2023
DOI: 10.1186/s42408-023-00188-1
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Simulating dynamic fire regime and vegetation change in a warming Siberia

Abstract: Background Climate change is expected to increase fire activity across the circumboreal zone, including central Siberia. However, few studies have quantitatively assessed potential changes in fire regime characteristics, or considered possible spatial variation in the magnitude of change. Moreover, while simulations indicate that changes in climate are likely to drive major shifts in Siberian vegetation, knowledge of future forest dynamics under the joint influence of changes in climate and fir… Show more

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Cited by 7 publications
(2 citation statements)
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“…We acknowledge, however, modelling limitations whose future incorporation in the model would improve the accuracy of our predictions. For example, directly addressing the effects of climate on vegetation is relevant to simulate landscape dynamics in the future (Williams et al 2023), particularly the post-re resprouters dynamics of some oak and shrub species (Batllori et al 2019;Baudena et al 2020) or future expansion of sweet chestnuts (Freitas et al 2021) in Mediterranean landscapes. Also, better integration of re-adaption traits of modelled species would improve the simulation of i) post-re regeneration, for example, by including variability in the degree of serotiny among individuals in P. pinaster stands depending on re regimes since it can affect the capacity of individuals to disperse and persist in the landscape (Hernández-Serrano et al 2013; Tapias et al 2004); or ii) re-resistance, for example, the bark thickness in P. menziesii provides resistance to most surface res (Uchytil 1991), but due to re-vegetation simulation mechanism, the user-de ned threshold in BFOLDS-FRM based on re intensity to kill vegetation (> 500 kW/m) overrides the " re tolerance" trait assigned to the species in the Age-Only extension, thereby potentially modifying species response to re.…”
Section: Modelling Limitationsmentioning
confidence: 99%
“…We acknowledge, however, modelling limitations whose future incorporation in the model would improve the accuracy of our predictions. For example, directly addressing the effects of climate on vegetation is relevant to simulate landscape dynamics in the future (Williams et al 2023), particularly the post-re resprouters dynamics of some oak and shrub species (Batllori et al 2019;Baudena et al 2020) or future expansion of sweet chestnuts (Freitas et al 2021) in Mediterranean landscapes. Also, better integration of re-adaption traits of modelled species would improve the simulation of i) post-re regeneration, for example, by including variability in the degree of serotiny among individuals in P. pinaster stands depending on re regimes since it can affect the capacity of individuals to disperse and persist in the landscape (Hernández-Serrano et al 2013; Tapias et al 2004); or ii) re-resistance, for example, the bark thickness in P. menziesii provides resistance to most surface res (Uchytil 1991), but due to re-vegetation simulation mechanism, the user-de ned threshold in BFOLDS-FRM based on re intensity to kill vegetation (> 500 kW/m) overrides the " re tolerance" trait assigned to the species in the Age-Only extension, thereby potentially modifying species response to re.…”
Section: Modelling Limitationsmentioning
confidence: 99%
“…The most dramatic changes are expected in the boreal zone, where the temperature could rise by 7 • C [3]. Large carbon pools in boreal forests are vulnerable to climate change, which calls into question the status of these forests as a carbon sink in the near future [1,[4][5][6].…”
Section: Introductionmentioning
confidence: 99%