Description: Global climate change affects marine fish through drivers such as ocean warming, acidification and oxygen depletion, causing changes in marine ecosystems and socioeconomic impacts. While experimental and observational results can inform about anticipated effects of different drivers, linking between these results and ecosystem-level changes requires quantitative integration of physiological and ecological processes into models to advance research and inform management. We give an overview of important physiological and ecological processes affected by environmental drivers. We then provide a review of available modelling approaches for marine fish, analysing their capacities for process-based integration of environmental drivers. Building on this, we propose approaches to advance important research questions. Examples of integration of environmental drivers exist for each model class. Recent extensions of modelling frameworks increase the potential for including detailed mechanisms and improving model projections. Experimental results on energy allocation, behaviour and physiological limitations will advance the understanding of organism-level trade-offs and thresholds in response to multiple drivers. More explicit representation of life cycles and biological traits can improve description of population dynamics and adaptation, and data on food web topology and feeding interactions help to detail the conditions for possible regime shifts. Identification of relevant processes will also benefit the coupling of different models to investigate spatial–temporal changes in stock productivity and integrated responses of social–ecological systems. Thus, a more process-informed foundation for models will promote the integration of experimental and observational results and increase the potential for model-based extrapolations into a future under changing environmental conditions.

Description: There is still considerable debate about which mechanisms drive the relationship between biodiversity and ecosystem function (BEF). Although most scientists agree on the existence of two underlying mechanisms, complementarity and selection, experimental studies keep producing contrasting results on the relative contributions of the two effects. We present a spatially explicit resource competition model and investigate how the strength of these effects is influenced by trait and environmental variability, resource distribution, and species pool size. Our results demonstrate that the increase of biomass production with increasing species numbers depends on the concurrence of environmental and trait variability: BEF relationships are stronger if functionally different species coexist in a landscape with heterogeneous resource supply. These large biodiversity effects arise from complementarity effects, whereas selection effects are maximized when broad trait ranges coincide with narrow ranges of resource supply ratios. Our results will therefore help to resolve the debate on complementarity and selection mechanisms.

Description: Lake Baikal, the world's most voluminous freshwater lake, has experienced unprecedented warming during the last decades. A uniquely diverse amphipod fauna inhabits the littoral zone and can serve as a model system to identify the role of thermal tolerance under climate change. This study aimed to identify sublethal thermal constraints in two of the most abundant endemic Baikal amphipods, Eulimnogammarus verrucosus and Eulimnogammarus cyaneus, and Gammarus lacustris, a ubiquitous gammarid of the Holarctic. As the latter is only found in some shallow isolated bays of the lake, we further addressed the question whether rising temperatures could promote the widespread invasion of this non-endemic species into the littoral zone. Animals were exposed to gradual temperature increases (4 week, 0.8 °C/d; 24 h, 1 °C/h) starting from the reported annual mean temperature of the Baikal littoral (6 °C). Within the framework of oxygen- and capacity-limited thermal tolerance (OCLTT), we used a nonlinear regression approach to determine the points at which the changing temperature-dependence of relevant physiological processes indicates the onset of limitation. Limitations in ventilation representing the first limits of thermal tolerance (pejus (= “getting worse”) temperatures (Tp)) were recorded at 10.6 (95% confidence interval; 9.5, 11.7), 19.1 (17.9, 20.2), and 21.1 (19.8, 22.4) °C in E. verrucosus, E. cyaneus, and G. lacustris, respectively. Field observations revealed that E. verrucosus retreated from the upper littoral to deeper and cooler waters once its Tp was surpassed, identifying Tp as the ecological thermal boundary. Constraints in oxygen consumption at higher than critical temperatures (Tc) led to an exponential increase in mortality in all species. Exposure to short-term warming resulted in higher threshold values, consistent with a time dependence of thermal tolerance. In conclusion, species-specific limits to oxygen supply capacity are likely key in the onset of constraining (beyond pejus) and then life-threatening (beyond critical) conditions. Ecological consequences of these limits are mediated through behavioral plasticity in E. verrucosus. However, similar upper thermal limits in E. cyaneus (endemic, Baikal) and G. lacustris (ubiquitous, Holarctic) indicate that the potential invader G. lacustris would not necessarily benefit from rising temperatures. Secondary effects of increasing temperatures remain to be investigated.

Description: The West African monsoon rainfall is essential for regional food production, and decadal predictions are necessary for policy makers and farmers. However, predictions with global climate models reveal precipitation biases. This study addresses the hypotheses that global prediction biases can be reduced by dynamical downscaling with a multimodel ensemble of three regional climate models (RCMs), a RCM coupled to a global ocean model and a RCM applying more realistic soil initialization and boundary conditions, i.e., aerosols, sea surface temperatures (SSTs), vegetation, and land cover. Numerous RCM predictions have been performed with REMO, COSMO-CLM (CCLM), and Weather Research and Forecasting (WRF) in various versions and for different decades. Global predictions reveal typical positive and negative biases over the Guinea Coast and the Sahel, respectively, related to a southward shifted Intertropical Convergence Zone (ITCZ) and a positive tropical Atlantic SST bias. These rainfall biases are reduced by some regional predictions in the Sahel but aggravated by all RCMs over the Guinea Coast, resulting from the inherited SST bias, increased westerlies and evaporation over the tropical Atlantic and shifted African easterly waves. The coupled regional predictions simulate high-resolution atmosphere-ocean interactions strongly improving the SST bias, the ITCZ shift and the Guinea Coast and Central Sahel precipitation biases. Some added values in rainfall bias are found for more realistic SST and land cover boundary conditions over the Guinea Coast and improved vegetation in the Central Sahel. Thus, the ability of RCMs and improved boundary conditions to reduce rainfall biases for climate impact research depends on the considered West African region.