climate change has affected biological systems already walther et al. nature 2002
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Climate Change has affected biological systems already
Walther et al. Nature 2002
CCIOB or
Climate Change Impacts on Birds
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
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
Why study Climate Change Impacts in Finland – benefits?
Climate Change Impacts on Birds – funding and staff
Project funded by– Academy of Finland– Maj and Tor Nessling Foundation– Kone Foundation– Period 2001-2004, hopefully longer
Staff– 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– http://www.met-office.gov.uk/research/hadleycentre/ HADLEY CENTRE
GREAT BRITAIN
– http://www.ipcc.ch/ INTERGOVERNMENTAL PANEL FOR CLIMATE CHANGE
– http://www.knmi.nl/samenw/eca/htmls/index5.html EUROPEAN CLIMATE ASSESSMENT & DATASET (ECA&D)
and nationally: agreement for scientific cooperation with http://www.fmi.fi FINNISH METEOROLOGICAL INSTITUTE
For public information concerning Climate and its change, look at:– http://www.ilmasto.org/index.htm
Bird data
Response variable group Data type available
Timing of migration Phenological projects 1749- Bird stations 1970-
Timing of breeding Nest card schemes 1941- Timing of moult Moult inquiry 1968- Integrated research of the annual schedule
Changes in population sizes Census programs 1941- Winter Birds Census 1957-
Changes in distributions Atlas projects 1974-1989 earlier and later zoogeographical information
Cooperation
National– Hanko and Jurmo bird stations
Anssi Vähätalo, Aleksi Lehikoinen– Natural History Musem of Helsinki University
Risto A. Väisänen, Juhani Terhivuo, Jari Valkama– Finnish Meteorological Institute
International– Institut für Vogelforschung - Vogelwarte Helgoland/Institute of Avian Research,
Germany Franz Bairlein, Ommo Hüppop
– Centre for Ecology and Hydrology (CEH)/Institute for Terrestrial Ecology (ITE), Great Britain
Tim Sparks– and others (Lithuania, France, Denmark)
Main questions
Confirmation of impacts already connected with Climate Change– quality assurance of data– validity of methods and realism of models used– quantification of changes (degree of response/year, degree of response/°C)
What is the relative role of CC in...– timing changes of the phases of the annual cycle– changes of numbers– changes of distributions
Which other factors contribute– habitat change, other human impacts
How impacts on different traits are intercorrelated– correlations between changes of different events of the annual cycle– indirect impacts on fitness traits: mismatches– community reorganisation
Making predictive models
Climate Background
Global Climate System Oscillations: El Niño (ENSO), AO, NAO, PDO Climate Change:
– including the idea that present day climate is changing due to human impact on Global Climate System
very long term oscillations (Ice Age ”cycles”)
• 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
North Atlantic Oscillation – NAO index
Temperature variation North of 60 °N
winter spring summer autumn
Fennoscandia
1900-45
1945-65
1966-2001
Spatial, periodical andseasonal variability of CC
Predictions of five models of future change in Ta
60-90 °N
global
Impacts on birds
Changes of – 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
Congresses and workshops: – Freising 2000 International Phenology Network
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…
1. 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
2. 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.
3. Rainio, K., Lehikoinen, A., Vähätalo, A. and Lehikoinen, E. () – “Second NAO paper” (untitled) – to be submitted in November-December 2003
4. 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)
5. 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).
6. 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?)
7. Laaksonen, T., Ahola, M., Eeva, T. and Lehikoinen, E () Long term changes of breeding success in a long-distance migrant.
= 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 varianceAtypical behaviourData 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
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
Some possible biases: minor and major
Questions concerning independent variables and approaches
Data selection and preparation– Local weather, or weather along the migratory route, spatio-
temporal fit– NAO: winter-NAO, other NAO’s– Weather periods used in analyses– Principles of selecting time periods for analysis– Target species selection
Analyses– Linear regression vs. non-parametric LO(W)ESS vs. time-
series– Autocorrelation problems– Lots of other tricky statistical things
Temperature has always affected arrival of birds –
Leche’s Data 1749-1763
Response type
(unit) Number of time series
Upper 95%
confidence limit Average response
Lower 95%
confidence limit
Trend, FA
(days/year) 590 -0.342 -0.373 -0.403
NAO, FA
(days/unit change of NAO-index) 128 -3.382 -3.959 -4.535
Local temperature, FA
(days/ ºC) 203 -2.472 -2.901 -3.331
Trend, MMT
(days/year) 225 -0.137 -0.100 -0.223
NAO, MMT
(days/unit change of NAO-index) 149 -1.350 -1.636 -1.921
Local temperature, MMT
(days/ ºC) 153 -1.433 -1.761 -2.089
Meta-analysis of arrival responses
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 Type IV SS F Value Pr > F
YEAR 29* 7840.7403656 4.62 0.0001
AREA 1* 854.2635848 14.59 0.0001
YEAR*AREA 10* 1183.0473934 2.02 0.0288
SEX 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
Willow Warbler – annual cycle intercorrelations
y = 0.4135x + 32.966
R
2
= 0.1526
30
32
34
36
38
40
42
44
46
48
50
10 15 20 25 30
Arrival day in May
Sta
rt o
f m
ou
lt (
1.6
= d
ay
1)
Moult is delayed if arrival is delayed, but differently in males and females
y = 0.0689x + 34.755
R2 = 0.0011
y = 0.4181x + 35.378
R2 = 0.077
20
25
30
35
40
45
50
55
10 12 14 16 18 20 22 24 26 28
Females
Males
Long term change of clutch size
Clutch size of pied flycatchers
YEAR
1940 1950 1960 1970 1980 1990 2000 2010
Clu
tch
siz
e
5,6
5,8
6,0
6,2
6,4
6,6
6,8
7,0
Standard deviation of the clutch size of pied flycatchers
YEAR
1940 1950 1960 1970 1980 1990 2000 2010
Sta
nd
ard
de
via
tio
n
0,4
0,6
0,8
1,0
1,2
1,4
1,6
Future within our lab / university?
Cooperation between groups studying (also) impacts of Climate Change
Regular seminars on the topic– 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