Fresh waters are particularly vulnerable to climate change because (i) many species within these fragmented habitats have limited abilities to disperse as the environment changes; (ii) water temperature and availability are climate-dependent; and (iii) many systems are already exposed to numerous anthropogenic stressors. Most climate change studies to date have focused on individuals or species populations, rather than the higher levels of organization (i.e. communities, food webs, ecosystems). We propose that an understanding of the connections between these different levels, which are all ultimately based on individuals, can help to develop a more coherent theoretical framework based on metabolic scaling, foraging theory and ecological stoichiometry, to predict the ecological consequences of climate change. For instance, individual basal metabolic rate scales with body size (which also constrains food web structure and dynamics) and temperature (which determines many ecosystem processes and key aspects of foraging behaviour). In addition, increasing atmospheric CO ₂ is predicted to alter molar CNP ratios of detrital inputs, which could lead to profound shifts in the stoichiometry of elemental fluxes between consumers and resources at the base of the food web. The different components of climate change (e.g. temperature, hydrology and atmospheric composition) not only affect multiple levels of biological organization, but they may also interact with the many other stressors to which fresh waters are exposed, and future research needs to address these potentially important synergies.

Pharmaceuticals have emerged as a major group of environmental contaminants over the past decade but relatively little is known about their occurrence in freshwaters compared to other pollutants. We present a global-scale analysis of the presence of 203 pharmaceuticals across 41 countries and show that contamination is extensive due to widespread consumption and subsequent disposal to rivers. There are clear regional biases in current understanding with little work outside North America, Europe, and China, and no work within Africa. Within individual countries, research is biased around a small number of populated provinces/states and the majority of research effort has focused upon just 14 compounds. Most research has adopted sampling techniques that are unlikely to provide reliable and representative data. This analysis highlights locations where concentrations of antibiotics, cardiovascular drugs, painkillers, contrast media, and antiepileptic drugs have been recorded well above thresholds known to cause toxic effects in aquatic biota. Studies of pharmaceutical occurrence and effects need to be seen as a global research priority due to increasing consumption, particularly among societies with aging populations. Researchers in all fields of environmental management need to work together more effectively to identify high risk compounds, improve the reliability and coverage of future monitoring studies, and develop new mitigation measures.

There is no clear agreement regarding the ideal combination of factors needed to optimize postactivation potentiation (PAP) after a conditioning activity. Therefore, a meta-analysis was conducted to evaluate the effects of training status, volume, rest period length, conditioning activity, and gender on power augmentation due to PAP. A total of 141 effect sizes (ESs) for muscular power were obtained from a total of 32 primary studies, which met our criteria of investigating the effects of a heavy preconditioning activity on power in randomized human trials. The mean overall ES for muscle power was 0.38 after a conditioning activity (p < 0.05). Significant differences were found between moderate intensity (60-84%) 1.06 and heavy intensity (>85%) 0.31 (p < 0.05). There were overall significant differences found between single sets 0.24 and multiple sets 0.66 (p < 0.05). Rest periods of 7-10 minutes (0.7) after a conditioning activity resulted in greater ES than 3-7 minutes (0.54), which was greater than rest periods of >10 minutes (0.02) (p < 0.05). Significant differences were found between untrained 0.14 and athletes 0.81 and between trained 0.29 and athletes. The primary findings of this study were that a conditioning activity augmented power output, and these effects increased with training experience, but did not differ significantly between genders. Moreover, potentiation was optimal after multiple (vs. single) sets, performed at moderate intensities, and using moderate rest periods lengths (7-10 minutes).