Climate change may make pine wilt disease more prevalent
Data files
Sep 24, 2024 version files 5.02 KB
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README.md
1.27 KB
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species_name.zip
3.75 KB
Abstract
Pine wilt disease is one of the most severe and devastating diseases affecting pine forests worldwide, resulting in huge economic losses in many countries. The pinewood nematode, Bursaphelenchus xylophilus, is the causal agent of pine wilt disease and is obligately vectored by pine sawyer beetles, of the genus Monochamus. For the disease to be present, the habitat must be suitable for the pinewood nematode, and include at least one vector species, and at least one host species. To predict its potential distribution, a model must consider all three components. However, no comprehensive study has examined the influence of climatic suitability on the distribution of this 'biological complex'. This study addresses this gap by incorporating biotic interactions, specifically involving 13 vectors and 61 host plants, into projections based on the pinewood nematode model. We predicted the global potential distribution of pine wilt disease and compared it with the pinewood nematode model to highlight the importance of including biotic interactions in species distribution models under climate change. We found that the model revealed an overall trend of increasing suitability scores for both the pinewood nematode and pine wilt disease models under future climate scenarios. Furthermore, compared to the pinewood nematode model, the biotic model results in an apparent increase in suitability worldwide in the future as the climate will be more suitable to vector and host complexes, suggesting that pine wilt disease could potentially spread to other places via available hosts and vectors.
Synthesis and applications:
By incorporating biotic interactions, we projected a more accurate suitable area for pine wilt disease, offering valuable insights into regions at high risk for future invasions by the disease and its vectors. This information supports the development of management and early detection strategies in areas of high suitability, helping to mitigate potential economic and ecological losses. Additionally, this study introduces a novel approach for integrating biotic factors into species distribution models.
README: Climate change may make pine wilt disease more prevalent
Data Description:
The zip file species_name.zip contains the scientific names of the species used in the study. Within the folder, hosts.csv lists the scientific names of host species, vectors.csv lists the scientific names of vector species, and pwn.csv lists the scientific name of pinewood nematode.
Code/Software:
R is required to run the following R script; the script was created using version 4.3.0.
Annotations are provided throughout the script.
- get_pa_data.R: This script generates pseudo-absence data for each species.
- get_pa_func.R: This script contains the function used in the
get_pa_data.R
script to create pseudo-absence data. - block_cv_data2.R: This script splits the pseudo-absence data into training and test datasets.
- block_cv_func.R: This script contains the function used in the
block_cv_data2.R
script for data splitting. - get_or_func.R: This script calculates the evaluation metrics used in the
biomod.R
script. - function_biomod_model.R: This script provides the model projection functions used in the
biomod.R
script. - biomod.R: The main script for generating model projections for each species.