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Auteur (up) Ben Othman, H.; Leboulanger, C.; Le Floc'h, E.; Mabrouk, H.H.; Hlaili, A.S. url  doi
openurl 
  Titre Toxicity of benz(a)anthracene and fluoranthene to marine phytoplankton in culture: Does cell size really matter? Type Article scientifique
  Année 2012 Publication Revue Abrégée J. Hazard. Mater.  
  Volume 243 Numéro Pages 204-211  
  Mots-Clés Benz(a)anthracene; Ecotoxicity; Fluoranthene; Size-sensitivity relationship; aquatic organisms; biodegradation; chlorophyll; fluorescence; food-web; fresh-water phytoplankton; in-vitro; organic pollutants; pahs; phytoplankton; polycyclic aromatic-hydrocarbons; surface sediments  
  Résumé The toxicity of benz(a)anthracene and fluoranthene (polycyclic aromatic hydrocarbons, PAHs) was evaluated on seven species of marine algae in culture belonging to pico-, nano-, and microphytoplankton, exposed to increasing concentrations of up to 2 mg L-1. The short-term (24 h) toxicity was assessed using chlorophyll a fluorescence transients, linked to photosynthetic parameters. The maximum quantum yield Fv/Fm was lower at the highest concentrations tested and the toxicity thresholds were species-dependent. For acute effects, fluoranthene was more toxic than benz(a)anthracene, with LOECs of 50.6 and 186 mu g L-1, respectively. After 72 h exposure, there was a dose-dependent decrease in cell density, fluoranthene being more toxic than benz(a)anthracene. The population endpoint at 72 h was affected to a greater extent than the photosynthetic endpoint at 24 h. EC50 was evaluated using the Hill model, and species sensitivity was negatively correlated to cell biovolume. The largest species tested, the dinoflagellate Alexandrium catenella, was almost insensitive to either PAH. The population endpoint EC50s for fluoranthene varied from 54 mu g L-1 for the picophytoplankton Picochlorum sp. to 418 mu g L-1 for the larger diatom Chaetoceros muelleri. The size/sensitivity relationship is proposed as a useful model when there is a lack of ecotoxicological data on hazardous chemicals, especially in marine microorganisms. (C) 2012 Elsevier B.V. All rights reserved.  
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  ISSN 0304-3894 ISBN Médium  
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  Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 915  
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Auteur (up) Joo, R.; Bertrand, S.; Chaigneau, A.; Niquen, M. url  doi
openurl 
  Titre Optimization of an artificial neural network for identifying fishing set positions from VMS data : an example from the Peruvian anchovy purse seine fishery Type Article scientifique
  Année 2011 Publication Revue Abrégée Ecological Modelling  
  Volume 222 Numéro Pages 1048-1059  
  Mots-Clés analysis; anchovy; Artificial; fishery; Fishing; locations; Monitoring; networks; neural; purse; seine; Sensitivity; set; System; Vessel  
  Résumé The spatial behavior of numerous fishing fleets is nowadays well documented thanks to satellite Vessel Monitoring Systems (VMS). Vessel positions are recorded on a frequent and regular basis which opens promising perspectives for improving fishing effort estimation and management. However, no specific information is provided on whether the vessel is fishing or not. To answer that question, existing works on VMS data usually apply simple criteria (e.g. threshold on speed). Those simple criteria generally focus in detecting true positives (a true fishing set detected as a fishing set); conversely, estimation errors are given no attention. For our case study, the Peruvian anchovy fishery, those criteria overestimate the total number of fishing sets by 182%. To overcome this problem an artificial neural network (ANN) approach is presented here. In order to set both the optimal parameterization and use “rules” for this ANN, we perform an extensive sensitivity analysis on the optimization of (1) the internal structure and training algorithm of the ANN and (2) the “rules” used for choosing both the relative size and the composition of the databases (DBs) used for training and inferring with the ANN. The “optimized” ANN greatly improves the estimates of the number and location of fishing events. For our case study, ANN reduces the total estimation error on the number of fishing sets to 1% (in average) and obtains 76% of true positives. This spatially explicit information on effort, provided with error estimation, should greatly reduce misleading interpretations of catch per unit effort and thus significantly improve the adaptive management of fisheries. While fitted on Peruvian anchovy fishery data, this type of neural network approach has wider potential and could be implemented in any fishery relying on both VMS and at-sea observer data. In order to increase the accuracy of the ANN results, we also suggest some criteria for improving sampling design by at-sea observers and VMS data.  
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Auteur (up) Legras, G.; Loiseau, N.; Gaertner, J.-C.; Poggiale, J.-C.; Gaertner-Mazouni, N. doi  openurl
  Titre Assessing functional diversity: the influence of the number of the functional traits Type Article scientifique
  Année 2020 Publication Revue Abrégée Theor. Ecol.  
  Volume 13 Numéro 1 Pages 117-126  
  Mots-Clés biodiversity; Dissimilarity metric; framework; Functional diversity; Functional traits; global hotspots; Index sensitivity; indexes; mismatch; redundancy; reveals; species richness; Trend analysis; vulnerability  
  Résumé The impact of the variation of the number of functional traits on functional diversity assessment is still poorly known. Although the covariation between these two parameters may be desirable in some situations (e.g. if adding functional traits provides relevant new functional information), it may also result from mathematical artefacts and lead to misinterpretation of the results obtained. Here, we have tested the behaviour of a set of nine indices widely used for assessing the three main components of functional diversity (i.e. functional richness, evenness and divergence), according to the variation in the number of functional traits. We found that the number of functional traits may strongly impact the values of most of the indices considered, whatever the functional information they contain. The FRic, TOP and n-hypervolume indices that have been developed to characterize the functional richness component appeared to be highly sensitive to the variation in the number of traits considered. Regarding functional divergence, most of the indices considered (i.e. Q, FDis and FSpe) also showed a high degree of sensitivity to the number of traits considered. In contrast, we found that indices used to compute functional evenness (FEve and Ru), as well as one of the indices related to functional divergence (FDiv), are weakly influenced by the variation in the number of traits. All these results suggest that interpretation of most of the functional diversity indices considered cannot only be based on their values as they are, but requires taking into account the way in which they have been computed.  
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  ISSN 1874-1738 ISBN Médium  
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  Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 2750  
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Auteur (up) Loiseau, N.; Gaertner, J.-C.; Kulbicki, M.; Mérigot, B.; Legras, G.; Taquet, M.; Gaertner-Mazouni, N. url  doi
openurl 
  Titre Assessing the multicomponent aspect of coral fish diversity: The impact of sampling unit dimensions Type Article scientifique
  Année 2016 Publication Revue Abrégée Ecological Indicators  
  Volume 60 Numéro Pages 815-823  
  Mots-Clés Evenness; Functional diversity; Index sensitivity; Sampling unit dimensions; species richness; Visual censuses  
  Résumé The influence of variations in sampling unit dimensions on the assessment of fish species structuring has been widely documented. However, this issue has been restricted to a very limited range of community and population indices (mainly species richness and density). Here, we have investigated this issue through the analysis of 13 diversity indices related to 3 diversity components (number of species, evenness and functional diversity). We analyzed a large set of 257 standardized underwater visual census (UVC) transects dealing with 254 coral fish species. The sensitivity of the indices to the variation in sampling unit dimensions was studied by comparing a range of 55 couples of transect length and width representing 34 sampling surfaces. We found that the extent and profile of the sensitivity to changes in transect dimensions strongly varied both from one index to another and from one dimension to another (length and width). The most sensitive indices were more strongly impacted by variation in length than width. We also showed that for a fixed transect surface, the couple of chosen length and width may alter the assessment of indices related to each of the three main diversity components studied. Some widely used diversity indices, such as species richness and Shannon index, appeared to be very sensitive to changes in transect length and width. In contrast, while still very little used in coral fish studies, two functional diversity indices (FDiv, FEve), and to a lesser extent an evenness index (Berger–Parker), remained robust in the face of change in sampling dimensions. By showing that the variation in sampling dimensions (length, width and surface) may impact diversity indices in a contrasting manner, we stress the need to take into account the sensitivity of the indices to this criterion in the process of selection of the indices to be analyzed in diversity studies. Finally, we found that 30 m long*5 m wide transects might be a suitable compromise size for assessing the patterns of each of the three major complementary components of coral fish diversity.  
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  ISSN 1470-160x ISBN Médium  
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  Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 1320  
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Auteur (up) Meynard, C.N.; Kaplan, D. url  doi
openurl 
  Titre Using virtual species to study species distributions and model performance Type Article scientifique
  Année 2013 Publication Revue Abrégée Journal of Biogeography  
  Volume 40 Numéro 1 Pages 1-8  
  Mots-Clés Auc; predictive ecology; presence-absence; prevalence; Sensitivity; simulations; specificity; threshold; virtual species  
  Résumé Simulations of virtual species (i.e. species for which the environmentoccupancy relationships are known) are increasingly being used to test the effects of different aspects of modelling and sampling strategy on performance of species distribution models (SDMs). Here we discuss an important step of the simulation process: the translation of simulated probabilities of occurrence into patterns of presence and absence. Often a threshold strategy is used to generate virtual occurrences, where presence always occurs above a specific simulated probability value and never below. This procedure effectively translates any shape of simulated species response into a threshold one and eliminates any stochasticity from the species occupancy pattern. We argue that a probabilistic approach should be preferred instead because the threshold response can be treated as a particular case within this framework. This also allows one to address questions relating to the shape of functional responses and avoids convergence issues with some of the most common SDMs. Furthermore, threshold-based virtual species studies generate over-optimistic performance measures that lack classification error or incorporate error from a mixture of sampling and modelling choices. Incorrect use of a threshold approach can have significant consequences for the practising biogeographer. For example, low model performance may be interpreted as due to sample bias or poor model choice, rather than being related to fundamental biological responses to environmental gradients. We exemplify these shortcomings with a case study where we compare results from threshold and probabilistic simulation approaches.  
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