CAMELEON- Carbon Dynamics in Mountain Ecosystems: analyzing landscape-scale effects of anthropogenic changes (climate and land-use)

CArbon dynamics in Mountain Ecosystems:
analyzing Landscape-scale
Effects Of aNthropogenic changes (climate and land use)

Main scientific question addressed
What are the impacts of changing land use and
climate on the carbon cycle and grassland
management of mountain landscapes?
CIRCLE MOUNTAIN final meeting, Barcelona 26 & 27 September 2013

project objectives
• Compile a unique database on climate, land cover,
land use, carbon and ecological data for three
contrasted mountain regions.
• Use information to improve representation of alpine
systems in a DGVM model
• Use the improved model to attribute the role of
climate, elevated CO2 and land use in past/present
and future changes in mountain systems (focus on
carbon cycle).
• Use the model to estimate possible adaptation of
grassland systems to climate and land use change

challenges
• Synthesizing available data at plant, ecosystem
and landscape level
• Upscaling process-based ecosystem information
to larger spatial and temporal scales
• Implementing fine-scale grassland processes in
global biogeochemical model (ORCHIDEE)
• Integrating natural sciences with stakeholder
perceptions and disseminating scenarios of C
dynamics across European mountain regions

5 partners
• LSCE (France)
• NOVELTIS (France)
• Zone Atelier Alpes (France)
• University of Innsbruck UIBK (Austria)
• CTFC (Spain)

3 regions
Stubai Valley
Alinya valley
Vercors Plateau

Data Synthesis

Land cover mapping
Historical period: based on photointerpretation
of aerial and remote sensing data (3 to 5 dates
been used).
Future: several scenarios, based on different
climate change and local socio-economic
constraints. Directly discussed with local
stakeholders

• For future projection, available for Stubai and
Vercors. Based on slighly different methods:
– Stubai: direct discussion with stakeholders
presenting socio-economic and climate projection
– Vercors: automatic projection for past as basis for
discussion with stakeholder to define the
scenarios.
But conduct to similar kind of scenarios at the end
(i.e business as usual or reverse trend).
Land cover mapping: future

1. Partitioning 1692 available vegetation
releves into k clusters
2. Listing the dominant plant
species of each cluster
3. Checking trait availability
in local or global DBs
4. Calculating
Community Weighted
Means and s.d. for key
traits
Synthesis and upscaling of functionnal diversity
5. Intra community
s.d for key traits

Remote sensing
• Compilation of existing remote sensing data, MODIS, SPOT-VGT
• Processing and selection of the most relevant datasets

Climate data
combination between ERA-WATCH/ECHAM A1B
scenario (0.25°, daily) and WORDCLIM (1km)
climatology
1950 2100
Statistical
downscaling
Era-watch +remo A1b
0.25°
1950
2100
Worldclim T,P 1km
climatology
Eraworldc daily 1km data

• Mainly compilation of existing flux
measurements from Alinya and Stubai +
management data
In situ carbon data

Main results

Statistical
model
of FI change
FIij = a0i + a1i YEARij + eij
a0i = b00 + b01 ELEVi + u0i
a1i = b10 + b11 ELEVi + u1i
Modeling land cover dynamics

• In-situ flux measurement and remote sensing
was used to evaluate and calibrate ORCHIDEE.
• Optimisation is based on 4D-VAR assimilation
system of ORCHIDEE (ORCHIS).
• Assimilation based on:
- Remote sensing data to optimize phenological
parameters
- Eddy fluxes for optimization of phosynthesis
etc…
Calibration/evaluation of ORCHIDEE

Example anomaly of vegetation onset
Onset anomaly from remote sensing
(Stubai)
Onset anomaly from ORCHIDEE
(Stubai)

Improvement of anomaly estimation
after assimilation
Correlation NDVI/model
Stubai
Correlation NDVI/model
Vercors
Prior Posterior

Comparison with eddy fluxes
Gross Primary production Ecosystem respiration Net carbon exchange
Stubai
Alinya
Obs
Model

Impact of functional diversity on carbon
cycle
Vercors Stubai Alinya
Simuled variabiliy of net primary production for each vegetation class
Estimated community weighed mean and variation of Vcmax for each vegetation class
Vercors Stubai Alinya

• Series of Simulations at regional scale to
understand role of climate and land use
change in the past and for future projection.
• Some parameters fixed whereas others are
varying
Attribution studies at regional scale

Climate change for the 3 sites
Stubai Vercors Alinya
Temp.
Rainfall

Historical land use change for the 3 sites
Stubai Vercors Alinya
Bare soil
Grassland
Forest

Future land use change

Present net primary productivity
Alinya Stubai Vercors

GPP
Ecosystem
respiration
Net carbon
exchange
Evolution of carbon fluxes
past/present/future
Stubai Vercors

Alinya
Attribution of carbon fluxes changes (present)
GPP Ecosystem respiration Net carbon exchange

Attribution of carbon fluxes changes (future)
GPP Ecosystem respiration Net carbon exchange
Alinya

• ORCHIDEE-GM is able to calculate an optimum
animal density assuming a close system where
grassland is separated between pure grazing/cut
system, and autosufficient system
• Algorithm has been adapted to take into account
for the 3 sites systems:
– Stubai and Alinya: evaluation at the whole region
instead of pixel based assumption.
– Vercors: take into account for transhumance: we
consider animal at Vercors in summer and in Crau
during winter (i.e different climate change…)
Evolution of sustainable animal density

Evolution of mean sustainable animal density
Stubai
Alinya
Large increase of animal density for Stubai, but stabilitation even small decrease after
2060 for Alinya

Attribution of climate and land use to change in
animal density
Stubai Vercors
Change in fraction
between int/ext
grassland has a large
impact on
animal density for
Stubai
Limited productivity
In Crau does not allow
To fully benefit for
Increase of grassland
Surface in Vercors

• ORCHIDEE after calibration have shown a
good ability to simulate the mountains
ecosystems.
• Land use change: 3 sites shown a similar trend
for reforestation for the past, the trend been
more important for Vercors, contrasted
response for future depending from the
scenario
Main conclusions

• Climate change:
– Increase of temperature (mainly after 1980)
– Contrasted response for precipitation between
Stubai and Alinya
Consequence for production and carbon
storage:
– temperature is the main driver in contrast to plain
regions
– High increase for Stubai, Vercors, less for Alinya
Conclusion (2)

Consequence for grassland management:
– possible increase of animal density, especially for Stubai.
But more limited even reversed for Alinya, limited by Crau
production for Vercors
But could be too optimistic because:
– Two high response of ORCHIDEE to CO2 ?
– moderate A1B scenario used
– Increase of interannual variability
Conclusion (3)
The story is not finish ! CAMELEON created a momentun between the
groups that will continue …..

CAMELEON- Carbon Dynamics in Mountain Ecosystems: analyzing landscape-scale effects of anthropogenic changes (climate and land-use)

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CAMELEON- Carbon Dynamics in Mountain Ecosystems: analyzing landscape-scale effects of anthropogenic changes (climate and land-use)