Why more extreme rain could mean more shark bites 31%

By Sam Nichols0%

7/8/2026, 10:30:00 AM

BS Summary: This article contains 23 faulty reasoning types, including Ambiguity (Equivocation), Confirmation Bias, and Hasty Generalization, with Post Hoc (False Cause) as the most egregious example at 26.2% saturation with 156 hits. Analysis detected 1,102 faulty-reasoning hits from 595 analyzed words, generating a BS Score of 40.5% and a BS Rank of 31% (14,702 of 21,202 articles). This article is better (less manipulative) than 69.30% of the article peer group.

In the space of just 48 hours this past January, four people were bitten by sharks along Australia’s east coast, with a 12-year-old boy dying from his injuries. 
Just one day prior, record-setting rain soaked the region. 
That sequence of events may not have been a coincidence: a growing body of research suggests that shark bites, though rare, may become less so as climate change triggers more heavy rain events, altering shark behavior. 
As with any shark bite, it’s impossible to determine the exact drivers behind this January cluster, says Charlie Huveneers, director of Flinders University’s Marine and Coastal Research Consortium in Australia. 
But the rainfall, he says, likely contributed: “It might be that because of the rain, they were more concentrated at that time.” 
The theory is that the deluge, which broke January daily rainfall records for Sydney, flushed sewage and other waste into the nearby coastal waters, attracting baitfish, which in turn lured sharks closer to shore. 
Previous studies in Australia have shown this correlation, including one analysis that suggests bites from tiger sharks are more common following heavy rainfall. 
Other research has found that increased sediment in water—common following intense rain—also raises risks because it reduces water visibility, making it more difficult for sharks to see and avoid people. 
Additional factors were likely at play in the January encounters, Huveneers says, including summer temperatures that drove people into the ocean. 
Bull sharks, the species believed to be behind the January bites, are also more common in the local waters during warmer months. 
“It really goes back to this overlap between people and sharks,” he says. 
Though extreme rain may not be the only factor behind the cluster, its likely involvement raises the question of how the risk of shark bites might change as these events become more frequent and severe globally, including in the U.S., where shark encounters are reported most. 
“Extreme rainfall is expected to increase in general because a warmer atmosphere can hold more water,” says John Nielsen-Gammon, a meteorologist at Texas A&M University. 
“And, of course, more extreme rainfall leads to more extreme runoff.” 
Figuring out the relationship between heavy rains and shark bites is complicated, though, because there’s a lot we don’t know about what drives a shark to bite someone, says Catherine Macdonald, director of the University of Miami’s Shark Research and Conservation Program. 
What we do know is that climate change is influencing their behavior. 
Rising ocean temperatures are already changing migration patterns, research suggests. 
One 2022 study tracking tiger sharks along the U.S. 
East Coast found that populations over the previous decade had increasingly shifted north. 
But different shark species and even different individuals within species may react differently to these changes, says shark scientist Neil Hammerschlag, executive director of the not-for-profit Shark Research Foundation and the 2022 study’s lead author. 
Warmer oceans may repel some species from coastlines while luring others toward it, he says. 
And though extreme rainfall may help attract baitfish closer to shore, the influx of fresh water lowers salinity levels, driving some shark species away. 
People shouldn’t be afraid, Hammerschlag says, because human-shark encounters are extremely rare—you’re statistically more likely to be killed by lightning. 
Instead beachgoers should be “shark smart” by knowing, for example, when and where certain species are typically most active or avoiding swimming at dusk and dawn. 
Proximity doesn’t guarantee interaction, he says, but the formula for any bite requires it. 
“And any environmental condition that makes those things happen will increase the chance of human-shark interaction.” 
Article reasoning-pattern comparisonThis article: 17.5%Sam Nichols: 5.9%Scientific American: 3.0%Confirmation Bias17.5%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.9%Anchoring Bias0.0%This article: 8.6%Sam Nichols: 3.7%Scientific American: 2.6%Availability Heuristic8.6%This article: 3.7%Sam Nichols: 0.9%Scientific American: 1.2%Representativeness Heuristic3.7%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.4%Hindsight Bias0.0%This article: 2.0%Sam Nichols: 1.5%Scientific American: 2.5%Overconfidence Bias2.0%This article: 5.5%Sam Nichols: 1.8%Scientific American: 4.2%Framing Effect5.5%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.3%Loss Aversion0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.9%Status Quo Bias0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.1%Sunk Cost Effect0.0%This article: 3.4%Sam Nichols: 0.8%Scientific American: 3.0%Optimism Bias3.4%This article: 0.0%Sam Nichols: 0.0%Scientific American: 1.1%Pessimism Bias0.0%This article: 4.7%Sam Nichols: 3.9%Scientific American: 3.3%Negativity Bias4.7%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.3%Self-Serving Bias0.0%This article: 3.5%Sam Nichols: 0.9%Scientific American: 0.3%Fundamental Attribution Error3.5%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.2%Actor-Observer Bias0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.1%In-Group Bias0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.0%Out-Group Homogeneity Bias0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.9%Halo Effect0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.0%Horn Effect0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.0%Dunning-Kruger Effect0.0%This article: 11.4%Sam Nichols: 3.2%Scientific American: 0.8%Recency Bias11.4%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.2%Primacy Effect0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.0%Blind-Spot Bias0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.1%Ad Hominem0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.3%Straw Man0.0%This article: 5.9%Sam Nichols: 2.4%Scientific American: 4.3%Appeal to Authority5.9%This article: 0.0%Sam Nichols: 0.0%Scientific American: 1.8%False Dilemma0.0%This article: 11.3%Sam Nichols: 4.7%Scientific American: 0.8%Slippery Slope11.3%This article: 2.4%Sam Nichols: 0.6%Scientific American: 0.1%Circular Reasoning2.4%This article: 13.8%Sam Nichols: 6.9%Scientific American: 4.1%Hasty Generalization13.8%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.2%Red Herring0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.6%Bandwagon0.0%This article: 7.7%Sam Nichols: 3.1%Scientific American: 4.2%Appeal to Emotion7.7%This article: 1.8%Sam Nichols: 0.5%Scientific American: 0.6%Begging the Question1.8%This article: 26.2%Sam Nichols: 15.1%Scientific American: 2.9%Post Hoc (False Cause)26.2%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.0%Tu Quoque0.0%This article: 4.4%Sam Nichols: 1.1%Scientific American: 0.6%Burden of Proof4.4%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.4%Appeal to Nature0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.3%Composition/Division0.0%This article: 8.4%Sam Nichols: 3.3%Scientific American: 1.0%Anecdotal8.4%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.1%No True Scotsman0.0%This article: 23.9%Sam Nichols: 6.0%Scientific American: 2.2%Ambiguity (Equivocation)23.9%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.0%Gambler’s Fallacy0.0%This article: 2.5%Sam Nichols: 0.6%Scientific American: 0.3%Middle Ground2.5%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.1%Personal Incredulity0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.2%Special Pleading0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.0%Genetic Fallacy0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.7%Unattributed Quote0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.7%Quote-first Misdirection0.0%This article: 7.9%Sam Nichols: 2.0%Scientific American: 4.3%Biased Writer Voice7.9%This article: 4.4%Sam Nichols: 4.4%Scientific American: 1.8%Indoctrination4.4%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.0%Politically Left Leaning Bias0.0%This article: 0.0%Sam Nichols: 0.0%Scientific American: 0.0%Politically Right Leaning Bias0.0%This article: 4.4%Sam Nichols: 1.1%Scientific American: 1.7%Attempt to Sell a Product or S…4.4%

595 words analyzed.

Speakers

5speakers44%attributed speech331writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 9 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 36 words • 100.0% coverageCharlie Huveneers • 30 words • 0.0% coverageCharlie Huveneers • 22 words • 0.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageHuveneers • 21 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageCharlie Huveneers • 13 words • 0.0% coverageWriter's voice • 46 words • 0.0% coverageJohn Nielsen-Gammon • 25 words • 0.0% coverageJohn Nielsen-Gammon • 11 words • 100.0% coverageCatherine Macdonald • 42 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageNeil Hammerschlag • 35 words • 0.0% coverageNeil Hammerschlag • 15 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageNeil Hammerschlag • 20 words • 0.0% coverageWriter's voice • 26 words • 100.0% coverageNeil Hammerschlag • 14 words • 0.0% coverageNeil Hammerschlag • 16 words • 0.0% coverage
Selected voice

Huveneers

100%flagged-word coverage
21 attributed words8.0% of attributed speech95% writer coverage
0%7.5%15.0%Biased Writer Voice-10.9 ptsWriter: 10.9%Huveneers: 0.0%0.0%Indoctrination-7.9 ptsWriter: 7.9%Huveneers: 0.0%0.0%Attempt to Sell a Product -7.9 ptsWriter: 7.9%Huveneers: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.