Hydrological, physicochemical, and microbial characterization of the Mar Menor lagoon and its groundwater sources - General dataset [Dataset]
2025
Rodríguez-Puig, Júlia | Romano Gude, Daniel | Rodellas, Valentí | Ruiz-González, Clara | Bravo, Andrea G. | García-Orellana, Jordi | Alorda-Montiel, Irene | Diego-Feliu, Marc | Alorda-Kleinglass, Aaron | Dordal Soriano, Júlia | Gilabert, Javier | Manzano Arellano, Marisol | Lavergne, Céline | Montero Curiel, María | Romera-Castillo, Cristina | Ministerio de Ciencia, Innovación y Universidades (España) | Agencia Estatal de Investigación (España) | Ministerio de Ciencia e Innovación (España) | Rodellas, Valentí | Alorda-Montiel, Irene; Diego-Feliu, Marc; Alorda-Kleinglass, Aaron; Dordal Soriano, Júlia | Rodríguez-Puig, Júlia; Ruiz-González, Clara | Gilabert, Javier; Manzano Arellano, Marisol | Lavergne, Céline; Montero Curiel, María; Romera-Castillo, Cristina
First release of the Mar Menor SGD general dataset. This dataset contains detailed information on groundwater and lagoon water collected in the Mar Menor coastal lagoon (SE Spain) from March 2021 to May 2022. This dataset contains detailed information on stream water, groundwater, lagoon water, and soils collected in the Mar Menor coastal lagoon (SE Spain) from March 2021 to May 2022. The data includes physicochemical parameters (e.g., temperature, salinity, pH, dissolved oxygen), radionuclide activities (e.g., Ra-223, Ra-224, Ra-226, Ra-228), dissolved nutrient concentrations (NO3-, NO2-, NH4+, Si(OH)4, PO43-, TDN), dissolved organic carbon concentrations (DOC), microbial parameters (e.g., total bacterial abundance, HNA fraction, 3H-leucine incorporation rates), and mercury chemical species (total dissolved mercury and dissolved methylmercury). This dataset was used to estimate the magnitude of different SGD pathways, including pollutant fluxes to the lagoon, and interpret their impact on microbial communities
Показать больше [+] Меньше [-]J. Rodriguez-Puig acknowledges financial support from FPU grant FPU20/01369, and the institutional support of the María de Maeztu Programme (CEX2019-000940-M) for Units of Excellence of the Spanish Ministry of Science and Innovation. M. Montero-Curiel acknowledges the funding from the FPI grant (PRE2020-096147), with the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S-20-5). D. Romano-Gude acknowledges the funding from the FPI grant (PRE2020-095468), with the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S-20-2). [...] This work acknowledges the Severo Ochoa Centre of Excellence accreditation (CEX2024-001494-S) funded by AEI 10.13039/501100011033
Показать больше [+] Меньше [-]Peer reviewed
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