In marginal habitats, populations should reach lower densities, as a consequence of both lower overall abundance and increasing home range size. To test if recently colonized riparian woods crossing intensively cultivated lowlands of NW Italy represent marginal habitats for the forest-specialist pine marten Martes martes, we assessed its population density by a recently developed, camera-trap-based non-invasive method, the Random Encounter Model (REM). As the central assumption of the REM is that animals move randomly with respect to cameras, we suspected that this method may be unsuitable for species with a strong tendency to use linear elements of the territory as usual paths and select habitats, such as woodland, which are likely to be under-represented in fragmented landscapes. To test for the efficacy of the REM, we also applied a faecal DNA-based genetic census to obtain an independent estimate of the minimum number of individuals occurring in the study area. Camera-trapping used 10 camera-traps, deployed for 10 days within a 2 km2 large unit, for a total of 6 units and 12 km2. Pine marten density was estimated at 0.48 (0.36-0.60) ind/km2. All the faecal samples identified by a mDNA-based PCR-RFLP method as pine marten were genotyped at 15 microsatellite loci using a multiplex protocol. We identified 15 different individuals, corresponding to a density ranging between 0.8 and 2.0 ind/km2. Using the most conservative genetic estimate, the REM underestimated population density of about 60% proving to be unreliable for estimating pine marten population size. We suggest that this may be the case for elusive species for which the assessment of average daily movements cannot be achieved without the use of invasive methods.

Balestrieri, A., Ruiz-Gonzalez, A., Vergara, M., Capelli, E., Tirozzi, P., Alfino, S., et al. (2016). Pine marten density in lowland riparian woods: A test of the Random Encounter Model based on genetic data. MAMMALIAN BIOLOGY, 81(5), 439-446 [10.1016/j.mambio.2016.05.005].

Pine marten density in lowland riparian woods: A test of the Random Encounter Model based on genetic data

Tirozzi, P;
2016

Abstract

In marginal habitats, populations should reach lower densities, as a consequence of both lower overall abundance and increasing home range size. To test if recently colonized riparian woods crossing intensively cultivated lowlands of NW Italy represent marginal habitats for the forest-specialist pine marten Martes martes, we assessed its population density by a recently developed, camera-trap-based non-invasive method, the Random Encounter Model (REM). As the central assumption of the REM is that animals move randomly with respect to cameras, we suspected that this method may be unsuitable for species with a strong tendency to use linear elements of the territory as usual paths and select habitats, such as woodland, which are likely to be under-represented in fragmented landscapes. To test for the efficacy of the REM, we also applied a faecal DNA-based genetic census to obtain an independent estimate of the minimum number of individuals occurring in the study area. Camera-trapping used 10 camera-traps, deployed for 10 days within a 2 km2 large unit, for a total of 6 units and 12 km2. Pine marten density was estimated at 0.48 (0.36-0.60) ind/km2. All the faecal samples identified by a mDNA-based PCR-RFLP method as pine marten were genotyped at 15 microsatellite loci using a multiplex protocol. We identified 15 different individuals, corresponding to a density ranging between 0.8 and 2.0 ind/km2. Using the most conservative genetic estimate, the REM underestimated population density of about 60% proving to be unreliable for estimating pine marten population size. We suggest that this may be the case for elusive species for which the assessment of average daily movements cannot be achieved without the use of invasive methods.
Articolo in rivista - Articolo scientifico
Camera-trapping; Marginal habitats; Martes martes; Microsatellite analysis; Non-invasive census;
Camera-trapping; Marginal habitats; Martes martes; Microsatellite analysis; Non-invasive census
English
2016
81
5
439
446
none
Balestrieri, A., Ruiz-Gonzalez, A., Vergara, M., Capelli, E., Tirozzi, P., Alfino, S., et al. (2016). Pine marten density in lowland riparian woods: A test of the Random Encounter Model based on genetic data. MAMMALIAN BIOLOGY, 81(5), 439-446 [10.1016/j.mambio.2016.05.005].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/254613
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