Plant pathogen responses to Late Pleistocene and Holocene climate change in the central Atacama Desert, Chile

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作者
Jamie R. Wood
Francisca P. Díaz
Claudio Latorre
Janet M. Wilmshurst
Olivia R. Burge
Rodrigo A. Gutiérrez
机构
[1] Manaaki Whenua Landcare Research,Departamento de Genética Molecular y Microbiología
[2] Pontificia Universidad Católica de Chile,Departamento de Ecología
[3] Avda. Libertador Bernardo O’Higgins 340,School of Environment
[4] FONDAP Center for Genome Regulation & Millennium Institute for Integrative Biology (iBio),undefined
[5] Pontificia Universidad Católica de Chile,undefined
[6] Institute of Ecology and Biodiversity (IEB),undefined
[7] Las Palmeras,undefined
[8] The University of Auckland,undefined
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关键词
Atacama; Plant Pathogens; Rodent Middens; Pucciniaceae; Pluvial Events;
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摘要
Future climate change has the potential to alter the distribution and prevalence of plant pathogens, which may have significant implications for both agricultural crops and natural plant communities. However, there are few long-term datasets against which modelled predictions of pathogen responses to climate change can be tested. Here, we use 18S metabarcoding of 28 rodent middens (solidified deposits of rodent coprolites and nesting material) from the Central Atacama, spanning the last ca. 49 ka, to provide the first long-term late Quaternary record of change in plant pathogen communities in response to changing climate. Plant pathogen richness was significantly greater in middens deposited during the Central Andean Pluvial Event (CAPE); a period of increased precipitation between 17.5–8.5 ka. Moreover, the occurrence frequency of Pucciniaceae (rust fungi) was significantly greater during the CAPE, and the highest relative abundances for five additional potentially pathogenic taxa also occurred during this period. The results demonstrate the promising potential for ancient DNA analysis of late Quaternary samples to reveal insights into how plant pathogens responded to past climatic and environmental change, which could help predict how pathogens may responded to future change.
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