TY - JOUR
T1 - An examination of how climate change could affect the future spread of Fusarium spp. around the world, using correlative models to model the changes
AU - Ejaz, Muhammad Riaz
AU - Jaoua, Samir
AU - Ahmadi, Mohsen
AU - Shabani, Farzin
PY - 2023/8
Y1 - 2023/8
N2 - Climate change is predicted to have a significant impact on the geographic distribution of various flora, fauna, and insect species by expanding, contracting, or shifting their suitable climate environment. The plant pathogenic fungus Fusarium is known for causing crop diseases like blight, root and stem rots, and wilts, making it the most significant mycotoxigenic genus in weeds and food across various climatic zones worldwide. In this study, we hypothesize that crop diseases caused by Fusarium spp. will increase across all four corners of the world by 2050 and 2070 in response to future climate conditions. A series of correlative species distribution models (SDMs), including a generalized linear model (GLM), maximum entropy (MaxEnt), generalized boosting model (GBM), and surface range envelope, were employed to project and compare how the niche of Fusarium spp. will change from the present time to 2050 and 2070 under two Climate Change Representative Concentration Pathways (RCPs) of 8.5 and 4.5 (scenarios of high and low greenhouse gas emissions, respectively). Our approach (the ensemble predictions of 4 SDMs) minimizes the uncertainty (differences) of the projection results from each one of the models. The findings of this study have global implications because Fusarium spp. are associated with host species that are present on major continents such as Asia, Europe, Australia, and North and South America. The information gathered could be beneficial to farmers and planners when creating strategies to prevent the proliferation of Fusarium spp. as well as calculating the expenses associated with using pesticides to minimize contamination and increase yields.
AB - Climate change is predicted to have a significant impact on the geographic distribution of various flora, fauna, and insect species by expanding, contracting, or shifting their suitable climate environment. The plant pathogenic fungus Fusarium is known for causing crop diseases like blight, root and stem rots, and wilts, making it the most significant mycotoxigenic genus in weeds and food across various climatic zones worldwide. In this study, we hypothesize that crop diseases caused by Fusarium spp. will increase across all four corners of the world by 2050 and 2070 in response to future climate conditions. A series of correlative species distribution models (SDMs), including a generalized linear model (GLM), maximum entropy (MaxEnt), generalized boosting model (GBM), and surface range envelope, were employed to project and compare how the niche of Fusarium spp. will change from the present time to 2050 and 2070 under two Climate Change Representative Concentration Pathways (RCPs) of 8.5 and 4.5 (scenarios of high and low greenhouse gas emissions, respectively). Our approach (the ensemble predictions of 4 SDMs) minimizes the uncertainty (differences) of the projection results from each one of the models. The findings of this study have global implications because Fusarium spp. are associated with host species that are present on major continents such as Asia, Europe, Australia, and North and South America. The information gathered could be beneficial to farmers and planners when creating strategies to prevent the proliferation of Fusarium spp. as well as calculating the expenses associated with using pesticides to minimize contamination and increase yields.
KW - Cash crop diseases
KW - Climate change
KW - Economic
KW - Fungal pathogens
KW - Fusarium spp.
KW - Management
KW - Species distribution model
UR - http://www.scopus.com/inward/record.url?scp=85158872652&partnerID=8YFLogxK
U2 - 10.1016/j.eti.2023.103177
DO - 10.1016/j.eti.2023.103177
M3 - Article
AN - SCOPUS:85158872652
SN - 2352-1864
VL - 31
JO - Environmental Technology and Innovation
JF - Environmental Technology and Innovation
M1 - 103177
ER -