Can citizen science accelerate climate adaptation by poor

farming households?

Jacob van Etten et al. (see next slide)Bioversity International

Montpellier

March 16-18, 2015

Jacob van Etten Jeffrey Alwang ElizabethArnaud Eskender Beza Luis CaldererRhiannon Crichton Anton Eitzinger Keesvan Duijvendijk Carlo Fadda BasazenFantahun Jeske van de Gevel ElisabettaGotor Dejene Kassahun Mengistu SSKaushik Yosef G. Kidane Prem MathurLeida Mercado Sarika Mittra AnneMarie Moeller Ashis Mondal M. EnricoPė Susan Richter Juan Carlos Rosas R.K.Singh Juan Carlos Rosas I.S SolankiJonathan Steinke Inge Van Den BerghKarl Zimmerer

Au

tho

rs

Affili

atio

ns

CSA 2015 ≠ CSA 2050P

rob

lem

CSA 2015 ≠ CSA 2050

CSA is location-specific

Pro

ble

m

CSA 2015 ≠ CSA 2050

CSA is location-specific

Constant, massive testing is required

Pro

ble

m

CSA 2015 ≠ CSA 2050

CSA is location-specific

Constant, massive testing is required

Can science be accelerated?

Pro

ble

m

So

lutio

n

Citizen science (also known as crowd science, crowdsourcedscience, civic science or networked science) is scientific research conducted, in whole or in part, by amateur or nonprofessional scientists.

Wikipedia

So

lutio

n

Crowdsourcing is the process of obtaining needed services, ideas, or content by soliciting contributions from a large group of people, and especially from an online community, rather than from traditional employees or suppliers.

Wikipedia

So

lutio

n

Big task

So

lutio

n

Big task

So

lutio

n

Big task

Micro-task

1

Micro-task

5

Micro-task

2

Micro-task

3

Micro-task

4

Micro-task

6

Micro-task

7

Micro-task

n

So

lutio

n

Big task

Micro-task

1

Micro-task

5

Micro-task

2

Micro-task

3

Micro-task

4

Micro-task

6

Micro-task

7

Micro-task

n

Job done

So

lutio

n

So

lutio

n

Imp

lem

en

tatio

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Imp

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en

tatio

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Imp

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1

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Imp

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Re

su

lts

Victoria

Macuzalito

Chepe

Cedrón

Campechano

Amadeus 77

Don Kike

Overall performance

Bradley-Terry model results

Worse Better

Re

su

lts

Re

su

lts

“Why do you participate in crowdsourcing?”

0

5

10

15

20

25

30

35

40

45

50

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

Pilot, 2011-12 Wheat, 2012-13

Rice, 2013 Wheat, 2013-14

Rice, 2014 Wheat, 2014-15

Var

ieti

es

Farm

ers

Upscaling process in India

Number of varieties Number of farmersRe

su

lts

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

100.00

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Yield of 31 varieties of rice (orange) and 5 locally grown varieties (blue)

(q/ha)R

esu

lts

Co

nclu

sio

ns

1. Local learning fostered, accelerated

2. Reliable, generalizable results

1. Reduced costs comparing to otherparticipatory approaches

2. Simple field experiments makeupscaling possible

Ne

xt

ste

ps

1. User-friendly information platform tobe launched mid-2015 – GxE analysis

2. Input retail: suitable business models

3. Building capacity for implementation

4. Observe other variables and evaluatemore CSA technologies