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The Changing Strength and Nature of Fire-Climate Relationships in the Northern Rocky Mountains, U.S.A., 1902-2008.

Higuera PE, Abatzoglou JT, Littell JS, Morgan P - PLoS ONE (2015)

Bottom Line: This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift.Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone.Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity.

View Article: PubMed Central - PubMed

Affiliation: College of Natural Resources, University of Idaho, Moscow, Idaho, United States of America.

ABSTRACT
Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity.

No MeSH data available.


Related in: MedlinePlus

Calibration accuracy and cross-validation skill of potential predictors of annual area burned.(A) Accuracy (r2 or R2adj) from the 87 continuous 21-yr regression models. Metrics are ranked (top to bottom) based on the median value. Boxplots display the median, 25th, and 75th quantiles, and whiskers extend to extreme values not considered outliers. (B) Cross-validation skill, CE, for all 87 cross-validation periods. Metrics are ranked from left to right based on the median value; CE ≤ 0 indicates no predictive skill. (C) Calibration accuracy as a function of cross-validation skill, where darker grey indicates a greater proportion of values. Overall metric rank (i.e., CE * r2 or R2adj) is indicated by the within-plot numbers.
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pone.0127563.g004: Calibration accuracy and cross-validation skill of potential predictors of annual area burned.(A) Accuracy (r2 or R2adj) from the 87 continuous 21-yr regression models. Metrics are ranked (top to bottom) based on the median value. Boxplots display the median, 25th, and 75th quantiles, and whiskers extend to extreme values not considered outliers. (B) Cross-validation skill, CE, for all 87 cross-validation periods. Metrics are ranked from left to right based on the median value; CE ≤ 0 indicates no predictive skill. (C) Calibration accuracy as a function of cross-validation skill, where darker grey indicates a greater proportion of values. Overall metric rank (i.e., CE * r2 or R2adj) is indicated by the within-plot numbers.

Mentions: Top predictors in the global analysis were also top predictors in the 21-yr, local analyses, lead by the multiple regression model including DMC and GDD0, and followed closely by the single-variable models of DMC and Soil Moisture (Table 2, Fig 4C). Calibration accuracy was also high for fire-danger and water-balance metrics, including Soil Moisture, DMC, Drought Code, and June-August Potential Evapotranspiration (PETJJA; Table 2, Fig 4A). The multiple regression model including DMC and GDD0 had higher accuracy (median R2adj = 0.483) relative to the model combining March-May and July-August temperature with June-August precipitation (TMAM, TJA, and PJJA; median R2adj = 0.371).


The Changing Strength and Nature of Fire-Climate Relationships in the Northern Rocky Mountains, U.S.A., 1902-2008.

Higuera PE, Abatzoglou JT, Littell JS, Morgan P - PLoS ONE (2015)

Calibration accuracy and cross-validation skill of potential predictors of annual area burned.(A) Accuracy (r2 or R2adj) from the 87 continuous 21-yr regression models. Metrics are ranked (top to bottom) based on the median value. Boxplots display the median, 25th, and 75th quantiles, and whiskers extend to extreme values not considered outliers. (B) Cross-validation skill, CE, for all 87 cross-validation periods. Metrics are ranked from left to right based on the median value; CE ≤ 0 indicates no predictive skill. (C) Calibration accuracy as a function of cross-validation skill, where darker grey indicates a greater proportion of values. Overall metric rank (i.e., CE * r2 or R2adj) is indicated by the within-plot numbers.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4482589&req=5

pone.0127563.g004: Calibration accuracy and cross-validation skill of potential predictors of annual area burned.(A) Accuracy (r2 or R2adj) from the 87 continuous 21-yr regression models. Metrics are ranked (top to bottom) based on the median value. Boxplots display the median, 25th, and 75th quantiles, and whiskers extend to extreme values not considered outliers. (B) Cross-validation skill, CE, for all 87 cross-validation periods. Metrics are ranked from left to right based on the median value; CE ≤ 0 indicates no predictive skill. (C) Calibration accuracy as a function of cross-validation skill, where darker grey indicates a greater proportion of values. Overall metric rank (i.e., CE * r2 or R2adj) is indicated by the within-plot numbers.
Mentions: Top predictors in the global analysis were also top predictors in the 21-yr, local analyses, lead by the multiple regression model including DMC and GDD0, and followed closely by the single-variable models of DMC and Soil Moisture (Table 2, Fig 4C). Calibration accuracy was also high for fire-danger and water-balance metrics, including Soil Moisture, DMC, Drought Code, and June-August Potential Evapotranspiration (PETJJA; Table 2, Fig 4A). The multiple regression model including DMC and GDD0 had higher accuracy (median R2adj = 0.483) relative to the model combining March-May and July-August temperature with June-August precipitation (TMAM, TJA, and PJJA; median R2adj = 0.371).

Bottom Line: This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift.Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone.Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity.

View Article: PubMed Central - PubMed

Affiliation: College of Natural Resources, University of Idaho, Moscow, Idaho, United States of America.

ABSTRACT
Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity.

No MeSH data available.


Related in: MedlinePlus