominant process of soil redistribution in the steep slope landscape. In gentle slope landscapes, both SOC and MBC contents increased downslope and these distribution patterns were closely linked to soil redistribution rates. In steep slope landscapes, only SOC contents increased downslope, dependent on soil redistribution. It is noticeable that MBC/SOC ratios were significantly lower in gentle slope landscapes than in steep slope landscapes, implying that water erosion has a negative effect on the microbial biomass compared with tillage erosion. It is suggested that MBC dynamics are closely associated with soil redistribution by water erosion but independent of that by tillage erosion, while SOC dynamics are influenced by soil redistribution by both water erosion and tillage erosion. [ABSTRACT FROM AUTHOR]

Devising policies for a low carbon city requires a careful understanding of the characteristics of urban residential lifestyle and consumption. The production-based accounting approach based on top-down statistical data has a limited ability to reflect the total greenhouse gas (GHG) emissions from residential consumption. In this paper, we present a survey-based GHG emissions accounting methodology for urban residential consumption, and apply it in Xiamen City, a rapidly urbanizing coastal city in southeast China. Based on this, the main influencing factors determining residential GHG emissions at the household and community scale are identified, and the typical profiles of low, medium and high GHG emission households and communities are identified. Up to 70% of household GHG emissions are from regional and national activities that support household consumption including the supply of energy and building materials, while 17% are from urban level basic services and supplies such as sewage treatment and solid waste management, and only 13% are direct emissions from household consumption. Housing area and household size are the two main factors determining GHG emissions from residential consumption at the household scale, while average housing area and building height were the main factors at the community scale. Our results show a large disparity in GHG emissions profiles among different households, with high GHG emissions households emitting about five times more than low GHG emissions households. Emissions from high GHG emissions communities are about twice as high as from low GHG emissions communities. Our findings can contribute to better tailored and targeted policies aimed at reducing household GHG emissions, and developing low GHG emissions residential communities in China. [ABSTRACT FROM AUTHOR]

Harvested wood products found in the built environment are an important carbon sink, helping to mitigate climate change, and their trends in use are determined by economic and demographic factors, which vary spatially. Spatially detailed projections of construction and stored carbon are needed for industry and public decision making, including for appreciating trends in values at risk from catastrophic disturbances. We specify econometric models of single-family and multifamily housing starts by U.S. Census Region, design a method for their spatial downscaling to the county level, and project their quantities and carbon content according to the five Shared Socioeconomic Pathways (SSPs). Starts are projected to decline across all scenarios and potentially drop to below housing replacement levels under SSP3 by mid-century. Wood products carbon stored nationally in structures in use and in landfills is projected to grow across all scenarios but with significant spatial heterogeneity related to disparate trends in construction across counties, ranging from strong growth in the urban counties of the coastal South and West to stagnation in rural counties of the Great Plains and the northern Rockies. The estimated average annual carbon stored in wood products used in and discarded from US residential housing units between 2015–2070 ranged from 51 million t CO2e in SSP3 to 85 million t CO2e in SSP5, representing 47% to 78% of total carbon uptake relative to uptake by all wood products in the United States in 2019. [ABSTRACT FROM AUTHOR]

Peatlands contain large amount of carbon stock that is vulnerable to release into the atmosphere. Mostly because of human impact, the peatlands at Zoige Wetlands face severe degradation, and the groundwater table is now lower than before, which has increased the population of the plateau zokor, a burrowing rodent. However, the impact of these changes on ecosystem carbon flows has not been studied. To investigate how the plateau zokor and the groundwater level alter the ecosystem respiration of the Zoige peatlands, we sampled the CO2 flux of hummocks shaped by the zokors and compared it with the CO2 flux of undisturbed sites with different groundwater table levels. The soil organic carbon (SOC), soil water content (SWC) and soil temperature at 5 cm (T5) were measured. SOC showed no significant difference among the four sampling sites and did not correlate with the CO2 flux, while SWC was found to partly determine the CO2 flux. A linear equation could adequately describe the relationship between the natural logarithm of the ecosystem respiration and the soil temperature. It is demonstrated that descending groundwater table might accelerate ecosystem respiration and the CO2 flux from hummocks was higher than the CO2 flux from the control site in the non-growing season. With rising temperature, the CO2 flux from the control site accelerated faster than that from the hummocks. Our results show that ecosystem respiration was significantly lower from hummocks than at the control site in the growing season. The results on the impact of zokors on greenhouse gas emissions presented in this paper provide a useful reference to help properly manage not only this, but other litter-burrowing mammals at peatland sites. [ABSTRACT FROM AUTHOR]

Net primary productivity (NPP) plays an important role in the carbon cycle of an ecosystem. To explore the impact of unused land development on NPP, this study adopted an improved Carnegie Ames Stanford Approach (CASA) model to analyze the changes in NPP before and after the development of unused land in Tang County, Hebei Province, in 2000, 2007, and 2018. The results showed that, due to the changes in land use types from unused land, forestland, arable land with high NPP values to urban and rural residential land, traffic land with low NPP values, and the changes in precipitation and temperature, the NPP in the study area showed an overall trend of decreasing first and then rising from 2000 to 2018. Before the development of unused land in 2000, the total NPP was 38.45×1010 g C. After the development in 2007 and 2018, the total NPP was 36.44×1010 g C and 41.05×1010 g C, respectively. The NPP of each land type in 2018 was arable land (1046.18 g C m-2) > forestland (464.42 g C m-2) > unused land (356.34 g C m-2) > grassland (343.77 g C m-2) > waters (182.56 g C m-2) > urban and rural settlements (120.86 g C m-2) > traffic land (120.70 g C m-2). The distribution of NPP was generally high in the north and low in the south before and after development. NPP was mainly concentrated in the interval of 300 g C m-2 yr-1–400 g C m-2 yr-1, and the range of NPP change was mostly within 100 g C m-2. The influence of elevation, temperature and precipitation on the spatial distribution of NPP was significant. Elevation and precipitation were positively correlated with NPP, while temperature was negatively correlated with NPP. The increase in NPP mainly originated from the conversion of unused land to forestland and arable land. The loss of NPP was mainly due to the conversion from forestland with high vegetation productivity to a land use type with low vegetation productivity, such as the conversion from forestland to urban and rural residential land. The results can provide references for making reasonable land planning decisions and ecological environment construction. [ABSTRACT FROM AUTHOR]

The rates of cell growth, division, and carbon loss of microbial populations are key parameters for understanding how organisms interact with their environment and how they contribute to the carbon cycle. However, the invasive nature of current analytical methods has hindered efforts to reliably quantify these parameters. In recent years, size-structured matrix population models (MPMs) have gained popularity for estimating division rates of microbial populations by mechanistically describing changes in microbial cell size distributions over time. Motivated by the mechanistic structure of these models, we employ a Bayesian approach to extend size-structured MPMs to capture additional biological processes describing the dynamics of a marine phytoplankton population over the day-night cycle. Our Bayesian framework is able to take prior scientific knowledge into account and generate biologically interpretable results. Using data from an exponentially growing laboratory culture of the cyanobacterium Prochlorococcus, we isolate respiratory and exudative carbon losses as critical parameters for the modeling of their population dynamics. The results suggest that this modeling framework can provide deeper insights into microbial population dynamics provided by size distribution time-series data. Author summary: Inferring the growth and population dynamics of marine microorganisms in their natural habitat is crucial to understanding the flow of carbon in the natural environment but remains a grand challenge due to the invasive nature of current measurement methods. As time-series observations of microorganism size distributions have become more commonplace in aquatic environments, matrix population models (MPMs), which aim to mechanistically describe the change in size distribution over time, have gained in popularity over the last decade to estimate rates of cell division of these populations. Here, we build upon this work to improve accuracy and interpretability of model output and assess the relevance of previously omitted biological processes. We evaluated the performance of our models on a dataset of laboratory experiment time-series measurements of the cyanobacterium Prochlorococcus, Earth's most abundant photosynthetic organism, and demonstrated improved accuracy of division rate estimates by incorporating respiratory and exudative carbon losses into the modeling of their population dynamics. [ABSTRACT FROM AUTHOR]

The ANEMI model is an integrated assessment model of global change that emphasizes the role of water resources. The model is based on the principles of system dynamics simulation to analyze changes in the Earth system using feedback processes. Securing water resources for the future is a key issue of global change, and ties into global systems of population growth, climate change, carbon cycle, hydrologic cycle, economy, energy production, land use and pollution generation. Here the third iteration of the model–ANEMI3 is described, along with the methods used for parameter estimation and model testing. The main differences between ANEMI3 and previous versions include: (i) implementation of the energy-economy system based on the principles of system dynamics simulation; (ii) incorporation of water supply as an additional sector in the global economy that parallels the production of energy; (iii) inclusion of climate change effects on land yield and potentially arable land for food production, and (iv) addition of nitrogen and phosphorus based nutrient cycles as indicators of global water quality, which affect the development of surface water supplies. The model is intended for analyzing long-term global feedbacks which drive global change. Because of this, there are limitations related to the spatial scale that is used. However, the model's simplicity can be considered a strength, as it allows for the driving feedbacks to be more easily identified. The model in its current form allows for a variety of scenarios to be created to address global issues such as climate change from an integrated perspective, or to examine the change in one model sector on Earth system behaviour. The endogenous structure of the model allows for global change to be driven entirely by model structure rather than exogenous inputs. The new additions to the ANEMI3 model are found to capture long term trends associated with global change, while allowing for the development of water supplies to be represented using an integrated approach considering global economy and surface water quality. [ABSTRACT FROM AUTHOR]

Microplastics (MPs), plastic particles <5 mm, are found in environments, including terrestrial ecosystems, planetwide. Most research so far has focused on ecotoxicology, examining effects on performance of soil biota in controlled settings. As research pivots to a more ecosystem and global change perspective, questions about soil-borne biogeochemical cycles become important. MPs can affect the carbon cycle in numerous ways, for example, by being carbon themselves and by influencing soil microbial processes, plant growth, or litter decomposition. Great uncertainty surrounds nano-sized plastic particles, an expected by-product of further fragmentation of MPs. A major concerted effort is required to understand the pervasive effects of MPs on the functioning of soils and terrestrial ecosystems; importantly, such research needs to capture the immense diversity of these particles in terms of chemistry, aging, size, and shape. This Essay proposes that a major concerted effort is required to understand the pervasive effects of microplastics on the functioning of soils and terrestrial ecosystems, including the immense diversity of microplastic particles in terms of their chemistry, aging, size, and shape. [ABSTRACT FROM AUTHOR]

The Toarcian Oceanic Anoxic Event (TOAE; Early Jurassic, ca. 182 Ma ago) represents one of the major environmental disturbances of the Mesozoic and is associated with global warming, widespread anoxia, and a severe perturbation of the global carbon cycle. Warming-related dysoxia-anoxia has long been considered the main cause of elevated marine extinction rates, although extinctions have been recorded also in environments without evidence for deoxygenation. We addressed the role of warming and disturbance of the carbon cycle in an oxygenated habitat in the Iberian Basin, Spain, by correlating high resolution quantitative faunal occurrences of early Toarcian benthic marine invertebrates with geochemical proxy data (δ18O and δ13C). We find that temperature, as derived from the δ18O record of shells, is significantly correlated with taxonomic and functional diversity and ecological composition, whereas we find no evidence to link carbon cycle variations to the faunal patterns. The local faunal assemblages before and after the TOAE are taxonomically and ecologically distinct. Most ecological change occurred at the onset of the TOAE, synchronous with an increase in water temperatures, and involved declines in multiple diversity metrics, abundance, and biomass. The TOAE interval experienced a complete turnover of brachiopods and a predominance of opportunistic species, which underscores the generality of this pattern recorded elsewhere in the western Tethys Ocean. Ecological instability during the TOAE is indicated by distinct fluctuations in diversity and in the relative abundance of individual modes of life. Local recovery to ecologically stable and diverse post-TOAE faunal assemblages occurred rapidly at the end of the TOAE, synchronous with decreasing water temperatures. Because oxygen-depleted conditions prevailed in many other regions during the TOAE, this study demonstrates that multiple mechanisms can be operating simultaneously with different relative contributions in different parts of the ocean. [ABSTRACT FROM AUTHOR]

Shrubs play an important role in the global carbon cycle and are particularly sensitive to climate change. However, the altitudinal pattern of biomass allocation in mountainous shrubs and its responses to climate change are still unclear. In this study, biomass accumulation and allocation of the shrub community and their relationships with climatic factors were investigated in 331 sampling sites along an extensive altitudinal gradient (311–4911 m) in Southwest China. The results showed that the above-ground biomass (AGB) and the total biomass (TB) of the shrub community decreased quadratically (R2 = 0.107) and linearly (R2 = 0.024) from 9.86 to 0.15 kg·m-2 and 15.61 to 0.26 kg·m-2 with increasing altitude, respectively. However, the below-ground biomass (BGB) and TB of the herb layer increased quadratically with increasing altitudes (R2 = 0.136 and 0.122, respectively. P<0.001). The root/shoot ratio (R/S) of the community and its component synusiae increased gradually with increasing altitudes (P<0.001). The standardized major axis (SMA) indicated an isometric relationship between AGB and BGB for the whole shrub community, but allometric relationships were found for the shrub and herb layer. Redundancy analysis and Pearson correlation analysis showed that the biomass and R/S were significantly correlated with mean annual temperature (MAT), mean annual precipitation (MAP) and reconnaissance drought index (RDI). These findings indicate that shrub biomass allocation is strongly affected by the altitude, MAT and MAP and support the isometric relationship of AGB and BGB partitioning at the community level on mountainous shrub biomes. [ABSTRACT FROM AUTHOR]

Developing a thorough understanding of how ectotherm physiology adapts to different thermal environments is of crucial importance, especially in the face of global climate change. A key aspect of an organism's thermal performance curve (TPC)—the relationship between fitness-related trait performance and temperature—is its thermal sensitivity, i.e., the rate at which trait values increase with temperature within its typically experienced thermal range. For a given trait, the distribution of thermal sensitivities across species, often quantified as "activation energy" values, is typically right-skewed. Currently, the mechanisms that generate this distribution are unclear, with considerable debate about the role of thermodynamic constraints versus adaptive evolution. Here, using a phylogenetic comparative approach, we study the evolution of the thermal sensitivity of population growth rate across phytoplankton (Cyanobacteria and eukaryotic microalgae) and prokaryotes (bacteria and archaea), 2 microbial groups that play a major role in the global carbon cycle. We find that thermal sensitivity across these groups is moderately phylogenetically heritable, and that its distribution is shaped by repeated evolutionary convergence throughout its parameter space. More precisely, we detect bursts of adaptive evolution in thermal sensitivity, increasing the amount of overlap among its distributions in different clades. We obtain qualitatively similar results from evolutionary analyses of the thermal sensitivities of 2 physiological rates underlying growth rate: net photosynthesis and respiration of plants. Furthermore, we find that these episodes of evolutionary convergence are consistent with 2 opposing forces: decrease in thermal sensitivity due to environmental fluctuations and increase due to adaptation to stable environments. Overall, our results indicate that adaptation can lead to large and relatively rapid shifts in thermal sensitivity, especially in microbes for which rapid evolution can occur at short timescales. Thus, more attention needs to be paid to elucidating the implications of rapid evolution in organismal thermal sensitivity for ecosystem functioning. Whether and how the thermal sensitivities of biological traits respond to different environments is a topic of active debate. This study shows that the thermal sensitivity of population growth rate does not evolve in a gradual manner across microbes, but often undergoes rapid adaptive evolution. [ABSTRACT FROM AUTHOR]

Transcriptomic responses of plants to weed presence gives insight on the physiological and molecular mechanisms involved in the stress response. This study evaluated transcriptomic and morphological responses of two teosinte (Zea mays ssp parviglumis) (an ancestor of domesticated maize) lines (Ames 21812 and Ames 21789) to weed presence and absence during two growing seasons. Responses were compared after 6 weeks of growth in Aurora, South Dakota, USA. Plant heights between treatments were similar in Ames 21812, whereas branch number decreased when weeds were present. Ames 21789 was 45% shorter in weedy vs weed-free plots, but branch numbers were similar between treatments. Season-long biomass was reduced in response to weed stress in both lines. Common down-regulated subnetworks in weed-stressed plants were related to light, photosynthesis, and carbon cycles. Several unique response networks (e.g. aging, response to chitin) and gene sets were present in each line. Comparing transcriptomic responses of maize (determined in an adjacent study) and teosinte lines indicated three common gene ontologies up-regulated when weed-stressed: jasmonic acid response/signaling, UDP-glucosyl and glucuronyltransferases, and quercetin glucosyltransferase (3-O and 7-O). Overall, morphologic and transcriptomic differences suggest a greater varietal (rather than a conserved) response to weed stress, and implies multiple responses are possible. These findings offer insights into opportunities to define and manipulate gene expression of several different pathways of modern maize varieties to improve performance under weedy conditions. [ABSTRACT FROM AUTHOR]

Diatoms play a key role in the marine carbon cycle with their high primary productivity and release of exudates such as extracellular polymeric substances (EPS) and transparent exopolymeric particles (TEP). These exudates contribute to aggregates (marine snow) that rapidly transport organic material to the seafloor, potentially capturing contaminants like petroleum components. Ocean acidification (OA) impacts marine organisms, especially those that utilize inorganic carbon for photosynthesis and EPS production. Here we investigated the response of the diatom Thalassiosira pseudonana grown to present day and future ocean conditions in the presence of a water accommodated fraction (WAF and OAWAF) of oil and a diluted chemically enhanced WAF (DCEWAF and OADCEWAF). T. pseudonana responded to WAF/DCEWAF but not OA and no multiplicative effect of the two factors (i.e., OA and oil/dispersant) was observed. T. pseudonana released more colloidal EPS (< 0.7 μm to > 3 kDa) in the presence of WAF/DCEWAF/OAWAF/OADCEWAF than in the corresponding Controls. Colloidal EPS and particulate EPS in the oil/dispersant treatments have higher protein-to-carbohydrate ratios than those in the control treatments, and thus are likely stickier and have a greater potential to form aggregates of marine oil snow. More TEP was produced in response to WAF than in Controls; OA did not influence its production. Polyaromatic hydrocarbon (PAH) concentrations and distributions were significantly impacted by the presence of dispersants but not OA. PAHs especially Phenanthrenes, Anthracenes, Chrysenes, Fluorenes, Fluoranthenes, Pyrenes, Dibenzothiophenes and 1-Methylphenanthrene show major variations in the aggregate and surrounding seawater fraction of oil and oil plus dispersant treatments. Studies like this add to the current knowledge of the combined effects of aggregation, marine snow formation, and the potential impacts of oil spills under ocean acidification scenarios. [ABSTRACT FROM AUTHOR]

Marine vegetated ecosystems such as seagrass meadows are increasingly acknowledged as important carbon sinks based on their ability to capture and store atmospheric carbon dioxide, thereby contributing to climate change mitigation. Most studies on carbon storage in marine ecosystems have focused on organic carbon, leaving inorganic carbon processes such as calcification unaccounted for, despite of their critical role in the global carbon budget. This is probably because of uncertainties regarding the role of calcification in marine carbon budgets as either atmospheric CO2 source or sink. Here, we conducted a laboratory experiment to investigate the influence of a calcifying alga (Corallina officinalis L.) on seawater carbon content, using a non-calcifying alga (Ulva lactuca L.) as a control. In a first part, algae were incubated separately while measuring changes in seawater pH, total alkalinity (TA) and total dissolved inorganic carbon (DIC). The amount of carbon used in photosynthetic uptake and production of CaCO3 was then calculated. In a second, directly following, part the algae were removed and DIC levels were allowed to equilibrate with air until the pH stabilized and the loss of CO2 to air was calculated as the difference in total DIC from the start of part one, to the end of the second part. The results showed that C. officinalis caused a significant and persistent reduction in total dissolved inorganic carbon (DIC), TA and seawater pH, while no such permanent changes were caused by U. lactuca. These findings indicate that calcification can release a significant amount of CO2 to the atmosphere and thereby possibly counteract the carbon sequestration in marine vegetated ecosystems if this CO2 is not re-fixed in the system. Our research emphasises the importance of considering algal calcification in future assessments on carbon storage in coastal areas. [ABSTRACT FROM AUTHOR]

Spatiotemporal patterns of global forest net primary productivity (NPP) are pivotal for us to understand the interaction between the climate and the terrestrial carbon cycle. In this study, we use Google Earth Engine (GEE), which is a powerful cloud platform, to study the dynamics of the global forest NPP with remote sensing and climate datasets. In contrast with traditional analyses that divide forest areas according to geographical location or climate types to retrieve general conclusions, we categorize forest regions based on their NPP levels. Nine categories of forests are obtained with the self-organizing map (SOM) method, and eight relative factors are considered in the analysis. We found that although forests can achieve higher NPP with taller, denser and more broad-leaved trees, the influence of the climate is stronger on the NPP; for the high-NPP categories, precipitation shows a weak or negative correlation with vegetation greenness, while lacking water may correspond to decrease in productivity for low-NPP categories. The low-NPP categories responded mainly to the La Niña event with an increase in the NPP, while the NPP of the high-NPP categories increased at the onset of the El Niño event and decreased soon afterwards when the warm phase of the El Niño-Southern Oscillation (ENSO) wore off. The influence of the ENSO changes correspondingly with different NPP levels, which infers that the pattern of climate oscillation and forest growth conditions have some degree of synchronization. These findings may facilitate the understanding of global forest NPP variation from a different perspective. [ABSTRACT FROM AUTHOR]

Foraminifera are expected to be particularly susceptible to future changes in ocean carbonate chemistry as a function of increased atmospheric CO2. Studies in an experimental recirculating seawater system were performed with a dominant benthic foraminiferal species collected from intertidal mudflats. We investigated the experimental impacts of ocean acidification on survival, growth/calcification, morphology and the biometric features of a calcareous species Elphidium williamsoni. Foraminifera were exposed for 6 weeks to four different pH treatments that replicated future scenarios of a high CO2 atmosphere resulting in lower seawater pH. Results revealed that declining seawater pH caused a decline in foraminiferal survival rate and growth/calcification (mainly through test weight reduction). Scanning electron microscopy image analysis of live specimens at the end of the experimental period show changes in foraminiferal morphology with clear signs of corrosion and cracking on the test surface, septal bridges, sutures and feeding structures of specimens exposed to the lowest pH conditions. These findings suggest that the morphological changes observed in shell feeding structures may serve to alter: (1) foraminiferal feeding efficiency and their long-term ecological competitiveness, (2) the energy transferred within the benthic food web with a subsequent shift in benthic community structures and (3) carbon cycling and total CaCO3 production, both highly significant processes in coastal waters. These experimental results open-up the possibility of modelling future impacts of ocean acidification on both calcification and dissolution in benthic foraminifera within mid-latitude intertidal environments, with potential implications for understanding the changing marine carbon cycle. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau is an important component of the global carbon cycle due to the large permafrost carbon pool and its vulnerability to climate warming. The Tibetan Plateau has experienced a noticeable warming over the past few decades and is projected to continue warming in the future. However, the direction and magnitude of carbon fluxes responses to climate change and elevated CO2 concentration under Representative Concentration Pathways (RCP) scenarios in the Tibetan Plateau grassland are poorly known. Here, we used a calibrated and validated biogeochemistry model, CENTURY, to quantify the contributions of climate change and elevated CO2 on the future carbon budget in the alpine grassland under three RCP scenarios. Though the Tibetan Plateau grassland was projected a net carbon sink of 16 ~ 25 Tg C yr-1 in the 21st century, the capacity of carbon sequestration was predicted to decrease gradually because climate-driven increases in heterotrophic respiration (Rh) (with linear slopes 0.49 ~ 1.62 g C m-2 yr-1) was greater than the net primary production (NPP) (0.35 ~ 1.52 g C m-2 yr-1). However, the elevated CO2 contributed more to plant growth (1.9% ~ 7.3%) than decomposition (1.7% ~ 6.1%), which could offset the warming-induced carbon loss. The interannual and decadal-scale dynamics of the carbon fluxes in the alpine grassland were primarily controlled by temperature, while the role of precipitation became increasingly important in modulating carbon cycle. The strengthened correlation between precipitation and carbon budget suggested that further research should consider the performance of precipitation in evaluating carbon dynamics in a warmer climate scenario. [ABSTRACT FROM AUTHOR]

Reducing uncertainties in Earth System Model predictions requires carefully evaluating core model processes. Here we examined how canopy radiative transfer model (RTM) parameter uncertainties, in combination with canopy structure, affect terrestrial carbon and energy projections in a demographic land-surface model, the Ecosystem Demography model (ED2). Our analyses focused on temperate deciduous forests and tested canopies of varying structural complexity. The results showed a strong sensitivity of tree productivity, albedo, and energy balance projections to RTM parameters. Impacts of radiative parameter uncertainty on stand-level canopy net primary productivity ranged from ~2 to > 20% and was most sensitive to canopy clumping and leaf reflectance/transmittance in the visible spectrum (~400–750 nm). ED2 canopy albedo varied by ~1 to ~10% and was most sensitive to near-infrared reflectance (~800–1200 nm). Bowen ratio, in turn, was most sensitive to wood optical properties parameterization; this was much larger than expected based on literature, suggesting model instabilities. In vertically and spatially complex canopies the model response to RTM parameterization may show an apparent reduced sensitivity when compared to simpler canopies, masking much larger changes occurring within the canopy. Our findings highlight both the importance of constraining canopy RTM parameters in models and valuating how the canopy structure responds to those parameter values. Finally, we advocate for more model evaluation, similar to this study, to highlight possible issues with model behavior or process representations, particularly models with demographic representations, and identify potential ways to inform and constrain model predictions. [ABSTRACT FROM AUTHOR]

Soil respiration is the second largest terrestrial carbon (C) flux; the responses of soil respiration to nitrogen (N) deposition have far-reaching influences on the global C cycle. N deposition has been documented to significantly affect soil respiration, but the results are conflicting. The response of soil respiration to N deposition gradients remains unclear, especially in ecosystems receiving increasing ambient N depositions. A field experiment was conducted in a natural evergreen broadleaf forest in western China from November 2013 to November 2015 to understand the effects of increasing N deposition on soil respiration. Four levels of N deposition were investigated: control (Ctr, without N added), low N (L, 50 kg N ha−1·a−1), medium N (M, 150 kg N ha−1·a−1), and high N (H, 300 kg N ha−1·a−1). The results show that (1) the mean soil respiration rates in the L, M, and H treatments were 9.13%, 15.8% (P < 0.05) and 22.57% (P < 0.05) lower than that in the Ctr treatment (1.56 ± 0.13 μmol·m−2·s−1), respectively; (2) soil respiration rates showed significant positive exponential and linear relationships with soil temperature and moisture (P < 0.01), respectively. Soil temperature is more important than soil moisture in controlling the soil respiration rate; (3) the Ctr, L, M, and H treatments yielded Q10 values of 2.98, 2.78, 2.65, and 2.63, respectively. N deposition decreased the temperature sensitivity of soil respiration; (4) simulated N deposition also significantly decreased the microbial biomass C and N, fine root biomass, pH and extractable dissolved organic C (P < 0.05). Overall, the results suggest that soil respiration declines in response to N deposition. The decrease in soil respiration caused by simulated N deposition may occur through decreasing the microbial biomass C and N, fine root biomass, pH and extractable dissolved organic C. Ongoing N deposition may have significant impacts on C cycles and increase C sequestration with the increase in global temperature in evergreen broadleaf forests. [ABSTRACT FROM AUTHOR]

Biogeochemical models use meteorological forcing data derived with different approaches (e.g. based on interpolation or reanalysis of observation data or a hybrid hereof) to simulate ecosystem processes such as gross primary productivity (GPP). This study assesses the impact of different widely used climate datasets on simulated gross primary productivity and evaluates the suitability of them for reproducing the global and regional carbon cycle as mapped from independent GPP data. We simulate GPP with the biogeochemical model LPJ-GUESS using six historical climate datasets (CRU, CRUNCEP, ECMWF, NCEP, PRINCETON, and WFDEI). The simulated GPP is evaluated using an observation-based GPP product derived from eddy covariance measurements in combination with remotely sensed data. Our results show that all datasets tested produce relatively similar GPP simulations at a global scale, corresponding fairly well to the observation-based data with a difference between simulations and observations ranging from -50 to 60 g m-2 yr-1. However, all simulations also show a strong underestimation of GPP (ranging from -533 to -870 g m-2 yr-1) and low temporal agreement (r < 0.4) with observations over tropical areas. As the shortwave radiation for tropical areas was found to have the highest uncertainty in the analyzed historical climate datasets, we test whether simulation results could be improved by a correction of the tested shortwave radiation for tropical areas using a new radiation product from the International Satellite Cloud Climatology Project (ISCCP). A large improvement (up to 48%) in simulated GPP magnitude was observed with bias corrected shortwave radiation, as well as an increase in spatio-temporal agreement between the simulated GPP and observation-based GPP. This study conducts a spatial inter-comparison and quantification of the performances of climate datasets and can thereby facilitate the selection of climate forcing data over any given study area for modelling purposes. [ABSTRACT FROM AUTHOR]

Fire as a dominant disturbance has profound implications on the terrestrial carbon cycle. We present the first ever multi-decadal, spatially-explicit, 30 meter assessment of fire regimes across the forested ecoregions of Canada at an annual time-step. From 1985 to 2015, 51 Mha burned, impacting over 6.5% of forested ecosystems. Mean annual area burned was 1,651,818 ha and varied markedly (σ = 1,116,119), with 25% of the total area burned occurring in three years: 1989, 1995, and 2015. Boreal forest types contained 98% of the total area burned, with the conifer-dominated Boreal Shield containing one-third of all burned area. While results confirm no significant national trend in burned area for the period of 1985 to 2015, a significant national increasing trend (α = 0.05) of 11% per year was evident for the past decade (2006 to 2015). Regionally, a significant increasing trend in total burned area from 1985 to 2015 was observed in the Montane Cordillera (2.4% increase per year), while the Taiga Plains and Taiga Shield West displayed significant increasing trends from 2006 to 2015 (26.1% and 12.7% increases per year, respectively). The Atlantic Maritime, which had the lowest burned area of all ecozones (0.01% burned per year), was the only ecozone to display a significant negative trend (2.4% decrease per year) from 1985 to 2015. Given the century-long fire return intervals in many of these ecozones, and large annual variability in burned area, short-term trends need to be interpreted with caution. Additional interpretive cautions are related to year used for trend initiation and the nature and extents of spatial regionalizations used for summarizing findings. The results of our analysis provide a baseline for monitoring future national and regional trends in burned area and offer spatially and temporally detailed insights to inform science, policy, and management. [ABSTRACT FROM AUTHOR]

Agricultural crops play an important role in the global carbon and water cycle. Global climate change scenarios predict enhanced water scarcity and altered precipitation pattern in many parts of the world. Hence, a mechanistic understanding of water fluxes, productivity and water use efficiency of cultivated crops is of major importance, i.e. to adapt management practices. We compared water and carbon fluxes of paddy and rainfed rice by canopy scale gas exchange measurements, crop growth, daily evapotranspiration, transpiration and carbon flux modeling. Throughout a monsoon rice growing season, soil evaporation in paddy rice contributed strongly to evapotranspiration (96.6% to 43.3% from initial growth to fully developed canopy and amounted to 57.9% of total water losses over the growing seasons. Evaporation of rainfed rice was significantly lower (by 65% on average) particularly before canopy closure. Water use efficiency (WUE) was significantly higher in rainfed rice both from an agronomic (WUEagro, i.e. grain yield per evapotranspiration) and ecosystem (WUEeco, i.e. gross primary production per evapotranspiration) perspective. However, our results also show that higher WUE in rainfed rice comes at the expense of higher respiration losses compared to paddy rice (26% higher on average). Hence, suggestions on water management depend on the regional water availability (i.e. Mediterranean vs. Monsoon climate) and the balance between higher respiratory losses versus a potential reduction in CH4 and other greenhouse gas emissions. Our results suggest that a shift from rainfed/unsaturated soil to waterlogged paddy conditions after closure of the rice canopy might be a good compromise towards a sustainable use of water while preserving grain yield, particularly for water-limited production areas. [ABSTRACT FROM AUTHOR]

Previous studies show that forest net primary productivity (NPP) varies pronouncedly with stand age, and these variations play a crucial role in determining forest carbon sinks or sources at regional scales. Some forest carbon cycling models, eg. InTEC (The integrated terrestrial ecosystem C-budget model), calculates annual forest NPP in the long term according to normalized NPP-age relationships and the reference forest NPP at a given age. Therefore, the accurate NPP-age relationship is important for forest NPP estimation. In this study, NPP at various stand ages for twelve major forest stand types in Heilongjiang Province in northeast China is derived from yield tables with consideration of the total biomass increment and foliage and fine-root turnovers. Similar to previous studies, our results also show that forest NPP increases quickly at young ages, reaches the maximum value at middle age (10–40 years old), and then decreases to a relative stable level at old ages. However, we additionally found that forests under better site conditions have faster growth rates in young ages and steeper declines after reaching the maximum. Therefore, when the NPP-age curves for different site indices are normalized against the maximum value of each curve, there are significant differences among them. These differences have implications on the methodology for estimating the spatial distribution of forest carbon sources and sinks. [ABSTRACT FROM AUTHOR]

Autotrophic picoplankton (APP) abundance and contribution to phytoplankton biomass was studied in Hungarian shallow lakes to test the effect of inorganic turbidity determining the size distribution of the phytoplankton. The studied lakes displayed wide turbidity (TSS: 4–2250 mg l-1) and phytoplankton biomass (chlorophyll a: 1–460 μg l-1) range, as well as APP abundance (0 and 100 million cells ml-1) and contribution (0–100%) to total phytoplankton biomass. Inorganic turbidity had a significant effect on the abundance and contribution of APP, resulting in higher values compared to other freshwater lakes with the same phytoplankton biomass. Our analysis has provided empirical evidence for a switching point (50 mg l-1 inorganic turbidity), above which turbidity is the key factor causing APP predominance regardless of phytoplankton biomass in shallow turbid lakes. Our results have shown that turbid shallow lakes are unique waters, where the formerly and widely accepted model (decreasing APP contribution with increasing phytoplankton biomass) is not applicable. We hypothesize that this unusual behaviour of APP in turbid waters is a result of either diminished underwater light intensity or a reduced grazing pressure due to high inorganic turbidity. [ABSTRACT FROM AUTHOR]

The net primary productivity (NPP) of tropical forests is a key process of the carbon cycle and therefore for the mitigation of global climate change. It has been proposed that NPP is limited by the availability of soil nutrients in lowland tropical forests and that belowground NPP decreases as edaphic fertility increases. This hypothesis was evaluated in two localities (Opogodó and Pacurita) of the Chocó Biogeographical region, one of the rainiest of the world, where the aboveground (litter and wood) and belowground (fine and coarse roots) components of NPP were measured. Fertility parameters (pH, nutrients, and texture) were also determined and related to NPP. Total NPP was similar between locations (23.7 vs. 24.2 t ha-1 year-1 for Opogodó and Pacurita, respectively). However, components of NPP showed differences: in Pacurita, with steeper topography, NPP of wood and coarse roots were higher; therefore, differences of topography and drainage between localities probably affected the NPP of wood. On the other hand, soils of Opogodó, where NPP of fine roots was higher, showed higher contents of sand, N+, and organic matter (OM). With the increase of pH, OM, N+, K, Mg, and sand, the NPP of leaves and fine roots as well as the percentage of NPP belowground also increased, which suggests NPP limitation by multiple nutrients. The increase of NPP belowground with the availability of edaphic nutrients evidenced a redistribution of the aboveground and belowground components of NPP with the increase of soil fertility in oligotrophic systems, probably as a mechanism to improve the capture of resources. [ABSTRACT FROM AUTHOR]

Despite the central role of soil microbial communities in global carbon (C) cycling, little is known about soil microbial community structure and even less about their metabolic pathways. Efforts to characterize soil communities often focus on identifying differences in gene content across environmental gradients, but an alternative question is what genes are similar in soils. These genes may indicate critical species or potential functions that are required in all soils. Here we identified the “core” set of C cycling sequences widely present in multiple soil metagenomes from a fertilized prairie (FP). Of 226,887 sequences associated with known enzymes involved in the synthesis, metabolism, and transport of carbohydrates, 843 were identified to be consistently prevalent across four replicate soil metagenomes. This core metagenome was functionally and taxonomically diverse, representing five enzyme classes and 99 enzyme families within the CAZy database. Though it only comprised 0.4% of all CAZy-associated genes identified in FP metagenomes, the core was found to be comprised of functions similar to those within cumulative soils. The FP CAZy-associated core sequences were present in multiple publicly available soil metagenomes and most similar to soils sharing geographic proximity. In soil ecosystems, where high diversity remains a key challenge for metagenomic investigations, these core genes represent a subset of critical functions necessary for carbohydrate metabolism, which can be targeted to evaluate important C fluxes in these and other similar soils. [ABSTRACT FROM AUTHOR]

The development of a soil cover is a dynamic process. Soil cover can be altered within a few decades, which requires updating of the legacy soil maps. Soil erosion is one of the most important processes quickly altering soil cover on agriculture land. Colluvial soils develop in concave parts of the landscape as a consequence of sedimentation of eroded material. Colluvial soils are recognised as important soil units because they are a vast sink of soil organic carbon. Terrain derivatives became an important tool in digital soil mapping and are among the most popular auxiliary data used for quantitative spatial prediction. Prediction success rates are often directly dependent on raster resolution. In our study, we tested how raster resolution (1, 2, 3, 5, 10, 20 and 30 meters) influences spatial prediction of colluvial soils. Terrain derivatives (altitude, slope, plane curvature, topographic position index, LS factor and convergence index) were calculated for the given raster resolutions. Four models were applied (boosted tree, neural network, random forest and Classification/Regression Tree) to spatially predict the soil cover over a 77 ha large study plot. Models training and validation was based on 111 soil profiles surveyed on a regular sampling grid. Moreover, the predicted real extent and shape of the colluvial soil area was examined. In general, no clear trend in the accuracy prediction was found without the given raster resolution range. Higher maximum prediction accuracy for colluvial soil, compared to prediction accuracy of total soil cover of the study plot, can be explained by the choice of terrain derivatives that were best for Colluvial soils differentiation from other soil units. Regarding the character of the predicted Colluvial soils area, maps of 2 to 10 m resolution provided reasonable delineation of the colluvial soil as part of the cover over the study area. [ABSTRACT FROM AUTHOR]

The lateral transport of dissolved organic carbon (DOC) plays an important role in linking the carbon cycles of terrestrial and aquatic ecosystems. Neglecting the lateral flow of dissolved organic carbon can lead to an underestimation of the organic carbon budget of terrestrial ecosystems. It is thus necessary to integrate DOC concentrations and flux into carbon cycle models, particularly with regard to the development of models that are intended to directly link terrestrial and ocean carbon cycles. However, to achieve this goal, more accurate information is needed to better understand and predict DOC dynamics. In this study, we compiled an inclusive database of available data collected from the Yangtze River, Yellow River and Pearl River in China. The database is collected based on online literature survey and analysed by statistic method. Overall, our results revealed a positive correlation between DOC flux and discharge in all three rivers, whereas the DOC concentration was more strongly correlated with the regional net primary productivity (NPP). We estimated the total DOC flux exported by the three rivers into the China Sea to be approximately 2.73 Tg yr-1. Specifically, the annual flux of DOC from the Yangtze River, Yellow River and Pearl River was estimated to be 1.85 Tg yr-1, 0.06 Tg yr-1 and 0.82 Tg yr-1, respectively, and the average annual DOC concentrations were estimated to be 2.24 ± 0.53 mg L-1, 2.70 ± 0.38 mg L-1 and 1.51 ± 0.09 mg L-1, respectively. Seasonal variations in DOC concentrations are greatly influenced by the interaction between temperature and precipitation. NPP is significantly and positively related to the DOC concentration in the Yangtze River and the Pearl River. In addition, differences in climate and the productivity of the vegetation may influence both the flux and concentrations of DOC transported by the rivers and thus potentially affect estuarine geochemistry. [ABSTRACT FROM AUTHOR]

Background: The decomposition of plant material in arid ecosystems is considered to be substantially controlled by water and N availability. The responses of litter decomposition to external N and water, however, remain controversial, and the interactive effects of supplementary N and water also have been largely unexamined. Methodology/Principal Findings: A 3.5-year field experiment with supplementary nitrogen and water was conducted to assess the effects of N and water addition on mass loss and nitrogen release in leaves and fine roots of three dominant plant species (i.e., Artemisia halondendron, Setaria viridis, and Phragmites australis) with contrasting substrate chemistry (e.g. N concentration, lignin content in this study) in a desertified dune grassland of Inner Mongolia, China. The treatments included N addition, water addition, combination of N and water, and an untreated control. The decomposition rate in both leaves and roots was related to the initial litter N and lignin concentrations of the three species. However, litter quality did not explain the slower mass loss in roots than in leaves in the present study, and thus warrant further research. Nitrogen addition, either alone or in combination with water, significantly inhibited dry mass loss and N release in the leaves and roots of the three species, whereas water input had little effect on the decomposition of leaf litter and fine roots, suggesting that there was no interactive effect of supplementary N and water on litter decomposition in this system. Furthermore, our results clearly indicate that the inhibitory effects of external N on dry mass loss and nitrogen release are relatively strong in high-lignin litter compared with low-lignin litter. Conclusion/Significance: These findings suggest that increasing precipitation hardly facilitates ecosystem carbon turnover but atmospheric N deposition can enhance carbon sequestration and nitrogen retention in desertified dune grasslands of northern China. Additionally, litter quality of plant species should be considered when modelling the carbon cycle and nutrient dynamics of this system. [ABSTRACT FROM AUTHOR]

The species concept in marine phytoplankton is defined based on genomic, morphological, and functional properties. Reports of intraspecific diversity are widespread across major phytoplankton groups but the impacts of this variation on ecological and biogeochemical processes are often overlooked. Intraspecific diversity is well known within coccolithophores, which play an important role in the marine carbon cycle via production of particulate inorganic carbon. In this study, we investigated strain-specific responses to temperature in terms of morphology, carbon production, and carbonate mineralogy using a combination of microscopy, elemental analysis, flow cytometry, and nuclear magnetic resonance. Two strains of the cosmopolitan coccolithophore E. huxleyi isolated from different regions (subtropical, CCMP371; temperate, CCMP3266) were cultured under a range of temperature conditions (10°C, 15°C, and 20°C) using batch cultures and sampled during both exponential and stationary growth. Results for both strains showed that growth rates decreased at lower temperatures while coccosphere size increased. Between 15°C and 20°C, both strains produced similar amounts of total carbon, but differed in allocation of that carbon between particulate inorganic carbon (PIC) and particulate organic carbon (POC), though temperature effects were not detected. Between 10°C and 20°C, temperature effects on daily production of PIC and POC, as well as the cellular quota of POC were detected in CCMP3266. Strain-specific differences in coccolith shedding rates were found during exponential growth. In addition, daily shedding rates were negatively related to temperature in CCMP371 but not in CCMP3266. Despite differences in rates of particulate inorganic carbon production, both strains were found to produce coccoliths composed entirely of pure calcite, as established by solid-state 13C and 43Ca NMR and X-ray diffraction measurements. These results highlight the limitations of the species concept and the need for a trait-based system to better quantify diversity within marine phytoplankton communities. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate changes in glucose metabolism at the early stage and onset of diabetes in Otsuka Long-Evans Tokushima Fatty (OLETF) rats. Specifically, after the oral administration of [1, 2, 3-13C]glucose, the levels of exhaled 13CO2, which most likely originated from pyruvate decarboxylation and tricarboxylic acid, were measured. Eight OLETF rats and eight control rats (Long-Evans Tokushima Otsuka [LETO]) were administered 13C-glucose. Three types of 13C-glucose breath tests were performed thrice in each period at 2-week intervals. [3-13C]glucose results in a 13C isotope at position 1 in the pyruvate molecule, which provides 13CO2. The 13C at carbons 1 and 2 of glucose is converted to 13C at carbons 2 and 1 of acetate, respectively, which produce 13CO2. Based on metabolic differences of the labeled sites, glucose metabolism was evaluated using the results of three breath tests. The increase in 13CO2 excretion in OLETF rats was delayed in all three breath tests compared to that in control rats, suggesting that OLETF rats had a lower glucose metabolism than control rats. In addition, overall glucose metabolism increased with age in both groups. The utilization of [2-13C]glucose was suppressed in OLETF rats at 6–12 weeks of age, but they showed higher [3-13C]glucose oxidation than control rats at 22–25 weeks of age. In the [1-13C]glucose breath test, no significant differences in the area under the curve until 180 minutes (AUC180) were observed between OLETF and LETO rats of any age. Glucose metabolism kinetics were different between the age groups and two groups of rats; however, these differences were not significant based on the overall AUC180 of [1-13C]glucose. We conclude that breath 13CO2 excretion is reduced in OLETF rats at the primary stage of prediabetes, indicating differences in glucose oxidation kinetics between OLETF and LETO rats. [ABSTRACT FROM AUTHOR]

Understanding interactions between native and invasive plant species in field settings and quantifying the impact of invaders in heterogeneous native ecosystems requires resolving the spatial scale on which these processes take place. Therefore, functional tracers are needed that enable resolving the alterations induced by exotic plant invasion in contrast to natural variation in a spatially explicit way. 15N isoscapes, i.e., spatially referenced representations of stable nitrogen isotopic signatures, have recently provided such a tracer. However, different processes, e.g. water, nitrogen or carbon cycles, may be affected at different spatial scales. Thus multi-isotope studies, by using different functional tracers, can potentially return a more integrated picture of invader impact. This is particularly true when isoscapes are submitted to statistical methods suitable to find homogeneous subgroups in multivariate data such as cluster analysis. Here, we used model-based clustering of spatially explicit foliar δ15N and δ13C isoscapes together with N concentration of a native indicator species, Corema album, to map regions of influence in a Portuguese dune ecosystem invaded by the N2-fixing Acacia longifolia. Cluster analysis identified regions with pronounced alterations in N budget and water use efficiency in the native species, with a more than twofold increase in foliar N, and δ13C and δ15N enrichment of up to 2‰ and 8‰ closer to the invader, respectively. Furthermore, clusters of multiple functional tracers indicated a spatial shift from facilitation through N addition in the proximity of the invader to competition for resources other than N in close contact. Finding homogeneous subgroups in multi-isotope data by means of model-based cluster analysis provided an effective tool for detecting spatial structure in processes affecting plant physiology and performance. The proposed method can give an objective measure of the spatial extent of influence of plant-plant interactions, thus improving our understanding of spatial pattern and interactions in plant communities. [ABSTRACT FROM AUTHOR]

Relief of iron (Fe) limitation in the surface Southern Ocean has been suggested as one driver of the regular glacial-interglacial cycles in atmospheric carbon dioxide (CO2). The proposed cause is enhanced deposition of Fe-bearing atmospheric dust to the oceans during glacial intervals, with consequent effects on export production and the carbon cycle. However, understanding the role of enhanced atmospheric Fe supply in biogeochemical cycles is limited by knowledge of the fluxes and ‘bioavailability’ of atmospheric Fe during glacial intervals. Here, we assess the effect of Fe fertilization by dust, dry-extracted from the Last Glacial Maximum portion of the EPICA Dome C Antarctic ice core, on the Antarctic diatom species Eucampia antarctica and Proboscia inermis. Both species showed strong but differing reactions to dust addition. E. antarctica increased cell number (3880 vs. 786 cells mL-1), chlorophyll a (51 vs. 3.9 μg mL-1) and particulate organic carbon (POC; 1.68 vs. 0.28 μg mL-1) production in response to dust compared to controls. P. inermis did not increase cell number in response to dust, but chlorophyll a and POC per cell both strongly increased compared to controls (39 vs. 15 and 2.13 vs. 0.95 ng cell-1 respectively). The net result of both responses was a greater production of POC and chlorophyll a, as well as decreased Si:C and Si:N incorporation ratios within cells. However, E, antarctica decreased silicate uptake for the same nitrate and carbon uptake, while P. inermis increased carbon and nitrate uptake for the same silicate uptake. This suggests that nutrient utilization changes in response to Fe addition could be driven by different underlying mechanisms between different diatom species. Enhanced supply of atmospheric dust to the surface ocean during glacial intervals could therefore have driven nutrient-utilization changes which could permit greater carbon fixation for lower silica utilization. Additionally, both species responded more strongly to lower amounts of direct Fe chloride addition than they did to dust, suggesting that not all the Fe released from dust was in a bioavailable form available for uptake by diatoms. [ABSTRACT FROM AUTHOR]