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Reflectance spectra classification for the rapid assessment of water ecological quality in Mediterranean ports

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Ports are open systems with direct connection to the sea, therefore any potential impact on port waters may have implications for the health of adjacent marine ecosystems. European WFD addressed ports in the category of Heavily Modified Water Bodies (HMWBs) and promoted implementation of protocols to monitor and improve their ecological status. TRIX index, which incorporates the main variables involved in the trophism of marine ecosystems (Nitrogen, Phosphorus, Chlorophyll a, Dissolved Oxygen), is widely utilized in European coastal areas to evaluate trophic status. The relationships between the variables involved in TRIX computation, particularly Chlorophyll a concentration, and water spectral reflectance provides an alternative method to evaluate the quality and ecological status of the port water. Hyper-spectral (380-710 nm) water reflectance data were recorded by a portable radiometric system in five ports from the Western and Eastern Mediterranean Basin. The spectral distance between samples was measured by two metrics using both the original and reduced spectra and was implemented within a hierarchical clustering algorithm. The four spectral classes that emerged from this operation were statistically analysed versus standard water quality descriptors and phytoplankton community features to evaluate the ecological significance of the information obtained. The results indicated a substantial coherence of different indicators with more than 60% of the total TRIX variability is accounted for by the proposed classification of reflectance spectra. This classification is therefore proposed as a promising Rapid Assessment Technique of ports water ecological quality, which can serve as an effective monitoring tool for sustainable management of ports.
Czasopismo
Rocznik
Strony
445--459
Opis fizyczny
Bibliogr. 71 poz., mapa, rys., tab., wykr.
Twórcy
autor
  • Department of Biology, University of Florence, Italy
  • Department of Biology, University of Florence, Italy
  • IBIMET CNR, Florence, Italy
  • Department of Biology, University of Florence, Italy
  • Department of Biology, University of Florence, Italy
  • Hellenic Centre for Marine Research, Institute of Marine Biology, Biotechnology and Aquaculture, Heraklion, Greece
  • Hellenic Centre for Marine Research, Institute of Marine Biology, Biotechnology and Aquaculture, Heraklion, Greece
  • Hellenic Centre for Marine Research, Institute of Marine Biology, Biotechnology and Aquaculture, Heraklion, Greece
  • Department of Biology, University of Florence, Italy
  • Department of Biology, University of Florence, Italy
  • Department of Biology, University of Florence, Italy
Bibliografia
  • [1] Arar, E. J., Collins, G. B., 1992. In vitro determination of Chlorophyll-a and Pheophytin in marine and freshwater phytoplankton by fluorescence. Environmental Monitoring and Support Laboratory, U.S. EPA, Cincinnati, OH, EPA/600/R-92/121.
  • [2] Autorità di Bacino del fiume Serchio, 2010. Piano di Bacino Stralcio “Bilancio idrico del bacino del lago di Massaciuccoli”. Valutazione Ambientale Strategica Rapporto ambientale. Relazione sullo Stato dell'ambiente, 210 pp., http://www.autorita.bacinoserchio.it/files/piani/massaciuccoli/adozione-2010/RA_1_StatoAmbiente% 20.pdf.
  • [3] Behrenfeld, M. J., Boss, E., 2006. Beam attenuation and chlorophyll concentration as alternative optical indices of phytoplankton biomass. J. Mar. Res. 64, 431-451, http://dx.doi.org/10.1357/002224006778189563.
  • [4] Brando, V. E., Lovell, J. L., King, E. A., Boadle, D., Scott, R., Schroeder, T., 2016. The potential of autonomous ship-borne hyperspectral radiometers for the validation of ocean color radiometry data. Remote Sens. 8 (2), 150, 18 pp., http://dx.doi.org/10.3390/rs8020150.
  • [5] Boyer, J. N., Keble, C. R., Ortner, P. B., Rudnic, D. T., 2009. Phytoplankton bloom status: Chlorophyll a biomass as an indicator of water quality condition in the southern estuaries of Florida, USA. Ecol. Indic. 9S, 56-67, http://dx.doi.org/10.1016/j.ecolind.2008.11.013.
  • [6] Cabassi, J., Rossano, C., Gambineri, S., Fani, F., Vaselli, O., Tassi, F., Giannini, L., Lazzara, L., Nuccio, C., Buccianti, A., Capecchiacci, F., Mannucci, M., Massi, L., Melillo, C., Mori, G., Scapini, F., 2017. Water quality in the Port of Viareggio: a geochemical and biological characterization. In: Conese, C. (Ed.), Monitoring of Mediterranean Coastal Areas: Problems and Measurements Techniques. Sixth International Symposium, Livorno, 28-29 September 2016. Firenze University Press, Proceeding and Reports, 112, 5-14. http://digital.casalini.it/9788864534282.
  • [7] Cabrita, M. T., Silva, A., Oliveira, P. B., Angélico, M. M., Nogueira, M., 2015. Assessing eutrophication in the Portuguese continental Exclusive Economic Zone within the European Marine Strategy Framework Directive. Ecol. Indic. 5, 286-299, http://dx.doi.org/10.1016/j.ecolind.2015.05.044.
  • [8] Caroppo, C., Buttino, I., Camatti, E., Caruso, G., De Angelis, R., Facca, C., Giovanardi, F., Lazzara, L., Mangoni, O., Magaletti, E., 2013. State of the art and perspectives on the use of planktonic communities as indicators of environmental status in relation to the EU Marine Strategy Framework Directive. Biol. Mar. Medit. 20, 65-73.
  • [9] Chatzinikolaou, E., Mandalakis, M., Damianidis, P., Dailianis, T., Gambineri, S., Rossano, C., Scapini, F., Carucci, A., Arvanitidis, C., 2018. Spatio-temporal benthic biodiversity patterns and pollution pressure in three Mediterranean touristic ports. Sci. Total Environ. 624, 648-660, http://dx.doi.org/10.1016/j.scitotenv.2017.12.111.
  • [10] Craig, S. E., Lohrenz, S. E., Lee, Z., Mahoney, K. L., Kirkpatrick, G. J., Schofield, O. M., Steward, R. G., 2006. Use of hyperspectral remote sensing reflectance for detection and assessment of the harmful alga, Karenia brevis. Appl. Optics 45, 5414-5425, http://dx.doi.org/10.1364/AO.45.005414.
  • [11] Dall'Olmo, G., Gitelson, A. A., 2006. Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: modeling results. Appl. Optics 45 (15), 3577-3593, http://dx.doi.org/10.1364/AO.45.003577.
  • [12] Dembowska, E. A., Mieszczankin, T., Napiórkowski, P., 2018. Changes of the phytoplankton community as symptoms of deterioration of water quality in a shallow lake. Environ. Monit. Assess. 190, Art. no. 95, 11 pp., http://dx.doi.org/10.1007/s10661-018-6465-1.
  • [13] Eleveld, M. A., Ruescas, A. B., Hommersom, A., Moore, T. S., Peters, S. W. M., Brockmann, C., 2017. An optical classification tool for global lake waters. Remote Sens. 9, 420, http://dx.doi.org/10.3390/rs9050420.
  • [14] Eloranta, P., 1978. Light penetration in different types of lakes in central Finland. Ecography 1, 362-366, http://dx.doi.org/10.1111/j.1600-0587.1978.tb00971.x.
  • [15] Ferrari, G. M., Dowell, M. D., Grossi, S., Targa, C., 1996. Relationship between the optical properties of chromophoric dissolved organic matter and total concentration of dissolved organic carbon in the southern Baltic Sea region. Mar. Chem. 55, 299-316, http://dx.doi.org/10.1016/S0304-4203(96)00061-8.
  • [16] Ficek, D., Meler, J., Zapadka, T., Wozniak, B., Dera, J., 2012. Inherent optical properties and remote sensing reflectance of Pomeranian lakes (Poland). Oceanologia 54 (4), 611-630, http://dx.doi.org/10.5697/oc.54-4.611.
  • [17] Fumanti, B., Cavacini, P., 2002. La Flora algale degli Stagni del Molentargius (Cagliari). Webbia 57, 217-244, http://dx.doi.org/10.1080/00837792.2002.10670736.
  • [18] Giovanardi, F., Vollenweider, R. A., 2004. Trophic conditions of marine coastal waters: experience in applying the Trophic Index TRIX to two areas of the Adriatic and Tyrrhenian seas. J. Limnol. 63, 199-218, http://dx.doi.org/10.4081/jlimnol.2004.199.
  • [19] Gitelson, A., 1992. The peak near 700 nm on radiance spectra of algae and water: relationships of its magnitude and position with chlorophyll concentration. Int. J. Remote Sens. 13, 3367-3373, http://dx.doi.org/10.1080/01431169208904125.
  • [20] Gitelson, A. A., Dall'Olmo, G., Moses, W., Rundquist, D. C., Barrow, T., Fisher, T. R., Gurlin, D., Holz, J., 2008. A simple semi-analytical model for remote estimation of chlorophyll-a in turbid waters: validation. Remote Sens. Environ. 112 (9), 3582-3593, http://dx.doi.org/10.1016/j.rse.2008.04.015.
  • [21] Gökçe, D., 2016. Algae as an indicator of water quality. In: Thajuddin, N., Dhanasekaran, D. (Eds.), Algae — Organisms for Imminent Biotechnology. InTech, 81-101, http://dx.doi.org/10.5772/62916.
  • [22] Gonzalez Vilas, L., Spyrakos, E., Torres Palenzuela, J. M., 2011. Neural network estimation of chlorophyll a from MERIS full resolution data for the coastal waters of Galician rias (NW Spain). Remote Sens. Environ. 115, 524-535, http://dx.doi.org/10.1016/j.rse.2010.09.021.
  • [23] Gordon, H., Morel, A., 1983. Remote Assessment of Ocean Colour for Interpretation of Satellite Visible Imagery: A Review. Lecture Notes on Coastal and Estuarine Studies, vol. 4. Springer Verlag, New York, 114 pp.
  • [24] Harvey, E. T., Kratzer, S., Philipson, P., 2015. Satellite-based water quality monitoring for improved spatial and temporal retrieval of chlorophyll-a in coastal waters. Remote Sens. Environ. 158, 417-430, http://dx.doi.org/10.1016/j.rse.2014.11.017.
  • [25] Hommersom, A., Kratzer, S., Laanen, M., Ansko, I., Ligi, M., Bresciani, M., Peters, S., 2012. Intercomparison in the field between the new WISP-3 and other radiometers (TriOS Ramses, ASD Field-Spec, and TACCS). J. Appl. Remote Sens. 6 (1), 063615, http://dx.doi.org/10.1117/1.JRS.6.063615.
  • [26] IOCCG (International Ocean Color Coordinating Group), 2000. Remote sensing of ocean colour in coastal, and other optically-complex, waters. In: Sathyendranath, S. (Ed.), Reports of the International Ocean-Colour Coordinating Group 3. IOCCG, Dartmouth, Canada, 140 pp., http://www.ioccg.org.
  • [27] Ivančić, I., Degobbis, D., 1984. An optimal manual procedure for ammonia analysis in natural waters by the indophenol blue method. Water Res. 18, 1143-1147, http://dx.doi.org/10.1016/0043-1354(84)90230-6.
  • [28] Johnsen, G., Bricaud, A., Nelson, N., Prezelin, B. B., Bidigare, R. R., 2011. In vivo bio-optical properties of phytoplankton pigments. In: Roy, S., Llewellyn, C. A., Egeland, E. S., Johnsen, G. (Eds.), Scientific Committee on Oceanic Research (SCOR). Cambridge University Press, 496-537.
  • [29] Kaczmarek, S., Wozniak, B., 1995. The application of the optical classification of the waters in the Baltic Sea (Case 2 Waters). Oceanologia 37 (2), 285-297.
  • [30] Kirk, J. T. O., 2011. Light and Photosynthesis in Aquatic Ecosystems, 3rd ed. Cambridge University Press, New York, 509 pp.
  • [31] Lastrucci, L., Dell'Olmo, L., Foggi, B., Massi, L., Nuccio, C., Vicenti, C., Viciani, D., 2017. Contribution to the knowledge of the vegetation of the Lake Massaciuccoli (northern Tuscany, Italy). Plant Sociol. 54, 1-23, http://dx.doi.org/10.7338/pls2017541/03.
  • [32] Lee, Z. P., Carder, K. L., 2002. Effect of spectral band numbers on the retrieval of water column and bottom properties from ocean color data. Appl. Optics 41, 2191-2201, http://dx.doi.org/10.1364/AO.41.002191.
  • [33] Lee, Z., Carder, K., Arnone, R., He, M., 2007. Determination of primary spectral bands for remote sensing of aquatic environments. Sensors 7 (12), 3428-3441, http://dx.doi.org/10.3390/s7123428.
  • [34] Lee, Z., Shang, S., Hu, C., Zibordi, G., 2014. Spectral interdependence of remote-sensing reflectance and its implications on the design of ocean color satellite sensors. Appl. Optics 53 (15), 3301, http://dx.doi.org/10.1364/AO.53.003301.
  • [35] Loisel, H., Morel, A., 2001. Non-isotropy of the upward radiance field in typical coastal (Case 2) waters. Int. J. Remote Sens. 22 (2-3), 275-295.
  • [36] MAPMED, 2015. General Guidelines for a rational and sustainable management of water, sediments and linked ecosystems of tourist port areas at Mediterranean sea basin level. European Union- ENPI CBCMED, 88 pp., http://www.mapmed.eu/general-guidelines.
  • [37] Maselli, F., Massi, L., Pieri, M., Santini, C., 2009. Spectral angle minimization for the retrieval of optically active seawater constituents from MODIS data. Photogramm. Eng. Remote Sens. 75, 595-605, http://dx.doi.org/10.14358/PERS.75.5.595.
  • [38] Mobley, C., 2018. Overview of Optical Oceanography: Reflectances, http://www.oceanopticsbook.info/view/overview_of_optical_oceanography/reflectances.
  • [39] Moore, T. S., Campbell, J. W., Dowell, M. D., 2009. A class-based approach to characterizing and mapping the uncertainty of the MODIS ocean chlorophyll product. Remote Sens. Environ. 113 (11), 2424-2430, http://dx.doi.org/10.1016/j.rse.2009.07.016.
  • [40] Moore, T. S., Dowell, M. D., Bradt, S., Ruiz Verdu, A., 2014. An optical water type framework for selecting and blending retrievals from biooptical algorithms in lakes and coastal waters. Remote Sens. Environ. 143, 97-111, http://dx.doi.org/10.1016/j.rse.2013.11.021.
  • [41] Morel, A., Prieur, L., 1977. Analysis of variation in ocean color. Limnol. Oceanogr. 22, 709-722.
  • [42] Morrison, D. F., 2004. Multivariate Statistical Methods, 4th edn., Duxbury Advanced Ser., Thomson/Brooks/Cole, 469 pp.
  • [43] Murtagh, F., Legendre, P., 2014. Ward's hierarchical agglomerative clustering method: which algorithms implement Ward's criterion? J. Classif. 31, 274-295, http://dx.doi.org/10.1007/s00357-014-9161-z.
  • [44] Nourisson, D. H., Scapini, F., Massi, L., Lazzara, L., 2013. Optical characterization of a coastal lagoon in Tunisia: ecological assessment to underpin conservation. Ecol. Inform. 14, 79-83, http://dx.doi.org/10.1016/j.ecoinf.2012.11.011.
  • [45] Nourisson, D. H., Scapini, F., Massi, L., Lazzara, L., 2016. Characterization of a Tunisian coastal lagoon through hyperspectral under-water irradiance. Afr. J. Aquat. Sci. 41 (2), 217-225, http://dx.doi.org/10.2989/16085914.2016.1165648.
  • [46] Ondiviela, B., Juanes, J. A., Gómez, A. G., Sámano, M. L., Revilla, J. A., 2012. Methodological procedure for water quality management in port areas at the EU level. Ecol. Indic. 13, 117-128, http://dx.doi.org/10.1016/j.ecolind.2011.05.018.
  • [47] Organelli, E., Nuccio, C., Lazzara, L., Uitz, J., Bricaud, A., Massi, L., 2017. On the discrimination of multiple phytoplankton groups from light absorption spectra of assemblages with mixed taxonomic composition and variable light conditions. Appl. Optics 56, 3952-3968, http://dx.doi.org/10.1364/AO.56.003952.
  • [48] Ouillon, S., Petrenko, A., 2005. Above-water measurements of reflectance and chlorophyll-a algorithms in the Gulf of Lions, NW Mediterranean Sea. Opt. Express 13, 2531-2548, http://dx.doi.org/10.1364/OPEX.13.002531.
  • [49] Palacios, S. L., Peterson, T. D., Kudela, R. M., 2012. Optical characterization of water masses within the Columbia River plume. J. Geophys. Res. 117, C11020, http://dx.doi.org/10.1029/2012JC008005.
  • [50] Penna, N., Capellacci, S., Ricci, F., 2004. The influence of the Po River discharge on phytoplankton bloom dynamics along the coastline of Pesaro (Italy) in the Adriatic Sea. Mar. Pollut. Bull. 48, 321-326, http://dx.doi.org/10.1016/j.marpolbul.2003.08.007.
  • [51] Pettine, M., Casentini, B., Fazi, S., Giovanardi, F., Pagnotta, R., 2007. A revisitation of TRIX for trophic status assessment in the light of the European Water Framework Directive: application to Italian coastal waters. Mar. Pollut. Bull. 54, 1413-1426, http://dx.doi.org/10.1016/j.marpolbul.2007.05.013.
  • [52] Primpas, I., Karydis, M., 2011. Scaling the trophic index (TRIX) in oligotrophic marine environments. Environ. Monit. Assess. 178, 257-269, http://dx.doi.org/10.1007/s10661-010-1687-x.
  • [53] Reinart, A., Herlevi, A., Helgi, A., Sipelgas, L., 2003. Preliminary optical classification of lakes and coastal waters in Estonia and south Finland. J. Sea Res. 49, 357-366, http://dx.doi.org/10.1016/S1385-1101(03)00019-4.
  • [54] Reynolds, C. S., 2006. Ecology of Phytoplankton. Cambridge University Press, Cambridge, 535 pp.
  • [55] Shalles, J. F., 2006. Optical remote sensing techniques to estimate phytoplankton chlorophyll a concentrations in coastal water with varying suspended matter and CDOM concentrations. In: Richardson, L. L., LeDrew, E. F. (Eds.), Remote Sensing of Aquatic Coastal Ecosystem Processes: Science and Management Applications. Springer, 27-79.
  • [56] Shen, Q., Li, J., Zhang, F., Sun, X., Li, J., Li, W., Zhang, B., 2015. Classification of several optically complex waters in China using in situ remote sensing reflectance. Remote Sens. 7, 14731-14756, http://dx.doi.org/10.3390/rs71114731.
  • [57] Shi, K., Li, Y., Zhang, Y., Li, L., Lv, H., Song, K., 2014. Classification of inland waters based on bio-optical properties. IEEE J. Sel. Top. Appl. 7, 543-561, http://dx.doi.org/10.1109/JSTARS.2013.2290744.
  • [58] Sokal, R., Rohlf, F. J., 1995. Biometry, 3rd edn., Freeman and Company, New York, 887 pp.
  • [59] Spyrakos, E., O'Donnell, R., Hunter, P. D., Miller, C., Scott, M., Simis, S. G. H., Neil, C., Barbosa, C. C. F., Binding, C. E., Bradt, S., Bresciani, M., Dall'Olmo, G., Giardino, C., Gitelson, A. A., Kutser, T., Li, L., Matsushita, B., Vicente, V., Matthews, M. W., Ogashawara, I., Ruiz-Verdu, A., Schalles, J. F., Tebbs, E., Zhang, Y., Tyler, A. N., 2018. Optical types of inland and coastal waters. Limnol. Oceanogr. 63 (2), 846-870, http://dx.doi.org/10.1002/lno.1067.
  • [60] Stedmon, C. A., Markeager, S., Kaas, H., 2000. Optical properties and signature of chromophoric dissolved organic matter (CDOM) in Danish coastal waters. Estuar. Coast. Shelf Sci. 51, 267-278, http://dx.doi.org/10.1006/ecss.2000.0645.
  • [61] Strickland, J. D. H., Parsons, T. R., 1972. A Practical Handbook of Seawater Analysis. Bull. Fish. Res. Board Canada 167, 310 pp.
  • [62] UNEP, 2007.In: Eutrophication monitoring strategy of MED POL (REVISION), UNEP(DEC)/MED WG 321/Inf.5. 12-14 December 2007, Athens, 12 pp.
  • [63] Uusitalo, L., Blanchet, H., Andersen, J. H., Beauchard, O., Berg, T., Bianchelli, S., Cantafaro, A., Carstensen, J., Carugati, L., Cochrane, S., Danovaro, R., Heiskanen, A.-S., Karvinen, V., Moncheva, S., Murray, C., Neto, J. M., Nygård, H., Pantazi, M., Papadopoulou, N., Simboura, N., Srebaliene, G., Uyarra, M. C., Borja, A., 2016. Indicator-based assessment of marine biological diversity — lessons from 10 case studies across the European seas. Front. Mar. Sci. 3, 159, http://dx.doi.org/10.3389/fmars.2016.00159.
  • [64] Van de Bund, W., Poikane, S., 2015. Water Framework Directive scientific and technical support related to ecological status, Summary Rep. JRC activities in 2015, EUR 27707 EN, http://dx.doi.org/10.2788/071200.
  • [65] Van der Linde, D. W., 1998. Protocol for Determination of Total Suspended Matter in Oceans and Coastal Zones, CEC-JRC-Ispra, Technical note I 98, 182 pp.
  • [66] Vantrepotte, V., Loisel, H., Dessailly, D., Meriaux, X., 2012. Optical classification of contrasted coastal waters. Remote Sens. Environ. 123, 306-323, http://dx.doi.org/10.1016/j.rse.2012.03.004.
  • [67] Vertucci, F. A., Likens, G. E., 1989. Spectral reflectance and water quality of Andirondack mountain region lakes. Limnol. Oceanogr. 34, 1656-1672, http://dx.doi.org/10.4319/lo.1989.34.8.1656.
  • [68] Vollenweider, R. A., Giovanardi, F., Montanari, G., Rinaldi, A., 1998. Characterization of the trophic conditions of marine coastal waters with special reference to the NW Adriatic Sea: proposal for a trophic scale, turbidity and generalized water quality index. Environmetrics 9, 329-357.
  • [69] Ward, J. H., 1963. Hierarchical grouping to optimize an objective function. J. Amer. Stat. Ass. 58, 236-244.
  • [70] Yentsch, C. S., Menzel, D. W., 1963. A method for the determination of phytoplankton chlorophyll and pheophytin by fluorescence. Deep Sea Res. 10, 221-231, http://dx.doi.org/10.1016/0011-7471(63)90358-9.
  • [71] Zingone, A., Totti, C., Sarno, D., Cabrini, C., Caroppo, C., Giacobbe, M. G., Lugliè, A., Nuccio, C., Socal, G., 2010. Fitoplancton: metodiche di analisi quali-quantitativa. In: Socal, G., Buttino, I., Cabrini, M., Mangoni, O., Penna, A., Totti, C. (Eds.), Metodologie di campionamento e di studio del plancton marino, Manuali e Linee guida 56. ISPRA-SIBM, Rome, 13-237.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-95646738-a2de-4415-8dc0-d11bd0c6db0c
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