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A shrinking envelope? Climate warming across the Pacific coastal temperate rainforest and its projected impact on a native defoliator

Author

Listed:
  • Michael Howe

    (Pacific Northwest Research Station, USDA Forest Service
    Oak Ridge Institute for Science and Education)

  • Elizabeth E Graham

    (USDA Forest Service)

  • Kellen N Nelson

    (Pacific Northwest Research Station, USDA Forest Service)

Abstract

Temperature regulates the location, frequency, and extent of irruptive forest insect herbivore outbreak cycles. Across the Pacific coastal temperate rainforest, recent outbreaks by a native defoliator, western blackheaded budworm, have impacted the greatest land area recorded since the advent of aerial detection programs and led to widespread losses of canopy leaf area and forest growth. Evidence suggests that the geographic distribution of budworm outbreaks has tracked a poleward shift in suitable temperature across the ecoregion. In this manuscript, we compile aerial observer estimates of insect defoliation, forest inventory data, and historical and projected climate data under three emissions scenarios to hind- and forecast the distribution of budworm outbreaks from 1901 to 2100. Climate data indicate that seasonal temperatures have warmed and are projected to warm further across the ecoregion, while seasonal precipitation has and will remain relatively constant. Models indicate that a range of spring and summer temperatures primarily constrain the biogeography of budworm outbreaks, while minimum host availability, autumn and winter temperatures, and seasonal precipitation further contribute. Projected warming will shift a substantial portion of regional forestland beyond the upper temperature threshold of historic outbreaks. Thus, our forecasts suggest that budworm outbreak distribution will narrow under all three future climatic scenarios tested. Across much of the ecoregion, the distribution of forestlands suitable for budworm outbreaks is projected to shift poleward and upslope, eventually eclipsing its host’s elevational distribution. The possible disruption of periodic defoliator outbreak disturbances in this system may have important ramifications for primary productivity, forest dynamics, and forest structure.

Suggested Citation

  • Michael Howe & Elizabeth E Graham & Kellen N Nelson, 2025. "A shrinking envelope? Climate warming across the Pacific coastal temperate rainforest and its projected impact on a native defoliator," Climatic Change, Springer, vol. 178(2), pages 1-23, February.
  • Handle: RePEc:spr:climat:v:178:y:2025:i:2:d:10.1007_s10584-025-03870-2
    DOI: 10.1007/s10584-025-03870-2
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    1. Dominick A. DellaSala & Seth R. Gorelik & Wayne S. Walker, 2022. "The Tongass National Forest, Southeast Alaska, USA: A Natural Climate Solution of Global Significance," Land, MDPI, vol. 11(5), pages 1-18, May.
    2. Daniel W. Apley & Jingyu Zhu, 2020. "Visualizing the effects of predictor variables in black box supervised learning models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(4), pages 1059-1086, September.
    3. Greg Dwyer & Jonathan Dushoff & Susan Harrell Yee, 2004. "The combined effects of pathogens and predators on insect outbreaks," Nature, Nature, vol. 430(6997), pages 341-345, July.
    4. Asma Bourougaaoui & Mohamed L. Ben Jamâa & Christelle Robinet, 2021. "Has North Africa turned too warm for a Mediterranean forest pest because of climate change?," Climatic Change, Springer, vol. 165(3), pages 1-20, April.
    5. Rupert Seidl & Mart-Jan Schelhaas & Werner Rammer & Pieter Johannes Verkerk, 2014. "Increasing forest disturbances in Europe and their impact on carbon storage," Nature Climate Change, Nature, vol. 4(9), pages 806-810, September.
    6. Lorenzo Marini & Matthew Ayres & Andrea Battisti & Massimo Faccoli, 2012. "Climate affects severity and altitudinal distribution of outbreaks in an eruptive bark beetle," Climatic Change, Springer, vol. 115(2), pages 327-341, November.
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