Using spatiotemporal correlative niche models for evaluating the effects of climate change on mountain pine beetle

Aaron M Sidder,Melinda Laituri,Sunil Kumar,Jason S Sibold

doi:10.1002/ecs2.1396

Abstract

AbstractOver the last decade, western North America has experienced the largest mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreak in recorded history, and Rocky Mountain forests have been severely impacted. Although bark beetles are indigenous to North American forests, climate change has facilitated the beetle's expansion into previously unsuitable habitats. We used three correlative niche models (maximum entropy [MaxEnt], boosted regression trees, and generalized linear models) to estimate (1) the current potential distribution of the beetle in the U.S. Rocky Mountain region, (2) how this distribution has changed since historical outbreaks in the 1960s and 1970s, and (3) how the distribution may be expected to change under future climate scenarios. Additionally, we evaluated the temporal transferability of the niche models by forecasting historical models and testing the model predictions using temporally independent outbreak data from the current outbreak. Our results indicated that there has been a significant expansion of climatically suitable habitat over the past 50 yr and that much of this expansion corresponds with an upward shift in elevation across the study area. Furthermore, our models indicated that drought was a more prominent driver of current outbreak than temperature, which suggests a change in the climatic signature between historical and current outbreaks. Projections under future conditions suggest that there will be a large reduction in climatically suitable habitat for the beetle and that high‐elevation forests will continue to become more susceptible to outbreak. While all three models generated reasonable predictions, the generalized linear model correctly predicted a higher percentage of current outbreak localities when trained on historical data. Our findings suggest that researchers aiming to reduce omission error in estimates of future species responses may have greater predictive success with simpler, generalized models.

Highlights

Global surface temperatures have warmed over the last three decades, with each successive decade warmer than the preceding decade (IPCC 2014)
All models displayed a good fit, meaning they captured a large fraction of the total variability in the data, with minimal difference between training and test AUC values for the maximum entropy (MaxEnt) and generalized linear models (GLM) models
My results imply that climatic changes in the latter half of the 20th century significantly increased the amount of climatically suitable habitat for MPB in the U.S Rocky Mountain region and that the recent MPB outbreak displayed a different climatic signature than historical outbreaks

Summary

Introduction

Global surface temperatures have warmed over the last three decades, with each successive decade warmer than the preceding decade (IPCC 2014). Combined with a shift in the timing and frequency of precipitation events, the Rocky Mountain region is forecast to grow hotter and more susceptible to drought in the coming decades (Seager et al 2007, Lukas and Gordon 2015). These climatic changes portend significant ecological changes including species range shifts and an increase in landscape-shaping disturbances such as outbreaks of the mountain pine beetle (MPB, Dendroctonus ponderosae Hopkins), one of the principal drivers of landscape-level change in western North America (Dale et al 2001, Parmesan 2006, Lenoir et al 2008, Negrón and Fettig 2014). The Rocky Mountain region has previously experienced large MPB outbreaks (Assal et al 2014), but fire suppression, reduced habitat heterogeneity, and the climatic release of previously unsuitable habitats have driven an outbreak unique in its scope and intensity (Taylor and Carroll 2003, Carroll et al 2006, Raffa et al 2008)

Results

Discussion

Conclusion