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Title: Predicting the effects of climate change on the cross-scale epidemiological dynamics of a fungal plant pathogen

Journal Article · · Scientific Reports
 [1];  [2];  [1];  [3];  [3];  [4];  [5]
  1. Princeton University, NJ (United States); Rocky Mountain Biological Laboratory, Crested Butte, OC (United States)
  2. Princeton University, NJ (United States); Rocky Mountain Biological Laboratory, Crested Butte, OC (United States); University of Virginia, Charlottesville, VA (United States)
  3. Rocky Mountain Biological Laboratory, Crested Butte, OC (United States)
  4. Rocky Mountain Biological Laboratory, Crested Butte, OC (United States); Utah State University, Logan, UT (United States)
  5. Princeton University, NJ (United States)
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The potential for climate change to exacerbate the burden of human infectious diseases is increasingly recognized, but its effects on infectious diseases of plants have received less attention. Understanding the impacts of climate on the epidemiological dynamics of plant pathogens is imperative, as these organisms play central roles in natural ecosystems and also pose a serious threat to agricultural production and food security. We use the fungal ‘flax rust’ pathogen (Melampsora lini) and its subalpine wildflower host Lewis flax (Linum lewisii) to investigate how climate change might affect the dynamics of fungal plant pathogen epidemics using a combination of empirical and modeling approaches. Our results suggest that climate change will initially slow transmission at both the within- and between-host scales. However, moderate resurgences in disease spread are predicted as warming progresses, especially if the rate of greenhouse gas emissions continues to increase at its current pace. These findings represent an important step towards building a holistic understanding of climate effects on plant infectious disease that encompasses demographic, epidemiological, and evolutionary processes. A core result is that neglecting processes at any one scale of plant pathogen transmission may bias projections of climate effects, as climate drivers have variable and cascading impacts on processes underlying transmission that occur at different scales.

Research Organization:
Princeton Univ., NJ (United States)
Sponsoring Organization:
USDOE; National Science Foundation (NSF); Princeton University; Rocky Mountain Biological Laboratory
OSTI ID:
1903942
Journal Information:
Scientific Reports, Vol. 12, Issue 1; ISSN 2045-2322
Publisher:
Nature Publishing GroupCopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

59 BASIC BIOLOGICAL SCIENCES
climate-change ecology
ecological epidemiology
ecological modelling