• Energy Research

# 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_total: Total methane flux (mg C / m2 day) water_level: water level in m wind_speed: wind speed in m /s ta: water temperature in celsius degree GPPC: Gross primary production in mg C / L day NPPC: Net primary production in mg C / L day CO2eq: Radiative forcing in carbon dioxide equivalents date: date in year-month-day **(3.2). Fluxlat.xlsx:** Dataset with fluxes from the literature at a global scale including data from this study. Dataset contains 4 sheets, 3 for each gas, and a forth one including the units. Columns: lat: latitude (degree) lon: longitude (degree) min: minimum flux value reported (see gases units below) max: maximum flux value reported (see gases units below) Reference: reference from where fluxes were obtained sheet CO2: Carbon dioxide flux (mg C / m2 day) sheet CH4_diffusive: Methane diffusive flux (mg C / m2 day) sheet N2O: Nitrous oxide flux (ug N / m2 day) **(3.3). fluxes_example.xlsx:** Example dataset for calculating GHG fluxes using the R code “flux_calculations.r”. Dataset contain 3 sheets, including raw data for fluxes, environmental data and the units. Columns: Date: date (d-m-y) time: time in seconds (one measurement per second) rep: replicate N2O_dry: Nitrous oxide in ppm CO2_dry: Carbon dioxide in ppm CH4_dry: Methane in ppm V: Volume of the floating chamber (m3) A: Area of the floating chamber (m2) P: Atmospheric pressure (Pa) R: Universal gas constant (m3 Pa / K mol) T: Temperature (Kelvin degree) 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 patterns into GHG emissions models, enhancing the prediction of global GHG emissions in the global change era. 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.

Abstract Litter breakdown in the streambed is an important pathway in organic carbon cycling and energy transfer in the biosphere that is mediated by a wide range of streambed organisms. However, most research on litter breakdown to date has focused on a small fraction of the taxa that drive it (e.g. microbial vs. macroinvertebrate‐mediated breakdown) and has been limited to the benthic zone (BZ). Despite the importance of the hyporheic zone (HZ) as a bioreactor, little is known about what, or who, mediates litter breakdown in this compartment and whether breakdown rates differ between the BZ and HZ. Here, we explore the relationship between litter breakdown and the variation in community structure of benthic and hyporheic communities by deploying two standardized bioassays (cotton strips and two types of commercially available tea bags) in 30 UK streams that encompass a range of environmental conditions. Then, we modelled these assays as a response of the streambed compartment and the biological features of the streambed assemblage (Prokaryota, Protozoa and Eumetazoa invertebrates) to understand the generality and efficiency of litter processing across communities. Litter breakdown was much faster in the BZ compared with the HZ (around 5 times higher for cotton strips and 1.5 times faster for the tea leaves). However, differences in litter breakdown between the BZ and the HZ were mediated by the biological features of the benthos and the hyporheos. Biomass of all the studied biotic groups, α‐diversity of Eumetazoa invertebrates and metabolic diversity of Prokaryota were important predictors that were positively related to breakdown coefficients demonstrating their importance in the functioning of the streambed ecosystem. Our study uses a novel multimetric bioassay that is able to disentangle the contribution by Prokaryota, Protozoa and Eumetazoa invertebrates to litter breakdown. In doing so, our study reveals new insights into how organic matter decomposition is partitioned across biota and streambed compartments.

Abstract Here we combined controlled experiments and field surveys to determine if estimates of heat tolerance predict distributional ranges and phenology of different Drosophila species in southern South America. We contrasted thermal death time curves, which consider both magnitude and duration of the challenge to estimate heat tolerance, against the thermal range where populations are viable based on field surveys in an 8‐year longitudinal study. We observed a strong correspondence of the physiological limits, the thermal niche for population growth, and the geographic ranges across studied species, which suggests that the thermal biology of different species provides a common currency to understand how species will respond to warming temperatures both at a local level and throughout their distribution range. Our approach represents a novel analytical toolbox to anticipate how natural communities of ectothermic organisms will respond to global warming.

AbstractA current controversy in ecology is whether biological communities are discrete biological entities or simply study units created for convenience; a debate that becomes even more heated when delimiting communities along ecotones. Here, we report an interdisciplinary study designed to address the interplay between environmental drivers and community ecology in a typical ecotone ecosystem: the streambed. Environmental filtering at a micro-scale determined how diversity, productivity and composition of the whole streambed assemblage varied with depth and with the direction of vertical water exchange. Biomass and production decreased with increasing depth, and were lower under upwelling than downwelling conditions. However, the rate at which biomass and production decreased with increasing depth differed significantly for different taxonomic groups. Using quantitative biocenosis analysis, we also showed that benthic and hyporheic zone assemblages (assemblages in close juxtaposition) could be clearly distinguished as discrete communities with individual integrity. Vertical hydrodynamic conditions also influenced the demarcation between both communities; the benthic community reached greater depths in downwelling than in upwelling zones.

Riverine ecosystems can be conceptualized as 'bioreactors' (the riverine bioreactor) which retain and decompose a wide range of organic substrates. The metabolic performance of the riverine bioreactor is linked to their community structure, the efficiency of energy transfer along food chains, and complex interactions among biotic and abiotic environmental factors. However, our understanding of the mechanistic functioning and capacity of the riverine bioreactor remains limited. We review the state of knowledge and outline major gaps in the understanding of biotic drivers of organic matter decomposition processes that occur in riverine ecosystems, across habitats, temporal dimensions, and latitudes influenced by climate change. We propose a novel, integrative analytical perspective to assess and predict decomposition processes in riverine ecosystems. We then use this model to analyse data to demonstrate that the size-spectra of a community can be used to predict decomposition rates by analysing an illustrative dataset. This modelling methodology allows comparison of the riverine bioreactor's performance across habitats and at a global scale. Our integrative analytical approach can be applied to advance understanding of the functioning and efficiency of the riverine bioreactor as hotspots of metabolic activity. Application of insights gained from such analyses could inform the development of strategies that promote the functioning of the riverine bioreactor across global ecosystems.

AbstractForecasting long‐term consequences of global warming requires knowledge on thermal mortality and how heat stress interacts with other environmental stressors on different timescales. Here, we describe a flexible analytical framework to forecast mortality risks by combining laboratory measurements on tolerance and field temperature records. Our framework incorporates physiological acclimation effects, temporal scale differences and the ecological reality of fluctuations in temperature, and other factors such as oxygen. As a proof of concept, we investigated the heat tolerance of amphipods Dikerogammarus villosus and Echinogammarus trichiatus in the river Waal, the Netherlands. These organisms were acclimated to different temperatures and oxygen levels. By integrating experimental data with high‐resolution field data, we derived the daily heat mortality probabilities for each species under different oxygen levels, considering current temperatures as well as 1 and 2°C warming scenarios. By expressing heat stress as a mortality probability rather than a upper critical temperature, these can be used to calculate cumulative annual mortality, allowing the scaling up from individuals to populations. Our findings indicate a substantial increase in annual mortality over the coming decades, driven by projected increases in summer temperatures. Thermal acclimation and adequate oxygenation improved heat tolerance and their effects were magnified on longer timescales. Consequently, acclimation effects appear to be more effective than previously recognized and crucial for persistence under current temperatures. However, even in the best‐case scenario, mortality of D. villosus is expected to approach 100% by 2100, while E. trichiatus appears to be less vulnerable with mortality increasing to 60%. Similarly, mortality risks vary spatially: In southern, warmer rivers, riverine animals will need to shift from the main channel toward the cooler head waters to avoid thermal mortality. Overall, this framework generates high‐resolution forecasts on how rising temperatures, in combination with other environmental stressors such as hypoxia, impact ecological communities.