The MOdelling System for Agricultural Impacts of Climate Change (MOSAICC) is an easily accessible web-based platform which allows users to assess the impacts of climate change on agricultural production. A new forestry component has been developed and integrated in the MOSAICC platform. This presentation presents the forest landscape simulation model which is used to generate projections of ecological process under different climate change scenarios. © FAO: http://www.fao.org

1. MOSAICC:
An inter-disciplinary system of models
to evaluate the impact of climate
change on agriculture and forestry
Renaud Colmant
November 2015

2. Concept
• Need for a tool to facilitate the user
experience by simplifying data processing and
simulation runs
• Include additional models
• Transferable (capacity reinforcement)
• At no cost (freeware)

3. Concept
MOSAICC: Modelling System for Agricultural Impacts of
Climate Change
•Capacity development tool for Assessing climate
change impacts on agriculture at national level (trends)
•By national experts (ministries, universities, research
institutions)
•Using own data
•In a perspective of decision support

4. Concept

5. Models selection
• Expert consultation
• Robustness rather than sophistication (low
data input, commonly available), flexibility,
wide application, open source
• 1 Statistical Downscaling tool, 2 crop models,
1 Hydrological model and 1 Economic model
• New: 1 forest model

6. LANDIS-II
•Developed by Portland State University
•LANDIS-II is a forest landscape simulation model. It simulates how
ecological processes including succession, seed dispersal, disturbances, and
climate change affect a forested landscape over time.
Models selection

7. LANDIS-II
Uses
• Across large (typically 10,000 - 20,000,000 ha) landscapes.
• Spatial and Temporal Flexibility
– variable time steps for each process
– variable spatial resolution and extent
• Built for Collaboration
– on-line database of extensions
– open-source extensions
– well documented
– flexible model architecture

8. LANDIS-II
PnET-Succession
• Purdue University, USA
• Assumption 1:
– Ecological models built on phenomenological relationships and behavior of the past are
“Not robust enough under novel conditions”
Gustafson, 2013 ; Williams et al., 2007
• Assumption 2:
– Process-based models have
“More robust predictions under novel conditions”
Cuddington et al. 2013; Gustafson, 2013
 PnET process-based model integrated
in LANDIS-II as succession process

10. Main Inputs
Ecoregions input map:
-Temperature
-Precipitation
-Soil
Climate data (by Ecoregion):
-From downscaled and interpolation
Initial communities:
-Input map
-List species age cohorts by Initial Site Classes
Species parameters:
-Longevity
-Sexual maturity
-Seeding distance
-Foliar characteristics
-Shade and Fire tolerance
Values have already been given to most of the
parameters (applied for categories of species)
Disturbances:
-Harvest
-Fire
-Wind

11. Main Outputs
Spatial annual maps:
- By species (user choice)
- By interest:
• Biomass
• LAI
• Soil water
• Establishment
Graphs and tables :
- For all the species
• Total Biomass
• LAI (m2
)
• Establishment
• Soil water
• CC impacts
• Disturbance impacts
• Harvested wood

12. Integration
• Server
• Spatial database
• Web interfaces (user profiles, work modes,
experiment definition and management, data
management)
• Shell (data preparation, experiment
execution, output storage)

13. Distribution
• Delivered to technical institutions
through:
– Constitution of a working group
– Trainings
– Support to carry out an integrated
impact study
• Operational in the Philippines,
Morocco and Peru
• Foreseen: Zambia, Malawi,
Paraguay

14. Distribution

15. Thank you for your attention
• Info:
– www.fao.org/climatechange/mosaicc
– MOSAICC@fao.org
• Partners
Mauro Evangelisti
Servizi Informatici
Numerical Ecology of
Aquatic Systems
AgroMetShell

16. Interfaces
• Home page – log-in

17. Interfaces
• Functions (utilities and models)

18. Interfaces
• Data management

19. Interfaces
• Experiment management

20. Advantages
• Participatory approach
• Remote access
• Nothing to install (web browser)
• Easy data exchange
• Low computing time
• No data format or unit conversion
• Data tracking down the flow

21. Decision support
• Relevance of simulations and modelisation
– Scenario testing (climate, varieties, crop management,
water use, demography, policies etc.)
– Facilitate understanding of processes at stake
– Very suitable for climate change studies
• Limitations:
– Reduced reality, non
comprehensive, under
assumptions
– Uncertainties

22. Decision support
• “Essentially, all models are wrong, but some
are useful” (G. Box, statistician)
• Data quality: garbage in = garbage out
• Not to be taken alone!

23. Demo
• Morocco server
http://81.192.163.58/