Prediction of Suitable Habitat Distribution of Cryptosphaeria pullmanensis in the World and China under Climate Change

Abstract

Years of outbreaks of woody canker (Cryptosphaeria pullmanensis) in the United States, Iran, and China have resulted in massive economic losses to biological forests and fruit trees. However, only limited information is available on their distribution, and their habitat requirements have not been well evaluated due to a lack of research. In recent years, scientists have utilized the MaxEnt model to estimate the effect of global temperature and specific environmental conditions on species distribution. Using occurrence and high resolution ecological data, we predicted the spatiotemporal distribution of C. pullmanensis under twelve climate change scenarios by applying the MaxEnt model. We identified climatic factors, geography, soil, and land cover that shape their distribution range and determined shifts in their habitat range. Then, we measured the suitable habitat area, the ratio of change in the area of suitable habitat, the expansion and shrinkage of maps under climate change, the direction and distance of range changes from the present to the end of the twenty-first century, and the effect of environmental variables. C. pullmanensis is mostly widespread in high-suitability regions in northwestern China, the majority of Iran, Afghanistan, and Turkey, northern Chile, southwestern Argentina, and the west coast of California in the United States. Under future climatic conditions, climate changes of varied intensities favored the expansion of suitable habitats for C. pullmanensis in China. However, appropriate land areas are diminishing globally. The trend in migration is toward latitudes and elevations that are higher. The estimated area of possible suitability shifted eastward in China. The results of the present study are valuable not only for countries such as Morocco, Spain, Chile, Turkey, Kazakhstan, etc., where the infection has not yet fully spread or been established, but also for nations where the species has been discovered. Authorities should take steps to reduce greenhouse gas emissions in order to restrict the spread of C. pullmanensis. Countries with highly appropriate locations should increase their surveillance, risk assessment, and response capabilities.

Comparative Assessment of Habitat Suitability and Niche Overlap of Three Cytospora Species in China

“…All georeferenced occurrence records in our study were obtained from three different sources: (1) GBIF (The Global Biodiversity Information Facility) (https://www.gbif.org/); (2) relevant articles from the China National Knowledge Infrastructure (CNKI) (https://www.cnki.net/), Web of Science (WOS) (https://www.webofscience.com/), and Google Scholar (https://scholar.google.com.hk); and (3) GPS, which was used to gather 135 C. chrysosperma, 34 C. mali, and 25 C. nivea occurrence points during fieldwork in the Xinjiang Uygur Autonomous Region, China in 2019 and 2023. By ensuring that no two occurrence data points were inside the same raster (~5 km 2 ) [6,48], ENMTools (https://github.com/danlwarren/ENMTools) was utilized to prevent spatial autocorrelation from impairing the model's performance [48,49]. Ultimately, 374 global occurrence data points for C. chrysosperma, 164 for C. mali, and 166 for C. nivea were retained by our study (Figure 1 and Supplementary Table S1).…”

“…To eliminate multivariate collinearity, we utilized ENMTools to evaluate the correlation coefficients of the bioclimatic variables. Finally, we kept several meaningful bioclimatic variables for each research species based on the correlation coefficient of the bioclimatic variables (|r| > 0.8) and the contribution of each bioclimatic variable (Supplementary Figure S1) [6,45,48].…”

“…Many studies have found that climate change is a major driver of plant pathogen spatial pattern changes and may improve plant pathogen overwintering survivability [3,4]. The distribution range of many plant pathogens is expected to continue shifting toward high-latitude and highaltitude locations [5,6]. Thus, understanding the spatial distribution patterns, population 2 of 17 diversity, and compositions of plant pathogens affected by climate is critical for reducing plant disease losses.…”

“…Global temperature change is widely acknowledged to significantly impact species distribution [6,31,32] and may increase fungal infections [6,33]. However, few studies [5,34,35] have explored the dispersion of fungi on large spatial and temporal scales due to their distinctive life cycles and development patterns.…”

“…The Maxent modeling approach is widely utilized among these models due to its superior predictive performance [5,45,46]. It is effective even when few occurrence records are known and the association between climatic and environmental elements is unpredictable [6,44,47]. Therefore, we used the Maxent model to analyze the potential distribution of the chosen species.…”