LIttoral ENvironnement et Sociétés

In this communication we introduce marmap, a package designed for downloading, plotting and manipulating bathymetric and topographic data in R. marmap can query the ETOPO1 bathymetry and topography database hosted by the NOAA, use simple latitude-longitude-depth data in ascii format, and take advantage of the advanced plotting tools available in R to build publication-quality bathymetric maps. Functions to query data (bathymetry, sampling information…) are available interactively by clicking on marmap maps. Bathymetric and topographic data can also be used to calculate projected surface areas within specified depth/altitude intervals, and constrain the calculation of realistic shortest path distances. Such information can be used in molecular ecology, for example, to evaluate genetic isolation by distance in a spatially-explicit framework.

The European Union (EU) Habitats Directive requires Member States to monitor and maintain at favourable conservation status those species identified to be in need of protection, including all cetaceans. In July 2005 we surveyed the entire EU Atlantic continental shelf to generate robust estimates of abundance for harbour porpoise and other cetacean species. The survey used line transect sampling methods and purpose built data collection equipment designed to minimise bias in estimates of abundance. Shipboard transects covered 19,725 km in sea conditions ⩽Beaufort 4 in an area of 1,005,743 km2. Aerial transects covered 15,802 km in good/moderate conditions (⩽Beaufort 3) in an area of 364,371 km2. Thirteen cetacean species were recorded; abundance was estimated for harbour porpoise (375,358; CV = 0.197), bottlenose dolphin (16,485; CV = 0.422), white-beaked dolphin (16,536; CV = 0.303), short-beaked common dolphin (56,221; CV = 0.234) and minke whale (18,958; CV = 0.347). Abundance in 2005 was similar to that estimated in July 1994 for harbour porpoise, white-beaked dolphin and minke whale in a comparable area. However, model-based density surfaces showed a marked difference in harbour porpoise distribution between 1994 and 2005. Our results allow EU Member States to discharge their responsibilities under the Habitats Directive and inform other international organisations concerning the assessment of conservation status of cetaceans and the impact of bycatch at a large spatial scale. The lack of evidence for a change in harbour porpoise abundance in EU waters as a whole does not exclude the possibility of an impact of bycatch in some areas. Monitoring bycatch and estimation of abundance continue to be essential.

from 1993 to 2012 is consistent with independent estimates from satellite altimetry, leading to overall acceleration larger than previously suggested. This feature is geographically dominated by the Indian Ocean-Southern Pacific region, marking a transition from lower-than-average rates before 1990 toward unprecedented high rates in recent decades. We demonstrate that VLM corrections, area weighting, and our use of a common reference datum for tide gauges may explain the lower rates compared with earlier GMSL estimates in approximately equal proportion. The trends and multidecadal variability of our GMSL curve also compare well to the sum of individual contributions obtained from historical outputs of the Coupled Model Intercomparison Project Phase 5. This, in turn, increases our confidence in process-based projections presented in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.

Environmental mercury (Hg) contamination is an urgent global health threat. The complexity of Hg in the environment can hinder accurate determination of ecological and human health risks, particularly within the context of the rapid global changes that are altering many ecological processes, socioeconomic patterns, and other factors like infectious disease incidence, which can affect Hg exposures and health outcomes. However, the success of global Hg-reduction efforts depends on accurate assessments of their effectiveness in reducing health risks. In this paper, we examine the role that key extrinsic and intrinsic drivers play on several aspects of Hg risk to humans and organisms in the environment. We do so within three key domains of ecological and human health risk. First, we examine how extrinsic global change drivers influence pathways of Hg bioaccumulation and biomagnification through food webs. Next, we describe how extrinsic socioeconomic drivers at a global scale, and intrinsic individual-level drivers, influence human Hg exposure. Finally, we address how the adverse health effects of Hg in humans and wildlife are modulated by a range of extrinsic and intrinsic drivers within the context of rapid global change. Incorporating components of these three domains into research and monitoring will facilitate a more holistic understanding of how ecological and societal drivers interact to influence Hg health risks.

An algorithm for finding minimum-weight words in large linear codes is developed. It improves all previous attacks on the public-key cryptosystems based on codes and it notably points out some weaknesses in McEliece's (1978) cipher. We also determine with it the minimum distance of some BCH codes of length 511.

International audience

This book is a thoroughly revised edition of a monograph that presents an approach to the design and implementation of programming languages based on the relationship between lambda-calculus and category theory. The foundations of a new combinatory logic are laid down. Compilation and evaluation techniques are investigated. A simple abstract machine, called the Categorical Abstract Machine, is presented: it has served as the core of the implementation of the language CAML, of the ML family, developed at INRIA-Roquencourt and Ecole Normale Superieure, and first released in 1987. The main characteristics of this approach are conceptual simplicity and compactness, with bearings on portability, efficiency, and correctness proofs. A mathematical semantics of sequentiality is proposed, in which sequential rather than functions are used to interpret procedures. The theoretical investigation has led to the development of a programming language, CDSO, in which basic and functional types are not differentiated. The evaluation framework is a demand-driven data flow network. The model of algorithms is fully abstract with respect to this language: two procedures have the same denotation if and only if they have the same behaviour. Background on full abstraction is given. The new edition covers new results, and introduces new connections, as suggested by the following non-exhaustive fist of keywords: confluence properties of categorical combinators, explicit substitutions, control operations, linear logic, geometry of interaction, strong stability.

We consider neural networks with a single hidden layer and non-decreasing homogeneous activa-tion functions like the rectified linear units. By letting the number of hidden units grow unbounded and using classical non-Euclidean regularization tools on the output weights, we provide a detailed theoretical analysis of their generalization performance, with a study of both the approximation and the estimation errors. We show in particular that they are adaptive to unknown underlying linear structures, such as the dependence on the projection of the input variables onto a low-dimensional subspace. Moreover, when using sparsity-inducing norms on the input weights, we show that high-dimensional non-linear variable selection may be achieved, without any strong assumption regarding the data and with a total number of variables potentially exponential in the number of ob-servations. In addition, we provide a simple geometric interpretation to the non-convex problem of addition of a new unit, which is the core potentially hard computational element in the framework of learning from continuously many basis functions. We provide simple conditions for convex relaxations to achieve the same generalization error bounds, even when constant-factor approxi-mations cannot be found (e.g., because it is NP-hard such as for the zero-homogeneous activation function). We were not able to find strong enough convex relaxations and leave open the existence or non-existence of polynomial-time algorithms.

In a series of recent theoretical works, it was shown that strongly over-parameterized neural networks trained with gradient-based methods could converge exponentially fast to zero training loss, with their parameters hardly varying. In this work, we show that this "lazy training" phenomenon is not specific to over-parameterized neural networks, and is due to a choice of scaling, often implicit, that makes the model behave as its linearization around the initialization, thus yielding a model equivalent to learning with positive-definite kernels. Through a theoretical analysis, we exhibit various situations where this phenomenon arises in non-convex optimization and we provide bounds on the distance between the lazy and linearized optimization paths. Our numerical experiments bring a critical note, as we observe that the performance of commonly used non-linear deep convolutional neural networks in computer vision degrades when trained in the lazy regime. This makes it unlikely that "lazy training" is behind the many successes of neural networks in difficult high dimensional tasks.

Connectivity among populations determines the dynamics and evolution of populations, and its assessment is essential in ecology in general and in conservation biology in particular. The robust basis of any ecological study is the accurate delimitation of evolutionary units, such as populations, metapopulations and species. Yet a disconnect still persists between the work of taxonomists describing species as working hypotheses and the use of species delimitation by molecular ecologists interested in describing patterns of gene flow. This problem is particularly acute in the marine environment where the inventory of biodiversity is relatively delayed, while for the past two decades, molecular studies have shown a high prevalence of cryptic species. In this study, we illustrate, based on marine case studies, how the failure to recognize boundaries of evolutionary-relevant unit leads to heavily biased estimates of connectivity. We review the conceptual framework within which species delimitation can be formalized as falsifiable hypotheses and show how connectivity studies can feed integrative taxonomic work and vice versa. Finally, we suggest strategies for spatial, temporal and phylogenetic sampling to reduce the probability of inadequately delimiting evolutionary units when engaging in connectivity studies.

Through the photosynthetic activity, microalgae process more than 25% of annual inorganic carbon dissolved in oceans into carbohydrates that ultimately, serve to feed the other levels of the trophic networks. Besides, microalgae synthesize bioactive molecules such as pigments and lipids that exhibit health properties. In addition, abiotic stresses, such as high irradiance, nutrient starvation, UV irradiation, trigger metabolic reorientations ending with the production of other bioactive compounds such as ω-3 fatty acids or carotenoids. Traditionally, these compounds are acquired through the dietary alimentation. The increasing, and often unsatisfied, demand for compounds from natural sources, combined with the decrease of the halieutic resources, forces the search for alternative resources for these bioactive components. Microalgae possess this strong potential. For instance, the diatom Odontella aurita is already commercialized as dietary complement and compete with fish oil for human nutrition. In this contribution, the microalga world is briefly presented. Then, the different types of biologically active molecules identified in microalgae are presented together with their potential use. Due to space limitation, only the biological activities of lipids and pigments are described in details. The contribution ends with a description of the possibilities to play with the environmental constrains to increase the productivity of biologically active molecules by microalgae and by a description of the progresses made in the field of alga culturing.

Marine Archaea are important players among microbial plankton and significantly contribute to biogeochemical cycles, but details regarding their community structure and long-term seasonal activity and dynamics remain largely unexplored. In this study, we monitored the interannual archaeal community composition of abundant and rare biospheres in northwestern Mediterranean Sea surface waters by pyrosequencing 16S rDNA and rRNA. A detailed analysis of the rare biosphere structure showed that the rare archaeal community was composed of three distinct fractions. One contained the rare Archaea that became abundant at different times within the same ecosystem; these cells were typically not dormant, and we hypothesize that they represent a local seed bank that is specific and essential for ecosystem functioning through cycling seasonal environmental conditions. The second fraction contained cells that were uncommon in public databases and not active, consisting of aliens to the studied ecosystem and representing a nonlocal seed bank of potential colonizers. The third fraction contained Archaea that were always rare but actively growing; their affiliation and seasonal dynamics were similar to the abundant microbes and could not be considered a seed bank. We also showed that the major archaeal groups, Thaumarchaeota marine group I and Euryarchaeota group II.B in winter and Euryarchaeota group II.A in summer, contained different ecotypes with varying activities. Our findings suggest that archaeal diversity could be associated with distinct metabolisms or life strategies, and that the rare archaeal biosphere is composed of a complex assortment of organisms with distinct histories that affect their potential for growth.

Abstract In a context of global change and increasing anthropic pressure on the environment, monitoring the Earth system and its evolution has become one of the key missions of geosciences. Geodesy is the geoscience that measures the geometric shape of the Earth, its orientation in space, and gravity field. Time‐variable gravity, because of its high accuracy, can be used to build an enhanced picture and understanding of the changing Earth. Ground‐based gravimetry can determine the change in gravity related to the Earth rotation fluctuation, to celestial body and Earth attractions, to the mass in the direct vicinity of the instruments, and to vertical displacement of the instrument itself on the ground. In this paper, we review the geophysical questions that can be addressed by ground gravimeters used to monitor time‐variable gravity. This is done in relation to the instrumental characteristics, noise sources, and good practices. We also discuss the next challenges to be met by ground gravimetry, the place that terrestrial gravimetry should hold in the Earth observation system, and perspectives and recommendations about the future of ground gravity instrumentation.

In this study, we show a fundamental difference between diatom species from different marine habitats in their ability to cope with changes in irradiance. Estuarine species show a higher and more flexible capacity for photoprotection than oceanic and coastal species, and when exposed to excess light, the impairment of their photosynthetic capacity because of photoinhibition was reduced. This resulted in maintenance of growth in a fluctuating light regime, conferring the estuarine species an adaptive advantage. The ability of diatoms, and to a larger extent other phytoplankton, to occupy a wide range of ecological niches depends critically on their capacity to exploit the differences in underwater light climate. These results might explain how diatoms adapt to the challenge of maintaining optimal photosynthetic production in turbulent waters, in which the rate of light change is high.

[1] This study focuses on the effects of time correlation in weekly GPS position time series on velocity estimates. Time series 2.5 to 13 years long from a homogeneously reprocessed solution of 275 globally distributed stations are analyzed in terms of noise content and velocity uncertainty assessment. Several noise models were tested, including power law and Gauss-Markov processes. The best noise model describing our global data set was a combination of variable white noise and power law noise models with mean amplitudes of ∼2 mm and ∼6 mm, respectively, for the sites considered. This noise model provided a mean vertical velocity uncertainty of ∼0.3 mm/yr, 4–5 times larger than the uncorrelated data assumption. We demonstrated that correlated noise content with homogeneously reprocessed data is dependent on time series length and, especially, on data time period. Time series of 2–3 years of the oldest data contain noise amplitude similar to that found for time series of 12 years. The data time period should be taken into account when estimating correlated noise content, when comparing different noise estimations, or when applying an external noise estimation to assess velocity uncertainty. We showed that the data period dependency cannot be explained by the increasing tracking network or the ambiguity fixation rate but is probably related to the amount and quality of recorded data.

We report the trophic structure of a myctophid assemblage by measuring the isotopic niches of 14 species living in Kerguelen waters, southern Indian Ocean. Most of the species show distinct isotopic niches that differ by at least one of the two niche axes (δ 13 C habitat and δ 15 N trophic position), indicating trophic partitioning within the assemblage. Strong niche segregation occurs within each of the three most common genera of myctophids ( Electrona , Gymnoscopelus , and Protomyctophum ), illustrating the different mechanisms (habitat and dietary segregation) that allow coexistence of closely related species. Calculated trophic levels (TLs) of myctophids ranged from 3.3 to 4.2, showing that they are secondary and tertiary consumers in the pelagic ecosystem. The positive relationship between TL and standard length of fish points out a structuring effect of size, with larger species ( Gymnoscopelus spp.) occupying a higher trophic position than smaller species ( Krefftichthys anderssoni and Protomyctophum spp.). Myctophids occupy an intermediate trophic position between macrozooplanktonic crustaceans and seabirds and marine mammals within the pelagic ecosystem. However, the TLs of large myctophids overlap those of crustacean‐eating seabirds [e.g., Eudypte s spp. (crested penguins) and Pachyptila belcheri ]. The isotopic niche of myctophids indicates that Aptenodytes patagonicus (king penguin) adults prey upon K. anderssoni when they feed for themselves, thus exemplifying the usefulness of isotopic datasets on potential prey of predators to depict trophic relationships.

Abstract Cancer is a ubiquitous disease of metazoans, predicted to disproportionately affect larger, long-lived organisms owing to their greater number of cell divisions, and thus increased probability of somatic mutations 1,2 . While elevated cancer risk with larger body size and/or longevity has been documented within species 3–5 , Peto’s paradox indicates the apparent lack of such an association among taxa 6 . Yet, unequivocal empirical evidence for Peto’s paradox is lacking, stemming from the difficulty of estimating cancer risk in non-model species. Here we build and analyse a database on cancer-related mortality using data on adult zoo mammals (110,148 individuals, 191 species) and map age-controlled cancer mortality to the mammalian tree of life. We demonstrate the universality and high frequency of oncogenic phenomena in mammals and reveal substantial differences in cancer mortality across major mammalian orders. We show that the phylogenetic distribution of cancer mortality is associated with diet, with carnivorous mammals (especially mammal-consuming ones) facing the highest cancer-related mortality. Moreover, we provide unequivocal evidence for the body size and longevity components of Peto’s paradox by showing that cancer mortality risk is largely independent of both body mass and adult life expectancy across species. These results highlight the key role of life-history evolution in shaping cancer resistance and provide major advancements in the quest for natural anticancer defences.

Abstract We present an automatic P- and S-wave onset-picking algorithm, using kurtosis-derived characteristic functions (CF) and eigenvalue decompositions on three-component seismic data. We modified the kurtosis CF (Saragiotis et al., 2002) to improve pick precision by computing the CF over several frequency bandwidths, window sizes, and smoothing parameters. Once phases are picked, our algorithm determines the onset type (P or S) using polarization parameters, removes bad picks using a clustering procedure and the signal-to-noise ratio (SNR) and assigns a pick quality index based on the SNR. We tested our algorithm on data from two different networks: (1) a 30-station, 100 × 100 km array of mostly onland wideband seismometers in a subduction context and (2) a four-station, 7 × 4 km array of ocean-bottom seismometers over a midocean ridgevolcano.We compared picks from the automatic algorithmwithmanual and short-term average/long-term average (STA/LTA)-based automatic picks on subsets of each dataset. For the larger array, the automatic algorithm resulted in more locations than manual picking (133 versus 93 locations out of 163 total events detected), picking as many P onsets and twice as many S onsets as with manual picking or the STA/ LTA algorithm. The difference between manual and automatic pick times for P-wave onsets was 0:01 0:08 s overall, compared with −0:18 0:19 s using the STA/LTA picker. For S-wave onsets, the difference was −0:09 0:23 s, which is comparable to the STA/LTA picker, but our picker provided nearly twice as many picks. The pick ac-curacy was constant over the range of event magnitudes (0.7–3.7Ml). For the smaller array, the time difference between our algorithm and manual picks is 0:04 0:17 s for Pwaves and 0:07 0:08 s for Swaves.Misfit between the automatic andmanual picks is significantly lower using our procedure than using the STA/LTA algorithm.

Abstract The atmosphere plays a fundamental role in the transport of microbes across the planet but it is often neglected as a microbial habitat. Although the ocean represents two thirds of the Earth’s surface, there is little information on the atmospheric microbial load over the open ocean. Here we provide a global estimate of microbial loads and air-sea exchanges over the tropical and subtropical oceans based on the data collected along the Malaspina 2010 Circumnavigation Expedition. Total loads of airborne prokaryotes and eukaryotes were estimated at 2.2 × 10 21 and 2.1 × 10 21 cells, respectively. Overall 33–68% of these microorganisms could be traced to a marine origin, being transported thousands of kilometres before re-entering the ocean. Moreover, our results show a substantial load of terrestrial microbes transported over the oceans, with abundances declining exponentially with distance from land and indicate that islands may act as stepping stones facilitating the transoceanic transport of terrestrial microbes.

Coastal areas epitomize the notion of ‘at-risk’ territory in the context of climate change and sea level rise (SLR). Knowledge of the water level changes at the coast resulting from the mean sea level variability, tide, atmospheric surge and wave setup is critical for coastal flooding assessment. This study investigates how coastal water level can be altered by interactions between SLR, tides, storm surges, waves and flooding. The main mechanisms of interaction are identified, mainly by analyzing the shallow water equations. Based on a literature review, the orders of magnitude of these interactions are estimated in different environments. The investigated interactions exhibit a strong spatiotemporal variability. Depending on the type of environments (e.g., morphology, hydrometeorological context), they can reach several tens of centimeters (positive or negative). As a consequence, probabilistic projections of future coastal water levels and flooding should identify whether interaction processes are of leading order, and, where appropriate, projections should account for these interactions through modeling or statistical methods.