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Harmful algal blooms (HABs) are common in many eutrophic lakes and frequently associated with nutrient excesses, warm waters, and calm conditions. While HABs can also occur in oligotrophic waterbodies, bloom‐stimulating factors remain elusive for these ecosystems. Here, using a high‐frequency sensor platform supported by hydrodynamic modeling, we document a clearly linked sequence of three hydrodynamic events that immediately preceded each HAB event on Skaneateles Lake, NY during 2018. HABs were first preceded by interactions between internal waves in the thermal structure of the lake with the northern slope of the lakebed. These interactions disturbed sediments resulting in upwelling of nutrient‐rich sediment and possibly cyanobacterial cells into the lower water column. Next, moderate winds stimulated Langmuir circulation which facilitated the transport of material from the lower water column to well‐lit surface waters. Finally, the sequence culminated with a calm wind period, which is often classically associated with surface HAB formation. While individual steps in this sequence occurred independently and repeatedly throughout the year, the complete sequence occurred only eight times, immediately preceding each of the eight documented HABs. We empirically derive thresholds for and timing of the sequence to independently predict HAB occurrence and elevated cyanobacteria levels in the lake. The discovery of this specific and repeated event sequence and the identified thresholds provides the potential for forecasting of HABs days in advance. Ongoing climate change impacts, including increasing water column thermal stratification and changing wind speeds may alter the frequency, timing, and duration of this sequence and consequent HAB formation. [ABSTRACT FROM AUTHOR]

Intermediate disturbances are an important component of many forest disturbance regimes, with effects on canopy structure and related functions that are highly dependent on the nature and intensity of the perturbation. Ice storms are an important disturbance mechanism in temperate forests that often result in moderate-severity, diffuse canopy damage. However, it has not previously been possible to distinguish the specific effect of ice storm intensity (as ice accretion) from predisturbance stand characteristics and physiographic factors. In this study, we utilized a novel experimental ice storm treatment to evaluate the effects of variable ice accretion levels on forest canopy structure. Our results verified significant impacts of ice storm disturbance on near-term canopy structural reorganization. Canopy openness, light transmission, and complexity increased significantly relative to predisturbance baselines and undisturbed controls. We documented variable impacts with disturbance intensity, as significant canopy changes largely occurred with ice accretion levels of [greater than or equal to]12.7 mm. Repeated ice storm disturbance (two consecutive years) had marginal, rather than compounding, effects on forest canopy structure. Our findings are relevant to understanding how ice storms can affect near-term forest canopy structural reorganization and ecosystem processes and add to a growing base of knowledge on the effects of intermediate disturbances on canopy structure. Key words: intermediate disturbance, canopy structure, complexity, ecosystem function. Les perturbations intermediaires sont une composante importante de plusieurs regimes de perturbation des forets qui ont des effets sur la structure du couvert forestier et les fonctions qui y sont reliees lesquels dependent fortement de la nature et de l'intensite de la perturbation. Les tempetes de verglas qui causent des dommages diffus et moderement severes dans le couvert forestier constituent un mecanisme important de perturbation dans les forets temperees. Cependant, il n'a pas precedemment ete possible de distinguer l'effet specifique de l'intensite d'une tempete de verglas (sous forme d'accumulation de glace) des facteurs physiographiques et des caracteristiques du peuplement avant d'etre perturbe. Dans cette etude, nous avons utilise un nouveau traitement experimental qui reproduit une tempete de verglas pour evaluer les effets de differents niveaux d'accumulation de verglas sur la structure du couvert forestier. Nos resultats ont permis de constater les impacts importants de la perturbation due a une tempete de verglas sur la reorganisation structurale a court terme du couvert forestier. L'ouverture, la transmission de la lumiere et la complexite du couvert forestier ont significativement augmente par rapport a la situation anterieure a la perturbation et aux temoins non perturbes. Nous avons observe des impacts variables selon l'intensite de la perturbation alors que des changements importants dans le couvert forestier sont surtout survenus avec des niveaux d'accumulation de verglas [greater than or equal to] 12,7 mm. Des perturbations repetees (deux annees consecutives) dues a une tempete de verglas ont eu des effets marginaux plutot que conjugues sur la structure du couvert forestier. Nos resultats sont pertinents pour comprendre de quelle facon les tempetes de verglas peuvent avoir un impact a court terme sur la reorganisation structurale du couvert forestier et alterer les processus de l'ecosysteme. Ils contribuent au developpement de la base de connaissances sur la structure du couvert forestier. [Traduit par la Redaction] Mots-cles : perturbation intermediaire, structure du couvert forestier, complexite, fonction de l'ecosysteme., Introduction Moderate-severity disturbances are an important driver of ecosystem functioning, structural development, and successional change in forest ecosystems (Frelich 2002; Cohen et al. 2016). Disturbances that result in damage to [...]

Critical loads (CLs) are frequently used to quantify terrestrial ecosystem impacts from nitrogen (N) deposition using ecological responses such as the growth and mortality of tree species. Typically, CLs are reported as a single value, with uncertainty, for an indicator across a species' entire range. Mediating factors such as climate and soil conditions can influence species' sensitivity to N, but the magnitudes of these effects are rarely calculated explicitly. Here, we quantify the spatial variability and estimation error in N CLs for the growth and survival of 10 different tree species while accounting for key environmental factors that mediate species sensitivity to N (e.g., soil characteristics). We used a bootstrapped machine learning approach to determine the level of N deposition at which a 1% decrease occurs in growth rate or survival probability at forest plot locations across the United States. We found minimal differences (<5 kg N ha−1 year−1) when comparing a single species' CLs across climatic regimes but found considerable variability in species' local N CLs (>8.5 kg N ha−1 year−1) within these regimes. We also evaluated the most important factors for predicting tree growth rates and mortality and found that climate, competition, and air pollution generally have the greatest influence on growth rates and survival probability. Lastly, we developed a new probability of exceedance metric for each species and found high likelihoods of exceedance across large portions (46%) of some species' ranges. Our analysis demonstrates that machine learning approaches provide a unique capability to: (1) quantify mediating factor influences on N sensitivity of trees, (2) estimate the error in local N CL estimates, and (3) generate localized N CLs with probabilities of exceedance for tree species. [ABSTRACT FROM AUTHOR]