Predicting the fundamental thermal niche of crop pests and diseases in a changing world: A case study on citrus greening

  1. Predicting where crop pests and diseases can occur, both now and in the future under different climate change scenarios, is a major challenge for crop management. One solution is to estimate the fundamental thermal niche of the pest/disease to indicate where establishment is possible. Here, we develop methods for estimating and displaying the fundamental thermal niche of pests and pathogens and apply these methods to Huanglongbing (HLB), a vector-borne disease that is currently threatening the citrus industry worldwide. 2. We derive a suitability metric based on a mathematical model of HLB transmission between tree hosts and its vector Diaphorina citri, and incorporate the effect of temperature on vector traits using data from laboratory experiments performed at different temperatures. We validate the model using data on the historical range of HLB. 3. Our model predicts that transmission of HLB is possible between 16 and 33 degrees C with peak transmission at similar to 25 degrees C. The greatest uncertainty in our suitability metric is associated with the mortality of the vectors at peak transmission, and fecundity at the edges of the thermal range, indicating that these parameters need further experimental work. 4. We produce global thermal niche maps by plotting how many months each location is suitable for establishment of the pest/disease. This analysis reveals that the highest suitability for HLB occurs near the equator in large citrus-producing regions, such as Brazil and South-East Asia. Within the Northern Hemisphere, the Iberian peninsula and California are HLB suitable for up to 7 months of the year and are free of HLB currently. 5. Policy implications. We create a thermal niche map which indicates the places at greatest risk of establishment should a crop disease or pest enter these regions. This indicates where surveillance should be focused to prevent establishment. Our mechanistic method can be used to predict new areas for Huanglongbing transmission under different climate change scenarios and is easily adapted to other vector-borne diseases and crop pests.
Asian Citrus Psyllid, Bayesian inference, crop management, Huanglongbing, risk of establishment, species distribution models, transmission suitability, vector-borne disease