Improving broad scale forage mapping and habitat selection analyses with airborne laser scanning: the case of moose

- Determining the spatial distribution of large herbivores is a key challenge in ecology and management. However, our ability to accurately predict this is often hampered by inadequate data on available forage and structural cover. Airborne laser scanning (ALS) can give direct and detailed measureme...

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Published in:Ecosphere
Main Authors: Lone, Karen, van Beest, Floris, Mysterud, Atle, Gobakken, Terje, Milner, Jocelyn Margarey, Ruud, Hans-Petter, Loe, Leif Egil
Format: Article in Journal/Newspaper
Language:English
Published: 2015
Subjects:
Online Access:http://hdl.handle.net/11250/275680
https://doi.org/10.1890/ES14-00156.1
id ftunivmob:oai:nmbu.brage.unit.no:11250/275680
record_format openpolar
spelling ftunivmob:oai:nmbu.brage.unit.no:11250/275680 2023-05-15T13:13:07+02:00 Improving broad scale forage mapping and habitat selection analyses with airborne laser scanning: the case of moose Lone, Karen van Beest, Floris Mysterud, Atle Gobakken, Terje Milner, Jocelyn Margarey Ruud, Hans-Petter Loe, Leif Egil 2015-01-23T13:52:04Z application/pdf http://hdl.handle.net/11250/275680 https://doi.org/10.1890/ES14-00156.1 eng eng urn:issn:2150-8925 http://hdl.handle.net/11250/275680 https://doi.org/10.1890/ES14-00156.1 cristin:1182010 Airborne laser scanning (ALS) Alces alces ecological indicators habitat mapping LiDAR population monitoring remote sensing Norway Journal article Peer reviewed 2015 ftunivmob https://doi.org/10.1890/ES14-00156.1 2021-09-23T20:15:49Z - Determining the spatial distribution of large herbivores is a key challenge in ecology and management. However, our ability to accurately predict this is often hampered by inadequate data on available forage and structural cover. Airborne laser scanning (ALS) can give direct and detailed measurements of vegetation structure.We assessed the effectiveness of ALS data to predict (1) the distribution of browse forage resources and (2) moose (Alces alces) habitat selection in southern Norway. Using ground reference data from 153 sampled forest stands, we predicted available browse biomass with predictor variables from ALS and/or forest inventory. Browse models based on both ALS and forest inventory variables performed better than either alone. Dominant tree species and development class of the forest stand remained important predictor variables and were not replaced by the ALS variables. The increased explanatory power from including ALS came from detection of canopy cover (negatively correlated with forage biomass) and understory density (positively correlated with forage biomass). Improved forage estimates resulted in improved predictive ability of moose resource selection functions (RSFs) at the landscape scale, but not at the home range scale. However, when also including ALS cover variables (understory cover density and canopy cover density) directly into the RSFs, we obtained the highest predictive ability, at both the landscape and home range scales. Generally, moose selected for high browse biomass, low amount of understory vegetation and for low or intermediate canopy cover depending on the time of day, season and scale of analyses. The auxiliary information on vegetation structure from ALS improved the prediction of browse moderately, but greatly improved the analysis of habitat selection, as it captured important functional gradients in the habitat apart fromforage.We conclude that ALS is an effective and valuable tool for wildlife managers and ecologists to estimate the distribution of large herbivores. Article in Journal/Newspaper Alces alces Open archive Norwegian University of Life Sciences: Brage NMBU Norway Ecosphere 5 11 art144
institution Open Polar
collection Open archive Norwegian University of Life Sciences: Brage NMBU
op_collection_id ftunivmob
language English
topic Airborne laser scanning (ALS)
Alces alces
ecological indicators
habitat mapping
LiDAR
population monitoring
remote sensing
Norway
spellingShingle Airborne laser scanning (ALS)
Alces alces
ecological indicators
habitat mapping
LiDAR
population monitoring
remote sensing
Norway
Lone, Karen
van Beest, Floris
Mysterud, Atle
Gobakken, Terje
Milner, Jocelyn Margarey
Ruud, Hans-Petter
Loe, Leif Egil
Improving broad scale forage mapping and habitat selection analyses with airborne laser scanning: the case of moose
topic_facet Airborne laser scanning (ALS)
Alces alces
ecological indicators
habitat mapping
LiDAR
population monitoring
remote sensing
Norway
description - Determining the spatial distribution of large herbivores is a key challenge in ecology and management. However, our ability to accurately predict this is often hampered by inadequate data on available forage and structural cover. Airborne laser scanning (ALS) can give direct and detailed measurements of vegetation structure.We assessed the effectiveness of ALS data to predict (1) the distribution of browse forage resources and (2) moose (Alces alces) habitat selection in southern Norway. Using ground reference data from 153 sampled forest stands, we predicted available browse biomass with predictor variables from ALS and/or forest inventory. Browse models based on both ALS and forest inventory variables performed better than either alone. Dominant tree species and development class of the forest stand remained important predictor variables and were not replaced by the ALS variables. The increased explanatory power from including ALS came from detection of canopy cover (negatively correlated with forage biomass) and understory density (positively correlated with forage biomass). Improved forage estimates resulted in improved predictive ability of moose resource selection functions (RSFs) at the landscape scale, but not at the home range scale. However, when also including ALS cover variables (understory cover density and canopy cover density) directly into the RSFs, we obtained the highest predictive ability, at both the landscape and home range scales. Generally, moose selected for high browse biomass, low amount of understory vegetation and for low or intermediate canopy cover depending on the time of day, season and scale of analyses. The auxiliary information on vegetation structure from ALS improved the prediction of browse moderately, but greatly improved the analysis of habitat selection, as it captured important functional gradients in the habitat apart fromforage.We conclude that ALS is an effective and valuable tool for wildlife managers and ecologists to estimate the distribution of large herbivores.
format Article in Journal/Newspaper
author Lone, Karen
van Beest, Floris
Mysterud, Atle
Gobakken, Terje
Milner, Jocelyn Margarey
Ruud, Hans-Petter
Loe, Leif Egil
author_facet Lone, Karen
van Beest, Floris
Mysterud, Atle
Gobakken, Terje
Milner, Jocelyn Margarey
Ruud, Hans-Petter
Loe, Leif Egil
author_sort Lone, Karen
title Improving broad scale forage mapping and habitat selection analyses with airborne laser scanning: the case of moose
title_short Improving broad scale forage mapping and habitat selection analyses with airborne laser scanning: the case of moose
title_full Improving broad scale forage mapping and habitat selection analyses with airborne laser scanning: the case of moose
title_fullStr Improving broad scale forage mapping and habitat selection analyses with airborne laser scanning: the case of moose
title_full_unstemmed Improving broad scale forage mapping and habitat selection analyses with airborne laser scanning: the case of moose
title_sort improving broad scale forage mapping and habitat selection analyses with airborne laser scanning: the case of moose
publishDate 2015
url http://hdl.handle.net/11250/275680
https://doi.org/10.1890/ES14-00156.1
geographic Norway
geographic_facet Norway
genre Alces alces
genre_facet Alces alces
op_relation urn:issn:2150-8925
http://hdl.handle.net/11250/275680
https://doi.org/10.1890/ES14-00156.1
cristin:1182010
op_doi https://doi.org/10.1890/ES14-00156.1
container_title Ecosphere
container_volume 5
container_issue 11
container_start_page art144
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