Ecology Letters, (2004) 7: 388–394
doi: 10.1111/j.1461-0248.2004.00588.x
REPORT
Regime shifts in the breeding of an Atlantic puffin
population
Joël M. Durant1, Tycho AnkerNilssen2, Dag Ø. Hjermann1 and
Nils Chr. Stenseth1,3*
1
Centre for Ecological and
Evolutionary Synthesis (CEES),
Department of Biology,
University of Oslo,
PO Box 1050 Blindern,
NO-0316 Oslo, Norway
2
Norwegian Institute for Nature
Research (NINA), Tungasletta 2,
NO-7485 Trondheim, Norway
3
Flødevigen Marine Research
Station, Institute of Marine
Research, NO-4817 His, Norway
Abstract
Timing of breeding is a key factor determining the reproductive success in bird
populations and known to be affected by climate fluctuations. We investigated the longterm (1978–2002) relationship between climate and hatching date within a population of
Atlantic puffin Fratercula arctica at Røst in the Norwegian Sea. The timing of puffin
breeding was found to be influenced by the North Atlantic Oscillation winter index
(NAO). We isolated two temporal regimes, one where NAO had a significant effect on
hatching date (1978–1986 and 1995–2002) and one where these variables were
independent (1987–1994). Hatching date could be modelled using, in addition to NAO,
hatching date and food abundance in the preceding breeding season (possibly proxies of
parental effort). The models remained significant for regime 1 but not for regime 2.
NAO differed between the two regimes suggesting that the shifts were induced by
climate change, possibly via its effect on the availability of prey in the preceding year.
The novelty of our study is the identification of temporal regimes in the effects of
climate within one population.
*Correspondence: E-mail:
n.c.stenseth@bio.uio.no
Keywords
Fratercula arctica, North Atlantic Oscillation, Timing of breeding.
Ecology Letters (2004) 7: 388–394
INTRODUCTION
Climate fluctuations are known to affect the phenology of
animals (see, e.g. Stenseth & Mysterud 2002) with
consequences for reproductive success and survival (review
in Stenseth et al. 2002). Indeed, to raise young successfully,
adults typically adjust their breeding decision so as ultimately
to match food availability during rearing (Lack 1968;
Nilsson 1999). For many species living in the temperate
zone, only a short period of the year is suitable for
reproduction (Murton & Westwood 1977). The timing of
the peak of food availability varies between areas and years
and as a consequence the optimal timing of reproduction
will also vary. It has, for instance, recently been found that
climatic warming may make birds breed earlier (Brown et al.
1999). However, birds and their food resources may not
respond in similar way to such a climate change (e.g. Visser
et al. 1998). Indeed, the advancement in bird breeding dates
is often not sufficient to anticipate the one in the food
resources leading to a mismatch (Visser et al. 1998; Thomas
et al. 2001; Winkler et al. 2002; Sanz et al. 2003). The fitness
consequences of timing are thus important (Nilsson 1999
2004 Blackwell Publishing Ltd/CNRS
and references therein). As reproduction is initiated much
earlier than the time of maximum food requirements for
offspring, individuals should start preparing for breeding in
response to cues that are available when that decision is
made. Within the reproduction window, such cues may be
internal (e.g. body condition, Price et al. 1988) and/or
external reflecting the environmental conditions (Meijer &
Drent 1999).
As a proxy of climate variation it has recently become
increasingly common to use the North Atlantic Oscillation
(NAO) (Stenseth et al. 2003), an integrated measure linked
to many climatic variables such as precipitation, wind speed
and temperature over a large part of the Northern
Hemisphere (Hurrell et al. 2003 and references therein).
The NAO is mainly a winter (December to March)
phenomenon affecting the strength of the westerlies and
the movement of air and water masses that modifies sea
temperature (Hurrell et al. 2003). When NAO is negative,
conditions in the Norwegian Sea are characterized by low
sea temperatures and dry weather, whereas the opposite
conditions are related to positive NAO. The NAO affects
the phenology of several species of birds and mammals on
Regime shifts in Atlantic puffins 389
both sides of the Atlantic (Hurrell et al. 2003) and was
recently also shown to affect the population dynamics of
seabirds (Thompson & Ollason 2001).
The impact of NAO on natural populations seems
complex as it may change with latitude (e.g. Sæther et al.
2003) or between local populations (e.g. Visser et al. 2003).
In addition, recent studies using sliding windows correlation
analyses, have shown that the relationship between largescale climate (e.g. El Niño-southern Oscillation, NAO) and
regional weather such as rain-fall, changes through time
(Krishna Kumar et al. 1999). Accordingly, the relationship
between large-scale climate and biological processes may
also shift through time and create a variety of regimes for
how animals respond to different climatic conditions. In this
study, we investigate a possible example of such a regime
shift phenomenon in the relationship between NAO and the
phenology of a single population of the Atlantic puffin
(Fratercula arctica L.), a seabird that breeds all around the
North Atlantic (Anker-Nilssen & Tatarinkova 2000).
The population ecology of the Atlantic puffin has been
studied since 1964 in the Røst archipelago, northern
Norway, which hosts one of the world’s largest breeding
colonies of the species (e.g. Anker-Nilssen 1992; AnkerNilssen & Aarvak 2003). Along the east coast of the
Norwegian Sea its reproduction is highly dependent on firstyear herring (Clupea harengus) produced by the Norwegian
spring-spawning stock off south-west Norway and drifting
northwards with the Norwegian coastal current (AnkerNilssen 1992; Durant et al. 2003). Consequently, at Røst the
timing of the puffin’s hatching in relation to the arrival (and
departure) of herring in the foraging areas outside the
colony is of uttermost importance. An incorrect assessment
may lead to the death of the chick and failure in a year’s
reproduction. This illustrates the importance of understanding what factors influence the onset of breeding in seabirds.
We analysed 25 years of data on hatching dates of puffins
on a single, small island in the Røst archipelago and
compared them with the corresponding NAO winter index
using a sliding window correlation analysis. Several other
variables measured annually for this population during the
same period (fledging success, duration of the nestling
period and the length of herring in the chick diet) were then
included in a multivariate analysis in an attempt to uncover
some of the mechanisms underlying the observed relationship between NAO and hatching dates.
MATERIAL AND METHODS
Location and data collection
The fieldwork was conducted at Hernyken (6726¢N,
1152¢E), which is one of the larger bird cliffs in the Røst
archipelago at the tip of the Lofoten Islands, northern
Norway. In 2002, Røst was the breeding ground for an
estimated 382 700 pairs of puffins, of which 31 900 pairs
bred on Hernyken (Anker-Nilssen & Aarvak 2003). The
island is only c. 400 m wide, so this sub-colony can be
regarded as a single population unit.
During 1980–2002, an annual average of 166 puffin nests
(range 10–304) were inspected regularly during the months
of June to August, most frequently (1–4 day intervals)
during hatching and periods of peak fledging or chick
mortality (Anker-Nilssen & Aarvak 2003). An average
hatching date was estimated for each year (annual average
77 nests, range 7–144) except 1987 (no data from the
hatching period) and 1995 (when only one of 281 eggs in the
study nests hatched). Annual fledging success was estimated
as the proportion of eggs hatched producing a fledgling.
Additional data for 1978 and 1979 were taken from Lid
(1981) and Tschanz (1979), respectively. Whenever possible,
the length of the nestling period (i.e. the age at which the
chick died or fledged) was determined for each nest (annual
average 63 nests, range 7–119). Throughout the chick
period, an annual average of 117 food loads (range 6–272)
intended for chicks were collected regularly from adults
caught in mist-nests erected in the colony. All individual
prey in each load were identified to species-level and their
body lengths measured to the nearest 1 mm. No dietary
information was collected in 1975–1978, 1987 and 1995 and
the samples from 1981 contained no herring. For each year
with available data, the average length of herring in the
puffin diet on 1 July was calculated by linear regression
based on mean herring length for each 5-day sampling
period. Further details on field methods and annual sample
sizes can be found in Anker-Nilssen (1992) and AnkerNilssen & Aarvak (2003) and references therein.
Environmental descriptors
Data on the winter index of the NAO (December to March)
were obtained from the website of Dr James W. Hurrell of
the National Centre for Atmospheric Research (http://
www.cgd.ucar.edu/jhurrell/nao.html#winter). This index
is known to carry clear climate signals (see, e.g., Stenseth
et al. 2003).
Data analyses
We conducted a 5-year sliding window correlation incremented by 1 year of the average hatching date of the puffins
and the NAO winter index during 1978–2002. A 5-year
window is the lowest meaningful window size for running
such correlations. We also inspected the effect of increasing
the window size successively by 2 years up to 11 years.
Because of the narrow time window used (5 years), and
because such analyses gives unequal weight to the various
2004 Blackwell Publishing Ltd/CNRS
RESULTS
Hatching date and NAO
The relationship between NAO and hatching date of
Atlantic puffins at Røst differed between two regimes
(Fig. 1a). The 5-year sliding window correlation analysis
determined two occasions where the response of hatching
to NAO changed: between 1986 and 1987, and between
1994 and 1995 (Fig. 1b). To compare the 1000 randomly
generated sequences with the observed pattern, we used the
number of correlations with r < )0.5. In the observed
sequence, 13 of the 21 correlations had r < )0.5 and the
other eight (r > )0.5) all occurred during a single period
(Fig. 1b). Of the 1000 randomly generated correlation
sequences, only 4.3% had 13 or more 5-year windows with
r < )0.5 and in most of these cases the correlation pattern
shifted more than twice. Only 0.6% of the shuffled data sets
had 13 or more 5-year windows with r < )0.5 in
combination with only one or two windows of r > )0.5.
Thus, we conclude that the pattern seen in Fig. 1b is
unlikely to be the result of chance events. It is worth noting
that the same pattern was still clearly visible when the sliding
window size was increased successively up to 9 years, but
disappeared with an 11-year window.
2004 Blackwell Publishing Ltd/CNRS
30
4
20
2
10
Winter NAO
(a) 6
0
30
( )
–2
20
–4
10
–6
1980
(b)
0.5
Correlation coefficient
data pairs (e.g. 1978 is used only once, while 1982 is used
five times), we compared the observed correlation pattern
with correlation patterns from 1000 random sequences of
the NAO-hatching data pairs. Since the pairs were not split
up, the overall correlation between NAO and hatching date
in all 1000 sequences was the same as the observed one but
the pattern of the sliding window correlations was changed.
This way, we could assess the probability that the observed
correlation pattern was a result of chance events.
We used generalized additive models (GAM in the
statistical package S-Plus, Venables & Ripley 1999) to test
for nonlinear associations between variables. When the test
was not significant, we applied linear models (LM). Each fit
was assessed by ANOVA analysis in order to examine the
validity of the model. We also considered two-way
interactions. The most appropriate model was found by
applying the Mallow’s Cp criterion (Venables & Ripley 1999),
a criterion to be used when comparing models that are not
nested. The model with the smallest Cp is the best in the
sense that the residual deviance is smallest compared with
the number of parameters estimated in the model. Using the
autocorrelation function (ACF), we tested whether the
residuals were auto-correlated, in which case ordinary
regression analysis is not valid. All correlations were
estimated using the Pearson’s product–moment correlation
test. The P-values were adjusted for autocorrelation
(Priestley 1981).
Hatching date (June–July)
390 J. M. Durant et al.
1985
Regime 1
1990
Year
Regime 2
1995
2000
Regime 1
0.0
–0.5
–1.0
1980
1985
1990
1995
Central year of sliding window
2000
Figure 1 Variation in the timing of breeding of Atlantic puffins at
Røst, northern Norway. (a) Superimposed to the average hatching
date of the puffins (black line, filled circles) is the NAO winter
index (grey line, open circles). The vertical dotted lines separate
two periods where the relationship between hatching date and
NAO differed (regimes 1 and 2; Fig. 1b). No hatching dates were
recorded in 1987, whereas hatching occurred in only one of the 281
study nests in 1995. (b) A 5-year sliding window correlation of the
average hatching date of the puffins and the NAO winter index
during 1978–2002 (black line). The Pearson’s product-moment
correlations were conducted for overlapping 5-year intervals
incremented by 1 year. The year 1996 was ignored in the analysis
(see text). Two main periods where the relationship between
hatching date and NAO differed were identified (delimited by
vertical dotted lines): before 1987 or after 1994 (regime 1, open
circles) and from 1987 to 1994 (regime 2, grey circles). The
correlations between NAO and hatching date (overall, regimes
1 and 2) are presented in Table 2. For comparison, the 7-year
sliding window correlation is also indicated on the graph (grey
dotted line).
Comparisons between the two regimes are presented in
Table 1. Interestingly, NAO was significantly lower in
regime 1 (1978–1986 and 1995–2002) than in the intervening regime 2 (1987–1994), whereas hatching date,
fledging success, duration of the nestling period and herring
length did not differ significantly between the two regimes.
The year 1996 is an outlier with very low NAO and very late
hatching that strongly influenced the relationship between
NAO and hatching date. The negative correlation between
the two parameters for the whole period 1978–2002
Regime shifts in Atlantic puffins 391
Table 1 Comparisons of mean values ± 1 SE of variables meas-
Table 2 Results of fitting linear models to the variation of hatching
ured during the two regimes
date of Atlantic puffins at Røst, northern Norway. For Regime 1,
the outlier 1996 was excluded from the analysis
Variables
Regime 1
Regime 2
d.f.
td.f.
P-value
Variables
Descriptive
Hatcht
Succt
Durt
Lengtht
24.2
0.29
26.8
41.6
±
±
±
±
2.3
0.09
3.9
2.4
26.2
0.54
34.3
48.2
±
±
±
±
1.2
0.14
5.1
2.7
21
23
21
18
0.540
1.537
1.150
1.733
0.590
0.138
0.260
0.100
Explanatory
NAOt
Hatcht)1
Succt)1
Succt)5
Durt)1
Lengtht)1
0.61
24.1
0.25
0.25
27.6
39.5
±
±
±
±
±
±
0.49
2.5
0.08
0.10
3.7
1.8
2.38
26.4
0.54
0.41
32.8
49.0
±
±
±
±
±
±
0.67
1.1
0.15
0.14
6.0
2.2
23
21
23
20
21
17
2.092
0.540
1.877
0.915
0.779
3.279
0.048
0.595
0.073
0.371
0.445
0.004
Hatch stands for hatching date (1 ¼ 1 June), Succ for fledging
success (scale 0–1), Dur for duration of the nestling period (days),
and Length for the average length (mm) of herring in the puffin
diet on 1 July. The year each variable was measured is indicated in
subscript. The descriptive variables are used to differentiate the
two regimes. The explanatory variables are factors that might affect
the timing of breeding and help explain the difference between the
two regimes.
(Table 2) disappeared when 1996 was omitted (r2 ¼ 0.045,
P ¼ 0.344).
In regime 1 no nonlinear effects of NAO on hatching
date (Hatcht) were detected (P ¼ 0.396), but hatching date
was significantly linearly related to climate as expressed by
NAO in the same year (NAOt, Table 2): Hatcht ¼ a + b
NAOt, where a ¼ 25.7688 ± 1.5629 and b ¼ )3.8547 ±
0.8439, F1,14 ¼ 20.86. Without the outlier 1996, a ¼
24.0328 ± 1.3959 and b ¼ )2.3830 ± 0.8486 (Table 2).
The residuals were not significantly auto-correlated at lag
1 (r ¼ 0.420, P ¼ 0.151).
In regime 2, we found neither a linear nor a nonlinear
effect of NAO on hatching date (Table 2 and P ¼ 0.480).
Effect on hatching dates of other variables
Inter-annual dependency of hatching dates
The timing of breeding was not independent from year to
year. Indeed, in regime 1, a significant part of the variation
in hatching date was explained by the date of hatching in the
preceding year (r2 ¼ 0.347). No such relationship was
detected in regime 2 (r2 ¼ 0.041).
Fledging success in preceding years
The average hatching date in year t was in general not
affected by the average fledging success in year t ) 1
(F1,21 ¼ 0.012, P ¼ 0.914, r2 ¼ 0.001), and fledging success in year t ) 1 did not differ significantly between the
Both Regimes
NAOt
Hatcht)1
Lengtht)1
Succt)5
NAOt + Hatcht)1
NAOt + Lengtht)1
NAOt + Lengtht)1
+ Hatcht)1
Regime 1 (–1996)
NAOt
Hatcht)1
Lengtht)1
Succt)5
NAOt + Hatcht)1
NAOt + Lengtht)1
NAOt + Lengtht)1
+ Hatcht)1
Regime 2
NAOt
Hatcht)1
Lengtht)1
Succt)5
NAOt + Hatcht)1
NAOt + Lengtht)1
NAOt + Lengtht)1
+ Hatcht)1
d.f.
Fd.f.
P-value r2
Cp
1,
1,
1,
1,
2,
2,
3,
21 7.038 0.015
18 12.060 0.003
15 4.634 0.048
18 8.473 0.009
17 6.110 0.010
14 5.137 0.021
13 6.290 0.007
0.251 1089.39
0.101 489.96
0.236 568.29
0.320 1025.84
0.418 508.26
0.423 512.41
0.592 464.80
1,
1,
1,
1,
2,
2,
3,
13 7.886 0.015
11 5.891 0.034
8
2.921 0.126
10 6.079 0.033
10 5.922 0.020
7 10.490 0.008
6 12.370 0.006
0.378
0.347
0.268
0.378
0.542
0.750
0.861
1,
1,
1,
1,
2,
2,
3,
5
4
4
5
3
3
2
0.012
0.041
0.002
0.042
0.117
0.132
0.141
0.059
0.141
0.007
0.219
0.199
0.227
0.109
0.818
0.701
0.939
0.660
0.830
0.809
0.947
304.24
316.32
328.61
332.47
250.32
186.91
165.91
The variables used in the models are the explanatory variables of
Table 1.
two regimes (Table 1). However, hatching date in year t was
affected by the average fledging success in year t ) 5,
corresponding to the minimum time lapse needed for the
young to reach breeding age (Table 2, r2 ¼ 0.320 or
F1,17 ¼ 4.38, P ¼ 0.051, r2 ¼ 0.205 when omitting 1996),
but this effect was only present in regime 1 (r2 ¼ 0.378) and
not in regime 2 (r2 ¼ 0.042). Fledging success in year t ) 5
was 46% lower in regime 1 than in regime 2, but the
difference was not statistically significant (Table 1).
Nestling period duration in the preceding year
The average hatching date in year t was not affected by the
average duration of the nestling period in year t ) 1
(F1,19 ¼ 0.921, P ¼ 0.349, r2 ¼ 0.046).
Food availability during the preceding breeding season
The average hatching date in year t was affected by the
average length of herring in the puffin diet on 1 July in year
t ) 1 (Table 2, r2 ¼ 0.236). This significance of the
2004 Blackwell Publishing Ltd/CNRS
392 J. M. Durant et al.
relationship disappeared when the regimes were tested
separately, but the same tendency remained for regime 1
(regime 1: r2 ¼ 0.268 and regime 2: r2 ¼ 0.002). Note that
hatching date in year t was not explained by the herring
length in the same year (F1,18 ¼ 1.42, P ¼ 0.249,
r2 ¼ 0.073) and this variable was therefore not used in the
further modelling.
Multiple model of hatching date
The variables used in the analysis were not correlated
(P > 0.20). The best model (lowest Cp) predicting the interannual variation in hatching date (Hatcht) in regime 1
included three variables, the NAO winter index in the same
year (NAOt), the food availability in the chick period of the
preceding year (Lengtht)1) and hatching date in the
preceding year (Hatcht)1), with no interactions between
the three. The model was significant both with
(F3,7 ¼ 13.93, P ¼ 0.003, r2 ¼ 0.857) and without the
outlier year 1996 (Table 2, r2 ¼ 0.861). Without the outlier,
the model is: Hatcht ¼ a + b NAOt + c Hatcht)1 + d
Lengtht)1, where a ¼ 7.6884 ± 6.6052, b ¼ )2.4105 ±
0.6215, c ¼ 0.2953 ± 0.1350 and d ¼ 0.2785 ± 0.1483.
DISCUSSION
We have shown that the onset of breeding in the Atlantic
puffin can be estimated using the NAO winter index, a
proxy of climate conditions during the pre-breeding season.
When NAO is high, the puffins generally tend to breed
earlier than when it is low. However, we found that the
study period was composed of two regimes: a regime with a
negative relationship between NAO and hatching date
interrupted by another regime where the timing of breeding
was independent of NAO.
High sea temperatures, related to positive NAO, are
favourable for the reproduction of many of the pelagic fish
stocks in these waters, among which is the Norwegian
spring-spawning herring (Toresen & Østvedt 2000; Hurrell
et al. 2003). Knowing its importance for the reproduction of
Atlantic puffins at Røst (Anker-Nilssen 1992; Anker-Nilssen
& Aarvak 2003; Durant et al. 2003), a positive relationship
between NAO and the timing of breeding for these puffins
is coherent with the hypothesis that the birds determine
when to breed in relation to some environmental cues
influenced (directly or indirectly) by climate (Wilson &
Arcese 2003).
The timing of breeding of the Atlantic puffin at St Kilda
(UK), as measured by the number of fledglings attracted to a
nearby army camp, was found to be positively related to the
sea temperature in spring (Harris et al. 1998), indicating a
trend opposite to that we documented for the Røst puffins.
It might however be that the fledglingsÕ attractiveness to the
2004 Blackwell Publishing Ltd/CNRS
camp is likely to be negatively correlated with their body
condition (and flight capability) which in turn may be
negatively affected by poor seasons (Anker-Nilssen &
Aarvak 2003).
In accordance with our results, a negative relationship
between sea temperature and hatching date has been
reported for two Pacific species of puffins breeding on
Triangle Island, British Columbia, the rhinoceros auklet
Cerorhinca monocerata (Bertram et al. 2001) and the tufted
puffin F. cirrhata (Gjerdrum et al. 2003). For the tufted
puffin, data on chick growth and fledging success also
suggested an optimal range of sea temperatures above which
adults could only partially compensate negative effects by
advancing the timing of breeding (Gjerdrum et al. 2003).
Rodway et al. (1998) suggested that the timing of Atlantic
puffins breeding in Newfoundland also was negatively
correlated to sea temperature and possibly mediated via
temperature effects on capelin spawning, although they
could not exclude weather effects (precipitation and air
temperature) on nest burrow quality. Interestingly, timing
might be constrained by burrow and soil conditions in
spring, at least in the northernmost parts of the breeding
range (Harris 1984; Anker-Nilssen & Tatarinkova 2000).
The strengthening of the North-Atlantic current and
increased air temperatures in the north-east Atlantic in
positive NAO years would imply earlier access to the nest
burrows and warmer nests, which are preferred by puffins
(Rodway et al. 1998).
Timing of breeding seemed not to be influenced by
previous reproductive effort as indicated by the lack of
relationship with fledging success or duration of the nestling
period in the preceding year. However, in regime 1, there
was a positive relationship with hatching date the preceding
year. This might be caused by ÔhabitÕ (i.e. a bird tends to
breed at the same date as it did last year) but it could also
indicate that some unknown, auto-correlated variable (e.g.
related to climatic conditions or ecosystem state) was
influencing breeding date.
The best model selected by the Cp criterion estimates the
hatching date using in addition to NAO both the hatching
date and an index of the food availability in the preceding
breeding season. The puffins at Røst tended to breed late
when their breeding in the preceding season also was late,
indicating a time constraint between consecutive breeding
attempts. Likewise, the timing of their breeding was delayed
when the availability of herring in the preceding year was
poor. The breeding conditions in regime 1 seem to be poorer
as indicated by the tendency of lower fledging success during
regime 1 than during regime 2. Moreover, the significantly
higher NAO during regime 2 suggests that the regime shifts
were induced by climate change, possibly via its effect on the
availability of prey the preceding year. Post-breeding
movements of puffins equipped with satellite transmitters
Regime shifts in Atlantic puffins 393
indicate that herring is probably also an important food
source for the adults in the first couple of months after
breeding (T. Anker-Nilssen et al., unpubl. data).
The relationship between large-scale climate and the
performance of individuals is described to be nonlinear
(Stenseth et al. 2003). The effect of NAO on hatching date
of the Atlantic puffin may therefore disappear above or
below certain thresholds (e.g. high positive NAO value). In
our study period, the NAO index was generally positive,
with several high extremes. Whereas the NAO was relatively
moderate during regime 1 it was generally high during
regime 2. This may explain why hatching date and NAO
were not correlated during regime 2. At the same time,
hatching date in regime 2 also appeared to be independent
of the other variables we tested it against. Thus, the greater
stability of hatching date during regime 2 (SE of 1.2 vs. 2.3
for regime 1, Table 1) seemed to be less dependent of
environmental constraints. Although we did not detect
nonlinearity in the relationship between NAO and hatching
date, there must be limits with respect to how early or late
puffins are willing or able to breed. Such limitations will
reduce the effect of NAO variation on timing of breeding,
particularly when environmental conditions (as reflected by
NAO) are close to the extremes. During the low NAO
years, breeding is generally delayed but cannot be postponed
over a certain limit (e.g. the possibly unavoidable onset of
body feather moult in early autumn). Conversely, in the high
NAO years, advanced start of breeding may be limited by
factors such as local conditions at the nest sites, the birdsÕ
body condition and the moult of flight feathers in midwinter. Thus, although even earlier breeding could be very
favourable in such years, other environmental or physiological factors may limit it. Consequently, the correlation between NAO and timing of breeding is expected to
be strongest when NAO is relatively intermediate, as in
regime 1.
Atlantic puffins at Røst have experienced series of failed
reproduction, which principally were located during the first
part of regime 1 (Anker-Nilssen & Aarvak 2003; Durant et al.
2003). Poor reproduction will lead to an equivalently poor
recruitment several years later, when that cohort (if still
present) is recruited into the breeding population. At Røst
the puffin usually starts breeding when 5–7 years old (AnkerNilssen & Aarvak 2003). Thus, knowing that first-time
breeders tend to lay later than experienced birds (e.g. Sæther
1990), the positive relationship between fledging success
5 years earlier and hatching date seems to indicate an effect
of recruitment. Assuming also an age-dependent difference
of response to climate (Pinaud & Weimerskirch 2002), a
change of age structure in the breeding population may
therefore have contributed to the appearance of regime 2.
While no annual data for the age structure of the Røst
population were available, the reproductive success in 1975–
1997 was positively correlated with the change in the
number of breeders 5 years later (Anker-Nilssen & Aarvak
2003).
With the exception of NAO, that has an indirect effect,
we did not have direct measurements of variables that may
reflect the actual conditions in spring (March to May). The
effect of such variables (e.g. timing and strength of the
plankton bloom and the parallel production of prey species)
deserves more attention. For instance, adult puffins
belonging to the Røst population are known to visit areas
close to the main spawning grounds of herring in early April
(Anker-Nilssen et al. 2003). Thus, one hypothesis would be
that they make an early assessment of the environment (e.g.
based on the timing of larval herring appearance) and
respond accordingly despite the fact that larval abundance at
that time of year does not reflect the later strength of the
herring year class (Sætre et al. 2002).
The impact of climate change on natural populations
seems very complex. For instance, the impact of the NAO
may not only change on the spatial scale between different
populations (e.g. Sæther et al. 2003; Visser et al. 2003) but
also temporally for a single population as illustrated by our
long-term study. In this context, the consequences for vital
population parameters of local variation in the timing of
breeding need to be explored in more detail.
ACKNOWLEDGEMENTS
We are indebted to all those involved in the data collection
at Røst over the years, which was partly funded by the
Directorate for Nature Management, NINA and in the most
recent years also by Statoil A.S, Norsk Hydro ASA and BP
Amoco Norge AS. We thank L. Ciannelli, K. Lekve,
G. Ottersen and three anonymous referees for helpful
comments on the manuscript. Funding for J.M.D. was
provided by a Marie Curie Fellowship of the European
Community programme IHP-FP5 under contract number
HPMF-CT-2002-01852.
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Editor, M. Lambrechts
Manuscript received 3 February 2004
First decision made 3 February 2004
Manuscript accepted 23 February 2004