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Chronologies of sediments that document the last glacial history of the Black Sea "Lake" are hampered by issues relating to reservoir age. Regulated by basin hydrology, reservoir ages represent a tool that could potentially be used to better understand the response of Black Sea "Lake" hydrology to climate change. Therefore, deciphering reservoir age evolution is crucial both for better constraining the basin chronological framework and for providing new insights into our understanding of Black Sea "Lake" hydrology. By tuning a meaningful new high-resolution geochemical dataset (obtained from core MD04-2790) to a climate reference record, here, we propose a reliable chronology spanning the last 32 kyr BP. The chronology is compared to a large AMS radiocarbon dataset (n = 51). Pairs of calendar and radiocarbon ages allowed us to compute reservoir ages, and to, then, reconstruct a high-resolution quantitative reservoir age record for the last glacial history of the Black Sea "Lake". The main factor controlling reservoir ages in lakes is the Hard Water Effect (HWE), which is regulated by basin hydrology. Therefore, changes in the reconstructed reservoir age record have been qualitatively interpreted in terms of the hydrologic responses of the Black Sea "Lake" to climate change. Our results allowed us to determine periods of complete isolation or outflow for the Black Sea "Lake". During Heinrich Event 2 (HE2) and during the Last Glacial Maximum (LGM) the basin was strictly isolated, whereas prior to HE2 and during HE1 it outflowed into the Marmara Sea. Following the onset of the Bølling-Allerød, factors other than the HWE are thought to have influenced the reservoir age, preventing conclusive interpretations. We also determined an undocumented, to date, phase of Black Sea "Lake" stratification during the full glacial (HE2 and LGM). Our results indicate that reservoir age is a powerful tool for investigating and better understanding past hydrologic changes in lakes and inland seas. Research highlights ► Reservoir ages record hydrologic responses to climate change. ► By tuning, we provide a calendar chronology for Black Sea "Lake" sediments. ► Then, using a 14 C age dataset, we provide a highresolution reservoir age record. ► The Black Sea "Lake" outflowed into the Marmara Sea prior to HE2 and during HE1. ► The basin was strictly isolated during the LGM, with water column stratified.

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An IR-laser fluorination technique is reported here for analyzing the oxygen isotope composition (delta18O) of microscopic biogenic silica grains (phytoliths and diatoms). Performed after a controlled isotopic exchanged (CIE) procedure, the laser fluorination technique that allows one to visually check the success of the fluorination reaction is faster than the conventional fluorination technique and allows analyzing delta18O of small to minute samples (1.6-0.3 mg) as required for high-resolution paleoenvironmental reconstructions. The long-term reproducibility achieved with the IR laser-heating fluorination/O2 delta18O analysis is lower than or equal to +/-0.26 per thousand (1 SD; n = 99) for phytoliths and +/-0.17 per thousand (1 SD; n = 47) for diatoms. When several CIE are taken into account in the SD calculation, the resulting reproducibility is lower than or equal to +/-0.51 per thousand for phytoliths (1 SD; n = 99; CIE > 5) and +/-0.54 per thousand (1 SD; n = 47; CIE = 13) for diatoms. A minimum reproducibility of +/-0.5 per thousand leads to an estimated uncertainty on delta18Osilica close to +/-0.5 per thousand. Resulting uncertainties on reconstructed temperature and delta18Oforming water are, respectively, +/-2 degrees C and +/-0.5 per thousand and fit in the precisions required for intertropical paleoenvironmental reconstructions. Several methodological points such as optimal extraction protocols and the necessity or not of performing two CIE prior to oxygen extraction are assessed.

[1] Bayesian analysis is becoming increasingly popular in a number of fields, including hydrology. It appears to be a convenient framework for deriving complex models in agreement with both physical reality and statistical requirements. The aim of this paper is to present an application to the regional frequency analysis of extremes in a nonstationary context. A nonstationary regional model is thus proposed, together with the related hypotheses. The Bayesian inference of this model is then described. Markov chain Monte Carlo (MCMC) methods are needed for this purpose because of the dimensionality of the model and are described in this paper. The usefulness of such a model is then illustrated on a hydrological case study concerning annual maximum discharges of several sites. The advantage of regional analysis compared to at-site estimation is thus highlighted. Moreover, the Bayesian framework allows for a direct and comprehensive inference based on the posterior distribution and is able to take into account modeling uncertainties, which is particularly useful when the stationarity of a series can neither be ensured nor be totally rejected.

Climate reconstructions from data sensitive to past climates provide estimates of what these climates were like. Comparing these reconstructions with simulations from climate models allows to validate the models used for future climate prediction. It has been shown that for fossil pollen data, gaining estimates by inverting a vegetation model allows inclusion of past changes in carbon dioxide values. As a new generation of dynamic vegetation model is available we have developed an inversion method for one model, LPJ-GUESS. When this novel method is used with high-resolution sediment it allows us to bypass the classic assumptions of (1) climate and pollen independence between samples and (2) equilibrium between the vegetation, represented as pollen, and climate. Our dynamic inversion method is based on a statistical model to describe the links among climate, simulated vegetation and pollen samples. The inversion is realised thanks to a particle filter algorithm. We perform a validation on 30 modern European sites and then apply the method to the sediment core of Meerfelder Maar (Germany), which covers the Holocene at a temporal resolution of approximately one sample per 30 years. We demonstrate that reconstructed temperatures are constrained. The reconstructed precipitation is less well constrained, due to the dimension considered (one precipitation by season), and the low sensitivity of LPJ-GUESS to precipitation changes.

Current modelling of inoculum transmission from a cropping season to the following one relies on the extrapolation of kernels estimated on data at short distances from punctual sources, because data collected at larger distances are scarce. We estimated the dispersal kernel of Leptosphaeria maculans ascospores from stubble left after harvest in the summer previous to newly sown oilseed rape fields, using phoma stem canker autumn disease severity. We built a dispersal model to analyse the data. Source strengths are described in the spatial domain covered by source fields by a log-Gaussian spatial process. Infection potentials in the following season are described in the space consisting of the target fields, by a convolution of sources and a power-exponential dispersal kernel. Data were collected on farmers' fields considered as sources in 2009 and 2011 (72 and 39 observation points) and as targets in 2010 and 2012 (172 and 200 points). We applied the Bayesian approach for model selection and parameter estimation. We obtained fat tail kernels for both data sets. This estimation is the first from data acquired over distances of 0 to 1000 m, using several non-punctual inoculum sources. It opens the prospect of refining the existing simulators, or developing disease risk maps.

Abstract. Important progresses have been made in palaeoclimatological studies by using statistical methods. But they are in somewhere limited as they take the present as an absolute reference. This is particularly true for the modern analogue technique. The availability of mechanistic models to simulate the proxies measured in the sediment cores gives now the possibility to relax this constraint. In particular, vegetation models provide outputs comparable to pollen data (assuming that there is a relationship between plant productivity and pollen counts). The input of such models is, among others, climate. The idea behind paleoclimatological reconstructions is then to obtain inputs, given outputs. This procedure, called model inversion, can be achieved with appropriate algorithms in the frame of the Bayesian statistical theory. But we have chosen to present it in an intuitive way, avoiding the mathematics behind it. Starting from a relative simple application, based on an equilibrium BIOME3 model with a single proxy (pollen), the approach has evolved into two directions: (1) by using several proxies measured on the same core (e.g. lake-level status and δ 13 C) when they are related to a component of the vegetation, and (2) by using a more complex vegetation model, the dynamic vegetation model LPJ-GUESS. Examples presented (most of them being already published) concern Last Glacial Maximum in Europe and Africa, Holocene in a site of the Swiss Jura, anCorrespondence to: J. Guiot (guiot@cerege.fr) Eemian site in France. The main results are that: (1) pollen alone is not able to provide exhaustive information on precipitation, (2) assuming past CO 2 equivalent to modern one may induce biases in climate reconstruction, (3) vegetation models seem to be too much constrained by temperature relative to precipitation in temperate regions. This paper attempts to organise some recent ideas in the palaeoclimatological reconstruction domain and to propose prospectives in that effervescent domain.