Plant diseases in a changing climate – approaches to assess … · Plant diseases in a changing...

Department of Crop Sciences, Plant Pathology & Crop Protection Division

Department of Crop Sciences, Plant Pathology and Crop Protection Division, Georg-August University Göttingen,

Germany

Andreas von Tiedemann et al.

Plant diseases in a changing climate – approaches to assess and estimate future crop risks

International Conference on Crop Losses, Paris, 16-18 October 2017


The disease triangle

Can CC be integrated in that concept and how? -


Climate change – the last 50,000 years (temperature proxy data from the greenland ice core)

Last Postglacial

Neolithic revolution, Agriculture (10.000 BP)

Behringer, Kulturgeschichte des Klimas, 2010 (adopted from Rahmstorf, 2003)

Years [x1,000] before present

Holocene


Climate change – the last 100 years (1900-2000 Germany)

Pretzsch et al. Nature Communications, 2014.

Temperature: + 1.0°C

Precipitation - summer: -3% - winter: +19%

CO2: 300 390 ppm

Vegetation period: +22 days


Terrestrial Net Primary Productivity Anomalies for East Asia, 1901-2002 Piao, S. et al. Global Change Biology, 2011

Negative desertification trend Sahel zone, 1982-2003 Herrmann, S.M., et al. Global Environmental Change, 2005.

Negative desertification trends in China, 1982-1999 Piao, S., et al. Geophysical Research Letters 2005.

Increase in aboveground biomass productivity of Brazilian humid forests since 1958. Phillips, O.L., et al. Science 1998.

Increased tree growth in the last century in N-America (oak, pine) and Europe (beech, spruce, fir) (several papers)

Corn

Wheat


0.0

0.2

0.4

0.6

0.8

1.0

0 2

4 6

8 10

12 14

16

5 10

15 20

25

Räder, T., Racca, P., Jörg, E., Hau, B. (2007). PUCREC/PUCTRI - a decision support system for the control of leaf rust of winter wheat and winter rye. OEPP/EPPO (37), 378-382.

Wheat leaf rust (Puccinia triticina) – Environmental drivers

Uredospores

Sporulation on host

Infection

6


Is climate change …

Secondary climate change impact on crop yield

… modulating severity of pre-existing diseases?

… creating novel pathogens/pathotypes/races?

… driving emergence of diseases in new areas?


80-90% of wheat lines susceptible to UG99!

Department of Crop Sciences, Plant Pathology & Crop Protection Division, University of Göttingen

20 March 2015: CAUTION – Increasing risk of stripe (yellow) rust outbreaks, North Africa to South Asia Posted on March 20, 2015 by David Hodson - ‘Warrior’: spreading rapidly throughout Europe since

2010; overcomes Yr1,2,3,4,-,6,7,-,9,-,-,17,-,25,-,32,Sp, Avs, Amb; since 2013 in N-Africa, 2014 in W-Asia

- ‘Yr27 virulence’: new aggressive races breaking Yr27 resistance in Europe, Africa, Asia

established in Denmark by the end of 2008, on behalf of CIMMYT, ICARDA and Aarhus University, Denmark

Yellow (stripe) rust since 2014 in Germany, up to 60% yield losses


Range expansions pests & diseases – causes

First reports of pathogens 2010-2015 (ProMED)

140 new reports

Viruses (36.6%), fungi (28,2%)

Maize (9.1%), banana (8.5%), citrus (7.7%), potato (7.0%)

Bebber, D.P., Range-expanding pests and pathogens in a warming world. Annual Review of Phytopathology, 2015.




… creating novel pathogens/pathotypes/races? no evidence for direct impact!

… driving emergence of diseases in new areas?



As a result of lacking disease control …

- ca. 1 million deaths

- 2.5 million emigrated

Potato late blight and the Great Irish famine 1845-50

1845

From: Agrios, 2005


World distribution of coffee rust. (Adapted from Schieber, E. and G.A. Zentmyer. 1984. Coffee rust in the Western Hemisphere. Plant Dis. 68:89-93. Used by permission from P.A. Arneson)

Global Spread of Coffee Rust (Hemileia vastatrix)


The three disasters in European vineyards

Powdery mildew (U. necator) 1845 Introduced from N-America

1854 80% Crop loss in France

Phylloxera 1858 Introduction with vines from N-America resistent to mildew

Downy mildew (P. viticola) 1878 Introduced from N-America

1882 ‚Bordeaux mixture‘ (Millardet)


History and Dispersal of Fire Blight in N-America and Europe

1780 Hudson Valley

1840 Canada

1888 California

1905 1957 Kent

1966 The Netherlands

1971 Schleswig-Holstein

1993 Lake Constance 1989

Switzerland

© K. Mendgen 2004


1930

1998 1997 1993

1999

1986

1898

1987 1988

Spread of Ramularia leaf spots in barley in Europe

( (1898 – 2000; Sachs, 2003)


1902

2001

2001

1996

2002

2004

1998 2003

2001

Asian Soybean Rust (Phakopsora pachyrhizi)


Pest/pathogen Spread Causes Downy & powdery mildew grapevine

N-America Europe Introduction by planting/grafting material

Potato late blight Central America Europe Introduction by planting material

Coffee rust E-Africa SE-Asia S/C-America

Introduction by planting material

Wheat stem rust UG99 Uganda Africa Central Asia Race evolution & selection; long distance transport with air streams

Wheat stripe rust Europe, N-Africa, Middle East, India

Race evolution & selection; long distance transport with air streams

Ramularia leaf spots barley

Within Europe, S-America Introduction by seeds (?); over-use of strobilurins

Asian soybean rust China Africa S-America N-America

Introduction; long distance transport with air streams (?)

Verticillium oilseed rape Europe: N S & W & E; Canada

High intensity of OSR production; plant/seed trade (?)

Fire blight apple, pear N-America Europe Introduction with planting material

Range expansion of diseases – cases and causes


… examples of climate change driving the emergence of infectious plant diseases have not yet been clearly identified. … … introduction by trade and traffic of alien pathogens or hosts is the most commonly cited driver of emerging infectious diseases. … the increasing volume of globalized trade has driven increased frequency of introduction events. Review: Anderson P. et al., 2004. Emerging infectious diseases of plants: pathogen pollution, climate change and agrotechnology drivers. Trends in Ecology and Evolution 19.

Range expansions pests & diseases – causes

Conclusions on range expansion of pests & pathogens

However: Is there an indirect climate effect on pathogen & pest expansion by shifting cropping zones?


Range expansion of maize diseases in Germany

Kabatiella zeae Exserohilum turcicum Puccinia sorghi 2012 2013

*

PHD project Lucia Ramos, 2012-2015


Cerrados

South

Wheat blast (Magnaporthe grisea)

Fusarium ear scab (Fusarium spp.)

ca. 90% of Brazilian wheat production

Range expansion of wheat diseases in Brazil




… causing emergence of diseases in new areas?


Since historic times, pests and pathogens have followed their crops. At present, introduction, crop area expansion and agrotechnology rather than direct climate effects are the main drivers of emergence of diseases in new areas. However, pathogens appear to be more climate-sensitive than their host crops.


Biotic stressors Pathogens 25

Insects 27

Nematodes 2

Weeds 37

Regional climate scenarios Reference period: 1971-2000

Shortterm: 2021-2050

Longterm: 2071-2100

(4) Sugar beet

(1) Wheat (2) Oilseed rape

(3) Maize

Crops

2009 - 2014 Climate change effects on agricultural crops in Lower Saxony


Methodological approaches: Experiments in model systems: Controlled conditions

Modelling: Linking pest & disease models with climate models

Risk analysis & adaptation

24


Climate change in Lower Saxony

2021-2050 2071-2100

Annual av. temperature +1°C +2.5°C

Vegetation period + 23 days + 60 days

Frost days - 32% - 66%

Snowfall - 30% - 50%

Precipitation + 7% Increase in all seasons

Winter + 19% Spring + 11%

Summer - 10% Autumn +17%

Source: Empfehlung für eine niedersächsische Strategie zur Anpassung an die Folgen des Klimawandels, 2012

Climate change in Lower Saxony simulated by REMO (A1B) and GLM compared to the reference period 1971-2000


Micro-greenhouses in the field

Climate chambers

Rain simulation in the greenhouse

Miniplot soil heating facility

Weed competition experiments with maize in the greenhouse

Experiments in model systems


Ambient

Ambient

Ambient

Ambient

+1.6°C

+1.6°C

+1.6°C

+3.2°C

+3.2°C

+3.2°C

+1.6°C +3.2°C

Göttingen Miniplot-Soil Heating Experiment

Warming scenarios for Lower Saxony (2050 and 2100)

Siebold M & A v Tiedemann (2012) Application of a robust experimental method to study soil warming effects on oilseed rape. Agricultural and Forest Meteorology 164, 20-28. 27


Climate chamber: r² = 0.27 Field: r² = 0.17 (n.s.)

Siebold M & A v Tiedemann (2013) Global Change Biology 19, 1736-1747.

Sclerotinia sclerotiorum

T0

T1

T2

T0 = Reference: 1971-2000 T1 = Shortterm: 2021-2050 T2 = Longterm: 2071-2100 DD = degree days, March-May 2011/12

28


Heros: r² = 0.45 SEM: r² = 0.77 Falcon: r² = 0.67

Siebold M & A v Tiedemann (2013) Global Change Biology 19, 1736-1747.

Verticillium longisporum

T0 T1 T2

29

T0 = Reference: 1971-2000 T1 = Shortterm: 2021-2050 T2 = Longterm: 2071-2100 DD = degree days, March-May 2011/12


Methodological approaches: Experiments in model systems: Controlled conditions

Modelling: Linking pest & disease models with climate models


30

Juroszek, P. & A. v. Tiedemann (2015) Linking plant disease models to climate change scenarios to project future risks of crop diseases – a review. Journal of Plant Diseases and Protection 122(1), 3-15. Juroszek, P. & A. v. Tiedemann (2013) Climate change and potential future risks through wheat diseases: A review. European Journal of Plant Pathology 136, 1, 21-33. Juroszek, P. & A. v. Tiedemann (2013) Plant pathogens, insect pests and weeds in a changing global climate – approaches, challenges, research gaps, key studies, and concepts. Journal of Agricultural Science 151, 163-188.


Modeled agricultural zones in Lower Saxony, Germany

Source of map: Bürger et al. (unpublished)

Region 1: WRa-WW-WW-WB

Region 2:

Maize monoculture Region 3: SB-WW-Potato-WW

Region 4: SB-WW-WW

Region 5: WRa-WW-WW-WB

Sowing dates (same in all regions): ● Wheat: 01.09., 15.09., 15.10., 01.11. (simulated) ● Rapeseed: 15.08., 31.08. (simulated) ● Sugar beet: 15.03., 01.04., 15.04. (simulated) ● Maize: Early April, End of April (expertise-based)

31

Counties Maize WW = winter wheat WRa = winter oilseed rape SB = sugar beet Potato

Time horizons: Presence 2021-2050 2071-2100


• … relevant changes (>50%) of diseases on leaves only in young growth stages (0-30) and at longterm climate change projections

• … potentially increased leaf diseases in autumn/winter requiring adapted sowing times or earlier fungicide application in spring

• ... shifting of disease prevalences: less powdery mildew, more leaf rust and tan spot

• … no significant changes for stem base and ear diseases

• ... potential shifts in the regional distribution of diseases

Future disease management in winter wheat

32




Potential climate change impact on crop diseases


… causing emergence of diseases in new areas?

Yes, resulting in regional shifts of disease & pest prevalences, but not in an overall risk increase. Modern crop protection technology and monitoring is required to adapt to such shifts, as practiced at present.

Since historic times, pests and pathogens have followed their crops. At present, introduction, crop area expansion and agrotechnology rather than direct climate effects are the main drivers of emergence of diseases in new areas. However, pathogens appear to be more climate-sensitive than their host crops.


Conclusions for future crop risks

34

At present, modern crop protection technology is effective to respond to annual changes in disease & pest incidence. No reason why longterm changes wouldn‘t be manageable.

CC may induce shifts in the regional priority of diseases & pests but will not necessarily cause an overall increase in unmanagable risks.

Like in the past: Agrotechnical progress (cultivars, crop rotation, soil tillage, agrochemicals …), agro-policy and markets are the main drivers of crop diseases. These factors have to be considered first when modelling/predicting future crop risks.


Modelled regional climates (REMO, A1B, MPI f. Meteorology, Hamburg)

Region Weather stations (n)

∆ annual mean temperature [°C]*

∆ annual precipitation [mm]

2021-50 2071-100 2021-50 2071-100

1 54 +0,3 +2,7 +37 +110

2 30 +0,3 +2,8 +19 +57

3 15 +0,4 +2,9 +8 +37

4 46 +0,3 +2,9 +4 +40

5 10 +0,3 +3,0 +10 +59

*) based on hourly records, related to the reference period 1971-2000

Year Ann. Temp. [°C] Ann. Precipitation [mm]

2003 9,5 542

2007 10,2 (∆=0.7) 942 (∆=400)

Interannual comparison 2003-2007 (22 locations, Lower Saxony)

35


Acknowledgements

To all partners in the KLIFF consortium (2009-14)

- Paolo Racca & Benno Kleinhenz, ZEPP, Bad-Kreuznach - Peter Juroszek, KLIFF - Joachim Kakau, University of Osnabrück - Magdalena Siebold, University of Göttingen

Ministery of Science and Culture in Lower Saxony for funding

Plant diseases in a changing climate – approaches to assess … · Plant diseases in a changing...

Documents

Transcript of Plant diseases in a changing climate – approaches to assess … · Plant diseases in a changing...