Combined Earth observations reveal the sequence of conditions leading to a large algal bloom in Lake Geneva.

Freshwater algae exhibit complex dynamics, particularly in meso-oligotrophic lakes with sudden and dramatic increases in algal biomass following long periods of low background concentration. While the fundamental prerequisites for algal blooms, namely light and nutrient availability, are well-known, their specific causation involves an intricate chain of conditions. Here we examine a recent massive Uroglena bloom in Lake Geneva (Switzerland/France). We show that a certain sequence of meteorological conditions triggered this specific algal bloom event: heavy rainfall promoting excessive organic matter and nutrients loading, followed by wind-induced coastal upwelling, and a prolonged period of warm, calm weather. The combination of satellite remote sensing, in-situ measurements, ad-hoc biogeochemical analyses, and three-dimensional modeling proved invaluable in unraveling the complex dynamics of algal blooms highlighting the substantial role of littoral-pelagic connectivities in large low-nutrient lakes. These findings underscore the advantages of state-of-the-art multidisciplinary approaches for an improved understanding of dynamic systems as a whole.

36Cl, a new tool to assess soil carbon dynamics.

Soil organic carbon is one of the largest surface pools of carbon that humans can manage in order to partially mitigate annual anthropogenic CO2 emissions. A significant element to assess soil sequestration potential is the carbon age, which is evaluated by modelling or experimentally using carbon isotopes. Results, however, are not consistent. The 14C derived approach seems to overestimate by a factor of 6-10 the average carbon age in soils estimated by modeling and 13C approaches and thus the sequestration potential. A fully independent method is needed. The cosmogenic chlorine nuclide, 36Cl, is a potential alternative. 36Cl is a naturally occurring cosmogenic radionuclide with a production that increased by three orders of magnitude during nuclear bomb tests. Part of this production is retained by soil organic matter in organochloride form and hence acts as a tracer of the fate of soil organic carbon. We here quantify the fraction and the duration of 36Cl retained in the soil and we show that retention time increases with depth from 20 to 322 years, in agreement with both modelling and 13C-derived estimates. This work demonstrates that 36Cl retention duration can be a proxy for the age of soil organic carbon.

Bioenergetic control of soil carbon dynamics across depth.

Soil carbon dynamics is strongly controlled by depth globally, with increasingly slow dynamics found at depth. The mechanistic basis remains however controversial, limiting our ability to predict carbon cycle-climate feedbacks. Here we combine radiocarbon and thermal analyses with long-term incubations in absence/presence of continuously 13C/14C-labelled plants to show that bioenergetic constraints of decomposers consistently drive the depth-dependency of soil carbon dynamics over a range of mineral reactivity contexts. The slow dynamics of subsoil carbon is tightly related to both its low energy density and high activation energy of decomposition, leading to an unfavourable 'return-on-energy-investment' for decomposers. We also observe strong acceleration of millennia-old subsoil carbon decomposition induced by roots ('rhizosphere priming'), showing that sufficient supply of energy by roots is able to alleviate the strong energy limitation of decomposition. These findings demonstrate that subsoil carbon persistence results from its poor energy quality together with the lack of energy supply by roots due to their low density at depth.

Review of Bayesian selection methods for categorical predictors using JAGS.

The formulation of variable selection has been widely developed in the Bayesian literature by linking a random binary indicator to each variable. This Bayesian inference has the advantage of stochastically exploring the set of possible sub-models, whatever their dimension. Bayesian selection approaches, appropriate for categorical predictors, are generally beyond the scope of the standard Bayesian selection of regressors in the linear model since all levels of a categorical variable should be jointly handled in the selection procedure. For categorical covariates, new strategies have been developed to detect the effect of grouped covariates rather than the single effect of a quantitative regressor. In this paper, we review three Bayesian selection methods for categorical predictors: Bayesian Group Lasso with Spike and Slab priors, Bayesian Sparse Group Selection and Bayesian Effect Fusion using model-based clustering. The motivation behind this paper is to provide detailed information about the implementation of the three Bayesian selection methods mentioned above, appropriate for categorical predictors, using the JAGS software. Selection performance and sensitivity analysis of the hyperparameters tuning for prior specifications are assessed under various simulated scenarios. JAGS helps user implement these three Bayesian selection methods for more complex model structures such as hierarchical ones with latent layers.

24.0 kyr cal BP stone artefact from Vale da Pedra Furada, Piauí, Brazil: Techno-functional analysis.

Current archaeological paradigm proposes that the first peopling of the Americas does not exceed the Last Glacial Maximum period. In this context, the acceptance of the anthropogenic character of the earliest stone artefacts generally rests on the presence of projectile points considered no more as typocentric but as typognomonic, since it allows, by itself, to certify the human character of the other associated artefacts. In other words, without this presence, nothing is certain. Archaeological research at Piauí (Brazil) attests to a Pleistocene human presence between 41 and 14 cal kyr BP, without any record of lithic projectile points. Here, we report the discovery and interpretation of an unusual stone artefact in the Vale da Pedra Furada site, in a context dating back to 24 cal kyr BP. The knapping stigmata and macroscopic use-wear traces reveal a conception centred on the configuration of double bevels and the production in the same specimen of at least two successive artefacts with probably different functions. This piece unambiguously presents an anthropic character and reveals a technical novelty during the Pleistocene occupation of South America.

Contribution of Peatland Permafrost to Dissolved Organic Matter along a Thaw Gradient in North Siberia.

Permafrost peatlands are important carbon stocks currently experiencing rapid evolution after permafrost thaw. Following thaw, dissolved organic matter (DOM) is a potentially important pathway for the release of permafrost carbon. This study investigates the origin and composition of DOM across sites at different stages of thaw in a discontinuous permafrost area of North Siberia. We determine the optical properties, molecular composition, and stable isotopic (δ13C) and radiocarbon (14C) contents of DOM. Early stages of thaw are characterized by high DOC concentrations, high aromaticity, contribution of vegetation-derived DOM, and a high contribution of permafrost carbon. In contrast, in later stages, the microbial contribution to DOM increases, and only modern carbon is detected. This work links DOM composition with its radiocarbon content in permafrost peatlands. It shows that DOM originating from previously frozen permafrost peatlands is highly aromatic and previously processed. It highlights the variability of post-thaw carbon dynamics in boreal and arctic ecosystems.

Including Stable Carbon Isotopes to Evaluate the Dynamics of Soil Carbon in the Land-Surface Model ORCHIDEE.

Soil organic carbon (SOC) is a crucial component of the terrestrial carbon cycle and its turnover time in models is a key source of uncertainty. Studies have highlighted the utility of δ13C measurements for benchmarking SOC turnover in global models. We used 13C as a tracer within a vertically discretized soil module of a land-surface model, Organising Carbon and Hydrology In Dynamic Ecosystems- Soil Organic Matter (ORCHIDEE-SOM). Our new module represents some of the processes that have been hypothesized to lead to a 13C enrichment with soil depth as follows: 1) the Suess effect and CO2 fertilization, 2) the relative 13C enrichment of roots compared to leaves, and 3) 13C discrimination associated with microbial activity. We tested if the upgraded soil module was able to reproduce the vertical profile of δ13C within the soil column at two temperate sites and the short-term change in the isotopic signal of soil after a shift in C3/C4 vegetation. We ran the model over Europe to test its performance at larger scale. The model was able to simulate a shift in the isotopic signal due to short-term changes in vegetation cover from C3 to C4; however, it was not able to reproduce the overall vertical profile in soil δ13C, which arises as a combination of short and long-term processes. At the European scale, the model ably reproduced soil CO2 fluxes and total SOC stock. These findings stress the importance of the long-term history of land cover for simulating vertical profiles of δ13C. This new soil module is an emerging tool for the diagnosis and improvement of global SOC models.

Atmosphere-soil carbon transfer as a function of soil depth.

The exchange of carbon between soil organic carbon (SOC) and the atmosphere affects the climate1,2 and-because of the importance of organic matter to soil fertility-agricultural productivity3. The dynamics of topsoil carbon has been relatively well quantified4, but half of the soil carbon is located in deeper soil layers (below 30 centimetres)5-7, and many questions remain regarding the exchange of this deep carbon with the atmosphere8. This knowledge gap restricts soil carbon management policies and limits global carbon models1,9,10. Here we quantify the recent incorporation of atmosphere-derived carbon atoms into whole-soil profiles, through a meta-analysis of changes in stable carbon isotope signatures at 112 grassland, forest and cropland sites, across different climatic zones, from 1965 to 2015. We find, in agreement with previous work5,6, that soil at a depth of 30-100 centimetres beneath the surface (the subsoil) contains on average 47 per cent of the topmost metre's SOC stocks. However, we show that this subsoil accounts for just 19 per cent of the SOC that has been recently incorporated (within the past 50 years) into the topmost metre. Globally, the median depth of recent carbon incorporation into mineral soil is 10 centimetres. Variations in the relative allocation of carbon to deep soil layers are better explained by the aridity index than by mean annual temperature. Land use for crops reduces the incorporation of carbon into the soil surface layer, but not into deeper layers. Our results suggest that SOC dynamics and its responses to climatic control or land use are strongly dependent on soil depth. We propose that using multilayer soil modules in global carbon models, tested with our data, could help to improve our understanding of soil-atmosphere carbon exchange.

The impact of Last Glacial climate variability in west-European loess revealed by radiocarbon dating of fossil earthworm granules.

The characterization of Last Glacial millennial-timescale warming phases, known as interstadials or Dansgaard-Oeschger events, requires precise chronologies for the study of paleoclimate records. On the European continent, such chronologies are only available for several Last Glacial pollen and rare speleothem archives principally located in the Mediterranean domain. Farther north, in continental lowlands, numerous high-resolution records of loess and paleosols sequences show a consistent environmental response to stadial-interstadial cycles. However, the limited precision and accuracy of luminescence dating methods commonly used in loess deposits preclude exact correlations of paleosol horizons with Greenland interstadials. To overcome this problem, a radiocarbon dating protocol has been developed to date earthworm calcite granules from the reference loess sequence of Nussloch (Germany). Its application yields a consistent radiocarbon chronology of all soil horizons formed between 47 and 20 ka and unambiguously shows the correlation of every Greenland interstadial identified in isotope records with specific soil horizons. Furthermore, eight additional minor soil horizons dated between 27.5 and 21 ka only correlate with minor decreases in Greenland dust records. This dating strategy reveals the high sensitivity of loess paleoenvironments to Northern Hemisphere climate changes. A connection between loess sedimentation rate, Fennoscandian ice sheet dynamics, and sea level changes is proposed. The chronological improvements enabled by the radiocarbon "earthworm clock" thus strongly enhance our understanding of loess records to a better perception of the impact of Last Glacial climate changes on European paleoenvironments.

Labelled microbial culture as a calibration medium for (13) C-isotope measurement of derivatized compounds: application to tert-butyldimethylsilyl amino acids.

RATIONALE: Compound-specific stable carbon isotope analysis by gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS) is widely used in studies of environmental or biological functioning. In the case of derivatized molecules, a calibration might be required due to added non-analyte carbon and in some cases non-stoichiometric recovery by the mass spectrometer. METHODS: Two biological materials of known isotopic composition were produced by microbial cell cultures on either (13) C-labelled glucose or non-labelled glucose as sole source of carbon. Subsequent hydrolyzed amino acids were derivatized as tert-butyldimethylsilyl (tBDMSi) derivatives and analyzed by GC/C/IRMS. The (13) C-enrichment measurements were used as a direct calibration to calculate the original (13) C/(12) C ratios of individual amino acids. We tested this calibration on both known and unknown samples. RESULTS: For the main proteinogenic amino acids we could determine the number of non-analyte added carbon atoms and assess the non-stoichiometrical recovery of tBDMSi carbon atoms, due to their incomplete oxidation in the combustion step of GC/C/IRMS. The calibration enabled the determination of the natural abundances (δ(13) C values) of amino acids with an average accuracy of ±1.1 ‰. We illustrate the application of the calibration to determine the (13) C/(12) C ratios of amino acids, and the associated uncertainty, in biological and plant materials. CONCLUSIONS: The analysis of a labelled microbial cell culture offers a straightforward, rapid and reliable estimate of non-analyte carbon contribution to stable isotope composition. We recommend this method as a calibration or a control in artificial or natural (13) C-tracing experiments. Copyright © 2016 John Wiley & Sons, Ltd.

Deep soil carbon dynamics are driven more by soil type than by climate: a worldwide meta-analysis of radiocarbon profiles.

The response of soil carbon dynamics to climate and land-use change will affect both the future climate and the quality of ecosystems. Deep soil carbon (>20 cm) is the primary component of the soil carbon pool, but the dynamics of deep soil carbon remain poorly understood. Therefore, radiocarbon activity (Δ14C), which is a function of the age of carbon, may help to understand the rates of soil carbon biodegradation and stabilization. We analyzed the published 14C contents in 122 profiles of mineral soil that were well distributed in most of the large world biomes, except for the boreal zone. With a multivariate extension of a linear mixed-effects model whose inference was based on the parallel combination of two algorithms, the expectation-maximization (EM) and the Metropolis-Hasting algorithms, we expressed soil Δ14C profiles as a four-parameter function of depth. The four-parameter model produced insightful predictions of soil Δ14C as dependent on depth, soil type, climate, vegetation, land-use and date of sampling (R2=0.68). Further analysis with the model showed that the age of topsoil carbon was primarily affected by climate and cultivation. By contrast, the age of deep soil carbon was affected more by soil taxa than by climate and thus illustrated the strong dependence of soil carbon dynamics on other pedologic traits such as clay content and mineralogy.

Measurement of δ13C values of soil amino acids by GC-C-IRMS using trimethylsilylation: a critical assessment.

In this study, we evaluated trimethylsilyl (TMS) derivatives as derivatization reagents for the compound-specific stable carbon isotope analysis of soil amino acids by gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS). We used non-proteinogenic amino acids to show that the extraction-derivatization-analysis procedure provides a reliable method to measure δ(13)C values of amino acids extracted from soil. However, we found a number of drawbacks that significantly increase the final total uncertainty. These include the following: production of multiple peaks for each amino acid, identified as di-, tri- and tetra-TMS derivatives; a number of TMS-carbon (TMS-C) atoms added lower than the stoichiometric one, possibly due to incomplete combustion; different TMS-C δ(13)C for di-, tri- and tetra-TMS derivatives. For soil samples, only four amino acids (leucine, valine, threonine and serine) provide reliable δ(13)C values with a total average uncertainty of 1.3 ‰. We conclude that trimethylsilyl derivatives are only suitable for determining the (13)C incorporation in amino acids within experiments using (13)C-labelled tracers but cannot be applied for amino acids with natural carbon isotope abundance until the drawbacks described here are overcome and the measured total uncertainty significantly decreased.

Elevation-induced climate change as a dominant factor causing the late Miocene C(4) plant expansion in the Himalayan foreland.

During the late Miocene, a dramatic global expansion of C4 plant distribution occurred with broad spatial and temporal variations. Although the event is well documented, whether subsequent expansions were caused by a decreased atmospheric CO2 concentration or climate change is a contentious issue. In this study, we used an improved inverse vegetation modeling approach that accounts for the physiological responses of C3 and C4 plants to quantitatively reconstruct the paleoclimate in the Siwalik of Nepal based on pollen and carbon isotope data. We also studied the sensitivity of the C3 and C4 plants to changes in the climate and the atmospheric CO2 concentration. We suggest that the expansion of the C4 plant distribution during the late Miocene may have been primarily triggered by regional aridification and temperature increases. The expansion was unlikely caused by reduced CO2 levels alone. Our findings suggest that this abrupt ecological shift mainly resulted from climate changes related to the decreased elevation of the Himalayan foreland.