Download Arctic oscillation

Climate Change has
affected biological systems already
Walther et al. Nature 2002
CCIOB
or
Climate Change Impacts on Birds
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Evidence for impacts – global reviews (you saw one
example already)
Funding and organisation of the project
Cooperation
Climate Change Background
Climate Change Scenarios
Main questions
Our approaches
Future
Why study Climate Change
Impacts in Finland – benefits?
Northern Dimension
• Higher proportion of migratory species
• More clear definition of migration
• Migrants from fewer populations and closer to goal
• More borders of distribution areas
• Stronger expected impacts
• Hence, larger expected effect sizes of responses
• Plenty of data for analysis
Climate Change Impacts on Birds –
funding and staff
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Project funded by
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Academy of Finland
Maj and Tor Nessling Foundation
Kone Foundation
Period 2001-2004, hopefully longer
Staff
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Leader Esa Lehikoinen
Post doc Toni Laaksonen
Postgraduate Kalle Rainio
Postgraduate Markus Ahola
MSc thesis finished Katja Sippola
Sources of CC background data
weather data and scenarios
– publicly available from centers of CC research
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http://www.met-office.gov.uk/research/hadleycentre/
HADLEY CENTRE
GREAT BRITAIN
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http://www.ipcc.ch/ INTERGOVERNMENTAL PANEL FOR CLIMATE CHANGE
http://www.knmi.nl/samenw/eca/htmls/index5.html EUROPEAN CLIMATE
ASSESSMENT & DATASET (ECA&D)
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and nationally: agreement for scientific cooperation with http://www.fmi.fi
FINNISH METEOROLOGICAL INSTITUTE
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For public information concerning Climate and its change, look at:
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http://www.ilmasto.org/index.htm
Bird data
Response variable group
Timing of migration
Timing of breeding
Timing of moult
Integrated research of the annual
schedule
Changes in population sizes
Changes in distributions
Data type available
Phenological projects 1749Bird stations 1970Nest card schemes 1941Moult inquiry 1968-
Census programs 1941Winter Birds Census 1957Atlas projects 1974-1989
earlier and later zoogeographical
information
Cooperation
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National
– Hanko and Jurmo bird stations
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Anssi Vähätalo, Aleksi Lehikoinen
Natural History Musem of Helsinki University
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Risto A. Väisänen, Juhani Terhivuo, Jari Valkama
Finnish Meteorological Institute
International
– Institut für Vogelforschung - Vogelwarte Helgoland/Institute of Avian Research,
Germany
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Centre for Ecology and Hydrology (CEH)/Institute for Terrestrial Ecology (ITE),
Great Britain
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Franz Bairlein, Ommo Hüppop
Tim Sparks
and others (Lithuania, France, Denmark)
Main questions
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Confirmation of impacts already connected with Climate Change
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What is the relative role of CC in...
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habitat change, other human impacts
How impacts on different traits are intercorrelated
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timing changes of the phases of the annual cycle
changes of numbers
changes of distributions
Which other factors contribute
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quality assurance of data
validity of methods and realism of models used
quantification of changes (degree of response/year, degree of response/°C)
correlations between changes of different events of the annual cycle
indirect impacts on fitness traits: mismatches
community reorganisation
Making predictive models
Climate Background
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Global Climate System
Oscillations: El Niño (ENSO), AO, NAO, PDO
Climate Change:
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including the idea that present day climate is
changing due to human impact on Global Climate
System
very long term oscillations (Ice Age ”cycles”)
North Atlantic Oscillation –
NAO index
• calculated from the pressure difference between Iceland low and
Azorean high (PC I from values of several meteorological stations)
• available back to 1821
• high values – warm and rainy winters in W Europe
Temperature variation North of 60 °N
Spatial, periodical and
seasonal variability of CC
winter
Fennoscand
ia
spring
summer
autumn
1900-45
1945-65
1966-2001
Predictions of five models
of future change in Ta
60-90 °N
global
Impacts on birds
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Changes of
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arrival time of migrants ***strong evidence
departure time of migrants *weak evidence
of breeding time ** medium evidence
of breeding performance *weak evidence
mismatch of food availability and breeding *weak evidence
overwinter survival in sedentary species *weak evidence
numbers (increase/decrease) *weak evidence
distributions: northern and/or southern borders *weak evidence
Our project’s recent activities
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Congresses and workshops:
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Freising 2000 International Phenology Network
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before start of the project
Cambridge 2002 IPN Impacts on Birds, specialist
workshop
Konstanz 2003 ESF BIRD workshop on Climate
Change Impacts
Chemnitz 2003 EOU meeting, session on climate
change impacts on birds
Project’s recent activities:
publications/manuscripts/drafts…
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7.
Lehikoinen, E., Sparks, T.H. and Zalakevicius, M. (in press): Arrival and departure dates In:
Møller, A.P., Fiedler, W. & Berthold, P. The Effect of Climatic Change on Birds. Advances in
Ecological Research. Academic Press. A Review
Anssi V. Vähätalo, Kalle Rainio, Aleksi Lehikoinen and Esa Lehikoinen (in press) Spring arrival of
birds depends on the North Atlantic Oscillation. – Journal of Avian Biology 34: 000-000.
Rainio, K., Lehikoinen, A., Vähätalo, A. and Lehikoinen, E. () – “Second NAO paper” (untitled) –
to be submitted in November-December 2003
Markus Ahola, Toni Laaksonen, Katja Sippola, Tapio Eeva and Esa Lehikoinen () Spring phenology
of a long-distance migrant bird is driven by spatio-temporally varying climate trends (about to
be submitted)
Rainio, K., Lehikoinen, E., Terhivuo, J. () Comparison of responses of birds to temperature and
NAO during different warming and cooling periods (about to be submitted).
T.H. Sparks, F. Bairlein, J. Bojarinova, O. Hüppop, E. Lehikoinen, K. Rainio, L.V. Sokolov & D.
Walker (): Examining the total arrival distribution of migratory birds (about to be submitted?)
Laaksonen, T., Ahola, M., Eeva, T. and Lehikoinen, E () Long term changes of breeding success in a
long-distance migrant.
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= short talks by Kalle and Markus in this seminar
= a couple of next slides
Lehikoinen, E., Sparks, T. and Zalakevicius, M.
(in press):
In: Møller, A.P., Fiedler, W. & Berthold, P. The Effect of Climatic
Change on Birds. Advances in Ecological Research. Academic Press
Arrival
and
departure
dates
Timing of migration –
what to measure?
Variable
Definition
Problems
Benefits
First
arrival/departure
First individual observed in
spring/autumn (of
transient/passage migrants)
Large random variance
Atypical behaviour
Data quality tests mostly
lacking
Easy to observe,
cheap,
volume of data
Median
arrival/departure
The middle individual arriving
in/departing from a closely
followed breeding population
Difficult, labour-intensive,
requires special study
Closest to fitness
consequences
Mean
arrival/departure
Average arrival/departure date of
all birds followed
As above, but not as easy,
because of complex arrival
distributions
Close to fitness
consequences
Median/Mean
migration time
The middle or average date of
migration in an intensively studied
migration flow
Unknown mixture of passing
populations, difficult statistical
distributions, problems with
mixing breeding populations
Is done in bird
stations in standard
ways, plenty of data
available
Some possible biases:
minor and major
minor technical biases (in relation to effect sizes and data resolution)
Calendar effects: leap years vs ordinary years after 29 February,
diff. of one day
Vernal Equinox is cycling c.0.8 or 1.5 days/100 years in 400 year
cycles (Nature 414:600, 2001)
the next ones can be major observational biases
Bird station seasons have fixed starts and ends
Missing observation days are incorrectly or not at all treated
Observer activity is weather dependent
biological covariates (originate from bird behaviour)
Population size affects timing records
Changes from migrant to resident strategy complicate analysis
Questions concerning independent
variables and approaches
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Data selection and preparation
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Local weather, or weather along the migratory route, spatiotemporal fit
NAO: winter-NAO, other NAO’s
Weather periods used in analyses
Principles of selecting time periods for analysis
Target species selection
Analyses
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Linear regression vs. non-parametric LO(W)ESS vs. timeseries
Autocorrelation problems
Lots of other tricky statistical things
Temperature has always
affected arrival of birds –
Leche’s Data 1749-1763
Meta-analysis of arrival responses
Response type
Upper 95%
Number of time series
(unit)
Lower 95%
Average response
confidence limit
confidence limit
Trend, FA
(days/year)
590
-0.342
-0.373
-0.403
128
-3.382
-3.959
-4.535
203
-2.472
-2.901
-3.331
225
-0.137
-0.100
-0.223
149
-1.350
-1.636
-1.921
153
-1.433
-1.761
-2.089
NAO, FA
(days/unit change of NAO-index)
Local temperature, FA
(days/ ºC)
Trend, MMT
(days/year)
NAO, MMT
(days/unit change of NAO-index)
Local temperature, MMT
(days/ ºC)
Dependence of departure dates on
temperature are less well
understood and more variable
Variation of moult start –
Willow Warbler
Sexed individuals, n=845, RSQ = 34.8%
Source
DF
YEAR
29*
7840.7403656
4.62
0.0001
AREA
1*
854.2635848
14.59
0.0001
10*
1183.0473934
2.02
0.0288
1*
1991.9488772
34.02
0.0001
YEAR*SEX
25*
2407.4581812
1.64
0.0250
AREA*SEX
1*
143.2869043
2.45
0.1182
YEAR*AREA*SEX
7
329.3295331
0.80
0.5846
YEAR*AREA
SEX
Type IV SS
F Value
Pr > F
Willow Warbler –
annual cycle intercorrelations
Moult is delayed if arrival is delayed, but differently in males and females
y = 0.4135x + 32.966
R = 0.1526
50
Start of moult (1.6= day 1)
48
2
46
50
Females
45
y = 0.4181x + 35.378
R2 = 0.077
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44
42
40
Males
38
35
36
y = 0.0689x + 34.755
2
30 R = 0.0011
34
32
25
30
10
55
15
20
25
Arrival day in May
30
20
10
12
14
16
18
20
22
24
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28
Long term change of clutch size
Standard deviation of the clutch size of pied flycatchers
Clutch size of pied flycatchers
1,6
7,0
6,8
Standard deviation
1,4
Clutch size
6,6
6,4
6,2
6,0
5,8
1,2
1,0
0,8
0,6
5,6
0,4
1940
1950
1960
1970
1980
YEAR
1990
2000
2010
1940
1950
1960
1970
1980
YEAR
1990
2000
2010
Future within our lab / university?
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Cooperation between groups studying (also) impacts
of Climate Change
Regular seminars on the topic
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Article reviews
Regular reports of current status in each separate project
Cooperation in handling background data and
predictive models
Impacts of CC on trophic interactions and community
structure