Climphen

Abk.

CLIMPHEN

Themenbereich

Phänologie, Österreich Klimawandel

Status

abgeschlossen

Zusammenfassung

Phänologie: Beobachtung der Eintrittszeitpunkte des Blühens von Pflanzen
© ZAMG

Der Klimawirkungsforschung ist es während der letzten Jahre gelungen, die Phänologie aus ihrem Dornröschenschlaf aufzuwecken und ihren Aussagen zum Einfluss der Klimavariabilität auf Erscheinungen in der belebten und unbelebten Welt einen hohen Stellenwert zuzuordnen.

Dieses Projekt hat sich zum Ziel gesetzt, die österreichischen Phänologiedaten möglichst umfassend in Hinsicht auf die Problematik der Klimawirkung auszuwerten. In diesem Umfang ist das bisher nicht geschehen. Der phänologische Datensatz der ZAMG weist einige Merkmale auf, die einmalig sind, wie zum Beispiel die große Zahl von beobachteten Phasen (244, von denen etwa 50 bis 100, je nach Zeitabschnitt, zu verwerten sind), die kontinuierlich seit 1951 im alpinen Raum (mit Stationshöhen von 150 m bis über 1400 m MSL) beobachtet und gesammelt werden. Die Alpen gelten klimatisch als besonders sensibel.

Folgende Themen werden behandelt: der Einfluss der komplexen Topographie der Alpen auf die phänologischen Eintrittsdaten; die Steuerung der Eintrittsdaten durch die Temperatur; der zeitliche Trend der Eintrittsdaten und der dazugehörigen Temperatur über den Zeitraum von 1951 – 2005; in welchem Ausmaß sich die phänologischen Eintrittsdaten in einem wärmeren Klima nach hinten verschieben, wie es durch Modellszenarien vorgegeben wird. Ein besonderer Punkt dieses Projektes ist die Studie der Beziehung zwischen dem Temperaturtrend und dem Trend langjähriger Maikäferflugdaten in Zusammenarbeit mit der Österreichischen Agentur für Gesundheit und Ernährungssicherheit.

Ausgangssituation

Within the last decade the scientific community’s view of phenology as a harmless pastime of natural historians has changed dramatically, because the value of phenological data in climate change research has been recognised. Faced with the prospect of a possible global warming, information is needed about how natural systems may respond to a warming climate. The study of the observed response to the warming during the last 4 to 5 decades may provide a hint on a possible future response. An increasing number of studies report that plants and animals of the mid- and higher latitudes of the northern hemisphere have been responding to the temperature increase of the last decades (Walther et al., 2002; Root et al., 2003; Parmesan and Yohe, 2003).

More specifically most phenological data sets reveal an advancing of flowering and leaf unfolding in Europe and North America by 1.2 to 3.8 days/decade, a delay of autumn phases by about 0.3 to 1.6 days/decade, which results in a lengthening of the vegetation period by about 1.5 to 5.2 days/decade during the last 40 to 50 years (Menzel, 2002). In Western Europe a shift to earlier first and peak appearances of butterflies have been recorded and flight periods have been lengthened in multi-brooded species. Bird migration timing and breeding times in Europe and North America have been responding to changes in temperature, predominantly shifting towards earlier dates in spring (Sparks and Menzel, 2002).

There are at least 3 factors stressing the importance of the study of Austrian phenological time series:
In contrast to the 0.6°C rise of the global mean temperature over the last 100 years, the temperature has risen more than twice the global rate in the Alpine area (about 1.5°C; TAR, 2001; Böhm et al., 2002).

In the Austrian part of this temperature sensitive area of the Alps a phenological data set has been systematically collected since 1951, which allows for a climate response study of phenological phases.

The integral analysis of plant and insect phenological observations offers the unique opportunity to compare their respective trends and get an indication of possible changes in synchronies or asynchronies in the food chain.

Projektziele

Objective 1. Spatial analysis

Based on the long term mean values of plant and insect phenological phases the speed with which the phenological phases progress across the area spanned by the stations in North - South, East – West direction and as a function of altitude will be investigated. A link with the spring warming of the European continent is to be established.
Austria’s complex topography causes local peculiarities of the climate, which in tern influence the spatial distribution of phenological occurrence dates. The spatial residual pattern of the multiple regression (phenological occurrence dates as function of station longitude, latitude and altitude) will be searched for patterns, which can be interpreted as a result of a topographical modulation of the local climate. Such patterns are to be searched for also in the temperature data set.
In case of all phenological plant and insect phases, where the multiple regression model can explain a large fraction of the spatial variance (say > 70%), maps of long term mean phenological occurrence dates will be drawn. In case residual patterns are meaningful, they will be used to enhance the quality of the spatial interpolation.
Spatial temperature sensitivity: The spatial distribution of long term mean occurrence dates of the phenological phases will be interpreted as function of temperature (days/°C).

Objective 2. Combined spatial and temporal analysis
Phenological and temperature time series will be used in 3 forms: as raw time series with their year-to-year variability and as smoothed and detrended time series to study the decadal variability and as linear trends of the time series.

Temporal temperature sensitivity: The correlation between temperature and phenological time series is to be investigated (year-to-year variability, decadal variability) as function of space.
Trend sensitivity: The linear trends of phenological phases and temperature are to be compared also as function of space. It has to be seen, if the phenological occurrence dates have remained at an earlier level since the discontinuity in 1989.

Objective 3. Contradicting trends of temperature and insect phases
Although temperature appears to govern the occurrence dates of the first insects, the linear trend of the insect phases generally show the opposite sign of the temperature trends in spring. Possible causes for that contradiction have to be searched for.

Objective 4. Phenology and future climate scenarios
An appropriate CCA model will be developed for each phenological phase, validated and applied to at least two current climate scenarios. Maps of changes in phenological occurrence dates in potential future climate scenarios are to be drawn.

trend towards later arrival times can be explained by that factor.

Methodik

Following procedures will be applied to achieve the above mentioned objectives:

Multiple regression models will be the tools to investigate the spatial relationships and to produce the phenological maps. Height detrended inverse distance weighting is the spatial interpolation method in case there are regular residual patterns. Maps will be drawn with a GIS.
Temporal variability will be studied with raw, smoothed (Gaussian low pass filter) and detrended time series and with the linear trends of the time series. Trend matrices support the trend analysis (Scheifinger et al., 2002, Fig. 9).
The Canonical Correlation Analysis of Empirical Orthogonal Functions has already been successfully applied to phenological data (Matulla et al., 2003). This method is the basis for the work of Objective 4 (Phenology and future climate scenarios).

Abwicklung

AUSTRIAN ACADEMY OF SCIENCES Research Programme Global Change und Austrian Federal Minestry of Agriculture, Forestry, Environment and Water Management (UW.1.3.2/0377-V/4/2005).

Ergebnisse

Beginn der Blüte des Schneeglöckchens

Räumliche Verteilung der mittleren Eintrittsdaten für die Phase ‘Beginn der Blüte des Schneeglöckchens’. Die Beobachtungen stammen aus dem Zeitraum 1951 – 2005. Das mittlere Blühdatum ist als Jahrtag angegeben, der vom 1. Jänner weg gezählt wird. Höhen über 1500 m sind weiß gelassen.

Spatial distribution of the mean entry dates of ‘Snow drop beginning of flowering’. The phonological observations span the time period from 1951 – 2005. The mean flowering date is given as year day, which is counted from the 1st January. Elevations higher than 1500 m are left white.

Endbericht

Projektbeginn

05.2005

Projektende

04.2007

Projektteam

Ansprechpartner	Abteilung	Fachgebiet	E-Mail	Telefon
Koch Elisabeth Dr.	Fachabteilung Klima	Leitung		+43 1 36026 2201
Scheifinger Helfried Dr.	ZAMG Wien/UMW	Global Atmosphere Watch		+43 1 36026 2410

Publikationen

Scheifinger, H., Koch, E. & Winkler, H. (2005): Arrival Dates of migrating Birds in Austria and Climate Variability. Annalen der Meteorologie 41, Vl 2, DWD, 2005.

Scheifinger, H., Koch, E. & Winkler, H. (2007): Erste Ergebnisse einer Analyse vogelphänologischer Beobachtungen der Zentralanstalt für Meteorologie und Geodynamik 1951-1999 in Österreich. promet 33: 1/2, 52-55

Scheifinger, H., E.Koch, P.Cate, C.Matulla: CLIMPHEN – a comprehensive analysis of Austria’s plant and insect phenological observations 1951-2005. 02-07 April 2006, Vienna, Proceedings of EGU general assembly

H. Scheifinger, E. Koch, P. Cate and C. Matulla: The spatial gradient law of phenology proposed, CLIMPHEN - a comprehensive analysis of Austria's plant and insect phenological observations.. N.R. Dalezios, S. Tzortzios (eds) HAICTA 2006 Conference 20-23/09/2006, Vol III, Volos). ISBN 960-8029-45-7

Scheifinger, H, E. Koch, P. Cate and C. Matulla (2007): New frontiers in plant phenological research. Oxley, L. and Kulasiri, D. (eds) MODSIM 2007 International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2007, pp. 497-503

Website

http://www.oeaw.ac.at/deutsch/forschung/programme/change.html