Quantifying airborne dispersal routes of pathogens over continents to safeguard global wheat supply

60 Pages·2017·17.72 MB·English

SUPPLEMENTARY INFORLMetATtIeOrNs
DOI: 10.1038/s41477-017-0017-5
In the format provided by the authors and unedited.
Quantifying airborne dispersal routes of
pathogens over continents to safeguard global
wheat supply
M. Meyer   1*, J. A. Cox1, M. D. T. Hitchings1, L. Burgin2, M. C. Hort2, D. P. Hodson3 and C. A. Gilligan   1*
1 Epidemiology and Modelling Group, Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, UK. 2 Atmospheric Dispersion and Air
Quality (ADAQ), Met Office, Exeter EX1 3PB, UK. 3 International Maize and Wheat Improvement Center (CIMMYT), PO Box 5689, Addis Ababa, Ethiopia.
*e-mail: [email protected]; [email protected]
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Supplementary Information
Title: Quantifying airborne dispersal routes of pathogens over continents to safeguard
global wheat supply
Authors: M. Meyer1*, J.A. Cox1, M.D.T. Hitchings1, L. Burgin2, M.C. Hort2, D.P.
Hodson3, C.A. Gilligan1*
Affiliations:

1 Epidemiology and Modelling Group, Department of Plant Sciences, University of
Cambridge, Cambridge, CB2 3EA, UK

2Atmospheric Dispersion and Air Quality (ADAQ), Met Office, Exeter, EX1 3PB, UK
3International Maize and Wheat Improvement Center (CIMMYT), PO Box 5689, Addis
Ababa, Ethiopia
*Corresponding authors: C.A.G. ([email protected]), M.M. ([email protected]).

Contents
List of Figures ..................................................................................................................... 2
List of Tables ...................................................................................................................... 2
1. Supplementary Methods ................................................................................................. 3
1.1 Heterogeneous and dynamic wheat fields ................................................................. 5
1.2 Turbulent atmospheric dispersion and deposition of Pgt-spores ............................ 11
1.3 Environmental suitability for infection after deposition ......................................... 19
1.5 Summary of key model parameters ........................................................................ 21
1.6 Pgt-spore transmission metrics .............................................................................. 23
2. Supplementary Notes .................................................................................................... 26
2.1 Seasonal Pgt-spore dispersal trends ........................................................................ 26
2.2 Environmental suitability for infection: comparison to field survey data .............. 28
2.3 Long-distance dispersal network ............................................................................ 29
2.4 Connectivity matrices of spore transmission frequencies and amounts ................. 31
2.5 Airborne migration routes between epidemiological zones .................................... 33
2.6 Airborne migration routes in the East African Rift Valley Zone............................ 39
2.7 Interannual variation of Pgt-spore transmission ..................................................... 44
2.8 Supportive evidence for simulation results ............................................................. 46
2.9 Effects of model layers ........................................................................................... 48
2.10 Summary of sensitivity analysis of key parameters .............................................. 52
3. Captions for Supplementary Movies (Movies 1-5) ...................................................... 56
References ......................................................................................................................... 57

1
List of Figures
Supplementary Figure 1: Flow-chart of the data-driven simulation framework ................ 4
Supplementary Figure 2: Representative wheat stem rust disease locations (RDLs) ......... 6
Supplementary Figure 3: Seasonal timing of wheat stem rust in countries ...................... 10
Supplementary Figure 4: Consistent seasonal spore dispersal trends ............................... 27
Supplementary Figure 5: Weight-matrix of the long-distance dispersal network ............ 30
Supplementary Figure 6: Connectivity matrices summarizing Pgt-spore dispersal ......... 32
Supplementary Figure 7: Pgt-spore dispersal between epidemiological zones for very
small and small outbreaks ................................................................................................. 34
Supplementary Figure 8: Pgt-spore dispersal between epidemiological zones for
moderate and large outbreaks ........................................................................................... 35
Supplementary Figure 9: Airborne migration routes in the East African Rift Valley Zone
for different outbreak scenarios ........................................................................................ 41
Supplementary Figure 10: Seasonal variations of Pgt-spore transmission along key
airborne migration routes in the East African Rift Valley Zone ....................................... 43
Supplementary Figure 11: Interannual variations of spore transmission along probable
routes of spread of the wheat stem rust race TTKSK (Ug99) ........................................... 45

List of Tables
Supplementary Table 1: Meteorological datasets ............................................................. 11
Supplementary Table 2: Pgt-spore canopy escape rates for different scenarios of wheat
stem rust outbreaks ........................................................................................................... 14
Supplementary Table 3: Key model parameters ............................................................... 22
Supplementary Table 4: Effect of model layers and key parameters on the annual mean
number of spore deposition days along selected airborne migration routes ..................... 51

2
1. Supplementary Methods
Supplementary details about input data, model layers, and analysis methods are provided
in the subsequent paragraphs and summarized in Supplementary Figure 1.

3
Supplementary Figure 1: Flow-chart of the data-driven simulation framework
Methodological details, including input data and model layers, are described in the Methods Section of the main text, as well as in the Supplementary Methods
(Section 1, Supplementary Information). Supplements to the main results are summarized in the Supplementary Notes (Section 2, Supplementary Information).
Seasonal spore deposition trends from all RDLs are summarized in a catalogue of monthly spore deposition maps in Supplementary Data 1. For a range of
disease outbreak scenarios spore transmission frequencies and amounts between countries are summarized in Supplementary Data 2.

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1.1 Heterogeneous and dynamic wheat fields
1.1.1 Identification of representative disease locations (RDLs)
Supplementary Figure 2 summarizes all RDLs and shows the underlying survey results.
To obtain the most realistic long-distance transmission trends, we would ideally want to
model release of Pgt-spores from every infected wheat field for the duration of the
infection. Two major limitations make this impractical at the time of this study. First,
there is a lack of field sampling data. Even though the Global Wheat Rust Monitoring
System19 has greatly increased our knowledge about distribution of wheat stem rust
during the last decade, incidence and severity are still unknown for large parts of wheat
fields in the spatial and time domain of the study. Second, modelling turbulent
atmospheric dispersion using a Lagrangian Particle Dispersion Model is computationally
very intense, hence it is not feasible to release simulation particles from every single grid
cell that contains infected wheat fields. To overcome these limitations, we model release
of spores from the set of RDLs. This way our calculations remain computationally
feasible, while still capturing airborne dispersal between all key wheat stem rust regions
on continental scales.

The following paragraphs briefly introduce the characteristics of wheat production and
wheat stem rust establishment in our domain of interest.

The majority of wheat in East Africa is grown in Ethiopia (harvested area = 1.7×106
ha), with significant amounts also being grown in Sudan (harvested area = 1.9×105 ha),
Kenya (harvested area = 1.5×105 ha), and Tanzania (harvested area=1.7×105 ha). The
East African Highlands are a known "hot-spot" for the evolution and survival of new rust
races15, despite not being an important wheat growing region globally. The favourable
environmental conditions and year-round presence of host plants facilitate the survival
and build-up of pathogen populations. In some areas the environment is suitable for Pgt
sporulation all year round and there is hardly any rain-free period8. The continuous
presence of wheat in some areas of the Rift Valley forms a green bridge, and alternate
hosts are present, creating a local endemic disease cycle. Selection pressures result from
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Supplementary Figure 2: Representative wheat stem rust disease locations (RDLs)
a, Wheat producing regions in Southern/East Africa, the Middle East, Central/South Asia. b, Wheat stem
rust detection sites and identification of representative disease locations (RDLs). RDLs are used as source
locations for daily simulations of turbulent airborne dispersal of fungal spores over 12 years. Field
detection sites are obtained from the dataset of the Global Wheat Rust Monitoring System19, complemented
by detecion sites in South-Africa and southern Iran5,16, which at the time of the study, had not been entered
into the dataset of Global Wheat Rust Monitoring System.

popular cultivars attaining large acreages under cultivation. There are a variety of
examples of severe wheat stem rust epidemics in this region, and a number of virulent
strains have been spreading within East Africa, as well as from East Africa to other
regions of the world. These include: (i) the epidemic in Ethiopia 1993 to 1994 when the
popular wheat variety Einkoy suffered major losses45, (ii) the spread of the Ug99 race
group, which has by now been detected in the entire Rift Valley and is spreading beyond
with the most recent detection in Egypt in 20145, and (iii) the two severe epidemics
caused by race TKTTF in Ethiopia in 2013/14 and 2014/155,21. Also, (iv) the Yr9-virulent
race of wheat yellow rust originated in East Africa, and there is circumstantial evidence
that it migrated in a stepwise manner to West Asia then South Asia8. Further, (v) the
aggressive yellow rust lineages PstS1 / PstS2 originated in East Africa46. The region
consisting of countries associated with the Rift Valley has been called the “Rift Valley
Epidemiological Zone” by Nagarajan and co-authors10. It has been speculated that there
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is regular, year-round exchange of inoculum within this zone by airborne dispersal of
spores along the Rift Valley “flyway”10, that can be thought of as the East African
Puccinia Pathway. Detection sites of wheat stem rust in East Africa are numerous19 and
clustered around central, southern and south-eastern Ethiopia, south-central Kenya,
Eritrea, eastern Uganda and Rwanda. We consider RDLs in the following key wheat
producing countries: (i) Ethiopia, (ii) Kenya, (iii) Sudan, (iv) Eritrea, (v) Yemen, (vi)
Uganda and (vii) Tanzania.

In Southern Africa, RDLs were identified in South-Africa (one in the South-West in the
Cape region and one in the Central-East), Zimbabwe and Zambia, so as to coincide with
this region’s clustering of wheat stem rust detection sites and large areas of wheat
production.

A large area covering several countries in the Middle East, including Turkey, Iran,
Egypt, Georgia, and Lebanon, has been described as the West Asia Epidemiological
Zone15. A similar set of countries has been called “The Iranian Epidemiological Zone” 9.
The TKTTF wheat stem rust race has been detected in many of these countries5. Ug99
has spread from East Africa to the Middle East, where it was detected first in Iran in
2007, and again in 2011, as well as in Egypt in 2014. We choose a number of RDLs to
cover the large wheat producing regions in (i) Iran, (ii) Turkey, (iii) Egypt, (iv) Georgia,
(v) Lebanon, (vi) Iraq, (vii) Saudi Arabia and (viii) Syria.

We include Afghanistan and Uzbekistan as potential spore sources in Central Asia
because of relatively large wheat producing regions, and their geographic position
between the Middle East (where Ug99 has been detected), and the plains of Pakistan and
India where millions of hectares of potentially susceptible crops are grown. In terms of
survey data only very little is known about Afghanistan and Uzbekistan; therefore RDLs
are chosen to coincide with regions of high wheat production, such that two different
areas of Central Asia are represented by one RDL each: the eastern regions of Uzbekistan
and the central western areas of Afghanistan.
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The South Asia Epidemiological Zone15 includes India, Pakistan, Nepal, Bangladesh,
Bhutan and south-east Afghanistan. A broadly similar set of countries has been referred
to as "The Indian Punjab Epidemiological Zone"9. India and Pakistan are the largest
producers of wheat in the Indian subcontinent with wheat producing areas of 3.0×107 ha
and 8.7×106 ha, respectively. There is a high density of wheat stem rust detection sites in
south Pakistan. There is widespread genetic vulnerability to novel stem rust races,
particularly the Ug99 race group, in a seasonal monoculture of wheat cultivars6–8. Serious
concerns regarding food security in India related to potential consequences of yield losses
in wheat production have been raised47. The annual cycle of wheat stem rust in the Indian
subcontinent has been well documented for many years48. Wheat is grown throughout the
year at higher elevations, allowing stem rust to over-summer. These areas provide
inoculum for reinfection of the main wheat crop grown in the plains of Bangladesh, India,
and Pakistan, which is typically sown in November and harvested by the end of April or
early May. We identify one RDL in southern Pakistan and one in the plains of northern
Pakistan, as wheat stem rust has been detected in both areas. In India we identify three
RDLs: one in the region around Indore; one close to the west coast; and one additional
source is in the northern plains. The first two coincide with field detection sites and the
latter is used to represent areas with very high wheat production as a potential source.
Furthermore, we consider RDLs in Nepal, Bhutan and Bangladesh.

A particular focus of the study is to assess the risk of airborne transmission from East
African countries as potential source regions for pathogen dispersal to the large wheat
producing regions in the Middle East and the Indian subcontinent as spore receptors.
Further, we focus on airborne transmission from source regions in the Middle East to the
Rift Valley and to South Asia. This is motivated by the detection and evolution of several
strains of the Ug99 race group in the Rift Valley, and detections of the TKTTF race in the
entire Middle East. Field surveys during the last decade indicate the spread of Ug99 from
the Rift Valley to the Middle East, and the spread of race TKTTF from the Middle East to
the Rift Valley. In this work we quantify the risk of further long-distance dispersal, for
example of Ug99, from the Middle East and the East African Rift Valley to the large
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wheat producing regions in Pakistan and India. Note, however, that we conduct the
analysis of airborne transmission between all sources, also between different countries in
South Asia, and e.g. from South Asia to the East African Rift Valley.

1.1.2 Seasonal timing of wheat stem rust
We obtain typical seasonal wheat stem rust timings for all wheat producing countries in
our domain of interest in collaboration with field experts 1 2 3 4 5 6 7 8 9 10 11 . When
national expertise was not available, we infer seasonal dynamics from the FAO crop
calendar country briefs26.

Supplementary Figure 3 summarizes seasonal dynamics for all countries in our domain of
interest by illustrating those months of the year in which wheat stem rust typically occurs
in the field. See Movie 1 for a time-lapse of seasonal dynamics. We use the time-
windows during which wheat stem rust is known to have occurred in the field for the
seasonal timing of release of spores from RDLs in the LPDM simulations, and also as
those time-windows for which deposition of spores on susceptible wheat areas in receptor
countries is possible. Airborne transmission along migration routes is only considered in
case of a green bridge of overlapping seasons at source, i, and receptor, j (Hij =1 in Eq.
t
1 in the main text). Due to different agro-ecological zones and diversity of individual
growing practices, there can be regional and local differences in wheat growing practices
and typical timing of occurrence of wheat stem rust, but we focus here on the main
seasons in all key wheat producing countries in an attempt to capture essential wheat and
wheat stem rust dynamics on continental scales.

1 South-Africa: Z.A. Pretorius, Professor of Plant Pathology, Department of Plant Sciences, Republic of South-Africa
2 Zimbabwe: B. Mutari, Crop Breeding Institute, Zimbabwe Ministry of Agriculture, Department of Research and Specialist Services
3 Kenya: R. Wanyera, Principal Research Scientist, Kenya Agriculture Livestock Research Organization, Kenya.
4 Eritrea: A.W. Tecle, Senior Researcher, Head Plant Protection Research Unit, National Agricultural Research Institute, Ministry of
Agriculture, Eritrea
5 West-Yemen: M.N.E. Nasser, Senior Scientist, The Agricultural Research and Extension Authority, Yemen
6 Iran: F. Afshari, Professor of Plant Pathology, Seed and Plant Improvement Institute, Iran. J. Kamali, Principal Scientist, CIMMYT,
Iran.
7 Turkey: Z. Mert, The Central Research Institute for Field Crops, Turkey
8 Egypt: A. Shahin, Wheat Disease Research Department, Plant Pathology, Research Institute, Agricultural Research Center, Egypt
9 Lebanon: R. El-Amil, Lebanese Agricultural Research Institute, Lebanon.
10 India: S. Bhardwaj, Principal Scientist, Directorate of Wheat Research, India.
11 Ethiopia: D. Hodson, International Maize and Wheat Improvement Center (CIMMYT).
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