Long-term tracking and quantification of individual behavior in bumble bee colonies
Social insects are ecologically dominant and provide vital ecosystem services. It is critical to understand collective responses of social insects such as bees to ecological perturbations. However, studying behavior of individual insects across entire colonies and across timescales relevant for colo...
Gespeichert in:
Veröffentlicht in: | Artificial life and robotics 2022-05, Vol.27 (2), p.401-406 |
---|---|
Hauptverfasser: | , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 406 |
---|---|
container_issue | 2 |
container_start_page | 401 |
container_title | Artificial life and robotics |
container_volume | 27 |
creator | Smith, Matthew A.-Y. Easton-Calabria, August Zhang, Tony Zmyslony, Szymon Thuma, Jessie Cronin, Kayleigh Pasadyn, Cassandra L. de Bivort, Benjamin L. Crall, James D. |
description | Social insects are ecologically dominant and provide vital ecosystem services. It is critical to understand collective responses of social insects such as bees to ecological perturbations. However, studying behavior of individual insects across entire colonies and across timescales relevant for colony performance (i.e., days or weeks) remains a central challenge. Here, we describe an approach for long-term monitoring of individuals within multiple bumble bee (
Bombus
spp.) colonies that combines the complementary strengths of multiple existing methods. Specifically, we combine (a) automated monitoring, (b) fiducial tag tracking, and (c) pose estimation to quantify behavior across multiple colonies over a 48 h period. Finally, we demonstrate the benefits of this approach by quantifying an important but subtle behavior (antennal activity) in bumble bee colonies, and how this behavior is impacted by a common environmental stressor (a neonicotinoid pesticide). |
doi_str_mv | 10.1007/s10015-022-00762-x |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2664061220</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2664061220</sourcerecordid><originalsourceid>FETCH-LOGICAL-c293t-15f917875ef5c043182dd79bbe1cbc63e300bdbc4f4f867df8362b3bfe8e5d3</originalsourceid><addsrcrecordid>eNp9kEtLAzEUhQdRsFb_gKuA62hek5lZSvEFBRd1H_KsqdOkTWZK_fdGR3Dn5r4451z4quoao1uMUHOXS8U1RITAsnICjyfVDHPMYMNqflpmRimsSdeeVxc5bxBiDeJ0Vq2WMazhYNMWDEnqDx_WQAYD9qMMg3dey8HHAKIDPhh_8GaUPVD2XR58TOUG1LhVvS0nC3TsY_A2X1ZnTvbZXv32ebV6fHhbPMPl69PL4n4JNenoAHHtOty0TW1drRGjuCXGNJ1SFmulObUUIWWUZo65ljfGtZQTRZWzra0NnVc3U-ouxf1o8yA2cUyhPBSEc4Y4JgQVFZlUOsWck3Vil_xWpk-BkfhGJyZ0oqATP-jEsZjoZMpFHNY2_UX_4_oCwrJy_Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2664061220</pqid></control><display><type>article</type><title>Long-term tracking and quantification of individual behavior in bumble bee colonies</title><source>SpringerLink Journals - AutoHoldings</source><creator>Smith, Matthew A.-Y. ; Easton-Calabria, August ; Zhang, Tony ; Zmyslony, Szymon ; Thuma, Jessie ; Cronin, Kayleigh ; Pasadyn, Cassandra L. ; de Bivort, Benjamin L. ; Crall, James D.</creator><creatorcontrib>Smith, Matthew A.-Y. ; Easton-Calabria, August ; Zhang, Tony ; Zmyslony, Szymon ; Thuma, Jessie ; Cronin, Kayleigh ; Pasadyn, Cassandra L. ; de Bivort, Benjamin L. ; Crall, James D.</creatorcontrib><description>Social insects are ecologically dominant and provide vital ecosystem services. It is critical to understand collective responses of social insects such as bees to ecological perturbations. However, studying behavior of individual insects across entire colonies and across timescales relevant for colony performance (i.e., days or weeks) remains a central challenge. Here, we describe an approach for long-term monitoring of individuals within multiple bumble bee (
Bombus
spp.) colonies that combines the complementary strengths of multiple existing methods. Specifically, we combine (a) automated monitoring, (b) fiducial tag tracking, and (c) pose estimation to quantify behavior across multiple colonies over a 48 h period. Finally, we demonstrate the benefits of this approach by quantifying an important but subtle behavior (antennal activity) in bumble bee colonies, and how this behavior is impacted by a common environmental stressor (a neonicotinoid pesticide).</description><identifier>ISSN: 1433-5298</identifier><identifier>EISSN: 1614-7456</identifier><identifier>DOI: 10.1007/s10015-022-00762-x</identifier><language>eng</language><publisher>Tokyo: Springer Japan</publisher><subject>Artificial Intelligence ; Bees ; Colonies ; Computation by Abstract Devices ; Computer Science ; Control ; Insect ecology ; Insects ; Mechatronics ; Monitoring ; Original Article ; Perturbation ; Pesticides ; Pose estimation ; Robotics ; Tracking</subject><ispartof>Artificial life and robotics, 2022-05, Vol.27 (2), p.401-406</ispartof><rights>The Author(s) 2022</rights><rights>The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-15f917875ef5c043182dd79bbe1cbc63e300bdbc4f4f867df8362b3bfe8e5d3</citedby><cites>FETCH-LOGICAL-c293t-15f917875ef5c043182dd79bbe1cbc63e300bdbc4f4f867df8362b3bfe8e5d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10015-022-00762-x$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10015-022-00762-x$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,27922,27923,41486,42555,51317</link.rule.ids></links><search><creatorcontrib>Smith, Matthew A.-Y.</creatorcontrib><creatorcontrib>Easton-Calabria, August</creatorcontrib><creatorcontrib>Zhang, Tony</creatorcontrib><creatorcontrib>Zmyslony, Szymon</creatorcontrib><creatorcontrib>Thuma, Jessie</creatorcontrib><creatorcontrib>Cronin, Kayleigh</creatorcontrib><creatorcontrib>Pasadyn, Cassandra L.</creatorcontrib><creatorcontrib>de Bivort, Benjamin L.</creatorcontrib><creatorcontrib>Crall, James D.</creatorcontrib><title>Long-term tracking and quantification of individual behavior in bumble bee colonies</title><title>Artificial life and robotics</title><addtitle>Artif Life Robotics</addtitle><description>Social insects are ecologically dominant and provide vital ecosystem services. It is critical to understand collective responses of social insects such as bees to ecological perturbations. However, studying behavior of individual insects across entire colonies and across timescales relevant for colony performance (i.e., days or weeks) remains a central challenge. Here, we describe an approach for long-term monitoring of individuals within multiple bumble bee (
Bombus
spp.) colonies that combines the complementary strengths of multiple existing methods. Specifically, we combine (a) automated monitoring, (b) fiducial tag tracking, and (c) pose estimation to quantify behavior across multiple colonies over a 48 h period. Finally, we demonstrate the benefits of this approach by quantifying an important but subtle behavior (antennal activity) in bumble bee colonies, and how this behavior is impacted by a common environmental stressor (a neonicotinoid pesticide).</description><subject>Artificial Intelligence</subject><subject>Bees</subject><subject>Colonies</subject><subject>Computation by Abstract Devices</subject><subject>Computer Science</subject><subject>Control</subject><subject>Insect ecology</subject><subject>Insects</subject><subject>Mechatronics</subject><subject>Monitoring</subject><subject>Original Article</subject><subject>Perturbation</subject><subject>Pesticides</subject><subject>Pose estimation</subject><subject>Robotics</subject><subject>Tracking</subject><issn>1433-5298</issn><issn>1614-7456</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><recordid>eNp9kEtLAzEUhQdRsFb_gKuA62hek5lZSvEFBRd1H_KsqdOkTWZK_fdGR3Dn5r4451z4quoao1uMUHOXS8U1RITAsnICjyfVDHPMYMNqflpmRimsSdeeVxc5bxBiDeJ0Vq2WMazhYNMWDEnqDx_WQAYD9qMMg3dey8HHAKIDPhh_8GaUPVD2XR58TOUG1LhVvS0nC3TsY_A2X1ZnTvbZXv32ebV6fHhbPMPl69PL4n4JNenoAHHtOty0TW1drRGjuCXGNJ1SFmulObUUIWWUZo65ljfGtZQTRZWzra0NnVc3U-ouxf1o8yA2cUyhPBSEc4Y4JgQVFZlUOsWck3Vil_xWpk-BkfhGJyZ0oqATP-jEsZjoZMpFHNY2_UX_4_oCwrJy_Q</recordid><startdate>20220501</startdate><enddate>20220501</enddate><creator>Smith, Matthew A.-Y.</creator><creator>Easton-Calabria, August</creator><creator>Zhang, Tony</creator><creator>Zmyslony, Szymon</creator><creator>Thuma, Jessie</creator><creator>Cronin, Kayleigh</creator><creator>Pasadyn, Cassandra L.</creator><creator>de Bivort, Benjamin L.</creator><creator>Crall, James D.</creator><general>Springer Japan</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20220501</creationdate><title>Long-term tracking and quantification of individual behavior in bumble bee colonies</title><author>Smith, Matthew A.-Y. ; Easton-Calabria, August ; Zhang, Tony ; Zmyslony, Szymon ; Thuma, Jessie ; Cronin, Kayleigh ; Pasadyn, Cassandra L. ; de Bivort, Benjamin L. ; Crall, James D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-15f917875ef5c043182dd79bbe1cbc63e300bdbc4f4f867df8362b3bfe8e5d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Artificial Intelligence</topic><topic>Bees</topic><topic>Colonies</topic><topic>Computation by Abstract Devices</topic><topic>Computer Science</topic><topic>Control</topic><topic>Insect ecology</topic><topic>Insects</topic><topic>Mechatronics</topic><topic>Monitoring</topic><topic>Original Article</topic><topic>Perturbation</topic><topic>Pesticides</topic><topic>Pose estimation</topic><topic>Robotics</topic><topic>Tracking</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Smith, Matthew A.-Y.</creatorcontrib><creatorcontrib>Easton-Calabria, August</creatorcontrib><creatorcontrib>Zhang, Tony</creatorcontrib><creatorcontrib>Zmyslony, Szymon</creatorcontrib><creatorcontrib>Thuma, Jessie</creatorcontrib><creatorcontrib>Cronin, Kayleigh</creatorcontrib><creatorcontrib>Pasadyn, Cassandra L.</creatorcontrib><creatorcontrib>de Bivort, Benjamin L.</creatorcontrib><creatorcontrib>Crall, James D.</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>CrossRef</collection><jtitle>Artificial life and robotics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Smith, Matthew A.-Y.</au><au>Easton-Calabria, August</au><au>Zhang, Tony</au><au>Zmyslony, Szymon</au><au>Thuma, Jessie</au><au>Cronin, Kayleigh</au><au>Pasadyn, Cassandra L.</au><au>de Bivort, Benjamin L.</au><au>Crall, James D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Long-term tracking and quantification of individual behavior in bumble bee colonies</atitle><jtitle>Artificial life and robotics</jtitle><stitle>Artif Life Robotics</stitle><date>2022-05-01</date><risdate>2022</risdate><volume>27</volume><issue>2</issue><spage>401</spage><epage>406</epage><pages>401-406</pages><issn>1433-5298</issn><eissn>1614-7456</eissn><abstract>Social insects are ecologically dominant and provide vital ecosystem services. It is critical to understand collective responses of social insects such as bees to ecological perturbations. However, studying behavior of individual insects across entire colonies and across timescales relevant for colony performance (i.e., days or weeks) remains a central challenge. Here, we describe an approach for long-term monitoring of individuals within multiple bumble bee (
Bombus
spp.) colonies that combines the complementary strengths of multiple existing methods. Specifically, we combine (a) automated monitoring, (b) fiducial tag tracking, and (c) pose estimation to quantify behavior across multiple colonies over a 48 h period. Finally, we demonstrate the benefits of this approach by quantifying an important but subtle behavior (antennal activity) in bumble bee colonies, and how this behavior is impacted by a common environmental stressor (a neonicotinoid pesticide).</abstract><cop>Tokyo</cop><pub>Springer Japan</pub><doi>10.1007/s10015-022-00762-x</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1433-5298 |
ispartof | Artificial life and robotics, 2022-05, Vol.27 (2), p.401-406 |
issn | 1433-5298 1614-7456 |
language | eng |
recordid | cdi_proquest_journals_2664061220 |
source | SpringerLink Journals - AutoHoldings |
subjects | Artificial Intelligence Bees Colonies Computation by Abstract Devices Computer Science Control Insect ecology Insects Mechatronics Monitoring Original Article Perturbation Pesticides Pose estimation Robotics Tracking |
title | Long-term tracking and quantification of individual behavior in bumble bee colonies |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-13T20%3A52%3A21IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Long-term%20tracking%20and%20quantification%20of%20individual%20behavior%20in%20bumble%20bee%20colonies&rft.jtitle=Artificial%20life%20and%20robotics&rft.au=Smith,%20Matthew%20A.-Y.&rft.date=2022-05-01&rft.volume=27&rft.issue=2&rft.spage=401&rft.epage=406&rft.pages=401-406&rft.issn=1433-5298&rft.eissn=1614-7456&rft_id=info:doi/10.1007/s10015-022-00762-x&rft_dat=%3Cproquest_cross%3E2664061220%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2664061220&rft_id=info:pmid/&rfr_iscdi=true |