Enhancing pest control interventions by linking species distribution model prediction and population density assessment of pine wilt disease vectors in South Korea
Pine wilt disease caused by pinewood nematode is one of the most destructive forest diseases, and still spreading in South Korea despite the various control efforts. Japanese pine sawyer (JPS) and Sakhalin pine sawyer (SPS) are the main vectors of the disease. Understanding the distribution and dens...
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Online Access: | http://dx.doi.org/10.3389/fevo.2023.1305573 https://www.frontiersin.org/articles/10.3389/fevo.2023.1305573/full |
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crfrontiers:10.3389/fevo.2023.1305573 2024-04-21T08:10:53+00:00 Enhancing pest control interventions by linking species distribution model prediction and population density assessment of pine wilt disease vectors in South Korea Kim, Inyoo Nam, Youngwoo Park, Sinyoung Cho, Wonhee Choi, Kwanghun Ko, Dongwook W. 2024 http://dx.doi.org/10.3389/fevo.2023.1305573 https://www.frontiersin.org/articles/10.3389/fevo.2023.1305573/full unknown Frontiers Media SA https://creativecommons.org/licenses/by/4.0/ Frontiers in Ecology and Evolution volume 11 ISSN 2296-701X Ecology Ecology, Evolution, Behavior and Systematics journal-article 2024 crfrontiers https://doi.org/10.3389/fevo.2023.1305573 2024-03-26T08:33:06Z Pine wilt disease caused by pinewood nematode is one of the most destructive forest diseases, and still spreading in South Korea despite the various control efforts. Japanese pine sawyer (JPS) and Sakhalin pine sawyer (SPS) are the main vectors of the disease. Understanding the distribution and density of the vectors is crucial since the control period is determined by the different emergence periods of the two vectors and the control method by its density and the expected damage severity. In this study, we predicted the distribution of JPS and SPS using Maxent and investigated the relationship between the resulting suitability value and the density. The population densities of JPS and SPS were obtained through a national survey using pheromone traps between 2020-2022. We converted the density data into presence/absence points to externally validate each species distribution model, then we used quantile regression to check the correlation between the suitability and population density, and finally we used three widely used thresholds to convert the model results into binary maps, and tested if they could distinguish the density by comparing the R b value of biserial correlation. The quantile regression revealed a positive relationship between the habitat suitability and population density sampled in the field. Moreover, the binary map with threshold criteria that maximizes the sum of the sensitivity and specificity had the best density discrimination capacity with the highest R b . A quantitative relationship between suitability and vector density measured in the field from our study provides reliability to species distribution model as practical tools for forest pest management. Article in Journal/Newspaper Sakhalin Frontiers (Publisher) Frontiers in Ecology and Evolution 11 |
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Ecology Ecology, Evolution, Behavior and Systematics |
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Ecology Ecology, Evolution, Behavior and Systematics Kim, Inyoo Nam, Youngwoo Park, Sinyoung Cho, Wonhee Choi, Kwanghun Ko, Dongwook W. Enhancing pest control interventions by linking species distribution model prediction and population density assessment of pine wilt disease vectors in South Korea |
topic_facet |
Ecology Ecology, Evolution, Behavior and Systematics |
description |
Pine wilt disease caused by pinewood nematode is one of the most destructive forest diseases, and still spreading in South Korea despite the various control efforts. Japanese pine sawyer (JPS) and Sakhalin pine sawyer (SPS) are the main vectors of the disease. Understanding the distribution and density of the vectors is crucial since the control period is determined by the different emergence periods of the two vectors and the control method by its density and the expected damage severity. In this study, we predicted the distribution of JPS and SPS using Maxent and investigated the relationship between the resulting suitability value and the density. The population densities of JPS and SPS were obtained through a national survey using pheromone traps between 2020-2022. We converted the density data into presence/absence points to externally validate each species distribution model, then we used quantile regression to check the correlation between the suitability and population density, and finally we used three widely used thresholds to convert the model results into binary maps, and tested if they could distinguish the density by comparing the R b value of biserial correlation. The quantile regression revealed a positive relationship between the habitat suitability and population density sampled in the field. Moreover, the binary map with threshold criteria that maximizes the sum of the sensitivity and specificity had the best density discrimination capacity with the highest R b . A quantitative relationship between suitability and vector density measured in the field from our study provides reliability to species distribution model as practical tools for forest pest management. |
format |
Article in Journal/Newspaper |
author |
Kim, Inyoo Nam, Youngwoo Park, Sinyoung Cho, Wonhee Choi, Kwanghun Ko, Dongwook W. |
author_facet |
Kim, Inyoo Nam, Youngwoo Park, Sinyoung Cho, Wonhee Choi, Kwanghun Ko, Dongwook W. |
author_sort |
Kim, Inyoo |
title |
Enhancing pest control interventions by linking species distribution model prediction and population density assessment of pine wilt disease vectors in South Korea |
title_short |
Enhancing pest control interventions by linking species distribution model prediction and population density assessment of pine wilt disease vectors in South Korea |
title_full |
Enhancing pest control interventions by linking species distribution model prediction and population density assessment of pine wilt disease vectors in South Korea |
title_fullStr |
Enhancing pest control interventions by linking species distribution model prediction and population density assessment of pine wilt disease vectors in South Korea |
title_full_unstemmed |
Enhancing pest control interventions by linking species distribution model prediction and population density assessment of pine wilt disease vectors in South Korea |
title_sort |
enhancing pest control interventions by linking species distribution model prediction and population density assessment of pine wilt disease vectors in south korea |
publisher |
Frontiers Media SA |
publishDate |
2024 |
url |
http://dx.doi.org/10.3389/fevo.2023.1305573 https://www.frontiersin.org/articles/10.3389/fevo.2023.1305573/full |
genre |
Sakhalin |
genre_facet |
Sakhalin |
op_source |
Frontiers in Ecology and Evolution volume 11 ISSN 2296-701X |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3389/fevo.2023.1305573 |
container_title |
Frontiers in Ecology and Evolution |
container_volume |
11 |
_version_ |
1796952477735583744 |