Unlike us, wildfire smoke has little health effect on Michigan’s tree canopy 59%

By Amanda LeClaire83%

7/24/2026, 6:49:03 PM

BS Summary: This article contains 12 faulty reasoning types, including Framing Effect, Biased Writer Voice, and Optimism Bias, with Appeal to Authority as the most egregious example at 20.7% saturation with 56 hits. Analysis detected 312 faulty-reasoning hits from 270 analyzed words, generating a BS Score of 54.9% and a BS Rank of 59% (9,175 of 21,887 articles). This article is worse (more manipulative) than 58.10% of the article peer group.

Michigan’s air quality declined dangerously earlier this month due to wildfire smoke from Minnesota and Canada. 
Pollutants in the smoke can have long-term health consequences for humans, pets, and wildlife. 
However, for trees themselves the health effects are less consequential. 
Wayne State University forestry professor Dan Kashian says that while our tree canopy is important for converting carbon dioxide into life-supporting oxygen, days or even weeks of heavy smoke plumes is unlikely to harm Michigan’s trees. 
He says the main effect would be on the amount of sunlight on smokey days. 
Kashian says, “Trees need to photosynthesize…anything that affects the amount of light that they’re receiving is going to affect how well they can grow.” 
According to Kashian, harmful pollutants from wildfire smoke can settle on leaves but are often washed away by rain without lasting harm to the tree’s health. 
“But when you’re talking about a couple of days of heavy smoke like this, especially when it’s hot, it can actually help them because they don’t really like really high temperatures either,” Kashian says. 
This story is a part of WDET’s ongoing series, the Detroit Tree Canopy Project . 
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The post Unlike us, wildfire smoke has little health effect on Michigan’s tree canopy appeared first on WDET 101.9 FM . 
Article reasoning-pattern comparisonThis article: 9.6%Amanda LeClaire: 5.1%WDET: 1.7%Confirmation Bias9.6%This article: 0.0%Amanda LeClaire: 1.3%WDET: 0.4%Anchoring Bias0.0%This article: 5.2%Amanda LeClaire: 2.1%WDET: 2.3%Availability Heuristic5.2%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.7%Representativeness Heuristic0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.2%Hindsight Bias0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 1.0%Overconfidence Bias0.0%This article: 17.0%Amanda LeClaire: 3.7%WDET: 4.7%Framing Effect17.0%This article: 0.0%Amanda LeClaire: 0.7%WDET: 0.9%Loss Aversion0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.3%Status Quo Bias0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.1%Sunk Cost Effect0.0%This article: 12.6%Amanda LeClaire: 8.1%WDET: 3.5%Optimism Bias12.6%This article: 0.0%Amanda LeClaire: 0.4%WDET: 0.9%Pessimism Bias0.0%This article: 5.9%Amanda LeClaire: 5.7%WDET: 3.4%Negativity Bias5.9%This article: 6.3%Amanda LeClaire: 2.1%WDET: 1.6%Self-Serving Bias6.3%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.2%Fundamental Attribution Error0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.1%Actor-Observer Bias0.0%This article: 0.0%Amanda LeClaire: 0.8%WDET: 1.2%In-Group Bias0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.6%Out-Group Homogeneity Bias0.0%This article: 0.0%Amanda LeClaire: 4.5%WDET: 5.6%Halo Effect0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.0%Horn Effect0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Amanda LeClaire: 0.7%WDET: 0.9%Recency Bias0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.3%Primacy Effect0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.0%Blind-Spot Bias0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.2%Ad Hominem0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.1%Straw Man0.0%This article: 20.7%Amanda LeClaire: 12.3%WDET: 3.3%Appeal to Authority20.7%This article: 0.0%Amanda LeClaire: 0.0%WDET: 1.0%False Dilemma0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.0%Slippery Slope0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.1%Circular Reasoning0.0%This article: 12.6%Amanda LeClaire: 6.6%WDET: 3.4%Hasty Generalization12.6%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.1%Red Herring0.0%This article: 0.0%Amanda LeClaire: 0.1%WDET: 0.5%Bandwagon0.0%This article: 0.0%Amanda LeClaire: 7.0%WDET: 4.6%Appeal to Emotion0.0%This article: 0.0%Amanda LeClaire: 0.8%WDET: 0.6%Begging the Question0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 1.5%Post Hoc (False Cause)0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.0%Tu Quoque0.0%This article: 0.0%Amanda LeClaire: 1.0%WDET: 0.4%Burden of Proof0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.1%Appeal to Nature0.0%This article: 0.0%Amanda LeClaire: 1.1%WDET: 0.1%Composition/Division0.0%This article: 0.0%Amanda LeClaire: 1.8%WDET: 1.8%Anecdotal0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.1%No True Scotsman0.0%This article: 4.4%Amanda LeClaire: 0.7%WDET: 1.2%Ambiguity (Equivocation)4.4%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.1%Middle Ground0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.1%Personal Incredulity0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.1%Special Pleading0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.0%Genetic Fallacy0.0%This article: 0.0%Amanda LeClaire: 1.8%WDET: 0.8%Unattributed Quote0.0%This article: 0.0%Amanda LeClaire: 1.5%WDET: 0.7%Quote-first Misdirection0.0%This article: 13.3%Amanda LeClaire: 6.6%WDET: 4.1%Biased Writer Voice13.3%This article: 1.1%Amanda LeClaire: 7.7%WDET: 2.6%Indoctrination1.1%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.3%Politically Left Leaning Bias0.0%This article: 0.0%Amanda LeClaire: 0.0%WDET: 0.1%Politically Right Leaning Bias0.0%This article: 6.7%Amanda LeClaire: 5.5%WDET: 7.1%Attempt to Sell a Product or S…6.7%

270 words analyzed.

Speakers

2speakers72%attributed speech76writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageDan Kashian • 36 words • 100.0% coverageDan Kashian • 15 words • 0.0% coverageDan Kashian • 24 words • 0.0% coverageDan Kashian • 26 words • 0.0% coverageDan Kashian • 34 words • 0.0% coverageWDET • 15 words • 0.0% coverageWriter's voice • 3 words • 100.0% coverageWDET • 9 words • 0.0% coverageWDET • 17 words • 0.0% coverageWDET • 18 words • 100.0% coverageWriter's voice • 21 words • 0.0% coverage
Selected voice

Dan Kashian

89%flagged-word coverage
135 attributed words70% of attributed speech72% writer coverage
0%15.0%30.0%Biased Writer Voice+26.7 ptsWriter: 0.0%Dan Kashian: 26.7%26.7%Indoctrination-3.9 ptsWriter: 3.9%Dan Kashian: 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.