Dynamic extreme values modeling and monitoring by means of sea shores water quality biomarkers and valvometry.
Water quality can be evaluated using biomarkers such as tissular enzymatic activities of endemic species. Measurement of molluscs bivalves activity at high frequency (e.g., valvometry) during a long time period is another way to record the animal behavior and to evaluate perturbations of the water quality in real time. As the pollution affects the activity of oysters, we consider the valves opening and closing velocities to monitor the water quality assessment. We propose to model the huge volume of velocity data collected in the framework of valvometry using a new nonparametric extreme values statistical model. The objective is to estimate the tail probabilities and the extreme quantiles of the distribution of valve closing velocity. The tail of the distribution function of valve closing velocity is modeled by a Pareto distribution with parameter 𝜃 t,τ , beyond a threshold τ according to the time t of the experiment. Our modeling approach reveals the dependence between the specific activity of two enzymatic biomarkers (Glutathione-S-transferase and acetylcholinesterase) and the continuous recording of oyster valve velocity, proving the suitability of this tool for water quality assessment. Thus, valvometry allows in real-time in situ analysis of the bivalves behavior and appears as an effective early warning tool in ecological risk assessment and marine environment monitoring.
Laboratoire de Mathématiques de Bretagne Atlantique LMBA, Université Bretagne Sud, UMR CNRS 6205, 56000, Vannes, France. gilles.durrieu@univ-ubs.fr.
Gilles
G
Durrieu
Department of Mathematics, Forestry University of Hanoi, Hanoi, Vietnam.
Quang-Khoai
QK
Pham
Institut de Recherche Dupuy de Lôme IRDL, Université Bretagne Sud, FRE CNRS 3744, 56000, Vannes, France.
Anne-Sophie
AS
Foltête
Institut de Recherche Dupuy de Lôme IRDL, Université Bretagne Sud, FRE CNRS 3744, 56000, Vannes, France.
Valérie
V
Maxime
Laboratoire de Mathématiques de Bretagne Atlantique LMBA, Université Bretagne Sud, UMR CNRS 6205, 56000, Vannes, France.
Ion
I
Grama
Institut de Recherche Dupuy de Lôme IRDL, Université Bretagne Sud, FRE CNRS 3744, 56000, Vannes, France.
Véronique Le
VL
Tilly
Institut de Recherche Dupuy de Lôme IRDL, Université Bretagne Sud, FRE CNRS 3744, 56000, Vannes, France.
Hélène
H
Duval
Laboratoire de Mathématiques de Bretagne Atlantique LMBA, Université Bretagne Sud, UMR CNRS 6205, 56000, Vannes, France.
Jean-Marie
JM
Tricot
Institut de Recherche Dupuy de Lôme IRDL, Université Bretagne Sud, FRE CNRS 3744, 56000, Vannes, France.
Chiraz Ben
CB
Naceur
Institut de Recherche Dupuy de Lôme IRDL, Université Bretagne Sud, FRE CNRS 3744, 56000, Vannes, France.
Olivier
O
Sire
D000110:Acetylcholinesterase / Q000378:metabolism; D000818:Animals; D015415:Biomarkers / Q000032:analysis*; D049872:Bivalvia; D004784:Environmental Monitoring / Q000379:methods*; D010125:Ostreidae; D060753:Water Quality
D015415:Biomarkers; D000110:Acetylcholinesterase
Acetylcholinesterase (AChE); Crassostrea gigas; Extreme conditional quantile; Glutathione-S-transferase (GST); Marine environment biomonitoring; Nonparametric estimation; Valvometry