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Modeling Tree Recovery in Wind-Disturbed Forests with Dense Understory Species under Climate Change

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  • Haga, Chihiro
  • Hotta, Wataru
  • Inoue, Takahiro
  • Matsui, Takanori
  • Aiba, Masahiro
  • Owari, Toshiaki
  • Suzuki, Satoshi N.
  • Shibata, Hideaki
  • Morimoto, Junko

Abstract

Future climate conditions will alter the frequency and intensity of typhoons. Thus, post-windthrow management, which can enhance tree recovery in wind-disturbed forests with dense understory species, is essential for sustainable forest management to adapt to climate change. This study explores management options that can recover the above-ground biomass (AGB) and tree species composition after windthrow damage even under climate change. A case study area was established in the Oshima–Hiyama National Forest in southern Hokkaido, northern Japan, which were damaged by typhoons in late August 2016. We incorporated the understory species Sasa kurilensis as understory vegetation into the LANDIS-II Net Ecosystem Carbon and Nitrogen Succession extension v6.3 model to simulate the outcome of tree establishment under climate change. AGB recovery up to the year 2100 at 1,753 damaged grid cells was simulated for the Intergovernmental Panel on Climate Change representative concentration pathway (RCP) 2.6 and 8.5 scenarios. Different post-windthrow management cases were designed by varying the treatment of fallen trees and the types of trees planted. The results demonstrated that salvage logging and planting successfully recovered the AGB by 2050 at the landscape scale regardless of the climate change scenario, whereas leaving fallen trees in the damaged site or salvage logging only did not facilitate the recovery of AGB. Leaving fallen trees in damaged grid cells as ecological legacies recovered the AGB only in damaged grid cells with a sufficient number of advanced seedlings of adequate types of species irrespective of the climate change scenario. The decreasing water equivalent of snowpack in the RCP scenarios caused Sasa kurilensis mortality and promoted the recovery of AGB of trees. The dominant species recovered in natural forests, which experienced either salvage logging or leaving trees in the damaged site, varied among climate change scenarios. The warmer climate condition facilitated the recovery of Fagus crenata by 2100. These results can help designing a robust forest recovery even in uncertain future climate.

Suggested Citation

  • Haga, Chihiro & Hotta, Wataru & Inoue, Takahiro & Matsui, Takanori & Aiba, Masahiro & Owari, Toshiaki & Suzuki, Satoshi N. & Shibata, Hideaki & Morimoto, Junko, 2022. "Modeling Tree Recovery in Wind-Disturbed Forests with Dense Understory Species under Climate Change," Ecological Modelling, Elsevier, vol. 472(C).
    • Handle: RePEc:eee:ecomod:v:472:y:2022:i:c:s030438002200179x
    DOI: 10.1016/j.ecolmodel.2022.110072
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    References listed on IDEAS

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    1. Seidl, Rupert & Fernandes, Paulo M. & Fonseca, Teresa F. & Gillet, François & Jönsson, Anna Maria & Merganičová, Katarína & Netherer, Sigrid & Arpaci, Alexander & Bontemps, Jean-Daniel & Bugmann, Hara, 2011. "Modelling natural disturbances in forest ecosystems: a review," Ecological Modelling, Elsevier, vol. 222(4), pages 903-924.
    2. Tobias Houska & Philipp Kraft & Alejandro Chamorro-Chavez & Lutz Breuer, 2015. "SPOTting Model Parameters Using a Ready-Made Python Package," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-22, December.
    3. Scheller, Robert M. & Domingo, James B. & Sturtevant, Brian R. & Williams, Jeremy S. & Rudy, Arnold & Gustafson, Eric J. & Mladenoff, David J., 2007. "Design, development, and application of LANDIS-II, a spatial landscape simulation model with flexible temporal and spatial resolution," Ecological Modelling, Elsevier, vol. 201(3), pages 409-419.
    4. Scheller, Robert M. & Hua, Dong & Bolstad, Paul V. & Birdsey, Richard A. & Mladenoff, David J., 2011. "The effects of forest harvest intensity in combination with wind disturbance on carbon dynamics in Lake States Mesic Forests," Ecological Modelling, Elsevier, vol. 222(1), pages 144-153.
    5. Rupert Seidl & Dominik Thom & Markus Kautz & Dario Martin-Benito & Mikko Peltoniemi & Giorgio Vacchiano & Jan Wild & Davide Ascoli & Michal Petr & Juha Honkaniemi & Manfred J. Lexer & Volodymyr Trotsi, 2017. "Forest disturbances under climate change," Nature Climate Change, Nature, vol. 7(6), pages 395-402, June.
    6. De Jager, Nathan R. & Drohan, Patrick J. & Miranda, Brian M. & Sturtevant, Brian R. & Stout, Susan L. & Royo, Alejandro A. & Gustafson, Eric J. & Romanski, Mark C., 2017. "Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II," Ecological Modelling, Elsevier, vol. 350(C), pages 11-29.
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