Nucleation in sessile saline microdroplets: induction time measurement via deliquescence-recrystallization cycling.

Induction time, a measure of how long one will wait for nucleation to occur, is an important parameter in quantifying nucleation kinetics and its underlying mechanisms. Due to the stochastic nature of nucleation, efficient methods for measuring large numbers of independent induction times are needed to ensure statistical reproducibility. In this work, we present a novel approach for measuring and analyzing induction times in sessile arrays of microdroplets via deliquescence/recrystallization cycling. With the help of a recently developed image analysis protocol, we show that the interfering diffusion-mediated interactions between microdroplets can be eliminated by controlling the relative humidity, thereby ensuring independent nucleation events. Moreover, possible influence of heterogeneities, impurities, and memory effect appear negligible as suggested by our 2-cycle experiment. Further statistical analysis (k-sample Anderson-Darling test) reveals that upon identifying possible outliers, the dimensionless induction times obtained from different datasets (microdroplet lines) obey the same distribution and thus can be pooled together to form a much larger dataset. The pooled dataset showed an excellent fit with the Weibull function, giving a mean supersaturation at nucleation of 1.61 and 1.85 for the 60 pL and 4 pL microdroplets respectively. This confirms the effect of confinement where smaller systems require higher supersaturations to nucleate. Both the experimental method and the data-treatment procedure presented herein offer promising routes in the study of fundamental aspects of nucleation kinetics, particularly confinement effects, and are adaptable to other salts, pharmaceuticals, or biological crystals of interest.

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.

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.

A new Sargassum drift model derived from features tracking in MODIS images.

Massive Sargassum stranding events affect erratically numerous countries from the Gulf of Guinea to the Gulf of Mexico. Forecasting transport and stranding of Sargassum aggregates require progress in detection and drift modelling. Here we evaluate the role of currents and wind, i.e. windage, on Sargassum drift. Sargassum drift is computed from automatic tracking using MODIS 1 km Sargassum detection dataset, and compared to reference surface current and wind estimates from collocated drifters and altimetric products. First, we confirm the strong total wind effect of ≈3 % (≈2 % of pure windage), but also show the existence of a deflection angle of ≈10° between Sargassum drift and wind directions. Second, our results suggest reducing the role of currents on drift to 80 % of its velocity, likely because of Sargassum resistance to flow. These results should significantly improve our understanding of the drivers of Sargassum dynamics and the forecast of stranding events.

Where to live? Landfast sea ice shapes emperor penguin habitat around Antarctica.

Predicting species survival in the face of climate change requires understanding the drivers that influence their distribution. Emperor penguins (Aptenodytes forsteri) incubate and rear chicks on landfast sea ice, whose extent, dynamics, and quality are expected to vary substantially due to climate change. Until recently, this species' continent-wide observations were scarce, and knowledge on their distribution and habitat limited. Advances in satellite imagery now allow their observation and characterization of habitats across Antarctica at high resolution. Using circumpolar high-resolution satellite images, unique fast ice metrics, and geographic and biological factors, we identified diverse penguin habitats across the continent, with no significant difference between areas with penguins or not. There is a clear geographic partitioning of colonies with respect to their defining habitat characteristics, indicating possible behavioral plasticity among different metapopulations. This coincides with geographic structures found in previous genetic studies. Given projections of quasi-extinction for this species in 2100, this study provides essential information for conservation measures.

Beneath the Antarctic sea-ice: Fine-scale analysis of Weddell seal (Leptonychotes weddellii) behavior and predator-prey interactions, using micro-sonar data in Terre Adélie.

Lactation is the most energy-demanding event in mammals' reproduction. In pinnipeds, females are the only food providers to the young and have developed numerous behavioral and physiological lactation strategies, from capital-breeding to income-breeding. Lactating females' fine-scale foraging strategy, and precise understanding of how females supplement their pup's needs as well as their own are important to understand the species' ecology and energetic balance. Polar pinnipeds, inhabiting extreme environments, are sensitive to climate change and variability, understanding their constraints and foraging strategy during lactation is therefore important. In 2019, three sonar tags were deployed on lactating Weddell seals in Terre Adélie (East Antarctica) for 7 days, to study fine-scale predator-prey interactions. Feeding activity was mostly benthic, reduced, central-placed, and spatially limited. Females spent most of their time hauled-out. A total of 331 prey capture attempts (PrCAs) were recorded using triaxial acceleration data, with 125 prey identified on echograms (5 cm, acoustic size). All PrCAs occurred on the seafloor, shallower than usual records (mean depth of 88 m, vs 280 m after their molt). We also found that they only fed in three of the five identified dive shapes, during the ascent or throughout the dive. Half of the prey were reactive to the seal's approach, either leaving the seafloor, or escaping just above the seafloor, suggesting that the seals hunt by chasing them from the seabed. Seals continuously scanned the area during the approach phase, evoking opportunistic foraging. Our results provide additional evidence that Weddell seal forage during lactation, displaying a mix of capital-breeding and income-breeding strategies during this period of physiological stress. This work sheds light on previously unexplored aspects of their foraging behavior, such as shallow water environments, targeting benthic prey, generally focusing on single prey rather than schools, and evidence of visual scanning through observed head movements.

Functional analysis and classification of phytoplankton based on data from an automated flow cytometer.

Analytical flow cytometry (FCM) is well suited for the analysis of phytoplankton communities in fresh and sea waters. The measurement of light scatter and autofluorescence properties of particles by FCM provides optical fingerprints, which enables different phytoplankton groups to be separated. A submersible version of the CytoSense flow cytometer (the CytoSub) has been designed for in situ autonomous sampling and analysis, making it possible to monitor phytoplankton at a short temporal scale and obtain accurate information about its dynamics. For data analysis, a manual clustering is usually performed a posteriori: data are displayed on histograms and scatterplots, and group discrimination is made by drawing and combining regions (gating). The purpose of this study is to provide greater objectivity in the data analysis by applying a nonmanual and consistent method to automatically discriminate clusters of particles. In other words, we seek for partitioning methods based on the optical fingerprints of each particle. As the CytoSense is able to record the full pulse shape for each variable, it quickly generates a large and complex dataset to analyze. The shape, length, and area of each curve were chosen as descriptors for the analysis. To test the developed method, numerical experiments were performed on simulated curves. Then, the method was applied and validated on phytoplankton cultures data. Promising results have been obtained with a mixture of various species whose optical fingerprints overlapped considerably and could not be accurately separated using manual gating.

Structural sensitivity of biological models revisited.

Enhancing the predictive power of models in biology is a challenging issue. Among the major difficulties impeding model development and implementation are the sensitivity of outcomes to variations in model parameters, the problem of choosing of particular expressions for the parametrization of functional relations, and difficulties in validating models using laboratory data and/or field observations. In this paper, we revisit the phenomenon which is referred to as structural sensitivity of a model. Structural sensitivity arises as a result of the interplay between sensitivity of model outcomes to variations in parameters and sensitivity to the choice of model functions, and this can be somewhat of a bottleneck in improving the models predictive power. We provide a rigorous definition of structural sensitivity and we show how we can quantify the degree of sensitivity of a model based on the Hausdorff distance concept. We propose a simple semi-analytical test of structural sensitivity in an ODE modeling framework. Furthermore, we emphasize the importance of directly linking the variability of field/experimental data and model predictions, and we demonstrate a way of assessing the robustness of modeling predictions with respect to data sampling variability. As an insightful illustrative example, we test our sensitivity analysis methods on a chemostat predator-prey model, where we use laboratory data on the feeding of protozoa to parameterize the predator functional response.

Organic additive release from plastic to seawater is lower under deep-sea conditions.

Plastic garbage patches at the ocean surface are symptomatic of a wider pollution affecting the whole marine environment. Sinking of plastic debris increasingly appears to be an important process in the global fate of plastic in the ocean. However, there is insufficient knowledge about the processes affecting plastic distributions and degradation and how this influences the release of additives under varying environmental conditions, especially in deep-sea environments. Here we show that in abiotic conditions increasing hydrostatic pressure inhibits the leaching of the heaviest organic additives such as tris(2-ethylhexyl) phosphate and diisononyl phthalate from polyethylene and polyvinylchloride materials, whereas deep-sea and surface marine prokaryotes promote the release of all targeted additives (phthalates, bisphenols, organophosphate esters). This study provides empirical evidences for more efficient additive release at the ocean surface than in deep seawater, where the major plastic burden is supposed to transit through before reaching the sediment compartment.

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.

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.

Effects of spilled oil on bacterial communities of mediterranean coastal anoxic sediments chronically subjected to oil hydrocarbon contamination.

The effects of spilled oil on sedimentary bacterial communities were examined in situ at 20 m water depth in a Mediterranean coastal area. Sediment collected at an experimental site chronically subjected to hydrocarbon inputs was reworked into PVC cores with or without a massive addition of crude Arabian light oil ( approximately 20 g kg(-1) dry weight). Cores were reinserted into the sediment and incubated in situ at the sampling site (20 m water depth) for 135 and 503 days. The massive oil contamination induced significant shifts in the structure of the indigenous bacterial communities as shown by ribosomal intergenic spacer analysis (RISA). The vertical heterogeneity of the bacterial communities within the sediment was more pronounced in the oiled sediments particularly after 503 days of incubation. Response to oil of the deeper depth communities (8-10 cm) was slower than that of superficial depth communities (0-1 and 2-4 cm). Analysis of the oil composition by gas chromatography revealed a typical microbial alteration of n-alkanes during the experiment. Predominant RISA bands in oiled sediments were affiliated to hydrocarbonoclastic bacteria sequences. In particular, a 395-bp RISA band, which was the dominant band in all the oiled sediments for both incubation times, was closely related to hydrocarbonoclastic sulfate-reducing bacteria (SRB). These bacteria may have contributed to the main fingerprint changes and to the observed biodegradation of n-alkanes. This study provides useful information on bacterial dynamics in anoxic contaminated infralittoral sediments and highlights the need to assess more precisely the contribution of SRB to bioremediation in oil anoxic contaminated areas.