Idiosyncratic phenology of greenhouse gas emissions in a Mediterranean reservoir
Metadatos
Mostrar el registro completo del ítemAutor
Rodríguez Velasco, Eva; Peralta Maraver, Ignacio Fernando; Martínez García, Andrés; García Alguacil, Miriam; Picazo Mota, Félix; J. Gonçalves, Rodrigo; L. Ramón, Cintia; Morales Baquero, Rafael; J. Rueda, Francisco; Reche Cañabate, IsabelEditorial
ASLO
Fecha
2024-06-05Referencia bibliográfica
Rodríguez Velasco, E. et. al. Limnol. Oceanogr. Lett, 9: 364-375. [https://doi.org/10.1002/lol2.10409]
Patrocinador
PID2022.1378650B.100 funded by MICIU/AEI/10.13039/501100011033/ and by ERDF, EU. ER-V and AM-G were supported by Ph.D; FPU 19/02161 and FPU20/05804 respectively from the Spanish Ministry of Science, Innovation, and Universities; IP-M and FP are PAIDI postdoctoral fellows funded by Junta de Andalucía; Next Generation European Union funds; Projects CRONOS (RTI2018-098849-B-I00); ANTICIPA (PID2022- 137865OB-I00) of Spanish Ministry of Science, Innovation, and Universities to IR and FJR.” has been replaced with "The grant PID2022.1378650B.100Resumen
Extreme hydrological and thermal regimes characterize the Mediterranean zone and can influence the phenology of greenhouse gas (GHG) emissions in reservoirs. Our study examined the seasonal changes in GHG emissions of a shallow, eutrophic, hardwater reservoir in Spain. We observed distinctive seasonal patterns for each gas. CH4 emissions substantially increased during stratification, influenced predominantly by the increase in water temperature, net ecosystem production, and the decline in reservoir mean depth. N2O emissions mirrored CH4's seasonal trend, significantly correlating to water temperature, wind speed, and gross primary production. Conversely, CO2 emissions decreased during stratification and displayed a quadratic, rather than a linear relationship with water temperature—an unexpected deviation from CH4 and N2O emission patterns—likely associated with photosynthetic uptake of bicarbonate and formation of intracellular calcite that might be exported to sediments. This investigation highlights the imperative of integrating these idiosyncratic patterns into GHG emissions models, enhancing their predictive power.





