NOAA's September forecast gives Chilean salmon producers a reason to pay attention to the coming summer. El Niño is strengthening, and NOAA estimates a greater than 90% chance that it will become very strong during the Northern Hemisphere autumn and winter of 2026–27. (NOAA's September ENSO discussion) We looked back at local surface temperatures during every completed El Niño since 1982 to see what actually occurred around salmon farms in Los Lagos and Aysén.
Manolin's surface-temperature record spans 44 years and roughly 21 million site-days across salmon-farming areas in Los Lagos and Aysén. We compared local temperatures against their 1991–2020 seasonal norms during 13 completed El Niño events since 1982.
How local temperatures responded during 13 El Niños
Los Lagos was warmer than normal during eight of those events; Aysén was warmer during six. Across all 13, the average anomaly was +0.018°C in Los Lagos and +0.010°C in Aysén.
During the 1997–98 El Niño, Los Lagos averaged about +0.26°C above normal and Aysén about +0.16°C. The similarly strong 1982–83 event coincided with much smaller local anomalies, around +0.07°C and +0.09°C respectively. In 2014–16, Los Lagos warmed modestly during the event, then averaged roughly +0.34°C in the following 12 months. During the strong 2023–24 El Niño, both regions were colder than their seasonal norms: about −0.16°C in Los Lagos and −0.22°C in Aysén.
The warming that followed 2014–16 in Los Lagos led us to check the lagged relationship month by month. In the Manolin series, the correlation between the ENSO index and local temperature anomalies is about 0.05–0.06 in the same month. It rises when ENSO leads local temperature, peaking around six months at 0.21 in Los Lagos and 0.20 in Aysén. Even at that peak, a simple linear comparison accounts for only about 4% of the variation in the regional monthly anomalies.
What regional temperatures leave unresolved for SRS
Winds, currents, freshwater inputs and the shape of each channel affect the water reaching a farm. The Manolin record also measures surface temperature; it has not been corrected for the difference between the surface and the depths where fish are held. Those limits become especially relevant if we try to use a regional temperature anomaly to understand what is happening inside a particular cage.
Suppose Los Lagos begins warming this summer. A farm experiencing a +0.5°C anomaly for several weeks has a different temperature history from one that briefly reaches the same anomaly and returns to normal. We would need to know what happened at the site, how long it lasted and what the fish experienced at depth before judging whether the warming had any bearing on SRS.
In the detailed mortality section of Sernapesca's 2025 health report, infectious causes accounted for 25.7% of reported Atlantic salmon mortality in marine farms. Of the mortality classified as infectious, 52.8% was attributed to piscirickettsiosis. Sernapesca's antimicrobial report attributes 97.51% of antimicrobial use by disease among production cycles closed in 2025 to SRS. The 52.8% figure refers to infectious mortality, while the antimicrobial figure measures use among closed cycles; neither describes the share of all salmon mortality caused by SRS. (Sernapesca's 2025 health report; 2025 antimicrobial report)
The bacterium itself is part of the challenge. P. salmonis can survive inside host cells, complicating efforts to control SRS once fish are infected. A farm's temperature history still leaves open whether those fish encountered the pathogen. Consider two sites with similar warming: if infected farms lie upstream of one and the other has little exposure through connected water, their situations differ before we even look at the condition of the fish. In Los Lagos, researchers combined disease records with hydrodynamic modeling and found that the number of infected farms in upstream waters, and the severity of infection at those farms, were among the strongest determinants of modeled piscirickettsiosis prevalence. Temperature and salinity contributed too. The model does not prove exactly how bacteria moved between farms, but it shows why the temperature measured at one site may need to be read alongside what is happening in the water connected to it. (Bravo and colleagues' study)
At a site where exposure is plausible, lice pressure may affect how fish respond to P. salmonis, although the size and mechanism of that effect remain uncertain. Weekly farm data from southern Chile found that egg-bearing female Caligus rogercresseyi levels predicted both greater SRS mortality risk and an earlier first reported outbreak. The researchers proposed that lice, P. salmonis and rising temperatures may place combined stress on fish; their observational analysis cannot establish that mechanism. (Diethelm-Varela and colleagues' study)
A newly stocked site and a site months into seawater production have accumulated different exposure histories, even if today's temperature and lice counts look alike. Across 571 Atlantic salmon production cycles, a recent study found a median of 41 weeks from seawater stocking to a classified SRS outbreak, with substantial variation between cycles. Stocking season and the stage at which antimicrobial treatment began were associated with outbreak timing. Those findings are observational: farms treated at different stages may already have been following different disease trajectories. (Gaete-Carrasco and colleagues' study)
During the 1997–98 El Niño, Chile's salmon regions did experience substantial local warming. To investigate what it means for SRS as this summer develops, we will need to follow the water at farms, including the duration of warming and temperatures at fish depth, while keeping each population's stocking date, lice pressure, early mortality and possible exposure through connected waters in view. Some of those observations may move together; others may give us reason to revise what we expected from the forecast.
Temperature-data note: Manolin site-level surface-temperature analysis, 1982–2026, 1991–2020 climatological baseline. The charted tropical index is ONI; the 2026 NOAA strength forecast uses RONI.
