Mapping Satellite Inherent Optical Properties Index in Coastal Waters of the Yucatán Peninsula (Mexico)

[EN] The Yucatan Peninsula hosts worldwide-known tourism destinations that concentrate most of the Mexico tourism activity. In this region, tourism has exponentially increased over the last years, including wildlife oriented tourism. Rapid tourism development, involving the consequent construction of hotels and tourist commodities, is associated with domestic sewage discharges from septic tanks. In this karstic environment, submarine groundwater discharges are very important and highly vulnerable to anthropogenic pollution. Nutrient loadings are linked to harmful algal blooms, which are an issue of concern to local and federal authorities due to their recurrence and socioeconomic and human health costs. In this study, we used satellite products from MODIS (Moderate Resolution Imaging Spectroradiometer) to calculate and map the satellite Inherent Optical Properties (IOP) Index. We worked with different scenarios considering both holiday and hydrological seasons. Our results showed that the satellite IOP Index allows one to build baseline information in a sustainable mid-term or long-term basis which is key for ecosystem-based management.This research was funded by CONACYT with a doctorate scholarship to Jesús A. Aguilar-Maldonado,with the announcement number 251025 in 2015. María-Teresa Sebastiá-Frasquet was a beneficiary of the BEST/2017/217 post-doctoral research grant, supported by the Valencian Conselleria d’Educació, Investigació,Cultura i Esport (Spain) during her stay at the Universidad Autónoma de Baja California (Mexico). The Secretariat of Public Education of Mexico (SEP) under the Program for Professional Development Teacher, covered the costs of publication in open access.Aguilar-Maldonado, J.; Santamaría-Del-Ángel, E.; González-Silvera, A.; Cervantes-Rosas, OD.; Sebastiá-Frasquet, M. (2018). Mapping Satellite Inherent Optical Properties Index in Coastal Waters of the Yucatán Peninsula (Mexico). Sustainability. 10(6). https://doi.org/10.3390/su10061894S1894106Bentz, J., Lopes, F., Calado, H., & Dearden, P. (2016). Sustaining marine wildlife tourism through linking Limits of Acceptable Change and zoning in the Wildlife Tourism Model. Marine Policy, 68, 100-107. doi:10.1016/j.marpol.2016.02.016Jarvis, D., Stoeckl, N., & Liu, H.-B. (2016). The impact of economic, social and environmental factors on trip satisfaction and the likelihood of visitors returning. Tourism Management, 52, 1-18. doi:10.1016/j.tourman.2015.06.003Ziegler, J., Dearden, P., & Rollins, R. (2012). But are tourists satisfied? Importance-performance analysis of the whale shark tourism industry on Isla Holbox, Mexico. Tourism Management, 33(3), 692-701. doi:10.1016/j.tourman.2011.08.004Duffus, D. A., & Dearden, P. (1990). Non-consumptive wildlife-oriented recreation: A conceptual framework. Biological Conservation, 53(3), 213-231. doi:10.1016/0006-3207(90)90087-6Aguilar-Trujillo, A. C., Okolodkov, Y. B., Herrera-Silveira, J. A., Merino-Virgilio, F. del C., & Galicia-García, C. (2017). Taxocoenosis of epibenthic dinoflagellates in the coastal waters of the northern Yucatan Peninsula before and after the harmful algal bloom event in 2011–2012. Marine Pollution Bulletin, 119(1), 396-406. doi:10.1016/j.marpolbul.2017.02.074Ulloa, M. J., Álvarez-Torres, P., Horak-Romo, K. P., & Ortega-Izaguirre, R. (2017). Harmful algal blooms and eutrophication along the mexican coast of the Gulf of Mexico large marine ecosystem. Environmental Development, 22, 120-128. doi:10.1016/j.envdev.2016.10.007Henrichs, D. W., Hetland, R. D., & Campbell, L. (2015). Identifying bloom origins of the toxic dinoflagellate Karenia brevis in the western Gulf of Mexico using a spatially explicit individual-based model. Ecological Modelling, 313, 251-258. doi:10.1016/j.ecolmodel.2015.06.038Murray, G. (2007). Constructing Paradise: The Impacts of Big Tourism in the Mexican Coastal Zone. Coastal Management, 35(2-3), 339-355. doi:10.1080/08920750601169600Heisler, J., Glibert, P. M., Burkholder, J. M., Anderson, D. M., Cochlan, W., Dennison, W. C., … Suddleson, M. (2008). Eutrophication and harmful algal blooms: A scientific consensus. Harmful Algae, 8(1), 3-13. doi:10.1016/j.hal.2008.08.006Smayda, T. J. (2008). Complexity in the eutrophication–harmful algal bloom relationship, with comment on the importance of grazing. Harmful Algae, 8(1), 140-151. doi:10.1016/j.hal.2008.08.018Klemas, V. (2012). Remote Sensing of Algal Blooms: An Overview with Case Studies. Journal of Coastal Research, 278, 34-43. doi:10.2112/jcoastres-d-11-00051.1COFEPRIS (Comisión Federal para la Protección contra Riesgos Sanitarios/Federal Commission for Protection against Health Risks)https://www.gob.mx/cofepris/acciones-y-programas/antecedentes-en-mexico-76707Antoine, D., & Morel, A. (1996). Oceanic primary production: 1. Adaptation of a spectral light-photosynthesis model in view of application to satellite chlorophyll observations. Global Biogeochemical Cycles, 10(1), 43-55. doi:10.1029/95gb02831Barocio-León, Ó. A., Millán-Núñez, R., Santamaría-del-Ángel, E., González-Silvera, A., & Trees, C. C. (2006). Spatial variability of phytoplankton absorption coefficients and pigments off Baja California during November 2002. Journal of Oceanography, 62(6), 873-885. doi:10.1007/s10872-006-0105-zSmith, V. H., Tilman, G. D., & Nekola, J. C. (1999). Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environmental Pollution, 100(1-3), 179-196. doi:10.1016/s0269-7491(99)00091-3Limoges, A., Londeix, L., & de Vernal, A. (2013). Organic-walled dinoflagellate cyst distribution in the Gulf of Mexico. Marine Micropaleontology, 102, 51-68. doi:10.1016/j.marmicro.2013.06.002Jiang, L., Xia, M., Ludsin, S. A., Rutherford, E. S., Mason, D. M., Marin Jarrin, J., & Pangle, K. L. (2015). Biophysical modeling assessment of the drivers for plankton dynamics in dreissenid-colonized western Lake Erie. Ecological Modelling, 308, 18-33. doi:10.1016/j.ecolmodel.2015.04.004Aguilar-Maldonado, J., Santamaría-del-Ángel, E., González-Silvera, A., Cervantes-Rosas, O., López, L., Gutiérrez-Magness, A., … Sebastiá-Frasquet, M.-T. (2018). Identification of Phytoplankton Blooms under the Index of Inherent Optical Properties (IOP Index) in Optically Complex Waters. Water, 10(2), 129. doi:10.3390/w10020129Wei, G., Tang, D., & Wang, S. (2008). Distribution of chlorophyll and harmful algal blooms (HABs): A review on space based studies in the coastal environments of Chinese marginal seas. Advances in Space Research, 41(1), 12-19. doi:10.1016/j.asr.2007.01.037Urquhart, E. A., Schaeffer, B. A., Stumpf, R. P., Loftin, K. A., & Werdell, P. J. (2017). A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing. Harmful Algae, 67, 144-152. doi:10.1016/j.hal.2017.06.001Harvey, 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 Sensing of Environment, 158, 417-430. doi:10.1016/j.rse.2014.11.017Malthus, T. J., & Mumby, P. J. (2003). Remote sensing of the coastal zone: An overview and priorities for future research. International Journal of Remote Sensing, 24(13), 2805-2815. doi:10.1080/0143116031000066954Matthews, M. W. (2011). A current review of empirical procedures of remote sensing in inland and near-coastal transitional waters. International Journal of Remote Sensing, 32(21), 6855-6899. doi:10.1080/01431161.2010.512947Miller, R. L., & McKee, B. A. (2004). Using MODIS Terra 250 m imagery to map concentrations of total suspended matter in coastal waters. Remote Sensing of Environment, 93(1-2), 259-266. doi:10.1016/j.rse.2004.07.012Loisel, H., Vantrepotte, V., Norkvist, K., Mériaux, X., Kheireddine, M., Ras, J., … Moutin, T. (2011). Characterization of the bio-optical anomaly and diurnal variability of particulate matter, as seen from scattering and backscattering coefficients, in ultra-oligotrophic eddies of the Mediterranean Sea. Biogeosciences, 8(11), 3295-3317. doi:10.5194/bg-8-3295-2011Werdell, P. J., Franz, B. A., Bailey, S. W., Feldman, G. C., Boss, E., Brando, V. E., … Mangin, A. (2013). Generalized ocean color inversion model for retrieving marine inherent optical properties. Applied Optics, 52(10), 2019. doi:10.1364/ao.52.002019Brezonik, P. L., Olmanson, L. G., Finlay, J. C., & Bauer, M. E. (2015). Factors affecting the measurement of CDOM by remote sensing of optically complex inland waters. Remote Sensing of Environment, 157, 199-215. doi:10.1016/j.rse.2014.04.033Odermatt, D., Gitelson, A., Brando, V. E., & Schaepman, M. (2012). Review of constituent retrieval in optically deep and complex waters from satellite imagery. Remote Sensing of Environment, 118, 116-126. doi:10.1016/j.rse.2011.11.013Enriquez, C., Mariño-Tapia, I., Jeronimo, G., & Capurro-Filograsso, L. (2013). Thermohaline processes in a tropical coastal zone. Continental Shelf Research, 69, 101-109. doi:10.1016/j.csr.2013.08.018Estadísticas del Agua en México. Secretaría de Medio Ambiente y Recursos Naturaleshttp://201.116.60.25/publicaciones/EAM_2016.pdfArcega-Cabrera, F., Garza-Pérez, R., Noreña-Barroso, E., & Oceguera-Vargas, I. (2014). Impacts of Geochemical and Environmental Factors on Seasonal Variation of Heavy Metals in a Coastal Lagoon Yucatan, Mexico. Bulletin of Environmental Contamination and Toxicology, 94(1), 58-65. doi:10.1007/s00128-014-1416-1Lopez-Maldonado, Y., Batllori-Sampedro, E., Binder, C. R., & Fath, B. D. (2017). Local groundwater balance model: stakeholders’ efforts to address groundwater monitoring and literacy. Hydrological Sciences Journal, 62(14), 2297-2312. doi:10.1080/02626667.2017.1372857Derrien, M., Cabrera, F. A., Tavera, N. L. V., Kantún Manzano, C. A., & Vizcaino, S. C. (2015). Sources and distribution of organic matter along the Ring of Cenotes, Yucatan, Mexico: Sterol markers and statistical approaches. Science of The Total Environment, 511, 223-229. doi:10.1016/j.scitotenv.2014.12.053INEGIhttp://www.beta.inegi.org.mx/temas/agua/Ramírez, R., Seeliger, L., & Di Pietro, F. (2016). Price, Virtues, Principles: How to Discern What Inspires Best Practices in Water Management? A Case Study about Small Farmers in the Yucatan Peninsula of Mexico. Sustainability, 8(4), 385. doi:10.3390/su8040385Null, K. A., Knee, K. L., Crook, E. D., de Sieyes, N. R., Rebolledo-Vieyra, M., Hernández-Terrones, L., & Paytan, A. (2014). Composition and fluxes of submarine groundwater along the Caribbean coast of the Yucatan Peninsula. Continental Shelf Research, 77, 38-50. doi:10.1016/j.csr.2014.01.011Álvarez-Góngora, C., & Herrera-Silveira, J. A. (2006). Variations of phytoplankton community structure related to water quality trends in a tropical karstic coastal zone. Marine Pollution Bulletin, 52(1), 48-60. doi:10.1016/j.marpolbul.2005.08.006Carruthers, T. J. B., van Tussenbroek, B. I., & Dennison, W. C. (2005). Influence of submarine springs and wastewater on nutrient dynamics of Caribbean seagrass meadows. Estuarine, Coastal and Shelf Science, 64(2-3), 191-199. doi:10.1016/j.ecss.2005.01.015Monterrubio, J. C., Sosa, A. P., & Josiam, B. M. (2014). Spring break e impacto social en Cancún, México. Un estudio para la gestión del turismo. Turismo y Sociedad, 15, 149. doi:10.18601/01207555.n15.09Lee, Z.-P. (2005). A model for the diffuse attenuation coefficient of downwelling irradiance. Journal of Geophysical Research, 110(C2). doi:10.1029/2004jc002275Gordon, H. R., Brown, O. B., Evans, R. H., Brown, J. W., Smith, R. C., Baker, K. S., & Clark, D. K. (1988). A semianalytic radiance model of ocean color. Journal of Geophysical Research, 93(D9), 10909. doi:10.1029/jd093id09p10909Roesler, C. S., Perry, M. J., & Carder, K. L. (1989). Modeling in situ phytoplankton absorption from total absorption spectra in productive inland marine waters. Limnology and Oceanography, 34(8), 1510-1523. doi:10.4319/lo.1989.34.8.1510SMN (Servicio Meteorológico Nacional/National Metereological Service)http://smn.cna.gob.mx/es/climatologia/temperaturas-y-lluvias/resumenes-mensuales-de-temperaturas-y-lluviasCarstensen, J., Klais, R., & Cloern, J. E. (2015). Phytoplankton blooms in estuarine and coastal waters: Seasonal patterns and key species. Estuarine, Coastal and Shelf Science, 162, 98-109. doi:10.1016/j.ecss.2015.05.005Winder, M., & Cloern, J. E. (2010). The annual cycles of phytoplankton biomass. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1555), 3215-3226. doi:10.1098/rstb.2010.0125Cloern, J. E., & Jassby, A. D. (2008). Complex seasonal patterns of primary producers at the land-sea interface. Ecology Letters, 11(12), 1294-1303. doi:10.1111/j.1461-0248.2008.01244.xAthie, G. (2011). Yucatan Current variability through the Cozumel and Yucatan channels. Ciencias Marinas, 37(4A), 471-492. doi:10.7773/cm.v37i4a.1794Pérez, R., Muller-Karger, F. E., Victoria, I., Melo, N., & Cerdeira, S. (1999). Cuban, Mexican, U.S. Researchers probing mysteries of Yucatan Current. Eos, Transactions American Geophysical Union, 80(14), 153-158. doi:10.1029/99eo00104Merino, M. (1997). Upwelling on the Yucatan Shelf: hydrographic evidence. Journal of Marine Systems, 13(1-4), 101-121. doi:10.1016/s0924-7963(96)00123-6Beusen, A. H. W., Slomp, C. P., & Bouwman, A. F. (2013). Global land–ocean linkage: direct inputs of nitrogen to coastal waters via submarine groundwater discharge. Environmental Research Letters, 8(3), 034035. doi:10.1088/1748-9326/8/3/034035Pacheco Castro, R., Pacheco Ávila, J., Ye, M., & Cabrera Sansores, A. (2017). Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer. Groundwater, 56(1), 62-72. doi:10.1111/gwat.12546Muñoz, J., Freile-Pelegrín, Y., & Robledo, D. (2004). Mariculture of Kappaphycus alvarezii (Rhodophyta, Solieriaceae) color strains in tropical waters of Yucatán, México. Aquaculture, 239(1-4), 161-177. doi:10.1016/j.aquaculture.2004.05.043Sebastiá, M.-T., Rodilla, M., Sanchis, J.-A., Altur, V., Gadea, I., & Falco, S. (2012). Influence of nutrient inputs from a wetland dominated by agriculture on the phytoplankton community in a shallow harbour at the Spanish Mediterranean coast. Agriculture, Ecosystems & Environment, 152, 10-20. doi:10.1016/j.agee.2012.02.006Enriquez, C., Mariño-Tapia, I. J., & Herrera-Silveira, J. A. (2010). Dispersion in the Yucatan coastal zone: Implications for red tide events. Continental Shelf Research, 30(2), 127-137. doi:10.1016/j.csr.2009.10.00

Identification of Phytoplankton Blooms under the Index of Inherent Optical Properties (IOP Index) in Optically Complex Waters

[EN] Phytoplankton blooms are sporadic events in time and are isolated in space. This complex phenomenon is produced by a variety of both natural and anthropogenic causes. Early detection of this phenomenon, as well as the classification of a water body under conditions of bloom or non-bloom, remains an unresolved problem. This research proposes the use of Inherent Optical Properties (IOPs) in optically complex waters to detect the bloom or non-bloom state of the phytoplankton community. An IOP index is calculated from the absorption coefficients of the colored dissolved organic matter (CDOM), the phytoplankton (phy) and the detritus (d), using the wavelength (lambda) 443 nm. The effectiveness of this index is tested in five bloom events in different places and with different characteristics from Mexican seas: 1. Dzilam (Caribbean Sea, Atlantic Ocean), a diatom bloom (Rhizosolenia hebetata); 2. Holbox (Caribbean Sea, Atlantic Ocean), a mixed bloom of dinoflagellates (Scrippsiella sp.) and diatoms (Chaetoceros sp.); 3. Campeche Bay in the Gulf of Mexico (Atlantic Ocean), a bloom of dinoflagellates (Karenia brevis); 4. Upper Gulf of California (UGC) (Pacific Ocean), a diatom bloom (Coscinodiscus and Pseudo-nitzschia) and 5. Todos Santos Bay, Ensenada (Pacific Ocean), a dinoflagellate bloom (Lingulodinium polyedrum). The diversity of sites show that the IOP index is a suitable method to determine the phytoplankton bloom conditions.CONACYT supported this research with a doctorate scholarship to Jesús A. Aguilar-Maldonado, with the announcement number 251025 in 2015. María-Teresa Sebastiá-Frasquet was a beneficiary of the BEST/2017/217 grant, supported by the Valencian Conselleria d Educació, Investigació, Cultura i Esport (Spain) during her stay at the Universidad Autónoma de Baja California (Mexico). Thanks are extended to the Strategic Action Program of the Gulf of Mexico Large Marine Ecosystem (GoM-LME), of the United Nations Industrial Development Organization (UNIDO).Aguilar-Maldonado, J.; Santamaría-Del-Ángel, E.; González-Silvera, A.; Cervantes-Rosas, OD.; López-Acuña, LM.; Gutiérrez-Magness, A.; Cerdeira, S.... (2018). Identification of Phytoplankton Blooms under the Index of Inherent Optical Properties (IOP Index) in Optically Complex Waters. Water. 10(2). https://doi.org/10.3390/w10020129S102Gower, J., King, S., Borstad, G., & Brown, L. (2005). Detection of intense plankton blooms using the 709 nm band of the MERIS imaging spectrometer. International Journal of Remote Sensing, 26(9), 2005-2012. doi:10.1080/01431160500075857Carstensen, J., & Conley, D. J. (2004). Frequency, composition, and causes of summer phytoplankton blooms in a shallow coastal ecosystem, the Kattegat. Limnology and Oceanography, 49(1), 191-201. doi:10.4319/lo.2004.49.1.0191Legendre, L. (1990). The significance of microalgal blooms for fisheries and for the export of particulate organic carbon in oceans. Journal of Plankton Research, 12(4), 681-699. doi:10.1093/plankt/12.4.681Ji, R., Edwards, M., Mackas, D. L., Runge, J. A., & Thomas, A. C. (2010). Marine plankton phenology and life history in a changing climate: current research and future directions. Journal of Plankton Research, 32(10), 1355-1368. doi:10.1093/plankt/fbq062Richardson, K. (1997). Harmful or Exceptional Phytoplankton Blooms in the Marine Ecosystem. Advances in Marine Biology Volume 31, 301-385. doi:10.1016/s0065-2881(08)60225-4Smayda, T. J. (1997). What is a bloom? A commentary. Limnology and Oceanography, 42(5part2), 1132-1136. doi:10.4319/lo.1997.42.5_part_2.1132Brody, S. R., Lozier, M. S., & Dunne, J. P. (2013). A comparison of methods to determine phytoplankton bloom initiation. Journal of Geophysical Research: Oceans, 118(5), 2345-2357. doi:10.1002/jgrc.20167Platt, T., Fuentes-Yaco, C., & Frank, K. T. (2003). Spring algal bloom and larval fish survival. Nature, 423(6938), 398-399. doi:10.1038/423398bSchneider, B., Kaitala, S., & Maunula, P. (2006). Identification and quantification of plankton bloom events in the Baltic Sea by continuous pCO2 and chlorophyll a measurements on a cargo ship. Journal of Marine Systems, 59(3-4), 238-248. doi:10.1016/j.jmarsys.2005.11.003Gittings, J. A., Raitsos, D. E., Racault, M.-F., Brewin, R. J. W., Pradhan, Y., Sathyendranath, S., & Platt, T. (2017). Seasonal phytoplankton blooms in the Gulf of Aden revealed by remote sensing. Remote Sensing of Environment, 189, 56-66. doi:10.1016/j.rse.2016.10.043Huppert, A., Blasius, B., & Stone, L. (2002). A Model of Phytoplankton Blooms. The American Naturalist, 159(2), 156-171. doi:10.1086/324789Fleming, V., & Kaitala, S. (2006). Phytoplankton Spring Bloom Intensity Index for the Baltic Sea Estimated for the years 1992 to 2004. Hydrobiologia, 554(1), 57-65. doi:10.1007/s10750-005-1006-7Carstensen, J., Henriksen, P., & Heiskanen, A.-S. (2007). Summer algal blooms in shallow estuaries: Definition, mechanisms, and link to eutrophication. Limnology and Oceanography, 52(1), 370-384. doi:10.4319/lo.2007.52.1.0370Cetinić, I., Perry, M. J., D’Asaro, E., Briggs, N., Poulton, N., Sieracki, M. E., & Lee, C. M. (2015). A simple optical index shows spatial and temporal heterogeneity in phytoplankton community composition during the 2008 North Atlantic Bloom Experiment. Biogeosciences, 12(7), 2179-2194. doi:10.5194/bg-12-2179-2015Alikas, K., Kangro, K., & Reinart, A. (2010). Detecting cyanobacterial blooms in large North European lakes using the Maximum Chlorophyll Index. OCEANOLOGIA, 52(2), 237-257. doi:10.5697/oc.52-2.237Platt, T., Sathyendranath, S., White, G. N., Fuentes-Yaco, C., Zhai, L., Devred, E., & Tang, C. (2009). Diagnostic Properties of Phytoplankton Time Series from Remote Sensing. Estuaries and Coasts, 33(2), 428-439. doi:10.1007/s12237-009-9161-0Cui, T., Cao, W., Zhang, J., Hao, Y., Yu, Y., Zu, T., & Wang, D. (2013). Diurnal variability of ocean optical properties during a coastal algal bloom: implications for ocean colour remote sensing. International Journal of Remote Sensing, 34(23), 8301-8318. doi:10.1080/01431161.2013.833356Loisel, H., Vantrepotte, V., Norkvist, K., Mériaux, X., Kheireddine, M., Ras, J., … Moutin, T. (2011). Characterization of the bio-optical anomaly and diurnal variability of particulate matter, as seen from scattering and backscattering coefficients, in ultra-oligotrophic eddies of the Mediterranean Sea. Biogeosciences, 8(11), 3295-3317. doi:10.5194/bg-8-3295-2011Mercado, J. M., Ramírez, T., Cortés, D., Sebastián, M., Reul, A., & Bautista, B. (2006). Diurnal changes in the bio-optical properties of the phytoplankton in the Alborán Sea (Mediterranean Sea). Estuarine, Coastal and Shelf Science, 69(3-4), 459-470. doi:10.1016/j.ecss.2006.05.019Hernández-Terrones, L., Rebolledo-Vieyra, M., Merino-Ibarra, M., Soto, M., Le-Cossec, A., & Monroy-Ríos, E. (2010). Groundwater Pollution in a Karstic Region (NE Yucatan): Baseline Nutrient Content and Flux to Coastal Ecosystems. Water, Air, & Soil Pollution, 218(1-4), 517-528. doi:10.1007/s11270-010-0664-xMoore, Y. H., Stoessell, R. K., & Easley, D. H. (1992). Fresh-Water/Sea-Water Relationship Within a Ground-Water Flow System, Northeastern Coast of the Yucatan Peninsula. Ground Water, 30(3), 343-350. doi:10.1111/j.1745-6584.1992.tb02002.xBeddows, P. A., Smart, P. L., Whitaker, F. F., & Smith, S. L. (2007). Decoupled fresh–saline groundwater circulation of a coastal carbonate aquifer: Spatial patterns of temperature and specific electrical conductivity. Journal of Hydrology, 346(1-2), 18-32. doi:10.1016/j.jhydrol.2007.08.013Hernández-Terrones, L. M., Null, K. A., Ortega-Camacho, D., & Paytan, A. (2015). Water quality assessment in the Mexican Caribbean: Impacts on the coastal ecosystem. Continental Shelf Research, 102, 62-72. doi:10.1016/j.csr.2015.04.015Merrell, W. J., & Morrison, J. M. (1981). On the circulation of the western Gulf of Mexico with observations from April 1978. Journal of Geophysical Research, 86(C5), 4181. doi:10.1029/jc086ic05p04181Carriquiry, J. D., & Sánchez, A. (1999). Sedimentation in the Colorado River delta and Upper Gulf of California after nearly a century of discharge loss. Marine Geology, 158(1-4), 125-145. doi:10.1016/s0025-3227(98)00189-3Brusca, R. C., Álvarez-Borrego, S., Hastings, P. A., & Findley, L. T. (2017). Colorado River flow and biological productivity in the Northern Gulf of California, Mexico. Earth-Science Reviews, 164, 1-30. doi:10.1016/j.earscirev.2016.10.012Daesslé, L. W., Orozco, A., Struck, U., Camacho-Ibar, V. F., van Geldern, R., Santamaría-del-Angel, E., & Barth, J. A. C. (2017). Sources and sinks of nutrients and organic carbon during the 2014 pulse flow of the Colorado River into Mexico. Ecological Engineering, 106, 799-808. doi:10.1016/j.ecoleng.2016.02.018Orozco-Durán, A., Daesslé, L. W., Camacho-Ibar, V. F., Ortiz-Campos, E., & Barth, J. A. C. (2015). Turnover and release of P-, N-, Si-nutrients in the Mexicali Valley (Mexico): Interactions between the lower Colorado River and adjacent ground- and surface water systems. Science of The Total Environment, 512-513, 185-193. doi:10.1016/j.scitotenv.2015.01.016Aguilar-Maldonado, J. A., Santamaría-del-Ángel, E., & Sebastiá-Frasquet, M. T. (2017). Reflectances of SPOT multispectral images associated with the turbidity of the Upper Gulf of California. Revista de Teledetección, (50), 1. doi:10.4995/raet.2017.7795Cepeda-Morales, J. (2017). Response of primary producers to the hydrographic variability in the southern region of the California Current System. Ciencias Marinas, 40(2), 123-135. doi:10.7773/cm.v43i2.2752Delgadillo-Hinojosa, F., Camacho-Ibar, V., Huerta-Díaz, M. A., Torres-Delgado, V., Pérez-Brunius, P., Lares, L., … Castro, R. (2015). Seasonal behavior of dissolved cadmium and Cd/PO4 ratio in Todos Santos Bay: A retention site of upwelled waters in the Baja California peninsula, Mexico. Marine Chemistry, 168, 37-48. doi:10.1016/j.marchem.2014.10.010Durazo, R. (2005). Oceanographic conditions west of the Baja California coast, 2002?2003: A weak El Niño and subarctic water enhancement. Ciencias Marinas, 31(3), 537-552. doi:10.7773/cm.v31i3.43Linacre, L., Durazo, R., Hernández-Ayón, J. M., Delgadillo-Hinojosa, F., Cervantes-Díaz, G., Lara-Lara, J. R., … Bazán-Guzmán, C. (2010). Temporal variability of the physical and chemical water characteristics at a coastal monitoring observatory: Station ENSENADA. Continental Shelf Research, 30(16), 1730-1742. doi:10.1016/j.csr.2010.07.011Espinosa-Carreón, T. L., Gaxiola-Castro, G., Durazo, R., De la Cruz-Orozco, M. E., Norzagaray-Campos, M., & Solana-Arellano, E. (2015). Influence of anomalous subarctic water intrusion on phytoplankton production off Baja California. Continental Shelf Research, 92, 108-121. doi:10.1016/j.csr.2014.10.003Gutierrez-Mejia, E., Lares, M. L., Huerta-Diaz, M. A., & Delgadillo-Hinojosa, F. (2016). Cadmium and phosphate variability during algal blooms of the dinoflagellate Lingulodinium polyedrum in Todos Santos Bay, Baja California, Mexico. Science of The Total Environment, 541, 865-876. doi:10.1016/j.scitotenv.2015.09.081Santamaría-del-Ángel, E., Millán-Núñez, R., González-Silvera, A., Callejas-Jiménez, M., Cajal-Medrano, R., & Galindo-Bect, M. S. (2010). The response of shrimp fisheries to climate variability off Baja California, México. ICES Journal of Marine Science, 68(4), 766-772. doi:10.1093/icesjms/fsq186Hirata, T., Aiken, J., Hardman-Mountford, N., Smyth, T. J., & Barlow, R. G. (2008). An absorption model to determine phytoplankton size classes from satellite ocean colour. Remote Sensing of Environment, 112(6), 3153-3159. doi:10.1016/j.rse.2008.03.011Aiken, J., Hardman-Mountford, N. J., Barlow, R., Fishwick, J., Hirata, T., & Smyth, T. (2007). Functional links between bioenergetics and bio-optical traits of phytoplankton taxonomic groups: an overarching hypothesis with applications for ocean colour remote sensing. Journal of Plankton Research, 30(2), 165-181. doi:10.1093/plankt/fbm098Stuart, V., Sathyendranath, S., Platt, T., Maass, H., & Irwin, B. D. (1998). Pigments and species composition of natural phytoplankton populations: effect on the absorption spectra. Journal of Plankton Research, 20(2), 187-217. doi:10.1093/plankt/20.2.187Lohrenz, S. E. (2003). Phytoplankton spectral absorption as influenced by community size structure and pigment composition. Journal of Plankton Research, 25(1), 35-61. doi:10.1093/plankt/25.1.35Wu, J., Hong, H., Shang, S., Dai, M., & Lee, Z. (2007). Variation of phytoplankton absorption coefficients in the northern South China Sea during spring and autumn. Biogeosciences Discussions, 4(3), 1555-1584. doi:10.5194/bgd-4-1555-2007Millán-Núñez, E., & Millán-Núñez, R. (2010). Specific absorption coefficient and phytoplankton community structure in the southern region of the California Current during January 2002. Journal of Oceanography, 66(5), 719-730. doi:10.1007/s10872-010-0059-zHaywood, A. J., Steidinger, K. A., Truby, E. W., Bergquist, P. R., Bergquist, P. L., Adamson, J., & Mackenzie, L. (2004). COMPARATIVE MORPHOLOGY AND MOLECULAR PHYLOGENETIC ANALYSIS OF THREE NEW SPECIES OF THE GENUS KARENIA (DINOPHYCEAE) FROM NEW ZEALAND1. Journal of Phycology, 40(1), 165-179. doi:10.1111/j.0022-3646.2004.02-149.xQuijano-Scheggia, S. (2016). The inhibitory effect of a non-yessotoxin-producing dinoflagellate, Lingulodinium polyedrum (Stein) Dodge, towards Vibrio vulnificus and Staphylococcus aureus. Revista de Biología Tropical, 64(2), 805. doi:10.15517/rbt.v64i2.19320Holm-Hansen, O., & Riemann, B. (1978). Chlorophyll a Determination: Improvements in Methodology. Oikos, 30(3), 438. doi:10.2307/3543338Aguilar-Trujillo, A. C., Okolodkov, Y. B., Herrera-Silveira, J. A., Merino-Virgilio, F. del C., & Galicia-García, C. (2017). Taxocoenosis of epibenthic dinoflagellates in the coastal waters of the northern Yucatan Peninsula before and after the harmful algal bloom event in 2011–2012. Marine Pollution Bulletin, 119(1), 396-406. doi:10.1016/j.marpolbul.2017.02.074Ulloa, M. J., Álvarez-Torres, P., Horak-Romo, K. P., & Ortega-Izaguirre, R. (2017). Harmful algal blooms and eutrophication along the mexican coast of the Gulf of Mexico large marine ecosystem. Environmental Development, 22, 120-128. doi:10.1016/j.envdev.2016.10.007Liefer, J. D., Robertson, A., MacIntyre, H. L., Smith, W. L., & Dorsey, C. P. (2013). Characterization of a toxic Pseudo-nitzschia spp. bloom in the Northern Gulf of Mexico associated with domoic acid accumulation in fish. Harmful Algae, 26, 20-32. doi:10.1016/j.hal.2013.03.002Schnetzer, A., Miller, P. E., Schaffner, R. A., Stauffer, B. A., Jones, B. H., Weisberg, S. B., … Caron, D. A. (2007). Blooms of Pseudo-nitzschia and domoic acid in the San Pedro Channel and Los Angeles harbor areas of the Southern California Bight, 2003–2004. Harmful Algae, 6(3), 372-387. doi:10.1016/j.hal.2006.11.004Peña Manjarrez, J. (2009). Environmental factors influencing the variability of Lingulodinium polyedrum and Scrippsiella trochoidea (Dinophyceae) cyst production. Ciencias Marinas, 35(1), 1-14. doi:10.7773/cm.v35i1.1406Ruiz-de la Torre, M. C., Maske, H., Ochoa, J., & Almeda-Jauregui, Cã©. O. (2013). Correction: Maintenance of Coastal Surface Blooms by Surface Temperature Stratification and Wind Drift. PLoS ONE, 8(6). doi:10.1371/annotation/a2f49bbd-e226-4a15-900a-5946cff07d75Kudela, R. M., Bickel, A., Carter, M. L., Howard, M. D. A., & Rosenfeld, L. (2015). The Monitoring of Harmful Algal Blooms through Ocean Observing. Coastal Ocean Observing Systems, 58-75. doi:10.1016/b978-0-12-802022-7.00005-

Interannual Climate Variability in the West Antarctic Peninsula under Austral Summer Conditions

[EN] This study aimed to describe the interannual climate variability in the West Antarctic Peninsula (WAP) under austral summer conditions. Time series of January sea-surface temperature (SST) at 1 km spatial resolution from satellite-based multi-sensor data from Moderate Resolution Imaging Spectrometer (MODIS) Terra, MODIS Aqua, and Visible Infrared Imager Radiometer Suite (VIIRS) were compiled between 2001 and 2020 at localities near the Gerlache Strait and the Carlini, Palmer, and Rothera research stations. The results revealed a well-marked spatial-temporal variability in SST at the WAP, with a one-year warm episode followed by a five-year cold episode. Warm waters (SST > 0 degrees C) reach the coast during warm episodes but remain far from the shore during cold episodes. This behavior of warm waters may be related to the regional variability of the Antarctic Circumpolar Current, particularly when the South Polar Front (carrying warm waters) reaches the WAP coast. The WAP can be divided into two zones representing two distinct ecoregions: the northern zone (including the Carlini and Gerlache stations) corresponds to the South Shetland Islands ecoregion, and the southern zone (including the Palmer and Rothera stations) corresponds to the Antarctic Peninsula ecoregion. The Gerlache Strait is likely situated on the border between the two ecoregions but under a greater influence of the northern zone. Our data showed that the Southern Annular Mode (SAM) is the primary driver of SST variability, while the El Nino Southern Oscillation (ENSO) plays a secondary role. However, further studies are needed to better understand regional climate variability in the WAP and its relation with SAM and ENSO; such studies should use an index that adequately describes the ENSO in these latitudes and addresses the limitations of the databases used for this purpose. Multi-sensor data are useful in describing the complex climate variability resulting from the combination of local and regional processes that elicit different responses across the WAP. It is also essential to continue improving SST approximations at high latitudes.This work was supported by the Universidad Autónoma de Baja California, AmeriGEOSS, and the CONACYT's project number CB-2012-01/179753.Santamaría-Del-Ángel, E.; Cañón-Páez, M.; Sebastiá-Frasquet, M.; González-Silvera, A.; Gutiérrez, A.; Aguilar-Maldonado, JA.; López-Calderón, J.... (2021). Interannual Climate Variability in the West Antarctic Peninsula under Austral Summer Conditions. Remote Sensing. 13(6). https://doi.org/10.3390/rs1306112213

The Effect of Cold and Warm Anomalies on Phytoplankton Pigment Composition in Waters off the Northern Baja California Peninsula (México): 2007–2016

In this study, we report the response of phytoplankton community composition to cold and warm interannual events affecting the waters off the Baja California Peninsula from 2007 to 2016 based on data obtained from a single marine station (31.75° N/116.96° W). Included variables were satellite chlorophyll a, sea surface temperature (MODIS/Aqua), upwelling intensity, and field data (phytoplankton pigments, inorganic nutrients, light penetration). Phytoplankton pigments were determined by high performance liquid chromatography, and CHEMTAX software was used to determine the relative contributions of the main taxonomic groups to chlorophyll a. Our results confirm the decrease in phytoplankton biomass due to the influence of the recent Pacific Warm Anomaly (2014) and El Niño 2015–2016. However, this decrease was especially marked at the surface. When data from the entire water column was considered, this decrease was not significant, because at the subsurface Chla did not decrease as much. Nevertheless, significant changes in community composition occurred in the entire water column with Cyanobacteria (including Prochlorococcus) and Prymnesiophytes being dominant at the surface, while Chlorophytes and Prasinophytes made a strong contribution at the subsurface. Analysis of the spatial distribution of SST and satellite chlorophyll a made it possible to infer the spatial extension of these anomalies at a regional scale

Evaluation of Semi-Analytical Algorithms to Retrieve Particulate and Dissolved Absorption Coefficients in Gulf of California Optically Complex Waters

Two semi-analytical algorithms, Generalized Inherent Optical Property (GIOP) and Garver-Siegel-Maritorena (GSM), were evaluated in terms of how well they reproduced the absorption coefficient of phytoplankton (aph(λ)) and dissolved and detrital organic matter (adg(λ)) at three wavelengths (λ of 412, 443, and 488 nm) in a zone with optically complex waters, the Upper Gulf of California (UGC) and the Northern Gulf of California (NGC). In the UGC, detritus determines most of the total light absorption, whereas, in the NGC, chromophoric dissolved organic material (CDOM) and phytoplankton dominate. Upon comparing the results of each model with a database assembled from four cruises done from spring to summer (March through September) between 2011 and 2013, it was found that GIOP is a better estimator for aph(λ) than GSM, independently of the region. However, both algorithms underestimate in situ values in the NGC, whereas they overestimate them in the UGC. Errors are associated with the following: (a) the constant a*ph(λ) value used by GSM and GIOP (0.055 m2 mgChla−1) is higher than the most frequent value observed in this study’s data (0.03 m2 mgChla−1), and (b) satellite-derived chlorophyll a concentration (Chla) is biased high compared with in situ Chla. GIOP gave also better results for the adg(λ) estimation than GSM, especially in the NGC. The spectral slope Sdg was identified as an important parameter for estimating adg(λ), and this study’s results indicated that the use of a fixed input value in models was not adequate. The evaluation confirms the lack of generality of algorithms like GIOP and GSM, whose reflectance model is too simplified to capture expected variability. Finally, a greater monitoring effort is suggested in the study area regarding the collection of in situ reflectance data, which would allow explaining the effects that detritus and CDOM may have on the semi-analytical reflectance inversions, as well as isolating the possible influence of the atmosphere on the satellite-derived water reflectance and Chla

Estructura de la comunidad fitoplanctónica en la Laguna Ojo de Liebre (B.C.S.) en febrero 2018

El propósito de este estudio fue caracterizar a la comunidad del fitoplancton en Laguna Ojo de Liebre, un sitio de gran importancia para la biodiversidad de la Reserva de la Biosfera El Vizcaíno. Utilizamos como parámetros la diversidad, abundancia y dominancia de los principales grupos del fitoplancton (microalgas) y las relacionamos con las variables hidrográficas temperatura y salinidad. Se utilizaron los análisis por microscopía óptica y cromatografía HPLC para cuantificar al fitoplancton en tres grupos de tamaño: microfitoplancton (diatomeas, dinoflagelados), nanofitoplancton (Chromophytas, Cryptophytas) y picofitoplancton (Cyanobacterias, Prochlorophytas). El análisis por HPLC mostró resultados similares al análisis por microscopía, en donde la fucoxantina (pigmento característico del grupo de las diatomeas) fue el carotenoide fotosintético más abundante y predominante en toda la laguna. En cuanto a la temperatura se observó una relación inversa con el microfitoplancton y una relación directa con el nanofitoplancton y el picofitoplancton

Use of Digital Images as a Low-Cost System to Estimate Surface Optical Parameters in the Ocean

[EN] Ocean color is the result of absorption and scattering, as light interacts with the water and the optically active constituents. The measurement of ocean color changes enables monitoring of these constituents (dissolved or particulate materials). The main objective of this research is to use digital images to estimate the light attenuation coefficient (Kd ), the Secchi disk depth (ZSD ), and the chlorophyll a (Chla) concentration and to optically classify plots of seawater using the criteria proposed by Jerlov and Forel using digital images captured at the ocean surface. The database used in this study was obtained from seven oceanographic cruises performed in oceanic and coastal areas. Three approaches were developed for each parameter: a general approach that can be applied under any optical condition, one for oceanic conditions, and another for coastal conditions. The results of the coastal approach showed higher correlations between the modeled and validation data, with rp values of 0.80 for Kd , 0.90 for ZSD , 0.85 for Chla, 0.73 for Jerlov, and 0.95 for Forel¿Ule. The oceanic approach failed to detect significant changes in a digital photograph. The most precise results were obtained when images were captured at 45° (n = 22; Fr cal=11.02>Fr crit=5.99 ). Therefore, to ensure precise results, the angle of photography is key. This methodology can be used in citizen science programs to estimate ZSD, Kd, and the Jerlov scale.The authors wish to thank Consejo Nacional de Ciencia y Tecnología (CONACyT) for the grant awarded to the first author for her studies. The authors also thank the SIMBIOS NASA Program, Universidad Autónoma de Baja California, Instituto de Investigaciones Oceanológicas, Centro de Investigación Científica y de Educación Superior de Ensenada, Secretaría de Marina Armada de México, Dirección General Adjunta de Oceanografía, Hidrografía y Meteorología, Instituto Politécnico Nacional. Maria Elena Sánchez-Salazar translated the manuscript into English.Castillo-Ramírez, A.; Santamaría-Del-Ángel, E.; González-Silvera, A.; Aguilar-Maldonado, JA.; Lopez Calderon, J.; Sebastiá-Frasquet, M. (2023). Use of Digital Images as a Low-Cost System to Estimate Surface Optical Parameters in the Ocean. Sensors. 23(6). https://doi.org/10.3390/s23063199319923

Identification of Phytoplankton Blooms under the Index of Inherent Optical Properties (IOP Index)

Phytoplankton blooms are sporadic events in time and isolated in space. This complex phenomenon is produced by a variety of both natural and anthropogenic causes. Early detection of this phenomenon, as well as the classification of a water body under conditions of bloom or non-bloom, remains an unresolved problem. This research proposes the use of Inherent Optical Properties (IOPs) in optically complex waters to detect the bloom or non-bloom state of the phytoplankton community. An IOP index is calculated from the absorption coefficients of the colored dissolved organic matter (CDOM), the phytoplankton (φ) and the detritus (d), using the wavelength (λ) 443 nm. The effectiveness of this index is tested in five bloom events in different places and with different characteristics from Mexican seas: (1) Dzilam (Caribbean Sea, Atlantic Ocean) a diatom bloom (Rhizosolenia hebetata); (2) Holbox (Caribbean Sea, Atlantic Ocean) a mixed bloom of dinoflagellates (Scrippsiella sp.) and diatoms (Chaetoceros sp.); (3) Campeche Bay in the Gulf of Mexico (Atlantic Ocean) a bloom of dinoflagellates (Karenia brevis); (4) Upper Gulf of California (UGC) (Pacific Ocean) a diatoms bloom (Planktoniella sol) and (5) Todos Santos Bay, Ensenada (Pacific Ocean) a dinoflagellates bloom (Lingulodinium polyedrum). The diversity of sites shows that the IOP index is a suitable method to determine the bloom conditions

A New Algorithm to Estimate Diffuse Attenuation Coefficient from Secchi Disk Depth

The vertical diffuse attenuation coefficient Kd (PAR) is used for calculating the euphotic zone, the first optical depth that is important for primary productivity models. Currently, Kd (PAR) can be estimated using an irradiometer or a Secchi disk (SD). The main objective of this work is to define a model that can be applied to a wide range of optical marine conditions to estimate Kd (PAR) by SD. We used irradiance profiles and SD depth (ZSD) from 679 stations in various marine regions. Three parametric models were developed, and their statistical performance was evaluated in view of previous approaches reported and remote sensing data. The best results were obtained with an adaptive model representing three cases: clear-water, turbid-water, and a transition zone (R2 = 0.965, MAE = 0.083, RMSD = 0.239, BIAS = 0.01, and MPI = 0.854). Previous models considering a single optical depth figure at which the SD disappears did not capture the marine optical complexity. Our classification of 113 stations with spectral absorption data into Jerlov water types indicated that no unique correspondence existed between estimated Kd (PAR) and water type, making it ambiguous to associate compatible inherent optical properties and chlorophyll with ZSD. Although obtaining Kd (PAR) from ZSD is simple/low-cost, care should be taken in the methodology used to measure ZSD to ensure consistent results across different optical marine conditions