Type of GEM
Category 1a GeM Project
Example: Estimating Vital Rates
Wolf survival and population trend using non-invasive capturerecapture
techniques in the Western Alps
Managers require reliable and precise estimates of population parameters such as abundance
and survival rates, but these are hard to obtain for elusive,
rare, and wide-ranging species (Boulanger
et al. 2004, Stetz
et al. 2010). Often, these are the very populations that require
such information in order to make management decisions within
a useful timeframe.
The Italian wolf (Canis lupus italicus) was
recognized as a distinct subspecies in 1999. Despite being the
national animal of Italy, wolves suffered from human persecution
as have many wolf populations around the world. It was considered
extirpated from the Alps in the early 20th century, and reached
its lowest population levels in the 1970s. The population is believed
to have been recovering since the 1980s, with current estimates
of population growth of nearly 7%. Now a fully protected species
in western Europe, the Italian wolf's range has expanded into
Switzerland and southern France (Boitani
Current estimated range of the Italian wolf.
Marucco et al. (2009) used open-model capture-mark-recapture
(CMR) sampling with non-invasive individual identifications derived
from fecal genotyping to estimate survival and growth rates for
wolves in the Western Alps between 1999 and 2006.
In an effort to minimize bias and increase the precision of the
estimates, they used a large-scale sampling strategy designed
to reduce heterogeneity in individual detection rates.
Teams of 320 people on skis or snowshoes searched for wolf
tracks a few days after a snowfall along transects that systematically
monitored the entire study area. Tracks were followed as long
as possible, with every scat along the track being collected.
All transects were searched one to seven times during each of
two winter sessions, plus fresh scats were collected when encountered
during other field activities.
Further, their sampling design increases the probability of characterizing
each individual based on differential marking behavior, especially
young and dispersing wolves. With this design, they produced a
dataset that met the assumptions of homogeneity in recapture rates,
which is fundamental for CMR modeling.
|They collected a total of 3382 scats from 3366 km of transects.
From 1399 genotyped scats, 87 unique individuals were identified
(39.1% F, 51.7% M, and 9.2% unknown sex).
Membership to one of seven documented packs was determined for
each individual. Outside of packs, three solitary wolves with
permanent territories and 18 dispersers were identified.
Using detection data from genotypes, the authors estimated apparent
survival and recapture rates of wolves with open population, Cormack-Jolly-Seber
(CJS) models. Their best models included age+season interactions
for apparent survival rates, and effort (both field and lab) was
significant for detection probabilities.
The Western Alps study area showing the location of genotyped
Estimated apparent survival rates for young and adult wolves
in the Western Alps, 19992006. Error bars represent
95% CI. Estimates were obtained by averaging the three best
Cormack-Jolly-Seber (CJS) models.
Young wolves had lower apparent annual survival rates (0.24 ±
0.06) than adult wolves (0.82 ± 0.04). Survival rates were
lower in the summer than in the winter for both young and adults.
The wolf population in the study area increased from 21 ±
9.6 wolves in 1999 to 47 ± 11.2 wolves in late winter 2005.
This equates to a population growth rate of lambda=1.04 (±
0.27), which was lower than has recorded for other recolonizing
Regardless of the statistical method used (i.e., snow tracking
index, CMR) they found a positive trend in wolf abundance. However,
the abundance estimate based on snow-tracking was on average 36.2%
(SD = 13.6%) lower than that from CMR modeling, likely because
young dispersing wolves are likely to have lower sign detection
rates in snow-tracks.
These are the first estimates for wolves in Italy and in the
Alps and have important management implications.
The authors note that the successful application of these new
sampling methods can be widely applied to broader spatial and
temporal scales for other elusive and wide-ranging species in
Europe and elsewhere. However, they suggest that a lower field
effort than the present study could be adopted by avoiding multiple
encounters of an individual within a sampling session.