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Climate change and freshwater ecosystems: impacts across multiple levels of organization

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 CO2is 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.
- Queen Mary University of London United Kingdom
- University of Leeds United Kingdom
Climate Change, Fresh Water, Ecosystem
Climate Change, Fresh Water, Ecosystem
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).1K popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 0.1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 0.1%
