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Unravelling the impact of climate change on honey bees: An ensemble modelling approach to predict shifts in habitat suitability in Queensland, Australia
Honey bees play a vital role in providing essential ecosystem services and contributing to global agriculture. However, the potential effect of climate change on honey bee distribution is still not well understood. This study aims to identify the most influential bioclimatic and environmental variab...
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Published in: | Ecology and evolution 2024-04, Vol.14 (4), p.e11300-n/a |
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description | Honey bees play a vital role in providing essential ecosystem services and contributing to global agriculture. However, the potential effect of climate change on honey bee distribution is still not well understood. This study aims to identify the most influential bioclimatic and environmental variables, assess their impact on honey bee distribution, and predict future distribution. An ensemble modelling approach using the biomod2 package in R was employed to develop three models: a climate‐only model, an environment‐only model, and a combined climate and environment model. By utilising bioclimatic data (radiation of the wettest and driest quarters and temperature seasonality) from 1990 to 2009, combined with observed honey bee presence and pseudo absence data, this model predicted suitable locations for honey bee apiaries for two future time spans: 2020–2039 and 2060–2079. The climate‐only model exhibited a true skill statistic (TSS) value of 0.85, underscoring the pivotal role of radiation and temperature seasonality in shaping honey bee distribution. The environment‐only model, incorporating proximity to floral resources, foliage projective cover, and elevation, demonstrated strong predictive performance, with a TSS of 0.88, emphasising the significance of environmental variables in determining habitat suitability for honey bees. The combined model had a higher TSS of 0.96, indicating that the combination of climate and environmental variables enhances the model's performance. By the 2020–2039 period, approximately 88% of highly suitable habitats for honey bees are projected to transition from their current state to become moderate (14.84%) to marginally suitable (13.46%) areas. Predictions for the 2060–2079 period reveal a concerning trend: 100% of highly suitable land transitions into moderately (0.54%), marginally (17.56%), or not suitable areas (81.9%) for honey bees. These results emphasise the critical need for targeted conservation efforts and the implementation of policies aimed at safeguarding honey bees and the vital apiary industry.
This study uses climate data from 1990 to 2009, environmental variables, and honey bee presence and pseudo absence data to produce three models: climate‐only, environment‐only, and a combined climate and environment model, along with suitability maps. Moreover, honey bee distribution is predicted for two future time spans: 2020–2039 and 2060–2079. |
doi_str_mv | 10.1002/ece3.11300 |
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This study uses climate data from 1990 to 2009, environmental variables, and honey bee presence and pseudo absence data to produce three models: climate‐only, environment‐only, and a combined climate and environment model, along with suitability maps. Moreover, honey bee distribution is predicted for two future time spans: 2020–2039 and 2060–2079.</description><identifier>ISSN: 2045-7758</identifier><identifier>EISSN: 2045-7758</identifier><identifier>DOI: 10.1002/ece3.11300</identifier><identifier>PMID: 38638367</identifier><language>eng</language><publisher>England: John Wiley & Sons, Inc</publisher><subject>Agricultural ecosystems ; Agriculture ; Agroecology ; Apis mellifera ; Bees ; Bioclimatology ; Biometeorology ; biomod2 ; Climate change ; Climate effects ; Climate models ; Ecosystem Ecology ; Ecosystem services ; ensemble modelling ; Environment models ; Environmental impact ; Foliage ; Habitats ; Honey ; honey bees ; Performance prediction ; Seasonal variations ; species distribution modelling</subject><ispartof>Ecology and evolution, 2024-04, Vol.14 (4), p.e11300-n/a</ispartof><rights>2024 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2024 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.</rights><rights>2024. 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><cites>FETCH-LOGICAL-c5130-d855006b2c1db74ca21ce18f66f5911c8748b5686b648563819fa19cb6768dde3</cites><orcidid>0000-0002-5412-8881 ; 0000-0001-9361-1983 ; 0000-0002-4275-2847</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/3047720431/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3047720431?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,11562,25753,27924,27925,37012,37013,44590,46052,46476,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38638367$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tennakoon, Sarasie</creatorcontrib><creatorcontrib>Apan, Armando</creatorcontrib><creatorcontrib>Maraseni, Tek</creatorcontrib><title>Unravelling the impact of climate change on honey bees: An ensemble modelling approach to predict shifts in habitat suitability in Queensland, Australia</title><title>Ecology and evolution</title><addtitle>Ecol Evol</addtitle><description>Honey bees play a vital role in providing essential ecosystem services and contributing to global agriculture. However, the potential effect of climate change on honey bee distribution is still not well understood. This study aims to identify the most influential bioclimatic and environmental variables, assess their impact on honey bee distribution, and predict future distribution. An ensemble modelling approach using the biomod2 package in R was employed to develop three models: a climate‐only model, an environment‐only model, and a combined climate and environment model. By utilising bioclimatic data (radiation of the wettest and driest quarters and temperature seasonality) from 1990 to 2009, combined with observed honey bee presence and pseudo absence data, this model predicted suitable locations for honey bee apiaries for two future time spans: 2020–2039 and 2060–2079. The climate‐only model exhibited a true skill statistic (TSS) value of 0.85, underscoring the pivotal role of radiation and temperature seasonality in shaping honey bee distribution. The environment‐only model, incorporating proximity to floral resources, foliage projective cover, and elevation, demonstrated strong predictive performance, with a TSS of 0.88, emphasising the significance of environmental variables in determining habitat suitability for honey bees. The combined model had a higher TSS of 0.96, indicating that the combination of climate and environmental variables enhances the model's performance. By the 2020–2039 period, approximately 88% of highly suitable habitats for honey bees are projected to transition from their current state to become moderate (14.84%) to marginally suitable (13.46%) areas. Predictions for the 2060–2079 period reveal a concerning trend: 100% of highly suitable land transitions into moderately (0.54%), marginally (17.56%), or not suitable areas (81.9%) for honey bees. These results emphasise the critical need for targeted conservation efforts and the implementation of policies aimed at safeguarding honey bees and the vital apiary industry.
This study uses climate data from 1990 to 2009, environmental variables, and honey bee presence and pseudo absence data to produce three models: climate‐only, environment‐only, and a combined climate and environment model, along with suitability maps. Moreover, honey bee distribution is predicted for two future time spans: 2020–2039 and 2060–2079.</description><subject>Agricultural ecosystems</subject><subject>Agriculture</subject><subject>Agroecology</subject><subject>Apis mellifera</subject><subject>Bees</subject><subject>Bioclimatology</subject><subject>Biometeorology</subject><subject>biomod2</subject><subject>Climate change</subject><subject>Climate effects</subject><subject>Climate models</subject><subject>Ecosystem Ecology</subject><subject>Ecosystem services</subject><subject>ensemble modelling</subject><subject>Environment models</subject><subject>Environmental impact</subject><subject>Foliage</subject><subject>Habitats</subject><subject>Honey</subject><subject>honey bees</subject><subject>Performance prediction</subject><subject>Seasonal variations</subject><subject>species distribution modelling</subject><issn>2045-7758</issn><issn>2045-7758</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp9kt9qFDEUhwdRbKm98QEk4I1ItyaTmSTrTVmWrRYKItjrkD9ndrLMJGMyU9k38XHNdNfSemFuEk6-fOSXnKJ4S_Alwbj8BAboJSEU4xfFaYmresF5LV4-WZ8U5yntcB4MlxXmr4sTKhgVlPHT4vedj-oeus75LRpbQK4flBlRaJDpXK9GQKZVfgsoeNQGD3ukAdJntPIIfIJed4D6YI8GNQwxKNOiMaAhgnVZlVrXjAm5fF5pN6pcmfKkXefG_Vz-PkFWdcrbC7Sa0hhV59Sb4lWjugTnx_msuLve_Fh_Xdx--3KzXt0uTJ1DL6yo6xxMl4ZYzSujSmKAiIaxpl4SYgSvhK6ZYJpVos6pybJRZGk040xYC_SsuDl4bVA7OcScOe5lUE4-FELcShVHZzqQtcaGl9wKbmhlCVZlg5tlhQluKpxL2XV1cA2T7sEa8HOWZ9LnO961chvuJSH5Z5ios-HD0RDDzwnSKHuXTH5c5SFMSVJcUczpkvCMvv8H3YUp-vxWM8V5_n9KMvXxQJkYUorQPN6GYDk3kJwbSD40UIbfPb3_I_q3XTJADsAv18H-Pyq5WW_oQfoH19TQdA</recordid><startdate>202404</startdate><enddate>202404</enddate><creator>Tennakoon, Sarasie</creator><creator>Apan, Armando</creator><creator>Maraseni, Tek</creator><general>John Wiley & Sons, Inc</general><general>John Wiley and Sons Inc</general><general>Wiley</general><scope>24P</scope><scope>WIN</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SN</scope><scope>7SS</scope><scope>7ST</scope><scope>7X2</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M0K</scope><scope>M7P</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>RC3</scope><scope>SOI</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-5412-8881</orcidid><orcidid>https://orcid.org/0000-0001-9361-1983</orcidid><orcidid>https://orcid.org/0000-0002-4275-2847</orcidid></search><sort><creationdate>202404</creationdate><title>Unravelling the impact of climate change on honey bees: An ensemble modelling approach to predict shifts in habitat suitability in Queensland, Australia</title><author>Tennakoon, Sarasie ; 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However, the potential effect of climate change on honey bee distribution is still not well understood. This study aims to identify the most influential bioclimatic and environmental variables, assess their impact on honey bee distribution, and predict future distribution. An ensemble modelling approach using the biomod2 package in R was employed to develop three models: a climate‐only model, an environment‐only model, and a combined climate and environment model. By utilising bioclimatic data (radiation of the wettest and driest quarters and temperature seasonality) from 1990 to 2009, combined with observed honey bee presence and pseudo absence data, this model predicted suitable locations for honey bee apiaries for two future time spans: 2020–2039 and 2060–2079. The climate‐only model exhibited a true skill statistic (TSS) value of 0.85, underscoring the pivotal role of radiation and temperature seasonality in shaping honey bee distribution. The environment‐only model, incorporating proximity to floral resources, foliage projective cover, and elevation, demonstrated strong predictive performance, with a TSS of 0.88, emphasising the significance of environmental variables in determining habitat suitability for honey bees. The combined model had a higher TSS of 0.96, indicating that the combination of climate and environmental variables enhances the model's performance. By the 2020–2039 period, approximately 88% of highly suitable habitats for honey bees are projected to transition from their current state to become moderate (14.84%) to marginally suitable (13.46%) areas. Predictions for the 2060–2079 period reveal a concerning trend: 100% of highly suitable land transitions into moderately (0.54%), marginally (17.56%), or not suitable areas (81.9%) for honey bees. These results emphasise the critical need for targeted conservation efforts and the implementation of policies aimed at safeguarding honey bees and the vital apiary industry.
This study uses climate data from 1990 to 2009, environmental variables, and honey bee presence and pseudo absence data to produce three models: climate‐only, environment‐only, and a combined climate and environment model, along with suitability maps. Moreover, honey bee distribution is predicted for two future time spans: 2020–2039 and 2060–2079.</abstract><cop>England</cop><pub>John Wiley & Sons, Inc</pub><pmid>38638367</pmid><doi>10.1002/ece3.11300</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0002-5412-8881</orcidid><orcidid>https://orcid.org/0000-0001-9361-1983</orcidid><orcidid>https://orcid.org/0000-0002-4275-2847</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Agricultural ecosystems Agriculture Agroecology Apis mellifera Bees Bioclimatology Biometeorology biomod2 Climate change Climate effects Climate models Ecosystem Ecology Ecosystem services ensemble modelling Environment models Environmental impact Foliage Habitats Honey honey bees Performance prediction Seasonal variations species distribution modelling |
title | Unravelling the impact of climate change on honey bees: An ensemble modelling approach to predict shifts in habitat suitability in Queensland, Australia |
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