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International audience; Quantitative imaging instruments produce a large number of images of plankton and marine snow, acquired in a controlled manner, from which the visual characteristics of individual objects and their in situ concentrations can be computed. To exploit this wealth of information, machine learning is necessary to automate tasks such as taxonomic classification. Through a review of the literature, we highlight the progress of those machine classifiers and what they can and still cannot be trusted for. Several examples showcase how the combination of quantitative imaging with machine learning has brought insights on pelagic ecology. They also highlight what is still missing and how images could be exploited further through trait-based approaches. In the future, we suggest deeper interactions with the computer sciences community, the adoption of data standards, and the more systematic sharing of databases to build a global community of pelagic image providers and users. Expected final online publication date for the Annual Review of Marine Science, Volume 14 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

This paper investigates the potential of Geographical Indications to enhance the environmental sustainability of bivalve aquaculture, with a focus on the Protected Designation of Origin (PDO) granted to the bouchot mussel of the bay of Mont Saint-Michel (BMSM). First, a retrospective analysis of the PDO application process was carried out to provide insight into specific environmental and regulatory issues facing mussel farming in the BMSM (e.g. common resource management). Second, further assessment relied on a comparative analysis with other public labelling strategies developed by mussel farmers, notably emerging organic certification. This involved setting up an ad-hoc analysis grid to evaluate different dimensions of sustainability, namely economic, environmental and governance. The discussion then addresses the potential of PDO to promote sustainable mussel farming with respect to the current trends in food/mussel labelling in the market and to the increasing demand for environmental preservation in marine and coastal areas. It also emphasises the overlap between different EU labelling schemes that questions their consistency and legibility, particularly for bivalve aquaculture. In conclusion, the system of quality linked to origin has provided an appropriate framework for supporting the implementation of sustainable bouchot mussel farming in the BMSM, thanks to the relevance and inclusiveness of the PDO labelling process and institutional support. Next, to strengthen the legitimacy of the PDO to guarantee the environmental sustainability of farming methods and increase protection on the market, more adaptive management of the PDO label is recommended. International audience

Speckle noise is inherent to radar measurements. For applications which need both a high temporal and high spatial resolution, a classical method for the reduction of the speckle noise by filtering the backscattered signal may not be sufficient. In particular, when radar observations are used to estimate ocean wave spectra from relative fluctuations of the radar signal within a given footprint, a method must be implemented to correct for the speckle effect in the Fourier domain (i.e., density spectrum). A theoretical background to model the speckle density spectrum for a radar with near-nadir incidences was proposed by Jackson in 1981 but it is based on a stationary sea surface assumption and ignores the variation of the main factor in the four-frequency moment near the origin. In this article, we revisit this theoretical background to extend this model to a time-varying sea surface and alleviate some assumptions on the Fresnel phase formulation. The results from the model applied in the configuration of an airborne system indicate that not only the displacement of the radar but also the dynamic properties of the sea surfaces have a significant effect on the speckle noise spectrum in certain directions of observations. The effects depend on the radar look direction in azimuth, and on sea surface conditions (wind speed, wind direction with respect to the aircraft route, surface wave spectrum). This new model is validated against observations of the airborne near-nadir incidence scatterometer--Ku-band Radar for Observation of Surfaces (KuROS). We show in particular that the errors between the experimental estimation of the omni-directional speckle noise spectrum from KuROS and the prediction by our model are below 10%.

Estuaries -- one of the most vulnerable ecosystems globally -- face anthropogenic threats, including biodiversity loss and the collapse of sustainable fisheries. Determining the factors contributing to the maintenance of estuarine biodiversity, especially that of fish, is vital for promoting estuarine conservation and sustainability. We used environmental DNA metabarcoding analysis to determine fish species composition in 22 estuaries around Japan and measured watershed-scale land-use factors (e.g., population size, urban area percentage, and forest area percentage). We sought to test the hypothesis that the richness of the most vulnerable estuarine fish species (i.e., registered by the Japanese Ministry of the Environment in the national species red-list) is determined by watershed-scale land-use factors. The richness of such species was greater where forest cover was highest; thus, forest cover contributes to their conservation. The proportion of agriculture cover was associated with low species richness of red-listed fishes (redundancy analysis, adjusted R² = 43.9% of total variance, df = 5, F = 5.3843, p = 0.0001). The number of red-listed species increased from 3 to 12 along a watershed land-use gradient ranging from a high proportion of agriculture cover to a large proportion of forest cover. Furthermore, the results showed that throughout Japan all the examined watersheds that were covered by >74.8% forest had more than the average (6.7 species per site) richness of red-listed fish species. This result can be attributed to the already high average forest cover in Japan of 67.2%. Our results demonstrate how the land use of watersheds can affect the coastal sea environment and its biodiversity and suggest that proper forest management in conjunction with land-use management may be of prime importance for threatened fish species and coastal ecosystems in general. 森林を守ることが海の生物多様性を守ることにつながる. 京都大学プレスリリース. 2021-10-26.

The accuracy of sea surface parameters retrieved from altimeter missions is predominantly governed by the choice of the so-called ``retracking'' algorithm, i.e., the model and inversion method implemented to obtain the surface parameters from the backscattered waveform. For continuity reasons, the choice of space agencies is usually to apply the same retracker from one satellite mission to the other to ensure long-time homogeneous series. In this article, taking the opportunity of a new configuration of the nadir pointing measurements onboard the recently launched China France Oceanography Satellite (CFOSAT) with the Surface Waves Investigation and Monitoring (SWIM) instrument (Hauser et al., 2020), the retracking method was upgraded, by implementing a novel algorithm, called ``Adaptive'' retracker. It combines the improvements brought by Poisson et al., (2018) for the estimation of surface parameters from peaked waveforms over sea ice, improvements in the way the instrumental characteristics are considered in the model (mispointing, point target response) and a more accurate consideration of speckle statistics. In this article, we first show from simulations carried out in the instrumental configuration of SWIM that the Adaptive algorithm has better accuracy and performance than the classical MLE4 algorithm. Then, the geophysical parameters obtained with real data from SWIM are analyzed with comparisons to reference data sets (model and products from altimeters). We show that this new algorithm has several benefits with respect to the classical MLE4 method: no need of lookup tables to correct biases, significant noise reduction on all geophysical variables especially the significant wave height, and performance of inversion over a large set of echo shapes, resulting from standard oceanic scenes as well as highly specular conditions such as over bloom or sea ice.

Benthic exchanges of oxygen and nutrient at the sediment-water interface were investigated under light and dark conditions at 5 selected sites in a sub-tropical atoll. Mean oxygen fluxes were - 1316.5 ± 242.0 μmol m−2 h−1 and mean effluxes of oxygen under light conditions were 2231.7 ± 626.4 μmol m−2 h−1, presumably due to microphytobenthos present at the sediment-water interface. The consequences of this high related productivity was a systematic consumption of nutrients (DIN, PO4 and Si(OH)4) during almost all light incubations, contrasting with the effluxes of nutrients during dark incubations. Our results suggest that the sediments were net autotrophic and the oxygen balance in favor of microbenthic production when compared to community demand. Diurnal rates of gross benthic primary productivity were high (3423 ± 1192 μmol m−2 h−1) which emphasize the role of microphytobenthos in maintaining the oxygen reservoir in tropical lagoons. International audience

Background Glossina austeni and Glossina brevipalpis (Diptera: Glossinidae) are the sole cyclical vectors of African trypanosomes in South Africa, Eswatini and southern Mozambique. These populations represent the southernmost distribution of tsetse flies on the African continent. Accurate knowledge of infested areas is a prerequisite to develop and implement efficient and cost-effective control strategies, and distribution models may reduce large-scale, extensive entomological surveys that are time consuming and expensive. The objective was to develop a MaxEnt species distribution model and habitat suitability maps for the southern tsetse belt of South Africa, Eswatini and southern Mozambique. Methodology/Principal findings The present study used existing entomological survey data of G. austeni and G. brevipalpis to develop a MaxEnt species distribution model and habitat suitability maps. Distribution models and a checkerboard analysis indicated an overlapping presence of the two species and the most suitable habitat for both species were protected areas and the coastal strip in KwaZulu-Natal Province, South Africa and Maputo Province, Mozambique. The predicted presence extents, to a small degree, into communal farming areas adjacent to the protected areas and coastline, especially in the Matutuíne District of Mozambique. The quality of the MaxEnt model was assessed using an independent data set and indicated good performance with high predictive power (AUC > 0.80 for both species). Conclusions/Significance The models indicated that cattle density, land surface temperature and protected areas, in relation with vegetation are the main factors contributing to the distribution of the two tsetse species in the area. Changes in the climate, agricultural practices and land-use have had a significant and rapid impact on tsetse abundance in the area. The model predicted low habitat suitability in the Gaza and Inhambane Provinces of Mozambique, i.e., the area north of the Matutuíne District. This might indicate that the southern tsetse population is isolated from the main tsetse belt in the north of Mozambique. The updated distribution models will be useful for planning tsetse and trypanosomosis interventions in the area. Author summary The two tsetse species transmitting nagana in South Africa, Eswatini and southern Mozambique represent the southernmost distribution of this genus on the African continent. Distribution models were developed to support tsetse control. These models indicated that the main factors contributing to tsetse distribution in the area are the presence of host animals, variation in climate and vegetation mostly observed in protected areas, agricultural practises and land-use also had a significant and rapid impact on tsetse abundance in the area. Application of the model to areas north of the southern distribution predict a low presence of suitable habitats in the Gaza and Inhambane Provinces of Mozambique, thereby indicating that this southern population is geographically isolated from the main tsetse belt starting in the north of Mozambique.