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Disentangling the effects of predation and oceanographic fluctuations in the mortality of two allopatric seabird populations

Abstract

Life-history traits of migratory seabirds are influenced by changing conditions at breeding and wintering grounds. Climatic conditions and predation are known to impact populations’ survival rates, but few studies examine their effect simultaneously. We used multievent capture–recapture models to assess mortality due to environmental conditions and predation in breeding European storm petrels (Hydrobates pelagicus) in two allopatric colonies (Mediterranean and Atlantic). Predatory mortality at the colonies showed annual variation, being around 0.05 in certain years. Mortality at sea differed between the two oceanic basins, and was lower in the Mediterranean colony [0.11, 95% CI (0.09, 0.14)] when compared to the Atlantic colony [0.18, 95% CI (0.15, 0.22)]. The Western Mediterranean Oscillation index (WeMOi) explained 57% of the temporal variability in mortality of Mediterranean breeders. In comparison, 43% of the temporal variability in mortality of Atlantic breeders was explained by the winter St Helena index (wHIX) and El Niño-Southern Oscillation index (wENSO). Our results suggest that Mediterranean breeders remain in this basin for wintering where they may face lower migratory costs and more favourable environmental conditions. In contrast, Atlantic breeders’ mortality may be due to higher cost of migration, changing upwelling conditions in the Benguela current and heavy storms over their migratory route during La Niña events. This study underlines the importance of modelling separately different causes of mortality when testing the effects of climatic covariates.

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Acknowledgements

We would like to acknowledge the wardens of the Iroise National Nature Reserve, Molène Archipelago, as well as the volunteers involved in fieldwork and the CRBPO (Centre de Recherche sur la Biologie des Populations d’Oiseaux) for approving this programme and providing the rings. The study on Enez Kreiz was conducted with financial support of the Conseil Départemental du Finistère, the DREAL Bretagne—Ministry of environment, the MPAs Agency—Iroise National Marine Park and the Conseil Régional de Bretagne. Furthermore, we are indebted to Environmental Monitoring Service of Benidorm Island (Natural Park Serra Gelada-Generalitat Valenciana). Miguel González Calleja (IMEDEA Geographic Information Systems Service) greatly helped with map generation. Liam Dickson greatly improved the English. The European Union for Bird Ringing (EURING) made the recovery data available through the EURING Data Bank.

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Correspondence to Ana Sanz-Aguilar.

Appendices

Appendix 1

See Tables (3, 4, 5).

Table 3 Goodness-of-fit (GOF) tests of the multistate Jolly Movement model and the transient and trap-dependence multistate models, for birds at Enez Kreiz Island, Brittany (noted EK) and birds at the at Benidorm Island (noted B)
Table 4 Model selection for recapture probabilities (p) of European storm petrel (Hydrobates pelagicus) on Enez Kreiz Island, Western Brittany (EK) and Benidorm Island, Western Mediterranean (B)
Table 5 Correlation between climatic covariates with Pearson’s r test below the diagonal and P value of a t test above the diagonal

Appendix 2

Specification of the multievent modelling approach in program E-SURGE

Multievent models were built in several stages using program E-SURGE (Choquet et al. 2009b). Multievent model uses three kinds of parameters: the initial state probabilities, the transition probabilities, and the event probabilities (conditional on the underlying states). Here the parameters of interest were mortality (m) and recapture probabilities (p). We used a specific structure of transition probabilities (decomposed in two steps, see below) that allows the differential modelling of two types of mortality (Pradel 2005) and accounts for trap-dependence effects (i.e., differential recapture probabilities in time t + 1 of alive individuals captured and not captured in time t) (Pradel and Sanz-Aguilar 2012).

The multievent framework distinguishes the events, coded in the capture histories, from the states, which must be inferred. The possible events were:

0 = “not seen”.

1 = “captured on the nest”.

2 = “recovered dead in a pellet”.

And the underlying biological states were:

AH:

alive captured

AS:

alive non-captured

RDc:

recently dead at the colony

RDs:

recently dead at sea

LD:

long dead

The symbols for parameters were

m :

mortality probability

p :

recapture probability

The transition probabilities are presented in stochastic matrices form with departure states in rows and arrival states in columns (see specific matrices below). Each row corresponds to a multinomial. Consequently, the total of cell probabilities was 1. Because of this constraint, one and only one cell probability in each row will be calculated as the complement to 1 of the others. This particular cell is denoted with a ‘*’ symbol. Inactive cells, i.e., cells whose associated probability is structurally 0 are denoted with a ‘-’ symbol. An active cell receives an arbitrary letter.

As every individual in presented data set was captured alive for the first time, all initial state probabilities (Vector 1) were 1 for the state “AH” and this kind of parameter was not used here.

Initial State probabilities

$${\text{Inital}}\;{\text{state}} = \begin{array}{*{20}c} {{\text{AH}}} & {{\text{AS}}} & {{\text{RDc}}} & {{\text{RDs}}} \\ {(1} & 0 & 0 & {0)} \\ \end{array} \quad ({\text{Vector}}\;1{\text{)}}.$$

The initial state probabilities vector is specified in GEPAT (E-SURGE) as:

1 2 3 4
*

Transition probabilities, step 1: Mortality

In the first step of transitions, the probabilities of mortality at the colony (m c) and at sea (m s) of alive individuals (states AH and AS) were modelled (Matrix 1). The last state—long dead ‘LD’ can only be reached from recently dead states (RDc and RDs) with probability 1, and once in this state an individual will remain in it forever (transition from ‘LD’ to ‘LD’ is 1: last row, last column).

Matrix 1 is specified in GEPAT (E-SURGE) as:

  1 2 3 4 5
1 * m m
2 * m m
3 *
4 *
5 *

Transition probabilities, step 2: recapture

In the second step of transitions, only the probabilities of recapture of alive individuals (states AH and AS) were modelled (Matrix 2), as dead individuals cannot be captured alive and the only possibility is to remain dead.

$${\text{Recapture}} = \begin{gathered} \hfill \\ \begin{array}{*{20}c} {} & & {\quad{\text{AH}}} \\ \end{array} \begin{array}{*{20}c} {\;{\text{AS}}} & {\;{\text{RDc}}} \\ \end{array} \begin{array}{*{20}c} {{\text{RDs}}} & {{\text{LD}}} \\ \end{array} \hfill \\ \begin{array}{*{20}c} {{\text{AH}}} \\ {{\text{AS}}} \\ {{\text{RDc}}} \\ {{\text{RDs}}} \\ {{\text{LD}}} \\ \end{array} \left( {\begin{array}{*{20}c} {p_{{\text{h}}} } & {{\text{1}} - p_{{\text{h}}} } & {{\text{0}}\quad } & {{\text{0}}\quad } & {\text{0}} \\ {p_{{\text{s}}} } & {{\text{1}} - p_{{\text{s}}} } & {{\text{0}}\quad } & {{\text{0}}\quad } & {\text{0}} \\ {\text{0}} & {\text{0}} & {{\text{1}}\quad } & {{\text{0}}\quad } & {\text{0}} \\ {\text{0}} & {\text{0}} & {{\text{0}}\quad } & {{\text{1}}\quad } & {\text{0}} \\ {\text{0}} & {\text{0}} & {{\text{0}}\quad } & {{\text{0}}\quad } & {\text{1}} \\ \end{array} } \right) \quad({\text{Matrix}}\, 2)\hfill \\ \end{gathered}.$$

Matrix 2 is specified in GEPAT (E-SURGE) as:

  1 2 3 4 5
1 p *
2 p *
3 *
4 *
5 *

Event probabilities, step 1

The event probabilities relate the observations coded in the capture histories to the underlying biological states (Matrix 3). Consequently, individuals alive and captured (AH) always have a code 1, and individuals alive but not captured (AS) always have a code 0. Dead individuals at the colony will have a code 2 with a probability 1 which assumes that every predated individual was recovered. Dead individuals at sea cannot be recovered in pellets and have a code 0 with a probability of 1.

$${\text{Event}} = \begin{gathered} \hfill \\ \begin{array}{*{20}c} {} & & {\qquad{\text{0}\quad}} \\ \end{array} \begin{array}{*{20}c} {{\text{1}\;}} & {\;\,\,{\text{2}\quad}} \\ \end{array} \hfill \\ \begin{array}{*{20}c} {{\text{AH}}} \\ {{\text{AS}}} \\ {{\text{RDc}}} \\ {{\text{RDs}}} \\ {{\text{LD}}} \\ \end{array} \left( {\begin{array}{*{20}c} {\text{0}\quad} & {\text{1}\quad} & {\text{0}} \\ {\text{1}\quad} & {\text{0}\quad} & {\text{0}} \\ {\text{0}\quad} & {\text{0}\quad} & {\text{1}} \\ {\text{1}\quad} & {\text{0}\quad} & {\text{0}} \\ {\text{1}\quad} & {\text{0}\quad} & {\text{0}} \\ \end{array} } \right) \quad ({\text{Matrix}} \,3) \hfill \\ \end{gathered}$$

Matrix 3 is specified in GEPAT (E-SURGE) as:

  1 2 3
1 *
2 *
3 *
4 *
5 *

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Matović, N., Cadiou, B., Oro, D. et al. Disentangling the effects of predation and oceanographic fluctuations in the mortality of two allopatric seabird populations. Popul Ecol 59, 225–238 (2017). https://doi.org/10.1007/s10144-017-0590-5

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Keywords

  • Capture–recapture
  • Climate
  • Multievent
  • Storm petrel
  • Survival