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Prospective Large-Scale Field Study Generates Predictive Model Identifying Major Contributors to Colony Losses

Over the last decade, unusually high losses of colonies have been reported by beekeepers across the USA. Multiple factors such as Varroa destructor, bee viruses, Nosema ceranae, weather, beekeeping practices, nutrition, and pesticides have been shown to contribute to colony losses. Here we describe...

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Autores principales: Kielmanowicz, Merav Gleit, Inberg, Alex, Lerner, Inbar Maayan, Golani, Yael, Brown, Nicholas, Turner, Catherine Louise, Hayes, Gerald J. R., Ballam, Joan M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4395366/
https://www.ncbi.nlm.nih.gov/pubmed/25875764
http://dx.doi.org/10.1371/journal.ppat.1004816
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author Kielmanowicz, Merav Gleit
Inberg, Alex
Lerner, Inbar Maayan
Golani, Yael
Brown, Nicholas
Turner, Catherine Louise
Hayes, Gerald J. R.
Ballam, Joan M.
author_facet Kielmanowicz, Merav Gleit
Inberg, Alex
Lerner, Inbar Maayan
Golani, Yael
Brown, Nicholas
Turner, Catherine Louise
Hayes, Gerald J. R.
Ballam, Joan M.
author_sort Kielmanowicz, Merav Gleit
collection PubMed
description Over the last decade, unusually high losses of colonies have been reported by beekeepers across the USA. Multiple factors such as Varroa destructor, bee viruses, Nosema ceranae, weather, beekeeping practices, nutrition, and pesticides have been shown to contribute to colony losses. Here we describe a large-scale controlled trial, in which different bee pathogens, bee population, and weather conditions across winter were monitored at three locations across the USA. In order to minimize influence of various known contributing factors and their interaction, the hives in the study were not treated with antibiotics or miticides. Additionally, the hives were kept at one location and were not exposed to potential stress factors associated with migration. Our results show that a linear association between load of viruses (DWV or IAPV) in Varroa and bees is present at high Varroa infestation levels (>3 mites per 100 bees). The collection of comprehensive data allowed us to draw a predictive model of colony losses and to show that Varroa destructor, along with bee viruses, mainly DWV replication, contributes to approximately 70% of colony losses. This correlation further supports the claim that insufficient control of the virus-vectoring Varroa mite would result in increased hive loss. The predictive model also indicates that a single factor may not be sufficient to trigger colony losses, whereas a combination of stressors appears to impact hive health.
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spelling pubmed-43953662015-04-21 Prospective Large-Scale Field Study Generates Predictive Model Identifying Major Contributors to Colony Losses Kielmanowicz, Merav Gleit Inberg, Alex Lerner, Inbar Maayan Golani, Yael Brown, Nicholas Turner, Catherine Louise Hayes, Gerald J. R. Ballam, Joan M. PLoS Pathog Research Article Over the last decade, unusually high losses of colonies have been reported by beekeepers across the USA. Multiple factors such as Varroa destructor, bee viruses, Nosema ceranae, weather, beekeeping practices, nutrition, and pesticides have been shown to contribute to colony losses. Here we describe a large-scale controlled trial, in which different bee pathogens, bee population, and weather conditions across winter were monitored at three locations across the USA. In order to minimize influence of various known contributing factors and their interaction, the hives in the study were not treated with antibiotics or miticides. Additionally, the hives were kept at one location and were not exposed to potential stress factors associated with migration. Our results show that a linear association between load of viruses (DWV or IAPV) in Varroa and bees is present at high Varroa infestation levels (>3 mites per 100 bees). The collection of comprehensive data allowed us to draw a predictive model of colony losses and to show that Varroa destructor, along with bee viruses, mainly DWV replication, contributes to approximately 70% of colony losses. This correlation further supports the claim that insufficient control of the virus-vectoring Varroa mite would result in increased hive loss. The predictive model also indicates that a single factor may not be sufficient to trigger colony losses, whereas a combination of stressors appears to impact hive health. Public Library of Science 2015-04-13 /pmc/articles/PMC4395366/ /pubmed/25875764 http://dx.doi.org/10.1371/journal.ppat.1004816 Text en © 2015 Kielmanowicz et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Kielmanowicz, Merav Gleit
Inberg, Alex
Lerner, Inbar Maayan
Golani, Yael
Brown, Nicholas
Turner, Catherine Louise
Hayes, Gerald J. R.
Ballam, Joan M.
Prospective Large-Scale Field Study Generates Predictive Model Identifying Major Contributors to Colony Losses
title Prospective Large-Scale Field Study Generates Predictive Model Identifying Major Contributors to Colony Losses
title_full Prospective Large-Scale Field Study Generates Predictive Model Identifying Major Contributors to Colony Losses
title_fullStr Prospective Large-Scale Field Study Generates Predictive Model Identifying Major Contributors to Colony Losses
title_full_unstemmed Prospective Large-Scale Field Study Generates Predictive Model Identifying Major Contributors to Colony Losses
title_short Prospective Large-Scale Field Study Generates Predictive Model Identifying Major Contributors to Colony Losses
title_sort prospective large-scale field study generates predictive model identifying major contributors to colony losses
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4395366/
https://www.ncbi.nlm.nih.gov/pubmed/25875764
http://dx.doi.org/10.1371/journal.ppat.1004816
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