The abiotic and biotic impacts of climate change on potato agriculture

Stewart Jennings, Ann-Kristin Koehler,

Steve Sait, Andy Challinor

Summary

● Biotic stresses – why are they important? ● Why are potatoes important?● Model set-up.● Impacts of climate change on potato

agriculture – UK and Colombia case studies.

Oerke, 2006

Oerke, 2006

Pest damage inclusion in crop models

Rivington and Koo, 2011

Pests moving spatially and temporally with climate change Bebber et al., 2013

Late blight (Phytophthora infestans)

● Phytophthora infestans – better known as late blight or potato blight – is the fungus-like oomycete responsible for the Irish potato famine of the mid-19th century.

● Global potato yield losses from diseases, pests and weeds estimated to be around 40% of attainable production (Oerke, 2006).

● Diseases alone accounted for 21% of this loss, with late blight generally considered the most important global disease.

● Potential yield losses from late blight in some cases reported to be as high as 30% (Dowley et al., 2008)

● Damages leaves, stems and tubers.

The neglected potato? Neglect Index = Global Crop Production / WoK Hits

● WoK search (Brown et al., 2011): “Potato and (radiation interception or radiation use efficiency or photosynthesis or extinction coefficient or phyllochron or leaf appearance or leaf size or leaf area index or harvest index)”.

● Global search - "potato and global and climate change and crop model and (yield or production or stress)"

Neg

lect

Ind

ex

Neg

lect

Ind

ex

The Polygon of Potato Pertinency

The Polygon of Potato Pertinency

Neglected

The Polygon of Potato Pertinency

Neglected Pest vulnerability

The Polygon of Potato Pertinency

Nutritious

Neglected Pest vulnerability

The Polygon of Potato Pertinency

Nutritious Delicious

Neglected Pest vulnerability

Which regions will present risks and opportunities for potato agriculture in a future climate?

Contrasting regions to study climate change and potato agriculture – UK and

ColombiaCIP, 2009

General Large Area Model for annual crops (GLAM)

● Process-based crop model.

● Designed to work at regional spatial scales (often around 100km²).

Challinor et al., 2004

High temperature

d(HI)/dt Pod fraction stress module

Biomass Yield

transpiration

efficiency

Root systemDevelopment Transpiration radiation

stage temperaturerainfall

Leaf canopy RH

CYG water Soil water

stress

GLAM-potato

crop planted

harvest emergence

senescence tuber initiation

GLAM-potato evaluation using comparison with stat. model:

Yield = Precip. * Mean Temp.

Run set-up for abiotic climate change analysis

● Yield change from current climate to 2045 measured for the UK and Colombia with RCP8.5 ISI-MIP data (Hempel et al., 2013).

● MIRCA growing areas (Portmann et al. 2010).

● One parameter set for each country.

● No adaptation: Rainfed crop, mid-range of reported planting dates.

● Adaptation: turn on irrigation and allow planting dates to vary.

Biotic stress – late blight● SimCast model used to measure the risk of late

blight attack (Sparks et al., 2011).

● “Blight units” calculated from levels of relative humidity and temperature and represent relative risk of blight occurrence for different cultivars of potato.

Blig

ht Un its

Biotic and abiotic impacts - UK

Ba

seline -future b light un it cha

nge (%

)

Baseline-future yield change (%)

Reg

ion

Biotic and abiotic impacts - Colombia

Baseline-future yield change (%)

Ba

seline -future b light un it chang

e (%)

Reg

ion

Adaptation – Colombia

Baseline-future yield change (%)

Reg

ion

(A. =

ad

apt

atio

n)

Biotic stresses – late blight (Sparks et al., 2011)

Col.

UK

The end. For now.

Thanks for listening.

References● Bebber, D., Ramotowski, M. and Gurr, S., 2013, Crop pests and pathogens move polewards in a

warming world, Nature Climate Change 3.

● Brown, H. E., Huth, N. and Holzworth, D., 2011, A potato model built using the APSIM Plant.NET Framework, 19th International Congress on Modelling and Simulation, Perth, Australia.

● Challinor, A. J., Wheeler, T. R., Craufurd, P. Q., Slingo, J. M. and Grimes, D. I. F., 2004, Design and optimisation of a large-area process-based model for annual crops, Agricultural and Forest Meteorology 123.

● Dowley, L.J. Grant, J. Griffin, D., 2008, Yield losses caused by late blight (Phytophthora infestans (Mont.) de Bary) in potato crops in Ireland, Irish Journal of Agricultural and Food Research, 47.

● FAO, (2014), Food and Agriculture Organization of the United Nations Statistical Database.

● Hempel, S., Frieler, K., Warszawski, L., Schewe, J. and Piontek, F., (2013), A trend-preserving bias correction - the ISI-MIP approach, Earth System Dynamics, 4.

● Oerke, E., 2006, Crop losses to pests, The Journal of Agricultural Science, 144.

● Portmann, F., Siebert, S. and Döll, P., 2010, MIRCA2000 - Global monthly irrigated and rainfed crop areas around the year 2000: A new high-resolution data set for agricultural and hydrological modeling, Global Biogeochemical Cycles, 24.

● Rivington, M. and Koo, J., 2010, Report on the Meta-Analysis of Crop Modelling for Climate Change and Food Security Survey.

● Sparks, A.H., Forbes, G.A., Hijmans, R.J. and Garrett, K. A., 2011, A metamodeling framework for extending the application domain of process-based ecological models, Ecosphere, 2.