I t t d d lli hIntegrated modelling approaches: FALLOW€¦ · landscape dynamics as consequences of farmers’ decisions in managing their plots. • Impacts on land use changes

I t t d d lli hIntegrated modelling approaches: FALLOW

Betha Lusiana, Thomas H. Hilger and Desi Suyamto

DAAD Summer SchoolHanoi

12 – 23 July 2010

Programme for today and tommorow

1. Introduction to FALLOW: underlying concepts andapproachesapproaches

2. Example of FALLOW applications

3 FALLOW installation3. FALLOW installation

4. Working with FALLOW

Forest, Agroforest, Low-value Landscape O W t l d?Or Wasteland?

Forest Agroforest Land-based LivelihoodForest, Agroforest, Land based Livelihood Options Weighting?

FALLOW - Forest, Agroforest, Land-basedLivelihood Options Weighting?Livelihood Options Weighting?

• FALLOW is a spatially explicit model that simulateslandscape dynamics as consequences of farmers’decisions in managing their plots.

• Impacts on land use changes for food security, carbonstocks, plant biodiversity indicators and watershedfunctions are estimatedfunctions are estimated

Static relation between respiration and growth

Crop Modelling - Classification of Models

Static - relation between respiration and growth

Dynamic - predicting how a system unfolds in time

Empirical or Regression models - direct descriptions of observational data (response of crop yield to fertiliser level)

Mechanistic models - quantitative description of the mechanisms and processes that cause the behaviour of a system (crop growth models, leaf rust - barley crop model), y p )

Explanatory models - useful to gain insight into the functioning of physiological processes; more complex, less predictive capabilityphysiological processes; more complex, less predictive capability

Predictive models - used to predict systems behaviour in response to external, environmental influences; simpler, contain fewer parameters

FALLOW (c’tinued)

• FALLOW is a dynamic, mechanistic model that can bef ‘ di ti ’/ tiuse for ‘predictive’/prospective purposes.

• intends to capture overall trends of landscape dynamicsi it i i th t th lt k

FALLOW 2 0 d l i PC R t ith Vi l B i

main criterion is that the results make sense(sensible)

• FALLOW 2.0 develop in PC-Raster with Visual BasicInterface

www.worldagroforestry.org/sea/project/tulsea

FALLOW in PCRaster

MODEL OVERVIEW

Extension Agent

Population density

Access to landExtension Agent

Carbon stocksWatershed function,

Biodiversity

Population density,Landscape resources, Cultural preferences

Land use & cover change

Farmers’ decision making & l i Biodiversity

Market access,

change

Aggregated

learningInitial drivers External

consequencesLandscape dynamics

Infrastructure,Land Use technology

Plot level soil

fertility

Aggregated household economics

q

PricesMigration

Prices

Land use & cover

Farmers’ decision

ki &

Landscape dynamicsInitial drivers External consequences

& cover change

Plot Aggregated h h ld

making & learning

consequenceslevel soil fertility

household economics

Soil fertility

Crop/plant

growth & productivity

Plot level soil fertility

Soil fertility

Yield

DYNAMIC MODULE: PLOT LEVEL SOIL FERTILITY

Simple Model of Crop-Fallow Rotation Systems of Trenbath (1984, 1989)

C i P i dF ll P i d Cropping PeriodFallow Period

Maximum Level ofSoil Fertility

CropProduction

Soil Fertility Depletion

Depletion Rate

RestorationHalf

Recovery

Effect f FertilizerTime

Model Overview

Land use & cover

Farmers’ decision

ki &


& cover change


making & learning


household economics

Soil fertility

Crop/plant


TradeLivelihoods (secon‐

Financial capital

Profitability of land & labour


Soil fertility

YieldAggregated household economics

Trade

Food consumption Storage

dary consumption)

DYNAMIC MODULE: AGGREGATED HOUSEHOLD ECONOMICS

Financial Capitalp

Pop. SizeC ti

AF Products+C Yi ld StorageStoring x

Food Req.ConsumptionCrop Yield

+Forest Products

StorageStoring

Loss

Model Overview

Farmers’ decision making & learning

L bLearning

Land

allocation

External information (β)

Adjusting expected yield

(Learning)

Labour

allocationFinancial

allocation

Learning style (α)

Land use & cover

Farmers’ decision

ki &

(Learning) allocation


& cover change


making & learning


household economics

Soil fertility

Crop/plant



Financial capital



Soil fertility


Trade


dary consumption)

DYNAMIC MODULE: FARMERS’ DECISION & LEARNING

Knowledge Dynamics Recent experience

Farmers’ knowledge

Actual• return to labour

Expected • return to labour

a e s o edge

Expectation

• return to land

• return to labour• return to land

Expectation Adjustment

Extension agent suggestion

Return to labour• Return to land

Model Overview

DYNAMIC MODULE: FARMERS’ DECISION & LEARNING

Decision on Livelihood options are driven by resource availability/capital and expectation of profitability

• Financial

CAPITAL

Expected

Farmers’ knowledge

Li lih d O ti

• Land• Labour

Expected • return to labour• return to land

• Off-farm

Livelihood Options

Maximising Limited by the• Forest (NTFP, logging)• Agriculture (crops)• Agroforestry

Maximising income/revenue

Limited by the least capital

Agroforestry

P t ti l f

Land use& cover changeSpatial access & attractiveness


L bLearning

Land

allocation


Land conversion

& succession

Potential area for expansion


(Learning)

Labour

allocationFinancial

allocation

Learning style (α)

Land use & cover

Farmers’ decision

ki &

& succession(Learning) allocation


& cover change


making & learning


household economics

Soil fertility

Crop/plant



Financial capital



Soil fertility


Trade


dary consumption)

DYNAMIC MODULE: LANDUSE/LANDCOVER CHANGE

AF Post/Primary For

Wild Fires/S&BLand use trajectory

AF Late/ Old Second

Primary For.

AF Early/Y S d

Old Second. Forest

AF/F t

Young Second. Forest

AF/ForestPioneer

Model Overview

Agriculture

CHOICE OF FIELDS: Where to plant?

DYNAMIC MODULE: LANDUSE/LANDCOVER CHANGE

CHOICE OF FIELDS: Where to plant?RANDOMLY SELECTED BASED ON FIELD ATTRACTIVENESS

obab

ility

o P

lant

Pro To

Field Attractiveness

Soil Fertility

Accessibility

Model Overview

• Distance to road & village• Tenure• Forest reserve & settlement

P t ti l f

Land use& cover changeSpatial access & attractiveness


L bLearning

Land

allocation


Land conversion

& succession

Potential area for expansion


(Learning)

Labour

allocationFinancial

allocation

Learning style (α)

Land use & cover

Farmers’ decision

ki &

& succession(Learning) allocation


& cover change


making & learning


household economics

C / l

Soil fertility

Crop/plant



Financial capital



Soil fertility

Yield

Aggregated household economics

Trade


dary consumption)

CONSEQUENCES MODULE: FOOD SECURITY

Landscape

Plot LevelSoil Fertility &

Crop Production

Household LevelRice Store &Consumption

Food Securityp p

Carbon Stocks

Biodiversity

Decision OnLand Use Intensity

Choice Of Fields& Crop Type Watershed Function

Model Overview

CONSEQUENCES MODULE: FOOD SECURITY

FoodRequirement

Population Size

FoodConsumption

Rice Store

Food Sufficiency = Food Requirement/Food Consumption

Model Overview

Food Sufficiency Food Requirement/Food Consumption

CONSEQUENCES MODULE: CARBON STOCKS

Landscape


Crop Production


Food Securityp p

Carbon Stocks

Biodiversity



Model Overview


ABOVEGROUND C STOCKSABOVEGROUND C-STOCKS

Maximumks S&B Loss Wild Fire

G C

-Sto

ck S&B Loss Loss

AG

Annual AGC-StocksIncrement

Fallow Time0

Model Overview


BELOWGROUND C STOCKSBELOWGROUND C-STOCKS

Maximumks

G C

-Sto

ckB

G

Relative Soil Fertility

Model Overview

CONSEQUENCES MODULE: BIODIVERSITY

Landscape


Crop Production


Food Securityp p

Carbon Stocks

Biodiversity



Model Overview


A h 1 S li R lApproach 1: Scaling Rule

ess Maximum

ess

ScalingParameter forNon AF ( )

es R

ichn

e

HalfRecovery es

Ric

hne Non-AF (zi)

+ForestNeighborhood

Time since last S&B

Spe

cie y

Time

LC Area (A)

Spe

cie g

Effect for AF(y)

PLOT LEVEL (S1)Time since last S&B

LANDCOVER TYPE (Si)LC Area (A)

Si=S1*Azi+S1*y

Model Overview

i 1 1 y


A h 1 S li R lApproach 1: Scaling Rule

ess

ScalingParameter forNon AF ( ) ss

es R

ichn

e Non-AF (zi)+ForestNeighborhood es

Ric

hne

LC Area (A)

Spe

cie g

Effect for AF(y)

Landscape

Spe

cie

LANDCOVER TYPE (Si)LC Area (A) Landscape

pij

pijOverlappingProbability

Model OverviewStotal=Σi(Si-(ΣjpijSj)


A h 2 P b bilit f O f Bi di it Pl t GApproach 2: Probability of Occurrence of Biodiversity Plant Group

45

50

30

35

40

mbe

r

20

25

30

peci

es N

um

5

10

15Sp

0

5

Late Successional Medium Seral Early Successional Pioneers

Model Overview

Plant Group


A h 2 P b bilit f O f Bi di it Pl t G

0.25

Approach 2: Probability of Occurrence of Biodiversity Plant Group

0 15

0.20

curr

ance

Pi

0.10

0.15

abili

ty o

f Occ Pioneer

Young Sec

Old Sec

0.00

0.05Prob

a Old Sec

Prim For

Late Successional Medium Seral EarlySuccessional

Pioneers

Plant Group

Model Overview

CONSEQUENCES MODULE: WATERSHED FUNCTION

Water Use

Rainfall

Water Use

Overland Flow

Infiltration

Net Sediment Loss

Subsurface Quick FlowInfiltration

Slope

Soil PhysicalQuality

B Fl

Groundwater

Model Overview

Base Flow

Documents

I t t d d lli hIntegrated modelling approaches: FALLOW€¦ · landscape dynamics as consequences of farmers’ decisions in managing their plots. • Impacts on land use changes