David Nerini

Analysis of oxygen rate time series in a strongly polluted lagoon using a regression tree method

Abstract This article presents results on daily forecasts of dissolved oxygen rates in a lagoon, the ‘Etang de Berre’, situated close to the French Mediterranean sea coast and submitted to particular meteorological conditions and freshwater inputs. To provide estimates of the response variable y (dissolved oxygen), a set of jointed decision rules is constructed by successive binary splitting of the predictor space composed of wind speed and freshwater flow data. The prediction model is displayed in the shape of a binary decision tree. We propose a transfer procedure in order to improve the prediction error of the tree model. Results obtained on the ‘Etang de Berre’ data set allow to describe and precise the effects of the environmental variables on the dissolved oxygen dynamics. The transfer procedure applied after the tree building process gives gains of prediction accuracy of about 17%.

Effects of Hydrostatic Pressure on Growth and Luminescence of a Moderately-Piezophilic Luminous Bacteria Photobacterium phosphoreum ANT-2200

Bacterial bioluminescence is commonly found in the deep sea and depends on environmental conditions. Photobacterium phosphoreum ANT-2200 has been isolated from the NW Mediterranean Sea at 2200-m depth (in situ temperature of 13°C) close to the ANTARES neutrino telescope. The effects of hydrostatic pressure on its growth and luminescence have been investigated under controlled laboratory conditions, using a specifically developed high-pressure bioluminescence system. The growth rate and the maximum population density of the strain were determined at different temperatures (from 4 to 37°C) and pressures (from 0.1 to 40 MPa), using the logistic model to define these two growth parameters. Indeed, using the growth rate only, no optimal temperature and pressure could be determined. However, when both growth rate and maximum population density were jointly taken into account, a cross coefficient was calculated. By this way, the optimum growth conditions for P. phosphoreum ANT-2200 were found to be 30°C and, 10 MPa defining this strain as mesophile and moderately piezophile. Moreover, the ratio of unsaturated vs. saturated cellular fatty acids was found higher at 22 MPa, in agreement with previously described piezophile strains. P. phosphoreum ANT-2200 also appeared to respond to high pressure by forming cell aggregates. Its maximum population density was 1.2 times higher, with a similar growth rate, than at 0.1 MPa. Strain ANT-2200 grown at 22 MPa produced 3 times more bioluminescence. The proposed approach, mimicking, as close as possible, the in situ conditions, could help studying deep-sea bacterial bioluminescence and validating hypotheses concerning its role into the carbon cycle in the deep ocean.

Consequence of a sudden wind event on the dynamics of a coastal phytoplankton community: an insight into specific population growth rates using a single cell high frequency approach

Phytoplankton is a key component in marine ecosystems. It is responsible for most of the marine primary production, particularly in eutrophic lagoons, where it frequently blooms. Because they are very sensitive to their environment, the dynamics of these microbial communities has to be observed over different time scales, however, assessment of short term variability is often out of reach of traditional monitoring methods. To overcome these limitations, we set up a Cytosense automated flow cytometer (Cytobuoy b.v.), designed for high frequency monitoring of phytoplankton composition, abundance, cell size, and pigment content, in one of the largest Mediterranean lagoons, the Berre lagoon (South-Eastern France). During October 2011, it recorded the cell optical properties of 12 groups of pico-, nano-, and microphytoplankton. Daily variations in the cluster optical properties were consistent with individual changes observed using microscopic imaging, during the cell cycle. We therefore used an adaptation of the size-structured matrix population model, developed by Sosik et al. (2003) to process the single cell analysis of the clusters and estimate the division rates of 2 dinoflagellate populations before, during, and after a strong wind event. The increase in the estimated in situ daily cluster growth rates suggest that physiological changes in the cells can prevail over the response of abundance.

Highly contrasted responses of Mediterranean octocorals to climate change along a depth gradient

Climate change has a strong impact on marine ecosystems, including temperate species. Analysing the diversity of thermotolerance levels within species along with their genetic structure enables a better understanding of their potential response to climate change. We performed this integrative study on the Mediterranean octocoral Eunicella cavolini, with samples from different depths and by means of a common garden experiment. This species does not host photosynthetic Symbiodinium, enabling us to focus on the cnidarian response. We compared the thermotolerance of individuals from 20 m and 40 m depths from the same site and with replicates from the same colony. On the basis of an innovative statistical analysis of necrosis kinetics and risk, we demonstrated the occurrence of a very different response between depths at this local scale, with lower thermotolerance of deep individuals. Strongly thermotolerant individuals were observed at 20 m with necrosis appearing at higher temperatures than observed in situ. On the basis of nine microsatellite loci, we showed that these marked thermotolerance differences occur within a single population. This suggests the importance of acclimatization processes in adaptation to these different depths. In addition, differences between replicates demonstrated the occurrence of a variability of response between fragments from the same colony with the possibility of an interaction with a tank effect. Our results provide a basis for studying adaptation and acclimatization in Mediterranean octocorals in a heterogeneous environment.

Scaling up the predator functional response in heterogeneous environment: When Holling type III can emerge?

Accurate parametrization of functional terms in model equations is of great importance for reproducing the dynamics of real food webs. Constructing models over large spatial and temporal scales using mathematical expressions obtained based on microcosm experiments can be erroneous. Here, using a generic spatial predator-prey model, we show that scaling up the microscale functional response of a predator can result in qualitative alterations of functional response on macroscales. In particular, a global functional response of sigmoid type (Holling type III) can emerge as a result of non-linear averaging of non-sigmoid local responses (Holling type I or II). We demonstrate that alteration between the local and the global response in the model is a result of the interplay between density-dependent dispersal of the predator across the habitat and heterogeneity of the environment. Using the method of aggregation of variables, we analytically derive the mathematical formulation of the global functional response as a function of the total amount of prey in the system, and reveal the key parameters which control the emergence of a Holling type III global response. We argue that this mechanism by which a global Holling type III emerges from a local Holling type II response has not been reported in the literature yet: in particular, Holling type III can emerge in the case of a fixed gradient of resource distribution across the habitat, which would be impossible in priorly suggested mechanisms. As a case study, we consider the interaction between phytoplankton and zooplankton grazers in the water column; and we show that the emergence of a Holling type III global response can allow for the efficient top-down regulation of primary producers and stabilization of planktonic ecosystems under eutrophic conditions.

Towards a simplification of models using regression trees.

Over-parametrization in modelling is a well-known issue that makes it hard to identify which part of a model is responsible for a given behaviour. In line with that ascertainment, this work presents the outline of an empirical method to simplify models by decreasing the number of parameters. By using regression trees to classify outputs according to related input parameters, the method provides the modeller with an objective tool to reduce the range of the used parameters and, under certain conditions, to establish relations between them. Thereby, the complexity of the model is reduced on the basis of mathematical arguments. As an example, a dynamic energy budget-based model of a mesopelagic bacterial ecosystem is simplified using the presented method. The main benefits of such a method are thus highlighted: (i) more robust parameter estimations; (ii) less complex formulations; and (iii) fewer modelling assumptions. To conclude, the difficulties encountered are discussed, and several solutions are proposed to deal with them.

Une méthode statistique de détermination de séquences caractéristiques dans une série temporelle de plusieurs variables. Application à la physico-chimie des eaux de l'étang de Berre

Abstract Situated close to the French Mediterranean coast, the Berre lagoon is a brackish water lagoon highly disturbed by freshwater inputs coming from an hydroelectric power station. Since 1996, in the framework of an ecological program, a self sampling station hourly samples physicochemical variables such as temperature salinity and dissolved oxygen rates. This paper presents a statistical method that allows to summarize the dynamics of the water column with a sequence of daily typical states. This method takes into account the heterogeneity of the variables and keeps their temporal structure. Thus, the typical states are described by the hourly evolution of the distributions of each variable. Most of the time (74% of the observations), the water column is in a stratified state. The water column rocks to a mixed state under the effects of wind (19% of the observations). Transient days between these two states can be isolated in 7% of cases. Results show that the long-term system dynamics is not correlated with the daily environmental variations.

Application of ordinal correspondence analysis for submerged aquatic vegetation monitoring

The European Water Framework states that macrophyte communities (seaweeds and seagrass) are key indicators of the ecological health of lagoons. Furthermore, the restoration of these communities, especially the Zostera meadows, is one of the main objectives of the Berre lagoon restoration plan. Consequently, a monitoring programme of the main macrophyte species still present in the lagoon was initiated in 1996. This monitoring resulted in a sequence of 11 spatially structured annual tables consisting of the observed density of these species. These tables are processed in this study. First, we specify the principles of Behs ordinal correspondence analysis (OCA), designed for ordered row/column categories, and compare this method to classical correspondence analysis (CA). Then, we show that OCA is straightforwardly adaptable for processing a sequence of ordered contingency tables like ours. Both OCA and CA are afterwards used to reveal and test the main patterns of spatio-temporal changes of two macrophyte species in the Berre lagoon: Ulva and Zostera. The results we obtained are compared and discussed.

A Linear Decomposition of the Southern Ocean Thermohaline Structure

The thermohaline structure of the Southern Ocean is deeply influenced by the presence of the Antarctic Circumpolar Current (ACC), where water masses of the World Ocean are advected, transformed, and redistributed to the other basins. It remains a challenge to describe and visualize the complex 3D pattern of this circulation and its associated tracer distribution. Here, a simple framework is presented to analyze the Southern Ocean thermohaline structure. A functional principal component analysis (PCA) is applied to temperature θ and salinity S profiles to determine the main spatial patterns of their variations. Using the Southern Ocean State Estimate (SOSE), this study determines the vertical modes describing the Southern Ocean thermohaline structure between 5 and 2000 m. The first two modes explain 92% of the combined θ–S variance, thus providing a surprisingly good approximation of the thermohaline properties in the Southern Ocean. The first mode (72% of total variance) accurately describes the north–south property gradients. The second mode (20%) mostly describes salinity at 500 m in the region of Antarctic Intermediate Water formation. These two modes present circumpolar patterns that can be closely related with standard frontal definitions. By projecting any given hydrographic profile onto the SOSE-based modes, it is possible to determine its position relative to the fronts. The projection is successfully applied on the hydrographic profiles of the WOCE SR3 section. The Southern Ocean thermohaline decomposition provides an objective way to define water mass boundaries and their spatial variability and has useful application for comparing model output with observations.

Is structural sensitivity a problem of oversimplified biological models? Insights from nested Dynamic Energy Budget models

Many current issues in ecology require predictions made by mathematical models, which are built on somewhat arbitrary choices. Their consequences are quantified by sensitivity analysis to quantify how changes in model parameters propagate into an uncertainty in model predictions. An extension called structural sensitivity analysis deals with changes in the mathematical description of complex processes like predation. Such processes are described at the population scale by a specific mathematical function taken among similar ones, a choice that can strongly drive model predictions. However, it has only been studied in simple theoretical models. Here, we ask whether structural sensitivity is a problem of oversimplified models. We found in predator-prey models describing chemostat experiments that these models are less structurally sensitive to the choice of a specific functional response if they include mass balance resource dynamics and individual maintenance. Neglecting these processes in an ecological model (for instance by using the well-known logistic growth equation) is not only an inappropriate description of the ecological system, but also a source of more uncertain predictions.