Abstract. Boreal forests of Siberia play a relevant role in the global carbon cycle. However, global warming threatens the existence of summergreen larch-dominated ecosystems, likely enabling a transition to evergreen tree taxa with deeper active layers. Complex permafrost–vegetation interactions make it uncertain whether these ecosystems could develop into a carbon source rather than continuing atmospheric carbon sequestration under global warming. Consequently, shedding light on the role of current and future active layer dynamics and the feedbacks with the apparent tree species is crucial to predict boreal forest transition dynamics and thus for aboveground forest biomass and carbon stock developments. Hence, we established a coupled model version amalgamating a one-dimensional permafrost multilayer forest land-surface model (CryoGrid) with LAVESI, an individual-based and spatially explicit forest model for larch species (Larix Mill.), extended for this study by including other relevant Siberian forest species and explicit terrain. Following parameterization, we ran simulations with the coupled version to the near future to 2030 with a mild climate-warming scenario. We focus on three regions covering a gradient of summergreen forests in the east at Spasskaya Pad, mixed summergreen–evergreen forests close to Nyurba, and the warmest area at Lake Khamra in the southeast of Yakutia, Russia. Coupled simulations were run with the newly implemented boreal forest species and compared to runs allowing only one species at a time, as well as to simulations using just LAVESI. Results reveal that the coupled version corrects for overestimation of active layer thickness (ALT) and soil moisture, and large differences in established forests are simulated. We conclude that the coupled version can simulate the complex environment of eastern Siberia by reproducing vegetation patterns, making it an excellent tool to disentangle processes driving boreal forest dynamics.
Abstract. Boreal forests of Siberia play a relevant role in the global carbon cycle. However, global warming threatens the existence of summergreen larch-dominated ecosystems likely enabling a transition to evergreen tree taxa with deeper active layers. Complex permafrost-vegetation interactions make it uncertain whether these ecosystems could develop into a carbon source rather than continuing atmospheric carbon sequestration under global warming. Consequently, shedding light on the role of current and future active-layer dynamics and the feedbacks with the apparent tree species is crucial to predict boreal forest transition dynamics, and thus for aboveground forest biomass and carbon stock developments. Hence, we established a coupled model version amalgamating a one-dimensional permafrost-multilayer forest land-surface model (CryoGrid), with LAVESI, an individual-based and spatially explicit forest model for larch species (Larix Mill.), extended for this study by including other relevant Siberian forest species and explicit terrain. Following parametrization, we ran simulations with the coupled version to the near future to 2030 with a mild climate-warming scenario. We focus on three regions, covering a gradient of summergreen forests in the east at Spasskaya Pad to mixed summergreen-evergreen forests close to Nyurba, and the warmest area at Lake Khamra in the south-east of Yakutia, Russia. Coupled simulations were run with the newly implemented boreal forest species and compared to runs allowing only one species at a time, as well as to simulations using just LAVESI. Results reveal that the coupled version corrects for overestimation of active-layer thickness (ALT) and soil moisture and large differences in established forests are simulated. We conclude that the coupled version can simulate the complex environment of central Siberia reproducing vegetation patterns making it an excellent tool to disentangle processes driving boreal forest dynamics.
<p>Even though wildfires are an important ecological component of larch-dominated boreal forests in eastern Siberia, intensifying fire regimes may induce large-scale shifts in forest structure and composition. Recent paleoecological research suggests that such a state change, apart from threatening human livelihoods, may result in a positive feedback on intensifying wildfires and increased permafrost degradation [1]. Common fire-vegetation models mostly do not explicitly include detailed individual-based tree population dynamics. However, setting a focus on patterns of forest structure emerging from interactions among individual trees in the unique forest system of eastern Siberia may provide beneficial perspectives on the impacts of changing fire regimes. LAVESI (<em>Larix</em> Vegetation Simulator) has been previously introduced as an individual-based, spatially explicit vegetation model for simulating fine-scale tree population dynamics [2]. It has since been expanded with wind-driven pollen dispersal, landscape topography, and the inclusion of multiple tree species. However, until now, it could not be used to simulate effects of changing fire regimes on those detailed tree population dynamics.</p> <p>We present simulations of annually computed tree populations during the past c. 20,000 years in LAVESI, while applying a newly implemented fire module. Wildfire ignitions can stochastically occur depending on the monthly fire weather. Within the affected area, fire intensity is mediated by surface moisture. Fire severity depends on the intensity, with scaled impacts on trees, seeds and the litter layer. Each tree has a chance to survive wildfires based on a resistivity estimated from its height and species-specific traits of bark thickness, crown height, and their ability to resprout. The modelled annual fire probability compares well with a local reconstruction of charcoal influx in lake sediments. Simulation results at a study site in Central Yakutia, Siberia, indicate that the inclusion of wildfires leads to a higher number of tree individuals and increased population size variability compared to simulations without fires. In the Late Pleistocene forests establish earlier when wildfires can occur. The new fire component enables LAVESI to serve as a tool to analyze effects of varying fire return intervals and fire intensities on long-term tree population dynamics, improving our understanding of potential state transitions in the Siberian boreal forest.</p> <p><strong>References:</strong></p> <p>[1] Gl&#252;ckler R. et al.: Holocene wildfire and vegetation dynamics in Central Yakutia, Siberia, reconstructed from lake-sediment proxies, <em>Frontiers in Ecology and Evolution</em> 10, 2022.</p> <p>[2] Kruse S. et al.: Treeline dynamics in Siberia under changing climates as inferred from an individual-based model for Larix, <em>Ecological Modelling</em> 338, 101&#8211;121, 2016.</p>
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