NACP meeting 2013
Tree-rings and vegetation models
Flurin Babst1,3, Ben Poulter1,2, Valerie Trouet3, Kun Tan2, Burkhard Neuwirth4,
Rob Wilson5, Marco Carrer6, Michael Grabner7, Willy Tegel8, Tom Levanic9,
Momchil Panayotov10, Carlo Urbinati11, Olivier Bouriaud12, Philippe Ciais2, David Frank1
1Swiss Federal Research
2LSCE CNRS,
Institute WSL, Switzerland
France
of Tree-ring Research, University of Arizona, USA
4DeLaWi TreeRingAnalyses, Windeck, Germany
5School of GeoSciences, University of Edinburgh, UK
6Forest Ecology Research Unit, University of Padova, Italy
3Laboratory
7Universität für
Bodenkultur Vienna, Austria
8University of Freiburg, Germany
9Slovenian Forestry Institute Ljubljana, Slovenia
10University of Forestry Sofia, Bulgaria
11Universita Politechnica delle Marche Ancona, Italy
12Forest Research and Management ICAS, Romania
Forests worldwide currently assimilate approximately 25% of the anthropogenic fossil
fuel emissions (Friedlingstein et al. 2010, Nature Geoscience).
 Understanding the climatic drivers of forest growth at a large scale.
 Empirical observations?
Nemani et al. 2003,
Science
Beer et al. 2010,
Science
2
Tree-ring data can help to:
i)
Assess the climate response of forests at large scales.
ii) Evaluate the climate sensitivity of dynamic global
vegetation models
~ 1000 sites
36 species
Common period:
1920-1970
3
Monthly climate data:
CRU 3.0, 1901-2006
Correlations between radial growth and
(Mitchell & Jones, 2005)
i) monthly temperature
ii) monthly precipitation
 Downscaled to 1 x 1 km
resolution
from previous April to current September
Pinus cembra:
Climate correlation
functions for all sites
 Basis for further analyses
temperature
precipitation
4
Self-organizing maps (SOMs) to
divide the network into clusters of
sites with similar climate responses.
SOM grid:
T signal
P signal
M signal
Babst et al. 2013, GEB
5
 Limiting factors for tree growth can be estimated
as a function of latitude and elevation (temperature)
6
T
Tree-rings
vs.
DGVMs
P
Novel application of
tree-ring data:
Large-scale validation
of vegetation models
Babst et al. 2013, GEB
7
Tan et al.
in review, ERL
temperate conifers
temperate broadleaf
boreal conifers
tree-rings
T
temperate conifers
P
model
% sites with sign. pos. correlations
boreal conifers
8
Nemani et al. 2003,
Science
Beer et al. 2010,
Science
Babst et al. 2013,
GEB
9
DGVMs show a stronger drought sensitivity than tree-rings.
Seasonality in climate response of DGVMs differs strongly from
observations.
 Lag-effects are not considered in simulations.
 Tree-ring network does not provide absolute productivity.


Outlook:
DGVMs:
- Improve seasonality and include carry-over effects
Tree-rings:
-Work towards absolute biomass increment
-Combinations with other in-situ measurements (e.g. eddy-fluxes)
10
Thank you!
11
12
13
14
All temperature and precipitation limited sites
Climate conditions (bootstrapped) leading to contemporaneous or lagged growth
extremes.
Babst et al. 2012, ERL
15