Caught in the mesh: roads and their network-scale impediment to animal movement
Roads have a pervasive multi-faceted influence on ecosystems, including pronounced impacts on wildlife movements. In recognition of the scale-transcending impacts of transportation infrastructure, ecologists have been encouraged to extend the study of barrier impacts from individual roads and animal...
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Format: | Article in Journal/Newspaper |
Language: | English |
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2016
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Online Access: | http://hdl.handle.net/11250/2425762 https://doi.org/10.1111/ecog.02801 |
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ftninstnf:oai:brage.nina.no:11250/2425762 2023-05-15T18:42:08+02:00 Caught in the mesh: roads and their network-scale impediment to animal movement Bischof, Richard Steyaert, Sam Kindberg, Jonas 2016 application/pdf http://hdl.handle.net/11250/2425762 https://doi.org/10.1111/ecog.02801 eng eng urn:issn:0906-7590 http://hdl.handle.net/11250/2425762 https://doi.org/10.1111/ecog.02801 cristin:1412408 Ecography non-invasive genetic sampling road network tile island biogeography road ecology spatial captuer-recapture fragmentation carnivores transportation network Journal article Peer reviewed 2016 ftninstnf https://doi.org/10.1111/ecog.02801 2021-12-23T07:16:59Z Roads have a pervasive multi-faceted influence on ecosystems, including pronounced impacts on wildlife movements. In recognition of the scale-transcending impacts of transportation infrastructure, ecologists have been encouraged to extend the study of barrier impacts from individual roads and animals to networks and populations. In this study, we adopt an analytical representation of road networks as mosaics of landscape tiles, separated by roads. We then adapt spatial capture-recapture analysis to estimate the propensity of wildlife to stay within the boundaries of the road network tiles (RNTs) that hold their activity centres. We fit the model to national non-invasive genetic monitoring data for brown bears (Ursus arctos) in Sweden and show that bears had up to 73% lower odds of using areas outside the network tile of their home range centre, even after accounting for the effect of natural barriers (major rivers) and the decrease in utilization with increasing distance from a bear’s activity centre. Our study highlights the pronounced landscape-level barrier effect on wildlife mobility and, in doing so, introduces a novel and flexible approach for quantifying contemporary fragmentation from the scale of RNTs and individual animals to transportation networks and populations. non-invasive genetic sampling, road network tile, island biogeography, road ecology, spatial capture-recapture, fragmentation, carnivores, transportation network Article in Journal/Newspaper Ursus arctos Norwegian Institute for Nature Research: Brage NINA Ecography 40 12 1369 1380 |
institution |
Open Polar |
collection |
Norwegian Institute for Nature Research: Brage NINA |
op_collection_id |
ftninstnf |
language |
English |
topic |
non-invasive genetic sampling road network tile island biogeography road ecology spatial captuer-recapture fragmentation carnivores transportation network |
spellingShingle |
non-invasive genetic sampling road network tile island biogeography road ecology spatial captuer-recapture fragmentation carnivores transportation network Bischof, Richard Steyaert, Sam Kindberg, Jonas Caught in the mesh: roads and their network-scale impediment to animal movement |
topic_facet |
non-invasive genetic sampling road network tile island biogeography road ecology spatial captuer-recapture fragmentation carnivores transportation network |
description |
Roads have a pervasive multi-faceted influence on ecosystems, including pronounced impacts on wildlife movements. In recognition of the scale-transcending impacts of transportation infrastructure, ecologists have been encouraged to extend the study of barrier impacts from individual roads and animals to networks and populations. In this study, we adopt an analytical representation of road networks as mosaics of landscape tiles, separated by roads. We then adapt spatial capture-recapture analysis to estimate the propensity of wildlife to stay within the boundaries of the road network tiles (RNTs) that hold their activity centres. We fit the model to national non-invasive genetic monitoring data for brown bears (Ursus arctos) in Sweden and show that bears had up to 73% lower odds of using areas outside the network tile of their home range centre, even after accounting for the effect of natural barriers (major rivers) and the decrease in utilization with increasing distance from a bear’s activity centre. Our study highlights the pronounced landscape-level barrier effect on wildlife mobility and, in doing so, introduces a novel and flexible approach for quantifying contemporary fragmentation from the scale of RNTs and individual animals to transportation networks and populations. non-invasive genetic sampling, road network tile, island biogeography, road ecology, spatial capture-recapture, fragmentation, carnivores, transportation network |
format |
Article in Journal/Newspaper |
author |
Bischof, Richard Steyaert, Sam Kindberg, Jonas |
author_facet |
Bischof, Richard Steyaert, Sam Kindberg, Jonas |
author_sort |
Bischof, Richard |
title |
Caught in the mesh: roads and their network-scale impediment to animal movement |
title_short |
Caught in the mesh: roads and their network-scale impediment to animal movement |
title_full |
Caught in the mesh: roads and their network-scale impediment to animal movement |
title_fullStr |
Caught in the mesh: roads and their network-scale impediment to animal movement |
title_full_unstemmed |
Caught in the mesh: roads and their network-scale impediment to animal movement |
title_sort |
caught in the mesh: roads and their network-scale impediment to animal movement |
publishDate |
2016 |
url |
http://hdl.handle.net/11250/2425762 https://doi.org/10.1111/ecog.02801 |
genre |
Ursus arctos |
genre_facet |
Ursus arctos |
op_source |
Ecography |
op_relation |
urn:issn:0906-7590 http://hdl.handle.net/11250/2425762 https://doi.org/10.1111/ecog.02801 cristin:1412408 |
op_doi |
https://doi.org/10.1111/ecog.02801 |
container_title |
Ecography |
container_volume |
40 |
container_issue |
12 |
container_start_page |
1369 |
op_container_end_page |
1380 |
_version_ |
1766231754359701504 |