Chapter 7 Tree Physiology and Intraspecific Responses to Extreme Events: Insights from the Most Extreme Heat Year in U.S. History

Extreme events such as droughts, heat waves and floods can have significant and long lasting financial, infrastructural and environmental impacts. While probabilistic seasonal outlooks are commonplace, there are relatively few probabilistic outlooks available on multiweek timescales. Additionally, many services focus on the middle of the distribution of possible outcomes &#8211; e.g., forecasts of probability of above or below median, or probability of mean conditions exceeding some threshold. These do not encompass the types of extreme events that can be the most damaging, such as several consecutive days of extreme heat, unusually large numbers of cold days in a season, or an extended period where rainfall is in the lowest decile of historical years.Advance warning of extreme events that impact particular industries enable managers to put in place response measures which can help to reduce their losses. This can involve:<ul><li>Active responses which aim to reduce the severity of the impact. For example, losses in dairy production due to extreme heat can be mitigated by adjusting grazing rotations such that cows are in shadier paddocks during these events</li> <li>Defensive responses which aim to account for any losses incurred due to an event. For example, the purchase of new farm equipment can be deferred if a forecast extreme event indicates a likely unavoidable financial loss in the near future</li> </ul>To meet this need, the Australian Bureau of Meteorology is developing a suite of forecast products communicating risk of extreme events using data from the Bureau&#8217;s new seasonal forecasting system ACCESS-S. Each prototype forecast product is trialed with external users through a webpage to assess usefulness and popularity.

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Climate change, extreme events, and increased risk of salmonellosis: foodborne diseases active surveillance network (FoodNet), 2004-2014

Environmental Health ◽

10.1186/s12940-021-00787-y ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Michele E. Morgado ◽

Chengsheng Jiang ◽

Jordan Zambrana ◽

Crystal Romeo Upperman ◽

Clifford Mitchell ◽

...

Keyword(s):

Active Surveillance ◽

Extreme Events ◽

Extreme Precipitation ◽

The United States ◽

Extreme Heat ◽

Extreme Weather Events ◽

Foodborne Diseases ◽

Surveillance Network ◽

Extreme Precipitation Events ◽

Precipitation Events

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 of Salmonella in soil and food. However, the impact of extreme weather events on Salmonella 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 for S. Enteriditis, S. Typhimurium, S. Newport, and S. 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 95th percentile 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 of S. 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 of S. 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 as S. Javiana and S. Newport, appear to be of particular significance regarding increased heat and rainfall events.

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