Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model : LAVESI-WIND 1.0
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...
Main Authors: | , , , |
---|---|
Format: | Text |
Language: | English |
Published: |
Universität Potsdam
2020
|
Subjects: | |
Online Access: | https://dx.doi.org/10.25932/publishup-44597 https://publishup.uni-potsdam.de/44597 |
id |
ftdatacite:10.25932/publishup-44597 |
---|---|
record_format |
openpolar |
spelling |
ftdatacite:10.25932/publishup-44597 2023-05-15T15:17:21+02:00 Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model : LAVESI-WIND 1.0 Kruse, Stefan Gerdes, Alexander Kath, Nadja J. Herzschuh, Ulrike 2020 application/pdf application/zip https://dx.doi.org/10.25932/publishup-44597 https://publishup.uni-potsdam.de/44597 en eng Universität Potsdam Creative Commons - Namensnennung, 4.0 International https://creativecommons.org/licenses/by/4.0 CC-BY article-journal Text ScholarlyArticle 2020 ftdatacite https://doi.org/10.25932/publishup-44597 2021-11-05T12:55:41Z 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. : Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe, 929 Text Arctic Global warming Siberia DataCite Metadata Store (German National Library of Science and Technology) Arctic |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
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. : Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe, 929 |
format |
Text |
author |
Kruse, Stefan Gerdes, Alexander Kath, Nadja J. Herzschuh, Ulrike |
spellingShingle |
Kruse, Stefan Gerdes, Alexander Kath, Nadja J. Herzschuh, Ulrike Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model : LAVESI-WIND 1.0 |
author_facet |
Kruse, Stefan Gerdes, Alexander Kath, Nadja J. Herzschuh, Ulrike |
author_sort |
Kruse, Stefan |
title |
Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model : LAVESI-WIND 1.0 |
title_short |
Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model : LAVESI-WIND 1.0 |
title_full |
Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model : LAVESI-WIND 1.0 |
title_fullStr |
Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model : LAVESI-WIND 1.0 |
title_full_unstemmed |
Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model : LAVESI-WIND 1.0 |
title_sort |
implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model : lavesi-wind 1.0 |
publisher |
Universität Potsdam |
publishDate |
2020 |
url |
https://dx.doi.org/10.25932/publishup-44597 https://publishup.uni-potsdam.de/44597 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Global warming Siberia |
genre_facet |
Arctic Global warming Siberia |
op_rights |
Creative Commons - Namensnennung, 4.0 International https://creativecommons.org/licenses/by/4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.25932/publishup-44597 |
_version_ |
1766347596137234432 |