Corresponding author: Agustín M. Abba (

The aim of this work was to obtain the first estimates of survival rates (

Armadillos are one of the most distinctive mammals of South America, and the only group that originated in this continent. Although these singular animals have attracted the attention of travelers and naturalists since the 15^{th} century, the development of scientific studies on their ecology and other topics is very scarce (

^{2} (

The aim of this work was to obtain the first estimates of survival rates for armadillos in South America by analyzing capture-mark-recapture (CMR) data obtained between 2006 and 2011 for adult individuals from a portion of the isolated population of

(1) Geographical range of

Temporal variation in annual survival probability of

We sought to capture armadillos within a 100 ha area located in an agricultural field (Figs

For each survey, three field observers walked 30-m-wide transects until the entire sampling area was covered; total sampling effort for all surveys was 61 days (4–5 days per survey) and 1500 hours of field time. During surveys, we attempted to capture and process (i.e., measured and marked) all armadillos that were detected during a survey. All burrows with signs of recent activity (e.g., accumulation of grass, soil that had been removed, etc.) were sampled to check for the presence of armadillos; this check consisted of a visual inspection of the initial 50 cm of the burrow. Animals were captured by hand or in a net and burrows were checked by hand or, on occasion, by opening the first 50 cm with a shovel. During the first two years of the study the ears of the animals were marked with numbered ear tags (National Band and Tag Company, Newport, KY, #1005-1); subsequently animals were marked using a passive transponder system (Trovan ID-100). For temporary identification we used a sticker affixed to the carapace, which allowed us to follow the animals after release and avoid recapturing them again on the same day. Age was estimated using body length and weight (

We used a Cormack-Jolly-Seber (CJS) modelling framework (

The CJS model was chosen because its assumptions best fit some important features of our study system. CJS models do not take into account migration, i.e., they assume a geographically closed population (

The set of candidate models was constructed as follows. We included the sex of individuals and the year in which a survey was conducted as potential effects to account for variation in survival rate. Capture effort was not constant among field surveys, as previously noted. Thus, to account for variation in capture probability, in addition to the sex of individuals as a potential effect, we included an indicator of the campaign for each field survey. Candidate models were constructed that included independent effects on survival rates and capture probability, and that considered both first-order effects and interactions between all effects. In order to explore the effect of interannual variation on survival rates, we considered time periods of one year that started and ended in winter (i.e., June of one year to July of the following year). However, this was problematic for the two-year period between June 2007 to June 2009. We therefore decided to retain the 2008 data, but to make only one estimate of survival probability for the entire 2007–2009 period. We felt this was reasonable because the low number of captures in the 2008 field survey, where only seven adult individuals were caught, provided insufficient data to make reliable estimates of survival probability for a one-year period.

CJS models are based on the binomial distribution, and as such do not independently model mean and variance. When fitting a capture-recapture model, it is not uncommon that observed variance is greater than expected, a phenomenon known as overdispersion (

Model selection was performed using an information-theoretic approach following

The CJS models were fitted using program MARK (

A total of 152 adult individuals were caught, 82 females and 70 males, in a total of 365 capture events (Table

In order to examine the effect of interannual variation on survival probability, a multi-model inference scheme was followed. The estimated annual survival probabilities were similar between sexes, but strongly varied between study periods (Fig.

The projected survivorship curves for

Descriptive summary of annual field surveys for

2006–2007 | 2007–2009 | 2009–2010 | 2010–2011 | |
---|---|---|---|---|

Adults individuals captured | 74 | 76 | 29 | 34 |

Sex | 43♀–31♂ | 40♀–36♂ | 16♀–13♂ | 17♀–17♂ |

Capture events | 117 | 131 | 43 | 74 |

Sampling effort (days) | 16 | 21 | 10 | 14 |

Mean values (± SE) of weekly capture probability (

CJS models fitted to the capture-recapture data of

Model | Parameters | Deviance | AICc | ΔAICc | Model likelihood | AICc Weight | |
---|---|---|---|---|---|---|---|

1 | 19 | 289.6 | 636.2 | – | 1.00 | 0.40 | |

2 | 16 | 298.7 | 638.4 | 2.18 | 0.34 | 0.13 | |

3 | 20 | 289.4 | 638.5 | 2.21 | 0.33 | 0.13 | |

4 | 20 | 289.5 | 638.6 | 2.32 | 0.31 | 0.12 | |

5 | 23 | 284.2 | 640.4 | 4.16 | 0.12 | 0.05 | |

6 | 21 | 289.2 | 640.6 | 4.35 | 0.11 | 0.05 | |

7 | 17 | 298.7 | 640.7 | 4.44 | 0.11 | 0.04 | |

8 | 17 | 298.7 | 640.7 | 4.46 | 0.11 | 0.04 | |

9 | 24 | 283.8 | 642.5 | 6.21 | 0.04 | 0.02 |

Projection of a survivorship curve for

This study provides the first estimates of demographic parameters for xenarthrans in South America, and just the second study of the population ecology of armadillos overall (and, importantly, the first for

As previously pointed out, the only study dealing with the population ecology of xenarthrans was performed by

On the other hand, the capture probability (

In the present study the influence of sex on survival probability was not significant compared with temporal variability. This is consistent with a range of studies conducted previously that have found few differences between male and female

The survivorship estimate for

The results of this work suggest that the survival rate is similar for adult individuals of both sexes, and that temporal variability is the main driver of variation in the survival of

We thank L.G. Pagano and M.C. Ezquiaga for their assistance during fieldwork, and Lic. Ana Teresa Gómez (Jefe Departamento, CIM, SMN) for her support with the climatic data (SMN, Exp_144540). We appreciate the improvements in English usage made by W. J. Loughry and the valuable comments. We also want to thank two anonymous reviewers for valuable input that helped us to improve the manuscript. This work was partially supported by the Agencia Nacional de Promoción Científica y Tecnológica (BID PICT2010-1412) and Universidad Nacional de La Plata (PPID/N004).