Here we document the regional effects of Tropical Cyclone Irene on thermal structure and ecosystem metabolism in nine lakes and reservoirs in northeastern North America using a network of high-frequency, in situ, automated sensors. Thermal stability declined within hours in all systems following passage of Irene, and the magnitude of change was related to the volume of water falling on the lake and catchment relative to lake volume. Across systems, temperature change predicted the change in primary production, but changes in mixed-layer thickness did not affect metabolism. Instead, respiration became a driver of ecosystem metabolism that was decoupled from in-lake primary production, likely due to addition of terrestrially derived carbon. Regionally, energetic disturbance of thermal structure was shorter-lived than disturbance from inflows of terrestrial materials. Given predicted regional increases in intense rain events with climate change, the magnitude and longevity of ecological impacts of these storms will be greater in systems with large catchments relative to lake volume, particularly when significant material is available for transport from the catchment. This case illustrates the power of automated sensor networks and associated human networks in assessing both system response and the characteristics that mediate physical and ecological responses to extreme events.

Fog is thought to influence ecological function in coastal forests worldwide, yet few data are available that illuminate the mechanisms underlying this influence. In a California redwood forest we measured water and nitrogen (N) fluxes from horizontally moving fog and vertically delivered rain as well as redwood tree function. The spatial heterogeneity of water and N fluxes, water availability, tree water use, and canopy N processing varied greatly across seasons. Water and N fluxes to soil (annual average of 98% and 89%, respectively) across the whole forest occurred primarily in the rain season and was relatively even across the whole forest. In contrast, below-canopy flux of fog water and N declined exponentially from the windward edge to the forest interior. Following large fog events, soil moisture was greater at the windward edge than anywhere else in the forest. Physiological activity in redwoods reflected these differences in inputs across seasons: tree physiological responses did not vary spatially in the rain season, but in the fog season, water use was greater, yet water stress was less, in trees at the windward edge of the forest versus the interior. In both seasons, vertical passage through the forest changed the amount of water and form and concentration of N, revealing the role of the tree canopy in processing atmospheric inputs. Although total fog water inputs were comparatively small, they may have important ecosystem functions, including relief of canopy water stress and, where there is fog drip, functional coupling of above-and belowground processes.

Here we draw attention to the potential for pelagic bloom‐forming cyanobacteria to have substantial effects on nutrient cycling and ecosystem resilience across a wide range of lakes. Specifically, we hypothesize that cyanobacterial blooms can influence lake nutrient cycling, resilience, and regime shifts by tapping into pools of nitrogen (N) and phosphorus (P) not usually accessible to phytoplankton. The ability of many cyanobacterial taxa to fix dissolved N2 gas is a well‐known potential source of N, but some taxa can also access pools of P in sediments and bottom waters. Both of these nutrients can be released to the water column via leakage or mortality, thereby increasing nutrient availability for other phytoplankton and microbes. Moreover, cyanobacterial blooms are not restricted to high nutrient (eutrophic) lakes: blooms also occur in lakes with low nutrient concentrations, suggesting that changes in nutrient cycling and ecosystem resilience mediated by cyanobacteria could affect lakes across a gradient of nutrient concentrations. We used a simple model of coupled N and P cycles to explore the effects of cyanobacteria on nutrient dynamics and resilience. Consistent with our hypothesis, parameters reflecting cyanobacterial modification of N and P cycling alter the number, location, and/or stability of model equilibria. In particular, the model demonstrates that blooms of cyanobacteria in low‐nutrient conditions can facilitate a shift to the high‐nutrient state by reducing the resilience of the low‐nutrient state. This suggests that cyanobacterial blooms warrant attention as potential drivers of the transition from a low‐nutrient, clear‐water regime to a high‐nutrient, turbid‐water regime, a prediction of particular concern given that such blooms are reported to be increasing in many regions of the world due in part to global climate change.

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