Change-Point Method Applied to the Detection of Temporal Variations in Seafloor Bacterial Mat Coverage

The paper is aimed at a methodological development of change-point detection, applicable in identifying abrupt changes in temporal or spatial data sequences. In earlier papers we developed a method for detecting a change in the parameters of a discrete distribution, with the simultaneous estimation of the (deterministic but unknown) distribution parameters before and after the change. In this paper we not only extend this method to the case of normal distributions, but also provide a new algorithm for the iterative refining of the estimation of the change-point, based on a "cleaning" of mixed-up parts of the samples. The appropriate size of reduced part of the sample is analytically calculated for the case of normal distributions. This "cleaning" is combined with our original change-point detection method. Our new algorithm is not only validated on artificial data, but also applied to a real environmental data set collected and analysed by other authors in a seafloor observatory. Our results detecting abrupt changes of bacterial mat coverage of a seafloor area are in harmony with the biological fluctuations and changes in the abiotic environment, analysed recently by other authors using a different method. We also provide a comparison with other existing change-point detection methods: a one-dimensional version of the gradient method widely used for edge detection, and a maximum type statistical method well-known in environmental studies. Although normality conditions of our method are rather restrictive, its application potential for environmental data sets is also demonstrated.

[1]  Daniela Jarušková,et al.  Some Problems with Application of Change-Point Detection Methods to Environmental Data , 1997 .

[2]  B. Brodsky,et al.  Nonparametric Methods in Change Point Problems , 1993 .

[3]  Philip K. Hopke,et al.  Fitting statistical distributions to air quality data by the maximum likelihood method , 1982 .

[4]  R. Durrett.  Probability: Theory and Examples , 1993 .

[5]  W. A. Taylor.  Change-Point Analysis : A Powerful New Tool For Detecting Changes , 2000 .

[6]  Zhi Qiang Cheng.  Using LS-SVM Pattern Recognizer to Detect Change-Point in ARMA Process , 2012 .

[7]  Chandra A. Madramootoo,et al.  Determining the Influence of Land Use Change and Soil Heterogeneities on Discharge, Sediment and Phosphorus , 2016 .

[8]  Jorge Mateu,et al.  Methods of Assessing and Achieving Normality Applied to Environmental Data , 1997, Environmental management.

[9]  Nathan C. Healey,et al.  A Mobile Instrumented Sensor Platform for Long-Term Terrestrial Ecosystem Analysis: An Example Application in an Arctic Tundra Ecosystem , 2014 .

[10]  Marie-Josée Fortin,et al.  Boundary Detection in Altitudinal Treeline Ecotones in the Spanish Central Pyrenees , 2000 .

[11]  David R. Legates,et al.  An evaluation of procedures to estimate monthly precipitation probabilities , 1991 .

[12]  Y. B. Wah,et al.  Power comparisons of Shapiro-Wilk , Kolmogorov-Smirnov , Lilliefors and Anderson-Darling tests , 2011 .

[13]  G. Bell.  Neutral macroecology. , 2001, Science.

[14]  E. S. Page.  CONTINUOUS INSPECTION SCHEMES , 1954 .

[15]  L. Horváth,et al.  Limit Theorems in Change-Point Analysis , 1997 .

[16]  Hochschule Emden Leer.  Automated image analysis , 2011 .

[17]  Yue Rong,et al.  Statistical Methods and Pitfalls in Environmental Data Analysis , 2000 .

[18]  Daniela Jarušková,et al.  Change-point detection in meteorological measurement , 1996 .

[19]  D. Hawkins.  Fitting multiple change-point models to data , 2001 .

[20]  Arjun K. Gupta,et al.  Parametric Statistical Change Point Analysis , 2000 .

[21]  József Garay,et al.  STATISTICAL DETECTION OF SPATIAL PLANT PATTERNS UNDER THE EFFECT OF FOREST USE , 2012 .

[22]  Paolo Menesatti,et al.  Multi-parametric study of behavioural modulation in demersal decapods at the VENUS cabled observatory in Saanich Inlet, British Columbia, Canada , 2011 .

[23]  Zhiqiang Cheng,et al.  An intelligent method of change-point detection based on LS-SVM algorithm , 2013 .

[24]  Francesca Antonucci,et al.  Automated Image Analysis for the Detection of Benthic Crustaceans and Bacterial Mat Coverage Using the VENUS Undersea Cabled Network , 2011, Sensors.

[25]  Jing-Long Wang,et al.  THE TEST AND CONFIDENCE INTERVAL FOR A CHANGE-POINT IN MEAN VECTOR OF MULTIVARIATE NORMAL DISTRIBUTION , 1994 .

[26]  Mike Hulme,et al.  Calculating regional climatic time series for temperature and precipitation: Methods and illustrations , 1996 .

[27]  A. R. Crathorne,et al.  Economic Control of Quality of Manufactured Product. , 1933 .

[28]  M Gámez,et al.  Application of Change-Point Problem to the Detection of Plant Patches , 2010, Acta biotheoretica.