ALBERT

Description: It is of major interest to estimate the feedback of arctic ecosystems to the global warming we expect in upcoming decades. The speed of this response is driven by the potential of species to migrate, tracking their climate optimum. For this, sessile plants have to produce and disperse seeds to newly available habitats, and pollination is needed for the seeds to be viable. These two processes are also the vectors that pass genetic information through a population. A restricted exchange among subpopulations might lead to a maladapted population due to diversity losses. Hence, a realistic implementation of these dispersal processes into a simulation model would allow an assessment of the importance of diversity for the migration of plant species in various environments worldwide. To date, dynamic global vegetation models have been optimised for a global application and overestimate the migration of biome shifts in currently warming temperatures. We hypothesise that this is caused by neglecting important fine-scale processes, which are necessary to estimate realistic vegetation trajectories. Recently, we built and parameterised a simulation model LAVESI for larches that dominate the latitudinal treelines in the northernmost areas of Siberia. In this study, we updated the vegetation model by including seed and pollen dispersal driven by wind speed and direction. The seed dispersal is modelled as a ballistic flight, and for the pollination of seeds produced, we implemented a wind-determined and distance-dependent probability distribution function using a von Mises distribution to select the potential pollen donor. This individual-based and spatially explicit implementation of both dispersal processes makes it easily feasible to inherit plant traits and genetic information to assess the impact of migration processes on the genetics. The final model can substantially help in unveiling the important drivers of migration dynamics and, with this, guide the improvement of recent global vegetation models.

Description: It is of major interest to estimate the feedback of arctic ecosystems to the global warming we expect in upcoming decades. The speed of this response is driven by the potential of species to migrate, tracking their climate optimum. For this, sessile plants have to produce and disperse seeds to newly available habitats, and pollination of ovules is needed for the seeds to be viable. These two processes are also the vectors that pass genetic information through a population. A restricted exchange among subpopulations might lead to a maladapted population due to diversity losses. Hence, a realistic implementation of these dispersal processes into a simulation model would allow an assessment of the importance of diversity for the migration of plant species in various environments worldwide. To date, dynamic global vegetation models have been optimized for a global application and overestimate the migration of biome shifts in currently warming temperatures. We hypothesize that this is caused by neglecting important fine-scale processes, which are necessary to estimate realistic vegetation trajectories. Recently, we built and parameterized a simulation model LAVESI for larches that dominate the latitudinal treelines in the northernmost areas of Siberia. In this study, we updated the vegetation model by including seed and pollen dispersal driven by wind speed and direction. The seed dispersal is modelled as a ballistic flight, and for the pollination of ovules of seeds produced, we implemented a wind-determined and distance-dependent probability distribution function using a von Mises distribution to select the pollen donor. A local sensitivity analysis of both processes supported the robustness of the model's results to the parameterization, although it highlighted the importance of recruitment and seed dispersal traits for migration rates. This individual-based and spatially explicit implementation of both dispersal processes makes it easily feasible to inherit plant traits and genetic information to assess the impact of migration processes on the genetics. Finally, we suggest how the final model can be applied to substantially help in unveiling the important drivers of migration dynamics and, with this, guide the improvement of recent global vegetation models.

Description: A strong temperature increase in the Arctic is expected to lead to latitudinal treeline shift. This tundra–taiga turnover would cause a positive vegetation–climate feedback due to albedo decrease. However, reliable estimates of tree migration rates are currently lacking due to the complex processes involved in forest establishment, which depend strongly on seed dispersal. We aim to fill this gap using LAVESI, an individual-based and spatially explicit Larix vegetation simulator. LAVESI was designed to simulate plots within homogeneous forests. Here, we improve the implementation of the seed dispersal function via field-based investigations. We inferred the effective seed dispersal distances of a typical open-forest stand on the southern Taymyr Peninsula (northern central Siberia) from genetic parentage analysis using eight nuclear microsatellite markers. The parentage analysis gives effective seed dispersal distances (median ∼10 m) close to the seed parents. A comparison between simulated and observed effective seed dispersal distances reveals an overestimation of recruits close to the releasing tree and a shorter dispersal distance generally. We thus adapted our model and used the newly parameterised version to simulate south-to-north transects; a slow-moving treeline front was revealed. The colonisation of the tundra areas was assisted by occasional long-distance seed dispersal events beyond the treeline area. The treeline (∼1 tree ha−1) advanced by ∼1.6 m yr−1, whereas the forest line (∼100 trees ha−1) advanced by only ∼0.6 m yr−1. We conclude that the treeline in northern central Siberia currently lags behind the current strong warming and will continue to lag in the near future.

Description: A strong temperature increase in the Arctic is expected to lead to latitudinal treeline shift. This tundra-taiga turnover would cause a positive vegetation-climate feedback due to albedo decrease. However, reliable estimates of tree migration rates are currently lacking due to the complex processes involved in forest establishment, which depend strongly on seed dispersal. We aim to fill this gap using LAVESI, an individual-based and spatially explicit Larix vegetation simulator. LAVESI was designed to simulate plots within homogeneous forests. Here, we improve the implementation of the seed dispersal function via field-based investigations. We inferred the effective seed dispersal distances of a typical open forest stand on the southern Taymyr Peninsula (north-central Siberia) from genetic parentage analysis using eight highly polymorphic nuclear microsatellite loci. The parentage analysis gives effective seed dispersal distances (median ~10m) close to the seed parents. A comparison between simulated and observed effective seed dispersal distances reveals an overestimation of recruits close to the releasing tree and a shorter dispersal distance generally. We thus adapted our model and used it to simulate south-to-north transects: a slow-moving treeline front was revealed. The colonisation of the tundra areas was assisted by occasional long-distance seed dispersal events beyond the treeline area. The treeline (~1treeha−1) advanced by ~1.6myr−1, whereas the forest line (~100treesha−1) advanced by only ~0.6myr−1. We conclude that the treeline in north-central Siberia currently lags behind the current strong warming and will continue to lag in the near future.

Description: The table contains the biallelic data for 8 loci (LOCUS#: "K241", "Ld56", "K225", "K224", "Ld45", "K235", "K260", "K066") for 612 Larix gmelinii individuals sampled within 100x100 m from site TY04-V1 located on the Taymyr Peninsula, Russia. This site is part of a dataset see further details in https://doi.pangaea.de/10.1594/PANGAEA.874612.

Description: The Arctic is currently experiencing the strongest temperature changes worldwide, causing a geographic shift in optimal habitats for many species. Trees are projected to advance into treeless tundra with increasing warmth, which will likely cause a positive vegetation-climate feedback due to an albedo decrease. To date, global simulation models generally assume that species follow the changing abiotic environment immediately. However, responses are strongly shaped by species’ traits determining seed dispersal, and the complex process of migration is not well understood. We approached better projections by parameterising dispersal processes in the individual-based spatially-explicit model LAVESI for larches at the treeline in Siberia. To do this, we inferred the effective seed dispersal based on a genetic parentage analysis using an assay of eight highly polymorphic nuclear microsatellite loci. We genotyped a total of 612 individuals from an open forest site, situated close to the border to treeless taiga at the southern Taymyr Peninsula in north-central Siberia. At this remote site, we sampled all mature trees within an area of 100x100 m2, and we sampled all recruits within the central area of the plot. The results indicated a high on-site recruitment rate of ~53%. The effective seed dispersal follows a pronounced Gaussian function with a fat-tail. The median dispersal distance of ~10 m is comparable to results from studies, but this is unexpectedly short for a wind-dispersed species in an open forest. Simulations with the improved model on hypothetical south-to-north transects revealed a slow-moving treeline front, advancing only by ~1.6 m yr-1 into tundra. While the observed colonisation of the tundra is assisted by occasional long-distance seed dispersal events beyond the treeline area, we conclude that the treeline advance in north-central Siberia currently lags behind the current strong warming and will continue to lag in the near future.

Description: It is of major interest to estimate the feedback of arctic ecosystems to the global warming we expect in upcoming decades. The speed of this response is driven by the potential of species to migrate, tracking their climate optimum. For this, sessile plants have to produce and disperse seeds to newly available habitats, and pollination of ovules is needed for the seeds to be viable. These two processes are also the vectors that pass genetic information through a population. A restricted exchange among subpopulations might lead to a maladapted population due to diversity losses. Hence, a realistic implementation of these dispersal processes into a simulation model would allow an assessment of the importance of diversity for the migration of plant species in various environments worldwide. To date, dynamic global vegetation models have been optimized for a global application and overestimate the migration of biome shifts in currently warming temperatures. We hypothesize that this is caused by neglecting important fine-scale processes, which are necessary to estimate realistic vegetation trajectories. Recently, we built and parameterized a simulation model LAVESI for larches that dominate the latitudinal treelines in the northernmost areas of Siberia. In this study, we updated the vegetation model by including seed and pollen dispersal driven by wind speed and direction. The seed dispersal is modelled as a ballistic flight, and for the pollination of ovules of seeds produced, we implemented a wind-determined and distance-dependent probability distribution function using a von Mises distribution to select the pollen donor. A local sensitivity analysis of both processes supported the robustness of the model's results to the parameterization, although it highlighted the importance of recruitment and seed dispersal traits for migration rates. This individual-based and spatially explicit implementation of both dispersal processes makes it easily feasible to inherit plant traits and genetic information to assess the impact of migration processes on the genetics. Finally, we suggest how the final model can be applied to substantially help in unveiling the important drivers of migration dynamics and, with this, guide the improvement of recent global vegetation models.

Description: A strong temperature increase in the Arctic is expected to lead to latitudinal treeline shift. This tundra–taiga turnover would cause a positive vegetation–climate feedback due to albedo decrease. However, reliable estimates of tree migration rates are currently lacking due to the complex processes involved in forest establishment, which depend strongly on seed dispersal. We aim to fill this gap using LAVESI, an individual-based and spatially explicit Larix vegetation simulator. LAVESI was designed to simulate plots within homogeneous forests. Here, we improve the implementation of the seed dispersal function via field-based investigations. We inferred the effective seed dispersal distances of a typical open-forest stand on the southern Taymyr Peninsula (northern central Siberia) from genetic parentage analysis using eight nuclear microsatellite markers. The parentage analysis gives effective seed dispersal distances (median ∼10 m) close to the seed parents. A comparison between simulated and observed effective seed dispersal distances reveals an overestimation of recruits close to the releasing tree and a shorter dispersal distance generally. We thus adapted our model and used the newly parameterised version to simulate south-to-north transects; a slow-moving treeline front was revealed. The colonisation of the tundra areas was assisted by occasional long-distance seed dispersal events beyond the treeline area. The treeline (∼1 tree/ha) advanced by ∼1.6 m/yr, whereas the forest line (∼100trees/ha) advanced by only ∼0.6m/yr. We conclude that the treeline in northern central Siberia currently lags behind the current strong warming and will continue to lag in the near future.