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Quantifying and predicting population connectivity of an outbreaking forest insect pest
CONTEXT: Dispersal has a key role in the population dynamics of outbreaking species such as the spruce budworm (Choristoneura fumiferana) as it can synchronize the demography of distant populations and favor the transition from endemic to epidemic states. However, we know very little about how lands...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8897358/ https://www.ncbi.nlm.nih.gov/pubmed/35273428 http://dx.doi.org/10.1007/s10980-021-01382-9 |
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author | Larroque, Jeremy Wittische, Julian James, Patrick M. A. |
author_facet | Larroque, Jeremy Wittische, Julian James, Patrick M. A. |
author_sort | Larroque, Jeremy |
collection | PubMed |
description | CONTEXT: Dispersal has a key role in the population dynamics of outbreaking species such as the spruce budworm (Choristoneura fumiferana) as it can synchronize the demography of distant populations and favor the transition from endemic to epidemic states. However, we know very little about how landscape structure influences dispersal in such systems while such knowledge is essential for better forecasting of spatially synchronous population dynamics and to guide management strategies. OBJECTIVES: We aimed to characterize the spatial environmental determinants of spruce budworm dispersal to determine how these features affect outbreak spread in Quebec (Canada). We then apply our findings to predict expected future landscape connectivity and explore its potential consequences on future outbreaks. METHODS: We used a machine-learning landscape genetics approach on 447 larvae covering most of the outbreak area and genotyped at 3562 SNP loci to identify the main variables affecting connectivity. RESULTS: We found that the connectivity between outbreak populations was driven by the combination of precipitation and host cover. Our forecasting suggests that between the current and next outbreaks, connectivity may increase between Ontario and Quebec, and might decrease in the eastern part, which could have the effect of limiting outbreak spread from Ontario and Quebec to the eastern provinces. CONCLUSIONS: Although we did not identify any discrete barriers, low connectivity areas might constrain dispersal in the current and future outbreaks and should in turn, be intensively monitored. However, continued sampling as the outbreak progresses is needed to confirm the temporal stability of the observed patterns. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10980-021-01382-9. |
format | Online Article Text |
id | pubmed-8897358 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-88973582022-03-08 Quantifying and predicting population connectivity of an outbreaking forest insect pest Larroque, Jeremy Wittische, Julian James, Patrick M. A. Landsc Ecol Research Article CONTEXT: Dispersal has a key role in the population dynamics of outbreaking species such as the spruce budworm (Choristoneura fumiferana) as it can synchronize the demography of distant populations and favor the transition from endemic to epidemic states. However, we know very little about how landscape structure influences dispersal in such systems while such knowledge is essential for better forecasting of spatially synchronous population dynamics and to guide management strategies. OBJECTIVES: We aimed to characterize the spatial environmental determinants of spruce budworm dispersal to determine how these features affect outbreak spread in Quebec (Canada). We then apply our findings to predict expected future landscape connectivity and explore its potential consequences on future outbreaks. METHODS: We used a machine-learning landscape genetics approach on 447 larvae covering most of the outbreak area and genotyped at 3562 SNP loci to identify the main variables affecting connectivity. RESULTS: We found that the connectivity between outbreak populations was driven by the combination of precipitation and host cover. Our forecasting suggests that between the current and next outbreaks, connectivity may increase between Ontario and Quebec, and might decrease in the eastern part, which could have the effect of limiting outbreak spread from Ontario and Quebec to the eastern provinces. CONCLUSIONS: Although we did not identify any discrete barriers, low connectivity areas might constrain dispersal in the current and future outbreaks and should in turn, be intensively monitored. However, continued sampling as the outbreak progresses is needed to confirm the temporal stability of the observed patterns. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10980-021-01382-9. Springer Netherlands 2021-12-23 2022 /pmc/articles/PMC8897358/ /pubmed/35273428 http://dx.doi.org/10.1007/s10980-021-01382-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Larroque, Jeremy Wittische, Julian James, Patrick M. A. Quantifying and predicting population connectivity of an outbreaking forest insect pest |
title | Quantifying and predicting population connectivity of an outbreaking forest insect pest |
title_full | Quantifying and predicting population connectivity of an outbreaking forest insect pest |
title_fullStr | Quantifying and predicting population connectivity of an outbreaking forest insect pest |
title_full_unstemmed | Quantifying and predicting population connectivity of an outbreaking forest insect pest |
title_short | Quantifying and predicting population connectivity of an outbreaking forest insect pest |
title_sort | quantifying and predicting population connectivity of an outbreaking forest insect pest |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8897358/ https://www.ncbi.nlm.nih.gov/pubmed/35273428 http://dx.doi.org/10.1007/s10980-021-01382-9 |
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