Improving distribution models of riparian vegetation with mobile laser scanning and hydraulic modelling
This study aimed at illustrating how direct measurements, mobile laser scanning and hydraulic modelling can be combined to quantify environmental drivers, improve vegetation models and increase our understanding of vegetation patterns in a sub-arctic river valley. Our results indicate that the resul...
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ftunivturku:oai:www.utupub.fi:10024/167355 2023-05-15T15:00:27+02:00 Improving distribution models of riparian vegetation with mobile laser scanning and hydraulic modelling Jouni Salmela Antero Kukko Tua Nylén Harri Kaartinen Elina Kasvi Juha Hyyppä Petteri Alho Anttoni Jaakkola maantiede, Geography 2606901 2022-10-28T13:46:47Z https://www.utupub.fi/handle/10024/167355 en eng United States Yhdysvallat (USA) US 14 e0225936 10.1371/journal.pone.0225936 PLoS ONE 12 https://www.utupub.fi/handle/10024/167355 URN:NBN:fi-fe2021042823453 1932-6203 2022 ftunivturku 2022-11-03T00:01:44Z This study aimed at illustrating how direct measurements, mobile laser scanning and hydraulic modelling can be combined to quantify environmental drivers, improve vegetation models and increase our understanding of vegetation patterns in a sub-arctic river valley. Our results indicate that the resultant vegetation models successfully predict riparian vegetation patterns (Rho = 0.8 for total species richness, AUC = 0.97 for distribution) and highlight differences between eight functional species groups (Rho 0.46–0.84; AUC 0.79–0.93; functional group-specific effects). In our study setting, replacing the laser scanning-based and hydraulic modelling-based variables with a proxy variable elevation did not significantly weaken the models. However, using directly measured and modelled variables allows relating species patterns to e.g. stream power or the length of the flood-free period. Substituting these biologically relevant variables with proxies mask important processes and may reduce the transferability of the results into other sites. At the local scale, the amount of litter is a highly important driver of total species richness, distribution and abundance patterns (relative influences 49, 72 and 83%, respectively) and across all functional groups (13–57%; excluding lichen species richness) in the sub-arctic river valley. Moreover, soil organic matter and soil water content shape vegetation patterns (on average 16 and 7%, respectively). Fluvial disturbance is a key limiting factor only for lichen, bryophyte and dwarf shrub species in this environment (on average 37, 6 and 10%, respectively). Fluvial disturbance intensity is the most important component of disturbance for most functional groups while the length of the disturbance-free period is more relevant for lichens. We conclude that striving for as accurate quantifications of environmental drivers as possible may reveal important processes and functional group differences and help anticipate future changes in vegetation. Mobile laser scanning, ... Other/Unknown Material Arctic University of Turku: UTUPub Arctic Rho ENVELOPE(-63.000,-63.000,-64.300,-64.300) |
institution |
Open Polar |
collection |
University of Turku: UTUPub |
op_collection_id |
ftunivturku |
language |
English |
description |
This study aimed at illustrating how direct measurements, mobile laser scanning and hydraulic modelling can be combined to quantify environmental drivers, improve vegetation models and increase our understanding of vegetation patterns in a sub-arctic river valley. Our results indicate that the resultant vegetation models successfully predict riparian vegetation patterns (Rho = 0.8 for total species richness, AUC = 0.97 for distribution) and highlight differences between eight functional species groups (Rho 0.46–0.84; AUC 0.79–0.93; functional group-specific effects). In our study setting, replacing the laser scanning-based and hydraulic modelling-based variables with a proxy variable elevation did not significantly weaken the models. However, using directly measured and modelled variables allows relating species patterns to e.g. stream power or the length of the flood-free period. Substituting these biologically relevant variables with proxies mask important processes and may reduce the transferability of the results into other sites. At the local scale, the amount of litter is a highly important driver of total species richness, distribution and abundance patterns (relative influences 49, 72 and 83%, respectively) and across all functional groups (13–57%; excluding lichen species richness) in the sub-arctic river valley. Moreover, soil organic matter and soil water content shape vegetation patterns (on average 16 and 7%, respectively). Fluvial disturbance is a key limiting factor only for lichen, bryophyte and dwarf shrub species in this environment (on average 37, 6 and 10%, respectively). Fluvial disturbance intensity is the most important component of disturbance for most functional groups while the length of the disturbance-free period is more relevant for lichens. We conclude that striving for as accurate quantifications of environmental drivers as possible may reveal important processes and functional group differences and help anticipate future changes in vegetation. Mobile laser scanning, ... |
author2 |
maantiede, Geography 2606901 |
author |
Jouni Salmela Antero Kukko Tua Nylén Harri Kaartinen Elina Kasvi Juha Hyyppä Petteri Alho Anttoni Jaakkola |
spellingShingle |
Jouni Salmela Antero Kukko Tua Nylén Harri Kaartinen Elina Kasvi Juha Hyyppä Petteri Alho Anttoni Jaakkola Improving distribution models of riparian vegetation with mobile laser scanning and hydraulic modelling |
author_facet |
Jouni Salmela Antero Kukko Tua Nylén Harri Kaartinen Elina Kasvi Juha Hyyppä Petteri Alho Anttoni Jaakkola |
author_sort |
Jouni Salmela |
title |
Improving distribution models of riparian vegetation with mobile laser scanning and hydraulic modelling |
title_short |
Improving distribution models of riparian vegetation with mobile laser scanning and hydraulic modelling |
title_full |
Improving distribution models of riparian vegetation with mobile laser scanning and hydraulic modelling |
title_fullStr |
Improving distribution models of riparian vegetation with mobile laser scanning and hydraulic modelling |
title_full_unstemmed |
Improving distribution models of riparian vegetation with mobile laser scanning and hydraulic modelling |
title_sort |
improving distribution models of riparian vegetation with mobile laser scanning and hydraulic modelling |
publisher |
United States |
publishDate |
2022 |
url |
https://www.utupub.fi/handle/10024/167355 |
long_lat |
ENVELOPE(-63.000,-63.000,-64.300,-64.300) |
geographic |
Arctic Rho |
geographic_facet |
Arctic Rho |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
14 e0225936 10.1371/journal.pone.0225936 PLoS ONE 12 https://www.utupub.fi/handle/10024/167355 URN:NBN:fi-fe2021042823453 1932-6203 |
_version_ |
1766332551563051008 |