Abstract
Wheat rusts are the key biological constraint to wheat production in Ethiopia-one of Africa's largest wheat producing countries. The fungal diseases cause economic losses and threaten livelihoods of smallholder farmers. While it is known that wheat rust epidemics have occurred in Ethiopia, to date no systematic long-term analysis of past outbreaks has been available. We present results from one of the most comprehensive surveillance campaigns of wheat rusts in Africa. More than 13,000 fields have been surveyed during the last 13 years. Using a combination of spatial data-analysis and visualization, statistical tools, and empirical modelling, we identify trends in the distribution of wheat stem rust (Sr), stripe rust (Yr) and leaf rust (Lr). Results show very high infection levels (mean incidence for Yr: 44%; Sr: 34%; Lr: 18%). These recurrent rust outbreaks lead to substantial economic losses, which we estimate to be of the order of 10s of millions of US-D annually. On the widely adopted wheat variety, Digalu, there is a marked increase in disease prevalence following the incursion of new rust races into Ethiopia, which indicates a pronounced boom-and-bust cycle of major gene resistance. Using spatial analyses, we identify hotspots of disease risk for all three rusts, show a linear correlation between altitude and disease prevalence, and find a pronounced north-south trend in stem rust prevalence. Temporal analyses show a sigmoidal increase in disease levels during the wheat season and strong inter-annual variations. While a simple logistic curve performs satisfactorily in predicting stem rust in some years, it cannot account for the complex outbreak patterns in other years and fails to predict the occurrence of stripe and leaf rust. The empirical insights into wheat rust epidemiology in Ethiopia presented here provide a basis for improving future surveillance and to inform the development of mechanistic models to predict disease spread.
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Claims 13
Claim · model-written summary
Mean stripe rust incidence was 44%.
- Taxon
- wheat
Triticum aestivumt0 - Interactor
- Yre0pathogen
- Outcome
- incidence for Yre0
- Value
- 44%e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“mean incidence for Yr: 44%”
t0“wheat”
Claim · model-written summary
Mean stem rust incidence was 34%.
- Taxon
- wheatTriticum aestivumt0
- Interactor
- Sre0pathogen
- Outcome
- Sre0
- Value
- 34%e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Sr: 34%”
e1“mean incidence for Yr: 44%; Sr: 34%”
t0“wheat”
Claim · model-written summary
Mean leaf rust incidence was 18%.
- Taxon
- wheatTriticum aestivumt0
- Interactor
- Lre0pathogen
- Outcome
- Lre0
- Value
- 18%e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Lr: 18%”
t0“wheat”
Claim · model-written summary
Recurrent wheat rust outbreaks caused estimated annual losses of tens of millions of US dollars.
- Taxon
- wheatTriticum aestivumt0
- Interactor
- ruste0pathogen
- Outcome
- economic lossese0
- Value
- 10s of millions of US-D annuallye0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“These recurrent rust outbreaks lead to substantial economic losses, which we estimate to be of the order of 10s of millions of US-D annually”
t0“wheat”
Claim · model-written summary
Rust prevalence rose markedly on Digalu after new rust races entered Ethiopia.
- Taxon
- wheatTriticum aestivume0
- Material
- Digalue0
- Interactor
- rust racese0pathogen
- Outcome
- disease prevalencee0
- Direction
- increasee0
- Setting
- Ethiopiae0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“On the widely adopted wheat variety, Digalu, there is a marked increase in disease prevalence following the incursion of new rust races into Ethiopia”
Claim · model-written summary
Disease risk hotspots were found for all three wheat rusts.
- Taxon
- wheatTriticum aestivumt0
- Interactor
- rustsPuccinialese0pathogen
- Outcome
- hotspots of disease riske0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“identify hotspots of disease risk for all three rusts”
t0“wheat”
Claim · model-written summary
Altitude correlated linearly with wheat rust prevalence.
- Taxon
- wheatTriticum aestivumt0
- Interactor
- rustt0pathogen
- Outcome
- disease prevalencee0
- Setting
- altitudee0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“show a linear correlation between altitude and disease prevalence”
t0“wheat rust”
Claim · model-written summary
Stem rust prevalence showed a pronounced north-south trend.
- Taxon
- wheatTriticum aestivumt0
- Interactor
- stem ruste0pathogen
- Outcome
- stem rust prevalencee0
- Setting
- north-southe0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“find a pronounced north-south trend in stem rust prevalence”
t0“wheat”
Claim · model-written summary
Wheat rust disease levels increased sigmoidally through the season.
- Taxon
- wheatTriticum aestivume0
- Outcome
- disease levelse0
- Direction
- increasee0
- Qualifier
- during the wheat seasone0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Temporal analyses show a sigmoidal increase in disease levels during the wheat season”
Claim · model-written summary
Wheat rust levels varied strongly between years.
- Taxon
- wheatTriticum aestivumt0
- Interactor
- rustt0pathogen
- Outcome
- inter-annual variationse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“strong inter-annual variations”
t0“wheat rust”
Claim · model-written summary
A logistic curve predicted stem rust satisfactorily in some years.
- Taxon
- wheatTriticum aestivumt0
- Interactor
- stem ruste0pathogen
- Outcome
- predicting stem ruste0
- Comparator
- some yearse0
Not reportedValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“a simple logistic curve performs satisfactorily in predicting stem rust in some years”
t0“wheat”
Claim · model-written summary
The logistic curve failed for complex stem rust outbreak patterns in other years.
- Taxon
- wheatTriticum aestivumt0
- Interactor
- stem ruste1pathogen
- Outcome
- complex outbreak patternse0
- Comparator
- other yearse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“it cannot account for the complex outbreak patterns in other years”
e1“predicting stem rust”
t0“wheat”
Claim · model-written summary
The logistic curve failed to predict stripe and leaf rust occurrence.
- Taxon
- wheatTriticum aestivumt0
- Outcome
- occurrence of stripe and leaf ruste0
Not reportedComparatorValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“fails to predict the occurrence of stripe and leaf rust”
t0“wheat”