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

Recombinant nodavirus vaccine produced in bacteria and administered without purification elicits humoral immunity and protects European sea bass against infection

Viral necrosis virus (NNV) or nodavirus causes fish viral encephalopathy and retinopathy worldwide. In some cases, mortalities in aquaculture industry can reach up to 100%, some species being especially sensitive as is the case of European sea bass (Dicentrarchus labrax), one of the main cultured species in the Mediterranean, with the consequent economical loses. Development of new vaccines against NNV is in the spotlight though few re- searches have focused in European sea bass. In this study we have generated a recombinant NNV (rNNV) vaccine produced in Escherichia coli expressing the capsid protein and administered it to European sea bass juveniles by two different routes (intraperitoneal and oral). The last being considered non-stressful and desired for fish farming of small fish, which in fact are the most affected by NNV. Oral vaccine was composed of feed pellets containing the recombinant whole bacteria, and injected vaccine was composed of recombinant bacteria pre- viously lysed. Our results revealed production of specific anti-NNV IgM following the two vaccination proce- dures, levels that were further increased in orally-vaccinated group after challenge with NNV. Genes related to interferon (IFN), T-cell and immunoglobulin markers were scarcely regulated in head-kidney (HK), gut or brain. Vaccination by either route elicited a relative survival response of 100% after NNV challenge. To our knowledge, this is the first report of a recombinant vaccine followed by no purification steps which resulted in a complete protection in European sea bass when challenged with NNV.Versión del edito

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-

Environmental regulation of carbon isotope composition and crassulacean acid metabolism in three plant communities along a water availability gradient

Expression of crassulacean acid metabolism (CAM) is characterized by extreme variability within and between taxa and its sensitivity to environmental variation. In this study, we determined seasonal fluctuations in CAM photosynthesis with measurements of nocturnal tissue acidification and carbon isotopic composition (δ13C) of bulk tissue and extracted sugars in three plant communities along a precipitation gradient (500, 700, and 1,000 mm year−1) on the Yucatan Peninsula. We also related the degree of CAM to light habitat and relative abundance of species in the three sites. For all species, the greatest tissue acid accumulation occurred during the rainy season. In the 500 mm site, tissue acidification was greater for the species growing at 30% of daily total photon flux density (PFD) than species growing at 80% PFD. Whereas in the two wetter sites, the species growing at 80% total PFD had greater tissue acidification. All species had values of bulk tissue δ13C less negative than −20‰, indicating strong CAM activity. The bulk tissue δ13C values in plants from the 500 mm site were 2‰ less negative than in plants from the wetter sites, and the only species growing in the three communities, Acanthocereus tetragonus (Cactaceae), showed a significant negative relationship between both bulk tissue and sugar δ13C values and annual rainfall, consistent with greater CO2 assimilation through the CAM pathway with decreasing water availability. Overall, variation in the use of CAM photosynthesis was related to water and light availability and CAM appeared to be more ecologically important in the tropical dry forests than in the coastal dune

International nosocomial infection control consortium (INICC) report, data summary of 36 countries, for 2004-2009

The results of a surveillance study conducted by the International Nosocomial Infection Control Consortium (INICC) from January 2004 through December 2009 in 422 intensive care units (ICUs) of 36 countries in Latin America, Asia, Africa, and Europe are reported. During the 6-year study period, using Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN; formerly the National Nosocomial Infection Surveillance system [NNIS]) definitions for device-associated health care-associated infections, we gathered prospective data from 313,008 patients hospitalized in the consortium's ICUs for an aggregate of 2,194,897 ICU bed-days. Despite the fact that the use of devices in the developing countries' ICUs was remarkably similar to that reported in US ICUs in the CDC's NHSN, rates of device-associated nosocomial infection were significantly higher in the ICUs of the INICC hospitals; the pooled rate of central line-associated bloodstream infection in the INICC ICUs of 6.8 per 1,000 central line-days was more than 3-fold higher than the 2.0 per 1,000 central line-days reported in comparable US ICUs. The overall rate of ventilator-associated pneumonia also was far higher (15.8 vs 3.3 per 1,000 ventilator-days), as was the rate of catheter-associated urinary tract infection (6.3 vs. 3.3 per 1,000 catheter-days). Notably, the frequencies of resistance of Pseudomonas aeruginosa isolates to imipenem (47.2% vs 23.0%), Klebsiella pneumoniae isolates to ceftazidime (76.3% vs 27.1%), Escherichia coli isolates to ceftazidime (66.7% vs 8.1%), Staphylococcus aureus isolates to methicillin (84.4% vs 56.8%), were also higher in the consortium's ICUs, and the crude unadjusted excess mortalities of device-related infections ranged from 7.3% (for catheter-associated urinary tract infection) to 15.2% (for ventilator-associated pneumonia). Copyright © 2012 by the Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved

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