Idiosyncratic phenology of greenhouse gas emissions in a Mediterranean reservoir
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Extreme hydrological and thermal regimes characterize the Mediterranean biome and can significantly impact 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 rise of water temperature and gross primary production and the drop in reservoir mean depth. N2O emissions mirrored CH4's seasonal trend, significantly correlating to water temperature, wind speed, and net 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 calcite formation coupled to photosynthesis. This investigation highlights the need to integrate these idiosyncratic p..., This study was conducted at the eutrophic Cubillas reservoir in southern Spain, from March 2021 to July 2022. It focused on weekly monitoring of CO2, CH4, and N2O emissions, capturing both diffusive and ebullitive fluxes. Measurements of these greenhouse gases were taken at the reservoir's surface using a Cavity Ring-Down Spectrometer (PICARRO G2508) connected to a floating chamber, with 4 to 6 readings recorded daily during daylight hours. In addition to greenhouse gas monitoring, the study also involved assessing environmental and biological factors that influence the seasonal patterns of these gases. This included measuring water temperature, oxygen concentration, depth, and wind speed. Furthermore, nitrate levels, Gross Primary Production (GPP), respiration (Res), and Net Ecosystem Production (NEP) were also systematically measured and analyzed. Finally, a multiple mixed linear model approach was employed to identify the primary drivers of greenhouse gas (GHG) emissions., , # Idiosyncratic phenology of greenhouse gas emissions in a Mediterranean reservoir [https://doi.org/10.5061/dryad.cnp5hqcbz](https://doi.org/10.5061/dryad.cnp5hqcbz) Contains 5 files: **(1) analysis.r -** R script to replicates analyses and the figures in the paper and Supplementary Material: **(2) flux_calculations.r** - R script to determine CO2, CH4 and N2O fluxes from floating chamber data. **(3) Datasets** (3 in total): **(3.1). clean_data.txt**: Comprises the analyzed dataset to reproduce figures and models from the manuscript.         Columns:                  date_time: date and time (year-month-day hour:min: sec)                  rep: sample replicate                  flux_N2O: Nitrous oxide flux (ug N / m2 day)                  flux_CO2: Carbon dioxide flux (mg C / m2 day)                  flux_CH4_diffusive: Methane diffusive flux (mg C / m2 day)                  flux_CH4_ebullitive: Methane ebullitive flux (mg C / m2 day)                  flux_CH4_tota...
地中海生物群系以极端水文与热况为特征，可显著影响水库温室气体（greenhouse gas, GHG）排放的物候特征。本研究针对西班牙一处浅富营养化硬水水库的温室气体排放季节变化展开调查。我们观测到不同气体各有独特的季节变化模式：甲烷（CH₄）排放在水体分层期显著升高，主要受水温上升、总初级生产力提升以及水库平均水深下降的调控。氧化亚氮（N₂O）的季节变化趋势与甲烷高度一致，且与水温、风速及净初级生产力（net primary production）显著相关。与之相反，二氧化碳（CO₂）排放在水体分层期有所降低，且与水温呈二次而非线性关系——这与甲烷、氧化亚氮的排放模式存在意外偏差，该现象可能与光合作用耦联的方解石形成有关。本研究凸显了整合这些独特的……，本研究于2021年3月至2022年7月在西班牙南部富营养化的库维利亚斯（Cubillas）水库开展，重点针对二氧化碳、甲烷与氧化亚氮排放进行每周监测，同步捕获扩散通量与冒泡（ebullitive）通量。研究采用连接漂浮箱的腔环衰减光谱仪（Cavity Ring-Down Spectrometer, PICARRO G2508）在水库表面开展温室气体测量，日间每日记录4至6组读数。除温室气体监测外，本研究还评估了影响这些气体季节变化模式的环境与生物因子，包括水温、溶解氧浓度、水深与风速。此外，硝酸盐水平、总初级生产力（Gross Primary Production, GPP）、呼吸作用（Respiration, Res）以及净生态系统生产力（Net Ecosystem Production, NEP）也得到了系统测定与分析。最终本研究采用多元混合线性模型方法，以识别温室气体排放的主要驱动因子。 # 地中海水库温室气体排放的独特物候特征 [https://doi.org/10.5061/dryad.cnp5hqcbz](https://doi.org/10.5061/dryad.cnp5hqcbz) 本数据集包含5个文件： **(1) analysis.r**：用于复现论文及补充材料中分析过程与图表的R脚本 **(2) flux_calculations.r**：用于基于漂浮箱数据计算CO₂、CH₄与N₂O通量的R脚本 **(3) 数据集（共3个）**： **(3.1) clean_data.txt**：包含用于复现论文图表与模型的已清洗数据集。 字段说明： date_time：日期与时间（年-月-日 时:分:秒） rep：样本重复次数 flux_N2O：氧化亚氮通量（μg N / m²·d） flux_CO2：二氧化碳通量（mg C / m²·d） flux_CH4_diffusive：甲烷扩散通量（mg C / m²·d） flux_CH4_ebullitive：甲烷冒泡通量（mg C / m²·d） flux_CH4_tota...
