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Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II

Author

Listed:
  • 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.

Abstract

Browsing ungulates alter forest productivity and vegetation succession through selective foraging on species that often dominate early succession. However, the long-term and large-scale effects of browsing on forest succession are not possible to project without the use of simulation models. To explore the effects of ungulates on succession in a spatially explicit manner, we developed a Browse Extension that simulates the effects of browsing ungulates on the growth and survival of plant species cohorts within the LANDIS-II spatially dynamic forest landscape simulation model framework. We demonstrate the capabilities of the new extension and explore the spatial effects of ungulates on forest composition and dynamics using two case studies. The first case study examined the long-term effects of persistently high white-tailed deer browsing rates in the northern hardwood forests of the Allegheny National Forest, USA. In the second case study, we incorporated a dynamic ungulate population model to simulate interactions between the moose population and boreal forest landscape of Isle Royale National Park, USA. In both model applications, browsing reduced total aboveground live biomass and caused shifts in forest composition. Simulations that included effects of browsing resulted in successional patterns that were more similar to those observed in the study regions compared to simulations that did not incorporate browsing effects. Further, model estimates of moose population density and available forage biomass were similar to previously published field estimates at Isle Royale and in other moose-boreal forest systems. Our simulations suggest that neglecting effects of browsing when modeling forest succession in ecosystems known to be influenced by ungulates may result in flawed predictions of aboveground biomass and tree species composition.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ecomod:v:350:y:2017:i:c:p:11-29
    DOI: 10.1016/j.ecolmodel.2017.01.014
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    References listed on IDEAS

    as
    1. 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.
    2. Riggs, Robert A. & Keane, Robert E. & Cimon, Norm & Cook, Rachel & Holsinger, Lisa & Cook, John & DelCurto, Timothy & Baggett, L.Scott & Justice, Donald & Powell, David & Vavra, Martin & Naylor, Bridg, 2015. "Biomass and fire dynamics in a temperate forest-grassland mosaic: Integrating multi-species herbivory, climate, and fire with the FireBGCv2/GrazeBGC system," Ecological Modelling, Elsevier, vol. 296(C), pages 57-78.
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    Cited by:

    1. 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).
    2. Barrere, Julien & Ligot, Gauthier & Boulanger, Vincent & Collet, Catherine & Courbaud, Benoît & de Coligny, François & Mårell, Anders & Saïd, Sonia & Balandier, Philippe, 2024. "Oak regeneration facing deer browsing: Can competition between saplings offset the diversion effect? A simulation experiment," Ecological Modelling, Elsevier, vol. 489(C).

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