A meta-analysis was conducted on 136 data sets of denitrification rates (DR) recorded both during the period of highest water temperature and monthly in five types of aquatic ecosystems: oceans, coastal environments, estuaries, lakes and rivers. There was a gradual increase of DR from the ocean to rivers and lakes at both scales, with the rivers showing the highest DR variability. Denitrification peaked during summertime and showed highest seasonal variability in lakes and rivers. High concentrations of nitrate and interstitially-dissolved organic carbon as well as low oxygen concentration in the overlying water enhanced DR both during summer and at a seasonal scale whereas total phosphorus did at the seasonal scale only. There was a positive linear relationship between overlying nitrate and DR over the range of 1-970 lmol NO 3 (r 2 = 0.86, P = 0.001). DR in lakes and rivers might reach values doubling those in the more denitrifying terrestrial ecosystems (e.g. agrosystems). Discrepancies in DR and its controlling factors between site-specific studies and this meta-analysis may arise from environmental variability at two, often confounded, scales of observation: the habitat and the ecosystem level. Future studies on denitrification in aquatic environments should address the topic of spatial heterogeneity more thoroughly.

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Growing interest in the effects of global change on the metabolism, stoichiometry and cycling of carbon in aquatic ecosystems has motivated research on the export of organic carbon (OCE) from catchments. In this article, quantitative and functional features of the annual export rates of total, particulate and dissolved organic carbon (TOC, POC and DOC) were reviewed, and the stoichiometry of export (OC:N, OC:P and N:P) from 550 catchments worldwide was reported. TOC export ranged 2.1-92,474 kg C km -2 year -1 , POC export ranged 0.4-73,979 kg C km -2 year -1 and DOC export ranged 1.2-56,946 kg C km -2 year -1 . Exports of TOC and DOC were strongly linked, but POC export was unrelated to DOC. The DOC fraction comprised on average 73 ± 21% of TOC export. The export rates of organic carbon were poorly related to those of total nitrogen and total phosphorus. Discrete and continuous environmental variables failed to predict TOC export, but DOC export was influenced by discharge and catchment area worldwide. Models of OCE in different catchment types were controlled by different environmental variables; hydrological variables were generally better predictors of OCE than anthropogenic and soil variables. Elemental ratios of carbon export in most catchments were above the Redfield ratio, suggesting that phosphorus may become the limiting nutrient for downstream plant growth. These ratios were marginally related to environmental data. More detailed hydrological data, consideration of in-stream processes and the use of quasi-empirical dynamical models are advocated to improve our knowledge of OCE rates and those of other nutrients.

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Summary Ecosystems are complex and multivariate; hence, methods to assess the dynamics of ecosystems should have the capacity to evaluate multiple indicators simultaneously. Most research on identifying leading indicators of regime shifts has focused on univariate methods and simple models which have limited utility when evaluating real ecosystems, particularly because drivers are often unknown. We discuss some common univariate and multivariate approaches for detecting critical transitions in ecosystems and demonstrate their capabilities via case studies. Synthesis and applications. We illustrate the utility of an information theory‐based index for assessing ecosystem dynamics. Trends in this index also provide a sentinel of both abrupt and gradual transitions in ecosystems.

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Ecological systems may occur in alternative states that differ in ecological structures, functions and processes. Resilience is the measure of disturbance an ecological system can absorb before changing states. However, how the intrinsic structures and processes of systems that characterize their states affects their resilience remains unclear. We analyzed time series of phytoplankton communities at three sites in a floodplain in central Spain to assess the dominant frequencies or “temporal scales” in community dynamics and compared the patterns between a wet and a dry alternative state. The identified frequencies and cross-scale structures are expected to arise from positive feedbacks that are thought to reinforce processes in alternative states of ecological systems and regulate emergent phenomena such as resilience. Our analyses show a higher species richness and diversity but lower evenness in the dry state. Time series modeling revealed a decrease in the importance of short-term variability in the communities, suggesting that community dynamics slowed down in the dry relative to the wet state. The number of temporal scales at which community dynamics manifested, and the explanatory power of time series models, was lower in the dry state. The higher diversity, reduced number of temporal scales and the lower explanatory power of time series models suggest that species dynamics tended to be more stochastic in the dry state. From a resilience perspective our results highlight a paradox: increasing species richness may not necessarily enhance resilience. The loss of cross-scale structure (i.e. the lower number of temporal scales) in community dynamics across sites suggests that resilience erodes during drought. Phytoplankton communities in the dry state are therefore likely less resilient than in the wet state. Our case study demonstrates the potential of time series modeling to assess attributes that mediate resilience. The approach is useful for assessing resilience of alternative states across ecological and other complex systems.