Freshwater ecosystems are particularly vulnerable to climate change due to their fragmented habitats, limited dispersal abilities, and exposure to multiple anthropogenic stressors. Most climate change studies have focused on individual or species populations, rather than higher levels of organization such as communities, food webs, and ecosystems. The authors propose that understanding the connections between these different levels can help develop a more coherent theoretical framework based on metabolic scaling, foraging theory, and ecological stoichiometry to predict the ecological consequences of climate change. They highlight the importance of individual metabolic rates, which scale with body size and temperature, and how these affect food web structure and dynamics. Increasing atmospheric CO2 levels are predicted to alter the stoichiometry of elemental fluxes between consumers and resources, potentially leading to profound shifts in food web structure. The different components of climate change, such as temperature, hydrology, and atmospheric composition, not only affect multiple levels of biological organization but may also interact with other stressors, emphasizing the need for future research to address these synergies. The review discusses the challenges in studying climate change impacts in freshwater ecosystems, including the use of various experimental and empirical approaches, and the importance of integrating long-term data with models and manipulative experiments to develop a mechanistic understanding of responses to future changes. The authors also explore the non-random species changes in freshwater ecosystems and the fragmentation of food webs in response to climate change, highlighting the differential impacts on different trophic levels. Finally, they discuss the potential impacts of climate change on metabolic, foraging, and stoichiometric constraints across multiple levels of biological organization, and the need to unify concepts within a biodiversity-ecosystem functioning context to predict future ecosystem responses.Freshwater ecosystems are particularly vulnerable to climate change due to their fragmented habitats, limited dispersal abilities, and exposure to multiple anthropogenic stressors. Most climate change studies have focused on individual or species populations, rather than higher levels of organization such as communities, food webs, and ecosystems. The authors propose that understanding the connections between these different levels can help develop a more coherent theoretical framework based on metabolic scaling, foraging theory, and ecological stoichiometry to predict the ecological consequences of climate change. They highlight the importance of individual metabolic rates, which scale with body size and temperature, and how these affect food web structure and dynamics. Increasing atmospheric CO2 levels are predicted to alter the stoichiometry of elemental fluxes between consumers and resources, potentially leading to profound shifts in food web structure. The different components of climate change, such as temperature, hydrology, and atmospheric composition, not only affect multiple levels of biological organization but may also interact with other stressors, emphasizing the need for future research to address these synergies. The review discusses the challenges in studying climate change impacts in freshwater ecosystems, including the use of various experimental and empirical approaches, and the importance of integrating long-term data with models and manipulative experiments to develop a mechanistic understanding of responses to future changes. The authors also explore the non-random species changes in freshwater ecosystems and the fragmentation of food webs in response to climate change, highlighting the differential impacts on different trophic levels. Finally, they discuss the potential impacts of climate change on metabolic, foraging, and stoichiometric constraints across multiple levels of biological organization, and the need to unify concepts within a biodiversity-ecosystem functioning context to predict future ecosystem responses.