Climate change increases exposure to risks associated with late breeding in a tropical bird
Supplementary material
Rainfall and timing of breeding – preliminary analysis
We wished to describe the relationship between rainfall and the timing of breeding (first egg laying date). Previous work on kestrels
has shown that the frequency of rainfall in the July to September (spring) period is correlated with the timing of breeding – birds breed
earlier in dryer springs (Nicoll 2004). In order to determine the specific period that influenced the timing of breeding within this three
month time-window, we constructed a series of models that added different rainfall variables to a null model. This null model was
defined using a linear mixed modelling framework (LMM), with female identity as a random effect to account for repeated
observations from individual females breeding in different years. We fitted a global model to the timing of breeding data including
individual and environmental variables other than rainfall (see Supplementary Table 1 for a list of candidate predictor variables), then
simplified this global model using the update method in R (Crawley 2007). This produced a minimum adequate model (MAM, Model
1), which was then used as the null model for exploring the effect of rainfall on the timing of breeding.
We explored two types of rainfall variable – total rainfall (mm) and the number of rain-days. To determine the important rainfall
variable(s) and time period related to the timing of breeding, we set up a series of four global models, including the null model
described above (Model 1), and three models differing in their time windows: Model 2 analysing the complete three month period
(July to September), Model 3 analysing two month periods (July to August, August to September, mid-July to mid -September) and
Model 4 analysing one month periods (July, August, September, mid-July to mid-August and mid-August to mid-September). Each
model was then simplified using the step AIC/update function in R (Crawley 2007), and the AIC of the final MAMs compared. The
results show that timing of breeding is closely related to the number of rain-days in August (Supplementary Table 2) – birds breed
earlier when it is dryer in August.
Supplementary Table 1: Definition of explanatory variables included in the generalised linear models
Variable name
Variable type
Definition
Female age
Categorical
Age of female*
Male age
Categorical
Age of male partner*
Pair PBE
Categorical
Previous breeding experience of the pair
Pair PBEAS
Categorical
Previous breeding experience of pair at particular territory
Season
Categorical
Year / season of breeding attempt
Territory
Categorical
Breeding territory
Density
Continuous
Total population density in the season of breeding
* Age split into three groups - Birds aged 1 year old; birds aged 2-7 years and birds aged 8 or more years (Categorisation based on previous
exploratory analyses)
Supplementary Table 2: Linear mixed models run to determine significant rainfall variable affecting the timing of breeding. All
models had female identity as a random effect and selection between models involving different time windows was done using AIC,
first within global models and then across the minimum adequate models. The final selected model is given in bold. N = 243 breeding
attempts (first clutches of birds breeding in two or more years only)
Model
1
Fixed effects tested in
global models
Male age group &
female age group
Fixed effects in
minimum
adequate model
Parameter
estimates
(±SE)
P value
Intercept
56.60 ± 2.60
<0.0001
Male age (2-7
years old)
-16.48 ± 2.64
<0.0001
Male age ( ≥ 8
years)
-10.76 ± 4.08
0.0092
Female age (2-7
-6.07 ± 2.88
0.0371
Log Likelihood
AIC
AICc
ΔAIC
AIC
weights
-809.76
1633.49
1634.07
5.78
0.04
years old)
2
3
Male age group, female
age group, July to
September rainfall & July
to September rain days
Male age group, female
age group, July to
August rainfall, July to
August rain days, August
to September rainfall,
August to September
rain days, mid July to
mid September rainfall &
mid July to mid
Female age ( ≥ 8
years)
-5.08 ± 4.23
0.2327
Intercept
45.64 ± 7.45
<0.0001
July – September
rain days
0.18 ± 0.12
0.0121
Male age (2-7
years old)
-16.31 ± 2.63
<0.0001
Male age ( ≥ 8
years)
-10.34 ± 4.08
0.0123
Female age (2-7
years old)
-6.88 ± 2.92
0.0199
Female age ( ≥ 8
years)
-7.26 ± 4.48
0.1071
Intercept
41.03 ± 7.51
<0.0001
July – August rain
days
0.36 ± 0.16
0.0293
Male age (2-7
years old)
-16.36 ± 2.61
<0.0001
Male age ( ≥ 8
-10.65 ± 4.04
0.0095
-808.6
1633.2
1633.93
5.49
0.05
-807.42
1630.81
1631.58
3.1
0.16
September rain days
4
Male age group, female
age group, July
rainfall, July rain days,
August rainfall, August
rain days, September
rainfall, September rain
days, mid July to mid
August rainfall, mid
July to mid August rain
days, mid August to
mid September rainfall
& mid August to mid
September rain days
years)
Female age (2-7
years old)
-7.04 ± 2.88
0.016
Female age ( ≥ 8
years)
-7.30 ± 4.33
0.094
Intercept
44.56 ± 4.97
<0.0001
August rain days
0.61 ± 0.22
0.0055
Male age (2-7
years old)
-16.37 ± 2.59
<0.0001
Male age ( ≥ 8
years)
-10.90 ± 4.02
0.0075
Female age (2-7
years old)
-7.11 ± 2.85
0.0138
Female age ( ≥ 8
years)
-7.12 ± 4.23
0.0949
-805.86
1627.71
1628.45
0
0.75
References cited in supplementary material
Crawley, M. J. 2007 The R Book. Chichester: John Wiley & Sons Ltd.
Nicoll, M. A. C. 2004 The ecology and management of a re-introduced population of the Mauritius kestrel (Falco punctatus). In The
ecology and management of a re-introduced population of the Mauritius kestrel (Falco punctatus). Unpublished PhD thesis.,
vol. PhD: University of Reading.