In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short‐term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well‐developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short‐ and long‐term. We summarize the current understanding of storm‐induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.
Extreme precipitation has increased in frequency and intensity across the Conterminous U.S. (CONUS). This trend is expected to continue under future climate change. The cause is a combination of thermodynamic (i.e., warmer temperatures increase the atmospheric moisture content) and dynamic changes (e.g., shifts in cyclone frequency and tracks). It is well‐established that thermodynamic changes will intensify extreme precipitation events, but the impacts of dynamic changes are more uncertain. Extreme events are, per definition, rare and occur in unusual weather situations that are distinctly different from regular day‐to‐day weather. We take advantage of this and identify extreme precipitation‐producing weather patterns (XWTs) for all major watersheds across the CONUS by using a novel algorithm. We show that a set of one to four XWTs per watershed are causing extreme precipitation accumulations. These XWTs can be detected based on their synoptic‐scale fingerprint and are associated with West Coast atmospheric rivers, troughing in the desert Southwest, cutoff lows and troughs in the central and northwestern plains, and tropical cyclones along the Gulf and Atlantic coast. The algorithm is flexible enough to provide reliable results for city to major watershed‐scales and can detect extremes that are unprecedented in the training record. Importantly, this approach allows us to assess long‐term trends in extreme precipitation dynamics and reveal that XWT frequencies increased significantly in most U.S. watersheds during the 20th century indicating that changes in the atmospheric dynamics played an important role in historic extreme precipitation increases.
more » « less- NSF-PAR ID:
- 10447978
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Atmospheres
- Volume:
- 126
- Issue:
- 7
- ISSN:
- 2169-897X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Background Infections with nontyphoidal
Salmonella cause an estimated 19,336 hospitalizations each year in the United States. Sources of infection can vary by state and include animal and plant-based foods, as well as environmental reservoirs. Several studies have recognized the importance of increased ambient temperature and precipitation in the spread and persistence ofSalmonella in soil and food. However, the impact of extreme weather events onSalmonella infection rates among the most prevalent serovars, has not been fully evaluated across distinct U.S. regions.Methods To address this knowledge gap, we obtained
Salmonella case data forS. Enteriditis,S. Typhimurium,S. Newport, andS. Javiana (2004-2014; n = 32,951) from the Foodborne Diseases Active Surveillance Network (FoodNet), and weather data from the National Climatic Data Center (1960-2014). Extreme heat and precipitation events for the study period (2004-2014) were identified using location and calendar day specific 95thpercentile thresholds derived using a 30-year baseline (1960-1989). Negative binomial generalized estimating equations were used to evaluate the association between exposure to extreme events and salmonellosis rates.Results We observed that extreme heat exposure was associated with increased rates of infection with
S. Newport in Maryland (Incidence Rate Ratio (IRR): 1.07, 95% Confidence Interval (CI): 1.01, 1.14), and Tennessee (IRR: 1.06, 95% CI: 1.04, 1.09), both FoodNet sites with high densities of animal feeding operations (e.g., broiler chickens and cattle). Extreme precipitation events were also associated with increased rates ofS. Javiana infections, by 22% in Connecticut (IRR: 1.22, 95% CI: 1.10, 1.35) and by 5% in Georgia (IRR: 1.05, 95% CI: 1.01, 1.08), respectively. In addition, there was an 11% (IRR: 1.11, 95% CI: 1.04-1.18) increased rate ofS . Newport infections in Maryland associated with extreme precipitation events.Conclusions Overall, our study suggests a stronger association between extreme precipitation events, compared to extreme heat, and salmonellosis across multiple U.S. regions. In addition, the rates of infection with
Salmonella serovars that persist in environmental or plant-based reservoirs, such asS. Javiana andS. Newport, appear to be of particular significance regarding increased heat and rainfall events.
