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Forçage environnemental et prédateurs marins ... - Cebc - CNRS

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686 CHRISTOPHE BARBRAUD AND HENRI WEIMERSKIRCH Ecology, Vol. 86, No. 3<br />

TABLE 1. Selection among models of state-dependent survival probability (S ), recapture probability<br />

(p) and transition probability () on Blue P<strong>et</strong>rels at Kerguelen Islands.<br />

Model np Dev QAIC c i w i<br />

Modeling capture probabilities<br />

r (S , p r, rs<br />

t t t )<br />

r (S , pt, rs<br />

t t )<br />

r (S , p 14, rs<br />

t t t )<br />

r (S , p 14, rs<br />

t t t )<br />

(S , p<br />

90<br />

76<br />

85<br />

78<br />

6699.851<br />

7076.431<br />

6699.851<br />

6709.016<br />

5345.051<br />

5604.819<br />

5334.246<br />

5326.256<br />

89.957<br />

349.725<br />

79.152<br />

71.162<br />

0.000<br />

0.000<br />

0.000<br />

0.000<br />

r r , rs<br />

t t )<br />

Modeling survival probabilities<br />

71 6743.980 5338.221 83.127 0.000<br />

(St, p 14, rs<br />

t t )<br />

(S, p 14, rs<br />

t t )<br />

r (S , p 14, rs<br />

t t t )<br />

23 (S , p 14, rs<br />

t t t )<br />

12 (S , p 14, rs<br />

t t t )<br />

34 (S , p 14, rs<br />

t t t )<br />

52<br />

46<br />

56<br />

55<br />

55<br />

55<br />

6745.725<br />

6762.701<br />

6730.239<br />

6745.239<br />

6733.866<br />

6736.230<br />

5299.446<br />

5299.986<br />

5295.915<br />

5305.362<br />

5296.606<br />

5298.426<br />

44.352<br />

44.892<br />

40.821<br />

50.268<br />

41.512<br />

43.332<br />

0.000<br />

0.000<br />

0.000<br />

0.000<br />

0.000<br />

0.000<br />

Modeling transition probabilities<br />

(S , p , rs r 14<br />

t t )<br />

27 6863.572 5338.395 83.301 0.000<br />

r (S , p 14<br />

t t, t)<br />

31 7580.973 5898.874 643.780 0.000<br />

r (S , p 14, rs<br />

t t t) 34 6749.806 5265.198 10.104 0.006<br />

(S r , p 14, 2434<br />

t t t )<br />

34 6756.545 5270.385 15.291 0.000<br />

(S r , p 14, 1124<br />

t t t )<br />

35 6826.792 5326.525 71.431 0.000<br />

(S r , p 14, 3444<br />

t t t )<br />

35 6776.181 5287.563 32.469 0.000<br />

Modeling covariates<br />

(S r , p 14, rs<br />

SSH t t) 32 6742.031 5255.094 0 0.964<br />

(S r , p 14, rs<br />

mass t t) 32 6753.940 5264.262 9.168 0.010<br />

(S r , p 14, rs<br />

SSHmass t t) 37 6738.805 5262.919 7.825 0.020<br />

(S r , p 14, rs<br />

SSH t SSH) 25 7033.339 5464.993 209.899 0.000<br />

(S r , p 14, rs<br />

SSH t mass) 25 6866.492 5336.550 81.456 0.000<br />

Notes: Model subscripts include: SSH, variation in sea surface height; mass, body mass;<br />

t, a year effect with interaction; t, an additive effect of year (i.e., no interaction). Model<br />

superscripts include: r and s, state-specific param<strong>et</strong>ers; 1, inexperienced nonbreeders; 2, firsttime<br />

breeders; 3, experienced breeders; 4, experienced nonbreeders. Abbreviation are: np,<br />

number of param<strong>et</strong>ers; Dev, relative deviance; QAIC c, Akaïke Information criterion corrected<br />

for ĉ; i, the QAIC c difference b<strong>et</strong>ween the current and lowest QAIC c model; w i, the current<br />

model weight.<br />

GOF statistic for our global model divided by the degrees<br />

of freedom of the model (Pradel <strong>et</strong> al. 2003).<br />

With the inflation factor, the AIC c becomes the quasilikelihood<br />

AIC c (QAIC c, Lebr<strong>et</strong>on <strong>et</strong> al. 1992). We used<br />

program M-SURGE (Choqu<strong>et</strong> <strong>et</strong> al. 2003b) for model<br />

selection and param<strong>et</strong>er estimation.<br />

RESULTS<br />

Goodness-of-fit tests<br />

The GOF test of our general model indicated a lack<br />

of fit (Test3G TestM LRT: 2 223.49, df 172,<br />

P 0.005). The relatively small value of the variance<br />

inflation factor from the global test (ĉ 1.299) was<br />

compatible with overdispersed data. To correct for<br />

overdispersion, we used ĉ 1.299 in the remaining<br />

analysis.<br />

Effect of time, breeding activity, and experience<br />

Recapture probabilities.—We first examined wh<strong>et</strong>her<br />

recapture probabilities varied with state. A model<br />

with no state effect on p (Table 1; [ Sr, p rs<br />

t t, t<br />

]) was not<br />

preferred to the general model ( Sr, r, rs<br />

t pt t<br />

). Because<br />

nests were checked two to three times during the incubation<br />

period to ensure that both partners who al-<br />

ternate incubation shifts were identified, we suspected<br />

that the recapture probabilities of breeders were high<br />

and constant. A model with capture rates constant over<br />

time for breeders and varying for nonbreeders ( Sr, 14<br />

t pt<br />

,<br />

rs t )was much b<strong>et</strong>ter in terms of QAICc than the general<br />

model ( r, r, rs St pt t<br />

). Recapture probability for breeders<br />

was close to 1.0 (0.999; deviance profile confidence<br />

interval: 0.984–1.000). A model in which temporal variations<br />

of recapture probabilities of experienced nonbreeders<br />

and of inexperienced nonbreeders were parallel<br />

on a logit scale ( Sr, 14, rs<br />

t ptt) was preferred over<br />

a model with an interaction b<strong>et</strong>ween state and year<br />

( , , ) or a model with no year effect ( , pr r 14 rs r , rs<br />

St pt t St t<br />

).<br />

This indicated that recapture probabilities of inexperienced<br />

and experienced nonbreeders varied synchronously<br />

over time. For all remaining models, recapture<br />

probabilities were modeled as in model ( Sr, 14, rs<br />

t ptt). For nonbreeders, there was an effect of experience<br />

on recapture probabilities, because experienced individuals<br />

had higher recapture probabilities than inexperienced<br />

ones in all years (pˆ 4 0.527 0.032 and<br />

pˆ 1 0.364 0.019 from model [ , p14 Sr , rs]).<br />

Estimated<br />

t t<br />

probabilities of recapture increased until 1996 for experienced<br />

birds, whereas they remained constant for

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