Sandra LAVOREL Laboratoire d’Ecologie Alpine, CNRS ...Sandra LAVOREL Laboratoire d’Ecologie...

Biodiversity in a changing world : land use and other effects on landscape and

regional diversity

Sandra LAVORELLaboratoire d’Ecologie Alpine, CNRS

Grenoble, FRANCE

Lecture outline

• Global change effects on biodiversity– Some observations – biodiversity change under our eyes– Projecting climate change effects on plant distributions– Projecting land use change effects on biodiversity

• Plant functional approaches: concepts and methodologies• Projecting land use change effects on plant diversity and

ecosystems• Assessing consequences for ecosystem service delivery

A discernible « fingerprint » of climate change effectson species distributions and phenology

Type of change Changed as predicted Changed opposite to prediction

Phenological 87% 13%

Distributional changes

At poleward/upper range boundaries 81% 19%

At equatorial/lower range boundaries 75% 25%

Community (abundance) changes

Cold-adapted species 74% 26%

Warm-adapted species 91% 9%

Overall 81% 19%

Meta-analyses

Range-boundaries 6.1 km / m per decade northward/upward shift

Phenologies 2.3 days per decade advancement

Parmesan & Yoh 2003

Under our eyes: changes in biodiversity in response to climate change

Invasion by warm-climate plants

Num

bero

f spe

cies

19001980

2003

Species colonization on high summits

A first methodology: expert opinion

1 = land use, 2 = climate, 3 = N deposition,4 = invasions, 5 = CO2 (Sala et al. 2000)

Sala et al. 2000

Expert opinion points to land use as the public enemy

Population: the public enemy

Cincotta et al. 2000

High population density in biodiv hotspots and effects of increasing numbers of small households

Observed land use effects on biodiversity

Warren et al. Nature 2001

British butterfly speciesBlack circle: climate suitable, presentRed circle: climate suitable, absentBlue circle: climate unsuitable, present

Landscape fragmentation impedes climate response;species-specific responses

Historic

migration

Methodologies to project diversity responseto global change

• Niche based modelling• More statistical models: habitat change and species-area• Modelling species distributions based on plant traits

Methodologies to project diversity response to climate change:

Niche-based modelling

Occurrence points

Current range prediction

Future range prediction

Projection back into geographicalspace

Water availability

Deg

ree-

days

Model of niche in ecological dimension

Ecological niche modelling

Geographic space Ecological space

Niche-based modelling of species distributions

Current distribution Environmental variables

Models

Response curves

Realised nicheSimulated current

distribution

Climate change scenarios

Niche-based models

Potentialrealised niche

Futur potential habitats0 200 400 600 800

0.0

0.2

0.4

0.6

0.8

1.0

Winter precipitation

Pro

babi

lité

de p

rése

nce

Pro

babi

lity

of p

rese

nce

Winter precipitation

Growing Degree D

ays

Moi

stur

e In

dex

Simulated distribution

Castanea sativa

Futurs suitable

climatic space

• Data adequate (species distribution and environmental variables)

• Environmental variables control geographic range limits

• Statistical methods detect correct relationships

• Climate and LU will change as predicted…

• … and the same species-environment relationships will hold (no plasticity or genetic adaptation)

• Niche conservatism

Niche-based models

Primary assumptions

2,3 – 18,2Max CC

2,9 – 16,3Mean CC

2,0 – 15,1Min CC

Extinction rates

Extinction risks for:

1350 species, 8 models

3 CC scénarios

8 fold!!

- Compiling of 18 distinct analyses- Different spatial scales- Different niche-based models- Different environmental variables

- Different climate change scenarios

Production species and aesthetic value: Larch (Larix decidua)

‘Economic’ scenario 2080

‘Environmental’scenario 2080

Conserving Europe’s natural capitalCommitments for biodiversity under Natura 2000

Pulsatilla alpina Aquilegia alpina

Impact on plant species richness

2080 - A1 HadCM3

Future – present richness

Method: Aggregating individual species responses to projectchanges in species diversity

Relative sensitivity of plant biodiversityto climate change (2080)

Mountain and mediterranean regions are the most threatenedregions in Europe

In mountains greatestchanges are expected atintermediate altitudes (e.g. Prealps)

Modelling effects of land use on biodiversityThe Millennium Ecosystem Assessment:

habitat change and species-area

S = CA z

Habitat availability

Estimated species loss

Biome-specificspecies-area relationship

Sala et al. 2005 MA

Effects of land use change on biodiversityMillennium Ecosystem Assessment projections

Including effects of climate changeand N deposition

Sala et al. 2005 MA

Relative sensitivity of different biomes to different factors

Sala et al. 2005 MA

Bringing some biology into models:Modelling species distributions

based on plant traits

Plant functional traits

• A tool to reduce the complexity of life…• A functional rather than taxonomic perspective

– Groups of species or populations• with a similar RESPONSE to environmental change• and/or similar effects on ecosystem function…

– … as a result of shared characters– Functional traits:

• morphology, ecophysiology, demography, biochemistry

Diaz (2001)

Wright et al. Science 2004

Nitroge

n conte

nt

Leaf mass area

Phot

osyn

thet

icra

te

2550 species175 sites

‘The world wide spectrum of leaf economy’

Traits as markers of plant function

Density, diameterSpecific root length

Absorption (nutrients, water)Carbon fluxes (exsudation…)

Plant canopy heightOther?

Light interceptionCompetitive ability

Soft trait

Seed massSeed characteristics

Function

FecundityDispersalEstablishment

Resorption of nutrients;decomposability of litter

Traits of living leavesNIRS spectrum; other?

Traits for ‘easy’ measurement on large numbers of species in the field

Towards a short (?) list of soft traits

Cornelissen et al. 2003 Aus. J. Bot

Leaf area on an aridity gradient: Functional trade-off between stress tolerance and productivity for leafdesign

Predictive value for regionaldistributions and climate response

Thuiller et al. 2004 Ecology

Effects of traits on species distributionsDistribution along regional climatic gradients

88 Leucadendron species in a 1x1 km grid

Leaf area (log)

OM

I axi

s1

2.0 2.5 3.0 3.5 4.0 4.5

-2-1

01

23

Arid

itygr

adie

nt

Leaf area (log)

Species niche position on the aridity gradient

Trait responses to climate at the global scale

Wright et al. 2005 GEB

RadiationRai

nfal

l

Leaf

N

Consistent average relationship :

=> selective pressures associated with adaptation to different climatic regimes.

High local variability

Using plant traits to model species distributions and diversity at the global scale

Plant Functional Groups to projectvegetation distributions at global scales

Neilson et al. 2005

Simulating species diversity based on traits

Kleidon & Mooney GCB 2000

Plant traits to explain community distributions within landscapes:

Projecting land use change effects on plant diversity and ecosystems

Explaining community distributionsusing plant traits:Methodology

• Community responses to environmental gradients– Changes in species composition– and/or changes in species traits– determine changes in community-level ‘aggregated traits’

∑=

=n

iiiagg traitptrait

1

*

calculated for species whose cumulated biomass represents at least 80% of the community maximum standing biomass

Biomass ratio hypothesis (Grime 1998): species effects on ecosystemsare proportional to their relative abundance.

Relative contribution of species i to the maximum biomass of the community

Trait value of species i

Garnier et al. 2004

FP5 VISTA

Vulnerability of Ecosystem Services to Land Use Change in Traditional Agricultural Landscapes

11 sites in 9 countries…in marginal agricultural areassubjected to rapid change:

decreased management intensityabandonment

VISTA sites: a climate gradient across Europe

Aridity

Israel

Garnier et al . 2007 Ann. Bot.

Rai

nx

Tem

p.

Cold when it rains

Mild temp. + high rainfall

Variation in Leaf Dry Matter Content with climate

Mean annual site temperature (°C)

0 5 10 15 20 25

Ave

rag

e si

te L

DM

C (

mg

g-1

)

180

200

220

240

260

280

300

320

340

r = - 0.63*

Aggregated LDMC per site

Same correlations than at species level (Wright et al. 2005)

Colder sites hard more ‘dense’ leaves

=> prevalence of more annual species (with lower LDMC) at warmer (e.g. Mediterranean-climate) sites

LDMC: ratio dry to fresh mass of leaves => density in structural tissue

Response of community-level LDMCto decreasing land use

Wald statistic = 8.45, P < 0.001

Increase in LDMC in response to less intensive land use

Strongest at the warmest sites

Decreasing Mean Annual Temperature

Garnier et al . 2007 Ann. Bot.

Extensive use

Intensive use

Trait responses to decreasing land use:Generalizable across VISTA sites

Extensification promotesplants that conserve mineral

resources

Extensification promotes tall plants

Site Trait VPH RPH Flowers Seed M SLA LDMC LNC LCC LPC St DMC Clonality France mon ** m m m ** *** * NS * *** Scotland NS NS * ** * * NS NS NS Germany *** *** NS * * *** *** NS France Pyr * NS ** NS * ** Portugal *** m m *** *** NS *** m m Greece NS * ** NS ** m * NS *** * * Sweden * * *** NS NS ** NS NS NS ** * Norway ** ** ** ** Czech ** ** NS * * NS Israel ** NS NS NS NS France Alp *** ** NS * *** *** *** *** *** *** *** m = marginally sig.

Soil covariates: These trait responses to land use result from declining fertility

Garnier et al . 2007 Ann. Bot.

From plant traits to ecosystem functioning

PFT to scale from communities to ecosystems

?

Environmentalchanges

Responsetraits

Communitystructure and

diversity

Effecttraits

EcosystemfunctioningChallenge:

Linking responseand effects

Chapin et al. Nature 2000Lavorel & Garnier Funct. Ecol. 2002

Effects of plant traits on ecosystem properties:

(-) land use: P < 0.001 (-) LDMC: P < 0.001Land use x LDMC: P = 0.007Land use effects greatest at sites with highest LDMC

Garnier et al . 2007 Ann. Bot.

Effects of community LDMC on litter pools

Accu

mul

ated

litte

r

Litter decomposability in vitro:relationship with LDMC

r = -0.56***(n = 105)

LDMC aggregated (mg g-1)

0 100 200 300 400 500 600

Lit

ter

dec

ay r

ate

(g k

g-1

d-1

)

0

5

10

15

20

Sweden

Israel

Fortunel et al. In prep.

Without climate/land use/soil effects

=> litter with higher LDMC decomposes less well

VISTA: Putting the picture together

Decreasingland use

Increasing LDMC

Decreasingdecomposition

Litteraccumulation

Declining fertility

=> Chain of correlation (hopefully causality) and feedbacks

Soil C:N

Nitrogen NI

P Olsen

SLA

LNC

LPC

LDMC

P NI

Land use

Litter

Max Biomass

Decomposition

Linking land use effects on soils,plant traits and ecosystem properties

Lavorel et al. unpublished

Soil Phosphorous Content

Phosphorous available for plant

Leaf phosphorous content

Nitrogen available for plant

Modelling changes in landscapes and ecosystem properties in response to land use

change1920

2003

?2050

Modelling dynamics at the landscape scale

4 PFTs represented by 4 dominant grass species: Festuca paniculata, Sesleria caerulea, Bromus erectus & Dactylis glomerata

Landscape modelling plateform LAMOS

Parameters estimated through experiments and field observations

Validated using historical land use data:Calibration under past conditions and simulation/validation under current conditions

Fertility

UnploughedPloughed

Mowing

No mowing

Limited recruitment of Festucapaniculata

A1

A1

21A3

C1C2

C2 C2

3b1A3

C2 C2C2C2

C2B1A2A3

B1

B2

B2

C1 C1

C2

A1

A3

A3

A2A2

Festuca density

Fertility

Landscape dynamics modelling using LAMOSValidation against field data

LAMOS

F. Quétier et al. subm.

Projecting scenario impacts using LAMOS

Initial Sesleria PFT abundance

Initial Festuca PFT abundance

Sesleria PFT abundance under A1 scenario

Festuca PFT abundance under A1 scenario

Projecting effects on ecosystem services

Stakeholders

Ecosystemservices

Ecosystemdescriptors

Ecosystemproperties

Plant traits

Scientists

Landscape model

Ecosystem services identified by stakeholdersand proxies to quantify them

Quétier et al. submitted

Statistical relationships between functionalcomposition and ecosystem properties

Quétier et al. submitted

Scenario projections of ecosystem services

Quétier et al. submitted

Main take home messages

• Different modelling tools can be applied to project changes in biodiversity– Conceptual models: e.g. Plant Functional Traits– Statistical models: e.g. niche-based models, trait-ecosystem– Dynamic models: e.g. landscape-scale models

• These need to be based on solid data bases and experimental data

Strong links between modellers and field ecologists

Do not forget: this is not reality, models are tools to understand the present and analyze the future!

Geographic distribution of different types of extinction risk

93% species will have overlapping distributions

2% will not have overlappingdistributions

5% will lose their habitat entirely

Study site: Lautaret south facing slopes

A changing land use

A well known site

Few trees by now

Will land use change affect the dynamic and colonization of trees in the study area?

Cotoneasterjuranus

SorbusaucupariaLarix

decidua L.Rosa

glauca/pendulina

Sambucusracemosus

Prunus padus

Tree colonization in mountain landscape

Absence Increasing Probability of presence

South facing grasslands of Villar d’Arêne are potentially suitable for Larix decidua

Ecological niche-based modelling

Several parameters required for each PFTMost found in literature: life span, maturation time, potential seed productivity, ....

Larix produces seeds every 10 years

Germination rate at different light level was determined with experiments

5 light levels 3 light types (L, V, A) 2 water levels50 seeds per treatment

Some sensitive parameters stay Unknown: we tested them with simulations

Tree PFT: Larix decidua

litter shadow (L) / plant shadow(V) / artificial shadow(A)

germination rate in different light and water treatment

0

0,2

0,4

0,6

0,8

1

1,2

100 A36 V35 A26 A10 L7 V5 L1 V0,1 L0 A0

light and water treatment

ger

min

atio

n r

ate

water

no water

LIGHTGERMINATION

Tree dynamics at landscape scale

Simulations with Lamos

Dispersal capacity Plant ability for resource uptake Interaction of seedlings and juveniles with resident vegetation

Are expected to affect the tree line response to a changing environment

Use of a factorial design combining:

- 2 dispersal modes: Long distance dispersal vs No long distance dispersal

- 2 resource uptakes: Large vs narrow niche breadth for productivity

- 2 juvenile responses to light competition: shade tolerant vs shade intolerant

- 3 types of disturbance: Early mowing / late mowing / no mowing

on a complex productivity gradient

24 simulations

Tree dynamics at landscape scale

3 types of response:

- A complete colonization(100 trees by pixel ~ ha)

- A colonization by patches

- No real colonization (a few trees everywhere) others

Results

Few treesPatchesColonized

Tree dynamics at landscape scale

No real effect of land use disturbance

No real impact on grassland composition

• Long distance dispersal• Large niche breadth for productivity• Shade tolerant Juveniles

Shade tolerant juveniles

Narrow niche breadth patches on high productive soil

Large niche breadth limited by dispersal