Forecasting forest dynamics with the individual-based model LAVESI across the Siberian treeline: from UAV surveys to simulations
Boreal forests in Siberia store huge amounts of aboveground carbon. Global warming potentially threatens this carbon storage due to more frequent droughts or other disturbances such as fires. These disturbances can change recruitment patterns, and thus may have long-lasting impacts on population dyn...
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ftawi:oai:epic.awi.de:52955 2024-09-15T18:38:39+00:00 Forecasting forest dynamics with the individual-based model LAVESI across the Siberian treeline: from UAV surveys to simulations Kruse, Stefan Shevtsova, Iuliia Brieger, Frederic Wieczorek, Mareike Pestryakova, Luidmila A. Herzschuh, Ulrike 2020-03 https://epic.awi.de/id/eprint/52955/ https://doi.org/10.5194%2Fegusphere-egu2020-13453 https://hdl.handle.net/10013/epic.522b1359-be7e-4ea4-9b6d-0c1d70337711 unknown Copernicus GmbH Kruse, S. orcid:0000-0003-1107-1958 , Shevtsova, I. orcid:0000-0002-6287-9431 , Brieger, F. orcid:0000-0001-7603-5689 , Wieczorek, M. orcid:0000-0002-3180-1607 , Pestryakova, L. A. and Herzschuh, U. orcid:0000-0003-0999-1261 (2020) Forecasting forest dynamics with the individual-based model LAVESI across the Siberian treeline: from UAV surveys to simulations , EGU General Assembly 2020, Online, 4 May 2020 - 8 May 2020 . doi:10.5194/egusphere-egu2020-13453 <https://doi.org/10.5194/egusphere-egu2020-13453> , hdl:10013/epic.522b1359-be7e-4ea4-9b6d-0c1d70337711 EPIC3EGU General Assembly 2020, Online, 2020-05-04-2020-05-08Copernicus GmbH Conference notRev 2020 ftawi https://doi.org/10.5194/egusphere-egu2020-13453 2024-06-24T04:26:11Z Boreal forests in Siberia store huge amounts of aboveground carbon. Global warming potentially threatens this carbon storage due to more frequent droughts or other disturbances such as fires. These disturbances can change recruitment patterns, and thus may have long-lasting impacts on population dynamics. Assessing high-resolution forest stand structures and forecasting their response for the upcoming decades with detailed models is needed to understand the involved key processes and consequences of global change. We present forest stand inventories derived from UAV imagery and a developed processing chain including Individual Tree Detection (ITD) and species determination for 56 sites on a bioclimatic gradient at the Tundra-Taiga-Ecotone in Northeastern Siberia. We will use these and further 58 traditional count and measurement data as starting points for the detailed individual-based spatially explicit forest model LAVESI to predict future forest dynamics covering multiple sites across the Siberian treeline. In our analyses, we will focus on assessing future structural changes of the forests and their aboveground biomass dynamics. For our discussion, we will evaluate the reliability of UAV-derived forest inventories by measuring the impact strength of error sources introduced in the methodology on the forecasts. Conference Object taiga Tundra Siberia Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
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Open Polar |
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Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
op_collection_id |
ftawi |
language |
unknown |
description |
Boreal forests in Siberia store huge amounts of aboveground carbon. Global warming potentially threatens this carbon storage due to more frequent droughts or other disturbances such as fires. These disturbances can change recruitment patterns, and thus may have long-lasting impacts on population dynamics. Assessing high-resolution forest stand structures and forecasting their response for the upcoming decades with detailed models is needed to understand the involved key processes and consequences of global change. We present forest stand inventories derived from UAV imagery and a developed processing chain including Individual Tree Detection (ITD) and species determination for 56 sites on a bioclimatic gradient at the Tundra-Taiga-Ecotone in Northeastern Siberia. We will use these and further 58 traditional count and measurement data as starting points for the detailed individual-based spatially explicit forest model LAVESI to predict future forest dynamics covering multiple sites across the Siberian treeline. In our analyses, we will focus on assessing future structural changes of the forests and their aboveground biomass dynamics. For our discussion, we will evaluate the reliability of UAV-derived forest inventories by measuring the impact strength of error sources introduced in the methodology on the forecasts. |
format |
Conference Object |
author |
Kruse, Stefan Shevtsova, Iuliia Brieger, Frederic Wieczorek, Mareike Pestryakova, Luidmila A. Herzschuh, Ulrike |
spellingShingle |
Kruse, Stefan Shevtsova, Iuliia Brieger, Frederic Wieczorek, Mareike Pestryakova, Luidmila A. Herzschuh, Ulrike Forecasting forest dynamics with the individual-based model LAVESI across the Siberian treeline: from UAV surveys to simulations |
author_facet |
Kruse, Stefan Shevtsova, Iuliia Brieger, Frederic Wieczorek, Mareike Pestryakova, Luidmila A. Herzschuh, Ulrike |
author_sort |
Kruse, Stefan |
title |
Forecasting forest dynamics with the individual-based model LAVESI across the Siberian treeline: from UAV surveys to simulations |
title_short |
Forecasting forest dynamics with the individual-based model LAVESI across the Siberian treeline: from UAV surveys to simulations |
title_full |
Forecasting forest dynamics with the individual-based model LAVESI across the Siberian treeline: from UAV surveys to simulations |
title_fullStr |
Forecasting forest dynamics with the individual-based model LAVESI across the Siberian treeline: from UAV surveys to simulations |
title_full_unstemmed |
Forecasting forest dynamics with the individual-based model LAVESI across the Siberian treeline: from UAV surveys to simulations |
title_sort |
forecasting forest dynamics with the individual-based model lavesi across the siberian treeline: from uav surveys to simulations |
publisher |
Copernicus GmbH |
publishDate |
2020 |
url |
https://epic.awi.de/id/eprint/52955/ https://doi.org/10.5194%2Fegusphere-egu2020-13453 https://hdl.handle.net/10013/epic.522b1359-be7e-4ea4-9b6d-0c1d70337711 |
genre |
taiga Tundra Siberia |
genre_facet |
taiga Tundra Siberia |
op_source |
EPIC3EGU General Assembly 2020, Online, 2020-05-04-2020-05-08Copernicus GmbH |
op_relation |
Kruse, S. orcid:0000-0003-1107-1958 , Shevtsova, I. orcid:0000-0002-6287-9431 , Brieger, F. orcid:0000-0001-7603-5689 , Wieczorek, M. orcid:0000-0002-3180-1607 , Pestryakova, L. A. and Herzschuh, U. orcid:0000-0003-0999-1261 (2020) Forecasting forest dynamics with the individual-based model LAVESI across the Siberian treeline: from UAV surveys to simulations , EGU General Assembly 2020, Online, 4 May 2020 - 8 May 2020 . doi:10.5194/egusphere-egu2020-13453 <https://doi.org/10.5194/egusphere-egu2020-13453> , hdl:10013/epic.522b1359-be7e-4ea4-9b6d-0c1d70337711 |
op_doi |
https://doi.org/10.5194/egusphere-egu2020-13453 |
_version_ |
1810483063068557312 |