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Extrapolating potential crop damage by insect pests based on land use data: examining inter-regional generality in agricultural landscapes

BACKGROUND: Inter-regional relationships between landscape factors and biological responses in natural conditions are important but difficult to predict because of the differences in each landscape context and local environment. To examine the inter-regional variability in relation to landscape fact...

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Autores principales: Tabuchi, Ken, Takahashi, Akihiko, Uesugi, Ryuji, Okudera, Shigeru, Yoshimura, Hideto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9131665/
https://www.ncbi.nlm.nih.gov/pubmed/35614432
http://dx.doi.org/10.1186/s12862-022-02024-7
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author Tabuchi, Ken
Takahashi, Akihiko
Uesugi, Ryuji
Okudera, Shigeru
Yoshimura, Hideto
author_facet Tabuchi, Ken
Takahashi, Akihiko
Uesugi, Ryuji
Okudera, Shigeru
Yoshimura, Hideto
author_sort Tabuchi, Ken
collection PubMed
description BACKGROUND: Inter-regional relationships between landscape factors and biological responses in natural conditions are important but difficult to predict because of the differences in each landscape context and local environment. To examine the inter-regional variability in relation to landscape factors and the biological response of an insect pest of rice, Stenotus rubrovittatus, we extrapolated a damage prediction model (the ‘original model’ of our previous study) for rice using land-use data. The ‘original model’ comprised as fixed factors the area of source habitat (i.e. pastures and graminoid-dominated fallow fields), soybean fields, and rice paddies within 300-m radii with research years as the random intercept. We hypothesized that the original model would be applicable to new regions, but the predictive accuracy would be reduced. We predicted that fitting a new extended model, adjusting the parameter coefficients of identical fixed factors of the ‘original model,’ and adding regional random intercepts would improve model performance (the ‘extended model’). A field experiment was conducted in two regions that had a similar landscape context with the original region, each in a different year of four years in total. The proportion of rice damage and surrounding land use within a 300-m radius was investigated, and the data were applied to the models and the applicability and accuracy of the models were examined. RESULTS: When the ‘original model’ was assigned to the combined data from the original and extrapolated regions, the relationship between the observed and the predicted values was statistically significant, suggesting that there was an inter-regional common relationship. The relationship was not statistically significant if the model was applied only to the new regions. The extended model accuracy improved by 14% compared with the original model and was applicable for unknown data within the examined regions as demonstrated by three-fold cross validation. CONCLUSIONS: These results imply that in this pest–crop system, there is likely to be a common inter-regional biological response of arthropods because of landscape factors, although we need to consider local environmental factors. We should be able to apply such relationships to identify or prevent pest hazards by offering region-wide management options. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12862-022-02024-7.
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spelling pubmed-91316652022-05-26 Extrapolating potential crop damage by insect pests based on land use data: examining inter-regional generality in agricultural landscapes Tabuchi, Ken Takahashi, Akihiko Uesugi, Ryuji Okudera, Shigeru Yoshimura, Hideto BMC Ecol Evol Research BACKGROUND: Inter-regional relationships between landscape factors and biological responses in natural conditions are important but difficult to predict because of the differences in each landscape context and local environment. To examine the inter-regional variability in relation to landscape factors and the biological response of an insect pest of rice, Stenotus rubrovittatus, we extrapolated a damage prediction model (the ‘original model’ of our previous study) for rice using land-use data. The ‘original model’ comprised as fixed factors the area of source habitat (i.e. pastures and graminoid-dominated fallow fields), soybean fields, and rice paddies within 300-m radii with research years as the random intercept. We hypothesized that the original model would be applicable to new regions, but the predictive accuracy would be reduced. We predicted that fitting a new extended model, adjusting the parameter coefficients of identical fixed factors of the ‘original model,’ and adding regional random intercepts would improve model performance (the ‘extended model’). A field experiment was conducted in two regions that had a similar landscape context with the original region, each in a different year of four years in total. The proportion of rice damage and surrounding land use within a 300-m radius was investigated, and the data were applied to the models and the applicability and accuracy of the models were examined. RESULTS: When the ‘original model’ was assigned to the combined data from the original and extrapolated regions, the relationship between the observed and the predicted values was statistically significant, suggesting that there was an inter-regional common relationship. The relationship was not statistically significant if the model was applied only to the new regions. The extended model accuracy improved by 14% compared with the original model and was applicable for unknown data within the examined regions as demonstrated by three-fold cross validation. CONCLUSIONS: These results imply that in this pest–crop system, there is likely to be a common inter-regional biological response of arthropods because of landscape factors, although we need to consider local environmental factors. We should be able to apply such relationships to identify or prevent pest hazards by offering region-wide management options. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12862-022-02024-7. BioMed Central 2022-05-25 /pmc/articles/PMC9131665/ /pubmed/35614432 http://dx.doi.org/10.1186/s12862-022-02024-7 Text en © The Author(s) 2022 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Tabuchi, Ken
Takahashi, Akihiko
Uesugi, Ryuji
Okudera, Shigeru
Yoshimura, Hideto
Extrapolating potential crop damage by insect pests based on land use data: examining inter-regional generality in agricultural landscapes
title Extrapolating potential crop damage by insect pests based on land use data: examining inter-regional generality in agricultural landscapes
title_full Extrapolating potential crop damage by insect pests based on land use data: examining inter-regional generality in agricultural landscapes
title_fullStr Extrapolating potential crop damage by insect pests based on land use data: examining inter-regional generality in agricultural landscapes
title_full_unstemmed Extrapolating potential crop damage by insect pests based on land use data: examining inter-regional generality in agricultural landscapes
title_short Extrapolating potential crop damage by insect pests based on land use data: examining inter-regional generality in agricultural landscapes
title_sort extrapolating potential crop damage by insect pests based on land use data: examining inter-regional generality in agricultural landscapes
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9131665/
https://www.ncbi.nlm.nih.gov/pubmed/35614432
http://dx.doi.org/10.1186/s12862-022-02024-7
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