KUER0%

Utah’s historic snow drought is one that trees will likely never forget 5%

By David Condos0%

3/27/2026, 11:37:22 AM

BS Summary: This article contains 26 faulty reasoning types, including Overconfidence Bias, Pessimism Bias, and Appeal to Emotion, with Negativity Bias as the most egregious example at 17.9% saturation with 136 hits. Analysis detected 1,286 faulty-reasoning hits from 761 analyzed words, generating a BS Score of 20.1% and a BS Rank of 5% (20,860 of 21,887 articles). This article is better (less manipulative) than 95.30% of the article peer group.

Utah’s towering ponderosa pines are tough customers. 
They can live for hundreds of years, surviving harsh conditions at high altitudes. 
But even giants have a breaking point. 
This winter was Utah’s warmeston record, and statewide snowpack has cratered to new record lows. 
That’s likely to leave a mark, said Justin DeRose, an associate professor of applied forest ecology at Utah State University. 
“2026 is shaping up to be a marker year in the tree ring record.” 
DeRose leads USU’s tree ring lab. 
His team reads the history of forests based on cross-section samples that show a tree’s layers of growth. 
It’s a field of science called dendrochronology. 
When a tree produces a wide ring, that tells DeRose it was a year with good growing conditions. 
A narrow ring points to a lean year. 
Scientists can match those marker years with similar patterns on nearby trees to create a timeline. 
Other bad snow years, such as 2002, 1977 and 1934, all left their mark in Utah’s tree ring history, but forests were able to bounce back. 
What’s troubling, DeRose said, is that bad marker years seem to be showing up more often. 
Utah trees produced noticeably narrow rings in both 2018 and 2021, and another is likely to be added this year. 
“We look for those marker years every couple of decades or so,” DeRose said. 
“But if they're becoming more frequent, what is that telling us about what's changing in the climate?” 
Scientists agree that climate change, driven by greenhouse gas emissions, has made many extreme events like droughts and warm spells more intense and more likely. 
If trees don’t have enough average or good years to catch their breath, that’s bad news for the health of forests that cover some of the state’s most beloved landscapes. 
“At some point, trees that continually get knocked down without being able to recover are going to grow less,” DeRose said. 
“They're going to be less competitive. 
They're going to be unable to resist the kinds of things that like to kill trees.” 
After a couple of consecutive dry seasons, he said forests could dry out and increase the area’s wildfire risk. 
Eventually, some ponderosa pine stands could die off and be replaced by a different species, such as juniper. 
Conditions will likely continue to make things harder on forests as climate change continues, said Marcos Robles, lead scientist with The Nature Conservancy in Arizona. 
A century of wildfire suppression hasn’t helped, either. 
“The climate is having an overarching impact that is reducing resilience, making these trees more vulnerable to drought and pathogens,” he said. 
“But also, we've had tremendous change in the forest conditions over the past 100 years.” 
Tree rings show that the Southwest’s forests used to burn every five to seven years, he said. 
Those natural fires removed seedlings and saplings. 
Ring records also indicate stands of ponderosa pine historically had just 10 to 20 trees per acre. 
Without fires sweeping through regularly, forest density now reaches thousands of trees per acre, Robles said, making the environment even more challenging. 
“Not only do you have a warmer climate, you also have more competition, as you have more trees that have their roots into the ground.” 
While individual forest managers may be limited in their ability to bend the curve of climate change globally, he said, there are things people can do to give trees a better chance. 
His team has partnered with the U.S. 
Forest Service on a long-term restoration project across nearly 2 million acres of Arizona. 
Over the past 15 years, they’ve thinned forests by removing hundreds of thousands of trees. 
The results so far show that this practice can significantly increase trees’ resilience to climate change, he said. 
Additional research his team is working on indicates that thinning ponderosa forests also improves snowmelt. 
When an area is packed with trees, snow is more likely to fall on branches and sublimate  get sucked into the atmosphere without becoming a liquid  before it ever reaches land. 
Their preliminary findings suggest that thinning the number of trees leads to a 10-30% increase in the amount of snowmelt and extends the snowmelt period by up to 10 days. 
“Reducing the drought risks through forest restoration not only has benefits for the forests themselves, but also for downstream communities,” Robles said. 
“That can have a big impact on the drinking water supply for millions of people across the West.” 
Disclosure: The Nature Conservancy is a financial sponsor of KUER. 
Article reasoning-pattern comparisonThis article: 6.6%David Condos: 3.1%KUER: 2.8%Confirmation Bias6.6%This article: 0.0%David Condos: 1.8%KUER: 1.3%Anchoring Bias0.0%This article: 3.4%David Condos: 3.0%KUER: 3.4%Availability Heuristic3.4%This article: 0.0%David Condos: 0.7%KUER: 1.2%Representativeness Heuristic0.0%This article: 0.0%David Condos: 0.6%KUER: 0.5%Hindsight Bias0.0%This article: 14.5%David Condos: 2.5%KUER: 1.9%Overconfidence Bias14.5%This article: 12.4%David Condos: 7.5%KUER: 7.4%Framing Effect12.4%This article: 3.9%David Condos: 2.2%KUER: 1.3%Loss Aversion3.9%This article: 0.0%David Condos: 1.0%KUER: 1.2%Status Quo Bias0.0%This article: 2.0%David Condos: 0.4%KUER: 0.3%Sunk Cost Effect2.0%This article: 6.2%David Condos: 5.8%KUER: 4.4%Optimism Bias6.2%This article: 13.0%David Condos: 5.7%KUER: 2.4%Pessimism Bias13.0%This article: 17.9%David Condos: 6.8%KUER: 6.3%Negativity Bias17.9%This article: 0.0%David Condos: 1.4%KUER: 2.2%Self-Serving Bias0.0%This article: 0.0%David Condos: 0.8%KUER: 0.9%Fundamental Attribution Error0.0%This article: 0.0%David Condos: 0.4%KUER: 0.2%Actor-Observer Bias0.0%This article: 0.0%David Condos: 1.2%KUER: 1.9%In-Group Bias0.0%This article: 0.0%David Condos: 0.4%KUER: 0.6%Out-Group Homogeneity Bias0.0%This article: 0.8%David Condos: 1.0%KUER: 2.3%Halo Effect0.8%This article: 0.0%David Condos: 0.1%KUER: 0.1%Horn Effect0.0%This article: 0.0%David Condos: 0.0%KUER: 0.0%Dunning-Kruger Effect0.0%This article: 4.7%David Condos: 1.8%KUER: 1.2%Recency Bias4.7%This article: 0.0%David Condos: 0.2%KUER: 0.3%Primacy Effect0.0%This article: 0.0%David Condos: 0.2%KUER: 0.1%Blind-Spot Bias0.0%This article: 0.0%David Condos: 0.4%KUER: 0.6%Ad Hominem0.0%This article: 0.0%David Condos: 0.3%KUER: 0.4%Straw Man0.0%This article: 8.7%David Condos: 5.6%KUER: 4.7%Appeal to Authority8.7%This article: 2.1%David Condos: 1.5%KUER: 1.7%False Dilemma2.1%This article: 7.8%David Condos: 2.3%KUER: 1.1%Slippery Slope7.8%This article: 3.3%David Condos: 0.1%KUER: 0.2%Circular Reasoning3.3%This article: 8.0%David Condos: 2.6%KUER: 4.1%Hasty Generalization8.0%This article: 0.0%David Condos: 0.1%KUER: 0.2%Red Herring0.0%This article: 0.0%David Condos: 0.5%KUER: 0.7%Bandwagon0.0%This article: 13.0%David Condos: 5.3%KUER: 5.6%Appeal to Emotion13.0%This article: 2.2%David Condos: 0.6%KUER: 0.7%Begging the Question2.2%This article: 10.4%David Condos: 2.9%KUER: 2.4%Post Hoc (False Cause)10.4%This article: 0.0%David Condos: 0.0%KUER: 0.1%Tu Quoque0.0%This article: 0.0%David Condos: 0.4%KUER: 0.4%Burden of Proof0.0%This article: 0.0%David Condos: 0.5%KUER: 0.2%Appeal to Nature0.0%This article: 3.3%David Condos: 0.3%KUER: 0.3%Composition/Division3.3%This article: 0.0%David Condos: 2.1%KUER: 3.1%Anecdotal0.0%This article: 0.0%David Condos: 0.0%KUER: 0.1%No True Scotsman0.0%This article: 4.3%David Condos: 1.0%KUER: 1.5%Ambiguity (Equivocation)4.3%This article: 0.0%David Condos: 0.0%KUER: 0.0%Gambler’s Fallacy0.0%This article: 0.0%David Condos: 0.1%KUER: 0.2%Middle Ground0.0%This article: 0.0%David Condos: 0.1%KUER: 0.1%Personal Incredulity0.0%This article: 0.0%David Condos: 0.0%KUER: 0.1%Special Pleading0.0%This article: 0.0%David Condos: 0.2%KUER: 0.2%Genetic Fallacy0.0%This article: 0.8%David Condos: 0.4%KUER: 0.8%Unattributed Quote0.8%This article: 1.8%David Condos: 0.4%KUER: 0.7%Quote-first Misdirection1.8%This article: 10.4%David Condos: 1.8%KUER: 2.2%Biased Writer Voice10.4%This article: 2.4%David Condos: 2.5%KUER: 1.6%Indoctrination2.4%This article: 0.0%David Condos: 2.1%KUER: 0.8%Politically Left Leaning Bias0.0%This article: 0.0%David Condos: 0.4%KUER: 0.3%Politically Right Leaning Bias0.0%This article: 5.3%David Condos: 0.5%KUER: 1.0%Attempt to Sell a Product or S…5.3%

761 words analyzed.

Speakers

2speakers53%attributed speech360writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 0.0% coverageWriter's voice • 7 words • 100.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 7 words • 100.0% coverageWriter's voice • 15 words • 0.0% coverageJustin DeRose • 20 words • 0.0% coverageJustin DeRose • 14 words • 100.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageJustin DeRose • 16 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageJustin DeRose • 14 words • 0.0% coverageJustin DeRose • 17 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 30 words • 100.0% coverageJustin DeRose • 21 words • 0.0% coverageJustin DeRose • 6 words • 100.0% coverageJustin DeRose • 16 words • 0.0% coverageJustin DeRose • 19 words • 0.0% coverageJustin DeRose • 18 words • 0.0% coverageMarcos Robles • 25 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageMarcos Robles • 22 words • 0.0% coverageMarcos Robles • 15 words • 0.0% coverageMarcos Robles • 17 words • 0.0% coverageMarcos Robles • 7 words • 0.0% coverageMarcos Robles • 17 words • 0.0% coverageMarcos Robles • 22 words • 0.0% coverageMarcos Robles • 25 words • 100.0% coverageMarcos Robles • 32 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageMarcos Robles • 18 words • 100.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageMarcos Robles • 22 words • 100.0% coverageMarcos Robles • 18 words • 100.0% coverageWriter's voice • 10 words • 100.0% coverage
Selected voice

Justin DeRose

91%flagged-word coverage
161 attributed words40% of attributed speech65% writer coverage
0%7.5%15.0%Biased Writer Voice-15.0 ptsWriter: 15.0%Justin DeRose: 0.0%0.0%Quote-first Misdirection+8.7 ptsWriter: 0.0%Justin DeRose: 8.7%8.7%Unattributed Quote+3.7 ptsWriter: 0.0%Justin DeRose: 3.7%3.7%

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.