Future Technology Transformation in Agriculture FTT:AGRI

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Future Technology Transformation in Agriculture FTT:AGRI Soeren Lindner and Jean Francois Mercure Department of Environmental Sciences, Radboud University, Netherlands C-EENRG, Department of Land Economy, University of Cambridge, UK

Transcript of Future Technology Transformation in Agriculture FTT:AGRI

Page 1: Future Technology Transformation in Agriculture FTT:AGRI

Future Technology Transformation in

Agriculture

FTT:AGRI

Soeren Lindner and Jean Francois MercureDepartment of Environmental Sciences, Radboud University, Netherlands

C-EENRG, Department of Land Economy, University of Cambridge, UK

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Outline

• Environment-Economic models

• FTT:Agri Model description and applications

• Land use and Land use change modelling with FTT: Agri

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Different types of global models

Earth

system

models

Environmental

Economic

Input – Output

models

FTT-Agri

Integrated

assessment

models

Macroeconomic

Models

Complex

environment

Simple

environment

Complex

economics

Simple

economics

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The E3ME-FTT-GENIE Integrated Assessment Model

FTT:Agri

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Human – Earth System interaction

Demand Drivers

nutrientsirrigation

Forest

manage

ment

Suitable land for crop

production

Pasture

and

livestock

system

Land cover

crops, grassland

Subsidy

Climate Policy

Afforestation

Land Use

Policy

Emissions

Human system

Agriculture and Land Use

The Farmer – as an Entrepreneur

Earth System

Land

Policy

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FTT:Agri

Basic classes / structure

Land types Land use types Final commoditiesCerealsRice

Agriculture Cropland rainfed PotatoesCropland irrigated Other roots

MaizeGrasslands Pasture Soy

SunflowerRapeseedOther oil cropsSugar cropspoultryporkbeefother meats/animal products

Natural ForestsManaged Forests fish

fruitvegetablesother

Crops

Explanation made up of:

1Temperate cereals Wheat Rye Barley

2 Riceis always irrigated, but may

have values for rainfed3 Maize

4Tropical cereals Millett Sorghum

5 Pulses field peas

6Temperate roots Sugar Beet

7Tropical roots Cassava

8 Sunflower9 Soybean10 Groundnut11 Rapeseed12 Sugarcane

13 Otherscitrus, vine coffee

14 Pastures modelled as crops

15 grassbioenergy crops type 1

16 treesbioenergy crops type 2

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E3ME – FTT:Agri – LPJml interaction

E3ME FTT-Agri

- Annual Demand for 19 Food Commodities

- Supply (tonnes) for base year (2005,FAO)

- Long-term: cumulative R&D investment

- Potential supply for subsequent years

- Emissions (tons CO2eq) as result of land use

changes

- Commodity prices

- Demand for other inputs

LPJml

Cost

Matrix

- Potential land area suitable for crop type

level: grid cell, means, stdev. taken as

country level

- historical dataset, base year: 2015

- Theoretical biophysical productivity

Simulations from 2000 – 2100 under

two climate change scenarios

level: grid cell: means, stdev taken at

country level

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FTT:Agri Basic conceptLand Supply - short term demand change

Land for

crop i

• Land for

crop j

Land for

crop type

k

Short-term demand changes for

commodities...

..met by use of

spare/rest land to

produce commodities

potential land area LPJml

land area used for harvest (FAOSTAT)

Potential supply is

higher than actual supply

Land use (capacity) factor:

LUF= G/Gp

LUF remains constant

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FTT:Agri Basic ConceptLand supply - long-term demand change

suitable area for

crop j crop k

commodity supply to meet demand

at time t

mean productivity, j mean productivity, k

country level

grid cell

level theoretical biophysical productivity

at grid cell level

Time

(t)

Management factor,

Technology by country

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FTT:Agri Basic ConceptLand supply - long-term demand change

suitable area for

crop j crop k

commodity supply to meet demand

at time t

mean productivity, j mean productivity, k

Country level

grid cell

levelChange in

theoretical biophysical productivity

with climate change

Time

(t)

Management factor,

Technology by country

Technological change

and productivity change over time

drive conversions

LUF changes

suitable area

for crop jcrop k

commodity supply to meet demand

at time t + x

Area of conversion

k to j

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Costs of Production

FTT-AgriCost

Matrix

-fixed costs

-variable costs

-land rental

-discount rates

-project lifetimes

Levelised costs Agriculture

Model of decision making

by groups of farmers

Farmers Business Plan (at country level)

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Cropland conversion

Example

Conversions take place over a

longer time horizon

driven by:

- changes in productivity (climate)

- Investments (technology,

management factor)

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Thank You!

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Policy

EnvironmentLand

Land Use Change

Macroeconomy

Planetary

Boundaries

Human

Development

Global Energy-Economy-Environment system

Energy

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Example:Agriculture and food in the Brazilian

economy

Source: Eurostat, OECD, national statistics, Asian Development Bank, UN prodcom

Shares of national export for agriculture and food

Agriculture-food exports for Brazil Agriculture-food employment for Brazil

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Additional slides

Aggregating productivity to distributions

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