Date post: | 20-Jun-2015 |
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Adapting to change: more realistic quantification of impacts and better informed adaptation alternatives
Daniel Rodriguez, Peter deVoil, Brendan Power, Howard Cox
Increase our (both researchers and the farming community) understanding (...we are all learning...) on what is changing (climate) and what are the likely consequences if those changes would persist;
Focus of the work
Work with our farmers and agronomists towards reducing their exposure to change (now and the next 5-10 years), by increasing our understanding on what farming systems are more profitable and less risky
ADAPTEDNESS
INCREMENTAL SYSTEMS
ADJUSTMENTS
TRANSFORMATIONGenerates a new social-
ecological systems
RESILIENCECapacity to absorb change and perform S
yste
ms
dis
turb
an
ces
After Nelson et al., 2007
Outcomes
Adaptation processes
System characteristics
Components of adaptation
• (Management) Systems that are more opportunistic-flexible-plastic versus systems that are more rigid or calendar driven
• Systems that can change function e.g. systems that
produce grain / fibre / meat
• Systems that can change scale or intensity e.g. irrigated
• Systems that are more diverse versus systems that are more like monocultures / products
Resilient farming systems by design
Case studies
Roma, grain & graze
Dalby, cotton-grains
Goondiwindi, rainfed cropping
Emerald, rainfed cropping
.
Case studies
Chick
Sorg1,2,.. Fallow
Whe1,2,..
Maize
Rainfed cropping (plastic)
Forageoats
Leucaena
Chickpea
Foragesorghum
Buffelgrass
Wheat
Fallow
Fallow
Grazing cycle
Cropping cycle
Mixed grain - grazing
Irrigated cropping
Cotton
Sorg Fallow
Maize
Mung
Fallow
Wheat
Fallow
Soy
Rainfed cropping
(rigid)
SF C
SF
W 1,2,..
SF
WF C
S 1,2,..
WF
SF
S 1,2,.. W 1,2,..
Whole farm configuration of the APSIM model
Simulates the impacts (i.e. biophysical, economic, environmental) of alternative allocations of limited resources (e.g. land, labour, time, irrigation water, livestock, machinery, and finance), at the whole farm level.
The APSFarm model
Rodriguez et al., 2011; Power et al., 2011 A1FI and A2, MRI-GCM232 and MIROC-H
2030
System disturbance
Sensitivity analysis
• Less land to cropping • More forages fewer pastures
Sensitivity analysis
A1FI 2030MRI-GCM232
Climatology
Allocation of resources
• Our case study farmers proved to be very good operators
• Percent reductions on farm profit can easily exceed percent changes on individual crop yields (not shown)
• Farms and farmers already operating on the efficiency frontier, would have fewer “easier” options to adapt
• More transformational changes will need to be explored
• Impact assessments and the identification of opportunities for adaptation to climate change should (also) be conducted at the whole farm level
Conclusions