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There has been a lengthy debate on whether the abundance of adult reef fishes depends on prerecruitment or postrecruitment processes; however, we still do not have the ability to predict the magnitude of local fish recruitment. Here we show that the success of the leopard grouper (Mycteroperca rosacea) recruitment in the Gulf of California, Mexico, is determined by the availability of nursery habitat, which in turn is strongly correlated to climate conditions. Observational and experimental studies showed that leopard grouper larvae recruit preferentially on shallow rocky bottoms with brown algal (Sargassum spp.) beds, and that abundance of recruits is determined by the availability of Sargassum. The biomass of Sargassum decreases linearly with an increase in the Multivariate El Niño Southern Oscillation (ENSO) Index (MEI; an index positively correlated with water temperature and negatively correlated with nutrient availability). We analyzed the relationship between the interannual variation of MEI and the recruitment of the leopard grouper using field estimates of abundance of juvenile groupers. Our results show that there is a nonlinear relationship between recruitment and the oceanographic climate, in that the density of recruits decreases exponentially with increasing MEI. The predictability of leopard grouper recruitment has important implications for fisheries management, since it could allow adaptive management without expensive stock assessment programs.

Global change is striking harder and faster in the Mediterranean Sea than elsewhere, where high levels of human pressure and proneness to climate change interact in modifying the structure and disrupting regulative mechanisms of marine ecosystems. Rocky reefs are particularly exposed to such environmental changes with ongoing trends of degradation being impressive. Due to the variety of habitat types and associated marine biodiversity, rocky reefs are critical for the functioning of marine ecosystems, and their decline could profoundly affect the provision of essential goods and services which human populations in coastal areas rely upon. Here, we provide an up-to-date overview of the status of rocky reefs, trends in human-driven changes undermining their integrity, and current and upcoming management and conservation strategies, attempting a projection on what could be the future of this essential component of Mediterranean marine ecosystems.

In this study, we assessed the effect of environmental salinity and pH as independent factors on larval survival of Atlantic bluefin tuna (ABFT –Thunnus thynnus) together with their whole-body Na+/K+-ATPase and v-type H+-ATPase activities. Fertilized eggs of ABFT were obtained from a spontaneous spawning of broodstock in the farming facilities at El Gorguel (Cartagena, SE Spain) and were transferred to facilities of the Spanish Institute of Oceanography (IEO) in Mazarrón (SE Spain). In a first experiment, eggs (200 fertilized eggs L−1 per treatment, in 3 replicates) were exposed to different salinities treatments and constant pH 8.0 (control) until hatch was completed (50 h post-fertilization, hpf, at 23 °C): 27, 30, 33, 36, 37, 38 (control), 39, 40, 43, 46 and 49 ppt. In a second experiment eggs (200 fertilized eggs L−1, in 3 replicates) were exposed to seawater salinity (SW: 38 ppt) and four reduced pH treatments until hatch was completed (50 hpf at 23 °C): 8.0 (control), 7.7, 7.5 and 7.3. An inverse “U-shaped” relationship was observed between environmental salinity and number of hatched larvae. An opposite pattern was observed for both Na+/K+-ATPase and H+-ATPase activities in hatched larvae, increasing both activities in groups exposed to extreme salinities. Thus, larval survival was higher at intermediate salinities and lower at the extreme salinities tested. These results suggest higher survival rates with lower active pumps activities. No significant differences in larval survival were observed with pH treatment, but lower H+-ATPase activity was detected at control environmental pH (pH 8.0). Survival results are discussed in terms of osmoregulatory cost adapting to a salinity and pH predicted for the near future scenarios. 2,041

While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends.

Coastal areas are more densely populated than inland areas and present faster rates of population increase and urbanization. This trend is expected to continue in the coming decades, and thus, the demand of natural resources in coastal areas, such as water and energy resources, increasing the pressure and impact on the environment, superposed to the effects of climate change. Currently, in Europe, the demand for heating in buildings and businesses outnumbers the demand for cooling. However, the latter is gradually catching up due to rising demand for air cooling or refrigeration for industry such as food, technological and medical supplies. The energy required to cool buildings in Europe is expected to increase by more than 70% by 2030, while energy used to heat buildings may decrease by 30% (UE, 2018). Low Temperature Geothermal Energy (LTGE) is most likely the green energy production method for heating and cooling with the highest potential to provide affordable and clean energy and meet the CO2-emissions reduction goals of the Green Deal. Despite advances on LTGE technologies, the efficiency of these systems remains inherently sensitive to changes in hydrodynamics and the media (e.g., changes in the groundwater thermal regime). Groundwater, on the other hand, is the world's largest freshwater resource, and it is especially important in coastal areas because interactions between aquifer systems and sea water may lead to salinization and resource loss. Because geothermal systems and coastal aquifers interact directly, specially at groundwater discharge areas, it is clear that a better understanding of the potential interactions of geothermal systems with current and prospective coastal aquifer processes is essential for their design and foreseeing potential environmental effects. To address these issues, we model variable-density groundwater coupled with heat transport to simulate the long-term evolution of groundwater salinity and aquifer thermal energy discharge. We find that the heating/cooling-induced water density variations affect the seawater intrusion. Understanding the behavior of the groundwater system is required to ensure sustainable water, energy, and coastal ecosystem management.

Fire danger indices are descriptors of fire potential in a large area, and combine a few variables that affect the initiation, spread and control of forest fires. The Canadian Fire Weather Index (FWI) is one of the most widely used fire danger indices in the world, and it is built upon instantaneous values of temperature, relative humidity and wind velocity at noon, together with 24 hourly accumulated precipitation. However, the scarcity of appropriate data has motivated the use of daily mean values as surrogates of the instantaneous ones in several studies that aimed to assess the impact of global warming on fire. In this paper we test the sensitivity of FWI values to both instantaneous and daily mean values, analyzing their effect on mean seasonal fire danger (seasonal severity rating, SSR) and extreme fire danger conditions (90th percentile, FWI90, and FWI>30, FOT30), with a special focus on its influence in climate change impact studies. To this aim, we analyzed reanalysis and regional climate model (RCM) simulations, and compared the resulting instantaneous and daily mean versions both in the present climate and in a future scenario. In particular, we were interested in determining the effect of these datasets on the projected changes obtained for the mean and extreme seasonal fire danger conditions in future climate scenarios, as given by a RCM. Overall, our results warn against the use of daily mean data for the computation of present and future fire danger conditions. Daily mean data lead to systematic negative biases of fire danger calculations. Although the mean seasonal fire danger indices might be corrected to compensate for this bias, fire danger extremes (FWI90 and specially FOT30) cannot be reliably transformed to accommodate the spatial pattern and magnitude of their respective instantaneous versions, leading to inconsistent results when projected into the future. As a result, we advocate caution when using daily mean data and strongly recommend the application of the standard definition for its calculation as closely as possible. Threshold-dependent indices derived from FWI are not reliably represented by the daily mean version and thus can neither be applied for the estimation of future fire danger season length and severity, nor for the estimation of future extreme events. The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement 243888 (FUME Project). J.F. acknowledges nancial support from the Spanish R&D&I programme through grant CGL2010-22158-C02 (CORWES project). The ESCENA project (200800050084265) of the Spanish \Strategic action on energy and climate change" provided the WRF RCM simulation used in this study. We acknowledge three anonymous referees for their useful comments that helped to improve the original manuscript.