black locust ( robinia pseudacacia l. ) in austria: the...
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Black Locust (Robinia pseudacacia L.) in Austria:The Interplay of Climate, Climate Change and Range Expansion
KLEINBAUER Ingrid*#, DULLINGER Stefan*, ESSL Franz°, PETERSEIL Johannes°, ENGLISCH Thorsten#
* VINCA – Institute for Nature Conservation and Analyses, Vienna, Austria
° UBA - Federal Environment Agency, Vienna, Austria
# University of Vienna, Austria
contact: [email protected]
FIRSTThe leguminous tree black locust arrived in Europe during
the 17th century. By now it has become the most problematic introduced tree species in Austria:
threatening silvicultures as well as rare endangered plant
communities, in particular species-rich dry and semi- dry,
nutrient poor grasslands and thermophilous oak forests.
Once established population density increases rapidly
due to efficient vegetative reproduction by root suckering.
We have to identify regions and habitats at risk of becoming invaded
under a warmer climate.
THAT‘S WHY
NOW
In Austria’s pannonical East and
Southeast black locust finds
perfect conditions for establishment (See Fig. 2).
We constructed the environmental envelop for black locust in Austria, using
Generalized Linear Models (GLM, McCullagh & Nelder, 1989) to regress
several factors (Fig. 3) against presence/absence of black locust.
Occurrence data was extracted from the “Mapping the Flora of Austria”
database: for each cell (3’ x 5’) in a raster - covering the whole country - the
BUT HOW?
But: is it really the temperature
that limits its spread?
And: what happens if climate
change forecasts come true
and temperatures rise? Fig. 3: Predictors used in the model
status of black locust is known
(see Fig. 2)
In a stepwise backward
selection (p<0.05) the following
factors were chosen as best predictors (see Fig. 3):
• mean April temperature
• mean winter precipitation
sums
• mean number of frost days
• land use index
• curvatur index
© Franz Essl
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NEXT STEPS
To account for differences in recruitment success
• in different habitat types +
• along a temperature gradient +
• under increased Nitrogen availability +
• and facing a competitor (native Quercus petraea) …
… we started a field experiment in late spring 2006 to test for
germination success and survival (see Fig. 6 and 7)The experiment will be finished by the end of 2008.
Fig. 6: Experimental Design
+N +N +N
Forest Bare Soil Grasslandlocations withineach study-site:
plots: 1 withand 1 without N added(within each location)
4 different study-sites covering a temperature (T) gradient
from about 6 – 10°C
Fig. 7: plots in different habitat types
forest bare soil grassland
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Fig. 2: Occurrences of Robinia pseudacacia
in Austria (source: Niklfeld, 1998)
Austrian Academy
of Sciences
McCullagh, P. & Nelder, J.A. 1989: Generalized Linear Models. New York, Chapman & Hall
Niklfeld, H. 1998: Mapping the flora of Austria and the eastern Alps. - Rev. Valdôt. Hist. Nat. 51, Suppl.: 53-62.
Pope, V. D., M. L. Gallani, P. R. Rowntree and R. A. Stratton, 2000: The impact of new physical parametrizations in the Hadley Centre climate model -- HadAM3.
Climate Dynamics, 16: 123-146Jacob et al., 2005: unpublished report within the EU-project prudence - Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate
change risks and Effects
REFERENCES:
FINANCIALSUPPORT BY:
THENMean April temperature and mean winter precipitation were
recalculated using two different climate change scenarios for the
end of the current century: 1) HadAM3 from the IPCC (Pope et
al.,2000) and 2) a regionalized model from ETH Zurich (Jacob et al.,
2005), CH, which has been downscaled for the whole Alpine region. Please see Fig. 4 and 5 for details in changes and comparison of
climate change scenarios.
Habitat Suitability Classes - Current Climate
Proportion of Area (%)
23,83
8,16
5,2910,98
51,75
not suitable bad good very good optimal
Habitat Suitability Classes - ETH scenario
Proportion of Area (%)
15,07
8,25
4,08
6,6865,93
not suitable bad good very good optimal
Habitat Suitability Classes - HadAM3 scenario
Proportion of Area (%)
77,65
5,74
4,447,494,68
not suitable bad good very good optimal
Fig. 5: Habitat Suitablility Classes and their area proportion Fig. 4: Distribution of potential habitats for Robinia pseudacacia in Austria
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The bootstrap-corrected final model’s regression coefficient R² is 0,71 and Somer’s index (Dxy) is 0,89.
mean April temperature
curvatur index number of frost days
land cover index winter precipitation sums
mean April temperature
curvatur index number of frost days
land cover index winter precipitation sums