MOSAICC:An inter-disciplinary system of models

to evaluate the impact of climate change on agriculture and forestry

Renaud ColmantNovember 2015

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)

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

Concept

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

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

LANDIS-IIUses

• 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

LANDIS-IIPnET-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

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

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

Integration

• Server• Spatial database• Web interfaces (user profiles, work modes,

experiment definition and management, data management)

• Shell (data preparation, experiment execution, output storage)

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

Distribution

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

Interfaces

• Home page – log-in

Interfaces• Functions (utilities and models)

Interfaces• Data management

Interfaces• Experiment management

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

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

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!

Demo

• Morocco serverhttp://81.192.163.58/