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...
Published in: | Geoscientific Model Development |
---|---|
Main Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Copernicus Publications
2018
|
Subjects: | |
Online Access: | https://doi.org/10.5194/gmd-11-4451-2018 https://doaj.org/article/4134c7a8ca9f49999d4beb9d2acc39c4 |
id |
ftdoajarticles:oai:doaj.org/article:4134c7a8ca9f49999d4beb9d2acc39c4 |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:4134c7a8ca9f49999d4beb9d2acc39c4 2023-05-15T15:15:30+02:00 Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model: LAVESI-WIND 1.0 S. Kruse A. Gerdes N. J. Kath U. Herzschuh 2018-11-01T00:00:00Z https://doi.org/10.5194/gmd-11-4451-2018 https://doaj.org/article/4134c7a8ca9f49999d4beb9d2acc39c4 EN eng Copernicus Publications https://www.geosci-model-dev.net/11/4451/2018/gmd-11-4451-2018.pdf https://doaj.org/toc/1991-959X https://doaj.org/toc/1991-9603 doi:10.5194/gmd-11-4451-2018 1991-959X 1991-9603 https://doaj.org/article/4134c7a8ca9f49999d4beb9d2acc39c4 Geoscientific Model Development, Vol 11, Pp 4451-4467 (2018) Geology QE1-996.5 article 2018 ftdoajarticles https://doi.org/10.5194/gmd-11-4451-2018 2022-12-30T21:23:21Z 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 ... Article in Journal/Newspaper Arctic Global warming Siberia Directory of Open Access Journals: DOAJ Articles Arctic Geoscientific Model Development 11 11 4451 4467 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Geology QE1-996.5 |
spellingShingle |
Geology QE1-996.5 S. Kruse A. Gerdes N. J. Kath U. Herzschuh Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model: LAVESI-WIND 1.0 |
topic_facet |
Geology QE1-996.5 |
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 ... |
format |
Article in Journal/Newspaper |
author |
S. Kruse A. Gerdes N. J. Kath U. Herzschuh |
author_facet |
S. Kruse A. Gerdes N. J. Kath U. Herzschuh |
author_sort |
S. Kruse |
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 |
Copernicus Publications |
publishDate |
2018 |
url |
https://doi.org/10.5194/gmd-11-4451-2018 https://doaj.org/article/4134c7a8ca9f49999d4beb9d2acc39c4 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Global warming Siberia |
genre_facet |
Arctic Global warming Siberia |
op_source |
Geoscientific Model Development, Vol 11, Pp 4451-4467 (2018) |
op_relation |
https://www.geosci-model-dev.net/11/4451/2018/gmd-11-4451-2018.pdf https://doaj.org/toc/1991-959X https://doaj.org/toc/1991-9603 doi:10.5194/gmd-11-4451-2018 1991-959X 1991-9603 https://doaj.org/article/4134c7a8ca9f49999d4beb9d2acc39c4 |
op_doi |
https://doi.org/10.5194/gmd-11-4451-2018 |
container_title |
Geoscientific Model Development |
container_volume |
11 |
container_issue |
11 |
container_start_page |
4451 |
op_container_end_page |
4467 |
_version_ |
1766345873378246656 |