Detecting desertificationin savanna systems

RJ (Bob) ScholesCouncil for Scientific and Industrial Research

Natural Resources and EnvironmentPretoria, South Africa

bscholes@csir.co.za

What is desertification?

[Hyperarid]Arid

SemiaridSubhumid

Desertification is degradation in dry lands

United Nations Convention on Combatting Desertification

Global distribution of savannas(basically the same as the summer-rainfall drylands)

Savannas are mixed tree-grass systems

Some facts about savannas

• World’s largest land biome (~12%)• Second largest Net Primary Productivity and

carbon store (16.8 x 1015 gC/y)• Large ‘natural’ impact on atmosphere through fire,

carbon cycle and dust• Home to ~1 billion people; source of food and

energy to most of them• Centre of biodiversity (7000 species in Africa

alone)

Desertification sucks!The single environmental issue affecting the livelihoods of

the largest number of people worldwide

41% of Earth’s land surface 2 billion inhabitants90% in developing countries

What is degradation?

Degradation is a persistent decrease in the capacity of an ecosystem to deliver ecosystem services

Does not spontaneously return to historical average within a reasonable time when you

reduce the cause of change

The benefits that people get from ecosystems

-Millennium Ecosystem Assessment

Ecosystem ServicesMillennium Ecosystem Assessment Classification

Provisioning

•Crops•Grazing and livestock

•Timber and fuel•Fisheries

•Water•Medicine

Regulating

•Climate•Floods

•Pest regulation •Disease control

Cultural

•Aesthetic•Recreation

•Amenity•Spiritual

•Educational

Supporting• Net Primary Production

• Nutrient cycling

Biodiversity: the variety of Life on Earth

Summary so far…

To detect desertification, we are looking for a change in state in savanna ecosystems

Ecohydrological state change(typically on silty soils)

runoff-

rainfall infiltration+

+ soil water+

plant productionplant cover++

herbivory-

Nutrient state change(typically on less-fertile, erodible soils eg sandy loams or loess)

rainfall plant production

vegetation andlitter cover

soil erosion

+

herbivory

-

+

-

fire

-

-

nutrients

harvest+

--

export from thelandscape

+

-

+

-

Change in the rain use efficiency

undegraded

degraded

Decrease in slopeor position

Measure of plant productionEg ΣFAPAR or similar

Rainfall in growing season

Production in water-limited pastoral systems

Tree growth

Rainfall

Grass growth

competitionAnimal

productionsoils

An electrical analogWhat controls the brightness of the lamp?

productivity

Sun nutrients

water

In pulsed systems, water availability controls the duration of growth opportunity

Linear relation betweengrass production and rainfall

0

100

200

300

400

500

0 200 400 600 800 1000

Annual rainfall

Gra

ss A

G N

PP

(g/m

2/y)

clay soilsand soil

The ‘inverse texturehypothesis’ ofNoy-Meir

Slope=‘rain use efficiency’

Intercept = index of unproductive water loss

Interannual variability of grass production is higher on clays than

sandy soils

0

100

200

300

400

500

0 200 400 600 800 1000

Annual rainfall

Gra

ss A

G N

PP

(g/m

2/y)

clay soilsand soil

σclay

σsand

σrain

Rain Use Efficiency(g/m2/mm)

0

2

4

6

8

10

12

50 60 70 80 90 100

Sand %

Rai

n us

e ef

ficie

ncy

(kg/

ha/m

m)

Intercept dependent on soil water holding capacity

-3000

-2500

-2000

-1500

-1000

-500

0

500

1000

1500

2000

0 5 10 15

Rain use efficiency (kg/ha/mm)

Inte

rcep

t of A

GG

NPP

vs

Rai

n

(kg/

ha/y

)

Changes in vegetation composition(to species less productive or less useful)

Woodyplants

grass grazers

browsers

firerain

+

+

-+

--

+

+

-

Tree mass has a non-linear inverse effect on grass production

0

300

600

900

1200

0 0.2 0.4 0.6 0.8 1Fraction of maximum tree quantity

Ann

ual g

rass

abo

vegr

ound

pr

oduc

tion

(g/m

2/y)

Walker et alBealeDonaldson & KelkAucamp et al

Scholes RJ 2003 Convex relationships in ecosystems containing trees and grass. Environment and Resource Economics 26, 559-574

Graphical stability analysis

Tree cover

Gra

ss p

rodu

ctio

nLow resilience

high resilience

Open, grassy ‘parkland’

∆w=0

∆g=0

Dense tree cover thicket‘bush encroached’

Scholes RJ 2003 Convex relationships in ecosystems containing trees and grass. Environment and Resource Economics 26, 559-574

The actual tree-grass interaction is much more complex

Flame height

Supresses

Grass biomass

Flame height = f(grass fuel)

GrazersBrowsers

Fire frequencyRainfall

ReducesSlows growth

seeds

Nutrients

Relation between rainfall and quantity of trees in savannasSankaran et al 2005 Determinants of woody cover in African savannas Nature 438, 846-9

Upward shift detectedby albedo changeor phenology change

Vegetation metricsRemote sensing Ecological

SAR interferometry biomass

% cover

FAPAR NPP

ETLAI

phenology

height

Albedobasal area

NDVISIEVIetc

intra- or inter-seasonalvariability

LIDAR time-to-pulse

ecosystemtype & area

‘degradation’

‘functional’spectral reflectanceIn key bands

BDRF ‘structural’

greenessindices

‘compositional’spectral features

‘Greeness’ Vegetation Indices

eg NDVI= (Red-NIR)/(Red+NIR)and many others (SI,SAVI,EVI etc)

Wavelength (nm)400 1000

Chlorophyllabsorption

Stable reference point

Red = reflectance @ 680nmNIR = reflectance @ 900 nm

reflectance

Leaf Area Index• The one-sided leaf area per unit of ground area• Can go down to near 0 in the dry season• Theoretical limit about 6

I=I0e –K*LAI (Beer’s Law)therefore for LAI=6, k=0.5: I=5% of Io

• Hard to measure in forests due to saturation above ~ 3

• Seldom above 3 in drylands– Typically ~1 in savannas

• Useful for estimating evaporation and interception, but FPAR has fewer assumptions for modellingproductivity

FAPARFraction of Absorbed Photosynthetically-Active Radiation

intercepted by the vegetation canopy (range 0-1)

GPP= ε Σ(PAR*FPAR)

NPP=GPP-Ra

*f (stress,nutrients)

GPP = Gross Primary productivity (g/m2) (dry matter = 42% C)ε = Radiation use efficiency (gC/MJ),

species dependent (0.3-0.8 gC/MJ)NPP = Net Primary Productivity (g/m2) PAR = Photosynthetically-active radiation (400-700 nm) (W/m2)Ra = respiration by plants (~50% of GPP)

Seasonal pattern of LAI

0.0

0.5

1.0

1.5

2.0

2.5

1 2 3 4 5 6 7 8 9 10 11 12

Month of the year

Leaf

are

a in

dex

(m2/

m2)

Tree LAIGrass LAIAll LAI

wet season wet season

Skukuza30% canopy

Unscrambling the tree and grass signals

2001

28-Jul-01 16-Sep-01 5-Nov-01 25-Dec-01 13-Feb-02 4-Apr-02 24-May-02

date

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

Gre

enne

ss

2002

13-Jul-02 1-Sep-02 21-Oct-02 10-Dec-02 29-Jan-03 20-Mar-03 9-May-03 28-Jun-03

date

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

Gre

enne

ss

Conclusions• It is possible to define desertification in a

rigorous and operational way, via the concept of persistent loss of ecosystem services

• There are mechanisms by which state change in ecosystem service delivery can occur: desertification is a real and widespread phenomenon

• These should be detectable using remote sensing, but require additional non-remote sensing data (soil and rainfall), time series, and often the unmixing of the tree and grass signal