Predicting the potential distribution of <i>Pseudomonas syringae</i> pv. <i>actinidiae</i> in China using ensemble models

Qin, Zhong; Zhang, J. E.; Jiang, Yuan; Wang, R. L.; Wu, Rui-shan

doi:10.1111/ppa.13112

Cited by 14 publications

(17 citation statements)

References 37 publications

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“…SDM model performance was assessed with the true skill statistic (TSS), Cohen's kappa statistic (Kappa), and the area under the receiver operating characteristic curve (AUC) [39][40][41]. The above three metrics are the most highly applied in assessing the performance of SDMs [17,42]. The TSS and Kappa values range from −1 to 1, and the AUC value ranges from 0.5 to 1; the closer their value is to 1, the more reliable the prediction results are [40,41].…”

Section: Modelling Proceduresmentioning

confidence: 99%

Modelling the Effects of Climate Change on the Distribution of Endangered Cypripedium japonicum in China

Huang

Hong-yan

et al. 2021

Forests

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Cypripedium japonicum is an endangered terrestrial orchid species with high ornamental and medicinal value. As global warming continues to intensify, the survival of C. japonicum will be further challenged. Understanding the impact of climate change on its potential distribution is of great significance to conserve this species. In this study, we established an ensemble species distribution model based on occurrence records of C. japonicum and 13 environmental variables to predict its potential distribution under current and future climatic conditions. The results show that the true skill statistic (TSS), Cohen’s kappa statistic (Kappa), and the area under the receiver operating characteristic curve (AUC) values of the ensemble model were 0.968, 0.906, and 0.995, respectively, providing more robust predictions. The key environmental variables affecting the distribution of C. japonicum were the precipitation in the warmest quarter (Bio18) and the mean temperature in the driest quarter (Bio9). Under future climatic conditions, the total suitable habitat of C. japonicum will increase slightly and tend to migrate northwestward, but the highly suitable areas will be severely lost. By 2070, the loss of its highly suitable habitat area will reach 57.69–72.24% under representative concentration pathway (RCP) 4.5 and 8.5 respectively, and the highly suitable habitats in Zhejiang and Anhui will almost disappear. It is noteworthy that the highly suitable habitat of C. japonicum has never crossed the Qinba mountainous area during the migration process of the suitable habitat to the northwest. Meanwhile, as the best-preserved area of highly suitable habitat for C. japonicum in the future, the Qinba mountainous area is of great significance to protect the wild germplasm resources of C. japonicum. In addition, we found that most of the changes predicted for 2070 will already be seen in 2050; the problem of climate change may be more urgent than it is believed.

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Section: Modelling Proceduresmentioning

confidence: 99%

Modelling the Effects of Climate Change on the Distribution of Endangered Cypripedium japonicum in China

Huang

Hong-yan

et al. 2021

Forests

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“…The Psa was first determined from kiwifruit plants in 1980 [ 3 ]. During the last two decades, the disease has broken out worldwide, including in Korea [ 4 ], Italy [ 5 ], Portugal [ 6 ], France [ 7 ], New Zealand [ 8 ], and China [ 9 ]. To date, Psa has been classified into six biovars (biovars 1–6), according to the secretion of different virulence factors [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Characterization of a Lytic Bacteriophage against Pseudomonas syringae pv. actinidiae and Its Endolysin

Wang

Deng

et al. 2021

Viruses

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Pseudomonas syringae pv. actinidiae (Psa) is a phytopathogen that causes canker in kiwifruit. Few conventional control methods are effective against this bacterium. Therefore, alternative approaches, such as phage therapy are warranted. In this study, a lytic bacteriophage (PN09) of Psa was isolated from surface water collected from a river in Hangzhou, China in 2019. Morphologically, PN09 was classified into the Myoviridae family, and could lyse all 29 Psa biovar 3 strains. The optimal temperature and pH ranges for PN09 activity were determined as 25 to 35 °C and 6.0 to 9.0, respectively. The complete genome of PN09 was found to be composed of a linear 99,229 bp double-stranded DNA genome with a GC content of 48.16%. The PN09 endolysin (LysPN09) was expressed in vitro and characterized. LysPN09 was predicted to belong to the Muraidase superfamily domain and showed lytic activity against the outer-membrane-permeabilized Psa strains. The lytic activity of LysPN09 was optimal over temperature and pH ranges of 25 to 40 °C and 6.0 to 8.0, respectively. When recombinant endolysin LysPN09 was combined with EDTA, Psa strains were effectively damaged. All these characteristics demonstrate that the phage PN09 and its endolysin, LysPN09, are potential candidates for biocontrol of Psa in the kiwifruit industry.

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Section: Discussionmentioning

confidence: 99%

“…Only four studies have been developed to model Psa distribution using SDMs [40,[43][44][45]. All these models focus on the potential distribution of Psa at a local scale and mostly rely on single models or the same type of models such as correlative models [43][44][45]. While some studies benefit from an ensemble approach [45], it is recommended that where possible, contributions to an ensemble model should be from different types of models and they should add information for building a better model [69].…”

Section: Discussionmentioning

confidence: 99%

“…They identified that environmental variables such as maximum April temperature, mean temperature of the coldest quarter, precipitation in May and minimum temperature in October contributed the most to the model projection. In a recent study focused on China, [45], an ensemble approach using three correlative models including generalized boosting models (GBM), random forests (RF) and classification tree analysis (CTA) was employed to predict the potential distribution of Psa in China under four general circulation models (GCMs). In all three models, precipitation in March contributed the most to model projection (28.2%) followed by the mean temperature of the warmest quarter (17.7%).…”

Section: Introductionmentioning

confidence: 99%

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The Potential Global Climate Suitability of Kiwifruit Bacterial Canker Disease (Pseudomonas syringae pv. actinidiae (Psa)) Using Three Modelling Approaches: CLIMEX, Maxent and Multimodel Framework

Narouei‐Khandan

Worner

Viljanen‐Rollinson

et al. 2022

Climate

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In recent years, outbreaks of kiwifruit bacterial canker (Pseudomonas syringae pv. actinidiae Psa) have caused huge economic losses to two major global kiwifruit producers, Italy and New Zealand. To evaluate the potential global risk areas of Psa, three modelling methods (MaxEnt, CLIMEX and a multimodel framework, including support vector machines or SVM) were used. Current global occurrence data for Psa were collected from different sources. The long-term climate data were sourced from WorldClim and CliMond websites. The model results were combined into a consensus model to identify the hotspots. The consensus model highlighted the areas where two or three models agreed on climate suitability for Psa. All three models agreed with respect to the climate suitability of areas where Psa is currently present and identified novel areas where Psa has not established yet. The SVM model predicted large areas in Central Asia, Australia, and Europe as more highly suitable compared to MaxEnt and CLIMEX. Annual mean temperature and annual precipitation contributed most to the MaxEnt prediction. Both MaxEnt and CLIMEX showed the probability of Psa establishment increased above 5 °C and decreased above 20 °C. The annual precipitation response curve showed that excessive rain (>1200 mm/y) constrains Psa establishment. Our modelling results will provide useful information for Psa management by highlighting the climatically susceptible areas where Psa has not established, such as the USA, Iran, Denmark, Belgium and especially South Africa, where kiwifruit has been planted commercially in recent years.

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Predicting the potential distribution of Pseudomonas syringae pv. actinidiae in China using ensemble models

Cited by 14 publications

References 37 publications

Modelling the Effects of Climate Change on the Distribution of Endangered Cypripedium japonicum in China

Modelling the Effects of Climate Change on the Distribution of Endangered Cypripedium japonicum in China

Characterization of a Lytic Bacteriophage against Pseudomonas syringae pv. actinidiae and Its Endolysin

The Potential Global Climate Suitability of Kiwifruit Bacterial Canker Disease (Pseudomonas syringae pv. actinidiae (Psa)) Using Three Modelling Approaches: CLIMEX, Maxent and Multimodel Framework

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