Determining the change point for the error in the Macrophyte Index for Rivers

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The consequences of the growing demand for water include a significant deterioration in its quality and a drastic decline in biodiversity, which is a serious threat to the hydrological and biocenotic balance of freshwater ecosystems. A good indicator of aquatic environment quality is macrophytes. Studies on macrophytes are one of the primary elements in the ecological status assessment of surface waters, in accordance with the guidelines of the Water Framework Directive. In Poland, research on the ecological status of rivers with regard to macrophytes has been carried out since 2008, using the Macrophyte Index for Rivers (MIR), which takes into account the number and coverage of macrophyte taxa. An analysis of numbers of species that need to be indicated at a site for valid assessment of the ecosystem was conducted on the basis of studies on macrophytes from 2008–2013, at 60 sites in small lowland rivers with a sandy substrate, of which 20 sites were selected on the most diverse watercourses: the least clean (quality class V), moderate (quality class III), and the cleanest (quality class I). The results of the botanical studies served to assess the completeness of the samples (the number of species recorded at a site) used to evaluate the ecological status of a river. The proposed analyses enabled estimation of the approximate number of species required to determine the MIR for rivers in each quality class.

Bacon D.W., Watts D.G. (1971): Estimating the transition between two intersecting straight lines. Biometrika 58: 525-534.

Bernatowicz S., Wolny P. (1969): Fisherman’s botany (in Polish). Państwowe Wydawnictwo Rolnicze i Leśne, Warszawa, Poland.

Carvalno L.B., Rojano-Delgado A.M, Costa Aguiar Alves P.L., Prado R. (2013): Differential content of glyphosate and its metabolites in Digitaria insularis biotypes. Communications in Plant Sciences 3(3-4): 17-20.

Ceschin S., Salerno G., Bisceglie S., Kumbaric A. (2010): Temporal floristic variations as indicator of environmental changes in the Tiber River in Rome. Aquatic Ecology 44: 93–100. doi: 10.1007/s10452-009-9292-1.

Chen J., Gupta A.K. (2000): Parametric statistical change point analysis, Birkhauser.

Dawson F.H., Newman J.R., Gravelle M.J., Rouen K.J., Henville P. (1999): Assessment of the Trophic Status of Rivers Using Macrophytes. Evaluation of the Mean Trophic Rank, R&D Technical Report E39, Environment Agency.

Dudley B., Dunbar M., Penning E., Kolada A., Hellsten S., Oggioni A. et al. (2013): Measurements of uncertainty in macrophyte metrics used to assess European lake water quality. Hydrobiologia 704: 179–191. doi: 10.1007/s10750-012-1338-z.

Official Journal (2016). Regulation of the Minister of the Environment of July 21, 2016 on the method of classification of the status of uniform surface water bodies and environmental quality standards for priority substances. Official Journal 2016. item 1187 (in Polish).

Eckley I.A., Fearnhead P., Killick R. (2011): Analysis of Changepoint Models. In Barber D., Cemgil A.T., Chiappa S. (eds.), Bayesian Time Series Models. Cambridge University Press.

Erdman C., Emerson J.W. (2007): An R Package for Performing a Bayesian Analysis of Change Point Problems. Journal of Statistical Software 23(3): 1-13.

Gupta A.K., Tang J. (1987): On Testing Homogeneity of Variances for Gaussian Models. Journal of Statistical Computation and Simulation 27(2): 155-173.

Haslam S.M. (1982): A proposed method for monitoring river pollution using macrophytes. Environmental Technology Letters 3: 19-34. doi: 10.1080/0959333 8209384094

Hinkley D.V. (1969): Inference about the intersection in two-phase regression. Biometrika 56: 495-504.

Hinkley D.V. (1970): Inference about the Change-Point in a Sequence of Random Variables. Biometrika 57(1): 1-17.

Hirotsu C., Harukazu T. (2017): An algorithm for a new method of change-point analysis in the independent Poisson sequence. Biometrical Letters 54(1): 1-24.

Holmes N.T.H., Newman J.R., Chadd S., Rouen K.J., Saint L., Dawson F.H. (1999): Technical report no E38 Environmental Agency of England Wales. Bristol: UK; Mean trophic rank: a user’s manual R.

Hudson D.J. (1966): Fitting segmented curves whose joint points have to be estimated. Journal of the American Statistical Association 61: 1097-1129.

Jusik S. (2012): Identification key to mosses and water liverwords required to the ecological status assessment of surface waters in Poland (in Polish). Biblioteka Monitoringu Środowiska, Warszawa, Poland.

Killick R., Eckley I., Haynes K. (2014): Changepoint: An R Package for Changepoint Analysis. R package version 1.1.5, URL

Killick R., Eckley I.A., Jonathan P., Ewans K. (2010): Detection of Changes in the Characteristics of Oceanographic Time-Series using Statistical Change Point Analysis. Ocean Engineering 37(13): 1120-1126.

Kirby E.J.M. (1974): Ear development in spring wheat. Journal of Agricultural Science 82: 437-447.

Kolada A. (2010): The use of aquatic vegetation in the lake assessment: testing the sensitivity of macrophyte metrics to anthropogenic pressures and water quality. Hydrobiologia 656: 133-147. doi: 10.1007/s10750-010-0428-z.

Kolkwitz R., Marsson M. (1902): Grundsatze fur die biologische Beurteilung des Wassers nach seiner Flora und Fauna. Mitt. Priifungsanst. Wasserversorg. Abwasserein 1: 33-72.

Lavielle M. (2005): Using Penalized Contrasts for the Change-Point Problem. Signal Processing 85(8): 1501-1510.

Lerman P.M. (1980): Fitting segmented regression model by grid search. Appl. Stat. 29: 77-84.

Nam C.F.H., Aston J.A.D., Johansen A.M. (2012): Quantifying the Uncertainty in Change Points. Journal of Time Series Analysis 33(5): 807-823.

Pruska K. (1996): Metody regresji przełącznikowej i ich zastosowanie (in Polish). Wyd. Uniw. Łódzkiego, Łódź.

Reeves J., Chen J., Wang X.L., Lund R., Lu Q. (2007): A Review and Comparison of Changepoint Detection Techniques for Climate Data. Journal of Applied Meteorology and Climatology 46(6): 900-915.

Rutkowski L. (2008): Identification key to vascular plants of Polish Lowland (in Polish). Wydawnictwo Naukowe PWN, Warszawa, Polska.

Seber G.A.F., Wild C.J. (1989): Nonlinear Regression. Wiley, New York.

Silva E.G., Teixeira A.A.C. (2008): Surveying Structural Change: Seminal Contributions and Bibliometric Account. Structural Change and Economic Dynamics 19(4): 273-300.

Sprent P. (1961): Some hypotheses concerning two phase regression lines. Biometrix 17: 634-645.

Staniszewski R., Szoszkiewicz K., Zbierska J., Leśny J., Jusik S, Clarke R.T. (2006): Assessment of sources of uncertainty in macrophyte surveys and the consequences for river classification. Hydrobiologia 566: 235-246.

Starmach K., Wróbel S., Pasternak K. (1976): Hydrobiologia. Limnologia. Warszawa: PWN.

Szoszkiewicz K., Zbierska J., Jusik S., Zgoła T. (2010): Macrophyte method for river assessment. Poznan: Bogucki Wydawnictwo Naukowe.

Szoszkiewicz K., Budka A., Pietruczuk K., Kayzer D., Gebler D. (2017): Is the macrophyte diversification along the trophic gradient distinct enough for river monitoring? Environtal Monitoring and Assessment 189: 4. doi:10.1007/s10661-016-5710-8.

Watts D.G., Bacon D.W. (1974): Using an hyperbola as a transition model to fit two-regime straight-line data. Technometrics 16: 369-373.

Wiegleb G. (1979): Der Zusammenhang zwischen Gewässergüte und Makrophyten Vegetation in niedersächsischen Fließgewässern. Landschaft + Stadt 11: 32-35.

Zeileis A., Leisch F., Hornik K., Kleiber C. (2002): Strucchange: An R Package for Testing for Structural Change in Linear Regression Models. Journal of Statistical Software 7(2): 1-38. URL

Zeileis A., Shah A., Patnaik I. (2010): Testing, Monitoring, and Dating Structural Changes in Exchange Rate Regimes. Computational Statistics & Data Analysis 54(6): 1696-1706.

Zelinka M., Marvan P. (1961): Zur Präzisierung der biologischen klassifikation der Reinheit flieβender Gewässer.-Arch. Hydrobiol. 57: 389-407.

Zimny H. (2006): Ekologiczna ocena stanu środowiska. Bioindykacja i biomonitoring (in Polish). Agencja Reklamowo-Wydawnicza Arkadiusz Grzegorczyk, Warszawa.

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