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231224s2017 xx |||||o 00| ||eng c |
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|a 10.1111/gcb.13492
|2 doi
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|a pubmed24n0880.xml
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|a (DE-627)NLM264064437
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|a (NLM)27596590
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Burgess, Treena I
|e verfasserin
|4 aut
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|a Current and projected global distribution of Phytophthora cinnamomi, one of the world's worst plant pathogens
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|c 2017
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Completed 20.10.2017
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|a Date Revised 02.12.2018
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2016 John Wiley & Sons Ltd.
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|a Globally, Phytophthora cinnamomi is listed as one of the 100 worst invasive alien species and active management is required to reduce impact and prevent spread in both horticulture and natural ecosystems. Conversely, there are regions thought to be suitable for the pathogen where no disease is observed. We developed a climex model for the global distribution of P. cinnamomi based on the pathogen's response to temperature and moisture and by incorporating extensive empirical evidence on the presence and absence of the pathogen. The climex model captured areas of climatic suitability where P. cinnamomi occurs that is congruent with all available records. The model was validated by the collection of soil samples from asymptomatic vegetation in areas projected to be suitable by the model for which there were few records. DNA was extracted, and the presence or absence of P. cinnamomi was determined by high-throughput sequencing (HTS). While not detected using traditional isolation methods, HTS detected P. cinnamomi at higher elevations in eastern Australia and central Tasmania as projected by the climex model. Further support for the climex model was obtained using the large data set from south-west Australia where the proportion of positive records in an area is related to the Ecoclimatic Index value for the same area. We provide for the first time a comprehensive global map of the current P. cinnamomi distribution, an improved climex model of the distribution, and a projection to 2080 of the distribution with predicted climate change. This information provides the basis for more detailed regional-scale modelling and supports risk assessment for governments to plan management of this important soil-borne plant pathogen
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|a Journal Article
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|a climate change
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|a high-throughput sequencing
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|a natural ecosystem
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|a plant disease
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4 |
|a soil pH
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|a Scott, John K
|e verfasserin
|4 aut
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|a Mcdougall, Keith L
|e verfasserin
|4 aut
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|a Stukely, Michael J C
|e verfasserin
|4 aut
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|a Crane, Colin
|e verfasserin
|4 aut
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|a Dunstan, William A
|e verfasserin
|4 aut
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|a Brigg, Frances
|e verfasserin
|4 aut
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|a Andjic, Vera
|e verfasserin
|4 aut
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|a White, Diane
|e verfasserin
|4 aut
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|a Rudman, Tim
|e verfasserin
|4 aut
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|a Arentz, Frans
|e verfasserin
|4 aut
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|a Ota, Noboru
|e verfasserin
|4 aut
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|a Hardy, Giles E St J
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Global change biology
|d 1999
|g 23(2017), 4 vom: 05. Apr., Seite 1661-1674
|w (DE-627)NLM098239996
|x 1365-2486
|7 nnns
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| 773 |
1 |
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|g volume:23
|g year:2017
|g number:4
|g day:05
|g month:04
|g pages:1661-1674
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| 856 |
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|u http://dx.doi.org/10.1111/gcb.13492
|3 Volltext
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