DOI: 10.5061/dryad.vx0k6djzp
title: Climate change may make pine wilt disease more prevalent

description: 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.
description: # 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. 1. **get_pa_data.R:** This
 script generates pseudo-absence data for each species. 2.
 **get_pa_func.R:** This script contains the function used in
 the`get_pa_data.R` script to create pseudo-absence data. 3.
 **block_cv_data2.R:** This script splits the pseudo-absence data into
 training and test datasets. 4. **block_cv_func.R:** This script contains
 the function used in the `block_cv_data2.R` script for data splitting. 5.
 **get_or_func.R:** This script calculates the evaluation metrics used in
 the `biomod.R` script. 6. **function_biomod_model.R:** This script
 provides the model projection functions used in the `biomod.R` script. 7.
 **biomod.R:** The main script for generating model projections for each
 species.